Using metabolic flux data to further constrain the metabolic solution space and predict internal flux patterns: the Escherichia coli spectrum.

PubMed

Wiback, Sharon J; Mahadevan, Radhakrishnan; Palsson, Bernhard Ø

2004-05-05

Constraint-based metabolic modeling has been used to capture the genome-scale, systems properties of an organism's metabolism. The first generation of these models has been built on annotated gene sequence. To further this field, we now need to develop methods to incorporate additional "omic" data types including transcriptomics, metabolomics, and fluxomics to further facilitate the construction, validation, and predictive capabilities of these models. The work herein combines metabolic flux data with an in silico model of central metabolism of Escherichia coli for model centric integration of the flux data. The extreme pathways for this network, which define the allowable solution space for all possible flux distributions, are analyzed using the alpha-spectrum. The alpha-spectrum determines which extreme pathways can and cannot contribute to the metabolic flux distribution for a given condition and gives the allowable range of weightings on each extreme pathway that can contribute. Since many extreme pathways cannot be used under certain conditions, the result is a "condition-specific" solution space that is a subset of the original solution space. The alpha-spectrum results are used to create a "condition-specific" extreme pathway matrix that can be analyzed using singular value decomposition (SVD). The first mode of the SVD analysis characterizes the solution space for a given condition. We show that SVD analysis of the alpha-spectrum extreme pathway matrix that incorporates measured uptake and byproduct secretion rates, can predict internal flux trends for different experimental conditions. These predicted internal flux trends are, in general, consistent with the flux trends measured using experimental metabolic flux analysis techniques. Copyright 2004 Wiley Periodicals, Inc.

Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis

DOE PAGES

Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav; ...

2016-04-07

The daily maximum relativistic electron flux at geostationary orbit can be predicted well with a set of daily averaged predictor variables including previous day's flux, seed electron flux, solar wind velocity and number density, AE index, IMF Bz, Dst, and ULF and VLF wave power. As predictor variables are intercorrelated, we used multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Empirical models produced from regressions of flux on measured predictors from 1 day previous were reasonably effective at predicting novel observations. Adding previous flux to the parameter set improves the predictionmore » of the peak of the increases but delays its anticipation of an event. Previous day's solar wind number density and velocity, AE index, and ULF wave activity are the most significant explanatory variables; however, the AE index, measuring substorm processes, shows a negative correlation with flux when other parameters are controlled. This may be due to the triggering of electromagnetic ion cyclotron waves by substorms that cause electron precipitation. VLF waves show lower, but significant, influence. The combined effect of ULF and VLF waves shows a synergistic interaction, where each increases the influence of the other on flux enhancement. Correlations between observations and predictions for this 1 day lag model ranged from 0.71 to 0.89 (average: 0.78). Furthermore, a path analysis of correlations between predictors suggests that solar wind and IMF parameters affect flux through intermediate processes such as ring current ( Dst), AE, and wave activity.« less

Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav

The daily maximum relativistic electron flux at geostationary orbit can be predicted well with a set of daily averaged predictor variables including previous day's flux, seed electron flux, solar wind velocity and number density, AE index, IMF Bz, Dst, and ULF and VLF wave power. As predictor variables are intercorrelated, we used multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Empirical models produced from regressions of flux on measured predictors from 1 day previous were reasonably effective at predicting novel observations. Adding previous flux to the parameter set improves the predictionmore » of the peak of the increases but delays its anticipation of an event. Previous day's solar wind number density and velocity, AE index, and ULF wave activity are the most significant explanatory variables; however, the AE index, measuring substorm processes, shows a negative correlation with flux when other parameters are controlled. This may be due to the triggering of electromagnetic ion cyclotron waves by substorms that cause electron precipitation. VLF waves show lower, but significant, influence. The combined effect of ULF and VLF waves shows a synergistic interaction, where each increases the influence of the other on flux enhancement. Correlations between observations and predictions for this 1 day lag model ranged from 0.71 to 0.89 (average: 0.78). Furthermore, a path analysis of correlations between predictors suggests that solar wind and IMF parameters affect flux through intermediate processes such as ring current ( Dst), AE, and wave activity.« less

The Space Shuttle Orbiter molecular environment induced by the supplemental flash evaporator system

NASA Technical Reports Server (NTRS)

Ehlers, H. K. F.

1985-01-01

The water vapor environment of the Space Shuttle Orbiter induced by the supplemental flash evaporator during the on-orbit flight phase has been analyzed based on Space II model predictions and orbital flight measurements. Model data of local density, column density, and return flux are presented. Results of return flux measurements with a mass spectrometer during STS-2 and of direct flux measurements during STS-4 are discussed and compared with model predictions.

Spatially explicit modeling of particulate nutrient flux in Large global rivers

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Mayorga, E.; Harrison, J. A.

2017-12-01

Water, sediment, nutrient and carbon fluxes along river networks have undergone considerable alterations in response to anthropogenic and climatic changes, with significant consequences to infrastructure, agriculture, water security, ecology and geomorphology worldwide. However, in a global setting, these changes in fluvial fluxes and their spatial and temporal characteristics are poorly constrained, due to the limited availability of continuous and long-term observations. We present results from a new global-scale particulate modeling framework (WBMsedNEWS) that combines the Global NEWS watershed nutrient export model with the spatially distributed WBMsed water and sediment model. We compare the model predictions against multiple observational datasets. The results indicate that the model is able to accurately predict particulate nutrient (Nitrogen, Phosphorus and Organic Carbon) fluxes on an annual time scale. Analysis of intra-basin nutrient dynamics and fluxes to global oceans is presented.

Predictive Uncertainty And Parameter Sensitivity Of A Sediment-Flux Model: Nitrogen Flux and Sediment Oxygen Demand

EPA Science Inventory

Estimating model predictive uncertainty is imperative to informed environmental decision making and management of water resources. This paper applies the Generalized Sensitivity Analysis (GSA) to examine parameter sensitivity and the Generalized Likelihood Uncertainty Estimation...

Modeling dry and wet deposition of sulfate, nitrate, and ammonium ions in Jiuzhaigou National Nature Reserve, China using a source-oriented CMAQ model: Part I. Base case model results.

PubMed

Qiao, Xue; Tang, Ya; Hu, Jianlin; Zhang, Shuai; Li, Jingyi; Kota, Sri Harsha; Wu, Li; Gao, Huilin; Zhang, Hongliang; Ying, Qi

2015-11-01

A source-oriented Community Multiscale Air Quality (CMAQ) model driven by the meteorological fields generated by the Weather Research and Forecasting (WRF) model was used to study the dry and wet deposition of nitrate (NO3(-)), sulfate (SO4(2-)), and ammonium (NH4(+)) ions in the Jiuzhaigou National Nature Reserve (JNNR), China from June to August 2010 and to identify the contributions of different emission sectors and source regions that were responsible for the deposition fluxes. The model performance is evaluated in this paper and the source contribution analyses are presented in a companion paper. The results show that WRF is capable of reproducing the observed precipitation rates with a Mean Normalized Gross Error (MNGE) of 8.1%. Predicted wet deposition fluxes of SO4(2-) and NO3(-) at the Long Lake (LL) site (3100 m a.s.l.) during the three-month episode are 2.75 and 0.34 kg S(N) ha(-1), which agree well with the observed wet deposition fluxes of 2.42 and 0.39 kg S(N) ha(-1), respectively. Temporal variations in the weekly deposition fluxes at LL are also well predicted. Wet deposition flux of NH4(+) at LL is over-predicted by approximately a factor of 3 (1.60 kg N ha(-1)vs. 0.56 kg N ha(-1)), likely due to missing alkaline earth cations such as Ca(2+) in the current CMAQ simulations. Predicted wet deposition fluxes are also in general agreement with observations at four Acid Deposition Monitoring Network in East Asia (EANET) sites in western China. Predicted dry deposition fluxes of SO4(2-) (including gas deposition of SO2) and NO3(-) (including gas deposition of HNO3) are 0.12 and 0.12 kg S(N) h a(-1) at LL and 0.07 and 0.08 kg S(N) ha(-1) at Jiuzhaigou Bureau (JB) in JNNR, respectively, which are much lower than the corresponding wet deposition fluxes. Dry deposition flux of NH4(+) (including gas deposition of NH3) is 0.21 kg N ha(-1) at LL, and is also much lower than the predicted wet deposition flux. For both dry and wet deposition fluxes, predictions from the 12-km resolution nested domain are similar to those from the 36-km resolution parent domain. Copyright © 2015 Elsevier B.V. All rights reserved.

On the effects of alternative optima in context-specific metabolic model predictions

PubMed Central

Nikoloski, Zoran

2017-01-01

The integration of experimental data into genome-scale metabolic models can greatly improve flux predictions. This is achieved by restricting predictions to a more realistic context-specific domain, like a particular cell or tissue type. Several computational approaches to integrate data have been proposed—generally obtaining context-specific (sub)models or flux distributions. However, these approaches may lead to a multitude of equally valid but potentially different models or flux distributions, due to possible alternative optima in the underlying optimization problems. Although this issue introduces ambiguity in context-specific predictions, it has not been generally recognized, especially in the case of model reconstructions. In this study, we analyze the impact of alternative optima in four state-of-the-art context-specific data integration approaches, providing both flux distributions and/or metabolic models. To this end, we present three computational methods and apply them to two particular case studies: leaf-specific predictions from the integration of gene expression data in a metabolic model of Arabidopsis thaliana, and liver-specific reconstructions derived from a human model with various experimental data sources. The application of these methods allows us to obtain the following results: (i) we sample the space of alternative flux distributions in the leaf- and the liver-specific case and quantify the ambiguity of the predictions. In addition, we show how the inclusion of ℓ1-regularization during data integration reduces the ambiguity in both cases. (ii) We generate sets of alternative leaf- and liver-specific models that are optimal to each one of the evaluated model reconstruction approaches. We demonstrate that alternative models of the same context contain a marked fraction of disparate reactions. Further, we show that a careful balance between model sparsity and metabolic functionality helps in reducing the discrepancies between alternative models. Finally, our findings indicate that alternative optima must be taken into account for rendering the context-specific metabolic model predictions less ambiguous. PMID:28557990

On the effects of alternative optima in context-specific metabolic model predictions.

PubMed

Robaina-Estévez, Semidán; Nikoloski, Zoran

2017-05-01

The integration of experimental data into genome-scale metabolic models can greatly improve flux predictions. This is achieved by restricting predictions to a more realistic context-specific domain, like a particular cell or tissue type. Several computational approaches to integrate data have been proposed-generally obtaining context-specific (sub)models or flux distributions. However, these approaches may lead to a multitude of equally valid but potentially different models or flux distributions, due to possible alternative optima in the underlying optimization problems. Although this issue introduces ambiguity in context-specific predictions, it has not been generally recognized, especially in the case of model reconstructions. In this study, we analyze the impact of alternative optima in four state-of-the-art context-specific data integration approaches, providing both flux distributions and/or metabolic models. To this end, we present three computational methods and apply them to two particular case studies: leaf-specific predictions from the integration of gene expression data in a metabolic model of Arabidopsis thaliana, and liver-specific reconstructions derived from a human model with various experimental data sources. The application of these methods allows us to obtain the following results: (i) we sample the space of alternative flux distributions in the leaf- and the liver-specific case and quantify the ambiguity of the predictions. In addition, we show how the inclusion of ℓ1-regularization during data integration reduces the ambiguity in both cases. (ii) We generate sets of alternative leaf- and liver-specific models that are optimal to each one of the evaluated model reconstruction approaches. We demonstrate that alternative models of the same context contain a marked fraction of disparate reactions. Further, we show that a careful balance between model sparsity and metabolic functionality helps in reducing the discrepancies between alternative models. Finally, our findings indicate that alternative optima must be taken into account for rendering the context-specific metabolic model predictions less ambiguous.

Evaluation of Deep Learning Models for Predicting CO2 Flux

NASA Astrophysics Data System (ADS)

Halem, M.; Nguyen, P.; Frankel, D.

2017-12-01

Artificial neural networks have been employed to calculate surface flux measurements from station data because they are able to fit highly nonlinear relations between input and output variables without knowing the detail relationships between the variables. However, the accuracy in performing neural net estimates of CO2 flux from observations of CO2 and other atmospheric variables is influenced by the architecture of the neural model, the availability, and complexity of interactions between physical variables such as wind, temperature, and indirect variables like latent heat, and sensible heat, etc. We evaluate two deep learning models, feed forward and recurrent neural network models to learn how they each respond to the physical measurements, time dependency of the measurements of CO2 concentration, humidity, pressure, temperature, wind speed etc. for predicting the CO2 flux. In this paper, we focus on a) building neural network models for estimating CO2 flux based on DOE data from tower Atmospheric Radiation Measurement data; b) evaluating the impact of choosing the surface variables and model hyper-parameters on the accuracy and predictions of surface flux; c) assessing the applicability of the neural network models on estimate CO2 flux by using OCO-2 satellite data; d) studying the efficiency of using GPU-acceleration for neural network performance using IBM Power AI deep learning software and packages on IBM Minsky system.

A Mechanistically Informed User-Friendly Model to Predict Greenhouse Gas (GHG) Fluxes and Carbon Storage from Coastal Wetlands

NASA Astrophysics Data System (ADS)

Abdul-Aziz, O. I.; Ishtiaq, K. S.

2015-12-01

We present a user-friendly modeling tool on MS Excel to predict the greenhouse gas (GHG) fluxes and estimate potential carbon sequestration from the coastal wetlands. The dominant controls of wetland GHG fluxes and their relative mechanistic linkages with various hydro-climatic, sea level, biogeochemical and ecological drivers were first determined by employing a systematic data-analytics method, including Pearson correlation matrix, principal component and factor analyses, and exploratory partial least squares regressions. The mechanistic knowledge and understanding was then utilized to develop parsimonious non-linear (power-law) models to predict wetland carbon dioxide (CO2) and methane (CH4) fluxes based on a sub-set of climatic, hydrologic and environmental drivers such as the photosynthetically active radiation, soil temperature, water depth, and soil salinity. The models were tested with field data for multiple sites and seasons (2012-13) collected from the Waquoit Bay, MA. The model estimated the annual wetland carbon storage by up-scaling the instantaneous predicted fluxes to an extended growing season (e.g., May-October) and by accounting for the net annual lateral carbon fluxes between the wetlands and estuary. The Excel Spreadsheet model is a simple ecological engineering tool for coastal carbon management and their incorporation into a potential carbon market under a changing climate, sea level and environment. Specifically, the model can help to determine appropriate GHG offset protocols and monitoring plans for projects that focus on tidal wetland restoration and maintenance.

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Nemani, Ramakrishma

2010-01-01

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

2017-12-01

Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation without the nitrogen transport module is also executed. The model without nitrogen transport fails in predicting the spatial patterns of vegetation carbon, which indicates the importance of having a nitrogen transport module in spatially distributed ecohydrologic modeling.

Size effects in non-linear heat conduction with flux-limited behaviors

NASA Astrophysics Data System (ADS)

Li, Shu-Nan; Cao, Bing-Yang

2017-11-01

Size effects are discussed for several non-linear heat conduction models with flux-limited behaviors, including the phonon hydrodynamic, Lagrange multiplier, hierarchy moment, nonlinear phonon hydrodynamic, tempered diffusion, thermon gas and generalized nonlinear models. For the phonon hydrodynamic, Lagrange multiplier and tempered diffusion models, heat flux will not exist in problems with sufficiently small scale. The existence of heat flux needs the sizes of heat conduction larger than their corresponding critical sizes, which are determined by the physical properties and boundary temperatures. The critical sizes can be regarded as the theoretical limits of the applicable ranges for these non-linear heat conduction models with flux-limited behaviors. For sufficiently small scale heat conduction, the phonon hydrodynamic and Lagrange multiplier models can also predict the theoretical possibility of violating the second law and multiplicity. Comparisons are also made between these non-Fourier models and non-linear Fourier heat conduction in the type of fast diffusion, which can also predict flux-limited behaviors.

Using passive capillary lysimeter water flux measurements to improve flow predictions in variably saturated soils.

USDA-ARS?s Scientific Manuscript database

Passive capillary lysimeters (PCLs) are uniquely suited for measuring water fluxes in variably-saturated soils. The objective of this work was to compare PCL flux measurements with simulated fluxes obtained with a calibrated unsaturated flow model. The Richards equation-based model was calibrated us...

A Semi-Empirical Model for Forecasting Relativistic Electrons at Geostationary Orbit

NASA Technical Reports Server (NTRS)

Lyatsky, Wladislaw; Khazanov, George V.

2008-01-01

We developed a new prediction model for forecasting relativistic (>2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/Interplanetary Magnetic Field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is about 0.9. The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible. The correlation coefficient between predicted and actual electron fluxes is stable and incredibly high.

Semianalytical model predicting transfer of volatile pollutants from groundwater to the soil surface.

PubMed

Atteia, Olivier; Höhener, Patrick

2010-08-15

Volatilization of toxic organic contaminants from groundwater to the soil surface is often considered an important pathway in risk analysis. Most of the risk models use simplified linear solutions that may overpredict the volatile flux. Although complex numerical models have been developed, their use is restricted to experienced users and for sites where field data are known in great detail. We present here a novel semianalytical model running on a spreadsheet that simulates the volatilization flux and vertical concentration profile in a soil based on the Van Genuchten functions. These widely used functions describe precisely the gas and water saturations and movement in the capillary fringe. The analytical model shows a good accuracy over several orders of magnitude when compared to a numerical model and laboratory data. The effect of barometric pumping is also included in the semianalytical formulation, although the model predicts that barometric pumping is often negligible. A sensitivity study predicts significant fluxes in sandy vadose zones and much smaller fluxes in other soils. Fluxes are linked to the dimensionless Henry's law constant H for H < 0.2 and increase by approximately 20% when temperature increases from 5 to 25 degrees C.

DOSIMETRY MODELING OF INHALED FORMALDEHYDE: BINNING NASAL FLUX PREDICTIONS FOR QUANTITATIVE RISK ASSESSMENT

EPA Science Inventory

Dosimetry Modeling of Inhaled Formaldehyde: Binning Nasal Flux Predictions for Quantitative Risk Assessment. Kimbell, J.S., Overton, J.H., Subramaniam, R.P., Schlosser, P.M., Morgan, K.T., Conolly, R.B., and Miller, F.J. (2001). Toxicol. Sci. 000, 000:000.

Interspecies e...

Prediction of ECS and SSC Models for Flux-Limited Samples of Gamma-Ray Blazars

NASA Technical Reports Server (NTRS)

Lister, Matthew L.; Marscher, Alan P.

1999-01-01

The external Compton scattering (ECS) and synchrotron self-Compton (SSC) models make distinct predictions for the amount of Doppler boosting of high-energy gamma-rays emitted by Nazar. We examine how these differences affect the predicted properties of active galactic nucleus (AGN) samples selected on the basis of Murray emission. We create simulated flux-limited samples based on the ECS and SSC models, and compare their properties to those of identified EGRET blazars. We find that for small gamma-ray-selected samples, the two models make very similar predictions, and cannot be reliably distinguished. This is primarily due to the fact that not only the Doppler factor, but also the cosmological distance and intrinsic luminosity play a role in determining whether an AGN is included in a flux-limited gamma-ray sample.

SEC proton prediction model: verification and analysis.

PubMed

Balch, C C

1999-06-01

This paper describes a model that has been used at the NOAA Space Environment Center since the early 1970s as a guide for the prediction of solar energetic particle events. The algorithms for proton event probability, peak flux, and rise time are described. The predictions are compared with observations. The current model shows some ability to distinguish between proton event associated flares and flares that are not associated with proton events. The comparisons of predicted and observed peak flux show considerable scatter, with an rms error of almost an order of magnitude. Rise time comparisons also show scatter, with an rms error of approximately 28 h. The model algorithms are analyzed using historical data and improvements are suggested. Implementation of the algorithm modifications reduces the rms error in the log10 of the flux prediction by 21%, and the rise time rms error by 31%. Improvements are also realized in the probability prediction by deriving the conditional climatology for proton event occurrence given flare characteristics.

Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush–steppe ecosystem

USGS Publications Warehouse

Wylie, Bruce K.; Johnson, Douglas A.; Laca, Emilio; Saliendra, Nicanor Z.; Gilmanov, Tagir G.; Reed, Bradley C.; Tieszen, Larry L.; Worstell, Bruce B.

2003-01-01

The net ecosystem exchange (NEE) of carbon flux can be partitioned into gross primary productivity (GPP) and respiration (R). The contribution of remote sensing and modeling holds the potential to predict these components and map them spatially and temporally. This has obvious utility to quantify carbon sink and source relationships and to identify improved land management strategies for optimizing carbon sequestration. The objective of our study was to evaluate prediction of 14-day average daytime CO2 fluxes (Fday) and nighttime CO2 fluxes (Rn) using remote sensing and other data. Fday and Rnwere measured with a Bowen ratio–energy balance (BREB) technique in a sagebrush (Artemisia spp.)–steppe ecosystem in northeast Idaho, USA, during 1996–1999. Micrometeorological variables aggregated across 14-day periods and time-integrated Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (iNDVI) were determined during four growing seasons (1996–1999) and used to predict Fday and Rn. We found that iNDVI was a strong predictor of Fday(R2=0.79, n=66, P<0.0001). Inclusion of evapotranspiration in the predictive equation led to improved predictions of Fday (R2=0.82, n=66, P<0.0001). Crossvalidation indicated that regression tree predictions of Fday were prone to overfitting and that linear regression models were more robust. Multiple regression and regression tree models predicted Rn quite well (R2=0.75–0.77, n=66) with the regression tree model being slightly more robust in crossvalidation. Temporal mapping of Fday and Rn is possible with these techniques and would allow the assessment of NEE in sagebrush–steppe ecosystems. Simulations of periodic Fday measurements, as might be provided by a mobile flux tower, indicated that such measurements could be used in combination with iNDVI to accurately predict Fday. These periodic measurements could maximize the utility of expensive flux towers for evaluating various carbon management strategies, carbon certification, and validation and calibration of carbon flux models.

Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush-steppe ecosystem

USGS Publications Warehouse

Wylie, B.K.; Johnson, D.A.; Laca, Emilio; Saliendra, Nicanor Z.; Gilmanov, T.G.; Reed, B.C.; Tieszen, L.L.; Worstell, B.B.

2003-01-01

The net ecosystem exchange (NEE) of carbon flux can be partitioned into gross primary productivity (GPP) and respiration (R). The contribution of remote sensing and modeling holds the potential to predict these components and map them spatially and temporally. This has obvious utility to quantify carbon sink and source relationships and to identify improved land management strategies for optimizing carbon sequestration. The objective of our study was to evaluate prediction of 14-day average daytime CO2 fluxes (Fday) and nighttime CO2 fluxes (Rn) using remote sensing and other data. Fday and Rn were measured with a Bowen ratio-energy balance (BREB) technique in a sagebrush (Artemisia spp.)-steppe ecosystem in northeast Idaho, USA, during 1996-1999. Micrometeorological variables aggregated across 14-day periods and time-integrated Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (iNDVI) were determined during four growing seasons (1996-1999) and used to predict Fday and Rn. We found that iNDVI was a strong predictor of Fday (R2 = 0.79, n = 66, P < 0.0001). Inclusion of evapotranspiration in the predictive equation led to improved predictions of Fday (R2= 0.82, n = 66, P < 0.0001). Crossvalidation indicated that regression tree predictions of Fday were prone to overfitting and that linear regression models were more robust. Multiple regression and regression tree models predicted Rn quite well (R2 = 0.75-0.77, n = 66) with the regression tree model being slightly more robust in crossvalidation. Temporal mapping of Fday and Rn is possible with these techniques and would allow the assessment of NEE in sagebrush-steppe ecosystems. Simulations of periodic Fday measurements, as might be provided by a mobile flux tower, indicated that such measurements could be used in combination with iNDVI to accurately predict Fday. These periodic measurements could maximize the utility of expensive flux towers for evaluating various carbon management strategies, carbon certification, and validation and calibration of carbon flux models. ?? 2003 Elsevier Science Inc. All rights reserved.

Validation of a Solid Rocket Motor Internal Environment Model

NASA Technical Reports Server (NTRS)

Martin, Heath T.

2017-01-01

In a prior effort, a thermal/fluid model of the interior of Penn State University's laboratory-scale Insulation Test Motor (ITM) was constructed to predict both the convective and radiative heat transfer to the interior walls of the ITM with a minimum of empiricism. These predictions were then compared to values of total and radiative heat flux measured in a previous series of ITM test firings to assess the capabilities and shortcomings of the chosen modeling approach. Though the calculated fluxes reasonably agreed with those measured during testing, this exercise revealed means of improving the fidelity of the model to, in the case of the thermal radiation, enable direct comparison of the measured and calculated fluxes and, for the total heat flux, compute a value indicative of the average measured condition. By replacing the P1-Approximation with the discrete ordinates (DO) model for the solution of the gray radiative transfer equation, the radiation intensity field in the optically thin region near the radiometer is accurately estimated, allowing the thermal radiation flux to be calculated on the heat-flux sensor itself, which was then compared directly to the measured values. Though the fully coupling the wall thermal response with the flow model was not attempted due to the excessive computational time required, a separate wall thermal response model was used to better estimate the average temperature of the graphite surfaces upstream of the heat flux gauges and improve the accuracy of both the total and radiative heat flux computations. The success of this modeling approach increases confidence in the ability of state-of-the-art thermal and fluid modeling to accurately predict SRM internal environments, offers corrections to older methods, and supplies a tool for further studies of the dynamics of SRM interiors.

Are Polar Field Magnetic Flux Concentrations Responsible for Missing Interplanetary Flux?

NASA Astrophysics Data System (ADS)

Linker, Jon A.; Downs, C.; Mikic, Z.; Riley, P.; Henney, C. J.; Arge, C. N.

2012-05-01

Magnetohydrodynamic (MHD) simulations are now routinely used to produce models of the solar corona and inner heliosphere for specific time periods. These models typically use magnetic maps of the photospheric magnetic field built up over a solar rotation, available from a number of ground-based and space-based solar observatories. The line-of-sight field at the Sun's poles is poorly observed, and the polar fields in these maps are filled with a variety of interpolation/extrapolation techniques. These models have been found to frequently underestimate the interplanetary magnetic flux (Riley et al., 2012, in press, Stevens et al., 2012, in press) near the minimum part of the cycle unless mitigating correction factors are applied. Hinode SOT observations indicate that strong concentrations of magnetic flux may be present at the poles (Tsuneta et al. 2008). The ADAPT flux evolution model (Arge et al. 2010) also predicts the appearance of such concentrations. In this paper, we explore the possibility that these flux concentrations may account for a significant amount of magnetic flux and alleviate discrepancies in interplanetary magnetic flux predictions. Research supported by AFOSR, NASA, and NSF.

Analysis and verification of a prediction model of solar energetic proton events

NASA Astrophysics Data System (ADS)

Wang, J.; Zhong, Q.

2017-12-01

The solar energetic particle event can cause severe radiation damages near Earth. The alerts and summary products of the solar energetic proton events were provided by the Space Environment Prediction Center (SEPC) according to the flux of the greater than 10 MeV protons taken by GOES satellite in geosynchronous orbit. The start of a solar energetic proton event is defined as the time when the flux of the greater than 10 MeV protons equals or exceeds 10 proton flux units (pfu). In this study, a model was developed to predict the solar energetic proton events, provide the warning for the solar energetic proton events at least minutes in advance, based on both the soft X-ray flux and integral proton flux taken by GOES. The quality of the forecast model was measured against verifications of accuracy, reliability, discrimination capability, and forecast skills. The peak flux and rise time of the solar energetic proton events in the six channels, >1MeV, >5 MeV, >10 MeV, >30 MeV, >50 MeV, >100 MeV, were also simulated and analyzed.

Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming.

PubMed

Wu, Stephen Gang; Wang, Yuxuan; Jiang, Wu; Oyetunde, Tolutola; Yao, Ruilian; Zhang, Xuehong; Shimizu, Kazuyuki; Tang, Yinjie J; Bao, Forrest Sheng

2016-04-01

13C metabolic flux analysis (13C-MFA) has been widely used to measure in vivo enzyme reaction rates (i.e., metabolic flux) in microorganisms. Mining the relationship between environmental and genetic factors and metabolic fluxes hidden in existing fluxomic data will lead to predictive models that can significantly accelerate flux quantification. In this paper, we present a web-based platform MFlux (http://mflux.org) that predicts the bacterial central metabolism via machine learning, leveraging data from approximately 100 13C-MFA papers on heterotrophic bacterial metabolisms. Three machine learning methods, namely Support Vector Machine (SVM), k-Nearest Neighbors (k-NN), and Decision Tree, were employed to study the sophisticated relationship between influential factors and metabolic fluxes. We performed a grid search of the best parameter set for each algorithm and verified their performance through 10-fold cross validations. SVM yields the highest accuracy among all three algorithms. Further, we employed quadratic programming to adjust flux profiles to satisfy stoichiometric constraints. Multiple case studies have shown that MFlux can reasonably predict fluxomes as a function of bacterial species, substrate types, growth rate, oxygen conditions, and cultivation methods. Due to the interest of studying model organism under particular carbon sources, bias of fluxome in the dataset may limit the applicability of machine learning models. This problem can be resolved after more papers on 13C-MFA are published for non-model species.

Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming

PubMed Central

Wu, Stephen Gang; Wang, Yuxuan; Jiang, Wu; Oyetunde, Tolutola; Yao, Ruilian; Zhang, Xuehong; Shimizu, Kazuyuki; Tang, Yinjie J.; Bao, Forrest Sheng

2016-01-01

13C metabolic flux analysis (13C-MFA) has been widely used to measure in vivo enzyme reaction rates (i.e., metabolic flux) in microorganisms. Mining the relationship between environmental and genetic factors and metabolic fluxes hidden in existing fluxomic data will lead to predictive models that can significantly accelerate flux quantification. In this paper, we present a web-based platform MFlux (http://mflux.org) that predicts the bacterial central metabolism via machine learning, leveraging data from approximately 100 13C-MFA papers on heterotrophic bacterial metabolisms. Three machine learning methods, namely Support Vector Machine (SVM), k-Nearest Neighbors (k-NN), and Decision Tree, were employed to study the sophisticated relationship between influential factors and metabolic fluxes. We performed a grid search of the best parameter set for each algorithm and verified their performance through 10-fold cross validations. SVM yields the highest accuracy among all three algorithms. Further, we employed quadratic programming to adjust flux profiles to satisfy stoichiometric constraints. Multiple case studies have shown that MFlux can reasonably predict fluxomes as a function of bacterial species, substrate types, growth rate, oxygen conditions, and cultivation methods. Due to the interest of studying model organism under particular carbon sources, bias of fluxome in the dataset may limit the applicability of machine learning models. This problem can be resolved after more papers on 13C-MFA are published for non-model species. PMID:27092947

Construction and completion of flux balance models from pathway databases.

PubMed

Latendresse, Mario; Krummenacker, Markus; Trupp, Miles; Karp, Peter D

2012-02-01

Flux balance analysis (FBA) is a well-known technique for genome-scale modeling of metabolic flux. Typically, an FBA formulation requires the accurate specification of four sets: biochemical reactions, biomass metabolites, nutrients and secreted metabolites. The development of FBA models can be time consuming and tedious because of the difficulty in assembling completely accurate descriptions of these sets, and in identifying errors in the composition of these sets. For example, the presence of a single non-producible metabolite in the biomass will make the entire model infeasible. Other difficulties in FBA modeling are that model distributions, and predicted fluxes, can be cryptic and difficult to understand. We present a multiple gap-filling method to accelerate the development of FBA models using a new tool, called MetaFlux, based on mixed integer linear programming (MILP). The method suggests corrections to the sets of reactions, biomass metabolites, nutrients and secretions. The method generates FBA models directly from Pathway/Genome Databases. Thus, FBA models developed in this framework are easily queried and visualized using the Pathway Tools software. Predicted fluxes are more easily comprehended by visualizing them on diagrams of individual metabolic pathways or of metabolic maps. MetaFlux can also remove redundant high-flux loops, solve FBA models once they are generated and model the effects of gene knockouts. MetaFlux has been validated through construction of FBA models for Escherichia coli and Homo sapiens. Pathway Tools with MetaFlux is freely available to academic users, and for a fee to commercial users. Download from: biocyc.org/download.shtml. mario.latendresse@sri.com Supplementary data are available at Bioinformatics online.

A Method to Constrain Genome-Scale Models with 13C Labeling Data

PubMed Central

García Martín, Héctor; Kumar, Vinay Satish; Weaver, Daniel; Ghosh, Amit; Chubukov, Victor; Mukhopadhyay, Aindrila; Arkin, Adam; Keasling, Jay D.

2015-01-01

Current limitations in quantitatively predicting biological behavior hinder our efforts to engineer biological systems to produce biofuels and other desired chemicals. Here, we present a new method for calculating metabolic fluxes, key targets in metabolic engineering, that incorporates data from 13C labeling experiments and genome-scale models. The data from 13C labeling experiments provide strong flux constraints that eliminate the need to assume an evolutionary optimization principle such as the growth rate optimization assumption used in Flux Balance Analysis (FBA). This effective constraining is achieved by making the simple but biologically relevant assumption that flux flows from core to peripheral metabolism and does not flow back. The new method is significantly more robust than FBA with respect to errors in genome-scale model reconstruction. Furthermore, it can provide a comprehensive picture of metabolite balancing and predictions for unmeasured extracellular fluxes as constrained by 13C labeling data. A comparison shows that the results of this new method are similar to those found through 13C Metabolic Flux Analysis (13C MFA) for central carbon metabolism but, additionally, it provides flux estimates for peripheral metabolism. The extra validation gained by matching 48 relative labeling measurements is used to identify where and why several existing COnstraint Based Reconstruction and Analysis (COBRA) flux prediction algorithms fail. We demonstrate how to use this knowledge to refine these methods and improve their predictive capabilities. This method provides a reliable base upon which to improve the design of biological systems. PMID:26379153

Utilizing patch and site level greenhouse-gas concentration measurements in tandem with the prognostic model, ecosys

NASA Astrophysics Data System (ADS)

Morin, T. H.; Rey Sanchez, C.; Bohrer, G.; Riley, W. J.; Angle, J.; Mekonnen, Z. A.; Stefanik, K. C.; Wrighton, K. C.

2016-12-01

Estimates of wetland greenhouse gas (GHG) budgets currently have large uncertainties. While wetlands are the largest source of natural methane (CH4) emissions worldwide, they are also important carbon dioxide (CO2) sinks. Determining the GHG budget of a wetland is challenging, particularly because wetlands have intrinsically temporally and spatially heterogeneous land cover patterns and complex dynamics of CH4 production and emissions. These issues pose challenges to both measuring and modeling GHG budgets from wetlands. To improve wetland GHG flux predictability, we utilized the ecosys model to predict CH4 fluxes from a natural temperate estuarine wetland in northern Ohio. Multiple patches of terrain (that included Typha spp. and Nelumbo lutea) were represented as separate grid cells in the model. Cells were initialized with measured values but were allowed to dynamically evolve in response to meteorological, hydrological, and thermodynamic conditions. Trace gas surface emissions were predicted as the end result of microbial activity, physical transport, and plant processes. Corresponding to each model gridcell, measurements of dissolved gas concentrations were conducted with pore-water dialysis samplers (peepers). The peeper measurements were taken via a series of tubes, providing an undisturbed observation of the pore water concentrations of in situ dissolved gases along a vertical gradient. Non-steady state chambers and a flux tower provided both patch level and integrated site-level fluxes of CO2 and CH4. New Typha chambers were also developed to enclose entire plants and segregate the plant fluxes from soil/water fluxes. We expect ecosys to predict the seasonal and diurnal fluxes of CH4 from within each land cover type and to resolve where CH4 is generated within the soil column and its transmission mechanisms. We demonstrate the need for detailed information at both the patch and site level when using models to predict whole wetland ecosystem-scale GHG budgets.

E-Flux2 and SPOT: Validated Methods for Inferring Intracellular Metabolic Flux Distributions from Transcriptomic Data.

PubMed

Kim, Min Kyung; Lane, Anatoliy; Kelley, James J; Lun, Desmond S

2016-01-01

Several methods have been developed to predict system-wide and condition-specific intracellular metabolic fluxes by integrating transcriptomic data with genome-scale metabolic models. While powerful in many settings, existing methods have several shortcomings, and it is unclear which method has the best accuracy in general because of limited validation against experimentally measured intracellular fluxes. We present a general optimization strategy for inferring intracellular metabolic flux distributions from transcriptomic data coupled with genome-scale metabolic reconstructions. It consists of two different template models called DC (determined carbon source model) and AC (all possible carbon sources model) and two different new methods called E-Flux2 (E-Flux method combined with minimization of l2 norm) and SPOT (Simplified Pearson cOrrelation with Transcriptomic data), which can be chosen and combined depending on the availability of knowledge on carbon source or objective function. This enables us to simulate a broad range of experimental conditions. We examined E. coli and S. cerevisiae as representative prokaryotic and eukaryotic microorganisms respectively. The predictive accuracy of our algorithm was validated by calculating the uncentered Pearson correlation between predicted fluxes and measured fluxes. To this end, we compiled 20 experimental conditions (11 in E. coli and 9 in S. cerevisiae), of transcriptome measurements coupled with corresponding central carbon metabolism intracellular flux measurements determined by 13C metabolic flux analysis (13C-MFA), which is the largest dataset assembled to date for the purpose of validating inference methods for predicting intracellular fluxes. In both organisms, our method achieves an average correlation coefficient ranging from 0.59 to 0.87, outperforming a representative sample of competing methods. Easy-to-use implementations of E-Flux2 and SPOT are available as part of the open-source package MOST (http://most.ccib.rutgers.edu/). Our method represents a significant advance over existing methods for inferring intracellular metabolic flux from transcriptomic data. It not only achieves higher accuracy, but it also combines into a single method a number of other desirable characteristics including applicability to a wide range of experimental conditions, production of a unique solution, fast running time, and the availability of a user-friendly implementation.

Improvement of solar-cycle prediction: Plateau of solar axial dipole moment

NASA Astrophysics Data System (ADS)

Iijima, H.; Hotta, H.; Imada, S.; Kusano, K.; Shiota, D.

2017-11-01

Aims: We report the small temporal variation of the axial dipole moment near the solar minimum and its application to the solar-cycle prediction by the surface flux transport (SFT) model. Methods: We measure the axial dipole moment using the photospheric synoptic magnetogram observed by the Wilcox Solar Observatory (WSO), the ESA/NASA Solar and Heliospheric Observatory Michelson Doppler Imager (MDI), and the NASA Solar Dynamics Observatory Helioseismic and Magnetic Imager (HMI). We also use the SFT model for the interpretation and prediction of the observed axial dipole moment. Results: We find that the observed axial dipole moment becomes approximately constant during the period of several years before each cycle minimum, which we call the axial dipole moment plateau. The cross-equatorial magnetic flux transport is found to be small during the period, although a significant number of sunspots are still emerging. The results indicate that the newly emerged magnetic flux does not contribute to the build up of the axial dipole moment near the end of each cycle. This is confirmed by showing that the time variation of the observed axial dipole moment agrees well with that predicted by the SFT model without introducing new emergence of magnetic flux. These results allow us to predict the axial dipole moment at the Cycle 24/25 minimum using the SFT model without introducing new flux emergence. The predicted axial dipole moment at the Cycle 24/25 minimum is 60-80 percent of Cycle 23/24 minimum, which suggests the amplitude of Cycle 25 is even weaker than the current Cycle 24. Conclusions: The plateau of the solar axial dipole moment is an important feature for the longer-term prediction of the solar cycle based on the SFT model.

Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models.

PubMed

Cotten, Cameron; Reed, Jennifer L

2013-01-30

Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets.

Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models

PubMed Central

2013-01-01

Background Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. Results In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. Conclusions This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets. PMID:23360254

User-Friendly Predictive Modeling of Greenhouse Gas (GHG) Fluxes and Carbon Storage in Tidal Wetlands

NASA Astrophysics Data System (ADS)

Ishtiaq, K. S.; Abdul-Aziz, O. I.

2015-12-01

We developed user-friendly empirical models to predict instantaneous fluxes of CO2 and CH4 from coastal wetlands based on a small set of dominant hydro-climatic and environmental drivers (e.g., photosynthetically active radiation, soil temperature, water depth, and soil salinity). The dominant predictor variables were systematically identified by applying a robust data-analytics framework on a wide range of possible environmental variables driving wetland greenhouse gas (GHG) fluxes. The method comprised of a multi-layered data-analytics framework, including Pearson correlation analysis, explanatory principal component and factor analyses, and partial least squares regression modeling. The identified dominant predictors were finally utilized to develop power-law based non-linear regression models to predict CO2 and CH4 fluxes under different climatic, land use (nitrogen gradient), tidal hydrology and salinity conditions. Four different tidal wetlands of Waquoit Bay, MA were considered as the case study sites to identify the dominant drivers and evaluate model performance. The study sites were dominated by native Spartina Alterniflora and characterized by frequent flooding and high saline conditions. The model estimated the potential net ecosystem carbon balance (NECB) both in gC/m2 and metric tonC/hectare by up-scaling the instantaneous predicted fluxes to the growing season and accounting for the lateral C flux exchanges between the wetlands and estuary. The entire model was presented in a single Excel spreadsheet as a user-friendly ecological engineering tool. The model can aid the development of appropriate GHG offset protocols for setting monitoring plans for tidal wetland restoration and maintenance projects. The model can also be used to estimate wetland GHG fluxes and potential carbon storage under various IPCC climate change and sea level rise scenarios; facilitating an appropriate management of carbon stocks in tidal wetlands and their incorporation into a potential carbon market.

KNT-artificial neural network model for flux prediction of ultrafiltration membrane producing drinking water.

PubMed

Oh, H K; Yu, M J; Gwon, E M; Koo, J Y; Kim, S G; Koizumi, A

2004-01-01

This paper describes the prediction of flux behavior in an ultrafiltration (UF) membrane system using a Kalman neuro training (KNT) network model. The experimental data was obtained from operating a pilot plant of hollow fiber UF membrane with groundwater for 7 months. The network was trained using operating conditions such as inlet pressure, filtration duration, and feed water quality parameters including turbidity, temperature and UV254. Pre-processing of raw data allowed the normalized input data to be used in sigmoid activation functions. A neural network architecture was structured by modifying the number of hidden layers, neurons and learning iterations. The structure of KNT-neural network with 3 layers and 5 neurons allowed a good prediction of permeate flux by 0.997 of correlation coefficient during the learning phase. Also the validity of the designed model was evaluated with other experimental data not used during the training phase and nonlinear flux behavior was accurately estimated with 0.999 of correlation coefficient and a lower error of prediction in the testing phase. This good flux prediction can provide preliminary criteria in membrane design and set up the proper cleaning cycle in membrane operation. The KNT-artificial neural network is also expected to predict the variation of transmembrane pressure during filtration cycles and can be applied to automation and control of full scale treatment plants.

Prediction of Greenhouse Gas (GHG) Fluxes from Coastal Salt Marshes using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Ishtiaq, K. S.; Abdul-Aziz, O. I.

2017-12-01

Coastal salt marshes are among the most productive ecosystems on earth. Given the complex interactions between ambient environment and ecosystem biological exchanges, it is difficult to predict the salt marsh greenhouse gas (GHG) fluxes (CO2 and CH4) from their environmental drivers. In this study, we developed an artificial neural network (ANN) model to robustly predict the salt marsh GHG fluxes using a limited number of input variables (photosynthetically active radiation, soil temperature and porewater salinity). The ANN parameterization involved an optimized 3-layer feed forward Levenberg-Marquardt training algorithm. Four tidal salt marshes of Waquoit Bay, MA — incorporating a gradient in land-use, salinity and hydrology — were considered as the case study sites. The wetlands were dominated by native Spartina Alterniflora, and characterized by high salinity and frequent flooding. The developed ANN model showed a good performance (training R2 = 0.87 - 0.96; testing R2 = 0.84 - 0.88) in predicting the fluxes across the case study sites. The model can be used to estimate wetland GHG fluxes and potential carbon balance under different IPCC climate change and sea level rise scenarios. The model can also aid the development of GHG offset protocols to set monitoring guidelines for restoration of coastal salt marshes.

Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.

Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration's (NASA) Terra satellite to scale up AmeriFlux NEE measurements to themore » continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE well (r = 0.73, p < 0.001). We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas.« less

Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory

DOE PAGES

Shi, Yuning; Eissenstat, David M.; He, Yuting; ...

2018-05-12

Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less

Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Yuning; Eissenstat, David M.; He, Yuting

Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less

Time-series analysis of energetic electron fluxes (1. 2 - 16 MeV) at geosynchronous altitude. Master's thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halpin, M.P.

This project used a Box and Jenkins time-series analysis of energetic electron fluxes measured at geosynchronous orbit in an effort to derive prediction models for the flux in each of five energy channels. In addition, the technique of transfer function modeling described by Box and Jenkins was used in an attempt to derive input-output relationships between the flux channels (viewed as the output) and the solar-wind speed or interplanetary magnetic field (IMF) north-south component, Bz, (viewed as the input). The transfer function modeling was done in order to investigate the theoretical dynamic relationship which is believed to exist between themore » solar wind, the IMF Bz, and the energetic electron flux in the magnetosphere. The models derived from the transfer-function techniques employed were also intended to be used in the prediction of flux values. The results from this study indicate that the energetic electron flux changes in the various channels are dependent on more than simply the solar-wind speed or the IMF Bz.« less

Comparisons of a Quantum Annealing and Classical Computer Neural Net Approach for Inferring Global Annual CO2 Fluxes over Land

NASA Astrophysics Data System (ADS)

Halem, M.; Radov, A.; Singh, D.

2017-12-01

Investigations of mid to high latitude atmospheric CO2 show growing amplitudes in seasonal variations over the past several decades. Recent high-resolution satellite measurements of CO2 concentration are now available for three years from the Orbiting Carbon Observatory-2. The Atmospheric Radiation Measurement (ARM) program of DOE has been making long-term CO2-flux measurements (in addition to CO2 concentration and an array of other meteorological quantities) at several towers and mobile sites located around the globe at half-hour frequencies. Recent papers have shown CO2 fluxes inferred by assimilating CO2 observations into ecosystem models are largely inconsistent with station observations. An investigation of how the biosphere has reacted to changes in atmospheric CO2 is essential to our understanding of potential climate-vegetation feedbacks. Thus, new approaches for calculating CO2-flux for assimilation into land surface models are necessary for improving the prediction of annual carbon uptake. In this study, we calculate and compare the predicted CO2 fluxes results employing a Feed Forward Backward Propagation Neural Network model on two architectures, (i) an IBM Minsky Computer node and (ii) a hybrid version of the ARC D-Wave quantum annealing computer. We compare the neural net results of predictions of CO2 flux from ARM station data for three different DOE ecosystem sites; an arid plains near Oklahoma City, a northern arctic site at Barrows AL, and a tropical rainforest site in the Amazon. Training times and predictive results for the calculating annual CO2 flux for the two architectures for each of the three sites are presented. Comparative results of predictions as measured by RMSE and MAE are discussed. Plots and correlations of observed vs predicted CO2 flux are also presented for all three sites. We show the estimated training times for quantum and classical calculations when extended to calculating global annual Carbon Uptake over land. We also examine the efficiency, dependability and resilience of the quantum neural net approach relative to classical computer systems in predicting annual CO2 flux globally.

Accuracy Quantification of the Loci-CHEM Code for Chamber Wall Heat Transfer in a GO2/GH2 Single Element Model Problem

NASA Technical Reports Server (NTRS)

West, Jeff; Westra, Doug; Lin, Jeff; Tucker, Kevin

2006-01-01

All solutions with Loci-CHEM achieved demonstrated steady state and mesh convergence. Preconditioning had no effect on solution accuracy and typically yields a 3-5times solution speed-up. The SST turbulence model has superior performance, relative to the data in the head end region, for the rise rate and peak heat flux. It was slightly worse than the others in the downstream region where all over-predicted the data by 30-100%.There was systematic mesh refinement in the unstructured volume and structured boundary layer areas produced only minor solution differences. Mesh convergence was achieved. Overall, Loci-CHEM satisfactorily predicts heat flux rise rate and peak heat flux and significantly over predicts the downstream heat flux.

Prediction Model for Relativistic Electrons at Geostationary Orbit

NASA Technical Reports Server (NTRS)

Khazanov, George V.; Lyatsky, Wladislaw

2008-01-01

We developed a new prediction model for forecasting relativistic (greater than 2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/interplanetary magnetic field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is stable and incredibly high (about 0.9). The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible.

Modeling the Relative Importance of Nutrient and Carbon Loads, Boundary Fluxes, and Sediment Fluxes on Gulf of Mexico Hypoxia.

PubMed

Feist, Timothy J; Pauer, James J; Melendez, Wilson; Lehrter, John C; DePetro, Phillip A; Rygwelski, Kenneth R; Ko, Dong S; Kreis, Russell G

2016-08-16

The Louisiana continental shelf in the northern Gulf of Mexico experiences bottom water hypoxia in the summer. In this study, we applied a biogeochemical model that simulates dissolved oxygen concentrations on the shelf in response to varying riverine nutrient and organic carbon loads, boundary fluxes, and sediment fluxes. Five-year model simulations demonstrated that midsummer hypoxic areas were most sensitive to riverine nutrient loads and sediment oxygen demand from settled organic carbon. Hypoxic area predictions were also sensitive to nutrient and organic carbon fluxes from lateral boundaries. The predicted hypoxic area decreased with decreases in nutrient loads, but the extent of change was influenced by the method used to estimate model boundary concentrations. We demonstrated that modeling efforts to predict changes in hypoxic area on the continental shelf in relationship to changes in nutrients should include representative boundary nutrient and organic carbon concentrations and functions for estimating sediment oxygen demand that are linked to settled organic carbon derived from water-column primary production. On the basis of our model analyses using the most representative boundary concentrations, nutrient loads would need to be reduced by 69% to achieve the Gulf of Mexico Nutrient Task Force Action Plan target hypoxic area of 5000 km(2).

A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions.

PubMed

Cheung, C Y Maurice; Williams, Thomas C R; Poolman, Mark G; Fell, David A; Ratcliffe, R George; Sweetlove, Lee J

2013-09-01

Flux balance models of metabolism generally utilize synthesis of biomass as the main determinant of intracellular fluxes. However, the biomass constraint alone is not sufficient to predict realistic fluxes in central heterotrophic metabolism of plant cells because of the major demand on the energy budget due to transport costs and cell maintenance. This major limitation can be addressed by incorporating transport steps into the metabolic model and by implementing a procedure that uses Pareto optimality analysis to explore the trade-off between ATP and NADPH production for maintenance. This leads to a method for predicting cell maintenance costs on the basis of the measured flux ratio between the oxidative steps of the oxidative pentose phosphate pathway and glycolysis. We show that accounting for transport and maintenance costs substantially improves the accuracy of fluxes predicted from a flux balance model of heterotrophic Arabidopsis cells in culture, irrespective of the objective function used in the analysis. Moreover, when the new method was applied to cells under control, elevated temperature and hyper-osmotic conditions, only elevated temperature led to a substantial increase in cell maintenance costs. It is concluded that the hyper-osmotic conditions tested did not impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources to cell maintenance. © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.

Evaluation of parameterization for turbulent fluxes of momentum and heat in stably stratified surface layers

NASA Astrophysics Data System (ADS)

Sodemann, H.; Foken, Th.

2003-04-01

General Circulation Models calculate the energy exchange between surface and atmosphere by means of parameterisations for turbulent fluxes of momentum and heat in the surface layer. However, currently implemented parameterisations after Louis (1979) create large discrepancies between predictions and observational data, especially in stably stratified surface layers. This work evaluates a new surface layer parameterisation proposed by Zilitinkevich et al. (2002), which was specifically developed to improve energy flux predictions in stable stratification. The evaluation comprises a detailed study of important surface layer characteristics, a sensitivity study of the parameterisation, and a direct comparison to observational data from Antarctica and predictions by the Louis (1979) parameterisation. The stability structure of the stable surface layer was found to be very complex, and strongly influenced fluxes in the surface layer. The sensitivity study revealed that the new parameterisation depends strongly on the ratio between roughness length and roughness temperature, which were both observed to be very variable parameters. The comparison between predictions and measurements showed good agreement for momentum fluxes, but large discrepancies for heat fluxes. A stability dependent evaluation of selected data showed better agreement for the new parameterisation of Zilitinkevich et al. (2002) than for the Louis (1979) scheme. Nevertheless, this comparison underlines the need for more detailed and physically sound concepts for parameterisations of heat fluxes in stably stratified surface layers. Zilitinkevich, S. S., V. Perov and J. C. King (2002). "Near-surface turbulent fluxes in stable stratification: Calculation techniques for use in General Circulation Models." Q. J. R. Meteorol. Soc. 128(583): 1571--1587. Louis, J. F. (1979). "A Parametric Model of Vertical Eddy Fluxes in the Atmosphere." Bound.-Layer Meteor. 17(2): 187--202.

The Empirical Low Energy Ion Flux Model for the Terrestrial Magnetosphere

NASA Technical Reports Server (NTRS)

Blackwell, William C.; Minow, Joseph I.; Diekmann, Anne M.

2007-01-01

This document includes a viewgraph presentation plus the full paper presented at the conference. The Living With a Star Ion Flux Model (IFM) is a radiation environment risk mitigation tool that provides magnetospheric ion flux values for varying geomagnetic disturbance levels in the geospace environment. IFM incorporates flux observations from the Polar and Geotail spacecraft in a single statistical flux model. IFM is an engineering environment model which predicts the proton flux not only in the magnetosphere, but also in the solar wind and magnetosheath phenomenological regions. This paper describes the ion flux databases that allows for IFM output to be correlated with the geomagnetic activity level, as represented by the Kp index.

Characterization And Partitioning Of CH4 And CO2 Eddy Flux Data Measured at NGEE-Arctic Sites

NASA Astrophysics Data System (ADS)

Dengel, S.; Chafe, O.; Curtis, J. B.; Biraud, S.; Torn, M. S.; Wullschleger, S. D.

2017-12-01

The high latitudes are experiencing rapid warming with permafrost ecosystems being highly vulnerable to this change. Since the advancement in Eddy Covariance (EC) measurements, the number of high latitude sites measuring greenhouse gases and energy (CO2, CH4 and H2O) fluxes is steadily increasing, with new sites being established each year. Data from these sites are not only valuable for annual carbon budget calculations, but also vital to the modeling community for improving their predictions of emission rates and trends. CH4 flux measurements are not as straightforward as CO2 fluxes. They tend to be less predictable or as easily interpretable as CO2 fluxes. Understanding CH4 emission patterns are often challenging. Moreover, gas flux fluctuations are spatially and temporally diverse, and in many cases event-based. An improvement in understanding would also contribute to improvements in the fidelity of model predictions. These rely on having high quality data, and thus will entail developing new QA/QC and gap-filling methods for Arctic systems, in particularly for CH4. Contributing to these challenges is the limited number of ancillary measurements carried out at many sites and the lack of standardized data processing, QA/QC, and gap-filling procedures, in particular for CH4. CO2, CH4, and energy flux measurements are ongoing at, both NGEE-Arctic/AmeriFlux, US-NGB (Arctic coastal plain), and US-NGC (subarctic tussock tundra) sites. The sites, with underlying continuous permafrost, show a high degree of inter-annual and seasonal variability in CH4 fluxes. In order to interpret this variability, we apply a variety of models, such as footprint characterization, generalized additive models, as well as artificial neural networks, in an attempt to decipher these diverse fluxes, patterns and events.

Estimating lake-atmosphere CO2 exchange

USGS Publications Warehouse

Anderson, D.E.; Striegl, Robert G.; Stannard, D.I.; Michmerhuizen, C.M.; McConnaughey, T.A.; LaBaugh, J.W.

1999-01-01

Lake-atmosphere CO2 flux was directly measured above a small, woodland lake using the eddy covariance technique and compared with fluxes deduced from changes in measured lake-water CO2 storage and with flux predictions from boundary-layer and surface-renewal models. Over a 3-yr period, lake-atmosphere exchanges of CO2 were measured over 5 weeks in spring, summer, and fall. Observed springtime CO2 efflux was large (2.3-2.7 ??mol m-2 s-1) immediately after lake-thaw. That efflux decreased exponentially with time to less than 0.2 ??mol m-2 s-1 within 2 weeks. Substantial interannual variability was found in the magnitudes of springtime efflux, surface water CO2 concentrations, lake CO2 storage, and meteorological conditions. Summertime measurements show a weak diurnal trend with a small average downward flux (-0.17 ??mol m-2 s-1) to the lake's surface, while late fall flux was trendless and smaller (-0.0021 ??mol m-2 s-1). Large springtime efflux afforded an opportunity to make direct measurement of lake-atmosphere fluxes well above the detection limits of eddy covariance instruments, facilitating the testing of different gas flux methodologies and air-water gas-transfer models. Although there was an overall agreement in fluxes determined by eddy covariance and those calculated from lake-water storage change in CO2, agreement was inconsistent between eddy covariance flux measurements and fluxes predicted by boundary-layer and surface-renewal models. Comparison of measured and modeled transfer velocities for CO2, along with measured and modeled cumulative CO2 flux, indicates that in most instances the surface-renewal model underpredicts actual flux. Greater underestimates were found with comparisons involving homogeneous boundary-layer models. No physical mechanism responsible for the inconsistencies was identified by analyzing coincidentally measured environmental variables.

A model to predict radon exhalation from walls to indoor air based on the exhalation from building material samples.

PubMed

Sahoo, B K; Sapra, B K; Gaware, J J; Kanse, S D; Mayya, Y S

2011-06-01

In recognition of the fact that building materials are an important source of indoor radon, second only to soil, surface radon exhalation fluxes have been extensively measured from the samples of these materials. Based on this flux data, several researchers have attempted to predict the inhalation dose attributable to radon emitted from walls and ceilings made up of these materials. However, an important aspect not considered in this methodology is the enhancement of the radon flux from the wall or the ceiling constructed using the same building material. This enhancement occurs mainly because of the change in the radon diffusion process from the former to the latter configuration. To predict the true radon flux from the wall based on the flux data of building material samples, we now propose a semi-empirical model involving radon diffusion length and the physical dimensions of the samples as well as wall thickness as other input parameters. This model has been established by statistically fitting the ratio of the solution to radon diffusion equations for the cases of three-dimensional cuboidal shaped building materials (such as brick, concrete block) and one dimensional wall system to a simple mathematical function. The model predictions have been validated against the measurements made at a new construction site. This model provides an alternative tool (substitute to conventional 1-D model) to estimate radon flux from a wall without relying on ²²⁶Ra content, radon emanation factor and bulk density of the samples. Moreover, it may be very useful in the context of developing building codes for radon regulation in new buildings. Copyright © 2011 Elsevier B.V. All rights reserved.

CFD modelling wall heat transfer inside a combustion chamber using ANSYS forte

NASA Astrophysics Data System (ADS)

Plengsa-ard, C.; Kaewbumrung, M.

2018-01-01

A computational model has been performed to analyze a wall heat transfer in a single cylinder, direct injection and four-stroke diesel engine. A direct integration using detailed chemistry CHEMKIN is employed in a combustion model and the Reynolds Averaged Navier Stokes (RANS) turbulence model is used to simulate the flow in the cylinder. To obtain heat flux results, a modified classical variable-density wall heat transfer model is also performed. The model is validated using experimental data from a CUMMINs engine operated with a conventional diesel combustion. One operating engine condition is simulated. Comparisons of simulated in-cylinder pressure and heat release rates with experimental data shows that the model predicts the cylinder pressure and heat release rates reasonably well. The contour plot of instantaneous temperature are presented. Also, the contours of predicted heat flux results are shown. The magnitude of peak heat fluxes as predicted by the wall heat transfer model is in the range of the typical measure values in diesel combustion.

The solar flare extreme ultraviolet to hard X-ray ratio

NASA Technical Reports Server (NTRS)

Mcclymont, A. N.; Canfield, R. C.

1986-01-01

Simultaneous measurements of the peak 10-1030 A extreme ultraviolet (EUV) flux enhancement and more than 10 keV hard X-ray (HXR) peak flux of many solar flare bursts, ranging over about four orders of magnitude in HXR intensity, are studied. A real departure from linearity is found in the relationship between the peak EUV and HXR fluxes in impulsive flare bursts. This relationship is well described by a given power law. Comparison of the predictions of the impulsive nonthermal thick-target electron beam model with observations shows that the model satisfactorily predicts the observed time differences between the HXR and EUV peaks and explains the data very well under given specific assumptions. It is concluded that the high-energy fluxes implied by the invariant area thick-target model cannot be completely ruled out, while the invariant area model with smaller low cutoff requires impossibly large beam densities. A later alternative thick-target model is suggested.

Radiation model predictions and validation using LDEF satellite data

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.

1993-01-01

Predictions and comparisons with the radiation dose measurements on Long Duration Exposure Facility (LDEF) by thermoluminescent dosimeters were made to evaluate the accuracy of models currently used in defining the ionizing radiation environment for low Earth orbit missions. The calculations include a detailed simulation of the radiation exposure (altitude and solar cycle variations, directional dependence) and shielding effects (three-dimensional LDEF geometry model) so that differences in the predicted and observed doses can be attributed to environment model uncertainties. The LDEF dose data are utilized to assess the accuracy of models describing the trapped proton flux, the trapped proton directionality, and the trapped electron flux.

Carbon and energy fluxes in cropland ecosystems: a model-data comparison

USGS Publications Warehouse

Lokupitiya, E.; Denning, A. Scott; Schaefer, K.; Ricciuto, D.; Anderson, R.; Arain, M. A.; Baker, I.; Barr, A. G.; Chen, G.; Chen, J.M.; Ciais, P.; Cook, D.R.; Dietze, M.C.; El Maayar, M.; Fischer, M.; Grant, R.; Hollinger, D.; Izaurralde, C.; Jain, A.; Kucharik, C.J.; Li, Z.; Liu, S.; Li, L.; Matamala, R.; Peylin, P.; Price, D.; Running, S. W.; Sahoo, A.; Sprintsin, M.; Suyker, A.E.; Tian, H.; Tonitto, Christina; Torn, M.S.; Verbeeck, Hans; Verma, S.B.; Xue, Y.

2016-01-01

Croplands are highly productive ecosystems that contribute to land–atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fed sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO2 seasonal uptake over agricultural regions.

Carbon and energy fluxes in cropland ecosystems: a model-data comparison

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lokupitiya, E.; Denning, A. S.; Schaefer, K.

2016-06-03

Croplands are highly productive ecosystems that contribute to land–atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fedmore » sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO 2 seasonal uptake over agricultural regions.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaggero, Daniele; Urbano, Alfredo; Valli, Mauro

We compute the γ-ray and neutrino diffuse emission of the Galaxy on the basis of a recently proposed phenomenological model characterized by radially dependent cosmic-ray (CR) transport properties. We show how this model, designed to reproduce both Fermi-LAT γ-ray data and local CR observables, naturally reproduces the anomalous TeV diffuse emission observed by Milagro in the inner Galactic plane. Above 100 TeV our picture predicts a neutrino flux that is about five (two) times larger than the neutrino flux computed with conventional models in the Galactic Center region (full-sky). Explaining in that way up to ∼25% of the flux measuredmore » by IceCube, we reproduce the full-sky IceCube spectrum adding an extra-Galactic component derived from the muonic neutrinos flux in the northern hemisphere. We also present precise predictions for the Galactic plane region where the flux is dominated by the Galactic emission.« less

Estimation of Net Ecosystem Carbon Exchange for the Conterminous UnitedStates by Combining MODIS and AmeriFlux Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.

Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board NASA's Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS andmore » AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a regression tree approach. The predictive model was trained and validated using NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE reasonably well at the site level. We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day period in 2005 using spatially-explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets for large areas.« less

TOPEX/POSEIDON orbit maintenance maneuver design

NASA Technical Reports Server (NTRS)

Bhat, R. S.; Frauenholz, R. B.; Cannell, Patrick E.

1990-01-01

The Ocean Topography Experiment (TOPEX/POSEIDON) mission orbit requirements are outlined, as well as its control and maneuver spacing requirements including longitude and time targeting. A ground-track prediction model dealing with geopotential, luni-solar gravity, and atmospheric-drag perturbations is considered. Targeting with all modeled perturbations is discussed, and such ground-track prediction errors as initial semimajor axis, orbit-determination, maneuver-execution, and atmospheric-density modeling errors are assessed. A longitude targeting strategy for two extreme situations is investigated employing all modeled perturbations and prediction errors. It is concluded that atmospheric-drag modeling errors are the prevailing ground-track prediction error source early in the mission during high solar flux, and that low solar-flux levels expected late in the experiment stipulate smaller maneuver magnitudes.

Origins of the high flux hohlraum model

NASA Astrophysics Data System (ADS)

Rosen, M. D.; Hinkel, D. E.; Williams, E. A.; Callahan, D. A.; Town, R. P. J.; Scott, H. A.; Kruer, W. L.; Suter, L. J.

2010-11-01

We review how the ``high flux model'' (HFM) helped clarify the performance of the Autumn 09 National Ignition Campaign (NIC) gas filled/capsule imploding hohlraum energetics campaign. This campaign showed good laser-hohlraum coupling, reasonably high drive, and implosion symmetry control via cross beam transfer. Mysteries that remained included the level and spectrum of the Stimulated Raman light, the tendency towards pancaked implosions, and drive that exceeded (standard model) predictions early in the campaign, and lagged those predictions late in the campaign. The HFM uses a detailed configuration accounting (DCA) atomic physics and a generous flux limiter (f=0.2) both of which contribute to predicting a hohlraum plasma that is cooler than the standard, XSN average atom, f=0.05 model. This cooler plasma proved to be key in solving all of those mysteries. Despite past successes of the HFM in correctly modeling Omega Laser Au sphere data and NIC empty hohlraum drive, the model lacked some credibility for this energetics campaign, because it predicted too much hohlraum drive. Its credibility was then boosted by a re-evaluation of the initially reported SRS levels.

Far-ultraviolet spectra and flux distributions of some Orion stars

NASA Technical Reports Server (NTRS)

Carruthers, G. R.; Heckathorn, H. M.; Opal, C. B.

1981-01-01

Far-ultraviolet (950-1800 A) spectra with about 2 A resolution were obtained of a number of stars in Orion during a sounding-rocket flight 1975 December 6. These spectra have been reduced to absolute flux distributions with the aid of preflight calibrations. The derived fluxes are in good agreement with model-atmosphere predictions and previous observations down to about 1200 A. In the 1200-1080 A range, the present results are in good agreement with model predictions but fall above the rocket measurements of Brune, Mount and Feldman. Below 1080 A, our measurements fall below the model predictions, reaching a deviation of a factor of 2 near 1010 A and a factor of 4 near 950 A. The present results are compared with those of Brune et al. via Copernicus U2 observations in this spectral range, and possible sources of discrepancies between the various observations and model-atmosphere predictions are discussed. Other aspects of the spectra, particularly with regard to spectral classification, are briefly discussed.

Multi-scale modeling of tsunami flows and tsunami-induced forces

NASA Astrophysics Data System (ADS)

Qin, X.; Motley, M. R.; LeVeque, R. J.; Gonzalez, F. I.

2016-12-01

The modeling of tsunami flows and tsunami-induced forces in coastal communities with the incorporation of the constructed environment is challenging for many numerical modelers because of the scale and complexity of the physical problem. A two-dimensional (2D) depth-averaged model can be efficient for modeling of waves offshore but may not be accurate enough to predict the complex flow with transient variance in vertical direction around constructed environments on land. On the other hand, using a more complex three-dimensional model is much more computational expensive and can become impractical due to the size of the problem and the meshing requirements near the built environment. In this study, a 2D depth-integrated model and a 3D Reynolds Averaged Navier-Stokes (RANS) model are built to model a 1:50 model-scale, idealized community, representative of Seaside, OR, USA, for which existing experimental data is available for comparison. Numerical results from the two numerical models are compared with each other as well as experimental measurement. Both models predict the flow parameters (water level, velocity, and momentum flux in the vicinity of the buildings) accurately, in general, except for time period near the initial impact, where the depth-averaged models can fail to capture the complexities in the flow. Forces predicted using direct integration of predicted pressure on structural surfaces from the 3D model and using momentum flux from the 2D model with constructed environment are compared, which indicates that force prediction from the 2D model is not always reliable in such a complicated case. Force predictions from integration of the pressure are also compared with forces predicted from bare earth momentum flux calculations to reveal the importance of incorporating the constructed environment in force prediction models.

Wind-invariant saltation heights imply linear scaling of aeolian saltation flux with shear stress.

PubMed

Martin, Raleigh L; Kok, Jasper F

2017-06-01

Wind-driven sand transport generates atmospheric dust, forms dunes, and sculpts landscapes. However, it remains unclear how the flux of particles in aeolian saltation-the wind-driven transport of sand in hopping trajectories-scales with wind speed, largely because models do not agree on how particle speeds and trajectories change with wind shear velocity. We present comprehensive measurements, from three new field sites and three published studies, showing that characteristic saltation layer heights remain approximately constant with shear velocity, in agreement with recent wind tunnel studies. These results support the assumption of constant particle speeds in recent models predicting linear scaling of saltation flux with shear stress. In contrast, our results refute widely used older models that assume that particle speed increases with shear velocity, thereby predicting nonlinear 3/2 stress-flux scaling. This conclusion is further supported by direct field measurements of saltation flux versus shear stress. Our results thus argue for adoption of linear saltation flux laws and constant saltation trajectories for modeling saltation-driven aeolian processes on Earth, Mars, and other planetary surfaces.

Wind-invariant saltation heights imply linear scaling of aeolian saltation flux with shear stress

PubMed Central

Martin, Raleigh L.; Kok, Jasper F.

2017-01-01

Wind-driven sand transport generates atmospheric dust, forms dunes, and sculpts landscapes. However, it remains unclear how the flux of particles in aeolian saltation—the wind-driven transport of sand in hopping trajectories—scales with wind speed, largely because models do not agree on how particle speeds and trajectories change with wind shear velocity. We present comprehensive measurements, from three new field sites and three published studies, showing that characteristic saltation layer heights remain approximately constant with shear velocity, in agreement with recent wind tunnel studies. These results support the assumption of constant particle speeds in recent models predicting linear scaling of saltation flux with shear stress. In contrast, our results refute widely used older models that assume that particle speed increases with shear velocity, thereby predicting nonlinear 3/2 stress-flux scaling. This conclusion is further supported by direct field measurements of saltation flux versus shear stress. Our results thus argue for adoption of linear saltation flux laws and constant saltation trajectories for modeling saltation-driven aeolian processes on Earth, Mars, and other planetary surfaces. PMID:28630907

Validation of PICA Ablation and Thermal-Response Model at Low Heat Flux

NASA Technical Reports Server (NTRS)

Milos, Frank S.; Chen, Yih-Kanq

2009-01-01

Phenolic Impregnated Carbon Ablator (PICA) was the forebody heatshield material on the Stardust sample-return capsule and is also a primary candidate material for the Mars Science Lander (MSL), the Orion Crew Module, and the SpaceX Dragon vehicle. As part of the heatshield qualification for Orion, physical and thermal properties of virgin and charred PICA were measured, and an ablation and thermal response model was developed. We validated the model by comparing it with recession and temperature data from stagnation arcjet tests conducted over a wide range of stagnation heat flux of 107 to 1102 W/sq cm. The effect of orthotropic thermal conductivity was evident in the thermal response of the arcjet models. In general, model predictions compared well with the data; however, the uncertainty of the recession prediction was greatest for heat fluxes below 200 W/sq cm. More recent MSL testing focused on the low heat flux regime of 45 to 250 W/sq cm. The new results confirm the recession uncertainty, especially for pressures below 6 kPa. In this work we focus on improving the model predictions for MSL and Orion tests below 250 W/sq cm.

Methodology for estimation of time-dependent surface heat flux due to cryogen spray cooling.

PubMed

Tunnell, James W; Torres, Jorge H; Anvari, Bahman

2002-01-01

Cryogen spray cooling (CSC) is an effective technique to protect the epidermis during cutaneous laser therapies. Spraying a cryogen onto the skin surface creates a time-varying heat flux, effectively cooling the skin during and following the cryogen spurt. In previous studies mathematical models were developed to predict the human skin temperature profiles during the cryogen spraying time. However, no studies have accounted for the additional cooling due to residual cryogen left on the skin surface following the spurt termination. We formulate and solve an inverse heat conduction (IHC) problem to predict the time-varying surface heat flux both during and following a cryogen spurt. The IHC formulation uses measured temperature profiles from within a medium to estimate the surface heat flux. We implement a one-dimensional sequential function specification method (SFSM) to estimate the surface heat flux from internal temperatures measured within an in vitro model in response to a cryogen spurt. Solution accuracy and experimental errors are examined using simulated temperature data. Heat flux following spurt termination appears substantial; however, it is less than that during the spraying time. The estimated time-varying heat flux can subsequently be used in forward heat conduction models to estimate temperature profiles in skin during and following a cryogen spurt and predict appropriate timing for onset of the laser pulse.

An investigation of transition boiling mechanisms of subcooled water under forced convective conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kwang-Won, Lee; Sang-Yong, Lee

1995-09-01

A mechanistic model for forced convective transition boiling has been developed to investigate transition boiling mechanisms and to predict transition boiling heat flux realistically. This model is based on a postulated multi-stage boiling process occurring during the passage time of the elongated vapor blanket specified at a critical heat flux (CHF) condition. Between the departure from nucleate boiling (DNB) and the departure from film boiling (DFB) points, the boiling heat transfer is established through three boiling stages, namely, the macrolayer evaporation and dryout governed by nucleate boiling in a thin liquid film and the unstable film boiling characterized by themore » frequent touches of the interface and the heated wall. The total heat transfer rates after the DNB is weighted by the time fractions of each stage, which are defined as the ratio of each stage duration to the vapor blanket passage time. The model predictions are compared with some available experimental transition boiling data. The parametric effects of pressure, mass flux, inlet subcooling on the transition boiling heat transfer are also investigated. From these comparisons, it can be seen that this model can identify the crucial mechanisms of forced convective transition boiling, and that the transition boiling heat fluxes including the maximum heat flux and the minimum film boiling heat flux are well predicted at low qualities/high pressures near 10 bar. In future, this model will be improved in the unstable film boiling stage and generalized for high quality and low pressure situations.« less

New Techniques Used in Modeling the 2017 Total Solar Eclipse: Energizing and Heating the Large-Scale Corona

NASA Astrophysics Data System (ADS)

Downs, Cooper; Mikic, Zoran; Linker, Jon A.; Caplan, Ronald M.; Lionello, Roberto; Torok, Tibor; Titov, Viacheslav; Riley, Pete; Mackay, Duncan; Upton, Lisa

2017-08-01

Over the past two decades, our group has used a magnetohydrodynamic (MHD) model of the corona to predict the appearance of total solar eclipses. In this presentation we detail recent innovations and new techniques applied to our prediction model for the August 21, 2017 total solar eclipse. First, we have developed a method for capturing the large-scale energized fields typical of the corona, namely the sheared/twisted fields built up through long-term processes of differential rotation and flux-emergence/cancellation. Using inferences of the location and chirality of filament channels (deduced from a magnetofrictional model driven by the evolving photospheric field produced by the Advective Flux Transport model), we tailor a customized boundary electric field profile that will emerge shear along the desired portions of polarity inversion lines (PILs) and cancel flux to create long twisted flux systems low in the corona. This method has the potential to improve the morphological shape of streamers in the low solar corona. Second, we apply, for the first time in our eclipse prediction simulations, a new wave-turbulence-dissipation (WTD) based model for coronal heating. This model has substantially fewer free parameters than previous empirical heating models, but is inherently sensitive to the 3D geometry and connectivity of the coronal field---a key property for modeling/predicting the thermal-magnetic structure of the solar corona. Overall, we will examine the effect of these considerations on white-light and EUV observables from the simulations, and present them in the context of our final 2017 eclipse prediction model.Research supported by NASA's Heliophysics Supporting Research and Living With a Star Programs.

The application of neural network model to the simulation nitrous oxide emission in the hydro-fluctuation belt of Three Gorges Reservoir

NASA Astrophysics Data System (ADS)

Song, Lanlan

2017-04-01

Nitrous oxide is much more potent greenhouse gas than carbon dioxide. However, the estimation of N2O flux is usually clouded with uncertainty, mainly due to high spatial and temporal variations. This hampers the development of general mechanistic models for N2O emission as well, as most previously developed models were empirical or exhibited low predictability with numerous assumptions. In this study, we tested General Regression Neural Networks (GRNN) as an alternative to classic empirical models for simulating N2O emission in riparian zones of Reservoirs. GRNN and nonlinear regression (NLR) were applied to estimate the N2O flux of 1-year observations in riparian zones of Three Gorge Reservoir. NLR resulted in lower prediction power and higher residuals compared to GRNN. Although nonlinear regression model estimated similar average values of N2O, it could not capture the fluctuation patterns accurately. In contrast, GRNN model achieved a fairly high predictability, with an R2 of 0.59 for model validation, 0.77 for model calibration (training), and a low root mean square error (RMSE), indicating a high capacity to simulate the dynamics of N2O flux. According to a sensitivity analysis of the GRNN, nonlinear relationships between input variables and N2O flux were well explained. Our results suggest that the GRNN developed in this study has a greater performance in simulating variations in N2O flux than nonlinear regressions.

The Predictability of Advection-dominated Flux-transport Solar Dynamo Models

NASA Astrophysics Data System (ADS)

Sanchez, Sabrina; Fournier, Alexandre; Aubert, Julien

2014-01-01

Space weather is a matter of practical importance in our modern society. Predictions of forecoming solar cycles mean amplitude and duration are currently being made based on flux-transport numerical models of the solar dynamo. Interested in the forecast horizon of such studies, we quantify the predictability window of a representative, advection-dominated, flux-transport dynamo model by investigating its sensitivity to initial conditions and control parameters through a perturbation analysis. We measure the rate associated with the exponential growth of an initial perturbation of the model trajectory, which yields a characteristic timescale known as the e-folding time τ e . The e-folding time is shown to decrease with the strength of the α-effect, and to increase with the magnitude of the imposed meridional circulation. Comparing the e-folding time with the solar cycle periodicity, we obtain an average estimate for τ e equal to 2.76 solar cycle durations. From a practical point of view, the perturbations analyzed in this work can be interpreted as uncertainties affecting either the observations or the physical model itself. After reviewing these, we discuss their implications for solar cycle prediction.

North Atlantic climate model bias influence on multiyear predictability

NASA Astrophysics Data System (ADS)

Wu, Y.; Park, T.; Park, W.; Latif, M.

2018-01-01

The influences of North Atlantic biases on multiyear predictability of unforced surface air temperature (SAT) variability are examined in the Kiel Climate Model (KCM). By employing a freshwater flux correction over the North Atlantic to the model, which strongly alleviates both North Atlantic sea surface salinity (SSS) and sea surface temperature (SST) biases, the freshwater flux-corrected integration depicts significantly enhanced multiyear SAT predictability in the North Atlantic sector in comparison to the uncorrected one. The enhanced SAT predictability in the corrected integration is due to a stronger and more variable Atlantic Meridional Overturning Circulation (AMOC) and its enhanced influence on North Atlantic SST. Results obtained from preindustrial control integrations of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) support the findings obtained from the KCM: models with large North Atlantic biases tend to have a weak AMOC influence on SAT and exhibit a smaller SAT predictability over the North Atlantic sector.

