Comparison of Predicted and Measured Turbine Vane Rough Surface Heat Transfer

NASA Technical Reports Server (NTRS)

Boyle, R. J.; Spuckler, C. M.; Lucci, B. L.

2000-01-01

The proposed paper compares predicted turbine vane heat transfer for a rough surface over a wide range of test conditions with experimental data. Predictions were made for the entire vane surface. However, measurements were made only over the suction surface of the vane, and the leading edge region of the pressure surface. Comparisons are shown for a wide range of test conditions. Inlet pressures varied between 3 and 15 psia, and exit Mach numbers ranged between 0.3 and 0.9. Thus, while a single roughened vane was used for the tests, the effective rougness,(k(sup +)), varied by more than a factor of ten. Results were obtained for freestream turbulence levels of 1 and 10%. Heat transfer predictions were obtained using the Navier-Stokes computer code RVCQ3D. Two turbulence models, suitable for rough surface analysis, are incorporated in this code. The Cebeci-Chang roughness model is part of the algebraic turbulence model. The k-omega turbulence model accounts for the effect of roughness in the application of the boundary condition. Roughness causes turbulent flow over the vane surface. Even after accounting for transition, surface roughness significantly increased heat transfer compared to a smooth surface. The k-omega results agreed better with the data than the Cebeci-Chang model. However, the low Reynolds number k-omega model did not accurately account for roughness when the freestream turbulence level was low. The high Reynolds number version of this model was more suitable when the freestream turbulence was low.

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.

Principal component analysis in construction of 3D human knee joint models using a statistical shape model method.

PubMed

Tsai, Tsung-Yuan; Li, Jing-Sheng; Wang, Shaobai; Li, Pingyue; Kwon, Young-Min; Li, Guoan

2015-01-01

The statistical shape model (SSM) method that uses 2D images of the knee joint to predict the three-dimensional (3D) joint surface model has been reported in the literature. In this study, we constructed a SSM database using 152 human computed tomography (CT) knee joint models, including the femur, tibia and patella and analysed the characteristics of each principal component of the SSM. The surface models of two in vivo knees were predicted using the SSM and their 2D bi-plane fluoroscopic images. The predicted models were compared to their CT joint models. The differences between the predicted 3D knee joint surfaces and the CT image-based surfaces were 0.30 ± 0.81 mm, 0.34 ± 0.79 mm and 0.36 ± 0.59 mm for the femur, tibia and patella, respectively (average ± standard deviation). The computational time for each bone of the knee joint was within 30 s using a personal computer. The analysis of this study indicated that the SSM method could be a useful tool to construct 3D surface models of the knee with sub-millimeter accuracy in real time. Thus, it may have a broad application in computer-assisted knee surgeries that require 3D surface models of the knee.

Predictive model for ice formation on superhydrophobic surfaces.

PubMed

Bahadur, Vaibhav; Mishchenko, Lidiya; Hatton, Benjamin; Taylor, J Ashley; Aizenberg, Joanna; Krupenkin, Tom

2011-12-06

The prevention and control of ice accumulation has important applications in aviation, building construction, and energy conversion devices. One area of active research concerns the use of superhydrophobic surfaces for preventing ice formation. The present work develops a physics-based modeling framework to predict ice formation on cooled superhydrophobic surfaces resulting from the impact of supercooled water droplets. This modeling approach analyzes the multiple phenomena influencing ice formation on superhydrophobic surfaces through the development of submodels describing droplet impact dynamics, heat transfer, and heterogeneous ice nucleation. These models are then integrated together to achieve a comprehensive understanding of ice formation upon impact of liquid droplets at freezing conditions. The accuracy of this model is validated by its successful prediction of the experimental findings that demonstrate that superhydrophobic surfaces can fully prevent the freezing of impacting water droplets down to surface temperatures of as low as -20 to -25 °C. The model can be used to study the influence of surface morphology, surface chemistry, and fluid and thermal properties on dynamic ice formation and identify parameters critical to achieving icephobic surfaces. The framework of the present work is the first detailed modeling tool developed for the design and analysis of surfaces for various ice prevention/reduction strategies. © 2011 American Chemical Society

Near-Surface Wind Predictions in Complex Terrain with a CFD Approach Optimized for Atmospheric Boundary Layer Flows

NASA Astrophysics Data System (ADS)

Wagenbrenner, N. S.; Forthofer, J.; Butler, B.; Shannon, K.

2014-12-01

Near-surface wind predictions are important for a number of applications, including transport and dispersion, wind energy forecasting, and wildfire behavior. Researchers and forecasters would benefit from a wind model that could be readily applied to complex terrain for use in these various disciplines. Unfortunately, near-surface winds in complex terrain are not handled well by traditional modeling approaches. Numerical weather prediction models employ coarse horizontal resolutions which do not adequately resolve sub-grid terrain features important to the surface flow. Computational fluid dynamics (CFD) models are increasingly being applied to simulate atmospheric boundary layer (ABL) flows, especially in wind energy applications; however, the standard functionality provided in commercial CFD models is not suitable for ABL flows. Appropriate CFD modeling in the ABL requires modification of empirically-derived wall function parameters and boundary conditions to avoid erroneous streamwise gradients due to inconsistences between inlet profiles and specified boundary conditions. This work presents a new version of a near-surface wind model for complex terrain called WindNinja. The new version of WindNinja offers two options for flow simulations: 1) the native, fast-running mass-consistent method available in previous model versions and 2) a CFD approach based on the OpenFOAM modeling framework and optimized for ABL flows. The model is described and evaluations of predictions with surface wind data collected from two recent field campaigns in complex terrain are presented. A comparison of predictions from the native mass-consistent method and the new CFD method is also provided.

Experimental High-Resolution Land Surface Prediction System for the Vancouver 2010 Winter Olympic Games

NASA Astrophysics Data System (ADS)

Belair, S.; Bernier, N.; Tong, L.; Mailhot, J.

2008-05-01

The 2010 Winter Olympic and Paralympic Games will take place in Vancouver, Canada, from 12 to 28 February 2010 and from 12 to 21 March 2010, respectively. In order to provide the best possible guidance achievable with current state-of-the-art science and technology, Environment Canada is currently setting up an experimental numerical prediction system for these special events. This system consists of a 1-km limited-area atmospheric model that will be integrated for 16h, twice a day, with improved microphysics compared with the system currently operational at the Canadian Meteorological Centre. In addition, several new and original tools will be used to adapt and refine predictions near and at the surface. Very high-resolution two-dimensional surface systems, with 100-m and 20-m grid size, will cover the Vancouver Olympic area. Using adaptation methods to improve the forcing from the lower-resolution atmospheric models, these 2D surface models better represent surface processes, and thus lead to better predictions of snow conditions and near-surface air temperature. Based on a similar strategy, a single-point model will be implemented to better predict surface characteristics at each station of an observing network especially installed for the 2010 events. The main advantage of this single-point system is that surface observations are used as forcing for the land surface models, and can even be assimilated (although this is not expected in the first version of this new tool) to improve initial conditions of surface variables such as snow depth and surface temperatures. Another adaptation tool, based on 2D stationnary solutions of a simple dynamical system, will be used to produce near-surface winds on the 100-m grid, coherent with the high- resolution orography. The configuration of the experimental numerical prediction system will be presented at the conference, together with preliminary results for winter 2007-2008.

Three-dimensional digital-computer model of the Ferron sandstone aquifer near Emery, Utah

USGS Publications Warehouse

Morrissey, Daniel J.; Lines, Gregory C.; Bartholoma, Scott D.

1980-01-01

A three-dimensional finite-difference computer model of the Ferron sandstone aquifer was used to simulate groundwater flow in the Emery coal field in east-central Utah. The model also was used to predict the effects of proposed surface mining and the resulting mine dewatering on potentiometric surfaces of the aquifer. The model was calibrated in a steady-state simulation using water levels and manmade discharges from the aquifer that were observed during 1979. Too few data were available to verify the calibrated model in a transient-state simulation with historical aquifer response to manmade discharges. Predictions made with the model are considered to be semiquantitative. Discharge from the proposed surface mine was predicted to average 0.3 cubic foot per second through 15 years of operation. Drawdowns of 5 feet in the potentiometric surface of the aquifer were predicted to extend as much as 3 miles from the proposed mine after 15 years of operation. (USGS)

Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface

NASA Technical Reports Server (NTRS)

Brown, Cliff

2015-01-01

Empirical models for the shielding and refection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and rejection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.

Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface

NASA Technical Reports Server (NTRS)

Brown, Clifford A.

2016-01-01

Empirical models for the shielding and reflection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and reflection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.

Heat Flow In Cylindrical Bodies During Laser Surface Transformation Hardening

NASA Astrophysics Data System (ADS)

Sandven, Ole A.

1980-01-01

A mathematical model for the transient heat flow in cylindrical specimens is presented. The model predicts the temperature distribution in the vicinity of a moving ring-shaped laser spot around the periphery of the outer surface of a cylinder, or the inner surface of a hollow cylinder. It can be used to predict the depth of case in laser surface transformation hardening. The validity of the model is tested against experimental results obtained on SAE 4140 steel.

Predicting knee replacement damage in a simulator machine using a computational model with a consistent wear factor.

PubMed

Zhao, Dong; Sakoda, Hideyuki; Sawyer, W Gregory; Banks, Scott A; Fregly, Benjamin J

2008-02-01

Wear of ultrahigh molecular weight polyethylene remains a primary factor limiting the longevity of total knee replacements (TKRs). However, wear testing on a simulator machine is time consuming and expensive, making it impractical for iterative design purposes. The objectives of this paper were first, to evaluate whether a computational model using a wear factor consistent with the TKR material pair can predict accurate TKR damage measured in a simulator machine, and second, to investigate how choice of surface evolution method (fixed or variable step) and material model (linear or nonlinear) affect the prediction. An iterative computational damage model was constructed for a commercial knee implant in an AMTI simulator machine. The damage model combined a dynamic contact model with a surface evolution model to predict how wear plus creep progressively alter tibial insert geometry over multiple simulations. The computational framework was validated by predicting wear in a cylinder-on-plate system for which an analytical solution was derived. The implant damage model was evaluated for 5 million cycles of simulated gait using damage measurements made on the same implant in an AMTI machine. Using a pin-on-plate wear factor for the same material pair as the implant, the model predicted tibial insert wear volume to within 2% error and damage depths and areas to within 18% and 10% error, respectively. Choice of material model had little influence, while inclusion of surface evolution affected damage depth and area but not wear volume predictions. Surface evolution method was important only during the initial cycles, where variable step was needed to capture rapid geometry changes due to the creep. Overall, our results indicate that accurate TKR damage predictions can be made with a computational model using a constant wear factor obtained from pin-on-plate tests for the same material pair, and furthermore, that surface evolution method matters only during the initial "break in" period of the simulation.

Simulations of surface winds at the Viking Lander sites using a one-level model

NASA Technical Reports Server (NTRS)

Bridger, Alison F. C.; Haberle, Robert M.

1992-01-01

The one-level model developed by Mass and Dempsey for use in predicting surface flows in regions of complex terrain was adapted to simulate surface flows at the Viking lander sites on Mars. In the one-level model, prediction equations for surface winds and temperatures are formulated and solved. Surface temperatures change with time in response to diabatic heating, horizontal advection, adiabatic heating and cooling effects, and horizontal diffusion. Surface winds can change in response to horizontal advection, pressure gradient forces, Coriolis forces, surface drag, and horizontal diffusion. Surface pressures are determined by integration of the hydrostatic equation from the surface to some reference level. The model has successfully simulated surface flows under a variety of conditions in complex-terrain regions on Earth.

Arcjet Testing and Thermal Model Development for Multilayer Felt Reusable Surface Insulation

NASA Technical Reports Server (NTRS)

Milos, Frank S.; Scott, Carl Douglas; Papa, Steven V.

2012-01-01

Felt Reusable Surface Insulation was used extensively on leeward external surfaces of the Shuttle Orbiter, where the material is reusable for temperatures up to 670 K. For application on leeward surfaces of the Orion Multi-Purpose Crew Vehicle, where predicted temperatures reach 1620 K, the material functions as a pyrolyzing conformal ablator. An arcjet test series was conducted to assess the performance of multilayer Felt Reusable Surface Insulation at high temperatures, and a thermal-response, pyrolysis, and ablation model was developed. Model predictions compare favorably with the arcjet test data

Land Surface Data Assimilation

NASA Astrophysics Data System (ADS)

Houser, P. R.

2012-12-01

Information about land surface water, energy and carbon conditions is of critical importance to real-world applications such as agricultural production, water resource management, flood prediction, water supply, weather and climate forecasting, and environmental preservation. While ground-based observational networks are improving, the only practical way to observe these land surface states on continental to global scales is via satellites. Remote sensing can make spatially comprehensive measurements of various components of the terrestrial system, but it cannot provide information on the entire system (e.g. evaporation), and the observations represent only an instant in time. Land surface process models may be used to predict temporal and spatial terrestrial dynamics, but these predictions are often poor, due to model initialization, parameter and forcing, and physics errors. Therefore, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses) to provide a superior terrestrial state estimate. This is the goal of land surface data assimilation. Data Assimilation combines observations into a dynamical model, using the model's equations to provide time continuity and coupling between the estimated fields. Land surface data assimilation aims to utilize both our land surface process knowledge, as embodied in a land surface model, and information that can be gained from observations. Both model predictions and observations are imperfect and we wish to use both synergistically to obtain a more accurate result. Moreover, both contain different kinds of information, that when used together, provide an accuracy level that cannot be obtained individually. Model biases can be mitigated using a complementary calibration and parameterization process. Limited point measurements are often used to calibrate the model(s) and validate the assimilation results. This presentation will provide a brief background on land surface observation, modeling and data assimilation, followed by a discussion of various hydrologic data assimilation challenges, and finally conclude with several land surface data assimilation case studies.

Wave Current Interactions and Wave-blocking Predictions Using NHWAVE Model

DTIC Science & Technology

2013-03-01

Navier-Stokes equation. In this approach, as with previous modeling techniques, there is difficulty in simulating the free surface that inhibits accurate...hydrostatic, free - surface , rotational flows in multiple dimensions. It is useful in predicting transformations of surface waves and rapidly varied...Stelling, G., and M. Zijlema, 2003: An accurate and efficient finite-differencing algorithm for non-hydrostatic free surface flow with application to

Application of Artificial Neural Network and Response Surface Methodology in Modeling of Surface Roughness in WS2 Solid Lubricant Assisted MQL Turning of Inconel 718

NASA Astrophysics Data System (ADS)

Maheshwera Reddy Paturi, Uma; Devarasetti, Harish; Abimbola Fadare, David; Reddy Narala, Suresh Kumar

2018-04-01

In the present paper, the artificial neural network (ANN) and response surface methodology (RSM) are used in modeling of surface roughness in WS2 (tungsten disulphide) solid lubricant assisted minimal quantity lubrication (MQL) machining. The real time MQL turning of Inconel 718 experimental data considered in this paper was available in the literature [1]. In ANN modeling, performance parameters such as mean square error (MSE), mean absolute percentage error (MAPE) and average error in prediction (AEP) for the experimental data were determined based on Levenberg–Marquardt (LM) feed forward back propagation training algorithm with tansig as transfer function. The MATLAB tool box has been utilized in training and testing of neural network model. Neural network model with three input neurons, one hidden layer with five neurons and one output neuron (3-5-1 architecture) is found to be most confidence and optimal. The coefficient of determination (R2) for both the ANN and RSM model were seen to be 0.998 and 0.982 respectively. The surface roughness predictions from ANN and RSM model were related with experimentally measured values and found to be in good agreement with each other. However, the prediction efficacy of ANN model is relatively high when compared with RSM model predictions.

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.

Finite-Rate Ablation Boundary Conditions for Carbon-Phenolic Heat-Shield

NASA Technical Reports Server (NTRS)

Chen, Y.-K.; Milos, Frank S.

2003-01-01

A formulation of finite-rate ablation surface boundary conditions, including oxidation, nitridation, and sublimation of carbonaceous material with pyrolysis gas injection, has been developed based on surface species mass conservation. These surface boundary conditions are discretized and integrated with a Navier-Stokes solver. This numerical procedure can predict aerothermal heating, chemical species concentration, and carbonaceous material ablation rate over the heatshield surface of re-entry space vehicles. In this study, the gas-gas and gas-surface interactions are established for air flow over a carbon-phenolic heatshield. Two finite-rate gas-surface interaction models are considered in the present study. The first model is based on the work of Park, and the second model includes the kinetics suggested by Zhluktov and Abe. Nineteen gas phase chemical reactions and four gas-surface interactions are considered in the present model. There is a total of fourteen gas phase chemical species, including five species for air and nine species for ablation products. Three test cases are studied in this paper. The first case is a graphite test model in the arc-jet stream; the second is a light weight Phenolic Impregnated Carbon Ablator at the Stardust re-entry peak heating conditions, and the third is a fully dense carbon-phenolic heatshield at the peak heating point of a proposed Mars Sample Return Earth Entry Vehicle. Predictions based on both finite-rate gas- surface interaction models are compared with those obtained using B' tables, which were created based on the chemical equilibrium assumption. Stagnation point convective heat fluxes predicted using Park's finite-rate model are far below those obtained from chemical equilibrium B' tables and Zhluktov's model. Recession predictions from Zhluktov's model are generally lower than those obtained from Park's model and chemical equilibrium B' tables. The effect of species mass diffusion on predicted ablation rate is also examined.

Method and apparatus for sensor fusion

NASA Technical Reports Server (NTRS)

Krishen, Kumar (Inventor); Shaw, Scott (Inventor); Defigueiredo, Rui J. P. (Inventor)

1991-01-01

Method and apparatus for fusion of data from optical and radar sensors by error minimization procedure is presented. The method was applied to the problem of shape reconstruction of an unknown surface at a distance. The method involves deriving an incomplete surface model from an optical sensor. The unknown characteristics of the surface are represented by some parameter. The correct value of the parameter is computed by iteratively generating theoretical predictions of the radar cross sections (RCS) of the surface, comparing the predicted and the observed values for the RCS, and improving the surface model from results of the comparison. Theoretical RCS may be computed from the surface model in several ways. One RCS prediction technique is the method of moments. The method of moments can be applied to an unknown surface only if some shape information is available from an independent source. The optical image provides the independent information.

The NASA Seasonal-to-Interannual Prediction Project (NSIPP). [Annual Report for 2000

NASA Technical Reports Server (NTRS)

Rienecker, Michele; Suarez, Max; Adamec, David; Koster, Randal; Schubert, Siegfried; Hansen, James; Koblinsky, Chester (Technical Monitor)

2001-01-01

The goal of the project is to develop an assimilation and forecast system based on a coupled atmosphere-ocean-land-surface-sea-ice model capable of using a combination of satellite and in situ data sources to improve the prediction of ENSO and other major S-I signals and their global teleconnections. The objectives of this annual report are to: (1) demonstrate the utility of satellite data, especially surface height surface winds, air-sea fluxes and soil moisture, in a coupled model prediction system; and (2) aid in the design of the observing system for short-term climate prediction by conducting OSSE's and predictability studies.

Re-Analysis of the Solar Phase Curves of the Icy Galilean Satellites

NASA Technical Reports Server (NTRS)

Domingue, Deborah; Verbiscer, Anne

1997-01-01

Re-analysis of the solar phase curves of the icy Galilean satellites demonstrates that the quantitative results are dependent on the single particle scattering function incorporated into the photometric model; however, the qualitative properties are independent. The results presented here show that the general physical characteristics predicted by a Hapke model (B. Hapke, 1986, Icarus 67, 264-280) incorporating a two parameter double Henyey-Greenstein scattering function are similar to the predictions given by the same model incorporating a three parameter double Henyey-Greenstein scattering function as long as the data set being modeled has adequate coverage in phase angle. Conflicting results occur when the large phase angle coverage is inadequate. Analysis of the role of isotropic versus anisotropic multiple scattering shows that for surfaces as bright as Europa the two models predict very similar results over phase angles covered by the data. Differences arise only at those phase angles for which there are no data. The single particle scattering behavior between the leading and trailing hemispheres of Europa and Ganymede is commensurate with magnetospheric alterations of their surfaces. Ion bombardment will produce more forward scattering single scattering functions due to annealing of potential scattering centers within regolith particles (N. J. Sack et al., 1992, Icarus 100, 534-540). Both leading and trailing hemispheres of Europa are consistent with a high porosity model and commensurate with a frost surface. There are no strong differences in predicted porosity between the two hemispheres of Callisto, both are consistent with model porosities midway between that deduced for Europa and the Moon. Surface roughness model estimates predict that surface roughness increases with satellite distance from Jupiter, with lunar surface roughness values falling midway between those measured for Ganymede and Callisto. There is no obvious variation in predicted surface roughness with hemisphere for any of the Galilean satellites.

A robust empirical seasonal prediction of winter NAO and surface climate.

PubMed

Wang, L; Ting, M; Kushner, P J

2017-03-21

A key determinant of winter weather and climate in Europe and North America is the North Atlantic Oscillation (NAO), the dominant mode of atmospheric variability in the Atlantic domain. Skilful seasonal forecasting of the surface climate in both Europe and North America is reflected largely in how accurately models can predict the NAO. Most dynamical models, however, have limited skill in seasonal forecasts of the winter NAO. A new empirical model is proposed for the seasonal forecast of the winter NAO that exhibits higher skill than current dynamical models. The empirical model provides robust and skilful prediction of the December-January-February (DJF) mean NAO index using a multiple linear regression (MLR) technique with autumn conditions of sea-ice concentration, stratospheric circulation, and sea-surface temperature. The predictability is, for the most part, derived from the relatively long persistence of sea ice in the autumn. The lower stratospheric circulation and sea-surface temperature appear to play more indirect roles through a series of feedbacks among systems driving NAO evolution. This MLR model also provides skilful seasonal outlooks of winter surface temperature and precipitation over many regions of Eurasia and eastern North America.

An Improved MUSIC Model for Gibbsite Surfaces

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

Mitchell, Scott C.; Bickmore, Barry R.; Tadanier, Christopher J.

2004-06-01

Here we use gibbsite as a model system with which to test a recently published, bond-valence method for predicting intrinsic pKa values for surface functional groups on oxides. At issue is whether the method is adequate when valence parameters for the functional groups are derived from ab initio structure optimization of surfaces terminated by vacuum. If not, ab initio molecular dynamics (AIMD) simulations of solvated surfaces (which are much more computationally expensive) will have to be used. To do this, we had to evaluate extant gibbsite potentiometric titration data that where some estimate of edge and basal surface area wasmore » available. Applying BET and recently developed atomic force microscopy methods, we found that most of these data sets were flawed, in that their surface area estimates were probably wrong. Similarly, there may have been problems with many of the titration procedures. However, one data set was adequate on both counts, and we applied our method of surface pKa int prediction to fitting a MUSIC model to this data with considerable success—several features of the titration data were predicted well. However, the model fit was certainly not perfect, and we experienced some difficulties optimizing highly charged, vacuum-terminated surfaces. Therefore, we conclude that we probably need to do AIMD simulations of solvated surfaces to adequately predict intrinsic pKa values for surface functional groups.« less

Using a hybrid model to predict solute transfer from initially saturated soil into surface runoff with controlled drainage water.

PubMed

Tong, Juxiu; Hu, Bill X; Yang, Jinzhong; Zhu, Yan

2016-06-01

The mixing layer theory is not suitable for predicting solute transfer from initially saturated soil to surface runoff water under controlled drainage conditions. By coupling the mixing layer theory model with the numerical model Hydrus-1D, a hybrid solute transfer model has been proposed to predict soil solute transfer from an initially saturated soil into surface water, under controlled drainage water conditions. The model can also consider the increasing ponding water conditions on soil surface before surface runoff. The data of solute concentration in surface runoff and drainage water from a sand experiment is used as the reference experiment. The parameters for the water flow and solute transfer model and mixing layer depth under controlled drainage water condition are identified. Based on these identified parameters, the model is applied to another initially saturated sand experiment with constant and time-increasing mixing layer depth after surface runoff, under the controlled drainage water condition with lower drainage height at the bottom. The simulation results agree well with the observed data. Study results suggest that the hybrid model can accurately simulate the solute transfer from initially saturated soil into surface runoff under controlled drainage water condition. And it has been found that the prediction with increasing mixing layer depth is better than that with the constant one in the experiment with lower drainage condition. Since lower drainage condition and deeper ponded water depth result in later runoff start time, more solute sources in the mixing layer are needed for the surface water, and larger change rate results in the increasing mixing layer depth.

Empirical Measurement and Model Validation of Infrared Spectra of Contaminated Surfaces

NASA Astrophysics Data System (ADS)

Archer, Sean

The goal of this thesis was to validate predicted infrared spectra of liquid contaminated surfaces from a micro-scale bi-directional reflectance distribution function (BRDF) model through the use of empirical measurement. Liquid contaminated surfaces generally require more sophisticated radiometric modeling to numerically describe surface properties. The Digital Image and Remote Sensing Image Generation (DIRSIG) model utilizes radiative transfer modeling to generate synthetic imagery for a variety of applications. Aside from DIRSIG, a micro-scale model known as microDIRSIG has been developed as a rigorous ray tracing physics-based model that could predict the BRDF of geometric surfaces that are defined as micron to millimeter resolution facets. The model offers an extension from the conventional BRDF models by allowing contaminants to be added as geometric objects to a micro-facet surface. This model was validated through the use of Fourier transform infrared spectrometer measurements. A total of 18 different substrate and contaminant combinations were measured and compared against modeled outputs. The substrates used in this experiment were wood and aluminum that contained three different paint finishes. The paint finishes included no paint, Krylon ultra-flat black, and Krylon glossy black. A silicon based oil (SF96) was measured out and applied to each surface to create three different contamination cases for each surface. Radiance in the longwave infrared region of the electromagnetic spectrum was measured by a Design and Prototypes (D&P) Fourier transform infrared spectrometer and a Physical Sciences Inc. Adaptive Infrared Imaging Spectroradiometer (AIRIS). The model outputs were compared against the measurements quantitatively in both the emissivity and radiance domains. A temperature emissivity separation (TES) algorithm had to be applied to the measured radiance spectra for comparison with the microDIRSIG predicted emissivity spectra. The model predicted emissivity spectra was also forward modeled through a DIRSIG simulation for comparisons to the radiance measurements. The results showed a promising agreement for homogeneous surfaces with liquid contamination that could be well characterized geometrically. Limitations arose in substrates that were modeled as homogeneous surfaces, but had spatially varying artifacts due to uncertainties with contaminant and surface interactions. There is high desire for accurate physics based modeling of liquid contaminated surfaces and this validation framework may be extended to include a wider array of samples for more realistic natural surfaces that are often found in real world scenarios.

Observations, models, and mechanisms of failure of surface rocks surrounding planetary surface loads

NASA Technical Reports Server (NTRS)

Schultz, R. A.; Zuber, M. T.

1994-01-01

Geophysical models of flexural stresses in an elastic lithosphere due to an axisymmetric surface load typically predict a transition with increased distance from the center of the load of radial thrust faults to strike-slip faults to concentric normal faults. These model predictions are in conflict with the absence of annular zones of strike-slip faults around prominent loads such as lunar maria, Martian volcanoes, and the Martian Tharsis rise. We suggest that this paradox arises from difficulties in relating failure criteria for brittle rocks to the stress models. Indications that model stresses are inappropriate for use in fault-type prediction include (1) tensile principal stresses larger than realistic values of rock tensile strength, and/or (2) stress differences significantly larger than those allowed by rock-strength criteria. Predictions of surface faulting that are consistent with observations can be obtained instead by using tensile and shear failure criteria, along with calculated stress differences and trajectories, with model stress states not greatly in excess of the maximum allowed by rock fracture criteria.

Proton exchange membrane fuel cell model for aging predictions: Simulated equivalent active surface area loss and comparisons with durability tests

NASA Astrophysics Data System (ADS)

Robin, C.; Gérard, M.; Quinaud, M.; d'Arbigny, J.; Bultel, Y.

2016-09-01

The prediction of Proton Exchange Membrane Fuel Cell (PEMFC) lifetime is one of the major challenges to optimize both material properties and dynamic control of the fuel cell system. In this study, by a multiscale modeling approach, a mechanistic catalyst dissolution model is coupled to a dynamic PEMFC cell model to predict the performance loss of the PEMFC. Results are compared to two 2000-h experimental aging tests. More precisely, an original approach is introduced to estimate the loss of an equivalent active surface area during an aging test. Indeed, when the computed Electrochemical Catalyst Surface Area profile is fitted on the experimental measures from Cyclic Voltammetry, the computed performance loss of the PEMFC is underestimated. To be able to predict the performance loss measured by polarization curves during the aging test, an equivalent active surface area is obtained by a model inversion. This methodology enables to successfully find back the experimental cell voltage decay during time. The model parameters are fitted from the polarization curves so that they include the global degradation. Moreover, the model captures the aging heterogeneities along the surface of the cell observed experimentally. Finally, a second 2000-h durability test in dynamic operating conditions validates the approach.

Simulation of Surface Erosion on a Logging Road in the Jackson Demonstration State Forest

Treesearch

Teresa Ish; David Tomberlin

2007-01-01

In constructing management models for the control of sediment delivery to streams, we have used a simulation model of road surface erosion known as the Watershed Erosion Prediction Project (WEPP) model, developed by the USDA Forest Service. This model predicts discharge, erosion, and sediment delivery at the road segment level, based on a stochastic climate simulator...

CFD validation experiments at McDonnell Aircraft Company

NASA Technical Reports Server (NTRS)

Verhoff, August

1987-01-01

Information is given in viewgraph form on computational fluid dynamics (CFD) validation experiments at McDonnell Aircraft Company. Topics covered include a high speed research model, a supersonic persistence fighter model, a generic fighter wing model, surface grids, force and moment predictions, surface pressure predictions, forebody models with 65 degree clipped delta wings, and the low aspect ratio wing/body experiment.

Combined Molecular Dynamics Simulation-Molecular-Thermodynamic Theory Framework for Predicting Surface Tensions.

PubMed

Sresht, Vishnu; Lewandowski, Eric P; Blankschtein, Daniel; Jusufi, Arben

2017-08-22

A molecular modeling approach is presented with a focus on quantitative predictions of the surface tension of aqueous surfactant solutions. The approach combines classical Molecular Dynamics (MD) simulations with a molecular-thermodynamic theory (MTT) [ Y. J. Nikas, S. Puvvada, D. Blankschtein, Langmuir 1992 , 8 , 2680 ]. The MD component is used to calculate thermodynamic and molecular parameters that are needed in the MTT model to determine the surface tension isotherm. The MD/MTT approach provides the important link between the surfactant bulk concentration, the experimental control parameter, and the surfactant surface concentration, the MD control parameter. We demonstrate the capability of the MD/MTT modeling approach on nonionic alkyl polyethylene glycol surfactants at the air-water interface and observe reasonable agreement of the predicted surface tensions and the experimental surface tension data over a wide range of surfactant concentrations below the critical micelle concentration. Our modeling approach can be extended to ionic surfactants and their mixtures with both ionic and nonionic surfactants at liquid-liquid interfaces.

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy.

PubMed

Dankers, Frank; Wijsman, Robin; Troost, Esther G C; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L

2017-05-07

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy

NASA Astrophysics Data System (ADS)

Dankers, Frank; Wijsman, Robin; Troost, Esther G. C.; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L.

2017-05-01

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Evaluation of Advanced Reactive Surface Area Estimates for Improved Prediction of Mineral Reaction Rates in Porous Media

NASA Astrophysics Data System (ADS)

Beckingham, L. E.; Mitnick, E. H.; Zhang, S.; Voltolini, M.; Yang, L.; Steefel, C. I.; Swift, A.; Cole, D. R.; Sheets, J.; Kneafsey, T. J.; Landrot, G.; Anovitz, L. M.; Mito, S.; Xue, Z.; Ajo Franklin, J. B.; DePaolo, D.

2015-12-01

CO2 sequestration in deep sedimentary formations is a promising means of reducing atmospheric CO2 emissions but the rate and extent of mineral trapping remains difficult to predict. Reactive transport models provide predictions of mineral trapping based on laboratory mineral reaction rates, which have been shown to have large discrepancies with field rates. This, in part, may be due to poor quantification of mineral reactive surface area in natural porous media. Common estimates of mineral reactive surface area are ad hoc and typically based on grain size, adjusted several orders of magnitude to account for surface roughness and reactivity. This results in orders of magnitude discrepancies in estimated surface areas that directly translate into orders of magnitude discrepancies in model predictions. Additionally, natural systems can be highly heterogeneous and contain abundant nano- and micro-porosity, which can limit connected porosity and access to mineral surfaces. In this study, mineral-specific accessible surface areas are computed for a sample from the reservoir formation at the Nagaoka pilot CO2 injection site (Japan). Accessible mineral surface areas are determined from a multi-scale image analysis including X-ray microCT, SEM QEMSCAN, XRD, SANS, and SEM-FIB. Powder and flow-through column laboratory experiments are performed and the evolution of solutes in the aqueous phase is tracked. Continuum-scale reactive transport models are used to evaluate the impact of reactive surface area on predictions of experimental reaction rates. Evaluated reactive surface areas include geometric and specific surface areas (eg. BET) in addition to their reactive-site weighted counterparts. The most accurate predictions of observed powder mineral dissolution rates were obtained through use of grain-size specific surface areas computed from a BET-based correlation. Effectively, this surface area reflects the grain-fluid contact area, or accessible surface area, in the powder dissolution experiment. In the model of the flow-through column experiment, the accessible mineral surface area, computed from the multi-scale image analysis, is evaluated in addition to the traditional surface area estimates.

Prediction of surface roughness and cutting force under MQL turning of AISI 4340 with nano fluid by using response surface methodology

NASA Astrophysics Data System (ADS)

Patole, Pralhad B.; Kulkarni, Vivek V.

2018-06-01

This paper presents an investigation into the minimum quantity lubrication mode with nano fluid during turning of alloy steel AISI 4340 work piece material with the objective of experimental model in order to predict surface roughness and cutting force and analyze effect of process parameters on machinability. Full factorial design matrix was used for experimental plan. According to design of experiment surface roughness and cutting force were measured. The relationship between the response variables and the process parameters is determined through the response surface methodology, using a quadratic regression model. Results show how much surface roughness is mainly influenced by feed rate and cutting speed. The depth of cut exhibits maximum influence on cutting force components as compared to the feed rate and cutting speed. The values predicted from the model and experimental values are very close to each other.

Are we near the predictability limit of tropical Indo-Pacific sea surface temperatures?

NASA Astrophysics Data System (ADS)

Newman, Matthew; Sardeshmukh, Prashant D.

2017-08-01

The predictability of seasonal anomalies worldwide rests largely on the predictability of tropical sea surface temperature (SST) anomalies. Tropical forecast skill is also a key metric of climate models. We find, however, that despite extensive model development, the tropical SST forecast skill of the operational North American Multi-Model Ensemble (NMME) of eight coupled atmosphere-ocean models remains close both regionally and temporally to that of a vastly simpler linear inverse model (LIM) derived from observed covariances of SST, sea surface height, and wind fields. The LIM clearly captures the essence of the predictable SST dynamics. The NMME and LIM skills also closely track and are only slightly lower than the potential skill estimated using the LIM's forecast signal-to-noise ratios. This suggests that the scope for further skill improvement is small in most regions, except in the western equatorial Pacific where the NMME skill is currently much lower than the LIM skill.

Improving Simulations of Precipitation Phase and Snowpack at a Site Subject to Cold Air Intrusions: Snoqualmie Pass, WA

NASA Astrophysics Data System (ADS)

Wayand, N. E.; Stimberis, J.; Zagrodnik, J.; Mass, C.; Lundquist, J. D.

2016-12-01

Low-level cold air from eastern Washington state often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet, these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface-air-temperature-based and mesoscale-model-based predictions of precipitation phase during the anomalously warm 2014-2015 winter. The skill of surface-based methods was greatly improved by using air temperature from a nearby higher-elevation station, which was less impacted by low-level inversions. Alternatively, we found a hybrid method that combines surface-based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill over both parent models. These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

Predictive Surface Complexation Modeling

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

Sverjensky, Dimitri A.

Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO 2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall,more » my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.« less

Real Time Land-Surface Hydrologic Modeling Over Continental US

NASA Technical Reports Server (NTRS)

Houser, Paul R.

1998-01-01

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

A Parameterization for Land-Atmosphere-Cloud Exchange (PLACE): Documentation and Testing of a Detailed Process Model of the Partly Cloudy Boundary Layer over Heterogeneous Land.

NASA Astrophysics Data System (ADS)

Wetzel, Peter J.; Boone, Aaron

1995-07-01

This paper presents a general description of, and demonstrates the capabilities of, the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE). The PLACE model is a detailed process model of the partly cloudy atmospheric boundary layer and underlying heterogeneous land surfaces. In its development, particular attention has been given to three of the model's subprocesses: the prediction of boundary layer cloud amount, the treatment of surface and soil subgrid heterogeneity, and the liquid water budget. The model includes a three-parameter nonprecipitating cumulus model that feeds back to the surface and boundary layer through radiative effects. Surface heterogeneity in the PLACE model is treated both statistically and by resolving explicit subgrid patches. The model maintains a vertical column of liquid water that is divided into seven reservoirs, from the surface interception store down to bedrock.Five single-day demonstration cases are presented, in which the PLACE model was initialized, run, and compared to field observations from four diverse sites. The model is shown to predict cloud amount well in these while predicting the surface fluxes with similar accuracy. A slight tendency to underpredict boundary layer depth is noted in all cases.Sensitivity tests were also run using anemometer-level forcing provided by the Project for Inter-comparison of Land-surface Parameterization Schemes (PILPS). The purpose is to demonstrate the relative impact of heterogeneity of surface parameters on the predicted annual mean surface fluxes. Significant sensitivity to subgrid variability of certain parameters is demonstrated, particularly to parameters related to soil moisture. A major result is that the PLACE-computed impact of total (homogeneous) deforestation of a rain forest is comparable in magnitude to the effect of imposing heterogeneity of certain surface variables, and is similarly comparable to the overall variance among the other PILPS participant models. Were this result to be bourne out by further analysis, it would suggest that today's average land surface parameterization has little credibility when applied to discriminating the local impacts of any plausible future climate change.

Validation of asphalt mixture pavement skid prediction model and development of skid prediction model for surface treatments.

DOT National Transportation Integrated Search

2017-04-01

Pavement skid resistance is primarily a function of the surface texture, which includes both microtexture and macrotexture. Earlier, under the Texas Department of Transportation (TxDOT) Research Project 0-5627, the researchers developed a method to p...

Improving Numerical Weather Predictions of Summertime Precipitation Over the Southeastern U.S. Through a High-Resolution Initialization of the Surface State

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Krikishen, Jayanthi; Jedlovec, Gary J.

2011-01-01

It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high resolution models. This paper presents model verification results of a case study period from June-August 2008 over the Southeastern U.S. using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the NASA Land Information System (LIS) and sea surface temperature (SST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spin-up run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer, but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS/MODIS data substantially impact surface and boundary layer properties.

The effects of topography on magma chamber deformation models: Application to Mt. Etna and radar interferometry

NASA Astrophysics Data System (ADS)

Williams, Charles A.; Wadge, Geoff

We have used a three-dimensional elastic finite element model to examine the effects of topography on the surface deformation predicted by models of magma chamber deflation. We used the topography of Mt. Etna to control the geometry of our model, and compared the finite element results to those predicted by an analytical solution for a pressurized sphere in an elastic half-space. Topography has a significant effect on the predicted surface deformation for both displacement profiles and synthetic interferograms. Not only are the predicted displacement magnitudes significantly different, but also the map-view patterns of displacement. It is possible to match the predicted displacement magnitudes fairly well by adjusting the elevation of a reference surface; however, the horizontal pattern of deformation is still significantly different. Thus, inversions based on constant-elevation reference surfaces may not properly estimate the horizontal position of a magma chamber. We have investigated an approach where the elevation of the reference surface varies for each computation point, corresponding to topography. For vertical displacements and tilts this method provides a good fit to the finite element results, and thus may form the basis for an inversion scheme. For radial displacements, a constant reference elevation provides a better fit to the numerical results.

Comparison of Orbiter STS-2 development flight instrumentation data with thermal math model predictions

NASA Technical Reports Server (NTRS)

Norman, I.; Rochelle, W. C.; Kimbrough, B. S.; Ritrivi, C. A.; Ting, P. C.; Dotts, R. L.

1982-01-01

Thermal performance verification of Reusable Surface Insulation (RSI) has been accomplished by comparisons of STS-2 Orbiter Flight Test (OFT) data with Thermal Math Model (TMM) predictions. The OFT data was obtained from Development Flight Instrumentation RSI plug and gap thermocouples. Quartertile RSI TMMs were developed using measured flight data for surface temperature and pressure environments. Reference surface heating rates, derived from surface temperature data, were multiplied by gap heating ratios to obtain tile sidewall heating rates. This TMM analysis resulted in good agreement of predicted temperatures with flight data for thermocouples located in the RSI, Strain Isolation Pad, filler bar and structure.

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

1992-01-01

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

SSUIS - a research model for predicting suspended solids loads in stormwater runoff from urban impervious surfaces.

PubMed

Brodie, Ian M

2012-01-01

Suspended solids from urban impervious surfaces (SSUIS) is a spreadsheet-based model that predicts the mass loading of suspended solids (SS) in stormwater runoff generated from impervious urban surfaces. The model is intended to be a research tool and incorporates several particle accumulation and washoff processes. Development of SSUIS is based on interpretation of storm event data obtained from a galvanised iron roof, a concrete car park and a bitumen road located in Toowoomba, Australia. SSUIS is a source area model that tracks the particle mass balance on the impervious surface and within its lateral drain to a point of discharge. Particles are separated into two groups: free and detained, depending on the rainfall energy required for surface washoff. Calibration and verification of SSUIS against the Toowoomba SS data yielded R(2) values ranging from 0.60 to 0.98. Parameter sensitivity analysis and an example of how SSUIS can be applied to predict the treatment efficiency of a grass swale are also provided.

A Geometric Model for Specularity Prediction on Planar Surfaces with Multiple Light Sources.

PubMed

Morgand, Alexandre; Tamaazousti, Mohamed; Bartoli, Adrien

2018-05-01

Specularities are often problematic in computer vision since they impact the dynamic range of the image intensity. A natural approach would be to predict and discard them using computer graphics models. However, these models depend on parameters which are difficult to estimate (light sources, objects' material properties and camera). We present a geometric model called JOLIMAS: JOint LIght-MAterial Specularity, which predicts the shape of specularities. JOLIMAS is reconstructed from images of specularities observed on a planar surface. It implicitly includes light and material properties, which are intrinsic to specularities. This model was motivated by the observation that specularities have a conic shape on planar surfaces. The conic shape is obtained by projecting a fixed quadric on the planar surface. JOLIMAS thus predicts the specularity using a simple geometric approach with static parameters (object material and light source shape). It is adapted to indoor light sources such as light bulbs and fluorescent lamps. The prediction has been tested on synthetic and real sequences. It works in a multi-light context by reconstructing a quadric for each light source with special cases such as lights being switched on or off. We also used specularity prediction for dynamic retexturing and obtained convincing rendering results. Further results are presented as supplementary video material, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TVCG.2017.2677445.

Modeling Wind Wave Evolution from Deep to Shallow Water

DTIC Science & Technology

2014-09-30

results are very promising (see Figure 2). However, for the sake of efficiency, non-hydrostatic models assume a single-valued free surface in the...1996) are ongoing. Figure 3 Smoothed-Particle Hydrodynamics ( SPH ) simulations of waves breaking over an artificial reef in the laboratory (see... surface as predicted by the SPH model (see Dalrymple & Rogers, 2006). The agreement in the breaker dynamics predicted by the model and seen in the

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.

Joint Prediction of Longitudinal Development of Cortical Surfaces and White Matter Fibers from Neonatal MRI

PubMed Central

Rekik, Islem; Li, Gang; Yap, Pew-Thian; Chen, Geng; Lin, Weili; Shen, Dinggang

2017-01-01

The human brain can be modeled as multiple interrelated shapes (or a multishape), each for characterizing one aspect of the brain, such as the cortex and white matter pathways. Predicting the developing multishape is a very challenging task due to the contrasting nature of the developmental trajectories of the constituent shapes: smooth for the cortical surface and non-smooth for white matter tracts due to changes such as bifurcation. We recently addressed this problem and proposed an approach for predicting the multishape developmental spatiotemporal trajectories of infant brains based only on neonatal MRI data using a set of geometric, dynamic, and fiber-to-surface connectivity features. In this paper, we propose two key innovations to further improve the prediction of multishape evolution. First, for a more accurate cortical surface prediction, instead of simply relying on one neonatal atlas to guide the prediction of the multishape, we propose to use multiple neonatal atlases to build a spatially heterogeneous atlas using the multidirectional varifold representation. This individualizes the atlas by locally maximizing its similarity to the testing baseline cortical shape for each cortical region, thereby better representing the baseline testing cortical surface, which founds the multishape prediction process. Second, for temporally consistent fiber prediction, we propose to reliably estimate spatiotemporal connectivity features using low-rank tensor completion, thereby capturing the variability and richness of the temporal development of fibers. Experimental results confirm that the proposed variants significantly improve the prediction performance of our original multishape prediction framework for both cortical surfaces and fiber tracts shape at 3, 6, and 9 months of age. Our pioneering model will pave the way for learning how to predict the evolution of anatomical shapes with abnormal changes. Ultimately, devising accurate shape evolution prediction models that can help quantify and predict the severity of a brain disorder as it progresses will be of great aid in individualized treatment planning. PMID:28284800

Joint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI.

PubMed

Rekik, Islem; Li, Gang; Yap, Pew-Thian; Chen, Geng; Lin, Weili; Shen, Dinggang

2017-05-15

The human brain can be modeled as multiple interrelated shapes (or a multishape), each for characterizing one aspect of the brain, such as the cortex and white matter pathways. Predicting the developing multishape is a very challenging task due to the contrasting nature of the developmental trajectories of the constituent shapes: smooth for the cortical surface and non-smooth for white matter tracts due to changes such as bifurcation. We recently addressed this problem and proposed an approach for predicting the multishape developmental spatiotemporal trajectories of infant brains based only on neonatal MRI data using a set of geometric, dynamic, and fiber-to-surface connectivity features. In this paper, we propose two key innovations to further improve the prediction of multishape evolution. First, for a more accurate cortical surface prediction, instead of simply relying on one neonatal atlas to guide the prediction of the multishape, we propose to use multiple neonatal atlases to build a spatially heterogeneous atlas using the multidirectional varifold representation. This individualizes the atlas by locally maximizing its similarity to the testing baseline cortical shape for each cortical region, thereby better representing the baseline testing cortical surface, which founds the multishape prediction process. Second, for temporally consistent fiber prediction, we propose to reliably estimate spatiotemporal connectivity features using low-rank tensor completion, thereby capturing the variability and richness of the temporal development of fibers. Experimental results confirm that the proposed variants significantly improve the prediction performance of our original multishape prediction framework for both cortical surfaces and fiber tracts shape at 3, 6, and 9 months of age. Our pioneering model will pave the way for learning how to predict the evolution of anatomical shapes with abnormal changes. Ultimately, devising accurate shape evolution prediction models that can help quantify and predict the severity of a brain disorder as it progresses will be of great aid in individualized treatment planning. Copyright © 2017 Elsevier Inc. All rights reserved.

Predictive model for convective flows induced by surface reactivity contrast

NASA Astrophysics Data System (ADS)

Davidson, Scott M.; Lammertink, Rob G. H.; Mani, Ali

2018-05-01

Concentration gradients in a fluid adjacent to a reactive surface due to contrast in surface reactivity generate convective flows. These flows result from contributions by electro- and diffusio-osmotic phenomena. In this study, we have analyzed reactive patterns that release and consume protons, analogous to bimetallic catalytic conversion of peroxide. Similar systems have typically been studied using either scaling analysis to predict trends or costly numerical simulation. Here, we present a simple analytical model, bridging the gap in quantitative understanding between scaling relations and simulations, to predict the induced potentials and consequent velocities in such systems without the use of any fitting parameters. Our model is tested against direct numerical solutions to the coupled Poisson, Nernst-Planck, and Stokes equations. Predicted slip velocities from the model and simulations agree to within a factor of ≈2 over a multiple order-of-magnitude change in the input parameters. Our analysis can be used to predict enhancement of mass transport and the resulting impact on overall catalytic conversion, and is also applicable to predicting the speed of catalytic nanomotors.

Potential Predictability of U.S. Summer Climate with "Perfect" Soil Moisture

NASA Technical Reports Server (NTRS)

Yang, Fanglin; Kumar, Arun; Lau, K.-M.

2004-01-01

The potential predictability of surface-air temperature and precipitation over the United States continent was assessed for a GCM forced by observed sea surface temperatures and an estimate of observed ground soil moisture contents. The latter was obtained by substituting the GCM simulated precipitation, which is used to drive the GCM's land-surface component, with observed pentad-mean precipitation at each time step of the model's integration. With this substitution, the simulated soil moisture correlates well with an independent estimate of observed soil moisture in all seasons over the entire US continent. Significant enhancements on the predictability of surface-air temperature and precipitation were found in boreal late spring and summer over the US continent. Anomalous pattern correlations of precipitation and surface-air temperature over the US continent in the June-July-August season averaged for the 1979-2000 period increased from 0.01 and 0.06 for the GCM simulations without precipitation substitution to 0.23 and 0.3 1, respectively, for the simulations with precipitation substitution. Results provide an estimate for the limits of potential predictability if soil moisture variability is to be perfectly predicted. However, this estimate may be model dependent, and needs to be substantiated by other modeling groups.

A numerical study of wave-current interaction through surface and bottom stresses: Coastal ocean response to Hurricane Fran of 1996

NASA Astrophysics Data System (ADS)

Xie, L.; Pietrafesa, L. J.; Wu, K.

2003-02-01

A three-dimensional wave-current coupled modeling system is used to examine the influence of waves on coastal currents and sea level. This coupled modeling system consists of the wave model-WAM (Cycle 4) and the Princeton Ocean Model (POM). The results from this study show that it is important to incorporate surface wave effects into coastal storm surge and circulation models. Specifically, we find that (1) storm surge models without coupled surface waves generally under estimate not only the peak surge but also the coastal water level drop which can also cause substantial impact on the coastal environment, (2) introducing wave-induced surface stress effect into storm surge models can significantly improve storm surge prediction, (3) incorporating wave-induced bottom stress into the coupled wave-current model further improves storm surge prediction, and (4) calibration of the wave module according to minimum error in significant wave height does not necessarily result in an optimum wave module in a wave-current coupled system for current and storm surge prediction.

Modeling the growth of Listeria monocytogenes on the surface of smear- or mold-ripened cheese.

PubMed

Schvartzman, M Sol; Gonzalez-Barron, Ursula; Butler, Francis; Jordan, Kieran

2014-01-01

Surface-ripened cheeses are matured by means of manual or mechanical technologies posing a risk of cross-contamination, if any cheeses are contaminated with Listeria monocytogenes. In predictive microbiology, primary models are used to describe microbial responses, such as growth rate over time and secondary models explain how those responses change with environmental factors. In this way, primary models were used to assess the growth rate of L. monocytogenes during ripening of the cheeses and the secondary models to test how much the growth rate was affected by either the pH and/or the water activity (aw) of the cheeses. The two models combined can be used to predict outcomes. The purpose of these experiments was to test three primary (the modified Gompertz equation, the Baranyi and Roberts model, and the Logistic model) and three secondary (the Cardinal model, the Ratowski model, and the Presser model) mathematical models in order to define which combination of models would best predict the growth of L. monocytogenes on the surface of artificially contaminated surface-ripened cheeses. Growth on the surface of the cheese was assessed and modeled. The primary models were firstly fitted to the data and the effects of pH and aw on the growth rate (μmax) were incorporated and assessed one by one with the secondary models. The Logistic primary model by itself did not show a better fit of the data among the other primary models tested, but the inclusion of the Cardinal secondary model improved the final fit. The aw was not related to the growth of Listeria. This study suggests that surface-ripened cheese should be separately regulated within EU microbiological food legislation and results expressed as counts per surface area rather than per gram.

The Potential for Predicting Precipitation on Seasonal-to-Interannual Timescales

NASA Technical Reports Server (NTRS)

Koster, R. D.

1999-01-01

The ability to predict precipitation several months in advance would have a significant impact on water resource management. This talk provides an overview of a project aimed at developing this prediction capability. NASA's Seasonal-to-Interannual Prediction Project (NSIPP) will generate seasonal-to-interannual sea surface temperature predictions through detailed ocean circulation modeling and will then translate these SST forecasts into forecasts of continental precipitation through the application of an atmospheric general circulation model and a "SVAT"-type land surface model. As part of the process, ocean variables (e.g., height) and land variables (e.g., soil moisture) will be updated regularly via data assimilation. The overview will include a discussion of the variability inherent in such a modeling system and will provide some quantitative estimates of the absolute upper limits of seasonal-to-interannual precipitation predictability.

Estimation of the Viscosities of Liquid Sn-Based Binary Lead-Free Solder Alloys

NASA Astrophysics Data System (ADS)

Wu, Min; Li, Jinquan

2018-01-01

The viscosity of a binary Sn-based lead-free solder alloy was calculated by combining the predicted model with the Miedema model. The viscosity factor was proposed and the relationship between the viscosity and surface tension was analyzed as well. The investigation result shows that the viscosity of Sn-based lead-free solders predicted from the predicted model shows excellent agreement with the reported values. The viscosity factor is determined by three physical parameters: atomic volume, electronic density, and electro-negativity. In addition, the apparent correlation between the surface tension and viscosity of the binary Sn-based Pb-free solder was obtained based on the predicted model.

Predicting silicon pore optics

NASA Astrophysics Data System (ADS)

Vacanti, Giuseppe; Barriére, Nicolas; Bavdaz, Marcos; Chatbi, Abdelhakim; Collon, Maximilien; Dekker, Danielle; Girou, David; Günther, Ramses; van der Hoeven, Roy; Landgraf, Boris; Sforzini, Jessica; Vervest, Mark; Wille, Eric

2017-09-01

Continuing improvement of Silicon Pore Optics (SPO) calls for regular extension and validation of the tools used to model and predict their X-ray performance. In this paper we present an updated geometrical model for the SPO optics and describe how we make use of the surface metrology collected during each of the SPO manufacturing runs. The new geometrical model affords the user a finer degree of control on the mechanical details of the SPO stacks, while a standard interface has been developed to make use of any type of metrology that can return changes in the local surface normal of the reflecting surfaces. Comparisons between the predicted and actual performance of samples optics will be shown and discussed.

Solar Atmosphere to Earth's Surface: Long Lead Time dB/dt Predictions with the Space Weather Modeling Framework

NASA Astrophysics Data System (ADS)

Welling, D. T.; Manchester, W.; Savani, N.; Sokolov, I.; van der Holst, B.; Jin, M.; Toth, G.; Liemohn, M. W.; Gombosi, T. I.

2017-12-01

The future of space weather prediction depends on the community's ability to predict L1 values from observations of the solar atmosphere, which can yield hours of lead time. While both empirical and physics-based L1 forecast methods exist, it is not yet known if this nascent capability can translate to skilled dB/dt forecasts at the Earth's surface. This paper shows results for the first forecast-quality, solar-atmosphere-to-Earth's-surface dB/dt predictions. Two methods are used to predict solar wind and IMF conditions at L1 for several real-world coronal mass ejection events. The first method is an empirical and observationally based system to estimate the plasma characteristics. The magnetic field predictions are based on the Bz4Cast system which assumes that the CME has a cylindrical flux rope geometry locally around Earth's trajectory. The remaining plasma parameters of density, temperature and velocity are estimated from white-light coronagraphs via a variety of triangulation methods and forward based modelling. The second is a first-principles-based approach that combines the Eruptive Event Generator using Gibson-Low configuration (EEGGL) model with the Alfven Wave Solar Model (AWSoM). EEGGL specifies parameters for the Gibson-Low flux rope such that it erupts, driving a CME in the coronal model that reproduces coronagraph observations and propagates to 1AU. The resulting solar wind predictions are used to drive the operational Space Weather Modeling Framework (SWMF) for geospace. Following the configuration used by NOAA's Space Weather Prediction Center, this setup couples the BATS-R-US global magnetohydromagnetic model to the Rice Convection Model (RCM) ring current model and a height-integrated ionosphere electrodynamics model. The long lead time predictions of dB/dt are compared to model results that are driven by L1 solar wind observations. Both are compared to real-world observations from surface magnetometers at a variety of geomagnetic latitudes. Metrics are calculated to examine how the simulated solar wind drivers impact forecast skill. These results illustrate the current state of long-lead-time forecasting and the promise of this technology for operational use.

A multisensor evaluation of the asymmetric convective model, version 2, in southeast Texas.

PubMed

Kolling, Jenna S; Pleim, Jonathan E; Jeffries, Harvey E; Vizuete, William

2013-01-01

There currently exist a number of planetary boundary layer (PBL) schemes that can represent the effects of turbulence in daytime convective conditions, although these schemes remain a large source of uncertainty in meteorology and air quality model simulations. This study evaluates a recently developed combined local and nonlocal closure PBL scheme, the Asymmetric Convective Model, version 2 (ACM2), against PBL observations taken from radar wind profilers, a ground-based lidar, and multiple daytime radiosonde balloon launches. These observations were compared against predictions of PBLs from the Weather Research and Forecasting (WRF) model version 3.1 with the ACM2 PBL scheme option, and the Fifth-Generation Meteorological Model (MM5) version 3.7.3 with the Eta PBL scheme option that is currently being used to develop ozone control strategies in southeast Texas. MM5 and WRF predictions during the regulatory modeling episode were evaluated on their ability to predict the rise and fall of the PBL during daytime convective conditions across southeastern Texas. The MM5 predicted PBLs consistently underpredicted observations, and were also less than the WRF PBL predictions. The analysis reveals that the MM5 predicted a slower rising and shallower PBL not representative of the daytime urban boundary layer. Alternatively, the WRF model predicted a more accurate PBL evolution improving the root mean square error (RMSE), both temporally and spatially. The WRF model also more accurately predicted vertical profiles of temperature and moisture in the lowest 3 km of the atmosphere. Inspection of median surface temperature and moisture time-series plots revealed higher predicted surface temperatures in WRF and more surface moisture in MM5. These could not be attributed to surface heat fluxes, and thus the differences in performance of the WRF and MM5 models are likely due to the PBL schemes. An accurate depiction of the diurnal evolution of the planetary boundary layer (PBL) is necessary for realistic air quality simulations, and for formulating effective policy. The meteorological model used to support the southeast Texas 03 attainment demonstration made predictions of the PBL that were consistently less than those found in observations. The use of the Asymmetric Convective Model, version 2 (ACM2), predicted taller PBL heights and improved model predictions. A lower predicted PBL height in an air quality model would increase precursor concentrations and change the chemical production of O3 and possibly the response to control strategies.

Regional climates in the GISS general circulation model: Surface air temperature

NASA Technical Reports Server (NTRS)

Hewitson, Bruce

1994-01-01

One of the more viable research techniques into global climate change for the purpose of understanding the consequent environmental impacts is based on the use of general circulation models (GCMs). However, GCMs are currently unable to reliably predict the regional climate change resulting from global warming, and it is at the regional scale that predictions are required for understanding human and environmental responses. Regional climates in the extratropics are in large part governed by the synoptic-scale circulation and the feasibility of using this interscale relationship is explored to provide a way of moving to grid cell and sub-grid cell scales in the model. The relationships between the daily circulation systems and surface air temperature for points across the continental United States are first developed in a quantitative form using a multivariate index based on principal components analysis (PCA) of the surface circulation. These relationships are then validated by predicting daily temperature using observed circulation and comparing the predicted values with the observed temperatures. The relationships predict surface temperature accurately over the major portion of the country in winter, and for half the country in summer. These relationships are then applied to the surface synoptic circulation of the Goddard Institute for Space Studies (GISS) GCM control run, and a set of surface grid cell temperatures are generated. These temperatures, based on the larger-scale validated circulation, may now be used with greater confidence at the regional scale. The generated temperatures are compared to those of the model and show that the model has regional errors of up to 10 C in individual grid cells.

Atlantic Meridional Overturning Circulation Influence on North Atlantic Sector Surface Air Temperature and its Predictability in the Kiel Climate Model

NASA Astrophysics Data System (ADS)

Latif, M.

2017-12-01

We investigate the influence of the Atlantic Meridional Overturning Circulation (AMOC) on the North Atlantic sector surface air temperature (SAT) in two multi-millennial control integrations of the Kiel Climate Model (KCM). One model version employs a freshwater flux correction over the North Atlantic, while the other does not. A clear influence of the AMOC on North Atlantic sector SAT only is simulated in the corrected model that depicts much reduced upper ocean salinity and temperature biases in comparison to the uncorrected model. Further, the model with much reduced biases depicts significantly enhanced multiyear SAT predictability in the North Atlantic sector relative to the uncorrected model. The enhanced SAT predictability in the corrected model is due to a stronger and more variable AMOC and its enhanced influence on North Atlantic sea surface temperature (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 SST and exhibit a smaller SAT predictability over the North Atlantic sector.

An Empirical Jet-Surface Interaction Noise Model with Temperature and Nozzle Aspect Ratio Effects

NASA Technical Reports Server (NTRS)

Brown, Cliff

2015-01-01

An empirical model for jet-surface interaction (JSI) noise produced by a round jet near a flat plate is described and the resulting model evaluated. The model covers unheated and hot jet conditions (1 less than or equal to jet total temperature ratio less than or equal to 2.7) in the subsonic range (0.5 less than or equal to M(sub a) less than or equal to 0.9), surface lengths 0.6 less than or equal to (axial distance from jet exit to surface trailing edge (inches)/nozzle exit diameter) less than or equal to 10, and surface standoff distances (0 less than or equal to (radial distance from jet lipline to surface (inches)/axial distance from jet exit to surface trailing edge (inches)) less than or equal to 1) using only second-order polynomials to provide predictable behavior. The JSI noise model is combined with an existing jet mixing noise model to produce exhaust noise predictions. Fit quality metrics and comparisons to between the predicted and experimental data indicate that the model is suitable for many system level studies. A first-order correction to the JSI source model that accounts for the effect of nozzle aspect ratio is also explored. This correction is based on changes to the potential core length and frequency scaling associated with rectangular nozzles up to 8:1 aspect ratio. However, more work is needed to refine these findings into a formal model.

Probabilistic Thermal Analysis During Mars Reconnaissance Orbiter Aerobraking

NASA Technical Reports Server (NTRS)

Dec, John A.

2007-01-01

A method for performing a probabilistic thermal analysis during aerobraking has been developed. The analysis is performed on the Mars Reconnaissance Orbiter solar array during aerobraking. The methodology makes use of a response surface model derived from a more complex finite element thermal model of the solar array. The response surface is a quadratic equation which calculates the peak temperature for a given orbit drag pass at a specific location on the solar panel. Five different response surface equations are used, one of which predicts the overall maximum solar panel temperature, and the remaining four predict the temperatures of the solar panel thermal sensors. The variables used to define the response surface can be characterized as either environmental, material property, or modeling variables. Response surface variables are statistically varied in a Monte Carlo simulation. The Monte Carlo simulation produces mean temperatures and 3 sigma bounds as well as the probability of exceeding the designated flight allowable temperature for a given orbit. Response surface temperature predictions are compared with the Mars Reconnaissance Orbiter flight temperature data.