Measuring and modeling the effects of drainage water management on soil greenhouse gas fluxes from corn and soybean fields.

PubMed

Nangia, V; Sunohara, M D; Topp, E; Gregorich, E G; Drury, C F; Gottschall, N; Lapen, D R

2013-11-15

Controlled tile drainage can boost crop yields and improve water quality, but it also has the potential to increase GHG emissions. This study compared in-situ chamber-based measures of soil CH4, N2O, and CO2 fluxes for silt loam soil under corn and soybean cropping with conventional tile drainage (UTD) and controlled tile drainage (CTD). A semi-empirical model (NEMIS-NOE) was also used to predict soil N2O fluxes from soils using observed soil data. Observed N2O and CH4 fluxes between UTD and CTD fields during the farming season were not significantly different at 0.05 level. Soils were primarily a sink for CH4 but in some cases a source (sources were associated exclusively with CTD). The average N2O fluxes measured ranged between 0.003 and 0.028 kg N ha(-1) day(-1). There were some significantly higher (p ≤ 0.05) CO2 fluxes associated with CTD relative to UTD during some years of study. Correlation analyses indicated that the shallower the water table, the greater the CO2 fluxes. Higher corn plant C for CTD tended to offset estimated higher CTD CO2 C losses via soil respiration by ∼100-300 kg C ha(-1). There were good fits between observed and predicted (NEMIS-NOE) N2O fluxes for corn (R(2) = 0.70) and soybean (R(2) = 0.53). Predicted N2O fluxes were higher for CTD for approximately 70% of the paired-field study periods suggesting that soil physical factors, such as water-filled pore space, imposed by CTD have potentially strong impacts on net N fluxes. Model predictions of daily cumulative N2O fluxes for the agronomically-active study period for corn-CTD and corn-UTD, as a percentage of total N fertilizer applied, were 3.1% and 2.6%, respectively. For predicted N2O fluxes on basis of yield units, indices were 0.0005 and 0.0004 (kg N kg(-1) crop grain yield) for CTD and UTD corn fields, respectively, and 0.0011 and 0.0005 for CTD and UTD soybean fields, respectively. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Hubble Space Telescope CALSPEC Flux Standards: Sirius (and Vega)

NASA Astrophysics Data System (ADS)

Bohlin, R. C.

2014-06-01

The Space Telescope Imaging Spectrograph (STIS) has measured the flux for Sirius from 0.17 to 1.01 μm on the Hubble Space Telescope (HST) White Dwarf scale. Because of the cool debris disk around Vega, Sirius is commonly recommended as the primary IR flux standard. The measured STIS flux agrees well with predictions of a special Kurucz model atmosphere, adding confidence to the modeled IR flux predictions. The IR flux agrees to 2%-3% with respect to the standard template of Cohen and to 2% with the Midcourse Space Experiment absolute flux measurements in the mid-IR. A weighted average of the independent visible and mid-IR absolute flux measures implies that the monochromatic flux at 5557.5 Å (5556 Å in air) for Sirius and Vega, respectively, is 1.35 × 10-8 and 3.44 × 10-9 erg cm-2 s-1 Å-1 with formal uncertainties of 0.5%. Contrary to previously published conclusions, the Hipparcos photometry offers no support for the variability of Vega. Pulse pileup severely affects the Hp photometry for the brightest stars.

A metabolite-centric view on flux distributions in genome-scale metabolic models

PubMed Central

2013-01-01

Background Genome-scale metabolic models are important tools in systems biology. They permit the in-silico prediction of cellular phenotypes via mathematical optimisation procedures, most importantly flux balance analysis. Current studies on metabolic models mostly consider reaction fluxes in isolation. Based on a recently proposed metabolite-centric approach, we here describe a set of methods that enable the analysis and interpretation of flux distributions in an integrated metabolite-centric view. We demonstrate how this framework can be used for the refinement of genome-scale metabolic models. Results We applied the metabolite-centric view developed here to the most recent metabolic reconstruction of Escherichia coli. By compiling the balance sheets of a small number of currency metabolites, we were able to fully characterise the energy metabolism as predicted by the model and to identify a possibility for model refinement in NADPH metabolism. Selected branch points were examined in detail in order to demonstrate how a metabolite-centric view allows identifying functional roles of metabolites. Fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass were identified as enzymatic reactions that can carry high fluxes in the model but are unlikely to exhibit significant activity in vivo. Performing a metabolite essentiality analysis, unconstrained import and export of iron ions could be identified as potentially problematic for the quality of model predictions. Conclusions The system-wide analysis of split ratios and branch points allows a much deeper insight into the metabolic network than reaction-centric analyses. Extending an earlier metabolite-centric approach, the methods introduced here establish an integrated metabolite-centric framework for the interpretation of flux distributions in genome-scale metabolic networks that can complement the classical reaction-centric framework. Analysing fluxes and their metabolic context simultaneously opens the door to systems biological interpretations that are not apparent from isolated reaction fluxes. Particularly powerful demonstrations of this are the analyses of the complete metabolic contexts of energy metabolism and the folate-dependent one-carbon pool presented in this work. Finally, a metabolite-centric view on flux distributions can guide the refinement of metabolic reconstructions for specific growth scenarios. PMID:23587327

Modeling and Optimization of NLDH/PVDF Ultrafiltration Nanocomposite Membrane Using Artificial Neural Network-Genetic Algorithm Hybrid.

PubMed

Arefi-Oskoui, Samira; Khataee, Alireza; Vatanpour, Vahid

2017-07-10

In this research, MgAl-CO 3 2- nanolayered double hydroxide (NLDH) was synthesized through a facile coprecipitation method, followed by a hydrothermal treatment. The prepared NLDHs were used as a hydrophilic nanofiller for improving the performance of the PVDF-based ultrafiltration membranes. The main objective of this research was to obtain the optimized formula of NLDH/PVDF nanocomposite membrane presenting the best performance using computational techniques as a cost-effective method. For this aim, an artificial neural network (ANN) model was developed for modeling and expressing the relationship between the performance of the nanocomposite membrane (pure water flux, protein flux and flux recovery ratio) and the affecting parameters including the NLDH, PVP 29000 and polymer concentrations. The effects of the mentioned parameters and the interaction between the parameters were investigated using the contour plot predicted with the developed model. Scanning electron microscopy (SEM), atomic force microscopy (AFM), and water contact angle techniques were applied to characterize the nanocomposite membranes and to interpret the predictions of the ANN model. The developed ANN model was introduced to genetic algorithm (GA) as a bioinspired optimizer to determine the optimum values of input parameters leading to high pure water flux, protein flux, and flux recovery ratio. The optimum values for NLDH, PVP 29000 and the PVDF concentration were determined to be 0.54, 1, and 18 wt %, respectively. The performance of the nanocomposite membrane prepared using the optimum values proposed by GA was investigated experimentally, in which the results were in good agreement with the values predicted by ANN model with error lower than 6%. This good agreement confirmed that the nanocomposite membranes prformance could be successfully modeled and optimized by ANN-GA system.

Comparison and evaluation of model structures for the simulation of pollution fluxes in a tile-drained river basin.

PubMed

Hoang, Linh; van Griensven, Ann; van der Keur, Peter; Refsgaard, Jens Christian; Troldborg, Lars; Nilsson, Bertel; Mynett, Arthur

2014-01-01

The European Union Water Framework Directive requires an integrated pollution prevention plan at the river basin level. Hydrological river basin modeling tools are therefore promising tools to support the quantification of pollution originating from different sources. A limited number of studies have reported on the use of these models to predict pollution fluxes in tile-drained basins. This study focused on evaluating different modeling tools and modeling concepts to quantify the flow and nitrate fluxes in the Odense River basin using DAISY-MIKE SHE (DMS) and the Soil and Water Assessment Tool (SWAT). The results show that SWAT accurately predicted flow for daily and monthly time steps, whereas simulation of nitrate fluxes were more accurate at a monthly time step. In comparison to the DMS model, which takes into account the uncertainty of soil hydraulic and slurry parameters, SWAT results for flow and nitrate fit well within the range of DMS simulated values in high-flow periods but were slightly lower in low-flow periods. Despite the similarities of simulated flow and nitrate fluxes at the basin outlet, the two models predicted very different separations into flow components (overland flow, tile drainage, and groundwater flow) as well as nitrate fluxes from flow components. It was concluded that the assessment on which the model provides a better representation of the reality in terms of flow paths should not only be based on standard statistical metrics for the entire river basin but also needs to consider additional data, field experiments, and opinions of field experts. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Evaluation of the DayCent model to predict carbon fluxes in French crop sites

NASA Astrophysics Data System (ADS)

Fujisaki, Kenji; Martin, Manuel P.; Zhang, Yao; Bernoux, Martial; Chapuis-Lardy, Lydie

2017-04-01

Croplands in temperate regions are an important component of the carbon balance and can act as a sink or a source of carbon, depending on pedoclimatic conditions and management practices. Therefore the evaluation of carbon fluxes in croplands by modelling approach is relevant in the context of global change. This study was part of the Comete-Global project funded by the multi-Partner call FACCE JPI. Carbon fluxes, net ecosystem exchange (NEE), leaf area index (LAI), biomass, and grain production were simulated at the site level in three French crop experiments from the CarboEurope project. Several crops were studied, like winter wheat, rapeseed, barley, maize, and sunflower. Daily NEE was measured with eddy covariance and could be partitioned between gross primary production (GPP) and total ecosystem respiration (TER). Measurements were compared to DayCent simulations, a process-based model predicting plant production and soil organic matter turnover at daily time step. We compared two versions of the model: the original one with a simplified plant module and a newer version that simulates LAI. Input data for modelling were soil properties, climate, and management practices. Simulations of grain yields and biomass production were acceptable when using optimized crop parameters. Simulation of NEE was also acceptable. GPP predictions were improved with the newer version of the model, eliminating temporal shifts that could be observed with the original model. TER was underestimated by the model. Predicted NEE was more sensitive to soil tillage and nitrogen applications than measured NEE. DayCent was therefore a relevant tool to predict carbon fluxes in French crops at the site level. The introduction of LAI in the model improved its performance.

Inference and Prediction of Metabolic Network Fluxes

PubMed Central

Nikoloski, Zoran; Perez-Storey, Richard; Sweetlove, Lee J.

2015-01-01

In this Update, we cover the basic principles of the estimation and prediction of the rates of the many interconnected biochemical reactions that constitute plant metabolic networks. This includes metabolic flux analysis approaches that utilize the rates or patterns of redistribution of stable isotopes of carbon and other atoms to estimate fluxes, as well as constraints-based optimization approaches such as flux balance analysis. Some of the major insights that have been gained from analysis of fluxes in plants are discussed, including the functioning of metabolic pathways in a network context, the robustness of the metabolic phenotype, the importance of cell maintenance costs, and the mechanisms that enable energy and redox balancing at steady state. We also discuss methodologies to exploit 'omic data sets for the construction of tissue-specific metabolic network models and to constrain the range of permissible fluxes in such models. Finally, we consider the future directions and challenges faced by the field of metabolic network flux phenotyping. PMID:26392262

Relativistic Electrons at Geostationary Orbit: Modeling Results

NASA Technical Reports Server (NTRS)

Khazanov, George V.; Lyatsky, Wladislaw

2008-01-01

We developed a new prediction model for forecasting relativistic (greater than 2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/interplanetary magnetic field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is stable and incredibly high (about 0.9). The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible.

Prediction of Continental-Scale Net Ecosystem Carbon Exchange by Combining MODIS and AmeriFlux Data

NASA Astrophysics Data System (ADS)

Xiao, J.; Zhuang, Q.

2007-12-01

There is growing interest in scaling up net ecosystem exchange (NEE) measured at eddy covariance flux towers to regional scales. Here we used remote sensing data from the MODIS instrument on board NASA's Terra satellite to extrapolate NEE measured at AmeriFlux sites to the continental scale. We combined MODIS data and NEE measurements from a number of AmeriFlux sites with a variety of vegetation types (e.g., forests, grasslands, shrublands, savannas, and croplands) to develop a predictive NEE model using a regression tree approach. The model was trained using 2000-2003 NEE measurements, and the performance of the model was evaluated using independent data over the period 2004-2006. We found that the model predicted NEE with reasonable accuracy at the continental scale. The R-squared values are 0.50 for all vegetation types combined and 0.72 for deciduous forests. We then applied the model to the conterminous U.S. and predicted NEE for each 500m by 500m cell over the period 2001-2006. Based on the wall-to-wall NEE estimates, we examined the spatial and temporal distributions of annual NEE and interannual variability of annual NEE across the conterminous U.S. over the study period (2001-2006). Our scaling-up approach implicitly considered the effects of climate variability, land use/land cover change, disturbances, extreme climate events, and management practices, and thus our annual NEE estimates represents the net carbon fluxes between the terrestrial biosphere and the atmosphere in the conterminous U.S.

The solar dynamo and prediction of sunspot cycles

NASA Astrophysics Data System (ADS)

Dikpati, Mausumi

2012-07-01

Much progress has been made in understanding the solar dynamo since Parker first developed the concepts of dynamo waves and magnetic buoyancy around 1955, and the German school first formulated the solar dynamo using the mean-field formalism. The essential ingredients of these mean-field dynamos are turbulent magnetic diffusivity, a source of lifting of flux, or 'alpha-effect', and differential rotation. With the advent of helioseismic and other observations at the Sun's photosphere and interior, as well as theoretical understanding of solar interior dynamics, solar dynamo models have evolved both in the realm of mean-field and beyond mean-field models. After briefly discussing the status of these models, I will focus on a class of mean-field model, called flux-transport dynamos, which include meridional circulation as an essential additional ingredient. Flux-transport dynamos have been successful in simulating many global solar cycle features, and have reached the stage that they can be used for making solar cycle predictions. Meridional circulation works in these models like a conveyor-belt, carrying a memory of the magnetic fields from 5 to 20 years back in past. The lower is the magnetic diffusivity, the longer is the model's memory. In the terrestrial system, the great-ocean conveyor-belt in oceanic models and Hadley, polar and Ferrel circulation cells in the troposphere, carry signatures from the past climatological events and influence the determination of future events. Analogously, the memory provided by the Sun's meridional circulation creates the potential for flux-transport dynamos to predict future solar cycle properties. Various groups in the world have built flux-transport dynamo-based predictive tools, which nudge the Sun's surface magnetic data and integrated forward in time to forecast the amplitude of the currently ascending cycle 24. Due to different initial conditions and different choices of unknown model-ingredients, predictions can vary; so it is for their cycle 24 forecasts. We all await the peak of cycle 24. I will close by discussing the prospects of improving dynamo-based predictive tools using more sophisticated data-assimilation techniques, such as the Ensemble Kalman Filter method and variational approaches.

Contaminant dispersal in bounded turbulent shear flow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wallace, J.M.; Bernard, P.S.; Chiang, K.F.

The dispersion of smoke downstream of a line source at the wall and at y{sup +} = 30 in a turbulent boundary layer has been predicted with a non-local model of the scalar fluxes {bar u}c and {bar v}c. The predicted plume from the wall source has been compared to high Schmidt number experimental measurements using a combination of hot-wire anemometry to obtain velocity component data synchronously with concentration data obtained optically. The predicted plumes from the source at y{sup +} = 30 and at the wall also have been compared to a low Schmidt number direct numerical simulation. Nearmore » the source, the non-local flux models give considerably better predictions than models which account solely for mean gradient transport. At a sufficient distance downstream the gradient models gives reasonably good predictions.« less

Transport phenomena governing nicotine emissions from electronic cigarettes: model formulation and experimental investigation

PubMed Central

Talih, Soha; Balhas, Zainab; Salman, Rola; El-Hage, Rachel; Karaoghlanian, Nareg; El-Hellani, Ahmad; Baassiri, Mohamad; Jaroudi, Ezzat; Eissenberg, Thomas; Saliba, Najat; Shihadeh, Alan

2017-01-01

Electronic cigarettes (ECIGs) electrically heat and aerosolize a liquid containing propylene glycol (PG), vegetable glycerin (VG), flavorants, water, and nicotine. ECIG effects and proposed methods to regulate them are controversial. One regulatory focal point involves nicotine emissions. We describe a mathematical model that predicts ECIG nicotine emissions. The model computes the vaporization rate of individual species by numerically solving the unsteady species and energy conservation equations. To validate model predictions, yields of nicotine, total particulate matter, PG, and VG were measured while manipulating puff topography, electrical power, and liquid composition across 100 conditions. Nicotine flux, the rate at which nicotine is emitted per unit time, was the primary outcome. Across conditions, the measured and computed nicotine flux were highly correlated (r = 0.85, p<.0001). As predicted, device power, nicotine concentration, PG/VG ratio, and puff duration influenced nicotine flux (p<.05), while water content and puff velocity did not. Additional empirical investigation revealed that PG/VG liquids act as ideal solutions, that liquid vaporization accounts for more than 95% of ECIG aerosol mass emissions, and that as device power increases the aerosol composition shifts towards the less volatile components of the parent liquid. To the extent that ECIG regulations focus on nicotine emissions, mathematical models like this one can be used to predict ECIG nicotine emissions and to test the effects of proposed regulation of factors that influence nicotine flux. PMID:28706340

Observed and modeled carbon and energy fluxes for agricultural sites under North American Carbon Program site-level interim synthesis

NASA Astrophysics Data System (ADS)

Lokupitiya, E. Y.; Denning, A.

2010-12-01

Croplands are unique, man-made ecosystems with dynamics mostly dependent on human decisions. Crops uptake a significant amount of Carbon dioxide (CO2) during their short growing seasons. Reliability of the available models to predict the carbon exchanges by croplands is important in estimating the cropland contribution towards overall land-atmosphere carbon exchange and global carbon cycle. The energy exchanges from croplands include both sensible and latent heat fluxes. This study focuses on analyzing the performance of 19 land surface models across five agricultural sites under the site-level interim synthesis of North American Carbon Program (NACP). Model simulations were performed using a common simulation protocol and input data, including gap-filled meteorological data corresponding to each site. The net carbon fluxes (i.e. net ecosystem exchange; NEE) and energy fluxes (sensible and latent heat) predicted by 12 models with sub-hourly/hourly temporal resolution and 7 models with daily temporal resolution were compared against the site-specific gap-filled observed flux tower data. Comparisons were made by site and crop type (i.e. maize, soybean, and wheat), mainly focusing on the coefficient of determination, correlation, root mean square error, and standard deviation. Analyses also compared the diurnal, seasonal, and inter-annual variability of the modeled fluxes against the observed data and the mean modeled data.

Testing a new flux rope model using the HELCATS CME catalogue

NASA Astrophysics Data System (ADS)

Rouillard, Alexis Paul; Lavarra, Michael

2017-04-01

We present a magnetically-driven flux rope model that computes the forces acting on a twisted magnetic flux rope from the Sun to 1AU. This model assumes a more realistic flux rope geometry than assumed before by these types of models. The balance of force is computed in an analogous manner to the well-known Chen flux-rope model. The 3-D vector components of the magnetic field measured by a probe flying through the flux rope can be extracted for any flux rope orientation imposed near the Sun. We test this model through a parametric study and a systematic comparison of the model with the HELCATS catalogues (imagery and in situ). We also report on our investigations of other physical mechanisms such as the shift of flux-surfaces associated with the magnetic forces acting to accelerate the flux rope from the lower to upper corona. Finally, we present an evaluation of this model for space-weather predictions. This work was partly funded by the HELCATS project under the FP7 EU contract number 606692.

Chandra Radiation Environment Modeling

NASA Technical Reports Server (NTRS)

Minow, Joseph I.; Blackwell, W. C.

2003-01-01

CRMFLX (Chandra Radiation Model of ion FluX) is a radiation environment risk mitigation tool for use as a decision aid in planning the operations times for Chandra's Advanced CCD Imaging Spectrometer (ACIS) detector. The accurate prediction of the proton flux environment with energies of 100 - 200 keV is needed in order to protect the ACIS detector against proton degradation. Unfortunately, protons of this energy are abundant in the region of space Chandra must operate, and on-board particle detectors do not measure proton flux levels of the required energy range. This presentation will describe the plasma environment data analysis and modeling basis of the CRMFLX engineering environment model developed to predict the proton flux in the solar wind, magnetosheath, and magnetosphere phenomenological regions of geospace. The recently released CRMFLX Version 2 implementation includes an algorithm that propagates flux from an observation location to other regions of the magnetosphere based on convective ExB and VB-curvature particle drift motions. This technique has the advantage of more completely filling out the database and makes maximum use of limited data obtained during high Kp periods or in areas of the magnetosphere with poor satellite flux measurement coverage.

Toward seamless hydrologic predictions across spatial scales

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-09-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

On the predictability of land surface fluxes from meteorological variables

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.

2018-01-01

Previous research has shown that land surface models (LSMs) are performing poorly when compared with relatively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appear to provide information about land surface fluxes that LSMs are not fully utilising. Here, we further quantify the information available in the meteorological forcing data that are used by LSMs for predicting land surface fluxes, by interrogating FLUXNET data, and extending the benchmarking methodology used in previous experiments. We show that substantial performance improvement is possible for empirical models using meteorological data alone, with no explicit vegetation or soil properties, thus setting lower bounds on a priori expectations on LSM performance. The process also identifies key meteorological variables that provide predictive power. We provide an ensemble of empirical benchmarks that are simple to reproduce and provide a range of behaviours and predictive performance, acting as a baseline benchmark set for future studies. We reanalyse previously published LSM simulations and show that there is more diversity between LSMs than previously indicated, although it remains unclear why LSMs are broadly performing so much worse than simple empirical models.

Genome-scale fluxes predicted under the guidance of enzyme abundance using a novel hyper-cube shrink algorithm.

PubMed

Xie, Zhengwei; Zhang, Tianyu; Ouyang, Qi

2018-02-01

One of the long-expected goals of genome-scale metabolic modelling is to evaluate the influence of the perturbed enzymes on flux distribution. Both ordinary differential equation (ODE) models and constraint-based models, like Flux balance analysis (FBA), lack the capacity to perform metabolic control analysis (MCA) for large-scale networks. In this study, we developed a hyper-cube shrink algorithm (HCSA) to incorporate the enzymatic properties into the FBA model by introducing a pseudo reaction V constrained by enzymatic parameters. Our algorithm uses the enzymatic information quantitatively rather than qualitatively. We first demonstrate the concept by applying HCSA to a simple three-node network, whereby we obtained a good correlation between flux and enzyme abundance. We then validate its prediction by comparison with ODE and with a synthetic network producing voilacein and analogues in Saccharomyces cerevisiae. We show that HCSA can mimic the state-state results of ODE. Finally, we show its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast. We show the ability of HCSA to operate without biomass flux and perform MCA to determine rate-limiting reactions. Algorithm was implemented by Matlab and C ++. The code is available at https://github.com/kekegg/HCSA. xiezhengwei@hsc.pku.edu.cn or qi@pku.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Metabolic network modeling with model organisms.

PubMed

Yilmaz, L Safak; Walhout, Albertha Jm

2017-02-01

Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions. Published by Elsevier Ltd.

Metabolic network modeling with model organisms

PubMed Central

Yilmaz, L. Safak; Walhout, Albertha J.M.

2017-01-01

Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions. PMID:28088694

Evaluating Clouds in Long-Term Cloud-Resolving Model Simulations with Observational Data

NASA Technical Reports Server (NTRS)

Zeng, Xiping; Tao, Wei-Kuo; Zhang, Minghua; Peters-Lidard, Christa; Lang, Stephen; Simpson, Joanne; Kumar, Sujay; Xie, Shaocheng; Eastman, Joseph L.; Shie, Chung-Lin;

Uncertainties in (E)UV model atmosphere fluxes

NASA Astrophysics Data System (ADS)

Rauch, T.

2008-04-01

Context: During the comparison of synthetic spectra calculated with two NLTE model atmosphere codes, namely TMAP and TLUSTY, we encounter systematic differences in the EUV fluxes due to the treatment of level dissolution by pressure ionization. Aims: In the case of Sirius B, we demonstrate an uncertainty in modeling the EUV flux reliably in order to challenge theoreticians to improve the theory of level dissolution. Methods: We calculated synthetic spectra for hot, compact stars using state-of-the-art NLTE model-atmosphere techniques. Results: Systematic differences may occur due to a code-specific cutoff frequency of the H I Lyman bound-free opacity. This is the case for TMAP and TLUSTY. Both codes predict the same flux level at wavelengths lower than about 1500 Å for stars with effective temperatures (T_eff) below about 30 000 K only, if the same cutoff frequency is chosen. Conclusions: The theory of level dissolution in high-density plasmas, which is available for hydrogen only should be generalized to all species. Especially, the cutoff frequencies for the bound-free opacities should be defined in order to make predictions of UV fluxes more reliable.

Investigation of metabolic objectives in cultured hepatocytes.

PubMed

Uygun, Korkut; Matthew, Howard W T; Huang, Yinlun

2007-06-15

Using optimization based methods to predict fluxes in metabolic flux balance models has been a successful approach for some microorganisms, enabling construction of in silico models and even inference of some regulatory motifs. However, this success has not been translated to mammalian cells. The lack of knowledge about metabolic objectives in mammalian cells is a major obstacle that prevents utilization of various metabolic engineering tools and methods for tissue engineering and biomedical purposes. In this work, we investigate and identify possible metabolic objectives for hepatocytes cultured in vitro. To achieve this goal, we present a special data-mining procedure for identifying metabolic objective functions in mammalian cells. This multi-level optimization based algorithm enables identifying the major fluxes in the metabolic objective from MFA data in the absence of information about critical active constraints of the system. Further, once the objective is determined, active flux constraints can also be identified and analyzed. This information can be potentially used in a predictive manner to improve cell culture results or clinical metabolic outcomes. As a result of the application of this method, it was found that in vitro cultured hepatocytes maximize oxygen uptake, coupling of urea and TCA cycles, and synthesis of serine and urea. Selection of these fluxes as the metabolic objective enables accurate prediction of the flux distribution in the system given a limited amount of flux data; thus presenting a workable in silico model for cultured hepatocytes. It is observed that an overall homeostasis picture is also emergent in the findings.

Improved measurement of the reactor antineutrino flux and spectrum at Daya Bay

DOE PAGES

An, F. P.; Balantekin, A. B.; Band, H. R.; ...

2017-01-01

Here, a new measurement of the reactor antineutrino flux and energy spectrum by the Daya Bay reactor neutrino experiment is reported. The antineutrinos were generated by six 2.9 GW th nuclear reactors and detected by eight antineutrino detectors deployed in two near (560 m and 600 m flux-weighted baselines) and one far (1640 m flux-weighted baseline) underground experimental halls. With 621 days of data, more than 1.2 million inverse beta decay (IBD) candidates were detected. The IBD yield in the eight detectors was measured, and the ratio of measured to predicted flux was found to be 0.946 ± 0.020 (0.992more » ± 0.021) for the Huber+Mueller (ILL+Vogel) model. A 2.9σ deviation was found in the measured IBD positron energy spectrum compared to the predictions. In particular, an excess of events in the region of 4$-$6 MeV was found in the measured spectrum, with a local significance of 4.4σ. Finally, a reactor antineutrino spectrum weighted by the IBD cross section is extracted for model-independent predictions.« less

Comments on QCD confinement, DTU model, and hadron-nucleus collisions. [Flux tube model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiu, C.B.

1981-04-01

Complementary discussions on the QCD flux tube model and the DTU model in connection with our previous work are given. It is also shown that the recent hadron-nucleus collision model has two important suppression mechanisms for particle production. Within the projectile cascade approximation, the model leads to the prediction of approximate anti ..nu.. universality.

The effect of physical parameterizations and initial data on the numerical prediction of the President's Day cyclone

NASA Technical Reports Server (NTRS)

Atlas, R.

1984-01-01

Results are presented from a series of forecast experiments which were conducted to assess the importance of large-scale dynamical processes, diabatic heating, and initial data to the prediction of the President's Day cyclone. The synoptic situation and NMC model forecasts for this case are summarized, and the analysis/forecast system and experiments are described. The GLAS Model forecast from the GLAS analysis at 0000 GMT 18 February is found to have correctly predicted intense coastal cyclogenesis and heavy precipitation. A forecast with surface heat and moisture fluxes eliminated failed to predict any cyclogenesis while a similar forecast with only the surface moisture flux excluded showed weak development. Diabatic heating resulting from oceanic fluxes significantly contributed to the generation of low-level cyclonic vorticity and the intensification and slow rate of movement of an upper level ridge over the western Atlantic.

A Comparison between High-Energy Radiation Background Models and SPENVIS Trapped-Particle Radiation Models

NASA Technical Reports Server (NTRS)

Krizmanic, John F.

2013-01-01

We have been assessing the effects of background radiation in low-Earth orbit for the next generation of X-ray and Cosmic-ray experiments, in particular for International Space Station orbit. Outside the areas of high fluxes of trapped radiation, we have been using parameterizations developed by the Fermi team to quantify the high-energy induced background. For the low-energy background, we have been using the AE8 and AP8 SPENVIS models to determine the orbit fractions where the fluxes of trapped particles are too high to allow for useful operation of the experiment. One area we are investigating is how the fluxes of SPENVIS predictions at higher energies match the fluxes at the low-energy end of our parameterizations. I will summarize our methodology for background determination from the various sources of cosmogenic and terrestrial radiation and how these compare to SPENVIS predictions in overlapping energy ranges.

Seasonality of Overstory and Understory Fluxes in a Semi-Arid Oak Savanna: What can be Learned from Comparing Measured and Modeled Fluxes?

NASA Astrophysics Data System (ADS)

Raz-Yaseef, N.; Sonnentag, O.; Kobayashi, H.; Chen, J. M.; Verfaillie, J. G.; Ma, S.; Baldocchi, D. D.

2011-12-01

Semi-arid climates experience large seasonal and inter-annual variability in radiation and precipitation, creating natural conditions adequate to study how year-to-year changes affect atmosphere-biosphere fluxes. Especially, savanna ecosystems, that combine tree and below-canopy components, create a unique environment in which phenology dramatically changes between seasons. We used a 10-year flux database in order to define seasonal and interannual variability of climatic inputs and fluxes, and evaluate model capability to reproduce observed variability. This is based on the perception that model capability to construct the deviation, and not the average, is important in order to correctly predict ecosystem sensitivity to climate change. Our research site is a low density and low LAI (0.8) semi-arid savanna, located at Tonzi Ranch, Northern California. In this system, trees are active during the warm season (Mar - Oct), and grasses are active during the wet season (Dec - May). Measurements of carbon and water fluxes above and below the tree canopy using eddy covariance and supplementary measurements have been made since 2001. Fluxes were simulated using bio-meteorological process-oriented ecosystem models: BEPS and 3D-CAONAK. Models were partly capable of reproducing fluxes on daily scales (R2=0.66). We then compared model outputs for different ecosystem components and seasons, and found distinct seasons with high correlations while other seasons were purely represented. Comparison was much higher for ET than for GPP. The understory was better simulated than the overstory. CANOAK overestimated spring understory fluxes, probably due to the capability to directly calculated 3D radiative transfer. BEPS underestimated spring understory fluxes, following the pre-description of grass die-off. Both models underestimated peak spring overstory fluxes. During winter tree dormant, modeled fluxes were null, but occasional high fluxes of both ET and GPP were measured following precipitation events, likely produced by an adverse measurement effect. This analysis enabled to pinpoint specific areas where models break, and stress that model capability to reproduce fluxes vary among seasons and ecosystem components. The combined response was such, that comparison decreases when ecosystem fluxes were partitioned between overstory and understory fluxes. Model performance decreases with time scale; while performance was high for some seasons, models were less capable of reproducing the high variability in understory fluxes vs. the conservative overstory fluxes on annual scales. Discrepancies were not always a result of models' faults; comparison largely improved when measurements of overstory fluxes during precipitation events were excluded. Conclusions raised from this research enable to answer the critical question of the level and type of details needed in order to correctly predict ecosystem respond to environmental and climatic change.

ANALYSIS OF WATER AND ENERGY FLUXES USING SATELLITE, ENERGY BALANCE MODELING AND OBSERVATIONS (Invited)

NASA Astrophysics Data System (ADS)

Irmak, A.

2009-12-01

Surface energy fluxes, including net radiation (Rn), sensible heat (H), latent heat (LE), and soil heat flux (G) are critical in surface energy balance of any terrain or landscapes. Estimation or measurement of these energy fluxes is important for completing the water balance in terrestrial ecosystems, and therefore accurately predicting the effects of global climate and land use change. The objectives of this study were to (1) use METRICtm (Mapping Evapotranspiration at high Resolution using Internalized Calibration) model for estimating land surface energy fluxes in Nebraska (NE) by utilizing satellite remote sensing data, (2) identify model bias in energy balance components compared with measurements from Bowen Ratio Energy Balance System (BREBS) in a subsurface drip-irrigated maize field in South-central Nebraska, and (3) understand the partitioning of available energy into latent heat for corn and soybean cropping systems at large scale. A total of 15 Landsat images were processed to estimate instantaneous surface energy fluxes at Landsat overpasses with METRIC model. Results showed that the model predictions of the surface energy fluxes and daily evapotranspiration were correlated well with the BREBS measurements. There is a need, however, to test the performance of the model with in-situ observations in other locations with different dataset before utilizing it for crucial water regulatory and policy decisions. The METRICtm approach illustrated how an ‘off-the-shelf’ model can be applied operationally over a significant time period and how that model behaves. The findings makes considerable contribution to our understanding of estimating land surface energy fluxes using remote sensing approach and experimentally describes the operational characteristics of METRICtm and presents its limitations.

Analytical Modeling of a Novel Transverse Flux Machine for Direct Drive Wind Turbine Applications: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasan, IIftekhar; Husain, Tausif; Uddin, Md Wasi

2015-08-24

This paper presents a nonlinear analytical model of a novel double-sided flux concentrating Transverse Flux Machine (TFM) based on the Magnetic Equivalent Circuit (MEC) model. The analytical model uses a series-parallel combination of flux tubes to predict the flux paths through different parts of the machine including air gaps, permanent magnets, stator, and rotor. The two-dimensional MEC model approximates the complex three-dimensional flux paths of the TFM and includes the effects of magnetic saturation. The model is capable of adapting to any geometry that makes it a good alternative for evaluating prospective designs of TFM compared to finite element solversmore » that are numerically intensive and require more computation time. A single-phase, 1-kW, 400-rpm machine is analytically modeled, and its resulting flux distribution, no-load EMF, and torque are verified with finite element analysis. The results are found to be in agreement, with less than 5% error, while reducing the computation time by 25 times.« less

Analytical Modeling of a Novel Transverse Flux Machine for Direct Drive Wind Turbine Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasan, IIftekhar; Husain, Tausif; Uddin, Md Wasi

2015-09-02

This paper presents a nonlinear analytical model of a novel double sided flux concentrating Transverse Flux Machine (TFM) based on the Magnetic Equivalent Circuit (MEC) model. The analytical model uses a series-parallel combination of flux tubes to predict the flux paths through different parts of the machine including air gaps, permanent magnets (PM), stator, and rotor. The two-dimensional MEC model approximates the complex three-dimensional flux paths of the TFM and includes the effects of magnetic saturation. The model is capable of adapting to any geometry which makes it a good alternative for evaluating prospective designs of TFM as compared tomore » finite element solvers which are numerically intensive and require more computation time. A single phase, 1 kW, 400 rpm machine is analytically modeled and its resulting flux distribution, no-load EMF and torque, verified with Finite Element Analysis (FEA). The results are found to be in agreement with less than 5% error, while reducing the computation time by 25 times.« less

Numerical modeling of incised-valley deposits in Tokyo lowland for the last 13 kyrs

NASA Astrophysics Data System (ADS)

Kubo, Y.; Syvitski, J. P.; Hutton, E. W.; Tanabe, S.

2006-12-01

A coupled-simulation by the hydrologic model HydroTrend and the stratigraphic model SedFlux is applied to the incised-valley-fill deposits in the Tokyo lowland for the last 13,000 years. The postglacial sediments supplied by paleo Tonegawa River have formed deltaic deposits controlled by eustatic sea-level rise after LGM. The effects of changes in sea level, climate, and morphology on the resultant architecture of the deposits are simulated and analyzed by the numerical models. Synthetic sediment flux from the paleo Tonegawa is computed by the hydrologic model HydroTrend. The model predicts variation in average rate of sediment production over geological time scale from changes in drainage area, precipitation, temperature and morphology. Random variation based on statistic climate data is added to the predicted average values to provide daily sediment discharge. The model prediction indicates that, despite 80% increase in drainage area in the past, competing effects of decreased precipitation resulted in relatively stable sediment discharge over the last 13,000 years. On the other hand, variation in daily sediment discharge shows drastic increase during infrequent storm events. Possible occurrence of hyperpycnal flows at the river mouth was indicated during such storms, which produced daily sediment load ten times larger than average yearly sediment discharge. The estimated sediment supply is used as input to the process-based forward-model 2D-SedFlux. SedFlux is able to simulate transport and deposition of sediments by such processes as river plume, bedload dumping and ocean storms with changing boundary conditions of sea level and basement morphology. The simulation is based on the initial paleo-morphology reconstructed from integrated core analysis from the area. 2D-SedFlux successfully predicts the formation of transgressive deposits and subsequent prograding delta deposits, and the results are comparable to general architecture of incised-valley fills in the area. Detailed comparison between the model predictions and field data shows some minor differences, which are then used to revise the local sea level curve.

Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism

PubMed Central

Fleming, R.M.T.; Thiele, I.; Provan, G.; Nasheuer, H.P.

2010-01-01

The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in E. coli and compare favourably with in silico prediction by flux balance analysis. PMID:20230840

Comparison of Optimal Thermodynamic Models of the Tricarboxylic Acid Cycle from Heterotrophs, Cyanobacteria, and Green Sulfur Bacteria.

PubMed

Thomas, Dennis G; Jaramillo-Riveri, Sebastian; Baxter, Douglas J; Cannon, William R

2014-12-26

We have applied a new stochastic simulation approach to predict the metabolite levels, material flux, and thermodynamic profiles of the oxidative TCA cycles found in E. coli and Synechococcus sp. PCC 7002, and in the reductive TCA cycle typical of chemolithoautotrophs and phototrophic green sulfur bacteria such as Chlorobaculum tepidum. The simulation approach is based on modeling states using statistical thermodynamics and employs an assumption similar to that used in transition state theory. The ability to evaluate the thermodynamics of metabolic pathways allows one to understand the relationship between coupling of energy and material gradients in the environment and the self-organization of stable biological systems, and it is shown that each cycle operates in the direction expected due to its environmental niche. The simulations predict changes in metabolite levels and flux in response to changes in cofactor concentrations that would be hard to predict without an elaborate model based on the law of mass action. In fact, we show that a thermodynamically unfavorable reaction can still have flux in the forward direction when it is part of a reaction network. The ability to predict metabolite levels, energy flow, and material flux should be significant for understanding the dynamics of natural systems and for understanding principles for engineering organisms for production of specialty chemicals.

A Simulation Model of Carbon Cycling and Methane Emissions in Amazon Wetlands

NASA Technical Reports Server (NTRS)

Potter, Christopher; Melack, John; Hess, Laura; Forsberg, Bruce; Novo, Evlyn Moraes; Klooster, Steven

2004-01-01

An integrative carbon study is investigating the hypothesis that measured fluxes of methane from wetlands in the Amazon region can be predicted accurately using a combination of process modeling of ecosystem carbon cycles and remote sensing of regional floodplain dynamics. A new simulation model has been build using the NASA- CASA concept for predicting methane production and emission fluxes in Amazon river and floodplain ecosystems. Numerous innovations area being made to model Amazon wetland ecosystems, including: (1) prediction of wetland net primary production (NPP) as the source for plant litter decomposition and accumulation of sediment organic matter in two major vegetation classes - flooded forests (varzea or igapo) and floating macrophytes, (2) representation of controls on carbon processing and methane evasion at the diffusive boundary layer, through the lake water column, and in wetland sediments as a function of changes in floodplain water level, (3) inclusion of surface emissions controls on wetland methane fluxes, including variations in daily surface temperature and of hydrostatic pressure linked to water level fluctuations. A model design overview and early simulation results are presented.

Using CO5BOLD models to predict the effects of granulation on colours .

NASA Astrophysics Data System (ADS)

Bonifacio, P.; Caffau, E.; Ludwig, H.-G.; Steffen, M.; Castelli, F.; Gallagher, A. J.; Prakapavičius, D.; Kučinskas, A.; Cayrel, R.; Freytag, B.; Plez, B.; Homeier, D.

In order to investigate the effects of granulation on fluxes and colours, we computed the emerging fluxes from the models in the CO5BOLD grid with metallicities [M/H]=0.0,-1.0,-2.0 and -3.0. These fluxes have been used to compute colours in different photometric systems. We explain here how our computations have been performed and provide some results.

Applying and Individual-Based Model to Simultaneously Evaluate Net Ecosystem Production and Tree Diameter Increment

NASA Astrophysics Data System (ADS)

Fang, F. J.

2017-12-01

Reconciling observations at fundamentally different scales is central in understanding the global carbon cycle. This study investigates a model-based melding of forest inventory data, remote-sensing data and micrometeorological-station data ("flux towers" estimating forest heat, CO2 and H2O fluxes). The individual tree-based model FORCCHN was used to evaluate the tree DBH increment and forest carbon fluxes. These are the first simultaneous simulations of the forest carbon budgets from flux towers and individual-tree growth estimates of forest carbon budgets using the continuous forest inventory data — under circumstances in which both predictions can be tested. Along with the global implications of such findings, this also improves the capacity for forest sustainable management and the comprehensive understanding of forest ecosystems. In forest ecology, diameter at breast height (DBH) of a tree significantly determines an individual tree's cross-sectional sapwood area, its biomass and carbon storage. Evaluation the annual DBH increment (ΔDBH) of an individual tree is central to understanding tree growth and forest ecology. Ecosystem Carbon flux is a consequence of key ecosystem processes in the forest-ecosystem carbon cycle, Gross and Net Primary Production (GPP and NPP, respectively) and Net Ecosystem Respiration (NEP). All of these closely relate with tree DBH changes and tree death. Despite advances in evaluating forest carbon fluxes with flux towers and forest inventories for individual tree ΔDBH, few current ecological models can simultaneously quantify and predict the tree ΔDBH and forest carbon flux.

Numerical prediction of the Mid-Atlantic states cyclone of 18-19 February 1979

NASA Technical Reports Server (NTRS)

Atlas, R.; Rosenberg, R.

1982-01-01

A series of forecast experiments was conducted to assess the accuracy of the GLAS model, and to determine the importance of large scale dynamical processes and diabatic heating to the cyclogenesis. The GLAS model correctly predicted intense coastal cyclogenesis and heavy precipitation. Repeated without surface heat and moisture fluxes, the model failed to predict any cyclone development. An extended range forecast, a forecast from the NMC analysis interpolated to the GLAS grid, and a forecast from the GLAS analysis with the surface moisture flux excluded predicted weak coastal low development. Diabatic heating resulting from oceanic fluxes significantly contributed to the generation of low level cyclonic vorticity and the intensification and slow rate of movement of an upper level ridge over the western Atlantic. As an upper level short wave trough approached this ridge, diabatic heating associated with the release of latent heat intensified, and the gradient of vorticity, vorticity advection and upper level divergence in advance of the trough were greatly increased, providing strong large scale forcing for the surface cyclogenesis.

Planetary X ray experiment: Supporting research for outer planets mission: Experiment definition phase

NASA Technical Reports Server (NTRS)

Hurley, K.; Anderson, K. A.

1972-01-01

Models of Jupiter's magnetosphere were examined to predict the X-ray flux that would be emitted in auroral or radiation zone processes. Various types of X-ray detection were investigated for energy resolution, efficiency, reliability, and background. From the model fluxes it was determined under what models Jovian X-rays could be detected.

Gyrokinetic modelling of the quasilinear particle flux for plasmas with neutral-beam fuelling

NASA Astrophysics Data System (ADS)

Narita, E.; Honda, M.; Nakata, M.; Yoshida, M.; Takenaga, H.; Hayashi, N.

2018-02-01

A quasilinear particle flux is modelled based on gyrokinetic calculations. The particle flux is estimated by determining factors, namely, coefficients of off-diagonal terms and a particle diffusivity. In this paper, the methodology to estimate the factors is presented using a subset of JT-60U plasmas. First, the coefficients of off-diagonal terms are estimated by linear gyrokinetic calculations. Next, to obtain the particle diffusivity, a semi-empirical approach is taken. Most experimental analyses for particle transport have assumed that turbulent particle fluxes are zero in the core region. On the other hand, even in the stationary state, the plasmas in question have a finite turbulent particle flux due to neutral-beam fuelling. By combining estimates of the experimental turbulent particle flux and the coefficients of off-diagonal terms calculated earlier, the particle diffusivity is obtained. The particle diffusivity should reflect a saturation amplitude of instabilities. The particle diffusivity is investigated in terms of the effects of the linear instability and linear zonal flow response, and it is found that a formula including these effects roughly reproduces the particle diffusivity. The developed framework for prediction of the particle flux is flexible to add terms neglected in the current model. The methodology to estimate the quasilinear particle flux requires so low computational cost that a database consisting of the resultant coefficients of off-diagonal terms and particle diffusivity can be constructed to train a neural network. The development of the methodology is the first step towards a neural-network-based particle transport model for fast prediction of the particle flux.

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE PAGES

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai; ...

2016-07-14

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Evaluation of DeNitrification DeComposition model for estimating ammonia fluxes from chemical fertilizer application

USDA-ARS?s Scientific Manuscript database

DeNitrification DeComposition (DNDC) model predictions of NH3 fluxes following chemical fertilizer application were evaluated by comparison to relaxed eddy accumulation (REA) measurements, in Central Illinois, United States, over the 2014 growing season of corn. Practical issues for evaluating closu...

7Be solar neutrino measurement with KamLAND

NASA Astrophysics Data System (ADS)

Gando, A.; Gando, Y.; Hanakago, H.; Ikeda, H.; Inoue, K.; Ishidoshiro, K.; Ishikawa, H.; Kishimoto, Y.; Koga, M.; Matsuda, R.; Matsuda, S.; Mitsui, T.; Motoki, D.; Nakajima, K.; Nakamura, K.; Obata, A.; Oki, A.; Oki, Y.; Otani, M.; Shimizu, I.; Shirai, J.; Suzuki, A.; Tamae, K.; Ueshima, K.; Watanabe, H.; Xu, B. D.; Yamada, S.; Yamauchi, Y.; Yoshida, H.; Kozlov, A.; Takemoto, Y.; Yoshida, S.; Grant, C.; Keefer, G.; McKee, D. W.; Piepke, A.; Banks, T. I.; Bloxham, T.; Freedman, S. J.; Fujikawa, B. K.; Han, K.; Hsu, L.; Ichimura, K.; Murayama, H.; O'Donnell, T.; Steiner, H. M.; Winslow, L. A.; Dwyer, D.; Mauger, C.; McKeown, R. D.; Zhang, C.; Berger, B. E.; Lane, C. E.; Maricic, J.; Miletic, T.; Learned, J. G.; Sakai, M.; Horton-Smith, G. A.; Tang, A.; Downum, K. E.; Tolich, K.; Efremenko, Y.; Kamyshkov, Y.; Perevozchikov, O.; Karwowski, H. J.; Markoff, D. M.; Tornow, W.; Detwiler, J. A.; Enomoto, S.; Heeger, K.; Decowski, M. P.; KamLAND Collaboration

2015-11-01

We report a measurement of the neutrino-electron elastic scattering rate of 862 keV 7Be solar neutrinos based on a 165.4 kt d exposure of KamLAND. The observed rate is 582 ±94 (kt d)-1, which corresponds to an 862-keV 7Be solar neutrino flux of (3.26 ±0.52 ) ×109cm-2s-1 , assuming a pure electron-flavor flux. Comparing this flux with the standard solar model prediction and further assuming three-flavor mixing, a νe survival probability of 0.66 ±0.15 is determined from the KamLAND data. Utilizing a global three-flavor oscillation analysis, we obtain a total 7Be solar neutrino flux of (5.82 ±1.02 ) ×109cm-2s-1 , which is consistent with the standard solar model predictions.

Performance of STICS model to predict rainfed corn evapotranspiration and biomass evaluated for 6 years between 1995 and 2006 using daily aggregated eddy covariance fluxes and ancillary measurements.

NASA Astrophysics Data System (ADS)

Pattey, Elizabeth; Jégo, Guillaume; Bourgeois, Gaétan

2010-05-01

Verifying the performance of process-based crop growth models to predict evapotranspiration and crop biomass is a key component of the adaptation of agricultural crop production to climate variations. STICS, developed by INRA, was part of the models selected by Agriculture and Agri-Food Canada to be implemented for environmental assessment studies on climate variations, because of its built-in ability to assimilate biophysical descriptors such as LAI derived from satellite imagery and its open architecture. The model prediction of shoot biomass was calibrated using destructive biomass measurements over one season, by adjusting six cultivar parameters and three generic plant parameters to define two grain corn cultivars adapted to the 1000-km long Mixedwood Plains ecozone. Its performance was then evaluated using a database of 40 years-sites of corn destructive biomass and yield. In this study we evaluate the temporal response of STICS evapotranspiration and biomass accumulation predictions against estimates using daily aggregated eddy covariance fluxes. The flux tower was located in an experimental farm south of Ottawa and measurements carried out over corn fields in 1995, 1996, 1998, 2000, 2002 and 2006. Daytime and nighttime fluxes were QC/QA and gap-filled separately. Soil respiration was partitioned to calculate the corn net daily CO2 uptake, which was converted into dry biomass. Out of the six growing seasons, three (1995, 1998, 2002) had water stress periods during corn grain filling. Year 2000 was cool and wet, while 1996 had heat and rainfall distributed evenly over the season and 2006 had a wet spring. STICS can predict evapotranspiration using either crop coefficients, when wind speed and air moisture are not available, or resistance. The first approach provided higher prediction for all the years than the resistance approach and the flux measurements. The dynamic of evapotranspiration prediction of STICS was very good for the growing seasons without water stress and was overestimated by 12-34% when rainfall deficit occurred. The preliminary comparison with intra-seasonal biomass accumulation showed that the total corn biomass derived from eddy fluxes was closer to the shoot biomass predicted by STICS than to the total biomass. The root to shoot ratio predicted by STICS was higher (30-40%) than the ratio reported in the literature (~20%). Some of the parameters controlling root growth might need a better calibration. The assembled database will help us identify the areas of greater uncertainty requiring improvement.

Rainfall and its seasonality over the Amazon in the 21st century as assessed by the coupled models for the IPCC AR4

NASA Astrophysics Data System (ADS)

Li, Wenhong; Fu, Rong; Dickinson, Robert E.

2006-01-01

The global climate models for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) predict very different changes of rainfall over the Amazon under the SRES A1B scenario for global climate change. Five of the eleven models predict an increase of annual rainfall, three models predict a decrease of rainfall, and the other three models predict no significant changes in the Amazon rainfall. We have further examined two models. The UKMO-HadCM3 model predicts an El Niño-like sea surface temperature (SST) change and warming in the northern tropical Atlantic which appear to enhance atmospheric subsidence and consequently reduce clouds over the Amazon. The resultant increase of surface solar absorption causes a stronger surface sensible heat flux and thus reduces relative humidity of the surface air. These changes decrease the rate and length of wet season rainfall and surface latent heat flux. This decreased wet season rainfall leads to drier soil during the subsequent dry season, which in turn can delay the transition from the dry to wet season. GISS-ER predicts a weaker SST warming in the western Pacific and the southern tropical Atlantic which increases moisture transport and hence rainfall in the Amazon. In the southern Amazon and Nordeste where the strongest rainfall increase occurs, the resultant higher soil moisture supports a higher surface latent heat flux during the dry and transition season and leads to an earlier wet season onset.

Model-driven analysis of experimentally determined growth phenotypes for 465 yeast gene deletion mutants under 16 different conditions

PubMed Central

Snitkin, Evan S; Dudley, Aimée M; Janse, Daniel M; Wong, Kaisheen; Church, George M; Segrè, Daniel

2008-01-01

Background Understanding the response of complex biochemical networks to genetic perturbations and environmental variability is a fundamental challenge in biology. Integration of high-throughput experimental assays and genome-scale computational methods is likely to produce insight otherwise unreachable, but specific examples of such integration have only begun to be explored. Results In this study, we measured growth phenotypes of 465 Saccharomyces cerevisiae gene deletion mutants under 16 metabolically relevant conditions and integrated them with the corresponding flux balance model predictions. We first used discordance between experimental results and model predictions to guide a stage of experimental refinement, which resulted in a significant improvement in the quality of the experimental data. Next, we used discordance still present in the refined experimental data to assess the reliability of yeast metabolism models under different conditions. In addition to estimating predictive capacity based on growth phenotypes, we sought to explain these discordances by examining predicted flux distributions visualized through a new, freely available platform. This analysis led to insight into the glycerol utilization pathway and the potential effects of metabolic shortcuts on model results. Finally, we used model predictions and experimental data to discriminate between alternative raffinose catabolism routes. Conclusions Our study demonstrates how a new level of integration between high throughput measurements and flux balance model predictions can improve understanding of both experimental and computational results. The added value of a joint analysis is a more reliable platform for specific testing of biological hypotheses, such as the catabolic routes of different carbon sources. PMID:18808699

Prediction of winter precipitation over northwest India using ocean heat fluxes

NASA Astrophysics Data System (ADS)

Nageswararao, M. M.; Mohanty, U. C.; Osuri, Krishna K.; Ramakrishna, S. S. V. S.

2016-10-01

The winter precipitation (December-February) over northwest India (NWI) is highly variable in terms of time and space. The maximum precipitation occurs over the Himalaya region and decreases towards south of NWI. The winter precipitation is important for water resources and agriculture sectors over the region and for the economy of the country. It is an exigent task to the scientific community to provide a seasonal outlook for the regional scale precipitation. The oceanic heat fluxes are known to have a strong linkage with the ocean and atmosphere. Henceforth, in this study, we obtained the relationship of NWI winter precipitation with total downward ocean heat fluxes at the global ocean surface, 15 regions with significant correlations are identified from August to November at 90 % confidence level. These strong relations encourage developing an empirical model for predicting winter precipitation over NWI. The multiple linear regression (MLR) and principal component regression (PCR) models are developed and evaluated using leave-one-out cross-validation. The developed regression models are able to predict the winter precipitation patterns over NWI with significant (99 % confidence level) index of agreement and correlations. Moreover, these models capture the signals of extremes, but could not reach the peaks (excess and deficit) of the observations. PCR performs better than MLR for predicting winter precipitation over NWI. Therefore, the total downward ocean heat fluxes at surface from August to November are having a significant impact on seasonal winter precipitation over the NWI. It concludes that these interrelationships are more useful for the development of empirical models and feasible to predict the winter precipitation over NWI with sufficient lead-time (in advance) for various risk management sectors.

Predicting watershed acidification under alternate rainfall conditions

USGS Publications Warehouse

Huntington, T.G.

1996-01-01

The effect of alternate rainfall scenarios on acidification of a forested watershed subjected to chronic acidic deposition was assessed using the model of acidification of groundwater in catchments (MAGIC). The model was calibrated at the Panola Mountain Research Watershed, near Atlanta, Georgia, U.S.A. using measured soil properties, wet and dry deposition, and modeled hydrologic routing. Model forecast simulations were evaluated to compare alternate temporal averaging of rainfall inputs and variations in rainfall amount and seasonal distribution. Soil water alkalinity was predicted to decrease to substantially lower concentrations under lower rainfall compared with current or higher rainfall conditions. Soil water alkalinity was also predicted to decrease to lower levels when the majority of rainfall occurred during the growing season compared with other rainfall distributions. Changes in rainfall distribution that result in decreases in net soil water flux will temporarily delay acidification. Ultimately, however, decreased soil water flux will result in larger increases in soil- adsorbed sulfur and soil-water sulfate concentrations and decreases in alkalinity when compared to higher water flux conditions. Potential climate change resulting in significant changes in rainfall amounts, seasonal distribution of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading.

A Novel A Posteriori Investigation of Scalar Flux Models for Passive Scalar Dispersion in Compressible Boundary Layer Flows

NASA Astrophysics Data System (ADS)

Braman, Kalen; Raman, Venkat

2011-11-01

A novel direct numerical simulation (DNS) based a posteriori technique has been developed to investigate scalar transport modeling error. The methodology is used to test Reynolds-averaged Navier-Stokes turbulent scalar flux models for compressible boundary layer flows. Time-averaged DNS velocity and turbulence fields provide the information necessary to evolve the time-averaged scalar transport equation without requiring the use of turbulence modeling. With this technique, passive dispersion of a scalar from a boundary layer surface in a supersonic flow is studied with scalar flux modeling error isolated from any flowfield modeling errors. Several different scalar flux models are used. It is seen that the simple gradient diffusion model overpredicts scalar dispersion, while anisotropic scalar flux models underpredict dispersion. Further, the use of more complex models does not necessarily guarantee an increase in predictive accuracy, indicating that key physics is missing from existing models. Using comparisons of both a priori and a posteriori scalar flux evaluations with DNS data, the main modeling shortcomings are identified. Results will be presented for different boundary layer conditions.

Stochastic multifractal forecasts: from theory to applications in radar meteorology

NASA Astrophysics Data System (ADS)

da Silva Rocha Paz, Igor; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2017-04-01

Radar meteorology has been very inspiring for the development of multifractals. It has enabled to work on a 3D+1 field with many challenging applications, including predictability and stochastic forecasts, especially nowcasts that are particularly demanding in computation speed. Multifractals are indeed parsimonious stochastic models that require only a few physically meaningful parameters, e.g. Universal Multifractal (UM) parameters, because they are based on non-trivial symmetries of nonlinear equations. We first recall the physical principles of multifractal predictability and predictions, which are so closely related that the latter correspond to the most optimal predictions in the multifractal framework. Indeed, these predictions are based on the fundamental duality of a relatively slow decay of large scale structures and an injection of new born small scale structures. Overall, this triggers a mulfitractal inverse cascade of unpredictability. With the help of high resolution rainfall radar data (≈ 100 m), we detail and illustrate the corresponding stochastic algorithm in the framework of (causal) UM Fractionally Integrated Flux models (UM-FIF), where the rainfall field is obtained with the help of a fractional integration of a conservative multifractal flux, whose average is strictly scale invariant (like the energy flux in a dynamic cascade). Whereas, the introduction of small structures is rather straightforward, the deconvolution of the past of the field is more subtle, but nevertheless achievable, to obtain the past of the flux. Then, one needs to only fractionally integrate a multiplicative combination of past and future fluxes to obtain a nowcast realisation.

Particle-laden weakly swirling free jets: Measurements and predictions. Ph.D. Thesis - Pennsylvania State Univ.

NASA Technical Reports Server (NTRS)

Bulzan, Daniel L.

1988-01-01

A theoretical and experimental investigation of particle-laden, weakly swirling, turbulent free jets was conducted. Glass particles, having a Sauter mean diameter of 39 microns, with a standard deviation of 15 microns, were used. A single loading ratio (the mass flow rate of particles per unit mass flow rate of air) of 0.2 was used in the experiments. Measurements are reported for three swirl numbers, ranging from 0 to 0.33. The measurements included mean and fluctuating velocities of both phases, and particle mass flux distributions. Measurements were also completed for single-phase non-swirling and swirling jets, as baselines. Measurements were compared with predictions from three types of multiphase flow analysis, as follows: (1) locally homogeneous flow (LHF) where slip between the phases was neglected; (2) deterministic separated flow (DSF), where slip was considered but effects of turbulence/particle interactions were neglected; and (3) stochastic separated flow (SSF), where effects of both interphase slip and turbulence/particle interactions were considered using random sampling for turbulence properties in conjunction with random-walk computations for particle motion. Single-phase weakly swirling jets were considered first. Predictions using a standard k-epsilon turbulence model, as well as two versions modified to account for effects of streamline curvature, were compared with measurements. Predictions using a streamline curvature modification based on the flux Richardson number gave better agreement with measurements for the single-phase swirling jets than the standard k-epsilon model. For the particle-laden jets, the LHF and DSF models did not provide very satisfactory predictions. The LHF model generally overestimated the rate of decay of particle mean axial and angular velocities with streamwise distance, and predicted particle mass fluxes also showed poor agreement with measurements, due to the assumption of no-slip between phases. The DSF model also performed quite poorly for predictions of particle mass flux because turbulent dispersion of the particles was neglected. The SSF model, which accounts for both particle inertia and turbulent dispersion of the particles, yielded reasonably good predictions throughout the flow field for the particle-laden jets.

AEETES - A solar reflux receiver thermal performance numerical model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogan, R.E. Jr.

1994-02-01

Reflux solar receivers for dish-Stirling electric power generation systems are currently being investigated by several companies and laboratories. In support of these efforts, the AEETES thermal performance numerical model has been developed to predict thermal performance of pool-boiler and heat-pipe reflux receivers. The formulation of the AEETES numerical model, which is applicable to axisymmetric geometries with asymmetric incident fluxes, is presented in detail. Thermal efficiency predictions agree to within 4.1% with test data from on-sun tests of a pool-boiler reflux receiver. Predicted absorber and sidewall temperatures agree with thermocouple data to within 3.3 and 7.3%, respectively. The importance of accountingmore » for the asymmetric incident fluxes is demonstrated in comparisons with predictions using azimuthally averaged variables. The predicted receiver heat losses are characterized in terms of convective, solar radiative, and infrared radiative, and conductive heat transfer mechanisms.« less

Numerical Modeling of STARx for Ex Situ Soil Remediation

NASA Astrophysics Data System (ADS)

Gerhard, J.; Solinger, R. L.; Grant, G.; Scholes, G.

2016-12-01

Growing stockpiles of contaminated soils contaminated with petroleum hydrocarbons are an outstanding problem worldwide. Self-sustaining Treatment for Active Remediation (STAR) is an emerging technology based on smouldering combustion that has been successfully deployed for in situ remediation. STAR has also been developed for ex situ applications (STARx). This work used a two-dimensional numerical model to systematically explore the sensitivity of ex situ remedial performance to key design and operational parameters. First the model was calibrated and validated against pilot scale experiments, providing confidence that the rate and extent of treatment were correctly predicted. Simulations then investigated sensitivity of remedial performance to injected air flux, contaminant saturation, system configuration, heterogeneity of intrinsic permeability, heterogeneity of contaminant saturation, and system scale. Remedial performance was predicted to be most sensitive to the injected air flux, with higher air fluxes achieving higher treatment rates and remediating larger fractions of the initial contaminant mass. The uniformity of the advancing smouldering front was predicted to be highly dependent on effective permeability contrasts between treated and untreated sections of the contaminant pack. As a result, increased heterogeneity (of intrinsic permeability in particular) is predicted to lower remedial performance. Full-scale systems were predicted to achieve treatment rates an order of magnitude higher than the pilot scale for similar contaminant saturation and injected air flux. This work contributed to the large scale STARx treatment system that is being tested at a field site in Fall 2016.

The effect of soot modeling on thermal radiation in buoyant turbulent diffusion flames

NASA Astrophysics Data System (ADS)

Snegirev, A.; Kokovina, E.; Tsoy, A.; Harris, J.; Wu, T.

2016-09-01

Radiative impact of buoyant turbulent diffusion flames is the driving force in fire development. Radiation emission and re-absorption is controlled by gaseous combustion products, mainly CO2 and H2O, and by soot. Relative contribution of gas and soot radiation depends on the fuel sooting propensity and on soot distribution in the flame. Soot modeling approaches incorporated in big commercial codes were developed and calibrated for momentum-dominated jet flames, and these approaches must be re-evaluated when applied to the buoyant flames occurring in fires. The purpose of this work is to evaluate the effect of the soot models available in ANSYS FLUENT on the predictions of the radiative fluxes produced by the buoyant turbulent diffusion flames with considerably different soot yields. By means of large eddy simulations, we assess capability of the Moss-Brooks soot formation model combined with two soot oxidation submodels to predict methane- and heptane-fuelled fires, for which radiative flux measurements are available in the literature. We demonstrate that the soot oxidation models could be equally important as soot formation ones to predict the soot yield in the overfire region. Contribution of soot in the radiation emission by the flame is also examined, and predicted radiative fluxes are compared to published experimental data.

Recent global methane trends: an investigation using hierarchical Bayesian methods

NASA Astrophysics Data System (ADS)

Rigby, M. L.; Stavert, A.; Ganesan, A.; Lunt, M. F.

2014-12-01

Following a decade with little growth, methane concentrations began to increase across the globe in 2007, and have continued to rise ever since. The reasons for this renewed growth are currently the subject of much debate. Here, we discuss the recent observed trends, and highlight some of the strengths and weaknesses in current "inverse" methods for quantifying fluxes using observations. In particular, we focus on the outstanding problems of accurately quantifying uncertainties in inverse frameworks. We examine to what extent the recent methane changes can be explained by the current generation of flux models and inventories. We examine the major modes of variability in wetland models along with the Global Fire Emissions Database (GFED) and the Emissions Database for Global Atmospheric Research (EDGAR). Using the Model for Ozone and Related Tracers (MOZART), we determine whether the spatial and temporal atmospheric trends predicted using these emissions can be brought into consistency with in situ atmospheric observations. We use a novel hierarchical Bayesian methodology in which scaling factors applied to the principal components of the flux fields are estimated simultaneously with the uncertainties associated with the a priori fluxes and with model representations of the observations. Using this method, we examine the predictive power of methane flux models for explaining recent fluctuations.

13C metabolic flux analysis at a genome-scale.

PubMed

Gopalakrishnan, Saratram; Maranas, Costas D

2015-11-01

Metabolic models used in 13C metabolic flux analysis generally include a limited number of reactions primarily from central metabolism. They typically omit degradation pathways, complete cofactor balances, and atom transition contributions for reactions outside central metabolism. This study addresses the impact on prediction fidelity of scaling-up mapping models to a genome-scale. The core mapping model employed in this study accounts for (75 reactions and 65 metabolites) primarily from central metabolism. The genome-scale metabolic mapping model (GSMM) (697 reaction and 595 metabolites) is constructed using as a basis the iAF1260 model upon eliminating reactions guaranteed not to carry flux based on growth and fermentation data for a minimal glucose growth medium. Labeling data for 17 amino acid fragments obtained from cells fed with glucose labeled at the second carbon was used to obtain fluxes and ranges. Metabolic fluxes and confidence intervals are estimated, for both core and genome-scale mapping models, by minimizing the sum of square of differences between predicted and experimentally measured labeling patterns using the EMU decomposition algorithm. Overall, we find that both topology and estimated values of the metabolic fluxes remain largely consistent between core and GSM model. Stepping up to a genome-scale mapping model leads to wider flux inference ranges for 20 key reactions present in the core model. The glycolysis flux range doubles due to the possibility of active gluconeogenesis, the TCA flux range expanded by 80% due to the availability of a bypass through arginine consistent with labeling data, and the transhydrogenase reaction flux was essentially unresolved due to the presence of as many as five routes for the inter-conversion of NADPH to NADH afforded by the genome-scale model. By globally accounting for ATP demands in the GSMM model the unused ATP decreased drastically with the lower bound matching the maintenance ATP requirement. A non-zero flux for the arginine degradation pathway was identified to meet biomass precursor demands as detailed in the iAF1260 model. Inferred ranges for 81% of the reactions in the genome-scale metabolic (GSM) model varied less than one-tenth of the basis glucose uptake rate (95% confidence test). This is because as many as 411 reactions in the GSM are growth coupled meaning that the single measurement of biomass formation rate locks the reaction flux values. This implies that accurate biomass formation rate and composition are critical for resolving metabolic fluxes away from central metabolism and suggests the importance of biomass composition (re)assessment under different genetic and environmental backgrounds. In addition, the loss of information associated with mapping fluxes from MFA on a core model to a GSM model is quantified. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Large Eddy Simulation Study for Fluid Disintegration and Mixing

NASA Technical Reports Server (NTRS)

Bellan, Josette; Taskinoglu, Ezgi

2011-01-01

A new modeling approach is based on the concept of large eddy simulation (LES) within which the large scales are computed and the small scales are modeled. The new approach is expected to retain the fidelity of the physics while also being computationally efficient. Typically, only models for the small-scale fluxes of momentum, species, and enthalpy are used to reintroduce in the simulation the physics lost because the computation only resolves the large scales. These models are called subgrid (SGS) models because they operate at a scale smaller than the LES grid. In a previous study of thermodynamically supercritical fluid disintegration and mixing, additional small-scale terms, one in the momentum and one in the energy conservation equations, were identified as requiring modeling. These additional terms were due to the tight coupling between dynamics and real-gas thermodynamics. It was inferred that if these terms would not be modeled, the high density-gradient magnitude regions, experimentally identified as a characteristic feature of these flows, would not be accurately predicted without the additional term in the momentum equation; these high density-gradient magnitude regions were experimentally shown to redistribute turbulence in the flow. And it was also inferred that without the additional term in the energy equation, the heat flux magnitude could not be accurately predicted; the heat flux to the wall of combustion devices is a crucial quantity that determined necessary wall material properties. The present work involves situations where only the term in the momentum equation is important. Without this additional term in the momentum equation, neither the SGS-flux constant-coefficient Smagorinsky model nor the SGS-flux constant-coefficient Gradient model could reproduce in LES the pressure field or the high density-gradient magnitude regions; the SGS-flux constant- coefficient Scale-Similarity model was the most successful in this endeavor although not totally satisfactory. With a model for the additional term in the momentum equation, the predictions of the constant-coefficient Smagorinsky and constant-coefficient Scale-Similarity models were improved to a certain extent; however, most of the improvement was obtained for the Gradient model. The previously derived model and a newly developed model for the additional term in the momentum equation were both tested, with the new model proving even more successful than the previous model at reproducing the high density-gradient magnitude regions. Several dynamic SGS-flux models, in which the SGS-flux model coefficient is computed as part of the simulation, were tested in conjunction with the new model for this additional term in the momentum equation. The most successful dynamic model was a "mixed" model combining the Smagorinsky and Gradient models. This work is directly applicable to simulations of gas turbine engines (aeronautics) and rocket engines (astronautics).

Reconstruction and flux analysis of coupling between metabolic pathways of astrocytes and neurons: application to cerebral hypoxia

PubMed Central

Çakιr, Tunahan; Alsan, Selma; Saybaşιlι, Hale; Akιn, Ata; Ülgen, Kutlu Ö

2007-01-01

Background It is a daunting task to identify all the metabolic pathways of brain energy metabolism and develop a dynamic simulation environment that will cover a time scale ranging from seconds to hours. To simplify this task and make it more practicable, we undertook stoichiometric modeling of brain energy metabolism with the major aim of including the main interacting pathways in and between astrocytes and neurons. Model The constructed model includes central metabolism (glycolysis, pentose phosphate pathway, TCA cycle), lipid metabolism, reactive oxygen species (ROS) detoxification, amino acid metabolism (synthesis and catabolism), the well-known glutamate-glutamine cycle, other coupling reactions between astrocytes and neurons, and neurotransmitter metabolism. This is, to our knowledge, the most comprehensive attempt at stoichiometric modeling of brain metabolism to date in terms of its coverage of a wide range of metabolic pathways. We then attempted to model the basal physiological behaviour and hypoxic behaviour of the brain cells where astrocytes and neurons are tightly coupled. Results The reconstructed stoichiometric reaction model included 217 reactions (184 internal, 33 exchange) and 216 metabolites (183 internal, 33 external) distributed in and between astrocytes and neurons. Flux balance analysis (FBA) techniques were applied to the reconstructed model to elucidate the underlying cellular principles of neuron-astrocyte coupling. Simulation of resting conditions under the constraints of maximization of glutamate/glutamine/GABA cycle fluxes between the two cell types with subsequent minimization of Euclidean norm of fluxes resulted in a flux distribution in accordance with literature-based findings. As a further validation of our model, the effect of oxygen deprivation (hypoxia) on fluxes was simulated using an FBA-derivative approach, known as minimization of metabolic adjustment (MOMA). The results show the power of the constructed model to simulate disease behaviour on the flux level, and its potential to analyze cellular metabolic behaviour in silico. Conclusion The predictive power of the constructed model for the key flux distributions, especially central carbon metabolism and glutamate-glutamine cycle fluxes, and its application to hypoxia is promising. The resultant acceptable predictions strengthen the power of such stoichiometric models in the analysis of mammalian cell metabolism. PMID:18070347

Modeling of indoor radon concentration from radon exhalation rates of building materials and validation through measurements.

PubMed

Kumar, Amit; Chauhan, R P; Joshi, Manish; Sahoo, B K

2014-01-01

Building materials are the second major source of indoor radon after soil. The contribution of building materials towards indoor radon depends upon the radium content and exhalation rates and can be used as a primary index for radon levels in the dwellings. The radon flux data from the building materials was used for calculation of the indoor radon concentrations and doses by many researchers using one and two dimensional model suggested by various researchers. In addition to radium content, the radon wall flux from a surface strongly depends upon the radon diffusion length (L) and thickness of the wall (2d). In the present work the indoor radon concentrations from the measured radon exhalation rate of building materials calculated using different models available in literature and validation of models was made through measurement. The variation in the predicted radon flux from different models was compared with d/L value for wall and roofs of different dwellings. The results showed that the radon concentrations predicted by models agree with experimental value. The applicability of different model with d/L ratio was discussed. The work aims to select a more appropriate and general model among available models in literature for the prediction of indoor radon. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analytical modeling for heat transfer in sheared flows of nanofluids.

PubMed

Ferrari, Claudio; Kaoui, Badr; L'vov, Victor S; Procaccia, Itamar; Rudenko, Oleksii; ten Thije Boonkkamp, J H M; Toschi, Federico

2012-07-01

We developed a model for the enhancement of the heat flux by spherical and elongated nanoparticles in sheared laminar flows of nanofluids. Besides the heat flux carried by the nanoparticles, the model accounts for the contribution of their rotation to the heat flux inside and outside the particles. The rotation of the nanoparticles has a twofold effect: it induces a fluid advection around the particle and it strongly influences the statistical distribution of particle orientations. These dynamical effects, which were not included in existing thermal models, are responsible for changing the thermal properties of flowing fluids as compared to quiescent fluids. The proposed model is strongly supported by extensive numerical simulations, demonstrating a potential increase of the heat flux far beyond the Maxwell-Garnett limit for the spherical nanoparticles. The road ahead, which should lead toward robust predictive models of heat flux enhancement, is discussed.

A model predictive current control of flux-switching permanent magnet machines for torque ripple minimization

NASA Astrophysics Data System (ADS)

Huang, Wentao; Hua, Wei; Yu, Feng

2017-05-01

Due to high airgap flux density generated by magnets and the special double salient structure, the cogging torque of the flux-switching permanent magnet (FSPM) machine is considerable, which limits the further applications. Based on the model predictive current control (MPCC) and the compensation control theory, a compensating-current MPCC (CC-MPCC) scheme is proposed and implemented to counteract the dominated components in cogging torque of an existing three-phase 12/10 FSPM prototyped machine, and thus to alleviate the influence of the cogging torque and improve the smoothness of electromagnetic torque as well as speed, where a comprehensive cost function is designed to evaluate the switching states. The simulated results indicate that the proposed CC-MPCC scheme can suppress the torque ripple significantly and offer satisfactory dynamic performances by comparisons with the conventional MPCC strategy. Finally, experimental results validate both the theoretical and simulated predictions.

Nowcast model for low-energy electrons in the inner magnetosphere

NASA Astrophysics Data System (ADS)

Ganushkina, N. Yu.; Amariutei, O. A.; Welling, D.; Heynderickx, D.

2015-01-01

We present the nowcast model for low-energy (<200 keV) electrons in the inner magnetosphere, which is the version of the Inner Magnetosphere Particle Transport and Acceleration Model (IMPTAM) for electrons. Low-energy electron fluxes are very important to specify when hazardous satellite surface-charging phenomena are considered. The presented model provides the low-energy electron flux at all L shells and at all satellite orbits, when necessary. The model is driven by the real-time solar wind and interplanetary magnetic field (IMF) parameters with 1 h time shift for propagation to the Earth's magnetopause and by the real time Dst index. Real-time geostationary GOES 13 or GOES 15 (whenever each is available) data on electron fluxes in three energies, such as 40 keV, 75 keV, and 150 keV, are used for comparison and validation of IMPTAM running online. On average, the model provides quite reasonable agreement with the data; the basic level of the observed fluxes is reproduced. The best agreement between the modeled and the observed fluxes are found for <100 keV electrons. At the same time, not all the peaks and dropouts in the observed electron fluxes are reproduced. For 150 keV electrons, the modeled fluxes are often smaller than the observed ones by an order of magnitude. The normalized root-mean-square deviation is found to range from 0.015 to 0.0324. Though these metrics are buoyed by large standard deviations, owing to the dynamic nature of the fluxes, they demonstrate that IMPTAM, on average, predicts the observed fluxes satisfactorily. The computed binary event tables for predicting high flux values within each 1 h window reveal reasonable hit rates being 0.660-0.318 for flux thresholds of 5 ·104-2 ·105 cm-2 s-1 sr-1 keV-1 for 40 keV electrons, 0.739-0.367 for flux thresholds of 3 ·104-1 ·105 cm-2 s-1 sr-1 keV-1 for 75 keV electrons, and 0.485-0.438 for flux thresholds of 3 ·103-3.5 ·103 cm-2 s-1 sr-1 keV-1 for 150 keV electrons but rather small Heidke Skill Scores (0.17 and below). This is the first attempt to model low-energy electrons in real time at 10 min resolution. The output of this model can serve as an input of electron seed population for real-time higher-energy radiation belt modeling.

Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production

NASA Astrophysics Data System (ADS)

Elmasri, B.; Rahman, A. F.

2010-12-01

Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation will result in improved GPP predictions. Although there might be a room for improvements in our model outcomes through improved parameterization, our results suggest that such a methodology for running BIOME-BGC model based entirely on routinely available data can produce good predictions of GPP.

Observations of the 10-micron natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Espenak, F.; Deming, D.; Jennings, D.; Kostiuk, T.; Mumma, M.; Zipoy, D.

1983-01-01

Observations of the total flux and center to limb dependence of the nonthermal emission occurring in the cores of the 9.4 and 10.4 micrometers CO2 bands on Mars are compared to a theoretical model based on this mechanism. The model successfully reproduces the observed center to limb dependence of this emission, to within the limits imposed by the spatial resolution of the observations of Mars and Venus. The observed flux from Mars agrees closely with the prediction of the model; the flux observed from Venus is 74 percent of the flux predicted by the model. This emission is used to obtain the kinetic temperatures of the Martian and Venusian mesospheres. For Mars near 70 km altitude, a rotational temperature analysis using five lines gives T = 135 + or - 20 K. The frequency width of the emission is also analyzed to derive a temperature of 126 + or - 6 K. In the case of the Venusian mesosphere near 109 km, the frequency width of the emission gives T = 204 + or - 10 K.

Evaluation of an urban land surface scheme over a tropical suburban neighborhood

NASA Astrophysics Data System (ADS)

Harshan, Suraj; Roth, Matthias; Velasco, Erik; Demuzere, Matthias

2017-07-01

The present study evaluates the performance of the SURFEX (TEB/ISBA) urban land surface parametrization scheme in offline mode over a suburban area of Singapore. Model performance (diurnal and seasonal characteristics) is investigated using measurements of energy balance fluxes, surface temperatures of individual urban facets, and canyon air temperature collected during an 11-month period. Model performance is best for predicting net radiation and sensible heat fluxes (both are slightly overpredicted during daytime), but weaker for latent heat (underpredicted during daytime) and storage heat fluxes (significantly underpredicted daytime peaks and nighttime storage). Daytime surface temperatures are generally overpredicted, particularly those containing horizontal surfaces such as roofs and roads. This result, together with those for the storage heat flux, point to the need for a better characterization of the thermal and radiative characteristics of individual urban surface facets in the model. Significant variation exists in model behavior between dry and wet seasons, the latter generally being better predicted. The simple vegetation parametrization used is inadequate to represent seasonal moisture dynamics, sometimes producing unrealistically dry conditions.

Observations of the 10 micrometer natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Deming, D.; Espenak, F.; Jennings, D.; Kostiuk, T.; Mumma, M. J.

1983-01-01

Observations of the total flux and center to limb dependence of the nonthermal emission occurring in the cores of the 9.4 and 10.4 micrometers CO2 bands on Mars are compared to a theoretical model based on this mechanism. The model successfully reproduces the observed center to limb dependence of this emission, to within the limits imposed by the spatial resolution of the observations of Mars and Venus. The observed flux from Mars agrees closely with the prediction of the model; the flux observed from Venus is 74% of the flux predicted by the model. This emission is used to obtain the kinetic temperatures of the Martian and Venusian mesospheres. For Mars near 70 km altitude, a rotational temperature analysis using five lines gives T = 135 + or - 20 K. The frequency width of the emission is also analyzed to derive a temperature of 126 + or - 6 K. In the case of the Venusian mesosphere near 109 km, the frequency width of the emission gives T = 204 + or - 10 K.

Numerical analysis of hypersonic turbulent film cooling flows

NASA Technical Reports Server (NTRS)

Chen, Y. S.; Chen, C. P.; Wei, H.

1992-01-01

As a building block, numerical capabilities for predicting heat flux and turbulent flowfields of hypersonic vehicles require extensive model validations. Computational procedures for calculating turbulent flows and heat fluxes for supersonic film cooling with parallel slot injections are described in this study. Two injectant mass flow rates with matched and unmatched pressure conditions using the database of Holden et al. (1990) are considered. To avoid uncertainties associated with the boundary conditions in testing turbulence models, detailed three-dimensional flowfields of the injection nozzle were calculated. Two computational fluid dynamics codes, GASP and FDNS, with the algebraic Baldwin-Lomax and k-epsilon models with compressibility corrections were used. It was found that the B-L model which resolves near-wall viscous sublayer is very sensitive to the inlet boundary conditions at the nozzle exit face. The k-epsilon models with improved wall functions are less sensitive to the inlet boundary conditions. The testings show that compressibility corrections are necessary for the k-epsilon model to realistically predict the heat fluxes of the hypersonic film cooling problems.

Comprehensive analysis of a Metabolic Model for lipid production in Rhodosporidium toruloides.

PubMed

Castañeda, María Teresita; Nuñez, Sebastián; Garelli, Fabricio; Voget, Claudio; Battista, Hernán De

2018-05-19

The yeast Rhodosporidium toruloides has been extensively studied for its application in biolipid production. The knowledge of its metabolism capabilities and the application of constraint-based flux analysis methodology provide useful information for process prediction and optimization. The accuracy of the resulting predictions is highly dependent on metabolic models. A metabolic reconstruction for R. toruloides metabolism has been recently published. On the basis of this model, we developed a curated version that unblocks the central nitrogen metabolism and, in addition, completes charge and mass balances in some reactions neglected in the former model. Then, a comprehensive analysis of network capability was performed with the curated model and compared with the published metabolic reconstruction. The flux distribution obtained by lipid optimization with Flux Balance Analysis was able to replicate the internal biochemical changes that lead to lipogenesis in oleaginous microorganisms. These results motivate the development of a genome-scale model for complete elucidation of R. toruloides metabolism. Copyright © 2018 Elsevier B.V. All rights reserved.

Free flux flow in two single crystals of V3Si with slightly different pinning strengths

NASA Astrophysics Data System (ADS)

Gafarov, O.; Gapud, A. A.; Moraes, S.; Thompson, J. R.; Christen, D. K.; Reyes, A. P.

2010-10-01

Results of recent measurements on two very clean, single-crystal samples of the A15 superconductor V3Si are presented. Magnetization and transport data already confirmed the ``clean'' quality of both samples, as manifested by: (i) high residual resistivity ratio, (ii) very low critical current densities, and (iii) a ``peak'' effect in the field dependence of critical current. The (H,T) phase line for this peak effect is shifted in the slightly ``dirtier'' sample, which consequently also has higher critical current density Jc(H). High-current Lorentz forces are applied on mixed-state vortices in order to induce the highly ordered free flux flow (FFF) phase, using the same methods as in previous work. A traditional model by Bardeen and Stephen (BS) predicts a simple field dependence of flux flow resistivity ρf(H), presuming a field-independent flux core size. A model by Kogan and Zelezhina (KZ) takes core size into account, and predict a clear deviation from BS. In this study, ρf(H) is confirmed to be consistent with predictions of KZ, as will be discussed.

Empirical prediction of net splanchnic release of ketogenic nutrients, acetate, butyrate and β-hydroxybutyrate in ruminants: a meta-analysis.

PubMed

Loncke, C; Nozière, P; Bahloul, L; Vernet, J; Lapierre, H; Sauvant, D; Ortigues-Marty, I

2015-03-01

For energy feeding systems for ruminants to evolve towards a nutrient-based system, dietary energy supply has to be determined in terms of amount and nature of nutrients. The objective of this study was to establish response equations of the net hepatic flux and net splanchnic release of acetate, butyrate and β-hydroxybutyrate to changes in diet and animal profiles. A meta-analysis was applied on published data compiled from the FLuxes of nutrients across Organs and tissues in Ruminant Animals database, which pools the results from international publications on net splanchnic nutrient fluxes measured in multi-catheterized ruminants. Prediction variables were identified from current knowledge on digestion, hepatic and other tissue metabolism. Subsequently, physiological and other, more integrative, predictors were obtained. Models were established for intakes up to 41 g dry matter per kg BW per day and diets containing up to 70 g concentrate per 100 g dry matter. Models predicted the net hepatic fluxes or net splanchnic release of each nutrient from its net portal appearance and the animal profile. Corrections were applied to account for incomplete hepatic recovery of the blood flow marker, para-aminohippuric acid. Changes in net splanchnic release (mmol/kg BW per hour) could then be predicted by combining the previously published net portal appearance models and the present net hepatic fluxes models. The net splanchnic release of acetate and butyrate were thus predicted from the intake of ruminally fermented organic matter (RfOM) and the nature of RfOM (acetate: residual mean square error (RMSE)=0.18; butyrate: RMSE=0.01). The net splanchnic release of β-hydroxybutyrate was predicted from RfOM intake and the energy balance of the animals (RMSE=0.035), or from the net portal appearance of butyrate and the energy balance of the animals (RMSE=0.050). Models obtained were independent of ruminant species, and presented low interfering factors on the residuals, least square means or individual slopes. The model equations highlighted the importance of considering the physiological state of animals when predicting splanchnic metabolism. This work showed that it is possible to use simple predictors to accurately predict the amount and nature of ketogenic nutrients released towards peripheral tissues in both sheep and cattle at different physiological status. These results provide deeper insight into biological processes and will contribute to the development of improved tools for dietary formulation.

Using Flux Site Observations to Calibrate Root System Architecture Stencils for Water Uptake of Plant Functional Types in Land Surface Models.

NASA Astrophysics Data System (ADS)

Bouda, M.

2017-12-01

Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, RSA has not been included because of its three-dimensional complexity, which makes RSA modelling generally too computationally costly. This work builds upon the recently introduced "RSA stencil," a process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA in response to heterogeneous soil moisture profiles. In validations using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, the RSA stencil predicts plant water potentials within 2% of the outputs of full 3D models, despite its trivial computational cost. In transient simulations, the RSA stencil yields improved predictions of water uptake and soil moisture profiles compared to a 1D model based on root fraction alone. Here I show how the RSA stencil can be calibrated to time-series observations of soil moisture and transpiration to yield a water uptake PFT definition for use in terrestrial models. This model-data integration exercise aims to improve LSM predictions of soil moisture dynamics and, under water-limiting conditions, surface fluxes. These improvements can be expected to significantly impact predictions of downstream variables, including surface fluxes, climate-vegetation feedbacks and soil nutrient cycling.

Be 7 solar neutrino measurement with KamLAND

DOE PAGES

Gando, A.; Gando, Y.; Hanakago, H.; ...

2015-11-30

In this article, we report a measurement of the neutrino-electron elastic scattering rate of 862 keV 7Be solar neutrinos based on a 165.4 kt d exposure of KamLAND. The observed rate is 582 ± 94 (kt d) -1, which corresponds to an 862-keV 7Be solar neutrino flux of (3.26 ± 0.52) × 10 9 cm -2s -1, assuming a pure electron-flavor flux. Comparing this flux with the standard solar model prediction and further assuming three-flavor mixing, a ν e survival probability of 0.66 ± 0.15 is determined from the KamLAND data. Utilizing a global three-flavor oscillation analysis, we obtain amore » total 7Be solar neutrino flux of (5.82 ± 1.02) × 10 9 cm -2s -1, which is consistent with the standard solar model predictions.« less

Be 7 solar neutrino measurement with KamLAND

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gando, A.; Gando, Y.; Hanakago, H.

2015-11-30

We report a measurement of the neutrino-electron elastic scattering rate of 862 keV 7Be solar neutrinos based on a 165.4 kt d exposure of KamLAND. The observed rate is 582±94(kt d) ₋1, which corresponds to an 862-keV 7Be solar neutrino flux of (3.26±0.52)×10 9cm ₋2s ₋1, assuming a pure electron-flavor flux. Comparing this flux with the standard solar model prediction and further assuming three-flavor mixing, a ν e survival probability of 0.66±0.15 is determined from the KamLAND data. Lastly, utilizing a global three-flavor oscillation analysis, we obtain a total 7Be solar neutrino flux of (5.82±1.02)×10 9cm ₋2s ₋1, which ismore » consistent with the standard solar model predictions.« less

The Large-scale Coronal Structure of the 2017 August 21 Great American Eclipse: An Assessment of Solar Surface Flux Transport Model Enabled Predictions and Observations

NASA Astrophysics Data System (ADS)

Nandy, Dibyendu; Bhowmik, Prantika; Yeates, Anthony R.; Panda, Suman; Tarafder, Rajashik; Dash, Soumyaranjan

2018-01-01

On 2017 August 21, a total solar eclipse swept across the contiguous United States, providing excellent opportunities for diagnostics of the Sun’s corona. The Sun’s coronal structure is notoriously difficult to observe except during solar eclipses; thus, theoretical models must be relied upon for inferring the underlying magnetic structure of the Sun’s outer atmosphere. These models are necessary for understanding the role of magnetic fields in the heating of the corona to a million degrees and the generation of severe space weather. Here we present a methodology for predicting the structure of the coronal field based on model forward runs of a solar surface flux transport model, whose predicted surface field is utilized to extrapolate future coronal magnetic field structures. This prescription was applied to the 2017 August 21 solar eclipse. A post-eclipse analysis shows good agreement between model simulated and observed coronal structures and their locations on the limb. We demonstrate that slow changes in the Sun’s surface magnetic field distribution driven by long-term flux emergence and its evolution governs large-scale coronal structures with a (plausibly cycle-phase dependent) dynamical memory timescale on the order of a few solar rotations, opening up the possibility for large-scale, global corona predictions at least a month in advance.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Anderson, C.; Bond-Lamberty, B. P.; Huang, M.; Xu, Y.; Stegen, J.

2016-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Heat transfer to throat tubes in a square-chambered rocket engine at the NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Nesbitt, James A.; Brindley, William J.

1989-01-01

A gaseous H2/O2 rocket engine was constructed at the NASA-Lewis to provide a high heat flux source representative of the heat flux to the blades in the high pressure fuel turbopump (HPFTP) during startup of the space shuttle main engines. The high heat flux source was required to evaluate the durability of thermal barrier coatings being investigated for use on these blades. The heat transfer, and specifically, the heat flux to tubes located at the throat of the test rocket engine was evaluated and compared to the heat flux to the blades in the HPFTP during engine startup. Gas temperatures, pressures and heat transfer coefficients in the test rocket engine were measured. Near surface metal temperatures below thin thermal barrier coatings were also measured at various angular orientations around the throat tube to indicate the angular dependence of the heat transfer coefficients. A finite difference model for a throat tube was developed and a thermal analysis was performed using the measured gas temperatures and the derived heat transfer coefficients to predict metal temperatures in the tube. Near surface metal temperatures of an uncoated throat tube were measured at the stagnation point and showed good agreement with temperatures predicted by the thermal model. The maximum heat flux to the throat tube was calculated and compared to that predicted for the leading edge of an HPFTP blade. It is shown that the heat flux to an uncooled throat tube is slightly greater than the heat flux to an HPFTP blade during engine startup.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Antonarakis, A. S.; Bogan, S.; Moorcroft, P. R.

2017-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Theoretical basal Ca II fluxes for late-type stars: results from magnetic wave models with time-dependent ionization and multi-level radiation treatments

NASA Astrophysics Data System (ADS)

Fawzy, Diaa E.; Stȩpień, K.

2018-03-01

In the current study we present ab initio numerical computations of the generation and propagation of longitudinal waves in magnetic flux tubes embedded in the atmospheres of late-type stars. The interaction between convective turbulence and the magnetic structure is computed and the obtained longitudinal wave energy flux is used in a self-consistent manner to excite the small-scale magnetic flux tubes. In the current study we reduce the number of assumptions made in our previous studies by considering the full magnetic wave energy fluxes and spectra as well as time-dependent ionization (TDI) of hydrogen, employing multi-level Ca II atomic models, and taking into account departures from local thermodynamic equilibrium. Our models employ the recently confirmed value of the mixing-length parameter α=1.8. Regions with strong magnetic fields (magnetic filling factors of up to 50%) are also considered in the current study. The computed Ca II emission fluxes show a strong dependence on the magnetic filling factors, and the effect of time-dependent ionization (TDI) turns out to be very important in the atmospheres of late-type stars heated by acoustic and magnetic waves. The emitted Ca II fluxes with TDI included into the model are decreased by factors that range from 1.4 to 5.5 for G0V and M0V stars, respectively, compared to models that do not consider TDI. The results of our computations are compared with observations. Excellent agreement between the observed and predicted basal flux is obtained. The predicted trend of Ca II emission flux with magnetic filling factor and stellar surface temperature also agrees well with the observations but the calculated maximum fluxes for stars of different spectral types are about two times lower than observations. Though the longitudinal MHD waves considered here are important for chromosphere heating in high activity stars, additional heating mechanism(s) are apparently present.

Preliminary validation of computational model for neutron flux prediction of Thai Research Reactor (TRR-1/M1)

NASA Astrophysics Data System (ADS)

Sabaibang, S.; Lekchaum, S.; Tipayakul, C.

2015-05-01

This study is a part of an on-going work to develop a computational model of Thai Research Reactor (TRR-1/M1) which is capable of accurately predicting the neutron flux level and spectrum. The computational model was created by MCNPX program and the CT (Central Thimble) in-core irradiation facility was selected as the location for validation. The comparison was performed with the typical flux measurement method routinely practiced at TRR-1/M1, that is, the foil activation technique. In this technique, gold foil is irradiated for a certain period of time and the activity of the irradiated target is measured to derive the thermal neutron flux. Additionally, the flux measurement with SPND (self-powered neutron detector) was also performed for comparison. The thermal neutron flux from the MCNPX simulation was found to be 1.79×1013 neutron/cm2s while that from the foil activation measurement was 4.68×1013 neutron/cm2s. On the other hand, the thermal neutron flux from the measurement using SPND was 2.47×1013 neutron/cm2s. An assessment of the differences among the three methods was done. The difference of the MCNPX with the foil activation technique was found to be 67.8% and the difference of the MCNPX with the SPND was found to be 27.8%.

Forward Modeling of Coronal Mass Ejection Flux Ropes in the Inner Heliosphere with 3DCORE.

PubMed

Möstl, C; Amerstorfer, T; Palmerio, E; Isavnin, A; Farrugia, C J; Lowder, C; Winslow, R M; Donnerer, J M; Kilpua, E K J; Boakes, P D

2018-03-01

Forecasting the geomagnetic effects of solar storms, known as coronal mass ejections (CMEs), is currently severely limited by our inability to predict the magnetic field configuration in the CME magnetic core and by observational effects of a single spacecraft trajectory through its 3-D structure. CME magnetic flux ropes can lead to continuous forcing of the energy input to the Earth's magnetosphere by strong and steady southward-pointing magnetic fields. Here we demonstrate in a proof-of-concept way a new approach to predict the southward field B z in a CME flux rope. It combines a novel semiempirical model of CME flux rope magnetic fields (Three-Dimensional Coronal ROpe Ejection) with solar observations and in situ magnetic field data from along the Sun-Earth line. These are provided here by the MESSENGER spacecraft for a CME event on 9-13 July 2013. Three-Dimensional Coronal ROpe Ejection is the first such model that contains the interplanetary propagation and evolution of a 3-D flux rope magnetic field, the observation by a synthetic spacecraft, and the prediction of an index of geomagnetic activity. A counterclockwise rotation of the left-handed erupting CME flux rope in the corona of 30° and a deflection angle of 20° is evident from comparison of solar and coronal observations. The calculated Dst matches reasonably the observed Dst minimum and its time evolution, but the results are highly sensitive to the CME axis orientation. We discuss assumptions and limitations of the method prototype and its potential for real time space weather forecasting and heliospheric data interpretation.

Forward Modeling of Coronal Mass Ejection Flux Ropes in the Inner Heliosphere with 3DCORE

NASA Astrophysics Data System (ADS)

Möstl, C.; Amerstorfer, T.; Palmerio, E.; Isavnin, A.; Farrugia, C. J.; Lowder, C.; Winslow, R. M.; Donnerer, J. M.; Kilpua, E. K. J.; Boakes, P. D.

2018-03-01

Forecasting the geomagnetic effects of solar storms, known as coronal mass ejections (CMEs), is currently severely limited by our inability to predict the magnetic field configuration in the CME magnetic core and by observational effects of a single spacecraft trajectory through its 3-D structure. CME magnetic flux ropes can lead to continuous forcing of the energy input to the Earth's magnetosphere by strong and steady southward-pointing magnetic fields. Here we demonstrate in a proof-of-concept way a new approach to predict the southward field Bz in a CME flux rope. It combines a novel semiempirical model of CME flux rope magnetic fields (Three-Dimensional Coronal ROpe Ejection) with solar observations and in situ magnetic field data from along the Sun-Earth line. These are provided here by the MESSENGER spacecraft for a CME event on 9-13 July 2013. Three-Dimensional Coronal ROpe Ejection is the first such model that contains the interplanetary propagation and evolution of a 3-D flux rope magnetic field, the observation by a synthetic spacecraft, and the prediction of an index of geomagnetic activity. A counterclockwise rotation of the left-handed erupting CME flux rope in the corona of 30° and a deflection angle of 20° is evident from comparison of solar and coronal observations. The calculated Dst matches reasonably the observed Dst minimum and its time evolution, but the results are highly sensitive to the CME axis orientation. We discuss assumptions and limitations of the method prototype and its potential for real time space weather forecasting and heliospheric data interpretation.

Minimum-dissipation scalar transport model for large-eddy simulation of turbulent flows

NASA Astrophysics Data System (ADS)

Abkar, Mahdi; Bae, Hyun J.; Moin, Parviz

2016-08-01

Minimum-dissipation models are a simple alternative to the Smagorinsky-type approaches to parametrize the subfilter turbulent fluxes in large-eddy simulation. A recently derived model of this type for subfilter stress tensor is the anisotropic minimum-dissipation (AMD) model [Rozema et al., Phys. Fluids 27, 085107 (2015), 10.1063/1.4928700], which has many desirable properties. It is more cost effective than the dynamic Smagorinsky model, it appropriately switches off in laminar and transitional flows, and it is consistent with the exact subfilter stress tensor on both isotropic and anisotropic grids. In this study, an extension of this approach to modeling the subfilter scalar flux is proposed. The performance of the AMD model is tested in the simulation of a high-Reynolds-number rough-wall boundary-layer flow with a constant and uniform surface scalar flux. The simulation results obtained from the AMD model show good agreement with well-established empirical correlations and theoretical predictions of the resolved flow statistics. In particular, the AMD model is capable of accurately predicting the expected surface-layer similarity profiles and power spectra for both velocity and scalar concentration.

Numerical Experiments Based on the Catastrophe Model of Solar Eruptions

NASA Astrophysics Data System (ADS)

Xie, X. Y.; Ziegler, U.; Mei, Z. X.; Wu, N.; Lin, J.

2017-11-01

On the basis of the catastrophe model developed by Isenberg et al., we use the NIRVANA code to perform the magnetohydrodynamics (MHD) numerical experiments to look into various behaviors of the coronal magnetic configuration that includes a current-carrying flux rope used to model the prominence levitating in the corona. These behaviors include the evolution in equilibrium heights of the flux rope versus the change in the background magnetic field, the corresponding internal equilibrium of the flux rope, dynamic properties of the flux rope after the system loses equilibrium, as well as the impact of the referential radius on the equilibrium heights of the flux rope. In our calculations, an empirical model of the coronal density distribution given by Sittler & Guhathakurta is used, and the physical diffusion is included. Our experiments show that the deviation of simulations in the equilibrium heights from the theoretical results exists, but is not apparent, and the evolutionary features of the two results are similar. If the flux rope is initially locate at the stable branch of the theoretical equilibrium curve, the flux rope will quickly reach the equilibrium position in the simulation after several rounds of oscillations as a result of the self-adjustment of the system; and the flux rope lose the equilibrium if the initial location of the flux rope is set at the critical point on the theoretical equilibrium curve. Correspondingly, the internal equilibrium of the flux rope can be reached as well, and the deviation from the theoretical results is somewhat apparent since the approximation of the small radius of the flux rope is lifted in our experiments, but such deviation does not affect the global equilibrium in the system. The impact of the referential radius on the equilibrium heights of the flux rope is consistent with the prediction of the theory. Our calculations indicate that the motion of the flux rope after the loss of equilibrium is consistent with which is predicted by the Lin-Forbes model and observations. Formation of the fast mode shock ahead of the flux rope is observed in our experiments. Outward motions of the flux rope are smooth, and magnetic energy is continuously converted into the other types of energy because both the diffusions are considered in calculations, and magnetic reconnection is allowed to occur successively in the current sheet behind the flux rope.

Estimation of Scale Deposition in the Water Walls of an Operating Indian Coal Fired Boiler: Predictive Modeling Approach Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Kumari, Amrita; Das, Suchandan Kumar; Srivastava, Prem Kumar

2016-04-01

Application of computational intelligence for predicting industrial processes has been in extensive use in various industrial sectors including power sector industry. An ANN model using multi-layer perceptron philosophy has been proposed in this paper to predict the deposition behaviors of oxide scale on waterwall tubes of a coal fired boiler. The input parameters comprises of boiler water chemistry and associated operating parameters, such as, pH, alkalinity, total dissolved solids, specific conductivity, iron and dissolved oxygen concentration of the feed water and local heat flux on boiler tube. An efficient gradient based network optimization algorithm has been employed to minimize neural predictions errors. Effects of heat flux, iron content, pH and the concentrations of total dissolved solids in feed water and other operating variables on the scale deposition behavior have been studied. It has been observed that heat flux, iron content and pH of the feed water have a relatively prime influence on the rate of oxide scale deposition in water walls of an Indian boiler. Reasonably good agreement between ANN model predictions and the measured values of oxide scale deposition rate has been observed which is corroborated by the regression fit between these values.

Evaluation of Radiation Belt Space Weather Forecasts for Internal Charging Analyses

NASA Technical Reports Server (NTRS)

Minow, Joseph I.; Coffey, Victoria N.; Jun, Insoo; Garrett, Henry B.

2007-01-01

A variety of static electron radiation belt models, space weather prediction tools, and energetic electron datasets are used by spacecraft designers and operations support personnel as internal charging code inputs to evaluate electrostatic discharge risks in space systems due to exposure to relativistic electron environments. Evaluating the environment inputs is often accomplished by comparing whether the data set or forecast tool reliability predicts measured electron flux (or fluence over a given period) for some chosen period. While this technique is useful as a model metric, it does not provide the information necessary to evaluate whether short term deviances of the predicted flux is important in the charging evaluations. In this paper, we use a 1-D internal charging model to compute electric fields generated in insulating materials as a function of time when exposed to relativistic electrons in the Earth's magnetosphere. The resulting fields are assumed to represent the "true" electric fields and are compared with electric field values computed from relativistic electron environments derived from a variety of space environment and forecast tools. Deviances in predicted fields compared to the "true" fields which depend on insulator charging time constants will be evaluated as a potential metric for determining the importance of predicted and measured relativistic electron flux deviations over a range of time scales.

Predicting dynamic metabolic demands in the photosynthetic eukaryote Chlorella vulgaris

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zuniga, Cristal; Levering, Jennifer; Antoniewicz, Maciek R.

Phototrophic organisms exhibit a highly dynamic proteome, adapting their biomass composition in response to diurnal light/dark cycles and nutrient availability. We used experimentally determined biomass compositions over the course of growth to determine and constrain the biomass objective function (BOF) in a genome-scale metabolic model of Chlorella vulgaris UTEX 395 over time. Changes in the BOF, which encompasses all metabolites necessary to produce biomass, influence the state of the metabolic network thus directly affecting predictions. Simulations using dynamic BOFs predicted distinct proteome demands during heterotrophic or photoautotrophic growth. Model-driven analysis of extracellular nitrogen concentrations and predicted nitrogen uptake rates revealedmore » an intracellular nitrogen pool, which contains 38% of the total nitrogen provided in the medium for photoautotrophic and 13% for heterotrophic growth. Agreement between flux and gene expression trends was determined by statistical comparison. Accordance between predicted fluxes trends and gene expression trends was found for 65% of multi-subunit enzymes and 75% of allosteric reactions. Reactions with the highest agreement between simulations and experimental data were associated with energy metabolism, terpenoid biosynthesis, fatty acids, nucleotides, and amino acids metabolism. Moreover, predicted flux distributions at each time point were compared with gene expression data to gain new insights into intracellular compartmentalization, specifically for transporters. A total of 103 genes related to internal transport reactions were identified and added to the updated model of C. vulgaris, iCZ946, thus increasing our knowledgebase by 10% for this model green alga.« less

Predicting dynamic metabolic demands in the photosynthetic eukaryote Chlorella vulgaris

DOE PAGES

Zuniga, Cristal; Levering, Jennifer; Antoniewicz, Maciek R.; ...

2017-09-26

Phototrophic organisms exhibit a highly dynamic proteome, adapting their biomass composition in response to diurnal light/dark cycles and nutrient availability. We used experimentally determined biomass compositions over the course of growth to determine and constrain the biomass objective function (BOF) in a genome-scale metabolic model of Chlorella vulgaris UTEX 395 over time. Changes in the BOF, which encompasses all metabolites necessary to produce biomass, influence the state of the metabolic network thus directly affecting predictions. Simulations using dynamic BOFs predicted distinct proteome demands during heterotrophic or photoautotrophic growth. Model-driven analysis of extracellular nitrogen concentrations and predicted nitrogen uptake rates revealedmore » an intracellular nitrogen pool, which contains 38% of the total nitrogen provided in the medium for photoautotrophic and 13% for heterotrophic growth. Agreement between flux and gene expression trends was determined by statistical comparison. Accordance between predicted fluxes trends and gene expression trends was found for 65% of multi-subunit enzymes and 75% of allosteric reactions. Reactions with the highest agreement between simulations and experimental data were associated with energy metabolism, terpenoid biosynthesis, fatty acids, nucleotides, and amino acids metabolism. Moreover, predicted flux distributions at each time point were compared with gene expression data to gain new insights into intracellular compartmentalization, specifically for transporters. A total of 103 genes related to internal transport reactions were identified and added to the updated model of C. vulgaris, iCZ946, thus increasing our knowledgebase by 10% for this model green alga.« less

Meteor Shower Forecasting for Spacecraft Operations

NASA Technical Reports Server (NTRS)

Moorhead, Althea V.; Cooke, William J.; Campbell-Brown, Margaret D.

2017-01-01

Although sporadic meteoroids generally pose a much greater hazard to spacecraft than shower meteoroids, meteor showers can significantly increase the risk of damage over short time periods. Because showers are brief, it is sometimes possible to mitigate the risk operationally, which requires accurate predictions of shower activity. NASA's Meteoroid Environment Office (MEO) generates an annual meteor shower forecast that describes the variations in the near-Earth meteoroid flux produced by meteor showers, and presents the shower flux both in absolute terms and relative to the sporadic flux. The shower forecast incorporates model predictions of annual variations in shower activity and quotes fluxes to several limiting particle kinetic energies. In this work, we describe our forecasting methods and present recent improvements to the temporal profiles based on flux measurements from the Canadian Meteor Orbit Radar (CMOR).

Analysis of optimality in natural and perturbed metabolic networks

PubMed Central

Segrè, Daniel; Vitkup, Dennis; Church, George M.

2002-01-01

An important goal of whole-cell computational modeling is to integrate detailed biochemical information with biological intuition to produce testable predictions. Based on the premise that prokaryotes such as Escherichia coli have maximized their growth performance along evolution, flux balance analysis (FBA) predicts metabolic flux distributions at steady state by using linear programming. Corroborating earlier results, we show that recent intracellular flux data for wild-type E. coli JM101 display excellent agreement with FBA predictions. Although the assumption of optimality for a wild-type bacterium is justifiable, the same argument may not be valid for genetically engineered knockouts or other bacterial strains that were not exposed to long-term evolutionary pressure. We address this point by introducing the method of minimization of metabolic adjustment (MOMA), whereby we test the hypothesis that knockout metabolic fluxes undergo a minimal redistribution with respect to the flux configuration of the wild type. MOMA employs quadratic programming to identify a point in flux space, which is closest to the wild-type point, compatibly with the gene deletion constraint. Comparing MOMA and FBA predictions to experimental flux data for E. coli pyruvate kinase mutant PB25, we find that MOMA displays a significantly higher correlation than FBA. Our method is further supported by experimental data for E. coli knockout growth rates. It can therefore be used for predicting the behavior of perturbed metabolic networks, whose growth performance is in general suboptimal. MOMA and its possible future extensions may be useful in understanding the evolutionary optimization of metabolism. PMID:12415116

Analysis of a multi-machine database on divertor heat fluxesa)

NASA Astrophysics Data System (ADS)

Makowski, M. A.; Elder, D.; Gray, T. K.; LaBombard, B.; Lasnier, C. J.; Leonard, A. W.; Maingi, R.; Osborne, T. H.; Stangeby, P. C.; Terry, J. L.; Watkins, J.

2012-05-01

A coordinated effort to measure divertor heat flux characteristics in fully attached, similarly shaped H-mode plasmas on C-Mod, DIII-D, and NSTX was carried out in 2010 in order to construct a predictive scaling relation applicable to next step devices including ITER, FNSF, and DEMO. Few published scaling laws are available and those that have been published were obtained under widely varying conditions and divertor geometries, leading to conflicting predictions for this critically important quantity. This study was designed to overcome these deficiencies. Analysis of the combined data set reveals that the primary dependence of the parallel heat flux width is robustly inverse with Ip, which all three tokamaks independently demonstrate. An improved Thomson scattering system on DIII-D has yielded very accurate scrape off layer (SOL) profile measurements from which tests of parallel transport models have been made. It is found that a flux-limited model agrees best with the data at all collisionalities, while a Spitzer resistivity model agrees at higher collisionality where it is more valid. The SOL profile measurements and divertor heat flux scaling are consistent with a heuristic drift based model as well as a critical gradient model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blijderveen, Maarten van; University of Twente, Department of Thermal Engineering, Drienerlolaan 5, 7522 NB Enschede; Bramer, Eddy A.

Highlights: Black-Right-Pointing-Pointer We model piloted ignition times of wood and plastics. Black-Right-Pointing-Pointer The model is applied on a packed bed. Black-Right-Pointing-Pointer When the air flow is above a critical level, no ignition can take place. - Abstract: To gain insight in the startup of an incinerator, this article deals with piloted ignition. A newly developed model is described to predict the piloted ignition times of wood, PMMA and PVC. The model is based on the lower flammability limit and the adiabatic flame temperature at this limit. The incoming radiative heat flux, sample thickness and moisture content are some of themore » used variables. Not only the ignition time can be calculated with the model, but also the mass flux and surface temperature at ignition. The ignition times for softwoods and PMMA are mainly under-predicted. For hardwoods and PVC the predicted ignition times agree well with experimental results. Due to a significant scatter in the experimental data the mass flux and surface temperature calculated with the model are hard to validate. The model is applied on the startup of a municipal waste incineration plant. For this process a maximum allowable primary air flow is derived. When the primary air flow is above this maximum air flow, no ignition can be obtained.« less

Impact of Satellite Remote Sensing Data on Simulations of ...

EPA Pesticide Factsheets

We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer (MODIS) were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability wasmissed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the

Terrestrial Carbon Sinks in the Brazilian Amazon and Cerrado Region Predicted from MODIS Satellite Data and Ecosystem Modeling

NASA Technical Reports Server (NTRS)

Potter, C.; Klooster, S.; Huete, A.; Genovese, V.; Bustamante, M.; Ferreira, L. Guimaraes; deOliveira, R. C., Jr.; Zepp, R.

2009-01-01

A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondonia and the northern portions of the state of Par a. These areas were not significantly impacted by the 2002-2003 El Nino event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhao and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly MODIS Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of MODIS Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.

Time variation of galactic cosmic rays

NASA Technical Reports Server (NTRS)

Evenson, Paul

1988-01-01

Time variations in the flux of galactic cosmic rays are the result of changing conditions in the solar wind. Maximum cosmic ray fluxes, which occur when solar activity is at a minimum, are well defined. Reductions from this maximum level are typically systematic and predictable but on occasion are rapid and unexpected. Models relating the flux level at lower energy to that at neutron monitor energy are typically accurate to 20 percent of the total excursion at that energy. Other models, relating flux to observables such as sunspot number, flare frequency, and current sheet tilt are phenomenological but nevertheless can be quite accurate.

AGM2015: Antineutrino Global Map 2015

PubMed Central

Usman, S.M.; Jocher, G.R.; Dye, S.T.; McDonough, W.F.; Learned, J.G.

2015-01-01

Every second greater than 1025 antineutrinos radiate to space from Earth, shining like a faint antineutrino star. Underground antineutrino detectors have revealed the rapidly decaying fission products inside nuclear reactors, verified the long-lived radioactivity inside our planet, and informed sensitive experiments for probing fundamental physics. Mapping the anisotropic antineutrino flux and energy spectrum advance geoscience by defining the amount and distribution of radioactive power within Earth while critically evaluating competing compositional models of the planet. We present the Antineutrino Global Map 2015 (AGM2015), an experimentally informed model of Earth’s surface antineutrino flux over the 0 to 11 MeV energy spectrum, along with an assessment of systematic errors. The open source AGM2015 provides fundamental predictions for experiments, assists in strategic detector placement to determine neutrino mass hierarchy, and aids in identifying undeclared nuclear reactors. We use cosmochemically and seismologically informed models of the radiogenic lithosphere/mantle combined with the estimated antineutrino flux, as measured by KamLAND and Borexino, to determine the Earth’s total antineutrino luminosity at . We find a dominant flux of geo-neutrinos, predict sub-equal crust and mantle contributions, with ~1% of the total flux from man-made nuclear reactors. PMID:26323507

AGM2015: Antineutrino Global Map 2015.

PubMed

Usman, S M; Jocher, G R; Dye, S T; McDonough, W F; Learned, J G

2015-09-01

Every second greater than 10(25) antineutrinos radiate to space from Earth, shining like a faint antineutrino star. Underground antineutrino detectors have revealed the rapidly decaying fission products inside nuclear reactors, verified the long-lived radioactivity inside our planet, and informed sensitive experiments for probing fundamental physics. Mapping the anisotropic antineutrino flux and energy spectrum advance geoscience by defining the amount and distribution of radioactive power within Earth while critically evaluating competing compositional models of the planet. We present the Antineutrino Global Map 2015 (AGM2015), an experimentally informed model of Earth's surface antineutrino flux over the 0 to 11 MeV energy spectrum, along with an assessment of systematic errors. The open source AGM2015 provides fundamental predictions for experiments, assists in strategic detector placement to determine neutrino mass hierarchy, and aids in identifying undeclared nuclear reactors. We use cosmochemically and seismologically informed models of the radiogenic lithosphere/mantle combined with the estimated antineutrino flux, as measured by KamLAND and Borexino, to determine the Earth's total antineutrino luminosity at . We find a dominant flux of geo-neutrinos, predict sub-equal crust and mantle contributions, with ~1% of the total flux from man-made nuclear reactors.

Prediction of LDEF exposure to the ionizing radiation environment

NASA Technical Reports Server (NTRS)

Watts, J. W.; Armstrong, T. W.; Colborn, B. L.

1996-01-01

Predictions of the LDEF mission's trapped proton and electron and galactic cosmic ray proton exposures have been made using the currently accepted models with improved resolution near mission end and better modeling of solar cycle effects. An extension of previous calculations, to provide a more definitive description of the LDEF exposure to ionizing radiation, is represented by trapped proton and electron flux as a function of mission time, presented considering altitude and solar activity variation during the mission and the change in galactic cosmic ray proton flux over the mission. Modifications of the AP8MAX and AP8MIN fluence led to a reduction of fluence by 20%. A modified interpolation model developed by Daly and Evans resulted in 30% higher dose and activation levels, which better agreed with measured values than results predicted using the Vette model.

Mass and heat transfer model of Tubular Solar Still

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahsan, Amimul; Fukuhara, Teruyuki

2010-07-15

In this paper, a new mass and heat transfer model of a Tubular Solar Still (TSS) was proposed incorporating various mass and heat transfer coefficients taking account of the humid air properties inside the still. The heat balance of the humid air and the mass balance of the water vapor in the humid air were formulized for the first time. As a result, the proposed model enabled to calculate the diurnal variations of the temperature, water vapor density and relative humidity of the humid air, and to predict the hourly condensation flux besides the temperatures of the water, cover andmore » trough, and the hourly evaporation flux. The validity of the proposed model was verified using the field experimental results carried out in Fukui, Japan and Muscat, Oman in 2008. The diurnal variations of the calculated temperatures and water vapor densities had a good agreement with the observed ones. Furthermore, the proposed model can predict the daily and hourly production flux precisely. (author)« less

Prediction of Turbulent Temperature Fluctuations in Hot Jets

NASA Technical Reports Server (NTRS)

DeBonis, James R.

2017-01-01

Large-eddy simulations (LES) were used to investigate turbulent temperature fluctuations and turbulent heat flux in hot jets. A high-resolution finite-difference Navier-Stokes solver was used to compute the flow from a 2-inch round nozzle. Three different flow conditions of varying jet Mach numbers and temperature ratios were examined. The LES results showed that the temperature field behaves similar to the velocity field, but with a more rapidly spreading mixing layer. Predictions of mean, mu-bar(sub i), and fluctuating, mu'(sub i), velocities were compared to particle image velocimetry data. Predictions of mean, T-bar, and fluctuating, T', temperature were compared to data obtained using Rayleigh scattering and Raman spectroscopy. Very good agreement with experimental data was demonstrated for the mean and fluctuating velocities. The LES correctly predicts the behavior of the turbulent temperature field, but over-predicts the levels of the fluctuations. The turbulent heat flux was examined and compared to Reynolds-averaged Navier-Stokes (RANS) results. The LES and RANS simulations produced very similar results for the radial heat flux. However, the axial heat flux obtained from the LES differed significantly from the RANS result in both structure and magnitude, indicating that the gradient diffusion type model in RANS is inadequate. Finally, the LES data was used to compute the turbulent Prandtl number and verify that a constant value of 0.7 used in the RANS models is a reasonable assumption.

Exploiting satellite earth observation to quantify current global oceanic DMS flux and its future climate sensitivity

NASA Astrophysics Data System (ADS)

Land, P. E.; Shutler, J. D.; Bell, T. G.; Yang, M.

2014-11-01

We used coincident Envisat RA2 and AATSR temperature and wind speed data from 2008/2009 to calculate the global net sea-air flux of dimethyl sulfide (DMS), which we estimate to be 19.6 Tg S a-1. Our monthly flux calculations are compared to open ocean eddy correlation measurements of DMS flux from 10 recent cruises, with a root mean square difference of 3.1 μmol m-2 day-1. In a sensitivity analysis, we varied temperature, salinity, surface wind speed, and aqueous DMS concentration, using fixed global changes as well as CMIP5 model output. The range of DMS flux in future climate scenarios is discussed. The CMIP5 model predicts a reduction in surface wind speed and we estimate that this will decrease the global annual sea-air flux of DMS by 22% over 25 years. Concurrent changes in temperature, salinity, and DMS concentration increase the global flux by much smaller amounts. The net effect of all CMIP5 modelled 25 year predictions was a 19% reduction in global DMS flux. 25 year DMS concentration changes had significant regional effects, some positive (Southern Ocean, North Atlantic, Northwest Pacific) and some negative (isolated regions along the Equator and in the Indian Ocean). Using satellite-detected coverage of coccolithophore blooms, our estimate of their contribution to North Atlantic DMS emissions suggests that the coccolithophores contribute only a small percentage of the North Atlantic annual flux estimate, but may be more important in the summertime and in the northeast Atlantic.

Comparison of radiation parametrizations within the HARMONIE-AROME NWP model

NASA Astrophysics Data System (ADS)

Rontu, Laura; Lindfors, Anders V.

2018-05-01

Downwelling shortwave radiation at the surface (SWDS, global solar radiation flux), given by three different parametrization schemes, was compared to observations in the HARMONIE-AROME numerical weather prediction (NWP) model experiments over Finland in spring 2017. Simulated fluxes agreed well with each other and with the observations in the clear-sky cases. In the cloudy-sky conditions, all schemes tended to underestimate SWDS at the daily level, as compared to the measurements. Large local and temporal differences between the model results and observations were seen, related to the variations and uncertainty of the predicted cloud properties. The results suggest a possibility to benefit from the use of different radiative transfer parametrizations in a NWP model to obtain perturbations for the fine-resolution ensemble prediction systems. In addition, we recommend usage of the global radiation observations for the standard validation of the NWP models.

Revisiting the global surface energy budgets with maximum-entropy-production model of surface heat fluxes

NASA Astrophysics Data System (ADS)

Huang, Shih-Yu; Deng, Yi; Wang, Jingfeng

2017-09-01

The maximum-entropy-production (MEP) model of surface heat fluxes, based on contemporary non-equilibrium thermodynamics, information theory, and atmospheric turbulence theory, is used to re-estimate the global surface heat fluxes. The MEP model predicted surface fluxes automatically balance the surface energy budgets at all time and space scales without the explicit use of near-surface temperature and moisture gradient, wind speed and surface roughness data. The new MEP-based global annual mean fluxes over the land surface, using input data of surface radiation, temperature data from National Aeronautics and Space Administration-Clouds and the Earth's Radiant Energy System (NASA CERES) supplemented by surface specific humidity data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA), agree closely with previous estimates. The new estimate of ocean evaporation, not using the MERRA reanalysis data as model inputs, is lower than previous estimates, while the new estimate of ocean sensible heat flux is higher than previously reported. The MEP model also produces the first global map of ocean surface heat flux that is not available from existing global reanalysis products.

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens Using Proteomic Data from a Field Biostimulation Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, Yilin; Wilkins, Michael J.; Yabusaki, Steven B.

2012-12-12

Biomass and shotgun global proteomics data that reflected relative protein abundances from samples collected during the 2008 experiment at the U.S. Department of Energy Integrated Field-Scale Subsurface Research Challenge site in Rifle, Colorado, provided an unprecedented opportunity to validate a genome-scale metabolic model of Geobacter metallireducens and assess its performance with respect to prediction of metal reduction, biomass yield, and growth rate under dynamic field conditions. Reconstructed from annotated genomic sequence, biochemical, and physiological data, the constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes.more » Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low fluxes through amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.« less

Increased sediment oxygen flux in lakes and reservoirs: The impact of hypolimnetic oxygenation

NASA Astrophysics Data System (ADS)

Bierlein, Kevin A.; Rezvani, Maryam; Socolofsky, Scott A.; Bryant, Lee D.; Wüest, Alfred; Little, John C.

2017-06-01

Hypolimnetic oxygenation is an increasingly common lake management strategy for mitigating hypoxia/anoxia and associated deleterious effects on water quality. A common effect of oxygenation is increased oxygen consumption in the hypolimnion and predicting the magnitude of this increase is the crux of effective oxygenation system design. Simultaneous measurements of sediment oxygen flux (JO2) and turbulence in the bottom boundary layer of two oxygenated lakes were used to investigate the impact of oxygenation on JO2. Oxygenation increased JO2 in both lakes by increasing the bulk oxygen concentration, which in turn steepens the diffusive gradient across the diffusive boundary layer. At high flow rates, the diffusive boundary layer thickness decreased as well. A transect along one of the lakes showed JO2 to be spatially quite variable, with near-field and far-field JO2 differing by a factor of 4. Using these in situ measurements, physical models of interfacial flux were compared to microprofile-derived JO2 to determine which models adequately predict JO2 in oxygenated lakes. Models based on friction velocity, turbulence dissipation rate, and the integral scale of turbulence agreed with microprofile-derived JO2 in both lakes. These models could potentially be used to predict oxygenation-induced oxygen flux and improve oxygenation system design methods for a broad range of reservoir systems.

Synergy between (13)C-metabolic flux analysis and flux balance analysis for understanding metabolic adaptation to anaerobiosis in E. coli.

PubMed

Chen, Xuewen; Alonso, Ana P; Allen, Doug K; Reed, Jennifer L; Shachar-Hill, Yair

2011-01-01

Genome-based Flux Balance Analysis (FBA) and steady-state isotopic-labeling-based Metabolic Flux Analysis (MFA) are complimentary approaches to predicting and measuring the operation and regulation of metabolic networks. Here, genome-derived models of Escherichia coli (E. coli) metabolism were used for FBA and ¹³C-MFA analyses of aerobic and anaerobic growths of wild-type E. coli (K-12 MG1655) cells. Validated MFA flux maps reveal that the fraction of maintenance ATP consumption in total ATP production is about 14% higher under anaerobic (51.1%) than aerobic conditions (37.2%). FBA revealed that an increased ATP utilization is consumed by ATP synthase to secrete protons from fermentation. The TCA cycle is shown to be incomplete in aerobically growing cells and submaximal growth is due to limited oxidative phosphorylation. An FBA was successful in predicting product secretion rates in aerobic culture if both glucose and oxygen uptake measurement were constrained, but the most-frequently predicted values of internal fluxes yielded from sampling the feasible space differ substantially from MFA-derived fluxes. © 2010 Elsevier Inc. All rights reserved.

Non-growing season nitrous oxide fluxes from agricultural soils

NASA Astrophysics Data System (ADS)

Kariyapperuma Athukoralage, Kumudinie

A two-year field experiment was conducted at the Arkell Research Station, Ontario, Canada to evaluate composting as a mitigation strategy for greenhouse gases (GHGs). The objectives were to quantify and compare non-growing season nitrous oxide (N2O) fluxes from agricultural soils after fall manure application of composted and untreated liquid swine manure. Nitrous oxide fluxes were measured using a micrometeorological method. Compared to untreated liquid swine manure (LSM), composted swine manure (CSM) resulted in 57% reduction of soil N2O emissions during February to April in 2005, but emissions during the same period in 2006 were not affected by treatments. This effect was related to fall and winter weather conditions with the significant reduction occurring in the year when soil freezing was more pronounced. The DNDC (DeNitrification-DeComposition) model was tested against data measured during the non-growing seasons from 2000 to 2004, for farming with conventional management at the Elora Research Station, Ontario, Canada. The objective was to assess the ability of the DNDC model to simulate non-growing season N2O fluxes from soils in southwestern Ontario. Comparison between model-simulated and measured data indicated that background fluxes were relatively well predicted. The spring thaw N2O flux event was correctly timed by the DNDC model, but was smaller than the measured spring thaw event. Though there was no N2O emission event measured in early May, the DNDC model predicted a large event, simultaneous with the physical release of predicted ice-trapped N2O. Removing the large and late predicted emission peak and increasing the contribution of newly produced N2O due to denitrification to the early spring thaw event were proposed. Three data sets from studies conducted in Ontario, Canada were used to estimate and compare the overall GHG (N2O and methane) emissions from LSM and CSM. Compared to LSM storage, the composting process reduced GHG emissions by 35% (CO2-eq), mainly due to decreased methane fluxes. Land application of CSM showed a 38% reduction of total GHGs (CO 2-eq), compared to fall application of LSM. In comparison to liquid swine manure management systems, aerobic composting reduced the overall GHG emissions on a CO2-equivalent basis by 35%.

Error Quantification and Confidence Assessment of Aerothermal Model Predictions for Hypersonic Aircraft (Preprint)

DTIC Science & Technology

2013-09-01

based confidence metric is used to compare several different model predictions with the experimental data. II. Aerothermal Model Definition and...whereas 5% measurement uncertainty is assumed for aerodynamic pressure and heat flux measurements 4p y and 4Q y . Bayesian updating according... definitive conclusions for these particular aerodynamic models. However, given the confidence associated with the 4 sdp predictions for Run 30 (H/D

In vivo and in silico dynamics of the development of Metabolic Syndrome.

PubMed

Rozendaal, Yvonne J W; Wang, Yanan; Paalvast, Yared; Tambyrajah, Lauren L; Li, Zhuang; Willems van Dijk, Ko; Rensen, Patrick C N; Kuivenhoven, Jan A; Groen, Albert K; Hilbers, Peter A J; van Riel, Natal A W

2018-06-01

The Metabolic Syndrome (MetS) is a complex, multifactorial disorder that develops slowly over time presenting itself with large differences among MetS patients. We applied a systems biology approach to describe and predict the onset and progressive development of MetS, in a study that combined in vivo and in silico models. A new data-driven, physiological model (MINGLeD: Model INtegrating Glucose and Lipid Dynamics) was developed, describing glucose, lipid and cholesterol metabolism. Since classic kinetic models cannot describe slowly progressing disorders, a simulation method (ADAPT) was used to describe longitudinal dynamics and to predict metabolic concentrations and fluxes. This approach yielded a novel model that can describe long-term MetS development and progression. This model was integrated with longitudinal in vivo data that was obtained from male APOE*3-Leiden.CETP mice fed a high-fat, high-cholesterol diet for three months and that developed MetS as reflected by classical symptoms including obesity and glucose intolerance. Two distinct subgroups were identified: those who developed dyslipidemia, and those who did not. The combination of MINGLeD with ADAPT could correctly predict both phenotypes, without making any prior assumptions about changes in kinetic rates or metabolic regulation. Modeling and flux trajectory analysis revealed that differences in liver fluxes and dietary cholesterol absorption could explain this occurrence of the two different phenotypes. In individual mice with dyslipidemia dietary cholesterol absorption and hepatic turnover of metabolites, including lipid fluxes, were higher compared to those without dyslipidemia. Predicted differences were also observed in gene expression data, and consistent with the emergence of insulin resistance and hepatic steatosis, two well-known MetS co-morbidities. Whereas MINGLeD specifically models the metabolic derangements underlying MetS, the simulation method ADAPT is generic and can be applied to other diseases where dynamic modeling and longitudinal data are available.

Variable Density Multilayer Insulation for Cryogenic Storage

NASA Technical Reports Server (NTRS)

Hedayat, A.; Brown, T. M.; Hastings, L. J.; Martin, J.

2000-01-01

Two analytical models for a foam/Variable Density Multi-Layer Insulation (VD-MLI) system performance are discussed. Both models are one-dimensional and contain three heat transfer mechanisms, namely conduction through the spacer material, radiation between the shields, and conduction through the gas. One model is based on the methodology developed by McIntosh while the other model is based on the Lockheed semi-empirical approach. All models input variables are based on the Multi-purpose Hydrogen Test Bed (MHTB) geometry and available values for material properties and empirical solid conduction coefficient. Heat flux predictions are in good agreement with the MHTB data, The heat flux predictions are presented for the foam/MLI combinations with 30, 45, 60, and 75 MLI layers

Colluvial deposits as a possible weathering reservoir in uplifting mountains

NASA Astrophysics Data System (ADS)

Carretier, Sébastien; Goddéris, Yves; Martinez, Javier; Reich, Martin; Martinod, Pierre

2018-03-01

The role of mountain uplift in the evolution of the global climate over geological times is controversial. At the heart of this debate is the capacity of rapid denudation to drive silicate weathering, which consumes CO2. Here we present the results of a 3-D model that couples erosion and weathering during mountain uplift, in which, for the first time, the weathered material is traced during its stochastic transport from the hillslopes to the mountain outlet. To explore the response of weathering fluxes to progressively cooler and drier climatic conditions, we run model simulations accounting for a decrease in temperature with or without modifications in the rainfall pattern based on a simple orographic model. At this stage, the model does not simulate the deep water circulation, the precipitation of secondary minerals, variations in the pH, below-ground pCO2, and the chemical affinity of the water in contact with minerals. Consequently, the predicted silicate weathering fluxes probably represent a maximum, although the predicted silicate weathering rates are within the range of silicate and total weathering rates estimated from field data. In all cases, the erosion rate increases during mountain uplift, which thins the regolith and produces a hump in the weathering rate evolution. This model thus predicts that the weathering outflux reaches a peak and then falls, consistent with predictions of previous 1-D models. By tracking the pathways of particles, the model can also consider how lateral river erosion drives mass wasting and the temporary storage of colluvial deposits on the valley sides. This reservoir is comprised of fresh material that has a residence time ranging from several years up to several thousand years. During this period, the weathering of colluvium appears to sustain the mountain weathering flux. The relative weathering contribution of colluvium depends on the area covered by regolith on the hillslopes. For mountains sparsely covered by regolith during cold periods, colluvium produces most of the simulated weathering flux for a large range of erosion parameters and precipitation rate patterns. In addition to other reservoirs such as deep fractured bedrock, colluvial deposits may help to maintain a substantial and constant weathering flux in rapidly uplifting mountains during cooling periods.

Modelling the Surface Distribution of Magnetic Activity on Sun-Like Stars

NASA Astrophysics Data System (ADS)

Isik, Emre

2018-04-01

With the advent of high-precision space-borne stellar photometry and prospects for direct imaging, it is timely and essential to improve our understanding of stellar magnetic activity in rotational time scales. We present models for 'younger suns' with rotation and flux emergence rates between 1 and 16 times the solar rate. The models provide latitudinal distributions and tilt angles of bipolar magnetic regions, using flux tube rise simulations. Using these emergence patterns, we model the subsequent surface flux transport, to predict surface distributions of star-spots. Based on these models, we present preliminary results from our further modelling of the observed azimuthal magnetic fields, which strengthen for more rapidly rotating Sun-like stars.

Simplification of the Gardner model: effects on maximum upward flux in the presence of a shallow water table

NASA Astrophysics Data System (ADS)

Xing, Xuguang; Ma, Xiaoyi

2018-06-01

The maximum upward flux ( E max) is a control condition for the development of groundwater evaporation models, which can be predicted through the Gardner model. A high-precision E max prediction helps to improve irrigation practice. When using the Gardner model, it has widely been accepted to ignore parameter b (a soil-water constant) for model simplification. However, this may affect the prediction accuracy; therefore, how parameter b affects E max requires detailed investigation. An indoor one-dimensional soil-column evaporation experiment was conducted to observe E max in the presence of a water table of depth 50 cm. The study consisted of 13 treatments based on four solutes and three concentrations in groundwater: KCl, NaCl, CaCl2, and MgCl2, with concentrations of 5, 30, and 100 g/L (salty groundwater); distilled water was used as a control treatment. Results indicated that for the experimental homogeneous loam, the average E max for the treatments supplied by salty groundwater was larger than that supplied by distilled water. Furthermore, during the prediction of the Gardner-model-based E max, ignoring b and including b always led to an overestimate and underestimate, respectively, compared to the observed E max. However, the maximum upward flux calculated including b (i.e. E bmax) had higher accuracy than that ignoring b for E max prediction. Moreover, the impact of ignoring b on E max gradually weakened with increasing b value. This research helps to reveal the groundwater evaporation mechanism.

Complete Proteomic-Based Enzyme Reaction and Inhibition Kinetics Reveal How Monolignol Biosynthetic Enzyme Families Affect Metabolic Flux and Lignin in Populus trichocarpa[W

PubMed Central

Wang, Jack P.; Naik, Punith P.; Chen, Hsi-Chuan; Shi, Rui; Lin, Chien-Yuan; Liu, Jie; Shuford, Christopher M.; Li, Quanzi; Sun, Ying-Hsuan; Tunlaya-Anukit, Sermsawat; Williams, Cranos M.; Muddiman, David C.; Ducoste, Joel J.; Sederoff, Ronald R.; Chiang, Vincent L.

2014-01-01

We established a predictive kinetic metabolic-flux model for the 21 enzymes and 24 metabolites of the monolignol biosynthetic pathway using Populus trichocarpa secondary differentiating xylem. To establish this model, a comprehensive study was performed to obtain the reaction and inhibition kinetic parameters of all 21 enzymes based on functional recombinant proteins. A total of 104 Michaelis-Menten kinetic parameters and 85 inhibition kinetic parameters were derived from these enzymes. Through mass spectrometry, we obtained the absolute quantities of all 21 pathway enzymes in the secondary differentiating xylem. This extensive experimental data set, generated from a single tissue specialized in wood formation, was used to construct the predictive kinetic metabolic-flux model to provide a comprehensive mathematical description of the monolignol biosynthetic pathway. The model was validated using experimental data from transgenic P. trichocarpa plants. The model predicts how pathway enzymes affect lignin content and composition, explains a long-standing paradox regarding the regulation of monolignol subunit ratios in lignin, and reveals novel mechanisms involved in the regulation of lignin biosynthesis. This model provides an explanation of the effects of genetic and transgenic perturbations of the monolignol biosynthetic pathway in flowering plants. PMID:24619611

Microbial Abundances Predict Methane and Nitrous Oxide Fluxes from a Windrow Composting System

PubMed Central

Li, Shuqing; Song, Lina; Gao, Xiang; Jin, Yaguo; Liu, Shuwei; Shen, Qirong; Zou, Jianwen

2017-01-01

Manure composting is a significant source of atmospheric methane (CH4) and nitrous oxide (N2O) that are two potent greenhouse gases. The CH4 and N2O fluxes are mediated by methanogens and methanotrophs, nitrifying and denitrifying bacteria in composting manure, respectively, while these specific bacterial functional groups may interplay in CH4 and N2O emissions during manure composting. To test the hypothesis that bacterial functional gene abundances regulate greenhouse gas fluxes in windrow composting systems, CH4 and N2O fluxes were simultaneously measured using the chamber method, and molecular techniques were used to quantify the abundances of CH4-related functional genes (mcrA and pmoA genes) and N2O-related functional genes (amoA, narG, nirK, nirS, norB, and nosZ genes). The results indicate that changes in interacting physicochemical parameters in the pile shaped the dynamics of bacterial functional gene abundances. The CH4 and N2O fluxes were correlated with abundances of specific compositional genes in bacterial community. The stepwise regression statistics selected pile temperature, mcrA and NH4+ together as the best predictors for CH4 fluxes, and the model integrating nirK, nosZ with pmoA gene abundances can almost fully explain the dynamics of N2O fluxes over windrow composting. The simulated models were tested against measurements in paddy rice cropping systems, indicating that the models can also be applicable to predicting the response of CH4 and N2O fluxes to elevated atmospheric CO2 concentration and rising temperature. Microbial abundances could be included as indicators in the current carbon and nitrogen biogeochemical models. PMID:28373862

A new estimate of micrometeoritic flux at Mercury

NASA Astrophysics Data System (ADS)

Borin, P.; Cremonese, G.; Marzari, F.; Bruno, M.; Marchi, S.

2009-04-01

Meteoroid impacts are an important source of neutral atoms in the exosphere of Mercury. Recent papers attribute to impacting particles smaller than 1 cm the major contribution to exospheric gases. However, fluxes and impact velocities for different sizes are based on old extrapolations of similar quantities at the Earth. In this work, in order to determine the meteoritic flux at the heliocentric distance of Mercury we utilize the dynamical evolution model of dust particles of Marzari and Vanzani (1994) that numerically solves a (N+1)+M body problem (Sun + N planets + M body with zero mass) with the high-precision integrator RA15 (Everhart 1985). The solar radiation pressure and Poynting-Robertson drag, together with the gravitational interactions of the planets, are taken as major perturbing forces affecting the orbital evolution of the dust particles. From our numerical simulations we extrapolate the flux of particles hitting Mercury's surface and the corresponding distribution of impact velocities. A precise calibration of the particle flux on Mercury has been performed by comparing the predictions of our model concerning the dust infall on the Earth with experimental data. The model provide the flux of different size particles impacting Mercury and their collisional velocity distribution. We compare our results with previous estimates, in particular we take into account the work of Cintala (1992), and we find lower velocities but significantly higher fluxes. Our results show that the number of impacts given by Cintala, measured in N/years, is 80.2 times higher, but the flux measured in g• cm2s, is 409.4 times lower. We can conclude that our model predicts a number of impacts smaller than Cintala, but a much higher mass contribution.

A comparison of critical heat flux in tubes and bilaterally heated annuli

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerffer, S.; Groeneveld, D.C.; Cheng, S.C.

1995-09-01

This paper examines the critical heat flux (CHF) behaviour for annular flow in bilaterally heated annuli and compares it to that in tubes and unilaterally heated annuli. It was found that the differences in CHF between bilaterally and unilaterally heated annuli or tubes strongly depend on pressure and quality. the CHF in bilaterally heated annuli can be predicted by tube CHF prediction methods for the simultaneous CHF occurrence at both surfaces, and the following flow conditions: pressure 7-10 MPa, mass flux 0.5-4.0 Mg/m{sup 2}s and critical quality 0.23-0.9. The effect on CHF of the outer-to-inner surface heat flux ratio, wasmore » also examined. The prediction of CHF for bilaterally heated annuli was based on the droplet-diffusion model proposed by Kirillov and Smogalev. While their model refers only to CHF occurrence at the inner surface, we extended it to cases where CHF occurs at the outer surface, and simultaneously at both surfaces, thus covering all cases of CHF occurrence in bilaterally heated annuli. From the annuli CHF data of Becker and Letzter, we derived empirical functions required by the model. the proposed equations provide good accuracy for the CHF data used in this study. Moreover, the equations can predict conditions at which CHF occurs simultaneously at both surfaces. Also, this method can be used for cases with only one heated surface.« less

The Net Carbon Flux due to Deforestation and Forest Re-Growth in the Brazilian Amazon: Analysis using a Process-Based Model

NASA Technical Reports Server (NTRS)

Hirsch, A. I.; Little, W. S.; Houghton, R. A.; Scott, N. A.; White, J. D.

2004-01-01

We developed a process-based model of forest growth, carbon cycling, and land cover dynamics named CARLUC (for CARbon and Land Use Change) to estimate the size of terrestrial carbon pools in terra firme (non-flooded) forests across the Brazilian Legal Amazon and the net flux of carbon resulting from forest disturbance and forest recovery from disturbance. Our goal in building the model was to construct a relatively simple ecosystem model that would respond to soil and climatic heterogeneity that allows us to study of the impact of Amazonian deforestation, selective logging, and accidental fire on the global carbon cycle. This paper focuses on the net flux caused by deforestation and forest re-growth over the period from 1970-1998. We calculate that the net flux to the atmosphere during this period reached a maximum of approx. 0.35 PgC/yr (1PgC = 1 x 10(exp I5) gC) in 1990, with a cumulative release of approx. 7 PgC from 1970- 1998. The net flux is higher than predicted by an earlier study by a total of 1 PgC over the period 1989-1 998 mainly because CARLUC predicts relatively high mature forest carbon storage compared to the datasets used in the earlier study. Incorporating the dynamics of litter and soil carbon pools into the model increases the cumulative net flux by approx. 1 PgC from 1970-1998, while different assumptions about land cover dynamics only caused small changes. The uncertainty of the net flux, calculated with a Monte-Carlo approach, is roughly 35% of the mean value (1 SD).

Prediction of Experimental Surface Heat Flux of Thin Film Gauges using ANFIS

NASA Astrophysics Data System (ADS)

Sarma, Shrutidhara; Sahoo, Niranjan; Unal, Aynur

2018-05-01

Precise quantification of surface heat fluxes in highly transient environment is of paramount importance from the design point of view of several engineering equipment like thermal protection or cooling systems. Such environments are simulated in experimental facilities by exposing the surface with transient heat loads typically step/impulsive in nature. The surface heating rates are then determined from highly transient temperature history captured by efficient surface temperature sensors. The classical approach is to use thin film gauges (TFGs) in which temperature variations are acquired within milliseconds, thereby allowing calculation of surface heat flux, based on the theory of one-dimensional heat conduction on a semi-infinite body. With recent developments in the soft computing methods, the present study is an attempt for the application of intelligent system technique, called adaptive neuro fuzzy inference system (ANFIS) to recover surface heat fluxes from a given temperature history recorded by TFGs without having the need to solve lengthy analytical equations. Experiments have been carried out by applying known quantity of `impulse heat load' through laser beam on TFGs. The corresponding voltage signals have been acquired and surface heat fluxes are estimated through classical analytical approach. These signals are then used to `train' the ANFIS model, which later predicts output for `test' values. Results from both methods have been compared and these surface heat fluxes are used to predict the non-linear relationship between thermal and electrical properties of the gauges that are exceedingly pertinent to the design of efficient TFGs. Further, surface plots have been created to give an insight about dimensionality effect of the non-linear dependence of thermal/electrical parameters on each other. Later, it is observed that a properly optimized ANFIS model can predict the impulsive heat profiles with significant accuracy. This paper thus shows the appropriateness of soft computing technique as a practically constructive replacement for tedious analytical formulation and henceforth, effectively quantifies the modeling of TFGs.

A Continuous Measure of Gross Primary Production for the Conterminous U.S. Derived from MODIS and AmeriFlux Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Jingfeng; Zhuang, Qianlai; Law, Beverly E.

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide rangemore » of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km x 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr{sup -1} for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances.« less

High fidelity chemistry and radiation modeling for oxy -- combustion scenarios

NASA Astrophysics Data System (ADS)

Abdul Sater, Hassan A.

To account for the thermal and chemical effects associated with the high CO2 concentrations in an oxy-combustion atmosphere, several refined gas-phase chemistry and radiative property models have been formulated for laminar to highly turbulent systems. This thesis examines the accuracies of several chemistry and radiative property models employed in computational fluid dynamic (CFD) simulations of laminar to transitional oxy-methane diffusion flames by comparing their predictions against experimental data. Literature review about chemistry and radiation modeling in oxy-combustion atmospheres considered turbulent systems where the predictions are impacted by the interplay and accuracies of the turbulence, radiation and chemistry models. Thus, by considering a laminar system we minimize the impact of turbulence and the uncertainties associated with turbulence models. In the first section of this thesis, an assessment and validation of gray and non-gray formulations of a recently proposed weighted-sum-of-gray gas model in oxy-combustion scenarios was undertaken. Predictions of gas, wall temperatures and flame lengths were in good agreement with experimental measurements. The temperature and flame length predictions were not sensitive to the radiative property model employed. However, there were significant variations between the gray and non-gray model radiant fraction predictions with the variations in general increasing with decrease in Reynolds numbers possibly attributed to shorter flames and steeper temperature gradients. The results of this section confirm that non-gray model predictions of radiative heat fluxes are more accurate than gray model predictions especially at steeper temperature gradients. In the second section, the accuracies of three gas-phase chemistry models were assessed by comparing their predictions against experimental measurements of temperature, species concentrations and flame lengths. The chemistry was modeled employing the Eddy Dissipation Concept (EDC) employing a 41-step detailed chemistry mechanism, the non-adiabatic extension of the equilibrium Probability Density Function (PDF) based mixture-fraction model and a two-step global finite rate chemistry model with modified rate constants proposed to work well in oxy-methane flames. Based on the results from this section, the equilibrium PDF model in conjunction with a high-fidelity non-gray model for the radiative properties of the gas-phase may be deemed as accurate to capture the major gas species concentrations, temperatures and flame lengths in oxy-methane flames. The third section examines the variations in radiative transfer predictions due to the choice of chemistry and gas-phase radiative property models. The radiative properties were estimated employing four weighted-sum-of-gray-gases models (WSGGM) that were formulated employing different spectroscopic/model databases. An average variation of 14 -- 17% in the wall incident radiative fluxes was observed between the EDC and equilibrium mixture fraction chemistry models, due to differences in their temperature predictions within the flame. One-dimensional, line-of-sight radiation calculations showed a 15 -- 25 % reduction in the directional radiative fluxes at lower axial locations as a result of ignoring radiation from CO and CH4. Under the constraints of fixed temperature and species distributions, the flame radiant power estimates and average wall incident radiative fluxes varied by nearly 60% and 11% respectively among the different WSGG models.

Fuel consumption models for pine flatwoods fuel types in the southeastern United States

Treesearch

Clinton S. Wright

2013-01-01

Modeling fire effects, including terrestrial and atmospheric carbon fluxes and pollutant emissions during wildland fires, requires accurate predictions of fuel consumption. Empirical models were developed for predicting fuel consumption from fuel and environmental measurements on a series of operational prescribed fires in pine flatwoods ecosystems in the southeastern...

Numerical experiment on the flow field properties of a blunted body with a counterflowing jet in supersonic flows

NASA Astrophysics Data System (ADS)

Huang, Wei; Zhang, Rui-Rui; Yan, Li; Ou, Min; Moradi, R.

2018-06-01

The prediction of the drag and heat flux reduction characteristics is a very important issue in the conceptual design phase of the hypersonic vehicle. In this paper, the flow field properties around a blunted body with a counterflowing jet in the supersonic flow with the freestream Mach number being 3.98 were investigated numerically, and they are obtained by means of the two-dimensional axisymmetric Reynolds-averaged Navier-Stokes (RANS) equations coupled with the two equation standard k-ε turbulence model. The surface Stanton number distributions, as well as the surface static pressures, were extracted from the flow field structures in order to evaluate the drag and heat flux reduction characteristics. Further, the influences of the jet pressure ratio and the jet Mach number on the drag and heat flux reduction were analyzed based on the detailed code validation and grid independency analysis process. The obtained results show that the flow cell Reynolds number has a great impact on the heat flux prediction, and its best value is 5.0 for the case studied in the current study. However, the flow cell Reynolds number and the grid scale both have only a slight impact on the prediction of the surface static pressure distribution, as well as the turbulence model. The larger jet pressure ratio is beneficial for the drag and heat flux reduction, and the smaller jet Mach number is beneficial for the heat flux reduction. Further, the long penetration mode is beneficial for the drag reduction, but it is not beneficial for the heat flux reduction.

RANS modeling of scalar dispersion from localized sources within a simplified urban-area model

NASA Astrophysics Data System (ADS)

Rossi, Riccardo; Capra, Stefano; Iaccarino, Gianluca

2011-11-01

The dispersion of a passive scalar downstream a localized source within a simplified urban-like geometry is examined by means of RANS scalar flux models. The computations are conducted under conditions of neutral stability and for three different incoming wind directions (0°, 45°, 90°) at a roughness Reynolds number of Ret = 391. A Reynolds stress transport model is used to close the flow governing equations whereas both the standard eddy-diffusivity closure and algebraic flux models are employed to close the transport equation for the passive scalar. The comparison with a DNS database shows improved reliability from algebraic scalar flux models towards predicting both the mean concentration and the plume structure. Since algebraic flux models do not increase substantially the computational effort, the results indicate that the use of tensorial-diffusivity can be promising tool for dispersion simulations for the urban environment.

Improved Measurement of Reactor Flux and Spectrum at Daya Bay

NASA Astrophysics Data System (ADS)

Zhan, Liang; Daya Bay Collaboration

2017-09-01

A new measurement of the reactor antineutrino flux and energy spectrum by the Daya Bay experiment is reported. With a live time of 621 days, more than 1.2 million inverse beta decay (IBD) candidates were collected by eight antineutrino detectors (ADs) deployed in two near (560 m and 600 m flux-weighted baselines) and one far (16400 m flux-weighted baseline) underground experimental halls. The IBD yield was measured and the ratio to the predicted flux using the Huber+Mueller (ILL+Vogel) model was determined to be 0.946 ± 0.020 (0.992 ± 0.021). A 2.9 σ deviation was found in the measured IBD positron energy spectrum compared to the predictions. In particular, an excess of events in the region of 4-6 MeV was found with a local significance of 4.4 σ.

Evidence of chaotic pattern in solar flux through a reproducible sequence of period-doubling-type bifurcations

NASA Technical Reports Server (NTRS)

Ashrafi, S.; Roszman, L.

1991-01-01

A preliminary study of the limits to solar flux intensity prediction, and of whether the general lack of predictability in the solar flux arises from the nonlinear chaotic nature of the Sun's physical activity is presented. Statistical analysis of a chaotic signal can extract only its most gross features, and detailed physical models fail, since even the simplest equations of motion for a nonlinear system can exhibit chaotic behavior. A recent theory by Feigenbaum suggests that nonlinear systems that can be led into chaotic behavior through a sequence of period-doubling bifurcations will exhibit a universal behavior. As the control parameter is increased, the bifurcation points occur in such a way that a proper ratio of these will approach the universal Feigenbaum number. Experimental evidence supporting the applicability of the Feigenbaum scenario to solar flux data is sparse. However, given the hypothesis that the Sun's convection zones are similar to a Rayleigh-Bernard mechanism, we can learn a great deal from the remarkable agreement observed between the prediction by theory (period doubling - a universal route to chaos) and the amplitude decrease of the signal's regular subharmonics. It is shown that period-doubling-type bifurcation is a possible route to a chaotic pattern of solar flux that is distinguishable from the logarithm of its power spectral density. This conclusion is the first positive step toward a reformulation of solar flux by a nonlinear chaotic approach. The ultimate goal of this research is to be able to predict an estimate of the upper and lower bounds for solar flux within its predictable zones. Naturally, it is an important task to identify the time horizons beyond which predictability becomes incompatible with computability.

Evidence of chaotic pattern in solar flux through a reproducible sequence of period-doubling-type bifurcations

NASA Technical Reports Server (NTRS)

Ashrafi, S.; Roszman, L.

1991-01-01

Presented here is a preliminary study of the limits to solar flux intensity prediction, and of whether the general lack of predictability in the solar flux arises from the nonlinear chaotic nature of the Sun's physical activity. Statistical analysis of a chaotic signal can extract only its most gross features, and detailed physical models fail, since even the simplest equations of motion for a nonlinear system can exhibit chaotic behavior. A recent theory by Feigenbaum suggests that nonlinear systems that can be led into chaotic behavior through a sequence of period-doubling bifurcations will exhibit a universal behavior. As the control parameter is increased, the bifurcation points occur in such a way that a proper ratio of these will approach the universal Feigenbaum number. Experimental evidence supporting the applicability of the Feigenbaum scenario to solar flux data is sparse. However, given the hypothesis that the Sun's convection zones are similar to a Rayleigh-Bernard mechanism, we can learn a great deal from the remarkable agreement observed between the prediction by theory (period doubling - a universal route to chaos) and the amplitude decrease of the signal's regular subharmonics. The authors show that period-doubling-type bifurcation is a possible route to a chaotic pattern of solar flux that is distinguishable from the logarithm of its power spectral density. This conclusion is the first positive step toward a reformulation of solar flux by a nonlinear chaotic approach. The ultimate goal of this research is to be able to predict an estimate of the upper and lower bounds for solar flux within its predictable zones. Naturally, it is an important task to identify the time horizons beyond which predictability becomes incompatible with computability.

Modelling carbon and water fluxes at global scale

NASA Astrophysics Data System (ADS)

Balzarolo, M.; Balsamo, G.; Barbu, A.; Boussetta, S.; Calvet, J.-C.; Chevallier, F.; de Vries, J.; Kullmann, L.; Lafont, S.; Maignan, F.; Papale, D.; Poulter, B.

2012-04-01

Modelling and predicting seasonal and inter-annual variability of terrestrial carbon and water fluxes play an important role in understanding processes and interactions between plant-atmosphere and climate. Testing the model's capability to simulate fluxes across and within the ecosystems against eddy covariance data is essential. Thanks to the existing eddy covariance (EC) networks (e.g FLUXNET), where CO2 and water exchanges are continuously measured, it is now possible to verify the model's goodness at global scale. This paper reports the outcomes of the verification activities of the Land Carbon Core Information Service (LC-CIS) of the Geoland2 European project. The three used land surface models are C-TESSEL from ECMWF, SURFEX from CNRM and ORCHIDEE from IPSL. These models differ in their hypotheses used to describe processes and the interactions between ecological compartments (plant, soil and atmosphere) and climate and environmental conditions. Results of the verification and model benchmarking are here presented. Surface fluxes of the models are verified against FLUXNET sites representing main worldwide Plant Functional Types (PFTs: forest, grassland and cropland). The quality and accuracy of the EC data is verified using the CarboEurope database methodology. Modelled carbon and water fluxes magnitude, daily and annual cycles, inter-annual anomalies are verified against eddy covariance data using robust statistical analysis (r, RMSE, E, BE). We also verify the performance of the models in predicting the functional responses of Gross Primary Production (GPP) and RE (Ecosystem Respiration) to the environmental driving variables (i.e. temperature, soil water content and radiation) by comparing the functional relationships obtained from the outputs and observed data. Obtained results suggest some ways of improving such models for global carbon modelling.

Modeling coupled interactions of carbon, water, and ozone exchange between terrestrial ecosystems and the atmosphere. I: model description.