Improving the Yule-Nielsen modified Neugebauer model by dot surface coverages depending on the ink superposition conditions

NASA Astrophysics Data System (ADS)

Hersch, Roger David; Crété, Frédérique

2004-12-01

Dot gain is different when dots are printed alone, printed in superposition with one ink or printed in superposition with two inks. In addition, the dot gain may also differ depending on which solid ink the considered halftone layer is superposed. In a previous research project, we developed a model for computing the effective surface coverage of a dot according to its superposition conditions. In the present contribution, we improve the Yule-Nielsen modified Neugebauer model by integrating into it our effective dot surface coverage computation model. Calibration of the reproduction curves mapping nominal to effective surface coverages in every superposition condition is carried out by fitting effective dot surfaces which minimize the sum of square differences between the measured reflection density spectra and reflection density spectra predicted according to the Yule-Nielsen modified Neugebauer model. In order to predict the reflection spectrum of a patch, its known nominal surface coverage values are converted into effective coverage values by weighting the contributions from different reproduction curves according to the weights of the contributing superposition conditions. We analyze the colorimetric prediction improvement brought by our extended dot surface coverage model for clustered-dot offset prints, thermal transfer prints and ink-jet prints. The color differences induced by the differences between measured reflection spectra and reflection spectra predicted according to the new dot surface estimation model are quantified on 729 different cyan, magenta, yellow patches covering the full color gamut. As a reference, these differences are also computed for the classical Yule-Nielsen modified spectral Neugebauer model incorporating a single halftone reproduction curve for each ink. Taking into account dot surface coverages according to different superposition conditions considerably improves the predictions of the Yule-Nielsen modified Neugebauer model. In the case of offset prints, the mean difference between predictions and measurements expressed in CIE-LAB CIE-94 ΔE94 values is reduced at 100 lpi from 1.54 to 0.90 (accuracy improvement factor: 1.7) and at 150 lpi it is reduced from 1.87 to 1.00 (accuracy improvement factor: 1.8). Similar improvements have been observed for a thermal transfer printer at 600 dpi, at lineatures of 50 and 75 lpi. In the case of an ink-jet printer at 600 dpi, the mean ΔE94 value is reduced at 75 lpi from 3.03 to 0.90 (accuracy improvement factor: 3.4) and at 100 lpi from 3.08 to 0.91 (accuracy improvement factor: 3.4).

Improving the Yule-Nielsen modified Neugebauer model by dot surface coverages depending on the ink superposition conditions

NASA Astrophysics Data System (ADS)

Hersch, Roger David; Crete, Frederique

2005-01-01

Dot gain is different when dots are printed alone, printed in superposition with one ink or printed in superposition with two inks. In addition, the dot gain may also differ depending on which solid ink the considered halftone layer is superposed. In a previous research project, we developed a model for computing the effective surface coverage of a dot according to its superposition conditions. In the present contribution, we improve the Yule-Nielsen modified Neugebauer model by integrating into it our effective dot surface coverage computation model. Calibration of the reproduction curves mapping nominal to effective surface coverages in every superposition condition is carried out by fitting effective dot surfaces which minimize the sum of square differences between the measured reflection density spectra and reflection density spectra predicted according to the Yule-Nielsen modified Neugebauer model. In order to predict the reflection spectrum of a patch, its known nominal surface coverage values are converted into effective coverage values by weighting the contributions from different reproduction curves according to the weights of the contributing superposition conditions. We analyze the colorimetric prediction improvement brought by our extended dot surface coverage model for clustered-dot offset prints, thermal transfer prints and ink-jet prints. The color differences induced by the differences between measured reflection spectra and reflection spectra predicted according to the new dot surface estimation model are quantified on 729 different cyan, magenta, yellow patches covering the full color gamut. As a reference, these differences are also computed for the classical Yule-Nielsen modified spectral Neugebauer model incorporating a single halftone reproduction curve for each ink. Taking into account dot surface coverages according to different superposition conditions considerably improves the predictions of the Yule-Nielsen modified Neugebauer model. In the case of offset prints, the mean difference between predictions and measurements expressed in CIE-LAB CIE-94 ΔE94 values is reduced at 100 lpi from 1.54 to 0.90 (accuracy improvement factor: 1.7) and at 150 lpi it is reduced from 1.87 to 1.00 (accuracy improvement factor: 1.8). Similar improvements have been observed for a thermal transfer printer at 600 dpi, at lineatures of 50 and 75 lpi. In the case of an ink-jet printer at 600 dpi, the mean ΔE94 value is reduced at 75 lpi from 3.03 to 0.90 (accuracy improvement factor: 3.4) and at 100 lpi from 3.08 to 0.91 (accuracy improvement factor: 3.4).

A prediction model based on artificial neural network for surface temperature simulation of nickel-metal hydride battery during charging

NASA Astrophysics Data System (ADS)

Fang, Kaizheng; Mu, Daobin; Chen, Shi; Wu, Borong; Wu, Feng

2012-06-01

In this study, a prediction model based on artificial neural network is constructed for surface temperature simulation of nickel-metal hydride battery. The model is developed from a back-propagation network which is trained by Levenberg-Marquardt algorithm. Under each ambient temperature of 10 °C, 20 °C, 30 °C and 40 °C, an 8 Ah cylindrical Ni-MH battery is charged in the rate of 1 C, 3 C and 5 C to its SOC of 110% in order to provide data for the model training. Linear regression method is adopted to check the quality of the model training, as well as mean square error and absolute error. It is shown that the constructed model is of excellent training quality for the guarantee of prediction accuracy. The surface temperature of battery during charging is predicted under various ambient temperatures of 50 °C, 60 °C, 70 °C by the model. The results are validated in good agreement with experimental data. The value of battery surface temperature is calculated to exceed 90 °C under the ambient temperature of 60 °C if it is overcharged in 5 C, which might cause battery safety issues.

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.

Quantifying errors in surface ozone predictions associated with clouds over the CONUS: a WRF-Chem modeling study using satellite cloud retrievals

NASA Astrophysics Data System (ADS)

Ryu, Young-Hee; Hodzic, Alma; Barre, Jerome; Descombes, Gael; Minnis, Patrick

2018-05-01

Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much error in O3 predictions can be directly attributed to error in cloud predictions. This study applies the Weather Research and Forecasting with Chemistry (WRF-Chem) model at 12 km horizontal resolution with the Morrison microphysics and Grell 3-D cumulus parameterization to quantify uncertainties in summertime surface O3 predictions associated with cloudiness over the contiguous United States (CONUS). All model simulations are driven by reanalysis of atmospheric data and reinitialized every 2 days. In sensitivity simulations, cloud fields used for photochemistry are corrected based on satellite cloud retrievals. The results show that WRF-Chem predicts about 55 % of clouds in the right locations and generally underpredicts cloud optical depths. These errors in cloud predictions can lead to up to 60 ppb of overestimation in hourly surface O3 concentrations on some days. The average difference in summertime surface O3 concentrations derived from the modeled clouds and satellite clouds ranges from 1 to 5 ppb for maximum daily 8 h average O3 (MDA8 O3) over the CONUS. This represents up to ˜ 40 % of the total MDA8 O3 bias under cloudy conditions in the tested model version. Surface O3 concentrations are sensitive to cloud errors mainly through the calculation of photolysis rates (for ˜ 80 %), and to a lesser extent to light-dependent BVOC emissions. The sensitivity of surface O3 concentrations to satellite-based cloud corrections is about 2 times larger in VOC-limited than NOx-limited regimes. Our results suggest that the benefits of accurate predictions of cloudiness would be significant in VOC-limited regions, which are typical of urban areas.

Wind noise measured at the ground surface.

PubMed

Yu, Jiao; Raspet, Richard; Webster, Jeremy; Abbott, Johnpaul

2011-02-01

Measurements of the wind noise measured at the ground surface outdoors are analyzed using the mirror flow model of anisotropic turbulence by Kraichnan [J. Acoust. Soc. Am. 28(3), 378-390 (1956)]. Predictions of the resulting behavior of the turbulence spectrum with height are developed, as well as predictions of the turbulence-shear interaction pressure at the surface for different wind velocity profiles and microphone mounting geometries are developed. The theoretical results of the behavior of the velocity spectra with height are compared to measurements to demonstrate the applicability of the mirror flow model to outdoor turbulence. The use of a logarithmic wind velocity profile for analysis is tested using meteorological models for wind velocity profiles under different stability conditions. Next, calculations of the turbulence-shear interaction pressure are compared to flush microphone measurements at the surface and microphone measurements with a foam covering flush with the surface. The measurements underneath the thin layers of foam agree closely with the predictions, indicating that the turbulence-shear interaction pressure is the dominant source of wind noise at the surface. The flush microphones measurements are intermittently larger than the predictions which may indicate other contributions not accounted for by the turbulence-shear interaction pressure.

[Optimal extraction of effective constituents from Aralia elata by central composite design and response surface methodology].

PubMed

Lv, Shao-Wa; Liu, Dong; Hu, Pan-Pan; Ye, Xu-Yan; Xiao, Hong-Bin; Kuang, Hai-Xue

2010-03-01

To optimize the process of extracting effective constituents from Aralia elata by response surface methodology. The independent variables were ethanol concentration, reflux time and solvent fold, the dependent variable was extraction rate of total saponins in Aralia elata. Linear or no-linear mathematic models were used to estimate the relationship between independent and dependent variables. Response surface methodology was used to optimize the process of extraction. The prediction was carried out through comparing the observed and predicted values. Regression coefficient of binomial fitting complex model was as high as 0.9617, the optimum conditions of extraction process were 70% ethanol, 2.5 hours for reflux, 20-fold solvent and 3 times for extraction. The bias between observed and predicted values was -2.41%. It shows the optimum model is highly predictive.

Representation of Vegetation and Other Nonerodible Elements in Aeolian Shear Stress Partitioning Models for Predicting Transport Threshold

NASA Technical Reports Server (NTRS)

King, James; Nickling, William G.; Gillies, John A.

2005-01-01

The presence of nonerodible elements is well understood to be a reducing factor for soil erosion by wind, but the limits of its protection of the surface and erosion threshold prediction are complicated by the varying geometry, spatial organization, and density of the elements. The predictive capabilities of the most recent models for estimating wind driven particle fluxes are reduced because of the poor representation of the effectiveness of vegetation to reduce wind erosion. Two approaches have been taken to account for roughness effects on sediment transport thresholds. Marticorena and Bergametti (1995) in their dust emission model parameterize the effect of roughness on threshold with the assumption that there is a relationship between roughness density and the aerodynamic roughness length of a surface. Raupach et al. (1993) offer a different approach based on physical modeling of wake development behind individual roughness elements and the partition of the surface stress and the total stress over a roughened surface. A comparison between the models shows the partitioning approach to be a good framework to explain the effect of roughness on entrainment of sediment by wind. Both models provided very good agreement for wind tunnel experiments using solid objects on a nonerodible surface. However, the Marticorena and Bergametti (1995) approach displays a scaling dependency when the difference between the roughness length of the surface and the overall roughness length is too great, while the Raupach et al. (1993) model's predictions perform better owing to the incorporation of the roughness geometry and the alterations to the flow they can cause.

Computational modelling of biomaterial surface interactions with blood platelets and osteoblastic cells for the prediction of contact osteogenesis.

PubMed

Amor, N; Geris, L; Vander Sloten, J; Van Oosterwyck, H

2011-02-01

Surface microroughness can induce contact osteogenesis (bone formation initiated at the implant surface) around oral implants, which may result from different mechanisms, such as blood platelet-biomaterial interactions and/or interaction with (pre-)osteoblast cells. We have developed a computational model of implant endosseous healing that takes into account these interactions. We hypothesized that the initial attachment and growth factor release from activated platelets is crucial in achieving contact osteogenesis. In order to investigate this, a computational model was applied to an animal experiment [7] that looked at the effect of surface microroughness on endosseous healing. Surface-specific model parameters were implemented based on in vitro data (Lincks et al. Biomaterials 1998;19:2219-32). The predicted spatio-temporal patterns of bone formation correlated with the histological data. It was found that contact osteogenesis could not be predicted if only the osteogenic response of cells was up-regulated by surface microroughness. This could only be achieved if platelet-biomaterial interactions were sufficiently up-regulated as well. These results confirmed our hypothesis and demonstrate the added value of the computational model to study the importance of surface-mediated events for peri-implant endosseous healing. Copyright © 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Use of Ocean Remote Sensing Data to Enhance Predictions with a Coupled General Circulation Model

NASA Technical Reports Server (NTRS)

Rienecker, Michele M.

1999-01-01

Surface height, sea surface temperature and surface wind observations from satellites have given a detailed time sequence of the initiation and evolution of the 1997/98 El Nino. The data have beet complementary to the subsurface TAO moored data in their spatial resolution and extent. The impact of satellite observations on seasonal prediction in the tropical Pacific using a coupled ocean-atmosphere general circulation model will be presented.

A Study of Water Wave Wakes of Washington State Ferries

NASA Astrophysics Data System (ADS)

Perfect, Bradley; Riley, James; Thomson, Jim; Fay, Endicott

2015-11-01

Washington State Ferries (WSF) operates a ferry route that travels through a 600m-wide channel called Rich Passage. Concerns of shoreline erosion in Rich Passage have prompted this study of the generation and propagation of surface wave wakes caused by WSF vessels. The problem was addressed in three ways: analytically, using an extension of the Kelvin wake model by Darmon et al. (J. Fluid Mech., 738, 2014); computationally, employing a RANS Navier-Stokes model in the CFD code OpenFOAM which uses the Volume of Fluid method to treat the free surface; and with field data taken in Sept-Nov, 2014, using a suite of surface wave measuring buoys. This study represents one of the first times that model predictions of ferry boat-generated wakes can be tested against measurements in open waters. The results of the models and the field data are evaluated using direct comparison of predicted and measured surface wave height as well as other metrics. Furthermore, the model predictions and field measurements suggest differences in wake amplitudes for different class vessels. Finally, the relative strengths and weaknesses of each prediction method as well as of the field measurements will be discussed. Washington State Department of Transportation.

NCEP/NLDAS Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Xia, Y.; Ek, M.; Wood, E.; Luo, L.; Sheffield, J.; Lettenmaier, D.; Livneh, B.; Cosgrove, B.; Mocko, D.; Meng, J.; Wei, H.; Restrepo, P.; Schaake, J.; Mo, K.

2009-05-01

The NCEP Environmental Modeling Center (EMC) collaborated with its CPPA (Climate Prediction Program of the Americas) partners to develop a North American Land Data Assimilation System (NLDAS, http://www.emc.ncep.noaa.gov/mmb/nldas) to monitor and predict the drought over the Continental United States (CONUS). The realtime NLDAS drought monitor, executed daily at NCEP/EMC, including daily, weekly and monthly anomaly and percentile of six fields (soil moisture, snow water equivalent, total runoff, streamflow, evaporation, precipitation) outputted from four land surface models (Noah, Mosaic, SAC, and VIC) on a common 1/8th degree grid using common hourly land surface forcing. The non-precipitation surface forcing is derived from NCEP's retrospective and realtime North American Regional Reanalysis System (NARR). The precipitation forcing is anchored to a daily gauge-only precipitation analysis over CONUS that applies a Parameter-elevation Regressions on Independent Slopes Model (PRISM) correction. This daily precipitation analysis is then temporally disaggregated to hourly precipitation amounts using radar and satellite precipitation. The NARR- based surface downward solar radiation is bias-corrected using seven years (1997-2004) of GOES satellite- derived solar radiation retrievals. The uncoupled ensemble seasonal drought prediction utilizes the following three independent approaches for generating downscaled ensemble seasonal forecasts of surface forcing: (1) Ensemble Streamflow Prediction, (2) CPC Official Seasonal Climate Outlook, and (3) NCEP CFS ensemble dynamical model prediction. For each of these three approaches, twenty ensemble members of forcing realizations are generated using a Bayesian merging algorithm developed by Princeton University. The three forcing methods are then used to drive the VIC model in seasonal prediction mode over thirteen large river basins that together span the CONUS domain. One to nine month ensemble seasonal prediction products such as air temperature, precipitation, soil moisture, snowpack, total runoff, evaporation and streamflow are derived for each forcing approach. The anomalies and percentiles of the predicted products for each approach may be used for CONUS drought prediction. This system is executed at the beginning of each month and distributes its products by the 10th of each month. The prediction products are evaluated using corresponding monitoring products for the VIC model and are compared with the prediction products from other research groups (e.g., University of Washington at Seattle, NASA Goddard) in the CONUS.

Evaluation of Finite-Rate Gas/Surface Interaction Models for a Carbon Based Ablator

NASA Technical Reports Server (NTRS)

Chen, Yih-Kanq; Goekcen, Tahir

2015-01-01

Two sets of finite-rate gas-surface interaction model between air and the carbon surface are studied. The first set is an engineering model with one-way chemical reactions, and the second set is a more detailed model with two-way chemical reactions. These two proposed models intend to cover the carbon surface ablation conditions including the low temperature rate-controlled oxidation, the mid-temperature diffusion-controlled oxidation, and the high temperature sublimation. The prediction of carbon surface recession is achieved by coupling a material thermal response code and a Navier-Stokes flow code. The material thermal response code used in this study is the Two-dimensional Implicit Thermal-response and Ablation Program, which predicts charring material thermal response and shape change on hypersonic space vehicles. The flow code solves the reacting full Navier-Stokes equations using Data Parallel Line Relaxation method. Recession analyses of stagnation tests conducted in NASA Ames Research Center arc-jet facilities with heat fluxes ranging from 45 to 1100 wcm2 are performed and compared with data for model validation. The ablating material used in these arc-jet tests is Phenolic Impregnated Carbon Ablator. Additionally, computational predictions of surface recession and shape change are in good agreement with measurement for arc-jet conditions of Small Probe Reentry Investigation for Thermal Protection System Engineering.

Energy- and wave-based beam-tracing prediction of room-acoustical parameters using different boundary conditions.

PubMed

Yousefzadeh, Behrooz; Hodgson, Murray

2012-09-01

A beam-tracing model was used to study the acoustical responses of three empty, rectangular rooms with different boundary conditions. The model is wave-based (accounting for sound phase) and can be applied to rooms with extended-reaction surfaces that are made of multiple layers of solid, fluid, or poroelastic materials-the acoustical properties of these surfaces are calculated using Biot theory. Three room-acoustical parameters were studied in various room configurations: sound strength, reverberation time, and RApid Speech Transmission Index. The main objective was to investigate the effects of modeling surfaces as either local or extended reaction on predicted values of these three parameters. Moreover, the significance of modeling interference effects was investigated, including the study of sound phase-change on surface reflection. Modeling surfaces as of local or extended reaction was found to be significant for surfaces consisting of multiple layers, specifically when one of the layers is air. For multilayers of solid materials with an air-cavity, this was most significant around their mass-air-mass resonance frequencies. Accounting for interference effects made significant changes in the predicted values of all parameters. Modeling phase change on reflection, on the other hand, was found to be relatively much less significant.

Simulating polarized light scattering in terrestrial snow based on bicontinuous random medium and Monte Carlo ray tracing

NASA Astrophysics Data System (ADS)

Xiong, Chuan; Shi, Jiancheng

2014-01-01

To date, the light scattering models of snow consider very little about the real snow microstructures. The ideal spherical or other single shaped particle assumptions in previous snow light scattering models can cause error in light scattering modeling of snow and further cause errors in remote sensing inversion algorithms. This paper tries to build up a snow polarized reflectance model based on bicontinuous medium, with which the real snow microstructure is considered. The accurate specific surface area of bicontinuous medium can be analytically derived. The polarized Monte Carlo ray tracing technique is applied to the computer generated bicontinuous medium. With proper algorithms, the snow surface albedo, bidirectional reflectance distribution function (BRDF) and polarized BRDF can be simulated. The validation of model predicted spectral albedo and bidirectional reflectance factor (BRF) using experiment data shows good results. The relationship between snow surface albedo and snow specific surface area (SSA) were predicted, and this relationship can be used for future improvement of snow specific surface area (SSA) inversion algorithms. The model predicted polarized reflectance is validated and proved accurate, which can be further applied in polarized remote sensing.

A new method to estimate average hourly global solar radiation on the horizontal surface

NASA Astrophysics Data System (ADS)

Pandey, Pramod K.; Soupir, Michelle L.

2012-10-01

A new model, Global Solar Radiation on Horizontal Surface (GSRHS), was developed to estimate the average hourly global solar radiation on the horizontal surfaces (Gh). The GSRHS model uses the transmission function (Tf,ij), which was developed to control hourly global solar radiation, for predicting solar radiation. The inputs of the model were: hour of day, day (Julian) of year, optimized parameter values, solar constant (H0), latitude, and longitude of the location of interest. The parameter values used in the model were optimized at a location (Albuquerque, NM), and these values were applied into the model for predicting average hourly global solar radiations at four different locations (Austin, TX; El Paso, TX; Desert Rock, NV; Seattle, WA) of the United States. The model performance was assessed using correlation coefficient (r), Mean Absolute Bias Error (MABE), Root Mean Square Error (RMSE), and coefficient of determinations (R2). The sensitivities of parameter to prediction were estimated. Results show that the model performed very well. The correlation coefficients (r) range from 0.96 to 0.99, while coefficients of determination (R2) range from 0.92 to 0.98. For daily and monthly prediction, error percentages (i.e. MABE and RMSE) were less than 20%. The approach we proposed here can be potentially useful for predicting average hourly global solar radiation on the horizontal surface for different locations, with the use of readily available data (i.e. latitude and longitude of the location) as inputs.

Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum

NASA Astrophysics Data System (ADS)

Wagle, Pradeep; Bhattarai, Nishan; Gowda, Prasanna H.; Kakani, Vijaya G.

2017-06-01

Robust evapotranspiration (ET) models are required to predict water usage in a variety of terrestrial ecosystems under different geographical and agrometeorological conditions. As a result, several remote sensing-based surface energy balance (SEB) models have been developed to estimate ET over large regions. However, comparison of the performance of several SEB models at the same site is limited. In addition, none of the SEB models have been evaluated for their ability to predict ET in rain-fed high biomass sorghum grown for biofuel production. In this paper, we evaluated the performance of five widely used single-source SEB models, namely Surface Energy Balance Algorithm for Land (SEBAL), Mapping ET with Internalized Calibration (METRIC), Surface Energy Balance System (SEBS), Simplified Surface Energy Balance Index (S-SEBI), and operational Simplified Surface Energy Balance (SSEBop), for estimating ET over a high biomass sorghum field during the 2012 and 2013 growing seasons. The predicted ET values were compared against eddy covariance (EC) measured ET (ETEC) for 19 cloud-free Landsat image. In general, S-SEBI, SEBAL, and SEBS performed reasonably well for the study period, while METRIC and SSEBop performed poorly. All SEB models substantially overestimated ET under extremely dry conditions as they underestimated sensible heat (H) and overestimated latent heat (LE) fluxes under dry conditions during the partitioning of available energy. METRIC, SEBAL, and SEBS overestimated LE regardless of wet or dry periods. Consequently, predicted seasonal cumulative ET by METRIC, SEBAL, and SEBS were higher than seasonal cumulative ETEC in both seasons. In contrast, S-SEBI and SSEBop substantially underestimated ET under too wet conditions, and predicted seasonal cumulative ET by S-SEBI and SSEBop were lower than seasonal cumulative ETEC in the relatively wetter 2013 growing season. Our results indicate the necessity of inclusion of soil moisture or plant water stress component in SEB models for the improvement of their performance, especially under too dry or wet environments.

Surface potential of methyl isobutyl carbinol adsorption layer at the air/water interface.

PubMed

Phan, Chi M; Nakahara, Hiromichi; Shibata, Osamu; Moroi, Yoshikiyo; Le, Thu N; Ang, Ha M

2012-01-26

The surface potential (ΔV) and surface tension (γ) of MIBC (methyl isobutyl carbinol) were measured on the subphase of pure water and electrolyte solutions (NaCl at 0.02 and 2 M). In contrast to ionic surfactants, it was found that surface potential gradually increased with MIBC concentration. The ΔV curves were strongly influenced by the presence of NaCl. The available model in literature, in which surface potential is linearly proportional to surface excess, failed to describe the experimental data. Consequently, a new model, employing a partial charge of alcohol adsorption layer, was proposed. The new model predicted the experimental data consistently for MIBC in different NaCl solutions. However, the model required additional information for ionic impurity to predict adsorption in the absence of electrolyte. Such inclusion of impurities is, however, unnecessary for industrial applications. The modeling results successfully quantify the influence of electrolytes on surface potential of MIBC, which is critical for froth stability.

Tuning and predicting the wetting of nanoengineered material surface

NASA Astrophysics Data System (ADS)

Ramiasa-MacGregor, M.; Mierczynska, A.; Sedev, R.; Vasilev, K.

2016-02-01

The wetting of a material can be tuned by changing the roughness on its surface. Recent advances in the field of nanotechnology open exciting opportunities to control macroscopic wetting behaviour. Yet, the benchmark theories used to describe the wettability of macroscopically rough surfaces fail to fully describe the wetting behaviour of systems with topographical features at the nanoscale. To shed light on the events occurring at the nanoscale we have utilised model gradient substrata where surface nanotopography was tailored in a controlled and robust manner. The intrinsic wettability of the coatings was varied from hydrophilic to hydrophobic. The measured water contact angle could not be described by the classical theories. We developed an empirical model that effectively captures the experimental data, and further enables us to predict the wetting of surfaces with nanoscale roughness by considering the physical and chemical properties of the material. The fundamental insights presented here are important for the rational design of advanced materials having tailored surface nanotopography with predictable wettability.The wetting of a material can be tuned by changing the roughness on its surface. Recent advances in the field of nanotechnology open exciting opportunities to control macroscopic wetting behaviour. Yet, the benchmark theories used to describe the wettability of macroscopically rough surfaces fail to fully describe the wetting behaviour of systems with topographical features at the nanoscale. To shed light on the events occurring at the nanoscale we have utilised model gradient substrata where surface nanotopography was tailored in a controlled and robust manner. The intrinsic wettability of the coatings was varied from hydrophilic to hydrophobic. The measured water contact angle could not be described by the classical theories. We developed an empirical model that effectively captures the experimental data, and further enables us to predict the wetting of surfaces with nanoscale roughness by considering the physical and chemical properties of the material. The fundamental insights presented here are important for the rational design of advanced materials having tailored surface nanotopography with predictable wettability. Electronic supplementary information (ESI) available: Detailed characterization of the nanorough substrates and model derivation. See DOI: 10.1039/c5nr08329j

Predictive Finite Rate Model for Oxygen-Carbon Interactions at High Temperature

NASA Astrophysics Data System (ADS)

Poovathingal, Savio

An oxidation model for carbon surfaces is developed to predict ablation rates for carbon heat shields used in hypersonic vehicles. Unlike existing empirical models, the approach used here was to probe gas-surface interactions individually and then based on an understanding of the relevant fundamental processes, build a predictive model that would be accurate over a wide range of pressures and temperatures, and even microstructures. Initially, molecular dynamics was used to understand the oxidation processes on the surface. The molecular dynamics simulations were compared to molecular beam experiments and good qualitative agreement was observed. The simulations reproduced cylindrical pitting observed in the experiments where oxidation was rapid and primarily occurred around a defect. However, the studies were limited to small systems at low temperatures and could simulate time scales only of the order of nanoseconds. Molecular beam experiments at high surface temperature indicated that a majority of surface reaction products were produced through thermal mechanisms. Since the reactions were thermal, they occurred over long time scales which were computationally prohibitive for molecular dynamics to simulate. The experiments provided detailed dynamical data on the scattering of O, O2, CO, and CO2 and it was found that the data from molecular beam experiments could be used directly to build a model. The data was initially used to deduce surface reaction probabilities at 800 K. The reaction probabilities were then incorporated into the direct simulation Monte Carlo (DSMC) method. Simulations were performed where the microstructure was resolved and dissociated oxygen convected and diffused towards it. For a gas-surface temperature of 800 K, it was found that despite CO being the dominant surface reaction product, a gas-phase reaction forms significant CO2 within the microstructure region. It was also found that surface area did not play any role in concentration of reaction products because the reaction probabilities were in the diffusion dominant regime. The molecular beam data at different surface temperatures was then used to build a finite rate model. Each reaction mechanism and all rate parameters of the new model were determined individually based on the molecular beam data. Despite the experiments being performed at near vacuum conditions, the finite rate model developed using the data could be used at pressures and temperatures relevant to hypersonic conditions. The new model was implemented in a computational fluid dynamics (CFD) solver and flow over a hypersonic vehicle was simulated. The new model predicted similar overall mass loss rates compared to existing models, however, the individual species production rates were completely different. The most notable difference was that the new model (based on molecular beam data) predicts CO as the oxidation reaction product with virtually no CO2 production, whereas existing models predict the exact opposite trend. CO being the dominant oxidation product is consistent with recent high enthalpy wind tunnel experiments. The discovery that measurements taken in molecular beam facilities are able to determine individual reaction mechanisms, including dependence on surface coverage, opens up an entirely new way of constructing ablation models.

Consequences of land-cover misclassification in models of impervious surface

USGS Publications Warehouse

McMahon, G.

2007-01-01

Model estimates of impervious area as a function of landcover area may be biased and imprecise because of errors in the land-cover classification. This investigation of the effects of land-cover misclassification on impervious surface models that use National Land Cover Data (NLCD) evaluates the consequences of adjusting land-cover within a watershed to reflect uncertainty assessment information. Model validation results indicate that using error-matrix information to adjust land-cover values used in impervious surface models does not substantially improve impervious surface predictions. Validation results indicate that the resolution of the landcover data (Level I and Level II) is more important in predicting impervious surface accurately than whether the land-cover data have been adjusted using information in the error matrix. Level I NLCD, adjusted for land-cover misclassification, is preferable to the other land-cover options for use in models of impervious surface. This result is tied to the lower classification error rates for the Level I NLCD. ?? 2007 American Society for Photogrammetry and Remote Sensing.

Biological Surface Adsorption Index of Nanomaterials: Modelling Surface Interactions of Nanomaterials with Biomolecules.

PubMed

Chen, Ran; Riviere, Jim E

2017-01-01

Quantitative analysis of the interactions between nanomaterials and their surrounding environment is crucial for safety evaluation in the application of nanotechnology as well as its development and standardization. In this chapter, we demonstrate the importance of the adsorption of surrounding molecules onto the surface of nanomaterials by forming biocorona and thus impact the bio-identity and fate of those materials. We illustrate the key factors including various physical forces in determining the interaction happening at bio-nano interfaces. We further discuss the mathematical endeavors in explaining and predicting the adsorption phenomena, and propose a new statistics-based surface adsorption model, the Biological Surface Adsorption Index (BSAI), to quantitatively analyze the interaction profile of surface adsorption of a large group of small organic molecules onto nanomaterials with varying surface physicochemical properties, first employing five descriptors representing the surface energy profile of the nanomaterials, then further incorporating traditional semi-empirical adsorption models to address concentration effects of solutes. These Advancements in surface adsorption modelling showed a promising development in the application of quantitative predictive models in biological applications, nanomedicine, and environmental safety assessment of nanomaterials.

Bayesian prediction of future ice sheet volume using local approximation Markov chain Monte Carlo methods

NASA Astrophysics Data System (ADS)

Davis, A. D.; Heimbach, P.; Marzouk, Y.

2017-12-01

We develop a Bayesian inverse modeling framework for predicting future ice sheet volume with associated formal uncertainty estimates. Marine ice sheets are drained by fast-flowing ice streams, which we simulate using a flowline model. Flowline models depend on geometric parameters (e.g., basal topography), parameterized physical processes (e.g., calving laws and basal sliding), and climate parameters (e.g., surface mass balance), most of which are unknown or uncertain. Given observations of ice surface velocity and thickness, we define a Bayesian posterior distribution over static parameters, such as basal topography. We also define a parameterized distribution over variable parameters, such as future surface mass balance, which we assume are not informed by the data. Hyperparameters are used to represent climate change scenarios, and sampling their distributions mimics internal variation. For example, a warming climate corresponds to increasing mean surface mass balance but an individual sample may have periods of increasing or decreasing surface mass balance. We characterize the predictive distribution of ice volume by evaluating the flowline model given samples from the posterior distribution and the distribution over variable parameters. Finally, we determine the effect of climate change on future ice sheet volume by investigating how changing the hyperparameters affects the predictive distribution. We use state-of-the-art Bayesian computation to address computational feasibility. Characterizing the posterior distribution (using Markov chain Monte Carlo), sampling the full range of variable parameters and evaluating the predictive model is prohibitively expensive. Furthermore, the required resolution of the inferred basal topography may be very high, which is often challenging for sampling methods. Instead, we leverage regularity in the predictive distribution to build a computationally cheaper surrogate over the low dimensional quantity of interest (future ice sheet volume). Continual surrogate refinement guarantees asymptotic sampling from the predictive distribution. Directly characterizing the predictive distribution in this way allows us to assess the ice sheet's sensitivity to climate variability and change.

Habitat of calling blue and fin whales in the Southern California Bight

NASA Astrophysics Data System (ADS)

Sirovic, A.; Chou, E.; Roch, M. A.

2016-02-01

Northeast Pacific blue whale B calls and fin whale 20 Hz calls were detected from passive acoustic data collected over seven years at 16 sites in the Southern California Bight (SCB). Calling blue whales were most common in the coastal areas, during the summer and fall months. Fin whales began calling in fall and continued through winter, in the southcentral SCB. These data were used to develop habitat models of calling blue and fin whales in areas of high and low abundance in the SCB, using remotely sensed variables such as sea surface temperature, sea surface height, chlorophyll a, and primary productivity as model covariates. A random forest framework was used for variable selection and generalized additive models were developed to explain functional relationships, evaluate relative contribution of each significant variable, and investigate predictive abilities of models of calling whales. Seasonal component was an important feature of all models. Additionally, areas of high calling blue and fin whale abundance both had a positive relationship with the sea surface temperature. In areas of lower abundance, chlorophyll a concentration and primary productivity were important variables for blue whale models and sea surface height and primary productivity were significant covariates in fin whale models. Predictive models were generally better for predicting general trends than absolute values, but there was a large degree of variation in year-to-year predictability across different sites.

Subtypes of developmental dyslexia: testing the predictions of the dual-route and connectionist frameworks.

PubMed

Peterson, Robin L; Pennington, Bruce F; Olson, Richard K

2013-01-01

We investigated the phonological and surface subtypes of developmental dyslexia in light of competing predictions made by two computational models of single word reading, the Dual-Route Cascaded Model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) and Harm and Seidenberg's connectionist model (HS model; Harm & Seidenberg, 1999). The regression-outlier procedure was applied to a large sample to identify children with disproportionately poor phonological coding skills (phonological dyslexia) or disproportionately poor orthographic coding skills (surface dyslexia). Consistent with the predictions of the HS model, children with "pure" phonological dyslexia, who did not have orthographic deficits, had milder phonological impairments than children with "relative" phonological dyslexia, who did have secondary orthographic deficits. In addition, pure cases of dyslexia were more common among older children. Consistent with the predictions of the DRC model, surface dyslexia was not well conceptualized as a reading delay; both phonological and surface dyslexia were associated with patterns of developmental deviance. In addition, some results were problematic for both models. We identified a small number of individuals with severe phonological dyslexia, relatively intact orthographic coding skills, and very poor real word reading. Further, a subset of controls could read normally despite impaired orthographic coding. The findings are discussed in terms of improvements to both models that might help better account for all cases of developmental dyslexia. Copyright © 2012 Elsevier B.V. All rights reserved.

Subtypes of developmental dyslexia: Testing the predictions of the dual-route and connectionist frameworks

PubMed Central

Peterson, Robin L.; Pennington, Bruce F.; Olson, Richard K.

2012-01-01

We investigated the phonological and surface subtypes of developmental dyslexia in light of competing predictions made by two computational models of single word reading, the dual-route cascaded model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) and Harm and Seidenberg’s connectionist model (HS model; Harm & Seidenberg, 1999). The regression-outlier procedure was applied to a large sample to identify children with disproportionately poor phonological coding skills (phonological dyslexia) or disproportionately poor orthographic coding skills (surface dyslexia). Consistent with the predictions of the HS model, children with “pure” phonological dyslexia, who did not have orthographic deficits, had milder phonological impairments than children with “relative” phonological dyslexia, who did have secondary orthographic deficits. In addition, pure cases of dyslexia were more common among older children. Consistent with the predictions of the DRC model, surface dyslexia was not well conceptualized as a reading delay; both phonological and surface dyslexia were associated with patterns of developmental deviance. In addition, some results were problematic for both models. We identified a small number of individuals with severe phonological dyslexia, relatively intact orthographic coding skills, and very poor real word reading. Further, a subset of controls could read normally despite impaired orthographic coding. The findings are discussed in terms of improvements to both models that might help better account for all cases of developmental dyslexia. PMID:23010562

Comparisons of predicted steady-state levels in rooms with extended- and local-reaction bounding surfaces

NASA Astrophysics Data System (ADS)

Hodgson, Murray; Wareing, Andrew

2008-01-01

A combined beam-tracing and transfer-matrix model for predicting steady-state sound-pressure levels in rooms with multilayer bounding surfaces was used to compare the effect of extended- and local-reaction surfaces, and the accuracy of the local-reaction approximation. Three rooms—an office, a corridor and a workshop—with one or more multilayer test surfaces were considered. The test surfaces were a single-glass panel, a double-drywall panel, a carpeted floor, a suspended-acoustical ceiling, a double-steel panel, and glass fibre on a hard backing. Each test surface was modeled as of extended or of local reaction. Sound-pressure levels were predicted and compared to determine the significance of the surface-reaction assumption. The main conclusions were that the difference between modeling a room surface as of extended or of local reaction is not significant when the surface is a single plate or a single layer of material (solid or porous) with a hard backing. The difference is significant when the surface consists of multilayers of solid or porous material and includes a layer of fluid with a large thickness relative to the other layers. The results are partially explained by considering the surface-reflection coefficients at the first-reflection angles.

A critical examination of the validity of simplified models for radiant heat transfer analysis.

NASA Technical Reports Server (NTRS)

Toor, J. S.; Viskanta, R.

1972-01-01

Examination of the directional effects of the simplified models by comparing the experimental data with the predictions based on simple and more detailed models for the radiation characteristics of surfaces. Analytical results indicate that the constant property diffuse and specular models do not yield the upper and lower bounds on local radiant heat flux. In general, the constant property specular analysis yields higher values of irradiation than the constant property diffuse analysis. A diffuse surface in the enclosure appears to destroy the effect of specularity of the other surfaces. Semigray and gray analyses predict the irradiation reasonably well provided that the directional properties and the specularity of the surfaces are taken into account. The uniform and nonuniform radiosity diffuse models are in satisfactory agreement with each other.

Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes

USGS Publications Warehouse

Dingman, John; Sweet, Lynn C.; McCullough, Ian M.; Davis, Frank W.; Flint, Alan L.; Franklin, Janet; Flint, Lorraine E.

2013-01-01

Abstract: Introduction: Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized. Methods: Using a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution. Results: The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m. Conclusion: Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.

Predictive simulation of bidirectional Glenn shunt using a hybrid blood vessel model.

PubMed

Li, Hao; Leow, Wee Kheng; Chiu, Ing-Sh

2009-01-01

This paper proposes a method for performing predictive simulation of cardiac surgery. It applies a hybrid approach to model the deformation of blood vessels. The hybrid blood vessel model consists of a reference Cosserat rod and a surface mesh. The reference Cosserat rod models the blood vessel's global bending, stretching, twisting and shearing in a physically correct manner, and the surface mesh models the surface details of the blood vessel. In this way, the deformation of blood vessels can be computed efficiently and accurately. Our predictive simulation system can produce complex surgical results given a small amount of user inputs. It allows the surgeon to easily explore various surgical options and evaluate them. Tests of the system using bidirectional Glenn shunt (BDG) as an application example show that the results produc by the system are similar to real surgical results.

Surface temperature distribution of GTA weld pools on thin-plate 304 stainless steel

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

Zacharia, T.; David, S.A.; Vitek, J.M.

1995-11-01

A transient multidimensional computational model was utilized to study gas tungsten arc (GTA) welding of thin-plate 304 stainless steel (SS). The model eliminates several of the earlier restrictive assumptions including temperature-independent thermal-physical properties. Consequently, all important thermal-physical properties were considered as temperature dependent throughout the range of temperatures experienced by the weld metal. The computational model was used to predict surface temperature distribution of the GTA weld pools in 1.5-mm-thick AISI 304 SS. The welding parameters were chosen so as to correspond with an earlier experimental study that produced high-resolution surface temperature maps. One of the motivations of the presentmore » study was to verify the predictive capability of the computational model. Comparison of the numerical predictions and experimental observations indicate excellent agreement, thereby verifying the model.« less

The plume head-continental lithosphere interaction using a tectonically realistic formulation for the lithosphere

NASA Astrophysics Data System (ADS)

Burov, E.; Guillou-Frottier, L.

2005-05-01

Current debates on the existence of mantle plumes largely originate from interpretations of supposed signatures of plume-induced surface topography that are compared with predictions of geodynamic models of plume-lithosphere interactions. These models often inaccurately predict surface evolution: in general, they assume a fixed upper surface and consider the lithosphere as a single viscous layer. In nature, the surface evolution is affected by the elastic-brittle-ductile deformation, by a free upper surface and by the layered structure of the lithosphere. We make a step towards reconciling mantle- and tectonic-scale studies by introducing a tectonically realistic continental plate model in large-scale plume-lithosphere interaction. This model includes (i) a natural free surface boundary condition, (ii) an explicit elastic-viscous(ductile)-plastic(brittle) rheology and (iii) a stratified structure of continental lithosphere. The numerical experiments demonstrate a number of important differences from predictions of conventional models. In particular, this relates to plate bending, mechanical decoupling of crustal and mantle layers and tension-compression instabilities, which produce transient topographic signatures such as uplift and subsidence at large (>500 km) and small scale (300-400, 200-300 and 50-100 km). The mantle plumes do not necessarily produce detectable large-scale topographic highs but often generate only alternating small-scale surface features that could otherwise be attributed to regional tectonics. A single large-wavelength deformation, predicted by conventional models, develops only for a very cold and thick lithosphere. Distinct topographic wavelengths or temporarily spaced events observed in the East African rift system, as well as over French Massif Central, can be explained by a single plume impinging at the base of the continental lithosphere, without evoking complex asthenospheric upwelling.

Predictions for the Effects of Free Stream Turbulence on Turbine Blade Heat Transfer

NASA Technical Reports Server (NTRS)

Boyle, Robert J.; Giel, Paul W.; Ames, Forrest E.

2004-01-01

An approach to predicting the effects of free stream turbulence on turbine vane and blade heat transfer is described. Four models for predicting the effects of free stream turbulence were in incorporated into a Navier-Stokes CFD analysis. Predictions were compared with experimental data in order to identify an appropriate model for use across a wide range of flow conditions. The analyses were compared with data from five vane geometries and from four rotor geometries. Each of these nine geometries had data for different Reynolds numbers. Comparisons were made for twenty four cases. Steady state calculations were done because all experimental data were obtained in steady state tests. High turbulence levels often result in suction surface transition upstream of the throat, while at low to moderate Reynolds numbers the pressure surface remains laminar. A two-dimensional analysis was used because the flow is predominately two-dimensional in the regions where free stream turbulence significantly augments surface heat transfer. Because the evaluation of models for predicting turbulence effects can be affected by other factors, the paper discusses modeling for transition, relaminarization, and near wall damping. Quantitative comparisons are given between the predictions and data.

Improving simulations of precipitation phase and snowpack at a site subject to cold air intrusions: Snoqualmie Pass, WA

NASA Astrophysics Data System (ADS)

Wayand, Nicholas E.; Stimberis, John; Zagrodnik, Joseph P.; Mass, Clifford F.; Lundquist, Jessica D.

2016-09-01

Low-level cold air from eastern Washington often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface-air-temperature-based and mesoscale-model-based predictions of precipitation phase during the anomalously warm 2014-2015 winter. Correlations of phase between surface-based methods and observations were greatly improved (r2 from 0.45 to 0.66) and frozen precipitation biases reduced (+36% to -6% of accumulated snow water equivalent) by using air temperature from a nearby higher-elevation station, which was less impacted by low-level inversions. Alternatively, we found a hybrid method that combines surface-based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill (r2 = 0.61) over both parent models (r2 = 0.42 and 0.55). These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

On the interest of combining an analog model to a regression model for the adaptation of the downscaling link. Application to probabilistic prediction of precipitation over France.

NASA Astrophysics Data System (ADS)

Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

2016-04-01

Scenarios of surface weather required for the impact studies have to be unbiased and adapted to the space and time scales of the considered hydro-systems. Hence, surface weather scenarios obtained from global climate models and/or numerical weather prediction models are not really appropriated. Outputs of these models have to be post-processed, which is often carried out thanks to Statistical Downscaling Methods (SDMs). Among those SDMs, approaches based on regression are often applied. For a given station, a regression link can be established between a set of large scale atmospheric predictors and the surface weather variable. These links are then used for the prediction of the latter. However, physical processes generating surface weather vary in time. This is well known for precipitation for instance. The most relevant predictors and the regression link are also likely to vary in time. A better prediction skill is thus classically obtained with a seasonal stratification of the data. Another strategy is to identify the most relevant predictor set and establish the regression link from dates that are similar - or analog - to the target date. In practice, these dates can be selected thanks to an analog model. In this study, we explore the possibility of improving the local performance of an analog model - where the analogy is applied to the geopotential heights 1000 and 500 hPa - using additional local scale predictors for the probabilistic prediction of the Safran precipitation over France. For each prediction day, the prediction is obtained from two GLM regression models - for both the occurrence and the quantity of precipitation - for which predictors and parameters are estimated from the analog dates. Firstly, the resulting combined model noticeably allows increasing the prediction performance by adapting the downscaling link for each prediction day. Secondly, the selected predictors for a given prediction depend on the large scale situation and on the considered region. Finally, even with such an adaptive predictor identification, the downscaling link appears to be robust: for a same prediction day, predictors selected for different locations of a given region are similar and the regression parameters are consistent within the region of interest.

Rapid recipe formulation for plasma etching of new materials

NASA Astrophysics Data System (ADS)

Chopra, Meghali; Zhang, Zizhuo; Ekerdt, John; Bonnecaze, Roger T.

2016-03-01

A fast and inexpensive scheme for etch rate prediction using flexible continuum models and Bayesian statistics is demonstrated. Bulk etch rates of MgO are predicted using a steady-state model with volume-averaged plasma parameters and classical Langmuir surface kinetics. Plasma particle and surface kinetics are modeled within a global plasma framework using single component Metropolis Hastings methods and limited data. The accuracy of these predictions is evaluated with synthetic and experimental etch rate data for magnesium oxide in an ICP-RIE system. This approach is compared and superior to factorial models generated from JMP, a software package frequently employed for recipe creation and optimization.

Physics-driven Spatiotemporal Regularization for High-dimensional Predictive Modeling: A Novel Approach to Solve the Inverse ECG Problem

NASA Astrophysics Data System (ADS)

Yao, Bing; Yang, Hui

2016-12-01

This paper presents a novel physics-driven spatiotemporal regularization (STRE) method for high-dimensional predictive modeling in complex healthcare systems. This model not only captures the physics-based interrelationship between time-varying explanatory and response variables that are distributed in the space, but also addresses the spatial and temporal regularizations to improve the prediction performance. The STRE model is implemented to predict the time-varying distribution of electric potentials on the heart surface based on the electrocardiogram (ECG) data from the distributed sensor network placed on the body surface. The model performance is evaluated and validated in both a simulated two-sphere geometry and a realistic torso-heart geometry. Experimental results show that the STRE model significantly outperforms other regularization models that are widely used in current practice such as Tikhonov zero-order, Tikhonov first-order and L1 first-order regularization methods.

Response surface modeling for hot, humid air decontamination of materials contaminated with Bacillus anthracis ∆Sterne and Bacillus thuringiensis Al Hakam spores

PubMed Central

2014-01-01

Response surface methodology using a face-centered cube design was used to describe and predict spore inactivation of Bacillus anthracis ∆Sterne and Bacillus thuringiensis Al Hakam spores after exposure of six spore-contaminated materials to hot, humid air. For each strain/material pair, an attempt was made to fit a first or second order model. All three independent predictor variables (temperature, relative humidity, and time) were significant in the models except that time was not significant for B. thuringiensis Al Hakam on nylon. Modeling was unsuccessful for wiring insulation and wet spores because there was complete spore inactivation in the majority of the experimental space. In cases where a predictive equation could be fit, response surface plots with time set to four days were generated. The survival of highly purified Bacillus spores can be predicted for most materials tested when given the settings for temperature, relative humidity, and time. These predictions were cross-checked with spore inactivation measurements. PMID:24949256

Modeling of estuarne chlorophyll a from an airborne scanner

USGS Publications Warehouse

Khorram, Siamak; Catts, Glenn P.; Cloern, James E.; Knight, Allen W.

1987-01-01

Near simultaneous collection of 34 surface water samples and airborne multispectral scanner data provided input for regression models developed to predict surface concentrations of estuarine chlorophyll a. Two wavelength ratios were employed in model development. The ratios werechosen to capitalize on the spectral characteristics of chlorophyll a, while minimizing atmospheric influences. Models were then applied to data previously acquired over the study area thre years earlier. Results are in the form of color-coded displays of predicted chlorophyll a concentrations and comparisons of the agreement among measured surface samples and predictions basedon coincident remotely sensed data. The influence of large variations in fresh-water inflow to the estuary are clearly apparent in the results. The synoptic view provided by remote sensing is another method of examining important estuarine dynamics difficult to observe from in situ sampling alone.

LDEF microenvironments, observed and predicted

NASA Astrophysics Data System (ADS)

Bourassa, R. J.; Pippin, H. G.; Gillis, J. R.

1993-04-01

A computer model for prediction of atomic oxygen exposure of spacecraft in low earth orbit, referred to as the primary atomic oxygen model, was originally described at the First Long Duration Exposure Facility (LDEF) Post-Retrieval Symposium. The primary atomic oxygen model accounts for variations in orbit parameters, the condition of the atmosphere, and for the orientation of exposed surfaces relative to the direction of spacecraft motion. The use of the primary atomic oxygen model to define average atomic oxygen exposure conditions for a spacecraft is discussed and a second microenvironments computer model is described that accounts for shadowing and scattering of atomic oxygen by complex surface protrusions and indentations. Comparisons of observed and predicted erosion of fluorinated ethylene propylene (FEP) thermal control blankets using the models are presented. Experimental and theoretical results are in excellent agreement. Work is in progress to expand modeling capability to include ultraviolet radiation exposure and to obtain more detailed information on reflecting and scattering characteristics of material surfaces.

LDEF microenvironments, observed and predicted

NASA Technical Reports Server (NTRS)

Bourassa, R. J.; Pippin, H. G.; Gillis, J. R.

1993-01-01

A computer model for prediction of atomic oxygen exposure of spacecraft in low earth orbit, referred to as the primary atomic oxygen model, was originally described at the First Long Duration Exposure Facility (LDEF) Post-Retrieval Symposium. The primary atomic oxygen model accounts for variations in orbit parameters, the condition of the atmosphere, and for the orientation of exposed surfaces relative to the direction of spacecraft motion. The use of the primary atomic oxygen model to define average atomic oxygen exposure conditions for a spacecraft is discussed and a second microenvironments computer model is described that accounts for shadowing and scattering of atomic oxygen by complex surface protrusions and indentations. Comparisons of observed and predicted erosion of fluorinated ethylene propylene (FEP) thermal control blankets using the models are presented. Experimental and theoretical results are in excellent agreement. Work is in progress to expand modeling capability to include ultraviolet radiation exposure and to obtain more detailed information on reflecting and scattering characteristics of material surfaces.

A Parametric Rosetta Energy Function Analysis with LK Peptides on SAM Surfaces.

PubMed

Lubin, Joseph H; Pacella, Michael S; Gray, Jeffrey J

2018-05-08

Although structures have been determined for many soluble proteins and an increasing number of membrane proteins, experimental structure determination methods are limited for complexes of proteins and solid surfaces. An economical alternative or complement to experimental structure determination is molecular simulation. Rosetta is one software suite that models protein-surface interactions, but Rosetta is normally benchmarked on soluble proteins. For surface interactions, the validity of the energy function is uncertain because it is a combination of independent parameters from energy functions developed separately for solution proteins and mineral surfaces. Here, we assess the performance of the RosettaSurface algorithm and test the accuracy of its energy function by modeling the adsorption of leucine/lysine (LK)-repeat peptides on methyl- and carboxy-terminated self-assembled monolayers (SAMs). We investigated how RosettaSurface predictions for this system compare with the experimental results, which showed that on both surfaces, LK-α peptides folded into helices and LK-β peptides held extended structures. Utilizing this model system, we performed a parametric analysis of Rosetta's Talaris energy function and determined that adjusting solvation parameters offered improved predictive accuracy. Simultaneously increasing lysine carbon hydrophilicity and the hydrophobicity of the surface methyl head groups yielded computational predictions most closely matching the experimental results. De novo models still should be interpreted skeptically unless bolstered in an integrative approach with experimental data.

A Coupled Surface Nudging Scheme for use in Retrospective ...

EPA Pesticide Factsheets

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem modeling. This scheme is known as the flux-adjusting surface data assimilation system (FASDAS) developed by Alapaty et al. (2008). This scheme provides continuous adjustments for soil moisture and temperature (via indirect nudging) and for surface air temperature and water vapor mixing ratio (via direct nudging). The simultaneous application of indirect and direct nudging maintains greater consistency between the soil temperature–moisture and the atmospheric surface layer mass-field variables. The new method, FASDAS, consistently improved the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as well as for high resolution regional climate predictions. This new capability has been released in WRF Version 3.8 as option grid_sfdda = 2. This new capability increased the accuracy of atmospheric inputs for use air quality, hydrology, and ecosystem modeling research to improve the accuracy of respective end-point research outcome. IMPACT: A new method, FASDAS, was implemented into the WRF model to consistently improve the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as wel

Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality

NASA Astrophysics Data System (ADS)

Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.

2017-12-01

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.

Overview of the 1986--1987 atomic mass predictions

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

Haustein, P.E.

1988-07-01

The need for a comprehensive update of earlier sets of atomic mass predictions is documented. A project that grew from this need and which resulted in the preparation of the 1986--1987 Atomic Mass Predictions is summarized. Ten sets of new mass predictions and expository text from a variety of types of mass models are combined with the latest evaluation of experimentally determined atomic masses. The methodology employed in constructing these mass predictions is outlined. The models are compared with regard to their reproduction of the experimental mass surface and their use of varying numbers of adjustable parameters. Plots are presented,more » for each set of predictions, of differences between model calculations and the measured masses. These plots may be used to estimate the reliability of the new mass predictions in unmeasured regions that border the experimetally known mass surface. copyright 1988 Academic Press, Inc.« less

Application of a GIS-/remote sensing-based approach for predicting groundwater potential zones using a multi-criteria data mining methodology.

PubMed

Mogaji, Kehinde Anthony; Lim, Hwee San

2017-07-01

This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of groundwater resources in the area. The overall results proved the efficacy of the data mining model and the geospatial technology in groundwater potential mapping.

Stem mortality in surface fires: Part II, experimental methods for characterizing the thermal response of tree stems to heating by fires

Treesearch

D. M. Jimenez; B. W. Butler; J. Reardon

2003-01-01

Current methods for predicting fire-induced plant mortality in shrubs and trees are largely empirical. These methods are not readily linked to duff burning, soil heating, and surface fire behavior models. In response to the need for a physics-based model of this process, a detailed model for predicting the temperature distribution through a tree stem as a function of...

Modeling of surface tension effects in venturi scrubbing

NASA Astrophysics Data System (ADS)

Ott, Robert M.; Wu, Tatsu K. L.; Crowder, Jerry W.

A modified model of venturi scrubber performance has been developed that addresses two effects of liquid surface tension: its effect on droplet size and its effect on particle penetration into the droplet. The predictions of the model indicate that, in general, collection efficiency increases with a decrease in liquid surface tension, but the range over which this increase is significant depends on the particle size and on the scrubber operating parameters. The predictions further indicate that the increases in collection efficiency are almost totally due to the effect of liquid surface tension on the mean droplet size, and that the collection efficiency is not significantly affected by the ability of the particle to penetrate the droplet.

Predicting surface fuel models and fuel metrics using lidar and CIR imagery in a dense mixed conifer forest

Treesearch

Marek K. Jakubowksi; Qinghua Guo; Brandon Collins; Scott Stephens; Maggi Kelly

2013-01-01

We compared the ability of several classification and regression algorithms to predict forest stand structure metrics and standard surface fuel models. Our study area spans a dense, topographically complex Sierra Nevada mixed-conifer forest. We used clustering, regression trees, and support vector machine algorithms to analyze high density (average 9 pulses/m

Heat transfer and vascular cambium necrosis in the boles of trees during surface fires

Treesearch

M. B. Dickinson

2002-01-01

Heat-transfer and cell-survival models are used to link surface fire behavior with vascular cambium necrosis from heating by flames. Vascular cambium cell survival was predicted with a numerical model based on the kinetics of protein denaturation and parameterized with data from the literature. Cell survival was predicted for vascular cambium temperature regimes...

Constraining the Sensitivity of Amazonian Rainfall with Observations of Surface Temperature

NASA Astrophysics Data System (ADS)

Dolman, A. J.; von Randow, C.; de Oliveira, G. S.; Martins, G.; Nobre, C. A.

2016-12-01

Earth System models generally do a poor job in predicting Amazonian rainfall, necessitating the need to look for observational constraints on their predictability. We use observed surface temperature and precipitation of the Amazon and a set of 21 CMIP5 models to derive an observational constraint of the sensitivity of rainfall to surface temperature (dP/dT). From first principles such a relation between the surface temperature of the earth and the amount of precipitation through the surface energy balance should exist, particularly in the tropics. When de-trended anomalies in surface temperature and precipitation from a set of datasets are plotted, a clear linear relation between surface temperature and precipitation appears. CMIP5 models show a similar relation with relatively cool models having a larger sensitivity, producing more rainfall. Using the ensemble of models and the observed surface temperature we were able to derive an emerging constraint, reducing the dPdt sensitivity of the CMIP5 model from -0.75 mm day-1 0C-1 (+/- 0.54 SD) to -0.77 mm day-1 0C-1 with a reduced uncertainty of about a factor 5. dPdT from the observation is -0.89 mm day-1 0C-1 . We applied the method to wet and dry season separately noticing that in the wet season we shifted the mean and reduced uncertainty, while in the dry season we very much reduced uncertainty only. The method can be applied to other model simulations such as specific deforestation scenarios to constrain the sensitivity of rainfall to surface temperature. We discuss the implications of the constrained sensitivity for future Amazonian predictions.

A Modeling and Experimental Investigation of the Effects of Antigen Density, Binding Affinity, and Antigen Expression Ratio on Bispecific Antibody Binding to Cell Surface Targets*

PubMed Central

Rhoden, John J.; Dyas, Gregory L.

2016-01-01

Despite the increasing number of multivalent antibodies, bispecific antibodies, fusion proteins, and targeted nanoparticles that have been generated and studied, the mechanism of multivalent binding to cell surface targets is not well understood. Here, we describe a conceptual and mathematical model of multivalent antibody binding to cell surface antigens. Our model predicts that properties beyond 1:1 antibody:antigen affinity to target antigens have a strong influence on multivalent binding. Predicted crucial properties include the structure and flexibility of the antibody construct, the target antigen(s) and binding epitope(s), and the density of antigens on the cell surface. For bispecific antibodies, the ratio of the expression levels of the two target antigens is predicted to be critical to target binding, particularly for the lower expressed of the antigens. Using bispecific antibodies of different valencies to cell surface antigens including MET and EGF receptor, we have experimentally validated our modeling approach and its predictions and observed several nonintuitive effects of avidity related to antigen density, target ratio, and antibody affinity. In some biological circumstances, the effect we have predicted and measured varied from the monovalent binding interaction by several orders of magnitude. Moreover, our mathematical framework affords us a mechanistic interpretation of our observations and suggests strategies to achieve the desired antibody-antigen binding goals. These mechanistic insights have implications in antibody engineering and structure/activity relationship determination in a variety of biological contexts. PMID:27022022

Modeling polyvinyl chloride Plasma Modification by Neural Networks

NASA Astrophysics Data System (ADS)

Wang, Changquan

2018-03-01

Neural networks model were constructed to analyze the connection between dielectric barrier discharge parameters and surface properties of material. The experiment data were generated from polyvinyl chloride plasma modification by using uniform design. Discharge voltage, discharge gas gap and treatment time were as neural network input layer parameters. The measured values of contact angle were as the output layer parameters. A nonlinear mathematical model of the surface modification for polyvinyl chloride was developed based upon the neural networks. The optimum model parameters were obtained by the simulation evaluation and error analysis. The results of the optimal model show that the predicted value is very close to the actual test value. The prediction model obtained here are useful for discharge plasma surface modification analysis.

Predicting nucleic acid binding interfaces from structural models of proteins

PubMed Central

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2011-01-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared to patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. PMID:22086767

Analytical Modeling for Mechanical Strength Prediction with Raman Spectroscopy and Fractured Surface Morphology of Novel Coconut Shell Powder Reinforced: Epoxy Composites

NASA Astrophysics Data System (ADS)

Singh, Savita; Singh, Alok; Sharma, Sudhir Kumar

2017-06-01

In this paper, an analytical modeling and prediction of tensile and flexural strength of three dimensional micro-scaled novel coconut shell powder (CSP) reinforced epoxy polymer composites have been reported. The novel CSP has a specific mixing ratio of different coconut shell particle size. A comparison is made between obtained experimental strength and modified Guth model. The result shows a strong evidence for non-validation of modified Guth model for strength prediction. Consequently, a constitutive modeled equation named Singh model has been developed to predict the tensile and flexural strength of this novel CSP reinforced epoxy composite. Moreover, high resolution Raman spectrum shows that 40 % CSP reinforced epoxy composite has high dielectric constant to become an alternative material for capacitance whereas fractured surface morphology revealed that a strong bonding between novel CSP and epoxy polymer for the application as light weight composite materials in engineering.

Geometric Image Biomarker Changes of the Parotid Gland Are Associated With Late Xerostomia.

PubMed

van Dijk, Lisanne V; Brouwer, Charlotte L; van der Laan, Hans Paul; Burgerhof, Johannes G M; Langendijk, Johannes A; Steenbakkers, Roel J H M; Sijtsema, Nanna M

2017-12-01

To identify a surrogate marker for late xerostomia 12 months after radiation therapy (Xer 12m ), according to information obtained shortly after treatment. Differences in parotid gland (PG) were quantified in image biomarkers (ΔIBMs) before and 6 weeks after radiation therapy in 107 patients. By performing stepwise forward selection, ΔIBMs that were associated with Xer 12m were selected. Subsequently other variables, such as PG dose and acute xerostomia scores, were added to improve the prediction performance. All models were internally validated. Prediction of Xer 12m based on PG surface reduction (ΔPG-surface) was good (area under the receiver operating characteristic curve, 0.82). Parotid gland dose was related to ΔPG-surface (P<.001, R 2  = 0.27). The addition of acute xerostomia scores to the ΔPG-surface improved the prediction of Xer 12m significantly, and vice versa. The final model including ΔPG-surface and acute xerostomia had outstanding performance in predicting Xer 12m early after radiation therapy (area under the receiver operating characteristic curve, 0.90). Parotid gland surface reduction was associated with late xerostomia. The early posttreatment model with ΔPG-surface and acute xerostomia scores can be considered as a surrogate marker for late xerostomia. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

NASA Trapezoidal Wing Computations Including Transition and Advanced Turbulence Modeling

NASA Technical Reports Server (NTRS)

Rumsey, C. L.; Lee-Rausch, E. M.