PubMed

Nikolov, Ned; Zeller, Karl F

2003-01-01

A new biophysical model (FORFLUX) is presented to study the simultaneous exchange of ozone, carbon dioxide, and water vapor between terrestrial ecosystems and the atmosphere. The model mechanistically couples all major processes controlling ecosystem flows trace gases and water implementing recent concepts in plant eco-physiology, micrometeorology, and soil hydrology. FORFLUX consists of four interconnected modules-a leaf photosynthesis model, a canopy flux model, a soil heat-, water- and CO2- transport model, and a snow pack model. Photosynthesis, water-vapor flux and ozone uptake at the leaf level are computed by the LEAFC3 sub-model. The canopy module scales leaf responses to a stand level by numerical integration of the LEAFC3model over canopy leaf area index (LAI). The integration takes into account (1) radiative transfer inside the canopy, (2) variation of foliage photosynthetic capacity with canopy depth, (3) wind speed attenuation throughout the canopy, and (4) rainfall interception by foliage elements. The soil module uses principles of the diffusion theory to predict temperature and moisture dynamics within the soil column, evaporation, and CO2 efflux from soil. The effect of soil heterogeneity on field-scale fluxes is simulated employing the Bresler-Dagan stochastic concept. The accumulation and melt of snow on the ground is predicted using an explicit energy balance approach. Ozone deposition is modeled as a sum of three fluxes- ozone uptake via plant stomata, deposition to non-transpiring plant surfaces, and ozone flux into the ground. All biophysical interactions are computed hourly while model projections are made at either hourly or daily time step. FORFLUX represents a comprehensive approach to studying ozone deposition and its link to carbon and water cycles in terrestrial ecosystems.

Forward Modeling of Coronal Mass Ejection Flux Ropes in the Inner Heliosphere with 3DCORE

PubMed Central

Amerstorfer, T.; Palmerio, E.; Isavnin, A.; Farrugia, C. J.; Lowder, C.; Winslow, R. M.; Donnerer, J. M.; Kilpua, E. K. J.; Boakes, P. D.

2018-01-01

Abstract Forecasting the geomagnetic effects of solar storms, known as coronal mass ejections (CMEs), is currently severely limited by our inability to predict the magnetic field configuration in the CME magnetic core and by observational effects of a single spacecraft trajectory through its 3‐D structure. CME magnetic flux ropes can lead to continuous forcing of the energy input to the Earth's magnetosphere by strong and steady southward‐pointing magnetic fields. Here we demonstrate in a proof‐of‐concept way a new approach to predict the southward field B z in a CME flux rope. It combines a novel semiempirical model of CME flux rope magnetic fields (Three‐Dimensional Coronal ROpe Ejection) with solar observations and in situ magnetic field data from along the Sun‐Earth line. These are provided here by the MESSENGER spacecraft for a CME event on 9–13 July 2013. Three‐Dimensional Coronal ROpe Ejection is the first such model that contains the interplanetary propagation and evolution of a 3‐D flux rope magnetic field, the observation by a synthetic spacecraft, and the prediction of an index of geomagnetic activity. A counterclockwise rotation of the left‐handed erupting CME flux rope in the corona of 30° and a deflection angle of 20° is evident from comparison of solar and coronal observations. The calculated Dst matches reasonably the observed Dst minimum and its time evolution, but the results are highly sensitive to the CME axis orientation. We discuss assumptions and limitations of the method prototype and its potential for real time space weather forecasting and heliospheric data interpretation. PMID:29780287

Annual net community production and the biological carbon flux in the ocean

NASA Astrophysics Data System (ADS)

Emerson, Steven

2014-01-01

The flux of biologically produced organic matter from the surface ocean (the biological pump), over an annual cycle, is equal to the annual net community production (ANCP). Experimental determinations of ANCP at ocean time series sites using a variety of different metabolite mass balances have made it possible to evaluate the accuracy of sediment trap fluxes and satellite-determined ocean carbon export. ANCP values at the Hawaii Ocean Time-series (HOT), the Bermuda Atlantic Time-series Study (BATS), Ocean Station Papa (OSP) are 3 ± 1 mol C m-2 yr-1—much less variable than presently suggested by satellite remote sensing measurements and global circulation models. ANCP determined from mass balances at these locations are 3-4 times particulate organic carbon fluxes measured in sediment traps. When the roles of dissolved organic carbon (DOC) flux, zooplankton migration, and depth-dependent respiration are considered these differences are reconciled at HOT and OSP but not at BATS, where measured particulate fluxes are about 3 times lower than expected. Even in the cases where sediment trap fluxes are accurate, it is not possible to "scale up" these measurements to determine ANCP without independent determinations of geographically variable DOC flux and zooplankton migration. Estimates of ANCP from satellite remote sensing using net primary production determined by the carbon-based productivity model suggests less geographic variability than its predecessor (the vertically generalized productivity model) and brings predictions at HOT and OSP closer to measurements; however, satellite-predicted ANCP at BATS is still 3 times too low.

Predicting Biological Information Flow in a Model Oxygen Minimum Zone

NASA Astrophysics Data System (ADS)

Louca, S.; Hawley, A. K.; Katsev, S.; Beltran, M. T.; Bhatia, M. P.; Michiels, C.; Capelle, D.; Lavik, G.; Doebeli, M.; Crowe, S.; Hallam, S. J.

2016-02-01

Microbial activity drives marine biochemical fluxes and nutrient cycling at global scales. Geochemical measurements as well as molecular techniques such as metagenomics, metatranscriptomics and metaproteomics provide great insight into microbial activity. However, an integration of molecular and geochemical data into mechanistic biogeochemical models is still lacking. Recent work suggests that microbial metabolic pathways are, at the ecosystem level, strongly shaped by stoichiometric and energetic constraints. Hence, models rooted in fluxes of matter and energy may yield a holistic understanding of biogeochemistry. Furthermore, such pathway-centric models would allow a direct consolidation with meta'omic data. Here we present a pathway-centric biogeochemical model for the seasonal oxygen minimum zone in Saanich Inlet, a fjord off the coast of Vancouver Island. The model considers key dissimilatory nitrogen and sulfur fluxes, as well as the population dynamics of the genes that mediate them. By assuming a direct translation of biocatalyzed energy fluxes to biosynthesis rates, we make predictions about the distribution and activity of the corresponding genes. A comparison of the model to molecular measurements indicates that the model explains observed DNA, RNA, protein and cell depth profiles. This suggests that microbial activity in marine ecosystems such as oxygen minimum zones is well described by DNA abundance, which, in conjunction with geochemical constraints, determines pathway expression and process rates. Our work further demonstrates how meta'omic data can be mechanistically linked to environmental redox conditions and biogeochemical processes.

Measurement of the Reactor Antineutrino Flux and Spectrum at Daya Bay

NASA Astrophysics Data System (ADS)

An, F. P.; Balantekin, A. B.; Band, H. R.; Bishai, M.; Blyth, S.; Butorov, I.; Cao, D.; Cao, G. F.; Cao, J.; Cen, W. R.; Chan, Y. L.; Chang, J. F.; Chang, L. C.; Chang, Y.; Chen, H. S.; Chen, Q. Y.; Chen, S. M.; Chen, Y. X.; Chen, Y.; Cheng, J. H.; Cheng, J.; Cheng, Y. P.; Cherwinka, J. J.; Chu, M. C.; Cummings, J. P.; de Arcos, J.; Deng, Z. Y.; Ding, X. F.; Ding, Y. Y.; Diwan, M. V.; Dove, J.; Draeger, E.; Dwyer, D. A.; Edwards, W. R.; Ely, S. R.; Gill, R.; Gonchar, M.; Gong, G. H.; Gong, H.; Grassi, M.; Gu, W. Q.; Guan, M. Y.; Guo, L.; Guo, X. H.; Hackenburg, R. W.; Han, R.; Hans, S.; He, M.; Heeger, K. M.; Heng, Y. K.; Higuera, A.; Hor, Y. K.; Hsiung, Y. B.; Hu, B. Z.; Hu, L. M.; Hu, L. J.; Hu, T.; Hu, W.; Huang, E. C.; Huang, H. X.; Huang, X. T.; Huber, P.; Hussain, G.; Jaffe, D. E.; Jaffke, P.; Jen, K. L.; Jetter, S.; Ji, X. P.; Ji, X. L.; Jiao, J. B.; Johnson, R. A.; Kang, L.; Kettell, S. H.; Kohn, S.; Kramer, M.; Kwan, K. K.; Kwok, M. W.; Kwok, T.; Langford, T. J.; Lau, K.; Lebanowski, L.; Lee, J.; Lei, R. T.; Leitner, R.; Leung, K. Y.; Leung, J. K. C.; Lewis, C. A.; Li, D. J.; Li, F.; Li, G. S.; Li, Q. J.; Li, S. C.; Li, W. D.; Li, X. N.; Li, X. Q.; Li, Y. F.; Li, Z. B.; Liang, H.; Lin, C. J.; Lin, G. L.; Lin, P. Y.; Lin, S. K.; Ling, J. J.; Link, J. M.; Littenberg, L.; Littlejohn, B. R.; Liu, D. W.; Liu, H.; Liu, J. L.; Liu, J. C.; Liu, S. S.; Lu, C.; Lu, H. Q.; Lu, J. S.; Luk, K. B.; Ma, Q. M.; Ma, X. Y.; Ma, X. B.; Ma, Y. Q.; Martinez Caicedo, D. A.; McDonald, K. T.; McKeown, R. D.; Meng, Y.; Mitchell, I.; Monari Kebwaro, J.; Nakajima, Y.; Napolitano, J.; Naumov, D.; Naumova, E.; Ngai, H. Y.; Ning, Z.; Ochoa-Ricoux, J. P.; Olshevski, A.; Pan, H.-R.; Park, J.; Patton, S.; Pec, V.; Peng, J. C.; Piilonen, L. E.; Pinsky, L.; Pun, C. S. J.; Qi, F. Z.; Qi, M.; Qian, X.; Raper, N.; Ren, B.; Ren, J.; Rosero, R.; Roskovec, B.; Ruan, X. C.; Shao, B. B.; Steiner, H.; Sun, G. X.; Sun, J. L.; Tang, W.; Taychenachev, D.; Tsang, K. V.; Tull, C. E.; Tung, Y. C.; Viaux, N.; Viren, B.; Vorobel, V.; Wang, C. H.; Wang, M.; Wang, N. Y.; Wang, R. G.; Wang, W.; Wang, W. W.; Wang, X.; Wang, Y. F.; Wang, Z.; Wang, Z.; Wang, Z. M.; Wei, H. Y.; Wen, L. J.; Whisnant, K.; White, C. G.; Whitehead, L.; Wise, T.; Wong, H. L. H.; Wong, S. C. F.; Worcester, E.; Wu, Q.; Xia, D. M.; Xia, J. K.; Xia, X.; Xing, Z. Z.; Xu, J. Y.; Xu, J. L.; Xu, J.; Xu, Y.; Xue, T.; Yan, J.; Yang, C. G.; Yang, L.; Yang, M. S.; Yang, M. T.; Ye, M.; Yeh, M.; Young, B. L.; Yu, G. Y.; Yu, Z. Y.; Zang, S. L.; Zhan, L.; Zhang, C.; Zhang, H. H.; Zhang, J. W.; Zhang, Q. M.; Zhang, Y. M.; Zhang, Y. X.; Zhang, Y. M.; Zhang, Z. J.; Zhang, Z. Y.; Zhang, Z. P.; Zhao, J.; Zhao, Q. W.; Zhao, Y. F.; Zhao, Y. B.; Zheng, L.; Zhong, W. L.; Zhou, L.; Zhou, N.; Zhuang, H. L.; Zou, J. H.; Daya Bay Collaboration

2016-02-01

This Letter reports a measurement of the flux and energy spectrum of electron antineutrinos from six 2.9 GWt h nuclear reactors with six detectors deployed in two near (effective baselines 512 and 561 m) and one far (1579 m) underground experimental halls in the Daya Bay experiment. Using 217 days of data, 296 721 and 41 589 inverse β decay (IBD) candidates were detected in the near and far halls, respectively. The measured IBD yield is (1.55 ±0.04 ) ×10-18 cm2 GW-1 day-1 or (5.92 ±0.14 ) ×10-43 cm2 fission-1 . This flux measurement is consistent with previous short-baseline reactor antineutrino experiments and is 0.946 ±0.022 (0.991 ±0.023 ) relative to the flux predicted with the Huber -Mueller (ILL -Vogel ) fissile antineutrino model. The measured IBD positron energy spectrum deviates from both spectral predictions by more than 2 σ over the full energy range with a local significance of up to ˜4 σ between 4-6 MeV. A reactor antineutrino spectrum of IBD reactions is extracted from the measured positron energy spectrum for model-independent predictions.

Comparison of free flux flow in two single crystals of V3Si with slightly different pinning strengths

NASA Astrophysics Data System (ADS)

Gafarov, Ozarfar; Gapud, Albert A.; Moraes, Sunhee; Thompson, James R.; Christen, David K.; Reyes, Arneil P.

2011-03-01

Results of recent measurements on two very clean, single-crystal samples of the A15 superconductor V3 Si are presented. Magnetization and transport data confirm the ``clean'' quality of both samples, as manifested by: (i) high residual resistivity ratio, (ii) low critical current densities, and (iii) a ``peak'' effect in the field dependence of critical current. The (H,T) phase line for this peak effect is shifted in the slightly ``dirtier'' sample, which also has higher critical current density Jc (H). High-current Lorentz forces are applied on mixed-state vortices in order to induce the highly ordered free flux flow (FFF) phase, using the same methods as in previous work. A traditional model by Bardeen and Stephen (BS) predicts a simple field dependence of flux flow resistivity ρf (H), presuming a field-independent flux core size. A model by Kogan and Zelezhina (KZ) takes core size into account, and predicts a deviation from BS. In this study, ρf (H) is confirmed to be consistent with predictions of KZ, as will be discussed. Funded by Research Corporation and the National Science Foundation.

Measurement of the reactor antineutrino flux and spectrum at Daya Bay

DOE PAGES

D. E. Jaffe; Bishai, M; Diwan, M.; ...

2016-02-12

This Letter reports a measurement of the flux and energy spectrum of electron antineutrinos from six 2.9~GW th nuclear reactors with six detectors deployed in two near (effective baselines 512~m and 561~m) and one far (1,579 m) underground experimental halls in the Daya Bay experiment. Using 217 days of data, 296,721 and 41,589 inverse beta decay (IBD) candidates were detected in the near and far halls, respectively. The measured IBD yield is (1.55 ± 0.04) × 10 –18 cm 2/GW/day or (5.92 ± 0.14) × 10 –43 cm 2/fission. This flux measurement is consistent with previous short-baseline reactor antineutrino experimentsmore » and is 0.946 ± 0.022 (0.991 ± 0.023) relative to the flux predicted with the Huber+Mueller (ILL+Vogel) fissile antineutrino model. The measured IBD positron energy spectrum deviates from both spectral predictions by more than 2σ over the full energy range with a local significance of up to ~4σ between 4-6 MeV. Furthermore, a reactor antineutrino spectrum of IBD reactions is extracted from the measured positron energy spectrum for model-independent predictions.« less

Free flux flow in two single crystals of V3Si with differing pinning strengths

NASA Astrophysics Data System (ADS)

Gafarov, O.; Gapud, A. A.; Moraes, S.; Thompson, J. R.; Christen, D. K.; Reyes, A. P.

2011-10-01

Results of measurements on two very clean, single-crystal samples of the A15 superconductor V3Si are presented. Magnetization and transport data have confirmed the ``clean'' quality of both samples, as manifested by: (i) high residual electrical resistivity ratio, (ii) very low critical current densities Jc, and (iii) a ``peak'' effect in the field dependence of critical current. The (H,T) phase line for this peak effect is shifted down for the slightly ``dirtier'' sample, which consequently also has higher critical current density Jc(H). Large Lorentz forces are applied on mixed-state vortices via large currents, in order to induce the highly ordered free flux flow (FFF) phase, using experimental methods developed previously. The traditional model by Bardeen and Stephen (BS) predicts a simple field dependence of flux flow resistivity ρf(H) ˜ H/Hc2, presuming a field-independent flux core size. A model by Kogan and Zelezhina (KZ) takes into account the effects of magnetic field on core size, and predict a clear deviation from the linear BS dependence. In this study, ρf(H) is confirmed to be consistent with predictions of KZ.

Predicting the Geothermal Heat Flux in Greenland: A Machine Learning Approach

NASA Astrophysics Data System (ADS)

Rezvanbehbahani, Soroush; Stearns, Leigh A.; Kadivar, Amir; Walker, J. Doug; van der Veen, C. J.

2017-12-01

Geothermal heat flux (GHF) is a crucial boundary condition for making accurate predictions of ice sheet mass loss, yet it is poorly known in Greenland due to inaccessibility of the bedrock. Here we use a machine learning algorithm on a large collection of relevant geologic features and global GHF measurements and produce a GHF map of Greenland that we argue is within ˜15% accuracy. The main features of our predicted GHF map include a large region with high GHF in central-north Greenland surrounding the NorthGRIP ice core site, and hot spots in the Jakobshavn Isbræ catchment, upstream of Petermann Gletscher, and near the terminus of Nioghalvfjerdsfjorden glacier. Our model also captures the trajectory of Greenland movement over the Icelandic plume by predicting a stripe of elevated GHF in central-east Greenland. Finally, we show that our model can produce substantially more accurate predictions if additional measurements of GHF in Greenland are provided.

Boric acid permeation in forward osmosis membrane processes: modeling, experiments, and implications.

PubMed

Jin, Xue; Tang, Chuyang Y; Gu, Yangshuo; She, Qianhong; Qi, Saren

2011-03-15

Forward osmosis (FO) is attracting increasing interest for its potential applications in desalination. In FO, permeation of contaminants from feed solution into draw solution through the semipermeable membrane can take place simultaneously with water diffusion. Understanding the contaminants transport through and rejection by FO membrane has significant technical implications in the way to separate clean water from the diluted draw solution. In this study, a model was developed to predict boron flux in FO operation. A strong agreement between modeling results and experimental data indicates that the model developed in this study can accurately predict the boron transport through FO membranes. Furthermore, the model can guide the fabrication of improved FO membranes with decreased boron permeability and structural parameter to minimize boron flux. Both theoretical model and experimental results demonstrated that when membrane active layer was facing draw solution, boron flux was substantially greater compared to the other membrane orientation due to more severe internal concentration polarization. In this investigation, for the first time, rejection of contaminants was defined in FO processes. This is critical to compare the membrane performance between different membranes and experimental conditions.

On the nature of the cosmic ray positron spectrum

NASA Technical Reports Server (NTRS)

Protheroe, R. J.

1981-01-01

A calculation was made of the flux of secondary positrons above 100 MeV expected for various propagation models. The models investigated were the leaky box or homogeneous model, a disk halo diffusion model, a dynamical halo model, and the closed galaxy model. In each case the parameters of these models were adjusted for agreement with the observed secondary or primary ratios and Be 10 abundance. The positron flux predicted for these models was compared with the available data. The possibility of a primary positron component was considered.

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling

PubMed Central

2011-01-01

Background A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades. Results Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas. Conclusions Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape. PMID:21835025

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling.

PubMed

Potter, Christopher; Klooster, Steven; Crabtree, Robert; Huang, Shengli; Gross, Peggy; Genovese, Vanessa

2011-08-11

A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades. Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas. Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape.

Modeling Studies of the Effects of Winds and Heat Flux on the Tropical Oceans

NASA Technical Reports Server (NTRS)

Seager, R.

1999-01-01

Over a decade ago, funding from this NASA grant supported the development of the Cane-Zebiak ENSO prediction model which remains in use to this day. It also supported our work developing schemes for modeling the air-sea heat flux in ocean models used for studying climate variability. We introduced a succession of simple boundary layer models that allow the fluxes to be computed internally in the model and avoid the need to specify the atmospheric thermodynamic state. These models have now reached a level of generality that allows modeling of the global, rather than just tropical, ocean, including sea ice cover. The most recent versions of these boundary layer models have been widely distributed around the world and are in use by many ocean modeling groups.

Erosion and re-deposition of lithium and boron coatings under high-flux plasma bombardment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abrams, Tyler Wayne

2015-01-01

Lithium and boron coatings are applied to the walls of many tokamaks to enhance performance and protect the underlying substrates. Li and B-coated high-Z substrates are planned for use in NSTX-U and are a candidate plasma-facing component (PFC) for DEMO. However, previous measurements of Li evaporation and thermal sputtering on low-flux devices indicate that the Li temperature permitted on such devices may be unacceptably low. Thus it is crucial to characterize gross and net Li erosion rates under high-flux plasma bombardment. Additionally, no quantitative measurements have been performed of the erosion rate of a boron-coated PFC during plasma bombardment. Amore » realistic model for the compositional evolution of a Li layer under D bombardment was developed that incorporates adsorption, implantation, and diffusion. A model was developed for temperature-dependent mixed-material Li-D erosion that includes evaporation, physical sputtering, chemical sputtering, preferential sputtering, and thermal sputtering. The re-deposition fraction of a Li coating intersecting a linear plasma column was predicted using atomic physics information and by solving the Li continuity equation. These models were tested in the Magnum-PSI linear plasma device at ion fluxes of 10^23-10^24 m^-2 s^-1 and Li surface temperatures less than 800 degrees C. Li erosion was measured during bombardment with a neon plasma that will not chemically react with Li and the results agreed well with the erosion model. Next the ratio of the total D fluence to the areal density of the Li coating was varied to quantify differences in Li erosion under D plasma bombardment as a function of the D concentration. The ratio of D/Li atoms was calculated using the results of MD simulations and good agreement is observed between measurements and the predictions of the mixed-material erosion model. Li coatings are observed to disappear from graphite much faster than from TZM Mo, indicating that fast Li diffusion into the bulk graphite substrate occurred, as predicted. Li re-deposition fractions very close to unity are observed in Magnum-PSI, as predicted by modeling. Finally, predictions of Li coating lifetimes in the NSTX-U divertor are calculated. The gross erosion rate of boron coatings was also measured for the first time in a high-flux plasma device.« less

Predicting the Magnetic Properties of ICMEs: A Pragmatic View

NASA Astrophysics Data System (ADS)

Riley, P.; Linker, J.; Ben-Nun, M.; Torok, T.; Ulrich, R. K.; Russell, C. T.; Lai, H.; de Koning, C. A.; Pizzo, V. J.; Liu, Y.; Hoeksema, J. T.

2017-12-01

The southward component of the interplanetary magnetic field plays a crucial role in being able to successfully predict space weather phenomena. Yet, thus far, it has proven extremely difficult to forecast with any degree of accuracy. In this presentation, we describe an empirically-based modeling framework for estimating Bz values during the passage of interplanetary coronal mass ejections (ICMEs). The model includes: (1) an empirically-based estimate of the magnetic properties of the flux rope in the low corona (including helicity and field strength); (2) an empirically-based estimate of the dynamic properties of the flux rope in the high corona (including direction, speed, and mass); and (3) a physics-based estimate of the evolution of the flux rope during its passage to 1 AU driven by the output from (1) and (2). We compare model output with observations for a selection of events to estimate the accuracy of this approach. Importantly, we pay specific attention to the uncertainties introduced by the components within the framework, separating intrinsic limitations from those that can be improved upon, either by better observations or more sophisticated modeling. Our analysis suggests that current observations/modeling are insufficient for this empirically-based framework to provide reliable and actionable prediction of the magnetic properties of ICMEs. We suggest several paths that may lead to better forecasts.

Modeling Water Flux at the Base of the Rooting Zone for Soils with Varying Glacial Parent Materials

NASA Astrophysics Data System (ADS)

Naylor, S.; Ellett, K. M.; Ficklin, D. L.; Olyphant, G. A.

2013-12-01

Soils of varying glacial parent materials in the Great Lakes Region (USA) are characterized by thin unsaturated zones and widespread use of agricultural pesticides and nutrients that affect shallow groundwater. To better our understanding of the fate and transport of contaminants, improved models of water fluxes through the vadose zones of various hydrogeologic settings are warranted. Furthermore, calibrated unsaturated zone models can be coupled with watershed models, providing a means for predicting the impact of varying climate scenarios on agriculture in the region. To address these issues, a network of monitoring sites was developed in Indiana that provides continuous measurements of precipitation, potential evapotranspiration (PET), soil volumetric water content (VWC), and soil matric potential to parameterize and calibrate models. Flux at the base of the root zone is simulated using two models of varying complexity: 1) the HYDRUS model, which numerically solves the Richards equation, and 2) the soil-water-balance (SWB) model, which assumes vertical flow under a unit gradient with infiltration and evapotranspiration treated as separate, sequential processes. Soil hydraulic parameters are determined based on laboratory data, a pedo-transfer function (ROSETTA), field measurements (Guelph permeameter), and parameter optimization. Groundwater elevation data are available at three of six sites to establish the base of the unsaturated zone model domain. Initial modeling focused on the groundwater recharge season (Nov-Feb) when PET is limited and much of the annual vertical flux occurs. HYDRUS results indicate that base of root zone fluxes at a site underlain by glacial ice-contact parent materials are 48% of recharge season precipitation (VWC RMSE=8.2%), while SWB results indicate that fluxes are 43% (VWC RMSE=3.7%). Due in part to variations in surface boundary conditions, more variable fluxes were obtained for a site underlain by alluvium with the SWB model (68% of recharge season precipitation, VWC RMSE=7.0%) predicting much greater drainage than HYDRUS (38% of recharge season precipitation, VWC RMSE=6.6%). Results also show that when calculating drainage flux over the recharge period, HYDRUS is highly sensitive to model initialization using observed water content from in-situ instrumentation. Simulated recharge season drainage flux is as much as 3.5 times higher when a one-month spin-up period was performed in the HYDRUS model for the same site. SWB results are less sensitive to water content initialization, but drainage flux is 1.6 times higher at one site using the same spin-up analysis. The long-term goals of this effort are to leverage the robust calibration data set to establish optimal approaches for determining hydraulic parameters such that water fluxes in the lower vadose zone can be modeled for a wider range of geomorphic settings where calibration data are unavailable.

Predicted and observed directional dependence of meteoroid/debris impacts on LDEF thermal blankets

NASA Technical Reports Server (NTRS)

Drolshagen, Gerhard

1993-01-01

The number of impacts from meteoroids and space debris particles to the various LDEF rows is calculated using ESABASE/DEBRIS, a 3-D numerical analysis tool. It is based on recent reference environment flux models and includes geometrical and directional effects. A comparison of model predictions and actual observations is made for penetrations of the thermal blankets which covered the UHCR experiment. The thermal blankets were located on all LDEF rows, except 3, 9, and 12. Because of their uniform composition and thickness, these blankets allow a direct analysis of the directional dependence of impacts and provide a test case for the latest meteoroid and debris flux models.

Oxygen Pickup Ions Measured by MAVEN Outside the Martian Bow Shock

NASA Astrophysics Data System (ADS)

Rahmati, A.; Cravens, T.; Larson, D. E.; Lillis, R. J.; Dunn, P.; Halekas, J. S.; Connerney, J. E. P.; Eparvier, F. G.; Thiemann, E.; Mitchell, D. L.; Jakosky, B. M.

2015-12-01

The MAVEN (Mars Atmosphere and Volatile EvolutioN) spacecraft entered orbit around Mars on September 21, 2014 and has since been detecting energetic oxygen pickup ions by its SEP (Solar Energetic Particles) and SWIA (Solar Wind Ion Analyzer) instruments. The oxygen pickup ions detected outside the Martian bowshock and in the upstream solar wind are associated with the extended hot oxygen exosphere of Mars, which is created mainly by the dissociative recombination of molecular oxygen ions with electrons in the ionosphere. We use analytic solutions to the equations of motion of pickup ions moving in the undisturbed upstream solar wind magnetic and motional electric fields and calculate the flux of oxygen pickup ions at the location of MAVEN. Our model calculates the ionization rate of oxygen atoms in the exosphere based on the hot oxygen densities predicted by Rahmati et al. (2014), and the sources of ionization include photo-ionization, charge exchange, and electron impact ionization. The photo-ionization frequency is calculated using the FISM (Flare Irradiance Spectral Model) solar flux model, based on MAVEN EUVM (Extreme Ultra-Violet Monitor) measurements. The frequency of charge exchange between a solar wind proton and an oxygen atom is calculated using MAVEN SWIA solar wind proton flux measurements, and the electron impact ionization frequency is calculated based on MAVEN SWEA (Solar Wind Electron Analyzer) solar wind electron flux measurements. The solar wind magnetic field used in the model is from the measurements taken by MAVEN MAG (magnetometer) in the upstream solar wind. The good agreement between our predicted pickup oxygen fluxes and the MAVEN SEP and SWIA measured ones confirms detection of oxygen pickup ions and these model-data comparisons can be used to constrain models of hot oxygen densities and photochemical escape flux.

Evapotranspiration and canopy resistance at an undeveloped prairie in a humid subtropical climate

USGS Publications Warehouse

Bidlake, W.R.

2002-01-01

Reliable estimates of evapotranspiration from areas of wildland vegetation are needed for many types of water-resource investigations. However, little is known about surface fluxes from many areally important vegetation types, and relatively few comparisons have been made to examine how well evapotranspiration models can predict evapotranspiration for soil-, climate-, or vegetation-types that differ from those under which the models have been calibrated. In this investigation at a prairie site in west-central Florida, latent heat flux (??E) computed from the energy balance and alternatively by eddy covariance during a 15-month period differed by 4 percent and 7 percent on hourly and daily time scales, respectively. Annual evapotranspiration computed from the energy balance and by eddy covariance were 978 and 944 mm, respectively. An hourly Penman-Monteith (PM) evapotranspiration model with stomatal control predicated on water-vapor-pressure deficit at canopy level, incoming solar radiation intensity, and soil water deficit was developed and calibrated using surface fluxes from eddy covariance. Model-predicted ??E agreed closely with ??E computed from the energy balance except when moisture from dew or precipitation covered vegetation surfaces. Finally, an hourly PM model developed for an Amazonian pasture predicted ??E for the Florida prairie with unexpected reliability. Additional comparisons of PM-type models that have been developed for differing types of short vegetation could aid in assessing interchangeability of such models.

Hot air impingement on a flat plate using Large Eddy Simulation (LES) technique

NASA Astrophysics Data System (ADS)

Plengsa-ard, C.; Kaewbumrung, M.

2018-01-01

Impinging hot gas jets to a flat plate generate very high heat transfer coefficients in the impingement zone. The magnitude of heat transfer prediction near the stagnation point is important and accurate heat flux distribution are needed. This research studies on heat transfer and flow field resulting from a single hot air impinging wall. The simulation is carried out using computational fluid dynamics (CFD) commercial code FLUENT. Large Eddy Simulation (LES) approach with a subgrid-scale Smagorinsky-Lilly model is present. The classical Werner-Wengle wall model is used to compute the predicted results of velocity and temperature near walls. The Smagorinsky constant in the turbulence model is set to 0.1 and is kept constant throughout the investigation. The hot gas jet impingement on the flat plate with a constant surface temperature is chosen to validate the predicted heat flux results with experimental data. The jet Reynolds number is equal to 20,000 and a fixed jet-to-plate spacing of H/D = 2.0. Nusselt number on the impingement surface is calculated. As predicted by the wall model, the instantaneous computed Nusselt number agree fairly well with experimental data. The largest values of calculated Nusselt number are near the stagnation point and decrease monotonically in the wall jet region. Also, the contour plots of instantaneous values of wall heat flux on a flat plate are captured by LES simulation.

The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes

NASA Astrophysics Data System (ADS)

Masson, V.; Le Moigne, P.; Martin, E.; Faroux, S.; Alias, A.; Alkama, R.; Belamari, S.; Barbu, A.; Boone, A.; Bouyssel, F.; Brousseau, P.; Brun, E.; Calvet, J.-C.; Carrer, D.; Decharme, B.; Delire, C.; Donier, S.; Essaouini, K.; Gibelin, A.-L.; Giordani, H.; Habets, F.; Jidane, M.; Kerdraon, G.; Kourzeneva, E.; Lafaysse, M.; Lafont, S.; Lebeaupin Brossier, C.; Lemonsu, A.; Mahfouf, J.-F.; Marguinaud, P.; Mokhtari, M.; Morin, S.; Pigeon, G.; Salgado, R.; Seity, Y.; Taillefer, F.; Tanguy, G.; Tulet, P.; Vincendon, B.; Vionnet, V.; Voldoire, A.

2013-07-01

SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D runs) or in coupled mode (from mesoscale models to numerical weather prediction and climate models). An assimilation mode is included for numerical weather prediction and monitoring. In addition to momentum, heat and water fluxes, SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. The main principles of the organisation of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally, the main applications of the code are summarised. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage.

Foraging theory predicts predator-prey energy fluxes.

PubMed

Brose, U; Ehnes, R B; Rall, B C; Vucic-Pestic, O; Berlow, E L; Scheu, S

2008-09-01

1. In natural communities, populations are linked by feeding interactions that make up complex food webs. The stability of these complex networks is critically dependent on the distribution of energy fluxes across these feeding links. 2. In laboratory experiments with predatory beetles and spiders, we studied the allometric scaling (body-mass dependence) of metabolism and per capita consumption at the level of predator individuals and per link energy fluxes at the level of feeding links. 3. Despite clear power-law scaling of the metabolic and per capita consumption rates with predator body mass, the per link predation rates on individual prey followed hump-shaped relationships with the predator-prey body mass ratios. These results contrast with the current metabolic paradigm, and find better support in foraging theory. 4. This suggests that per link energy fluxes from prey populations to predator individuals peak at intermediate body mass ratios, and total energy fluxes from prey to predator populations decrease monotonically with predator and prey mass. Surprisingly, contrary to predictions of metabolic models, this suggests that for any prey species, the per link and total energy fluxes to its largest predators are smaller than those to predators of intermediate body size. 5. An integration of metabolic and foraging theory may enable a quantitative and predictive understanding of energy flux distributions in natural food webs.

Human impact on sediment fluxes within the Blue Nile and Atbara River basins

NASA Astrophysics Data System (ADS)

Balthazar, Vincent; Vanacker, Veerle; Girma, Atkilt; Poesen, Jean; Golla, Semunesh

2013-01-01

A regional assessment of the spatial variability in sediment yields allows filling the gap between detailed, process-based understanding of erosion at field scale and empirical sediment flux models at global scale. In this paper, we focus on the intrabasin variability in sediment yield within the Blue Nile and Atbara basins as biophysical and anthropogenic factors are presumably acting together to accelerate soil erosion. The Blue Nile and Atbara River systems are characterized by an important spatial variability in sediment fluxes, with area-specific sediment yield (SSY) values ranging between 4 and 4935 t/km2/y. Statistical analyses show that 41% of the observed variation in SSY can be explained by remote sensing proxy data of surface vegetation cover, rainfall intensity, mean annual temperature, and human impact. The comparison of a locally adapted regression model with global predictive sediment flux models indicates that global flux models such as the ART and BQART models are less suited to capture the spatial variability in area-specific sediment yields (SSY), but they are very efficient to predict absolute sediment yields (SY). We developed a modified version of the BQART model that estimates the human influence on sediment yield based on a high resolution composite measure of local human impact (human footprint index) instead of countrywide estimates of GNP/capita. Our modified version of the BQART is able to explain 80% of the observed variation in SY for the Blue Nile and Atbara basins and thereby performs only slightly less than locally adapted regression models.

Molecular Modeling of Chem-Bio (CB) Contaminant Sorption/Desorption and Reactions in Chlorinated Water Systems

DTIC Science & Technology

2012-05-01

The Smoluchowski model allows us to predict both the flux of DMMP molecules onto the channel membrane in the initial phase of the simulations, as... predicts both the transient and steady-state behavior of the MD simulations. However, the model breaks down for the silica sur- faces, because the...within the range predicted by the “one versus two contact point” conjecture outlined above. Subsequent chemical modeling obtained by Ginsberg (ERDC

Bare soil respiration in a temperate climate: multiyear evaluation of a coupled CO2 transport and carbon turnover model

NASA Astrophysics Data System (ADS)

Herbst, M.; Hellebrand, H. J.; Bauer, J.; Vanderborght, J.; Vereecken, H.

2006-12-01

The modelling of soil respiration plays an important role in the prediction of climate change. Soil respiration is usually divided in autotrophic and heterotrophic fractions orginating from root respiration and microbial decomposition of soil organic carbon, respectively. We report on the coupling of a one dimensional water, heat and CO2 flux model (SOILCO2) with a model of carbon turnover (RothC) for the prediction of soil heterotrophic respiration. The coupled model was tested using soil temperature, soil moisture, and CO2 flux measurements in a bare soil experimental plot located in Bornim, Germany. A seven year record of soil and CO2 measurements covering a broad range of atmospheric and soil conditions was availabe to evaluate the model performance. After calibrating the decomposition rate constant of the humic fraction pool, the overall model performance on CO2 efflux prediction was acceptable. The root mean square error for the CO2 efflux prediction was 0.12 cm ³/cm ²/d. During the severe summer draught of 2003 very high CO2 efluxes were measured, which could not be explained by the model. Those high fluxes were attributed to a pressure pumping effect. The soil temperature dependency of CO2 production was well described by th e model, whereas the biggest opportunity for improvement is seen in a better description of the soil moisture dependency of CO2 production. The calibration of the humus decomposition rate constant revealed a value of 0.09 1/d, which is higher than the original value suggested by the RothC model developers but within the range of literature values.

Stochastic modeling of macrodispersion in unsaturated heterogeneous porous media. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yeh, T.C.J.

1995-02-01

Spatial heterogeneity of geologic media leads to uncertainty in predicting both flow and transport in the vadose zone. In this work an efficient and flexible, combined analytical-numerical Monte Carlo approach is developed for the analysis of steady-state flow and transient transport processes in highly heterogeneous, variably saturated porous media. The approach is also used for the investigation of the validity of linear, first order analytical stochastic models. With the Monte Carlo analysis accurate estimates of the ensemble conductivity, head, velocity, and concentration mean and covariance are obtained; the statistical moments describing displacement of solute plumes, solute breakthrough at a compliancemore » surface, and time of first exceedance of a given solute flux level are analyzed; and the cumulative probability density functions for solute flux across a compliance surface are investigated. The results of the Monte Carlo analysis show that for very heterogeneous flow fields, and particularly in anisotropic soils, the linearized, analytical predictions of soil water tension and soil moisture flux become erroneous. Analytical, linearized Lagrangian transport models also overestimate both the longitudinal and the transverse spreading of the mean solute plume in very heterogeneous soils and in dry soils. A combined analytical-numerical conditional simulation algorithm is also developed to estimate the impact of in-situ soil hydraulic measurements on reducing the uncertainty of concentration and solute flux predictions.« less

Observations of diurnal to weekly variations of monoterpene-dominated fluxes of volatile organic compounds from mediterranean forests: implications for regional modeling.

PubMed

Fares, Silvano; Schnitzhofer, Ralf; Jiang, Xiaoyan; Guenther, Alex; Hansel, Armin; Loreto, Francesco

2013-10-01

The Estate of Castelporziano (Rome, Italy) hosts many ecosystems representative of Mediterranean vegetation, especially holm oak and pine forests and dune vegetation. In this work, basal emission factors (BEFs) of biogenic volatile organic compounds (BVOCs) obtained by Eddy Covariance in a field campaign using a proton transfer reaction-time-of-flight-mass spectrometer (PTR-TOF-MS) were compared to BEFs reported in previous studies that could not measure fluxes in real-time. Globally, broadleaf forests are dominated by isoprene emissions, but these Mediterranean ecosystems are dominated by strong monoterpene emitters, as shown by the new BEFs. The original and new BEFs were used to parametrize the model of emissions of gases and aerosols from nature (MEGAN v2.1), and model outputs were compared with measured fluxes. Results showed good agreement between modeled and measured fluxes when a model was used to predict radiative transfer and energy balance across the canopy. We then evaluated whether changes in BVOC emissions can affect the chemistry of the atmosphere and climate at a regional level. MEGAN was run together with the land surface model (community land model, CLM v4.0) of the community earth system model (CESM v1.0). Results highlighted that tropospheric ozone concentration and air temperature predicted from the model are sensitive to the magnitude of BVOC emissions, thus demonstrating the importance of adopting the proper BEF values for model parametrization.

Enhanced Ahead-of-Eye TC Coastal Ocean Cooling Processes and their Impact on Air-Sea Heat Fluxes and Storm Intensity

NASA Astrophysics Data System (ADS)

Seroka, G. N.; Miles, T. N.; Glenn, S. M.; Xu, Y.; Forney, R.; Roarty, H.; Schofield, O.; Kohut, J. T.

2016-02-01

Any landfalling tropical cyclone (TC) must first traverse the coastal ocean. TC research, however, has focused over the deep ocean, where TCs typically spend the vast majority of their lifetime. This paper will show that the ocean's response to TCs can be different between deep and shallow water, and that the additional shallow water processes must be included in coupled models for accurate air-sea flux treatment and TC intensity prediction. The authors will present newly observed coastal ocean processes that occurred in response to Hurricane Irene (2011), due to the presence of a coastline, an ocean bottom, and highly stratified conditions. These newly observed processes led to enhanced ahead-of-eye SST cooling that significantly impacted air-sea heat fluxes and Irene's operationally over-predicted storm intensity. Using semi-idealized modeling, we find that in shallow water in Irene, only 6% of cooling due to air-sea heat fluxes, 17% of cooling due to 1D vertical mixing, and 50% of cooling due to all processes (1D mixing, air-sea heat fluxes, upwelling, and advection) occurred ahead-of-eye—consistent with previous studies. Observations from an underwater glider and buoys, however, indicated 75-100% of total SST cooling over the continental shelf was ahead-of-eye. Thus, the new coastal ocean cooling processes found in this study must occur almost completely ahead-of-eye. We show that Irene's intense cooling was not captured by basic satellite SST products and coupled ocean-atmosphere hurricane models, and that including the cooling in WRF modeling mitigated the high bias in model predictions. Finally, we provide evidence that this SST cooling—not track, wind shear, or dry air intrusion—was the key missing contribution to Irene's decay just prior to NJ landfall. Ongoing work is exploring the use of coupled WRF-ROMS modeling in the coastal zone.

Impact of Land Model Calibration on Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry and wet land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystem in NASA's Land Information System (LIS-OPT/UE). The impact of the calibration on the a) spinup of the land surface used as initial conditions, and b) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. Changes in ambient weather and land-atmosphere coupling are evaluated along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Results indicate that the offline calibration leads to systematic improvements in land-PBL fluxes and near-surface temperature and humidity, and in the process provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.

Numerical Study of Hydrothermal Wave Suppression in Thermocapillary Flow Using a Predictive Control Method

NASA Astrophysics Data System (ADS)

Muldoon, F. H.

2018-04-01

Hydrothermal waves in flows driven by thermocapillary and buoyancy effects are suppressed by applying a predictive control method. Hydrothermal waves arise in the manufacturing of crystals, including the "open boat" crystal growth process, and lead to undesirable impurities in crystals. The open boat process is modeled using the two-dimensional unsteady incompressible Navier-Stokes equations under the Boussinesq approximation and the linear approximation of the surface thermocapillary force. The flow is controlled by a spatially and temporally varying heat flux density through the free surface. The heat flux density is determined by a conjugate gradient optimization algorithm. The gradient of the objective function with respect to the heat flux density is found by solving adjoint equations derived from the Navier-Stokes ones in the Boussinesq approximation. Special attention is given to heat flux density distributions over small free-surface areas and to the maximum admissible heat flux density.

Self-consistent core-pedestal transport simulations with neural network accelerated models

DOE PAGES

Meneghini, Orso; Smith, Sterling P.; Snyder, Philip B.; ...

2017-07-12

Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflowmore » that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. Finally, the NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.« less

Self-consistent core-pedestal transport simulations with neural network accelerated models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meneghini, Orso; Smith, Sterling P.; Snyder, Philip B.

Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflowmore » that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. Finally, the NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.« less

Self-consistent core-pedestal transport simulations with neural network accelerated models

NASA Astrophysics Data System (ADS)

Meneghini, O.; Smith, S. P.; Snyder, P. B.; Staebler, G. M.; Candy, J.; Belli, E.; Lao, L.; Kostuk, M.; Luce, T.; Luda, T.; Park, J. M.; Poli, F.

2017-08-01

Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflow that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. The NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.

Cabauw experimental results from the Project for Intercomparison of Land-Surface Parameterization Schemes

USGS Publications Warehouse

Chen, T.H.; Henderson-Sellers, A.; Milly, P.C.D.; Pitman, A.J.; Beljaars, A.C.M.; Polcher, J.; Abramopoulos, F.; Boone, A.; Chang, S.; Chen, F.; Dai, Y.; Desborough, C.E.; Dickinson, R.E.; Dumenil, L.; Ek, M.; Garratt, J.R.; Gedney, N.; Gusev, Y.M.; Kim, J.; Koster, R.; Kowalczyk, E.A.; Laval, K.; Lean, J.; Lettenmaier, D.; Liang, X.; Mahfouf, Jean-Francois; Mengelkamp, H.-T.; Mitchell, Ken; Nasonova, O.N.; Noilhan, J.; Robock, A.; Rosenzweig, C.; Schaake, J.; Schlosser, C.A.; Schulz, J.-P.; Shao, Y.; Shmakin, A.B.; Verseghy, D.L.; Wetzel, P.; Wood, E.F.; Xue, Y.; Yang, Z.-L.; Zeng, Q.

1997-01-01

In the Project for Intercomparison of Land-Surface Parameterization Schemes phase 2a experiment, meteorological data for the year 1987 from Cabauw, the Netherlands, were used as inputs to 23 land-surface flux schemes designed for use in climate and weather models. Schemes were evaluated by comparing their outputs with long-term measurements of surface sensible heat fluxes into the atmosphere and the ground, and of upward longwave radiation and total net radiative fluxes, and also comparing them with latent heat fluxes derived from a surface energy balance. Tuning of schemes by use of the observed flux data was not permitted. On an annual basis, the predicted surface radiative temperature exhibits a range of 2 K across schemes, consistent with the range of about 10 W m-2 in predicted surface net radiation. Most modeled values of monthly net radiation differ from the observations by less than the estimated maximum monthly observational error (±10 W m-2). However, modeled radiative surface temperature appears to have a systematic positive bias in most schemes; this might be explained by an error in assumed emissivity and by models' neglect of canopy thermal heterogeneity. Annual means of sensible and latent heat fluxes, into which net radiation is partitioned, have ranges across schemes of 30 W m-2 and 25 W m-2, respectively. Annual totals of evapotranspiration and runoff, into which the precipitation is partitioned, both have ranges of 315 mm. These ranges in annual heat and water fluxes were approximately halved upon exclusion of the three schemes that have no stomatal resistance under non-water-stressed conditions. Many schemes tend to underestimate latent heat flux and overestimate sensible heat flux in summer, with a reverse tendency in winter. For six schemes, root-mean-square deviations of predictions from monthly observations are less than the estimated upper bounds on observation errors (5 W m-2 for sensible heat flux and 10 W m-2 for latent heat flux). Actual runoff at the site is believed to be dominated by vertical drainage to groundwater, but several schemes produced significant amounts of runoff as overland flow or interflow. There is a range across schemes of 184 mm (40% of total pore volume) in the simulated annual mean root-zone soil moisture. Unfortunately, no measurements of soil moisture were available for model evaluation. A theoretical analysis suggested that differences in boundary conditions used in various schemes are not sufficient to explain the large variance in soil moisture. However, many of the extreme values of soil moisture could be explained in terms of the particulars of experimental setup or excessive evapotranspiration.

Cabauw Experimental Results from the Project for Intercomparison of Land-Surface Parameterization Schemes.

NASA Astrophysics Data System (ADS)

Chen, T. H.; Henderson-Sellers, A.; Milly, P. C. D.; Pitman, A. J.; Beljaars, A. C. M.; Polcher, J.; Abramopoulos, F.; Boone, A.; Chang, S.; Chen, F.; Dai, Y.; Desborough, C. E.; Dickinson, R. E.; Dümenil, L.; Ek, M.; Garratt, J. R.; Gedney, N.; Gusev, Y. M.;  Kim, J.;  Koster, R.;  Kowalczyk, E. A.;  Laval, K.;  Lean, J.;  Lettenmaier, D.;  Liang, X.;  Mahfouf, J.-F.;  Mengelkamp, H.-T.;  Mitchell, K.;  Nasonova, O. N.;  Noilhan, J.;  Robock, A.;  Rosenzweig, C.;  Schaake, J.;  Schlosser, C. A.;  Schulz, J.-P.;  Shao, Y.;  Shmakin, A. B.;  Verseghy, D. L.;  Wetzel, P.;  Wood, E. F.;  Xue, Y.;  Yang, Z.-L.;  Zeng, Q.

1997-06-01

In the Project for Intercomparison of Land-Surface Parameterization Schemes phase 2a experiment, meteorological data for the year 1987 from Cabauw, the Netherlands, were used as inputs to 23 land-surface flux schemes designed for use in climate and weather models. Schemes were evaluated by comparing their outputs with long-term measurements of surface sensible heat fluxes into the atmosphere and the ground, and of upward longwave radiation and total net radiative fluxes, and also comparing them with latent heat fluxes derived from a surface energy balance. Tuning of schemes by use of the observed flux data was not permitted. On an annual basis, the predicted surface radiative temperature exhibits a range of 2 K across schemes, consistent with the range of about 10 W m2 in predicted surface net radiation. Most modeled values of monthly net radiation differ from the observations by less than the estimated maximum monthly observational error (±10 W m2). However, modeled radiative surface temperature appears to have a systematic positive bias in most schemes; this might be explained by an error in assumed emissivity and by models' neglect of canopy thermal heterogeneity. Annual means of sensible and latent heat fluxes, into which net radiation is partitioned, have ranges across schemes of30 W m2 and 25 W m2, respectively. Annual totals of evapotranspiration and runoff, into which the precipitation is partitioned, both have ranges of 315 mm. These ranges in annual heat and water fluxes were approximately halved upon exclusion of the three schemes that have no stomatal resistance under non-water-stressed conditions. Many schemes tend to underestimate latent heat flux and overestimate sensible heat flux in summer, with a reverse tendency in winter. For six schemes, root-mean-square deviations of predictions from monthly observations are less than the estimated upper bounds on observation errors (5 W m2 for sensible heat flux and 10 W m2 for latent heat flux). Actual runoff at the site is believed to be dominated by vertical drainage to groundwater, but several schemes produced significant amounts of runoff as overland flow or interflow. There is a range across schemes of 184 mm (40% of total pore volume) in the simulated annual mean root-zone soil moisture. Unfortunately, no measurements of soil moisture were available for model evaluation. A theoretical analysis suggested that differences in boundary conditions used in various schemes are not sufficient to explain the large variance in soil moisture. However, many of the extreme values of soil moisture could be explained in terms of the particulars of experimental setup or excessive evapotranspiration.

Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes

USGS Publications Warehouse

Yuan, W.; Liu, S.; Zhou, G.; Tieszen, L.L.; Baldocchi, D.; Bernhofer, C.; Gholz, H.; Goldstein, Allen H.; Goulden, M.L.; Hollinger, D.Y.; Hu, Y.; Law, B.E.; Stoy, Paul C.; Vesala, T.; Wofsy, S.C.

2007-01-01

The quantitative simulation of gross primary production (GPP) at various spatial and temporal scales has been a major challenge in quantifying the global carbon cycle. We developed a light use efficiency (LUE) daily GPP model from eddy covariance (EC) measurements. The model, called EC-LUE, is driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux (used to calculate moisture stress). The EC-LUE model relies on two assumptions: First, that the fraction of absorbed PAR (fPAR) is a linear function of NDVI; Second, that the realized light use efficiency, calculated from a biome-independent invariant potential LUE, is controlled by air temperature or soil moisture, whichever is most limiting. The EC-LUE model was calibrated and validated using 24,349 daily GPP estimates derived from 28 eddy covariance flux towers from the AmeriFlux and EuroFlux networks, covering a variety of forests, grasslands and savannas. The model explained 85% and 77% of the observed variations of daily GPP for all the calibration and validation sites, respectively. A comparison with GPP calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS) indicated that the EC-LUE model predicted GPP that better matched tower data across these sites. The realized LUE was predominantly controlled by moisture conditions throughout the growing season, and controlled by temperature only at the beginning and end of the growing season. The EC-LUE model is an alternative approach that makes it possible to map daily GPP over large areas because (1) the potential LUE is invariant across various land cover types and (2) all driving forces of the model can be derived from remote sensing data or existing climate observation networks.

Revisiting low-fidelity two-fluid models for gas-solids transport

NASA Astrophysics Data System (ADS)

Adeleke, Najeem; Adewumi, Michael; Ityokumbul, Thaddeus

2016-08-01

Two-phase gas-solids transport models are widely utilized for process design and automation in a broad range of industrial applications. Some of these applications include proppant transport in gaseous fracking fluids, air/gas drilling hydraulics, coal-gasification reactors and food processing units. Systems automation and real time process optimization stand to benefit a great deal from availability of efficient and accurate theoretical models for operations data processing. However, modeling two-phase pneumatic transport systems accurately requires a comprehensive understanding of gas-solids flow behavior. In this study we discuss the prevailing flow conditions and present a low-fidelity two-fluid model equation for particulate transport. The model equations are formulated in a manner that ensures the physical flux term remains conservative despite the inclusion of solids normal stress through the empirical formula for modulus of elasticity. A new set of Roe-Pike averages are presented for the resulting strictly hyperbolic flux term in the system of equations, which was used to develop a Roe-type approximate Riemann solver. The resulting scheme is stable regardless of the choice of flux-limiter. The model is evaluated by the prediction of experimental results from both pneumatic riser and air-drilling hydraulics systems. We demonstrate the effect and impact of numerical formulation and choice of numerical scheme on model predictions. We illustrate the capability of a low-fidelity one-dimensional two-fluid model in predicting relevant flow parameters in two-phase particulate systems accurately even under flow regimes involving counter-current flow.

Theoretical Prediction of Microgravity Ignition Delay of Polymeric Fuels in Low Velocity Flows

NASA Technical Reports Server (NTRS)

Fernandez-Pello, A. C.; Torero, J. L.; Zhou, Y. Y.; Walther, D.; Ross, H. D.

2001-01-01

A new flammability apparatus and protocol, FIST (Forced Flow Ignition and Flame Spread Test), is under development. Based on the LIFT (Lateral Ignition and Flame Spread Test) protocol, FIST better reflects the environments expected in spacebased facilities. The final objective of the FIST research is to provide NASA with a test methodology that complements the existing protocol and provides a more comprehensive assessment of material flammability of practical materials for space applications. Theoretical modeling, an extensive normal gravity data bank and a few validation space experiments will support the testing methodology. The objective of the work presented here is to predict the ignition delay and critical heat flux for ignition of solid fuels in microgravity at airflow velocities below those induced in normal gravity. This is achieved through the application of a numerical model previously developed of piloted ignition of solid polymeric materials exposed to an external radiant heat flux. The model predictions will provide quantitative results about ignition of practical materials in the limiting conditions expected in space facilities. Experimental data of surface temperature histories and ignition delay obtained in the KC-135 aircraft are used to determine the critical pyrolysate mass flux for ignition and this value is subsequently used to predict the ignition delay and the critical heat flux for ignition of the material. Surface temperature and piloted ignition delay calculations for Polymethylmethacrylate (PMMA) and a Polypropylene/Fiberglass (PP/GL) composite were conducted under both reduced and normal gravity conditions. It was found that ignition delay times are significantly shorter at velocities below those induced by natural convection.

The role of ecosystem memory in predicting inter-annual variations of the tropical carbon balance.

NASA Astrophysics Data System (ADS)

Bloom, A. A.; Liu, J.; Bowman, K. W.; Konings, A. G.; Saatchi, S.; Worden, J. R.; Worden, H. M.; Jiang, Z.; Parazoo, N.; Williams, M. D.; Schimel, D.

2017-12-01

Understanding the trajectory of the tropical carbon balance remains challenging, in part due to large uncertainties in the integrated response of carbon cycle processes to climate variability. Satellite observations atmospheric CO2 from GOSAT and OCO-2, together with ancillary satellite measurements, provide crucial constraints on continental-scale terrestrial carbon fluxes. However, an integrated understanding of both climate forcings and legacy effects (or "ecosystem memory") on the terrestrial carbon balance is ultimately needed to reduce uncertainty on its future trajectory. Here we use the CARbon DAta-MOdel fraMework (CARDAMOM) diagnostic model-data fusion approach - constrained by an array of C cycle satellite surface observations, including MODIS leaf area, biomass, GOSAT solar-induced fluorescence, as well as "top-down" atmospheric inversion estimates of CO2 and CO surface fluxes from the NASA Carbon Monitoring System Flux (CMS-Flux) - to constrain and predict spatially-explicit tropical carbon state variables during 2010-2015. We find that the combined assimilation of land surface and atmospheric datasets places key constraints on the temperature sensitivity and first order carbon-water feedbacks throughout the tropics and combustion factors within biomass burning regions. By varying the duration of the assimilation period, we find that the prediction skill on inter-annual net biospheric exchange is primarily limited by record length rather than model structure and process representation. We show that across all tropical biomes, quantitative knowledge of memory effects - which account for 30-50% of interannual variations across the tropics - is critical for understanding and ultimately predicting the inter-annual tropical carbon balance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meyer, Eileen T.; Breiding, Peter; Georganopoulos, Markos

The Chandra X-ray observatory has discovered several dozen anomalously X-ray-bright jets associated with powerful quasars. A popular explanation for the X-ray flux from the knots in these jets is that relativistic synchrotron-emitting electrons inverse-Compton scatter cosmic microwave background (CMB) photons to X-ray energies (the IC/CMB model). This model predicts a high gamma-ray flux that should be detectable by the Fermi /Large Area Telescope (LAT) for many sources. GeV-band upper limits from Fermi /LAT for the well-known anomalous X-ray jet in PKS 0637−752 were previously shown in Meyer et al. to violate the predictions of the IC/CMB model. Previously, measurements ofmore » the jet synchrotron spectrum, important for accurately predicting the gamma-ray flux level, were lacking between radio and infrared wavelengths. Here, we present new Atacama Large Millimeter/submillimeter Array (ALMA) observations of the large-scale jet at 100, 233, and 319 GHz, which further constrain the synchrotron spectrum, supporting the previously published empirical model. We also present updated limits from the Fermi /LAT using the new “Pass 8” calibration and approximately 30% more time on source. With these deeper limits, we rule out the IC/CMB model at the 8.7 σ level. Finally, we demonstrate that complete knowledge of the synchrotron SED is critical in evaluating the IC/CMB model.« less

Simulation of high-energy radiation belt electron fluxes using NARMAX-VERB coupled codes

PubMed Central

Pakhotin, I P; Drozdov, A Y; Shprits, Y Y; Boynton, R J; Subbotin, D A; Balikhin, M A

2014-01-01

This study presents a fusion of data-driven and physics-driven methodologies of energetic electron flux forecasting in the outer radiation belt. Data-driven NARMAX (Nonlinear AutoRegressive Moving Averages with eXogenous inputs) model predictions for geosynchronous orbit fluxes have been used as an outer boundary condition to drive the physics-based Versatile Electron Radiation Belt (VERB) code, to simulate energetic electron fluxes in the outer radiation belt environment. The coupled system has been tested for three extended time periods totalling several weeks of observations. The time periods involved periods of quiet, moderate, and strong geomagnetic activity and captured a range of dynamics typical of the radiation belts. The model has successfully simulated energetic electron fluxes for various magnetospheric conditions. Physical mechanisms that may be responsible for the discrepancies between the model results and observations are discussed. PMID:26167432

Estimation of maximum transdermal flux of nonionized xenobiotics from basic physicochemical determinants

PubMed Central

Milewski, Mikolaj; Stinchcomb, Audra L.

2012-01-01

An ability to estimate the maximum flux of a xenobiotic across skin is desirable both from the perspective of drug delivery and toxicology. While there is an abundance of mathematical models describing the estimation of drug permeability coefficients, there are relatively few that focus on the maximum flux. This article reports and evaluates a simple and easy-to-use predictive model for the estimation of maximum transdermal flux of xenobiotics based on three common molecular descriptors: logarithm of octanol-water partition coefficient, molecular weight and melting point. The use of all three can be justified on the theoretical basis of their influence on the solute aqueous solubility and the partitioning into the stratum corneum lipid domain. The model explains 81% of the variability in the permeation dataset comprised of 208 entries and can be used to obtain a quick estimate of maximum transdermal flux when experimental data is not readily available. PMID:22702370

Observations of Diurnal to Weekly Variations of Monoterpene-Dominated Fluxes of Volatile Organic Compounds from Mediterranean Forests: Implications for Regional Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fares, Silvano; Schnitzhofer, Ralf; Jiang, Xiaoyan

2013-10-01

The Estate of Castelporziano (Rome, Italy) hosts many ecosystems representative of Mediterranean vegetation, especially holm oak and pine forests and dune vegetation. In this work, basal emission factors (BEFs) of biogenic volatile organic compounds (BVOCs) obtained by Eddy Covariance in a field campaign using a proton transfer reaction–time-of-flight–mass spectrometer (PTR-TOF-MS) were compared to BEFs reported in previous studies that could not measure fluxes in real-time. Globally, broadleaf forests are dominated by isoprene emissions, but these Mediterranean ecosystems are dominated by strong monoterpene emitters, as shown by the new BEFs. The original and new BEFs were used to parametrize the modelmore » of emissions of gases and aerosols from nature (MEGAN v2.1), and model outputs were compared with measured fluxes. Results showed good agreement between modeled and measured fluxes when a model was used to predict radiative transfer and energy balance across the canopy. We then evaluated whether changes in BVOC emissions can affect the chemistry of the atmosphere and climate at a regional level. MEGAN was run together with the land surface model (community land model, CLM v4.0) of the community earth system model (CESM v1.0). Finally, results highlighted that tropospheric ozone concentration and air temperature predicted from the model are sensitive to the magnitude of BVOC emissions, thus demonstrating the importance of adopting the proper BEF values for model parametrization.« less

On the modelling of scalar and mass transport in combustor flows

NASA Technical Reports Server (NTRS)

Nikjooy, M.; So, R. M. C.

1989-01-01

Results are presented of a numerical study of swirling and nonswirling combustor flows with and without density variations. Constant-density arguments are used to justify closure assumptions invoked for the transport equations for turbulent momentum and scalar fluxes, which are written in terms of density-weighted variables. Comparisons are carried out with measurements obtained from three different axisymmetric model combustor experiments covering recirculating flow, swirling flow, and variable-density swirling flow inside the model combustors. Results show that the Reynolds stress/flux models do a credible job of predicting constant-density swirling and nonswirling combustor flows with passive scalar transport. However, their improvements over algebraic stress/flux models are marginal. The extension of the constant-density models to variable-density flow calculations shows that the models are equally valid for such flows.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michael, A. T.; Opher, M.; Provornikova, E.

In the heliosheath (HS), Voyager 2 has observed a flow with constant radial velocity and magnetic flux conservation. Voyager 1, however, has observed a decrease in the flow’s radial velocity and an order of magnitude decrease in magnetic flux. We investigate the role of the 11 yr solar cycle variation of the magnetic field strength on the magnetic flux within the HS using a global 3D magnetohydrodynamic model of the heliosphere. We use time and latitude-dependent solar wind velocity and density inferred from Solar and Heliospheric Observatory/SWAN and interplanetary scintillations data and implemented solar cycle variations of the magnetic fieldmore » derived from 27 day averages of the field magnitude average of the magnetic field at 1 AU from the OMNI database. With the inclusion of the solar cycle time-dependent magnetic field intensity, the model matches the observed intensity of the magnetic field in the HS along both Voyager 1 and 2. This is a significant improvement from the same model without magnetic field solar cycle variations, which was over a factor of two larger. The model accurately predicts the radial velocity observed by Voyager 2; however, the model predicts a flow speed ∼100 km s{sup −1} larger than that derived from LECP measurements at Voyager 1. In the model, magnetic flux is conserved along both Voyager trajectories, contrary to observations. This implies that the solar cycle variations in solar wind magnetic field observed at 1 AU does not cause the order of magnitude decrease in magnetic flux observed in the Voyager 1 data.« less

Approach to Integrate Global-Sun Models of Magnetic Flux Emergence and Transport for Space Weather Studies

NASA Technical Reports Server (NTRS)

Mansour, Nagi N.; Wray, Alan A.; Mehrotra, Piyush; Henney, Carl; Arge, Nick; Godinez, H.; Manchester, Ward; Koller, J.; Kosovichev, A.; Scherrer, P.;

Numerical Analysis of a Radiant Heat Flux Calibration System

NASA Technical Reports Server (NTRS)

Jiang, Shanjuan; Horn, Thomas J.; Dhir, V. K.

1998-01-01

A radiant heat flux gage calibration system exists in the Flight Loads Laboratory at NASA's Dryden Flight Research Center. This calibration system must be well understood if the heat flux gages calibrated in it are to provide useful data during radiant heating ground tests or flight tests of high speed aerospace vehicles. A part of the calibration system characterization process is to develop a numerical model of the flat plate heater element and heat flux gage, which will help identify errors due to convection, heater element erosion, and other factors. A 2-dimensional mathematical model of the gage-plate system has been developed to simulate the combined problem involving convection, radiation and mass loss by chemical reaction. A fourth order finite difference scheme is used to solve the steady state governing equations and determine the temperature distribution in the gage and plate, incident heat flux on the gage face, and flat plate erosion. Initial gage heat flux predictions from the model are found to be within 17% of experimental results.

Assessing FPAR Source and Parameter Optimization Scheme in Application of a Diagnostic Carbon Flux Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, D P; Ritts, W D; Wharton, S

2009-02-26

The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors.more » FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.« less

Prediction of Breakthrough Curves for Conservative and Reactive Transport from the Structural Parameters of Highly Heterogeneous Media

NASA Astrophysics Data System (ADS)

Hansen, S. K.; Haslauer, C. P.; Cirpka, O. A.; Vesselinov, V. V.

2016-12-01

It is desirable to predict the shape of breakthrough curves downgradient of a solute source from subsurface structural parameters (as in the small-perturbation macrodispersion theory) both for realistically heterogeneous fields, and at early time, before any sort of Fickian model is applicable. Using a combination of a priori knowledge, large-scale Monte Carlo simulation, and regression techniques, we have developed closed-form predictive expressions for pre- and post-Fickian flux-weighted solute breakthrough curves as a function of distance from the source (in integral scales) and variance of the log hydraulic conductivity field. Using the ensemble of Monte Carlo realizations, we have simultaneously computed error envelopes for the estimated flux-weighted breakthrough, and for the divergence of point breakthrough curves from the flux-weighted average, as functions of the predictive parameters. We have also obtained implied late-time macrodispersion coefficients for highly heterogeneous environments from the breakthrough statistics. This analysis is relevant for the modelling of reactive as well as conservative transport, since for many kinetic sorption and decay reactions, Laplace-domain modification of the breakthrough curve for conservative solute produces the correct curve for the reactive system.

Combining Diffusive Shock Acceleration with Acceleration by Contracting and Reconnecting Small-scale Flux Ropes at Heliospheric Shocks

NASA Astrophysics Data System (ADS)

le Roux, J. A.; Zank, G. P.; Webb, G. M.; Khabarova, O. V.

2016-08-01

Computational and observational evidence is accruing that heliospheric shocks, as emitters of vorticity, can produce downstream magnetic flux ropes and filaments. This led Zank et al. to investigate a new paradigm whereby energetic particle acceleration near shocks is a combination of diffusive shock acceleration (DSA) with downstream acceleration by many small-scale contracting and reconnecting (merging) flux ropes. Using a model where flux-rope acceleration involves a first-order Fermi mechanism due to the mean compression of numerous contracting flux ropes, Zank et al. provide theoretical support for observations that power-law spectra of energetic particles downstream of heliospheric shocks can be harder than predicted by DSA theory and that energetic particle intensities should peak behind shocks instead of at shocks as predicted by DSA theory. In this paper, a more extended formalism of kinetic transport theory developed by le Roux et al. is used to further explore this paradigm. We describe how second-order Fermi acceleration, related to the variance in the electromagnetic fields produced by downstream small-scale flux-rope dynamics, modifies the standard DSA model. The results show that (I) this approach can qualitatively reproduce observations of particle intensities peaking behind the shock, thus providing further support for the new paradigm, and (II) stochastic acceleration by compressible flux ropes tends to be more efficient than incompressible flux ropes behind shocks in modifying the DSA spectrum of energetic particles.

COMBINING DIFFUSIVE SHOCK ACCELERATION WITH ACCELERATION BY CONTRACTING AND RECONNECTING SMALL-SCALE FLUX ROPES AT HELIOSPHERIC SHOCKS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Le Roux, J. A.; Zank, G. P.; Webb, G. M.

2016-08-10

Computational and observational evidence is accruing that heliospheric shocks, as emitters of vorticity, can produce downstream magnetic flux ropes and filaments. This led Zank et al. to investigate a new paradigm whereby energetic particle acceleration near shocks is a combination of diffusive shock acceleration (DSA) with downstream acceleration by many small-scale contracting and reconnecting (merging) flux ropes. Using a model where flux-rope acceleration involves a first-order Fermi mechanism due to the mean compression of numerous contracting flux ropes, Zank et al. provide theoretical support for observations that power-law spectra of energetic particles downstream of heliospheric shocks can be harder thanmore » predicted by DSA theory and that energetic particle intensities should peak behind shocks instead of at shocks as predicted by DSA theory. In this paper, a more extended formalism of kinetic transport theory developed by le Roux et al. is used to further explore this paradigm. We describe how second-order Fermi acceleration, related to the variance in the electromagnetic fields produced by downstream small-scale flux-rope dynamics, modifies the standard DSA model. The results show that (i) this approach can qualitatively reproduce observations of particle intensities peaking behind the shock, thus providing further support for the new paradigm, and (ii) stochastic acceleration by compressible flux ropes tends to be more efficient than incompressible flux ropes behind shocks in modifying the DSA spectrum of energetic particles.« less

Mass Transport through Nanostructured Membranes: Towards a Predictive Tool

PubMed Central

Darvishmanesh, Siavash; Van der Bruggen, Bart

2016-01-01

This study proposes a new mechanism to understand the transport of solvents through nanostructured membranes from a fundamental point of view. The findings are used to develop readily applicable mathematical models to predict solvent fluxes and solute rejections through solvent resistant membranes used for nanofiltration. The new model was developed based on a pore-flow type of transport. New parameters found to be of fundamental importance were introduced to the equation, i.e., the affinity of the solute and the solvent for the membrane expressed as the hydrogen-bonding contribution of the solubility parameter for the solute, solvent and membrane. A graphical map was constructed to predict the solute rejection based on the hydrogen-bonding contribution of the solubility parameter. The model was evaluated with performance data from the literature. Both the solvent flux and the solute rejection calculated with the new approach were similar to values reported in the literature. PMID:27918434

The effect on empirical atmospheric modeling of the mass-flux as an independent parameter. [in sun and Be stars

NASA Technical Reports Server (NTRS)

Thomas, R. N.

1982-01-01

Observational data on atmospheric structure and mass fluxes from the sun and Be stars are applied to test the adequacy of the original Parker 'hot corona' approach to predicting atmospheric structure and the size of the mass flux from only the radiative and nonradiative energy fluxes, and from gravity, and imposing the condition that thermal and escape points must coincide. Observations do not support this latter condition. It is concluded that the Parker approach is an asymptotic approximation to the very low mass flux limit in a nonvariable stellar atmosphere.

The connection characteristics of flux pinned docking interface

NASA Astrophysics Data System (ADS)

Zhang, Mingliang; Han, Yanjun; Guo, Xing; Zhao, Cunbao; Deng, Feiyue

2017-03-01

This paper presents the mechanism and potential advantages of flux pinned docking interface mainly composed of a high temperature superconductor and an electromagnet. In order to readily assess the connection characteristics of flux pinned docking interface, the force between a high temperature superconductor and an electromagnet needs to be investigated. Based on the magnetic dipole method and the Ampere law method, the force between two current coils can be compared, which shows that the Ampere law method has the higher calculated accuracy. Based on the improved frozen image model and the Ampere law method, the force between high temperature superconductor bulk and permanent magnet can be calculated, which is validated experimentally. Moreover, the force between high temperature superconductor and electromagnet applied to flux pinned docking interface is able to be predicted and analyzed. The connection stiffness between high temperature superconductor and permanent magnet can be calculated based on the improved frozen image model and Hooke's law. The relationship between the connection stiffness and field cooling height is analyzed. Furthermore, the connection stiffness of the flux pinned docking interface is predicted and optimized, and its effective working range is defined and analyzed in case of some different parameters.

Suspended sediment flux modeling with artificial neural network: An example of the Longchuanjiang River in the Upper Yangtze Catchment, China

NASA Astrophysics Data System (ADS)

Zhu, Yun-Mei; Lu, X. X.; Zhou, Yue

2007-02-01

Artificial neural network (ANN) was used to model the monthly suspended sediment flux in the Longchuanjiang River, the Upper Yangtze Catchment, China. The suspended sediment flux was related to the average rainfall, temperature, rainfall intensity and water discharge. It is demonstrated that ANN is capable of modeling the monthly suspended sediment flux with fairly good accuracy when proper variables and their lag effect on the suspended sediment flux are used as inputs. Compared with multiple linear regression and power relation models, ANN can generate a better fit under the same data requirement. In addition, ANN can provide more reasonable predictions for extremely high or low values, because of the distributed information processing system and the nonlinear transformation involved. Compared with the ANNs that use the values of the dependent variable at previous time steps as inputs, the ANNs established in this research with only climate variables have an advantage because it can be used to assess hydrological responses to climate change.

Revealing the Earth's mantle from the tallest mountains using the Jinping Neutrino Experiment.

PubMed

Šrámek, Ondřej; Roskovec, Bedřich; Wipperfurth, Scott A; Xi, Yufei; McDonough, William F

2016-09-09

The Earth's engine is driven by unknown proportions of primordial energy and heat produced in radioactive decay. Unfortunately, competing models of Earth's composition reveal an order of magnitude uncertainty in the amount of radiogenic power driving mantle dynamics. Recent measurements of the Earth's flux of geoneutrinos, electron antineutrinos from terrestrial natural radioactivity, reveal the amount of uranium and thorium in the Earth and set limits on the residual proportion of primordial energy. Comparison of the flux measured at large underground neutrino experiments with geologically informed predictions of geoneutrino emission from the crust provide the critical test needed to define the mantle's radiogenic power. Measurement at an oceanic location, distant from nuclear reactors and continental crust, would best reveal the mantle flux, however, no such experiment is anticipated. We predict the geoneutrino flux at the site of the Jinping Neutrino Experiment (Sichuan, China). Within 8 years, the combination of existing data and measurements from soon to come experiments, including Jinping, will exclude end-member models at the 1σ level, define the mantle's radiogenic contribution to the surface heat loss, set limits on the composition of the silicate Earth, and provide significant parameter bounds for models defining the mode of mantle convection.

A DOUBLE-RING ALGORITHM FOR MODELING SOLAR ACTIVE REGIONS: UNIFYING KINEMATIC DYNAMO MODELS AND SURFACE FLUX-TRANSPORT SIMULATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Munoz-Jaramillo, Andres; Martens, Petrus C. H.; Nandy, Dibyendu

The emergence of tilted bipolar active regions (ARs) and the dispersal of their flux, mediated via processes such as diffusion, differential rotation, and meridional circulation, is believed to be responsible for the reversal of the Sun's polar field. This process (commonly known as the Babcock-Leighton mechanism) is usually modeled as a near-surface, spatially distributed {alpha}-effect in kinematic mean-field dynamo models. However, this formulation leads to a relationship between polar field strength and meridional flow speed which is opposite to that suggested by physical insight and predicted by surface flux-transport simulations. With this in mind, we present an improved double-ring algorithmmore » for modeling the Babcock-Leighton mechanism based on AR eruption, within the framework of an axisymmetric dynamo model. Using surface flux-transport simulations, we first show that an axisymmetric formulation-which is usually invoked in kinematic dynamo models-can reasonably approximate the surface flux dynamics. Finally, we demonstrate that our treatment of the Babcock-Leighton mechanism through double-ring eruption leads to an inverse relationship between polar field strength and meridional flow speed as expected, reconciling the discrepancy between surface flux-transport simulations and kinematic dynamo models.« less

Mesoscopic fluctuations in biharmonically driven flux qubits

NASA Astrophysics Data System (ADS)

Ferrón, Alejandro; Domínguez, Daniel; Sánchez, María José

2017-01-01

We investigate flux qubits driven by a biharmonic magnetic signal, with a phase lag that acts as an effective time reversal broken parameter. The driving induced transition rate between the ground and the excited state of the flux qubit can be thought of as an effective transmittance, profiting from a direct analogy between interference effects at avoided level crossings and scattering events in disordered electronic systems. For time scales prior to full relaxation, but large compared to the decoherence time, this characteristic rate has been accessed experimentally by Gustavsson et al. [Phys. Rev. Lett. 110, 016603 (2013)], 10.1103/PhysRevLett.110.016603 and its sensitivity with both the phase lag and the dc flux detuning explored. In this way, signatures of universal conductance fluctuationslike effects have been analyzed and compared with predictions from a phenomenological model that only accounts for decoherence, as a classical noise. Here we go beyond the classical noise model and solve the full dynamics of the driven flux qubit in contact with a quantum bath employing the Floquet-Born-Markov master equation. Within this formalism, the computed relaxation and decoherence rates turn out to be strongly dependent on both the phase lag and the dc flux detuning. Consequently, the associated pattern of fluctuations in the characteristic rates display important differences with those obtained within the mentioned phenomenological model. In particular, we demonstrate the weak localizationlike effect in the average values of the relaxation rate. Our predictions can be tested for accessible but longer time scales than the current experimental times.

Two-Scale 13C Metabolic Flux Analysis for Metabolic Engineering.

PubMed

Ando, David; Garcia Martin, Hector

2018-01-01

Accelerating the Design-Build-Test-Learn (DBTL) cycle in synthetic biology is critical to achieving rapid and facile bioengineering of organisms for the production of, e.g., biofuels and other chemicals. The Learn phase involves using data obtained from the Test phase to inform the next Design phase. As part of the Learn phase, mathematical models of metabolic fluxes give a mechanistic level of comprehension to cellular metabolism, isolating the principle drivers of metabolic behavior from the peripheral ones, and directing future experimental designs and engineering methodologies. Furthermore, the measurement of intracellular metabolic fluxes is specifically noteworthy as providing a rapid and easy-to-understand picture of how carbon and energy flow throughout the cell. Here, we present a detailed guide to performing metabolic flux analysis in the Learn phase of the DBTL cycle, where we show how one can take the isotope labeling data from a 13 C labeling experiment and immediately turn it into a determination of cellular fluxes that points in the direction of genetic engineering strategies that will advance the metabolic engineering process.For our modeling purposes we use the Joint BioEnergy Institute (JBEI) Quantitative Metabolic Modeling (jQMM) library, which provides an open-source, python-based framework for modeling internal metabolic fluxes and making actionable predictions on how to modify cellular metabolism for specific bioengineering goals. It presents a complete toolbox for performing different types of flux analysis such as Flux Balance Analysis, 13 C Metabolic Flux Analysis, and it introduces the capability to use 13 C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13 C Metabolic Flux Analysis (2S- 13 C MFA) [1]. In addition to several other capabilities, the jQMM is also able to predict the effects of knockouts using the MoMA and ROOM methodologies. The use of the jQMM library is illustrated through a step-by-step demonstration, which is also contained in a digital Jupyter Notebook format that enhances reproducibility and provides the capability to be adopted to the user's specific needs. As an open-source software project, users can modify and extend the code base and make improvements at will, providing a base for future modeling efforts.

Time Dependent Predictive Modeling of DIII-D ITER Baseline Scenario using Predictive TRANSP

NASA Astrophysics Data System (ADS)

Grierson, B. A.; Andre, R. G.; Budny, R. V.; Solomon, W. M.; Yuan, X.; Candy, J.; Pinsker, R. I.; Staebler, G. M.; Holland, C.; Rafiq, T.

2015-11-01

ITER baseline scenario discharges on DIII-D are modeled with TGLF and MMM transitioning from combined ECH (3.3MW) +NBI(2.8MW) heating to NBI only (3.0 MW) heating maintaining βN = 2.0 on DIII-D predicting temperature, density and rotation for comparison to experimental measurements. These models capture the reduction of confinement associated with direct electron heating H98y2 = 0.89 vs. 1.0) consistent with stiff electron transport. Reasonable agreement between experimental and modeled temperature profiles is achieved for both heating methods, whereas density and momentum predictions differ significantly. Transport fluxes from TGLF indicate that on DIII-D the electron energy flux has reached a transition from low-k to high-k turbulence with more stiff high-k transport that inhibits an increase in core electron stored energy with additional electron heating. Projections to ITER also indicate high electron stiffness. Supported by US DOE DE-AC02-09CH11466, DE-FC02-04ER54698, DE-FG02-07ER54917, DE-FG02-92-ER54141.

Derivation of the Energy and Flux Morphology in an Aurora Observed at Midlatitude Using Multispectral Imaging

NASA Astrophysics Data System (ADS)

Aryal, Saurav; Finn, Susanna C.; Hewawasam, Kuravi; Maguire, Ryan; Geddes, George; Cook, Timothy; Martel, Jason; Baumgardner, Jeffrey L.; Chakrabarti, Supriya

2018-05-01

Energies and fluxes of precipitating electrons in an aurora over Lowell, MA on 22-23 June 2015 were derived based on simultaneous, high-resolution (≈ 0.02 nm) brightness measurements of N2+ (427.8 nm, blue line), OI (557.7 nm, green line), and OI (630.0 nm, red line) emissions. The electron energies and energy fluxes as a function of time and look direction were derived by nonlinear minimization of model predictions with respect to the measurements. Three different methods were compared; in the first two methods, we constrained the modeled brightnesses and brightness ratios, respectively, with measurements to simultaneously derive energies and fluxes. Then we used a hybrid method where we constrained the individual modeled brightness ratios with measurements to derive energies and then constrained modeled brightnesses with measurements to derive fluxes. Derived energy, assuming Maxwellian distribution, during this storm ranged from 109 to 262 eV and the total energy flux ranged from 0.8 to 2.2 ergs·cm-2·s-1. This approach provides a way to estimate energies and energy fluxes of the precipitating electrons using simultaneous multispectral measurements.

Modeling the pyrolysis study of non-charring polymers under reduced pressure environments

NASA Astrophysics Data System (ADS)

Zong, Ruowen; Kang, Ruxue; Hu, Yanghui; Zhi, Youran

2018-04-01

In order to study the pyrolysis of non-charring polymers under reduced pressure environments, a series of experiments based on black acrylonitrile butadiene styrene (ABS) was conducted in a reduced pressure chamber under different external heat fluxes. The temperatures of the top surface and the bottom of the sample and the mass loss during the whole process were measured in real time. A one-dimensional numerical model was developed to predict the top surface and the bottom surface temperatures of ABS during the pyrolysis at different reduced pressures and external heat fluxes, and the model was validated by the experimental data. The results of the study indicate that the profiles of the top surface and the bottom surface temperatures are different at different pressures and heat fluxes. The temperature and the mass loss rate of the sample under a lower heat flux decreased significantly as the pressure was increased. However, under a higher heat flux, the temperature and the mass loss rate showed little sensitivity to the pressure. The simulated results fitted the experimental results better at the higher heat flux than at the lower heat flux.

Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling

NASA Astrophysics Data System (ADS)

Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.

2017-12-01

Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model. This complex model then serves as the basis to compare simpler model structures. Through this approach, predictive uncertainty can be quantified relative to a known reference solution.

A new technique for observationally derived boundary conditions for space weather

NASA Astrophysics Data System (ADS)

Pagano, Paolo; Mackay, Duncan Hendry; Yeates, Anthony Robinson

2018-04-01

Context. In recent years, space weather research has focused on developing modelling techniques to predict the arrival time and properties of coronal mass ejections (CMEs) at the Earth. The aim of this paper is to propose a new modelling technique suitable for the next generation of Space Weather predictive tools that is both efficient and accurate. The aim of the new approach is to provide interplanetary space weather forecasting models with accurate time dependent boundary conditions of erupting magnetic flux ropes in the upper solar corona. Methods: To produce boundary conditions, we couple two different modelling techniques, MHD simulations and a quasi-static non-potential evolution model. Both are applied on a spatial domain that covers the entire solar surface, although they extend over a different radial distance. The non-potential model uses a time series of observed synoptic magnetograms to drive the non-potential quasi-static evolution of the coronal magnetic field. This allows us to follow the formation and loss of equilibrium of magnetic flux ropes. Following this a MHD simulation captures the dynamic evolution of the erupting flux rope, when it is ejected into interplanetary space. Results.The present paper focuses on the MHD simulations that follow the ejection of magnetic flux ropes to 4 R⊙. We first propose a technique for specifying the pre-eruptive plasma properties in the corona. Next, time dependent MHD simulations describe the ejection of two magnetic flux ropes, that produce time dependent boundary conditions for the magnetic field and plasma at 4 R⊙ that in future may be applied to interplanetary space weather prediction models. Conclusions: In the present paper, we show that the dual use of quasi-static non-potential magnetic field simulations and full time dependent MHD simulations can produce realistic inhomogeneous boundary conditions for space weather forecasting tools. Before a fully operational model can be produced there are a number of technical and scientific challenges that still need to be addressed. Nevertheless, we illustrate that coupling quasi-static and MHD simulations in this way can significantly reduce the computational time required to produce realistic space weather boundary conditions.

A state-space modeling approach to estimating canopy conductance and associated uncertainties from sap flux density data.

PubMed

Bell, David M; Ward, Eric J; Oishi, A Christopher; Oren, Ram; Flikkema, Paul G; Clark, James S

2015-07-01

Uncertainties in ecophysiological responses to environment, such as the impact of atmospheric and soil moisture conditions on plant water regulation, limit our ability to estimate key inputs for ecosystem models. Advanced statistical frameworks provide coherent methodologies for relating observed data, such as stem sap flux density, to unobserved processes, such as canopy conductance and transpiration. To address this need, we developed a hierarchical Bayesian State-Space Canopy Conductance (StaCC) model linking canopy conductance and transpiration to tree sap flux density from a 4-year experiment in the North Carolina Piedmont, USA. Our model builds on existing ecophysiological knowledge, but explicitly incorporates uncertainty in canopy conductance, internal tree hydraulics and observation error to improve estimation of canopy conductance responses to atmospheric drought (i.e., vapor pressure deficit), soil drought (i.e., soil moisture) and above canopy light. Our statistical framework not only predicted sap flux observations well, but it also allowed us to simultaneously gap-fill missing data as we made inference on canopy processes, marking a substantial advance over traditional methods. The predicted and observed sap flux data were highly correlated (mean sensor-level Pearson correlation coefficient = 0.88). Variations in canopy conductance and transpiration associated with environmental variation across days to years were many times greater than the variation associated with model uncertainties. Because some variables, such as vapor pressure deficit and soil moisture, were correlated at the scale of days to weeks, canopy conductance responses to individual environmental variables were difficult to interpret in isolation. Still, our results highlight the importance of accounting for uncertainty in models of ecophysiological and ecosystem function where the process of interest, canopy conductance in this case, is not observed directly. The StaCC modeling framework provides a statistically coherent approach to estimating canopy conductance and transpiration and propagating estimation uncertainty into ecosystem models, paving the way for improved prediction of water and carbon uptake responses to environmental change. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lafontaine Rivera, Jimmy G.; Theisen, Matthew K.; Chen, Po-Wei

The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here in this paper we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realisticmore » quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.« less

The continuous UV flux of Alpha Lyrae - Non-LTE results

NASA Technical Reports Server (NTRS)

Snijders, M. A. J.

1977-01-01

Non-LTE calculations for the ultraviolet C I and Si I continuous opacity show that LTE results overestimate the importance of these sources of opacity and underestimate the emergent flux in Alpha Lyr. The largest errors occur between 1100 and 1160 A, where the predicted flux in non-LTE is as much as 50 times larger than in LTE, in reasonable accord with Copernicus observations. The discrepancy between LTE models and observations has been interpreted to result from the existence of a chromosphere. Until a self-consistent non-LTE model atmosphere becomes available, such an interpretation is premature.

Quantifying the impact of El Niño-driven variations in temperature and precipitation on regional atmospheric CO2 growth rate variations

NASA Astrophysics Data System (ADS)

Keppel-Aleks, G.; Butterfield, Z.; Doney, S. C.; Dlugokencky, E. J.; Miller, J.; Morton, D. C.

2017-12-01

Quantifying the climatic drivers of variations in atmospheric CO2 observations over a range of timescales is necessary to develop a mechanistic understanding of the global carbon cycle that will enable prediction of future changes. Here, we combine NOAA cooperative global air sampling network CO2 observations, remote sensing data, and a flux perturbation model to quantify the feedbacks between interannual variability in physical climate and the atmospheric CO2 growth rate. In particular, we focus on the differences between the 1997/1998 El Niño and the 2015/2016 El Niño during which atmospheric CO2 increased at an unprecedented rate. The flux perturbation model was trained on data from 1997 to 2012, and then used to predict regional atmospheric CO2 growth rate anomalies for the period from 2013 through 2016. Given gridded temperature anomalies from the Hadley Center's Climate Research Unit (CRU), precipitation anomalies from the Global Precipitation Climatology Project (GPCP), and fire emissions from the Global Fire Emissions Database (GFEDv4s), the model was able to the reproduce regional growth rate variations observed at marine boundary layer stations in the NOAA network, including the rapid CO2 growth rate in 2015/2016. The flux perturbation model output suggests that the carbon cycle responses differed for1997 and 2015 El Niño periods, with tropical precipitation anomalies causing a much larger net flux of CO2 to the atmosphere during the latter period, while direct fire emissions dominated the former. The flux perturbation model also suggests that high temperature stress in the Northern Hemisphere extratropics contributed almost one-third of the CO2 growth rate enhancement during the 2015 El Niño. We use satellite-based metrics for atmospheric column CO2, vegetation, and moisture to corroborate the regional El Niño impacts from the flux perturbation model. Finally, we discuss how these observational results and independent data on ocean air-sea flux anomalies, couched in an empirical model, may be useful for evaluating the fidelity of mechanistic land models.

Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed

USGS Publications Warehouse

Moyer, Douglas; Hirsch, Robert M.; Hyer, Kenneth

2012-01-01

Nutrient and sediment fluxes and changes in fluxes over time are key indicators that water resource managers can use to assess the progress being made in improving the structure and function of the Chesapeake Bay ecosystem. The U.S. Geological Survey collects annual nutrient (nitrogen and phosphorus) and sediment flux data and computes trends that describe the extent to which water-quality conditions are changing within the major Chesapeake Bay tributaries. Two regression-based approaches were compared for estimating annual nutrient and sediment fluxes and for characterizing how these annual fluxes are changing over time. The two regression models compared are the traditionally used ESTIMATOR and the newly developed Weighted Regression on Time, Discharge, and Season (WRTDS). The model comparison focused on answering three questions: (1) What are the differences between the functional form and construction of each model? (2) Which model produces estimates of flux with the greatest accuracy and least amount of bias? (3) How different would the historical estimates of annual flux be if WRTDS had been used instead of ESTIMATOR? One additional point of comparison between the two models is how each model determines trends in annual flux once the year-to-year variations in discharge have been determined. All comparisons were made using total nitrogen, nitrate, total phosphorus, orthophosphorus, and suspended-sediment concentration data collected at the nine U.S. Geological Survey River Input Monitoring stations located on the Susquehanna, Potomac, James, Rappahannock, Appomattox, Pamunkey, Mattaponi, Patuxent, and Choptank Rivers in the Chesapeake Bay watershed. Two model characteristics that uniquely distinguish ESTIMATOR and WRTDS are the fundamental model form and the determination of model coefficients. ESTIMATOR and WRTDS both predict water-quality constituent concentration by developing a linear relation between the natural logarithm of observed constituent concentration and three explanatory variables—the natural log of discharge, time, and season. ESTIMATOR uses two additional explanatory variables—the square of the log of discharge and time-squared. Both models determine coefficients for variables for a series of estimation windows. ESTIMATOR establishes variable coefficients for a series of 9-year moving windows; all observed constituent concentration data within the 9-year window are used to establish each coefficient. Conversely, WRTDS establishes variable coefficients for each combination of discharge and time using only observed concentration data that are similar in time, season, and discharge to the day being estimated. As a result of these distinguishing characteristics, ESTIMATOR reproduces concentration-discharge relations that are closely approximated by a quadratic or linear function with respect to both the log of discharge and time. Conversely, the linear model form of WRTDS coupled with extensive model windowing for each combination of discharge and time allows WRTDS to reproduce observed concentration-discharge relations that are more sinuous in form. Another distinction between ESTIMATOR and WRTDS is the reporting of uncertainty associated with the model estimates of flux and trend. ESTIMATOR quantifies the standard error of prediction associated with the determination of flux and trends. The standard error of prediction enables the determination of the 95-percent confidence intervals for flux and trend as well as the ability to test whether the reported trend is significantly different from zero (where zero equals no trend). Conversely, WRTDS is unable to propagate error through the many (over 5,000) models for unique combinations of flow and time to determine a total standard error. As a result, WRTDS flux estimates are not reported with confidence intervals and a level of significance is not determined for flow-normalized fluxes. The differences between ESTIMATOR and WRTDS, with regard to model form and determination of model coefficients, have an influence on the determination of nutrient and sediment fluxes and associated changes in flux over time as a result of management activities. The comparison between the model estimates of flux and trend was made for combinations of five water-quality constituents at nine River Input Monitoring stations. The major findings with regard to nutrient and sediment fluxes are as follows: (1)WRTDS produced estimates of flux for all combinations that were more accurate, based on reduction in root mean squared error, than flux estimates from ESTIMATOR; (2) for 67 percent of the combinations, WRTDS and ESTIMATOR both produced estimates of flux that were minimally biased compared to observed fluxes(flux bias = tendency to over or underpredict flux observations); however, for 33 percent of the combinations, WRTDS produced estimates of flux that were considerably less biased (by at least 10 percent) than flux estimates from ESTIMATOR; (3) the average percent difference in annual fluxes generated by ESTIMATOR and WRTDS was less than 10 percent at 80 percent of the combinations; and (4) the greatest differences related to flux bias and annual fluxes all occurred for combinations where the pattern in observed concentration-discharge relation was sinuous (two points of inflection) rather than linear or quadratic (zero or one point of inflection). The major findings with regard to trends are as follows: (1) both models produce water-quality trends that have factored in the year-to-year variations in flow; (2) trends in water-quality condition are represented by ESTIMATOR as a trend in flow-adjusted concentration and by WRTDS as a flow normalized flux; (3) for 67 percent of the combinations with trend estimates, the WRTDS trends in flow-normalized flux are in the same direction and magnitude to the ESTIMATOR trends in flow-adjusted concentration, and at the remaining 33 percent the differences in trend magnitude and direction are related to fundamental differences between concentration and flux; and (4) the majority (85 percent) of the total nitrogen, nitrate, and orthophosphorus combinations exhibited long-term (1985 to 2010) trends in WRTDS flow-normalized flux that indicate improvement or reduction in associated flux and the majority (83 percent) of the total phosphorus (from 1985 to 2010) and suspended sediment (from 2001 to 2010) combinations exhibited trends in WRTDS flow-normalized flux that indicate degradation or increases in the flux delivered.

CSMP (Continuous System Modeling Program) modeling of brushless DC motors

NASA Astrophysics Data System (ADS)

Thomas, S. M.

1984-09-01

Recent improvements in rare earth magnets have made it possible to construct strong, lightweight, high horsepower DC motors. This has occasioned a reassessment of electromechanical actuators as alternatives to comparable pneumatic and hydraulic systems for use in flight control actuators for tactical missiles. This thesis develops a low-order mathematical model for the simulation and analysis of brushless DC motor performance. This model is implemented in CSMP language. It is used to predict such motor performance curves as speed, current and power versus torque. Electronic commutation based on Hall effect sensor positional feedback is simulated. Steady state motor behavior is studied under both constant and variable air gap flux conditions. The variable flux takes two different forms. In the first case, the flux is varied as a simple sinusoid. In the second case, the flux is varied as the sum of a sinusoid and one of its harmonics.

Analysis of edge stability for models of heat flux width

DOE PAGES

Makowski, Michael A.; Lasnier, Charles J.; Leonard, Anthony W.; ...

2017-05-12

Detailed measurements of the n e, and T e, and T i profiles in the vicinity of the separatrix of ELMing H-mode discharges have been used to examine plasma stability at the extreme edge of the plasma and assess stability dependent models of the heat flux width. The results are strongly contrary to the critical gradient model, which posits that a ballooning instability determines a gradient scale length related to the heat flux width. The results of this analysis are not sensitive to the choice of location to evaluate stability. Significantly, it is also found that the results are completelymore » consistent with the heuristic drift model for the heat flux width. Here the edge pressure gradient scales with plasma density and is proportional to the pressure gradient inferred from the equilibrium in accordance with the predictions of that theory.« less

Computational Platform for Flux Analysis Using 13C-Label Tracing- Phase I SBIR Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Dien, Stephen J.

Isotopic label tracing is a powerful experimental technique that can be combined with metabolic models to quantify metabolic fluxes in an organism under a particular set of growth conditions. In this work we constructed a genome-scale metabolic model of Methylobacterium extorquens, a facultative methylotroph with potential application in the production of useful chemicals from methanol. A series of labeling experiments were performed using 13C-methanol, and the resulting distribution of labeled carbon in the proteinogenic amino acids was determined by mass spectrometry. Algorithms were developed to analyze this data in context of the metabolic model, yielding flux distributions for wild-type andmore » several engineered strains of M. extorquens. These fluxes were compared to those predicted by model simulation alone, and also integrated with microarray data to give an improved understanding of the metabolic physiology of this organism.« less

Constraints on dark matter models from a Fermi LAT search for high-energy cosmic-ray electrons from the Sun

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ajello, M.; Atwood, W. B.; Baldini, L.

During its first year of data taking, the Large Area Telescope (LAT) onboard the Fermi Gamma-Ray Space Telescope has collected a large sample of high-energy cosmic-ray electrons and positrons (CREs). We present the results of a directional analysis of the CRE events, in which we searched for a flux excess correlated with the direction of the Sun. Two different and complementary analysis approaches were implemented, and neither yielded evidence of a significant CRE flux excess from the Sun. Here, we derive upper limits on the CRE flux from the Sun’s direction, and use these bounds to constrain two classes ofmore » dark matter models which predict a solar CRE flux: (1) models in which dark matter annihilates to CREs via a light intermediate state, and (2) inelastic dark matter models in which dark matter annihilates to CREs.« less

Constraints on dark matter models from a Fermi LAT search for high-energy cosmic-ray electrons from the Sun

DOE PAGES

Ajello, M.; Atwood, W. B.; Baldini, L.; ...

2011-08-15

During its first year of data taking, the Large Area Telescope (LAT) onboard the Fermi Gamma-Ray Space Telescope has collected a large sample of high-energy cosmic-ray electrons and positrons (CREs). We present the results of a directional analysis of the CRE events, in which we searched for a flux excess correlated with the direction of the Sun. Two different and complementary analysis approaches were implemented, and neither yielded evidence of a significant CRE flux excess from the Sun. Here, we derive upper limits on the CRE flux from the Sun’s direction, and use these bounds to constrain two classes ofmore » dark matter models which predict a solar CRE flux: (1) models in which dark matter annihilates to CREs via a light intermediate state, and (2) inelastic dark matter models in which dark matter annihilates to CREs.« less

An improved empirical model of electron and ion fluxes at geosynchronous orbit based on upstream solar wind conditions

DOE PAGES

Denton, M. H.; Henderson, M. G.; Jordanova, V. K.; ...

2016-07-01

In this study, a new empirical model of the electron fluxes and ion fluxes at geosynchronous orbit (GEO) is introduced, based on observations by Los Alamos National Laboratory (LANL) satellites. The model provides flux predictions in the energy range ~1 eV to ~40 keV, as a function of local time, energy, and the strength of the solar wind electric field (the negative product of the solar wind speed and the z component of the magnetic field). Given appropriate upstream solar wind measurements, the model provides a forecast of the fluxes at GEO with a ~1 h lead time. Model predictionsmore » are tested against in-sample observations from LANL satellites and also against out-of-sample observations from the Compact Environmental Anomaly Sensor II detector on the AMC-12 satellite. The model does not reproduce all structure seen in the observations. However, for the intervals studied here (quiet and storm times) the normalized root-mean-square deviation < ~0.3. It is intended that the model will improve forecasting of the spacecraft environment at GEO and also provide improved boundary/input conditions for physical models of the magnetosphere.« less

Sensitivity of subtropical wetland CH4 flux predictions to inundation parameterizations: A case study over the southeastern U.S.

NASA Astrophysics Data System (ADS)

Resovsky, A.; Yang, Z. L.

2015-12-01

Methane (CH4) is an important greenhouse gas, and the predominant source of natural atmospheric CH4 globally is its production in wetland soils. Wetlands and marshes in the southeastern U.S. comprise over 40 million acres of land and thus represent a significant component of the global climate system. CH4 contributions from these and other subtropical systems remain difficult to quantify, however. Existing field measurements are lacking in both spatial and temporal coverage, inhibiting efforts to produce regional estimates through upscaling. Top-down constraints on emissions have been generated using satellite remote sensing retrievals of column CH4 (e.g., Frankenberg et al., 2005, 2008, Bergamaschi et al., 2007, 2013, Bloom et al., 2010, Wecht et al., 2014), but such approaches typically require preexisting emissions estimates to discern individual source contributions. Land Surface Models (LSMs) have the potential to produce realistic results, but such predictions rely on accurate representations of sub-grid scale processes responsible for emissions. Since net fluxes are governed by complex interactions between local environmental and biogeochemical factors including water table position, soil temperature, soil substrate availability and vegetation type, reliable flux simulations depend not only upon how such processes are resolved but how skillfully the land surface state itself is predicted by a given model. Here, we examine simulations using CLM4Me, a CH4 biogeochemistry model run within CESM, and compare results to recently compiled flux estimations from satellite remote sensing data. We then examine how seasonal CH4 flux simulations in CLM4Me are affected by alternative parameterizations of inundated land fraction. A global inundation dataset is calculated using DYPTOP, a newly-developed TOPMODEL implementation specifically designed to simulate the dynamics of wetland spatial distribution. We find evidence that DYPTOP may improve wetland CH4 flux predictions over subtropical regions in CLM4.5, and propose a computationally efficient framework for fine-scale tuning of this scheme to more accurately represent the role of subtropical and temperate wetlands in global climate projections.

Tractable flux-driven temperature, density, and rotation profile evolution with the quasilinear gyrokinetic transport model QuaLiKiz

NASA Astrophysics Data System (ADS)

Citrin, J.; Bourdelle, C.; Casson, F. J.; Angioni, C.; Bonanomi, N.; Camenen, Y.; Garbet, X.; Garzotti, L.; Görler, T.; Gürcan, O.; Koechl, F.; Imbeaux, F.; Linder, O.; van de Plassche, K.; Strand, P.; Szepesi, G.; Contributors, JET

2017-12-01

Quasilinear turbulent transport models are a successful tool for prediction of core tokamak plasma profiles in many regimes. Their success hinges on the reproduction of local nonlinear gyrokinetic fluxes. We focus on significant progress in the quasilinear gyrokinetic transport model QuaLiKiz (Bourdelle et al 2016 Plasma Phys. Control. Fusion 58 014036), which employs an approximated solution of the mode structures to significantly speed up computation time compared to full linear gyrokinetic solvers. Optimisation of the dispersion relation solution algorithm within integrated modelling applications leads to flux calculations × {10}6-7 faster than local nonlinear simulations. This allows tractable simulation of flux-driven dynamic profile evolution including all transport channels: ion and electron heat, main particles, impurities, and momentum. Furthermore, QuaLiKiz now includes the impact of rotation and temperature anisotropy induced poloidal asymmetry on heavy impurity transport, important for W-transport applications. Application within the JETTO integrated modelling code results in 1 s of JET plasma simulation within 10 h using 10 CPUs. Simultaneous predictions of core density, temperature, and toroidal rotation profiles for both JET hybrid and baseline experiments are presented, covering both ion and electron turbulence scales. The simulations are successfully compared to measured profiles, with agreement mostly in the 5%-25% range according to standard figures of merit. QuaLiKiz is now open source and available at www.qualikiz.com.

Comparison of Meteoroid Flux Models for Near Earth Space

NASA Technical Reports Server (NTRS)

Drolshagen, G.; Liou, J.-C.; Dikarev, V.; Landgraf, M.; Krag, H.; Kuiper, W.

2007-01-01

Over the last decade several new models for the sporadic interplanetary meteoroid flux have been developed. These include the Meteoroid Engineering Model (MEM), the Divine-Staubach model and the Interplanetary Meteoroid Engineering Model (IMEM). They typically cover mass ranges from 10-12 g (or lower) to 1 g and are applicable for model specific sun distance ranges between 0.2 A.U. and 10 A.U. Near 1 A.U. averaged fluxes (over direction and velocities) for all these models are tuned to the well established interplanetary model by Gr?n et. al. However, in many respects these models differ considerably. Examples are the velocity and directional distributions and the assumed meteoroid sources. In this paper flux predictions by the various models to Earth orbiting spacecraft are compared. Main differences are presented and analysed. The persisting differences even for near Earth space can be seen as surprising in view of the numerous ground based (optical, radar) and in-situ (captured IDPs, in-situ detectors and analysis of retrieved hardware) measurements and simulations. Remaining uncertainties and potential additional studies to overcome the existing model discrepancies are discussed.

Progress towards a more predictive model for hohlraum radiation drive and symmetry

NASA Astrophysics Data System (ADS)

Jones, O. S.; Suter, L. J.; Scott, H. A.; Barrios, M. A.; Farmer, W. A.; Hansen, S. B.; Liedahl, D. A.; Mauche, C. W.; Moore, A. S.; Rosen, M. D.; Salmonson, J. D.; Strozzi, D. J.; Thomas, C. A.; Turnbull, D. P.

2017-05-01

For several years, we have been calculating the radiation drive in laser-heated gold hohlraums using flux-limited heat transport with a limiter of 0.15, tabulated values of local thermodynamic equilibrium gold opacity, and an approximate model for not in a local thermodynamic equilibrium (NLTE) gold emissivity (DCA_2010). This model has been successful in predicting the radiation drive in vacuum hohlraums, but for gas-filled hohlraums used to drive capsule implosions, the model consistently predicts too much drive and capsule bang times earlier than measured. In this work, we introduce a new model that brings the calculated bang time into better agreement with the measured bang time. The new model employs (1) a numerical grid that is fully converged in space, energy, and time, (2) a modified approximate NLTE model that includes more physics and is in better agreement with more detailed offline emissivity models, and (3) a reduced flux limiter value of 0.03. We applied this model to gas-filled hohlraum experiments using high density carbon and plastic ablator capsules that had hohlraum He fill gas densities ranging from 0.06 to 1.6 mg/cc and hohlraum diameters of 5.75 or 6.72 mm. The new model predicts bang times to within ±100 ps for most experiments with low to intermediate fill densities (up to 0.85 mg/cc). This model predicts higher temperatures in the plasma than the old model and also predicts that at higher gas fill densities, a significant amount of inner beam laser energy escapes the hohlraum through the opposite laser entrance hole.

Analysis of the Daya Bay Reactor Antineutrino Flux Changes with Fuel Burnup

DOE PAGES

Hayes, A. C.; Ricard-McCutchan, E. A.; Jungman, Gerard; ...

2018-01-12

We investigate the recent Daya Bay results on the changes in the antineutrino flux and spectrum with the burnup of the reactor fuel. We find that the discrepancy between current model predictions and the Daya Bay results can be traced to the original measured 235U/ 239Pu ratio of the fission beta spectra that were used as a base for the expected antineutrino fluxes. An analysis of the antineutrino spectra that is based on a summation over all fission fragment beta-decays, using nuclear database input, explains all of the features seen in the Daya Bay evolution data. However, this summation methodmore » still predicts an anomaly. Thus, we conclude that there is currently not enough information to use the antineutrino flux changes to rule out the possible existence of sterile neutrinos.« less

Measurement of Solar pp-neutrino flux with Borexino: results and implications

NASA Astrophysics Data System (ADS)

Smirnov, O. Yu; Agostini, M.; Appel, S.; Bellini, G.; Benziger, J.; Bick, D.; Bonfini, G.; Bravo, D.; Caccianiga, B.; Calaprice, F.; Caminata, A.; Cavalcante, P.; Chepurnov, A.; D'Angelo, D.; Davini, S.; Derbin, A.; Di Noto, L.; Drachnev, I.; Etenko, A.; Fomenko, K.; Franco, D.; Gabriele, F.; Galbiati, C.; Ghiano, C.; Giammarchi, M.; Goeger-Neff, M.; Goretti, A.; Gromov, M.; Hagner, C.; Hungerford, E.; Ianni, Aldo; Ianni, Andrea; Jedrzejczak, K.; Kaiser, M.; Kobychev, V.; Korablev, D.; Korga, G.; Kryn, D.; Laubenstein, M.; Lehnert, B.; Litvinovich, E.; Lombardi, F.; Lombardi, P.; Ludhova, L.; Lukyanchenko, G.; Machulin, O.; Manecki, S.; Maneschg, W.; Marcocci, S.; Meroni, E.; Meyer, M.; Miramonti, L.; Misiaszek, M.; Montuschi, M.; Mosteiro, P.; Muratova, V.; Neumair, B.; Oberauer, L.; Obolensky, M.; Ortica, F.; Pallavicini, M.; Papp, L.; Perasso, L.; Pocar, A.; Ranucci, G.; Razeto, A.; Re, A.; Romani, A.; Roncin, R.; Rossi, N.; Schönert, S.; Semenov, D.; Simgen, H.; Skorokhvatov, M.; Sotnikov, A.; Sukhotin, S.; Suvorov, Y.; Tartaglia, R.; Testera, G.; Thurn, J.; Toropova, M.; Unzhakov, E.; Vishneva, A.; Vogelaar, R. B.; von Feilitzsch, F.; Wang, H.; Weinz, S.; Winter, J.; Wojcik, M.; Wurm, M.; Yokley, Z.; Zaimidoroga, O.; Zavatarelli, S.; Zuber, K.; Zuzel, G.

2016-02-01

Measurement of the Solar pp-neutrino flux completed the measurement of Solar neutrino fluxes from the pp-chain of reactions in Borexino experiment. The result is in agreement with the prediction of the Standard Solar Model and the MSW/LMA oscillation scenario. A comparison of the total neutrino flux from the Sun with Solar luminosity in photons provides a test of the stability of the Sun on the 105 years time scale, and sets a strong limit on the power production by the unknown energy sources in the Sun.

MAGNETIC FLUX TRANSPORT AND THE LONG-TERM EVOLUTION OF SOLAR ACTIVE REGIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ugarte-Urra, Ignacio; Upton, Lisa; Warren, Harry P.

2015-12-20

With multiple vantage points around the Sun, Solar Terrestrial Relations Observatory (STEREO) and Solar Dynamics Observatory imaging observations provide a unique opportunity to view the solar surface continuously. We use He ii 304 Å data from these observatories to isolate and track ten active regions and study their long-term evolution. We find that active regions typically follow a standard pattern of emergence over several days followed by a slower decay that is proportional in time to the peak intensity in the region. Since STEREO does not make direct observations of the magnetic field, we employ a flux-luminosity relationship to infermore » the total unsigned magnetic flux evolution. To investigate this magnetic flux decay over several rotations we use a surface flux transport model, the Advective Flux Transport model, that simulates convective flows using a time-varying velocity field and find that the model provides realistic predictions when information about the active region's magnetic field strength and distribution at peak flux is available. Finally, we illustrate how 304 Å images can be used as a proxy for magnetic flux measurements when magnetic field data is not accessible.« less

Time-varying Entry Heating Profile Replication with a Rotating Arc Jet Test Article

NASA Technical Reports Server (NTRS)

Grinstead, Jay Henderson; Venkatapathy, Ethiraj; Noyes, Eric A.; Mach, Jeffrey J.; Empey, Daniel M.; White, Todd R.

2014-01-01

A new approach for arc jet testing of thermal protection materials at conditions approximating the time-varying conditions of atmospheric entry was developed and demonstrated. The approach relies upon the spatial variation of heat flux and pressure over a cylindrical test model. By slowly rotating a cylindrical arc jet test model during exposure to an arc jet stream, each point on the test model will experience constantly changing applied heat flux. The predicted temporal profile of heat flux at a point on a vehicle can be replicated by rotating the cylinder at a prescribed speed and direction. An electromechanical test model mechanism was designed, built, and operated during an arc jet test to demonstrate the technique.

Evaluation of simulated biospheric carbon dioxide fluxes and atmospheric concentrations using global in situ observations

NASA Astrophysics Data System (ADS)

Philip, S.; Johnson, M. S.; Potter, C. S.; Genovese, V. B.

2016-12-01

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emission sources and biospheric sources/sinks. Global biospheric fluxes of CO2 are controlled by complex processes facilitating the exchange of carbon between terrestrial ecosystems and the atmosphere. These processes which play a key role in these terrestrial ecosystem-atmosphere carbon exchanges are currently not fully understood, resulting in large uncertainties in the quantification of biospheric CO2 fluxes. Current models with these inherent deficiencies have difficulties simulating the global carbon cycle with high accuracy. We are developing a new modeling platform, GEOS-Chem-CASA by integrating the year-specific NASA-CASA (National Aeronautics and Space Administration - Carnegie Ames Stanford Approach) biosphere model with the GEOS-Chem (Goddard Earth Observation System-Chemistry) chemical transport model to improve the simulation of atmosphere-terrestrial ecosystem carbon exchange. We use NASA-CASA to explicitly represent the exchange of CO2 between terrestrial ecosystem and atmosphere by replacing the baseline GEOS-Chem land net CO2 flux and forest biomass burning CO2 emissions. We will present the estimation and evaluation of these "bottom-up" land CO2 fluxes, simulated atmospheric mixing ratios, and forest disturbance changes over the last decade. In addition, we will present our initial comparison of atmospheric column-mean dry air mole fraction of CO2 predicted by the model and those retrieved from NASA's OCO-2 (Orbiting Carbon Observatory-2) satellite instrument and model-predicted surface CO2 mixing ratios with global in situ observations. This evaluation is the first step necessary for our future work planned to constrain the estimates of biospheric carbon fluxes through "top-down" inverse modeling, which will improve our understanding of the processes controlling atmosphere-terrestrial ecosystem greenhouse gas exchanges, especially over regions which lack in situ observations.

B33C-0612: Evaluation of Simulated Biospheric Carbon Dioxide Fluxes and Atmospheric Concentrations Using Global in Situ Observations

NASA Technical Reports Server (NTRS)

Philip, Sajeev; Johnson, Matthew S.; Potter, Christopher S.; Genovese, Vanessa

2016-01-01

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emission sources and biospheric sources/sinks. Global biospheric fluxes of CO2 are controlled by complex processes facilitating the exchange of carbon between terrestrial ecosystems and the atmosphere. These processes which play a key role in these terrestrial ecosystem-atmosphere carbon exchanges are currently not fully understood, resulting in large uncertainties in the quantification of biospheric CO2 fluxes. Current models with these inherent deficiencies have difficulties simulating the global carbon cycle with high accuracy. We are developing a new modeling platform, GEOS-Chem-CASA by integrating the year-specific NASA-CASA (National Aeronautics and Space Administration - Carnegie Ames Stanford Approach) biosphere model with the GEOS-Chem (Goddard Earth Observation System-Chemistry) chemical transport model to improve the simulation of atmosphere-terrestrial ecosystem carbon exchange. We use NASA-CASA to explicitly represent the exchange of CO2 between terrestrial ecosystem and atmosphere by replacing the baseline GEOS-Chem land net CO2 flux and forest biomass burning CO2 emissions. We will present the estimation and evaluation of these "bottom-up" land CO2 fluxes, simulated atmospheric mixing ratios, and forest disturbance changes over the last decade. In addition, we will present our initial comparison of atmospheric column-mean dry air mole fraction of CO2 predicted by the model and those retrieved from NASA's OCO-2 (Orbiting Carbon Observatory-2) satellite instrument and model-predicted surface CO2 mixing ratios with global in situ observations. This evaluation is the first step necessary for our future work planned to constrain the estimates of biospheric carbon fluxes through "top-down" inverse modeling, which will improve our understanding of the processes controlling atmosphere-terrestrial ecosystem greenhouse gas exchanges, especially over regions which lack in situ observations.

Assessing river-groundwater exchange fluxes of the Wairau River, New Zealand

NASA Astrophysics Data System (ADS)

Wilson, Scott; Woehling, Thomas; Davidson, Peter

2014-05-01

Allocation limits in river-recharged aquifers have traditionally been based on static observations of river gains and losses undertaken when river flow is low. This approach to setting allocation limits does not consider the dynamic relationship between river flows and groundwater levels. Predicting groundwater availability based on a better understanding of coupled river - aquifer systems opens the possibility for dynamic groundwater allocation approaches. Numerical groundwater models are most commonly used for regional scale allocation assessments. Using these models for predicting future system states is challenging, particularly under changing management and climate scenarios. The large degree of uncertainty associated with these predictions is caused by insufficient knowledge about the heterogeneity of subsurface flow characteristics, ineffective monitoring designs, and the inability to confidently predict the spatially and temporally varying river - groundwater exchange fluxes. These uncertainties are characteristic to many coupled surface water - groundwater systems worldwide. Braided river systems, however, create additional challenges due to their highly dynamic morphological character and mobile beds which also make river flow measurements extremely difficult. This study focuses on the characterization of river - groundwater exchange fluxes along a section of the Wairau River in the Northwest of the South Island of New Zealand. The braided river recharges the Wairau Aquifer which is an important source for irrigation and municipal water requirements of the city of Blenheim. The Wairau Aquifer is hosted by the highly permeable Rapaura Formation gravels that extend to a depth of about 20 to 30 m. However, the overall thickness of the alluvial sequence forming the Wairau Plain may be up to 500 m. The landuse in the area is mainly grapes but landsurface recharge to the aquifer is considered to be considerably smaller than the recharge from the Wairau river. This study aims at the assessment of river-groundwater exchange fluxes and presents first results from data mining and analysis of river flow records, stage gaugings, groundwater head data, pumping test, and the sampling of spring flows. In addition, a methodology is presented that will allow the prediction of transient river exchange fluxes by using a Modflow model, global optimisation techniques, and techniques for quantifying predictive uncertainty which have been recently developed (Wöhling et al 2013). A long-term goal of the study is the reduction of predictive uncertainty of model predictions by optimal design of sensor networks as well as the assessment of this utility by different observation types. Preliminary results indicate that about 7 cumec from the Wairau River is recharged to the aquifer under low flow conditions. A similar volume of groundwater re-emerges as springs where groundwater is forced upwards by the confining Dillons Point Formation. References Wöhling, Th., Gosses, M.J., Leyes Pérez, M., Geiges, A., Moore, C.R., Osenbrück, K., Scott, D.M. (2013). Optimizing monitoring design to increase predictive reliability of groundwater flow models at different scales. Geophysical Research Abstracts Vol. 15, EGU2013-3981, EGU General Assembly 2013.

Analysis of riverine suspended particulate matter fluxes (Gulf of Lion, Mediterranean Sea) using a synergy of ocean color observations with a 3-D hydrodynamic sediment transport model

NASA Astrophysics Data System (ADS)

Le Fouest, Vincent; Chami, Malik; Verney, Romaric

2015-02-01

The export of riverine suspended particulate matter (SPM) in the coastal ocean has major implications for the biogeochemical cycles. In the Mediterranean Sea (France), the Rhone River inputs of SPM into the Gulf of Lion (GoL) are highly variable in time, which severely impedes the assessment of SPM fluxes. The objectives of this study are (i) to investigate the prediction of the land-to-ocean flux of SPM using the complementarity (i.e., synergy) between a hydrodynamic sediment transport model and satellite observations, and (ii) to analyze the spatial distribution of the SPM export. An original approach that combines the MARS-3D model with satellite ocean color data is proposed. Satellite-derived SPM and light penetration depth are used to initialize MARS-3D and to validate its predictions. A sensitivity analysis is performed to quantify the impact of riverine SPM size composition and settling rate on the horizontal export of SPM. The best agreement between the model and the satellite in terms of SPM spatial distribution and export is obtained for two conditions: (i) when the relative proportion of "heavy and fast" settling particles significantly increases relative to the "light and slow" ones, and (ii) when the settling rate of heavy and light SPM increases by fivefold. The synergy between MARS-3D and the satellite data improved the SPM flux predictions by 48% near the Rhone River mouth. Our results corroborate the importance of implementing satellite observations within initialization procedures of ocean models since data assimilation techniques may fail for river floods showing strong seasonal variability.

Discovering the Importance of Bi-directional Water Fluxes in Leaves

NASA Astrophysics Data System (ADS)

Kayler, Z. E.; Saurer, M.; Siegwolf, R.

2007-12-01

The stable isotope ratio 18O/16O is used for constraining climate change models, partitioning ecosystem water fluxes and for studies of plant ecophysiology. Leaf water enrichment is an essential starting point for each of these applications. In order to obtain a complete picture of the role leaf water plays, not only the 18O values from leaf water but also the signature of transpired water must be accurately predicted for plants under varying environmental conditions. We used a novel chamber approach using highly depleted water (-330 ‰) as a vapor source to leaves of the velvet bean (Mucuna pruriens). We used a Walz gas exchange system consisting of a chamber that is controlled for humidity, light, and temperature. Water and carbon dioxide fluxes were measured by an infrared gas analyzer and chamber vapor was collected in cold traps chilled to - 60°C. Three leaves were collected after 2 hours to insure isotopic steady-state followed by leaf water extraction and isotope analysis. From this experiment we were able to measure the outward flux of soil source water and the inward flux of ambient vapor over a range of environments that varied in relative humidity (80%, 45%, 20%), light (50, 1000 μmolm-2s-1) and CO2 (50, 800 ppm). Leaf water isotopic values were below the source water values reflecting the influx of the labeled vapor. The degree to which leaf water values were depleted was strongly related to the relative humidity. The Craig-Gordon model overestimated depletion of leaf water under high relative humidity and predictions were improved with the Péclet correction. However, our initial analysis indicates that these models may not fully account for stomatal conductance in predicting leaf water isotopic values.

Low energy intake plus low energy expenditure (low energy flux), not energy surfeit, predicts future body fat gain12

PubMed Central

Yokum, Sonja; Stice, Eric

2016-01-01

Background: There is a paucity of studies that have prospectively tested the energy surfeit theory of obesity with the use of objectively estimated energy intake and energy expenditure in humans. An alternative theory is that homeostatic regulation of body weight is more effective when energy intake and expenditure are both high (high energy flux), implying that low energy flux should predict weight gain. Objective: We aimed to examine the predictive relations of energy balance and energy flux to future weight gain and tested whether results were replicable in 2 independent samples. Design: Adolescents (n = 154) and college-aged women (n = 75) underwent 2-wk objective doubly labeled water, resting metabolic rate, and percentage of body fat measures at baseline. Percentage of body fat was measured annually for 3 y of follow-up for the adolescent sample and for 2 y of follow-up for the young adult sample. Results: Low energy flux, but not energy surfeit, predicted future increases in body fat in both studies. Furthermore, high energy flux appeared to prevent fat gain in part because it was associated with a higher resting metabolic rate. Conclusion: Counter to the energy surfeit model of obesity, results suggest that increasing energy expenditure may be more effective for reducing body fat than caloric restriction, which is currently the treatment of choice for obesity. This trial was registered at clinicaltrials.gov as NCT02084836. PMID:27169833

Low energy intake plus low energy expenditure (low energy flux), not energy surfeit, predicts future body fat gain.

PubMed

Hume, David John; Yokum, Sonja; Stice, Eric

2016-06-01

There is a paucity of studies that have prospectively tested the energy surfeit theory of obesity with the use of objectively estimated energy intake and energy expenditure in humans. An alternative theory is that homeostatic regulation of body weight is more effective when energy intake and expenditure are both high (high energy flux), implying that low energy flux should predict weight gain. We aimed to examine the predictive relations of energy balance and energy flux to future weight gain and tested whether results were replicable in 2 independent samples. Adolescents (n = 154) and college-aged women (n = 75) underwent 2-wk objective doubly labeled water, resting metabolic rate, and percentage of body fat measures at baseline. Percentage of body fat was measured annually for 3 y of follow-up for the adolescent sample and for 2 y of follow-up for the young adult sample. Low energy flux, but not energy surfeit, predicted future increases in body fat in both studies. Furthermore, high energy flux appeared to prevent fat gain in part because it was associated with a higher resting metabolic rate. Counter to the energy surfeit model of obesity, results suggest that increasing energy expenditure may be more effective for reducing body fat than caloric restriction, which is currently the treatment of choice for obesity. This trial was registered at clinicaltrials.gov as NCT02084836. © 2016 American Society for Nutrition.

Evaluation of Lower East Fork Poplar Creek Mercury Sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watson, David B.; Brooks, Scott C.; Mathews, Teresa J.

This report summarizes a 3-year research project undertaken to better understand the nature and magnitude of mercury (Hg) fluxes in East Fork Poplar Creek (EFPC). This project addresses the requirements of Action Plan 1 in the 2011 Oak Ridge Reservation-wide Comprehensive Environmental Response, Compensation, and Liability Act Five Year Review (FYR). The Action Plan is designed to address a twofold 2011 FYR issue: (1) new information suggests mobilization of mercury from the upper and lower EFPC streambeds and stream banks is the primary source of mercury export during high-flow conditions, and (2) the current Record of Decision did not addressmore » the entire hydrologic system and creek bank or creek bed sediments. To obtain a more robust watershed-scale understanding of mercury sources and processes in lower EFPC (LEFPC), new field and laboratory studies were coupled with existing data from multiple US Department of Energy programs to develop a dynamic watershed and bioaccumulation model. LEFPC field studies for the project focused primarily on quantification of streambank erosion and an evaluation of mercury dynamics in shallow groundwater adjacent to LEFPC and potential connection to the surface water. The approach to the stream bank study was innovative in using imagery from kayak floats’ surveys from the headwaters to the mouth of EFPC to estimate erosion, coupled with detailed bank soil mercury analyses. The goal of new field assessments and modeling was to generate a more holistic and quantitative understanding of the watershed and the sources, flux, concentration, transformation, and bioaccumulation of inorganic mercury (IHg) and methylmercury (MeHg). Model development used a hybrid approach that dynamically linked a spreadsheet-based physical and chemical watershed model to a systems dynamics, mercury bioaccumulation model for key fish species. The watershed model tracks total Hg and MeHg fluxes and concentrations by examining upstream inputs, floodplain runoff, floodplain leaching, bank soil erosion, and periphyton matrix dynamics. The bioaccumulation model tracks the feeding, growth, and mercury assimilation of representative individual fish through their typical life span using key inputs of fish size, water temperature, and diet. The LEFPC watershed was divided into five modeling reaches, and fluxes and concentrations are assessed at this spatial scale. Following are the key findings of the field and laboratory studies and the watershed and bioaccumulation modeling: • The greatest flux of total mercury (HgT) in LEFPC is related to stormflow transport of Hg-contaminated solids entering the creek because of bank erosion in the upper reaches of the creek. • The second greatest flux originates from upper EFPC (Station 17 representing the exit stream sampling point near the boundary of the Y-12 Complex), and appears to control base flow fluxes. • The observed increase in MeHg concentration and flux from upstream to downstream is related primarily to instream methylation by periphyton and other biological activity. • A meaningful substantial reduction of the HgT flux in LEFPC would require addressing the flux of HgT originating from bank erosion and from Station 17. • Actions to reduce LEFPC floodplain leaching and runoff would not produce much of an impact on HgT or MeHg concentrations or fluxes unless other major sources are eliminated first. This project addresses the Action Plan goal to evaluate the role of LEFPC bank soil sources and to consider the entire EFPC hydrologic system. Model conclusions are dependent on the data available at the time of this assessment. However, a robust understanding and quantification for some mercury-related parameters and relationships is still lacking; there is a continued need for field data collection and modeling improvements. Model predictions should be viewed cautiously, with comparisons of the magnitude of predictions between scenarios being more valid than absolute predictions of concentrations or fluxes. With continued updates and refinement, the watershed-scale model can be a useful, valuable tool for future EFPC research prioritization, technology development, and remedial decision-making.« less

Expanding a dynamic flux balance model of yeast fermentation to genome-scale

PubMed Central

2011-01-01

Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919

New model for burnout prediction in channels of various cross-section

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bobkov, V.P.; Kozina, N.V.; Vinogrado, V.N.

1995-09-01

The model developed to predict a critical heat flux (CHF) in various channels is presented together with the results of data analysis. A model is the realization of relative method of CHF describing based on the data for round tube and on the system of correction factors. The results of data description presented here are for rectangular and triangular channels, annuli and rod bundles.

Cosmic ray antiprotons in closed galaxy model

NASA Technical Reports Server (NTRS)

Protheroe, R.

1981-01-01

The flux of secondary antiprotons expected for the leaky-box model was calculated as well as that for the closed galaxy model of Peters and Westergard (1977). The antiproton/proton ratio observed at several GeV is a factor of 4 higher than the prediction for the leaky-box model but is consistent with that predicted for the closed galaxy model. New low energy data is not consistent with either model. The possibility of a primary antiproton component is discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hay, J.; Schwender, J.

Plant oils are an important renewable resource, and seed oil content is a key agronomical trait that is in part controlled by the metabolic processes within developing seeds. A large-scale model of cellular metabolism in developing embryos of Brassica napus (bna572) was used to predict biomass formation and to analyze metabolic steady states by flux variability analysis under different physiological conditions. Predicted flux patterns are highly correlated with results from prior 13C metabolic flux analysis of B. napus developing embryos. Minor differences from the experimental results arose because bna572 always selected only one sugar and one nitrogen source from themore » available alternatives, and failed to predict the use of the oxidative pentose phosphate pathway. Flux variability, indicative of alternative optimal solutions, revealed alternative pathways that can provide pyruvate and NADPH to plastidic fatty acid synthesis. The nutritional values of different medium substrates were compared based on the overall carbon conversion efficiency (CCE) for the biosynthesis of biomass. Although bna572 has a functional nitrogen assimilation pathway via glutamate synthase, the simulations predict an unexpected role of glycine decarboxylase operating in the direction of NH4+ assimilation. Analysis of the light-dependent improvement of carbon economy predicted two metabolic phases. At very low light levels small reductions in CO2 efflux can be attributed to enzymes of the tricarboxylic acid cycle (oxoglutarate dehydrogenase, isocitrate dehydrogenase) and glycine decarboxylase. At higher light levels relevant to the 13C flux studies, ribulose-1,5-bisphosphate carboxylase activity is predicted to account fully for the light-dependent changes in carbon balance.« less

Controllable morphology of flux avalanches in microstructured superconductors

NASA Astrophysics Data System (ADS)

Motta, M.; Colauto, F.; Vestgârden, J. I.; Fritzsche, J.; Timmermans, M.; Cuppens, J.; Attanasio, C.; Cirillo, C.; Moshchalkov, V. V.; Van de Vondel, J.; Johansen, T. H.; Ortiz, W. A.; Silhanek, A. V.

2014-04-01

The morphology of abrupt bursts of magnetic flux into superconducting films with engineered periodic pinning centers (antidots) has been investigated. Guided flux avalanches of thermomagnetic origin develop a treelike structure, with the main trunk perpendicular to the borders of the sample, while secondary branches follow well-defined directions determined by the geometrical details of the underlying periodic pinning landscape. Strikingly, we demonstrate that in a superconductor with relatively weak random pinning the morphology of such flux avalanches can be fully controlled by proper combinations of lattice symmetry and antidot geometry. Moreover, the resulting flux patterns can be reproduced, to the finest details, by simulations based on a phenomenological thermomagnetic model. In turn, this model can be used to predict such complex structures and to estimate physical variables of more difficult experimental access, such as the local values of temperature and electric field.

Plasma wall sheath contributions to flux retention during the formation of field-reversed configurations

NASA Astrophysics Data System (ADS)

Milroy, R. D.; Slough, J. T.; Hoffman, A. L.

1984-06-01

Flux loss during field reversal on the TRX-1 field-reversed θ pinch is found to be much less than predicted by the inertial model of Green and Newton. This can be explained by a pressure bearing, conducting sheath which naturally forms at the wall and limits the flux loss. A one-dimensional (r-t) magnetohydrodynamic (MHD) numerical model has been used to study the formation and effectiveness of the sheath. The calculations are in excellent agreement with experimental measurements over a wide range of operating parameters. The results indicate that good flux trapping can be achieved through the field reversal phase of FRC formation with much slower external field reversal rates than in current experiments.

Uncertainty in predictions of forest carbon dynamics: separating driver error from model error.

PubMed

Spadavecchia, L; Williams, M; Law, B E

2011-07-01

We present an analysis of the relative magnitude and contribution of parameter and driver uncertainty to the confidence intervals on estimates of net carbon fluxes. Model parameters may be difficult or impractical to measure, while driver fields are rarely complete, with data gaps due to sensor failure and sparse observational networks. Parameters are generally derived through some optimization method, while driver fields may be interpolated from available data sources. For this study, we used data from a young ponderosa pine stand at Metolius, Central Oregon, and a simple daily model of coupled carbon and water fluxes (DALEC). An ensemble of acceptable parameterizations was generated using an ensemble Kalman filter and eddy covariance measurements of net C exchange. Geostatistical simulations generated an ensemble of meteorological driving variables for the site, consistent with the spatiotemporal autocorrelations inherent in the observational data from 13 local weather stations. Simulated meteorological data were propagated through the model to derive the uncertainty on the CO2 flux resultant from driver uncertainty typical of spatially extensive modeling studies. Furthermore, the model uncertainty was partitioned between temperature and precipitation. With at least one meteorological station within 25 km of the study site, driver uncertainty was relatively small ( 10% of the total net flux), while parameterization uncertainty was larger, 50% of the total net flux. The largest source of driver uncertainty was due to temperature (8% of the total flux). The combined effect of parameter and driver uncertainty was 57% of the total net flux. However, when the nearest meteorological station was > 100 km from the study site, uncertainty in net ecosystem exchange (NEE) predictions introduced by meteorological drivers increased by 88%. Precipitation estimates were a larger source of bias in NEE estimates than were temperature estimates, although the biases partly compensated for each other. The time scales on which precipitation errors occurred in the simulations were shorter than the temporal scales over which drought developed in the model, so drought events were reasonably simulated. The approach outlined here provides a means to assess the uncertainty and bias introduced by meteorological drivers in regional-scale ecological forecasting.

Ares I Reaction Control System Propellant Feedline Decontamination Modeling

NASA Technical Reports Server (NTRS)

Pasch, James J.

2010-01-01

The objective of the work presented here is to quantify the effects of purge gas temperature, pressure, and mass flow rate on Hydrazine (Hz) decontamination rates of the Ares I Roll Control System and Reaction Control System. A survey of experts in this field revealed the absence of any decontamination rate prediction models. Three basic decontamination methods were identified for analysis and modeling. These include low pressure eduction, high flow rate purge, and pulse purge. For each method, an approach to predict the Hz mass transfer rate, as a function of system pressure, temperature, and purge gas mass flow rate, is developed based on the applicable physics. The models show that low pressure eduction is two orders of magnitude more effective than the high velocity purge, which in turn is two orders of magnitude more effective than the pure diffusion component of pulse purging of deadheads. Eduction subjects the system to low pressure conditions that promote the extraction of Hz vapors. At 120 F, Hz is saturated at approximately 1 psia. At lower pressures and 120 F, Hz will boil, which is an extremely efficient means to remove liquid Hz. The Hz boiling rate is predicted by equating the rate at which energy is added to the saturated liquid Hz through heaters at the tube outer wall with the energy removed from the liquid through evaporation. Boil-off fluxes were predicted by iterating through the range of local pressures with limits set by the minimum allowed pressure of 0.2 psia and maximum allowed wall temperature of 120 F established by the heaters, which gives a saturation pressure of approximately 1.0 psia. Figure 1 shows the resulting boil-off fluxes as a function of local eduction pressure. As depicted in figure 1, the flux is a strong inverse function of eduction pressure, and that minimizing the eduction pressure maximizes the boil-off flux. Also, higher outer wall temperatures lead to higher boil-off fluxes and allow for boil-off over a greater range of eduction pressures.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2016-12-01

Forest carbon processes are affected by, among other factors, soil moisture, soil temperature, soil nutrients and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve the topographically driven hill-slope land surface heterogeneity or the spatial pattern of nutrient availability. A spatially distributed forest ecosystem model, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while soil nitrogen is transported among model grids via subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation information, while BBGC provides Flux-PIHM with leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). Model results suggest that the vegetation and soil carbon distribution is primarily constrained by nitorgen availability (affected by nitorgen transport via topographically driven subsurface flow), and also constrained by solar radiation and root zone soil moisture. The predicted vegetation and soil carbon distribution generally agrees with the macro pattern observed within the watershed. The coupled ecosystem-hydrologic model provides an important tool to study the impact of topography on watershed carbon processes, as well as the impact of climate change on water resources.

Forecasting Responses of a Northern Peatland Carbon Cycle to Elevated CO2 and a Gradient of Experimental Warming

NASA Astrophysics Data System (ADS)

Jiang, Jiang; Huang, Yuanyuan; Ma, Shuang; Stacy, Mark; Shi, Zheng; Ricciuto, Daniel M.; Hanson, Paul J.; Luo, Yiqi

2018-03-01

The ability to forecast ecological carbon cycling is imperative to land management in a world where past carbon fluxes are no longer a clear guide in the Anthropocene. However, carbon-flux forecasting has not been practiced routinely like numerical weather prediction. This study explored (1) the relative contributions of model forcing data and parameters to uncertainty in forecasting flux- versus pool-based carbon cycle variables and (2) the time points when temperature and CO2 treatments may cause statistically detectable differences in those variables. We developed an online forecasting workflow (Ecological Platform for Assimilation of Data (EcoPAD)), which facilitates iterative data-model integration. EcoPAD automates data transfer from sensor networks, data assimilation, and ecological forecasting. We used the Spruce and Peatland Responses Under Changing Experiments data collected from 2011 to 2014 to constrain the parameters in the Terrestrial Ecosystem Model, forecast carbon cycle responses to elevated CO2 and a gradient of warming from 2015 to 2024, and specify uncertainties in the model output. Our results showed that data assimilation substantially reduces forecasting uncertainties. Interestingly, we found that the stochasticity of future external forcing contributed more to the uncertainty of forecasting future dynamics of C flux-related variables than model parameters. However, the parameter uncertainty primarily contributes to the uncertainty in forecasting C pool-related response variables. Given the uncertainties in forecasting carbon fluxes and pools, our analysis showed that statistically different responses of fast-turnover pools to various CO2 and warming treatments were observed sooner than slow-turnover pools. Our study has identified the sources of uncertainties in model prediction and thus leads to improve ecological carbon cycling forecasts in the future.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sherlock, M.; Brodrick, J. P.; Ridgers, C. P.

Here, we compare the reduced non-local electron transport model developed to Vlasov-Fokker-Planck simulations. Two new test cases are considered: the propagation of a heat wave through a high density region into a lower density gas, and a one-dimensional hohlraum ablation problem. We find that the reduced model reproduces the peak heat flux well in the ablation region but significantly over-predicts the coronal preheat. The suitability of the reduced model for computing non-local transport effects other than thermal conductivity is considered by comparing the computed distribution function to the Vlasov-Fokker-Planck distribution function. It is shown that even when the reduced modelmore » reproduces the correct heat flux, the distribution function is significantly different to the Vlasov-Fokker-Planck prediction. Two simple modifications are considered which improve agreement between models in the coronal region.« less

Sensitivity Analysis of Flux Determination in Heart by H2 18O -provided Labeling Using a Dynamic Isotopologue Model of Energy Transfer Pathways

PubMed Central

Schryer, David W.; Peterson, Pearu; Illaste, Ardo; Vendelin, Marko

2012-01-01

To characterize intracellular energy transfer in the heart, two organ-level methods have frequently been employed: inversion and saturation transfer, and dynamic labeling. Creatine kinase (CK) fluxes obtained by following oxygen labeling have been considerably smaller than the fluxes determined by saturation transfer. It has been proposed that dynamic labeling determines net flux through CK shuttle, whereas saturation transfer measures total unidirectional flux. However, to our knowledge, no sensitivity analysis of flux determination by oxygen labeling has been performed, limiting our ability to compare flux distributions predicted by different methods. Here we analyze oxygen labeling in a physiological heart phosphotransfer network with active CK and adenylate kinase (AdK) shuttles and establish which fluxes determine the labeling state. A mathematical model consisting of a system of ordinary differential equations was composed describing enrichment in each phosphoryl group and inorganic phosphate. By varying flux distributions in the model and calculating the labeling, we analyzed labeling sensitivity to different fluxes in the heart. We observed that the labeling state is predominantly sensitive to total unidirectional CK and AdK fluxes and not to net fluxes. We conclude that measuring dynamic incorporation of into the high-energy phosphotransfer network in heart does not permit unambiguous determination of energetic fluxes with a higher magnitude than the ATP synthase rate when the bidirectionality of fluxes is taken into account. Our analysis suggests that the flux distributions obtained using dynamic labeling, after removing the net flux assumption, are comparable with those from inversion and saturation transfer. PMID:23236266

Estimation of the curvature of the solid liquid interface during Bridgman crystal growth

NASA Astrophysics Data System (ADS)

Barat, Catherine; Duffar, Thierry; Garandet, Jean-Paul

1998-11-01

An approximate solution for the solid/liquid interface curvature due to the crucible effect in crystal growth is derived from simple heat flux considerations. The numerical modelling of the problem carried out with the help of the finite element code FIDAP supports the predictions of our analytical expression and allows to identify its range of validity. Experimental interface curvatures, measured in gallium antimonide samples grown by the vertical Bridgman method, are seen to compare satisfactorily to analytical and numerical results. Other literature data are also in fair agreement with the predictions of our models in the case where the amount of heat carried by the crucible is small compared to the overall heat flux.

Collision frequency of artificial satellites - The creation of a debris belt

NASA Technical Reports Server (NTRS)

Kessler, D. J.; Cour-Palais, B. G.

1978-01-01

The probability of satellite collisions increases with the number of satellites. In the present paper, possible time scales for the growth of a debris belt from collision fragments are determined, and possible consequences of continued unrestrained launch activities are examined. Use is made of techniques formerly developed for studying the evolution (growth) of the asteroid belt. A model describing the flux from the known earth-orbiting satellites is developed, and the results from this model are extrapolated in time to predict the collision frequency between satellites. Hypervelocity impact phenomena are then examined to predict the debris flux resulting from collisions. The results are applied to design requirements for three types of future space missions.

Landscape-level terrestrial methane flux observed from a very tall tower

USGS Publications Warehouse

Desai, Ankur R.; Xu, Ke; Tian, Hanqin; Weishampel, Peter; Thom, Jonthan; Baumann, Daniel D.; Andrews, Arlyn E.; Cook, Bruce D.; King, Jennifer Y.; Kolka, Randall

2015-01-01

Simulating the magnitude and variability of terrestrial methane sources and sinks poses a challenge to ecosystem models because the biophysical and biogeochemical processes that lead to methane emissions from terrestrial and freshwater ecosystems are, by their nature, episodic and spatially disjunct. As a consequence, model predictions of regional methane emissions based on field campaigns from short eddy covariance towers or static chambers have large uncertainties, because measurements focused on a particular known source of methane emission will be biased compared to regional estimates with regards to magnitude, spatial scale, or frequency of these emissions. Given the relatively large importance of predicting future terrestrial methane fluxes for constraining future atmospheric methane growth rates, a clear need exists to reduce spatiotemporal uncertainties. In 2010, an Ameriflux tower (US-PFa) near Park Falls, WI, USA, was instrumented with closed-path methane flux measurements at 122 m above ground in a mixed wetland–upland landscape representative of the Great Lakes region. Two years of flux observations revealed an average annual methane (CH4) efflux of 785 ± 75 mg CCH4 m−2 yr−1, compared to a mean CO2 sink of −80 g CCO2 m−2 yr−1, a ratio of 1% in magnitude on a mole basis. Interannual variability in methane flux was 30% of the mean flux and driven by suppression of methane emissions during dry conditions in late summer 2012. Though relatively small, the magnitude of the methane source from the very tall tower measurements was mostly within the range previously measured using static chambers at nearby wetlands, but larger than a simple scaling of those fluxes to the tower footprint. Seasonal patterns in methane fluxes were similar to those simulated in the Dynamic Land Ecosystem Model (DLEM), but magnitude depends on model parameterization and input data, especially regarding wetland extent. The model was unable to simulate short-term (sub-weekly) variability. Temperature was found to be a stronger driver of regional CH4flux than moisture availability or net ecosystem production at the daily to monthly scale. Taken together, these results emphasize the multi-timescale dependence of drivers of regional methane flux and the importance of long, continuous time series for their characterization.

Sediment size fractionation and focusing in the equatorial Pacific: Effect on 230Th normalization and paleoflux measurements

NASA Astrophysics Data System (ADS)

Lyle, Mitchell; Marcantonio, Franco; Moore, Willard S.; Murray, Richard W.; Huh, Chih-An; Finney, Bruce P.; Murray, David W.; Mix, Alan C.

2014-07-01

We use flux, dissolution, and excess 230Th data from the Joint Global Ocean Flux Study and Manganese Nodule Project equatorial Pacific study Site C to assess the extent of sediment focusing in the equatorial Pacific. Measured mass accumulation rates (MAR) from sediment cores were compared to reconstructed MAR by multiplying the particulate rain caught in sediment traps by the 230Th focusing factor and subtracting measured dissolution. CaCO3 MAR is severely overestimated when the 230Th focusing factor correction is large but is estimated correctly when the focusing factor is small. In contrast, Al fluxes in the sediment fine fraction are well matched when the focusing correction is used. Since CaCO3 is primarily a coarse sediment component, we propose that there is significant sorting of fine and coarse sediments during lateral sediment transport by weak currents. Because CaCO3 does not move with 230Th, normalization typically overcorrects the CaCO3 MAR; and because CaCO3 is 80% of the total sediment, 230Th normalization overestimates lateral sediment flux. Fluxes of 230Th in particulate rain caught in sediment traps agree with the water column production-sorption model, except within 500 m of the bottom. Near the bottom, 230Th flux measurements are as much as 3 times higher than model predictions. There is also evidence for lateral near-bottom 230Th transport in the bottom nepheloid layer since 230Th fluxes caught by near-bottom sediment traps are higher than predicted by resuspension of surface sediments alone. Resuspension and nepheloid layer transport under weak currents need to be better understood in order to use 230Th within a quantitative model of lateral sediment transport.

Combined constraints on the structure and physical properties of the East Antarctic lithosphere from geology and geophysics.

NASA Astrophysics Data System (ADS)

Reading, A. M.; Staal, T.; Halpin, J.; Whittaker, J. M.; Morse, P. E.

2017-12-01

The lithosphere of East Antarctica is one of the least explored regions of the planet, yet it is gaining in importance in global scientific research. Continental heat flux density and 3D glacial isostatic adjustment studies, for example, rely on a good knowledge of the deep structure in constraining model inputs.In this contribution, we use a multidisciplinary approach to constrain lithospheric domains. To seismic tomography models, we add constraints from magnetic studies and also new geological constraints. Geological knowledge exists around the periphery of East Antarctica and is reinforced in the knowledge of plate tectonic reconstructions. The subglacial geology of the Antarctic hinterland is largely unknown but the plate reconstructions allow the well-posed extrapolation of major terranes into the interior of the continent, guided by the seismic tomography and magnetic images. We find that the northern boundary of the lithospheric domain centred on the Gamburtsev Subglacial Mountains has a possible trend that runs south of the Lambert Glacier region, turning coastward through Wilkes Land. Other periphery-to-interior connections are less well constrained and the possibility of lithospheric domains that are entirely sub-glacial is high. We develop this framework to include a probabilistic method of handling alternate models and quantifiable uncertainties. We also show first results in using a Bayesian approach to predicting lithospheric boundaries from multivariate data.Within the newly constrained domains, we constrain heat flux (density) as the sum of basal heat flux and upper crustal heat flux. The basal heat flux is constrained by geophysical methods while the upper crustal heat flux is constrained by geology or predicted geology. In addition to heat flux constraints, we also consider the variations in friction experienced by moving ice sheets due to varying geology.

Simulating air temperature in an urban street canyon in all weather conditions using measured data at a reference meteorological station

NASA Astrophysics Data System (ADS)

Erell, E.; Williamson, T.

2006-10-01

A model is proposed that adapts data from a standard meteorological station to provide realistic site-specific air temperature in a city street exposed to the same meso-scale environment. In addition to a rudimentary description of the two sites, the canyon air temperature (CAT) model requires only inputs measured at standard weather stations; yet it is capable of accurately predicting the evolution of air temperature in all weather conditions for extended periods. It simulates the effect of urban geometry on radiant exchange; the effect of moisture availability on latent heat flux; energy stored in the ground and in building surfaces; air flow in the street based on wind above roof height; and the sensible heat flux from individual surfaces and from the street canyon as a whole. The CAT model has been tested on field data measured in a monitoring program carried out in Adelaide, Australia, in 2000-2001. After calibrating the model, predicted air temperature correlated well with measured data in all weather conditions over extended periods. The experimental validation provides additional evidence in support of a number of parameterisation schemes incorporated in the model to account for sensible heat and storage flux.

Modelling carbon fluxes of forest and grassland ecosystems in Western Europe using the CARAIB dynamic vegetation model: evaluation against eddy covariance data.

NASA Astrophysics Data System (ADS)

Henrot, Alexandra-Jane; François, Louis; Dury, Marie; Hambuckers, Alain; Jacquemin, Ingrid; Minet, Julien; Tychon, Bernard; Heinesch, Bernard; Horemans, Joanna; Deckmyn, Gaby

2015-04-01

Eddy covariance measurements are an essential resource to understand how ecosystem carbon fluxes react in response to climate change, and to help to evaluate and validate the performance of land surface and vegetation models at regional and global scale. In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), vegetation dynamics and carbon fluxes of forest and grassland ecosystems simulated by the CARAIB dynamic vegetation model (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) are evaluated and validated by comparison of the model predictions with eddy covariance data. Here carbon fluxes (e.g. net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO)) and evapotranspiration (ET) simulated with the CARAIB model are compared with the fluxes measured at several eddy covariance flux tower sites in Belgium and Western Europe, chosen from the FLUXNET global network (http://fluxnet.ornl.gov/). CARAIB is forced either with surface atmospheric variables derived from the global CRU climatology, or with in situ meteorological data. Several tree (e.g. Pinus sylvestris, Fagus sylvatica, Picea abies) and grass species (e.g. Poaceae, Asteraceae) are simulated, depending on the species encountered on the studied sites. The aim of our work is to assess the model ability to reproduce the daily, seasonal and interannual variablility of carbon fluxes and the carbon dynamics of forest and grassland ecosystems in Belgium and Western Europe.

A comparison of the thick-target model with stereo data on the height structure of solar hard X-ray bursts

NASA Technical Reports Server (NTRS)

Brown, J. C.; Carlaw, V. A.; Cromwell, D.; Kane, S. R.

1983-01-01

The thick target, hard solar X-ray source height structure is predicted for the case of a beam that is injected vertically downward, having a power law spectrum, being dominated by Coulomb collisional energy losses, and being structurally characterized by the ratio of hard X-ray flux from an upper part of the source to that from the entire source. These predictions are compared with the flux ratios at 150 and 350 keV which were observed by two spacecraft for five events in which the solar limb occults part of the source for one spacecraft. The energy dependence of the occultation ratio is found to be inconsistent with that predicted by the model, and it is concluded that noncollisional losses must be significant in beam dynamics.

Mapping the landscape of metabolic goals of a cell

DOE PAGES

Zhao, Qi; Stettner, Arion I.; Reznik, Ed; ...

2016-05-23

Here, genome-scale flux balance models of metabolism provide testable predictions of all metabolic rates in an organism, by assuming that the cell is optimizing a metabolic goal known as the objective function. We introduce an efficient inverse flux balance analysis (invFBA) approach, based on linear programming duality, to characterize the space of possible objective functions compatible with measured fluxes. After testing our algorithm on simulated E. coli data and time-dependent S. oneidensis fluxes inferred from gene expression, we apply our inverse approach to flux measurements in long-term evolved E. coli strains, revealing objective functions that provide insight into metabolic adaptationmore » trajectories.« less

Martian Radiation Environment: Model Calculations and Recent Measurements with "MARIE"

NASA Technical Reports Server (NTRS)

Saganti, P. B.; Cucinotta, F. A.; zeitlin, C. J.; Cleghorn, T. F.

2004-01-01

The Galactic Cosmic Ray spectra in Mars orbit were generated with the recently expanded HZETRN (High Z and Energy Transport) and QMSFRG (Quantum Multiple-Scattering theory of nuclear Fragmentation) model calculations. These model calculations are compared with the first eighteen months of measured data from the MARIE (Martian Radiation Environment Experiment) instrument onboard the 2001 Mars Odyssey spacecraft that is currently in Martian orbit. The dose rates observed by the MARIE instrument are within 10% of the model calculated predictions. Model calculations are compared with the MARIE measurements of dose, dose-equivalent values, along with the available particle flux distribution. Model calculated particle flux includes GCR elemental composition of atomic number, Z = 1-28 and mass number, A = 1-58. Particle flux calculations specific for the current MARIE mapping period are reviewed and presented.

A comparison of non-local electron transport models for laser-plasmas relevant to inertial confinement fusion

DOE PAGES

Sherlock, M.; Brodrick, J. P.; Ridgers, C. P.

2017-08-08

Here, we compare the reduced non-local electron transport model developed to Vlasov-Fokker-Planck simulations. Two new test cases are considered: the propagation of a heat wave through a high density region into a lower density gas, and a one-dimensional hohlraum ablation problem. We find that the reduced model reproduces the peak heat flux well in the ablation region but significantly over-predicts the coronal preheat. The suitability of the reduced model for computing non-local transport effects other than thermal conductivity is considered by comparing the computed distribution function to the Vlasov-Fokker-Planck distribution function. It is shown that even when the reduced modelmore » reproduces the correct heat flux, the distribution function is significantly different to the Vlasov-Fokker-Planck prediction. Two simple modifications are considered which improve agreement between models in the coronal region.« less

Winds from T Tauri stars. I - Spherically symmetric models

NASA Technical Reports Server (NTRS)

Hartmann, Lee; Avrett, Eugene H.; Loeser, Rudolf; Calvet, Nuria

1990-01-01

Line fluxes and profiles are computed for a sequence of spherically symmetric T Tauri wind models. The calculations indicate that the H-alpha emission of T Tauri stars arises in an extended and probably turbulent circumstellar envelope at temperatures above about 8000 K. The models predict that Mg II resonance line emission should be strongly correlated with H-alpha fluxes; observed Mg II/H-alpha ratios are inconsistent with the models unless extinction corrections have been underestimated. The models predict that most of the Ca II resonance line and IR triplet emission arises in dense layers close to the star rather than in the wind. H-alpha emission levels suggest mass loss rates of about 10 to the -8th solar mass/yr for most T Tauri stars, in reasonable agreement with independent analysis of forbidden emission lines. These results should be useful for interpreting observed line profiles in terms of wind densities, temperatures, and velocity fields.

The role of hydrodynamic transport in greenhouse gas fluxes at a wetland with emergent vegetation

NASA Astrophysics Data System (ADS)

Poindexter, C.; Gilson, E.; Knox, S. H.; Matthes, J. H.; Verfaillie, J. G.; Baldocchi, D. D.; Variano, E. A.

2013-12-01

In wetlands with emergent vegetation, the hydrodynamic transport of dissolved gases is often neglected because emergent plants transport gases directly and limit wind-driven air-water gas exchange by sheltering the water surface. Nevertheless, wetland hydrodynamics, and thermally-driven stirring in particular, have the potential to impact gas fluxes in these environments. We are evaluating the importance of hydrodynamic dissolved gas transport at a re-established marsh on Twitchell Island in the Sacramento-San Joaquin Delta (California, USA). At this marsh, the U.S. Geological Survey has previously observed rapid accumulation of organic material (carbon sequestration) as well as very high methane emissions. To assess the role of hydrodynamics in the marsh's greenhouse gas fluxes, we measured dissolved carbon dioxide and methane in the water column on a bi-weekly basis beginning in July 2012. We employed a model for air-water gas fluxes in wetlands with emergent vegetation that predicts gas transfer velocities from meteorological conditions. Modeled air-water gas fluxes were compared with net gas fluxes measured at the marsh via the eddy covariance technique. This comparison revealed that hydrodynamic transport due to thermal convection was responsible for approximately one third of net carbon dioxide and methane fluxes. The cooling at the water surface driving thermal convection occurred each night and was most pronounced during the warmest months of the year. These finding have implications for the prediction and management of greenhouse gas fluxes at re-established marshes in the Sacramento-San Joaquin Delta and other similar wetlands.

An Analysis of Inter-annual Variability and Uncertainty of Continental Surface Heat Fluxes

NASA Astrophysics Data System (ADS)

Huang, S. Y.; Deng, Y.; Wang, J.

2016-12-01

The inter-annual variability and the corresponding uncertainty of land surface heat fluxes during the first decade of the 21st century are re-evaluated at continental scale based on the heat fluxes estimated by the maximum entropy production (MEP) model. The MEP model predicted heat fluxes are constrained by surface radiation fluxes, automatically satisfy surface energy balance, and are independent of temperature/moisture gradient, wind speed, and roughness lengths. The surface radiation fluxes and temperature data from Clouds and the Earth's Radiant Energy System and the surface specific humidity data from Modern-Era Retrospective analysis for Research and Applications were used to reproduce the global surface heat fluxes with land-cover data from the NASA Energy and Water cycle Study (NEWS). Our analysis shows that the annual means of continental latent heat fluxes have increasing trends associated with increasing trends in surface net radiative fluxes. The sensible heat fluxes also have increasing trends over most continents except for South America. Ground heat fluxes have little trends. The continental-scale analysis of the MEP fluxes are compared with other existing global surface fluxes data products and the implications of the results for inter-annual to decadal variability of regional surface energy budget are discussed.

Calculating flux to predict future cave radon concentrations.