2012-01-01

Flow about the NASA Trapezoidal Wing is computed with several turbulence models by using grids from the first High Lift Prediction Workshop in an effort to advance understanding of computational fluid dynamics modeling for this type of flowfield. Transition is accounted for in many of the computations. In particular, a recently-developed 4-equation transition model is utilized and works well overall. Accounting for transition tends to increase lift and decrease moment, which improves the agreement with experiment. Upper surface flap separation is reduced, and agreement with experimental surface pressures and velocity profiles is improved. The predicted shape of wakes from upstream elements is strongly influenced by grid resolution in regions above the main and flap elements. Turbulence model enhancements to account for rotation and curvature have the general effect of increasing lift and improving the resolution of the wing tip vortex as it convects downstream. However, none of the models improve the prediction of surface pressures near the wing tip, where more grid resolution is needed.

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

2016-01-01

Model benchmarking allows us to separate uncertainty in model predictions caused 1 by model inputs from uncertainty due to model structural error. We extend this method with a large-sample approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

PubMed Central

Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

2018-01-01

Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. We extend this method with a “large-sample” approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances. PMID:29697706

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions.

PubMed

Nearing, Grey S; Mocko, David M; Peters-Lidard, Christa D; Kumar, Sujay V; Xia, Youlong

2016-03-01

Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. We extend this method with a "large-sample" approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

Modeling sorption of divalent metal cations on hydrous manganese oxide using the diffuse double layer model

USGS Publications Warehouse

Tonkin, J.W.; Balistrieri, L.S.; Murray, J.W.

2004-01-01

Manganese oxides are important scavengers of trace metals and other contaminants in the environment. The inclusion of Mn oxides in predictive models, however, has been difficult due to the lack of a comprehensive set of sorption reactions consistent with a given surface complexation model (SCM), and the discrepancies between published sorption data and predictions using the available models. The authors have compiled a set of surface complexation reactions for synthetic hydrous Mn oxide (HMO) using a two surface site model and the diffuse double layer SCM which complements databases developed for hydrous Fe (III) oxide, goethite and crystalline Al oxide. This compilation encompasses a range of data observed in the literature for the complex HMO surface and provides an error envelope for predictions not well defined by fitting parameters for single or limited data sets. Data describing surface characteristics and cation sorption were compiled from the literature for the synthetic HMO phases birnessite, vernadite and ??-MnO2. A specific surface area of 746 m2g-1 and a surface site density of 2.1 mmol g-1 were determined from crystallographic data and considered fixed parameters in the model. Potentiometric titration data sets were adjusted to a pH1EP value of 2.2. Two site types (???XOH and ???YOH) were used. The fraction of total sites attributed to ???XOH (??) and pKa2 were optimized for each of 7 published potentiometric titration data sets using the computer program FITEQL3.2. pKa2 values of 2.35??0.077 (???XOH) and 6.06??0.040 (???YOH) were determined at the 95% confidence level. The calculated average ?? value was 0.64, with high and low values ranging from 1.0 to 0.24, respectively. pKa2 and ?? values and published cation sorption data were used subsequently to determine equilibrium surface complexation constants for Ba2+, Ca2+, Cd 2+, Co2+, Cu2+, Mg2+, Mn 2+, Ni2+, Pb2+, Sr2+ and Zn 2+. In addition, average model parameters were used to predict additional sorption data for which complementary titration data were not available. The two-site model accounts for variability in the titration data and most metal sorption data are fit well using the pKa2 and ?? values reported above. A linear free energy relationship (LFER) appears to exist for some of the metals; however, redox and cation exchange reactions may limit the prediction of surface complexation constants for additional metals using the LFER. ?? 2003 Elsevier Ltd. All rights reserved.

Transient finite element analysis of electric double layer using Nernst-Planck-Poisson equations with a modified Stern layer.

PubMed

Lim, Jongil; Whitcomb, John; Boyd, James; Varghese, Julian

2007-01-01

A finite element implementation of the transient nonlinear Nernst-Planck-Poisson (NPP) and Nernst-Planck-Poisson-modified Stern (NPPMS) models is presented. The NPPMS model uses multipoint constraints to account for finite ion size, resulting in realistic ion concentrations even at high surface potential. The Poisson-Boltzmann equation is used to provide a limited check of the transient models for low surface potential and dilute bulk solutions. The effects of the surface potential and bulk molarity on the electric potential and ion concentrations as functions of space and time are studied. The ability of the models to predict realistic energy storage capacity is investigated. The predicted energy is much more sensitive to surface potential than to bulk solution molarity.

Modeling laser-induced periodic surface structures: Finite-difference time-domain feedback simulations

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

Skolski, J. Z. P., E-mail: j.z.p.skolski@utwente.nl; Vincenc Obona, J.; Römer, G. R. B. E.

2014-03-14

A model predicting the formation of laser-induced periodic surface structures (LIPSSs) is presented. That is, the finite-difference time domain method is used to study the interaction of electromagnetic fields with rough surfaces. In this approach, the rough surface is modified by “ablation after each laser pulse,” according to the absorbed energy profile, in order to account for inter-pulse feedback mechanisms. LIPSSs with a periodicity significantly smaller than the laser wavelength are found to “grow” either parallel or orthogonal to the laser polarization. The change in orientation and periodicity follow from the model. LIPSSs with a periodicity larger than the wavelengthmore » of the laser radiation and complex superimposed LIPSS patterns are also predicted by the model.« less

Predictability and Quantification of Complex Groundwater Table Dynamics Driven by Irregular Surface Water Fluctuations

NASA Astrophysics Data System (ADS)

Xin, Pei; Wang, Shen S. J.; Shen, Chengji; Zhang, Zeyu; Lu, Chunhui; Li, Ling

2018-03-01

Shallow groundwater interacts strongly with surface water across a quarter of global land area, affecting significantly the terrestrial eco-hydrology and biogeochemistry. We examined groundwater behavior subjected to unimodal impulse and irregular surface water fluctuations, combining physical experiments, numerical simulations, and functional data analysis. Both the experiments and numerical simulations demonstrated a damped and delayed response of groundwater table to surface water fluctuations. To quantify this hysteretic shallow groundwater behavior, we developed a regression model with the Gamma distribution functions adopted to account for the dependence of groundwater behavior on antecedent surface water conditions. The regression model fits and predicts well the groundwater table oscillations resulting from propagation of irregular surface water fluctuations in both laboratory and large-scale aquifers. The coefficients of the Gamma distribution function vary spatially, reflecting the hysteresis effect associated with increased amplitude damping and delay as the fluctuation propagates. The regression model, in a relatively simple functional form, has demonstrated its capacity of reproducing high-order nonlinear effects that underpin the surface water and groundwater interactions. The finding has important implications for understanding and predicting shallow groundwater behavior and associated biogeochemical processes, and will contribute broadly to studies of groundwater-dependent ecology and biogeochemistry.

Surface complexation modeling for predicting solid phase arsenic concentrations in the sediments of the Mississippi River Valley alluvial aquifer, Arkansas, USA

USGS Publications Warehouse

Sharif, M.S.U.; Davis, R.K.; Steele, K.F.; Kim, B.; Hays, P.D.; Kresse, T.M.; Fazio, J.A.

2011-01-01

The potential health impact of As in drinking water supply systems in the Mississippi River Valley alluvial aquifer in the state of Arkansas, USA is significant. In this context it is important to understand the occurrence, distribution and mobilization of As in the Mississippi River Valley alluvial aquifer. Application of surface complexation models (SCMs) to predict the sorption behavior of As and hydrous Fe oxides (HFO) in the laboratory has increased in the last decade. However, the application of SCMs to predict the sorption of As in natural sediments has not often been reported, and such applications are greatly constrained by the lack of site-specific model parameters. Attempts have been made to use SCMs considering a component additivity (CA) approach which accounts for relative abundances of pure phases in natural sediments, followed by the addition of SCM parameters individually for each phase. Although few reliable and internally consistent sorption databases related to HFO exist, the use of SCMs using laboratory-derived sorption databases to predict the mobility of As in natural sediments has increased. This study is an attempt to evaluate the ability of the SCMs using the geochemical code PHREEQC to predict solid phase As in the sediments of the Mississippi River Valley alluvial aquifer in Arkansas. The SCM option of the double-layer model (DLM) was simulated using ferrihydrite and goethite as sorbents quantified from chemical extractions, calculated surface-site densities, published surface properties, and published laboratory-derived sorption constants for the sorbents. The model results are satisfactory for shallow wells (10.6. m below ground surface), where the redox condition is relatively oxic or mildly suboxic. However, for the deep alluvial aquifer (21-36.6. m below ground surface) where the redox condition is suboxic to anoxic, the model results are unsatisfactory. ?? 2011 Elsevier Ltd.

Development of a Pavement Maintenance Management System. Volume 9. Development of Airfield Pavement Performance Prediction Models.

DTIC Science & Technology

1984-05-01

materials, traffic, and climate, were used to develop PCI and key distress prediction models for both asphalt-concrete- and jointed-concrete- surfaced...Predicted PCI for PCC and AC/PCC Pavements Using Model Presented in Section III ...... 35 31 Effect of PCC Thickness on the PCI as a Function of Age...of Corner Breaking Observed vs Predicted Percent of Corner Breaking Using Model Presented in Section III

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.

On the State of Stress and Failure Prediction Near Planetary Surface Loads

NASA Astrophysics Data System (ADS)

Schultz, R. A.

1996-03-01

The state of stress surrounding planetary surface loads has been used extensively to predict failure of surface rocks and to invert this information for effective elastic thickness. As demonstrated previously, however, several factors can be important including an explicit comparison between model stresses and rock strength as well as the magnitude of calculated stress. As re-emphasized below, failure to take stress magnitudes into account can lead to erroneous predictions of near-surface faulting. This abstract results from discussions on graben formation at Fall 1995 AGU.

Comparison of two free-energy expressions and their implications in surface enrichment

NASA Astrophysics Data System (ADS)

Jerry, Rocco A.; Nauman, E. Bruce

1993-08-01

We compare two free-energy expressions, developed by Cohen and Muthukumar [J. Chem. Phys. 90, 5749 (1989)] and by Jerry and Nauman [J. Colloid Interface Sci. 154, 122 (1992)], in terms of their predictions concerning surface enrichment. We show that a term must be added to the former expression so that it may predict the correct dependence of the surface composition on the bulk. The latter expression does predict the correct dependence. We have also derived the quadratic surface-energy contribution from a finite (nonzero) range interaction model.

The remarkable ability of turbulence model equations to describe transition

NASA Technical Reports Server (NTRS)

Wilcox, David C.

1992-01-01

This paper demonstrates how well the k-omega turbulence model describes the nonlinear growth of flow instabilities from laminar flow into the turbulent flow regime. Viscous modifications are proposed for the k-omega model that yield close agreement with measurements and with Direct Numerical Simulation results for channel and pipe flow. These modifications permit prediction of subtle sublayer details such as maximum dissipation at the surface, k approximately y(exp 2) as y approaches 0, and the sharp peak value of k near the surface. With two transition specific closure coefficients, the model equations accurately predict transition for an incompressible flat-plate boundary layer. The analysis also shows why the k-epsilon model is so difficult to use for predicting transition.

Three-dimensional localized coherent structures of surface turbulence: Model validation with experiments and further computations.

PubMed

Demekhin, E A; Kalaidin, E N; Kalliadasis, S; Vlaskin, S Yu

2010-09-01

We validate experimentally the Kapitsa-Shkadov model utilized in the theoretical studies by Demekhin [Phys. Fluids 19, 114103 (2007)10.1063/1.2793148; Phys. Fluids 19, 114104 (2007)]10.1063/1.2793149 of surface turbulence on a thin liquid film flowing down a vertical planar wall. For water at 15° , surface turbulence typically occurs at an inlet Reynolds number of ≃40 . Of particular interest is to assess experimentally the predictions of the model for three-dimensional nonlinear localized coherent structures, which represent elementary processes of surface turbulence. For this purpose we devise simple experiments to investigate the instabilities and transitions leading to such structures. Our experimental results are in good agreement with the theoretical predictions of the model. We also perform time-dependent computations for the formation of coherent structures and their interaction with localized structures of smaller amplitude on the surface of the film.

Computational Fluid Dynamics Simulation of Flows in an Oxidation Ditch Driven by a New Surface Aerator.

PubMed

Huang, Weidong; Li, Kun; Wang, Gan; Wang, Yingzhe

2013-11-01

In this article, we present a newly designed inverse umbrella surface aerator, and tested its performance in driving flow of an oxidation ditch. Results show that it has a better performance in driving the oxidation ditch than the original one with higher average velocity and more uniform flow field. We also present a computational fluid dynamics model for predicting the flow field in an oxidation ditch driven by a surface aerator. The improved momentum source term approach to simulate the flow field of the oxidation ditch driven by an inverse umbrella surface aerator was developed and validated through experiments. Four kinds of turbulent models were investigated with the approach, including the standard k - ɛ model, RNG k - ɛ model, realizable k - ɛ model, and Reynolds stress model, and the predicted data were compared with those calculated with the multiple rotating reference frame approach (MRF) and sliding mesh approach (SM). Results of the momentum source term approach are in good agreement with the experimental data, and its prediction accuracy is better than MRF, close to SM. It is also found that the momentum source term approach has lower computational expenses, is simpler to preprocess, and is easier to use.

Modeling of ESD events from polymeric surfaces

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

Pfeifer, Kent Bryant

2014-03-01

Transient electrostatic discharge (ESD) events are studied to assemble a predictive model of discharge from polymer surfaces. An analog circuit simulation is produced and its response is compared to various literature sources to explore its capabilities and limitations. Results suggest that polymer ESD events can be predicted to within an order of magnitude. These results compare well to empirical findings from other sources having similar reproducibility.

Towards a National Hydrological Forecasting system for Canada : Lessons Learned from the Great Lakes and St. Lawrence Prediction System

NASA Astrophysics Data System (ADS)

Fortin, V.; Durnford, D.; Gaborit, E.; Davison, B.; Dimitrijevic, M.; Matte, P.

2016-12-01

Environment and Climate Change Canada has recently deployed a water cycle prediction system for the Great Lakes and St. Lawrence River. The model domain includes both the Canadian and US portions of the watershed. It provides 84-h forecasts of weather elements, lake level, lake ice cover and surface currents based on two-way coupling of the GEM numerical weather prediction (NWP) model with the NEMO ocean model. Streamflow of all the major tributaries of the Great Lakes and St. Lawrence River are estimated by the WATROUTE routing model, which routes the surface runoff forecasted by GEM's land-surface scheme and assimilates streamflow observations where available. Streamflow forecasts are updated twice daily and are disseminated through an OGC compliant web map service (WMS) and a web feature service (WFS). In this presentation, in addition to describing the system and documenting its forecast skill, we show how it is being used by clients for various environmental prediction applications. We then discuss the importance of two-way coupling, land-surface and hillslope modelling and the impact of horizontal resolution on hydrological prediction skill. In the second portion of the talk, we discuss plans for implementing a similar system at the national scale, using what we have learned in the Great Lakes and St. Lawrence watershed. Early results obtained for the headwaters of the Saskatchewan River as well as for the whole Nelson-Churchill watershed are presented.

Aeroacoustic Analysis of a Simplified Landing Gear

NASA Technical Reports Server (NTRS)

Lockard, David P.; Khorrami, Mehdi, R.; Li, Fei

2004-01-01

A hybrid approach is used to investigate the noise generated by a simplified landing gear without small scale parts such as hydraulic lines and fasteners. The Ffowcs Williams and Hawkings equation is used to predict the noise at far-field observer locations from flow data provided by an unsteady computational fluid dynamics calculation. A simulation with 13 million grid points has been completed, and comparisons are made between calculations with different turbulence models. Results indicate that the turbulence model has a profound effect on the levels and character of the unsteadiness. Flow data on solid surfaces and a set of permeable surfaces surrounding the gear have been collected. Noise predictions using the porous surfaces appear to be contaminated by errors caused by large wake fluctuations passing through the surfaces. However, comparisons between predictions using the solid surfaces with the near-field CFD solution are in good agreement giving confidence in the far-field results.

Experimental evaluation of a mathematical model for predicting transfer efficiency of a high volume-low pressure air spray gun.

PubMed

Tan, Y M; Flynn, M R

2000-10-01

The transfer efficiency of a spray-painting gun is defined as the amount of coating applied to the workpiece divided by the amount sprayed. Characterizing this transfer process allows for accurate estimation of the overspray generation rate, which is important for determining a spray painter's exposure to airborne contaminants. This study presents an experimental evaluation of a mathematical model for predicting the transfer efficiency of a high volume-low pressure spray gun. The effects of gun-to-surface distance and nozzle pressure on the agreement between the transfer efficiency measurement and prediction were examined. Wind tunnel studies and non-volatile vacuum pump oil in place of commercial paint were used to determine transfer efficiency at nine gun-to-surface distances and four nozzle pressure levels. The mathematical model successfully predicts transfer efficiency within the uncertainty limits. The least squares regression between measured and predicted transfer efficiency has a slope of 0.83 and an intercept of 0.12 (R2 = 0.98). Two correction factors were determined to improve the mathematical model. At higher nozzle pressure settings, 6.5 psig and 5.5 psig, the correction factor is a function of both gun-to-surface distance and nozzle pressure level. At lower nozzle pressures, 4 psig and 2.75 psig, gun-to-surface distance slightly influences the correction factor, while nozzle pressure has no discernible effect.

Elucidating Inherent Uncertainties in Data Assimilation for Predictions Incorporating Non-stationary Processes - Focus on Predictive Phenology

NASA Astrophysics Data System (ADS)

Lowman, L.; Barros, A. P.

2017-12-01

Data assimilation (DA) is the widely accepted procedure for estimating parameters within predictive models because of the adaptability and uncertainty quantification offered by Bayesian methods. DA applications in phenology modeling offer critical insights into how extreme weather or changes in climate impact the vegetation life cycle. Changes in leaf onset and senescence, root phenology, and intermittent leaf shedding imply large changes in the surface radiative, water, and carbon budgets at multiple scales. Models of leaf phenology require concurrent atmospheric and soil conditions to determine how biophysical plant properties respond to changes in temperature, light and water demand. Presently, climatological records for fraction of photosynthetically active radiation (FPAR) and leaf area index (LAI), the modelled states indicative of plant phenology, are not available. Further, DA models are typically trained on short periods of record (e.g. less than 10 years). Using limited records with a DA framework imposes non-stationarity on estimated parameters and the resulting predicted model states. This talk discusses how uncertainty introduced by the inherent non-stationarity of the modeled processes propagates through a land-surface hydrology model coupled to a predictive phenology model. How water demand is accounted for in the upscaling of DA model inputs and analysis period serves as a key source of uncertainty in the FPAR and LAI predictions. Parameters estimated from different DA effectively calibrate a plant water-use strategy within the land-surface hydrology model. For example, when extreme droughts are included in the DA period, the plants are trained to uptake water, transpire, and assimilate carbon under favorable conditions and quickly shut down at the onset of water stress.

CONTRIBUTION OF NUTRIENTS AND E. COLI TO SURFACE WATER CONDITION IN THE OZARKS I. USING PARTIAL LEAST SQUARES PREDICTIONS WHEN STANDARD REGRESSION ASSUMPTIONS ARE VIOLATED

EPA Science Inventory

We present here the application of PLS regression to predicting surface water total phosphorous, total ammonia and Escherichia coli from landscape metrics. The amount of variability in surface water constituents explained by each model reflects the composition of the contributi...

A model for the plastic flow of landslides

USGS Publications Warehouse

Savage, William Z.; Smith, William K.

1986-01-01

To further the understanding of the mechanics of landslide flow, we present a model that predicts many of the observed attributes of landslides. The model is based on an integration of the hyperbolic differential equations for stress and velocity fields in a two-dimensional, inclined, semi-infinite half-space of Coulomb plastic material under elevated pore pressure and gravity. Our landslide model predicts commonly observed features. For example, compressive (passive), plug, or extending (active) flow will occur under appropriate longitudinal strain rates. Also, the model predicts that longitudinal stresses increase elliptically with depth to the basal slide plane, and that stress and velocity characteristics, surfaces along which discontinuities in stress and velocity are propagated, are coincident. Finally, the model shows how thrust and normal faults develop at the landslide surface in compressive and extending flow.

Investigation of models for large-scale meteorological prediction experiments

NASA Technical Reports Server (NTRS)

Spar, J.

1973-01-01

Studies are reported of the long term responses of the model atmosphere to anomalies in snow cover and sea surface temperature. An abstract of a previously issued report on the computed response to surface anomalies in a global atmospheric model is presented, and the experiments on the effects of transient sea surface temperature on the Mintz-Arakawa atmospheric model are reported.

Evaluation of an atmospheric model with surface and ABL meteorological data for energy applications in structured areas

NASA Astrophysics Data System (ADS)

Triantafyllou, A. G.; Kalogiros, J.; Krestou, A.; Leivaditou, E.; Zoumakis, N.; Bouris, D.; Garas, S.; Konstantinidis, E.; Wang, Q.

2018-03-01

This paper provides the performance evaluation of the meteorological component of The Air Pollution Model (TAPM), a nestable prognostic model, in predicting meteorological variables in urban areas, for both its surface layer and atmospheric boundary layer (ABL) turbulence parameterizations. The model was modified by incorporating four urban land surface types, replacing the existing single urban surface. Control runs were carried out over the wider area of Kozani, an urban area in NW Greece. The model was evaluated for both surface and ABL meteorological variables by using measurements of near-surface and vertical profiles of wind and temperature. The data were collected by using monitoring surface stations in selected sites as well as an acoustic sounder (SOnic Detection And Ranging (SODAR), up to 300 m above ground) and a radiometer profiler (up to 600 m above ground). The results showed the model demonstrated good performance in predicting the near-surface meteorology in the Kozani region for both a winter and a summer month. In the ABL, the comparison showed that the model's forecasts generally performed well with respect to the thermal structure (temperature profiles and ABL height) but overestimated wind speed at the heights of comparison (mostly below 200 m) up to 3-4 ms-1.

Modeling uranium(VI) adsorption onto montmorillonite under varying carbonate concentrations: A surface complexation model accounting for the spillover effect on surface potential

NASA Astrophysics Data System (ADS)

Tournassat, C.; Tinnacher, R. M.; Grangeon, S.; Davis, J. A.

2018-01-01

The prediction of U(VI) adsorption onto montmorillonite clay is confounded by the complexities of: (1) the montmorillonite structure in terms of adsorption sites on basal and edge surfaces, and the complex interactions between the electrical double layers at these surfaces, and (2) U(VI) solution speciation, which can include cationic, anionic and neutral species. Previous U(VI)-montmorillonite adsorption and modeling studies have typically expanded classical surface complexation modeling approaches, initially developed for simple oxides, to include both cation exchange and surface complexation reactions. However, previous models have not taken into account the unique characteristics of electrostatic surface potentials that occur at montmorillonite edge sites, where the electrostatic surface potential of basal plane cation exchange sites influences the surface potential of neighboring edge sites ('spillover' effect). A series of U(VI) - Na-montmorillonite batch adsorption experiments was conducted as a function of pH, with variable U(VI), Ca, and dissolved carbonate concentrations. Based on the experimental data, a new type of surface complexation model (SCM) was developed for montmorillonite, that specifically accounts for the spillover effect using the edge surface speciation model by Tournassat et al. (2016a). The SCM allows for a prediction of U(VI) adsorption under varying chemical conditions with a minimum number of fitting parameters, not only for our own experimental results, but also for a number of published data sets. The model agreed well with many of these datasets without introducing a second site type or including the formation of ternary U(VI)-carbonato surface complexes. The model predictions were greatly impacted by utilizing analytical measurements of dissolved inorganic carbon (DIC) concentrations in individual sample solutions rather than assuming solution equilibration with a specific partial pressure of CO2, even when the gas phase was laboratory air. Because of strong aqueous U(VI)-carbonate solution complexes, the measurement of DIC concentrations was even important for systems set up in the 'absence' of CO2, due to low levels of CO2 contamination during the experiment.

The influence of open fracture anisotropy on CO2 movement within geological storage complexes

NASA Astrophysics Data System (ADS)

Bond, C. E.; Wightman, R.; Ringrose, P. S.

2012-12-01

Carbon mitigation through the geological storage of carbon dioxide is dependent on the ability of geological formations to store CO2 trapping it within a geological storage complex. Secure long-term containment needs to be demonstrated, due to both political and social drivers, meaning that this containment must be verifiable over periods of 100-105 years. The effectiveness of sub-surface geological storage systems is dependent on trapping CO2 within a volume of rock and is reliant on the integrity of the surrounding rocks, including their chemical and physical properties, to inhibit migration to the surface. Oil and gas reservoir production data, and field evidence show that fracture networks have the potential to act as focused pathways for fluid movement. Fracture networks can allow large volumes of fluid to migrate to the surface within the time scales of interest. In this paper we demonstrate the importance of predicting the effects of fracture networks in storage, using a case study from the In Salah CO2 storage site, and show how the fracture permeability is closely controlled by the stress regime that determines the open fracture network. Our workflow combines well data of imaged fractures, with a discrete fracture network (DFN) model of tectonically induced fractures, within the horizon of interest. The modelled and observed fractures have been compared and combined with present day stress data to predict the open fracture network and its implications for anisotropic movement of CO2 in the sub-surface. The created fracture network model has been used to calculate the 2D permeability tensor for the reservoir for two scenarios: 1) a model in which all fractures are permeable, based on the whole DFN model and 2) those fractures determined to be in dilatational failure under the present day stress regime, a sub-set of the DFN. The resulting permeability anisotropy tensors show distinct anisotropies for the predicted CO2 movement within the reservoir. These predictions have been compared with InSAR imagery of surface uplift, used as an indicator of fluid pressure and movement in the sub-surface, around the CO2 injection wells. The analysis shows that the permeability tensor with the greatest anisotropy, that for the DFN sub-set of open fractures, matches well with the anisotropy in surface uplift imaged by InSAR. We demonstrate that predicting fracture networks alone does not predict fluid movement in the sub-surface, and that fracture permeability is closely controlled by the stress regime that determines the open fracture network. Our results show that a workflow of fracture network prediction combined with present day stress analysis can be used to successfully predict CO2 movement in the sub-surface at an active injection site.

Response surface models for effects of temperature and previous growth sodium chloride on growth kinetics of Salmonella typhimurium on cooked chicken breast.

PubMed

Oscar, T P

1999-12-01

Response surface models were developed and validated for effects of temperature (10 to 40 degrees C) and previous growth NaCl (0.5 to 4.5%) on lag time (lambda) and specific growth rate (mu) of Salmonella Typhimurium on cooked chicken breast. Growth curves for model development (n = 55) and model validation (n = 16) were fit to a two-phase linear growth model to obtain lambda and mu of Salmonella Typhimurium on cooked chicken breast. Response surface models for natural logarithm transformations of lambda and mu as a function of temperature and previous growth NaCl were obtained by regression analysis. Both lambda and mu of Salmonella Typhimurium were affected (P < 0.0001) by temperature but not by previous growth NaCl. Models were validated against data not used in their development. Mean absolute relative error of predictions (model accuracy) was 26.6% for lambda and 15.4% for mu. Median relative error of predictions (model bias) was 0.9% for lambda and 5.2% for mu. Results indicated that the models developed provided reliable predictions of lambda and mu of Salmonella Typhimurium on cooked chicken breast within the matrix of conditions modeled. In addition, results indicated that previous growth NaCl (0.5 to 4.5%) was not a major factor affecting subsequent growth kinetics of Salmonella Typhimurium on cooked chicken breast. Thus, inclusion of previous growth NaCl in predictive models may not significantly improve our ability to predict growth of Salmonella spp. on food subjected to temperature abuse.

Prediction of health effects of cross-border atmospheric pollutants using an aerosol forecast model.

PubMed

Onishi, Kazunari; Sekiyama, Tsuyoshi Thomas; Nojima, Masanori; Kurosaki, Yasunori; Fujitani, Yusuke; Otani, Shinji; Maki, Takashi; Shinoda, Masato; Kurozawa, Youichi; Yamagata, Zentaro

2018-08-01

Health effects of cross-border air pollutants and Asian dust are of significant concern in Japan. Currently, models predicting the arrival of aerosols have not investigated the association between arrival predictions and health effects. We investigated the association between subjective health symptoms and unreleased aerosol data from the Model of Aerosol Species in the Global Atmosphere (MASINGAR) acquired from the Japan Meteorological Agency, with the objective of ascertaining if these data could be applied to predicting health effects. Subjective symptom scores were collected via self-administered questionnaires and, along with modeled surface aerosol concentration data, were used to conduct a risk evaluation using generalized estimating equations between October and November 2011. Altogether, 29 individuals provided 1670 responses. Spearman's correlation coefficients were determined for the relationship between the proportion of the participants reporting the maximum score of two or more for each symptom and the surface concentrations for each considered aerosol species calculated using MASINGAR; the coefficients showed significant intermediate correlations between surface sulfate aerosol concentration and respiratory, throat, and fever symptoms (R = 0.557, 0.454, and 0.470, respectively; p < 0.01). In the general estimation equation (logit link) analyses, a significant linear association of surface sulfate aerosol concentration, with an endpoint determined by reported respiratory symptom scores of two or more, was observed (P trend = 0.001, odds ratio [OR] of the highest quartile [Q4] vs. the lowest [Q1] = 5.31, 95% CI = 2.18 to 12.96), with adjustment for potential confounding. The surface sulfate aerosol concentration was also associated with throat and fever symptoms. In conclusion, our findings suggest that modeled data are potentially useful for predicting health risks of cross-border aerosol arrivals. Copyright © 2018 Elsevier Ltd. All rights reserved.

Molecular surface area based predictive models for the adsorption and diffusion of disperse dyes in polylactic acid matrix.

PubMed

Xu, Suxin; Chen, Jiangang; Wang, Bijia; Yang, Yiqi

2015-11-15

Two predictive models were presented for the adsorption affinities and diffusion coefficients of disperse dyes in polylactic acid matrix. Quantitative structure-sorption behavior relationship would not only provide insights into sorption process, but also enable rational engineering for desired properties. The thermodynamic and kinetic parameters for three disperse dyes were measured. The predictive model for adsorption affinity was based on two linear relationships derived by interpreting the experimental measurements with molecular structural parameters and compensation effect: ΔH° vs. dye size and ΔS° vs. ΔH°. Similarly, the predictive model for diffusion coefficient was based on two derived linear relationships: activation energy of diffusion vs. dye size and logarithm of pre-exponential factor vs. activation energy of diffusion. The only required parameters for both models are temperature and solvent accessible surface area of the dye molecule. These two predictive models were validated by testing the adsorption and diffusion properties of new disperse dyes. The models offer fairly good predictive ability. The linkage between structural parameter of disperse dyes and sorption behaviors might be generalized and extended to other similar polymer-penetrant systems. Copyright © 2015 Elsevier Inc. All rights reserved.

The effect of changes in space shuttle parameters on the NASA/MSFC multilayer diffusion model predictions of surface HCl concentrations

NASA Technical Reports Server (NTRS)

Glasser, M. E.; Rundel, R. D.

1978-01-01

A method for formulating these changes into the model input parameters using a preprocessor program run on a programed data processor was implemented. The results indicate that any changes in the input parameters are small enough to be negligible in comparison to meteorological inputs and the limitations of the model and that such changes will not substantially increase the number of meteorological cases for which the model will predict surface hydrogen chloride concentrations exceeding public safety levels.

Downscaling Satellite Data for Predicting Catchment-scale Root Zone Soil Moisture with Ground-based Sensors and an Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Lin, H.; Baldwin, D. C.; Smithwick, E. A. H.

2015-12-01

Predicting root zone (0-100 cm) soil moisture (RZSM) content at a catchment-scale is essential for drought and flood predictions, irrigation planning, weather forecasting, and many other applications. Satellites, such as the NASA Soil Moisture Active Passive (SMAP), can estimate near-surface (0-5 cm) soil moisture content globally at coarse spatial resolutions. We develop a hierarchical Ensemble Kalman Filter (EnKF) data assimilation modeling system to downscale satellite-based near-surface soil moisture and to estimate RZSM content across the Shale Hills Critical Zone Observatory at a 1-m resolution in combination with ground-based soil moisture sensor data. In this example, a simple infiltration model within the EnKF-model has been parameterized for 6 soil-terrain units to forecast daily RZSM content in the catchment from 2009 - 2012 based on AMSRE. LiDAR-derived terrain variables define intra-unit RZSM variability using a novel covariance localization technique. This method also allows the mapping of uncertainty with our RZSM estimates for each time-step. A catchment-wide satellite-to-surface downscaling parameter, which nudges the satellite measurement closer to in situ near-surface data, is also calculated for each time-step. We find significant differences in predicted root zone moisture storage for different terrain units across the experimental time-period. Root mean square error from a cross-validation analysis of RZSM predictions using an independent dataset of catchment-wide in situ Time-Domain Reflectometry (TDR) measurements ranges from 0.060-0.096 cm3 cm-3, and the RZSM predictions are significantly (p < 0.05) correlated with TDR measurements [r = 0.47-0.68]. The predictive skill of this data assimilation system is similar to the Penn State Integrated Hydrologic Modeling (PIHM) system. Uncertainty estimates are significantly (p < 0.05) correlated to cross validation error during wet and dry conditions, but more so in dry summer seasons. Developing an EnKF-model system that downscales satellite data and predicts catchment-scale RZSM content is especially timely, given the anticipated release of SMAP surface moisture data in 2015.

A validated computational model for the design of surface textures in full-film lubricated sliding

NASA Astrophysics Data System (ADS)

Schuh, Jonathon; Lee, Yong Hoon; Allison, James; Ewoldt, Randy

2016-11-01

Our recent experimental work showed that asymmetry is needed for surface textures to decrease friction in full-film lubricated sliding (thrust bearings) with Newtonian fluids; textures reduce the shear load and produce a separating normal force. The sign of the separating normal force is not predicted by previous 1-D theories. Here we model the flow with the Reynolds equation in cylindrical coordinates, numerically implemented with a pseudo-spectral method. The model predictions match experiments, rationalize the sign of the normal force, and allow for design of surface texture geometry. To minimize sliding friction with angled cylindrical textures, an optimal angle of asymmetry β exists. The optimal angle depends on the film thickness but not the sliding velocity within the applicable range of the model. The model has also been used to optimize generalized surface texture topography while satisfying manufacturability constraints.

An algorithm for modeling entrainment and naturally and chemically dispersed oil droplet size distribution under surface breaking wave conditions.

PubMed

Li, Zhengkai; Spaulding, Malcolm L; French-McCay, Deborah

2017-06-15

A surface oil entrainment model and droplet size model have been developed to estimate the flux of oil under surface breaking waves. Both equations are expressed in dimensionless Weber number (We) and Ohnesorge number (Oh, which explicitly accounts for the oil viscosity, density, and oil-water interfacial tension). Data from controlled lab studies, large-scale wave tank tests, and field observations have been used to calibrate the constants of the two independent equations. Predictions using the new algorithm compared well with the observed amount of oil removed from the surface and the sizes of the oil droplets entrained in the water column. Simulations with the new algorithm, implemented in a comprehensive spill model, show that entrainment rates increase more rapidly with wind speed than previously predicted based on the existing Delvigne and Sweeney's (1988) model, and a quasi-stable droplet size distribution (d<~50μm) is developed in the near surface water. Copyright © 2017 Elsevier Ltd. All rights reserved.

Surface Energy and Mass Balance Model for Greenland Ice Sheet and Future Projections

NASA Astrophysics Data System (ADS)

Liu, Xiaojian

The Greenland Ice Sheet contains nearly 3 million cubic kilometers of glacial ice. If the entire ice sheet completely melted, sea level would raise by nearly 7 meters. There is thus considerable interest in monitoring the mass balance of the Greenland Ice Sheet. Each year, the ice sheet gains ice from snowfall and loses ice through iceberg calving and surface melting. In this thesis, we develop, validate and apply a physics based numerical model to estimate current and future surface mass balance of the Greenland Ice Sheet. The numerical model consists of a coupled surface energy balance and englacial model that is simple enough that it can be used for long time scale model runs, but unlike previous empirical parameterizations, has a physical basis. The surface energy balance model predicts ice sheet surface temperature and melt production. The englacial model predicts the evolution of temperature and meltwater within the ice sheet. These two models can be combined with estimates of precipitation (snowfall) to estimate the mass balance over the Greenland Ice Sheet. We first compare model performance with in-situ observations to demonstrate that the model works well. We next evaluate how predictions are degraded when we statistically downscale global climate data. We find that a simple, nearest neighbor interpolation scheme with a lapse rate correction is able to adequately reproduce melt patterns on the Greenland Ice Sheet. These results are comparable to those obtained using empirical Positive Degree Day (PDD) methods. Having validated the model, we next drove the ice sheet model using the suite of atmospheric model runs available through the CMIP5 atmospheric model inter-comparison, which in turn built upon the RCP 8.5 (business as usual) scenarios. From this exercise we predict how much surface melt production will increase in the coming century. This results in 4-10 cm sea level equivalent, depending on the CMIP5 models. Finally, we try to bound melt water production from CMIP5 data with the model by assuming that the Greenland Ice Sheet is covered in black carbon (lowering the albedo) and perpetually covered by optically thick clouds (increasing long wave radiation). This upper bound roughly triples surface meltwater production, resulting in 30 cm of sea level rise by 2100. These model estimates, combined with prior research suggesting an additional 40-100 cm of sea level rise associated with dynamical discharge, suggest that the Greenland Ice Sheet is poised to contribute significantly to sea level rise in the coming century.

Short-Term Retrospective Land Data Assimilation Schemes

NASA Technical Reports Server (NTRS)

Houser, P. R.; Cosgrove, B. A.; Entin, J. K.; Lettenmaier, D.; ODonnell, G.; Mitchell, K.; Marshall, C.; Lohmann, D.; Schaake, J. C.; Duan, Q.;

Analytical prediction of sub-surface thermal history in translucent tissue phantoms during plasmonic photo-thermotherapy (PPTT).

PubMed

Dhar, Purbarun; Paul, Anup; Narasimhan, Arunn; Das, Sarit K

2016-12-01

Knowledge of thermal history and/or distribution in biological tissues during laser based hyperthermia is essential to achieve necrosis of tumour/carcinoma cells. A semi-analytical model to predict sub-surface thermal distribution in translucent, soft, tissue mimics has been proposed. The model can accurately predict the spatio-temporal temperature variations along depth and the anomalous thermal behaviour in such media, viz. occurrence of sub-surface temperature peaks. Based on optical and thermal properties, the augmented temperature and shift of the peak positions in case of gold nanostructure mediated tissue phantom hyperthermia can be predicted. Employing inverse approach, the absorption coefficient of nano-graphene infused tissue mimics is determined from the peak temperature and found to provide appreciably accurate predictions along depth. Furthermore, a simplistic, dimensionally consistent correlation to theoretically determine the position of the peak in such media is proposed and found to be consistent with experiments and computations. The model shows promise in predicting thermal distribution induced by lasers in tissues and deduction of therapeutic hyperthermia parameters, thereby assisting clinical procedures by providing a priori estimates. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Modeling and Experimental Investigation of the Effects of Antigen Density, Binding Affinity, and Antigen Expression Ratio on Bispecific Antibody Binding to Cell Surface Targets.

PubMed

Rhoden, John J; Dyas, Gregory L; Wroblewski, Victor J

2016-05-20

Despite the increasing number of multivalent antibodies, bispecific antibodies, fusion proteins, and targeted nanoparticles that have been generated and studied, the mechanism of multivalent binding to cell surface targets is not well understood. Here, we describe a conceptual and mathematical model of multivalent antibody binding to cell surface antigens. Our model predicts that properties beyond 1:1 antibody:antigen affinity to target antigens have a strong influence on multivalent binding. Predicted crucial properties include the structure and flexibility of the antibody construct, the target antigen(s) and binding epitope(s), and the density of antigens on the cell surface. For bispecific antibodies, the ratio of the expression levels of the two target antigens is predicted to be critical to target binding, particularly for the lower expressed of the antigens. Using bispecific antibodies of different valencies to cell surface antigens including MET and EGF receptor, we have experimentally validated our modeling approach and its predictions and observed several nonintuitive effects of avidity related to antigen density, target ratio, and antibody affinity. In some biological circumstances, the effect we have predicted and measured varied from the monovalent binding interaction by several orders of magnitude. Moreover, our mathematical framework affords us a mechanistic interpretation of our observations and suggests strategies to achieve the desired antibody-antigen binding goals. These mechanistic insights have implications in antibody engineering and structure/activity relationship determination in a variety of biological contexts. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Forecasting the Northern African Dust Outbreak Towards Europe in April 2011: A Model Intercomparison

NASA Technical Reports Server (NTRS)

Huneeus, N.; Basart, S.; Fiedler, S.; Morcrette, J.-J.; Benedetti, A.; Mulcahy, J.; Terradellas, E.; Pérez García-Pando, C.; Pejanovic, G.; Nickovic, S.

2016-01-01

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 hours using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. Our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.

A physical-based gas-surface interaction model for rarefied gas flow simulation

NASA Astrophysics Data System (ADS)

Liang, Tengfei; Li, Qi; Ye, Wenjing

2018-01-01

Empirical gas-surface interaction models, such as the Maxwell model and the Cercignani-Lampis model, are widely used as the boundary condition in rarefied gas flow simulations. The accuracy of these models in the prediction of macroscopic behavior of rarefied gas flows is less satisfactory in some cases especially the highly non-equilibrium ones. Molecular dynamics simulation can accurately resolve the gas-surface interaction process at atomic scale, and hence can predict accurate macroscopic behavior. They are however too computationally expensive to be applied in real problems. In this work, a statistical physical-based gas-surface interaction model, which complies with the basic relations of boundary condition, is developed based on the framework of the washboard model. In virtue of its physical basis, this new model is capable of capturing some important relations/trends for which the classic empirical models fail to model correctly. As such, the new model is much more accurate than the classic models, and in the meantime is more efficient than MD simulations. Therefore, it can serve as a more accurate and efficient boundary condition for rarefied gas flow simulations.

Combining a Spatial Model and Demand Forecasts to Map Future Surface Coal Mining in Appalachia

PubMed Central

Strager, Michael P.; Strager, Jacquelyn M.; Evans, Jeffrey S.; Dunscomb, Judy K.; Kreps, Brad J.; Maxwell, Aaron E.

2015-01-01

Predicting the locations of future surface coal mining in Appalachia is challenging for a number of reasons. Economic and regulatory factors impact the coal mining industry and forecasts of future coal production do not specifically predict changes in location of future coal production. With the potential environmental impacts from surface coal mining, prediction of the location of future activity would be valuable to decision makers. The goal of this study was to provide a method for predicting future surface coal mining extents under changing economic and regulatory forecasts through the year 2035. This was accomplished by integrating a spatial model with production demand forecasts to predict (1 km2) gridded cell size land cover change. Combining these two inputs was possible with a ratio which linked coal extraction quantities to a unit area extent. The result was a spatial distribution of probabilities allocated over forecasted demand for the Appalachian region including northern, central, southern, and eastern Illinois coal regions. The results can be used to better plan for land use alterations and potential cumulative impacts. PMID:26090883

Predicting nucleic acid binding interfaces from structural models of proteins.

PubMed

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2012-02-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

Using Ground Measurements to Examine the Surface Layer Parameterization Scheme in NCEP GFS

NASA Astrophysics Data System (ADS)

Zheng, W.; Ek, M. B.; Mitchell, K.

2017-12-01

Understanding the behavior and the limitation of the surface layer parameneterization scheme is important for parameterization of surface-atmosphere exchange processes in atmospheric models, accurate prediction of near-surface temperature and identifying the role of different physical processes in contributing to errors. In this study, we examine the surface layer paramerization scheme in the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) using the ground flux measurements including the FLUXNET data. The model simulated surface fluxes, surface temperature and vertical profiles of temperature and wind speed are compared against the observations. The limits of applicability of the Monin-Obukhov similarity theory (MOST), which describes the vertical behavior of nondimensionalized mean flow and turbulence properties within the surface layer, are quantified in daytime and nighttime using the data. Results from unstable regimes and stable regimes are discussed.

Abrasive slurry jet cutting model based on fuzzy relations

NASA Astrophysics Data System (ADS)

Qiang, C. H.; Guo, C. W.

2017-12-01

The cutting process of pre-mixed abrasive slurry or suspension jet (ASJ) is a complex process affected by many factors, and there is a highly nonlinear relationship between the cutting parameters and cutting quality. In this paper, guided by fuzzy theory, the fuzzy cutting model of ASJ was developed. In the modeling of surface roughness, the upper surface roughness prediction model and the lower surface roughness prediction model were established respectively. The adaptive fuzzy inference system combines the learning mechanism of neural networks and the linguistic reasoning ability of the fuzzy system, membership functions, and fuzzy rules are obtained by adaptive adjustment. Therefore, the modeling process is fast and effective. In this paper, the ANFIS module of MATLAB fuzzy logic toolbox was used to establish the fuzzy cutting model of ASJ, which is found to be quite instrumental to ASJ cutting applications.

Molecular dynamics simulation of potentiometric sensor response: the effect of biomolecules, surface morphology and surface charge.

PubMed

Lowe, B M; Skylaris, C-K; Green, N G; Shibuta, Y; Sakata, T

2018-05-10

The silica-water interface is critical to many modern technologies in chemical engineering and biosensing. One technology used commonly in biosensors, the potentiometric sensor, operates by measuring the changes in electric potential due to changes in the interfacial electric field. Predictive modelling of this response caused by surface binding of biomolecules remains highly challenging. In this work, through the most extensive molecular dynamics simulation of the silica-water interfacial potential and electric field to date, we report a novel prediction and explanation of the effects of nano-morphology on sensor response. Amorphous silica demonstrated a larger potentiometric response than an equivalent crystalline silica model due to increased sodium adsorption, in agreement with experiments showing improved sensor response with nano-texturing. We provide proof-of-concept that molecular dynamics can be used as a complementary tool for potentiometric biosensor response prediction. Effects that are conventionally neglected, such as surface morphology, water polarisation, biomolecule dynamics and finite-size effects, are explicitly modelled.

Sorption of uranium (VI) on homoionic sodium smectite experimental study and surface complexation modeling.

PubMed

Korichi, Smain; Bensmaili, Aicha

2009-09-30

This paper is an extension of a previous paper where the natural and purified clay in the homoionic Na form were physico-chemically characterized (doi:10.1016/j.clay.2008.04.014). In this study, the adsorption behavior of U (VI) on a purified Na-smectite suspension is studied using batch adsorption experiments and surface complexation modeling (double layer model). The sorption of uranium was investigated as a function of pH, uranium concentration, solid to liquid ratio, effect of natural organic matter (NOM) and NaNO(3) background electrolyte concentration. Using the MINTEQA2 program, the speciation of uranium was calculated as a function of pH and uranium concentration. Model predicted U (VI) aqueous speciation suggests that important aqueous species in the [U (VI)]=1mg/L and pH range 3-7 including UO(2)(2+), UO(2)OH(+), and (UO(2))(3)(OH)(5)(+). The concentration of UO(2)(2+) decreased and that of (UO(2))(3)(OH)(5)(+) increased with increasing pH. The potentiometric titration values and uptake of uranium in the sodium smectite suspension were simulated by FITEQL 4.0 program using a two sites model, which is composed of silicate and aluminum reaction sites. We compare the acidity constants values obtained by potentiometric titration from the purified sodium smectite with those obtained from single oxides (quartz and alpha-alumina), taking into account the surface heterogeneity and the complex nature of natural colloids. We investigate the uranium sorption onto purified Na-smectite assuming low, intermediate and high edge site surfaces which are estimated from specific surface area percentage. The sorption data is interpreted and modeled as a function of edge site surfaces. A relationship between uranium sorption and total site concentration was confirmed and explained through variation in estimated edge site surface value. The modeling study shows that, the convergence during DLM modeling is related to the best estimation of the edge site surface from the N(2)-BET specific surface area, SSA(BET) (thus, total edge site concentrations). The specific surface area should be at least 80-100m(2)/g for smectite clays in order to reach convergence during the modeling. The range of 10-20% SSA(BET) was used to estimate the values of edge site surfaces that led to the convergence during modeling. An agreement between the experimental data and model predictions is found reasonable when 15% SSA(BET) was used as edge site surface. However, the predicted U (VI) adsorption underestimated and overestimated the experimental observations at the 10 and 20% of the measured SSA(BET), respectively. The dependence of uranium sorption modeling results on specific surface area and edge site surface is useful to describe and predict U (VI) retardation as a function of chemical conditions in the field-scale reactive transport simulations. Therefore this approach can be used in the environmental quality assessment.

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.

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 1: Development of models predicting surface shelter temperatures

NASA Technical Reports Server (NTRS)

Epperson, David L.; Davis, Jerry M.; Bloomfield, Peter; Karl, Thomas R.; Mcnab, Alan L.; Gallo, Kevin P.

1995-01-01

Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate and site-specific data to represent the local landscape. Global monthly mean temperature models were developed using data from over 5000 stations available in the Global Historical Climate Network (GHCN). Monthly maximum, mean, and minimum temperature models for the United States were also developed using data from over 1000 stations available in the U.S. Cooperative (COOP) Network and comparative monthly mean temperature models were developed using over 1150 U.S. stations in the GHCN. Three-, six-, and full-variable models were developed for comparative purposes. Inferences about the variables selected for the various models were easier for the GHCN models, which displayed month-to-month consistency in which variables were selected, than for the COOP models, which were assigned a different list of variables for nearly every month. These and other results suggest that global calibration is preferred because data from the global spectrum of physical processes that control surface temperatures are incorporated in a global model. All of the models that were developed in this study validated relatively well, especially the global models. Recalibration of the models with validation data resulted in only slightly poorer regression statistics, indicating that the calibration list of variables was valid. Predictions using data from the validation dataset in the calibrated equation were better for the GHCN models, and the globally calibrated GHCN models generally provided better U.S. predictions than the U.S.-calibrated COOP models. Overall, the GHCN and COOP models explained approximately 64%-95% of the total variance of surface shelter temperatures, depending on the month and the number of model variables. In addition, root-mean-square errors (rmse's) were over 3 C for GHCN models and over 2 C for COOP models for winter months, and near 2 C for GHCN models and near 1.5 C for COOP models for summer months.

Martian aeolian features and deposits - Comparisons with general circulation model results

NASA Astrophysics Data System (ADS)

Greeley, R.; Skypeck, A.; Pollack, J. B.

1993-02-01

The relationships between near-surface winds and the distribution of wind-related features are investigated by means of a general circulation model of Mars' atmosphere. Predictions of wind surface stress as a function of season and dust optical depth are used to investigate the distribution and orientation of wind streaks, yardangs, and rock abundance on the surface. The global distribution of rocks on the surface correlates well with predicted wind stress, particularly during the dust storm season. The rocky areas are sites of strong winds, suggesting that fine material is swept away by the wind, leaving rocks and coarser material behind.

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

Biophysical Mechanistic Modelling Quantifies the Effects of Plant Traits on Fire Severity: Species, Not Surface Fuel Loads, Determine Flame Dimensions in Eucalypt Forests

PubMed Central

Bedward, Michael; Penman, Trent D.; Doherty, Michael D.; Weber, Rodney O.; Gill, A. Malcolm; Cary, Geoffrey J.

2016-01-01

The influence of plant traits on forest fire behaviour has evolutionary, ecological and management implications, but is poorly understood and frequently discounted. We use a process model to quantify that influence and provide validation in a diverse range of eucalypt forests burnt under varying conditions. Measured height of consumption was compared to heights predicted using a surface fuel fire behaviour model, then key aspects of our model were sequentially added to this with and without species-specific information. Our fully specified model had a mean absolute error 3.8 times smaller than the otherwise identical surface fuel model (p < 0.01), and correctly predicted the height of larger (≥1 m) flames 12 times more often (p < 0.001). We conclude that the primary endogenous drivers of fire severity are the species of plants present rather than the surface fuel load, and demonstrate the accuracy and versatility of the model for quantifying this. PMID:27529789

Biophysical Mechanistic Modelling Quantifies the Effects of Plant Traits on Fire Severity: Species, Not Surface Fuel Loads, Determine Flame Dimensions in Eucalypt Forests.

PubMed

Zylstra, Philip; Bradstock, Ross A; Bedward, Michael; Penman, Trent D; Doherty, Michael D; Weber, Rodney O; Gill, A Malcolm; Cary, Geoffrey J

2016-01-01

The influence of plant traits on forest fire behaviour has evolutionary, ecological and management implications, but is poorly understood and frequently discounted. We use a process model to quantify that influence and provide validation in a diverse range of eucalypt forests burnt under varying conditions. Measured height of consumption was compared to heights predicted using a surface fuel fire behaviour model, then key aspects of our model were sequentially added to this with and without species-specific information. Our fully specified model had a mean absolute error 3.8 times smaller than the otherwise identical surface fuel model (p < 0.01), and correctly predicted the height of larger (≥1 m) flames 12 times more often (p < 0.001). We conclude that the primary endogenous drivers of fire severity are the species of plants present rather than the surface fuel load, and demonstrate the accuracy and versatility of the model for quantifying this.

Evaluation of the land surface water budget in NCEP/NCAR and NCEP/DOE reanalyses using an off-line hydrologic model

NASA Astrophysics Data System (ADS)

Maurer, Edwin P.; O'Donnell, Greg M.; Lettenmaier, Dennis P.; Roads, John O.

2001-08-01

The ability of the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis (NRA1) and the follow-up NCEP/Department of Energy (DOE) reanalysis (NRA2), to reproduce the hydrologic budgets over the Mississippi River basin is evaluated using a macroscale hydrology model. This diagnosis is aided by a relatively unconstrained global climate simulation using the NCEP global spectral model, and a more highly constrained regional climate simulation using the NCEP regional spectral model, both employing the same land surface parameterization (LSP) as the reanalyses. The hydrology model is the variable infiltration capacity (VIC) model, which is forced by gridded observed precipitation and temperature. It reproduces observed streamflow, and by closure is constrained to balance other terms in the surface water and energy budgets. The VIC-simulated surface fluxes therefore provide a benchmark for evaluating the predictions from the reanalyses and the climate models. The comparisons, conducted for the 10-year period 1988-1997, show the well-known overestimation of summer precipitation in the southeastern Mississippi River basin, a consistent overestimation of evapotranspiration, and an underprediction of snow in NRA1. These biases are generally lower in NRA2, though a large overprediction of snow water equivalent exists. NRA1 is subject to errors in the surface water budget due to nudging of modeled soil moisture to an assumed climatology. The nudging and precipitation bias alone do not explain the consistent overprediction of evapotranspiration throughout the basin. Another source of error is the gravitational drainage term in the NCEP LSP, which produces the majority of the model's reported runoff. This may contribute to an overprediction of persistence of surface water anomalies in much of the basin. Residual evapotranspiration inferred from an atmospheric balance of NRA1, which is more directly related to observed atmospheric variables, matches the VIC prediction much more closely than the coupled models. However, the persistence of the residual evapotranspiration is much less than is predicted by the hydrological model or the climate models.

Assessment of Protein Side-Chain Conformation Prediction Methods in Different Residue Environments

PubMed Central

Peterson, Lenna X.; Kang, Xuejiao; Kihara, Daisuke

2016-01-01

Computational prediction of side-chain conformation is an important component of protein structure prediction. Accurate side-chain prediction is crucial for practical applications of protein structure models that need atomic detailed resolution such as protein and ligand design. We evaluated the accuracy of eight side-chain prediction methods in reproducing the side-chain conformations of experimentally solved structures deposited to the Protein Data Bank. Prediction accuracy was evaluated for a total of four different structural environments (buried, surface, interface, and membrane-spanning) in three different protein types (monomeric, multimeric, and membrane). Overall, the highest accuracy was observed for buried residues in monomeric and multimeric proteins. Notably, side-chains at protein interfaces and membrane-spanning regions were better predicted than surface residues even though the methods did not all use multimeric and membrane proteins for training. Thus, we conclude that the current methods are as practically useful for modeling protein docking interfaces and membrane-spanning regions as for modeling monomers. PMID:24619909

A plastic flow model for the Acquara - Vadoncello landslide in Senerchia, Southern Italy

USGS Publications Warehouse

Savage, W.; Wasowski, J.

2006-01-01

A previously developed model for stress and velocity fields in two-dimensional Coulomb plastic materials under self-weight and pore pressure predicts that long, shallow landslides develop slip surfaces that manifest themselves as normal faults and normal fault scarps at the surface in areas of extending flow and as thrust faults and thrust fault scarps at the surface in areas of compressive flow. We have applied this model to describe the geometry of slip surfaces and ground stresses developed during the 1995 reactivation of the Acquara - Vadoncello landslide in Senerchia, southern Italy. This landslide is a long and shallow slide in which regions of compressive and extending flow are clearly identified. Slip surfaces in the main scarp region of the landslide have been reconstructed using surface surveys and subsurface borehole logging and inclinometer observations made during retrogression of the main scarp. Two of the four inferred main scarp slip surfaces are best constrained by field data. Slip surfaces in the toe region are reconstructed in the same way and three of the five inferred slip surfaces are similarly constrained. The location of the basal shear surface of the landslide is inferred from borehole logging and borehole inclinometry. Extensive data on material properties, landslide geometries, and pore pressures collected for the Acquara - Vadoncello landslide give values for cohesion, friction angle, and unit weight, plus average basal shear-surface slopes, and pore-pressures required for modelling slip surfaces and stress fields. Results obtained from the landslide-flow model and the field data show that predicted slip surface shapes are consistent with inferred slip surface shapes in both the extending flow main scarp region and in the compressive flow toe region of the Acquara - Vadoncello landslide. Also predicted stress distributions are found to explain deformation features seen in the toe and main scarp regions of the landslide. ?? 2005 Elsevier B.V. All rights reserved.

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.

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.

Modeling streamflow in a snow-dominated forest watershed using the Water Erosion Prediction Project (WEPP) model

USDA-ARS?s Scientific Manuscript database

The Water Erosion Prediction Project (WEPP) model was originally developed for hillslope and small watershed applications. The model simulates complex interactive processes influencing erosion, such as surface runoff, soil-water changes, vegetation growth and senescence, and snow accumulation and me...

Measurement of deformations of models in a wind tunnel

NASA Astrophysics Data System (ADS)

Charpin, F.; Armand, C.; Selvaggini, R.

Techniques used at the ONERA Modane Center to monitor geometric variations in scale-models in wind tunnel trials are described. The methods include: photography of reflections from mirrors embedded in the model surface; laser-based torsiometry with polarized mirrors embedded in the model surface; predictions of the deformations using numerical codes for the model surface mechanical characteristics and the measured surface stresses; and, use of an optical detector to monitor the position of luminous fiber optic sources emitting from the model surfaces. The data enhance the confidence that the wind tunnel aerodynamic data will correspond with the in-flight performance of full scale flight surfaces.

Surface complexation modeling of Cd(II) sorption to montmorillonite, bacteria, and their composite

NASA Astrophysics Data System (ADS)

Wang, Ning; Du, Huihui; Huang, Qiaoyun; Cai, Peng; Rong, Xingmin; Feng, Xionghan; Chen, Wenli

2016-10-01

Surface complexation modeling (SCM) has emerged as a powerful tool for simulating heavy metal adsorption processes on the surface of soil solid components under different geochemical conditions. The component additivity (CA) approach is one of the strategies that have been widely used in multicomponent systems. In this study, potentiometric titration, isothermal adsorption, zeta potential measurement, and extended X-ray absorption fine-structure (EXAFS) spectra analysis were conducted to investigate Cd adsorption on 2 : 1 clay mineral montmorillonite, on Gram-positive bacteria Bacillus subtilis, and their mineral-organic composite. We developed constant capacitance models of Cd adsorption on montmorillonite, bacterial cells, and mineral-organic composite. The adsorption behavior of Cd on the surface of the composite was well explained by CA-SCM. Some deviations were observed from the model simulations at pH < 5, where the values predicted by the model were lower than the experimental results. The Cd complexes of X2Cd, SOCd+, R-COOCd+, and R-POCd+ were the predominant species on the composite surface over the pH range of 3 to 8. The distribution ratio of the adsorbed Cd between montmorillonite and bacterial fractions in the composite as predicted by CA-SCM closely coincided with the estimated value of EXAFS at pH 6. The model could be useful for the prediction of heavy metal distribution at the interface of multicomponents and their risk evaluation in soils and associated environments.

Mapping the global depth to bedrock for land surface modeling

NASA Astrophysics Data System (ADS)

Shangguan, Wei; Hengl, Tomislav; Mendes de Jesus, Jorge; Yuan, Hua; Dai, Yongjiu

2017-03-01

Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 1,30,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surface reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forest and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250 m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.

Biogeochemical modeling of CO2 and CH4 production in anoxic Arctic soil microcosms

NASA Astrophysics Data System (ADS)

Tang, Guoping; Zheng, Jianqiu; Xu, Xiaofeng; Yang, Ziming; Graham, David E.; Gu, Baohua; Painter, Scott L.; Thornton, Peter E.

2016-09-01

Soil organic carbon turnover to CO2 and CH4 is sensitive to soil redox potential and pH conditions. However, land surface models do not consider redox and pH in the aqueous phase explicitly, thereby limiting their use for making predictions in anoxic environments. Using recent data from incubations of Arctic soils, we extend the Community Land Model with coupled carbon and nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) enables us to approximately describe the observed pH evolution without additional parameterization. Although Fe(III) reduction is normally assumed to compete with methanogenesis, the model predicts that Fe(III) reduction raises the pH from acidic to neutral, thereby reducing environmental stress to methanogens and accelerating methane production when substrates are not limiting. The equilibrium speciation predicts a substantial increase in CO2 solubility as pH increases, and taking into account CO2 adsorption to surface sites of metal oxides further decreases the predicted headspace gas-phase fraction at low pH. Without adequate representation of these speciation reactions, as well as the impacts of pH, temperature, and pressure, the CO2 production from closed microcosms can be substantially underestimated based on headspace CO2 measurements only. Our results demonstrate the efficacy of geochemical models for simulating soil biogeochemistry and provide predictive understanding and mechanistic representations that can be incorporated into land surface models to improve climate predictions.

Predicting surface scatter using a linear systems formulation of non-paraxial scalar diffraction

NASA Astrophysics Data System (ADS)

Krywonos, Andrey

Scattering effects from rough surfaces are non-paraxial diffraction phenomena resulting from random phase variations in the reflected wavefront. The ability to predict these effects is important in a variety of applications including x-ray and EUV imaging, the design of stray light rejection systems, and reflection modeling for rendering realistic scenes and animations of physical objects in computer graphics. Rayleigh-Rice (small perturbation method) and Beckmann-Kirchoff (Kirchhoff approximation) theories are commonly used to predict surface scatter effects. In addition, Harvey and Shack developed a linear systems formulation of surface scatter phenomena in which the scattering behavior is characterized by a surface transfer function. This treatment provided insight and understanding not readily gleaned from the two previous theories, and has been incorporated into a variety of computer software packages (ASAP, Zemax, Tracepro). However, smooth surface and paraxial approximations have severely limited the range of applicability of each of the above theoretical treatments. In this dissertation, a linear systems formulation of non-paraxial scalar diffraction theory is first developed and then applied to sinusoidal phase gratings, resulting in diffraction efficiency predictions far more accurate than those provided by classical scalar theories. The application of the theory to these gratings was motivated by the fact that rough surfaces are frequently modeled as a superposition of sinusoidal surfaces of different amplitudes, periods, and orientations. The application of the non-paraxial scalar diffraction theory to surface scatter phenomena resulted first in a modified Beckmann-Kirchhoff surface scattering model, then a generalized Harvey-Shack theory, both of which produce accurate results for rougher surfaces than the Rayleigh-Rice theory and for larger incident and scattering angles than the classical Beckmann-Kirchhoff theory. These new developments enable the analysis and simplify the understanding of wide-angle scattering behavior from rough surfaces illuminated at large incident angles. In addition, they provide an improved BRDF (Bidirectional Reflectance Distribution Function) model, particularly for the smooth surface inverse scattering problem of determining surface power spectral density (PSD) curves from BRDF measurements.