PubMed

Rowberry, Matt D; Martí, Xavi; Frontera, Carlos; Van De Wiel, Marco J; Briestenský, Miloš

2016-06-01

Cave radon concentration measurements reflect the outcome of a perpetual competition which pitches flux against ventilation and radioactive decay. The mass balance equations used to model changes in radon concentration through time routinely treat flux as a constant. This mathematical simplification is acceptable as a first order approximation despite the fact that it sidesteps an intrinsic geological problem: the majority of radon entering a cavity is exhaled as a result of advection along crustal discontinuities whose motions are inhomogeneous in both time and space. In this paper the dynamic nature of flux is investigated and the results are used to predict cave radon concentration for successive iterations. The first part of our numerical modelling procedure focuses on calculating cave air flow velocity while the second part isolates flux in a mass balance equation to simulate real time dependence among the variables. It is then possible to use this information to deliver an expression for computing cave radon concentration for successive iterations. The dynamic variables in the numerical model are represented by the outer temperature, the inner temperature, and the radon concentration while the static variables are represented by the radioactive decay constant and a range of parameters related to geometry of the cavity. Input data were recorded at Driny Cave in the Little Carpathians Mountains of western Slovakia. Here the cave passages have developed along splays of the NE-SW striking Smolenice Fault and a series of transverse faults striking NW-SE. Independent experimental observations of fault slip are provided by three permanently installed mechanical extensometers. Our numerical modelling has revealed four important flux anomalies between January 2010 and August 2011. Each of these flux anomalies was preceded by conspicuous fault slip anomalies. The mathematical procedure outlined in this paper will help to improve our understanding of radon migration along crustal discontinuities and its subsequent exhalation into the atmosphere. Furthermore, as it is possible to supply the model with continuous data, future research will focus on establishing a series of underground monitoring sites with the aim of generating the first real time global radon flux maps. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of Trapped Radiation Model Uncertainties for Spacecraft Design

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.

2000-01-01

The standard AP8 and AE8 models for predicting trapped proton and electron environments have been compared with several sets of flight data to evaluate model uncertainties. Model comparisons are made with flux, dose, and activation measurements made on various U.S. low-Earth orbit satellites (APEX, CRRES, DMSP, LDEF, NOAA) and Space Shuttle flights, on Russian satellites (Photon-8, Cosmos-1887, Cosmos-2044), and on the Russian Mir Space Station. This report gives a summary of the model-data comparisons-detailed results are given in a companion report. Results from the model comparisons with flic,ht data show, for example, the AP8 model underpredicts the trapped proton flux at low altitudes by a factor of about two (independent of proton energy and solar cycle conditions), and that the AE8 model overpredicts the flux in the outer electron belt by an order of magnitude or more.

Evaluation of Trapped Radiation Model Uncertainties for Spacecraft Design

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.

2000-01-01

The standard AP8 and AE8 models for predicting trapped proton and electron environments have been compared with several sets of flight data to evaluate model uncertainties. Model comparisons are made with flux, dose, and activation measurements made on various U.S. low-Earth orbit satellites (APEX, CRRES, DMSP. LDEF, NOAA) and Space Shuttle flights, on Russian satellites (Photon-8, Cosmos-1887, Cosmos-2044), and on the Russian Mir space station. This report gives a summary of the model-data given in a companion report. Results from the model comparisons with flight data show, for example, that the AP8 model underpredicts the trapped proton flux at low altitudes by a factor of about two (independent of proton energy and solar cycle conditions), and that the AE8 model overpredict the flux in the outer electron belt be an order of magnitude or more.

Ablation Predictions for Carbonaceous Materials Using Two Databases for Species Thermodynamics

NASA Technical Reports Server (NTRS)

Milos, F. S.; Chen, Y.-K.

2013-01-01

During previous work at NASA Ames Research Center, most ablation predictions were obtained using a species thermodynamics database derived primarily from the JANAF thermochemical tables. However, the chemical equilibrium with applications thermodynamics database, also used by NASA, is considered more up to date. In this work, ablation analyses were performed for carbon and carbon phenolic materials using both sets of species thermodynamics. The ablation predictions are comparable at low and moderate heat fluxes, where the dominant mechanism is carbon oxidation. For high heat fluxes where sublimation is important, the predictions differ, with the chemical equilibrium with applications model predicting a lower ablation rate. The disagreement is greater for carbon phenolic than for carbon, and this difference is attributed to hydrocarbon species that may contribute to the ablation rate. Sample calculations for representative Orion and Stardust environments show significant differences only in the sublimation regime. For Stardust, if the calculations include a nominal environmental uncertainty for aeroheating, then the chemical equilibrium with applications model predicts a range of recession that is consistent with measurements for both heatshield cores.

Development and validation of a low-frequency modeling code for high-moment transmitter rod antennas

NASA Astrophysics Data System (ADS)

Jordan, Jared Williams; Sternberg, Ben K.; Dvorak, Steven L.

2009-12-01

The goal of this research is to develop and validate a low-frequency modeling code for high-moment transmitter rod antennas to aid in the design of future low-frequency TX antennas with high magnetic moments. To accomplish this goal, a quasi-static modeling algorithm was developed to simulate finite-length, permeable-core, rod antennas. This quasi-static analysis is applicable for low frequencies where eddy currents are negligible, and it can handle solid or hollow cores with winding insulation thickness between the antenna's windings and its core. The theory was programmed in Matlab, and the modeling code has the ability to predict the TX antenna's gain, maximum magnetic moment, saturation current, series inductance, and core series loss resistance, provided the user enters the corresponding complex permeability for the desired core magnetic flux density. In order to utilize the linear modeling code to model the effects of nonlinear core materials, it is necessary to use the correct complex permeability for a specific core magnetic flux density. In order to test the modeling code, we demonstrated that it can accurately predict changes in the electrical parameters associated with variations in the rod length and the core thickness for antennas made out of low carbon steel wire. These tests demonstrate that the modeling code was successful in predicting the changes in the rod antenna characteristics under high-current nonlinear conditions due to changes in the physical dimensions of the rod provided that the flux density in the core was held constant in order to keep the complex permeability from changing.

Revisiting low-fidelity two-fluid models for gas–solids transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adeleke, Najeem, E-mail: najm@psu.edu; Adewumi, Michael, E-mail: m2a@psu.edu; Ityokumbul, Thaddeus

Two-phase gas–solids transport models are widely utilized for process design and automation in a broad range of industrial applications. Some of these applications include proppant transport in gaseous fracking fluids, air/gas drilling hydraulics, coal-gasification reactors and food processing units. Systems automation and real time process optimization stand to benefit a great deal from availability of efficient and accurate theoretical models for operations data processing. However, modeling two-phase pneumatic transport systems accurately requires a comprehensive understanding of gas–solids flow behavior. In this study we discuss the prevailing flow conditions and present a low-fidelity two-fluid model equation for particulate transport. The modelmore » equations are formulated in a manner that ensures the physical flux term remains conservative despite the inclusion of solids normal stress through the empirical formula for modulus of elasticity. A new set of Roe–Pike averages are presented for the resulting strictly hyperbolic flux term in the system of equations, which was used to develop a Roe-type approximate Riemann solver. The resulting scheme is stable regardless of the choice of flux-limiter. The model is evaluated by the prediction of experimental results from both pneumatic riser and air-drilling hydraulics systems. We demonstrate the effect and impact of numerical formulation and choice of numerical scheme on model predictions. We illustrate the capability of a low-fidelity one-dimensional two-fluid model in predicting relevant flow parameters in two-phase particulate systems accurately even under flow regimes involving counter-current flow.« less

Predicted net efflux of radiocarbon from the ocean and increase in atmospheric radiocarbon content

NASA Astrophysics Data System (ADS)

Caldeira, Ken; Rau, Greg H.; Duffy, Philip B.

Prior to changes introduced by man, production of radiocarbon (14C) in the stratosphere nearly balanced the flux of 14C from the atmosphere to the ocean and land biosphere, which in turn nearly balanced radioactive decay in these 14C reservoirs. This balance has been altered by land-use changes, fossil-fuel burning, and atmospheric nuclear detonations. Here, we use a model of the global carbon cycle to quantify these radiocarbon fluxes and make predictions about their magnitude in the future. Atmospheric nuclear detonations increased atmospheric 14C content by about 80% by the mid-1960's. Since that time, the 14C content of the atmosphere has been diminishing as this bomb radiocarbon has been entering the oceans and terrestrial biosphere. However, we predict that atmospheric 14C content will reach a minimum and start to increase within the next few years if fossil-fuel burning continues according to a “business-as-usual” scenario, even though fossil fuels are devoid of 14C. This will happen because fossil-fuel carbon diminishes the net flux of 14C from the atmosphere to the oceans and land biosphere, forcing 14C to accumulate in the atmosphere. Furthermore, the net flux of both bomb and natural 14C into the ocean are predicted to continue to slow and then, in the middle of the next century, to reverse, so that there will be a net flux of 14C from the ocean to the atmosphere. The predicted reversal of net 14C fluxes into the ocean is a further example of human impacts on the global carbon cycle.

Acceleration of Relativistic Electrons: A Comparison of Two Models

NASA Astrophysics Data System (ADS)

Green, J. C.; Kivelson, M. G.

2001-12-01

Observations of relativistic electron fluxes show order of magnitude increases during some geomagnetic storms. Many electron acceleration models have been proposed to explain the flux enhancements but attempts to validate these models have yielded ambiguous results. Here we examine two models of electron acceleration, radial diffusion via enhanced ULF wave activity [Elkington et al.,1999] and acceleration by resonant interaction with whistler waves[Summers,1998; Roth et al.,1999]. Two methods are used to compare observations with features predicted by the models. First, the evolution of phase space density as a function of L during flux enhancement events is evaluated. The phase space density (PSD) is calculated at constant first, second and third adiabatic invariants using data obtained by the CEPPAD-HIST instrument and the MFE instrument onboard the Polar spacecraft. Liouville's theorem states that PSD calculated at constant adiabatic invariants does not change with time unless some mechanism violates one of the invariants. The radial diffusion model predicts that only the flux invariant will be violated during the acceleration process while acceleration by whistler waves violates the first invariant. Therefore, the two models predict a different evolution of the PSD as a function of time and L. Previous examinations of the evolution of PSD have yielded ambiguous results because PSD calculations are highly dependent on the global accuracy of magnetic field models. We examine the PSD versus L profiles for a series of geomagnetic storms and in addition determine how errors in the Tsyganenko 96 field model affect the results by comparing the measured magnetic field to the model magnetic field used in the calculations. Second, the evolution of the relativistic electron pitch angle distributions is evaluated. Previous studies of pitch angle distributions were limited because few spacecraft have the necessary instrumentation and global coverage. The CEPPAD-HIST instrument measures 16 look directions and along with measurements from the MFE experiment allows calculation of complete pitch angle distributions. The evolving orbit of the Polar spacecraft over the 6 years mission has given measurements over a wide range of L and local time. Using data extending over the entire mission we use superposed epoch analysis to examine the evolution of pitch angle distributions during flux enhancement events as a function of L, magnetic local time, and storm phase.

A Computational Fluid Dynamic and Heat Transfer Model for Gaseous Core and Gas Cooled Space Power and Propulsion Reactors

NASA Technical Reports Server (NTRS)

Anghaie, S.; Chen, G.

1996-01-01

A computational model based on the axisymmetric, thin-layer Navier-Stokes equations is developed to predict the convective, radiation and conductive heat transfer in high temperature space nuclear reactors. An implicit-explicit, finite volume, MacCormack method in conjunction with the Gauss-Seidel line iteration procedure is utilized to solve the thermal and fluid governing equations. Simulation of coolant and propellant flows in these reactors involves the subsonic and supersonic flows of hydrogen, helium and uranium tetrafluoride under variable boundary conditions. An enthalpy-rebalancing scheme is developed and implemented to enhance and accelerate the rate of convergence when a wall heat flux boundary condition is used. The model also incorporated the Baldwin and Lomax two-layer algebraic turbulence scheme for the calculation of the turbulent kinetic energy and eddy diffusivity of energy. The Rosseland diffusion approximation is used to simulate the radiative energy transfer in the optically thick environment of gas core reactors. The computational model is benchmarked with experimental data on flow separation angle and drag force acting on a suspended sphere in a cylindrical tube. The heat transfer is validated by comparing the computed results with the standard heat transfer correlations predictions. The model is used to simulate flow and heat transfer under a variety of design conditions. The effect of internal heat generation on the heat transfer in the gas core reactors is examined for a variety of power densities, 100 W/cc, 500 W/cc and 1000 W/cc. The maximum temperature, corresponding with the heat generation rates, are 2150 K, 2750 K and 3550 K, respectively. This analysis shows that the maximum temperature is strongly dependent on the value of heat generation rate. It also indicates that a heat generation rate higher than 1000 W/cc is necessary to maintain the gas temperature at about 3500 K, which is typical design temperature required to achieve high efficiency in the gas core reactors. The model is also used to predict the convective and radiation heat fluxes for the gas core reactors. The maximum value of heat flux occurs at the exit of the reactor core. Radiation heat flux increases with higher wall temperature. This behavior is due to the fact that the radiative heat flux is strongly dependent on wall temperature. This study also found that at temperature close to 3500 K the radiative heat flux is comparable with the convective heat flux in a uranium fluoride failed gas core reactor.

Measurement and simulation of thermal neutron flux distribution in the RTP core

NASA Astrophysics Data System (ADS)

Rabir, Mohamad Hairie B.; Jalal Bayar, Abi Muttaqin B.; Hamzah, Na'im Syauqi B.; Mustafa, Muhammad Khairul Ariff B.; Karim, Julia Bt. Abdul; Zin, Muhammad Rawi B. Mohamed; Ismail, Yahya B.; Hussain, Mohd Huzair B.; Mat Husin, Mat Zin B.; Dan, Roslan B. Md; Ismail, Ahmad Razali B.; Husain, Nurfazila Bt.; Jalil Khan, Zareen Khan B. Abdul; Yakin, Shaiful Rizaide B. Mohd; Saad, Mohamad Fauzi B.; Masood, Zarina Bt.

2018-01-01

The in-core thermal neutron flux distribution was determined using measurement and simulation methods for the Malaysian’s PUSPATI TRIGA Reactor (RTP). In this work, online thermal neutron flux measurement using Self Powered Neutron Detector (SPND) has been performed to verify and validate the computational methods for neutron flux calculation in RTP calculations. The experimental results were used as a validation to the calculations performed with Monte Carlo code MCNP. The detail in-core neutron flux distributions were estimated using MCNP mesh tally method. The neutron flux mapping obtained revealed the heterogeneous configuration of the core. Based on the measurement and simulation, the thermal flux profile peaked at the centre of the core and gradually decreased towards the outer side of the core. The results show a good agreement (relatively) between calculation and measurement where both show the same radial thermal flux profile inside the core: MCNP model over estimation with maximum discrepancy around 20% higher compared to SPND measurement. As our model also predicts well the neutron flux distribution in the core it can be used for the characterization of the full core, that is neutron flux and spectra calculation, dose rate calculations, reaction rate calculations, etc.

Model-data integration for developing the Cropland Carbon Monitoring System (CCMS)

NASA Astrophysics Data System (ADS)

Jones, C. D.; Bandaru, V.; Pnvr, K.; Jin, H.; Reddy, A.; Sahajpal, R.; Sedano, F.; Skakun, S.; Wagle, P.; Gowda, P. H.; Hurtt, G. C.; Izaurralde, R. C.

2017-12-01

The Cropland Carbon Monitoring System (CCMS) has been initiated to improve regional estimates of carbon fluxes from croplands in the conterminous United States through integration of terrestrial ecosystem modeling, use of remote-sensing products and publically available datasets, and development of improved landscape and management databases. In order to develop these improved carbon flux estimates, experimental datasets are essential for evaluating the skill of estimates, characterizing the uncertainty of these estimates, characterizing parameter sensitivities, and calibrating specific modeling components. Experiments were sought that included flux tower measurement of CO2 fluxes under production of major agronomic crops. Currently data has been collected from 17 experiments comprising 117 site-years from 12 unique locations. Calibration of terrestrial ecosystem model parameters using available crop productivity and net ecosystem exchange (NEE) measurements resulted in improvements in RMSE of NEE predictions of between 3.78% to 7.67%, while improvements in RMSE for yield ranged from -1.85% to 14.79%. Model sensitivities were dominated by parameters related to leaf area index (LAI) and spring growth, demonstrating considerable capacity for model improvement through development and integration of remote-sensing products. Subsequent analyses will assess the impact of such integrated approaches on skill of cropland carbon flux estimates.

Delta Clipper-Experimental In-Ground Effect on Base-Heating Environment

NASA Technical Reports Server (NTRS)

Wang, Ten-See

1998-01-01

A quasitransient in-ground effect method is developed to study the effect of vertical landing on a launch vehicle base-heating environment. This computational methodology is based on a three-dimensional, pressure-based, viscous flow, chemically reacting, computational fluid dynamics formulation. Important in-ground base-flow physics such as the fountain-jet formation, plume growth, air entrainment, and plume afterburning are captured with the present methodology. Convective and radiative base-heat fluxes are computed for comparison with those of a flight test. The influence of the laminar Prandtl number on the convective heat flux is included in this study. A radiative direction-dependency test is conducted using both the discrete ordinate and finite volume methods. Treatment of the plume afterburning is found to be very important for accurate prediction of the base-heat fluxes. Convective and radiative base-heat fluxes predicted by the model using a finite rate chemistry option compared reasonably well with flight-test data.

Measurement of the neutrino component of an antineutrino beam observed by a nonmagnetized detector

NASA Astrophysics Data System (ADS)

Aguilar-Arevalo, A. A.; Anderson, C. E.; Brice, S. J.; Brown, B. C.; Bugel, L.; Conrad, J. M.; Dharmapalan, R.; Djurcic, Z.; Fleming, B. T.; Ford, R.; Garcia, F. G.; Garvey, G. T.; Grange, J.; Green, J. A.; Imlay, R.; Johnson, R. A.; Karagiorgi, G.; Katori, T.; Kobilarcik, T.; Linden, S. K.; Louis, W. C.; Mahn, K. B. M.; Marsh, W.; Mauger, C.; Metcalf, W.; Mills, G. B.; Mirabal, J.; Moore, C. D.; Mousseau, J.; Nelson, R. H.; Nguyen, V.; Nienaber, P.; Nowak, J. A.; Osmanov, B.; Patch, A.; Pavlovic, Z.; Perevalov, D.; Polly, C. C.; Ray, H.; Roe, B. P.; Russell, A. D.; Shaevitz, M. H.; Sorel, M.; Spitz, J.; Stancu, I.; Stefanski, R. J.; Tayloe, R.; Tzanov, M.; van de Water, R. G.; Wascko, M. O.; White, D. H.; Wilking, M. J.; Zeller, G. P.; Zimmerman, E. D.

2011-10-01

Two methods are employed to measure the neutrino flux of the antineutrino-mode beam observed by the MiniBooNE detector. The first method compares data to simulated event rates in a high-purity νμ-induced charged-current single π+ (CC1π+) sample while the second exploits the difference between the angular distributions of muons created in νμ and ν¯μ charged-current quasielastic (CCQE) interactions. The results from both analyses indicate the prediction of the neutrino flux component of the predominately antineutrino beam is overestimated—the CC1π+ analysis indicates the predicted νμ flux should be scaled by 0.76±0.11, while the CCQE angular fit yields 0.65±0.23. The energy spectrum of the flux prediction is checked by repeating the analyses in bins of reconstructed neutrino energy, and the results show that the spectral shape is well-modeled. These analyses are a demonstration of techniques for measuring the neutrino contamination of antineutrino beams observed by future nonmagnetized detectors.

Ozone risk assessment for agricultural crops in Europe: Further development of stomatal flux and flux-response relationships for European wheat and potato

NASA Astrophysics Data System (ADS)

Pleijel, H.; Danielsson, H.; Emberson, L.; Ashmore, M. R.; Mills, G.

Applications of a parameterised Jarvis-type multiplicative stomatal conductance model with data collated from open-top chamber experiments on field grown wheat and potato were used to derive relationships between relative yield and stomatal ozone uptake. The relationships were based on thirteen experiments from four European countries for wheat and seven experiments from four European countries for potato. The parameterisation of the conductance model was based both on an extensive literature review and primary data. Application of the stomatal conductance models to the open-top chamber experiments resulted in improved linear regressions between relative yield and ozone uptake compared to earlier stomatal conductance models, both for wheat ( r2=0.83) and potato ( r2=0.76). The improvement was largest for potato. The relationships with the highest correlation were obtained using a stomatal ozone flux threshold. For both wheat and potato the best performing exposure index was AF st6 (accumulated stomatal flux of ozone above a flux rate threshold of 6 nmol ozone m -2 projected sunlit leaf area, based on hourly values of ozone flux). The results demonstrate that flux-based models are now sufficiently well calibrated to be used with confidence to predict the effects of ozone on yield loss of major arable crops across Europe. Further studies, using innovations in stomatal conductance modelling and plant exposure experimentation, are needed if these models are to be further improved.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The approach used follows the non-equilibrium statistical mechanical approach through a master equation. The aim is to represent the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and mass flux is a non-linear function of convective cell area, mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated mass flux variability under diurnally varying forcing. Besides its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of providing alternative, non-equilibrium, closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

Physiologically Shrinking the Solution Space of a Saccharomyces cerevisiae Genome-Scale Model Suggests the Role of the Metabolic Network in Shaping Gene Expression Noise.

PubMed

Chi, Baofang; Tao, Shiheng; Liu, Yanlin

2015-01-01

Sampling the solution space of genome-scale models is generally conducted to determine the feasible region for metabolic flux distribution. Because the region for actual metabolic states resides only in a small fraction of the entire space, it is necessary to shrink the solution space to improve the predictive power of a model. A common strategy is to constrain models by integrating extra datasets such as high-throughput datasets and C13-labeled flux datasets. However, studies refining these approaches by performing a meta-analysis of massive experimental metabolic flux measurements, which are closely linked to cellular phenotypes, are limited. In the present study, experimentally identified metabolic flux data from 96 published reports were systematically reviewed. Several strong associations among metabolic flux phenotypes were observed. These phenotype-phenotype associations at the flux level were quantified and integrated into a Saccharomyces cerevisiae genome-scale model as extra physiological constraints. By sampling the shrunken solution space of the model, the metabolic flux fluctuation level, which is an intrinsic trait of metabolic reactions determined by the network, was estimated and utilized to explore its relationship to gene expression noise. Although no correlation was observed in all enzyme-coding genes, a relationship between metabolic flux fluctuation and expression noise of genes associated with enzyme-dosage sensitive reactions was detected, suggesting that the metabolic network plays a role in shaping gene expression noise. Such correlation was mainly attributed to the genes corresponding to non-essential reactions, rather than essential ones. This was at least partially, due to regulations underlying the flux phenotype-phenotype associations. Altogether, this study proposes a new approach in shrinking the solution space of a genome-scale model, of which sampling provides new insights into gene expression noise.

Assessing the Importance of Prior Biospheric Fluxes on Inverse Model Estimates of CO2

NASA Astrophysics Data System (ADS)

Philip, S.; Johnson, M. S.; Potter, C. S.; Genovese, V. B.

2017-12-01

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emissions and biospheric sources/sinks. The processes controlling terrestrial biosphere-atmosphere carbon exchange are currently not fully understood, resulting in models having significant differences in the quantification of biospheric CO2 fluxes. Currently, atmospheric chemical transport models (CTM) and global climate models (GCM) use multiple different biospheric CO2 flux models resulting in large differences in simulating the global carbon cycle. The Orbiting Carbon Observatory 2 (OCO-2) satellite mission was designed to allow for the improved understanding of the processes involved in the exchange of carbon between terrestrial ecosystems and the atmosphere, and therefore allowing for more accurate assessment of the seasonal/inter-annual variability of CO2. OCO-2 provides much-needed CO2 observations in data-limited regions allowing for the evaluation of model simulations of greenhouse gases (GHG) and facilitating global/regional estimates of "top-down" CO2 fluxes. We conduct a 4-D Variation (4D-Var) data assimilation with the GEOS-Chem (Goddard Earth Observation System-Chemistry) CTM using 1) OCO-2 land nadir and land glint retrievals and 2) global in situ surface flask observations to constrain biospheric CO2 fluxes. We apply different state-of-the-science year-specific CO2 flux models (e.g., NASA-CASA (NASA-Carnegie Ames Stanford Approach), CASA-GFED (Global Fire Emissions Database), Simple Biosphere Model version 4 (SiB-4), and LPJ (Lund-Postdam-Jena)) to assess the impact of "a priori" flux predictions to "a posteriori" estimates. We will present the "top-down" CO2 flux estimates for the year 2015 using OCO-2 and in situ observations, and a complete indirect evaluation of the a priori and a posteriori flux estimates using independent in situ observations. We will also present our assessment of the variability of "top-down" CO2 flux estimates when using different biospheric CO2 flux models. This work will improve our understanding of the global carbon cycle, specifically, how OCO-2 observations can be used to constrain biospheric CO2 flux model estimates.

Astroparticle physics with solar neutrinos

PubMed Central

NAKAHATA, Masayuki

2011-01-01

Solar neutrino experiments observed fluxes smaller than the expectations from the standard solar model. This discrepancy is known as the “solar neutrino problem”. Flux measurements by Super-Kamiokande and SNO have demonstrated that the solar neutrino problem is due to neutrino oscillations. Combining the results of all solar neutrino experiments, parameters for solar neutrino oscillations are obtained. Correcting for the effect of neutrino oscillations, the observed neutrino fluxes are consistent with the prediction from the standard solar model. In this article, results of solar neutrino experiments are reviewed with detailed descriptions of what Kamiokande and Super-Kamiokande have contributed to the history of astroparticle physics with solar neutrino measurements. PMID:21558758

UK-5 Van Allen belt radiation exposure: A special study to determine the trapped particle intensities on the UK-5 satellite with spatial mapping of the ambient flux environment

NASA Technical Reports Server (NTRS)

Stassinopoulos, E. G.

1972-01-01

Vehicle encountered electron and proton fluxes were calculated for a set of nominal UK-5 trajectories with new computational methods and new electron environment models. Temporal variations in the electron data were considered and partially accounted for. Field strength calculations were performed with an extrapolated model on the basis of linear secular variation predictions. Tabular maps for selected electron and proton energies were constructed as functions of latitude and longitude for specified altitudes. Orbital flux integration results are presented in graphical and tabular form; they are analyzed, explained, and discussed.

Experimental Study of Fire Hazards of Thermal-Insulation Material in Diesel Locomotive: Aluminum-Polyurethane.

PubMed

Zhang, Taolin; Zhou, Xiaodong; Yang, Lizhong

2016-03-05

This work investigated experimentally and theoretically the fire hazards of thermal-insulation materials used in diesel locomotives under different radiation heat fluxes. Based on the experimental results, the critical heat flux for ignition was determined to be 6.15 kW/m² and 16.39 kW/m² for pure polyurethane and aluminum-polyurethane respectively. A theoretical model was established for both to predict the fire behaviors under different circumstances. The fire behavior of the materials was evaluated based on the flashover and the total heat release rate (HRR). The fire hazards levels were classified based on different experimental results. It was found that the fire resistance performance of aluminum-polyurethane is much better than that of pure-polyurethane under various external heat fluxes. The concentration of toxic pyrolysis volatiles generated from aluminum-polyurethane materials is much higher than that of pure polyurethane materials, especially when the heat flux is below 50 kW/m². The hazard index HI during peak width time was proposed based on the comprehensive impact of time and concentrations. The predicted HI in this model coincides with the existed N-gas and FED models which are generally used to evaluate the fire gas hazard in previous researches. The integrated model named HNF was proposed as well to estimate the fire hazards of materials by interpolation and weighted average calculation.

Experimental Study of Fire Hazards of Thermal-Insulation Material in Diesel Locomotive: Aluminum-Polyurethane

PubMed Central

Zhang, Taolin; Zhou, Xiaodong; Yang, Lizhong

2016-01-01

This work investigated experimentally and theoretically the fire hazards of thermal-insulation materials used in diesel locomotives under different radiation heat fluxes. Based on the experimental results, the critical heat flux for ignition was determined to be 6.15 kW/m2 and 16.39 kW/m2 for pure polyurethane and aluminum-polyurethane respectively. A theoretical model was established for both to predict the fire behaviors under different circumstances. The fire behavior of the materials was evaluated based on the flashover and the total heat release rate (HRR). The fire hazards levels were classified based on different experimental results. It was found that the fire resistance performance of aluminum-polyurethane is much better than that of pure-polyurethane under various external heat fluxes. The concentration of toxic pyrolysis volatiles generated from aluminum-polyurethane materials is much higher than that of pure polyurethane materials, especially when the heat flux is below 50 kW/m2. The hazard index HI during peak width time was proposed based on the comprehensive impact of time and concentrations. The predicted HI in this model coincides with the existed N-gas and FED models which are generally used to evaluate the fire gas hazard in previous researches. The integrated model named HNF was proposed as well to estimate the fire hazards of materials by interpolation and weighted average calculation. PMID:28773295

Cycle flux algebra for ion and water flux through the KcsA channel single-file pore links microscopic trajectories and macroscopic observables.

PubMed

Oiki, Shigetoshi; Iwamoto, Masayuki; Sumikama, Takashi

2011-01-31

In narrow pore ion channels, ions and water molecules diffuse in a single-file manner and cannot pass each other. Under such constraints, ion and water fluxes are coupled, leading to experimentally observable phenomena such as the streaming potential. Analysis of this coupled flux would provide unprecedented insights into the mechanism of permeation. In this study, ion and water permeation through the KcsA potassium channel was the focus, for which an eight-state discrete-state Markov model has been proposed based on the crystal structure, exhibiting four ion-binding sites. Random transitions on the model lead to the generation of the net flux. Here we introduced the concept of cycle flux to derive exact solutions of experimental observables from the permeation model. There are multiple cyclic paths on the model, and random transitions complete the cycles. The rate of cycle completion is called the cycle flux. The net flux is generated by a combination of cyclic paths with their own cycle flux. T.L. Hill developed a graphical method of exact solutions for the cycle flux. This method was extended to calculate one-way cycle fluxes of the KcsA channel. By assigning the stoichiometric numbers for ion and water transfer to each cycle, we established a method to calculate the water-ion coupling ratio (CR(w-i)) through cycle flux algebra. These calculations predicted that CR(w-i) would increase at low potassium concentrations. One envisions an intuitive picture of permeation as random transitions among cyclic paths, and the relative contributions of the cycle fluxes afford experimental observables.

Cycle Flux Algebra for Ion and Water Flux through the KcsA Channel Single-File Pore Links Microscopic Trajectories and Macroscopic Observables

PubMed Central

Oiki, Shigetoshi; Iwamoto, Masayuki; Sumikama, Takashi

2011-01-01

In narrow pore ion channels, ions and water molecules diffuse in a single-file manner and cannot pass each other. Under such constraints, ion and water fluxes are coupled, leading to experimentally observable phenomena such as the streaming potential. Analysis of this coupled flux would provide unprecedented insights into the mechanism of permeation. In this study, ion and water permeation through the KcsA potassium channel was the focus, for which an eight-state discrete-state Markov model has been proposed based on the crystal structure, exhibiting four ion-binding sites. Random transitions on the model lead to the generation of the net flux. Here we introduced the concept of cycle flux to derive exact solutions of experimental observables from the permeation model. There are multiple cyclic paths on the model, and random transitions complete the cycles. The rate of cycle completion is called the cycle flux. The net flux is generated by a combination of cyclic paths with their own cycle flux. T.L. Hill developed a graphical method of exact solutions for the cycle flux. This method was extended to calculate one-way cycle fluxes of the KcsA channel. By assigning the stoichiometric numbers for ion and water transfer to each cycle, we established a method to calculate the water-ion coupling ratio (CR w-i) through cycle flux algebra. These calculations predicted that CR w-i would increase at low potassium concentrations. One envisions an intuitive picture of permeation as random transitions among cyclic paths, and the relative contributions of the cycle fluxes afford experimental observables. PMID:21304994

Parameter and prediction uncertainty in an optimized terrestrial carbon cycle model: Effects of constraining variables and data record length

NASA Astrophysics Data System (ADS)

Ricciuto, Daniel M.; King, Anthony W.; Dragoni, D.; Post, Wilfred M.

2011-03-01

Many parameters in terrestrial biogeochemical models are inherently uncertain, leading to uncertainty in predictions of key carbon cycle variables. At observation sites, this uncertainty can be quantified by applying model-data fusion techniques to estimate model parameters using eddy covariance observations and associated biometric data sets as constraints. Uncertainty is reduced as data records become longer and different types of observations are added. We estimate parametric and associated predictive uncertainty at the Morgan Monroe State Forest in Indiana, USA. Parameters in the Local Terrestrial Ecosystem Carbon (LoTEC) are estimated using both synthetic and actual constraints. These model parameters and uncertainties are then used to make predictions of carbon flux for up to 20 years. We find a strong dependence of both parametric and prediction uncertainty on the length of the data record used in the model-data fusion. In this model framework, this dependence is strongly reduced as the data record length increases beyond 5 years. If synthetic initial biomass pool constraints with realistic uncertainties are included in the model-data fusion, prediction uncertainty is reduced by more than 25% when constraining flux records are less than 3 years. If synthetic annual aboveground woody biomass increment constraints are also included, uncertainty is similarly reduced by an additional 25%. When actual observed eddy covariance data are used as constraints, there is still a strong dependence of parameter and prediction uncertainty on data record length, but the results are harder to interpret because of the inability of LoTEC to reproduce observed interannual variations and the confounding effects of model structural error.

Energy budgets and resistances to energy transport in sparsely vegetated rangeland

USGS Publications Warehouse

Nichols, W.D.

1992-01-01

Partitioning available energy between plants and bare soil in sparsely vegetated rangelands will allow hydrologists and others to gain a greater understanding of water use by native vegetation, especially phreatophytes. Standard methods of conducting energy budget studies result in measurements of latent and sensible heat fluxes above the plant canopy which therefore include the energy fluxes from both the canopy and the soil. One-dimensional theoretical numerical models have been proposed recently for the partitioning of energy in sparse crops. Bowen ratio and other micrometeorological data collected over phreatophytes growing in areas of shallow ground water in central Nevada were used to evaluate the feasibility of using these models, which are based on surface and within-canopy aerodynamic resistances, to determine heat and water vapor transport in sparsely vegetated rangelands. The models appear to provide reasonably good estimates of sensible heat flux from the soil and latent heat flux from the canopy. Estimates of latent heat flux from the soil were less satisfactory. Sensible heat flux from the canopy was not well predicted by the present resistance formulations. Also, estimates of total above-canopy fluxes were not satisfactory when using a single value for above-canopy bulk aerodynamic resistance. ?? 1992.

Revealing the Earth’s mantle from the tallest mountains using the Jinping Neutrino Experiment

NASA Astrophysics Data System (ADS)

Šrámek, Ondřej; Roskovec, Bedřich; Wipperfurth, Scott A.; Xi, Yufei; McDonough, William F.

2016-09-01

The Earth’s engine is driven by unknown proportions of primordial energy and heat produced in radioactive decay. Unfortunately, competing models of Earth’s composition reveal an order of magnitude uncertainty in the amount of radiogenic power driving mantle dynamics. Recent measurements of the Earth’s flux of geoneutrinos, electron antineutrinos from terrestrial natural radioactivity, reveal the amount of uranium and thorium in the Earth and set limits on the residual proportion of primordial energy. Comparison of the flux measured at large underground neutrino experiments with geologically informed predictions of geoneutrino emission from the crust provide the critical test needed to define the mantle’s radiogenic power. Measurement at an oceanic location, distant from nuclear reactors and continental crust, would best reveal the mantle flux, however, no such experiment is anticipated. We predict the geoneutrino flux at the site of the Jinping Neutrino Experiment (Sichuan, China). Within 8 years, the combination of existing data and measurements from soon to come experiments, including Jinping, will exclude end-member models at the 1σ level, define the mantle’s radiogenic contribution to the surface heat loss, set limits on the composition of the silicate Earth, and provide significant parameter bounds for models defining the mode of mantle convection.

Revealing the Earth’s mantle from the tallest mountains using the Jinping Neutrino Experiment

PubMed Central

Šrámek, Ondřej; Roskovec, Bedřich; Wipperfurth, Scott A.; Xi, Yufei; McDonough, William F.

2016-01-01

The Earth’s engine is driven by unknown proportions of primordial energy and heat produced in radioactive decay. Unfortunately, competing models of Earth’s composition reveal an order of magnitude uncertainty in the amount of radiogenic power driving mantle dynamics. Recent measurements of the Earth’s flux of geoneutrinos, electron antineutrinos from terrestrial natural radioactivity, reveal the amount of uranium and thorium in the Earth and set limits on the residual proportion of primordial energy. Comparison of the flux measured at large underground neutrino experiments with geologically informed predictions of geoneutrino emission from the crust provide the critical test needed to define the mantle’s radiogenic power. Measurement at an oceanic location, distant from nuclear reactors and continental crust, would best reveal the mantle flux, however, no such experiment is anticipated. We predict the geoneutrino flux at the site of the Jinping Neutrino Experiment (Sichuan, China). Within 8 years, the combination of existing data and measurements from soon to come experiments, including Jinping, will exclude end-member models at the 1σ level, define the mantle’s radiogenic contribution to the surface heat loss, set limits on the composition of the silicate Earth, and provide significant parameter bounds for models defining the mode of mantle convection. PMID:27611737

Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate.

PubMed

Beer, Christian; Reichstein, Markus; Tomelleri, Enrico; Ciais, Philippe; Jung, Martin; Carvalhais, Nuno; Rödenbeck, Christian; Arain, M Altaf; Baldocchi, Dennis; Bonan, Gordon B; Bondeau, Alberte; Cescatti, Alessandro; Lasslop, Gitta; Lindroth, Anders; Lomas, Mark; Luyssaert, Sebastiaan; Margolis, Hank; Oleson, Keith W; Roupsard, Olivier; Veenendaal, Elmar; Viovy, Nicolas; Williams, Christopher; Woodward, F Ian; Papale, Dario

2010-08-13

Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.

Kinetically accessible yield (KAY) for redirection of metabolism to produce exo-metabolites

DOE PAGES

Lafontaine Rivera, Jimmy G.; Theisen, Matthew K.; Chen, Po-Wei; ...

2017-04-05

The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here in this paper we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realisticmore » quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.« less

The Chandra X-Ray Observatory Radiation Environment Model

NASA Technical Reports Server (NTRS)

Blackwell, W. C.; Minow, Joseph I.; Smith, Shawn; Swift, Wesley R.; ODell, Stephen L.; Cameron, Robert A.

2003-01-01

CRMFLX (Chandra Radiation Model of ion FluX) is an environmental risk mitigation tool for use as a decision aid in planning the operations times for Chandra's Advanced CCD Imaging Spectrometer (ACIS) detector. The accurate prediction of the proton flux environment with energies of 100 - 200 keV is needed in order to protect the ACIS detector against proton degradation. Unfortunately, protons of this energy are abundant in the region of space Chandra must operate, and the on-board Electron, Proton, and Helium Instrument (EPHIN) does not measure proton flux levels of the required energy range. In addition to the concerns arising from the radiation belts, substorm injections of plasma from the magnetotail may increase the protons flux by orders of magnitude in this energy range. The Earth's magnetosphere is a dynamic entity, with the size and location of the magnetopause driven by the highly variable solar wind parameters (number density, velocity, and magnetic field components). Operational times for the telescope must be made weeks in advance, decisions which are complicated by the variability of the environment. CRMFLX is an engineering model developed to address these problems and provides proton flux and fluence statistics for the terrestrial outer magnetosphere, magnetosheath, and solar wind for use in scheduling ACIS operations. CRMFLX implements a number of standard models to predict the bow shock, magnetopause, and plasma sheet boundaries based on the sampling of historical solar wind data sets. Measurements from the GEOTAIL and POLAR spacecraft are used to create the proton flux database. This paper describes the recently released CRMFLX v2 implementation that includes an algorithm that propagates flux from an observation location to other regions of the magnetosphere based on convective ExB and VB-curvature particle drift motions in electric and magnetic fields. This technique has the advantage of more completely filling out the database and makes maximum use of limited data obtained during high Kp periods or in areas of the magnetosphere with poor satellite coverage.

[A Predictive Model for the Magnetic Field in the Heliosphere and Acceleration of Suprathermal Particles in the Solar Wind

NASA Technical Reports Server (NTRS)

Fisk, L. A.

2005-01-01

The purpose of this grant was to develop a theoretical understanding of the processes by which open magnetic flux undergoes large-scale transport in the solar corona, and to use this understanding to develop a predictive model for the heliospheric magnetic field, the configuration for which is determined by such motions.

Osmotically-driven membrane processes for water reuse and energy recovery

NASA Astrophysics Data System (ADS)

Achilli, Andrea

Osmotically-driven membrane processes are an emerging class of membrane separation processes that utilize concentrated brines to separate liquid streams. Their versatility of application make them an attractive alternative for water reuse and energy production/recovery. This work focused on innovative applications of osmotically-driven membrane processes. The novel osmotic membrane bioreactor (OMBR) system for water reuse was presented. Experimental results demonstrated high sustainable flux and relatively low reverse diffusion of solutes from the draw solution into the mixed liquor. Membrane fouling was minimal and controlled with osmotic backwashing. The OMBR system was found to remove greater than 99% of organic carbon and ammonium-nitrogen. Forward osmosis (FO) can employ different draw solution in its process. More than 500 inorganic compounds were screened as draw solution candidates, the desktop screening process resulted in 14 draw solutions suitable for FO applications. The 14 draw solutions were then tested in the laboratory to evaluate water flux and reverse salt diffusion through the membrane. Results indicated a wide range of water flux and reverse salt diffusion depending on the draw solution utilized. Internal concentration polarization was found to lower both water flux and reverse salt diffusion by reducing the draw solution concentration at the interface between the support and dense layer of the membrane. A small group of draw solutions was found to be most suitable for FO processes with currently available FO membranes. Another application of osmotically-driven membrane processes is pressure retarded osmosis (PRO). PRO was investigated as a viable source of renewable energy. A PRO model was developed to predict water flux and power density under specific experimental conditions. The predictive model was tested using experimental results from a bench-scale PRO system. Previous investigations of PRO were unable to verify model predictions due to the lack of suitable membranes and membrane modules. In this investigation, for the first time, the use of a custom-made laboratory-scale membrane module enabled the collection of experimental PRO data. Results obtained with a flat-sheet cellulose triacetate FO membrane and NaCl feed and draw solutions closely matched model predictions. Power density was substantially reduced due to internal concentration polarization in the asymmetric membrane and, to a lesser degree, to salt passage. External concentration polarization was found to exhibit a relatively small effect on reducing the osmotic pressure driving force. Using the predictive PRO model, optimal membrane characteristics and module configuration can be determined in order to design a system specifically tailored for PRO processes.

Impact of a Regional Drought on Terrestrial Carbon Fluxes and Atmospheric Carbon: Results from a Coupled Carbon Cycle Model

NASA Technical Reports Server (NTRS)

Lee, Eunjee; Koster, Randal D.; Ott, Lesley E.; Weir, Brad; Mahanama, Sarith; Chang, Yehui; Zeng, Fan-Wei

2017-01-01

Understanding the underlying processes that control the carbon cycle is key to predicting future global change. Much of the uncertainty in the magnitude and variability of the atmospheric carbon dioxide (CO2) stems from uncertainty in terrestrial carbon fluxes, and the relative impacts of temperature and moisture variations on regional and global scales are poorly understood. Here we investigate the impact of a regional drought on terrestrial carbon fluxes and CO2 mixing ratios over North America using the NASA Goddard Earth Observing System (GEOS) Model. Results show a sequence of changes in carbon fluxes and atmospheric CO2, induced by the drought. The relative contributions of meteorological changes to the neighboring carbon dynamics are also presented. The coupled modeling approach allows a direct quantification of the impact of the regional drought on local and proximate carbon exchange at the land surface via the carbon-water feedback processes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Post, Wilfred M; King, Anthony Wayne; Dragoni, Danilo

Many parameters in terrestrial biogeochemical models are inherently uncertain, leading to uncertainty in predictions of key carbon cycle variables. At observation sites, this uncertainty can be quantified by applying model-data fusion techniques to estimate model parameters using eddy covariance observations and associated biometric data sets as constraints. Uncertainty is reduced as data records become longer and different types of observations are added. We estimate parametric and associated predictive uncertainty at the Morgan Monroe State Forest in Indiana, USA. Parameters in the Local Terrestrial Ecosystem Carbon (LoTEC) are estimated using both synthetic and actual constraints. These model parameters and uncertainties aremore » then used to make predictions of carbon flux for up to 20 years. We find a strong dependence of both parametric and prediction uncertainty on the length of the data record used in the model-data fusion. In this model framework, this dependence is strongly reduced as the data record length increases beyond 5 years. If synthetic initial biomass pool constraints with realistic uncertainties are included in the model-data fusion, prediction uncertainty is reduced by more than 25% when constraining flux records are less than 3 years. If synthetic annual aboveground woody biomass increment constraints are also included, uncertainty is similarly reduced by an additional 25%. When actual observed eddy covariance data are used as constraints, there is still a strong dependence of parameter and prediction uncertainty on data record length, but the results are harder to interpret because of the inability of LoTEC to reproduce observed interannual variations and the confounding effects of model structural error.« less

Mullite ceramic membranes for industrial oily wastewater treatment: experimental and neural network modeling.

PubMed

Shokrkar, H; Salahi, A; Kasiri, N; Mohammadi, T

2011-01-01

In this paper, results of an experimental and modeling of separation of oil from industrial oily wastewaters (desalter unit effluent of Seraje, Ghom gas wells, Iran) with mullite ceramic membranes are presented. Mullite microfiltration symmetric membranes were synthesized from kaolin clay and alpha-alumina powder. The results show that the mullite ceramic membrane has a high total organic carbon and chemical oxygen demand rejection (94 and 89%, respectively), a low fouling resistance (30%) and a high final permeation flux (75 L/m2 h). Also, an artificial neural network, a predictive tool for tracking the inputs and outputs of a non-linear problem, is used to model the permeation flux decline during microfiltration of oily wastewater. The aim was to predict the permeation flux as a function of feed temperature, trans-membrane pressure, cross-flow velocity, oil concentration and filtration time, using a feed-forward neural network. Finally the structure of hidden layers and nodes in each layer with minimum error were reported leading to a 4-15 structure which demonstrated good agreement with the experimental measurements with an average error of less than 2%.

Modeling the 21 August 2017 Total Solar Eclipse: Prediction Results and New Techniques

NASA Astrophysics Data System (ADS)

Downs, C.; Mikic, Z.; Caplan, R. M.; Linker, J.; Lionello, R.; Torok, T.; Titov, V. S.; Riley, P.; MacKay, D.; Upton, L.

2017-12-01

As has been our tradition for past solar eclipses, we conducted a high resolution magnetohydrodynamic (MHD) simulation of the corona to predict the appearance of the 21 August 2017 solar eclipse. In this presentation, we discuss our model setup and our forward modeled predictions for the corona's appearance, including images of polarized brightness and EUV/soft X-Ray emission. We show how the combination of forward modeled observables and knowledge of the underlying magnetic field from the model can be used to interpret the structures seen during the eclipse. We also discuss two new features added to this year's prediction. First, in an attempt to improve the morphological shape of streamers in the low corona, we energize the large-scale magnetic field by emerging shear and canceling flux within filament channels. The handedness of the shear is deduced from a magnetofrictional model, which is driven by the evolving photospheric field produced by the Advective Flux Transport model. Second, we apply our new wave-turbulence-driven (WTD) model for coronal heating. This model has substantially fewer free parameters than previous empirical heating models, but is inherently sensitive to the 3D geometry and connectivity of the magnetic field--a key property for modeling the thermal-magnetic structure of the corona. We examine the effect of these considerations on forward modeled observables, and present them in the context of our final 2017 eclipse prediction (www.predsci.com/corona/aug2017eclipse). Research supported by NASA's Heliophysics Supporting Research and Living With a Star Programs.

Carbon Emissions from Deforestation in the Brazilian Amazon Region

NASA Technical Reports Server (NTRS)

Potter, C.; Klooster, S.; Genovese, V.

2009-01-01

A simulation model based on satellite observations of monthly vegetation greenness from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2002. The NASA-CASA (Carnegie Ames Stanford Approach) model estimates of annual forest production were used for the first time as the basis to generate a prediction for the standing pool of carbon in above-ground biomass (AGB; gC/sq m) for forested areas of the Brazilian Amazon region. Plot-level measurements of the residence time of carbon in wood in Amazon forest from Malhi et al. (2006) were interpolated by inverse distance weighting algorithms and used with CASA to generate a new regional map of AGB. Data from the Brazilian PRODES (Estimativa do Desflorestamento da Amazonia) project were used to map deforested areas. Results show that net primary production (NPP) sinks for carbon varied between 4.25 Pg C/yr (1 Pg=10(exp 15)g) and 4.34 Pg C for the region and were highest across the eastern and northern Amazon areas, whereas deforestation sources of CO2 flux from decomposition of residual woody debris were higher and less seasonal in the central Amazon than in the eastern and southern areas. Increased woody debris from past deforestation events was predicted to alter the net ecosystem carbon balance of the Amazon region to generate annual CO2 source fluxes at least two times higher than previously predicted by CASA modeling studies. Variations in climate, land cover, and forest burning were predicted to release carbon at rates of 0.5 to 1 Pg C/yr from the Brazilian Amazon. When direct deforestation emissions of CO2 from forest burning of between 0.2 and 0.6 Pg C/yr in the Legal Amazon are overlooked in regional budgets, the year-to-year variations in this net biome flux may appear to be large, whereas our model results implies net biome fluxes had actually been relatively consistent from year to year during the period 2000-2002. This is the first study to use MODIS data to model all carbon pools (wood, leaf, root) dynamically in simulations of Amazon forest deforestation from clearing and burning of all kinds.

Turbulent scalar flux transport in head-on quenching of turbulent premixed flames: a direct numerical simulations approach to assess models for Reynolds averaged Navier Stokes simulations

NASA Astrophysics Data System (ADS)

Lai, Jiawei; Alwazzan, Dana; Chakraborty, Nilanjan

2017-11-01

The statistical behaviour and the modelling of turbulent scalar flux transport have been analysed using a direct numerical simulation (DNS) database of head-on quenching of statistically planar turbulent premixed flames by an isothermal wall. A range of different values of Damköhler, Karlovitz numbers and Lewis numbers has been considered for this analysis. The magnitudes of the turbulent transport and mean velocity gradient terms in the turbulent scalar flux transport equation remain small in comparison to the pressure gradient, molecular dissipation and reaction-velocity fluctuation correlation terms in the turbulent scalar flux transport equation when the flame is away from the wall but the magnitudes of all these terms diminish and assume comparable values during flame quenching before vanishing altogether. It has been found that the existing models for the turbulent transport, pressure gradient, molecular dissipation and reaction-velocity fluctuation correlation terms in the turbulent scalar flux transport equation do not adequately address the respective behaviours extracted from DNS data in the near-wall region during flame quenching. Existing models for transport equation-based closures of turbulent scalar flux have been modified in such a manner that these models provide satisfactory prediction both near to and away from the wall.

Peculiarities of field penetration in the presence of cross-flux interaction

NASA Astrophysics Data System (ADS)

Berseth, V.; Buzdin, A. I.; Indenbom, M. V.; Benoit, W.

1996-02-01

The attractive core interaction between two orthogonal vortex lattices in alayered superconductor is calculated. When one of these lattices is moving, this interaction gives rise to a drag force acting on the other one. Considering a moving in-plane flux lattice, the effect of the drag force on the perpendicular flux is modelled through a modification of the bulk critical current for this field component. The new critical current depends on the direction of motion of both parallel and perpendicular vortices. The results are derived within the critical-state model for the infinite slab and for the thin strip. For this latter geometry, computations are made with the help of a new numerical method simulating flux penetration in the critical state. The new predicted qualitative phenomena (like the formation of a vortex-free region between two zones of opposite flux in the flat geometry) can be directly verified by the magneto-optic technique.

Rotating reverse osmosis: a dynamic model for flux and rejection

NASA Technical Reports Server (NTRS)

Lee, S.; Lueptow, R. M.

2001-01-01

Reverse osmosis (RO) is a compact process for the removal of ionic and organic pollutants from contaminated water. However, flux decline and rejection deterioration due to concentration polarization and membrane fouling hinders the application of RO technology. In this study, a rotating cylindrical RO membrane is theoretically investigated as a novel method to reduce polarization and fouling. A dynamic model based on RO membrane transport incorporating concentration polarization is used to predict the performance of rotating RO system. Operating parameters such as rotational speed and transmembrane pressure play an important role in determining the flux and rejection in rotating RO. For a given geometry, a rotational speed sufficient to generate Taylor vortices in the annulus is essential to maintain high flux as well as high rejection. The flux and rejection were calculated for wide range of operating pressures and rotational speeds. c 2001 Elsevier Science B.V. All rights reserved.

Dynamic flux balancing elucidates NAD(P)H production as limiting response to furfural inhibition in Saccharomyces cerevisiae.

PubMed

Pornkamol, Unrean; Franzen, Carl J

2015-08-01

Achieving efficient and economical lignocellulose-based bioprocess requires a robust organism tolerant to furfural, a major inhibitory compound present in lignocellulosic hydrolysate. The aim of this study was to develop a model that could generate quantitative descriptions of cell metabolism for elucidating the cell's adaptive response to furfural. Such a modelling tool could provide strategies for the design of more robust cells. A dynamic flux balance (dFBA) model of Saccharomyces cerevisiae was created by coupling a kinetic fermentation model with a previously published genome-scale stoichiometric model. The dFBA model was used for studying intracellular and extracellular flux responses to furfural perturbations under steady state and dynamic conditions. The predicted effects of furfural on dynamic flux profiles agreed well with previously published experimental results. The model showed that the yeast cell adjusts its metabolism in response to furfural challenge by increasing fluxes through the pentose phosphate pathway, TCA cycle, and proline and serine biosynthesis in order to meet the high demand of NAD(P)H cofactors. The model described here can be used to aid in systematic optimization of the yeast, as well as of the fermentation process, for efficient lignocellulosic ethanol production. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicted Water and Carbon Fluxes as well as Vegetation Distribution on the Korean Peninsula in the Future with the Ecosystem Demography Model version 2

NASA Astrophysics Data System (ADS)

Kim, J. B.; Kim, Y.

2017-12-01

This study investigates how the water and carbon fluxes as well as vegetation distribution on the Korean peninsula would vary with climate change. Ecosystem Demography (ED) Model version 2 (ED2) is used in this study, which is an integrated terrestrial biosphere model that can utilize a set of size- and age- structured partial differential equations that track the changing structure and composition of the plant canopy. With using the vegetation distribution data of Jeju Island, located at the southern part of the Korean Peninsula, ED2 is setup and driven for the past 10 years. Then the results of ED2 are evaluated and adjusted with observed forestry data, i.e., growth and mortality, and the flux tower and MODIS satellite data, i.e., evapotranspiration (ET) and gross primary production (GPP). This adjusted ED2 are used to simulate the water and carbon fluxes as well as vegetation dynamics in the Korean Peninsula for the historical period with evaluating the model against the MODIS satellite data. Finally, the climate scenarios of RCP 2.6 and 6.0 are used to predict the fluxes and vegetation distribution of the Korean Peninsula in the future. With using the state-of-art terrestrial ecosystem model, this study would provide us better understanding of the future ecosystem vulnerability of the Korean Peninsula. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800) and by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180. This work was also supported by the Yonsei University Future-leading Research Initiative of 2015(2016-22-0061).

Dynamic response of a modified water tank exposed to concentrated solar energy

NASA Astrophysics Data System (ADS)

Alhamdo, M. H.; Alkhakani, A. J.

2017-08-01

Power generation by using concentrated solar thermal energy on liquid enclosures is one of the most promising renewable energy technologies. In this work, a developed liquid enclosure fitted with various number and configurations of horizontal metal rings have been analyzed, fabricated and tested. The influence of adding metal rings arrangement is investigated for its potential to enhance radial heat conduction to the center-line of the enclosure from the side-walls. Experiments were carried out for fluid in both static and dynamic modes of operation inside the enclosure that subjected to high heat flux. A developed two-dimensional CFD model to predict the transient flow and thermal fields within liquid enclosure subjected to heat flux has been developed and tested. The developed numerical model takes into consideration energy transport between the liquid inside enclosure and the solid material of the enclosure. The numerical simulations have been compared with experimental measurement. The computational code has been found in a good level of agreement with the experimental data except for liquid at the peak part of the enclosure. The results indicate that adding metal rings produce significant impact on the transient temperature difference inside enclosure during both static and dynamic modes. The six-ring model is found to be more effective for enhancing radial heat transfer than other three models that have been tested. The in-line arrangement is found to provide better thermal effect as compared to the staggered rings. Two new correlations for natural heat transfer inside liquid enclosures subjected to high heat flux have been formulated (one for no-ring model and the other for six-ring model). The natural Nusselt number is found to be around a constant value for Rayleigh number less than (5 X 108). The recommended use of metal rings inside liquid enclosures subjected to heat flux, and the predicted Nusselt number correlation, will add to local knowledge a significant mean to gain more heat in large scale concentrated solar power plants. Two new correlations for natural heat transfer inside liquid enclosures subjected to high heat flux have been formulated (one for no-ring model and the other for six-ring model). The natural Nusselt number is found to be around a constant value for Rayleigh number less than (5 X 108). The recommended use of metal rings inside liquid enclosures subjected to heat flux, and the predicted Nusselt number correlation, will add to local knowledge a significant mean to gain more heat in large scale concentrated solar power plants.

Comparison of Flux-Surface Aligned Curvilinear Coordinate Systems and Neoclassical Magnetic Field Predictions

NASA Astrophysics Data System (ADS)

Collart, T. G.; Stacey, W. M.

2015-11-01

Several methods are presented for extending the traditional analytic ``circular'' representation of flux-surface aligned curvilinear coordinate systems to more accurately describe equilibrium plasma geometry and magnetic fields in DIII-D. The formalism originally presented by Miller is extended to include different poloidal variations in the upper and lower hemispheres. A coordinate system based on separate Fourier expansions of major radius and vertical position greatly improves accuracy in edge plasma structure representation. Scale factors and basis vectors for a system formed by expanding the circular model minor radius can be represented using linear combinations of Fourier basis functions. A general method for coordinate system orthogonalization is presented and applied to all curvilinear models. A formalism for the magnetic field structure in these curvilinear models is presented, and the resulting magnetic field predictions are compared against calculations performed in a Cartesian system using an experimentally based EFIT prediction for the Grad-Shafranov equilibrium. Supported by: US DOE under DE-FG02-00ER54538.

Comparison of Heat and Moisture Fluxes from a Modified Soil-plant-atmosphere Model with Observations from BOREAS. Chapter 3

NASA Technical Reports Server (NTRS)

Lee, Young-Hee; Mahrt, L.

2005-01-01

This study evaluates the prediction of heat and moisture fluxes from a new land surface scheme with eddy correlation data collected at the old aspen site during the Boreal Ecosystem-Atmosphere Study (BOREAS) in 1994. The model used in this study couples a multilayer vegetation model with a soil model. Inclusion of organic material in the upper soil layer is required to adequately simulate exchange between the soil and subcanopy air. Comparisons between the model and observations are discussed to reveal model misrepresentation of some aspects of the diurnal variation of subcanopy processes. Evapotranspiration

Electromagnetic Torque in Tokamaks with Toroidal Asymmetries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Logan, Nikolas Christopher

2015-01-01

Lithium and boron coatings are applied to the walls of many tokamaks to enhance performance and protect the underlying substrates. Li and B-coated high-Z substrates are planned for use in NSTX-U and are a candidate plasma-facing component (PFC) for DEMO. However, previous measurements of Li evaporation and thermal sputtering on low-flux devices indicate that the Li temperature permitted on such devices may be unacceptably low. Thus it is crucial to characterize gross and net Li erosion rates under high-flux plasma bombardment. Additionally, no quantitative measurements have been performed of the erosion rate of a boron-coated PFC during plasma bombardment. Amore » realistic model for the compositional evolution of a Li layer under D bombardment was developed that incorporates adsorption, implantation, and diffusion. A model was developed for temperature-dependent mixed-material Li-D erosion that includes evaporation, physical sputtering, chemical sputtering, preferential sputtering, and thermal sputtering. The re-deposition fraction of a Li coating intersecting a linear plasma column was predicted using atomic physics information and by solving the Li continuity equation. These models were tested in the Magnum-PSI linear plasma device at ion fluxes of 10^23-10^24 m^-2 s^-1 and Li surface temperatures less than 800 degrees C. Li erosion was measured during bombardment with a neon plasma that will not chemically react with Li and the results agreed well with the erosion model. Next the ratio of the total D fluence to the areal density of the Li coating was varied to quantify differences in Li erosion under D plasma bombardment as a function of the D concentration. The ratio of D/Li atoms was calculated using the results of MD simulations and good agreement is observed between measurements and the predictions of the mixed-material erosion model. Li coatings are observed to disappear from graphite much faster than from TZM Mo, indicating that fast Li diffusion into the bulk graphite substrate occurred, as predicted. Li re-deposition fractions very close to unity are observed in Magnum-PSI, as predicted by modeling. Finally, predictions of Li coating lifetimes in the NSTX-U divertor are calculated. The gross erosion rate of boron coatings was also measured for the first time in a high-flux plasma device.« less

Eddy Covariance Measurements Assessing NOx Emission in London, UK

NASA Astrophysics Data System (ADS)

Drysdale, W. S.; Lee, J. D.; Purvis, R.; Squires, F. A.; Vaughan, A. R.; Metzger, S.

2017-12-01

NOx (the sum of NO + NO2) is emitted during most combustion processes. NO2is a well known air pollutant detrimental to human health, and is regulated in many cities. London often finds itself in breach of these emission regulations. Emission inventories are used in air quality forecast models to predict current and future air pollution levels and to guide abatement strategy. It is therefore crucial that inventories accurately predict emissions; validation can be carried out using direct measurements. Measurements of NO and NO2 at 5 Hz have been made at the BT Tower, 190 m above street level in central London. Eddy covariance calculations have been performed using both classical and "continuous wavelet transformation" method, producing half hour and 1 minute resolved NOx fluxes respectively. We present a first look at these flux data measured in early 2017. A strong diurnal profile for NOx flux is observed, with an increase from 5am to 7am, and remaining constant around 1400 ng m2 m-1 throughout the day, before decreasing to background levels towards midnight. Data is also compared to previous NOx flux measurements over two periods, June-July 2012 and March-April 2013 to examine how emissions have changed over this period. A significant decrease in NOx emissions ( 64%, a mean flux of 2400 ng m2 s-1 in 2012 to a mean 870 ng m2 s-1 in 2017) is observed. When the fluxes are separated by wind flow from the east and west, there is negligible difference in 2017, where 2012 saw lower fluxes from the east, especially in the afternoon. By coupling the measurements with a footprint model we compare the data to emission estimates from the UK's National Atmospheric Emission Inventory (NAEI). In 2012-13 emissions were measured to be twice as high than the NAEI predicted and the latest data shows a much better agreement.

Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling

USGS Publications Warehouse

Briggs, Martin A.; Lautz, Laura K.; Buckley, Sean F.; Lane, John W.

2014-01-01

Groundwater upwelling to streams creates unique habitat by influencing stream water quality and temperature; upwelling zones also serve as vectors for contamination when groundwater is degraded. Temperature time series data acquired along vertical profiles in the streambed have been applied to simple analytical models to determine rates of vertical fluid flux. These models are based on the downward propagation characteristics (amplitude attenuation and phase-lag) of the surface diurnal signal. Despite the popularity of these models, there are few published characterizations of moderate-to-strong upwelling. We attribute this limitation to the thermodynamics of upwelling, under which the downward conductive signal transport from the streambed interface occurs opposite the upward advective fluid flux. Governing equations describing the advection–diffusion of heat within the streambed predict that under upwelling conditions, signal amplitude attenuation will increase, but, counterintuitively, phase-lag will decrease. Therefore the extinction (measurable) depth of the diurnal signal is very shallow, but phase lag is also short, yielding low signal to noise ratio and poor model sensitivity. Conversely, amplitude attenuation over similar sensor spacing is strong, yielding greater potential model sensitivity. Here we present streambed thermal time series over a range of moderate to strong upwelling sites in the Quashnet River, Cape Cod, Massachusetts. The predicted inverse relationship between phase-lag and rate of upwelling was observed in the field data over a range of conditions, but the observed phase-lags were consistently shorter than predicted. Analytical solutions for fluid flux based on signal amplitude attenuation return results consistent with numerical models and physical seepage meters, but the phase-lag analytical model results are generally unreasonable. Through numerical modeling we explore reasons why phase-lag may have been over-predicted by the analytical models, and develop guiding relations of diurnal temperature signal extinction depth based on stream diurnal signal amplitude, upwelling magnitude, and streambed thermal properties that will be useful in designing future experiments.

Development of a New Model for Accurate Prediction of Cloud Water Deposition on Vegetation

NASA Astrophysics Data System (ADS)

Katata, G.; Nagai, H.; Wrzesinsky, T.; Klemm, O.; Eugster, W.; Burkard, R.

2006-12-01

Scarcity of water resources in arid and semi-arid areas is of great concern in the light of population growth and food shortages. Several experiments focusing on cloud (fog) water deposition on the land surface suggest that cloud water plays an important role in water resource in such regions. A one-dimensional vegetation model including the process of cloud water deposition on vegetation has been developed to better predict cloud water deposition on the vegetation. New schemes to calculate capture efficiency of leaf, cloud droplet size distribution, and gravitational flux of cloud water were incorporated in the model. Model calculations were compared with the data acquired at the Norway spruce forest at the Waldstein site, Germany. High performance of the model was confirmed by comparisons of calculated net radiation, sensible and latent heat, and cloud water fluxes over the forest with measurements. The present model provided a better prediction of measured turbulent and gravitational fluxes of cloud water over the canopy than the Lovett model, which is a commonly used cloud water deposition model. Detailed calculations of evapotranspiration and of turbulent exchange of heat and water vapor within the canopy and the modifications are necessary for accurate prediction of cloud water deposition. Numerical experiments to examine the dependence of cloud water deposition on the vegetation species (coniferous and broad-leaved trees, flat and cylindrical grasses) and structures (Leaf Area Index (LAI) and canopy height) are performed using the presented model. The results indicate that the differences of leaf shape and size have a large impact on cloud water deposition. Cloud water deposition also varies with the growth of vegetation and seasonal change of LAI. We found that the coniferous trees whose height and LAI are 24 m and 2.0 m2m-2, respectively, produce the largest amount of cloud water deposition in all combinations of vegetation species and structures in the experiments.

A search of UARS data for ozone depletions caused by the highly relativistic electron precipitation events of May 1992

NASA Astrophysics Data System (ADS)

Pesnell, W. Dean; Goldberg, Richard A.; Jackman, Charles H.; Chenette, D. L.; Gaines, E. E.

1999-01-01

Highly relativistic electron precipitation (HRE) events containing significant fluxes of electrons with E>1MeV have been predicted by models to deplete mesospheric ozone. For the electron fluxes measured during the great HRE of May 1992, depletions were predicted to occur between altitudes of 55 and 80 km, where HOx reactions cause a local minimum in the ozone number density and mixing ratio. Measurements of the precipitating electron fluxes by the particle environment monitor (PEM) tend to underestimate their intensity; thus the predictions of ozone depletion should be considered an estimate of a lower limit. Since the horizontal distribution of the electron precipitation follows the terrestrial magnetic field, it would show a distinct boundary equatorward of the L=3 magnetic shell and be readily distinguished from material that was not affected by the HRE precipitation. To search for possible ozone depletion effects, we have analyzed data from the cryogenic limb array etalon spectrometer and microwave limb sounder instruments on UARS for the above HRE. A simplified diurnal model is proposed to understand the ozone data from UARS, also illustrating the limitations of the UARS instruments for seeing the ozone depletions caused by the HRE events. This diurnal analysis limits the relative ozone depletion at around 60 km altitude to values of <10% during the very intense May 1992 event, consistent with our prediction using an improved Goddard Space Flight Center two-dimensional model.

Measurement of Coherent π+ Production in Low Energy Neutrino-Carbon Scattering

NASA Astrophysics Data System (ADS)

Abe, K.; Andreopoulos, C.; Antonova, M.; Aoki, S.; Ariga, A.; Assylbekov, S.; Autiero, D.; Ban, S.; Barbi, M.; Barker, G. J.; Barr, G.; Bartet-Friburg, P.; Batkiewicz, M.; Bay, F.; Berardi, V.; Berkman, S.; Bhadra, S.; Blondel, A.; Bolognesi, S.; Bordoni, S.; Boyd, S. B.; Brailsford, D.; Bravar, A.; Bronner, C.; Buizza Avanzini, M.; Calland, R. G.; Campbell, T.; Cao, S.; Caravaca Rodríguez, J.; Cartwright, S. L.; Castillo, R.; Catanesi, M. G.; Cervera, A.; Cherdack, D.; Chikuma, N.; Christodoulou, G.; Clifton, A.; Coleman, J.; Collazuol, G.; Coplowe, D.; Cremonesi, L.; Dabrowska, A.; De Rosa, G.; Dealtry, T.; Denner, P. F.; Dennis, S. R.; Densham, C.; Dewhurst, D.; Di Lodovico, F.; Di Luise, S.; Dolan, S.; Drapier, O.; Duffy, K. E.; Dumarchez, J.; Dytman, S.; Dziewiecki, M.; Emery-Schrenk, S.; Ereditato, A.; Feusels, T.; Finch, A. J.; Fiorentini, G. A.; Friend, M.; Fujii, Y.; Fukuda, D.; Fukuda, Y.; Furmanski, A. P.; Galymov, V.; Garcia, A.; Giffin, S. G.; Giganti, C.; Gizzarelli, F.; Gonin, M.; Grant, N.; Hadley, D. R.; Haegel, L.; Haigh, M. D.; Hamilton, P.; Hansen, D.; Harada, J.; Hara, T.; Hartz, M.; Hasegawa, T.; Hastings, N. C.; Hayashino, T.; Hayato, Y.; Helmer, R. L.; Hierholzer, M.; Hillairet, A.; Himmel, A.; Hiraki, T.; Hirota, S.; Hogan, M.; Holeczek, J.; Horikawa, S.; Hosomi, F.; Huang, K.; Ichikawa, A. K.; Ieki, K.; Ikeda, M.; Imber, J.; Insler, J.; Intonti, R. A.; Irvine, T. J.; Ishida, T.; Ishii, T.; Iwai, E.; Iwamoto, K.; Izmaylov, A.; Jacob, A.; Jamieson, B.; Jiang, M.; Johnson, S.; Jo, J. H.; Jonsson, P.; Jung, C. K.; Kabirnezhad, M.; Kaboth, A. C.; Kajita, T.; Kakuno, H.; Kameda, J.; Karlen, D.; Karpikov, I.; Katori, T.; Kearns, E.; Khabibullin, M.; Khotjantsev, A.; Kielczewska, D.; Kikawa, T.; Kim, H.; Kim, J.; King, S.; Kisiel, J.; Knight, A.; Knox, A.; Kobayashi, T.; Koch, L.; Koga, T.; Konaka, A.; Kondo, K.; Kopylov, A.; Kormos, L. L.; Korzenev, A.; Koshio, Y.; Kropp, W.; Kudenko, Y.; Kurjata, R.; Kutter, T.; Lagoda, J.; Lamont, I.; Larkin, E.; Lasorak, P.; Laveder, M.; Lawe, M.; Lazos, M.; Lindner, T.; Liptak, Z. J.; Litchfield, R. P.; Li, X.; Longhin, A.; Lopez, J. P.; Ludovici, L.; Lu, X.; Magaletti, L.; Mahn, K.; Malek, M.; Manly, S.; Marino, A. D.; Marteau, J.; Martin, J. F.; Martins, P.; Martynenko, S.; Maruyama, T.; Matveev, V.; Mavrokoridis, K.; Ma, W. Y.; Mazzucato, E.; McCarthy, M.; McCauley, N.; McFarland, K. S.; McGrew, C.; Mefodiev, A.; Metelko, C.; Mezzetto, M.; Mijakowski, P.; Minamino, A.; Mineev, O.; Mine, S.; Missert, A.; Miura, M.; Moriyama, S.; Mueller, Th. A.; Murphy, S.; Myslik, J.; Nakadaira, T.; Nakahata, M.; Nakamura, K. G.; Nakamura, K.; Nakamura, K. D.; Nakayama, S.; Nakaya, T.; Nakayoshi, K.; Nantais, C.; Nielsen, C.; Nirkko, M.; Nishikawa, K.; Nishimura, Y.; Novella, P.; Nowak, J.; O'Keeffe, H. M.; Ohta, R.; Okumura, K.; Okusawa, T.; Oryszczak, W.; Oser, S. M.; Ovsyannikova, T.; Owen, R. A.; Oyama, Y.; Palladino, V.; Palomino, J. L.; Paolone, V.; Patel, N. D.; Pavin, M.; Payne, D.; Perkin, J. D.; Petrov, Y.; Pickard, L.; Pickering, L.; Pinzon Guerra, E. S.; Pistillo, C.; Popov, B.; Posiadala-Zezula, M.; Poutissou, J.-M.; Poutissou, R.; Przewlocki, P.; Quilain, B.; Radermacher, T.; Radicioni, E.; Ratoff, P. N.; Ravonel, M.; Rayner, M. A. M.; Redij, A.; Reinherz-Aronis, E.; Riccio, C.; Rojas, P.; Rondio, E.; Roth, S.; Rubbia, A.; Rychter, A.; Sacco, R.; Sakashita, K.; Sánchez, F.; Sato, F.; Scantamburlo, E.; Scholberg, K.; Schoppmann, S.; Schwehr, J.; Scott, M.; Seiya, Y.; Sekiguchi, T.; Sekiya, H.; Sgalaberna, D.; Shah, R.; Shaikhiev, A.; Shaker, F.; Shaw, D.; Shiozawa, M.; Shirahige, T.; Short, S.; Smy, M.; Sobczyk, J. T.; Sobel, H.; Sorel, M.; Southwell, L.; Stamoulis, P.; Steinmann, J.; Stewart, T.; Stowell, P.; Suda, Y.; Suvorov, S.; Suzuki, A.; Suzuki, K.; Suzuki, S. Y.; Suzuki, Y.; Tacik, R.; Tada, M.; Takahashi, S.; Takeda, A.; Takeuchi, Y.; Tanaka, H. K.; Tanaka, H. A.; Terhorst, D.; Terri, R.; Thakore, T.; Thompson, L. F.; Tobayama, S.; Toki, W.; Tomura, T.; Touramanis, C.; Tsukamoto, T.; Tzanov, M.; Uchida, Y.; Vacheret, A.; Vagins, M.; Vallari, Z.; Vasseur, G.; Wachala, T.; Wakamatsu, K.; Walter, C. W.; Wark, D.; Warzycha, W.; Wascko, M. O.; Weber, A.; Wendell, R.; Wilkes, R. J.; Wilking, M. J.; Wilkinson, C.; Wilson, J. R.; Wilson, R. J.; Yamada, Y.; Yamamoto, K.; Yamamoto, M.; Yanagisawa, C.; Yano, T.; Yen, S.; Yershov, N.; Yokoyama, M.; Yoo, J.; Yoshida, K.; Yuan, T.; Yu, M.; Zalewska, A.; Zalipska, J.; Zambelli, L.; Zaremba, K.; Ziembicki, M.; Zimmerman, E. D.; Zito, M.; Żmuda, J.; T2K Collaboration

2016-11-01

We report the first measurement of the flux-averaged cross section for charged current coherent π+ production on carbon for neutrino energies less than 1.5 GeV, and with a restriction on the final state phase space volume in the T2K near detector, ND280. Comparisons are made with predictions from the Rein-Sehgal coherent production model and the model by Alvarez-Ruso et al., the latter representing the first implementation of an instance of the new class of microscopic coherent models in a neutrino interaction Monte Carlo event generator. We observe a clear event excess above background, disagreeing with the null results reported by K2K and SciBooNE in a similar neutrino energy region. The measured flux-averaged cross sections are below those predicted by both the Rein-Sehgal and Alvarez-Ruso et al. models.

Short-Term Forecasting of Radiation Belt and Ring Current

NASA Technical Reports Server (NTRS)

Fok, Mei-Ching

2007-01-01

A computer program implements a mathematical model of the radiation-belt and ring-current plasmas resulting from interactions between the solar wind and the Earth s magnetic field, for the purpose of predicting fluxes of energetic electrons (10 keV to 5 MeV) and protons (10 keV to 1 MeV), which are hazardous to humans and spacecraft. Given solar-wind and interplanetary-magnetic-field data as inputs, the program solves the convection-diffusion equations of plasma distribution functions in the range of 2 to 10 Earth radii. Phenomena represented in the model include particle drifts resulting from the gradient and curvature of the magnetic field; electric fields associated with the rotation of the Earth, convection, and temporal variation of the magnetic field; and losses along particle-drift paths. The model can readily accommodate new magnetic- and electric-field submodels and new information regarding physical processes that drive the radiation-belt and ring-current plasmas. Despite the complexity of the model, the program can be run in real time on ordinary computers. At present, the program can calculate present electron and proton fluxes; after further development, it should be able to predict the fluxes 24 hours in advance

A calculation of the radiation environment on the Martian surface

NASA Astrophysics Data System (ADS)

de Wet, Wouter C.; Townsend, Lawrence W.

2017-08-01

In this work, the radiation environment on the Martian surface, as produced by galactic cosmic radiation incident on the atmosphere, is modeled using the Monte Carlo radiation transport code, High Energy Transport Code-Human Exploration and Development in Space (HETC-HEDS). This work is performed in participation of the 2016 Mars Space Radiation Modeling Workshop held in Boulder, CO, and is part of a larger collaborative effort to study the radiation environment on the surface of Mars. Calculated fluxes for neutrons, protons, deuterons, tritons, helions, alpha particles, and heavier ions up to Fe are compared with measurements taken by Radiation Assessment Detector (RAD) instrument aboard the Mars Science Laboratory over a period of 2 months. The degree of agreement between measured and calculated surface flux values over the limited energy range of the measurements is found to vary significantly depending on the particle species or group. However, in many cases the fluxes predicted by HETC-HEDS fall well within the experimental uncertainty. The calculated results for alpha particles and the heavy ion groups Z = 3-5, Z = 6-8, Z = 9-13 and Z > 24 are in the best agreement, each with an average relative difference from measured data of less than 40%. Predictions for neutrons, protons, deuterons, tritons, Helium-3, and the heavy ion group Z = 14-24 have differences from the measurements, in some cases, greater than 50%. Future updates to the secondary light particle production methods in the nuclear model within HETC-HEDS are expected to improve light ion flux predictions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seco, Roger; Karl, Thomas; Guenther, Alex B.