Simulation of synthetic gecko arrays shearing on rough surfaces

PubMed Central

Gillies, Andrew G.; Fearing, Ronald S.

2014-01-01

To better understand the role of surface roughness and tip geometry in the adhesion of gecko synthetic adhesives, a model is developed that attempts to uncover the relationship between surface feature size and the adhesive terminal feature shape. This model is the first to predict the adhesive behaviour of a plurality of hairs acting in shear on simulated rough surfaces using analytically derived contact models. The models showed that the nanoscale geometry of the tip shape alters the macroscale adhesion of the array of fibres by nearly an order of magnitude, and that on sinusoidal surfaces with amplitudes much larger than the nanoscale features, spatula-shaped features can increase adhesive forces by 2.5 times on smooth surfaces and 10 times on rough surfaces. Interestingly, the summation of the fibres acting in concert shows behaviour much more complex that what could be predicted with the pull-off model of a single fibre. Both the Johnson–Kendall–Roberts and Kendall peel models can explain the experimentally observed frictional adhesion effect previously described in the literature. Similar to experimental results recently reported on the macroscale features of the gecko adhesive system, adhesion drops dramatically when surface roughness exceeds the size and spacing of the adhesive fibrillar features. PMID:24694893

An Assessment of the Predictability of Northern Winter Seasonal Means with the NSIPP 1 AGCM

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Pegion, Philip J.; Schubert, Siegfried D.

2000-01-01

This atlas assesses the predictability of January-February-March (JFM) means using version 1 of the NASA Seasonal-to-Interannual Prediction Project Atmospheric General Circulation Model (the NSIPP 1 AGCM). The AGCM is part of the NSIPP coupled atmosphere-land-ocean model. For these results, the atmosphere was run uncoupled from the ocean, but coupled with an interactive land model. The results are based on 20 ensembles of nine JFM hindcasts for the period 1980-1999, with sea surface temperature (SST) and sea ice specified from observations. The model integrations were started from initial atmospheric conditions (taken from NCEP/NCAR reanalyses) centered on December 15. The analysis focuses on 200 mb height, precipitation, surface temperature, and sea-level pressure. The results address issues of both predictability and forecast skill. Various signal-to-noise measures are computed to demonstrate the potential for skillful prediction on seasonal time scales under the assumption of a perfect model and perfectly known oceanic boundary forcings. The results show that the model produces a realistic ENSO response in both the tropics and extratropics.

Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

PubMed Central

Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

2016-01-01

Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

Nonequilibrium Ablation of Phenolic Impregnated Carbon Ablator

NASA Technical Reports Server (NTRS)

Milos, Frank S.; Chen, Yih K.; Gokcen, Tahir

2012-01-01

In previous work, an equilibrium ablation and thermal response model for Phenolic Impregnated Carbon Ablator was developed. In general, over a wide range of test conditions, model predictions compared well with arcjet data for surface recession, surface temperature, in-depth temperature at multiple thermocouples, and char depth. In this work, additional arcjet tests were conducted at stagnation conditions down to 40 W/sq cm and 1.6 kPa. The new data suggest that nonequilibrium effects become important for ablation predictions at heat flux or pressure below about 80 W/sq cm or 10 kPa, respectively. Modifications to the ablation model to account for nonequilibrium effects are investigated. Predictions of the equilibrium and nonequilibrium models are compared with the arcjet data.

River Discharge and Bathymetry Estimation from Hydraulic Inversion of Surface Currents and Water Surface Elevation Observations

NASA Astrophysics Data System (ADS)

Simeonov, J.; Holland, K. T.

2015-12-01

We developed an inversion model for river bathymetry and discharge estimation based on measurements of surface currents, water surface elevation and shoreline coordinates. The model uses a simplification of the 2D depth-averaged steady shallow water equations based on a streamline following system of coordinates and assumes spatially uniform bed friction coefficient and eddy viscosity. The spatial resolution of the predicted bathymetry is related to the resolution of the surface currents measurements. The discharge is determined by minimizing the difference between the predicted and the measured streamwise variation of the total head. The inversion model was tested using in situ and remote sensing measurements of the Kootenai River east of Bonners Ferry, ID. The measurements were obtained in August 2010 when the discharge was about 223 m3/s and the maximum river depth was about 6.5 m. Surface currents covering a 10 km reach with 8 m spatial resolution were estimated from airborne infrared video and were converted to depth-averaged currents using acoustic Doppler current profiler (ADCP) measurements along eight cross-stream transects. The streamwise profile of the water surface elevation was measured using real-time kinematic GPS from a drifting platform. The value of the friction coefficient was obtained from forward calibration simulations that minimized the difference between the predicted and measured velocity and water level along the river thalweg. The predicted along/cross-channel water depth variation was compared to the depth measured with a multibeam echo sounder. The rms error between the measured and predicted depth along the thalweg was found to be about 60cm and the estimated discharge was 5% smaller than the discharge measured by the ADCP.

Effect of Solvent and Substrate on the Surface Binding Mode of Carboxylate-Functionalized Aromatic Molecules

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

Domenico, Janna; Foster, Michael E.; Spoerke, Erik D.

Here, the efficiency of dye-sensitized solar cells (DSSCs) is strongly influenced by dye molecule orientation and interactions with the substrate. Understanding the factors controlling the surface orientation of sensitizing organic molecules will aid in the improvement of both traditional DSSCs and other devices that integrate molecular linkers at interfaces. Here, we describe a general approach to understand relative dye–substrate orientation and provide analytical expressions predicting orientation. We consider the effects of substrate, solvent, and protonation state on dye molecule orientation. In the absence of solvent, our model predicts that most carboxylic acid-functionalized molecules prefer to lie flat (parallel) on themore » surface, due to van der Waals interactions, as opposed to a tilted orientation with respect to the surface that is favored by covalent bonding of the carboxylic acid group to the substrate. When solvation effects are considered, however, the molecules are predicted to orient perpendicular to the surface. We extend this approach to help understand and guide the orientation of metal–organic framework (MOF) thin-film growth on various metal–oxide substrates. A two-part analytical model is developed on the basis of the results of DFT calculations and ab initio MD simulations that predicts the binding energy of a molecule by chemical and dispersion forces on rutile and anatase TiO 2 surfaces, and quantifies the dye solvation energy for two solvents. The model is in good agreement with the DFT calculations and enables rapid prediction of dye molecule and MOF linker binding preference on the basis of the size of the adsorbing molecule, identity of the surface, and the solvent environment. We establish the threshold molecular size, governing dye molecule orientation, for each condition.« less

Effect of Solvent and Substrate on the Surface Binding Mode of Carboxylate-Functionalized Aromatic Molecules

DOE PAGES

Domenico, Janna; Foster, Michael E.; Spoerke, Erik D.; ...

2018-04-25

Here, the efficiency of dye-sensitized solar cells (DSSCs) is strongly influenced by dye molecule orientation and interactions with the substrate. Understanding the factors controlling the surface orientation of sensitizing organic molecules will aid in the improvement of both traditional DSSCs and other devices that integrate molecular linkers at interfaces. Here, we describe a general approach to understand relative dye–substrate orientation and provide analytical expressions predicting orientation. We consider the effects of substrate, solvent, and protonation state on dye molecule orientation. In the absence of solvent, our model predicts that most carboxylic acid-functionalized molecules prefer to lie flat (parallel) on themore » surface, due to van der Waals interactions, as opposed to a tilted orientation with respect to the surface that is favored by covalent bonding of the carboxylic acid group to the substrate. When solvation effects are considered, however, the molecules are predicted to orient perpendicular to the surface. We extend this approach to help understand and guide the orientation of metal–organic framework (MOF) thin-film growth on various metal–oxide substrates. A two-part analytical model is developed on the basis of the results of DFT calculations and ab initio MD simulations that predicts the binding energy of a molecule by chemical and dispersion forces on rutile and anatase TiO 2 surfaces, and quantifies the dye solvation energy for two solvents. The model is in good agreement with the DFT calculations and enables rapid prediction of dye molecule and MOF linker binding preference on the basis of the size of the adsorbing molecule, identity of the surface, and the solvent environment. We establish the threshold molecular size, governing dye molecule orientation, for each condition.« less

Forced synchronization of large-scale circulation to increase predictability of surface states

NASA Astrophysics Data System (ADS)

Shen, Mao-Lin; Keenlyside, Noel; Selten, Frank; Wiegerinck, Wim; Duane, Gregory

2016-04-01

Numerical models are key tools in the projection of the future climate change. The lack of perfect initial condition and perfect knowledge of the laws of physics, as well as inherent chaotic behavior limit predictions. Conceptually, the atmospheric variables can be decomposed into a predictable component (signal) and an unpredictable component (noise). In ensemble prediction the anomaly of ensemble mean is regarded as the signal and the ensemble spread the noise. Naturally the prediction skill will be higher if the signal-to-noise ratio (SNR) is larger in the initial conditions. We run two ensemble experiments in order to explore a way to reduce the SNR of surface winds and temperature. One ensemble experiment is AGCM with prescribing sea surface temperature (SST); the other is AGCM with both prescribing SST and nudging the high-level temperature and winds to ERA-Interim. Each ensemble has 30 members. Larger SNR is expected and found over the tropical ocean in the first experiment because the tropical circulation is associated with the convection and the associated surface wind convergence as these are to a large extent driven by the SST. However, small SNR is found over high latitude ocean and land surface due to the chaotic and non-synchronized atmosphere states. In the second experiment the higher level temperature and winds are forced to be synchronized (nudged to reanalysis) and hence a larger SNR of surface winds and temperature is expected. Furthermore, different nudging coefficients are also tested in order to understand the limitation of both synchronization of large-scale circulation and the surface states. These experiments will be useful for the developing strategies to synchronize the 3-D states of atmospheric models that can be later used to build a super model.

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

DTIC Science & Technology

2012-09-30

characterization of extratropical storms and extremes and link these to LFV modes. Mingfang Ting, Yochanan Kushnir, Andrew W. Robertson...simulating and predicting a wide range of climate phenomena including ENSO, tropical Atlantic sea surface temperatures (SSTs), storm track variability...into empirical prediction models. Use observations to improve low-order dynamical MJO models. Adam Sobel, Daehyun Kim. Extratropical variability

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;

Study of surface modes on a vibrating electrowetting liquid lens

NASA Astrophysics Data System (ADS)

Strauch, Matthias; Shao, Yifeng; Bociort, Florian; Urbach, H. Paul

2017-10-01

The increased usage of liquid lenses motivates us to investigate surface waves on the liquid's surface. During fast focal switching, the surface waves decrease the imaging quality. We propose a model that describes the surface modes appearing on a liquid lens and predicts the resonance frequencies. The effects of those surface modes on a laser beam are simulated using Fresnel propagation, and the model is verified experimentally.

No Future in the Past? The role of initial topography on landform evolution model predictions

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Coulthard, T. J.; Lowry, J.

2014-12-01

Our understanding of earth surface processes is based on long-term empirical understandings, short-term field measurements as well as numerical models. In particular, numerical landscape evolution models (LEMs) have been developed which have the capability to capture a range of both surface (erosion and deposition), tectonics, as well as near surface or critical zone processes (i.e. pedogenesis). These models have a range of applications for understanding both surface and whole of landscape dynamics through to more applied situations such as degraded site rehabilitation. LEMs are now at the stage of development where if calibrated, can provide some level of reliability. However, these models are largely calibrated based on parameters determined from present surface conditions which are the product of much longer-term geology-soil-climate-vegetation interactions. Here, we assess the effect of the initial landscape dimensions and associated error as well as parameterisation for a potential post-mining landform design. The results demonstrate that subtle surface changes in the initial DEM as well as parameterisation can have a large impact on landscape behaviour, erosion depth and sediment discharge. For example, the predicted sediment output from LEM's is shown to be highly variable even with very subtle changes in initial surface conditions. This has two important implications in that decadal time scale field data is needed to (a) better parameterise models and (b) evaluate their predictions. We question how a LEM using parameters derived from field plots can firstly be employed to examine long-term landscape evolution. Secondly, the potential range of outcomes is examined based on estimated temporal parameter change and thirdly, the need for more detailed and rigorous field data for calibration and validation of these models is discussed.

Influence of yield surface curvature on the macroscopic yielding and ductile failure of isotropic porous plastic materials

NASA Astrophysics Data System (ADS)

Dæhli, Lars Edvard Bryhni; Morin, David; Børvik, Tore; Hopperstad, Odd Sture

2017-10-01

Numerical unit cell models of an approximative representative volume element for a porous ductile solid are utilized to investigate differences in the mechanical response between a quadratic and a non-quadratic matrix yield surface. A Hershey equivalent stress measure with two distinct values of the yield surface exponent is employed as the matrix description. Results from the unit cell calculations are further used to calibrate a heuristic extension of the Gurson model which incorporates effects of the third deviatoric stress invariant. An assessment of the porous plasticity model reveals its ability to describe the unit cell response to some extent, however underestimating the effect of the Lode parameter for the lower triaxiality ratios imposed in this study when compared to unit cell simulations. Ductile failure predictions by means of finite element simulations using a unit cell model that resembles an imperfection band are then conducted to examine how the non-quadratic matrix yield surface influences the failure strain as compared to the quadratic matrix yield surface. Further, strain localization predictions based on bifurcation analyses and imperfection band analyses are undertaken using the calibrated porous plasticity model. These simulations are then compared to the unit cell calculations in order to elucidate the differences between the various modelling strategies. The current study reveals that strain localization analyses using an imperfection band model and a spatially discretized unit cell are in reasonable agreement, while the bifurcation analyses predict higher strain levels at localization. Imperfection band analyses are finally used to calculate failure loci for the quadratic and the non-quadratic matrix yield surface under a wide range of loading conditions. The underlying matrix yield surface is demonstrated to have a pronounced influence on the onset of strain localization.

Space shuttle main engine plume radiation model

NASA Technical Reports Server (NTRS)

Reardon, J. E.; Lee, Y. C.

1978-01-01

The methods are described which are used in predicting the thermal radiation received by space shuttles, from the plumes of the main engines. Radiation to representative surface locations were predicted using the NASA gaseous plume radiation GASRAD program. The plume model is used with the radiative view factor (RAVFAC) program to predict sea level radiation at specified body points. The GASRAD program is described along with the predictions. The RAVFAC model is also discussed.

Image Analysis of a Negatively Curved Graphitic Sheet Model for Amorphous Carbon

NASA Astrophysics Data System (ADS)

Bursill, L. A.; Bourgeois, Laure N.

High-resolution electron micrographs are presented which show essentially curved single sheets of graphitic carbon. Image calculations are then presented for the random surface schwarzite-related model of Townsend et al. (Phys. Rev. Lett. 69, 921-924, 1992). Comparison with experimental images does not rule out the contention that such models, containing surfaces of negative curvature, may be useful for predicting some physical properties of specific forms of nanoporous carbon. Some difficulties of the model predictions, when compared with the experimental images, are pointed out. The range of application of this model, as well as competing models, is discussed briefly.

Development of a Coupled Hydrological/Sediment Yield Model for a Watershed at Regional Level

NASA Technical Reports Server (NTRS)

Rajbhandaril, Narayan; Crosson, William; Tsegaye, Teferi; Coleman, Tommy; Liu, Yaping; Soman, Vishwas

1998-01-01

Development of a hydrologic model for the study of environmental conservation requires a comprehensive understanding of individual-storm affecting hydrologic and sedimentologic processes. The hydrologic models that we are currently coupling are the Simulator for Hydrology and Energy Exchange at the Land Surface (SHEELS) and the Distributed Runoff Model (DRUM). SHEELS runs continuously to estimate surface energy fluxes and sub-surface soil water fluxes, while DRUM operates during and following precipitation events to predict surface runoff and peak flow through channel routing. The lateral re-distribution of surface water determined by DRUM is passed to SHEELS, which then adjusts soil water contents throughout the profile. The model SHEELS is well documented in Smith et al. (1993) and Laymen and Crosson (1995). The model DRUM is well documented in Vieux et al. (1990) and Vieux and Gauer (1994). The coupled hydrologic model, SHEELS/DRUM, does not simulate sedimentologic processes. The simulation of the sedimentologic process is important for environmental conservation planning and management. Therefore, we attempted to develop a conceptual frame work for coupling a sediment yield model with SHEELS/DRUM to estimate individual-storm sediment yield from a watershed at a regional level. The sediment yield model that will be used for this study is the Universal Soil Loss Equation (USLE) with some modifications to enable the model to predict individual-storm sediment yield. The predicted sediment yield does not include wind erosion and erosion caused by irrigation and snow melt. Units used for this study are those given by Foster et al. (1981) for SI units.

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...

Thermal regimes of Rocky Mountain lakes warm with climate change

PubMed Central

Roberts, James J.

2017-01-01

Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade-1 increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans. PMID:28683083

Thermal regimes of Rocky Mountain lakes warm with climate change

USGS Publications Warehouse

Roberts, James J.; Fausch, Kurt D.; Schmidt, Travis S.; Walters, David M.

2017-01-01

Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade-1increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans.

Thermal regimes of Rocky Mountain lakes warm with climate change.

PubMed

Roberts, James J; Fausch, Kurt D; Schmidt, Travis S; Walters, David M

2017-01-01

Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade-1 increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans.

Perceived Surface Slant Is Systematically Biased in the Actively-Generated Optic Flow

PubMed Central

Fantoni, Carlo; Caudek, Corrado; Domini, Fulvio

2012-01-01

Humans make systematic errors in the 3D interpretation of the optic flow in both passive and active vision. These systematic distortions can be predicted by a biologically-inspired model which disregards self-motion information resulting from head movements (Caudek, Fantoni, & Domini 2011). Here, we tested two predictions of this model: (1) A plane that is stationary in an earth-fixed reference frame will be perceived as changing its slant if the movement of the observer's head causes a variation of the optic flow; (2) a surface that rotates in an earth-fixed reference frame will be perceived to be stationary, if the surface rotation is appropriately yoked to the head movement so as to generate a variation of the surface slant but not of the optic flow. Both predictions were corroborated by two experiments in which observers judged the perceived slant of a random-dot planar surface during egomotion. We found qualitatively similar biases for monocular and binocular viewing of the simulated surfaces, although, in principle, the simultaneous presence of disparity and motion cues allows for a veridical recovery of surface slant. PMID:22479473

Advancing land surface model development with satellite-based Earth observations

NASA Astrophysics Data System (ADS)

Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

2017-04-01

The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

Potential predictability of Northern America surface temperature in AGCMs and CGCMs

NASA Astrophysics Data System (ADS)

Tang, Youmin; Chen, Dake; Yan, Xiaoqin

2015-07-01

In this study, the potential predictability of the Northern America (NA) surface air temperature (SAT) was explored using an information-based predictability framework and two multiple model ensemble products: a one-tier prediction by coupled models (T1), and a two-tier prediction by atmospheric models only (T2). Furthermore, the potential predictability was optimally decomposed into different modes for both T1 and T2, by extracting the most predictable structures. Emphasis was placed on the comparison of the predictability between T1 and T2. It was found that the potential predictability of the NA SAT is seasonal and spatially dependent in both T1 and T2. Higher predictability occurs in spring and winter and over the southeastern US and northwestern Canada. There is no significant difference of potential predictability between T1 and T2 for most areas of NA, although T1 has higher potential predictability than T2 in the southeastern US. Both T1 and T2 display similar most predictable components (PrCs) for the NA SAT, characterized by the inter-annual variability mode and the long-term trend mode. The first one is inherent to the tropical Pacific sea surface temperature forcing, such as the El Nino-Southern Oscillation, whereas the second one is closely associated with global warming. In general, the PrC modes can better characterize the predictability in T1 than in T2, in particular for the inter-annual variability mode in the fall. The prediction skill against observations is better measured by the PrC analysis than by principal component analysis for all seasons, indicating the stronger capability of PrCA in extracting prediction targets.

A CONTINUUM HARD-SPHERE MODEL OF PROTEIN ADSORPTION

PubMed Central

Finch, Craig; Clarke, Thomas; Hickman, James J.

2012-01-01

Protein adsorption plays a significant role in biological phenomena such as cell-surface interactions and the coagulation of blood. Two-dimensional random sequential adsorption (RSA) models are widely used to model the adsorption of proteins on solid surfaces. Continuum equations have been developed so that the results of RSA simulations can be used to predict the kinetics of adsorption. Recently, Brownian dynamics simulations have become popular for modeling protein adsorption. In this work a continuum model was developed to allow the results from a Brownian dynamics simulation to be used as the boundary condition in a computational fluid dynamics (CFD) simulation. Brownian dynamics simulations were used to model the diffusive transport of hard-sphere particles in a liquid and the adsorption of the particles onto a solid surface. The configuration of the adsorbed particles was analyzed to quantify the chemical potential near the surface, which was found to be a function of the distance from the surface and the fractional surface coverage. The near-surface chemical potential was used to derive a continuum model of adsorption that incorporates the results from the Brownian dynamics simulations. The equations of the continuum model were discretized and coupled to a CFD simulation of diffusive transport to the surface. The kinetics of adsorption predicted by the continuum model closely matched the results from the Brownian dynamics simulation. This new model allows the results from mesoscale simulations to be incorporated into micro- or macro-scale CFD transport simulations of protein adsorption in practical devices. PMID:23729843

Modeling Surface Growth of Escherichia coli on Agar Plates

PubMed Central

Fujikawa, Hiroshi; Morozumi, Satoshi

2005-01-01

Surface growth of Escherichia coli cells on a membrane filter placed on a nutrient agar plate under various conditions was studied with a mathematical model. The surface growth of bacterial cells showed a sigmoidal curve with time on a semilogarithmic plot. To describe it, a new logistic model that we presented earlier (H. Fujikawa et al., Food Microbiol. 21:501-509, 2004) was modified. Growth curves at various constant temperatures (10 to 34°C) were successfully described with the modified model (model III). Model III gave better predictions of the rate constant of growth and the lag period than a modified Gompertz model and the Baranyi model. Using the parameter values of model III at the constant temperatures, surface growth at various temperatures was successfully predicted. Surface growth curves at various initial cell numbers were also sigmoidal and converged to the same maximum cell numbers at the stationary phase. Surface growth curves at various nutrient levels were also sigmoidal. The maximum cell number and the rate of growth were lower as the nutrient level decreased. The surface growth curve was the same as that in a liquid, except for the large curvature at the deceleration period. These curves were also well described with model III. The pattern of increase in the ATP content of cells grown on a surface was sigmoidal, similar to that for cell growth. We discovered several characteristics of the surface growth of bacterial cells under various growth conditions and examined the applicability of our model to describe these growth curves. PMID:16332768

COSIM: A Finite-Difference Computer Model to Predict Ternary Concentration Profiles Associated With Oxidation and Interdiffusion of Overlay-Coated Substrates

NASA Technical Reports Server (NTRS)

Nesbitt, James A.

2001-01-01

A finite-difference computer program (COSIM) has been written which models the one-dimensional, diffusional transport associated with high-temperature oxidation and interdiffusion of overlay-coated substrates. The program predicts concentration profiles for up to three elements in the coating and substrate after various oxidation exposures. Surface recession due to solute loss is also predicted. Ternary cross terms and concentration-dependent diffusion coefficients are taken into account. The program also incorporates a previously-developed oxide growth and spalling model to simulate either isothermal or cyclic oxidation exposures. In addition to predicting concentration profiles after various oxidation exposures, the program can also be used to predict coating life based on a concentration dependent failure criterion (e.g., surface solute content drops to 2%). The computer code is written in FORTRAN and employs numerous subroutines to make the program flexible and easily modifiable to other coating oxidation problems.

Highly Improved Predictability in the Forecasting of the East Asian Summer Monsoon

NASA Astrophysics Data System (ADS)

Lee, E.; Chase, T. N.; Rajagopalan, B.

2007-12-01

The East Asian summer monsoon greatly influences the lives and property of about a quarter of all the people in the world. However, the predictability of the monsoon is very low in comparison with that of Indian summer monsoon because of the complexity of the system which involves both tropical and sub-tropical climates. Previous monsoon prediction models emphasized ocean factors as the primary monsoon forcing. Here we show that pre-season land surface cover is at least as important as ocean indices. A new statistical forecast model of the East Asian summer monsoon using land cover conditions in addition to ocean heat sources doubles the predictability relative to a model using ocean factors alone. This work highlights the, as yet, undocumented importance of seasonal land cover in monsoon prediction and the role of the biosphere in the climate system as a whole. We also detail the physical mechanisms involved in these land surface forcings.

Towards predictive models for transitionally rough surfaces

NASA Astrophysics Data System (ADS)

Abderrahaman-Elena, Nabil; Garcia-Mayoral, Ricardo

2017-11-01

We analyze and model the previously presented decomposition for flow variables in DNS of turbulence over transitionally rough surfaces. The flow is decomposed into two contributions: one produced by the overlying turbulence, which has no footprint of the surface texture, and one induced by the roughness, which is essentially the time-averaged flow around the surface obstacles, but modulated in amplitude by the first component. The roughness-induced component closely resembles the laminar steady flow around the roughness elements at the same non-dimensional roughness size. For small - yet transitionally rough - textures, the roughness-free component is essentially the same as over a smooth wall. Based on these findings, we propose predictive models for the onset of the transitionally rough regime. Project supported by the Engineering and Physical Sciences Research Council (EPSRC).

Analysis of seismograms from a downhole array in sediments near San Francisco Bay

USGS Publications Warehouse

Joyner, William B.; Warrick, Richard E.; Oliver, Adolph A.

1976-01-01

A four-level downhole array of three-component instruments was established on the southwest shore of San Francisco Bay to monitor the effect of the sediments on low-amplitude seismic ground motion. The deepest instrument is at a depth of 186 meters, two meters below the top of the Franciscan bedrock. Earthquake data from regional distances (29 km ≤ Δ ≤ 485 km) over a wide range of azimuths are compared with the predictions of a simple plane-layered model with material properties independently determined. Spectral ratios between the surface and bedrock computed for the one horizontal component of motion that was analyzed agree rather well with the model predictions; the model predicts the frequencies of the first three peaks within 10 percent in most cases and the height of the peaks within 50 percent in most cases. Surface time histories computed from the theoretical model predict the time variations of amplitude and frequency content reasonably well, but correlations of individual cycles cannot be made between observed and predicted traces.

Applying horizontal diffusion on pressure surface to mesoscale models on terrain-following coordinates

Treesearch

Hann-Ming Henry Juang; Ching-Teng Lee; Yongxin Zhang; Yucheng Song; Ming-Chin Wu; Yi-Leng Chen; Kevin Kodama; Shyh-Chin Chen

2005-01-01

The National Centers for Environmental Prediction regional spectral model and mesoscale spectral model (NCEP RSM/MSM) use a spectral computation on perturbation. The perturbation is defined as a deviation between RSM/MSM forecast value and their outer model or analysis value on model sigma-coordinate surfaces. The horizontal diffusion used in the models applies...

Prediction of lake depth across a 17-state region in the United States

USGS Publications Warehouse

Oliver, Samantha K.; Soranno, Patricia A.; Fergus, C. Emi; Wagner, Tyler; Winslow, Luke A.; Scott, Caren E.; Webster, Katherine E.; Downing, John A.; Stanley, Emily H.

2016-01-01

Lake depth is an important characteristic for understanding many lake processes, yet it is unknown for the vast majority of lakes globally. Our objective was to develop a model that predicts lake depth using map-derived metrics of lake and terrestrial geomorphic features. Building on previous models that use local topography to predict lake depth, we hypothesized that regional differences in topography, lake shape, or sedimentation processes could lead to region-specific relationships between lake depth and the mapped features. We therefore used a mixed modeling approach that included region-specific model parameters. We built models using lake and map data from LAGOS, which includes 8164 lakes with maximum depth (Zmax) observations. The model was used to predict depth for all lakes ≥4 ha (n = 42 443) in the study extent. Lake surface area and maximum slope in a 100 m buffer were the best predictors of Zmax. Interactions between surface area and topography occurred at both the local and regional scale; surface area had a larger effect in steep terrain, so large lakes embedded in steep terrain were much deeper than those in flat terrain. Despite a large sample size and inclusion of regional variability, model performance (R2 = 0.29, RMSE = 7.1 m) was similar to other published models. The relative error varied by region, however, highlighting the importance of taking a regional approach to lake depth modeling. Additionally, we provide the largest known collection of observed and predicted lake depth values in the United States.

Predicting the Best Fit: A Comparison of Response Surface Models for Midazolam and Alfentanil Sedation in Procedures With Varying Stimulation.

PubMed

Liou, Jing-Yang; Ting, Chien-Kun; Mandell, M Susan; Chang, Kuang-Yi; Teng, Wei-Nung; Huang, Yu-Yin; Tsou, Mei-Yung

2016-08-01

Selecting an effective dose of sedative drugs in combined upper and lower gastrointestinal endoscopy is complicated by varying degrees of pain stimulation. We tested the ability of 5 response surface models to predict depth of sedation after administration of midazolam and alfentanil in this complex model. The procedure was divided into 3 phases: esophagogastroduodenoscopy (EGD), colonoscopy, and the time interval between the 2 (intersession). The depth of sedation in 33 adult patients was monitored by Observer Assessment of Alertness/Scores. A total of 218 combinations of midazolam and alfentanil effect-site concentrations derived from pharmacokinetic models were used to test 5 response surface models in each of the 3 phases of endoscopy. Model fit was evaluated with objective function value, corrected Akaike Information Criterion (AICc), and Spearman ranked correlation. A model was arbitrarily defined as accurate if the predicted probability is <0.5 from the observed response. The effect-site concentrations tested ranged from 1 to 76 ng/mL and from 5 to 80 ng/mL for midazolam and alfentanil, respectively. Midazolam and alfentanil had synergistic effects in colonoscopy and EGD, but additivity was observed in the intersession group. Adequate prediction rates were 84% to 85% in the intersession group, 84% to 88% during colonoscopy, and 82% to 87% during EGD. The reduced Greco and Fixed alfentanil concentration required for 50% of the patients to achieve targeted response Hierarchy models performed better with comparable predictive strength. The reduced Greco model had the lowest AICc with strong correlation in all 3 phases of endoscopy. Dynamic, rather than fixed, γ and γalf in the Hierarchy model improved model fit. The reduced Greco model had the lowest objective function value and AICc and thus the best fit. This model was reliable with acceptable predictive ability based on adequate clinical correlation. We suggest that this model has practical clinical value for patients undergoing procedures with varying degrees of stimulation.

Numerical Study for a Large-Volume Droplet on the Dual-Rough Surface: Apparent Contact Angle, Contact Angle Hysteresis, and Transition Barrier.

PubMed

Dong, Jian; Jin, Yanli; Dong, He; Liu, Jiawei; Ye, Senbin

2018-06-26

The profile, apparent contact angle (ACA), contact angle hysteresis (CAH), and wetting state transmission energy barrier (WSTEB) are important static and dynamic properties of a large-volume droplet on the hierarchical surface. Understanding them can provide us with important insights into functional surfaces and promote the application in corresponding areas. In this paper, we establish three theoretical models (models 1-3) and the corresponding numerical methods, which were obtained by the free energy minimization and the nonlinear optimization algorithm, to predict the profile, ACA, CAH, and WSTEB of a large-volume droplet on the horizontal regular dual-rough surface. In consideration of the gravity, the energy barrier on the contact circle, the dual heterogeneous structures and their roughness on the surface, the models are more universal and accurate than the previous models. It showed that the predictions of the models were in good agreement with the results from the experiment or literature. The models are promising to become novel design approaches of functional surfaces, which are frequently applied in microfluidic chips, water self-catchment system, and dropwise condensation heat transfer system.

THE ORIGIN OF THE HOT GAS IN THE GALACTIC HALO: TESTING GALACTIC FOUNTAIN MODELS' X-RAY EMISSION

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

Henley, David B.; Shelton, Robin L.; Kwak, Kyujin

2015-02-20

We test the X-ray emission predictions of galactic fountain models against XMM-Newton measurements of the emission from the Milky Way's hot halo. These measurements are from 110 sight lines, spanning the full range of Galactic longitudes. We find that a magnetohydrodynamical simulation of a supernova-driven interstellar medium, which features a flow of hot gas from the disk to the halo, reproduces the temperature but significantly underpredicts the 0.5-2.0 keV surface brightness of the halo (by two orders of magnitude, if we compare the median predicted and observed values). This is true for versions of the model with and without anmore » interstellar magnetic field. We consider different reasons for the discrepancy between the model predictions and the observations. We find that taking into account overionization in cooled halo plasma, which could in principle boost the predicted X-ray emission, is unlikely in practice to bring the predictions in line with the observations. We also find that including thermal conduction, which would tend to increase the surface brightnesses of interfaces between hot and cold gas, would not overcome the surface brightness shortfall. However, charge exchange emission from such interfaces, not included in the current model, may be significant. The faintness of the model may also be due to the lack of cosmic ray driving, meaning that the model may underestimate the amount of material transported from the disk to the halo. In addition, an extended hot halo of accreted material may be important, by supplying hot electrons that could boost the emission of the material driven out from the disk. Additional model predictions are needed to test the relative importance of these processes in explaining the observed halo emission.« less

The Origin of the Hot Gas in the Galactic Halo: Testing Galactic Fountain Models' X-Ray Emission

NASA Astrophysics Data System (ADS)

Henley, David B.; Shelton, Robin L.; Kwak, Kyujin; Hill, Alex S.; Mac Low, Mordecai-Mark

2015-02-01

We test the X-ray emission predictions of galactic fountain models against XMM-Newton measurements of the emission from the Milky Way's hot halo. These measurements are from 110 sight lines, spanning the full range of Galactic longitudes. We find that a magnetohydrodynamical simulation of a supernova-driven interstellar medium, which features a flow of hot gas from the disk to the halo, reproduces the temperature but significantly underpredicts the 0.5-2.0 keV surface brightness of the halo (by two orders of magnitude, if we compare the median predicted and observed values). This is true for versions of the model with and without an interstellar magnetic field. We consider different reasons for the discrepancy between the model predictions and the observations. We find that taking into account overionization in cooled halo plasma, which could in principle boost the predicted X-ray emission, is unlikely in practice to bring the predictions in line with the observations. We also find that including thermal conduction, which would tend to increase the surface brightnesses of interfaces between hot and cold gas, would not overcome the surface brightness shortfall. However, charge exchange emission from such interfaces, not included in the current model, may be significant. The faintness of the model may also be due to the lack of cosmic ray driving, meaning that the model may underestimate the amount of material transported from the disk to the halo. In addition, an extended hot halo of accreted material may be important, by supplying hot electrons that could boost the emission of the material driven out from the disk. Additional model predictions are needed to test the relative importance of these processes in explaining the observed halo emission.

Topological characterization of antireflective and hydrophobic rough surfaces: are random process theory and fractal modeling applicable?

NASA Astrophysics Data System (ADS)

Borri, Claudia; Paggi, Marco

2015-02-01

The random process theory (RPT) has been widely applied to predict the joint probability distribution functions (PDFs) of asperity heights and curvatures of rough surfaces. A check of the predictions of RPT against the actual statistics of numerically generated random fractal surfaces and of real rough surfaces has been only partially undertaken. The present experimental and numerical study provides a deep critical comparison on this matter, providing some insight into the capabilities and limitations in applying RPT and fractal modeling to antireflective and hydrophobic rough surfaces, two important types of textured surfaces. A multi-resolution experimental campaign using a confocal profilometer with different lenses is carried out and a comprehensive software for the statistical description of rough surfaces is developed. It is found that the topology of the analyzed textured surfaces cannot be fully described according to RPT and fractal modeling. The following complexities emerge: (i) the presence of cut-offs or bi-fractality in the power-law power-spectral density (PSD) functions; (ii) a more pronounced shift of the PSD by changing resolution as compared to what was expected from fractal modeling; (iii) inaccuracy of the RPT in describing the joint PDFs of asperity heights and curvatures of textured surfaces; (iv) lack of resolution-invariance of joint PDFs of textured surfaces in case of special surface treatments, not accounted for by fractal modeling.

Biological Environmental Arctic Project (BEAP) Preliminary Data (Arctic West Summer 1986 Cruise).

DTIC Science & Technology

1986-11-01

predictive model of bioluminescence in near-surface arctic waters . Data were collected during Arctic West Summer 1986 from USCG POLAR STAR (WAGB 10). . %. J...2 20ODISTRIBUTION AVAILABILIT "Y OF ABSTRACT 21 ABSTRACT SECURITY CLASSIFICATION C]UNCLASSIFIED UNLIMITED SAME AS RPT C] DTIC USERS UNCLASSIFIED David...correlates for a predictive model of bioluminescence in near-surface arctic waters . - In previous years, these measurements were conducted from the USCG

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

The additivity model assumed that field-scale reaction properties in a sediment including surface area, reactive site concentration, and reaction rate can be predicted from field-scale grain-size distribution by linearly adding reaction properties estimated in laboratory for individual grain-size fractions. This study evaluated the additivity model in scaling mass transfer-limited, multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment. Experimental data of rate-limited U(VI) desorption in a stirred flow-cell reactor were used to estimate the statistical properties of the rate constants for individual grain-size fractions, which were then used to predict rate-limited U(VI) desorption in the composite sediment. The resultmore » indicated that the additivity model with respect to the rate of U(VI) desorption provided a good prediction of U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel-size fraction (2 to 8 mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

A unified theory for ice vapor growth suitable for cloud models: Testing and implications for cold cloud evolution

NASA Astrophysics Data System (ADS)

Zhang, Chengzhu

A new microphysical model for the vapor growth and aspect ratio evolution of atmospheric ice crystals is presented. The method is based on the adaptive habit model of Chen and Lamb (1994), but is modified to include surface kinetic processes for crystal growth. Inclusion of surface kinetic effects is accomplished with a new theory that accounts for axis dependent growth. Deposition coefficients (growth efficiencies) are predicted for two axis directions based on laboratory-determined parameters for growth initiation (critical supersaturations) on each face. In essence, the new theory extends the adaptive habit approach of Chen and Lamb (1994) to ice saturation states below that of liquid saturation, where Chen and Lamb (1994) is likely most valid. The new model is used to simulate changes in crystal primary habit as a function of temperature and ice supersaturation. Predictions are compared with a detailed hexagonal growth model both in a single particle framework and in a Lagrangian parcel model to indicate the accuracy of the new method. Moreover, predictions of the ratio of the axis deposition coefficients match laboratory-generated data. A parameterization for predicting deposition coefficients is developed for the bulk microphysics frame work in Regional Atmospheric Modeling System (RAMS). Initial eddy-resolving model simulation is conducted to study the effect of surface kinetics on microphysical and dynamical processes in cold cloud development.

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

NASA Technical Reports Server (NTRS)

MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.

2005-01-01

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

Computational Fluid Dynamics Simulation of Flows in an Oxidation Ditch Driven by a New Surface Aerator

PubMed Central

Huang, Weidong; Li, Kun; Wang, Gan; Wang, Yingzhe

2013-01-01

Abstract In this article, we present a newly designed inverse umbrella surface aerator, and tested its performance in driving flow of an oxidation ditch. Results show that it has a better performance in driving the oxidation ditch than the original one with higher average velocity and more uniform flow field. We also present a computational fluid dynamics model for predicting the flow field in an oxidation ditch driven by a surface aerator. The improved momentum source term approach to simulate the flow field of the oxidation ditch driven by an inverse umbrella surface aerator was developed and validated through experiments. Four kinds of turbulent models were investigated with the approach, including the standard k−ɛ model, RNG k−ɛ model, realizable k−ɛ model, and Reynolds stress model, and the predicted data were compared with those calculated with the multiple rotating reference frame approach (MRF) and sliding mesh approach (SM). Results of the momentum source term approach are in good agreement with the experimental data, and its prediction accuracy is better than MRF, close to SM. It is also found that the momentum source term approach has lower computational expenses, is simpler to preprocess, and is easier to use. PMID:24302850

Measured and calculated acoustic attenuation rates of tuned resonator arrays for two surface impedance distribution models with flow

NASA Technical Reports Server (NTRS)

Parrott, Tony L.; Abrahamson, A. Louis; Jones, Michael G.

1988-01-01

An experiment was performed to validate two analytical models for predicting low frequency attenuation of duct liner configurations built from an array of seven resonators that could be individually tuned via adjustable cavity depths. These analytical models had previously been developed for high frequency aero-engine inlet duct liner design. In the low frequency application, the liner surface impedance distribution is unavoidably spatially varying by virtue of available fabrication techniques. The characteristic length of this spatial variation may be a significant fraction of the acoustic wavelength. Comparison of measured and predicted attenuation rates and transmission losses for both modal decomposition and finite element propagation models were in good to excellent agreement for a test frequency range that included the first and second cavity resonance frequencies. This was true for either of two surface impedance distribution modeling procedures used to simplify the impedance boundary conditions. In the presence of mean flow, measurements revealed a fine scale structure of acoustic hot spots in the attenuation and phase profiles. These details were accurately predicted by the finite element model. Since no impedance changes due to mean flow were assumed, it is concluded that this fine scale structure was due to convective effects of the mean flow interacting with the surface impedance nonuniformities.

Effects of modeled tropical sea surface temperature variability on coral reef bleaching predictions

NASA Astrophysics Data System (ADS)

Van Hooidonk, R. J.

2011-12-01

Future widespread coral bleaching and subsequent mortality has been projected with sea surface temperature (SST) data from global, coupled ocean-atmosphere general circulation models (GCMs). While these models possess fidelity in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Niño Southern Oscillation (ENSO) variability. These model weaknesses likely reduce the skill of coral bleaching predictions, but little attention has been paid to the important issue of understanding potential errors and biases, the interaction of these biases with trends and their propagation in predictions. To analyze the relative importance of various types of model errors and biases on coral reef bleaching predictive skill, various intra- and inter-annual frequency bands of observed SSTs were replaced with those frequencies from GCMs 20th century simulations to be included in the Intergovernmental Panel on Climate Change (IPCC) 5th assessment report. Subsequent thermal stress was calculated and predictions of bleaching were made. These predictions were compared with observations of coral bleaching in the period 1982-2007 to calculate skill using an objective measure of forecast quality, the Peirce Skill Score (PSS). This methodology will identify frequency bands that are important to predicting coral bleaching and it will highlight deficiencies in these bands in models. The methodology we describe can be used to improve future climate model derived predictions of coral reef bleaching and it can be used to better characterize the errors and uncertainty in predictions.

A Finite Difference Numerical Model for the Propagation of Finite Amplitude Acoustical Blast Waves Outdoors Over Hard and Porous Surfaces

DTIC Science & Technology

1991-09-01

Difference Numerical Model for the Propagation of Finite Amplitude Acoustical Blast Waves Outdoors Over Hard and Porous Surfaces by Victor W. Sparrow...The nonlinear acoustic propagation effects require a numerical solution in the time domain. To model a porous ground surface, which in the frequency...incident on the hard and porous surfaces were produced. The model predicted that near grazing finite amplitude acoustic blast waves decay with distance

High Resolution Land Surface Modeling with the next generation Land Data Assimilation Systems

NASA Astrophysics Data System (ADS)

Kumar, S. V.; Eylander, J.; Peters-Lidard, C.

2005-12-01

Knowledge of land surface processes is important to many real-world applications such as agricultural production, water resources management, and flood predication. The Air Force Weather Agency (AFWA) has provided the USDA and other customers global soil moisture and temperature data for the past 30 years using the agrometeorological data assimilation model (now called AGRMET), merging atmospheric data. Further, accurate initialization of land surface conditions has been shown to greatly influence and improve weather forecast model and seasonal-to-interannual climate predictions. The AFWA AGRMET model exploits real time precipitation observations and analyses, global forecast model and satellite data to generate global estimates of soil moisture, soil temperature and other land surface states at 48km spatial resolution. However, to truly address the land surface initialization and climate prediction problem, and to mitigate the errors introduced by the differences in spatial scales of models, representations of land surface conditions need to be developed at the same fine scales such as that of cloud resolving models. NASA's Goddard Space Flight Center has developed an offline land data assimilation system known as the Land Information System (LIS) capable of modeling land atmosphere interactions at spatial resolutions as fine as 1km. LIS provides a software architecture that integrates the use of the state of the art land surface models, data assimilation techniques, and high performance computing and data management tools. LIS also employs many high resolution surface parameters such as the NASA Earth Observing System (EOS)-era products. In this study we describe the development of a next generation high resolution land surface modeling and data assimilation system, combining the capabilities of LIS and AGRMET. We investigate the influence of high resolution land surface data and observations on the land surface conditions by comparing with the operational AGRMET outputs.

A spatially distributed model for the dynamic prediction of sediment erosion and transport in mountainous forested watersheds

NASA Astrophysics Data System (ADS)

Doten, Colleen O.; Bowling, Laura C.; Lanini, Jordan S.; Maurer, Edwin P.; Lettenmaier, Dennis P.

2006-04-01

Erosion and sediment transport in a temperate forested watershed are predicted with a new sediment model that represents the main sources of sediment generation in forested environments (mass wasting, hillslope erosion, and road surface erosion) within the distributed hydrology-soil-vegetation model (DHSVM) environment. The model produces slope failures on the basis of a factor-of-safety analysis with the infinite slope model through use of stochastically generated soil and vegetation parameters. Failed material is routed downslope with a rule-based scheme that determines sediment delivery to streams. Sediment from hillslopes and road surfaces is also transported to the channel network. A simple channel routing scheme is implemented to predict basin sediment yield. We demonstrate through an initial application of this model to the Rainy Creek catchment, a tributary of the Wenatchee River, which drains the east slopes of the Cascade Mountains, that the model produces plausible sediment yield and ratios of landsliding and surface erosion when compared to published rates for similar catchments in the Pacific Northwest. A road removal scenario and a basin-wide fire scenario are both evaluated with the model.

Physical re-examination of parameters on a molecular collisions-based diffusion model for diffusivity prediction in polymers.

PubMed

Ohashi, Hidenori; Tamaki, Takanori; Yamaguchi, Takeo

2011-12-29

Molecular collisions, which are the microscopic origin of molecular diffusive motion, are affected by both the molecular surface area and the distance between molecules. Their product can be regarded as the free space around a penetrant molecule defined as the "shell-like free volume" and can be taken as a characteristic of molecular collisions. On the basis of this notion, a new diffusion theory has been developed. The model can predict molecular diffusivity in polymeric systems using only well-defined single-component parameters of molecular volume, molecular surface area, free volume, and pre-exponential factors. By consideration of the physical description of the model, the actual body moved and which neighbor molecules are collided with are the volume and the surface area of the penetrant molecular core. In the present study, a semiempirical quantum chemical calculation was used to calculate both of these parameters. The model and the newly developed parameters offer fairly good predictive ability. © 2011 American Chemical Society

Freeze-cast alumina pore networks: Effects of freezing conditions and dispersion medium

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

Miller, S. M.; Xiao, X.; Faber, K. T.

Alumina ceramics were freeze-cast from water- and camphene-based slurries under varying freezing conditions and examined using X-ray computed tomography (XCT). Pore network characteristics, i.e., porosity, pore size, geometric surface area, and tortuosity, were measured from XCT reconstructions and the data were used to develop a model to predict feature size from processing conditions. Classical solidification theory was used to examine relationships between pore size, temperature gradients, and freezing front velocity. Freezing front velocity was subsequently predicted from casting conditions via the two-phase Stefan problem. Resulting models for water-based samples agreed with solidification-based theories predicting lamellar spacing of binary eutectic alloys,more » and models for camphene-based samples concurred with those for dendritic growth. Relationships between freezing conditions and geometric surface area were also modeled by considering the inverse relationship between pore size and surface area. Tortuosity was determined to be dependent primarily on the type of dispersion medium. (C) 2015 Elsevier Ltd. All rights reserved.« less

Land-atmosphere coupling and climate prediction over the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Williams, Ian N.; Lu, Yaqiong; Kueppers, Lara M.; Riley, William J.; Biraud, Sebastien C.; Bagley, Justin E.; Torn, Margaret S.

2016-10-01

Biases in land-atmosphere coupling in climate models can contribute to climate prediction biases, but land models are rarely evaluated in the context of this coupling. We tested land-atmosphere coupling and explored effects of land surface parameterizations on climate prediction in a single-column version of the National Center for Atmospheric Research Community Earth System Model (CESM1.2.2) and an off-line Community Land Model (CLM4.5). The correlation between leaf area index (LAI) and surface evaporative fraction (ratio of latent to total turbulent heat flux) was substantially underpredicted compared to observations in the U.S. Southern Great Plains, while the correlation between soil moisture and evaporative fraction was overpredicted by CLM4.5. To estimate the impacts of these errors on climate prediction, we modified CLM4.5 by prescribing observed LAI, increasing soil resistance to evaporation, increasing minimum stomatal conductance, and increasing leaf reflectance. The modifications improved the predicted soil moisture-evaporative fraction (EF) and LAI-EF correlations in off-line CLM4.5 and reduced the root-mean-square error in summer 2 m air temperature and precipitation in the coupled model. The modifications had the largest effect on prediction during a drought in summer 2006, when a warm bias in daytime 2 m air temperature was reduced from +6°C to a smaller cold bias of -1.3°C, and a corresponding dry bias in precipitation was reduced from -111 mm to -23 mm. The role of vegetation in droughts and heat waves is underpredicted in CESM1.2.2, and improvements in land surface models can improve prediction of climate extremes.

Building the ensemble flood prediction system by using numerical weather prediction data: Case study in Kinu river basin, Japan

NASA Astrophysics Data System (ADS)

Ishitsuka, Y.; Yoshimura, K.

2016-12-01

Floods have a potential to be a major source of economic or human damage caused by natural disasters. Flood prediction systems were developed all over the world and to treat the uncertainty of the prediction ensemble simulation is commonly adopted. In this study, ensemble flood prediction system using global scale land surface and hydrodynamic model was developed. The system requests surface atmospheric forcing and Land Surface Model, MATSIRO, calculates runoff. Those generated runoff is inputted to hydrodynamic model CaMa-Flood to calculate discharge and flood inundation. CaMa-Flood can simulate flood area and its fraction by introducing floodplain connected to river channel. Forecast leadtime was set 39hours according to forcing data. For the case study, the flood occurred at Kinu river basin, Japan in 2015 was hindcasted. In a 1761 km² Kinu river basin, 3-days accumulated average rainfall was 384mm and over 4000 people was left in the inundated area. Available ensemble numerical weather prediction data at that time was inputted to the system in a resolution of 0.05 degrees and 1hour time step. As a result, the system predicted the flood occurrence by 45% and 84% at 23 and 11 hours before the water level exceeded the evacuation threshold, respectively. Those prediction lead time may provide the chance for early preparation for the floods such as levee reinforcement or evacuation. Adding to the discharge, flood area predictability was also analyzed. Although those models were applied for Japan region, this system can be applied easily to other region or even global scale. The areal flood prediction in meso to global scale would be useful for detecting hot zones or vulnerable areas over each region.

Plant traits determine forest flammability

NASA Astrophysics Data System (ADS)

Zylstra, Philip; Bradstock, Ross

2016-04-01

Carbon and nutrient cycles in forest ecosystems are influenced by their inherent flammability - a property determined by the traits of the component plant species that form the fuel and influence the micro climate of a fire. In the absence of a model capable of explaining the complexity of such a system however, flammability is frequently represented by simple metrics such as surface fuel load. The implications of modelling fire - flammability feedbacks using surface fuel load were examined and compared to a biophysical, mechanistic model (Forest Flammability Model) that incorporates the influence of structural plant traits (e.g. crown shape and spacing) and leaf traits (e.g. thickness, dimensions and moisture). Fuels burn with values of combustibility modelled from leaf traits, transferring convective heat along vectors defined by flame angle and with plume temperatures that decrease with distance from the flame. Flames are re-calculated in one-second time-steps, with new leaves within the plant, neighbouring plants or higher strata ignited when the modelled time to ignition is reached, and other leaves extinguishing when their modelled flame duration is exceeded. The relative influence of surface fuels, vegetation structure and plant leaf traits were examined by comparing flame heights modelled using three treatments that successively added these components within the FFM. Validation was performed across a diverse range of eucalypt forests burnt under widely varying conditions during a forest fire in the Brindabella Ranges west of Canberra (ACT) in 2003. Flame heights ranged from 10 cm to more than 20 m, with an average of 4 m. When modelled from surface fuels alone, flame heights were on average 1.5m smaller than observed values, and were predicted within the error range 28% of the time. The addition of plant structure produced predicted flame heights that were on average 1.5m larger than observed, but were correct 53% of the time. The over-prediction in this case was the result of a small number of large errors, where higher strata such as forest canopy were modelled to ignite but did not. The addition of leaf traits largely addressed this error, so that the mean flame height over-prediction was reduced to 0.3m and the fully parameterised FFM gave correct predictions 62% of the time. When small (<1m) flames were excluded, the fully parameterised model correctly predicted flame heights 12 times more often than could be predicted using surface fuels alone, and the Mean Absolute Error was 4 times smaller. The inadequate consideration of plant traits within a mechanistic framework introduces significant error to forest fire behaviour modelling. The FFM provides a solution to this, and an avenue by which plant trait information can be used to better inform Global Vegetation Models and decision-making tools used to mitigate the impacts of fire.

The impact of Surface Wind Velocity Data Assimilation on the Predictability of Plume Advection in the Lower Troposphere

NASA Astrophysics Data System (ADS)

Sekiyama, Thomas; Kajino, Mizuo; Kunii, Masaru

2017-04-01

The authors investigated the impact of surface wind velocity data assimilation on the predictability of plume advection in the lower troposphere exploiting the radioactive cesium emitted by the Fukushima nuclear accident in March 2011 as an atmospheric tracer. It was because the radioactive cesium plume was dispersed from the sole point source exactly placed at the Fukushima Daiichi Nuclear Power Plant and its surface concentration was measured at many locations with a high frequency and high accuracy. We used a non-hydrostatic regional weather prediction model with a horizontal resolution of 3 km, which was coupled with an ensemble Kalman filter data assimilation system in this study, to simulate the wind velocity and plume advection. The main module of this weather prediction model has been developed and used operationally by the Japan Meteorological Agency (JMA) since before March 2011. The weather observation data assimilated into the model simulation were provided from two data resources; [#1] the JMA observation archives collected for numerical weather predictions (NWPs) and [#2] the land-surface wind velocity data archived by the JMA surface weather observation network. The former dataset [#1] does not contain land-surface wind velocity observations because their spatial representativeness is relatively small and therefore the land-surface wind velocity data assimilation normally deteriorates the more than one day NWP performance. The latter dataset [#2] is usually used for real-time weather monitoring and never used for the data assimilation of more than one day NWPs. We conducted two experiments (STD and TEST) to reproduce the radioactive cesium plume behavior for 48 hours from 12UTC 14 March to 12UTC 16 March 2011 over the land area of western Japan. The STD experiment was performed to replicate the operational NWP using only the #1 dataset, not assimilating land-surface wind observations. In contrast, the TEST experiment was performed assimilating both the #1 dataset and the #2 dataset including land-surface wind observations measured at more than 200 stations in the model domain. The meteorological boundary conditions for both the experiments were imported from the JMA operational global NWP model results. The modeled radioactive cesium concentrations were examined for plume arrival timing at each observatory comparing with the hourly-measured "suspended particulate matter" filter tape's cesium concentrations retrieved by Tsuruta et al. at more than 40 observatories. The averaged difference of the plume arrival times at 40 observatories between the observational reality and the STD experiment was 82.0 minutes; at this time, the forecast period was 13 hours on average. Meanwhile, The averaged difference of the TEST experiment was 72.8 minutes, which was smaller than that of the STD experiment with a statistical significance of 99.2 %. In summary, the land-surface wind velocity data assimilation improves the predictability of plume advection in the lower troposphere at least in the case of wintertime air pollution over complex terrain. We need more investigation into the data assimilation impact of land-surface weather observations on the predictability of pollutant dispersion especially in the planetary boundary layer.

Initialization shock in decadal hindcasts due to errors in wind stress over the tropical Pacific

NASA Astrophysics Data System (ADS)

Pohlmann, Holger; Kröger, Jürgen; Greatbatch, Richard J.; Müller, Wolfgang A.

2017-10-01

Low prediction skill in the tropical Pacific is a common problem in decadal prediction systems, especially for lead years 2-5 which, in many systems, is lower than in uninitialized experiments. On the other hand, the tropical Pacific is of almost worldwide climate relevance through its teleconnections with other tropical and extratropical regions and also of importance for global mean temperature. Understanding the causes of the reduced prediction skill is thus of major interest for decadal climate predictions. We look into the problem of reduced prediction skill by analyzing the Max Planck Institute Earth System Model (MPI-ESM) decadal hindcasts for the fifth phase of the Climate Model Intercomparison Project and performing a sensitivity experiment in which hindcasts are initialized from a model run forced only by surface wind stress. In both systems, sea surface temperature variability in the tropical Pacific is successfully initialized, but most skill is lost at lead years 2-5. Utilizing the sensitivity experiment enables us to pin down the reason for the reduced prediction skill in MPI-ESM to errors in wind stress used for the initialization. A spurious trend in the wind stress forcing displaces the equatorial thermocline in MPI-ESM unrealistically. When the climate model is then switched into its forecast mode, the recovery process triggers artificial El Niño and La Niña events at the surface. Our results demonstrate the importance of realistic wind stress products for the initialization of decadal predictions.

Evaluation of the AnnAGNPS model for predicting runoff and sediment yield in a small Mediterranean agricultural watershed in Navarre (Spain)

USDA-ARS?s Scientific Manuscript database

AnnAGNPS (Annualized Agricultural Non-Point Source Pollution Model) is a system of computer models developed to predict non-point source pollutant loadings within agricultural watersheds. It contains a daily time step distributed parameter continuous simulation surface runoff model designed to assis...

Subtypes of Developmental Dyslexia: Testing the Predictions of the Dual-Route and Connectionist Frameworks

ERIC Educational Resources Information Center

Peterson, Robin L.; Pennington, Bruce F.; Olson, Richard K.

2013-01-01

We investigated the phonological and surface subtypes of developmental dyslexia in light of competing predictions made by two computational models of single word reading, the Dual-Route Cascaded Model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) and Harm and Seidenberg's connectionist model (HS model; Harm & Seidenberg, 1999). The…

The Minimum-Mass Surface Density of the Solar Nebula using the Disk Evolution Equation

NASA Technical Reports Server (NTRS)

Davis, Sanford S.

2005-01-01

The Hayashi minimum-mass power law representation of the pre-solar nebula (Hayashi 1981, Prog. Theo. Phys.70,35) is revisited using analytic solutions of the disk evolution equation. A new cumulative-planetary-mass-model (an integrated form of the surface density) is shown to predict a smoother surface density compared with methods based on direct estimates of surface density from planetary data. First, a best-fit transcendental function is applied directly to the cumulative planetary mass data with the surface density obtained by direct differentiation. Next a solution to the time-dependent disk evolution equation is parametrically adapted to the planetary data. The latter model indicates a decay rate of r -1/2 in the inner disk followed by a rapid decay which results in a sharper outer boundary than predicted by the minimum mass model. The model is shown to be a good approximation to the finite-size early Solar Nebula and by extension to extra solar protoplanetary disks.

Sensitivity of two dispersion models (AERMOD and ISCST3) to input parameters for a rural ground-level area source.

PubMed

Faulkner, William B; Shaw, Bryan W; Grosch, Tom

2008-10-01

As of December 2006, the American Meteorological Society/U.S. Environmental Protection Agency (EPA) Regulatory Model with Plume Rise Model Enhancements (AERMOD-PRIME; hereafter AERMOD) replaced the Industrial Source Complex Short Term Version 3 (ISCST3) as the EPA-preferred regulatory model. The change from ISCST3 to AERMOD will affect Prevention of Significant Deterioration (PSD) increment consumption as well as permit compliance in states where regulatory agencies limit property line concentrations using modeling analysis. Because of differences in model formulation and the treatment of terrain features, one cannot predict a priori whether ISCST3 or AERMOD will predict higher or lower pollutant concentrations downwind of a source. The objectives of this paper were to determine the sensitivity of AERMOD to various inputs and compare the highest downwind concentrations from a ground-level area source (GLAS) predicted by AERMOD to those predicted by ISCST3. Concentrations predicted using ISCST3 were sensitive to changes in wind speed, temperature, solar radiation (as it affects stability class), and mixing heights below 160 m. Surface roughness also affected downwind concentrations predicted by ISCST3. AERMOD was sensitive to changes in albedo, surface roughness, wind speed, temperature, and cloud cover. Bowen ratio did not affect the results from AERMOD. These results demonstrate AERMOD's sensitivity to small changes in wind speed and surface roughness. When AERMOD is used to determine property line concentrations, small changes in these variables may affect the distance within which concentration limits are exceeded by several hundred meters.

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

Tang, Guoping; Zheng, Jianqiu; Xu, Xiaofeng

Soil organic carbon turnover to CO 2 and CH 4 is sensitive to soil redox potential and pH conditions. But, land surface models do not consider redox and pH in the aqueous phase explicitly, thereby limiting their use for making predictions in anoxic environments. Using recent data from incubations of Arctic soils, we extend the Community Land Model with coupled carbon and nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) enables us to approximatelymore » describe the observed pH evolution without additional parameterization. Though Fe(III) reduction is normally assumed to compete with methanogenesis, the model predicts that Fe(III) reduction raises the pH from acidic to neutral, thereby reducing environmental stress to methanogens and accelerating methane production when substrates are not limiting. Furthermore, the equilibrium speciation predicts a substantial increase in CO 2 solubility as pH increases, and taking into account CO 2 adsorption to surface sites of metal oxides further decreases the predicted headspace gas-phase fraction at low pH. Without adequate representation of these speciation reactions, as well as the impacts of pH, temperature, and pressure, the CO 2 production from closed microcosms can be substantially underestimated based on headspace CO 2 measurements only. Our results demonstrate the efficacy of geochemical models for simulating soil biogeochemistry and provide predictive understanding and mechanistic representations that can be incorporated into land surface models to improve climate predictions.« less

Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture

USDA-ARS?s Scientific Manuscript database

This paper examines the potential for improving Soil and Water Assessment Tool (SWAT) hydrologic predictions within the 341 km2 Cobb Creek Watershed in southwestern Oklahoma through the assimilation of surface soil moisture observations using an Ensemble Kalman filter (EnKF). In a series of synthet...

A unifying model for adsorption and nucleation of vapors on solid surfaces.

PubMed

Laaksonen, Ari

2015-04-23

Vapor interaction with solid surfaces is traditionally described with adsorption isotherms in the undersaturated regime and with heterogeneous nucleation theory in the supersaturated regime. A class of adsorption isotherms is based on the idea of vapor molecule clustering around so-called active sites. However, as the isotherms do not account for the surface curvature effects of the clusters, they predict an infinitely thick adsorption layer at saturation and do not recognize the existence of the supersaturated regime. The classical heterogeneous nucleation theory also builds on the idea of cluster formation, but describes the interactions between the surface and the cluster with a single parameter, the contact angle, which provides limited information compared with adsorption isotherms. Here, a new model of vapor adsorption on nonporous solid surfaces is derived. The basic assumption is that adsorption proceeds via formation of molecular clusters, modeled as liquid caps. The equilibrium of the individual clusters with the vapor phase is described with the Frenkel-Halsey-Hill (FHH) adsorption theory modified with the Kelvin equation that corrects for the curvature effect on vapor pressure. The new model extends the FHH adsorption isotherm to be applicable both at submonolayer surface coverages and at supersaturated conditions. It shows good agreement with experimental adsorption data from 12 different adsorbent-adsorbate systems. The model predictions are also compared against heterogeneous nucleation data, and they show much better agreement than predictions of the classical heterogeneous nucleation theory.

Forecasting the northern African dust outbreak towards Europe in April 2011: A model intercomparison

DOE PAGES

Huneeus, N.; Basart, S.; Fiedler, S.; ...

2016-04-21

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 h using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distributionmore » was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. In this paper, our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.« less

Does the uncertainty in the representation of terrestrial water flows affect precipitation predictability? A WRF-Hydro ensemble analysis for Central Europe

NASA Astrophysics Data System (ADS)

Arnault, Joel; Rummler, Thomas; Baur, Florian; Lerch, Sebastian; Wagner, Sven; Fersch, Benjamin; Zhang, Zhenyu; Kerandi, Noah; Keil, Christian; Kunstmann, Harald

2017-04-01

Precipitation predictability can be assessed by the spread within an ensemble of atmospheric simulations being perturbed in the initial, lateral boundary conditions and/or modeled processes within a range of uncertainty. Surface-related processes are more likely to change precipitation when synoptic forcing is weak. This study investigates the effect of uncertainty in the representation of terrestrial water flows on precipitation predictability. The tools used for this investigation are the Weather Research and Forecasting (WRF) model and its hydrologically-enhanced version WRF-Hydro, applied over Central Europe during April-October 2008. The WRF grid is that of COSMO-DE, with a resolution of 2.8 km. In WRF-Hydro, the WRF grid is coupled with a sub-grid at 280 m resolution to resolve lateral terrestrial water flows. Vertical flow uncertainty is considered by modifying the parameter controlling the partitioning between surface runoff and infiltration in WRF, and horizontal flow uncertainty is considered by comparing WRF with WRF-Hydro. Precipitation predictability is deduced from the spread of an ensemble based on three turbulence parameterizations. Model results are validated with E-OBS precipitation and surface temperature, ESA-CCI soil moisture, FLUXNET-MTE surface evaporation and GRDC discharge. It is found that the uncertainty in the representation of terrestrial water flows is more likely to significantly affect precipitation predictability when surface flux spatial variability is high. In comparison to the WRF ensemble, WRF-Hydro slightly improves the adjusted continuous ranked probability score of daily precipitation. The reproduction of observed daily discharge with Nash-Sutcliffe model efficiency coefficients up to 0.91 demonstrates the potential of WRF-Hydro for flood forecasting.

Selection for the best ETS (error, trend, seasonal) model to forecast weather in the Aceh Besar District

NASA Astrophysics Data System (ADS)

Amora Jofipasi, Chesilia; Miftahuddin; Hizir

2018-05-01

Weather is a phenomenon that occurs in certain areas that indicate a change in natural activity. Weather can be predicted using data in previous periods over a period. The purpose of this study is to get the best ETS model to predict the weather in Aceh Besar. The ETS model is a time series univariate forecasting method; its use focuses on trend and seasonal components. The data used are air temperature, dew point, sea level pressure, station pressure, visibility, wind speed, and sea surface temperature from January 2006 to December 2016. Based on AIC, AICc and BIC the smallest values obtained the conclusion that the ETS (M, N, A) is used to predict air temperature, and sea surface temperature, ETS (A, N, A) is used to predict dew point, sea level pressure and station pressure, ETS (A, A, N) is used to predict visibility, and ETS (A, N, N) is used to predict wind speed.

Surface tension driven flow in glass melts and model fluids

NASA Technical Reports Server (NTRS)

Mcneil, T. J.; Cole, R.; Subramanian, R. S.

1982-01-01

Surface tension driven flow has been investigated analytically and experimentally using an apparatus where a free column of molten glass or model fluids was supported at its top and bottom faces by solid surfaces. The glass used in the experiments was sodium diborate, and the model fluids were silicone oils. In both the model fluid and glass melt experiments, conclusive evidence was obtained to prove that the observed flow was driven primarily by surface tension forces. The experimental observations are in qualitative agreement with predictions from the theoretical model.

A Theoretical Model for Predicting Fracture Strength and Critical Flaw Size of the ZrB2-ZrC Composites at High Temperatures

NASA Astrophysics Data System (ADS)

Wang, Ruzhuan; Li, Xiaobo; Wang, Jing; Jia, Bi; Li, Weiguo

2018-06-01

This work shows a new rational theoretical model for quantitatively predicting fracture strength and critical flaw size of the ZrB2-ZrC composites at different temperatures, which is based on a new proposed temperature dependent fracture surface energy model and the Griffith criterion. The fracture model takes into account the combined effects of temperature and damage terms (surface flaws and internal flaws) with no any fitting parameters. The predictions of fracture strength and critical flaw size of the ZrB2-ZrC composites at high temperatures agree well with experimental data. Then using the theoretical method, the improvement and design of materials are proposed. The proposed model can be used to predict the fracture strength, find the critical flaw and study the effects of microstructures on the fracture mechanism of the ZrB2-ZrC composites at high temperatures, which thus could become a potential convenient, practical and economical technical means for predicting fracture properties and material design.

[Application of three compartment model and response surface model to clinical anesthesia using Microsoft Excel].

PubMed

Abe, Eiji; Abe, Mari

2011-08-01

With the spread of total intravenous anesthesia, clinical pharmacology has become more important. We report Microsoft Excel file applying three compartment model and response surface model to clinical anesthesia. On the Microsoft Excel sheet, propofol, remifentanil and fentanyl effect-site concentrations are predicted (three compartment model), and probabilities of no response to prodding, shaking, surrogates of painful stimuli and laryngoscopy are calculated using predicted effect-site drug concentration. Time-dependent changes in these calculated values are shown graphically. Recent development in anesthetic drug interaction studies are remarkable, and its application to clinical anesthesia with this Excel file is simple and helpful for clinical anesthesia.

Structure and dynamics of microbe-exuded polymers and their interactions with calcite surfaces.

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

Cygan, Randall Timothy; Mitchell, Ralph; Perry, Thomas D.

2005-12-01

Cation binding by polysaccharides is observed in many environments and is important for predictive environmental modeling, and numerous industrial and food technology applications. The complexities of these organo-cation interactions are well suited to predictive molecular modeling studies for investigating the roles of conformation and configuration of polysaccharides on cation binding. In this study, alginic acid was chosen as a model polymer and representative disaccharide and polysaccharide subunits were modeled. The ability of disaccharide subunits to bind calcium and to associate with the surface of calcite was investigated. The findings were extended to modeling polymer interactions with calcium ions.

Optimizing Hyperspectral Imagery Anomaly Detection through Robust Parameter Design

DTIC Science & Technology

2011-10-01

72 3.2.1 Standard RSM Model ( y (1)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 3.2.2 RPD Model Including N ×N ( y (2...LT surface plot for y (1) model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 3.6. LT surface plot for y (2) model...88 3.12. AutoGAD y (1) residual versus predicted plot. . . . . . . . . . . . . . . . . . . . . . . . 96 3.13

The impact of surface area, volume, curvature, and Lennard-Jones potential to solvation modeling.

PubMed

Nguyen, Duc D; Wei, Guo-Wei

2017-01-05

This article explores the impact of surface area, volume, curvature, and Lennard-Jones (LJ) potential on solvation free energy predictions. Rigidity surfaces are utilized to generate robust analytical expressions for maximum, minimum, mean, and Gaussian curvatures of solvent-solute interfaces, and define a generalized Poisson-Boltzmann (GPB) equation with a smooth dielectric profile. Extensive correlation analysis is performed to examine the linear dependence of surface area, surface enclosed volume, maximum curvature, minimum curvature, mean curvature, and Gaussian curvature for solvation modeling. It is found that surface area and surfaces enclosed volumes are highly correlated to each other's, and poorly correlated to various curvatures for six test sets of molecules. Different curvatures are weakly correlated to each other for six test sets of molecules, but are strongly correlated to each other within each test set of molecules. Based on correlation analysis, we construct twenty six nontrivial nonpolar solvation models. Our numerical results reveal that the LJ potential plays a vital role in nonpolar solvation modeling, especially for molecules involving strong van der Waals interactions. It is found that curvatures are at least as important as surface area or surface enclosed volume in nonpolar solvation modeling. In conjugation with the GPB model, various curvature-based nonpolar solvation models are shown to offer some of the best solvation free energy predictions for a wide range of test sets. For example, root mean square errors from a model constituting surface area, volume, mean curvature, and LJ potential are less than 0.42 kcal/mol for all test sets. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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

Nasehi Tehrani, J; Wang, J; McEwan, A

Purpose: In this study, we developed and evaluated a method for predicting lung surface deformation vector fields (SDVFs) based on surrogate signals such as chest and abdomen motion at selected locations and spirometry measurements. Methods: A Patient-specific 3D triangular surface mesh of the lung region at end-expiration (EE) phase was obtained by threshold-based segmentation method. For each patient, a spirometer recorded the flow volume changes of the lungs; and 192 selected points at a regular spacing of 2cm X 2cm matrix points over a total area of 34cm X 24cm on the surface of chest and abdomen was used tomore » detect chest wall motions. Preprocessing techniques such as QR factorization with column pivoting (QRCP) were employed to remove redundant observations of the chest and abdominal area. To create a statistical model between the lung surface and the corresponding surrogate signals, we developed a predictive model based on canonical ridge regression (CRR). Two unique weighting vectors were selected for each vertex on the surface of the lung, and they were optimized during the training process using the all other phases of 4D-CT except the end-inspiration (EI) phase. These parameters were employed to predict the vertices locations of a testing data set, which was the EI phase of 4D-CT. Results: For ten lung cancer patients, the deformation vector field of each vertex of lung surface mesh was estimated from the external motion at selected positions on the chest wall surface plus spirometry measurements. The average estimation of 98th percentile of error was less than 1 mm (AP= 0.85, RL= 0.61, and SI= 0.82). Conclusion: The developed predictive model provides a non-invasive approach to derive lung boundary condition. Together with personalized biomechanical respiration modelling, the proposed model can be used to derive the lung tumor motion during radiation therapy accurately from non-invasive measurements.« less

A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods

NASA Astrophysics Data System (ADS)

Tang, Youhua; Pagowski, Mariusz; Chai, Tianfeng; Pan, Li; Lee, Pius; Baker, Barry; Kumar, Rajesh; Delle Monache, Luca; Tong, Daniel; Kim, Hyun-Cheol

2017-12-01

This study applies the Gridpoint Statistical Interpolation (GSI) 3D-Var assimilation tool originally developed by the National Centers for Environmental Prediction (NCEP), to improve surface PM2.5 predictions over the contiguous United States (CONUS) by assimilating aerosol optical depth (AOD) and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ) modeling system. An optimal interpolation (OI) method implemented earlier (Tang et al., 2015) for the CMAQ modeling system is also tested for the same period (July 2011) over the same CONUS. Both GSI and OI methods assimilate surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC, and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI and OI generally help reduce the prediction biases and improve correlation between model predictions and observations. In the GSI experiments, assimilation of surface PM2.5 (particle matter with diameter < 2.5 µm) leads to stronger increments in surface PM2.5 compared to its MODIS AOD assimilation at the 550 nm wavelength. In contrast, we find a stronger OI impact of the MODIS AOD on surface aerosols at 18:00 UTC compared to the surface PM2.5 OI method. GSI produces smoother result and yields overall better correlation coefficient and root mean squared error (RMSE). It should be noted that the 3D-Var and OI methods used here have several big differences besides the data assimilation schemes. For instance, the OI uses relatively big model uncertainties, which helps yield smaller mean biases, but sometimes causes the RMSE to increase. We also examine and discuss the sensitivity of the assimilation experiments' results to the AOD forward operators.

Tectonic predictions with mantle convection models

NASA Astrophysics Data System (ADS)

Coltice, Nicolas; Shephard, Grace E.

2018-04-01

Over the past 15 yr, numerical models of convection in Earth's mantle have made a leap forward: they can now produce self-consistent plate-like behaviour at the surface together with deep mantle circulation. These digital tools provide a new window into the intimate connections between plate tectonics and mantle dynamics, and can therefore be used for tectonic predictions, in principle. This contribution explores this assumption. First, initial conditions at 30, 20, 10 and 0 Ma are generated by driving a convective flow with imposed plate velocities at the surface. We then compute instantaneous mantle flows in response to the guessed temperature fields without imposing any boundary conditions. Plate boundaries self-consistently emerge at correct locations with respect to reconstructions, except for small plates close to subduction zones. As already observed for other types of instantaneous flow calculations, the structure of the top boundary layer and upper-mantle slab is the dominant character that leads to accurate predictions of surface velocities. Perturbations of the rheological parameters have little impact on the resulting surface velocities. We then compute fully dynamic model evolution from 30 and 10 to 0 Ma, without imposing plate boundaries or plate velocities. Contrary to instantaneous calculations, errors in kinematic predictions are substantial, although the plate layout and kinematics in several areas remain consistent with the expectations for the Earth. For these calculations, varying the rheological parameters makes a difference for plate boundary evolution. Also, identified errors in initial conditions contribute to first-order kinematic errors. This experiment shows that the tectonic predictions of dynamic models over 10 My are highly sensitive to uncertainties of rheological parameters and initial temperature field in comparison to instantaneous flow calculations. Indeed, the initial conditions and the rheological parameters can be good enough for an accurate prediction of instantaneous flow, but not for a prediction after 10 My of evolution. Therefore, inverse methods (sequential or data assimilation methods) using short-term fully dynamic evolution that predict surface kinematics are promising tools for a better understanding of the state of the Earth's mantle.

Assessing Confidence in Pliocene Sea Surface Temperatures to Evaluate Predictive Models

NASA Technical Reports Server (NTRS)

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling. M.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.;

Assessing confidence in Pliocene sea surface temperatures to evaluate predictive models

USGS Publications Warehouse

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling M.; Stoll, Danielle K.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.; Bragg, Fran J.; Lunt, Daniel J.; Foley, Kevin M.; Riesselman, Christina R.

2012-01-01

In light of mounting empirical evidence that planetary warming is well underway, the climate research community looks to palaeoclimate research for a ground-truthing measure with which to test the accuracy of future climate simulations. Model experiments that attempt to simulate climates of the past serve to identify both similarities and differences between two climate states and, when compared with simulations run by other models and with geological data, to identify model-specific biases. Uncertainties associated with both the data and the models must be considered in such an exercise. The most recent period of sustained global warmth similar to what is projected for the near future occurred about 3.3–3.0 million years ago, during the Pliocene epoch. Here, we present Pliocene sea surface temperature data, newly characterized in terms of level of confidence, along with initial experimental results from four climate models. We conclude that, in terms of sea surface temperature, models are in good agreement with estimates of Pliocene sea surface temperature in most regions except the North Atlantic. Our analysis indicates that the discrepancy between the Pliocene proxy data and model simulations in the mid-latitudes of the North Atlantic, where models underestimate warming shown by our highest-confidence data, may provide a new perspective and insight into the predictive abilities of these models in simulating a past warm interval in Earth history. This is important because the Pliocene has a number of parallels to present predictions of late twenty-first century climate.

Development of a Response Surface Thermal Model for Orion Mated to the International Space Station

NASA Technical Reports Server (NTRS)

Miller, Stephen W.; Meier, Eric J.

2010-01-01

A study was performed to determine if a Design of Experiments (DOE)/Response Surface Methodology could be applied to on-orbit thermal analysis and produce a set of Response Surface Equations (RSE) that accurately predict vehicle temperatures. The study used an integrated thermal model of the International Space Station and the Orion Outer mold line model. Five separate factors were identified for study: yaw, pitch, roll, beta angle, and the environmental parameters. Twenty external Orion temperatures were selected as the responses. A DOE case matrix of 110 runs was developed. The data from these cases were analyzed to produce an RSE for each of the temperature responses. The initial agreement between the engineering data and the RSE predictions was encouraging, although many RSEs had large uncertainties on their predictions. Fourteen verification cases were developed to test the predictive powers of the RSEs. The verification showed mixed results with some RSE predicting temperatures matching the engineering data within the uncertainty bands, while others had very large errors. While this study to not irrefutably prove that the DOE/RSM approach can be applied to on-orbit thermal analysis, it does demonstrate that technique has the potential to predict temperatures. Additional work is needed to better identify the cases needed to produce the RSEs

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.

How predictable are equatorial Atlantic surface winds?

NASA Astrophysics Data System (ADS)

Richter, Ingo; Doi, Takeshi; Behera, Swadhin

2017-04-01

Sensitivity tests with the SINTEX-F general circulation model (GCM) as well as experiments from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used to examine the extent to which sea-surface temperature (SST) anomalies contribute to the variability and predictability of monthly mean surface winds in the equatorial Atlantic. In the SINTEX-F experiments, a control experiment with prescribed observed SST for the period 1982-2014 is modified by inserting climatological values in certain regions, thereby eliminating SST anomalies. When SSTs are set to climatology in the tropical Atlantic only (30S to 30N), surface wind variability over the equatorial Atlantic (5S-5N) decreases by about 40% in April-May-June (AMJ). This suggests that about 60% of surface wind variability is due to either internal atmospheric variability or SSTs anomalies outside the tropical Atlantic. A further experiment with climatological SSTs in the equatorial Pacific indicates that another 10% of variability in AMJ may be due to remote influences from that basin. Experiments from the CMIP5 archive, in which climatological SSTs are prescribed globally, tend to confirm the results from SINTEX-F but show a wide spread. In some models, the equatorial Atlantic surface wind variability decreases by more than 90%, while in others it even increases. Overall, the results suggest that about 50-60% of surface wind variance in AMJ is predictable, while the rest is due to internal atmospheric variability. Other months show significantly lower predictability. The relatively strong internal variability as well as the influence of remote SSTs suggest a limited role for coupled ocean-atmosphere feedbacks in equatorial Atlantic variability.

Modeling and optimization of trihalomethanes formation potential of surface water (a drinking water source) using Box-Behnken design.

PubMed

Singh, Kunwar P; Rai, Premanjali; Pandey, Priyanka; Sinha, Sarita

2012-01-01

The present research aims to investigate the individual and interactive effects of chlorine dose/dissolved organic carbon ratio, pH, temperature, bromide concentration, and reaction time on trihalomethanes (THMs) formation in surface water (a drinking water source) during disinfection by chlorination in a prototype laboratory-scale simulation and to develop a model for the prediction and optimization of THMs levels in chlorinated water for their effective control. A five-factor Box-Behnken experimental design combined with response surface and optimization modeling was used for predicting the THMs levels in chlorinated water. The adequacy of the selected model and statistical significance of the regression coefficients, independent variables, and their interactions were tested by the analysis of variance and t test statistics. The THMs levels predicted by the model were very close to the experimental values (R(2) = 0.95). Optimization modeling predicted maximum (192 μg/l) TMHs formation (highest risk) level in water during chlorination was very close to the experimental value (186.8 ± 1.72 μg/l) determined in laboratory experiments. The pH of water followed by reaction time and temperature were the most significant factors that affect the THMs formation during chlorination. The developed model can be used to determine the optimum characteristics of raw water and chlorination conditions for maintaining the THMs levels within the safe limit.

Streamflow simulation for continental-scale river basins

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Lettenmaier, Dennis P.; Liang, Xu; Wetzel, Suzanne W.; Wood, Eric F.

1997-04-01

A grid network version of the two-layer variable infiltration capacity (VIC-2L) macroscale hydrologic model is described. VIC-2L is a hydrologically based soil- vegetation-atmosphere transfer scheme designed to represent the land surface in numerical weather prediction and climate models. The grid network scheme allows streamflow to be predicted for large continental rivers. Off-line (observed and estimated surface meteorological and radiative forcings) applications of the model to the Columbia River (1° latitude-longitude spatial resolution) and Delaware River (0.5° resolution) are described. The model performed quite well in both applications, reproducing the seasonal hydrograph and annual flow volumes to within a few percent. Difficulties in reproducing observed streamflow in the arid portion of the Snake River basin are attributed to groundwater-surface water interactions, which are not modeled by VIC-2L.

Forecasting near-surface weather conditions and precipitation in Alaska's Prince William Sound with the PWS-WRF modeling system

NASA Astrophysics Data System (ADS)

Olsson, Peter Q.; Volz, Karl P.; Liu, Haibo

2013-07-01

In the summer of 2009, several scientific teams engaged in a field program in Prince William Sound (PWS), Alaska to test an end-to-end atmosphere/ocean prediction system specially designed for this region. The "Sound Predictions Field Experiment" (FE) was a test of the PWS-Observing System (PWS-OS) and the culmination of a five-year program to develop an observational and prediction system for the Sound. This manuscript reports on results of an 18-day high-resolution atmospheric forecasting field project using the Weather Research and Forecasting (WRF) model.Special attention was paid to surface meteorological properties and precipitation. Upon reviewing the results of the real-time forecasts, modifications were incorporated in the PWS-WRF modeling system in an effort to improve objective forecast skill. Changes were both geometric (model grid structure) and physical (different physics parameterizations).The weather during the summer-time FE was typical of the PWS in that it was characterized by a number of minor disturbances rotating around an anchored low, but with no major storms in the Gulf of Alaska. The basic PWS-WRF modeling system as implemented operationally for the FE performed well, especially considering the extremely complex terrain comprising the greater PWS region.Modifications to the initial PWS-WRF modeling system showed improvement in predicting surface variables, especially where the ambient flow interacted strongly with the terrain. Prediction of precipitation on an accumulated basis was more accurate than prediction on a day-to-day basis. The 18-day period was too short to provide reliable assessment and intercomparison of the quantitative precipitation forecasting (QPF) skill of the PWS-WRF model variants.

Biogeochemical modeling of CO 2 and CH 4 production in anoxic Arctic soil microcosms

DOE PAGES

Tang, Guoping; Zheng, Jianqiu; Xu, Xiaofeng; ...

2016-09-12

Soil organic carbon turnover to CO 2 and CH 4 is sensitive to soil redox potential and pH conditions. But, land surface models do not consider redox and pH in the aqueous phase explicitly, thereby limiting their use for making predictions in anoxic environments. Using recent data from incubations of Arctic soils, we extend the Community Land Model with coupled carbon and nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) enables us to approximatelymore » describe the observed pH evolution without additional parameterization. Though Fe(III) reduction is normally assumed to compete with methanogenesis, the model predicts that Fe(III) reduction raises the pH from acidic to neutral, thereby reducing environmental stress to methanogens and accelerating methane production when substrates are not limiting. Furthermore, the equilibrium speciation predicts a substantial increase in CO 2 solubility as pH increases, and taking into account CO 2 adsorption to surface sites of metal oxides further decreases the predicted headspace gas-phase fraction at low pH. Without adequate representation of these speciation reactions, as well as the impacts of pH, temperature, and pressure, the CO 2 production from closed microcosms can be substantially underestimated based on headspace CO 2 measurements only. Our results demonstrate the efficacy of geochemical models for simulating soil biogeochemistry and provide predictive understanding and mechanistic representations that can be incorporated into land surface models to improve climate predictions.« less

A New Stochastic Approach to Predict Peak and Residual Shear Strength of Natural Rock Discontinuities

NASA Astrophysics Data System (ADS)

Casagrande, D.; Buzzi, O.; Giacomini, A.; Lambert, C.; Fenton, G.

2018-01-01

Natural discontinuities are known to play a key role in the stability of rock masses. However, it is a non-trivial task to estimate the shear strength of large discontinuities. Because of the inherent complexity to access to the full surface of the large in situ discontinuities, researchers or engineers tend to work on small-scale specimens. As a consequence, the results are often plagued by the well-known scale effect. A new approach is here proposed to predict shear strength of discontinuities. This approach has the potential to avoid the scale effect. The rationale of the approach is as follows: a major parameter that governs the shear strength of a discontinuity within a rock mass is roughness, which can be accounted for by surveying the discontinuity surface. However, this is typically not possible for discontinuities contained within the rock mass where only traces are visible. For natural surfaces, it can be assumed that traces are, to some extent, representative of the surface. It is here proposed to use the available 2D information (from a visible trace, referred to as a seed trace) and a random field model to create a large number of synthetic surfaces (3D data sets). The shear strength of each synthetic surface can then be estimated using a semi-analytical model. By using a large number of synthetic surfaces and a Monte Carlo strategy, a meaningful shear strength distribution can be obtained. This paper presents the validation of the semi-analytical mechanistic model required to support the new approach for prediction of discontinuity shear strength. The model can predict both peak and residual shear strength. The second part of the paper lays the foundation of a random field model to support the creation of synthetic surfaces having statistical properties in line with those of the data of the seed trace. The paper concludes that it is possible to obtain a reasonable estimate of peak and residual shear strength of the discontinuities tested from the information from a single trace, without having access to the whole surface.

A first generation dynamic ingress, redistribution and transport model of soil track-in: DIRT.

PubMed

Johnson, D L

2008-12-01

This work introduces a spatially resolved quantitative model, based on conservation of mass and first order transfer kinetics, for following the transport and redistribution of outdoor soil to, and within, the indoor environment by track-in on footwear. Implementations of the DIRT model examined the influence of room size, rug area and location, shoe size, and mass transfer coefficients for smooth and carpeted floor surfaces using the ratio of mass loading on carpeted to smooth floor surfaces as a performance metric. Results showed that in the limit for large numbers of random steps the dual aspects of deposition to and track-off from the carpets govern this ratio. Using recently obtained experimental measurements, historic transport and distribution parameters, cleaning efficiencies for the different floor surfaces, and indoor dust deposition rates to provide model boundary conditions, DIRT predicts realistic floor surface loadings. The spatio-temporal variability in model predictions agrees with field observations and suggests that floor surface dust loadings are constantly in flux; steady state distributions are hardly, if ever, achieved.

Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

NASA Astrophysics Data System (ADS)

Ko, P.; Kurosawa, S.

2014-03-01

The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine.

The Impact of Satellite-Derived Land Surface Temperatures on Numerical Weather Prediction Analyses and Forecasts

NASA Astrophysics Data System (ADS)

Candy, B.; Saunders, R. W.; Ghent, D.; Bulgin, C. E.

2017-09-01

Land surface temperature (LST) observations from a variety of satellite instruments operating in the infrared have been compared to estimates of surface temperature from the Met Office operational numerical weather prediction (NWP) model. The comparisons show that during the day the NWP model can underpredict the surface temperature by up to 10 K in certain regions such as the Sahel and southern Africa. By contrast at night the differences are generally smaller. Matchups have also been performed between satellite LSTs and observations from an in situ radiometer located in Southern England within a region of mixed land use. These matchups demonstrate good agreement at night and suggest that the satellite uncertainties in LST are less than 2 K. The Met Office surface analysis scheme has been adapted to utilize nighttime LST observations. Experiments using these analyses in an NWP model have shown a benefit to the resulting forecasts of near-surface air temperature, particularly over Africa.

Prediction of surface distress using neural networks

NASA Astrophysics Data System (ADS)

Hamdi, Hadiwardoyo, Sigit P.; Correia, A. Gomes; Pereira, Paulo; Cortez, Paulo

2017-06-01

Road infrastructures contribute to a healthy economy throughout a sustainable distribution of goods and services. A road network requires appropriately programmed maintenance treatments in order to keep roads assets in good condition, providing maximum safety for road users under a cost-effective approach. Surface Distress is the key element to identify road condition and may be generated by many different factors. In this paper, a new approach is aimed to predict Surface Distress Index (SDI) values following a data-driven approach. Later this model will be accordingly applied by using data obtained from the Integrated Road Management System (IRMS) database. Artificial Neural Networks (ANNs) are used to predict SDI index using input variables related to the surface of distress, i.e., crack area and width, pothole, rutting, patching and depression. The achieved results show that ANN is able to predict SDI with high correlation factor (R2 = 0.996%). Moreover, a sensitivity analysis was applied to the ANN model, revealing the influence of the most relevant input parameters for SDI prediction, namely rutting (59.8%), crack width (29.9%) and crack area (5.0%), patching (3.0%), pothole (1.7%) and depression (0.3%).

Effect of stacking sequence and surface treatment on the thermal conductivity of multilayered hybrid nano-composites

NASA Astrophysics Data System (ADS)

Papanicolaou, G. C.; Pappa, E. J.; Portan, D. V.; Kotrotsos, A.; Kollia, E.

2018-02-01

The aim of the present investigation was to study the effect of both the stacking sequence and surface treatment on the thermal conductivity of multilayered hybrid nano-composites. Four types of multilayered hybrid nanocomposites were manufactured and tested: Nitinol- CNTs (carbon nanotubes)- Acrylic resin; Nitinol- Acrylic resin- CNTs; Surface treated Nitinol- CNTs- Acrylic resin and Surface treated Nitinol- Acrylic resin- CNTs. Surface treatment of Nitinol plies was realized by means of the electrochemical anodization. Surface topography of the anodized nitinol sheets was investigated through Scanning Electron Microscopy (SEM). It was found that the overall thermal response of the manufactured multilayered nano-composites was greatly influenced by both the anodization and the stacking sequence. A theoretical model for the prediction of the overall thermal conductivity has been developed considering the nature of the different layers, their stacking sequence as well as the interfacial thermal resistance. Thermal conductivity and Differential Scanning Calorimetry (DSC) measurements were conducted, to verify the predicted by the model overall thermal conductivities. In all cases, a good agreement between theoretical predictions and experimental results was found.

Experimental and theoretical analysis of defocused CO2 laser microchanneling on PMMA for enhanced surface finish

NASA Astrophysics Data System (ADS)

Prakash, Shashi; Kumar, Subrata

2017-02-01

The poor surface finish of CO2 laser-micromachined microchannel walls is a major limitation of its utilization despite several key advantages, like low fabrication cost and low time consumption. Defocused CO2 laser beam machining is an effective solution for fabricating smooth microchannel walls on polymer and glass substrates. In this research work, the CO2 laser microchanneling process on PMMA has been analyzed at different beam defocus positions. Defocused processing has been investigated both theoretically and experimentally, and the depth of focus and beam diameter have been determined experimentally. The effect of beam defocusing on the microchannel width, depth, surface roughness, heat affected zone and microchannel profile were examined. A previously developed analytical model for microchannel depth prediction has been improved by incorporating the threshold energy density factor. A semi-analytical model for predicting the microchannel width at different defocus positions has been developed. A semi-empirical model has also been developed for predicting microchannel widths at different defocusing conditions for lower depth values. The developed models were compared and verified by performing actual experiments. Multi-objective optimization was performed to select the best optimum set of input parameters for achieving the desired surface roughness.

Tree-Structured Methods for Prediction and Data Visualization

DTIC Science & Technology

2009-03-18

which variables are most important for predicting smoking abstinence . GUIDE, on the other hand, can model interactions of any order. Fur- ther, it...tree for predicting smoking abstinence after one week of treatment. An observation goes to the left node if and only if the stated condition is...H. E., and Loh, W.-Y. (2009). Which surface atmospheric variable drives the seasonal cycle of sea surface temperature over the global ocean

Comparison of experimental surface pressures with theoretical predictions on twin two-dimensional convergent-divergent nozzles

NASA Technical Reports Server (NTRS)

Carlson, J. R.; Pendergraft, O. C., Jr.; Burley, J. R., II

1986-01-01

A three-dimensional subsonic aerodynamic panel code (VSAERO) was used to predict the effects of upper and lower external nozzle flap geometry on the external afterbody/nozzle pressure coefficient distributions and external nozzle drag of nonaxisymmetric convergent-divergent exhaust nozzles having parallel external sidewalls installed on a generic twin-engine high performance aircraft model. Nozzle static pressure coefficient distributions along the upper and lower surfaces near the model centerline and near the outer edges (corner) of the two surfaces were calculated, and nozzle drag was predicted using these surface pressure distributions. A comparison between the theoretical predictions and experimental wind tunnel data is made to evaluate the utility of the code in calculating the flow about these types of non-axisymmetric afterbody configurations. For free-stream Mach numbers of 0.60 and 0.90, the conditions where the flows were attached on the boattails yielded the best comparison between the theoretical predictions and the experimental data. For the Boattail terminal angles of greater than 15 deg., the experimental data for M = 0.60 and 0.90 indicated areas of separated flow, so the theoretical predictions failed to match the experimental data. Even though calculations of regions of separated flows are within the capabilities of the theoretical method, acceptable solutions were not obtained.

Predicting biomaterial property-dendritic cell phenotype relationships from the multivariate analysis of responses to polymethacrylates

PubMed Central

Kou, Peng Meng; Pallassana, Narayanan; Bowden, Rebeca; Cunningham, Barry; Joy, Abraham; Kohn, Joachim; Babensee, Julia E.

2011-01-01

Dendritic cells (DCs) play a critical role in orchestrating the host responses to a wide variety of foreign antigens and are essential in maintaining immune tolerance. Distinct biomaterials have been shown to differentially affect the phenotype of DCs, which suggested that biomaterials may be used to modulate immune response towards the biologic component in combination products. The elucidation of biomaterial property-DC phenotype relationships is expected to inform rational design of immuno-modulatory biomaterials. In this study, DC response to a set of 12 polymethacrylates (pMAs) was assessed in terms of surface marker expression and cytokine profile. Principal component analysis (PCA) determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an immature DC phenotype. Partial square linear regression, a multivariate modeling approach, was implemented and successfully predicted biomaterial-induced DC phenotype in terms of surface marker expression from biomaterial properties with R2prediction = 0.76. Furthermore, prediction of DC phenotype was effective based on only theoretical chemical composition of the bulk polymers with R2prediction = 0.80. These results demonstrated that immune cell response can be predicted from biomaterial properties, and computational models will expedite future biomaterial design and selection. PMID:22136715

Study on two operating conditions of a full-scale oxidation ditch for optimization of energy consumption and effluent quality by using CFD model.

PubMed

Yang, Yin; Yang, Jiakuan; Zuo, Jiaolan; Li, Ye; He, Shu; Yang, Xiao; Zhang, Kai

2011-05-01

The operating condition of an oxidation ditch (OD) has significant impact on energy consumption and effluent quality of wastewater treatment plants (WWTPs). An experimentally validated numerical tool, based on computational fluid dynamics (CFD) model, was proposed to optimize the operating condition by considering two important factors: flow field and dissolved oxygen (DO) concentration profiles. The model is capable of predicting flow pattern and oxygen mass transfer characteristics in ODs equipped with surface aerators and submerged impellers. Performance demonstration and comparison of two operating conditions (existing and improved) were carried out in two full-scale Carrousel ODs at the Ping Dingshan WWTP in Henan, China. A moving wall model and a fan model were designed to simulate surface aerators and submerged impellers, respectively. Oxygen mass transfer in the ditch was predicted by using a unit analysis method. In aeration zones, the mass inlets representing the surface aerators were set as one source of DO. In the whole straight channel, the oxygen consumption was modeled by using modified BOD-DO model. The following results were obtained: (1) the CFD model characterized flow pattern and DO concentration profiles in the full-scale OD. The predicted flow field values were within 1.98 ± 4.28% difference from the actual measured values while the predicted DO concentration values were within -4.71 ± 4.15% of the measured ones, (2) a surface aerator should be relocated to around 15m from the curve bend entrance to reduce energy loss caused by fierce collisions at the wall of the curve bend, and (3) DO concentration gradients in the OD under the improved operating condition were more favorable for occurrence of simultaneous nitrification and denitrification (SND). Copyright © 2011 Elsevier Ltd. All rights reserved.

Measured effects of surface cloth impressions on polar backscatter and comparison with a reflection grating model

NASA Technical Reports Server (NTRS)

Madaras, Eric I.; Brush, Edwin F., III; Bridal, S. L.; Holland, Mark R.; Miller, James G.

1992-01-01

This paper focuses on the nature of a typical composite surface and its effects on scattering. Utilizing epoxy typical of that in composites and standard composite fabrication methods, a sample with release cloth impressions on its surface is produced. A simple model for the scattering from the surface impressions of this sample is constructed and then polar backscatter measurements are made on the sample and compared with the model predictions.

Low-high junction theory applied to solar cells

NASA Technical Reports Server (NTRS)

Godlewski, M. P.; Baraona, C. R.; Brandhorst, H. W., Jr.

1974-01-01

Recent use of alloying techniques for rear contact formation has yielded a new kind of silicon solar cell, the back surface field (BSF) cell, with abnormally high open-circuit voltage and improved radiation resistance. Several analytical models for open-circuit voltage based on the reverse saturation current are formulated to explain these observations. The zero surface recombination velocity (SRV) case of the conventional cell model, the drift field model, and the low-high junction (LHJ) model can predict the experimental trends. The LHJ model applies the theory of the low-high junction and is considered to reflect a more realistic view of cell fabrication. This model can predict the experimental trends observed for BSF cells.

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

NASA Technical Reports Server (NTRS)

Grass, David; Jasinski, Michael F.; Govere, John

2003-01-01

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

A Novel Hybrid Model for Drawing Trace Reconstruction from Multichannel Surface Electromyographic Activity.

PubMed

Chen, Yumiao; Yang, Zhongliang

2017-01-01

Recently, several researchers have considered the problem of reconstruction of handwriting and other meaningful arm and hand movements from surface electromyography (sEMG). Although much progress has been made, several practical limitations may still affect the clinical applicability of sEMG-based techniques. In this paper, a novel three-step hybrid model of coordinate state transition, sEMG feature extraction and gene expression programming (GEP) prediction is proposed for reconstructing drawing traces of 12 basic one-stroke shapes from multichannel surface electromyography. Using a specially designed coordinate data acquisition system, we recorded the coordinate data of drawing traces collected in accordance with the time series while 7-channel EMG signals were recorded. As a widely-used time domain feature, Root Mean Square (RMS) was extracted with the analysis window. The preliminary reconstruction models can be established by GEP. Then, the original drawing traces can be approximated by a constructed prediction model. Applying the three-step hybrid model, we were able to convert seven channels of EMG activity recorded from the arm muscles into smooth reconstructions of drawing traces. The hybrid model can yield a mean accuracy of 74% in within-group design (one set of prediction models for all shapes) and 86% in between-group design (one separate set of prediction models for each shape), averaged for the reconstructed x and y coordinates. It can be concluded that it is feasible for the proposed three-step hybrid model to improve the reconstruction ability of drawing traces from sEMG.

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.

Potential impact of remote sensing data on sea-state analysis and prediction

NASA Technical Reports Server (NTRS)

Cardone, V. J.

1983-01-01

The severe North Atlantic storm which damaged the ocean liner Queen Elizabeth 2 (QE2) was studied to assess the impact of remotely sensed marine surface wind data obtained by SEASAT-A, on sea state specifications and forecasts. Alternate representations of the surface wind field in the QE2 storm were produced from the SEASAT enhanced data base, and from operational analyses based upon conventional data. The wind fields were used to drive a high resolution spectral ocean surface wave prediction model. Results show that sea state analyses would have been vastly improved during the period of storm formation and explosive development had remote sensing wind data been available in real time. A modest improvement in operational 12 to 24 hour wave forecasts would have followed automatically from the improved initial state specification made possible by the remote sensing data in both numerical and sea state prediction models. Significantly improved 24 to 48 hour wave forecasts require in addition to remote sensing data, refinement in the numerical and physical aspects of weather prediction models.

Exploring load, velocity, and surface disorder dependence of friction with one-dimensional and two-dimensional models.

PubMed

Dagdeviren, Omur E

2018-08-03

The effect of surface disorder, load, and velocity on friction between a single asperity contact and a model surface is explored with one-dimensional and two-dimensional Prandtl-Tomlinson (PT) models. We show that there are fundamental physical differences between the predictions of one-dimensional and two-dimensional models. The one-dimensional model estimates a monotonic increase in friction and energy dissipation with load, velocity, and surface disorder. However, a two-dimensional PT model, which is expected to approximate a tip-sample system more realistically, reveals a non-monotonic trend, i.e. friction is inert to surface disorder and roughness in wearless friction regime. The two-dimensional model discloses that the surface disorder starts to dominate the friction and energy dissipation when the tip and the sample interact predominantly deep into the repulsive regime. Our numerical calculations address that tracking the minimum energy path and the slip-stick motion are two competing effects that determine the load, velocity, and surface disorder dependence of friction. In the two-dimensional model, the single asperity can follow the minimum energy path in wearless regime; however, with increasing load and sliding velocity, the slip-stick movement dominates the dynamic motion and results in an increase in friction by impeding tracing the minimum energy path. Contrary to the two-dimensional model, when the one-dimensional PT model is employed, the single asperity cannot escape to the minimum energy minimum due to constraint motion and reveals only a trivial dependence of friction on load, velocity, and surface disorder. Our computational analyses clarify the physical differences between the predictions of the one-dimensional and two-dimensional models and open new avenues for disordered surfaces for low energy dissipation applications in wearless friction regime.

Colour Model for Outdoor Machine Vision for Tropical Regions and its Comparison with the CIE Model

NASA Astrophysics Data System (ADS)

Sahragard, Nasrolah; Ramli, Abdul Rahman B.; Hamiruce Marhaban, Mohammad; Mansor, Shattri B.

2011-02-01

Accurate modeling of daylight and surface reflectance are very useful for most outdoor machine vision applications specifically those which are based on color recognition. Existing daylight CIE model has drawbacks that limit its ability to predict the color of incident light. These limitations include lack of considering ambient light, effects of light reflected off the ground, and context specific information. Previously developed color model is only tested for a few geographical places in North America and its accountability is under question for other places in the world. Besides, existing surface reflectance models are not easily applied to outdoor images. A reflectance model with combined diffuse and specular reflection in normalized HSV color space could be used to predict color. In this paper, a new daylight color model showing the color of daylight for a broad range of sky conditions is developed which will suit weather conditions of tropical places such as Malaysia. A comparison of this daylight color model and daylight CIE model will be discussed. The colors of matte and specular surfaces have been estimated by use of the developed color model and surface reflection function in this paper. The results are shown to be highly reliable.

Surface Temperature Prediction of a Bridge for Tactical Decision Aide Modelling

DTIC Science & Technology

1988-01-01

Roadway And Piling Surface Temperature Predictions (No Radiosity Incident on Lower Surface) Compared to Temperature Estimates...Heat gained from water = Heat lost by long wave radiosity radiation. Algebraically, with the conduction term expressed in the same manner as for...5 10 15 20 LOCAL TIME (hrs.) Figure 8. Effect of No Radiosity Incident on Lower Surface. 37 U 8a M OT U% 60-- 0- o.. 20- 0- 1 T I I 5 10 15 20 LOCAL

Prediction of protein orientation upon immobilization on biological and nonbiological surfaces

NASA Astrophysics Data System (ADS)

Talasaz, Amirali H.; Nemat-Gorgani, Mohsen; Liu, Yang; Ståhl, Patrik; Dutton, Robert W.; Ronaghi, Mostafa; Davis, Ronald W.

2006-10-01

We report on a rapid simulation method for predicting protein orientation on a surface based on electrostatic interactions. New methods for predicting protein immobilization are needed because of the increasing use of biosensors and protein microarrays, two technologies that use protein immobilization onto a solid support, and because the orientation of an immobilized protein is important for its function. The proposed simulation model is based on the premise that the protein interacts with the electric field generated by the surface, and this interaction defines the orientation of attachment. Results of this model are in agreement with experimental observations of immobilization of mitochondrial creatine kinase and type I hexokinase on biological membranes. The advantages of our method are that it can be applied to any protein with a known structure; it does not require modeling of the surface at atomic resolution and can be run relatively quickly on readily available computing resources. Finally, we also propose an orientation of membrane-bound cytochrome c, a protein for which the membrane orientation has not been unequivocally determined. electric double layer | electrostatic simulations | orientation flexibility

Using Simplistic Shape/Surface Models to Predict Brightness in Estimation Filters

NASA Astrophysics Data System (ADS)

Wetterer, C.; Sheppard, D.; Hunt, B.

The prerequisite for using brightness (radiometric flux intensity) measurements in an estimation filter is to have a measurement function that accurately predicts a space objects brightness for variations in the parameters of interest. These parameters include changes in attitude and articulations of particular components (e.g. solar panel east-west offsets to direct sun-tracking). Typically, shape models and bidirectional reflectance distribution functions are combined to provide this forward light curve modeling capability. To achieve precise orbit predictions with the inclusion of shape/surface dependent forces such as radiation pressure, relatively complex and sophisticated modeling is required. Unfortunately, increasing the complexity of the models makes it difficult to estimate all those parameters simultaneously because changes in light curve features can now be explained by variations in a number of different properties. The classic example of this is the connection between the albedo and the area of a surface. If, however, the desire is to extract information about a single and specific parameter or feature from the light curve, a simple shape/surface model could be used. This paper details an example of this where a complex model is used to create simulated light curves, and then a simple model is used in an estimation filter to extract out a particular feature of interest. In order for this to be successful, however, the simple model must be first constructed using training data where the feature of interest is known or at least known to be constant.

Ocean surface waves in Hurricane Ike (2008) and Superstorm Sandy (2012): Coupled model predictions and observations

NASA Astrophysics Data System (ADS)

Chen, Shuyi S.; Curcic, Milan

2016-07-01

Forecasting hurricane impacts of extreme winds and flooding requires accurate prediction of hurricane structure and storm-induced ocean surface waves days in advance. The waves are complex, especially near landfall when the hurricane winds and water depth varies significantly and the surface waves refract, shoal and dissipate. In this study, we examine the spatial structure, magnitude, and directional spectrum of hurricane-induced ocean waves using a high resolution, fully coupled atmosphere-wave-ocean model and observations. The coupled model predictions of ocean surface waves in Hurricane Ike (2008) over the Gulf of Mexico and Superstorm Sandy (2012) in the northeastern Atlantic and coastal region are evaluated with the NDBC buoy and satellite altimeter observations. Although there are characteristics that are general to ocean waves in both hurricanes as documented in previous studies, wave fields in Ike and Sandy possess unique properties due mostly to the distinct wind fields and coastal bathymetry in the two storms. Several processes are found to significantly modulate hurricane surface waves near landfall. First, the phase speed and group velocities decrease as the waves become shorter and steeper in shallow water, effectively increasing surface roughness and wind stress. Second, the bottom-induced refraction acts to turn the waves toward the coast, increasing the misalignment between the wind and waves. Third, as the hurricane translates over land, the left side of the storm center is characterized by offshore winds over very short fetch, which opposes incoming swell. Landfalling hurricanes produce broader wave spectra overall than that of the open ocean. The front-left quadrant is most complex, where the combination of windsea, swell propagating against the wind, increasing wind-wave stress, and interaction with the coastal topography requires a fully coupled model to meet these challenges in hurricane wave and surge prediction.

Geospatial application of the Water Erosion Prediction Project (WEPP) Model

Treesearch

D. C. Flanagan; J. R. Frankenberger; T. A. Cochrane; C. S. Renschler; W. J. Elliot

2011-01-01

The Water Erosion Prediction Project (WEPP) model is a process-based technology for prediction of soil erosion by water at hillslope profile, field, and small watershed scales. In particular, WEPP utilizes observed or generated daily climate inputs to drive the surface hydrology processes (infiltration, runoff, ET) component, which subsequently impacts the rest of the...

Assessment of Turbulent Shock-Boundary Layer Interaction Computations Using the OVERFLOW Code

NASA Technical Reports Server (NTRS)

Oliver, A. B.; Lillard, R. P.; Schwing, A. M.; Blaisdell, G> A.; Lyrintzis, A. S.

2007-01-01

The performance of two popular turbulence models, the Spalart-Allmaras model and Menter s SST model, and one relatively new model, Olsen & Coakley s Lag model, are evaluated using the OVERFLOWcode. Turbulent shock-boundary layer interaction predictions are evaluated with three different experimental datasets: a series of 2D compression ramps at Mach 2.87, a series of 2D compression ramps at Mach 2.94, and an axisymmetric coneflare at Mach 11. The experimental datasets include flows with no separation, moderate separation, and significant separation, and use several different experimental measurement techniques (including laser doppler velocimetry (LDV), pitot-probe measurement, inclined hot-wire probe measurement, preston tube skin friction measurement, and surface pressure measurement). Additionally, the OVERFLOW solutions are compared to the solutions of a second CFD code, DPLR. The predictions for weak shock-boundary layer interactions are in reasonable agreement with the experimental data. For strong shock-boundary layer interactions, all of the turbulence models overpredict the separation size and fail to predict the correct skin friction recovery distribution. In most cases, surface pressure predictions show too much upstream influence, however including the tunnel side-wall boundary layers in the computation improves the separation predictions.

Improving land surface emissivty parameter for land surface models using portable FTIR and remote sensing observation in Taklimakan Desert

NASA Astrophysics Data System (ADS)

Liu, Yongqiang; Mamtimin, Ali; He, Qing

2014-05-01

Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply assumption, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, 0.96 for soil and wetland in the Global and Regional Assimilation and Prediction System (GRAPES) Common Land Model (CoLM). This is the so-called emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the emissivity induces errors in modeling the surface energy budget over Taklimakan Desert where ɛ is far smaller than original value. One feasible solution to this problem is to apply the accurate broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity required by land surface models. In order to calibrate the regression equations, using a portable Fourier Transform infrared (FTIR) spectrometer instrument, crossing Taklimakan Desert along with highway from north to south, to measure the accurate broadband emissivity. The observed emissivity data show broadband ɛ around 0.89-0.92. To examine the impact of improved ɛ to radiative energy redistribution, simulation studies were conducted using offline CoLM. The results illustrate that large impacts of surface ɛ occur over desert, with changes up in surface skin temperature, as well as evident changes in sensible heat fluxes. Keywords: Taklimakan Desert, surface broadband emissivity, Fourier Transform infrared spectrometer, MODIS, CoLM

Modeling the investment casting of a titanium crown.

PubMed

Atwood, R C; Lee, P D; Curtis, R V; Maijer, D M

2007-01-01

The objective of this study was to apply computational modeling tools to assist in the design of titanium dental castings. The tools developed should incorporate state-of-the-art micromodels to predict the depth to which the mechanical properties of the crown are affected by contamination from the mold. The model should also be validated by comparison of macro- and micro-defects found in a typical investment cast titanium tooth crown. Crowns were hand-waxed and investment cast in commercial purity grade 1 (CP-1) titanium by a commercial dental laboratory. The castings were analyzed using X-ray microtomography (XMT). Following sectioning, analysis continued with optical and scanning electron microscopy, and microhardness testing. An in-house cellular-automata solidification and finite-difference diffusion program was coupled with a commercial casting program to model the investment casting process. A three-dimensional (3D) digital image generated by X-ray tomography was used to generate an accurate geometric representation of a molar crown casting. Previously reported work was significantly expanded upon by including transport of dissolved oxygen and impurity sources upon the arbitrarily shaped surface of the crown, and improved coupling of micro- and macro-scale simulations. Macroscale modeling was found to be sufficient to accurately predict the location of the large internal porosity. These are shrinkage pores located in the thick sections of the cusp. The model was used to determine the influence of sprue design on the size and location of these pores. Combining microscale with macroscale modeling allowed the microstructure and depth of contamination to be predicted qualitatively. This combined model predicted a surprising result--the dissolution of silicon from the mold into the molten titanium is sufficient to depress the freezing point of the liquid metal such that the crown solidifies the subsurface. Solidification then progresses inwards and back out to the surface through the silicon-enriched near-surface layer. The microstructure and compositional analysis of the near-surface region are consistent with this prediction. A multiscale model was developed and validated, which can be used to design CP-Ti dental castings to minimize both macro- and micro-defects, including shrinkage porosity, grain size and the extent of surface contamination due to reaction with the mold material. The model predicted the surprising result that the extent of Si contamination from the mold was sufficient to suppress the liquidus temperature to the extent that the surface (to a depth of approximately 100 microm) of the casting solidifies after the bulk. This significantly increases the oxygen pickup, thereby increasing the depth of formation of alpha casing. The trend towards mold materials with reduced Si in order to produce easier-to-finish titanium castings is a correct approach.

EMI-Sensor Data to Identify Areas of Manure Accumulation on a Feedlot Surface

USDA-ARS?s Scientific Manuscript database

A study was initiated to test the validity of using electromagnetic induction (EMI) survey data, a prediction-based sampling strategy and ordinary linear regression modeling to predict spatially variable feedlot surface manure accumulation. A 30 m × 60 m feedlot pen with a central mound was selecte...

Role of Viscous Dissipative Processes on the Wetting of Textured Surfaces

PubMed Central

Grewal, H. S.; Nam Kim, Hong; Cho, Il-Joo; Yoon, Eui-Sung

2015-01-01

We investigate the role of viscous forces on the wetting of hydrophobic, semi-hydrophobic, and hydrophilic textured surfaces as second-order effects. We show that during the initial contact, the transition from inertia- to viscous-dominant regime occurs regardless of their surface topography and chemistry. Furthermore, we demonstrate the effect of viscosity on the apparent contact angle under quasi-static conditions by modulating the ratio of a water/glycerol mixture and show the effect of viscosity, especially on the semi-hydrophobic and hydrophobic textured substrates. The reason why the viscous force does not affect the apparent contact angle of the hydrophilic surface is explained based on the relationship between the disjoining pressure and surface chemistry. We further propose a wetting model that can predict the apparent contact angle of a liquid drop on a textured substrate by incorporating a viscous force component in the force balance equation. This model can predict apparent contact angles on semi-hydrophobic and hydrophobic textured surfaces exhibiting Wenzel state more accurately than the Wenzel model, indicating the importance of viscous forces in determining the apparent contact angle. The modified model can be applied for estimating the wetting properties of arbitrary engineered surfaces. PMID:26390958

An Assessment of ECMWF Analyses and Model Forecasts over the North Slope of Alaska Using Observations from the ARM Mixed-Phase Arctic Cloud Experiment

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

Xie, Shaocheng; Klein, Stephen A.; Yio, J. John

2006-03-11

European Centre for Medium-Range Weather Forecasts (ECMWF) analysis and model forecast data are evaluated using observations collected during the Atmospheric Radiation Measurement (ARM) October 2004 Mixed-Phase Arctic Cloud Experiment (M-PACE) at its North Slope of Alaska (NSA) site. It is shown that the ECMWF analysis reasonably represents the dynamic and thermodynamic structures of the large-scale systems that affected the NSA during M-PACE. The model-analyzed near-surface horizontal winds, temperature, and relative humidity also agree well with the M-PACE surface measurements. Given the well-represented large-scale fields, the model shows overall good skill in predicting various cloud types observed during M-PACE; however, themore » physical properties of single-layer boundary layer clouds are in substantial error. At these times, the model substantially underestimates the liquid water path in these clouds, with the concomitant result that the model largely underpredicts the downwelling longwave radiation at the surface and overpredicts the outgoing longwave radiation at the top of the atmosphere. The model also overestimates the net surface shortwave radiation, mainly because of the underestimation of the surface albedo. The problem in the surface albedo is primarily associated with errors in the surface snow prediction. Principally because of the underestimation of the surface downwelling longwave radiation at the times of single-layer boundary layer clouds, the model shows a much larger energy loss (-20.9 W m-2) than the observation (-9.6 W m-2) at the surface during the M-PACE period.« less

The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

NASA Astrophysics Data System (ADS)

Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

2013-10-01

Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

Seasonal Prediction of Regional Surface Air Temperature and First-flowering Date in South Korea using Dynamical Downscaling

NASA Astrophysics Data System (ADS)

Ahn, J. B.; Hur, J.

2015-12-01

The seasonal prediction of both the surface air temperature and the first-flowering date (FFD) over South Korea are produced using dynamical downscaling (Hur and Ahn, 2015). Dynamical downscaling is performed using Weather Research and Forecast (WRF) v3.0 with the lateral forcing from hourly outputs of Pusan National University (PNU) coupled general circulation model (CGCM) v1.1. Gridded surface air temperature data with high spatial (3km) and temporal (daily) resolution are obtained using the physically-based dynamical models. To reduce systematic bias, simple statistical correction method is then applied to the model output. The FFDs of cherry, peach and pear in South Korea are predicted for the decade of 1999-2008 by applying the corrected daily temperature predictions to the phenological thermal-time model. The WRF v3.0 results reflect the detailed topographical effect, despite having cold and warm biases for warm and cold seasons, respectively. After applying the correction, the mean temperature for early spring (February to April) well represents the general pattern of observation, while preserving the advantages of dynamical downscaling. The FFD predictabilities for the three species of trees are evaluated in terms of qualitative, quantitative and categorical estimations. Although FFDs derived from the corrected WRF results well predict the spatial distribution and the variation of observation, the prediction performance has no statistical significance or appropriate predictability. The approach used in the study may be helpful in obtaining detailed and useful information about FFD and regional temperature by accounting for physically-based atmospheric dynamics, although the seasonal predictability of flowering phenology is not high enough. Acknowledgements This work was carried out with the support of the Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under Grant Project No. PJ009953 and Project No. PJ009353, Republic of Korea. Reference Hur, J., J.-B. Ahn, 2015. Seasonal Prediction of Regional Surface Air Temperature and First-flowering Date over South Korea, Int. J. Climatol., DOI: 10.1002/joc.4323.

Computation of flows in a turn-around duct and a turbine cascade using advanced turbulence models

NASA Technical Reports Server (NTRS)

Lakshminarayana, B.; Luo, J.

1993-01-01

Numerical investigation has been carried out to evaluate the capability of the Algebraic Reynolds Stress Model (ARSM) and the Nonlinear Stress Model (NLSM) to predict strongly curved turbulent flow in a turn-around duct (TAD). The ARSM includes the near-wall damping term of pressure-strain correlation phi(sub ij,w), which enables accurate prediction of individual Reynolds stress components in wall flows. The TAD mean flow quantities are reasonably well predicted by various turbulence models. The ARSM yields better predictions for both the mean flow and the turbulence quantities than the NLSM and the k-epsilon (k = turbulent kinetic energy, epsilon = dissipation rate of k) model. The NLSM also shows slight improvement over the k-epsilon model. However, all the models fail to capture the recovery of the flow from strong curvature effects. The formulation for phi(sub ij,w) appears to be incorrect near the concave surface. The hybrid k-epsilon/ARSM, Chien's k-epsilon model, and Coakley's q-omega (q = the square root of k, omega = epsilon/k) model have also been employed to compute the aerodynamics and heat transfer of a transonic turbine cascade. The surface pressure distributions and the wake profiles are predicted well by all the models. The k-epsilon model and the k-epsilon/ARSM model provide better predictions of heat transfer than the q-omega model. The k-epsilon/ARSM solutions show significant differences in the predicted skin friction coefficients, heat transfer rates and the cascade performance parameters, as compared to the k-epsilon model. The k-epsilon/ARSM model appears to capture, qualitatively, the anisotropy associated with by-pass transition.

Turbine Vane External Heat Transfer. Volume 1: Analytical and Experimental Evaluation of Surface Heat Transfer Distributions with Leading Edge Showerhead Film Cooling

NASA Technical Reports Server (NTRS)

Turner, E. R.; Wilson, M. D.; Hylton, L. D.; Kaufman, R. M.

1985-01-01

Progress in predictive design capabilities for external heat transfer to turbine vanes was summarized. A two dimensional linear cascade (previously used to obtain vane surface heat transfer distributions on nonfilm cooled airfoils) was used to examine the effect of leading edge shower head film cooling on downstream heat transfer. The data were used to develop and evaluate analytical models. Modifications to the two dimensional boundary layer model are described. The results were used to formulate and test an effective viscosity model capable of predicting heat transfer phenomena downstream of the leading edge film cooling array on both the suction and pressure surfaces, with and without mass injection.

A simple 2-d thermal model for GMA welds

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

Matteson, M.A.; Franke, G.L.; Vassilaros, M.G.

1996-12-31

The Rosenthal model of heat distribution from a moving source has been used in many applications to predict the temperature distribution during welding. The equation has performed well in its original form or as modified. The expression has a significant limitation for application to gas metal arc welds (GMAW) that have a papilla extending from the root of the weld bead. The shape of the fusion line between the papilla and the plate surface has a concave shape rather than the expected convex shape. However, at some distance from the fusion line the heat affected zone (HAZ) made visible bymore » etching has the expected convex shape predicted by the Rosenthal expression. This anomaly creates a limitation to the use of the Rosenthal expression for predicting GMAW bead shapes or HAZ temperature histories. Current research at the Naval Surface Warfare Center--Carderock Division (NSWC--CD) to develop a computer based model to predict the microstructure of multi-pass GMAW requires a simple expression to predict the fusion line and temperature history of the HAZ for each weld pass. The solution employed for the NSWC--CD research is a modified Rosenthal expression that has a dual heat source. One heat source is a disk source above the plate surface supplying the majority of the heat. The second heat source is smaller and below the surface of the plate. This second heat source helps simulate the penetration power of many GMAW welds that produces the papilla. The assumptions, strengths and limitations of the model are presented along with some applications.« less

Improving the Long-Term Stability of Atmospheric Surface Deformation Predictions by Mitigating the Effects of Orography Updates in Operational Weather Forecast Models

NASA Astrophysics Data System (ADS)

Dill, Robert; Bergmann-Wolf, Inga; Thomas, Maik; Dobslaw, Henryk

2016-04-01

The global numerical weather prediction model routinely operated at the European Centre for Medium-Range Weather Forecasts (ECMWF) is typically updated about two times a year to incorporate the most recent improvements in the numerical scheme, the physical model or the data assimilation procedures into the system for steadily improving daily weather forecasting quality. Even though such changes frequently affect the long-term stability of meteorological quantities, data from the ECMWF deterministic model is often preferred over alternatively available atmospheric re-analyses due to both the availability of the data in near real-time and the substantially higher spatial resolution. However, global surface pressure time-series, which are crucial for the interpretation of geodetic observables, such as Earth rotation, surface deformation, and the Earth's gravity field, are in particular affected by changes in the surface orography of the model associated with every major change in horizontal resolution happened, e.g., in February 2006, January 2010, and May 2015 in case of the ECMWF operational model. In this contribution, we present an algorithm to harmonize surface pressure time-series from the operational ECMWF model by projecting them onto a time-invariant reference topography under consideration of the time-variable atmospheric density structure. The effectiveness of the method will be assessed globally in terms of pressure anomalies. In addition, we will discuss the impact of the method on predictions of crustal deformations based on ECMWF input, which have been recently made available by GFZ Potsdam.

Projections of Future Summertime Ozone over the U.S.

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

Pfister, G. G.; Walters, Stacy; Lamarque, J. F.

This study uses a regional fully coupled chemistry-transport model to assess changes in surface ozone over the summertime U.S. between present and a 2050 future time period at high spatial resolution (12 km grid spacing) under the SRES A2 climate and RCP8.5 anthropogenic pre-cursor emission scenario. The impact of predicted changes in climate and global background ozone is estimated to increase surface ozone over most of the U.S; the 5th - 95th percentile range for daily 8-hour maximum surface ozone increases from 31-79 ppbV to 30-87 ppbV between the present and future time periods. The analysis of a set ofmore » meteorological drivers suggests that these mostly will add to increasing ozone, but the set of simulations conducted does not allow to separate this effect from that through enhanced global background ozone. Statistically the most robust positive feedbacks are through increased temperature, biogenic emissions and solar radiation. Stringent emission controls can counteract these feedbacks and if considered, we estimate large reductions in surface ozone with the 5th-95th percentile reduced to 27-55 ppbV. A comparison of the high-resolution projections to global model projections shows that even though the global model is biased high in surface ozone compared to the regional model and compared to observations, both the global and the regional model predict similar changes in ozone between the present and future time periods. However, on smaller spatial scales, the regional predictions show more pronounced changes between urban and rural regimes that cannot be resolved at the coarse resolution of global model. In addition, the sign of the changes in overall ozone mixing ratios can be different between the global and the regional predictions in certain regions, such as the Western U.S. This study confirms the key role of emission control strategies in future air quality predictions and demonstrates the need for considering degradation of air quality with future climate change in emission policy making. It also illustrates the need for high resolution modeling when the objective is to address regional and local air quality or establish links to human health and society.« less

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.

Modeling the Acid-Base Properties of Montmorillonite Edge Surfaces.