Considerable amounts and varieties of biogenic volatile organic compounds (BVOCs) are exchanged between vegeta-tion and the surrounding air. These BVOCs play key ecological and atmospheric roles that must be adequately repre-sented for accurately modeling the coupled biosphere–atmosphere–climate earth system. One key uncertainty in existing models is the response of BVOC fluxes to an important global change process: drought. We describe the diur-nal and seasonal variation in isoprene, monoterpene, and methanol fluxes from a temperate forest ecosystem before, during, and after an extreme 2012 drought event in the Ozark region of the central USA. BVOC fluxes were domi-nated by isoprene, whichmore » attained high emission rates of up to 35.4 mg m -2h -1 at midday. Methanol fluxes were characterized by net deposition in the morning, changing to a net emission flux through the rest of the daylight hours. Net flux of CO 2 reached its seasonal maximum approximately a month earlier than isoprenoid fluxes, which high-lights the differential response of photosynthesis and isoprenoid emissions to progressing drought conditions. Never-theless, both processes were strongly suppressed under extreme drought, although isoprene fluxes remained relatively high compared to reported fluxes from other ecosystems. Methanol exchange was less affected by drought throughout the season, conflrming the complex processes driving biogenic methanol fluxes. The fraction of daytime (7–17 h) assimilated carbon released back to the atmosphere combining the three BVOCs measured was 2% of gross primary productivity (GPP) and 4.9% of net ecosystem exchange (NEE) on average for our whole measurement cam-paign, while exceeding 5% of GPP and 10% of NEE just before the strongest drought phase. The MEGANv2.1 model correctly predicted diurnal variations in fluxes driven mainly by light and temperature, although further research is needed to address model BVOC fluxes during drought events.« less

Assessing impacts of PBL and surface layer schemes in simulating the surface–atmosphere interactions and precipitation over the tropical ocean using observations from AMIE/DYNAMO

DOE PAGES

Qian, Yun; Yan, Huiping; Berg, Larry K.; ...

2016-10-28

Accuracy of turbulence parameterization in representing Planetary Boundary Layer (PBL) processes in climate models is critical for predicting the initiation and development of clouds, air quality issues, and underlying surface-atmosphere-cloud interactions. In this study, we 1) evaluate WRF model-simulated spatial patterns of precipitation and surface fluxes, as well as vertical profiles of potential temperature, humidity, moist static energy and moisture tendency terms as simulated by WRF at various spatial resolutions and with PBL, surface layer and shallow convection schemes against measurements, 2) identify model biases by examining the moisture tendency terms contributed by PBL and convection processes through nudging experiments,more » and 3) evaluate the dependence of modeled surface latent heat (LH) fluxes onPBL and surface layer schemes over the tropical ocean. The results show that PBL and surface parameterizations have surprisingly large impacts on precipitation, convection initiation and surface moisture fluxes over tropical oceans. All of the parameterizations tested tend to overpredict moisture in PBL and free atmosphere, and consequently result in larger moist static energy and precipitation. Moisture nudging tends to suppress the initiation of convection and reduces the excess precipitation. The reduction in precipitation bias in turn reduces the surface wind and LH flux biases, which suggests that the model drifts at least partly because of a positive feedback between precipitation and surface fluxes. The updated shallow convection scheme KF-CuP tends to suppress the initiation and development of deep convection, consequently decreasing precipitation. The Eta surface layer scheme predicts more reasonable LH fluxes and the LH-Wind Speed relationship than the MM5 scheme, especially when coupled with the MYJ scheme. By examining various parameterization schemes in WRF, we identify sources of biases and weaknesses of current PBL, surface layer and shallow convection schemes in reproducing PBL processes, the initiation of convection and intra-seasonal variability of precipitation.« less

Sensitivity of Vadose Zone Water Fluxes to Climate Shifts in Arid Settings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pfletschinger, H.; Prömmel, K.; Schüth, C.

2014-01-01

Vadose zone water fluxes in arid settings are investigated regarding their sensitivity to hydraulic soil parameters and meteorological data. The study is based on the inverse modeling of highly defined soil column experiments and subsequent scenario modeling comparing different climate projections for a defined arid region. In arid regions, groundwater resources are prone to depletion due to excessive water use and little recharge potential. Especially in sand dune areas, groundwater recharge is highly dependent on vadose zone properties and corresponding water fluxes. Nevertheless, vadose zone water fluxes under arid conditions are hard to determine owing to, among other reasons, deepmore » vadose zones with generally low fluxes and only sporadic high infiltration events. In this study, we present an inverse model of infiltration experiments accounting for variable saturated nonisothermal water fluxes to estimate effective hydraulic and thermal parameters of dune sands. A subsequent scenario modeling links the results of the inverse model with projections of a global climate model until 2100. The scenario modeling clearly showed the high dependency of groundwater recharge on precipitation amounts and intensities, whereas temperature increases are only of minor importance for deep infiltration. However, simulated precipitation rates are still affected by high uncertainties in the response to the hydrological input data of the climate model. Thus, higher certainty in the prediction of precipitation pattern is a major future goal for climate modeling to constrain future groundwater management strategies in arid regions.« less

"Modeled and measured carbon cycling in Mojave Desert soils: toward present and projected greenhouse gas budgets for arid regions

NASA Astrophysics Data System (ADS)

Maurer, G. E.; Amundson, R.; Lammers, L. N.; Mills, J.; Oerter, E.

2017-12-01

Drylands comprise roughly 35% of the Earth's surface, store globally significant amounts of carbon, and cycle this carbon at rates that vary greatly from year to year. Consequently, drylands are thought to contribute to inter-annual changes in the global atmospheric CO2 budget. Sparse measurements and limited process-based modeling have made quantifying dryland carbon cycling at regional or larger scales a major challenge. We parameterized and ran the DayCent model, an ecosystem model that simulates soil C and N cycling and greenhouse gas (GHG) fluxes, using long-term regional climate, soil, and vegetation data for the Mojave Desert region (southwest USA). DayCent predicted somewhat greater soil organic C than was observed in a database of 186 measured Mojave soil survey samples, but successfully recreated climate-driven patterns in soil carbon storage across the landscape. Modeled soil organic carbon storage increased by between 4.1 and 5.1 kg/m2 per km of elevation gained, while Mojave soil survey data indicated an increase of 4.6 kg/m2. Model predictions of soil CO2 flux were validated and calibrated against field observations from ten Mojave soil gas profile studies sampled intermittently between 1986 and the present. DayCent had a tendency to overestimate soil respiration measured at some sites by up to 600% compared to profile measurements. Modeled soil CO2 fluxes increased by between 1280 and 4141 kg/ha/yr per km of elevation gained.This elevational pattern did not match well with landscape-level changes in observed soil profile CO2 flux data, indicating further calibration of DayCent will be needed to produce regional estimates of GHG flux. This ongoing synthesis of modeling and measurements extends the current knowledge of the Mojave's contribution to the global GHG budget and will provide a basis from which to project future emissions from the Mojave and other dryland regions.

Coupled carbon-water exchange of the Amazon rain forest, II. Comparison of predicted and observed seasonal exchange of energy, CO2, isoprene and ozone at a remote site in Rondônia

NASA Astrophysics Data System (ADS)

Simon, E.; Meixner, F. X.; Rummel, U.; Ganzeveld, L.; Ammann, C.; Kesselmeier, J.

2005-04-01

A one-dimensional multi-layer scheme describing the coupled exchange of energy and CO2, the emission of isoprene and the dry deposition of ozone is applied to a rain forest canopy in southwest Amazonia. The model was constrained using mean diel cycles of micrometeorological quantities observed during two periods in the wet and dry season 1999. Predicted net fluxes and concentration profiles for both seasonal periods are compared to observations made at two nearby towers.

The predicted day- and nighttime thermal stratification of the canopy layer is consistent with observations in dense canopies. The observed and calculated net fluxes above and H2O and CO2 concentration profiles within the canopy show a good agreement. The predicted net carbon sink decreases from 2.5 t C ha-1yr-1 for wet season conditions to 1 t C ha-1yr-1 for dry season conditions, whereas observed and predicted midday Bowen ratio increases from 0.5 to 0.8. The evaluation results confirmed a seasonal variability of leaf physiological parameters, as already suggested in the companion study. The predicted midday canopy net flux of isoprene increased from 7.1 mg C m-2h-1 during the wet season to 11.4 mg C m-2h-1 during the late dry season. Applying a constant emission capacity in all canopy layers, resulted in a disagreement between observed and simulated profiles of isoprene concentrations, suggesting a smaller emission capacity of shade adapted leaves and deposition to the soil or leaf surfaces. Assuming a strong light acclimation of emission capacity, equivalent to a 66% reduction of the standard emission factor for leaves in the lower canopy, resulted in a better agreement of observed and calculated concentration profiles and a 30% reduction of the canopy net flux. The mean calculated ozone flux for dry season condition at noontime was ≍12 nmol m-2s-1, agreeing well with observed values. The corresponding deposition velocity increased from 0.8 cm s-1 to >1.6 cm s-1 in the wet season, which can not be explained by increased stomatal uptake. Considering reasonable physiological changes in stomatal regulation, the predicted value was not larger than 1.05 cm s-1. Instead, the observed fluxes could be explained with the model by decreasing the cuticular resistance to ozone deposition from 5000 to 1000 s m-1. For doubled atmospheric CO2 concentrations the model predicts a strong increase of surface temperatures (0.1-1°C) and net assimilation (22%), a considerable shift in the energy budget (≍25% decreasing transpiration and increasing sensible heat), a slight increase of isoprene emissions (10%) and a strong decrease of ozone deposition (35%).

Coupled carbon-water exchange of the Amazon rain forest, I. Model description, parameterization and sensitivity analysis

NASA Astrophysics Data System (ADS)

Simon, E.; Meixner, F. X.; Ganzeveld, L.; Kesselmeier, J.

2005-04-01

Detailed one-dimensional multilayer biosphere-atmosphere models, also referred to as CANVEG models, are used for more than a decade to describe coupled water-carbon exchange between the terrestrial vegetation and the lower atmosphere. Within the present study, a modified CANVEG scheme is described. A generic parameterization and characterization of biophysical properties of Amazon rain forest canopies is inferred using available field measurements of canopy structure, in-canopy profiles of horizontal wind speed and radiation, canopy albedo, soil heat flux and soil respiration, photosynthetic capacity and leaf nitrogen as well as leaf level enclosure measurements made on sunlit and shaded branches of several Amazonian tree species during the wet and dry season. The sensitivity of calculated canopy energy and CO2 fluxes to the uncertainty of individual parameter values is assessed. In the companion paper, the predicted seasonal exchange of energy, CO2, ozone and isoprene is compared to observations.

A bi-modal distribution of leaf area density with a total leaf area index of 6 is inferred from several observations in Amazonia. Predicted light attenuation within the canopy agrees reasonably well with observations made at different field sites. A comparison of predicted and observed canopy albedo shows a high model sensitivity to the leaf optical parameters for near-infrared short-wave radiation (NIR). The predictions agree much better with observations when the leaf reflectance and transmission coefficients for NIR are reduced by 25-40%. Available vertical distributions of photosynthetic capacity and leaf nitrogen concentration suggest a low but significant light acclimation of the rain forest canopy that scales nearly linearly with accumulated leaf area.

Evaluation of the biochemical leaf model, using the enclosure measurements, showed that recommended parameter values describing the photosynthetic light response, have to be optimized. Otherwise, predicted net assimilation is overestimated by 30-50%. Two stomatal models have been tested, which apply a well established semi-empirical relationship between stomatal conductance and net assimilation. Both models differ in the way they describe the influence of humidity on stomatal response. However, they show a very similar performance within the range of observed environmental conditions. The agreement between predicted and observed stomatal conductance rates is reasonable. In general, the leaf level data suggests seasonal physiological changes, which can be reproduced reasonably well by assuming increased stomatal conductance rates during the wet season, and decreased assimilation rates during the dry season.

The sensitivity of the predicted canopy fluxes of energy and CO2 to the parameterization of canopy structure, the leaf optical parameters, and the scaling of photosynthetic parameters is relatively low (1-12%), with respect to parameter uncertainty. In contrast, modifying leaf model parameters within their uncertainty range results in much larger changes of the predicted canopy net fluxes (5-35%).

Coupled carbon-water exchange of the Amazon rain forest, I. Model description, parameterization and sensitivity analysis

NASA Astrophysics Data System (ADS)

Simon, E.; Meixner, F. X.; Ganzeveld, L.; Kesselmeier, J.

2005-09-01

Detailed one-dimensional multilayer biosphere-atmosphere models, also referred to as CANVEG models, are used for more than a decade to describe coupled water-carbon exchange between the terrestrial vegetation and the lower atmosphere. Within the present study, a modified CANVEG scheme is described. A generic parameterization and characterization of biophysical properties of Amazon rain forest canopies is inferred using available field measurements of canopy structure, in-canopy profiles of horizontal wind speed and radiation, canopy albedo, soil heat flux and soil respiration, photosynthetic capacity and leaf nitrogen as well as leaf level enclosure measurements made on sunlit and shaded branches of several Amazonian tree species during the wet and dry season. The sensitivity of calculated canopy energy and CO2 fluxes to the uncertainty of individual parameter values is assessed. In the companion paper, the predicted seasonal exchange of energy, CO2, ozone and isoprene is compared to observations.

A bi-modal distribution of leaf area density with a total leaf area index of 6 is inferred from several observations in Amazonia. Predicted light attenuation within the canopy agrees reasonably well with observations made at different field sites. A comparison of predicted and observed canopy albedo shows a high model sensitivity to the leaf optical parameters for near-infrared short-wave radiation (NIR). The predictions agree much better with observations when the leaf reflectance and transmission coefficients for NIR are reduced by 25-40%. Available vertical distributions of photosynthetic capacity and leaf nitrogen concentration suggest a low but significant light acclimation of the rain forest canopy that scales nearly linearly with accumulated leaf area.

Evaluation of the biochemical leaf model, using the enclosure measurements, showed that recommended parameter values describing the photosynthetic light response, have to be optimized. Otherwise, predicted net assimilation is overestimated by 30-50%. Two stomatal models have been tested, which apply a well established semi-empirical relationship between stomatal conductance and net assimilation. Both models differ in the way they describe the influence of humidity on stomatal response. However, they show a very similar performance within the range of observed environmental conditions. The agreement between predicted and observed stomatal conductance rates is reasonable. In general, the leaf level data suggests seasonal physiological changes, which can be reproduced reasonably well by assuming increased stomatal conductance rates during the wet season, and decreased assimilation rates during the dry season.

The sensitivity of the predicted canopy fluxes of energy and CO2 to the parameterization of canopy structure, the leaf optical parameters, and the scaling of photosynthetic parameters is relatively low (1-12%), with respect to parameter uncertainty. In contrast, modifying leaf model parameters within their uncertainty range results in much larger changes of the predicted canopy net fluxes (5-35%).

Evidence of Microbial Regulation of Biogeochemical Cycles from a Study on Methane Flux and Land Use Change

PubMed Central

Nazaries, Loïc; Pan, Yao; Bodrossy, Levente; Baggs, Elizabeth M.; Millard, Peter; Murrell, J. Colin

2013-01-01

Microbes play an essential role in ecosystem functions, including carrying out biogeochemical cycles, but are currently considered a black box in predictive models and all global biodiversity debates. This is due to (i) perceived temporal and spatial variations in microbial communities and (ii) lack of ecological theory explaining how microbes regulate ecosystem functions. Providing evidence of the microbial regulation of biogeochemical cycles is key for predicting ecosystem functions, including greenhouse gas fluxes, under current and future climate scenarios. Using functional measures, stable-isotope probing, and molecular methods, we show that microbial (community diversity and function) response to land use change is stable over time. We investigated the change in net methane flux and associated microbial communities due to afforestation of bog, grassland, and moorland. Afforestation resulted in the stable and consistent enhancement in sink of atmospheric methane at all sites. This change in function was linked to a niche-specific separation of microbial communities (methanotrophs). The results suggest that ecological theories developed for macroecology may explain the microbial regulation of the methane cycle. Our findings provide support for the explicit consideration of microbial data in ecosystem/climate models to improve predictions of biogeochemical cycles. PMID:23624469

HARP targets pion production cross section and yield measurements: Implications for MiniBooNE neutrino flux

NASA Astrophysics Data System (ADS)

Wickremasinghe, Don Athula Abeyarathna

The prediction of the muon neutrino flux from a 71.0 cm long beryllium target for the MiniBooNE experiment is based on a measured pion production cross section which was taken from a short beryllium target (2.0 cm thick - 5% nuclear interaction length) in the Hadron Production (HARP) experiment at CERN. To verify the extrapolation to our longer target, HARP also measured the pion production from 20.0 cm and 40.0 cm beryllium targets. The measured production yields on targets of 50% and 100% nuclear interaction lengths in the kinematic rage of momentum from 0.75 GeV/c to 6.5 GeV/c and the range of angle from 30 mrad to 210 mrad are presented along with an update of the short target cross sections. The best fitted extended Sanford-Wang (SW) model parameterization for updated short beryllium target positive pion production cross section is presented. Yield measurements for all three targets are also compared with that from the Monte Carlo predictions in the MiniBooNE experiment for different SW parameterization. The comparisons of muon neutrino flux predictions for updated SW model is presented.

Spectrophotometry of comets Giacobini-Zinner and Halley

NASA Technical Reports Server (NTRS)

Tegler, Stephen C.; O'Dell, C. R.

1987-01-01

Optical window spectrophotometry was performed on comets Giacobini-Zinner and Halley over the interval 300-1000 nm. Band and band-sequence fluxes were obtained for the brightest features of OH, CN, NH, and C2, special care having been given to determinations of extinction, instrumental sensitivities, and corrections for Fraunhofer lines. C2 Swan band-sequence flux ratios were determined with unprecedented accuracy and compared with the predictions of the detailed equilibrium models of Krishna Swamy et al. (1977, 1979, 1981, and 1987). It is found that these band sequences do not agree with the predictions, which calls into question the assumptions made in deriving the model, namely resonance fluorescence statistical equilibrium. Suggestions are made as to how to resolve this discrepancy.

Search for Ultra-High Energy Photons with the Pierre Auger Observatory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Homola, Piotr

One of key scientific objectives of the Pierre Auger Observatory is the search for ultra-high energy photons. Such photons could originate either in the interactions of energetic cosmic-ray nuclei with the cosmic microwave background (so-called cosmogenic photons) or in the exotic scenarios, e.g. those assuming a production and decay of some hypothetical super-massive particles. The latter category of models would imply relatively large fluxes of photons with ultra-high energies at Earth, while the former, involving interactions of cosmic-ray nuclei with the microwave background - just the contrary: very small fractions. The investigations on the data collected so far in themore » Pierre Auger Observatory led to placing very stringent limits to ultra-high energy photon fluxes: below the predictions of the most of the exotic models and nearing the predicted fluxes of the cosmogenic photons. In this paper the status of these investigations and perspectives for further studies are summarized.« less

Double-null divertor configuration discharge and disruptive heat flux simulation using TSC on EAST

NASA Astrophysics Data System (ADS)

Bo, SHI; Jinhong, YANG; Cheng, YANG; Desheng, CHENG; Hui, WANG; Hui, ZHANG; Haifei, DENG; Junli, QI; Xianzu, GONG; Weihua, WANG

2018-07-01

The tokamak simulation code (TSC) is employed to simulate the complete evolution of a disruptive discharge in the experimental advanced superconducting tokamak. The multiplication factor of the anomalous transport coefficient was adjusted to model the major disruptive discharge with double-null divertor configuration based on shot 61 916. The real-time feed-back control system for the plasma displacement was employed. Modeling results of the evolution of the poloidal field coil currents, the plasma current, the major radius, the plasma configuration all show agreement with experimental measurements. Results from the simulation show that during disruption, heat flux about 8 MW m‑2 flows to the upper divertor target plate and about 6 MW m‑2 flows to the lower divertor target plate. Computations predict that different amounts of heat fluxes on the divertor target plate could result by adjusting the multiplication factor of the anomalous transport coefficient. This shows that TSC has high flexibility and predictability.

South American smoke coverage and flux estimations from the Fire Locating and Modeling of Burning Emissions (FLAMBE') system.

NASA Astrophysics Data System (ADS)

Reid, J. S.; Westphal, D. L.; Christopher, S. A.; Prins, E. M.; Gasso, S.; Reid, E.; Theisen, M.; Schmidt, C. C.; Hunter, J.; Eck, T.

2002-05-01

The Fire Locating and Modeling of Burning Emissions (FLAMBE') project is a joint Navy, NOAA, NASA and university project to integrate satellite products with numerical aerosol models to produce a real time fire and emissions inventory. At the center of the program is the Wildfire Automated Biomass Burning Algorithm (WF ABBA) which provides real-time fire products and the NRL Aerosol Analysis and Prediction System to model smoke transport. In this presentation we give a brief overview of the system and methods, but emphasize new estimations of smoke coverage and emission fluxes from the South American continent. Temporal and smoke patterns compare reasonably well with AERONET and MODIS aerosol optical depth products for the 2000 and 2001 fire seasons. Fluxes are computed by relating NAAPS output fields and MODIS optical depth maps with modeled wind fields. Smoke emissions and transport fluxes out of the continent can then be estimated by perturbing the modeled emissions to gain agreement with the satellite and wind products. Regional smoke emissions are also presented for grass and forest burning.

3DCORE: Forward modeling of solar storm magnetic flux ropes for space weather prediction

NASA Astrophysics Data System (ADS)

Möstl, C.; Amerstorfer, T.; Palmerio, E.; Isavnin, A.; Farrugia, C. J.; Lowder, C.; Winslow, R. M.; Donnerer, J. M.; Kilpua, E. K. J.; Boakes, P. D.

2018-05-01

3DCORE forward models solar storm magnetic flux ropes called 3-Dimensional Coronal Rope Ejection (3DCORE). The code is able to produce synthetic in situ observations of the magnetic cores of solar coronal mass ejections sweeping over planets and spacecraft. Near Earth, these data are taken currently by the Wind, ACE and DSCOVR spacecraft. Other suitable spacecraft making these kind of observations carrying magnetometers in the solar wind were MESSENGER, Venus Express, MAVEN, and even Helios.

Predicted and observed directional dependence of meteoroid/debris impacts on LDEF thermal blankets

NASA Astrophysics Data System (ADS)

Drolshagen, Gerhard

1992-06-01

The number of impacts from meteoroids and space debris particles to the various Long Duration Exposure Facility (LDEF) rows is calculated using ESABASE/DEBRIS, a 3-D numerical analysis tool. It is based on the latest environment flux models and includes geometrical and directional effects. A detailed comparison of model predictions and actual observations is made for impacts on the thermal blankets which covered the USCR experiment. Impact features on these blankets were studied intensively in European laboratories and hypervelocity impacts for calibration were performed. The thermal blankets were located on all LDEF rows, except 3, 9, and 12. Because of their uniform composition and thickness, these blankets allow a direct analysis of the directional dependence of impacts and provide a unique test case for the latest meteoroid and debris flux models.

Density-driven transport of gas phase chemicals in unsaturated soils

NASA Astrophysics Data System (ADS)

Fen, Chiu-Shia; Sun, Yong-tai; Cheng, Yuen; Chen, Yuanchin; Yang, Whaiwan; Pan, Changtai

2018-01-01

Variations of gas phase density are responsible for advective and diffusive transports of organic vapors in unsaturated soils. Laboratory experiments were conducted to explore dense gas transport (sulfur hexafluoride, SF6) from different source densities through a nitrogen gas-dry soil column. Gas pressures and SF6 densities at transient state were measured along the soil column for three transport configurations (horizontal, vertically upward and vertically downward transport). These measurements and others reported in the literature were compared with simulation results obtained from two models based on different diffusion approaches: the dusty gas model (DGM) equations and a Fickian-type molar fraction-based diffusion expression. The results show that the DGM and Fickian-based models predicted similar dense gas density profiles which matched the measured data well for horizontal transport of dense gas at low to high source densities, despite the pressure variations predicted in the soil column were opposite to the measurements. The pressure evolutions predicted by both models were in trend similar to the measured ones for vertical transport of dense gas. However, differences between the dense gas densities predicted by the DGM and Fickian-based models were discernible for vertically upward transport of dense gas even at low source densities, as the DGM-based predictions matched the measured data better than the Fickian results did. For vertically downward transport, the dense gas densities predicted by both models were not greatly different from our experimental measurements, but substantially greater than the observations obtained from the literature, especially at high source densities. Further research will be necessary for exploring factors affecting downward transport of dense gas in soil columns. Use of the measured data to compute flux components of SF6 showed that the magnitudes of diffusive flux component based on the Fickian-type diffusion expressions in terms of molar concentration, molar fraction and mass density fraction gradient were almost the same. However, they were greater than the result computed with the mass fraction gradient for > 24% and the DGM-based result for more than one time. As a consequence, the DGM-based total flux of SF6 was in magnitude greatly less than the Fickian result not only for horizontal transport (diffusion-dominating) but also for vertical transport (advection and diffusion) of dense gas. Particularly, the Fickian-based total flux was more than two times in magnitude as much as the DGM result for vertically upward transport of dense gas.

Estimation of Turbulent Heat Fluxes by Assimilation of Land Surface Temperature Observations From GOES Satellites Into an Ensemble Kalman Smoother Framework

NASA Astrophysics Data System (ADS)

Xu, Tongren; Bateni, S. M.; Neale, C. M. U.; Auligne, T.; Liu, Shaomin

2018-03-01

In different studies, land surface temperature (LST) observations have been assimilated into the variational data assimilation (VDA) approaches to estimate turbulent heat fluxes. The VDA methods yield accurate turbulent heat fluxes, but they need an adjoint model, which is difficult to derive and code. They also cannot directly calculate the uncertainty of their estimates. To overcome the abovementioned drawbacks, this study assimilates LST data from Geostationary Operational Environmental Satellite into the ensemble Kalman smoother (EnKS) data assimilation system to estimate turbulent heat fluxes. EnKS does not need to derive the adjoint term and directly generates statistical information on the accuracy of its predictions. It uses the heat diffusion equation to simulate LST. EnKS with the state augmentation approach finds the optimal values for the unknown parameters (i.e., evaporative fraction and neutral bulk heat transfer coefficient, CHN) by minimizing the misfit between LST observations from Geostationary Operational Environmental Satellite and LST estimations from the heat diffusion equation. The augmented EnKS scheme is tested over six Ameriflux sites with a wide range of hydrological and vegetative conditions. The results show that EnKS can predict not only the model parameters and turbulent heat fluxes but also their uncertainties over a variety of land surface conditions. Compared to the variational method, EnKS yields suboptimal turbulent heat fluxes. However, suboptimality of EnKS is small, and its results are comparable to those of the VDA method. Overall, EnKS is a feasible and reliable method for estimation of turbulent heat fluxes.

Fast Radio Bursts’ Recipes for the Distributions of Dispersion Measures, Flux Densities, and Fluences

NASA Astrophysics Data System (ADS)

Niino, Yuu

2018-05-01

We investigate how the statistical properties of dispersion measure (DM) and apparent flux density/fluence of (nonrepeating) fast radio bursts (FRBs) are determined by unknown cosmic rate density history [ρ FRB(z)] and luminosity function (LF) of the transient events. We predict the distributions of DMs, flux densities, and fluences of FRBs taking account of the variation of the receiver efficiency within its beam, using analytical models of ρ FRB(z) and LF. Comparing the predictions with the observations, we show that the cumulative distribution of apparent fluences suggests that FRBs originate at cosmological distances and ρ FRB increases with redshift resembling the cosmic star formation history (CSFH). We also show that an LF model with a bright-end cutoff at log10 L ν (erg s‑1 Hz‑1) ∼ 34 are favored to reproduce the observed DM distribution if ρ FRB(z) ∝ CSFH, although the statistical significance of the constraints obtained with the current size of the observed sample is not high. Finally, we find that the correlation between DM and flux density of FRBs is potentially a powerful tool to distinguish whether FRBs are at cosmological distances or in the local universe more robustly with future observations.

A comparison of non-local electron transport models relevant to inertial confinement fusion

NASA Astrophysics Data System (ADS)

Sherlock, Mark; Brodrick, Jonathan; Ridgers, Christopher

2017-10-01

We compare the reduced non-local electron transport model developed by Schurtz et al. to Vlasov-Fokker-Planck simulations. Two new test cases are considered: the propagation of a heat wave through a high density region into a lower density gas, and a 1-dimensional hohlraum ablation problem. We find the reduced model reproduces the peak heat flux well in the ablation region but significantly over-predicts the coronal preheat. The suitability of the reduced model for computing non-local transport effects other than thermal conductivity is considered by comparing the computed distribution function to the Vlasov-Fokker-Planck distribution function. It is shown that even when the reduced model reproduces the correct heat flux, the distribution function is significantly different to the Vlasov-Fokker-Planck prediction. Two simple modifications are considered which improve agreement between models in the coronal region. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Modelling field scale spatial variation in water run-off, soil moisture, N2O emissions and herbage biomass of a grazed pasture using the SPACSYS model.

PubMed

Liu, Yi; Li, Yuefen; Harris, Paul; Cardenas, Laura M; Dunn, Robert M; Sint, Hadewij; Murray, Phil J; Lee, Michael R F; Wu, Lianhai

2018-04-01

In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N 2 O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for not only temporal dynamics but also the within-field spatial variation in these key ecosystem indicators. Spatial variability in nutrient and water presence at the field-scale is a key source of uncertainty when quantifying nutrient cycling and water movement in an agricultural system. Results demonstrated that the new spatially distributed version of SPACSYS provided a worthy improvement in accuracy over the standard (single-point) version for biomass productivity. No difference in model prediction performance was observed for water run-off, reflecting the closed-system nature of this variable. Similarly, no difference in model prediction performance was found for N 2 O fluxes, but here the N 2 O predictions were noticeably poor in both cases. Further developmental work, informed by this study's findings, is proposed to improve model predictions for N 2 O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hay, J.; Schwender, J.

Computational simulation of large-scale biochemical networks can be used to analyze and predict the metabolic behavior of an organism, such as a developing seed. Based on the biochemical literature, pathways databases and decision rules defining reaction directionality we reconstructed bna572, a stoichiometric metabolic network model representing Brassica napus seed storage metabolism. In the highly compartmentalized network about 25% of the 572 reactions are transport reactions interconnecting nine subcellular compartments and the environment. According to known physiological capabilities of developing B. napus embryos, four nutritional conditions were defined to simulate heterotrophy or photoheterotrophy, each in combination with the availability of inorganicmore » nitrogen (ammonia, nitrate) or amino acids as nitrogen sources. Based on mathematical linear optimization the optimal solution space was comprehensively explored by flux variability analysis, thereby identifying for each reaction the range of flux values allowable under optimality. The range and variability of flux values was then categorized into flux variability types. Across the four nutritional conditions, approximately 13% of the reactions have variable flux values and 10-11% are substitutable (can be inactive), both indicating metabolic redundancy given, for example, by isoenzymes, subcellular compartmentalization or the presence of alternative pathways. About one-third of the reactions are never used and are associated with pathways that are suboptimal for storage synthesis. Fifty-seven reactions change flux variability type among the different nutritional conditions, indicating their function in metabolic adjustments. This predictive modeling framework allows analysis and quantitative exploration of storage metabolism of a developing B. napus oilseed.« less

Estimation of regional surface CO2 fluxes with GOSAT observations using two inverse modeling approaches

NASA Astrophysics Data System (ADS)

Maksyutov, Shamil; Takagi, Hiroshi; Belikov, Dmitry A.; Saeki, Tazu; Zhuravlev, Ruslan; Ganshin, Alexander; Lukyanov, Alexander; Yoshida, Yukio; Oshchepkov, Sergey; Bril, Andrey; Saito, Makoto; Oda, Tomohiro; Valsala, Vinu K.; Saito, Ryu; Andres, Robert J.; Conway, Thomas; Tans, Pieter; Yokota, Tatsuya

2012-11-01

Inverse estimation of surface C02 fluxes is performed with atmospheric transport model using ground-based and GOSAT observations. The NIES-retrieved C02 column mixing (Xc02) and column averaging kernel are provided by GOSAT Level 2 product v. 2.0 and PPDF-DOAS method. Monthly mean C02 fluxes for 64 regions are estimated together with a global mean offset between GOSAT data and ground-based data. We used the fixed-lag Kalman filter to infer monthly fluxes for 42 sub-continental terrestrial regions and 22 oceanic basins. We estimate fluxes and compare results obtained by two inverse modeling approaches. In basic approach adopted in GOSAT Level4 product v. 2.01, we use aggregation of the GOSAT observations into monthly mean over 5x5 degree grids, fluxes are estimated independently for each region, and NIES atmospheric transport model is used for forward simulation. In the alternative method, the model-observation misfit is estimated for each observation separately and fluxes are spatially correlated using EOF analysis of the simulated flux variability similar to geostatistical approach, while transport simulation is enhanced by coupling with a Lagrangian transport model Flexpart. Both methods use using the same set of prior fluxes and region maps. Daily net ecosystem exchange (NEE) is predicted by the Vegetation Integrative Simulator for Trace gases (VISIT) optimized to match seasonal cycle of the atmospheric C02 . Monthly ocean-atmosphere C02 fluxes are produced with an ocean pC02 data assimilation system. Biomass burning fluxes were provided by the Global Fire Emissions Database (GFED); and monthly fossil fuel C02 emissions are estimated with ODIAC inventory. The results of analyzing one year of the GOSAT data suggest that when both GOSAT and ground-based data are used together, fluxes in tropical and other remote regions with lower associated uncertainties are obtained than in the analysis using only ground-based data. With version 2.0 of L2 Xc02 the fluxes appear reasonable for many regions and seasons, however there is a need for improving the L2 bias correction, data filtering and the inverse modeling method to reduce estimated flux anomalies visible in some areas. We also observe that application of spatial flux correlations with EOF­ based approach reduces flux anomalies.

Use of Plant Hydraulic Theory to Predict Ecosystem Fluxes Across Mountainous Gradients in Environmental Controls and Insect Disturbances

NASA Astrophysics Data System (ADS)

Ewers, B. E.; Pendall, E.; Reed, D. E.; Barnard, H. R.; Whitehouse, F.; Frank, J. M.; Massman, W. J.; Brooks, P. D.; Biederman, J. A.; Harpold, A. A.; Naithani, K. J.; Mitra, B.; Mackay, D. S.; Norton, U.; Borkhuu, B.

2011-12-01

While mountainous areas are critical for providing numerous ecosystem benefits at the regional scale, the strong gradients in environmental controls make predictions difficult. A key part of the problem is quantifying and predicting the feedback between mountain gradients and plant function which then controls ecosystem cycling. The emerging theory of plant hydraulics provides a rigorous yet simple platform from which to generate testable hypotheses and predictions of ecosystem pools and fluxes. Plant hydraulic theory predicts that plant controls over carbon, water, energy and nutrient fluxes can be derived from the limitation of plant water transport from the soil through xylem and out of stomata. In addition, the limit to plant water transport can be predicted by combining plant structure (e.g. xylem diameters or root-to-shoot ratios) and plant function (response of stomatal conductance to vapor pressure deficit or root vulnerability to cavitation). We evaluate the predictions of the plant hydraulic theory by testing it against data from a mountain gradient encompassing sagebrush steppe through subalpine forests (2700 to 3400 m). We further test the theory by predicting the carbon, water and nutrient exchanges from several coniferous trees in the same gradient that are dying from xylem dysfunction caused by blue-stain fungi carried by bark beetles. The common theme of both of these data sets is a change in water limitation caused by either changing precipitation along the mountainous gradient or lack of access to soil water from xylem-occluding fungi. Across all of the data sets which range in scale from individual plants to hillslopes, the data fit the predictions of plant hydraulic theory. Namely, there was a proportional tradeoff between the reference canopy stomatal conductance to water vapor and the sensitivity of that conductance to vapor pressure deficit that quantitatively fits the predictions of plant hydraulic theory. Incorporating this result into whole plant mass and energy exchange models allows prediction of plant carbon, energy and nitrogen exchange that fits recently collected data including plant sap flux, leaf gas exchange, eddy covariance towers and stand and watershed-scale biogeochemistry measurements. The results of our work will allow the next generation of ecosystem to regional scale coupled-biogeochemistry models to incorporate a simple plant hydraulic mechanism that will enable defensible predictions of carbon, water, energy and nutrient cycling with changing climate and land use.

Heat transport modeling of the dot spectroscopy platform on NIF

DOE PAGES

Farmer, W. A.; Jones, O. S.; Barrios, M. A.; ...

2018-02-13

Electron heat transport within an inertial-fusion hohlraum plasma is difficult to model due to the complex interaction of kinetic plasma effects, magnetic fields, laser-plasma interactions, and microturbulence. In this paper, simulations using the radiation-hydrodynamic code, HYDRA, are compared to hohlraum plasma experiments which contain a Manganese–Cobalt tracer dot (Barrios et al 2016 Phys. Plasmas 23 056307). The dot is placed either on the capsule or on a film midway between the capsule and the laser-entrance hole. From spectroscopic measurements, electron temperature and position of the dot are inferred. Simulations are performed with ad hoc flux limiters of f = 0.15more » and f = 0.03 (with electron heat flux, q, limited to fnT 3/2/m 1/2), and two more physical means of flux limitation: the magnetohydrodynamics and nonlocal packages. The nonlocal model agrees best with the temperature of the dot-on-film and dot-on-capsule. The hohlraum produced x-ray flux is over-predicted by roughly ~11% for the f = 0.03 model and the remaining models by ~16%. The simulated trajectories of the dot-on-capsule are slightly ahead of the experimental trajectory for all but the f = 0.03 model. The simulated dot-on-film position disagrees with the experimental measurement for all transport models. In the MHD simulation of the dot-on-film, the dot is strongly perturbative, though the simulation predicts a peak dot-on-film temperature 2–3 keV higher than the measurement. Finally, this suggests a deficiency in the MHD modeling possibly due to the neglect of the Righi–Leduc term or interpenetrating flows of multiple ion species which would reduce the strength of the self-generated fields.« less

Heat transport modeling of the dot spectroscopy platform on NIF

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farmer, W. A.; Jones, O. S.; Barrios, M. A.

Electron heat transport within an inertial-fusion hohlraum plasma is difficult to model due to the complex interaction of kinetic plasma effects, magnetic fields, laser-plasma interactions, and microturbulence. In this paper, simulations using the radiation-hydrodynamic code, HYDRA, are compared to hohlraum plasma experiments which contain a Manganese–Cobalt tracer dot (Barrios et al 2016 Phys. Plasmas 23 056307). The dot is placed either on the capsule or on a film midway between the capsule and the laser-entrance hole. From spectroscopic measurements, electron temperature and position of the dot are inferred. Simulations are performed with ad hoc flux limiters of f = 0.15more » and f = 0.03 (with electron heat flux, q, limited to fnT 3/2/m 1/2), and two more physical means of flux limitation: the magnetohydrodynamics and nonlocal packages. The nonlocal model agrees best with the temperature of the dot-on-film and dot-on-capsule. The hohlraum produced x-ray flux is over-predicted by roughly ~11% for the f = 0.03 model and the remaining models by ~16%. The simulated trajectories of the dot-on-capsule are slightly ahead of the experimental trajectory for all but the f = 0.03 model. The simulated dot-on-film position disagrees with the experimental measurement for all transport models. In the MHD simulation of the dot-on-film, the dot is strongly perturbative, though the simulation predicts a peak dot-on-film temperature 2–3 keV higher than the measurement. Finally, this suggests a deficiency in the MHD modeling possibly due to the neglect of the Righi–Leduc term or interpenetrating flows of multiple ion species which would reduce the strength of the self-generated fields.« less

Heat transport modeling of the dot spectroscopy platform on NIF

NASA Astrophysics Data System (ADS)

Farmer, W. A.; Jones, O. S.; Barrios, M. A.; Strozzi, D. J.; Koning, J. M.; Kerbel, G. D.; Hinkel, D. E.; Moody, J. D.; Suter, L. J.; Liedahl, D. A.; Lemos, N.; Eder, D. C.; Kauffman, R. L.; Landen, O. L.; Moore, A. S.; Schneider, M. B.

2018-04-01

Electron heat transport within an inertial-fusion hohlraum plasma is difficult to model due to the complex interaction of kinetic plasma effects, magnetic fields, laser-plasma interactions, and microturbulence. Here, simulations using the radiation-hydrodynamic code, HYDRA, are compared to hohlraum plasma experiments which contain a Manganese-Cobalt tracer dot (Barrios et al 2016 Phys. Plasmas 23 056307). The dot is placed either on the capsule or on a film midway between the capsule and the laser-entrance hole. From spectroscopic measurements, electron temperature and position of the dot are inferred. Simulations are performed with ad hoc flux limiters of f = 0.15 and f = 0.03 (with electron heat flux, q, limited to fnT 3/2/m 1/2), and two more physical means of flux limitation: the magnetohydrodynamics and nonlocal packages. The nonlocal model agrees best with the temperature of the dot-on-film and dot-on-capsule. The hohlraum produced x-ray flux is over-predicted by roughly ˜11% for the f = 0.03 model and the remaining models by ˜16%. The simulated trajectories of the dot-on-capsule are slightly ahead of the experimental trajectory for all but the f = 0.03 model. The simulated dot-on-film position disagrees with the experimental measurement for all transport models. In the MHD simulation of the dot-on-film, the dot is strongly perturbative, though the simulation predicts a peak dot-on-film temperature 2-3 keV higher than the measurement. This suggests a deficiency in the MHD modeling possibly due to the neglect of the Righi-Leduc term or interpenetrating flows of multiple ion species which would reduce the strength of the self-generated fields.

Infiltration-driven metamorphism, New England, USA: Regional CO2 fluxes and implications for Devonian climate and extinctions

NASA Astrophysics Data System (ADS)

Stewart, E. M.; Ague, Jay J.

2018-05-01

We undertake thermodynamic pseudosection modeling of metacarbonate rocks in the Wepawaug Schist, Connecticut, USA, and examine the implications for CO2 outgassing from collisional orogenic belts. Two broad types of pseudosections are calculated: (1) a fully closed-system model with no fluid infiltration and (2) a fluid-buffered model including an H2O-CO2 fluid of a fixed composition. This fluid-buffered model is used to approximate a system open to infiltration by a water-bearing fluid. In all cases the fully closed-system model fails to reproduce the observed major mineral zones, mineral compositions, reaction temperatures, and fluid compositions. The fluid-infiltrated models, on the other hand, successfully reproduce these observations when the XCO2 of the fluid is in the range ∼0.05 to ∼0.15. Fluid-infiltrated models predict significant progressive CO2 loss, peaking at ∼50% decarbonation at amphibolite facies. The closed-system models dramatically underestimate the degree of decarbonation, predicting only ∼15% CO2 loss at peak conditions, and, remarkably, <1% CO2 loss below ∼600 °C. We propagate the results of fluid-infiltrated pseudosections to determine an areal CO2 flux for the Wepawaug Schist. This yields ∼1012 mol CO2 km-2 Myr-1, consistent with multiple independent estimates of the metamorphic CO2 flux, and comparable in magnitude to fluxes from mid-ocean ridges and volcanic arcs. Extrapolating to the area of the Acadian orogenic belt, we suggest that metamorphic CO2 degassing is a plausible driver of global warming, sea level rise, and, perhaps, extinction in the mid- to late-Devonian.

The HIRLAM fast radiation scheme for mesoscale numerical weather prediction models

NASA Astrophysics Data System (ADS)

Rontu, Laura; Gleeson, Emily; Räisänen, Petri; Pagh Nielsen, Kristian; Savijärvi, Hannu; Hansen Sass, Bent

2017-07-01

This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the model, without compromising on computational efficiency. In mesoscale models fast interactions between clouds and radiation and the surface and radiation can be of greater importance than accounting for the spectral details of clear-sky radiation; thus calling the routines more frequently can be of greater benefit than the deterioration due to loss of spectral details. Fast but physically based radiation parametrizations are expected to be valuable for high-resolution ensemble forecasting, because as well as the speed of their execution, they may provide realistic physical perturbations. Results from single-column diagnostic experiments based on CIRC benchmark cases and an evaluation of 10 years of radiation output from the FMI operational archive of HIRLAM forecasts indicate that HLRADIA performs sufficiently well with respect to the clear-sky downwelling SW and longwave LW fluxes at the surface. In general, HLRADIA tends to overestimate surface fluxes, with the exception of LW fluxes under cold and dry conditions. The most obvious overestimation of the surface SW flux was seen in the cloudy cases in the 10-year comparison; this bias may be related to using a cloud inhomogeneity correction, which was too large. According to the CIRC comparisons, the outgoing LW and SW fluxes at the top of atmosphere are mostly overestimated by HLRADIA and the net LW flux is underestimated above clouds. The absorption of SW radiation by the atmosphere seems to be underestimated and LW absorption seems to be overestimated. Despite these issues, the overall results are satisfying and work on the improvement of HLRADIA for the use in HARMONIE-AROME NWP system is ongoing. In a HARMONIE-AROME 3-D forecast experiment we have shown that the frequency of the call for the radiation parametrization and choice of the parametrization scheme makes a difference to the surface radiation fluxes and changes the spatial distribution of the vertically integrated cloud cover and precipitation.

Impact of Different Correlations on TRACEv4.160 Predicted Critical Heat Flux

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jasiulevicius, A.; Macian-Juan, R.

2006-07-01

This paper presents an independent assessment of the Critical Heat Flux (CHF) models implemented in TRACEv4.160 with data from the experiments carried out at the Royal Institute of Technology (RIT) in Stockholm, Sweden, with single vertical uniformly heated 7.0 m long tubes. In previous CHF assessment studies with TRACE, it was noted that, although the overall code predictions in long single tubes with inner diameters of 1.0 to 2.49 cm agreed rather well with the results of experiments (with r.m.s. error being 25.6%), several regions of pressure and coolant mass flux could be identified, in which the code strongly under-predictsmore » or over-predicts the CHF. In order to evaluate the possibility of improving the code performance, some of the most widely used and assessed CHF correlations were additionally implemented in TRACEv4.160, namely Bowring, Levitan - Lantsman, and Tong-W3. The results obtained for the CHF predictions in single tubes with uniform axial heat flux by using these correlations, were compared to the results produced with the standard TRACE correlations (Biasi and CISE-GE), and with the experimental data from RIT, which covered a broad range of pressures (3-20 MPa) and coolant mass fluxes (500-3000 kg/m{sup 2}s). Several hundreds of experimental points were calculated to cover the parameter range mentioned above for the evaluation of the newly implemented correlations in the TRACEv4.160 code. (author)« less

Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments.

PubMed

Zhuang, Kai; Izallalen, Mounir; Mouser, Paula; Richter, Hanno; Risso, Carla; Mahadevan, Radhakrishnan; Lovley, Derek R

2011-02-01

The advent of rapid complete genome sequencing, and the potential to capture this information in genome-scale metabolic models, provide the possibility of comprehensively modeling microbial community interactions. For example, Rhodoferax and Geobacter species are acetate-oxidizing Fe(III)-reducers that compete in anoxic subsurface environments and this competition may have an influence on the in situ bioremediation of uranium-contaminated groundwater. Therefore, genome-scale models of Geobacter sulfurreducens and Rhodoferax ferrireducens were used to evaluate how Geobacter and Rhodoferax species might compete under diverse conditions found in a uranium-contaminated aquifer in Rifle, CO. The model predicted that at the low rates of acetate flux expected under natural conditions at the site, Rhodoferax will outcompete Geobacter as long as sufficient ammonium is available. The model also predicted that when high concentrations of acetate are added during in situ bioremediation, Geobacter species would predominate, consistent with field-scale observations. This can be attributed to the higher expected growth yields of Rhodoferax and the ability of Geobacter to fix nitrogen. The modeling predicted relative proportions of Geobacter and Rhodoferax in geochemically distinct zones of the Rifle site that were comparable to those that were previously documented with molecular techniques. The model also predicted that under nitrogen fixation, higher carbon and electron fluxes would be diverted toward respiration rather than biomass formation in Geobacter, providing a potential explanation for enhanced in situ U(VI) reduction in low-ammonium zones. These results show that genome-scale modeling can be a useful tool for predicting microbial interactions in subsurface environments and shows promise for designing bioremediation strategies.

[Factors affecting benzene diffusion from contaminated soils to the atmosphere and flux characteristics].

PubMed

Du, Ping; Wang, Shi-Jie; Zhao, Huan-Huan; Wu, Bin; Han, Chun-Mei; Fang, Ji-Dun; Li, Hui-Ying; Hosomi, Masaaki; Li, Fa-Sheng

2013-12-01

The influencing factors of benzene diffusion fluxes from sand and black soil to atmosphere were investigated using a flux chamber (30.0 cm x 17.5 cm x 29.0 cm). In this study, the benzene diffusion fluxes were estimated by measuring the benzene concentrations both in the headspace of the chamber and in the soils of different layers. The results indicated that the soil water content played an important role in benzene diffusion fluxes. The diffusion flux showed positive correlation with the initial benzene concentration and the benzene dissolution concentration for both soil types. The changes of air flow rate from 300 to 900 mL x min(-1) and temperature from 20 degrees C to 40 degrees C resulted in increases of the benzene diffusion flux. Our study of benzene diffusion fluxes from contaminated soils will be beneficial for the predicting model, and emergency management and precautions.

Photohadronic scenario in interpreting the February-March 2014 flare of 1ES 1011+496

NASA Astrophysics Data System (ADS)

Sahu, Sarira; de León, Alberto Rosales; Miranda, Luis Salvador

2017-11-01

The extraordinary multi-TeV flare from 1ES 1011+496 during February-March 2014 was observed by the MAGIC telescopes for 17 nights and the average spectrum of the whole period has a non-trivial shape. We have used the photohadronic model and a template extragalactic background light model to explain the average spectrum which fits the flare data well. The spectral index α is the only free parameter in our model. We have also shown that the non-trivial nature of the spectrum is due to the change in the behavior of the optical depth above ˜ 600 GeV γ -ray energy accompanied with the high SSC flux. This corresponds to an almost flat intrinsic flux for the multi-TeV γ -rays. Our model prediction can constrain the SSC flux of the leptonic models in the quiescent state.

WEB-DHM: A distributed biosphere hydrological model developed by coupling a simple biosphere scheme with a hillslope hydrological model

USDA-ARS?s Scientific Manuscript database

The coupling of land surface models and hydrological models potentially improves the land surface representation, benefiting both the streamflow prediction capabilities as well as providing improved estimates of water and energy fluxes into the atmosphere. In this study, the simple biosphere model 2...

Astroparticle physics with solar neutrinos.

PubMed

Nakahata, Masayuki

2011-01-01

Solar neutrino experiments observed fluxes smaller than the expectations from the standard solar model. This discrepancy is known as the "solar neutrino problem". Flux measurements by Super-Kamiokande and SNO have demonstrated that the solar neutrino problem is due to neutrino oscillations. Combining the results of all solar neutrino experiments, parameters for solar neutrino oscillations are obtained. Correcting for the effect of neutrino oscillations, the observed neutrino fluxes are consistent with the prediction from the standard solar model. In this article, results of solar neutrino experiments are reviewed with detailed descriptions of what Kamiokande and Super-Kamiokande have contributed to the history of astroparticle physics with solar neutrino measurements. (Communicated by Toshimitsu Yamazaki, M.J.A.).

Integrating ecosystems measurements from multiple eddy-covariance sites to a simple model of ecosystem process - Are there possibilities for a uniform model calibration?

NASA Astrophysics Data System (ADS)

Minunno, Francesco; Peltoniemi, Mikko; Launiainen, Samuli; Mäkelä, Annikki

2014-05-01

Biogeochemical models quantify the material and energy flux exchanges between biosphere, atmosphere and soil, however there is still considerable uncertainty underpinning model structure and parametrization. The increasing availability of data from of multiple sources provides useful information for model calibration and validation at different space and time scales. We calibrated a simplified ecosystem process model PRELES to data from multiple sites. In this work we had the following objective: to compare a multi-site calibration and site-specific calibrations, in order to test if PRELES is a model of general applicability, and to test how well one parameterization can predict ecosystem fluxes. Model calibration and evaluation were carried out by the means of the Bayesian method; Bayesian calibration (BC) and Bayesian model comparison (BMC) were used to quantify the uncertainty in model parameters and model structure. Evapotranspiration (ET) and gross primary production (GPP) measurements collected in 9 sites of Finland and Sweden were used in the study; half dataset was used for model calibrations and half for the comparative analyses. 10 BCs were performed; the model was independently calibrated for each of the nine sites (site-specific calibrations) and a multi-site calibration was achieved using the data from all the sites in one BC. Then 9 BMCs were carried out, one for each site, using output from the multi-site and the site-specific versions of PRELES. Similar estimates were obtained for the parameters at which model outputs are most sensitive. Not surprisingly, the joint posterior distribution achieved through the multi-site calibration was characterized by lower uncertainty, because more data were involved in the calibration process. No significant differences were encountered in the prediction of the multi-site and site-specific versions of PRELES, and after BMC, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. Despite being a simple model, PRELES provided good estimates of GPP and ET; only for one site PRELES multi-site version underestimated water fluxes. Our study implies convergence of GPP and water processes in boreal zone to the extent that their plausible prediction is possible with a simple model using global parameterization.

Evaluation of a genome-scale in silico metabolic model for Geobacter metallireducens by using proteomic data from a field biostimulation experiment.

PubMed

Fang, Yilin; Wilkins, Michael J; Yabusaki, Steven B; Lipton, Mary S; Long, Philip E

2012-12-01

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens-specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

High-frequency predictions for number counts and spectral properties of extragalactic radio sources. New evidence of a break at mm wavelengths in spectra of bright blazar sources

NASA Astrophysics Data System (ADS)

Tucci, M.; Toffolatti, L.; de Zotti, G.; Martínez-González, E.

2011-09-01

We present models to predict high-frequency counts of extragalactic radio sources using physically grounded recipes to describe the complex spectral behaviour of blazars that dominate the mm-wave counts at bright flux densities. We show that simple power-law spectra are ruled out by high-frequency (ν ≥ 100 GHz) data. These data also strongly constrain models featuring the spectral breaks predicted by classical physical models for the synchrotron emission produced in jets of blazars. A model dealing with blazars as a single population is, at best, only marginally consistent with data coming from current surveys at high radio frequencies. Our most successful model assumes different distributions of break frequencies, νM, for BL Lacs and flat-spectrum radio quasars (FSRQs). The former objects have substantially higher values of νM, implying that the synchrotron emission comes from more compact regions; therefore, a substantial increase of the BL Lac fraction at high radio frequencies and at bright flux densities is predicted. Remarkably, our best model is able to give a very good fit to all the observed data on number counts and on distributions of spectral indices of extragalactic radio sources at frequencies above 5 and up to 220 GHz. Predictions for the forthcoming sub-mm blazar counts from Planck, at the highest HFI frequencies, and from Herschel surveys are also presented. Appendices are available in electronic form at http://www.aanda.org

Modelling thermal radiation from one-meter diameter methane pool fires

NASA Astrophysics Data System (ADS)

Consalvi, J. L.; Demarco, R.

2012-06-01

The first objective of this article is to implement a comprehensive radiation model in order to predict the radiant fractions and radiative fluxes on remote surfaces in large-scale methane pool fires. The second aim is to quantify the importance of Turbulence-Radiation Interactions (TRIs) in such buoyant flames. The fire-induced flow is modelled by using a buoyancy-modified k-ɛ model and the Steady Laminar Flamelet (SLF) model coupled with a presumed probability density function (pdf) approach. Spectral radiation is modelled by using the Full-Spectrum Correlated-k (FSCK) method. TRIs are taken into account by considering the Optically-Thin Fluctuation Approximation (OTFA). The emission term and the mean absorption coefficient are closed by using a presumed pdf of the mixture fraction, scalar dissipation rate and enthalpy defect. Two 1m-diameter fires with Heat Release Rates (HRR) of 49 kW and 162 kW were simulated. Predicted radiant fractions and radiative heat fluxes are found in reasonable agreement with experimental data. The importance of TRIs is evidenced, computed radiant fractions and radiative heat fluxes being considerably higher than those obtained from calculations based on mean properties. Finally, model results show that the complete absorption coefficient-Planck function correlation should be considered in order to properly take into account the influence of TRIs on the emission term, whereas the absorption coefficient self-correlation in the absorption term reduces significantly the radiant fractions.

Evaluation of an urban canopy model in a tropical city: the role of tree evapotranspiration

NASA Astrophysics Data System (ADS)

Liu, Xuan; Li, Xian-Xiang; Harshan, Suraj; Roth, Matthias; Velasco, Erik

2017-09-01

A single layer urban canopy model (SLUCM) with enhanced hydrologic processes, is evaluated in a tropical city, Singapore. The evaluation was performed using an 11 month offline simulation with the coupled Noah land surface model/SLUCM over a compact low-rise residential area. Various hydrological processes are considered, including anthropogenic latent heat release, and evaporation from impervious urban facets. Results show that the prediction of energy fluxes, in particular latent heat flux, is improved when these processes were included. However, the simulated latent heat flux is still underestimated by ∼40%. Considering Singapore’s high green cover ratio, the tree evapotranspiration process is introduced into the model, which significantly improves the simulated latent heat flux. In particular, the systematic error of the model is greatly reduced, and becomes lower than the unsystematic error in some seasons. The effect of tree evapotranspiration on the urban surface energy balance is further demonstrated during an unusual dry spell. The present study demonstrates that even at sites with relatively low (11%) tree coverage, ignoring evapotranspiration from trees may cause serious underestimation of the latent heat flux and atmospheric humidity. The improved model is also transferable to other tropical or temperate regions to study the impact of tree evapotranspiration on urban climate.

Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux?

DOE PAGES

Zhu, Qing; Zhuang, Qianlai

2015-12-21

Reliability of terrestrial ecosystem models highly depends on the quantity and quality of thedata that have been used to calibrate the models. Nowadays, in situ observations of carbon fluxes areabundant. However, the knowledge of how much data (data length) and which subset of the time seriesdata (data period) should be used to effectively calibrate the model is still lacking. This study uses theAmeriFlux carbon flux data to parameterize the Terrestrial Ecosystem Model (TEM) with an adjoint-baseddata assimilation technique for various ecosystem types. Parameterization experiments are thus conductedto explore the impact of both data length and data period on the uncertaintymore » reduction of the posteriormodel parameters and the quantification of site and regional carbon dynamics. We find that: the modelis better constrained when it uses two-year data comparing to using one-year data. Further, two-year datais sufficient in calibrating TEM’s carbon dynamics, since using three-year data could only marginallyimprove the model performance at our study sites; the model is better constrained with the data thathave a higher‘‘climate variability’’than that having a lower one. The climate variability is used to measurethe overall possibility of the ecosystem to experience all climatic conditions including drought and extremeair temperatures and radiation; the U.S. regional simulations indicate that the effect of calibration datalength on carbon dynamics is amplified at regional and temporal scales, leading to large discrepanciesamong different parameterization experiments, especially in July and August. Our findings areconditioned on the specific model we used and the calibration sites we selected. The optimal calibrationdata length may not be suitable for other models. However, this study demonstrates that there may exist athreshold for calibration data length and simply using more data would not guarantee a better modelparameterization and prediction. More importantly, climate variability might be an effective indicator ofinformation within the data, which could help data selection for model parameterization. As a result, we believe ourfindings will benefit the ecosystem modeling community in using multiple-year data to improve modelpredictability.« less

Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Qing; Zhuang, Qianlai

Reliability of terrestrial ecosystem models highly depends on the quantity and quality of thedata that have been used to calibrate the models. Nowadays, in situ observations of carbon fluxes areabundant. However, the knowledge of how much data (data length) and which subset of the time seriesdata (data period) should be used to effectively calibrate the model is still lacking. This study uses theAmeriFlux carbon flux data to parameterize the Terrestrial Ecosystem Model (TEM) with an adjoint-baseddata assimilation technique for various ecosystem types. Parameterization experiments are thus conductedto explore the impact of both data length and data period on the uncertaintymore » reduction of the posteriormodel parameters and the quantification of site and regional carbon dynamics. We find that: the modelis better constrained when it uses two-year data comparing to using one-year data. Further, two-year datais sufficient in calibrating TEM’s carbon dynamics, since using three-year data could only marginallyimprove the model performance at our study sites; the model is better constrained with the data thathave a higher‘‘climate variability’’than that having a lower one. The climate variability is used to measurethe overall possibility of the ecosystem to experience all climatic conditions including drought and extremeair temperatures and radiation; the U.S. regional simulations indicate that the effect of calibration datalength on carbon dynamics is amplified at regional and temporal scales, leading to large discrepanciesamong different parameterization experiments, especially in July and August. Our findings areconditioned on the specific model we used and the calibration sites we selected. The optimal calibrationdata length may not be suitable for other models. However, this study demonstrates that there may exist athreshold for calibration data length and simply using more data would not guarantee a better modelparameterization and prediction. More importantly, climate variability might be an effective indicator ofinformation within the data, which could help data selection for model parameterization. As a result, we believe ourfindings will benefit the ecosystem modeling community in using multiple-year data to improve modelpredictability.« less

Advance and application of the stratigraphic simulation model 2D- SedFlux: From tank experiment to geological scale simulation

NASA Astrophysics Data System (ADS)

Kubo, Yu'suke; Syvitski, James P. M.; Hutton, Eric W. H.; Paola, Chris

2005-07-01

The stratigraphic simulation model 2D- SedFlux is further developed and applied to a turbidite experiment in a subsiding minibasin. The new module dynamically simulates evolving hyperpycnal flows and their interaction with the basin bed. Comparison between the numerical results and the experimental results verifies the ability of 2D- SedFlux to predict the distribution of the sediments and the possible feedback from subsidence. The model was subsequently applied to geological-scale minibasins such as are located in the Gulf of Mexico. Distance from the sediment source is determined to be more influential than the sediment entrapment in upstream minibasin. The results suggest that efficiency of sediment entrapment by a basin was not influenced by the distance from the sediment source.

Technical note: Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO)

NASA Astrophysics Data System (ADS)

Beringer, Jason; McHugh, Ian; Hutley, Lindsay B.; Isaac, Peter; Kljun, Natascha

2017-03-01

Standardised, quality-controlled and robust data from flux networks underpin the understanding of ecosystem processes and tools necessary to support the management of natural resources, including water, carbon and nutrients for environmental and production benefits. The Australian regional flux network (OzFlux) currently has 23 active sites and aims to provide a continental-scale national research facility to monitor and assess Australia's terrestrial biosphere and climate for improved predictions. Given the need for standardised and effective data processing of flux data, we have developed a software suite, called the Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO), that enables gap-filling and partitioning of the primary fluxes into ecosystem respiration (Fre) and gross primary productivity (GPP) and subsequently provides diagnostics and results. We outline the processing pathways and methodologies that are applied in DINGO (v13) to OzFlux data, including (1) gap-filling of meteorological and other drivers; (2) gap-filling of fluxes using artificial neural networks; (3) the u* threshold determination; (4) partitioning into ecosystem respiration and gross primary productivity; (5) random, model and u* uncertainties; and (6) diagnostic, footprint calculation, summary and results outputs. DINGO was developed for Australian data, but the framework is applicable to any flux data or regional network. Quality data from robust systems like DINGO ensure the utility and uptake of the flux data and facilitates synergies between flux, remote sensing and modelling.

The Ability of Atmospheric Data to Reduce Disagreements in Wetland Methane Flux Estimates over North America

NASA Astrophysics Data System (ADS)

Miller, S. M.; Andrews, A. E.; Benmergui, J. S.; Commane, R.; Dlugokencky, E. J.; Janssens-Maenhout, G.; Melton, J. R.; Michalak, A. M.; Sweeney, C.; Worthy, D. E. J.

2015-12-01

Existing estimates of methane fluxes from wetlands differ in both magnitude and distribution across North America. We discuss seven different bottom-up methane estimates in the context of atmospheric methane data collected across the US and Canada. In the first component of this study, we explore whether the observation network can even detect a methane pattern from wetlands. We find that the observation network can identify a methane pattern from Canadian wetlands but not reliably from US wetlands. Over Canada, the network can even identify spatial patterns at multi-provence scales. Over the US, by contrast, anthropogenic emissions and modeling errors obscure atmospheric patterns from wetland fluxes. In the second component of the study, we then use these observations to reconcile disagreements in the magnitude, seasonal cycle, and spatial distribution of existing estimates. Most existing estimates predict fluxes that are too large with a seasonal cycle that is too narrow. A model known as LPJ-Bern has a spatial distribution most consistent with atmospheric observations. By contrast, a spatially-constant model outperforms the distribution of most existing flux estimates across Canada. The results presented here provide several pathways to reduce disagreements among existing wetland flux estimates across North America.

Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River Basin

USDA-ARS?s Scientific Manuscript database

Regional evapotranspiration (ET) can be estimated using diagnostic remote sensing models, generally based on principles of energy balance, or with spatially distributed prognostic models that simultaneously balance both the energy and water budgets over landscapes using predictive equations for land...

Multiscale Metabolic Modeling of C4 Plants: Connecting Nonlinear Genome-Scale Models to Leaf-Scale Metabolism in Developing Maize Leaves

PubMed Central

Bogart, Eli; Myers, Christopher R.

2016-01-01

C4 plants, such as maize, concentrate carbon dioxide in a specialized compartment surrounding the veins of their leaves to improve the efficiency of carbon dioxide assimilation. Nonlinear relationships between carbon dioxide and oxygen levels and reaction rates are key to their physiology but cannot be handled with standard techniques of constraint-based metabolic modeling. We demonstrate that incorporating these relationships as constraints on reaction rates and solving the resulting nonlinear optimization problem yields realistic predictions of the response of C4 systems to environmental and biochemical perturbations. Using a new genome-scale reconstruction of maize metabolism, we build an 18000-reaction, nonlinearly constrained model describing mesophyll and bundle sheath cells in 15 segments of the developing maize leaf, interacting via metabolite exchange, and use RNA-seq and enzyme activity measurements to predict spatial variation in metabolic state by a novel method that optimizes correlation between fluxes and expression data. Though such correlations are known to be weak in general, we suggest that developmental gradients may be particularly suited to the inference of metabolic fluxes from expression data, and we demonstrate that our method predicts fluxes that achieve high correlation with the data, successfully capture the experimentally observed base-to-tip transition between carbon-importing tissue and carbon-exporting tissue, and include a nonzero growth rate, in contrast to prior results from similar methods in other systems. PMID:26990967

Lognormal Kalman filter for assimilating phase space density data in the radiation belts

NASA Astrophysics Data System (ADS)

Kondrashov, D.; Ghil, M.; Shprits, Y.

2011-11-01

Data assimilation combines a physical model with sparse observations and has become an increasingly important tool for scientists and engineers in the design, operation, and use of satellites and other high-technology systems in the near-Earth space environment. Of particular importance is predicting fluxes of high-energy particles in the Van Allen radiation belts, since these fluxes can damage spaceborne platforms and instruments during strong geomagnetic storms. In transiting from a research setting to operational prediction of these fluxes, improved data assimilation is of the essence. The present study is motivated by the fact that phase space densities (PSDs) of high-energy electrons in the outer radiation belt—both simulated and observed—are subject to spatiotemporal variations that span several orders of magnitude. Standard data assimilation methods that are based on least squares minimization of normally distributed errors may not be adequate for handling the range of these variations. We propose herein a modification of Kalman filtering that uses a log-transformed, one-dimensional radial diffusion model for the PSDs and includes parameterized losses. The proposed methodology is first verified on model-simulated, synthetic data and then applied to actual satellite measurements. When the model errors are sufficiently smaller then observational errors, our methodology can significantly improve analysis and prediction skill for the PSDs compared to those of the standard Kalman filter formulation. This improvement is documented by monitoring the variance of the innovation sequence.

Verifiable metamodels for nitrate losses to drains and groundwater in the corn belt, USA

USDA-ARS?s Scientific Manuscript database

Metamodels (MMs) consisting of artificial neural networks were developed to simplify and upscale mechanistic fate and transport models for prediction of nitrate losses to drains and groundwater in the Corn Belt, USA. The two final MMs predicted nitrate concentration and flux, respectively, in the sh...

Patterns in coupled water and energy cycle: Modeling, synthesis with observations, and assessing the subsurface-landsurface interactions

NASA Astrophysics Data System (ADS)

Rahman, A.; Kollet, S. J.; Sulis, M.

2013-12-01

In the terrestrial hydrological cycle, the atmosphere and the free groundwater table act as the upper and lower boundary condition, respectively, in the non-linear two-way exchange of mass and energy across the land surface. Identifying and quantifying the interactions among various atmospheric-subsurface-landsurface processes is complicated due to the diverse spatiotemporal scales associated with these processes. In this study, the coupled subsurface-landsurface model ParFlow.CLM was applied over a ~28,000 km2 model domain encompassing the Rur catchment, Germany, to simulate the fluxes of the coupled water and energy cycle. The model was forced by hourly atmospheric data from the COSMO-DE model (numerical weather prediction system of the German Weather Service) over one year. Following a spinup period, the model results were synthesized with observed river discharge, soil moisture, groundwater table depth, temperature, and landsurface energy flux data at different sites in the Rur catchment. It was shown that the model is able to reproduce reasonably the dynamics and also absolute values in observed fluxes and state variables without calibration. The spatiotemporal patterns in simulated water and energy fluxes as well as the interactions were studied using statistical, geostatistical and wavelet transform methods. While spatial patterns in the mass and energy fluxes can be predicted from atmospheric forcing and power law scaling in the transition and winter months, it appears that, in the summer months, the spatial patterns are determined by the spatially correlated variability in groundwater table depth. Continuous wavelet transform techniques were applied to study the variability of the catchment average mass and energy fluxes at varying time scales. From this analysis, the time scales associated with significant interactions among different mass and energy balance components were identified. The memory of precipitation variability in subsurface hydrodynamics acts at the 20-30 day time scale, while the groundwater contribution to sustain the long-term variability patterns in evapotranspiration acts at the 40-60 day scale. Diurnal patterns in connection with subsurface hydrodynamics were also detected. Thus, it appears that the subsurface hydrodynamics respond to the temporal patterns in land surface fluxes due to the variability in atmospheric forcing across multiple space and time scales.

Stochastic Analysis of Orbital Lifetimes of Spacecraft

NASA Technical Reports Server (NTRS)

Sasamoto, Washito; Goodliff, Kandyce; Cornelius, David

2008-01-01

A document discusses (1) a Monte-Carlo-based methodology for probabilistic prediction and analysis of orbital lifetimes of spacecraft and (2) Orbital Lifetime Monte Carlo (OLMC)--a Fortran computer program, consisting of a previously developed long-term orbit-propagator integrated with a Monte Carlo engine. OLMC enables modeling of variances of key physical parameters that affect orbital lifetimes through the use of probability distributions. These parameters include altitude, speed, and flight-path angle at insertion into orbit; solar flux; and launch delays. The products of OLMC are predicted lifetimes (durations above specified minimum altitudes) for the number of user-specified cases. Histograms generated from such predictions can be used to determine the probabilities that spacecraft will satisfy lifetime requirements. The document discusses uncertainties that affect modeling of orbital lifetimes. Issues of repeatability, smoothness of distributions, and code run time are considered for the purpose of establishing values of code-specific parameters and number of Monte Carlo runs. Results from test cases are interpreted as demonstrating that solar-flux predictions are primary sources of variations in predicted lifetimes. Therefore, it is concluded, multiple sets of predictions should be utilized to fully characterize the lifetime range of a spacecraft.

Predicting growth of the healthy infant using a genome scale metabolic model.

PubMed

Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

2017-01-01

An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

Effect of Global Warming and Increased Freshwater Flux on Northern Hemispheric Cooling

NASA Astrophysics Data System (ADS)

Girihagama, L. N.; Nof, D.

2016-02-01

We wish to answer the, fairly complicated, question of whether global warming and an increased freshwater flux can cause Northern Hemispheric warming or cooling. Starting from the assumption that the ocean is the primary source of variability in the Northern hemispheric ocean-atmosphere coupled system, we employed a simple non-linear one-dimensional coupled ocean-atmosphere model. The simplicity of the model allows us to analytically predict the evolution of many dynamical variables of interest such as, the strength of the Atlantic Meridional overturning circulation (AMOC), temperatures of the ocean and atmosphere, mass transports, salinity, and ocean-atmosphere heat fluxes. The model results show that a reduced AMOC transport due to an increased freshwater flux causes cooling in both the atmosphere and ocean in the North Atlantic (NA) deep-water formation region. Cooling in both the ocean and atmosphere can cause reduction of the ocean-atmosphere temperature difference, which in turn reduces heat fluxes in both the ocean and atmosphere. For present day climate parameters, the calculated critical freshwater flux needed to arrest AMOC is 0.08 Sv. For a constant atmospheric zonal flow, there is minimal reduction in the AMOC strength, as well as minimal warming of the ocean and atmosphere. This model provides a conceptual framework for a dynamically sound response of the ocean and atmosphere to AMOC variability as a function of increased freshwater flux. The results are qualitatively consistent with numerous realistic coupled numerical models of varying complexity.

Gluon correlations from a glasma flux-tube model compared to measured hadron correlations on transverse momentum (p t,p t) and angular differences (η Δ,φ Δ)

DOE PAGES

Trainor, Thomas A.; Ray, R. L.

2011-09-09

A glasma flux-tube model has been proposed to explain strong elongation on pseudorapidity η of the same-side two-dimensional (2D) peak in minimum-bias angular correlations from √( sNN)=200 GeV Au-Au collisions. The same-side peak or “soft ridge” is said to arise from coupling of flux tubes to radial flow whereby gluons radiated transversely from flux tubes are boosted by radial flow to form a narrow structure or ridge on azimuth. In this study we test the theory conjecture by comparing measurements to predictions for particle production, spectra, and correlations from the glasma model and from conventional fragmentation processes. We conclude thatmore » the glasma model is contradicted by measured hadron yields, spectra, and correlations, whereas a two-component model of hadron production, including minimum-bias parton fragmentation, provides a quantitative description of most features of the data, although η elongation of the same-side 2D peak remains undescribed.« less

Preferential flow, diffuse flow, and perching in an interbedded fractured-rock unsaturated zone

NASA Astrophysics Data System (ADS)

Nimmo, John R.; Creasey, Kaitlyn M.; Perkins, Kim S.; Mirus, Benjamin B.

2017-03-01

Layers of strong geologic contrast within the unsaturated zone can control recharge and contaminant transport to underlying aquifers. Slow diffuse flow in certain geologic layers, and rapid preferential flow in others, complicates the prediction of vertical and lateral fluxes. A simple model is presented, designed to use limited geological site information to predict these critical subsurface processes in response to a sustained infiltration source. The model is developed and tested using site-specific information from the Idaho National Laboratory in the Eastern Snake River Plain (ESRP), USA, where there are natural and anthropogenic sources of high-volume infiltration from floods, spills, leaks, wastewater disposal, retention ponds, and hydrologic field experiments. The thick unsaturated zone overlying the ESRP aquifer is a good example of a sharply stratified unsaturated zone. Sedimentary interbeds are interspersed between massive and fractured basalt units. The combination of surficial sediments, basalts, and interbeds determines the water fluxes through the variably saturated subsurface. Interbeds are generally less conductive, sometimes causing perched water to collect above them. The model successfully predicts the volume and extent of perching and approximates vertical travel times during events that generate high fluxes from the land surface. These developments are applicable to sites having a thick, geologically complex unsaturated zone of substantial thickness in which preferential and diffuse flow, and perching of percolated water, are important to contaminant transport or aquifer recharge.

Prediction of forced convective heat transfer and critical heat flux for subcooled water flowing in miniature tubes

NASA Astrophysics Data System (ADS)

Shibahara, Makoto; Fukuda, Katsuya; Liu, Qiusheng; Hata, Koichi

2018-02-01

The heat transfer characteristics of forced convection for subcooled water in small tubes were clarified using the commercial computational fluid dynamic (CFD) code, PHENICS ver. 2013. The analytical model consists of a platinum tube (the heated section) and a stainless tube (the non-heated section). Since the platinum tube was heated by direct current in the authors' previous experiments, a uniform heat flux with the exponential function was given as a boundary condition in the numerical simulation. Two inner diameters of the tubes were considered: 1.0 and 2.0 mm. The upward flow velocities ranged from 2 to 16 m/s and the inlet temperature ranged from 298 to 343 K. The numerical results showed that the difference between the surface temperature and the bulk temperature was in good agreement with the experimental data at each heat flux. The numerical model was extended to the liquid sublayer analysis for the CHF prediction and was evaluated by comparing its results with the experimental data. It was postulated that the CHF occurs when the fluid temperature near the heated wall exceeds the saturated temperature, based on Celata et al.'s superheated layer vapor replenishment (SLVR) model. The suggested prediction method was in good agreement with the experimental data and with other CHF data in literature within ±25%.

Preferential flow, diffuse flow, and perching in an interbedded fractured-rock unsaturated zone

USGS Publications Warehouse

Nimmo, John R.; Creasey, Kaitlyn M; Perkins, Kimberlie; Mirus, Benjamin B.

2017-01-01

Layers of strong geologic contrast within the unsaturated zone can control recharge and contaminant transport to underlying aquifers. Slow diffuse flow in certain geologic layers, and rapid preferential flow in others, complicates the prediction of vertical and lateral fluxes. A simple model is presented, designed to use limited geological site information to predict these critical subsurface processes in response to a sustained infiltration source. The model is developed and tested using site-specific information from the Idaho National Laboratory in the Eastern Snake River Plain (ESRP), USA, where there are natural and anthropogenic sources of high-volume infiltration from floods, spills, leaks, wastewater disposal, retention ponds, and hydrologic field experiments. The thick unsaturated zone overlying the ESRP aquifer is a good example of a sharply stratified unsaturated zone. Sedimentary interbeds are interspersed between massive and fractured basalt units. The combination of surficial sediments, basalts, and interbeds determines the water fluxes through the variably saturated subsurface. Interbeds are generally less conductive, sometimes causing perched water to collect above them. The model successfully predicts the volume and extent of perching and approximates vertical travel times during events that generate high fluxes from the land surface. These developments are applicable to sites having a thick, geologically complex unsaturated zone of substantial thickness in which preferential and diffuse flow, and perching of percolated water, are important to contaminant transport or aquifer recharge.

Biogenic Emission Inventories: Scaling Local Biogenic Measurements to Regions

NASA Astrophysics Data System (ADS)

Lamb, B.; Pressley, S.; Westberg, H.; Guenther, A.

2002-12-01

Biogenic Hydrocarbons, such as isoprene, are important trace gas species that are naturally emitted by vegetation and that affect the oxidative capacity of the atmosphere. Biogenic emissions are regulated by many environmental variables; the most important variables are thought to be temperature and light. Long-term isoprene flux measurements are useful for verifying existing canopy models and exploring other correlations between isoprene fluxes and environmental parameters. Biogenic Emission Models, such as BEIS (Biogenic Emission Inventory System) rely on above canopy environmental parameters and below canopy scaling factors to estimate canopy scale biogenic hydrocarbon fluxes. Other models, which are more complex, are coupled micrometeorological and physiological modules that provide feedback mechanisms present in a canopy environment. These types of models can predict biogenic emissions well, however, the required input is extensive, and for regional applications, they can be cumbersome. This paper presents analyses based on long-term isoprene flux measurements that have been collected since 1999 at the AmeriFlux site located at the University of Michigan Biological Station (UMBS) as part of the Program for Research on Oxidants: PHotochemistry, Emissions, and Transport (PROPHET). The goals of this research were to explore a potential relationship between the surface energy budget (primarily sensible heat flux) and isoprene emissions. Our hypothesis is that the surface energy flux is a better model parameter for isoprene emissions at the canopy scale than temperature and light levels, and the link to the surface energy budget will provide a significant improvement in isoprene emission models. Preliminary results indicate a significant correlation between daily isoprene emissions and sensible heat fluxes for a predominantly aspen/oak stand located in northern Michigan. Since surface energy budgets are an integral part of mesoscale meteorological models, this could potentially be a useful tool for including biogenic emissions into regional atmospheric models. Comparison of measured isoprene fluxes with current BEIS estimates will also be shown as an example of where emission inventories currently stand.