PubMed

Tournassat, Christophe; Davis, James A; Chiaberge, Christophe; Grangeon, Sylvain; Bourg, Ian C

2016-12-20

The surface reactivity of clay minerals remains challenging to characterize because of a duality of adsorption surfaces and mechanisms that does not exist in the case of simple oxide surfaces: edge surfaces of clay minerals have a variable proton surface charge arising from hydroxyl functional groups, whereas basal surfaces have a permanent negative charge arising from isomorphic substitutions. Hence, the relationship between surface charge and surface potential on edge surfaces cannot be described using the Gouy-Chapman relation, because of a spillover of negative electrostatic potential from the basal surface onto the edge surface. While surface complexation models can be modified to account for these features, a predictive fit of experimental data was not possible until recently, because of uncertainty regarding the densities and intrinsic pK a values of edge functional groups. Here, we reexamine this problem in light of new knowledge on intrinsic pK a values obtained over the past decade using ab initio molecular dynamics simulations, and we propose a new formalism to describe edge functional groups. Our simulation results yield reasonable predictions of the best available experimental acid-base titration data.

Predictive Model of Supercooled Water Droplet Pinning/Repulsion Impacting a Superhydrophobic Surface: The Role of the Gas-Liquid Interface Temperature.

PubMed

Mohammadi, Morteza; Tembely, Moussa; Dolatabadi, Ali

2017-02-28

Dynamical analysis of an impacting liquid drop on superhydrophobic surfaces is mostly carried out by evaluating the droplet contact time and maximum spreading diameter. In this study, we present a general transient model of the droplet spreading diameter developed from the previously defined mass-spring model for bouncing drops. The effect of viscosity was also considered in the model by definition of a dash-pot term extracted from experiments on various viscous liquid droplets on a superhydrophobic surface. Furthermore, the resultant shear force of the stagnation air flow was also considered with the help of the classical Homann flow approach. It was clearly shown that the proposed model predicts the maximum spreading diameter and droplet contact time very well. On the other hand, where stagnation air flow is present in contradiction to the theoretical model, the droplet contact time was reduced as a function of both droplet Weber numbers and incoming air velocities. Indeed, the reduction in the droplet contact time (e.g., 35% at a droplet Weber number of up to 140) was justified by the presence of a formed thin air layer underneath the impacting drop on the superhydrophobic surface (i.e., full slip condition). Finally, the droplet wetting model was also further developed to account for low temperature through the incorporation of classical nucleation theory. Homogeneous ice nucleation was integrated into the model through the concept of the reduction of the supercooled water drop surface tension as a function of the gas-liquid interface temperature, which was directly correlated with the Nusselt number of incoming air flow. It was shown that the experimental results was qualitatively predicted by the proposed model under all supercooling conditions (i.e., from -10 to -30 °C).

Assessment of the Risks of Mixtures of Major Use Veterinary Antibiotics in European Surface Waters.

PubMed

Guo, Jiahua; Selby, Katherine; Boxall, Alistair B A

2016-08-02

Effects of single veterinary antibiotics on a range of aquatic organisms have been explored in many studies. In reality, surface waters will be exposed to mixtures of these substances. In this study, we present an approach for establishing risks of antibiotic mixtures to surface waters and illustrate this by assessing risks of mixtures of three major use antibiotics (trimethoprim, tylosin, and lincomycin) to algal and cyanobacterial species in European surface waters. Ecotoxicity tests were initially performed to assess the combined effects of the antibiotics to the cyanobacteria Anabaena flos-aquae. The results were used to evaluate two mixture prediction models: concentration addition (CA) and independent action (IA). The CA model performed best at predicting the toxicity of the mixture with the experimental 96 h EC50 for the antibiotic mixture being 0.248 μmol/L compared to the CA predicted EC50 of 0.21 μmol/L. The CA model was therefore used alongside predictions of exposure for different European scenarios and estimations of hazards obtained from species sensitivity distributions to estimate risks of mixtures of the three antibiotics. Risk quotients for the different scenarios ranged from 0.066 to 385 indicating that the combination of three substances could be causing adverse impacts on algal communities in European surface waters. This could have important implications for primary production and nutrient cycling. Tylosin contributed most to the risk followed by lincomycin and trimethoprim. While we have explored only three antibiotics, the combined experimental and modeling approach could readily be applied to the wider range of antibiotics that are in use.

Optimum surface roughness prediction for titanium alloy by adopting response surface methodology

NASA Astrophysics Data System (ADS)

Yang, Aimin; Han, Yang; Pan, Yuhang; Xing, Hongwei; Li, Jinze

Titanium alloy has been widely applied in industrial engineering products due to its advantages of great corrosion resistance and high specific strength. This paper investigated the processing parameters for finish turning of titanium alloy TC11. Firstly, a three-factor central composite design of experiment, considering the cutting speed, feed rate and depth of cut, are conducted in titanium alloy TC11 and the corresponding surface roughness are obtained. Then a mathematic model is constructed by the response surface methodology to fit the relationship between the process parameters and the surface roughness. The prediction accuracy was verified by the one-way ANOVA. Finally, the contour line of the surface roughness under different combination of process parameters are obtained and used for the optimum surface roughness prediction. Verification experimental results demonstrated that material removal rate (MRR) at the obtained optimum can be significantly improved without sacrificing the surface roughness.

APEX sensitivity to atrazine dissipation rate on surface runoff loss within a coastal zone in Southeastern Puerto Rico

USDA-ARS?s Scientific Manuscript database

Simulation models are increasingly used to predict effects of conservation practices on transport of pesticides to water bodies. We used two models - the Agricultural Policy/Environmental eXtender (APEX) and the Riparian Ecosystem Management Model (REMM) to predict the movement of the herbicide, at...

WRF-Fire: coupled weather-wildland fire modeling with the weather research and forecasting model

Treesearch

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2012-01-01

A wildland fire behavior module (WRF-Fire) was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire behavior model that is two-way coupled with the atmospheric model. Near-surface winds from the atmospheric model are interpolated to a finer fire grid and used, with fuel properties...

Coupled land surface/hydrologic/atmospheric models

NASA Technical Reports Server (NTRS)

Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers

1993-01-01

The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.

Thermomechanical modelling of laser surface glazing for H13 tool steel

NASA Astrophysics Data System (ADS)

Kabir, I. R.; Yin, D.; Tamanna, N.; Naher, S.

2018-03-01

A two-dimensional thermomechanical finite element (FE) model of laser surface glazing (LSG) has been developed for H13 tool steel. The direct coupling technique of ANSYS 17.2 (APDL) has been utilised to solve the transient thermomechanical process. A H13 tool steel cylindrical cross-section has been modelled for laser power 200 W and 300 W at constant 0.2 mm beam width and 0.15 ms residence time. The model can predict temperature distribution, stress-strain increments in elastic and plastic region with time and space. The crack formation tendency also can be assumed by analysing the von Mises stress in the heat-concentrated zone. Isotropic and kinematic hardening models have been applied separately to predict the after-yield phenomena. At 200 W laser power, the peak surface temperature achieved is 1520 K which is below the melting point (1727 K) of H13 tool steel. For laser power 300 W, the peak surface temperature is 2523 K. Tensile residual stresses on surface have been found after cooling, which are in agreement with literature. Isotropic model shows higher residual stress that increases with laser power. Conversely, kinematic model gives lower residual stress which decreases with laser power. Therefore, both plasticity models could work in LSG for H13 tool steel.

Asteroid Bennu Temperature Maps for OSIRIS-REx Spacecraft and Instrument Thermal Analyses

NASA Technical Reports Server (NTRS)

Choi, Michael K.; Emery, Josh; Delbo, Marco

2014-01-01

A thermophysical model has been developed to generate asteroid Bennu surface temperature maps for OSIRIS-REx spacecraft and instrument thermal design and analyses at the Critical Design Review (CDR). Two-dimensional temperature maps for worst hot and worst cold cases are used in Thermal Desktop to assure adequate thermal design margins. To minimize the complexity of the Bennu geometry in Thermal Desktop, it is modeled as a sphere instead of the radar shape. The post-CDR updated thermal inertia and a modified approach show that the new surface temperature predictions are more benign. Therefore the CDR Bennu surface temperature predictions are conservative.

Partially soluble organics as cloud condensation nuclei: Role of trace soluble and surface active species

NASA Astrophysics Data System (ADS)

Broekhuizen, K.; Kumar, P. Pradeep; Abbatt, J. P. D.

2004-01-01

The ability of partially soluble organic species to act as cloud condensation nuclei (CCN) has been studied. A Köhler model incorporating solute solubility and droplet surface tension describes the behavior of solid adipic and succinic acid particles, whereas solid azelaic acid activates much more efficiently that predicted. In addition, it was shown that trace levels of either sulfate or surface active species have a dramatic effect on the activation of adipic acid, a moderately soluble organic, as predicted by the full Köhler model. For internally mixed particles in the atmosphere, these effects will greatly enhance the role of organic aerosols as CCN.

Fluorescence quenching near small metal nanoparticles.

PubMed

Pustovit, V N; Shahbazyan, T V

2012-05-28

We develop a microscopic model for fluorescence of a molecule (or semiconductor quantum dot) near a small metal nanoparticle. When a molecule is situated close to metal surface, its fluorescence is quenched due to energy transfer to the metal. We perform quantum-mechanical calculations of energy transfer rates for nanometer-sized Au nanoparticles and find that nonlocal and quantum-size effects significantly enhance dissipation in metal as compared to those predicted by semiclassical electromagnetic models. However, the dependence of transfer rates on molecule's distance to metal nanoparticle surface, d, is significantly weaker than the d(-4) behavior for flat metal surface with a sharp boundary predicted by previous calculations within random phase approximation.

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.

COSIM: A Finite-Difference Computer Model to Predict Ternary Concentration Profiles Associated with Oxidation and Interdiffusion of Overlay-Coated Substrates

NASA Technical Reports Server (NTRS)

Nesbitt, James A.

2000-01-01

A finite-difference computer program (COSIM) has been written which models the one-dimensional, diffusional transport associated with high-temperature oxidation and interdiffusion of overlay-coated substrates. The program predicts concentration profiles for up to three elements in the coating and substrate after various oxidation exposures. Surface recession due to solute loss is also predicted. Ternary cross terms and concentration-dependent diffusion coefficients are taken into account. The program also incorporates a previously-developed oxide growth and spalling model to simulate either isothermal or cyclic oxidation exposures. In addition to predicting concentration profiles after various oxidation exposures, the program can also be used to predict coating fife based on a concentration dependent failure criterion (e.g., surface solute content drops to two percent). The computer code, written in an extension of FORTRAN 77, employs numerous subroutines to make the program flexible and easily modifiable to other coating oxidation problems.

Model-based conifer crown surface reconstruction from multi-ocular high-resolution aerial imagery

NASA Astrophysics Data System (ADS)

Sheng, Yongwei

2000-12-01

Tree crown parameters such as width, height, shape and crown closure are desirable in forestry and ecological studies, but they are time-consuming and labor intensive to measure in the field. The stereoscopic capability of high-resolution aerial imagery provides a way to crown surface reconstruction. Existing photogrammetric algorithms designed to map terrain surfaces, however, cannot adequately extract crown surfaces, especially for steep conifer crowns. Considering crown surface reconstruction in a broader context of tree characterization from aerial images, we develop a rigorous perspective tree image formation model to bridge image-based tree extraction and crown surface reconstruction, and an integrated model-based approach to conifer crown surface reconstruction. Based on the fact that most conifer crowns are in a solid geometric form, conifer crowns are modeled as a generalized hemi-ellipsoid. Both the automatic and semi-automatic approaches are investigated to optimal tree model development from multi-ocular images. The semi-automatic 3D tree interpreter developed in this thesis is able to efficiently extract reliable tree parameters and tree models in complicated tree stands. This thesis starts with a sophisticated stereo matching algorithm, and incorporates tree models to guide stereo matching. The following critical problems are addressed in the model-based surface reconstruction process: (1) the problem of surface model composition from tree models, (2) the occlusion problem in disparity prediction from tree models, (3) the problem of integrating the predicted disparities into image matching, (4) the tree model edge effect reduction on the disparity map, (5) the occlusion problem in orthophoto production, and (6) the foreshortening problem in image matching, which is very serious for conifer crown surfaces. Solutions to the above problems are necessary for successful crown surface reconstruction. The model-based approach was applied to recover the canopy surface of a dense redwood stand using tri-ocular high-resolution images scanned from 1:2,400 aerial photographs. The results demonstrate the approach's ability to reconstruct complicated stands. The model-based approach proposed in this thesis is potentially applicable to other surfaces recovering problems with a priori knowledge about objects.

Coupling fast all-season soil strength land surface model with weather research and forecasting model to assess low-level icing in complex terrain

NASA Astrophysics Data System (ADS)

Sines, Taleena R.

Icing poses as a severe hazard to aircraft safety with financial resources and even human lives hanging in the balance when the decision to ground a flight must be made. When analyzing the effects of ice on aviation, a chief cause for danger is the disruption of smooth airflow, which increases the drag force on the aircraft therefore decreasing its ability to create lift. The Weather Research and Forecast (WRF) model Advanced Research WRF (WRF-ARW) is a collaboratively created, flexible model designed to run on distributed computing systems for a variety of applications including forecasting research, parameterization research, and real-time numerical weather prediction. Land-surface models, one of the physics options available in the WRF-ARW, output surface heat and moisture flux given radiation, precipitation, and surface properties such as soil type. The Fast All-Season Soil STrength (FASST) land-surface model was developed by the U.S. Army ERDC-CRREL in Hanover, New Hampshire. Designed to use both meteorological and terrain data, the model calculates heat and moisture within the surface layer as well as the exchange of these parameters between the soil, surface elements (such as snow and vegetation), and atmosphere. Focusing on the Presidential Mountain Range of New Hampshire under the NASA Experimental Program to Stimulate Competitive Research (EPSCoR) Icing Assessments in Cold and Alpine Environments project, one of the main goals is to create a customized, high resolution model to predict and assess ice accretion in complex terrain. The purpose of this research is to couple the FASST land-surface model with the WRF to improve icing forecasts in complex terrain. Coupling FASST with the WRF-ARW may improve icing forecasts because of its sophisticated approach to handling processes such as meltwater, freezing, thawing, and others that would affect the water and energy budget and in turn affect icing forecasts. Several transformations had to take place in order for the FASST land-surface model and WRF-ARW to work together as fully coupled models. Changes had to be made to the WRF-ARW build mechanisms (Chapter 1, section a) so that FASST would be recognized as a new option that could be chosen through the namelist and compiled with other modules. Similarly, FASST had to be altered to no longer read meteorological data from a file, but accept input from WRF-ARW at each time step in a way that did not alter the integrity or run-time processes of the model. Several icing events were available to test the newly coupled model as well as the performance of other available land-surface models from the WRF-ARW. A variation of event intensities and durations from these events were chosen to give a broader view of the land-surface models' abilities to accurately predict icing in complex terrain. Non- icing events were also used in testing to ensure the land-surface models were not predicting ice in the events where none occurred. When compared to the other land-surface models and observations FASST showed a warm bias in several regions. As the forecasts progressed, FASST appeared to attempt to correct this bias and performed similarly to the other land-surface models and at times better than these land-surface models in areas of the domain not affected by this bias. To correct this warm bias, future investigation should be conducted into the reasoning behind this warm bias, including but not limited to: FASST operation and elevation modeling, WRF-ARW variables and forecasting methods, as well as allowing for spin-up prior to forecast times. Following the correction to the warm bias, FASST can be parallelized to allow for operational forecast performance and included in the WRF-ARW forecasting suite for future software releases. (Abstract shortened by UMI.).

Prediction of Sliding Friction Coefficient Based on a Novel Hybrid Molecular-Mechanical Model.

PubMed

Zhang, Xiaogang; Zhang, Yali; Wang, Jianmei; Sheng, Chenxing; Li, Zhixiong

2018-08-01

Sliding friction is a complex phenomenon which arises from the mechanical and molecular interactions of asperities when examined in a microscale. To reveal and further understand the effects of micro scaled mechanical and molecular components of friction coefficient on overall frictional behavior, a hybrid molecular-mechanical model is developed to investigate the effects of main factors, including different loads and surface roughness values, on the sliding friction coefficient in a boundary lubrication condition. Numerical modelling was conducted using a deterministic contact model and based on the molecular-mechanical theory of friction. In the contact model, with given external loads and surface topographies, the pressure distribution, real contact area, and elastic/plastic deformation of each single asperity contact were calculated. Then asperity friction coefficient was predicted by the sum of mechanical and molecular components of friction coefficient. The mechanical component was mainly determined by the contact width and elastic/plastic deformation, and the molecular component was estimated as a function of the contact area and interfacial shear stress. Numerical results were compared with experimental results and a good agreement was obtained. The model was then used to predict friction coefficients in different operating and surface conditions. Numerical results explain why applied load has a minimum effect on the friction coefficients. They also provide insight into the effect of surface roughness on the mechanical and molecular components of friction coefficients. It is revealed that the mechanical component dominates the friction coefficient when the surface roughness is large (Rq > 0.2 μm), while the friction coefficient is mainly determined by the molecular component when the surface is relatively smooth (Rq < 0.2 μm). Furthermore, optimal roughness values for minimizing the friction coefficient are recommended.

Modeling packed bed sorbent systems with the Pore Surface Diffusion Model: Evidence of facilitated surface diffusion of arsenate in nano-metal (hydr)oxide hybrid ion exchange media.

PubMed

Dale, Sachie; Markovski, Jasmina; Hristovski, Kiril D

2016-09-01

This study explores the possibility of employing the Pore Surface Diffusion Model (PSDM) to predict the arsenic breakthrough curve of a packed bed system operated under continuous flow conditions with realistic groundwater, and consequently minimize the need to conduct pilot scale tests. To provide the nano-metal (hydr)oxide hybrid ion exchange media's performance in realistic water matrices without engaging in taxing pilot scale testing, the multi-point equilibrium batch sorption tests under pseudo-equilibrium conditions were performed; arsenate breakthrough curve of short bed column (SBC) was predicted by the PSDM in the continuous flow experiments; SBC tests were conducted under the same conditions to validate the model. The overlapping Freundlich isotherms suggested that the water matrix and competing ions did not have any denoting effect on sorption capacity of the media when the matrix was changed from arsenic-only model water to real groundwater. As expected, the PSDM provided a relatively good prediction of the breakthrough profile for arsenic-only model water limited by intraparticle mass transports. In contrast, the groundwater breakthrough curve demonstrated significantly faster intraparticle mass transport suggesting to a surface diffusion process, which occurs in parallel to the pore diffusion. A simple selection of DS=1/2 DP appears to be sufficient when describing the facilitated surface diffusion of arsenate inside metal (hydr)oxide nano-enabled hybrid ion-exchange media in presence of sulfate, however, quantification of the factors determining the surface diffusion coefficient's magnitude under different treatment scenarios remained unexplored. Copyright © 2015 Elsevier B.V. All rights reserved.

Chain pooling to minimize prediction error in subset regression. [Monte Carlo studies using population models

NASA Technical Reports Server (NTRS)

Holms, A. G.

1974-01-01

Monte Carlo studies using population models intended to represent response surface applications are reported. Simulated experiments were generated by adding pseudo random normally distributed errors to population values to generate observations. Model equations were fitted to the observations and the decision procedure was used to delete terms. Comparison of values predicted by the reduced models with the true population values enabled the identification of deletion strategies that are approximately optimal for minimizing prediction errors.

Radar Cross Section Prediction for Coated Perfect Conductors with Arbitrary Geometries.

DTIC Science & Technology

1986-01-01

equivalent electric and magnetic surface currents as the desired unknowns. Triangular patch modelling is ap- plied to the boundary surfaces. The method of...matrix inversion for the unknown surface current coefficients. Huygens’ principle is again applied to calculate the scattered electric field produced...differential equations with the equivalent electric and magnetic surface currents as the desired unknowns. Triangular patch modelling is ap- plied to the

Optical Properties of Three Beach Waters: Implications for Predictive Modeling of Enterococci

EPA Science Inventory

Sunlight plays an important role in the inactivation of fecal indicator bacteria in recreational waters. Solar radiation can explain temporal trends in bacterial counts and is commonly used as an explanatory variable in predictive models. Broadband surface radiation provides a ba...

Influence of surface conductivity on the apparent zeta potential of calcite.

PubMed

Li, Shuai; Leroy, Philippe; Heberling, Frank; Devau, Nicolas; Jougnot, Damien; Chiaberge, Christophe

2016-04-15

Zeta potential is a physicochemical parameter of particular importance in describing the surface electrical properties of charged porous media. However, the zeta potential of calcite is still poorly known because of the difficulty to interpret streaming potential experiments. The Helmholtz-Smoluchowski (HS) equation is widely used to estimate the apparent zeta potential from these experiments. However, this equation neglects the influence of surface conductivity on streaming potential. We present streaming potential and electrical conductivity measurements on a calcite powder in contact with an aqueous NaCl electrolyte. Our streaming potential model corrects the apparent zeta potential of calcite by accounting for the influence of surface conductivity and flow regime. We show that the HS equation seriously underestimates the zeta potential of calcite, particularly when the electrolyte is diluted (ionic strength ⩽ 0.01 M) because of calcite surface conductivity. The basic Stern model successfully predicted the corrected zeta potential by assuming that the zeta potential is located at the outer Helmholtz plane, i.e. without considering a stagnant diffuse layer at the calcite-water interface. The surface conductivity of calcite crystals was inferred from electrical conductivity measurements and computed using our basic Stern model. Surface conductivity was also successfully predicted by our surface complexation model. Copyright © 2016 Elsevier Inc. All rights reserved.

Method of and apparatus for modeling interactions

DOEpatents

Budge, Kent G.

2004-01-13

A method and apparatus for modeling interactions can accurately model tribological and other properties and accommodate topological disruptions. Two portions of a problem space are represented, a first with a Lagrangian mesh and a second with an ALE mesh. The ALE and Lagrangian meshes are constructed so that each node on the surface of the Lagrangian mesh is in a known correspondence with adjacent nodes in the ALE mesh. The interaction can be predicted for a time interval. Material flow within the ALE mesh can accurately model complex interactions such as bifurcation. After prediction, nodes in the ALE mesh in correspondence with nodes on the surface of the Lagrangian mesh can be mapped so that they are once again adjacent to their corresponding Lagrangian mesh nodes. The ALE mesh can then be smoothed to reduce mesh distortion that might reduce the accuracy or efficiency of subsequent prediction steps. The process, from prediction through mapping and smoothing, can be repeated until a terminal condition is reached.

Surface Complexation Modeling of Calcite Zeta Potential Measurement in Mixed Brines for Carbonate Wettability Characterization

NASA Astrophysics Data System (ADS)

Song, J.; Zeng, Y.; Biswal, S. L.; Hirasaki, G. J.

2017-12-01

We presents zeta potential measurements and surface complexation modeling (SCM) of synthetic calcite in various conditions. The systematic zeta potential measurement and the proposed SCM provide insight into the role of four potential determining cations (Mg2+, SO42- , Ca2+ and CO32-) and CO2 partial pressure in calcite surface charge formation and facilitate the revealing of calcite wettability alteration induced by brines with designed ionic composition ("smart water"). Brines with varying potential determining ions (PDI) concentration in two different CO2 partial pressure (PCO2) are investigated in experiments. Then, a double layer SCM is developed to model the zeta potential measurements. Moreover, we propose a definition for contribution of charged surface species and quantitatively analyze the variation of charged species contribution when changing brine composition. After showing our model can accurately predict calcite zeta potential in brines containing mixed PDIs, we apply it to predict zeta potential in ultra-low and pressurized CO2 environments for potential applications in carbonate enhanced oil recovery including miscible CO2 flooding and CO2 sequestration in carbonate reservoirs. Model prediction reveals that pure calcite surface will be positively charged in all investigated brines in pressurized CO2 environment (>1atm). Moreover, the sensitivity of calcite zeta potential to CO2 partial pressure in the various brine is found to be in the sequence of Na2CO3 > Na2SO4 > NaCl > MgCl2 > CaCl2 (Ionic strength=0.1M).

Using dry spell dynamics of land surface temperature to evaluate large-scale model representation of soil moisture control on evapotranspiration

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.

2017-04-01

The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description of aerodynamic coupling, uncertainties in vegetation mapping, and errors in down-welling radiation. Rather than compare long-term average LST values with models, we focus on the dynamics of LST during dry spells, when negligible rain falls, and the soil moisture store is drying out. The rate of warming of the land surface, or, more precisely, its warming rate relative to the atmosphere, emphasises the impact of changes in soil moisture control on the surface energy balance. Here we show the application of this approach to model evaluation, with examples at continental and global scales. We can compare the behaviour of both fully-coupled land-atmosphere models, and land surface models forced by observed meteorology. This approach provides insight into a fundamental process that affects predictions on multiple time scales, and which has an important impact for society.

Experimental validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, T. W.; Wu, X. F.

1994-01-01

This research report is presented in three parts. In the first part, acoustical analyses were performed on modes of vibration of the housing of a transmission of a gear test rig developed by NASA. The modes of vibration of the transmission housing were measured using experimental modal analysis. The boundary element method (BEM) was used to calculate the sound pressure and sound intensity on the surface of the housing and the radiation efficiency of each mode. The radiation efficiency of each of the transmission housing modes was then compared to theoretical results for a finite baffled plate. In the second part, analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise level radiated from the box. The FEM was used to predict the vibration, while the BEM was used to predict the sound intensity and total radiated sound power using surface vibration as the input data. Vibration predicted by the FEM model was validated by experimental modal analysis; noise predicted by the BEM was validated by measurements of sound intensity. Three types of results are presented for the total radiated sound power: sound power predicted by the BEM model using vibration data measured on the surface of the box; sound power predicted by the FEM/BEM model; and sound power measured by an acoustic intensity scan. In the third part, the structure used in part two was modified. A rib was attached to the top plate of the structure. The FEM and BEM were then used to predict structural vibration and radiated noise respectively. The predicted vibration and radiated noise were then validated through experimentation.

Predicting wettability behavior of fluorosilica coated metal surface using optimum neural network

NASA Astrophysics Data System (ADS)

Taghipour-Gorjikolaie, Mehran; Valipour Motlagh, Naser

2018-02-01

The interaction between variables, which are effective on the surface wettability, is very complex to predict the contact angles and sliding angles of liquid drops. In this paper, in order to solve this complexity, artificial neural network was used to develop reliable models for predicting the angles of liquid drops. Experimental data are divided into training data and testing data. By using training data and feed forward structure for the neural network and using particle swarm optimization for training the neural network based models, the optimum models were developed. The obtained results showed that regression index for the proposed models for the contact angles and sliding angles are 0.9874 and 0.9920, respectively. As it can be seen, these values are close to unit and it means the reliable performance of the models. Also, it can be inferred from the results that the proposed model have more reliable performance than multi-layer perceptron and radial basis function based models.

[Fire behavior of ground surface fuels in Pinus koraiensis and Quercus mongolica mixed forest under no wind and zero slope condition: a prediction with extended Rothermel model].

PubMed

Zhang, Ji-Li; Liu, Bo-Fei; Chu, Teng-Fei; Di, Xue-Ying; Jin, Sen

2012-06-01

A laboratory burning experiment was conducted to measure the fire spread speed, residual time, reaction intensity, fireline intensity, and flame length of the ground surface fuels collected from a Korean pine (Pinus koraiensis) and Mongolian oak (Quercus mongolica) mixed stand in Maoer Mountains of Northeast China under the conditions of no wind, zero slope, and different moisture content, load, and mixture ratio of the fuels. The results measured were compared with those predicted by the extended Rothermel model to test the performance of the model, especially for the effects of two different weighting methods on the fire behavior modeling of the mixed fuels. With the prediction of the model, the mean absolute errors of the fire spread speed and reaction intensity of the fuels were 0.04 m X min(-1) and 77 kW X m(-2), their mean relative errors were 16% and 22%, while the mean absolute errors of residual time, fireline intensity and flame length were 15.5 s, 17.3 kW X m(-1), and 9.7 cm, and their mean relative errors were 55.5%, 48.7%, and 24%, respectively, indicating that the predicted values of residual time, fireline intensity, and flame length were lower than the observed ones. These errors could be regarded as the lower limits for the application of the extended Rothermel model in predicting the fire behavior of similar fuel types, and provide valuable information for using the model to predict the fire behavior under the similar field conditions. As a whole, the two different weighting methods did not show significant difference in predicting the fire behavior of the mixed fuels by extended Rothermel model. When the proportion of Korean pine fuels was lower, the predicted values of spread speed and reaction intensity obtained by surface area weighting method and those of fireline intensity and flame length obtained by load weighting method were higher; when the proportion of Korean pine needles was higher, the contrary results were obtained.

Surface-rain interactions: differences in copper runoff for copper sheet of different inclination, orientation, and atmospheric exposure conditions.

PubMed

Hedberg, Yolanda S; Goidanich, Sara; Herting, Gunilla; Wallinder, Inger Odnevall

2015-01-01

Predictions of the diffuse dispersion of metals from outdoor constructions such as roofs and facades are necessary for environmental risk assessment and management. An existing predictive model has been compared with measured data of copper runoff from copper sheets exposed at four different inclinations facing four orientations at two different urban sites (Stockholm, Sweden, and Milan, Italy) during a 4-year period. Its applicability has also been investigated for copper sheet exposed at two marine sites(Cadiz, Spain, for 5 years, and Brest, France, for 9 years). Generally the model can be used for all given conditions. However, vertical surfaces should be considered as surfaces inclined 60-80 due to wind driven effects. The most important parameters that influence copper runoff, and not already included in the model, are the wind and rain characteristics that influence the actual rainfall volume impinging the surface of interest.

Assessment of Mars Pathfinder landing site predictions

USGS Publications Warehouse

Golombek, M.P.; Moore, H.J.; Haldemann, A.F.C.; Parker, T.J.; Schofield, J.T.

1999-01-01

Remote sensing data at scales of kilometers and an Earth analog were used to accurately predict the characteristics of the Mars Pathfinder landing site at a scale of meters. The surface surrounding the Mars Pathfinder lander in Ares Vallis appears consistent with orbital interpretations, namely, that it would be a rocky plain composed of materials deposited by catastrophic floods. The surface and observed maximum clast size appears similar to predictions based on an analogous surface of the Ephrata Fan in the Channeled Scabland of Washington state. The elevation of the site measured by relatively small footprint delay-Doppler radar is within 100 m of that determined by two-way ranging and Doppler tracking of the spacecraft. The nearly equal elevations of the Mars Pathfinder and Viking Lander 1 sites allowed a prediction of the atmospheric conditions with altitude (pressure, temperature, and winds) that were well within the entry, descent, and landing design margins. High-resolution (~38 m/pixel) Viking Orbiter 1 images showed a sparsely cratered surface with small knobs with relatively low slopes, consistent with observations of these features from the lander. Measured rock abundance is within 10% of that expected from Viking orbiter thermal observations and models. The fractional area covered by large, potentially hazardous rocks observed is similar to that estimated from model rock distributions based on data from the Viking landing sites, Earth analog sites, and total rock abundance. The bulk and fine-component thermal inertias measured from orbit are similar to those calculated from the observed rock size-frequency distribution. A simple radar echo model based on the reflectivity of the soil (estimated from its bulk density), and the measured fraction of area covered by rocks was used to approximate the quasi-specular and diffuse components of the Earth-based radar echos. Color and albedo orbiter data were used to predict the relatively dust free or unweathered surface around the Pathfinder lander compared to the Viking landing sites. Comparisons with the experiences of selecting the Viking landing sites demonstrate the enormous benefit the Viking data and its analyses and models had on the successful predictions of the Pathfinder site. The Pathfinder experience demonstrates that, in certain locations, geologic processes observed in orbiter data can be used to infer surface characteristics where those processes dominate over other processes affecting the Martian surface layer. Copyright 1999 by the American Geophysical Union.

Assessing the influence of climate change and inter-basin water diversion on Haihe River basin, eastern China: a coupled model approach

NASA Astrophysics Data System (ADS)

Xia, Jun; Wang, Qiang; Zhang, Xiang; Wang, Rui; She, Dunxian

2018-04-01

The modeling of changes in surface water and groundwater in the areas of inter-basin water diversion projects is quite difficult because surface water and groundwater models are run separately most of the time and the lack of sufficient data limits the application of complex surface-water/groundwater coupling models based on physical laws, especially for developing countries. In this study, a distributed surface-water and groundwater coupling model, named the distributed time variant gain model-groundwater model (DTVGM-GWM), was used to assess the influence of climate change and inter-basin water diversion on a watershed hydrological cycle. The DTVGM-GWM model can reflect the interaction processes of surface water and groundwater at basin scale. The model was applied to the Haihe River Basin (HRB) in eastern China. The possible influences of climate change and the South-to-North Water Diversion Project (SNWDP) on surface water and groundwater in the HRB were analyzed under various scenarios. The results showed that the newly constructed model DTVGM-GWM can reasonably simulate the surface and river runoff, and describe the spatiotemporal distribution characteristics of groundwater level, groundwater storage and phreatic recharge. The prediction results under different scenarios showed a decline in annual groundwater exploitation and also runoff in the HRB, while an increase of groundwater storage and groundwater level after the SNWDP's operation. Additionally, as the project also addresses future scenarios, a slight increase is predicted in the actual evapotranspiration, soil water content and phreatic recharge. This study provides valuable insights for developing sustainable groundwater management options for the HRB.

Optimal averaging of soil moisture predictions from ensemble land surface model simulations

USDA-ARS?s Scientific Manuscript database

The correct interpretation of ensemble information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble’s mutual error covariance. Here we propose a new technique for obtaining such information using an instrumental variabl...

Challenges in soil erosion research and prediction model development

USDA-ARS?s Scientific Manuscript database

Quantification of soil erosion has been traditionally considered as a surface hydrologic process with equations for soil detachment and sediment transport derived from the mechanics and hydraulics of the rainfall and surface flow. Under the current erosion modeling framework, the soil has a constant...

Predicting drought propagation within peat layers using a three dimensionally explicit voxel based model

NASA Astrophysics Data System (ADS)

Condro, A. A.; Pawitan, H.; Risdiyanto, I.

2018-05-01

Peatlands are very vulnerable to widespread fires during dry seasons, due to availability of aboveground fuel biomass on the surface and belowground fuel biomass on the sub-surface. Hence, understanding drought propagation occurring within peat layers is crucial with regards to disaster mitigation activities on peatlands. Using a three dimensionally explicit voxel-based model of peatland hydrology, this study predicted drought propagation time lags into sub-surface peat layers after drought events occurrence on the surface of about 1 month during La-Nina and 2.5 months during El-Nino. The study was carried out on a high-conservation-value area of oil palm plantation in West Kalimantan. Validity of the model was evaluated and its applicability for disaster mitigation was discussed. The animations of simulated voxels are available at: goo.gl/HDRMYN (El-Nino 2015 episode) and goo.gl/g1sXPl (La-Nina 2016 episode). The model is available at: goo.gl/RiuMQz.

Demonstrating the Importance of `` Good" Models of Land Surface Hydrological Processes

NASA Astrophysics Data System (ADS)

Pitman, A.; Irannejad, P.; McGuffie, K.; Henderson-Sellers, A.

2003-12-01

To reduce the uncertainty in the prediction of land surface climates,, the Atmospheric Model Intercomparison Project (AMIP) Diagnostic Subproject 12 (DSP 12) and the Project for Intercomparison of Land-surface Parameterisation Schemes (PILPS) have analysed dependence of climate simulations on the land-surface schemes (LSSs). This analysis has comprised three efforts: (i) proving that LSSs matter in coupled simulations; (ii) investigating whether improvements in LSSs have occurred over time; and (iii) searching for novel means of validating LSS predictions. In the first, Irannejad et al. (2003) introduce a novel method for evaluating the dependence of 19 AMIP AGCMs' LH on the LSS by excluding the impact of the atmosphere. Pseudo LSSs (PLSSs) for LH in the form of multi-variable linear models expressing mean monthly LH as a function of atmospheric forcing are developed. Analysis over three large and climatically diverse river basins shows estimates of mean annual LH from the PLSSs agreeing well with the AGCMs' simulations. RMS errors range from 0.4 to 2.2 W m-2 depending on the region and the AGCM. When the PLSSs are driven by single atmospheric forcings, different LSSs behave differently, and the variability of mean annual LH among AGCMs increases. The second strand of our investigation uncovered a clear generational sequence of land-surface schemes: first generation 'no canopy'; second generation ` SiBlings'; and ` recent schemes'. We conclude that although continental surface modelling has improved over the last 30 years, full confidence remains elusive, in part due to tuning to available observations. Finally, we show that stable water isotopes challenge predictions of evaporation and condensation processes. These three-pronged findings prove that LSSs are important to AGCM and coupled climate predictions; demonstrate that new, or changed, land-surface components increase diversity among simulations; underline the need for validation data and also challenge current parameterisations with novel observations.

Effects of meteorological models on the solution of the surface energy balance and soil temperature variations in bare soils

NASA Astrophysics Data System (ADS)

Saito, Hirotaka; Šimůnek, Jiri

2009-07-01

SummaryA complete evaluation of the soil thermal regime can be obtained by evaluating the movement of liquid water, water vapor, and thermal energy in the subsurface. Such an evaluation requires the simultaneous solution of the system of equations for the surface water and energy balance, and subsurface heat transport and water flow. When only daily climatic data is available, one needs not only to estimate diurnal cycles of climatic data, but to calculate the continuous values of various components in the energy balance equation, using different parameterization methods. The objective of this study is to quantify the impact of the choice of different estimation and parameterization methods, referred together to as meteorological models in this paper, on soil temperature predictions in bare soils. A variety of widely accepted meteorological models were tested on the dataset collected at a proposed low-level radioactive-waste disposal site in the Chihuahua Desert in West Texas. As the soil surface was kept bare during the study, no vegetation effects were evaluated. A coupled liquid water, water vapor, and heat transport model, implemented in the HYDRUS-1D program, was used to simulate diurnal and seasonal soil temperature changes in the engineered cover installed at the site. The modified version of HYDRUS provides a flexible means for using various types of information and different models to evaluate surface mass and energy balance. Different meteorological models were compared in terms of their prediction errors for soil temperatures at seven observation depths. The results obtained indicate that although many available meteorological models can be used to solve the energy balance equation at the soil-atmosphere interface in coupled water, vapor, and heat transport models, their impact on overall simulation results varies. For example, using daily average climatic data led to greater prediction errors, while relatively simple meteorological models may significantly improve soil temperature predictions. On the other hand, while models for the albedo and soil emissivity had little impact on soil temperature predictions, the choice of the atmospheric emissivity models had a greater impact. A comparison of all the different models indicates that the error introduced at the soil atmosphere interface propagates to deeper layers. Therefore, attention needs to be paid not only to the precise determination of the soil hydraulic and thermal properties, but also to the selection of proper meteorological models for the components involved in the surface energy balance calculations.

Imposing constraints on parameter values of a conceptual hydrological model using baseflow response

NASA Astrophysics Data System (ADS)

Dunn, S. M.

Calibration of conceptual hydrological models is frequently limited by a lack of data about the area that is being studied. The result is that a broad range of parameter values can be identified that will give an equally good calibration to the available observations, usually of stream flow. The use of total stream flow can bias analyses towards interpretation of rapid runoff, whereas water quality issues are more frequently associated with low flow condition. This paper demonstrates how model distinctions between surface an sub-surface runoff can be used to define a likelihood measure based on the sub-surface (or baseflow) response. This helps to provide more information about the model behaviour, constrain the acceptable parameter sets and reduce uncertainty in streamflow prediction. A conceptual model, DIY, is applied to two contrasting catchments in Scotland, the Ythan and the Carron Valley. Parameter ranges and envelopes of prediction are identified using criteria based on total flow efficiency, baseflow efficiency and combined efficiencies. The individual parameter ranges derived using the combined efficiency measures still cover relatively wide bands, but are better constrained for the Carron than the Ythan. This reflects the fact that hydrological behaviour in the Carron is dominated by a much flashier surface response than in the Ythan. Hence, the total flow efficiency is more strongly controlled by surface runoff in the Carron and there is a greater contrast with the baseflow efficiency. Comparisons of the predictions using different efficiency measures for the Ythan also suggest that there is a danger of confusing parameter uncertainties with data and model error, if inadequate likelihood measures are defined.

Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100.

PubMed

Aalto, Juha; Harrison, Stephan; Luoto, Miska

2017-09-11

The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO 2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Cryogenic land surface processes characterise the periglacial realm and control landscape development and ecosystem functioning. Here, via statistical modelling, the authors predict a 72% reduction of the periglacial realm in Northern Europe by 2050, and almost complete disappearance by 2100.

Modeling and experiments of the adhesion force distribution between particles and a surface.

PubMed

You, Siming; Wan, Man Pun

2014-06-17

Due to the existence of surface roughness in real surfaces, the adhesion force between particles and the surface where the particles are deposited exhibits certain statistical distributions. Despite the importance of adhesion force distribution in a variety of applications, the current understanding of modeling adhesion force distribution is still limited. In this work, an adhesion force distribution model based on integrating the root-mean-square (RMS) roughness distribution (i.e., the variation of RMS roughness on the surface in terms of location) into recently proposed mean adhesion force models was proposed. The integration was accomplished by statistical analysis and Monte Carlo simulation. A series of centrifuge experiments were conducted to measure the adhesion force distributions between polystyrene particles (146.1 ± 1.99 μm) and various substrates (stainless steel, aluminum and plastic, respectively). The proposed model was validated against the measured adhesion force distributions from this work and another previous study. Based on the proposed model, the effect of RMS roughness distribution on the adhesion force distribution of particles on a rough surface was explored, showing that both the median and standard deviation of adhesion force distribution could be affected by the RMS roughness distribution. The proposed model could predict both van der Waals force and capillary force distributions and consider the multiscale roughness feature, greatly extending the current capability of adhesion force distribution prediction.

Comparisons of the Maxwell and CLL gas/surface interaction models using DSMC

NASA Technical Reports Server (NTRS)

Hedahl, Marc O.; Wilmoth, Richard G.

1995-01-01

The behavior of two different models of gas-surface interactions is studied using the Direct Simulation Monte Carlo (DSMC) method. The DSMC calculations examine differences in predictions of aerodynamic forces and heat transfer between the Maxwell and the Cercignani-Lampis-Lord (CLL) models for flat plate configurations at freestream conditions corresponding to a 140 km orbit around Venus. The size of the flat plate represents one of the solar panels on the Magellan spacecraft, and the freestream conditions correspond to those experienced during aerobraking maneuvers. Results are presented for both a single flat plate and a two-plate configuration as a function of angle of attack and gas-surface accommodation coefficients. The two-plate system is not representative of the Magellan geometry but is studied to explore possible experiments that might be used to differentiate between the two gas-surface interaction models. The Maxwell and CLL models produce qualitatively similar results for the aerodynamic forces and heat transfer on a single flat plate. However, the flow fields produced with the two models are qualitatively different for both the single-plate and two-plate calculations. These differences in the flowfield lead to predictions of the angle of attack for maximum heat transfer in a two plate configuration that are distinctly different for the two gas-surface interactions models.

Impact of land surface conditions on the predictability of hydrologic processes and mountain-valley circulations in the North American Monsoon region

NASA Astrophysics Data System (ADS)

Xiang, T.; Vivoni, E. R.; Gochis, D. J.; Mascaro, G.

2015-12-01

Heterogeneous land surface conditions are essential components of land-atmosphere interactions in regions of complex terrain and have the potential to affect convective precipitation formation. Yet, due to their high complexity, hydrologic processes over mountainous regions are not well understood, and are usually parameterized in simple ways within coupled land-atmosphere modeling frameworks. With the improving model physics and spatial resolution of numerical weather prediction models, there is an urgent need to understand how land surface processes affect local and regional meteorological processes. In the North American Monsoon (NAM) region, the summer rainy season is accompanied by a dramatic greening of mountain ecosystems that adds spatiotemporal variability in vegetation which is anticipated to impact the conditions leading to convection, mountain-valley circulations and mesoscale organization. In this study, we present results from a detailed analysis of a high-resolution (1 km) land surface model, Noah-MP, in a large, mountainous watershed of the NAM region - the Rio Sonora (21,264 km2) in Mexico. In addition to capturing the spatial variations in terrain and soil distributions, recently-developed features in Noah-MP allow the model to read time-varying vegetation parameters derived from remotely-sensed vegetation indices; however, this new implementation has not been fully evaluated. Therefore, we assess the simulated spatiotemporal fields of soil moisture, surface temperature and surface energy fluxes through comparisons to remote sensing products and results from coarser land surface models obtained from the North American Land Data Assimilation System. We focus attention on the impact of vegetation changes along different elevation bands on the diurnal cycle of surface energy fluxes to provide a baseline for future analyses of mountain-valley circulations using a coupled land-atmosphere modeling system. Our study also compares limited streamflow observations in the large watershed to simulations using the terrain and channel routing when Noah-MP is run within the WRF-Hydro modeling framework, with the goals of validating the rainfall-runoff partitioning and translating the spatiotemporal mountain processes into improvements in streamflow predictions.

The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations

NASA Astrophysics Data System (ADS)

Walters, David; Boutle, Ian; Brooks, Malcolm; Melvin, Thomas; Stratton, Rachel; Vosper, Simon; Wells, Helen; Williams, Keith; Wood, Nigel; Allen, Thomas; Bushell, Andrew; Copsey, Dan; Earnshaw, Paul; Edwards, John; Gross, Markus; Hardiman, Steven; Harris, Chris; Heming, Julian; Klingaman, Nicholas; Levine, Richard; Manners, James; Martin, Gill; Milton, Sean; Mittermaier, Marion; Morcrette, Cyril; Riddick, Thomas; Roberts, Malcolm; Sanchez, Claudio; Selwood, Paul; Stirling, Alison; Smith, Chris; Suri, Dan; Tennant, Warren; Vidale, Pier Luigi; Wilkinson, Jonathan; Willett, Martin; Woolnough, Steve; Xavier, Prince

2017-04-01

We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

A compound reconstructed prediction model for nonstationary climate processes

NASA Astrophysics Data System (ADS)

Wang, Geli; Yang, Peicai

2005-07-01

Based on the idea of climate hierarchy and the theory of state space reconstruction, a local approximation prediction model with the compound structure is built for predicting some nonstationary climate process. By means of this model and the data sets consisting of north Indian Ocean sea-surface temperature, Asian zonal circulation index and monthly mean precipitation anomaly from 37 observation stations in the Inner Mongolia area of China (IMC), a regional prediction experiment for the winter precipitation of IMC is also carried out. When using the same sign ratio R between the prediction field and the actual field to measure the prediction accuracy, an averaged R of 63% given by 10 predictions samples is reached.

Model for the prediction of subsurface strata movement due to underground mining

NASA Astrophysics Data System (ADS)

Cheng, Jianwei; Liu, Fangyuan; Li, Siyuan

2017-12-01

The problem of ground control stability due to large underground mining operations is often associated with large movements and deformations of strata. It is a complicated problem, and can induce severe safety or environmental hazards either at the surface or in strata. Hence, knowing the subsurface strata movement characteristics, and making any subsidence predictions in advance, are desirable for mining engineers to estimate any damage likely to affect the ground surface or subsurface strata. Based on previous research findings, this paper broadly applies a surface subsidence prediction model based on the influence function method to subsurface strata, in order to predict subsurface stratum movement. A step-wise prediction model is proposed, to investigate the movement of underground strata. The model involves a dynamic iteration calculation process to derive the movements and deformations for each stratum layer; modifications to the influence method function are also made for more precise calculations. The critical subsidence parameters, incorporating stratum mechanical properties and the spatial relationship of interest at the mining level, are thoroughly considered, with the purpose of improving the reliability of input parameters. Such research efforts can be very helpful to mining engineers’ understanding of the moving behavior of all strata over underground excavations, and assist in making any damage mitigation plan. In order to check the reliability of the model, two methods are carried out and cross-validation applied. One is to use a borehole TV monitor recording to identify the progress of subsurface stratum bedding and caving in a coal mine, the other is to conduct physical modelling of the subsidence in underground strata. The results of these two methods are used to compare with theoretical results calculated by the proposed mathematical model. The testing results agree well with each other, and the acceptable accuracy and reliability of the proposed prediction model are thus validated.

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.

Rainfall-runoff model for prediction of waterborne viral contamination in a small river catchment

NASA Astrophysics Data System (ADS)

Gelati, E.; Dommar, C.; Lowe, R.; Polcher, J.; Rodó, X.

2013-12-01

We present a lumped rainfall-runoff model aimed at providing useful information for the prediction of waterborne viral contamination in small rivers. Viral contamination of water bodies may occur because of the discharge of sewage effluents and of surface runoff over areas affected by animal waste loads. Surface runoff is caused by precipitation that cannot infiltrate due to its intensity and to antecedent soil water content. It may transport animal feces to adjacent water bodies and cause viral contamination. We model streamflow by separating it into two components: subsurface flow, which is produced by infiltrated precipitation; and surface runoff. The model estimates infiltrated and non-infiltrated precipitation and uses impulse-response functions to compute the corresponding fractions of streamflow. The developed methodologies are applied to the Glafkos river, whose catchment extends for 102 km2 and includes the city of Patra. Streamflow and precipitation observations are available at a daily time resolution. Waterborne virus concentration measurements were performed approximately every second week from the beginning of 2011 to mid 2012. Samples were taken at several locations: in river water upstream of Patras and in the urban area; in sea water at the river outlet and approximately 2 km south-west of Patras; in sewage effluents before and after treatment. The rainfall-runoff model was calibrated and validated using observed streamflow and precipitation data. The model contribution to waterborne viral contamination prediction was benchmarked by analyzing the virus concentration measurements together with the estimated surface runoff values. The presented methodology may be a first step towards the development of waterborne viral contamination alert systems. Predicting viral contamination of water bodies would benefit sectors such as water supply and tourism.

Monte Carlo Computational Modeling of Atomic Oxygen Interactions

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Stueber, Thomas J.; Miller, Sharon K.; De Groh, Kim K.

2017-01-01

Computational modeling of the erosion of polymers caused by atomic oxygen in low Earth orbit (LEO) is useful for determining areas of concern for spacecraft environment durability. Successful modeling requires that the characteristics of the environment such as atomic oxygen energy distribution, flux, and angular distribution be properly represented in the model. Thus whether the atomic oxygen is arriving normal to or inclined to a surface and whether it arrives in a consistent direction or is sweeping across the surface such as in the case of polymeric solar array blankets is important to determine durability. When atomic oxygen impacts a polymer surface it can react removing a certain volume per incident atom (called the erosion yield), recombine, or be ejected as an active oxygen atom to potentially either react with other polymer atoms or exit into space. Scattered atoms can also have a lower energy as a result of partial or total thermal accommodation. Many solutions to polymer durability in LEO involve protective thin films of metal oxides such as SiO2 to prevent atomic oxygen erosion. Such protective films also have their own interaction characteristics. A Monte Carlo computational model has been developed which takes into account the various types of atomic oxygen arrival and how it reacts with a representative polymer (polyimide Kapton H) and how it reacts at defect sites in an oxide protective coating, such as SiO2 on that polymer. Although this model was initially intended to determine atomic oxygen erosion behavior at defect sites for the International Space Station solar arrays, it has been used to predict atomic oxygen erosion or oxidation behavior on many other spacecraft components including erosion of polymeric joints, durability of solar array blanket box covers, and scattering of atomic oxygen into telescopes and microwave cavities where oxidation of critical component surfaces can take place. The computational model is a two dimensional model which has the capability to tune the interactions of how the atomic oxygen reacts, scatters, or recombines on polymer or nonreactive surfaces. In addition to the specification of atomic oxygen arrival details, a total of 15 atomic oxygen interaction parameters have been identified as necessary to properly simulate observed interactions and resulting polymer erosion that have been observed in LEO. The tuning of the Monte Carlo model has been accomplished by adjusting interaction parameters so the erosion patterns produced by the model match those from several actual LEO space experiments. Surface texturing in LEO can also be predicted by the model. Such comparison of space tests with ground laboratory experiments have enabled confidence in ground laboratory lifetime prediction of protected polymers. Results of Monte Carlo tuning, examples of surface texturing and undercutting erosion prediction, and several examples of how the model can be used to predict other LEO and Mars orbital space results are presented.

OH+ emission from cometary knots in planetary nebulae

NASA Astrophysics Data System (ADS)

Priestley, F. D.; Barlow, M. J.

2018-05-01

We model the molecular emission from cometary knots in planetary nebulae (PNe) using a combination of photoionization and photodissociation region (PDR) codes, for a range of central star properties and gas densities. Without the inclusion of ionizing extreme ultraviolet (EUV) radiation, our models require central star temperatures T* to be near the upper limit of the range investigated in order to match observed H2 and OH+ surface brightnesses consistent with observations - with the addition of EUV flux, our models reproduce observed OH+ surface brightnesses for T* ≥ 100 kK. For T* < 80 kK, the predicted OH+ surface brightness is much lower, consistent with the non-detection of this molecule in PNe with such central star temperatures. Our predicted level of H2 emission is somewhat weaker than commonly observed in PNe, which may be resolved by the inclusion of shock heating or fluorescence due to UV photons. Some of our models also predict ArH+ and HeH+ rotational line emission above detection thresholds, despite neither molecule having been detected in PNe, although the inclusion of photodissociation by EUV photons, which is neglected by our models, would be expected to reduce their detectability.

Contact and Impact Dynamic Modeling Capabilities of LS-DYNA for Fluid-Structure Interaction Problems

DTIC Science & Technology

2010-12-02

rigid sphere in a vertical water entry,” Applied Ocean Research, 13(1), pp. 43-48. Monaghan, J.J., 1994. “ Simulating free surface flows with SPH ...The kinematic free surface condition was used to determine the intersection between the free surface and the body in the outer flow domain...and the results were compared with analytical and numerical predictions. The predictive capability of ALE and SPH features of LS-DYNA for simulation

Detailed ADM-based Modeling of Shock Retreat and X-ray Emission of τ Sco

NASA Astrophysics Data System (ADS)

Fletcher, C. L.; Petit, V.; Cohen, D. H.; Townsend, R. H.; Wade, G. A.

2018-01-01

Leveraging the improvement of spectropolarimeters over the past few decades, surveys have found that about 10% of OB-type stars host strong (˜ kG) and mostly dipolar surface magnetic fields. One B-type star, τ Sco, has a more complex surface magnetic field than the general population of OB stars. Interestingly, its X-ray luminosity is an order of magnitude higher than predicted from analytical models of magnetized winds. Previous studies of τ Sco's magnetosphere have predicted that the region of closed field loops should be located close to the stellar surface. However, the lack of X-ray variability and the location of the shock-heated plasma measured from forbidden-to-intercombination X-ray line ratios suggest that the hot plasma, and hence the closed magnetic loops, extend considerably farther from the stellar surface, implying a significantly lower mass loss rate than initially assumed. We present an adaptation of the Analytic Dynamical Magnetosphere model, describing the magnetic confinement of the stellar wind, for an arbitrary field loop configuration. This model is used to predict the shock-heated plasma temperatures for individual field loops, which are then compared to high resolution grating spectra from the Chandra X-ray Observatory. This comparison shows that larger closed magnetic loops are needed.

Crucial nesting habitat for gunnison sage-grouse: A spatially explicit hierarchical approach

USGS Publications Warehouse

Aldridge, Cameron L.; Saher, D.J.; Childers, T.M.; Stahlnecker, K.E.; Bowen, Z.H.

2012-01-01

Gunnison sage-grouse (Centrocercus minimus) is a species of special concern and is currently considered a candidate species under Endangered Species Act. Careful management is therefore required to ensure that suitable habitat is maintained, particularly because much of the species' current distribution is faced with exurban development pressures. We assessed hierarchical nest site selection patterns of Gunnison sage-grouse inhabiting the western portion of the Gunnison Basin, Colorado, USA, at multiple spatial scales, using logistic regression-based resource selection functions. Models were selected using Akaike Information Criterion corrected for small sample sizes (AIC c) and predictive surfaces were generated using model averaged relative probabilities. Landscape-scale factors that had the most influence on nest site selection included the proportion of sagebrush cover >5%, mean productivity, and density of 2 wheel-drive roads. The landscape-scale predictive surface captured 97% of known Gunnison sage-grouse nests within the top 5 of 10 prediction bins, implicating 57% of the basin as crucial nesting habitat. Crucial habitat identified by the landscape model was used to define the extent for patch-scale modeling efforts. Patch-scale variables that had the greatest influence on nest site selection were the proportion of big sagebrush cover >10%, distance to residential development, distance to high volume paved roads, and mean productivity. This model accurately predicted independent nest locations. The unique hierarchical structure of our models more accurately captures the nested nature of habitat selection, and allowed for increased discrimination within larger landscapes of suitable habitat. We extrapolated the landscape-scale model to the entire Gunnison Basin because of conservation concerns for this species. We believe this predictive surface is a valuable tool which can be incorporated into land use and conservation planning as well the assessment of future land-use scenarios. ?? 2011 The Wildlife Society.

Implicit Coupling Approach for Simulation of Charring Carbon Ablators

NASA Technical Reports Server (NTRS)

Chen, Yih-Kanq; Gokcen, Tahir

2013-01-01

This study demonstrates that coupling of a material thermal response code and a flow solver with nonequilibrium gas/surface interaction for simulation of charring carbon ablators can be performed using an implicit approach. The material thermal response code used in this study is the three-dimensional version of Fully Implicit Ablation and Thermal response program, which predicts charring material thermal response and shape change on hypersonic space vehicles. The flow code solves the reacting Navier-Stokes equations using Data Parallel Line Relaxation method. Coupling between the material response and flow codes is performed by solving the surface mass balance in flow solver and the surface energy balance in material response code. Thus, the material surface recession is predicted in flow code, and the surface temperature and pyrolysis gas injection rate are computed in material response code. It is demonstrated that the time-lagged explicit approach is sufficient for simulations at low surface heating conditions, in which the surface ablation rate is not a strong function of the surface temperature. At elevated surface heating conditions, the implicit approach has to be taken, because the carbon ablation rate becomes a stiff function of the surface temperature, and thus the explicit approach appears to be inappropriate resulting in severe numerical oscillations of predicted surface temperature. Implicit coupling for simulation of arc-jet models is performed, and the predictions are compared with measured data. Implicit coupling for trajectory based simulation of Stardust fore-body heat shield is also conducted. The predicted stagnation point total recession is compared with that predicted using the chemical equilibrium surface assumption

Numerical Study Comparing RANS and LES Approaches on a Circulation Control Airfoil

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Nishino, Takafumi

2011-01-01

A numerical study over a nominally two-dimensional circulation control airfoil is performed using a large-eddy simulation code and two Reynolds-averaged Navier-Stokes codes. Different Coanda jet blowing conditions are investigated. In addition to investigating the influence of grid density, a comparison is made between incompressible and compressible flow solvers. The incompressible equations are found to yield negligible differences from the compressible equations up to at least a jet exit Mach number of 0.64. The effects of different turbulence models are also studied. Models that do not account for streamline curvature effects tend to predict jet separation from the Coanda surface too late, and can produce non-physical solutions at high blowing rates. Three different turbulence models that account for streamline curvature are compared with each other and with large eddy simulation solutions. All three models are found to predict the Coanda jet separation location reasonably well, but one of the models predicts specific flow field details near the Coanda surface prior to separation much better than the other two. All Reynolds-averaged Navier-Stokes computations produce higher circulation than large eddy simulation computations, with different stagnation point location and greater flow acceleration around the nose onto the upper surface. The precise reasons for the higher circulation are not clear, although it is not solely a function of predicting the jet separation location correctly.

Feedbacks Between Shallow Groundwater Dynamics and Surface Topography on Runoff Generation in Flat Fields

NASA Astrophysics Data System (ADS)

Appels, Willemijn M.; Bogaart, Patrick W.; van der Zee, Sjoerd E. A. T. M.

2017-12-01

In winter, saturation excess (SE) ponding is observed regularly in temperate lowland regions. Surface runoff dynamics are controlled by small topographical features that are unaccounted for in hydrological models. To better understand storage and routing effects of small-scale topography and their interaction with shallow groundwater under SE conditions, we developed a model of reduced complexity to investigate SE runoff generation, emphasizing feedbacks between shallow groundwater dynamics and mesotopography. The dynamic specific yield affected unsaturated zone water storage, causing rapid switches between negative and positive head and a flatter groundwater mound than predicted by analytical agrohydrological models. Accordingly, saturated areas were larger and local groundwater fluxes smaller than predicted, leading to surface runoff generation. Mesotopographic features routed water over larger distances, providing a feedback mechanism that amplified changes to the shape of the groundwater mound. This in turn enhanced runoff generation, but whether it also resulted in runoff events depended on the geometry and location of the depressions. Whereas conditions favorable to runoff generation may abound during winter, these feedbacks profoundly reduce the predictability of SE runoff: statistically identical rainfall series may result in completely different runoff generation. The model results indicate that waterlogged areas in any given rainfall event are larger than those predicted by current analytical groundwater models used for drainage design. This change in the groundwater mound extent has implications for crop growth and damage assessments.

Multi-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability

NASA Astrophysics Data System (ADS)

Ardilouze, Constantin; Batté, L.; Bunzel, F.; Decremer, D.; Déqué, M.; Doblas-Reyes, F. J.; Douville, H.; Fereday, D.; Guemas, V.; MacLachlan, C.; Müller, W.; Prodhomme, C.

2017-12-01

Land surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992-2010 period performed by five different global coupled ocean-atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land-atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.

Mathematical model reveals role of nucleotide signaling in airway surface liquid homeostasis and its dysregulation in cystic fibrosis

PubMed Central

Sandefur, Conner I.; Boucher, Richard C.; Elston, Timothy C.

2017-01-01

Mucociliary clearance is composed of three components (i.e., mucin secretion, airway surface hydration, and ciliary-activity) which function coordinately to clear inhaled microbes and other foreign particles from airway surfaces. Airway surface hydration is maintained by water fluxes driven predominantly by active chloride and sodium ion transport. The ion channels that mediate electrogenic ion transport are regulated by extracellular purinergic signals that signal through G protein-coupled receptors. These purinoreceptors and the signaling pathways they activate have been identified as possible therapeutic targets for treating lung disease. A systems-level description of airway surface liquid (ASL) homeostasis could accelerate development of such therapies. Accordingly, we developed a mathematical model to describe the dynamic coupling of ion and water transport to extracellular purinergic signaling. We trained our model from steady-state and time-dependent experimental measurements made using normal and cystic fibrosis (CF) cultured human airway epithelium. To reproduce CF conditions, reduced chloride secretion, increased potassium secretion, and increased sodium absorption were required. The model accurately predicted ASL height under basal normal and CF conditions and the collapse of surface hydration due to the accelerated nucleotide metabolism associated with CF exacerbations. Finally, the model predicted a therapeutic strategy to deliver nucleotide receptor agonists to effectively rehydrate the ASL of CF airways. PMID:28808008

High Performance Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System at NASA/GSFC

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Kumar, S. V.; Santanello, J. A.; Tian, Y.; Rodell, M.; Mocko, D.; Reichle, R.

2008-12-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters-Lidard et al., 2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. The LIS software was the co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts - North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell et al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of these systems, now use specific configurations of the LIS software in their current implementations. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through 'plugins'. In addition to these capabilities, LIS has also been demonstrated for parameter estimation (Peters-Lidard et al., 2008; Santanello et al., 2007) and data assimilation (Kumar et al., 2008). Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, land data assimilation and parameter estimation will be presented.

Numerical Representation of Wintertime Near-Surface Inversions in the Arctic with a 2.5-km Version of the Global Environmental Multiscale (GEM) Model

NASA Astrophysics Data System (ADS)

Dehghan, A.; Mariani, Z.; Gascon, G.; Bélair, S.; Milbrandt, J.; Joe, P. I.; Crawford, R.; Melo, S.

2017-12-01

Environment and Climate Change Canada (ECCC) is implementing a 2.5-km resolution version of the Global Environmental Multiscale (GEM) model over the Canadian Arctic. Radiosonde observations were used to evaluate the numerical representation of surface-based temperature inversion which is a major feature in the Arctic region. Arctic surface-based inversions are often created by imbalance between radiative cooling processes at surface and warm air advection above. This can have a significant effect on vertical mixing of pollutants and moisture, and ultimately, on cloud formation. It is therefore important to correctly predict the existence of surface inversions along with their characteristics (i.e., intensity and depth). Previous climatological studies showed that the frequency and intensity of surface-based inversions are larger during colder months in the Arctic. Therefore, surface-based inversions were estimated using radiosonde measurements during winter (December 2015 to February 2016) at Iqaluit (Nunavut, Canada). Results show that the inversion intensity can exceed 10 K with depths as large as 1 km. Preliminary evaluation of GEM outputs reveals that the model tends to underestimate the intensity of near-surface inversions, and in some cases, the model failed to predict an inversion. This study presents the factors contributing to this bias including surface temperature and snow cover.

Improved Decadal Climate Prediction in the North Atlantic using EnOI-Assimilated Initial Condition

NASA Astrophysics Data System (ADS)

Li, Q.; Xin, X.; Wei, M.; Zhou, W.

2017-12-01

Decadal prediction experiments of Beijing Climate Center climate system model version 1.1(BCC-CSM1.1) participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation (SODA) reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature (SST) of the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation (EnOI). Then a suite of decadal re-forecasts launched annually over the period 1961-2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal Oscillation (AMO), which is consistent with the better skill of Atlantic meridional overturning circulation (AMOC) predicted by the re-forecasts. We conclude that the EnOI assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.

Optimal averaging of soil moisture predictions from ensemble land surface model simulations

USDA-ARS?s Scientific Manuscript database

The correct interpretation of ensemble 3 soil moisture information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble’s mutual error covariance. Here we propose a new technique for obtaining such information using an inst...

Particulate matter pollution in the coal-producing regions of the Appalachian Mountains: Integrated ground-based measurements and satellite analysis.

PubMed

Aneja, Viney P; Pillai, Priya R; Isherwood, Aaron; Morgan, Peter; Aneja, Saurabh P

2017-04-01

This study integrates the relationship between measured surface concentrations of particulate matter 10 μm or less in diameter (PM 10 ), satellite-derived aerosol optical depth (AOD), and meteorology in Roda, Virginia, during 2008. A multiple regression model was developed to predict the concentrations of particles 2.5 μm or less in diameter (PM 2.5 ) at an additional location in the Appalachia region, Bristol, TN. The model was developed by combining AOD retrievals from Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor on board the EOS Terra and Aqua Satellites with the surface meteorological observations. The multiple regression model predicted PM 2.5 (r 2 = 0.62), and the two-variable (AOD-PM 2.5 ) model predicted PM 2.5 (r 2 = 0.4). The developed model was validated using particulate matter recordings and meteorology observations from another location in the Appalachia region, Hazard, Kentucky. The model was extrapolated to the Roda, VA, sampling site to predict PM 2.5 mass concentrations. We used 10 km x 10 km resolution MODIS 550 nm AOD to predict ground level PM 2.5 . For the relevant period in 2008, in Roda, VA, the predicted PM 2.5 mass concentration is 9.11 ± 5.16 μg m -3 (mean ± 1SD). This is the first study that couples ground-based Particulate Matter measurements with satellite retrievals to predict surface air pollution at Roda, Virginia. Roda is representative of the Appalachian communities that are commonly located in narrow valleys, or "hollows," where homes are placed directly along the roads in a region of active mountaintop mining operations. Our study suggests that proximity to heavy coal truck traffic subjects these communities to chronic exposure to coal dust and leads us to conclude that there is an urgent need for new regulations to address the primary sources of this particulate matter.

Experimental evaluation of radiosity for room sound-field prediction.

PubMed

Hodgson, Murray; Nosal, Eva-Marie

2006-08-01

An acoustical radiosity model was evaluated for how it performs in predicting real room sound fields. This was done by comparing radiosity predictions with experimental results for three existing rooms--a squash court, a classroom, and an office. Radiosity predictions were also compared with those by ray tracing--a "reference" prediction model--for both specular and diffuse surface reflection. Comparisons were made for detailed and discretized echograms, sound-decay curves, sound-propagation curves, and the variations with frequency of four room-acoustical parameters--EDT, RT, D50, and C80. In general, radiosity and diffuse ray tracing gave very similar predictions. Predictions by specular ray tracing were often very different. Radiosity agreed well with experiment in some cases, less well in others. Definitive conclusions regarding the accuracy with which the rooms were modeled, or the accuracy of the radiosity approach, were difficult to draw. The results suggest that radiosity predicts room sound fields with some accuracy, at least as well as diffuse ray tracing and, in general, better than specular ray tracing. The predictions of detailed echograms are less accurate, those of derived room-acoustical parameters more accurate. The results underline the need to develop experimental methods for accurately characterizing the absorptive and reflective characteristics of room surfaces, possible including phase.

Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

Evaluation of black carbon estimations in global aerosol models

NASA Astrophysics Data System (ADS)

Koch, D.; Schulz, M.; Kinne, S.; McNaughton, C.; Spackman, J. R.; Balkanski, Y.; Bauer, S.; Berntsen, T.; Bond, T. C.; Boucher, O.; Chin, M.; Clarke, A.; de Luca, N.; Dentener, F.; Diehl, T.; Dubovik, O.; Easter, R.; Fahey, D. W.; Feichter, J.; Fillmore, D.; Freitag, S.; Ghan, S.; Ginoux, P.; Gong, S.; Horowitz, L.; Iversen, T.; Kirkevåg, A.; Klimont, Z.; Kondo, Y.; Krol, M.; Liu, X.; Miller, R.; Montanaro, V.; Moteki, N.; Myhre, G.; Penner, J. E.; Perlwitz, J.; Pitari, G.; Reddy, S.; Sahu, L.; Sakamoto, H.; Schuster, G.; Schwarz, J. P.; Seland, Ø.; Stier, P.; Takegawa, N.; Takemura, T.; Textor, C.; van Aardenne, J. A.; Zhao, Y.

2009-11-01

We evaluate black carbon (BC) model predictions from the AeroCom model intercomparison project by considering the diversity among year 2000 model simulations and comparing model predictions with available measurements. These model-measurement intercomparisons include BC surface and aircraft concentrations, aerosol absorption optical depth (AAOD) retrievals from AERONET and Ozone Monitoring Instrument (OMI) and BC column estimations based on AERONET. In regions other than Asia, most models are biased high compared to surface concentration measurements. However compared with (column) AAOD or BC burden retreivals, the models are generally biased low. The average ratio of model to retrieved AAOD is less than 0.7 in South American and 0.6 in African biomass burning regions; both of these regions lack surface concentration measurements. In Asia the average model to observed ratio is 0.7 for AAOD and 0.5 for BC surface concentrations. Compared with aircraft measurements over the Americas at latitudes between 0 and 50N, the average model is a factor of 8 larger than observed, and most models exceed the measured BC standard deviation in the mid to upper troposphere. At higher latitudes the average model to aircraft BC ratio is 0.4 and models underestimate the observed BC loading in the lower and middle troposphere associated with springtime Arctic haze. Low model bias for AAOD but overestimation of surface and upper atmospheric BC concentrations at lower latitudes suggests that most models are underestimating BC absorption and should improve estimates for refractive index, particle size, and optical effects of BC coating. Retrieval uncertainties and/or differences with model diagnostic treatment may also contribute to the model-measurement disparity. Largest AeroCom model diversity occurred in northern Eurasia and the remote Arctic, regions influenced by anthropogenic sources. Changing emissions, aging, removal, or optical properties within a single model generated a smaller change in model predictions than the range represented by the full set of AeroCom models. Upper tropospheric concentrations of BC mass from the aircraft measurements are suggested to provide a unique new benchmark to test scavenging and vertical dispersion of BC in global models.

Heat transfer to an unconfined ceiling from an impinging buoyant diffusion flame

NASA Astrophysics Data System (ADS)

Weng, W. G.; Hasemi, Y.

2006-05-01

Impinging flames are used in fire safety research, industrial heating and melting, and aerospace applications. Multiple modes of heat transfer, such as natural convection, forced convection and thermal radiation, etc. are commonly important in those processes. However, the detailed heat transfer mechanisms are not well understood. In this paper, a model is developed to calculate the thermal response of an unconfined nonburning ceiling from an impinging buoyant diffusion flame. This model uses an algorithm for conduction into the ceiling material. It takes account of heat transfer due to radiation from the fire source to the ceiling surface, and due to reradiation from the ceiling surface to other items. Using experimental data, the convective heat transfer coefficient at lower surface is deduced from this model. In addition, the predicted heat fluxes are compared with the existing experimental data, and the comparison results validate the presented model. It is indicated that this model can be used to predict radial-dependent surface temperature histories under a variety of different realistic levels of fire energy generation rates and fire-to-ceiling separation distance.

Computational modeling of in vitro biological responses on polymethacrylate surfaces

PubMed Central

Ghosh, Jayeeta; Lewitus, Dan Y; Chandra, Prafulla; Joy, Abraham; Bushman, Jared; Knight, Doyle; Kohn, Joachim

2011-01-01

The objective of this research was to examine the capabilities of QSPR (Quantitative Structure Property Relationship) modeling to predict specific biological responses (fibrinogen adsorption, cell attachment and cell proliferation index) on thin films of different polymethacrylates. Using 33 commercially available monomers it is theoretically possible to construct a library of over 40,000 distinct polymer compositions. A subset of these polymers were synthesized and solvent cast surfaces were prepared in 96 well plates for the measurement of fibrinogen adsorption. NIH 3T3 cell attachment and proliferation index were measured on spin coated thin films of these polymers. Based on the experimental results of these polymers, separate models were built for homo-, co-, and terpolymers in the library with good correlation between experiment and predicted values. The ability to predict biological responses by simple QSPR models for large numbers of polymers has important implications in designing biomaterials for specific biological or medical applications. PMID:21779132

Model for the ultrasound reflection from micro-beads and cells distributed in layers on a uniform surface

NASA Astrophysics Data System (ADS)

Couture, O.; Cherin, E.; Foster, F. S.

2007-07-01

A model predicting the reflection of ultrasound from multiple layers of small scattering spheres is developed. Predictions of the reflection coefficient, which takes into account the interferences between the different sphere layers, are compared to measurements performed in the 10-80 MHz and 15-35 MHz frequency range with layers of glass beads and spherical acute myeloid leukemia (AML) cells, respectively. For both types of scatterers, the reflection coefficient increases as a function of their density on the surface for less than three superimposed layers, at which point it saturates at 0.38 for glass beads and 0.02 for AML cells. Above three layers, oscillations of the reflection coefficient due to constructive or destructive interference between layers are observed experimentally and are accurately predicted by the model. The use of such a model could lead to a better understanding of the structures observed in layered tissue images.

Construction of a model for predicting creatinine clearance in Japanese patients treated with Cisplatin therapy.

PubMed

Yajima, Airi; Uesawa, Yoshihiro; Ogawa, Chiaki; Yatabe, Megumi; Kondo, Naoki; Saito, Shinichiro; Suzuki, Yoshihiko; Atsuda, Kouichiro; Kagaya, Hajime

2015-05-01

There exist various useful predictive models, such as the Cockcroft-Gault model, for estimating creatinine clearance (CLcr). However, the prediction of renal function is difficult in patients with cancer treated with cisplatin. Therefore, we attempted to construct a new model for predicting CLcr in such patients. Japanese patients with head and neck cancer who had received cisplatin-based chemotherapy were used as subjects. A multiple regression equation was constructed as a model for predicting CLcr values based on background and laboratory data. A model for predicting CLcr, which included body surface area, serum creatinine and albumin, was constructed. The model exhibited good performance prior to cisplatin therapy. In addition, it performed better than previously reported models after cisplatin therapy. The predictive model constructed in the present study displayed excellent potential and was useful for estimating the renal function of patients treated with cisplatin therapy. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Predicting Ground Illuminance

NASA Astrophysics Data System (ADS)

Lesniak, Michael V.; Tregoning, Brett D.; Hitchens, Alexandra E.

2015-01-01

Our Sun outputs 3.85 x 1026 W of radiation, of which roughly 37% is in the visible band. It is directly responsible for nearly all natural illuminance experienced on Earth's surface, either in the form of direct/refracted sunlight or in reflected light bouncing off the surfaces and/or atmospheres of our Moon and the visible planets. Ground illuminance, defined as the amount of visible light intercepting a unit area of surface (from all incident angles), varies over 7 orders of magnitude from day to night. It is highly dependent on well-modeled factors such as the relative positions of the Sun, Earth, and Moon. It is also dependent on less predictable factors such as local atmospheric conditions and weather.Several models have been proposed to predict ground illuminance, including Brown (1952) and Shapiro (1982, 1987). The Brown model is a set of empirical data collected from observation points around the world that has been reduced to a smooth fit of illuminance against a single variable, solar altitude. It provides limited applicability to the Moon and for cloudy conditions via multiplicative reduction factors. The Shapiro model is a theoretical model that treats the atmosphere as a three layer system of light reflectance and transmittance. It has different sets of reflectance and transmittance coefficients for various cloud types.In this paper we compare the models' predictions to ground illuminance data from an observing run at the White Sands missile range (data was obtained from the United Kingdom's Meteorology Office). Continuous illuminance readings were recorded under various cloud conditions, during both daytime and nighttime hours. We find that under clear skies, the Shapiro model tends to better fit the observations during daytime hours with typical discrepancies under 10%. Under cloudy skies, both models tend to poorly predict ground illuminance. However, the Shapiro model, with typical average daytime discrepancies of 25% or less in many cases, performed somewhat better than the Brown model during daytime hours. During nighttime hours under cloudy skies, both models produced erratic results.

Modeling nanostructural surface modifications in metal cutting by an approach of thermodynamic irreversibility: Derivation and experimental validation

NASA Astrophysics Data System (ADS)

Buchkremer, S.; Klocke, F.

2017-01-01

Performance and operational safety of many metal parts in engineering depend on their surface integrity. During metal cutting, large thermomechanical loads and high gradients of the loads concerning time and location act on the surfaces and may yield significant structural material modifications, which alter the surface integrity. In this work, the derivation and validation of a model of nanostructural surface modifications in metal cutting are presented. For the first time in process modeling, initiation and kinetics of these modifications are predicted using a thermodynamic potential, which considers the interdependent developments of plastic work, dissipation, heat conduction and interface energy as well as the associated productions and flows of entropy. The potential is expressed based on the free Helmholtz energy. The irreversible thermodynamic state changes in the workpiece surface are homogenized over the volume in order to bridge the gap between discrete phenomena involved with the initiation and kinetics of dynamic recrystallization and its macroscopic implications for surface integrity. The formulation of the thermodynamic potential is implemented into a finite element model of orthogonal cutting of steel AISI 4140. Close agreement is achieved between predicted nanostructures and those obtained in transmission electron microscopical investigations of specimen produced in cutting experiments.

Evaluation of snow modeling with Noah and Noah-MP land surface models in NCEP GFS/CFS system

NASA Astrophysics Data System (ADS)

Dong, J.; Ek, M. B.; Wei, H.; Meng, J.

2017-12-01

Land surface serves as lower boundary forcing in global forecast system (GFS) and climate forecast system (CFS), simulating interactions between land and the atmosphere. Understanding the underlying land model physics is a key to improving weather and seasonal prediction skills. With the upgrades in land model physics (e.g., release of newer versions of a land model), different land initializations, changes in parameterization schemes used in the land model (e.g., land physical parametrization options), and how the land impact is handled (e.g., physics ensemble approach), it always prompts the necessity that climate prediction experiments need to be re-conducted to examine its impact. The current NASA LIS (version 7) integrates NOAA operational land surface and hydrological models (NCEP's Noah, versions from 2.7.1 to 3.6 and the future Noah-MP), high-resolution satellite and observational data, and land DA tools. The newer versions of the Noah LSM used in operational models have a variety of enhancements compared to older versions, where the Noah-MP allows for different physics parameterization options and the choice could have large impact on physical processes underlying seasonal predictions. These impacts need to be reexamined before implemented into NCEP operational systems. A set of offline numerical experiments driven by the GFS forecast forcing have been conducted to evaluate the impact of snow modeling with daily Global Historical Climatology Network (GHCN).

Uncertainty of climate change impact on groundwater reserves - Application to a chalk aquifer

NASA Astrophysics Data System (ADS)

Goderniaux, Pascal; Brouyère, Serge; Wildemeersch, Samuel; Therrien, René; Dassargues, Alain

2015-09-01

Recent studies have evaluated the impact of climate change on groundwater resources for different geographical and climatic contexts. However, most studies have either not estimated the uncertainty around projected impacts or have limited the analysis to the uncertainty related to climate models. In this study, the uncertainties around impact projections from several sources (climate models, natural variability of the weather, hydrological model calibration) are calculated and compared for the Geer catchment (465 km2) in Belgium. We use a surface-subsurface integrated model implemented using the finite element code HydroGeoSphere, coupled with climate change scenarios (2010-2085) and the UCODE_2005 inverse model, to assess the uncertainty related to the calibration of the hydrological model. This integrated model provides a more realistic representation of the water exchanges between surface and subsurface domains and constrains more the calibration with the use of both surface and subsurface observed data. Sensitivity and uncertainty analyses were performed on predictions. The linear uncertainty analysis is approximate for this nonlinear system, but it provides some measure of uncertainty for computationally demanding models. Results show that, for the Geer catchment, the most important uncertainty is related to calibration of the hydrological model. The total uncertainty associated with the prediction of groundwater levels remains large. By the end of the century, however, the uncertainty becomes smaller than the predicted decline in groundwater levels.

Estimation of soil hydraulic properties with microwave techniques

NASA Technical Reports Server (NTRS)

Oneill, P. E.; Gurney, R. J.; Camillo, P. J.

1985-01-01

Useful quantitative information about soil properties may be obtained by calibrating energy and moisture balance models with remotely sensed data. A soil physics model solves heat and moisture flux equations in the soil profile and is driven by the surface energy balance. Model generated surface temperature and soil moisture and temperature profiles are then used in a microwave emission model to predict the soil brightness temperature. The model hydraulic parameters are varied until the predicted temperatures agree with the remotely sensed values. This method is used to estimate values for saturated hydraulic conductivity, saturated matrix potential, and a soil texture parameter. The conductivity agreed well with a value measured with an infiltration ring and the other parameters agreed with values in the literature.

Skilful multi-year predictions of tropical trans-basin climate variability

PubMed Central

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-01-01

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation. PMID:25897996

Skilful multi-year predictions of tropical trans-basin climate variability.

PubMed

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-04-21

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation.

Predicting the Occurrence of Cave-Inhabiting Fauna Based on Features of the Earth Surface Environment.

PubMed

Christman, Mary C; Doctor, Daniel H; Niemiller, Matthew L; Weary, David J; Young, John A; Zigler, Kirk S; Culver, David C

2016-01-01

One of the most challenging fauna to study in situ is the obligate cave fauna because of the difficulty of sampling. Cave-limited species display patchy and restricted distributions, but it is often unclear whether the observed distribution is a sampling artifact or a true restriction in range. Further, the drivers of the distribution could be local environmental conditions, such as cave humidity, or they could be associated with surface features that are surrogates for cave conditions. If surface features can be used to predict the distribution of important cave taxa, then conservation management is more easily obtained. We examined the hypothesis that the presence of major faunal groups of cave obligate species could be predicted based on features of the earth surface. Georeferenced records of cave obligate amphipods, crayfish, fish, isopods, beetles, millipedes, pseudoscorpions, spiders, and springtails within the area of Appalachian Landscape Conservation Cooperative in the eastern United States (Illinois to Virginia and New York to Alabama) were assigned to 20 x 20 km grid cells. Habitat suitability for these faunal groups was modeled using logistic regression with twenty predictor variables within each grid cell, such as percent karst, soil features, temperature, precipitation, and elevation. Models successfully predicted the presence of a group greater than 65% of the time (mean = 88%) for the presence of single grid cell endemics, and for all faunal groups except pseudoscorpions. The most common predictor variables were latitude, percent karst, and the standard deviation of the Topographic Position Index (TPI), a measure of landscape rugosity within each grid cell. The overall success of these models points to a number of important connections between the surface and cave environments, and some of these, especially soil features and topographic variability, suggest new research directions. These models should prove to be useful tools in predicting the presence of species in understudied areas.

Predicting the Occurrence of Cave-Inhabiting Fauna Based on Features of the Earth Surface Environment

PubMed Central

Doctor, Daniel H.; Niemiller, Matthew L.; Weary, David J.; Young, John A.; Zigler, Kirk S.

2016-01-01

One of the most challenging fauna to study in situ is the obligate cave fauna because of the difficulty of sampling. Cave-limited species display patchy and restricted distributions, but it is often unclear whether the observed distribution is a sampling artifact or a true restriction in range. Further, the drivers of the distribution could be local environmental conditions, such as cave humidity, or they could be associated with surface features that are surrogates for cave conditions. If surface features can be used to predict the distribution of important cave taxa, then conservation management is more easily obtained. We examined the hypothesis that the presence of major faunal groups of cave obligate species could be predicted based on features of the earth surface. Georeferenced records of cave obligate amphipods, crayfish, fish, isopods, beetles, millipedes, pseudoscorpions, spiders, and springtails within the area of Appalachian Landscape Conservation Cooperative in the eastern United States (Illinois to Virginia and New York to Alabama) were assigned to 20 x 20 km grid cells. Habitat suitability for these faunal groups was modeled using logistic regression with twenty predictor variables within each grid cell, such as percent karst, soil features, temperature, precipitation, and elevation. Models successfully predicted the presence of a group greater than 65% of the time (mean = 88%) for the presence of single grid cell endemics, and for all faunal groups except pseudoscorpions. The most common predictor variables were latitude, percent karst, and the standard deviation of the Topographic Position Index (TPI), a measure of landscape rugosity within each grid cell. The overall success of these models points to a number of important connections between the surface and cave environments, and some of these, especially soil features and topographic variability, suggest new research directions. These models should prove to be useful tools in predicting the presence of species in understudied areas. PMID:27532611

Predicting the occurrence of cave-inhabiting fauna based on features of the earth surface environment

USGS Publications Warehouse

Christman, Mary C.; Doctor, Daniel H.; Niemiller, Matthew L.; Weary, David J.; Young, John A.; Zigler, Kirk S.; Culver, David C.

2016-01-01

One of the most challenging fauna to study in situ is the obligate cave fauna because of the difficulty of sampling. Cave-limited species display patchy and restricted distributions, but it is often unclear whether the observed distribution is a sampling artifact or a true restriction in range. Further, the drivers of the distribution could be local environmental conditions, such as cave humidity, or they could be associated with surface features that are surrogates for cave conditions. If surface features can be used to predict the distribution of important cave taxa, then conservation management is more easily obtained. We examined the hypothesis that the presence of major faunal groups of cave obligate species could be predicted based on features of the earth surface. Georeferenced records of cave obligate amphipods, crayfish, fish, isopods, beetles, millipedes, pseudoscorpions, spiders, and springtails within the area of Appalachian Landscape Conservation Cooperative in the eastern United States (Illinois to Virginia and New York to Alabama) were assigned to 20 x 20 km grid cells. Habitat suitability for these faunal groups was modeled using logistic regression with twenty predictor variables within each grid cell, such as percent karst, soil features, temperature, precipitation, and elevation. Models successfully predicted the presence of a group greater than 65% of the time (mean = 88%) for the presence of single grid cell endemics, and for all faunal groups except pseudoscorpions. The most common predictor variables were latitude, percent karst, and the standard deviation of the Topographic Position Index (TPI), a measure of landscape rugosity within each grid cell. The overall success of these models points to a number of important connections between the surface and cave environments, and some of these, especially soil features and topographic variability, suggest new research directions. These models should prove to be useful tools in predicting the presence of species in understudied areas.

MOLECULAR DYNAMICS MODELING OF SORPTION OF PESTICIDES ONTO THE SURFACES OF KAOLINITE

EPA Science Inventory

To accurately predict the fate of contaminants in the environment and to make sound decisions about environmental remediation, we must accurately understand sorption mechanisms and surface reactivity of environmental particles. Sorption of selected pesticides on kaolinite surface...

Modeling uranium(VI) adsorption onto montmorillonite under varying carbonate concentrations: A surface complexation model accounting for the spillover effect on surface potential

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

Tournassat, C.; Tinnacher, R. M.; Grangeon, S.

The prediction of U(VI) adsorption onto montmorillonite clay is confounded by the complexities of: (1) the montmorillonite structure in terms of adsorption sites on basal and edge surfaces, and the complex interactions between the electrical double layers at these surfaces, and (2) U(VI) solution speciation, which can include cationic, anionic and neutral species. Previous U(VI)-montmorillonite adsorption and modeling studies have typically expanded classical surface complexation modeling approaches, initially developed for simple oxides, to include both cation exchange and surface complexation reactions. However, previous models have not taken into account the unique characteristics of electrostatic surface potentials that occur at montmorillonitemore » edge sites, where the electrostatic surface potential of basal plane cation exchange sites influences the surface potential of neighboring edge sites (‘spillover’ effect).« less

Modeling uranium(VI) adsorption onto montmorillonite under varying carbonate concentrations: A surface complexation model accounting for the spillover effect on surface potential

DOE PAGES

Tournassat, C.; Tinnacher, R. M.; Grangeon, S.; ...

2017-10-06

The prediction of U(VI) adsorption onto montmorillonite clay is confounded by the complexities of: (1) the montmorillonite structure in terms of adsorption sites on basal and edge surfaces, and the complex interactions between the electrical double layers at these surfaces, and (2) U(VI) solution speciation, which can include cationic, anionic and neutral species. Previous U(VI)-montmorillonite adsorption and modeling studies have typically expanded classical surface complexation modeling approaches, initially developed for simple oxides, to include both cation exchange and surface complexation reactions. However, previous models have not taken into account the unique characteristics of electrostatic surface potentials that occur at montmorillonitemore » edge sites, where the electrostatic surface potential of basal plane cation exchange sites influences the surface potential of neighboring edge sites (‘spillover’ effect).« less

The effectiveness and limitations of fuel modeling using the fire and fuels extension to the Forest Vegetation Simulator

Treesearch

Erin K. Noonan-Wright; Nicole M. Vaillant; Alicia L. Reiner

2014-01-01

Fuel treatment effectiveness is often evaluated with fire behavior modeling systems that use fuel models to generate fire behavior outputs. How surface fuels are assigned, either using one of the 53 stylized fuel models or developing custom fuel models, can affect predicted fire behavior. We collected surface and canopy fuels data before and 1, 2, 5, and 8 years after...

A test of source-surface model predictions of heliospheric current sheet inclination

NASA Technical Reports Server (NTRS)

Burton, M. E.; Crooker, N. U.; Siscoe, G. L.; Smith, E. J.

1994-01-01

The orientation of the heliospheric current sheet predicted from a source surface model is compared with the orientation determined from minimum-variance analysis of International Sun-Earth Explorer (ISEE) 3 magnetic field data at 1 AU near solar maximum. Of the 37 cases analyzed, 28 have minimum variance normals that lie orthogonal to the predicted Parker spiral direction. For these cases, the correlation coefficient between the predicted and measured inclinations is 0.6. However, for the subset of 14 cases for which transient signatures (either interplanetary shocks or bidirectional electrons) are absent, the agreement in inclinations improves dramatically, with a correlation coefficient of 0.96. These results validate not only the use of the source surface model as a predictor but also the previously questioned usefulness of minimum variance analysis across complex sector boundaries. In addition, the results imply that interplanetary dynamics have little effect on current sheet inclination at 1 AU. The dependence of the correlation on transient occurrence suggests that the leading edge of a coronal mass ejection (CME), where transient signatures are detected, disrupts the heliospheric current sheet but that the sheet re-forms between the trailing legs of the CME. In this way the global structure of the heliosphere, reflected both in the source surface maps and in the interplanetary sector structure, can be maintained even when the CME occurrence rate is high.

Study on cavitation effect of mechanical seals with laser-textured porous surface

NASA Astrophysics Data System (ADS)

Liu, T.; Chen, H. l.; Liu, Y. H.; Wang, Q.; Liu, Z. B.; Hou, D. H.

2012-11-01

Study on the mechanisms underlying generation of hydrodynamic pressure effect associated with laser-textured porous surface on mechanical seal, is the key to seal and lubricant properties. The theory model of mechanical seals with laser-textured porous surface (LES-MS) based on cavitation model was established. The LST-MS was calculated and analyzed by using Fluent software with full cavitation model and non-cavitation model and film thickness was predicted by the dynamic mesh technique. The results indicate that the effect of hydrodynamic pressure and cavitation are the important reasons to generate liquid film opening force on LST-MS; Cavitation effect can enhance hydrodynamic pressure effect of LST-MS; The thickness of liquid film could be well predicted with the method of dynamic mesh technique on Fluent and it becomes larger as the increasing of shaft speed and the decreasing of pressure.

Modeling, Measurements, and Fundamental Database Development for Nonequilibrium Hypersonic Aerothermodynamics

NASA Technical Reports Server (NTRS)

Bose, Deepak

2012-01-01

The design of entry vehicles requires predictions of aerothermal environment during the hypersonic phase of their flight trajectories. These predictions are made using computational fluid dynamics (CFD) codes that often rely on physics and chemistry models of nonequilibrium processes. The primary processes of interest are gas phase chemistry, internal energy relaxation, electronic excitation, nonequilibrium emission and absorption of radiation, and gas-surface interaction leading to surface recession and catalytic recombination. NASAs Hypersonics Project is advancing the state-of-the-art in modeling of nonequilibrium phenomena by making detailed spectroscopic measurements in shock tube and arcjets, using ab-initio quantum mechanical techniques develop fundamental chemistry and spectroscopic databases, making fundamental measurements of finite-rate gas surface interactions, implementing of detailed mechanisms in the state-of-the-art CFD codes, The development of new models is based on validation with relevant experiments. We will present the latest developments and a roadmap for the technical areas mentioned above

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Kummerow, Christian D.; Einaudi, Franco (Technical Monitor)

2000-01-01

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

AFT: Extending Solar Cycle Prediction with Data Assimilation

NASA Astrophysics Data System (ADS)

Upton, L.; Hathaway, D. H.

2017-12-01

The Advective Flux Transport (AFT) model is an innovative surface flux transport model that simulates the evolution of the radial magnetic field on the surface of the Sun. AFT was designed to be as realistic as possible by 1: incorporating the observed surface flows (meridional flow, differential rotation, and an explicit evolving convective pattern) and by 2: using data assimilation to incorporate the observed magnetic fields directly from line-of-sight (LOS) magnetograms. AFT has proven to be successful in simulating the evolution of the surface magnetic fields on both short time scales (days-weeks) as well as for long time scales (years). In particular, AFT has been shown to accurately predict the evolution of the Sun's dipolar magnetic field 3-5 years in advance. Since the Sun's polar magnetic field strength at solar cycle minimum is the best indicator of the amplitude of the next cycle, this has in turn extended our ability to make solar cycle predictions to 3-5 years before solar minimum occurs. Here, we will discuss some of the challenges of implementing data assimilation into AFT. We will also discuss the role of data assimilation in advancing solar cycle predictive capability.

From crystal chemistry to colloid stability

NASA Astrophysics Data System (ADS)

Gilbert, B.; Burrows, N.; Penn, R. L.

2008-12-01

Aqueous suspensions of ferrihydrite nanoparticles form a colloid with properties that can be understood using classical theories but which additionally exhibit the distinctive phenomenon of nanocluster formation. While use of in situ light and x-ray scattering methods permit the quantitative determination of colloid stability, interparticle interactions, and cluster or aggregate geometry, there are currently few approaches to predict the colloidal behavior of mineral nanoparticles. A longstanding goal of aqueous geochemistry is the rationalization and prediction of the chemical properties of hydrated mineral interfaces from knowledge of interface structure at the molecular scale. Because interfacial acid-base reactions typically lead to the formation of a net electrostatic charge at the surfaces of oxide, hydroxide, and oxyhydroxide mineral surfaces, quantitative descriptions of this behavior have the potential to permit the prediction of long-range interactions between mineral particles. We will evaluate the feasibility of this effort by constructing a model for surface charge formation for ferrihydrite that combines recent insights into the crystal structure of this phase and proposed methods for estimating the pKa of acidic surface groups. We will test the ability of this model to predict the colloidal stability of ferrihydrite suspensions as a function of solution chemistry.

The role of advanced reactive surface area characterization in improving predictions of mineral reaction rates

NASA Astrophysics Data System (ADS)

Beckingham, L. E.; Zhang, S.; Mitnick, E.; Cole, D. R.; Yang, L.; Anovitz, L. M.; Sheets, J.; Swift, A.; Kneafsey, T. J.; Landrot, G.; Mito, S.; Xue, Z.; Steefel, C. I.; DePaolo, D. J.; Ajo Franklin, J. B.

2014-12-01

Geologic sequestration of CO2 in deep sedimentary formations is a promising means of mitigating carbon emissions from coal-fired power plants but the long-term fate of injected CO2 is challenging to predict. Reactive transport models are used to gain insight over long times but rely on laboratory determined mineral reaction rates that have been difficult to extrapolate to field systems. This, in part, is due to a lack of understanding of mineral reactive surface area. Many models use an arbitrary approximation of reactive surface area, applying orders of magnitude scaling factors to measured BET or geometric surface areas. Recently, a few more sophisticated approaches have used 2D and 3D image analyses to determine mineral-specific reactive surface areas that account for the accessibility of minerals. However, the ability of these advanced surface area estimates to improve predictions of mineral reaction rates has yet to be determined. In this study, we fuse X-ray microCT, SEM QEMSCAN, XRD, SANS, and SEM-FIB analysis to determine mineral-specific accessible reactive surface areas for a core sample from the Nagaoka pilot CO2 injection site (Japan). This sample is primarily quartz, plagioclase, smectite, K-feldspar, and pyroxene. SEM imaging shows abundant smectite cement and grain coatings that decrease the fluid accessibility of other minerals. However, analysis of FIB-SEM images reveals that smectite nano-pores are well connected such that access to underlying minerals is not occluded by smectite coatings. Mineral-specific accessible surfaces are determined, accounting for the connectivity of the pore space with and without connected smectite nano-pores. The large-scale impact of variations in accessibility and dissolution rates are then determined through continuum scale modeling using grid-cell specific information on accessible surface areas. This approach will be compared with a traditional continuum scale model using mineral abundances and common surface area estimates. Ultimately, the effectiveness of advanced surface area characterization to improve mineral dissolution rates will be evaluated by comparison of model results with dissolution rates measured from a flow-through column experiment.

Helium segregation on surfaces of plasma-exposed tungsten

DOE PAGES

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; ...

2016-01-21

Here we report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He-n (1 <= n <= 7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides themore » thermodynamic driving force for surface segregation. Elastic interaction force induces drift fluxes of these mobile Hen clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters' drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. Moreover, these near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.« less

Helium segregation on surfaces of plasma-exposed tungsten

NASA Astrophysics Data System (ADS)

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; Hammond, Karl D.; Wirth, Brian D.

2016-02-01

We report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He n (1  ⩽  n  ⩽  7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides the thermodynamic driving force for surface segregation. This elastic interaction force induces drift fluxes of these mobile He n clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters’ drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. These near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.

Modelling Aerodynamically Generated Sound: Recent Advances in Rotor Noise Prediction

NASA Technical Reports Server (NTRS)

Brentner, Kenneth S.

2000-01-01

A great deal of progress has been made in the modeling of aerodynamically generated sound for rotors over the past decade. The Ffowcs Williams-Hawkings (FW-H ) equation has been the foundation for much of the development. Both subsonic and supersonic quadrupole noise formulations have been developed for the prediction of high-speed impulsive noise. In an effort to eliminate the need to compute the quadrupole contribution, the FW-H has also been utilized on permeable surfaces surrounding all physical noise sources. Comparison of the Kirchhoff formulation for moving surfaces with the FW-H equation have shown that the Kirchhoff formulation for moving surfaces can give erroneous results for aeroacoustic problems.

Modeling spray drift and runoff-related inputs of pesticides to receiving water.

PubMed

Zhang, Xuyang; Luo, Yuzhou; Goh, Kean S

2018-03-01

Pesticides move to surface water via various pathways including surface runoff, spray drift and subsurface flow. Little is known about the relative contributions of surface runoff and spray drift in agricultural watersheds. This study develops a modeling framework to address the contribution of spray drift to the total loadings of pesticides in receiving water bodies. The modeling framework consists of a GIS module for identifying drift potential, the AgDRIFT model for simulating spray drift, and the Soil and Water Assessment Tool (SWAT) for simulating various hydrological and landscape processes including surface runoff and transport of pesticides. The modeling framework was applied on the Orestimba Creek Watershed, California. Monitoring data collected from daily samples were used for model evaluation. Pesticide mass deposition on the Orestimba Creek ranged from 0.08 to 6.09% of applied mass. Monitoring data suggests that surface runoff was the major pathway for pesticide entering water bodies, accounting for 76% of the annual loading; the rest 24% from spray drift. The results from the modeling framework showed 81 and 19%, respectively, for runoff and spray drift. Spray drift contributed over half of the mass loading during summer months. The slightly lower spray drift contribution as predicted by the modeling framework was mainly due to SWAT's under-prediction of pesticide mass loading during summer and over-prediction of the loading during winter. Although model simulations were associated with various sources of uncertainties, the overall performance of the modeling framework was satisfactory as evaluated by multiple statistics: for simulation of daily flow, the Nash-Sutcliffe Efficiency Coefficient (NSE) ranged from 0.61 to 0.74 and the percent bias (PBIAS) < 28%; for daily pesticide loading, NSE = 0.18 and PBIAS = -1.6%. This modeling framework will be useful for assessing the relative exposure from pesticides related to spray drift and runoff in receiving waters and the design of management practices for mitigating pesticide exposure within a watershed. Published by Elsevier Ltd.

Description of surface transport in the region of the Belizean Barrier Reef based on observations and alternative high-resolution models

NASA Astrophysics Data System (ADS)

Lindo-Atichati, D.; Curcic, M.; Paris, C. B.; Buston, P. M.

2016-10-01

The gains from implementing high-resolution versus less costly low-resolution models to describe coastal circulation are not always clear, often lacking statistical evaluation. Here we construct a hierarchy of ocean-atmosphere models operating at multiple scales within a 1 × 1° domain of the Belizean Barrier Reef (BBR). The various components of the atmosphere-ocean models are evaluated with in situ observations of surface drifters, wind and sea surface temperature. First, we compare the dispersion and velocity of 55 surface drifters released in the field in summer 2013 to the dispersion and velocity of simulated drifters under alternative model configurations. Increasing the resolution of the ocean model (from 1/12° to 1/100°, from 1 day to 1 h) and atmosphere model forcing (from 1/2° to 1/100°, from 6 h to 1 h), and incorporating tidal forcing incrementally reduces discrepancy between simulated and observed velocities and dispersion. Next, in trying to understand why the high-resolution models improve prediction, we find that resolving both the diurnal sea-breeze and semi-diurnal tides is key to improving the Lagrangian statistics and transport predictions along the BBR. Notably, the model with the highest ocean-atmosphere resolution and with tidal forcing generates a higher number of looping trajectories and sub-mesoscale coherent structures that are otherwise unresolved. Finally, simulations conducted with this model from June to August of 2013 show an intensification of the velocity fields throughout the summer and reveal a mesoscale anticyclonic circulation around Glovers Reef, and sub-mesoscale cyclonic eddies formed in the vicinity of Columbus Island. This study provides a general framework to assess the best surface transport prediction from alternative ocean-atmosphere models using metrics derived from high frequency drifters' data and meteorological stations.

Band Gaps for Elastic Wave Propagation in a Periodic Composite Beam Structure Incorporating Microstructure and Surface Energy Effects

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

Zhang, G. Y.; Gao, X. -L.; Bishop, J. E.

Here, a new model for determining band gaps for elastic wave propagation in a periodic composite beam structure is developed using a non-classical Bernoulli–Euler beam model that incorporates the microstructure, surface energy and rotational inertia effects. The Bloch theorem and transfer matrix method for periodic structures are employed in the formulation. The new model reduces to the classical elasticity-based model when both the microstructure and surface energy effects are not considered. The band gaps predicted by the new model depend on the microstructure and surface elasticity of each constituent material, the unit cell size, the rotational inertia, and the volumemore » fraction. To quantitatively illustrate the effects of these factors, a parametric study is conducted. The numerical results reveal that the band gap predicted by the current non-classical model is always larger than that predicted by the classical model when the beam thickness is very small, but the difference is diminishing as the thickness becomes large. Also, it is found that the first frequency for producing the band gap and the band gap size decrease with the increase of the unit cell length according to both the current and classical models. In addition, it is observed that the effect of the rotational inertia is larger when the exciting frequency is higher and the unit cell length is smaller. Furthermore, it is seen that the volume fraction has a significant effect on the band gap size, and large band gaps can be obtained by tailoring the volume fraction and material parameters.« less

Band Gaps for Elastic Wave Propagation in a Periodic Composite Beam Structure Incorporating Microstructure and Surface Energy Effects

DOE PAGES

Zhang, G. Y.; Gao, X. -L.; Bishop, J. E.; ...

2017-11-20

Here, a new model for determining band gaps for elastic wave propagation in a periodic composite beam structure is developed using a non-classical Bernoulli–Euler beam model that incorporates the microstructure, surface energy and rotational inertia effects. The Bloch theorem and transfer matrix method for periodic structures are employed in the formulation. The new model reduces to the classical elasticity-based model when both the microstructure and surface energy effects are not considered. The band gaps predicted by the new model depend on the microstructure and surface elasticity of each constituent material, the unit cell size, the rotational inertia, and the volumemore » fraction. To quantitatively illustrate the effects of these factors, a parametric study is conducted. The numerical results reveal that the band gap predicted by the current non-classical model is always larger than that predicted by the classical model when the beam thickness is very small, but the difference is diminishing as the thickness becomes large. Also, it is found that the first frequency for producing the band gap and the band gap size decrease with the increase of the unit cell length according to both the current and classical models. In addition, it is observed that the effect of the rotational inertia is larger when the exciting frequency is higher and the unit cell length is smaller. Furthermore, it is seen that the volume fraction has a significant effect on the band gap size, and large band gaps can be obtained by tailoring the volume fraction and material parameters.« less

Understanding the creation of & reducing surface microroughness during polishing & post-processing of glass optics

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

Suratwala, Tayyab

2016-09-22

In the follow study, we have developed a detailed understanding of the chemical and mechanical microscopic interactions that occur during polishing affecting the resulting surface microroughness of the workpiece. Through targeted experiments and modeling, the quantitative relationships of many important polishing parameters & characteristics affecting surface microroughness have been determined. These behaviors and phenomena have been described by a number of models including: (a) the Ensemble Hertzian Multi Gap (EHMG) model used to predict the removal rate and roughness at atomic force microscope (AFM) scale lengths as a function of various polishing parameters, (b) the Island Distribution Gap (IDG) modelmore » used to predict the roughness at larger scale lengths, (c) the Deraguin-Verwey-Landau-Overbeek (DLVO) 3-body electrostatic colloidal model used to predict the interaction of slurry particles at the interface and roughness behavior as a function of pH, and (d) a diffusion/chemical reaction rate model of the incorporation of impurities species into the polishing surface layer (called the Bielby layer). Based on this improved understanding, novel strategies to polish the workpiece have been developed simultaneously leading to both ultrasmooth surfaces and high material removal rates. Some of these strategies include: (a) use of narrow PSD slurries, (b) a novel diamond conditioning recipe of the lap to increase the active contact area between the workpiece and lap without destroying its surface figure, (c) proper control of pH for a given glass type to allow for a uniform distribution of slurry particles at the interface, and (d) increase in applied load just up to the transition between molecular to plastic removal regime for a single slurry particle. These techniques have been incorporated into a previously developed finishing process called Convergent Polishing leading to not just economical finishing process with improved surface figure control, but also simultaneously leading to low roughness surface with high removal rates.« less

The controlling effect of viscous dissipation on magma flow in silicic conduits

USGS Publications Warehouse

Mastin, L.G.

2005-01-01

Nearly all volcanic conduit models assume that flow is Newtonian and isothermal. Such models predict that, during high-flux silicic eruptions, gradients in pressure with depth increase upward as magma accelerates and becomes more viscous, leading to extremely low pressure and fragmentation at a depth of kilometers below the surface. In this paper I show that shear heating, also known as viscous dissipation, dramatically reduces the pressure gradient required for flow and concentrates shear in narrow zones along the conduit margin. The reduction in friction may eliminate the zone of low pressure predicted by isothermal models and move the fragmentation level up to the surface.

Surface Protonation at the Rutile (110) Interface: Explicit Incorporation of Solvation Structure within the Refined MUSIC Model Framework

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

Machesky, Michael L.; Predota, M.; Wesolowski, David J

The detailed solvation structure at the (110) surface of rutile ({alpha}-TiO{sub 2}) in contact with bulk liquid water has been obtained primarily from experimentally verified classical molecular dynamics (CMD) simulations of the ab initio-optimized surface in contact with SPC/E water. The results are used to explicitly quantify H-bonding interactions, which are then used within the refined MUSIC model framework to predict surface oxygen protonation constants. Quantum mechanical molecular dynamics (QMD) simulations in the presence of freely dissociable water molecules produced H-bond distributions around deprotonated surface oxygens very similar to those obtained by CMD with nondissociable SPC/E water, thereby confirming thatmore » the less computationally intensive CMD simulations provide accurate H-bond information. Utilizing this H-bond information within the refined MUSIC model, along with manually adjusted Ti-O surface bond lengths that are nonetheless within 0.05 {angstrom} of those obtained from static density functional theory (DFT) calculations and measured in X-ray reflectivity experiments (as well as bulk crystal values), give surface protonation constants that result in a calculated zero net proton charge pH value (pHznpc) at 25 C that agrees quantitatively with the experimentally determined value (5.4 {+-} 0.2) for a specific rutile powder dominated by the (110) crystal face. Moreover, the predicted pH{sub znpc} values agree to within 0.1 pH unit with those measured at all temperatures between 10 and 250 C. A slightly smaller manual adjustment of the DFT-derived Ti-O surface bond lengths was sufficient to bring the predicted pH{sub znpc} value of the rutile (110) surface at 25 C into quantitative agreement with the experimental value (4.8 {+-} 0.3) obtained from a polished and annealed rutile (110) single crystal surface in contact with dilute sodium nitrate solutions using second harmonic generation (SHG) intensity measurements as a function of ionic strength. Additionally, the H-bond interactions between protolyzable surface oxygen groups and water were found to be stronger than those between bulk water molecules at all temperatures investigated in our CMD simulations (25, 150 and 250 C). Comparison with the protonation scheme previously determined for the (110) surface of isostructural cassiterite ({alpha}-SnO{sub 2}) reveals that the greater extent of H-bonding on the latter surface, and in particular between water and the terminal hydroxyl group (Sn-OH) results in the predicted protonation constant for that group being lower than for the bridged oxygen (Sn-O-Sn), while the reverse is true for the rutile (110) surface. These results demonstrate the importance of H-bond structure in dictating surface protonation behavior, and that explicit use of this solvation structure within the refined MUSIC model framework results in predicted surface protonation constants that are also consistent with a variety of other experimental and computational data.« less

Surface protonation at the rutile (110) interface: explicit incorporation of solvation structure within the refined MUSIC model framework.

PubMed

Machesky, Michael L; Predota, Milan; Wesolowski, David J; Vlcek, Lukas; Cummings, Peter T; Rosenqvist, Jörgen; Ridley, Moira K; Kubicki, James D; Bandura, Andrei V; Kumar, Nitin; Sofo, Jorge O

2008-11-04

The detailed solvation structure at the (110) surface of rutile (alpha-TiO2) in contact with bulk liquid water has been obtained primarily from experimentally verified classical molecular dynamics (CMD) simulations of the ab initio-optimized surface in contact with SPC/E water. The results are used to explicitly quantify H-bonding interactions, which are then used within the refined MUSIC model framework to predict surface oxygen protonation constants. Quantum mechanical molecular dynamics (QMD) simulations in the presence of freely dissociable water molecules produced H-bond distributions around deprotonated surface oxygens very similar to those obtained by CMD with nondissociable SPC/E water, thereby confirming that the less computationally intensive CMD simulations provide accurate H-bond information. Utilizing this H-bond information within the refined MUSIC model, along with manually adjusted Ti-O surface bond lengths that are nonetheless within 0.05 A of those obtained from static density functional theory (DFT) calculations and measured in X-ray reflectivity experiments (as well as bulk crystal values), give surface protonation constants that result in a calculated zero net proton charge pH value (pHznpc) at 25 degrees C that agrees quantitatively with the experimentally determined value (5.4+/-0.2) for a specific rutile powder dominated by the (110) crystal face. Moreover, the predicted pHznpc values agree to within 0.1 pH unit with those measured at all temperatures between 10 and 250 degrees C. A slightly smaller manual adjustment of the DFT-derived Ti-O surface bond lengths was sufficient to bring the predicted pHznpcvalue of the rutile (110) surface at 25 degrees C into quantitative agreement with the experimental value (4.8+/-0.3) obtained from a polished and annealed rutile (110) single crystal surface in contact with dilute sodium nitrate solutions using second harmonic generation (SHG) intensity measurements as a function of ionic strength. Additionally, the H-bond interactions between protolyzable surface oxygen groups and water were found to be stronger than those between bulk water molecules at all temperatures investigated in our CMD simulations (25, 150 and 250 degrees C). Comparison with the protonation scheme previously determined for the (110) surface of isostructural cassiterite (alpha-SnO2) reveals that the greater extent of H-bonding on the latter surface, and in particular between water and the terminal hydroxyl group (Sn-OH) results in the predicted protonation constant for that group being lower than for the bridged oxygen (Sn-O-Sn), while the reverse is true for the rutile (110) surface. These results demonstrate the importance of H-bond structure in dictating surface protonation behavior, and that explicit use of this solvation structure within the refined MUSIC model framework results in predicted surface protonation constants that are also consistent with a variety of other experimental and computational data.

Land-atmosphere coupling and climate prediction over the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Williams, I. N.; Lu, Y.; Kueppers, L. M.; Riley, W. J.; Biraud, S.; Bagley, J. E.; Torn, M. S.

2016-12-01

Biases in land-atmosphere coupling in climate models can contribute to climate prediction biases, but land models are rarely evaluated in the context of this coupling. We tested land-atmosphere coupling and explored effects of land surface parameterizations on climate prediction in a single-column version of the NCAR Community Earth System Model (CESM1.2.2) and an offline Community Land Model (CLM4.5). The correlation between leaf area index (LAI) and surface evaporative fraction (ratio of latent to total turbulent heat flux) was substantially underpredicted compared to observations in the U.S. Southern Great Plains, while the correlation between soil moisture and evaporative fraction was overpredicted by CLM4.5. These correlations were improved by prescribing observed LAI, increasing soil resistance to evaporation, increasing minimum stomatal conductance, and increasing leaf reflectance. The modifications reduced the root mean squared error (RMSE) in daytime 2 m air temperature from 3.6 C to 2 C in summer (JJA), and reduced RMSE in total JJA precipitation from 133 to 84 mm. The modifications had the largest effect on prediction of summer drought in 2006, when a warm bias in daytime 2 m air temperature was reduced from +6 C to a smaller cold bias of -1.3 C, and a corresponding dry bias in total JJA precipitation was reduced from -111 mm to -23 mm. Thus, the role of vegetation in droughts and heat waves is likely underpredicted in CESM1.2.2, and improvements in land surface models can improve prediction of climate extremes.

The role of mechanics during brain development

NASA Astrophysics Data System (ADS)

Budday, Silvia; Steinmann, Paul; Kuhl, Ellen

2014-12-01

Convolutions are a classical hallmark of most mammalian brains. Brain surface morphology is often associated with intelligence and closely correlated with neurological dysfunction. Yet, we know surprisingly little about the underlying mechanisms of cortical folding. Here we identify the role of the key anatomic players during the folding process: cortical thickness, stiffness, and growth. To establish estimates for the critical time, pressure, and the wavelength at the onset of folding, we derive an analytical model using the Föppl-von Kármán theory. Analytical modeling provides a quick first insight into the critical conditions at the onset of folding, yet it fails to predict the evolution of complex instability patterns in the post-critical regime. To predict realistic surface morphologies, we establish a computational model using the continuum theory of finite growth. Computational modeling not only confirms our analytical estimates, but is also capable of predicting the formation of complex surface morphologies with asymmetric patterns and secondary folds. Taken together, our analytical and computational models explain why larger mammalian brains tend to be more convoluted than smaller brains. Both models provide mechanistic interpretations of the classical malformations of lissencephaly and polymicrogyria. Understanding the process of cortical folding in the mammalian brain has direct implications on the diagnostics of neurological disorders including severe retardation, epilepsy, schizophrenia, and autism.

The role of mechanics during brain development

PubMed Central

Budday, Silvia; Steinmann, Paul; Kuhl, Ellen

2014-01-01

Convolutions are a classical hallmark of most mammalian brains. Brain surface morphology is often associated with intelligence and closely correlated to neurological dysfunction. Yet, we know surprisingly little about the underlying mechanisms of cortical folding. Here we identify the role of the key anatomic players during the folding process: cortical thickness, stiffness, and growth. To establish estimates for the critical time, pressure, and the wavelength at the onset of folding, we derive an analytical model using the Föppl-von-Kármán theory. Analytical modeling provides a quick first insight into the critical conditions at the onset of folding, yet it fails to predict the evolution of complex instability patterns in the post-critical regime. To predict realistic surface morphologies, we establish a computational model using the continuum theory of finite growth. Computational modeling not only confirms our analytical estimates, but is also capable of predicting the formation of complex surface morphologies with asymmetric patterns and secondary folds. Taken together, our analytical and computational models explain why larger mammalian brains tend to be more convoluted than smaller brains. Both models provide mechanistic interpretations of the classical malformations of lissencephaly and polymicrogyria. Understanding the process of cortical folding in the mammalian brain has direct implications on the diagnostics of neurological disorders including severe retardation, epilepsy, schizophrenia, and autism. PMID:25202162

Utilization of data and modeling at multiple scales to compare varying formulations of the soil resistance term affecting evaporative flux from the soil surface.

NASA Astrophysics Data System (ADS)

Smits, K. M.; Forsythe, L.; Riley, W. J.; Bisht, G.

2016-12-01

Land Surface Models (LSMs) are used to predict heat, energy, and momentum fluxesoccurring at the land surface and the resulting effects in the soil and atmosphere at various scales.Evaporation from bare soil is an integral component of the water balance that is very difficult toaccurately predict since it is complexly affected by the coupled effects of atmospheric conditions andsoil properties. Inaccurate or simplifying assumptions can have drastic effects on regional and globalLSM predictions and cause available LSMs to predict conflicting values for the soil moistureconditions and surface fluxes (e.g. evapotranspiration, infiltration, run off). The goal of this work isto see how heterogeneities in soil properties can be properly represented with a soil resistance termthat accounts for physically based parameters of the soil system at the land-atmosphere interface.Utilizing a comprehensive, experimental dataset generated from a soil with known, heterogeneousproperties under highly controlled atmospheric conditions, we are able to compare the effectivenessof various parameterizations in two different models. The first being a multiphase, non-equilibrium,and non-isothermal model that minimizes the dependence on fitting parameters. The effects ofcertain mechanisms are better understood at this fine scale and incorporated into the land surfacecomponent of the Accelerated Climate Modeling for Energy project (ALM), which is focused oncapturing the interactions between the surface and the atmosphere at larger scales. The formulationsof the resistance parameter, soil water retention curve (SWRC), and diffusivity through partiallysaturated porous media are of particular interest. The fine scale model was used in conjunction withthe experimental data to test formulations before implementing them into the ACME Land Model(ALM). Effects of these alterations were compared to the existing mechanisms in ALM and thentested against lab and field scale data sets. Initial findings suggest the Tang and Riley (2013a) soilresistance more accurately reproduces results lab and field results on multiple scales whereheterogeneity is present. Further understanding of soil resistance will lead to more robust landsurface models which decrease the reliance on such empirical relationships.

Study of Aerothermodynamic Modeling Issues Relevant to High-Speed Sample Return Vehicles

NASA Technical Reports Server (NTRS)

Johnston, Christopher O.

2014-01-01

This paper examines the application of state-of-the-art coupled ablation and radiation simulations to highspeed sample return vehicles, such as those returning from Mars or an asteroid. A defining characteristic of these entries is that the surface recession rates and temperatures are driven by nonequilibrium convective and radiative heating through a boundary layer with significant surface blowing and ablation products. Measurements relevant to validating the simulation of these phenomena are reviewed and the Stardust entry is identified as providing the best relevant measurements. A coupled ablation and radiation flowfield analysis is presented that implements a finite-rate surface chemistry model. Comparisons between this finite-rate model and a equilibrium ablation model show that, while good agreement is seen for diffusion-limited oxidation cases, the finite-rate model predicts up to 50% lower char rates than the equilibrium model at sublimation conditions. Both the equilibrium and finite rate models predict significant negative mass flux at the surface due to sublimation of atomic carbon. A sensitivity analysis to flowfield and surface chemistry rates show that, for a sample return capsule at 10, 12, and 14 km/s, the sublimation rates for C and C3 provide the largest changes to the convective flux, radiative flux, and char rate. A parametric uncertainty analysis of the radiative heating due to radiation modeling parameters indicates uncertainties ranging from 27% at 10 km/s to 36% at 14 km/s. Applying the developed coupled analysis to the Stardust entry results in temperatures within 10% of those inferred from observations, and final recession values within 20% of measurements, which improves upon the 60% over-prediction at the stagnation point obtained through an uncoupled analysis. Emission from CN Violet is shown to be over-predicted by nearly and order-of-magnitude, which is consistent with the results of previous independent analyses. Finally, the coupled analysis is applied to a 14 km/s Earth entry representative of a Mars sample return. Although the radiative heating provides a larger fraction of the total heating, the influence of ablation and radiation on the flowfield are shown to be similar to Stardust.

Numerical Modelling and Prediction of Erosion Induced by Hydrodynamic Cavitation

NASA Astrophysics Data System (ADS)

Peters, A.; Lantermann, U.; el Moctar, O.

2015-12-01

The present work aims to predict cavitation erosion using a numerical flow solver together with a new developed erosion model. The erosion model is based on the hypothesis that collapses of single cavitation bubbles near solid boundaries form high velocity microjets, which cause sonic impacts with high pressure amplitudes damaging the surface. The erosion model uses information from a numerical Euler-Euler flow simulation to predict erosion sensitive areas and assess the erosion aggressiveness of the flow. The obtained numerical results were compared to experimental results from tests of an axisymmetric nozzle.

Modeling of Turbulent Boundary Layer Surface Pressure Fluctuation Auto and Cross Spectra - Verification and Adjustments Based on TU-144LL Data

NASA Technical Reports Server (NTRS)

Rackl, Robert; Weston, Adam

2005-01-01

The literature on turbulent boundary layer pressure fluctuations provides several empirical models which were compared to the measured TU-144 data. The Efimtsov model showed the best agreement. Adjustments were made to improve its agreement further, consisting of the addition of a broad band peak in the mid frequencies, and a minor modification to the high frequency rolloff. The adjusted Efimtsov predicted and measured results are compared for both subsonic and supersonic flight conditions. Measurements in the forward and middle portions of the fuselage have better agreement with the model than those from the aft portion. For High Speed Civil Transport supersonic cruise, interior levels predicted by use of this model are expected to increase by 1-3 dB due to the adjustments to the Efimtsov model. The space-time cross-correlations and cross-spectra of the fluctuating surface pressure were also investigated. This analysis is an important ingredient in structural acoustic models of aircraft interior noise. Once again the measured data were compared to the predicted levels from the Efimtsov model.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul

2016-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning retrospective predictions at the decadal (5-years), seasonal and sub-seasonal time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and sub-seasonal time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; van den Hurk, B.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2016-12-01

The European consortium earth system model (EC-Earth; http://www.ec-earth.org) has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-08-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

On interfacial properties of tetrahydrofuran: Atomistic and coarse-grained models from molecular dynamics simulation

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

Garrido, J. M.; Algaba, J.; Blas, F. J., E-mail: felipe@uhu.es

2016-04-14

We have determined the interfacial properties of tetrahydrofuran (THF) from direct simulation of the vapor-liquid interface. The molecules are modeled using six different molecular models, three of them based on the united-atom approach and the other three based on a coarse-grained (CG) approach. In the first case, THF is modeled using the transferable parameters potential functions approach proposed by Chandrasekhar and Jorgensen [J. Chem. Phys. 77, 5073 (1982)] and a new parametrization of the TraPPE force fields for cyclic alkanes and ethers [S. J. Keasler et al., J. Phys. Chem. B 115, 11234 (2012)]. In both cases, dispersive and coulombicmore » intermolecular interactions are explicitly taken into account. In the second case, THF is modeled as a single sphere, a diatomic molecule, and a ring formed from three Mie monomers according to the SAFT-γ Mie top-down approach [V. Papaioannou et al., J. Chem. Phys. 140, 054107 (2014)]. Simulations were performed in the molecular dynamics canonical ensemble and the vapor-liquid surface tension is evaluated from the normal and tangential components of the pressure tensor along the simulation box. In addition to the surface tension, we have also obtained density profiles, coexistence densities, critical temperature, density, and pressure, and interfacial thickness as functions of temperature, paying special attention to the comparison between the estimations obtained from different models and literature experimental data. The simulation results obtained from the three CG models as described by the SAFT-γ Mie approach are able to predict accurately the vapor-liquid phase envelope of THF, in excellent agreement with estimations obtained from TraPPE model and experimental data in the whole range of coexistence. However, Chandrasekhar and Jorgensen model presents significant deviations from experimental results. We also compare the predictions for surface tension as obtained from simulation results for all the models with experimental data. The three CG models predict reasonably well (but only qualitatively) the surface tension of THF, as a function of temperature, from the triple point to the critical temperature. On the other hand, only the TraPPE united-atoms models are able to predict accurately the experimental surface tension of the system in the whole temperature range.« less

Effects of modeled tropical sea surface temperature variability on coral reef bleaching predictions

NASA Astrophysics Data System (ADS)

van Hooidonk, R.; Huber, M.

2012-03-01

Future widespread coral bleaching and subsequent mortality has been projected using sea surface temperature (SST) data derived from global, coupled ocean-atmosphere general circulation models (GCMs). While these models possess fidelity in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Niño Southern Oscillation (ENSO) variability. Such weaknesses most likely reduce the accuracy of predicting coral bleaching, but little attention has been paid to the important issue of understanding potential errors and biases, the interaction of these biases with trends, and their propagation in predictions. To analyze the relative importance of various types of model errors and biases in predicting coral bleaching, various intra- and inter-annual frequency bands of observed SSTs were replaced with those frequencies from 24 GCMs 20th century simulations included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. Subsequent thermal stress was calculated and predictions of bleaching were made. These predictions were compared with observations of coral bleaching in the period 1982-2007 to calculate accuracy using an objective measure of forecast quality, the Peirce skill score (PSS). Major findings are that: (1) predictions are most sensitive to the seasonal cycle and inter-annual variability in the ENSO 24-60 months frequency band and (2) because models tend to understate the seasonal cycle at reef locations, they systematically underestimate future bleaching. The methodology we describe can be used to improve the accuracy of bleaching predictions by characterizing the errors and uncertainties involved in the predictions.