Inter-annual Variability of Evapotranspiration in a Semi-arid Oak-savanna Ecosystem: Measured and Modeled Buffering to Precipitation Changes

NASA Astrophysics Data System (ADS)

Raz-Yaseef, N.; Sonnentag, O.; Kobayashi, H.; Baldocchi, D. D.

2010-12-01

Precipitation (P) is the primary control on vegetation dynamics and productivity, implying that climate induced disturbances in frequency and timing of P are intimately coupled with fluxes of carbon, water and energy. Future climate change is expected to increase extreme rainfall events as well as droughts, suggesting linked vegetation changes to an unknown extent. Semi-arid climates experience large inter-annual variability (IAV) in P, creating natural conditions adequate to study how year-to-year changes in P affect atmosphere-biosphere fluxes. We used a 10-year flux database collected at a semi-arid savanna site in order to: (1) define IAV in P by means of frequency and timing; (2) investigate how changes in P affect the ecohydrology of the forest and its partitioning into the main vapor fluxes, and (3) evaluate model capability to predict IAV of carbon and water fluxes above and below the canopy. This is based on the perception that the capability of process-oriented models to construct the deviation, and not the average, is important in order to correctly predict ecosystem sensitivity to climate change. Our research site was a low density and low LAI (0.8) semi-arid (P=523±180 mm yr-1) savanna site, combined of oaks and grass, and located at Tonzi ranch, California. Measurements of carbon and water fluxes above and below the tree canopy using eddy covariance and supplementary measurements have been made since 2001. Measured fluxes were compared to modeled based on two bio-meteorological process-oriented ecosystem models: BEPS and 3D-CAONAK. Our results show that IAV in P was large, and standard deviation (STD) was 38% of the average. Accordingly, the wet soil period (measured volumetric water content > 8%) varied between 156 days in dry years to 301 days in wet years. IAV of the vapor fluxes were lower than that of P (STD was 17% for the trees and 23% for the floor components), suggesting on ecosystem buffering to changes in P. The timing of grass green up was correlated with the timing of first rains, emphasizing the higher dependence of the floor component on P, as reflected in higher IAV of the grasses compared to the trees. On average, models simulated annual fluxes well (R2>0.93), but IAV of the trees was higher than measured (24%), mostly due to model underestimation during dry years. A threshold at P~500 mm yr-1 was observed (both in measurements and modeled results), above which tree transpiration barely increased. The high IAV of the floor component was not replicated in the models (SDV=5%), although this flux accounted for 55% of total ET. Based on our study we conclude that trees in this semi-arid ecosystem have developed adaptive mechanisms that buffer themselves from the year-to-year variations in precipitation.

New constraints on all flavor Galactic diffuse neutrino emission with the ANTARES telescope

NASA Astrophysics Data System (ADS)

Albert, A.; André, M.; Anghinolfi, M.; Anton, G.; Ardid, M.; Aubert, J.-J.; Avgitas, T.; Baret, B.; Barrios-Martí, J.; Basa, S.; Belhorma, B.; Bertin, V.; Biagi, S.; Bormuth, R.; Bourret, S.; Bouwhuis, M. C.; Bruijn, R.; Brunner, J.; Busto, J.; Capone, A.; Caramete, L.; Carr, J.; Celli, S.; Cherkaoui El Moursli, R.; Chiarusi, T.; Circella, M.; Coelho, J. A. B.; Coleiro, A.; Coniglione, R.; Costantini, H.; Coyle, P.; Creusot, A.; Díaz, A. F.; Deschamps, A.; de Bonis, G.; Distefano, C.; di Palma, I.; Domi, A.; Donzaud, C.; Dornic, D.; Drouhin, D.; Eberl, T.; El Bojaddaini, I.; El Khayati, N.; Elsässer, D.; Enzenhöfer, A.; Ettahiri, A.; Fassi, F.; Felis, I.; Fusco, L. A.; Galatà, S.; Gay, P.; Giordano, V.; Glotin, H.; Grégoire, T.; Gracia Ruiz, R.; Graf, K.; Hallmann, S.; van Haren, H.; Heijboer, A. J.; Hello, Y.; Hernández-Rey, J. J.; Hößl, J.; Hofestädt, J.; Hugon, C.; Illuminati, G.; James, C. W.; de Jong, M.; Jongen, M.; Kadler, M.; Kalekin, O.; Katz, U.; Kießling, D.; Kouchner, A.; Kreter, M.; Kreykenbohm, I.; Kulikovskiy, V.; Lachaud, C.; Lahmann, R.; Lefèvre, D.; Leonora, E.; Lotze, M.; Loucatos, S.; Marcelin, M.; Margiotta, A.; Marinelli, A.; Martínez-Mora, J. A.; Mele, R.; Melis, K.; Michael, T.; Migliozzi, P.; Moussa, A.; Navas, S.; Nezri, E.; Organokov, M.; Pǎvǎlaş, G. E.; Pellegrino, C.; Perrina, C.; Piattelli, P.; Popa, V.; Pradier, T.; Quinn, L.; Racca, C.; Riccobene, G.; Sánchez-Losa, A.; Saldaña, M.; Salvadori, I.; Samtleben, D. F. E.; Sanguineti, M.; Sapienza, P.; Schüssler, F.; Sieger, C.; Spurio, M.; Stolarczyk, Th.; Taiuti, M.; Tayalati, Y.; Trovato, A.; Turpin, D.; Tönnis, C.; Vallage, B.; van Elewyck, V.; Versari, F.; Vivolo, D.; Vizzoca, A.; Wilms, J.; Zornoza, J. D.; Zúñiga, J.; Gaggero, D.; Grasso, D.; ANTARES Collaboration

2017-09-01

The flux of very high-energy neutrinos produced in our Galaxy by the interaction of accelerated cosmic rays with the interstellar medium is not yet determined. The characterization of this flux will shed light on Galactic accelerator features, gas distribution morphology and Galactic cosmic ray transport. The central Galactic plane can be the site of an enhanced neutrino production, thus leading to anisotropies in the extraterrestrial neutrino signal as measured by the IceCube Collaboration. The ANTARES neutrino telescope, located in the Mediterranean Sea, offers a favorable view of this part of the sky, thereby allowing for a contribution to the determination of this flux. The expected diffuse Galactic neutrino emission can be obtained, linking a model of generation and propagation of cosmic rays with the morphology of the gas distribution in the Milky Way. In this paper, the so-called "gamma model" introduced recently to explain the high-energy gamma-ray diffuse Galactic emission is assumed as reference. The neutrino flux predicted by the "gamma model" depends on the assumed primary cosmic ray spectrum cutoff. Considering a radially dependent diffusion coefficient, this proposed scenario is able to account for the local cosmic ray measurements, as well as for the Galactic gamma-ray observations. Nine years of ANTARES data are used in this work to search for a possible Galactic contribution according to this scenario. All flavor neutrino interactions are considered. No excess of events is observed, and an upper limit is set on the neutrino flux of 1.1 (1.2) times the prediction of the "gamma model," assuming the primary cosmic ray spectrum cutoff at 5 (50) PeV. This limit excludes the diffuse Galactic neutrino emission as the major cause of the "spectral anomaly" between the two hemispheres measured by IceCube.

Environmental Barrier Coating Fracture, Fatigue and High-Heat-Flux Durability Modeling and Stochastic Progressive Damage Simulation

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Nemeth, Noel N.

2017-01-01

Advanced environmental barrier coatings will play an increasingly important role in future gas turbine engines because of their ability to protect emerging light-weight SiC/SiC ceramic matrix composite (CMC) engine components, further raising engine operating temperatures and performance. Because the environmental barrier coating systems are critical to the performance, reliability and durability of these hot-section ceramic engine components, a prime-reliant coating system along with established life design methodology are required for the hot-section ceramic component insertion into engine service. In this paper, we have first summarized some observations of high temperature, high-heat-flux environmental degradation and failure mechanisms of environmental barrier coating systems in laboratory simulated engine environment tests. In particular, the coating surface cracking morphologies and associated subsequent delamination mechanisms under the engine level high-heat-flux, combustion steam, and mechanical creep and fatigue loading conditions will be discussed. The EBC compostion and archtechture improvements based on advanced high heat flux environmental testing, and the modeling advances based on the integrated Finite Element Analysis Micromechanics Analysis Code/Ceramics Analysis and Reliability Evaluation of Structures (FEAMAC/CARES) program will also be highlighted. The stochastic progressive damage simulation successfully predicts mud flat damage pattern in EBCs on coated 3-D specimens, and a 2-D model of through-the-thickness cross-section. A 2-parameter Weibull distribution was assumed in characterizing the coating layer stochastic strength response and the formation of damage was therefore modeled. The damage initiation and coalescence into progressively smaller mudflat crack cells was demonstrated. A coating life prediction framework may be realized by examining the surface crack initiation and delamination propagation in conjunction with environmental degradation under high-heat-flux and environment load test conditions.

Critical Decay Index at the Onset of Solar Eruptions

NASA Astrophysics Data System (ADS)

Zuccarello, F. P.; Aulanier, G.; Gilchrist, S. A.

2015-12-01

Magnetic flux ropes are topological structures consisting of twisted magnetic field lines that globally wrap around an axis. The torus instability model predicts that a magnetic flux rope of major radius R undergoes an eruption when its axis reaches a location where the decay index -d({ln}{B}{ex})/d({ln}R) of the ambient magnetic field Bex is larger than a critical value. In the current-wire model, the critical value depends on the thickness and time evolution of the current channel. We use magnetohydrodynamic simulations to investigate whether the critical value of the decay index at the onset of the eruption is affected by the magnetic flux rope’s internal current profile and/or by the particular pre-eruptive photospheric dynamics. The evolution of an asymmetric, bipolar active region is driven by applying different classes of photospheric motions. We find that the critical value of the decay index at the onset of the eruption is not significantly affected by either the pre-erupitve photospheric evolution of the active region or the resulting different magnetic flux ropes. As in the case of the current-wire model, we find that there is a “critical range” [1.3-1.5], rather than a “critical value” for the onset of the torus instability. This range is in good agreement with the predictions of the current-wire model, despite the inclusion of line-tying effects and the occurrence of tether-cutting magnetic reconnection.

Calibration of Ocean Forcing with satellite Flux Estimates (COFFEE)

NASA Astrophysics Data System (ADS)

Barron, Charlie; Jan, Dastugue; Jackie, May; Rowley, Clark; Smith, Scott; Spence, Peter; Gremes-Cordero, Silvia

2016-04-01

Predicting the evolution of ocean temperature in regional ocean models depends on estimates of surface heat fluxes and upper-ocean processes over the forecast period. Within the COFFEE project (Calibration of Ocean Forcing with satellite Flux Estimates, real-time satellite observations are used to estimate shortwave, longwave, sensible, and latent air-sea heat flux corrections to a background estimate from the prior day's regional or global model forecast. These satellite-corrected fluxes are used to prepare a corrected ocean hindcast and to estimate flux error covariances to project the heat flux corrections for a 3-5 day forecast. In this way, satellite remote sensing is applied to not only inform the initial ocean state but also to mitigate errors in surface heat flux and model representations affecting the distribution of heat in the upper ocean. While traditional assimilation of sea surface temperature (SST) observations re-centers ocean models at the start of each forecast cycle, COFFEE endeavors to appropriately partition and reduce among various surface heat flux and ocean dynamics sources. A suite of experiments in the southern California Current demonstrates a range of COFFEE capabilities, showing the impact on forecast error relative to a baseline three-dimensional variational (3DVAR) assimilation using operational global or regional atmospheric forcing. Experiment cases combine different levels of flux calibration with assimilation alternatives. The cases use the original fluxes, apply full satellite corrections during the forecast period, or extend hindcast corrections into the forecast period. Assimilation is either baseline 3DVAR or standard strong-constraint 4DVAR, with work proceeding to add a 4DVAR expanded to include a weak constraint treatment of the surface flux errors. Covariance of flux errors is estimated from the recent time series of forecast and calibrated flux terms. While the California Current examples are shown, the approach is equally applicable to other regions. These approaches within a 3DVAR application are anticipated to be useful for global and larger regional domains where a full 4DVAR methodology may be cost-prohibitive.

The Role of Surface Energy Exchange for Simulating Wind Inflow: An Evaluation of Multiple Land Surface Models in WRF for the Southern Great Plains Site Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wharton, Sonia; Simpson, Matthew; Osuna, Jessica

The Weather Research and Forecasting (WRF) model is used to investigate choice of land surface model (LSM) on the near-surface wind profile, including heights reached by multi-megawatt wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil-plant-atmosphere feedbacks for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) Central Facility in Oklahoma. Surface-flux and wind-profile measurements were available for validation. The WRF model was run for three two-week periods during which varying canopy and meteorological conditions existed. Themore » LSMs predicted a wide range of energy-flux and wind-shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil-plant-atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear also were sensitive to LSM choice and were partially related to the accuracy of energy flux data. The variability of LSM performance was relatively high, suggesting that LSM representation of energy fluxes in the WRF model remains a significant source of uncertainty for simulating wind turbine inflow conditions.« less

The timing and intensity of column collapse during explosive volcanic eruptions

NASA Astrophysics Data System (ADS)

Carazzo, Guillaume; Kaminski, Edouard; Tait, Stephen

2015-02-01

Volcanic columns produced by explosive eruptions commonly reach, at some stage, a collapse regime with associated pyroclastic density currents propagating on the ground. The threshold conditions for the entrance into this regime are mainly controlled by the mass flux and exsolved gas content at the source. However, column collapse is often partial and the controls on the fraction of total mass flux that feeds the pyroclastic density currents, defined here as the intensity of collapse, are unknown. To better understand this regime, we use a new experimental apparatus reproducing at laboratory scale the convecting and collapsing behavior of hot particle-laden air jets. We validate the predictions of a 1D theoretical model for the entrance into the regime of partial collapse. Furthermore, we show that where a buoyant plume and a collapsing fountain coexist, the intensity of collapse can be predicted by a universal scaling relationship. We find that the intensity of collapse in the partial collapse regime is controlled by magma gas content and temperature, and always exceeds 40%, independent of peak mass flux and total erupted volume. The comparison between our theoretical predictions and a set of geological data on historic and pre-historic explosive eruptions shows that the model can be used to predict both the onset and intensity of column collapse, hence it can be used for rapid assessment of volcanic hazards notably ash dispersal during eruptive crises.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenberg, Jim; Penuelas, J.; Guenther, Alex B.

To survey landscape-scale fluxes of biogenic gases, a100-meterTeflon tube was attached to a tethered balloon as a sampling inlet for a fast response Proton Transfer Reaction Mass Spectrometer (PTRMS). Along with meteorological instruments deployed on the tethered balloon and at 3-mand outputs from a regional weather model, these observations were used to estimate landscape scale biogenic volatile organic compound fluxes with two micrometeorological techniques: mixed layer variance and surface layer gradients. This highly mobile sampling system was deployed at four field sites near Barcelona to estimate landscape-scale BVOC emission factors in a relatively short period (3 weeks). The two micrometeorologicalmore » techniques agreed within the uncertainty of the flux measurements at all four sites even though the locations had considerable heterogeneity in species distribution and complex terrain. The observed fluxes were significantly different than emissions predicted with an emission model using site-specific emission factors and land-cover characteristics. Considering the wide range in reported BVOC emission factors of VOCs for individual vegetation species (more than an order of magnitude), this flux estimation technique is useful for constraining BVOC emission factors used as model inputs.« less

Performance prediction using geostatistics and window reservoir simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fontanilla, J.P.; Al-Khalawi, A.A.; Johnson, S.G.

1995-11-01

This paper is the first window model study in the northern area of a large carbonate reservoir in Saudi Arabia. It describes window reservoir simulation with geostatistics to model uneven water encroachment in the southwest producing area of the northern portion of the reservoir. In addition, this paper describes performance predictions that investigate the sweep efficiency of the current peripheral waterflood. A 50 x 50 x 549 (240 m. x 260 m. x 0.15 m. average grid block size) geological model was constructed with geostatistics software. Conditional simulation was used to obtain spatial distributions of porosity and volume of dolomite.more » Core data transforms were used to obtain horizontal and vertical permeability distributions. Simple averaging techniques were used to convert the 549-layer geological model to a 50 x 50 x 10 (240 m. x 260 m. x 8 m. average grid block size) window reservoir simulation model. Flux injectors and flux producers were assigned to the outermost grid blocks. Historical boundary flux rates were obtained from a coarsely-ridded full-field model. Pressure distribution, water cuts, GORs, and recent flowmeter data were history matched. Permeability correction factors and numerous parameter adjustments were required to obtain the final history match. The permeability correction factors were based on pressure transient permeability-thickness analyses. The prediction phase of the study evaluated the effects of infill drilling, the use of artificial lifts, workovers, horizontal wells, producing rate constraints, and tight zone development to formulate depletion strategies for the development of this area. The window model will also be used to investigate day-to-day reservoir management problems in this area.« less

Modelling of the 10-micrometer natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Deming, D.; Mumma, M. J.

1983-01-01

The NLTE radiative transfer problem is solved to obtain the 00 deg 1 vibrational state population. This model successfully reproduces the existing center-to-limb observations, although higher spatial resolution observations are needed for a definitive test. The model also predicts total fluxes which are close to the observed values. The strength of the emission is predicted to be closely related to the instantaneous near-IR solar heating rate.

Modeling of the 10-micron natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Deming, D.; Mumma, M. J.

1983-01-01

The NLTE radiative transfer problem is solved to obtain the 00 deg 1 vibrational state population. This model successfully reproduces the existing center-to-limb observations, although higher spatial resolution observations are needed for a definitive test. The model also predicts total fluxes which are close to the observed values. The strength of the emission is predicted to be closely related to the instantaneous near-IR solar heating rate.

An Improved Analytic Model for Microdosimeter Response

NASA Technical Reports Server (NTRS)

Shinn, Judy L.; Wilson, John W.; Xapsos, Michael A.

2001-01-01

An analytic model used to predict energy deposition fluctuations in a microvolume by ions through direct events is improved to include indirect delta ray events. The new model can now account for the increase in flux at low lineal energy when the ions are of very high energy. Good agreement is obtained between the calculated results and available data for laboratory ion beams. Comparison of GCR (galactic cosmic ray) flux between Shuttle TEPC (tissue equivalent proportional counter) flight data and current calculations draws a different assessment of developmental work required for the GCR transport code (HZETRN) than previously concluded.

Constraining terrestrial ecosystem CO2 fluxes by integrating models of biogeochemistry and atmospheric transport and data of surface carbon fluxes and atmospheric CO2 concentrations

NASA Astrophysics Data System (ADS)

Zhu, Q.; Zhuang, Q.; Henze, D.; Bowman, K.; Chen, M.; Liu, Y.; He, Y.; Matsueda, H.; Machida, T.; Sawa, Y.; Oechel, W.

2014-09-01

Regional net carbon fluxes of terrestrial ecosystems could be estimated with either biogeochemistry models by assimilating surface carbon flux measurements or atmospheric CO2 inversions by assimilating observations of atmospheric CO2 concentrations. Here we combine the ecosystem biogeochemistry modeling and atmospheric CO2 inverse modeling to investigate the magnitude and spatial distribution of the terrestrial ecosystem CO2 sources and sinks. First, we constrain a terrestrial ecosystem model (TEM) at site level by assimilating the observed net ecosystem production (NEP) for various plant functional types. We find that the uncertainties of model parameters are reduced up to 90% and model predictability is greatly improved for all the plant functional types (coefficients of determination are enhanced up to 0.73). We then extrapolate the model to a global scale at a 0.5° × 0.5° resolution to estimate the large-scale terrestrial ecosystem CO2 fluxes, which serve as prior for atmospheric CO2 inversion. Second, we constrain the large-scale terrestrial CO2 fluxes by assimilating the GLOBALVIEW-CO2 and mid-tropospheric CO2 retrievals from the Atmospheric Infrared Sounder (AIRS) into an atmospheric transport model (GEOS-Chem). The transport inversion estimates that: (1) the annual terrestrial ecosystem carbon sink in 2003 is -2.47 Pg C yr-1, which agrees reasonably well with the most recent inter-comparison studies of CO2 inversions (-2.82 Pg C yr-1); (2) North America temperate, Europe and Eurasia temperate regions act as major terrestrial carbon sinks; and (3) The posterior transport model is able to reasonably reproduce the atmospheric CO2 concentrations, which are validated against Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) CO2 concentration data. This study indicates that biogeochemistry modeling or atmospheric transport and inverse modeling alone might not be able to well quantify regional terrestrial carbon fluxes. However, combining the two modeling approaches and assimilating data of surface carbon flux as well as atmospheric CO2 mixing ratios might significantly improve the quantification of terrestrial carbon fluxes.

Evaluating the Classical Versus an Emerging Conceptual Model of Peatland Methane Dynamics

NASA Astrophysics Data System (ADS)

Yang, Wendy H.; McNicol, Gavin; Teh, Yit Arn; Estera-Molina, Katerina; Wood, Tana E.; Silver, Whendee L.

2017-09-01

Methane (CH4) is a potent greenhouse gas that is both produced and consumed in soils by microbially mediated processes sensitive to soil redox. We evaluated the classical conceptual model of peatland CH4 dynamics—in which the water table position determines the vertical distribution of methanogenesis and methanotrophy—versus an emerging model in which methanogenesis and methanotrophy can both occur throughout the soil profile due to spatially heterogeneous redox and anaerobic CH4 oxidation. We simultaneously measured gross CH4 production and oxidation in situ across a microtopographical gradient in a drained temperate peatland and ex situ along the soil profile, giving us novel insight into the component fluxes of landscape-level net CH4 fluxes. Net CH4 fluxes varied among landforms (p < 0.001), ranging from 180.3 ± 81.2 mg C m-2 d-1 in drainage ditches to -0.7 ± 1.2 mg C m-2 d-1 in the highest landform. Contrary to prediction by the classical conceptual model, variability in methanogenesis alone drove the landscape-level net CH4 flux patterns. Consistent with the emerging model, freshly collected soils from above the water table produced CH4 within anaerobic microsites. Even in soil from beneath the water table, gross CH4 production was best predicted by the methanogenic fraction of carbon mineralization, an index of highly reducing microsites. We measured low rates of anaerobic CH4 oxidation, which may have been limited by relatively low in situ CH4 concentrations in the hummock/hollow soil profile. Our study revealed complex CH4 dynamics better represented by the emerging heterogeneous conceptual model than the classical model based on redox strata.

Comparison of Austenite Decomposition Models During Finite Element Simulation of Water Quenching and Air Cooling of AISI 4140 Steel

NASA Astrophysics Data System (ADS)

Babu, K.; Prasanna Kumar, T. S.

2014-08-01

An indigenous, non-linear, and coupled finite element (FE) program has been developed to predict the temperature field and phase evolution during heat treatment of steels. The diffusional transformations during continuous cooling of steels were modeled using Johnson-Mehl-Avrami-Komogorov equation, and the non-diffusion transformation was modeled using Koistinen-Marburger equation. Cylindrical quench probes made of AISI 4140 steel of 20-mm diameter and 50-mm long were heated to 1123 K (850 °C), quenched in water, and cooled in air. The temperature history during continuous cooling was recorded at the selected interior locations of the quench probes. The probes were then sectioned at the mid plane and resultant microstructures were observed. The process of water quenching and air cooling of AISI 4140 steel probes was simulated with the heat flux boundary condition in the FE program. The heat flux for air cooling process was calculated through the inverse heat conduction method using the cooling curve measured during air cooling of a stainless steel 304L probe as an input. The heat flux for the water quenching process was calculated from a surface heat flux model proposed for quenching simulations. The isothermal transformation start and finish times of different phases were taken from the published TTT data and were also calculated using Kirkaldy model and Li model and used in the FE program. The simulated cooling curves and phases using the published TTT data had a good agreement with the experimentally measured values. The computation results revealed that the use of published TTT data was more reliable in predicting the phase transformation during heat treatment of low alloy steels than the use of the Kirkaldy or Li model.

Development of a General Form CO 2 and Brine Flux Input Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mansoor, K.; Sun, Y.; Carroll, S.

2014-08-01

The National Risk Assessment Partnership (NRAP) project is developing a science-based toolset for the quantitative analysis of the potential risks associated with changes in groundwater chemistry from CO 2 injection. In order to address uncertainty probabilistically, NRAP is developing efficient, reduced-order models (ROMs) as part of its approach. These ROMs are built from detailed, physics-based process models to provide confidence in the predictions over a range of conditions. The ROMs are designed to reproduce accurately the predictions from the computationally intensive process models at a fraction of the computational time, thereby allowing the utilization of Monte Carlo methods to probemore » variability in key parameters. This report presents the procedures used to develop a generalized model for CO 2 and brine leakage fluxes based on the output of a numerical wellbore simulation. The resulting generalized parameters and ranges reported here will be used for the development of third-generation groundwater ROMs.« less

A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

PubMed Central

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-01-01

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing. PMID:24803190

Radio Properties of the BAT AGNs: the FIR-radio Relation, the Fundamental Plane, and the Main Sequence of Star Formation

NASA Astrophysics Data System (ADS)

Smith, Krista Lynne; Mushotzky, Richard F.; Vogel, Stuart; Shimizu, Thomas T.; Miller, Neal

2016-12-01

We conducted 22 GHz 1″ JVLA imaging of 70 radio-quiet active galactic nuclei (AGNs) from the Swift-BAT survey. We find radio cores in all but three objects. The radio morphologies of the sample fall into three groups: compact and core-dominated, extended, and jet-like. We spatially decompose each image into core flux and extended flux, and compare the extended radio emission with that predicted from previous Herschel observations using the canonical FIR-radio relation. After removing the AGN contribution to the FIR and radio flux densities, we find that the relation holds remarkably well despite the potentially different star formation physics in the circumnuclear environment. We also compare our core radio flux densities with predictions of coronal models and scale-invariant jet models for the origin of radio emission in radio-quiet AGNs, and find general consistency with both models. However, we find that the L R/L X relation does not distinguish between star formation and non-relativistic AGN-driven outflows as the origin of radio emission in radio-quiet AGNs. Finally, we examine where objects with different radio morphologies fall in relation to the main sequence (MS) of star formation, and conclude that those AGNs that fall below the MS, as X-ray selected AGNs have been found to do, have core-dominated or jet-like 22 GHz morphologies.

The scatter and evolution of the global hot gas properties of simulated galaxy cluster populations

NASA Astrophysics Data System (ADS)

Le Brun, Amandine M. C.; McCarthy, Ian G.; Schaye, Joop; Ponman, Trevor J.

2017-04-01

We use the cosmo-OverWhelmingly Large Simulation (cosmo-OWLS) suite of cosmological hydrodynamical simulations to investigate the scatter and evolution of the global hot gas properties of large simulated populations of galaxy groups and clusters. Our aim is to compare the predictions of different physical models and to explore the extent to which commonly adopted assumptions in observational analyses (e.g. self-similar evolution) are violated. We examine the relations between (true) halo mass and the X-ray temperature, X-ray luminosity, gas mass, Sunyaev-Zel'dovich (SZ) flux, the X-ray analogue of the SZ flux (YX) and the hydrostatic mass. For the most realistic models, which include active galactic nuclei (AGN) feedback, the slopes of the various mass-observable relations deviate substantially from the self-similar ones, particularly at late times and for low-mass clusters. The amplitude of the mass-temperature relation shows negative evolution with respect to the self-similar prediction (I.e. slower than the prediction) for all models, driven by an increase in non-thermal pressure support at higher redshifts. The AGN models predict strong positive evolution of the gas mass fractions at low halo masses. The SZ flux and YX show positive evolution with respect to self-similarity at low mass but negative evolution at high mass. The scatter about the relations is well approximated by log-normal distributions, with widths that depend mildly on halo mass. The scatter decreases significantly with increasing redshift. The exception is the hydrostatic mass-halo mass relation, for which the scatter increases with redshift. Finally, we discuss the relative merits of various hot gas-based mass proxies.

An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

PubMed

Nandi, Sutanu; Subramanian, Abhishek; Sarkar, Ram Rup

2017-07-25

Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems, like imbalanced provision of training datasets, biased choice of the best model for a given balanced dataset, choice of a complex machine learning algorithm, and data-based automated selection of biologically relevant features for classification. Here, we propose a simple support vector machine-based learning strategy for the prediction of essential genes in Escherichia coli K-12 MG1655 metabolism that integrates a non-conventional combination of an appropriate sample balanced training set, a unique organism-specific genotype, phenotype attributes that characterize essential genes, and optimal parameters of the learning algorithm to generate the best machine learning model (the model with the highest accuracy among all the models trained for different sample training sets). For the first time, we also introduce flux-coupled metabolic subnetwork-based features for enhancing the classification performance. Our strategy proves to be superior as compared to previous SVM-based strategies in obtaining a biologically relevant classification of genes with high sensitivity and specificity. This methodology was also trained with datasets of other recent supervised classification techniques for essential gene classification and tested using reported test datasets. The testing accuracy was always high as compared to the known techniques, proving that our method outperforms known methods. Observations from our study indicate that essential genes are conserved among homologous bacterial species, demonstrate high codon usage bias, GC content and gene expression, and predominantly possess a tendency to form physiological flux modules in metabolism.

Calculating the dermal flux of chemicals with OELs based on their molecular structure: An attempt to assign the skin notation.

PubMed

Kupczewska-Dobecka, Małgorzata; Jakubowski, Marek; Czerczak, Sławomir

2010-09-01

Our objectives included calculating the permeability coefficient and dermal penetration rates (flux value) for 112 chemicals with occupational exposure limits (OELs) according to the LFER (linear free-energy relationship) model developed using published methods. We also attempted to assign skin notations based on each chemical's molecular structure. There are many studies available where formulae for coefficients of permeability from saturated aqueous solutions (K(p)) have been related to physicochemical characteristics of chemicals. The LFER model is based on the solvation equation, which contains five main descriptors predicted from chemical structure: solute excess molar refractivity, dipolarity/polarisability, summation hydrogen bond acidity and basicity, and the McGowan characteristic volume. Descriptor values, available for about 5000 compounds in the Pharma Algorithms Database were used to calculate permeability coefficients. Dermal penetration rate was estimated as a ratio of permeability coefficient and concentration of chemical in saturated aqueous solution. Finally, estimated dermal penetration rates were used to assign the skin notation to chemicals. Defined critical fluxes defined from the literature were recommended as reference values for skin notation. The application of Abraham descriptors predicted from chemical structure and LFER analysis in calculation of permeability coefficients and flux values for chemicals with OELs was successful. Comparison of calculated K(p) values with data obtained earlier from other models showed that LFER predictions were comparable to those obtained by some previously published models, but the differences were much more significant for others. It seems reasonable to conclude that skin should not be characterised as a simple lipophilic barrier alone. Both lipophilic and polar pathways of permeation exist across the stratum corneum. It is feasible to predict skin notation on the basis of the LFER and other published models; from among 112 chemicals 94 (84%) should have the skin notation in the OEL list based on the LFER calculations. The skin notation had been estimated by other published models for almost 94% of the chemicals. Twenty-nine (25.8%) chemicals were identified to have significant absorption and 65 (58%) the potential for dermal toxicity. We found major differences between alternative published analytical models and their ability to determine whether particular chemicals were potentially dermotoxic. Copyright © 2010 Elsevier B.V. All rights reserved.

Diagnosing Undersampling in Monte Carlo Eigenvalue and Flux Tally Estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perfetti, Christopher M; Rearden, Bradley T

2015-01-01

This study explored the impact of undersampling on the accuracy of tally estimates in Monte Carlo (MC) calculations. Steady-state MC simulations were performed for models of several critical systems with varying degrees of spatial and isotopic complexity, and the impact of undersampling on eigenvalue and fuel pin flux/fission estimates was examined. This study observed biases in MC eigenvalue estimates as large as several percent and biases in fuel pin flux/fission tally estimates that exceeded tens, and in some cases hundreds, of percent. This study also investigated five statistical metrics for predicting the occurrence of undersampling biases in MC simulations. Threemore » of the metrics (the Heidelberger-Welch RHW, the Geweke Z-Score, and the Gelman-Rubin diagnostics) are commonly used for diagnosing the convergence of Markov chains, and two of the methods (the Contributing Particles per Generation and Tally Entropy) are new convergence metrics developed in the course of this study. These metrics were implemented in the KENO MC code within the SCALE code system and were evaluated for their reliability at predicting the onset and magnitude of undersampling biases in MC eigenvalue and flux tally estimates in two of the critical models. Of the five methods investigated, the Heidelberger-Welch RHW, the Gelman-Rubin diagnostics, and Tally Entropy produced test metrics that correlated strongly to the size of the observed undersampling biases, indicating their potential to effectively predict the size and prevalence of undersampling biases in MC simulations.« less

Solar Particle Radiation Storms Forecasting and Analysis within the Framework of the `HESPERIA' HORIZON 2020 Project

NASA Astrophysics Data System (ADS)

Posner, A.; Malandraki, O.; Nunez, M.; Heber, B.; Labrenz, J.; Kühl, P.; Milas, N.; Tsiropoula, G.; Pavlos, E.

2017-12-01

Two prediction tools that have been developed in the framework of HESPERIA based upon the proven concepts UMASEP and REleASE. Near-relativistic (NR) electrons traveling faster than ions (30 MeV protons have 0.25c) are used to forecast the arrival of protons of Solar Energetic Particle (SEP) events with real-time measurements of NR electrons. The faster electrons arrive at L1 30 to 90 minutes before the slower protons. REleASE (Relativistic Electron Alert System for Exploration, Posner, 2007) uses this effect to predict the proton flux by utilizing actual electron fluxes and their most recent increases. Through HESPERIA, a clone of REleASE was built in open source programming language. The same forecasting principle was adapted to real-time data from ACE/EPAM. It is shown that HESPERIA REleASE forecasting works with any NR electron flux measurements. >500 MeV solar protons are so energetic that they usually have effects on the ground, producing Ground Level Enhancement (GLE) events. Within HESPERIA, a predictor of >500 SEP proton events near earth (geostationary orbit) has been developed. In order to predict these events, UMASEP (Núñez, 2011, 2015) has been used. UMASEP makes a lag-correlation of solar electromagnetic (EM) flux with the particle flux near earth. If the correlation is high, the model infers that there is a magnetic connection through which particles are arriving. If, additionally, the intensity of the flux of the associated solar event is also high, then UMASEP issues a SEP prediction. In the case of the prediction of >500 MeV SEP events, the implemented system, called HESPERIA UMASEP-500, correlates X-ray flux with differential proton fluxes by GOES, and with fluxes collected by neutron monitor stations around the world. When the correlation estimation and flare surpasses thresholds, a >500 MeV SEP forecast is issued. These findings suggest that a synthesis of the various approaches may improve over the status quo. Both forecasting tools are operational on the HESPERIA server maintained at the National Observatory of Athens (https://www.hesperia.astro.noa.gr/). This project received funding from the EU's Horizon 2020 research and innovation programme under grant No 637324.

On the physical air-sea fluxes for climate modeling

NASA Astrophysics Data System (ADS)

Bonekamp, J. G.

2001-02-01

At the sea surface, the atmosphere and the ocean exchange momentum, heat and freshwater. Mechanisms for the exchange are wind stress, turbulent mixing, radiation, evaporation and precipitation. These surface fluxes are characterized by a large spatial and temporal variability and play an important role in not only the mean atmospheric and oceanic circulation, but also in the generation and sustainment of coupled climate fluctuations such as the El Niño/La Niña phenomenon. Therefore, a good knowledge of air-sea fluxes is required for the understanding and prediction of climate changes. As part of long-term comprehensive atmospheric reanalyses with `Numerical Weather Prediction/Data assimilation' systems, data sets of global air-sea fluxes are generated. A good example is the 15-year atmospheric reanalysis of the European Centre for Medium--Range Weather Forecasts (ECMWF). Air-sea flux data sets from these reanalyses are very beneficial for climate research, because they combine a good spatial and temporal coverage with a homogeneous and consistent method of calculation. However, atmospheric reanalyses are still imperfect sources of flux information due to shortcomings in model variables, model parameterizations, assimilation methods, sampling of observations, and quality of observations. Therefore, assessments of the errors and the usefulness of air-sea flux data sets from atmospheric (re-)analyses are relevant contributions to the quantitative study of climate variability. Currently, much research is aimed at assessing the quality and usefulness of the reanalysed air-sea fluxes. Work in this thesis intends to contribute to this assessment. In particular, it attempts to answer three relevant questions. The first question is: What is the best parameterization of the momentum flux? A comparison is made of the wind stress parameterization of the ERA15 reanalysis, the currently generated ERA40 reanalysis and the wind stress measurements over the open ocean. The comparison reveals some clear differences in the mean drag coefficient. In addition, this study has indicated that progress has been made from the ERA15 to the ERA40 reanalyses by replacing the model parameterization with a constant Charnock parameter with one which depends on the sea state. The second research question is whether comparison of the response of an ocean model with ocean observations can be exploited to assess the quality of air-sea fluxes of the ERA15 reanalysis. To answer this question in a systematic way an inverse modeling approach is adopted using a four-dimensional variational data assimilation (4DVAR) scheme. Firstly, the functioning of the 4DVAR system is demonstrated from identical twin experiments. These experiments reveal that in the equatorial Pacific, a large reduction in wind-stress and upper-ocean temperature misfits can be achieved using an assimilation time window of eight weeks. It is concluded that the usefulness of inverse ocean modeling technique for global surface flux assessment is limited. The main merit of the developed ocean 4DVAR scheme will be to diagnose errors in the ocean analyses of the ocean model. The last research question is: are the ERA15 fluxes useful for the study of regional patterns of climate variability? The climate mode of consideration is the Antarctic Circumpolar Wave. This study stresses the importance to have the right climatological forcing conditions to assess time scales of climate variability and it confirms the usefulness of ERA15 air-sea fluxes as ocean model forcing fields to study climate variability on the interannual time scale.

Improved measurement of the reactor antineutrino flux and spectrum at Daya Bay

NASA Astrophysics Data System (ADS)

An, F. P.; Balantekin, A. B.; Band, H. R.; Bishai, M.; Blyth, S.; Cao, D.; Cao, G. F.; Cao, J.; Cen, W. R.; Chan, Y. L.; Chang, J. F.; Chang, L. C.; Chang, Y.; Chen, H. S.; Chen, Q. Y.; Chen, S. M.; Chen, Y. X.; Chen, Y.; Cheng, J.-H.; Cheng, J.; Cheng, Y. P.; Cheng, Z. K.; Cherwinka, J. J.; Chu, M. C.; Chukanov, A.; Cummings, J. P.; de Arcos, J.; Deng, Z. Y.; Ding, X. F.; Ding, Y. Y.; Diwan, M. V.; Dolgareva, M.; Dove, J.; Dwyer, D. A.; Edwards, W. R.; Gill, R.; Gonchar, M.; Gong, G. H.; Gong, H.; Grassi, M.; Gu, W. Q.; Guan, M. Y.; Guo, L.; Guo, R. P.; Guo, X. H.; Guo, Z.; Hackenburg, R. W.; Han, R.; Hans, S.; He, M.; Heeger, K. M.; Heng, Y. K.; Higuera, A.; Hor, Y. K.; Hsiung, Y. B.; Hu, B. Z.; Hu, T.; Hu, W.; Huang, E. C.; Huang, H. X.; Huang, X. T.; Huber, P.; Huo, W.; Hussain, G.; Jaffe, D. E.; Jaffke, P.; Jen, K. L.; Jetter, S.; Ji, X. P.; Ji, X. L.; Jiao, J. B.; Johnson, R. A.; Jones, D.; Joshi, J.; Kang, L.; Kettell, S. H.; Kohn, S.; Kramer, M.; Kwan, K. K.; Kwok, M. W.; Kwok, T.; Langford, T. J.; Lau, K.; Lebanowski, L.; Lee, J.; Lee, J. H. C.; Lei, R. T.; Leitner, R.; Li, C.; Li, D. J.; Li, F.; Li, G. S.; Li, Q. J.; Li, S.; Li, S. C.; Li, W. D.; Li, X. N.; Li, Y. F.; Li, Z. B.; Liang, H.; Lin, C. J.; Lin, G. L.; Lin, S.; Lin, S. K.; Lin, Y.-C.; Ling, J. J.; Link, J. M.; Littenberg, L.; Littlejohn, B. R.; Liu, D. W.; Liu, J. L.; Liu, J. C.; Loh, C. W.; Lu, C.; Lu, H. Q.; Lu, J. S.; Luk, K. B.; Lv, Z.; Ma, Q. M.; Ma, X. Y.; Ma, X. B.; Ma, Y. Q.; Malyshkin, Y.; Martinez Caicedo, D. A.; McDonald, K. T.; McKeown, R. D.; Mitchell, I.; Mooney, M.; Nakajima, Y.; Napolitano, J.; Naumov, D.; Naumova, E.; Ngai, H. Y.; Ning, Z.; Ochoa-Ricoux, J. P.; Olshevskiy, A.; Pan, H.-R.; Park, J.; Patton, S.; Pec, V.; Peng, J. C.; Pinsky, L.; Pun, C. S. J.; Qi, F. Z.; Qi, M.; Qian, X.; Raper, N.; Ren, J.; Rosero, R.; Roskovec, B.; Ruan, X. C.; Steiner, H.; Sun, G. X.; Sun, J. L.; Tang, W.; Taychenachev, D.; Treskov, K.; Tsang, K. V.; Tull, C. E.; Viaux, N.; Viren, B.; Vorobel, V.; Wang, C. H.; Wang, M.; Wang, N. Y.; Wang, R. G.; Wang, W.; Wang, X.; Wang, Y. F.; Wang, Z.; Wang, Z.; Wang, Z. M.; Wei, H. Y.; Wen, L. J.; Whisnant, K.; White, C. G.; Whitehead, L.; Wise, T.; Wong, H. L. H.; Wong, S. C. F.; Worcester, E.; Wu, C.-H.; Wu, Q.; Wu, W. J.; Xia, D. M.; Xia, J. K.; Xing, Z. Z.; Xu, J. Y.; Xu, J. L.; Xu, Y.; Xue, T.; Yang, C. G.; Yang, H.; Yang, L.; Yang, M. S.; Yang, M. T.; Ye, M.; Ye, Z.; Yeh, M.; Young, B. L.; Yu, Z. Y.; Zeng, S.; Zhan, L.; Zhang, C.; Zhang, H. H.; Zhang, J. W.; Zhang, Q. M.; Zhang, X. T.; Zhang, Y. M.; Zhang, Y. X.; Zhang, Y. M.; Zhang, Z. J.; Zhang, Z. Y.; Zhang, Z. P.; Zhao, J.; Zhao, Q. W.; Zhao, Y. B.; Zhong, W. L.; Zhou, L.; Zhou, N.; Zhuang, H. L.; Zou, J. H.; Daya Bay Collaboration

2017-01-01

A new measurement of the reactor antineutrino flux and energy spectrum by the Daya Bay reactor neutrino experiment is reported. The antineutrinos were generated by six 2.9 GWth nuclear reactors and detected by eight antineutrino detectors deployed in two near (560 m and 600 m flux-weighted baselines) and one far (1640 m flux-weighted baseline) underground experimental halls. With 621 days of data, more than 1.2 million inverse beta decay (IBD) candidates were detected. The IBD yield in the eight detectors was measured, and the ratio of measured to predicted flux was found to be 0.946±0.020 (0.992±0.021) for the Huber+Mueller (ILL+Vogel) model. A 2.9σ deviation was found in the measured IBD positron energy spectrum compared to the predictions. In particular, an excess of events in the region of 4-6 MeV was found in the measured spectrum, with a local significance of 4.4σ. A reactor antineutrino spectrum weighted by the IBD cross section is extracted for model-independent predictions. Supported in part by the Ministry of Science and Technology of China, the United States Department of Energy, the Chinese Academy of Sciences, the CAS Center for Excellence in Particle Physics, the National Natural Science Foundation of China, the Guangdong provincial government, the Shenzhen municipal government, the China General Nuclear Power Group, the Research Grants Council of the Hong Kong Special Administrative Region of China, the MOST and MOE in Taiwan, the U.S. National Science Foundation, the Ministry of Education, Youth and Sports of the Czech Republic, the Joint Institute of Nuclear Research in Dubna, Russia, the NSFC-RFBR joint research program, the National Commission for Scientific and Technological Research of Chile

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites: SURROGATE-BASED MCMC FOR CLM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

2016-07-04

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically-average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

DOE PAGES

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; ...

2016-06-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites

NASA Astrophysics Data System (ADS)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; Ren, Huiying; Liu, Ying; Swiler, Laura

2016-07-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesian model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.

Sedimentary Flux to Passive Margins From Inversion of Drainage Patterns: Examples from Africa

NASA Astrophysics Data System (ADS)

Lodhia, Bhavik Harish; Roberts, Gareth G.; Fraser, Alastair

2017-04-01

We show that inversion of more than 14000 rivers from the African continent provides information about Cenozoic uplift and sedimentary flux to its passive margins. We test predicted sedimentary flux using a dense two-dimensional seismic dataset offshore northwest Africa. First, six biostratigraphically dated horizons were mapped (seabed, 5.6 Ma, 23.8 Ma, 58.40 Ma, 89.4 Ma and basement) across the Mauritanian margin and used to construct isopachs. Check-shot data were used to convert time to depth and to determine best-fitting compaction parameters. Observed solid sedimentary fluxes are ˜2x103 km3 /Ma between 58.4 and 23.8 Ma, ˜4x103 km3 /Ma between 23.8 and 5.6 Ma, and ˜28x103 km3 /Ma between 5.6 and 0 Ma. Compaction errors were propagated into our history of sedimentary flux. Secondly, we inverted our drainage inventory to explore the relationship between uplift and erosion onshore and our measured flux. The stream power erosional model was calibrated using independent observations of marine terrace elevations and ages. We integrate incision rates along best-fitting theoretical river profiles to predict sedimentary flux at mouths of the rivers draining northwest Africa (e.g. Senegal). Calculated Neogene uplift and erosion is staged. Our predicted history of sedimentary flux increases in three stages towards the present-day, which agrees with the offshore measurements. Finally, using our inverse approach we systematically tested different erosional scenarios. We find that sedimentary flux to Africa's passive margins is controlled up the history of uplift and erosional processes play a moderating role. Predicted fluxes are indistinguishable if precipitation rate varies with a period less than ˜ 1 Ma or drainage area varies by less than 50%. To investigate the geodynamic setting of the Mauritanian margin we backstripped eight commercial wells that penetrate Neogene stratigraphy. Wells in the central part of the Mauritania basin include 500-800 m of Neogene water-loaded subsidence that cannot be attributed to extension, thermal subsidence, salt-tectonics or glacio-eustasy. Stratigraphy mapped across the margin shows that this anomalous subsidence affected an area larger than 500 by 500 km. We suggest that this anomalous subsidence was caused by Neogene dynamic drawdown. Conversion of the Schaeffer & Lebedev (2013) velocity model to temperature and simple isostatic calculations indicate that negative buoyancy anomalies directly beneath the Mauritanian margin generate up to 500 m of drawdown today. Measured ocean-age depth residuals and calculated subsidence histories suggest that dynamic uplift of the Cape Verde swell and dynamic drawdown in the east generated a gradient in dynamic support during the last 25 Ma.

Monitoring Cosmic Radiation Risk: Comparisons between Observations and Predictive Codes for Naval Aviation

DTIC Science & Technology

2009-01-01

proton PARMA PHITS -based Analytical Radiation Model in the Atmosphere PCAIRE Predictive Code for Aircrew Radiation Exposure PHITS Particle and...radiation transport code utilized is called PARMA ( PHITS based Analytical Radiation Model in the Atmosphere) [36]. The particle fluxes calculated from the...same dose equivalent coefficient regulations from the ICRP-60 regulations. As a result, the transport codes utilized by EXPACS ( PHITS ) and CARI-6

Monitoring Cosmic Radiation Risk: Comparisons Between Observations and Predictive Codes for Naval Aviation

DTIC Science & Technology

2009-07-05

proton PARMA PHITS -based Analytical Radiation Model in the Atmosphere PCAIRE Predictive Code for Aircrew Radiation Exposure PHITS Particle and Heavy...transport code utilized is called PARMA ( PHITS based Analytical Radiation Model in the Atmosphere) [36]. The particle fluxes calculated from the input...dose equivalent coefficient regulations from the ICRP-60 regulations. As a result, the transport codes utilized by EXPACS ( PHITS ) and CARI-6 (PARMA

Measurement of Coherent π^{+} Production in Low Energy Neutrino-Carbon Scattering.

PubMed

Abe, K; Andreopoulos, C; Antonova, M; Aoki, S; Ariga, A; Assylbekov, S; Autiero, D; Ban, S; Barbi, M; Barker, G J; Barr, G; Bartet-Friburg, P; Batkiewicz, M; Bay, F; Berardi, V; Berkman, S; Bhadra, S; Blondel, A; Bolognesi, S; Bordoni, S; Boyd, S B; Brailsford, D; Bravar, A; Bronner, C; Buizza Avanzini, M; Calland, R G; Campbell, T; Cao, S; Caravaca Rodríguez, J; Cartwright, S L; Castillo, R; Catanesi, M G; Cervera, A; Cherdack, D; Chikuma, N; Christodoulou, G; Clifton, A; Coleman, J; Collazuol, G; Coplowe, D; Cremonesi, L; Dabrowska, A; De Rosa, G; Dealtry, T; Denner, P F; Dennis, S R; Densham, C; Dewhurst, D; Di Lodovico, F; Di Luise, S; Dolan, S; Drapier, O; Duffy, K E; Dumarchez, J; Dytman, S; Dziewiecki, M; Emery-Schrenk, S; Ereditato, A; Feusels, T; Finch, A J; Fiorentini, G A; Friend, M; Fujii, Y; Fukuda, D; Fukuda, Y; Furmanski, A P; Galymov, V; Garcia, A; Giffin, S G; Giganti, C; Gizzarelli, F; Gonin, M; Grant, N; Hadley, D R; Haegel, L; Haigh, M D; Hamilton, P; Hansen, D; Harada, J; Hara, T; Hartz, M; Hasegawa, T; Hastings, N C; Hayashino, T; Hayato, Y; Helmer, R L; Hierholzer, M; Hillairet, A; Himmel, A; Hiraki, T; Hirota, S; Hogan, M; Holeczek, J; Horikawa, S; Hosomi, F; Huang, K; Ichikawa, A K; Ieki, K; Ikeda, M; Imber, J; Insler, J; Intonti, R A; Irvine, T J; Ishida, T; Ishii, T; Iwai, E; Iwamoto, K; Izmaylov, A; Jacob, A; Jamieson, B; Jiang, M; Johnson, S; Jo, J H; Jonsson, P; Jung, C K; Kabirnezhad, M; Kaboth, A C; Kajita, T; Kakuno, H; Kameda, J; Karlen, D; Karpikov, I; Katori, T; Kearns, E; Khabibullin, M; Khotjantsev, A; Kielczewska, D; Kikawa, T; Kim, H; Kim, J; King, S; Kisiel, J; Knight, A; Knox, A; Kobayashi, T; Koch, L; Koga, T; Konaka, A; Kondo, K; Kopylov, A; Kormos, L L; Korzenev, A; Koshio, Y; Kropp, W; Kudenko, Y; Kurjata, R; Kutter, T; Lagoda, J; Lamont, I; Larkin, E; Lasorak, P; Laveder, M; Lawe, M; Lazos, M; Lindner, T; Liptak, Z J; Litchfield, R P; Li, X; Longhin, A; Lopez, J P; Ludovici, L; Lu, X; Magaletti, L; Mahn, K; Malek, M; Manly, S; Marino, A D; Marteau, J; Martin, J F; Martins, P; Martynenko, S; Maruyama, T; Matveev, V; Mavrokoridis, K; Ma, W Y; Mazzucato, E; McCarthy, M; McCauley, N; McFarland, K S; McGrew, C; Mefodiev, A; Metelko, C; Mezzetto, M; Mijakowski, P; Minamino, A; Mineev, O; Mine, S; Missert, A; Miura, M; Moriyama, S; Mueller, Th A; Murphy, S; Myslik, J; Nakadaira, T; Nakahata, M; Nakamura, K G; Nakamura, K; Nakamura, K D; Nakayama, S; Nakaya, T; Nakayoshi, K; Nantais, C; Nielsen, C; Nirkko, M; Nishikawa, K; Nishimura, Y; Novella, P; Nowak, J; O'Keeffe, H M; Ohta, R; Okumura, K; Okusawa, T; Oryszczak, W; Oser, S M; Ovsyannikova, T; Owen, R A; Oyama, Y; Palladino, V; Palomino, J L; Paolone, V; Patel, N D; Pavin, M; Payne, D; Perkin, J D; Petrov, Y; Pickard, L; Pickering, L; Pinzon Guerra, E S; Pistillo, C; Popov, B; Posiadala-Zezula, M; Poutissou, J-M; Poutissou, R; Przewlocki, P; Quilain, B; Radermacher, T; Radicioni, E; Ratoff, P N; Ravonel, M; Rayner, M A M; Redij, A; Reinherz-Aronis, E; Riccio, C; Rojas, P; Rondio, E; Roth, S; Rubbia, A; Rychter, A; Sacco, R; Sakashita, K; Sánchez, F; Sato, F; Scantamburlo, E; Scholberg, K; Schoppmann, S; Schwehr, J; Scott, M; Seiya, Y; Sekiguchi, T; Sekiya, H; Sgalaberna, D; Shah, R; Shaikhiev, A; Shaker, F; Shaw, D; Shiozawa, M; Shirahige, T; Short, S; Smy, M; Sobczyk, J T; Sobel, H; Sorel, M; Southwell, L; Stamoulis, P; Steinmann, J; Stewart, T; Stowell, P; Suda, Y; Suvorov, S; Suzuki, A; Suzuki, K; Suzuki, S Y; Suzuki, Y; Tacik, R; Tada, M; Takahashi, S; Takeda, A; Takeuchi, Y; Tanaka, H K; Tanaka, H A; Terhorst, D; Terri, R; Thakore, T; Thompson, L F; Tobayama, S; Toki, W; Tomura, T; Touramanis, C; Tsukamoto, T; Tzanov, M; Uchida, Y; Vacheret, A; Vagins, M; Vallari, Z; Vasseur, G; Wachala, T; Wakamatsu, K; Walter, C W; Wark, D; Warzycha, W; Wascko, M O; Weber, A; Wendell, R; Wilkes, R J; Wilking, M J; Wilkinson, C; Wilson, J R; Wilson, R J; Yamada, Y; Yamamoto, K; Yamamoto, M; Yanagisawa, C; Yano, T; Yen, S; Yershov, N; Yokoyama, M; Yoo, J; Yoshida, K; Yuan, T; Yu, M; Zalewska, A; Zalipska, J; Zambelli, L; Zaremba, K; Ziembicki, M; Zimmerman, E D; Zito, M; Żmuda, J

2016-11-04

We report the first measurement of the flux-averaged cross section for charged current coherent π^{+} production on carbon for neutrino energies less than 1.5 GeV, and with a restriction on the final state phase space volume in the T2K near detector, ND280. Comparisons are made with predictions from the Rein-Sehgal coherent production model and the model by Alvarez-Ruso et al., the latter representing the first implementation of an instance of the new class of microscopic coherent models in a neutrino interaction Monte Carlo event generator. We observe a clear event excess above background, disagreeing with the null results reported by K2K and SciBooNE in a similar neutrino energy region. The measured flux-averaged cross sections are below those predicted by both the Rein-Sehgal and Alvarez-Ruso et al.

A proof for loop-law constraints in stoichiometric metabolic networks

PubMed Central

2012-01-01

Background Constraint-based modeling is increasingly employed for metabolic network analysis. Its underlying assumption is that natural metabolic phenotypes can be predicted by adding physicochemical constraints to remove unrealistic metabolic flux solutions. The loopless-COBRA approach provides an additional constraint that eliminates thermodynamically infeasible internal cycles (or loops) from the space of solutions. This allows the prediction of flux solutions that are more consistent with experimental data. However, it is not clear if this approach over-constrains the models by removing non-loop solutions as well. Results Here we apply Gordan’s theorem from linear algebra to prove for the first time that the constraints added in loopless-COBRA do not over-constrain the problem beyond the elimination of the loops themselves. Conclusions The loopless-COBRA constraints can be reliably applied. Furthermore, this proof may be adapted to evaluate the theoretical soundness for other methods in constraint-based modeling. PMID:23146116

Magnetoconductance oscillations at a nanoparticle film-superconductor interface: a means for probing flux penetration depth.

PubMed

Dunford, Jeffrey L; Dhirani, Al-Amin

2008-11-12

Interfaces between disordered normal materials and superconductors (S) can exhibit 'reflectionless tunnelling' (RT)-a phenomenon that arises from repeated disorder-driven elastic scattering, multiple Andreev reflections, and electron/hole interference. RT has been used to explain zero-bias conductance peaks (ZBCPs) observed using doped semiconductors and evaporated granular metal films as the disordered normal materials. Recently, in addition to ZBCPs, magnetoconductance oscillations predicted by RT theory have been observed using a novel normal disordered material: self-assembled nanoparticle films. In the present study, we find that the period of these oscillations decreases as temperature (T) increases. This suggests that the magnetic flux associated with interfering pathways increases accordingly. We propose that the increasing flux can be attributed to magnetic field penetration into S as [Formula: see text]. This model agrees remarkably well with known T dependence of penetration depth predicted by Bardeen-Cooper-Schrieffer theory. Our study shows that this additional region of flux is significant and must be considered in experimental and theoretical studies of RT.

Modeling Gas and Gas Hydrate Accumulation in Marine Sediments Using a K-Nearest Neighbor Machine-Learning Technique

NASA Astrophysics Data System (ADS)

Wood, W. T.; Runyan, T. E.; Palmsten, M.; Dale, J.; Crawford, C.

2016-12-01

Natural Gas (primarily methane) and gas hydrate accumulations require certain bio-geochemical, as well as physical conditions, some of which are poorly sampled and/or poorly understood. We exploit recent advances in the prediction of seafloor porosity and heat flux via machine learning techniques (e.g. Random forests and Bayesian networks) to predict the occurrence of gas and subsequently gas hydrate in marine sediments. The prediction (actually guided interpolation) of key parameters we use in this study is a K-nearest neighbor technique. KNN requires only minimal pre-processing of the data and predictors, and requires minimal run-time input so the results are almost entirely data-driven. Specifically we use new estimates of sedimentation rate and sediment type, along with recently derived compaction modeling to estimate profiles of porosity and age. We combined the compaction with seafloor heat flux to estimate temperature with depth and geologic age, which, with estimates of organic carbon, and models of methanogenesis yield limits on the production of methane. Results include geospatial predictions of gas (and gas hydrate) accumulations, with quantitative estimates of uncertainty. The Generic Earth Modeling System (GEMS) we have developed to derive the machine learning estimates is modular and easily updated with new algorithms or data.

Effect of Particle Size Distribution on Wall Heat Flux in Pulverized-Coal Furnaces and Boilers

NASA Astrophysics Data System (ADS)

Lu, Jun

A mathematical model of combustion and heat transfer within a cylindrical enclosure firing pulverized coal has been developed and tested against two sets of measured data (one is 1993 WSU/DECO Pilot test data, the other one is the International Flame Research Foundation 1964 Test (Beer, 1964)) and one independent code FURN3D from the Argonne National Laboratory (Ahluwalia and IM, 1992). The model called PILC assumes that the system is a sequence of many well-stirred reactors. A char burnout model combining diffusion to the particle surface, pore diffusion, and surface reaction is employed for predicting the char reaction, heat release, and evolution of char. The ash formation model included relates the ash particle size distribution to the particle size distribution of pulverized coal. The optical constants of char and ash particles are calculated from dispersion relations derived from reflectivity, transmissivity and extinction measurements. The Mie theory is applied to determine the extinction and scattering coefficients. The radiation heat transfer is modeled using the virtual zone method, which leads to a set of simultaneous nonlinear algebraic equations for the temperature field within the furnace and on its walls. This enables the heat fluxes to be evaluated. In comparisons with the experimental data and one independent code, the model is successful in predicting gas temperature, wall temperature, and wall radiative flux. When the coal with greater fineness is burnt, the particle size of pulverized coal has a consistent influence on combustion performance: the temperature peak was higher and nearer to burner, the radiation flux to combustor wall increased, and also the absorption and scattering coefficients of the combustion products increased. The effect of coal particle size distribution on absorption and scattering coefficients and wall heat flux is significant. But there is only a small effect on gas temperature and fuel fraction burned; it is speculated that this may be a characteristic special to the test combustor used.

Design of a transportable high efficiency fast neutron spectrometer

DOE PAGES

Roecker, C.; Bernstein, A.; Bowden, N. S.; ...

2016-04-12

A transportable fast neutron detection system has been designed and constructed for measuring neutron energy spectra and flux ranging from tens to hundreds of MeV. The transportability of the spectrometer reduces the detector-related systematic bias between different neutron spectra and flux measurements, which allows for the comparison of measurements above or below ground. The spectrometer will measure neutron fluxes that are of prohibitively low intensity compared to the site-specific background rates targeted by other transportable fast neutron detection systems. To measure low intensity high-energy neutron fluxes, a conventional capture-gating technique is used for measuring neutron energies above 20 MeV andmore » a novel multiplicity technique is used for measuring neutron energies above 100 MeV. The spectrometer is composed of two Gd containing plastic scintillator detectors arranged around a lead spallation target. To calibrate and characterize the position dependent response of the spectrometer, a Monte Carlo model was developed and used in conjunction with experimental data from gamma ray sources. Multiplicity event identification algorithms were developed and used with a Cf-252 neutron multiplicity source to validate the Monte Carlo model Gd concentration and secondary neutron capture efficiency. The validated Monte Carlo model was used to predict an effective area for the multiplicity and capture gating analyses. For incident neutron energies between 100 MeV and 1000 MeV with an isotropic angular distribution, the multiplicity analysis predicted an effective area of 500 cm 2 rising to 5000 cm 2. For neutron energies above 20 MeV, the capture-gating analysis predicted an effective area between 1800 cm 2 and 2500 cm 2. As a result, the multiplicity mode was found to be sensitive to the incident neutron angular distribution.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roecker, C.; Bernstein, A.; Bowden, N. S.

A transportable fast neutron detection system has been designed and constructed for measuring neutron energy spectra and flux ranging from tens to hundreds of MeV. The transportability of the spectrometer reduces the detector-related systematic bias between different neutron spectra and flux measurements, which allows for the comparison of measurements above or below ground. The spectrometer will measure neutron fluxes that are of prohibitively low intensity compared to the site-specific background rates targeted by other transportable fast neutron detection systems. To measure low intensity high-energy neutron fluxes, a conventional capture-gating technique is used for measuring neutron energies above 20 MeV andmore » a novel multiplicity technique is used for measuring neutron energies above 100 MeV. The spectrometer is composed of two Gd containing plastic scintillator detectors arranged around a lead spallation target. To calibrate and characterize the position dependent response of the spectrometer, a Monte Carlo model was developed and used in conjunction with experimental data from gamma ray sources. Multiplicity event identification algorithms were developed and used with a Cf-252 neutron multiplicity source to validate the Monte Carlo model Gd concentration and secondary neutron capture efficiency. The validated Monte Carlo model was used to predict an effective area for the multiplicity and capture gating analyses. For incident neutron energies between 100 MeV and 1000 MeV with an isotropic angular distribution, the multiplicity analysis predicted an effective area of 500 cm 2 rising to 5000 cm 2. For neutron energies above 20 MeV, the capture-gating analysis predicted an effective area between 1800 cm 2 and 2500 cm 2. As a result, the multiplicity mode was found to be sensitive to the incident neutron angular distribution.« less

Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling

DOE PAGES

Miller, Scot M.; Commane, Roisin; Melton, Joe R.; ...

2016-03-02

Existing estimates of methane (CH 4) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH 4 observations from the US and Canada to analyze seven different bottom-up, wetland CH 4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH 4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use realmore » data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. Lastly, these models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.« less

Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling

NASA Astrophysics Data System (ADS)

Miller, Scot M.; Commane, Roisin; Melton, Joe R.; Andrews, Arlyn E.; Benmergui, Joshua; Dlugokencky, Edward J.; Janssens-Maenhout, Greet; Michalak, Anna M.; Sweeney, Colm; Worthy, Doug E. J.

2016-03-01

Existing estimates of methane (CH4) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH4 observations from the US and Canada to analyze seven different bottom-up, wetland CH4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use real data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. These models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.

Statistical mechanics of shell models for two-dimensional turbulence

NASA Astrophysics Data System (ADS)

Aurell, E.; Boffetta, G.; Crisanti, A.; Frick, P.; Paladin, G.; Vulpiani, A.

1994-12-01

We study shell models that conserve the analogs of energy and enstrophy and hence are designed to mimic fluid turbulence in two-dimensions (2D). The main result is that the observed state is well described as a formal statistical equilibrium, closely analogous to the approach to two-dimensional ideal hydrodynamics of Onsager [Nuovo Cimento Suppl. 6, 279 (1949)], Hopf [J. Rat. Mech. Anal. 1, 87 (1952)], and Lee [Q. Appl. Math. 10, 69 (1952)]. In the presence of forcing and dissipation we observe a forward flux of enstrophy and a backward flux of energy. These fluxes can be understood as mean diffusive drifts from a source to two sinks in a system which is close to local equilibrium with Lagrange multipliers (``shell temperatures'') changing slowly with scale. This is clear evidence that the simplest shell models are not adequate to reproduce the main features of two-dimensional turbulence. The dimensional predictions on the power spectra from a supposed forward cascade of enstrophy and from one branch of the formal statistical equilibrium coincide in these shell models in contrast to the corresponding predictions for the Navier-Stokes and Euler equations in 2D. This coincidence has previously led to the mistaken conclusion that shell models exhibit a forward cascade of enstrophy. We also study the dynamical properties of the models and the growth of perturbations.

Changing ecophysiological processes and carbon budget in East Asian ecosystems under near-future changes in climate: implications for long-term monitoring from a process-based model.

PubMed

Ito, Akihiko

2010-07-01

Using a process-based model, I assessed how ecophysiological processes would respond to near-future global changes predicted by coupled atmosphere-ocean climate models. An ecosystem model, Vegetation Integrative SImulator for Trace gases (VISIT), was applied to four sites in East Asia (different types of forest in Takayama, Tomakomai, and Fujiyoshida, Japan, and an Alpine grassland in Qinghai, China) where observational flux data are available for model calibration. The climate models predicted +1-3 degrees C warming and slight change in annual precipitation by 2050 as a result of an increase in atmospheric CO2. Gross primary production (GPP) was estimated to increase substantially at each site because of improved efficiency in the use of water and radiation. Although increased respiration partly offset the GPP increase, the simulation showed that these ecosystems would act as net carbon sinks independent of disturbance-induced uptake for recovery. However, the carbon budget response relied strongly on nitrogen availability, such that photosynthetic down-regulation resulting from leaf nitrogen dilution largely decreased GPP. In relation to long-term monitoring, these results indicate that the impacts of global warming may be more evident in gross fluxes (e.g., photosynthesis and respiration) than in the net CO2 budget, because changes in these fluxes offset each other.

A Physically Based Analytical Model to Describe Effective Excess Charge for Streaming Potential Generation in Water Saturated Porous Media

NASA Astrophysics Data System (ADS)

Guarracino, L.; Jougnot, D.

2018-01-01

Among the different contributions generating self-potential, the streaming potential is of particular interest in hydrogeology for its sensitivity to water flow. Estimating water flux in porous media using streaming potential data relies on our capacity to understand, model, and upscale the electrokinetic coupling at the mineral-solution interface. Different approaches have been proposed to predict streaming potential generation in porous media. One of these approaches is the flux averaging which is based on determining the excess charge which is effectively dragged in the medium by water flow. In this study, we develop a physically based analytical model to predict the effective excess charge in saturated porous media using a flux-averaging approach in a bundle of capillary tubes with a fractal pore size distribution. The proposed model allows the determination of the effective excess charge as a function of pore water ionic concentration and hydrogeological parameters like porosity, permeability, and tortuosity. The new model has been successfully tested against different set of experimental data from the literature. One of the main findings of this study is the mechanistic explanation to the empirical dependence between the effective excess charge and the permeability that has been found by several researchers. The proposed model also highlights the link to other lithological properties, and it is able to reproduce the evolution of effective excess charge with electrolyte concentrations.

Cluster electric current density measurements within a magnetic flux rope in the plasma sheet

NASA Technical Reports Server (NTRS)

Slavin, J. A.; Lepping, R. P.; Gjerloev, J.; Goldstein, M. L.; Fairfield, D. H.; Acuna, M. H.; Balogh, A.; Dunlop, M.; Kivelson, M. G.; Khurana, K.

2003-01-01

On August 22, 2001 all 4 Cluster spacecraft nearly simultaneously penetrated a magnetic flux rope in the tail. The flux rope encounter took place in the central plasma sheet, Beta(sub i) approx. 1-2, near the leading edge of a bursty bulk flow. The "time-of-flight" of the flux rope across the 4 spacecraft yielded V(sub x) approx. 700 km/s and a diameter of approx.1 R(sub e). The speed at which the flux rope moved over the spacecraft is in close agreement with the Cluster plasma measurements. The magnetic field profiles measured at each spacecraft were first modeled separately using the Lepping-Burlaga force-free flux rope model. The results indicated that the center of the flux rope passed northward (above) s/c 3, but southward (below) of s/c 1, 2 and 4. The peak electric currents along the central axis of the flux rope predicted by these single-s/c models were approx.15-19 nA/sq m. The 4-spacecraft Cluster magnetic field measurements provide a second means to determine the electric current density without any assumption regarding flux rope structure. The current profile determined using the curlometer technique was qualitatively similar to those determined by modeling the individual spacecraft magnetic field observations and yielded a peak current density of 17 nA/m2 near the central axis of the rope. However, the curlometer results also showed that the flux rope was not force-free with the component of the current density perpendicular to the magnetic field exceeding the parallel component over the forward half of the rope, perhaps due to the pressure gradients generated by the collision of the BBF with the inner magnetosphere. Hence, while the single-spacecraft models are very successful in fitting flux rope magnetic field and current variations, they do not provide a stringent test of the force-free condition.

Ecosystem-scale volatile organic compound fluxes during an extreme drought in a broadleaf temperate forest of the Missouri Ozarks (central USA)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seco, Roger; Karl, Thomas; Guenther, Alex

Considerable amounts and varieties of biogenic volatile organic compounds (BVOCs) are exchanged between vegetation and the surrounding air. These BVOCs play key ecological and atmospheric roles that must be adequately represented for accurately modeling the coupled biosphere–atmosphere–climate earth system. One key uncertainty in existing models is the response of BVOC fluxes to an important global change process: drought. Here, we describe the diurnal and seasonal variation in isoprene, monoterpene, and methanol fluxes from a temperate forest ecosystem before, during, and after an extreme 2012 drought event in the Ozark region of the central USA. BVOC fluxes were dominated by isoprene,more » which attained high emission rates of up to 35.4 mg m 2 h 1 at midday. Methanol fluxes were characterized by net deposition in the morning, changing to a net emission flux through the rest of the daylight hours. Net flux of CO 2 reached its seasonal maximum approximately a month earlier than isoprenoid fluxes, which highlights the differential response of photosynthesis and isoprenoid emissions to progressing drought conditions. Nevertheless, both processes were strongly suppressed under extreme drought, although isoprene fluxes remained relatively high compared to reported fluxes from other ecosystems. Methanol exchange was less affected by drought throughout the season, confirming the complex processes driving biogenic methanol fluxes. The fraction of daytime (7–17 h) assimilated carbon released back to the atmosphere combining the three BVOCs measured was 2% of gross primary productivity (GPP) and 4.9% of net ecosystem exchange (NEE) on average for our whole measurement campaign, while exceeding 5% of GPP and 10% of NEE just before the strongest drought phase. In conclusion, the MEGANv2.1 model correctly predicted diurnal variations in fluxes driven mainly by light and temperature, although further research is needed to address model BVOC fluxes during drought events.« less

Ecosystem-scale volatile organic compound fluxes during an extreme drought in a broadleaf temperate forest of the Missouri Ozarks (central USA).

PubMed

Seco, Roger; Karl, Thomas; Guenther, Alex; Hosman, Kevin P; Pallardy, Stephen G; Gu, Lianhong; Geron, Chris; Harley, Peter; Kim, Saewung

2015-10-01

Considerable amounts and varieties of biogenic volatile organic compounds (BVOCs) are exchanged between vegetation and the surrounding air. These BVOCs play key ecological and atmospheric roles that must be adequately represented for accurately modeling the coupled biosphere-atmosphere-climate earth system. One key uncertainty in existing models is the response of BVOC fluxes to an important global change process: drought. We describe the diurnal and seasonal variation in isoprene, monoterpene, and methanol fluxes from a temperate forest ecosystem before, during, and after an extreme 2012 drought event in the Ozark region of the central USA. BVOC fluxes were dominated by isoprene, which attained high emission rates of up to 35.4 mg m(-2)  h(-1) at midday. Methanol fluxes were characterized by net deposition in the morning, changing to a net emission flux through the rest of the daylight hours. Net flux of CO2 reached its seasonal maximum approximately a month earlier than isoprenoid fluxes, which highlights the differential response of photosynthesis and isoprenoid emissions to progressing drought conditions. Nevertheless, both processes were strongly suppressed under extreme drought, although isoprene fluxes remained relatively high compared to reported fluxes from other ecosystems. Methanol exchange was less affected by drought throughout the season, confirming the complex processes driving biogenic methanol fluxes. The fraction of daytime (7-17 h) assimilated carbon released back to the atmosphere combining the three BVOCs measured was 2% of gross primary productivity (GPP) and 4.9% of net ecosystem exchange (NEE) on average for our whole measurement campaign, while exceeding 5% of GPP and 10% of NEE just before the strongest drought phase. The meganv2.1 model correctly predicted diurnal variations in fluxes driven mainly by light and temperature, although further research is needed to address model BVOC fluxes during drought events. © 2015 John Wiley & Sons Ltd.

Ecosystem-scale volatile organic compound fluxes during an extreme drought in a broadleaf temperate forest of the Missouri Ozarks (central USA)

DOE PAGES

Seco, Roger; Karl, Thomas; Guenther, Alex; ...

2015-07-07

Considerable amounts and varieties of biogenic volatile organic compounds (BVOCs) are exchanged between vegetation and the surrounding air. These BVOCs play key ecological and atmospheric roles that must be adequately represented for accurately modeling the coupled biosphere–atmosphere–climate earth system. One key uncertainty in existing models is the response of BVOC fluxes to an important global change process: drought. Here, we describe the diurnal and seasonal variation in isoprene, monoterpene, and methanol fluxes from a temperate forest ecosystem before, during, and after an extreme 2012 drought event in the Ozark region of the central USA. BVOC fluxes were dominated by isoprene,more » which attained high emission rates of up to 35.4 mg m 2 h 1 at midday. Methanol fluxes were characterized by net deposition in the morning, changing to a net emission flux through the rest of the daylight hours. Net flux of CO 2 reached its seasonal maximum approximately a month earlier than isoprenoid fluxes, which highlights the differential response of photosynthesis and isoprenoid emissions to progressing drought conditions. Nevertheless, both processes were strongly suppressed under extreme drought, although isoprene fluxes remained relatively high compared to reported fluxes from other ecosystems. Methanol exchange was less affected by drought throughout the season, confirming the complex processes driving biogenic methanol fluxes. The fraction of daytime (7–17 h) assimilated carbon released back to the atmosphere combining the three BVOCs measured was 2% of gross primary productivity (GPP) and 4.9% of net ecosystem exchange (NEE) on average for our whole measurement campaign, while exceeding 5% of GPP and 10% of NEE just before the strongest drought phase. In conclusion, the MEGANv2.1 model correctly predicted diurnal variations in fluxes driven mainly by light and temperature, although further research is needed to address model BVOC fluxes during drought events.« less

Using SDO/AIA to Understand the Thermal Evolution of Solar Prominence Formation

NASA Astrophysics Data System (ADS)

Viall, Nicholeen; M.; Kucera, Therese T.; Karpen, Judith

2016-10-01

In this study, we investigate prominence formation using time series analysis of Solar Dynamics Observatory's Atmospheric Imaging Assembly (SDO/AIA) data. We investigate the thermal properties of forming prominences by analyzing observed light curves using the same technique that we have already successfully applied to active regions to diagnose heating and cooling cycles. This technique tracks the thermal evolution using emission formed at different temperatures, made possible by AIA's different wavebands and high time resolution. We also compute the predicted light curves in the same SDO/AIA channels of a hydrodynamic model of thermal nonequilibrium formation of prominence material, an evaporation-condensation model. In these models of prominence formation, heating at the foot-points of sheared coronal flux-tubes results in evaporation of material of a few MK into the corona followed by catastrophic cooling of the hot material to form cool ( 10,000 K) prominence material. We demonstrate that the SDO/AIA light curves for flux tubes undergoing thermal nonequilibrium vary at different locations along the flux tube, especially in the region where the condensate forms, and we compare the predicted light curves with those observed. Supported by NASA's Living with a Star program.

N2 triplet band systems and atomic oxygen in the dayglow

NASA Astrophysics Data System (ADS)

Broadfoot, A. L.; Hatfield, D. B.; Anderson, E. R.; Stone, T. C.; Sandel, B. R.; Gardner, J. A.; Murad, E.; Knecht, D. J.; Pike, C. P.; Viereck, R. A.

1997-06-01

New spectrographic observations of the Earth's dayglow have been acquired by the Arizona Airglow Experiment (GLO) flown on the space shuttle. GLO is an imaging spectrograph that records simultaneous vertical profiles of prominent Earth limb emissions occurring at wavelengths between 115 and 900 nm. This study addresses the measured emissions from the N2 triplet states (first positive, second positive, and Vegard-Kaplan band systems) and their excitation by the local photoelectron flux. The triplet state population distributions modeled for aurora by Cartwright [1978] are modified for dayglow conditions by changing to a photoelectron-flux energy distribution and including resonance scattering by the first positive system. Modeled and observed intensities are in excellent agreement, in contrast to the well-studied auroral case. This work concentrates on dayglow conditions at 200 km altitude near the subsolar point. Parameters to infer the local photoelectron flux from the emission band intensities are provided. Several atomic oxygen dayglow emission features were analyzed to complement the N2 analysis. The photoelectron-excited O I(135.6, 777.4 nm) lines were found to be 3 to 4 times weaker than predicted while the O I(630.0, 844.6 nm) lines were in close agreement with the model prediction.