Development of a multi-ensemble Prediction Model for China

NASA Astrophysics Data System (ADS)

Brasseur, G. P.; Bouarar, I.; Petersen, A. K.

2016-12-01

As part of the EU-sponsored Panda and MarcoPolo Projects, a multi-model prediction system including 7 models has been developed. Most regional models use global air quality predictions provided by the Copernicus Atmospheric Monitoring Service and downscale the forecast at relatively high spatial resolution in eastern China. The paper will describe the forecast system and show examples of forecasts produced for several Chinese urban areas and displayed on a web site developed by the Dutch Meteorological service. A discussion on the accuracy of the predictions based on a detailed validation process using surface measurements from the Chinese monitoring network will be presented.

Equilibrium Wall Model Implementation in a Nodal Finite Element Flow Solver JENRE for Large Eddy Simulations

DTIC Science & Technology

2017-11-13

condition is applied to the inviscid and viscous fluxes on the wall to satisfy the surface physical condition, but a non -zero surface tangential...velocity profiles and turbulence quantities predicted by the current wall-model implementation agree well with available experimental data and...implementations. The volume and surface integrals based on the non -zero surface velocity in a cell adjacent to the wall show a good agreement with those

The Impact of Ensemble Kalman Filter Assimilation of Near-Surface Observations on the Predictability of Atmospheric Conditions over Complex Terrain: Results from Recent MATERHORN Field Program

NASA Astrophysics Data System (ADS)

Pu, Z.; Zhang, H.

2013-12-01

Near-surface atmospheric observations are the main conventional observations for weather forecasts. However, in modern numerical weather prediction, the use of surface observations, especially those data over complex terrain, remains a unique challenge. There are fundamental difficulties in assimilating surface observations with three-dimensional variational data assimilation (3DVAR). In our early study[1] (Pu et al. 2013), a series of observing system simulation experiments was performed with the ensemble Kalman filter (EnKF) and compared with 3DVAR for its ability to assimilate surface observations with 3DVAR. Using the advanced research version of the Weather Research and Forecasting (WRF) model, results demonstrate that the EnKF can overcome some fundamental limitations that 3DVAR has in assimilating surface observations over complex terrain. Specifically, through its flow-dependent background error term, the EnKF produces more realistic analysis increments over complex terrain in general. Over complex terrain, the EnKF clearly performs better than 3DVAR, because it is more capable of handling surface data in the presence of terrain misrepresentation. With this presentation, we further examine the impact of EnKF data assimilation on the predictability of atmospheric conditions over complex terrain with the WRF model and the observations obtained from the most recent field experiments of the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program. The MATERHORN program provides comprehensive observations over mountainous regions, allowing the opportunity to study the predictability of atmospheric conditions over complex terrain in great details. Specifically, during fall 2012 and spring 2013, comprehensive observations were collected of soil states, surface energy budgets, near-surface atmospheric conditions, and profiling measurements from multiple platforms (e.g., balloon, lidar, radiosondes, etc.) over Dugway Proving Ground (DPG), Utah. With the near-surface observations and sounding data obtained during the MATERHORN fall 2012 field experiment, a month-long cycled EnKF analysis and forecast was produced with the WRF model and an advanced EnKF data assimilation system. Results are compared with the WRF near real-time forecasting during the same month and a set of analysis with 3DVAR data assimilation. Overall evaluation suggests some useful insights on the impacts of different data assimilation methods, surface and soil states, terrain representation on the predictability of atmospheric conditions over mountainous terrain. Details will be presented. References [1] Pu, Z., H. Zhang, and J. A. Anderson,. 'Ensemble Kalman filter assimilation of near-surface observations over complex terrain: Comparison with 3DVAR for short-range forecasts.' Tellus A, vol. 65,19620. 2013. http://dx.doi.org/10.3402/tellusa.v65i0. 19620.

Metal powder absorptivity: Modeling and experiment

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

Boley, C. D.; Mitchell, S. C.; Rubenchik, A. M.

Here, we present results of numerical modeling and direct calorimetric measurements of the powder absorptivity for a number of metals. The modeling results generally correlate well with experiment. We show that the powder absorptivity is determined, to a great extent, by the absorptivity of a flat surface at normal incidence. Our results allow the prediction of the powder absorptivity from normal flat-surface absorptivity measurements.

Metal powder absorptivity: Modeling and experiment

DOE PAGES

Boley, C. D.; Mitchell, S. C.; Rubenchik, A. M.; ...

2016-08-10

Here, we present results of numerical modeling and direct calorimetric measurements of the powder absorptivity for a number of metals. The modeling results generally correlate well with experiment. We show that the powder absorptivity is determined, to a great extent, by the absorptivity of a flat surface at normal incidence. Our results allow the prediction of the powder absorptivity from normal flat-surface absorptivity measurements.

Study on Development of 1D-2D Coupled Real-time Urban Inundation Prediction model

NASA Astrophysics Data System (ADS)

Lee, Seungsoo

2017-04-01

In recent years, we are suffering abnormal weather condition due to climate change around the world. Therefore, countermeasures for flood defense are urgent task. In this research, study on development of 1D-2D coupled real-time urban inundation prediction model using predicted precipitation data based on remote sensing technology is conducted. 1 dimensional (1D) sewerage system analysis model which was introduced by Lee et al. (2015) is used to simulate inlet and overflow phenomena by interacting with surface flown as well as flows in conduits. 2 dimensional (2D) grid mesh refinement method is applied to depict road networks for effective calculation time. 2D surface model is coupled with 1D sewerage analysis model in order to consider bi-directional flow between both. Also parallel computing method, OpenMP, is applied to reduce calculation time. The model is estimated by applying to 25 August 2014 extreme rainfall event which caused severe inundation damages in Busan, Korea. Oncheoncheon basin is selected for study basin and observed radar data are assumed as predicted rainfall data. The model shows acceptable calculation speed with accuracy. Therefore it is expected that the model can be used for real-time urban inundation forecasting system to minimize damages.

Experimental Evaluation of the Thermal Performance of a Water Shield for a Surface Power Reactor

NASA Technical Reports Server (NTRS)

Pearson, J. Boise; Stewart, Eric T.; Reid, Robert S.

2007-01-01

A water based shielding system is being investigated for use on initial lunar surface power systems. The use of water may lower overall cost (as compared to development cost for other materials) and simplify operations in the setup and handling. The thermal hydraulic performance of the shield is of significant interest. The mechanism for transferring heat through the shield is natural convection. Natural convection in a representative lunar surface reactor shield design is evaluated at various power levels in the Water Shield Testbed (WST) at the NASA Marshall Space Flight Center. The experimental data from the WST is used to anchor a CFD model. Performance of a water shield on the lunar surface is then predicted by CFD models anchored to test data. The accompanying viewgraph presentation includes the following topics: 1) Testbed Configuration; 2) Core Heater Placement and Instrumentation; 3) Thermocouple Placement; 4) Core Thermocouple Placement; 5) Outer Tank Thermocouple Placement; 6) Integrated Testbed; 7) Methodology; 8) Experimental Results: Core Temperatures; 9) Experimental Results; Outer Tank Temperatures; 10) CFD Modeling; 11) CFD Model: Anchored to Experimental Results (1-g); 12) CFD MOdel: Prediction for 1/6-g; and 13) CFD Model: Comparison of 1-g to 1/6-g.

Development and application of a catchment scale pesticide fate and transport model for use in drinking water risk assessment.

PubMed

Pullan, S P; Whelan, M J; Rettino, J; Filby, K; Eyre, S; Holman, I P

2016-09-01

This paper describes the development and application of IMPT (Integrated Model for Pesticide Transport), a parameter-efficient tool for predicting diffuse-source pesticide concentrations in surface waters used for drinking water supply. The model was applied to a small UK headwater catchment with high frequency (8h) pesticide monitoring data and to five larger catchments (479-1653km(2)) with sampling approximately every 14days. Model performance was good for predictions of both flow (Nash Sutcliffe Efficiency generally >0.59 and PBIAS <10%) and pesticide concentrations, although low sampling frequency in the larger catchments is likely to mask the true episodic nature of exposure. The computational efficiency of the model, along with the fact that most of its parameters can be derived from existing national soil property data mean that it can be used to rapidly predict pesticide exposure in multiple surface water resources to support operational and strategic risk assessments. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Underestimated AMOC Variability and Implications for AMV and Predictability in CMIP Models

NASA Astrophysics Data System (ADS)

Yan, Xiaoqin; Zhang, Rong; Knutson, Thomas R.

2018-05-01

The Atlantic Meridional Overturning Circulation (AMOC) has profound impacts on various climate phenomena. Using both observations and simulations from the Coupled Model Intercomparison Project Phase 3 and 5, here we show that most models underestimate the amplitude of low-frequency AMOC variability. We further show that stronger low-frequency AMOC variability leads to stronger linkages between the AMOC and key variables associated with the Atlantic multidecadal variability (AMV), and between the subpolar AMV signal and northern hemisphere surface air temperature. Low-frequency extratropical northern hemisphere surface air temperature variability might increase with the amplitude of low-frequency AMOC variability. Atlantic decadal predictability is much higher in models with stronger low-frequency AMOC variability and much lower in models with weaker or without AMOC variability. Our results suggest that simulating realistic low-frequency AMOC variability is very important, both for simulating realistic linkages between AMOC and AMV-related variables and for achieving substantially higher Atlantic decadal predictability.

Effect of Surface Nonequilibrium Thermochemistry in Simulation of Carbon Based Ablators

NASA Technical Reports Server (NTRS)

Chen, Yih-Kang; Gokcen, Tahir

2012-01-01

This study demonstrates that coupling of a material thermal response code and a flow solver using finite-rate gas/surface interaction model provides time-accurate solutions for multidimensional ablation of carbon based charring ablators. The material thermal response code used in this study is the Two-dimensional Implicit Thermal Response and Ablation Program (TITAN), which predicts charring material thermal response and shape change on hypersonic space vehicles. Its governing equations include total energy balance, pyrolysis gas momentum conservation, and a three-component decomposition model. The flow code solves the reacting Navier-Stokes equations using Data Parallel Line Relaxation (DPLR) method. Loose coupling between material response and flow codes is performed by solving the surface mass balance in DPLR and the surface energy balance in TITAN. Thus, the material surface recession is predicted by finite-rate gas/surface interaction boundary conditions implemented in DPLR, and the surface temperature and pyrolysis gas injection rate are computed in TITAN. Two sets of gas/surface interaction chemistry between air and carbon surface developed by Park and Zhluktov, respectively, are studied. Coupled fluid-material response analyses of stagnation tests conducted in NASA Ames Research Center arc-jet facilities are considered. The ablating material used in these arc-jet tests was a Phenolic Impregnated Carbon Ablator (PICA). Computational predictions of in-depth material thermal response and surface recession are compared with the experimental measurements for stagnation cold wall heat flux ranging from 107 to 1100 Watts per square centimeter.

Effect of Non-Equilibrium Surface Thermochemistry in Simulation of Carbon Based Ablators

NASA Technical Reports Server (NTRS)

Chen, Yih-Kanq; Gokcen, Tahir

2012-01-01

This study demonstrates that coupling of a material thermal response code and a flow solver using non-equilibrium gas/surface interaction model provides time-accurate solutions for the multidimensional ablation of carbon based charring ablators. The material thermal response code used in this study is the Two-dimensional Implicit Thermal-response and AblatioN Program (TITAN), which predicts charring material thermal response and shape change on hypersonic space vehicles. Its governing equations include total energy balance, pyrolysis gas mass conservation, and a three-component decomposition model. The flow code solves the reacting Navier-Stokes equations using Data Parallel Line Relaxation (DPLR) method. Loose coupling between the material response and flow codes is performed by solving the surface mass balance in DPLR and the surface energy balance in TITAN. Thus, the material surface recession is predicted by finite-rate gas/surface interaction boundary conditions implemented in DPLR, and the surface temperature and pyrolysis gas injection rate are computed in TITAN. Two sets of nonequilibrium gas/surface interaction chemistry between air and the carbon surface developed by Park and Zhluktov, respectively, are studied. Coupled fluid-material response analyses of stagnation tests conducted in NASA Ames Research Center arc-jet facilities are considered. The ablating material used in these arc-jet tests was Phenolic Impregnated Carbon Ablator (PICA). Computational predictions of in-depth material thermal response and surface recession are compared with the experimental measurements for stagnation cold wall heat flux ranging from 107 to 1100 Watts per square centimeter.

The role of shoe design on the prediction of free torque at the shoe-surface interface using pressure insole technology.

PubMed

Weaver, Brian Thomas; Fitzsimons, Kathleen; Braman, Jerrod; Haut, Roger

2016-09-01

The goal of the current study was to expand on previous work to validate the use of pressure insole technology in conjunction with linear regression models to predict the free torque at the shoe-surface interface that is generated while wearing different athletic shoes. Three distinctly different shoe designs were utilised. The stiffness of each shoe was determined with a material's testing machine. Six participants wore each shoe that was fitted with an insole pressure measurement device and performed rotation trials on an embedded force plate. A pressure sensor mask was constructed from those sensors having a high linear correlation with free torque values. Linear regression models were developed to predict free torques from these pressure sensor data. The models were able to accurately predict their own free torque well (RMS error 3.72 ± 0.74 Nm), but not that of the other shoes (RMS error 10.43 ± 3.79 Nm). Models performing self-prediction were also able to measure differences in shoe stiffness. The results of the current study showed the need for participant-shoe specific linear regression models to insure high prediction accuracy of free torques from pressure sensor data during isolated internal and external rotations of the body with respect to a planted foot.

A coarse grain model for protein-surface interactions

NASA Astrophysics Data System (ADS)

Wei, Shuai; Knotts, Thomas A.

2013-09-01

The interaction of proteins with surfaces is important in numerous applications in many fields—such as biotechnology, proteomics, sensors, and medicine—but fundamental understanding of how protein stability and structure are affected by surfaces remains incomplete. Over the last several years, molecular simulation using coarse grain models has yielded significant insights, but the formalisms used to represent the surface interactions have been rudimentary. We present a new model for protein surface interactions that incorporates the chemical specificity of both the surface and the residues comprising the protein in the context of a one-bead-per-residue, coarse grain approach that maintains computational efficiency. The model is parameterized against experimental adsorption energies for multiple model peptides on different types of surfaces. The validity of the model is established by its ability to quantitatively and qualitatively predict the free energy of adsorption and structural changes for multiple biologically-relevant proteins on different surfaces. The validation, done with proteins not used in parameterization, shows that the model produces remarkable agreement between simulation and experiment.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.

2011-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

Water balance model for mean annual hydrogen and oxygen isotope distributions in surface waters of the contiguous United States

NASA Astrophysics Data System (ADS)

Bowen, Gabriel J.; Kennedy, Casey D.; Liu, Zhongfang; Stalker, Jeremy

2011-12-01

The stable H and O isotope composition of river and stream water records information on runoff sources and land-atmosphere water fluxes within the catchment and is a potentially powerful tool for network-based monitoring of ecohydrological systems. Process-based hydrological models, however, have thus far shown limited power to replicate observed large-scale variation in U.S. surface water isotope ratios. Here we develop a geographic information system-based model to predict long-term annual average surface water isotope ratios across the contiguous United States. We use elevation-explicit, gridded precipitation isotope maps as model input and data from a U.S. Geological Survey monitoring program for validation. We find that models incorporating monthly variation in precipitation-evapotranspiration (P-E) amounts account for the majority (>89%) of isotopic variation and have reduced regional bias relative to models that do not consider intra-annual P-E effects on catchment water balance. Residuals from the water balance model exhibit strong spatial patterning and correlations that suggest model residuals isolate additional hydrological signal. We use interpolated model residuals to generate optimized prediction maps for U.S. surface water δ2H and δ18O values. We show that the modeled surface water values represent a relatively accurate and unbiased proxy for drinking water isotope ratios across the United States, making these data products useful in ecological and criminal forensics applications that require estimates of the local environmental water isotope variation across large geographic regions.

Psychophysically based model of surface gloss perception

NASA Astrophysics Data System (ADS)

Ferwerda, James A.; Pellacini, Fabio; Greenberg, Donald P.

2001-06-01

In this paper we introduce a new model of surface appearance that is based on quantitative studies of gloss perception. We use image synthesis techniques to conduct experiments that explore the relationships between the physical dimensions of glossy reflectance and the perceptual dimensions of glossy appearance. The product of these experiments is a psychophysically-based model of surface gloss, with dimensions that are both physically and perceptually meaningful and scales that reflect our sensitivity to gloss variations. We demonstrate that the model can be used to describe and control the appearance of glossy surfaces in synthesis images, allowing prediction of gloss matches and quantification of gloss differences. This work represents some initial steps toward developing psychophyscial models of the goniometric aspects of surface appearance to complement widely-used colorimetric models.

The effects of finite-rate reactions at the gas/surface interface in support of thermal protection system design

NASA Astrophysics Data System (ADS)

Beerman, Adam Farrell

2011-12-01

Gas-surface modeling is dependent on material type and atmospheric reentry conditions. Lower molecular collisions at the low pressure trajectories make it more likely for occurrences of nonequilibrium, or finite-rate, reactions. Equilibrium is often assumed at the surface of a material as it is a subset of nonequilibrium and is easier to compute, though it can lead to overly conservative predictions. A case where a low density material experiences a low pressure trajectory and designed for equilibrium is the Stardust Return Capsule (SRC) with the Phenolic Impregnated Carbon Ablator (PICA) as its heatshield. Post-flight analysis of the recession on the SRC found that the prediction from the equilibrium model can be more than 50% larger than the measured recession. The Modified Park Model was chosen as the finite-rate model as it contains simple four reactions (oxidation, sublimation, and nitridation) and has been previously used to study individual points of the SRC trajectory. The Modified Park Model cannot model equilibrium so a model BFIAT was developed that allows finite-rate reactions to be applied to the surface for a certain length of time. Finite-rate sublimation was determined to be reaction of importance in the Park Model for SRC-like conditions. The predicted recession on the SRC heatshield experienced a reduction in its overprediction; the finite-rate predictions fall with the measurement error of the recession at three points on the heatshield. The recession reduction was driven by a significant reduction in char formation. There was little change in the pyrolysis gas rate. The finite-rate model was also applied to simulations of various arc-jet tests that covered a range of heating conditions on the surface of the PICA material. Comparison to this experimental data further showed the role of finite-rate reactions and sublimation in the Park Model and conditions that favor the nonequilibrium assumption (heating over 1000 W/cm2). For the emerging PICA material, used for the Mars Science Laboratory and one of two material choices for the Crew Exploration Vehicle, and SRC-like trajectories, a finite-rate model was developed such that the more robust nonequilibrium assumption can be applied to design processes to reduce heatshield mass.

Influence of lake surface area and total phosphorus on annual bluegill growth in small impoundments of central Georgia

USGS Publications Warehouse

Jennings, Cecil A.; Sundmark, Aaron P.

2017-01-01

The relationships between environmental variables and the growth rates of fishes are important and rapidly expanding topics in fisheries ecology. We used an informationtheoretic approach to evaluate the influence of lake surface area and total phosphorus on the age-specific growth rates of Lepomis macrochirus (Bluegill) in 6 small impoundments in central Georgia. We used model averaging to create composite models and determine the relative importance of the variables within each model. Results indicated that surface area was the most important factor in the models predicting growth of Bluegills aged 1–4 years; total phosphorus was also an important predictor for the same age-classes. These results suggest that managers can use water quality and lake morphometry variables to create predictive models specific to their waterbody or region to help develop lake-specific management plans that select for and optimize local-level habitat factors for enhancing Bluegill growth.

Sinker tectonics - An approach to the surface of Miranda

NASA Technical Reports Server (NTRS)

Janes, D. M.; Melosh, H. J.

1988-01-01

Two of the proposed explanations for the coronae seen on Miranda involve mantle convection driven by density anomalies. In the sinker model, the coronae result from late-accreting large silicate bodies slowly sinking through an icy mantle toward the body's center; in the riser model, they result from a compositionally produced, low-density, rising diapir. The present study determines the surface stresses induced by such density anomalies and the expected surface expressions. The results are in good agreement with the predictions of the sinker model.

General predictive model of friction behavior regimes for metal contacts based on the formation stability and evolution of nanocrystalline surface films.

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

Argibay, Nicolas; Cheng, Shengfeng; Sawyer, W. G.

2015-09-01

The prediction of macro-scale friction and wear behavior based on first principles and material properties has remained an elusive but highly desirable target for tribologists and material scientists alike. Stochastic processes (e.g. wear), statistically described parameters (e.g. surface topography) and their evolution tend to defeat attempts to establish practical general correlations between fundamental nanoscale processes and macro-scale behaviors. We present a model based on microstructural stability and evolution for the prediction of metal friction regimes, founded on recently established microstructural deformation mechanisms of nanocrystalline metals, that relies exclusively on material properties and contact stress models. We show through complementary experimentalmore » and simulation results that this model overcomes longstanding practical challenges and successfully makes accurate and consistent predictions of friction transitions for a wide range of contact conditions. This framework not only challenges the assumptions of conventional causal relationships between hardness and friction, and between friction and wear, but also suggests a pathway for the design of higher performance metal alloys.« less

Evaluation of real-time high-resolution MM5 predictions over the Great Lakes region

Treesearch

Shiyuan Zhong; Hee-Jin In; Xindi Bian; Joseph Charney; Warren Heilman; Brian Potter

2005-01-01

Real-time high-resolution mesoscale predictions using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) over the Great Lakes region are evaluated for the 2002/03 winter and 2003 summer seasons using surface and upper-air observations, with a focus on near-surface and boundary layer properties that are important for applications such as air...

Modeling environmental contamination in hospital single- and four-bed rooms.

PubMed

King, M-F; Noakes, C J; Sleigh, P A

2015-12-01

Aerial dispersion of pathogens is recognized as a potential transmission route for hospital acquired infections; however, little is known about the link between healthcare worker (HCW) contacts' with contaminated surfaces, the transmission of infections and hospital room design. We combine computational fluid dynamics (CFD) simulations of bioaerosol deposition with a validated probabilistic HCW-surface contact model to estimate the relative quantity of pathogens accrued on hands during six types of care procedures in two room types. Results demonstrate that care type is most influential (P < 0.001), followed by the number of surface contacts (P < 0.001) and the distribution of surface pathogens (P = 0.05). Highest hand contamination was predicted during Personal care despite the highest levels of hand hygiene. Ventilation rates of 6 ac/h vs. 4 ac/h showed only minor reductions in predicted hand colonization. Pathogens accrued on hands decreased monotonically after patient care in single rooms due to the physical barrier of bioaerosol transmission between rooms and subsequent hand sanitation. Conversely, contamination was predicted to increase during contact with patients in four-bed rooms due to spatial spread of pathogens. Location of the infectious patient with respect to ventilation played a key role in determining pathogen loadings (P = 0.05). We present the first quantitative model predicting the surface contacts by HCW and the subsequent accretion of pathogenic material as they perform standard patient care. This model indicates that single rooms may significantly reduce the risk of cross-contamination due to indirect infection transmission. Not all care types pose the same risks to patients, and housekeeping performed by HCWs may be an important contribution in the transmission of pathogens between patients. Ventilation rates and positioning of infectious patients within four-bed rooms can mitigate the accretion of pathogens, whereby reducing the risk of missed hand hygiene opportunities. The model provides a tool to quantitatively evaluate the influence of hospital room design on infection risk. © 2015 The Authors. Indoor Air Published by John Wiley & Sons Ltd.

Modeling Water-Surface Elevations and Virtual Shorelines for the Colorado River in Grand Canyon, Arizona

USGS Publications Warehouse

Magirl, Christopher S.; Breedlove, Michael J.; Webb, Robert H.; Griffiths, Peter G.

2008-01-01

Using widely-available software intended for modeling rivers, a new one-dimensional hydraulic model was developed for the Colorado River through Grand Canyon from Lees Ferry to Diamond Creek. Solving one-dimensional equations of energy and continuity, the model predicts stage for a known steady-state discharge at specific locations, or cross sections, along the river corridor. This model uses 2,680 cross sections built with high-resolution digital topography of ground locations away from the river flowing at a discharge of 227 m3/s; synthetic bathymetry was created for topography submerged below the 227 m3/s water surface. The synthetic bathymetry was created by adjusting the water depth at each cross section up or down until the model?s predicted water-surface elevation closely matched a known water surface. This approach is unorthodox and offers a technique to construct one-dimensional hydraulic models of bedrock-controlled rivers where bathymetric data have not been collected. An analysis of this modeling approach shows that while effective in enabling a useful model, the synthetic bathymetry can differ from the actual bathymetry. The known water-surface profile was measured using elevation data collected in 2000 and 2002, and the model can simulate discharges up to 5,900 m3/s. In addition to the hydraulic model, GIS-based techniques were used to estimate virtual shorelines and construct inundation maps. The error of the hydraulic model in predicting stage is within 0.4 m for discharges less than 1,300 m3/s. Between 1,300-2,500 m3/s, the model accuracy is about 1.0 m, and for discharges between 2,500-5,900 m3/s, the model accuracy is on the order of 1.5 m. In the absence of large floods on the flow-regulated Colorado River in Grand Canyon, the new hydraulic model and the accompanying inundation maps are a useful resource for researchers interested in water depths, shorelines, and stage-discharge curves for flows within the river corridor with 2002 topographic conditions.

Measuring and modeling surface sorption dynamics of organophosphate flame retardants on impervious surfaces.

PubMed

Liang, Y; Liu, X; Allen, M R

2018-02-01

Understanding the sorption mechanisms for organophosphate flame retardants (OPFRs) on impervious surfaces is important to improve our knowledge of the fate and transport of OPFRs in indoor environments. The sorption processes of semivolatile organic compounds (SVOCs) on indoor surfaces are heterogeneous (multilayer sorption) or homogeneous (monolayer sorption). In this study, we adopted simplified Langmuir isotherm and Freundlich isotherm in a dynamic sink model to characterize the sorption dynamics of OPFRs on impervious surfaces such as stainless steel and made comparisons between the two models through a series of empty chamber studies. The tests involve two types of stainless steel chambers (53-L small chambers and 44-mL micro chambers) using tris(2-chloroethyl)phosphate (TCEP) and tris(1-chloro-2-propyl)phosphate (TCPP) as target compounds. Our test results show that the dynamic sink model using Freundlich isotherm can better represent the sorption process in the empty small chamber. Micro chamber test results from this study show that the sink model using both simplified Langmuir isotherm and Freundlich isotherm can well fit the measured gas-phase concentrations of OPFRs. We further applied both models and the parameters obtained to predict the gas phase concentrations of OPFRs in a small chamber with an emission source. Comparisons between model predictions and measurements demonstrate the reliability and applicability of the sorption parameters. Published by Elsevier Ltd.

Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

Modeling snowmelt infiltration in seasonally frozen ground

NASA Astrophysics Data System (ADS)

Budhathoki, S.; Ireson, A. M.

2017-12-01

In cold regions, freezing and thawing of the soil govern soil hydraulic properties that shape the surface and subsurface hydrological processes. The partitioning of snowmelt into infiltration and runoff has also important implications for integrated water resource management and flood risk. However, there is an inadequate representation of the snowmelt infiltration into frozen soils in most land-surface and hydrological models, creating the need for improved models and methods. Here we apply, the Frozen Soil Infiltration Model, FroSIn, which is a novel algorithm for infiltration in frozen soils that can be implemented in physically based models of coupled flow and heat transport. In this study, we apply the model in a simple configuration to reproduce observations from field sites in the Canadian prairies, specifically St Denis and Brightwater Creek in Saskatchewan, Canada. We demonstrate the limitations of conventional approaches to simulate infiltration, which systematically over-predict runoff and under predict infiltration. The findings show that FroSIn enables models to predict more reasonable infiltration volumes in frozen soils, and also represent how infiltration-runoff partitioning is impacted by antecedent soil moisture.

Variation of surface ozone in Campo Grande, Brazil: meteorological effect analysis and prediction.

PubMed

Pires, J C M; Souza, A; Pavão, H G; Martins, F G

2014-09-01

The effect of meteorological variables on surface ozone (O3) concentrations was analysed based on temporal variation of linear correlation and artificial neural network (ANN) models defined by genetic algorithms (GAs). ANN models were also used to predict the daily average concentration of this air pollutant in Campo Grande, Brazil. Three methodologies were applied using GAs, two of them considering threshold models. In these models, the variables selected to define different regimes were daily average O3 concentration, relative humidity and solar radiation. The threshold model that considers two O3 regimes was the one that correctly describes the effect of important meteorological variables in O3 behaviour, presenting also a good predictive performance. Solar radiation, relative humidity and rainfall were considered significant for both O3 regimes; however, wind speed (dispersion effect) was only significant for high concentrations. According to this model, high O3 concentrations corresponded to high solar radiation, low relative humidity and wind speed. This model showed to be a powerful tool to interpret the O3 behaviour, being useful to define policy strategies for human health protection regarding air pollution.

Predicting risk of trace element pollution from municipal roads using site-specific soil samples and remotely sensed data.

PubMed

Reeves, Mari Kathryn; Perdue, Margaret; Munk, Lee Ann; Hagedorn, Birgit

2018-07-15

Studies of environmental processes exhibit spatial variation within data sets. The ability to derive predictions of risk from field data is a critical path forward in understanding the data and applying the information to land and resource management. Thanks to recent advances in predictive modeling, open source software, and computing, the power to do this is within grasp. This article provides an example of how we predicted relative trace element pollution risk from roads across a region by combining site specific trace element data in soils with regional land cover and planning information in a predictive model framework. In the Kenai Peninsula of Alaska, we sampled 36 sites (191 soil samples) adjacent to roads for trace elements. We then combined this site specific data with freely-available land cover and urban planning data to derive a predictive model of landscape scale environmental risk. We used six different model algorithms to analyze the dataset, comparing these in terms of their predictive abilities and the variables identified as important. Based on comparable predictive abilities (mean R 2 from 30 to 35% and mean root mean square error from 65 to 68%), we averaged all six model outputs to predict relative levels of trace element deposition in soils-given the road surface, traffic volume, sample distance from the road, land cover category, and impervious surface percentage. Mapped predictions of environmental risk from toxic trace element pollution can show land managers and transportation planners where to prioritize road renewal or maintenance by each road segment's relative environmental and human health risk. Published by Elsevier B.V.

Translational Modeling in Schizophrenia: Predicting Human Dopamine D2 Receptor Occupancy.

PubMed

Johnson, Martin; Kozielska, Magdalena; Pilla Reddy, Venkatesh; Vermeulen, An; Barton, Hugh A; Grimwood, Sarah; de Greef, Rik; Groothuis, Geny M M; Danhof, Meindert; Proost, Johannes H

2016-04-01

To assess the ability of a previously developed hybrid physiology-based pharmacokinetic-pharmacodynamic (PBPKPD) model in rats to predict the dopamine D2 receptor occupancy (D2RO) in human striatum following administration of antipsychotic drugs. A hybrid PBPKPD model, previously developed using information on plasma concentrations, brain exposure and D2RO in rats, was used as the basis for the prediction of D2RO in human. The rat pharmacokinetic and brain physiology parameters were substituted with human population pharmacokinetic parameters and human physiological information. To predict the passive transport across the human blood-brain barrier, apparent permeability values were scaled based on rat and human brain endothelial surface area. Active efflux clearance in brain was scaled from rat to human using both human brain endothelial surface area and MDR1 expression. Binding constants at the D2 receptor were scaled based on the differences between in vitro and in vivo systems of the same species. The predictive power of this physiology-based approach was determined by comparing the D2RO predictions with the observed human D2RO of six antipsychotics at clinically relevant doses. Predicted human D2RO was in good agreement with clinically observed D2RO for five antipsychotics. Models using in vitro information predicted human D2RO well for most of the compounds evaluated in this analysis. However, human D2RO was under-predicted for haloperidol. The rat hybrid PBPKPD model structure, integrated with in vitro information and human pharmacokinetic and physiological information, constitutes a scientific basis to predict the time course of D2RO in man.

Effect of different emission inventories on modeled ozone and carbon monoxide in Southeast Asia

NASA Astrophysics Data System (ADS)

Amnuaylojaroen, T.; Barth, M. C.; Emmons, L. K.; Carmichael, G. R.; Kreasuwun, J.; Prasitwattanaseree, S.; Chantara, S.

2014-12-01

In order to improve our understanding of air quality in Southeast Asia, the anthropogenic emissions inventory must be well represented. In this work, we apply different anthropogenic emission inventories in the Weather Research and Forecasting Model with Chemistry (WRF-Chem) version 3.3 using Model for Ozone and Related Chemical Tracers (MOZART) gas-phase chemistry and Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) aerosols to examine the differences in predicted carbon monoxide (CO) and ozone (O3) surface mixing ratios for Southeast Asia in March and December 2008. The anthropogenic emission inventories include the Reanalysis of the TROpospheric chemical composition (RETRO), the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B), the MACCity emissions (adapted from the Monitoring Atmospheric Composition and Climate and megacity Zoom for the Environment projects), the Southeast Asia Composition, Cloud, Climate Coupling Regional Study (SEAC4RS) emissions, and a combination of MACCity and SEAC4RS emissions. Biomass-burning emissions are from the Fire Inventory from the National Center for Atmospheric Research (NCAR) (FINNv1) model. WRF-Chem reasonably predicts the 2 m temperature, 10 m wind, and precipitation. In general, surface CO is underpredicted by WRF-Chem while surface O3 is overpredicted. The NO2 tropospheric column predicted by WRF-Chem has the same magnitude as observations, but tends to underpredict the NO2 column over the equatorial ocean and near Indonesia. Simulations using different anthropogenic emissions produce only a slight variability of O3 and CO mixing ratios, while biomass-burning emissions add more variability. The different anthropogenic emissions differ by up to 30% in CO emissions, but O3 and CO mixing ratios averaged over the land areas of the model domain differ by ~4.5% and ~8%, respectively, among the simulations. Biomass-burning emissions create a substantial increase for both O3 and CO by ~29% and ~16%, respectively, when comparing the March biomass-burning period to the December period with low biomass-burning emissions. The simulations show that none of the anthropogenic emission inventories are better than the others for predicting O3 surface mixing ratios. However, the simulations with different anthropogenic emission inventories do differ in their predictions of CO surface mixing ratios producing variations of ~30% for March and 10-20% for December at Thai surface monitoring sites.

Prediction Activities at NASA's Global Modeling and Assimilation Office

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2010-01-01

The Global Modeling and Assimilation Office (GMAO) is a core NASA resource for the development and use of satellite observations through the integrating tools of models and assimilation systems. Global ocean, atmosphere and land surface models are developed as components of assimilation and forecast systems that are used for addressing the weather and climate research questions identified in NASA's science mission. In fact, the GMAO is actively engaged in addressing one of NASA's science mission s key questions concerning how well transient climate variations can be understood and predicted. At weather time scales the GMAO is developing ultra-high resolution global climate models capable of resolving high impact weather systems such as hurricanes. The ability to resolve the detailed characteristics of weather systems within a global framework greatly facilitates addressing fundamental questions concerning the link between weather and climate variability. At sub-seasonal time scales, the GMAO is engaged in research and development to improve the use of land information (especially soil moisture), and in the improved representation and initialization of various sub-seasonal atmospheric variability (such as the MJO) that evolves on time scales longer than weather and involves exchanges with both the land and ocean The GMAO has a long history of development for advancing the seasonal-to-interannual (S-I) prediction problem using an older version of the coupled atmosphere-ocean general circulation model (AOGCM). This includes the development of an Ensemble Kalman Filter (EnKF) to facilitate the multivariate assimilation of ocean surface altimetry, and an EnKF developed for the highly inhomogeneous nature of the errors in land surface models, as well as the multivariate assimilation needed to take advantage of surface soil moisture and snow observations. The importance of decadal variability, especially that associated with long-term droughts is well recognized by the climate community. An improved understanding of the nature of decadal variability and its predictability has important implications for efforts to assess the impacts of global change in the coming decades. In fact, the GMAO has taken on the challenge of carrying out experimental decadal predictions in support of the IPCC AR5 effort.

Artificial neural network based particle size prediction of polymeric nanoparticles.

PubMed

Youshia, John; Ali, Mohamed Ehab; Lamprecht, Alf

2017-10-01

Particle size of nanoparticles and the respective polydispersity are key factors influencing their biopharmaceutical behavior in a large variety of therapeutic applications. Predicting these attributes would skip many preliminary studies usually required to optimize formulations. The aim was to build a mathematical model capable of predicting the particle size of polymeric nanoparticles produced by a pharmaceutical polymer of choice. Polymer properties controlling the particle size were identified as molecular weight, hydrophobicity and surface activity, and were quantified by measuring polymer viscosity, contact angle and interfacial tension, respectively. A model was built using artificial neural network including these properties as input with particle size and polydispersity index as output. The established model successfully predicted particle size of nanoparticles covering a range of 70-400nm prepared from other polymers. The percentage bias for particle prediction was 2%, 4% and 6%, for the training, validation and testing data, respectively. Polymer surface activity was found to have the highest impact on the particle size followed by viscosity and finally hydrophobicity. Results of this study successfully highlighted polymer properties affecting particle size and confirmed the usefulness of artificial neural networks in predicting the particle size and polydispersity of polymeric nanoparticles. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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.

Thermokinetic Modeling of Phase Transformation in the Laser Powder Deposition Process

NASA Astrophysics Data System (ADS)

Foroozmehr, Ehsan; Kovacevic, Radovan

2009-08-01

A finite element model coupled with a thermokinetic model is developed to predict the phase transformation of the laser deposition of AISI 4140 on a substrate with the same material. Four different deposition patterns, long-bead, short-bead, spiral-in, and spiral-out, are used to cover a similar area. Using a finite element model, the temperature history of the laser powder deposition (LPD) process is determined. The martensite transformation as well as martensite tempering is considered to calculate the final fraction of martensite, ferrite, cementite, ɛ-carbide, and retained austenite. Comparing the surface hardness topography of different patterns reveals that path planning is a critical parameter in laser surface modification. The predicted results are in a close agreement with the experimental results.

Path Loss Prediction Over the Lunar Surface Utilizing a Modified Longley-Rice Irregular Terrain Model

NASA Technical Reports Server (NTRS)

Foore, Larry; Ida, Nathan

2007-01-01

This study introduces the use of a modified Longley-Rice irregular terrain model and digital elevation data representative of an analogue lunar site for the prediction of RF path loss over the lunar surface. The results are validated by theoretical models and past Apollo studies. The model is used to approximate the path loss deviation from theoretical attenuation over a reflecting sphere. Analysis of the simulation results provides statistics on the fade depths for frequencies of interest, and correspondingly a method for determining the maximum range of communications for various coverage confidence intervals. Communication system engineers and mission planners are provided a link margin and path loss policy for communication frequencies of interest.

Remote sensing of solar radiation absorbed and reflected by vegetated land surfaces

NASA Technical Reports Server (NTRS)

Myneni, Ranga B.; Asrar, Ghassem; Tanre, Didier; Choudhury, Bhaskar J.

1992-01-01

1D and 3D radiative-transfer models have been used to investigate the problem of remotely sensed determination of vegetated land surface-absorbed and reflected solar radiation. Calculations were conducted for various illumination conditions to determine surface albedo, soil- and canopy-absorbed photosynthetically active and nonactive radiation, and normalized difference vegetation index. Simple predictive models are developed on the basis of the relationships among these parameters.

Modeling of reservoir compaction and surface subsidence at South Belridge

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

Hansen, K.S.; Chan, C.K.; Prats, M.

1995-08-01

Finite-element models of depletion-induced reservoir compaction and surface subsidence have been calibrated with observed subsidence, locations of surface fissures, and regions of subsurface casing damage at South Belridge and used predictively for the evaluation of alternative reservoir-development plans. Pressure maintenance through diatomite waterflooding appears to be a beneficial means of minimizing additional subsidence and fissuring as well as reducing axial-compressive-type casing damage.

Generation of Accurate Lateral Boundary Conditions for a Surface-Water Groundwater Interaction Model

NASA Astrophysics Data System (ADS)

Khambhammettu, P.; Tsou, M.; Panday, S. M.; Kool, J.; Wei, X.

2010-12-01

The 106 mile long Peace River in Florida flows south from Lakeland to Charlotte Harbor and has a drainage basin of approximately 2,350 square miles. A long-term decline in stream flows and groundwater potentiometric levels has been observed in the region. Long-term trends in rainfall, along with effects of land use changes on runoff, surface-water storage, recharge and evapotranspiration patterns, and increased groundwater and surface-water withdrawals have contributed to this decline. The South West Florida Water Management District (SWFWMD) has funded the development of the Peace River Integrated Model (PRIM) to assess the effects of land use, water use, and climatic changes on stream flows and to evaluate the effectiveness of various management alternatives for restoring stream flows. The PRIM was developed using MODHMS, a fully integrated surface-water groundwater flow and transport simulator developed by HydroGeoLogic, Inc. The development of the lateral boundary conditions (groundwater inflow and outflow) for the PRIM in both historical and predictive contexts is discussed in this presentation. Monthly-varying specified heads were used to define the lateral boundary conditions for the PRIM. These head values were derived from the coarser Southern District Groundwater Model (SDM). However, there were discrepancies between the simulated SDM heads and measured heads: the likely causes being spatial (use of a coarser grid) and temporal (monthly average pumping rates and recharge rates) approximations in the regional SDM. Finer re-calibration of the SDM was not feasible, therefore, an innovative approach was adopted to remove the discrepancies. In this approach, point discrepancies/residuals between the observed and simulated heads were kriged with an appropriate variogram to generate a residual surface. This surface was then added to the simulated head surface of the SDM to generate a corrected head surface. This approach preserves the trends associated with groundwater pumping / recharge in the SDM and adds the kriged residual surface as variations back to the trend. The variations could be from the scale effects of grid resolution and from the temporal averaging of stresses (pumping, recharge, etc.,). The validity of the approach is demonstrated by visual and statistical comparison of the observed and simulated heads before and after correction. For predictive simulations, an Artificial Neural Network was trained to predict heads at monitoring wells based on precipitation and pumping. These predicted head values could then be used as surrogate observations for correcting the results of the regional SDM. In summary, an appropriate approach to link a regional groundwater model to a detailed surface-water groundwater interaction model is demonstrated with an example.

A numerical forecast model for road meteorology

NASA Astrophysics Data System (ADS)

Meng, Chunlei

2017-05-01

A fine-scale numerical model for road surface parameters prediction (BJ-ROME) is developed based on the Common Land Model. The model is validated using in situ observation data measured by the ROSA road weather stations of Vaisala Company, Finland. BJ-ROME not only takes into account road surface factors, such as imperviousness, relatively low albedo, high heat capacity, and high heat conductivity, but also considers the influence of urban anthropogenic heat, impervious surface evaporation, and urban land-use/land-cover changes. The forecast time span and the update interval of BJ-ROME in vocational operation are 24 and 3 h, respectively. The validation results indicate that BJ-ROME can successfully simulate the diurnal variation of road surface temperature both under clear-sky and rainfall conditions. BJ-ROME can simulate road water and snow depth well if the artificial removing was considered. Road surface energy balance in rainy days is quite different from that in clear-sky conditions. Road evaporation could not be neglected in road surface water cycle research. The results of sensitivity analysis show solar radiation correction coefficient, asphalt depth, and asphalt heat conductivity are important parameters in road interface temperatures simulation. The prediction results could be used as a reference of maintenance decision support system to mitigate the traffic jam and urban water logging especially in large cities.

Interference effects in laser-induced plasma emission from surface-bound metal micro-particles

DOE PAGES

Feigenbaum, Eyal; Malik, Omer; Rubenchik, Alexander M.; ...

2017-04-19

Here, the light-matter interaction of an optical beam and metal micro-particulates at the vicinity of an optical substrate surface is critical to the many fields of applied optics. Examples of impacted fields are laser-induced damage in high power laser systems, sub-wavelength laser machining of transmissive materials, and laser-target interaction in directed energy applications. We present a full-wave-based model that predicts the laser-induced plasma pressure exerted on a substrate surface as a result of light absorption in surface-bound micron-scale metal particles. The model predictions agree with experimental observation of laser-induced shallow pits, formed by plasma emission and etching from surface-bound metalmore » micro-particulates. It provides an explanation for the prototypical side lobes observed along the pit profile, as well as for the dependence of the pit shape on the incident laser and particle parameters. Furthermore, the model highlights the significance of the interference of the incident light in the open cavity geometry formed between the micro-particle and the substrate in the resulting pit shape.« less

Interference effects in laser-induced plasma emission from surface-bound metal micro-particles.

PubMed

Feigenbaum, Eyal; Malik, Omer; Rubenchik, Alexander M; Matthews, Manyalibo J

2017-05-01

The light-matter interaction of an optical beam and metal micro-particulates at the vicinity of an optical substrate surface is critical to the many fields of applied optics. Examples of impacted fields are laser-induced damage in high power laser systems, sub-wavelength laser machining of transmissive materials, and laser-target interaction in directed energy applications. We present a full-wave-based model that predicts the laser-induced plasma pressure exerted on a substrate surface as a result of light absorption in surface-bound micron-scale metal particles. The model predictions agree with experimental observation of laser-induced shallow pits, formed by plasma emission and etching from surface-bound metal micro-particulates. It provides an explanation for the prototypical side lobes observed along the pit profile, as well as for the dependence of the pit shape on the incident laser and particle parameters. Furthermore, the model highlights the significance of the interference of the incident light in the open cavity geometry formed between the micro-particle and the substrate in the resulting pit shape.

The devil is in the dispersers: Predictions of landscape connectivity change with demography

Treesearch

Nicholas B. Elliot; Samuel A. Cushman; David W. Macdonald; Andrew J. Loveridge

2014-01-01

Concern about the effects of habitat fragmentation has led to increasing interest in dispersal and connectivity modelling. Most modern techniques for connectivity modelling have resistance surfaces as their foundation. However, resistance surfaces for animal movement are frequently estimated without considering dispersal, despite being the principal natural mechanism...

Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover

DOE PAGES

Stegen, James C.; Fredrickson, James K.; Wilkins, Michael J.; ...

2016-04-07

Environmental transition zones are associated with geochemical gradients that overcome energy limitations to microbial metabolism, resulting in biogeochemical hot spots and moments. Riverine systems where groundwater mixes with surface water (the hyporheic zone) are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. To investigate the coupling among groundwater-surface water mixing, microbial communities, and biogeochemistry we applied ecological theory, aqueous biogeochemistry, DNA sequencing, and ultra-high resolution organic carbon profiling to field samples collected across times and locations representing amore » broad range of mixing conditions. Mixing of groundwater and surface water resulted in a shift from transport-driven stochastic dynamics to a deterministic microbial structure associated with elevated biogeochemical rates. While the dynamics of the hyporheic make predictive modeling a challenge, we provide new knowledge that can improve the tractability of such models.« less

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

Ion mobilities in diatomic gases: measurement versus prediction with non-specular scattering models.

PubMed

Larriba, Carlos; Hogan, Christopher J

2013-05-16

Ion/electrical mobility measurements of nanoparticles and polyatomic ions are typically linked to particle/ion physical properties through either application of the Stokes-Millikan relationship or comparison to mobilities predicted from polyatomic models, which assume that gas molecules scatter specularly and elastically from rigid structural models. However, there is a discrepancy between these approaches; when specular, elastic scattering models (i.e., elastic-hard-sphere scattering, EHSS) are applied to polyatomic models of nanometer-scale ions with finite-sized impinging gas molecules, predictions are in substantial disagreement with the Stokes-Millikan equation. To rectify this discrepancy, we developed and tested a new approach for mobility calculations using polyatomic models in which non-specular (diffuse) and inelastic gas-molecule scattering is considered. Two distinct semiempirical models of gas-molecule scattering from particle surfaces were considered. In the first, which has been traditionally invoked in the study of aerosol nanoparticles, 91% of collisions are diffuse and thermally accommodating, and 9% are specular and elastic. In the second, all collisions are considered to be diffuse and accommodating, but the average speed of the gas molecules reemitted from a particle surface is 8% lower than the mean thermal speed at the particle temperature. Both scattering models attempt to mimic exchange between translational, vibrational, and rotational modes of energy during collision, as would be expected during collision between a nonmonoatomic gas molecule and a nonfrozen particle surface. The mobility calculation procedure was applied considering both hard-sphere potentials between gas molecules and the atoms within a particle and the long-range ion-induced dipole (polarization) potential. Predictions were compared to previous measurements in air near room temperature of multiply charged poly(ethylene glycol) (PEG) ions, which range in morphology from compact to highly linear, and singly charged tetraalkylammonium cations. It was found that both non-specular, inelastic scattering rules lead to excellent agreement between predictions and experimental mobility measurements (within 5% of each other) and that polarization potentials must be considered to make correct predictions for high-mobility particles/ions. Conversely, traditional specular, elastic scattering models were found to substantially overestimate the mobilities of both types of ions.

Impact of atmosphere and land surface initial conditions on seasonal forecast of global surface temperature

NASA Astrophysics Data System (ADS)

Materia, Stefano; Borrelli, Andrea; Bellucci, Alessio; Alessandri, Andrea; Di Pietro, Pierluigi; Athanasiadis, Panagiotis; Navarra, Antonio; Gualdi, Silvio

2014-05-01

The impact of land surface and atmosphere initialization on the forecast skill of a seasonal prediction system is investigated, and an effort to disentangle the role played by the individual components to the global predictability is done, via a hierarchy of seasonal forecast experiments performed under different initialization strategies. A realistic atmospheric initial state allows an improved equilibrium between the ocean and overlying atmosphere, mitigating the coupling shock and possibly increasing the model predictive skill in the ocean. In fact, in a few regions characterized by strong air-sea coupling, the atmosphere initial condition affects the forecast skill for several months. In particular, the ENSO region, the eastern tropical Atlantic and the North Pacific benefit significantly from the atmosphere initialization. On mainland, the impact of atmospheric initial conditions is detected in the early phase of the forecast, while the quality of land surface initialization affects the forecast skill in the following lead seasons. The winter forecast in the high latitude plains of Siberia and Canada benefit from the snow initialization, while the impact of soil moisture initial state is particularly effective in the Mediterranean region, in central Asia and Australia. However, initialization through land surface reanalysis does not systematically guarantee an enhancement of the predictive skill: the quality of the forecast is sometimes higher for the non-constrained model. Overall, the introduction of a realistic initialization of land surface and atmosphere substantially increases skill and accuracy. However, further developments in the operating procedure for land surface initialization are required for more accurate seasonal forecasts.

Role of surface plasmon polaritons and other waves in the radiation of resonant optical dipole antennas

PubMed Central

Jia, Hongwei; Liu, Haitao; Zhong, Ying

2015-01-01

The radiation of an electric dipole emitter can be drastically enhanced if the emitter is placed in the nano-gap of a metallic dipole antenna. By assuming that only surface plasmon polaritons (SPPs) are excited on the antenna, we build up an intuitive pure-SPP model that is able to comprehensively predict the electromagnetic features of the antenna radiation, such as the total or radiative emission rate and the far-field radiation pattern. With the model we can distinguish the respective contributions from SPPs and from other surface waves to the antenna radiation. It is found that for antennas with long arms that support higher-order resonances, SPPs provide a dominant contribution to the antenna radiation, while for other cases, the contribution of surface waves other than SPPs should be considered. The model reveals an intuitive picture that the enhancement of the antenna radiation is due to surface waves that are resonantly excited on the two antenna arms and that are further coupled into the nano-gap or scattered into free space. From the model we can derive a phase-matching condition that predicts the antenna resonance and the resultant enhanced radiation. The model is helpful for a physical understanding and intuitive design of antenna devices. PMID:25678191

Numerical Simulation of Thin Film Breakup on Nonwettable Surfaces

NASA Astrophysics Data System (ADS)

Suzzi, N.; Croce, G.

2017-01-01

When a continuous film flows on a nonwettable substrate surface, it may break up, with the consequent formation of a dry-patch. The actual shape of the resulting water layer is of great interest in several engineering applications, from in-flight icing simulation to finned dehumidifier behavior modeling. Here, a 2D numerical solver for the prediction of film flow behavior is presented. The effect of the contact line is introduced via the disjoining pressure terms, and both gravity and shear are included in the formulation. The code is validated with literature experimental data for the case of a stationary dry-patch on an inclined plane. Detailed numerical results are compared with literature simplified model prediction. Numerical simulation are then performed in order to predict the threshold value of the film thickness allowing for film breakup and to analyze the dependence of the dynamic contact angle on film velocity and position along the contact line. Those informations will be useful in order to efficiently predict more complex configuration involving multiple breakups on arbitrarily curved substrate surfaces (as those involved in in-flight icing phenomena on aircraft).

Human and Server Docking Prediction for CAPRI Round 30–35 Using LZerD with Combined Scoring Functions

PubMed Central

Peterson, Lenna X.; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2016-01-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues’ spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, i.e. whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. PMID:27654025

Topographies and dynamics on multidimensional potential energy surfaces

NASA Astrophysics Data System (ADS)

Ball, Keith Douglas

The stochastic master equation is a valuable tool for elucidating potential energy surface (PES) details that govern structural relaxation in clusters, bulk systems, and protein folding. This work develops a comprehensive framework for studying non-equilibrium relaxation dynamics using the master equation. Since our master equations depend upon accurate partition function models for use in Rice-Ramsperger-Kassel-Marcus (RRK(M) transition state theory, this work introduces several such models employing various harmonic and anharmonic approximations and compares their predicted equilibrium population distributions with those determined from molecular dynamics. This comparison is performed for the fully-delineated surfaces (KCl)5 and Ar9 to evaluate model performance for potential surfaces with long- and short-range interactions, respectively. For each system, several models perform better than a simple harmonic approximation. While no model gives acceptable results for all minima, and optimal modeling strategies differ for (KCl)5 and Ar9, a particular one-parameter model gives the best agreement with simulation for both systems. We then construct master equations from these models and compare their isothermal relaxation predictions for (KCl)5 and Ar9 with molecular dynamics simulations. This is the first comprehensive test of the kinetic performance of partition function models of its kind. Our results show that accurate modeling of transition-state partition functions is more important for (KCl)5 than for Ar9 in reproducing simulation results, due to a marked stiffening anharmonicity in the transition-state normal modes of (KCl)5. For both systems, several models yield qualitative agreement with simulation over a large temperature range. To examine the robustness of the master equation when applied to larger systems, for which full topographical descriptions would be either impossible or infeasible, we compute relaxation predictions for Ar11 using a master equation constructed from data representing the full PES, and compare these predictions to those of reduced master equations based on statistical samples of the full PES. We introduce a sampling method which generates random, Boltzmann-weighted, energetically 'downhill' sequences. The study reveals that, at moderate temperatures, the slowest relaxation timescale converges as the number of sequences in a sample grows to ~1000. Furthermore, the asymptotic timescale is comparable to the full-PES value.

A Self-Organizing Map Based Evaluation of the Antarctic Mesoscale Prediction System Using Observations from a 30-m Instrumented Tower on the Ross Ice Shelf, Antarctica

NASA Astrophysics Data System (ADS)

Nigro, M. A.; Cassano, J. J.; Wille, J.; Bromwich, D. H.; Lazzara, M. A.

2015-12-01

An accurate representation of the atmospheric boundary layer in numerical weather prediction models is important for predicting turbulence and energy exchange in the atmosphere. This study uses two years of observations from a 30-m automatic weather station (AWS) installed on the Ross Ice Shelf, Antarctica to evaluate forecasts from the Antarctic Mesoscale Prediction System (AMPS), a numerical weather prediction system based on the polar version of the Weather Research and Forecasting (Polar WRF) model that uses the MYJ planetary boundary layer scheme and that primarily supports the extensive aircraft operations of the U.S. Antarctic Program. The 30-m AWS has six levels of instrumentation, providing vertical profiles of temperature, wind speed, and wind direction. The observations show the atmospheric boundary layer over the Ross Ice Shelf is stable approximately 80% of the time, indicating the influence of the permanent ice surface in this region. The observations from the AWS are further analyzed using the method of self-organizing maps (SOM) to identify the range of potential temperature profiles that occur over the Ross Ice Shelf. The SOM analysis identified 30 patterns, which range from strong inversions to slightly unstable profiles. The corresponding AMPS forecasts were evaluated for each of the 30 patterns to understand the accuracy of the AMPS near surface layer under different atmospheric conditions. The results indicate that under stable conditions AMPS with MYJ under predicts the inversion strength by as much as 7.4 K over the 30-m depth of the tower and over predicts the near surface wind speed by as much as 3.8 m s-1. Conversely, under slightly unstable conditions, AMPS predicts both the inversion strength and near surface wind speeds with reasonable accuracy.

Non-metallic coating thickness prediction using artificial neural network and support vector machine with time resolved thermography

NASA Astrophysics Data System (ADS)

Wang, Hongjin; Hsieh, Sheng-Jen; Peng, Bo; Zhou, Xunfei

2016-07-01

A method without requirements on knowledge about thermal properties of coatings or those of substrates will be interested in the industrial application. Supervised machine learning regressions may provide possible solution to the problem. This paper compares the performances of two regression models (artificial neural networks (ANN) and support vector machines for regression (SVM)) with respect to coating thickness estimations made based on surface temperature increments collected via time resolved thermography. We describe SVM roles in coating thickness prediction. Non-dimensional analyses are conducted to illustrate the effects of coating thicknesses and various factors on surface temperature increments. It's theoretically possible to correlate coating thickness with surface increment. Based on the analyses, the laser power is selected in such a way: during the heating, the temperature increment is high enough to determine the coating thickness variance but low enough to avoid surface melting. Sixty-one pain-coated samples with coating thicknesses varying from 63.5 μm to 571 μm are used to train models. Hyper-parameters of the models are optimized by 10-folder cross validation. Another 28 sets of data are then collected to test the performance of the three methods. The study shows that SVM can provide reliable predictions of unknown data, due to its deterministic characteristics, and it works well when used for a small input data group. The SVM model generates more accurate coating thickness estimates than the ANN model.

Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

NASA Astrophysics Data System (ADS)

DY, C. Y.; Fung, J. C. H.

2016-08-01

A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

Data-Driven Correlation Analysis Between Observed 3D Fatigue-Crack Path and Computed Fields from High-Fidelity, Crystal-Plasticity, Finite-Element Simulations

NASA Astrophysics Data System (ADS)

Pierson, Kyle D.; Hochhalter, Jacob D.; Spear, Ashley D.

2018-05-01

Systematic correlation analysis was performed between simulated micromechanical fields in an uncracked polycrystal and the known path of an eventual fatigue-crack surface based on experimental observation. Concurrent multiscale finite-element simulation of cyclic loading was performed using a high-fidelity representation of grain structure obtained from near-field high-energy x-ray diffraction microscopy measurements. An algorithm was developed to parameterize and systematically correlate the three-dimensional (3D) micromechanical fields from simulation with the 3D fatigue-failure surface from experiment. For comparison, correlation coefficients were also computed between the micromechanical fields and hypothetical, alternative surfaces. The correlation of the fields with hypothetical surfaces was found to be consistently weaker than that with the known crack surface, suggesting that the micromechanical fields of the cyclically loaded, uncracked microstructure might provide some degree of predictiveness for microstructurally small fatigue-crack paths, although the extent of such predictiveness remains to be tested. In general, gradients of the field variables exhibit stronger correlations with crack path than the field variables themselves. Results from the data-driven approach implemented here can be leveraged in future model development for prediction of fatigue-failure surfaces (for example, to facilitate univariate feature selection required by convolution-based models).

Polarity Comparison Between the Coronal PFSS Model Field and the Heliospheric Magnetic Field at 1 AU Over Solar Cycles 21-24

NASA Astrophysics Data System (ADS)

Koskela, J. S.; Virtanen, I. I.; Mursula, K.

2015-12-01

The solar coronal magnetic field forms an important link between the underlying source in the solar photosphere and the heliospheric magnetic field (HMF). The coronal field has traditionally been calculated from the photospheric observations using various magnetic field models between the photosphere and the corona, in particular the potential field source surface (PFSS) model. Despite its simplicity, the predictions of the PFSS model generally agree quite well with the heliospheric observations and match very well with the predictions of more elaborate models. We make here a detailed comparison between the predictions of the PFSS model with the HMF field observed at 1 AU. We use the photospheric field measured at the Wilcox Solar Observatory, SDO/HMI, SOHO/MDI and SOLIS, and the heliospheric magnetic field measurements at 1 AU collected within the OMNI 2 dataset. This database covers the solar cycles 21-24. We use different source surface distances and different numbers of harmonic components for the PFSS model. We find an optimum polarity match between the coronal field and the HMF for source surface distance of 3.5 Rs. Increasing the number of harmonic components beyond the quadrupole does not essentially improve polarity agreement, indicating that the large scale structure of the HMF at 1 AU is responsible for the agreement while the small scale structure is greatly modified between corona and 1 AU. We also discuss the solar cycle evolution of polarity match and find that the PFSS model prediction is most reliable during the declining phase of the solar cycle. We also find large differences in match percentage between northern and southern hemispheres during the times of systematic southward shift of the heliospheric current sheet (the Bashful ballerina).

Advances in land modeling of KIAPS based on the Noah Land Surface Model

NASA Astrophysics Data System (ADS)

Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

2017-08-01

As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

TThe role of nitrogen availability in land-atmosphere interactions: a systematic evaluation of carbon-nitrogen coupling in a global land surface model using plot-level nitrogen fertilization experiments

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Goodale, C. L.; Bonan, G. B.; Mahowald, N. M.; Ricciuto, D. M.; Thornton, P. E.

2010-12-01

Recent research from global land surface models emphasizes the important role of nitrogen cycling on global climate, via its control on the terrestrial carbon balance. Despite the implications of nitrogen cycling on global climate predictions, the research community has not performed a systematic evaluation of nitrogen cycling in global models. Here, we present such an evaluation for one global land model, CLM-CN. In the evaluation we simulated 45 plot-scale nitrogen-fertilization experiments distributed across 33 temperate and boreal forest sites. Model predictions were evaluated against field observations by comparing the vegetation and soil carbon responses to the additional nitrogen. Aggregated across all experiments, the model predicted a larger vegetation carbon response and a smaller soil carbon response than observed; the responses partially offset each other, leading to a slightly larger total ecosystem carbon response than observed. However, the model-observation agreement improved for vegetation carbon when the sites with observed negative carbon responses to nitrogen were excluded, which may be because the model lacks mechanisms whereby nitrogen additions increase tree mortality. Among experiments, younger forests and boreal forests’ vegetation carbon responses were less than predicted and mature forests (> 40 years old) were greater than predicted. Specific to the CLM-CN, this study used a systematic evaluation to identify key areas to focus model development, especially soil carbon- nitrogen interactions and boreal forest nitrogen cycling. Applicable to the modeling community, this study demonstrates a standardized protocol for comparing carbon-nitrogen interactions among global land models.

The prediction of sea-surface temperature variations by means of an advective mixed-layer ocean model

NASA Technical Reports Server (NTRS)

Atlas, R. M.

1976-01-01

An advective mixed layer ocean model was developed by eliminating the assumption of horizontal homogeneity in an already existing mixed layer model, and then superimposing a mean and anomalous wind driven current field. This model is based on the principle of conservation of heat and mechanical energy and utilizes a box grid for the advective part of the calculation. Three phases of experiments were conducted: evaluation of the model's ability to account for climatological sea surface temperature (SST) variations in the cooling and heating seasons, sensitivity tests in which the effect of hypothetical anomalous winds was evaluated, and a thirty-day synoptic calculation using the model. For the case studied, the accuracy of the predictions was improved by the inclusion of advection, although nonadvective effects appear to have dominated.

Beaked Whale Habitat Characterization and Prediction

DTIC Science & Technology

2005-09-30

trying to develop a better understanding of beaked whale distribution. For long - range planning, the static habitat prediction maps provide a broad... whale presence ranged from 79.3% to 100.0% for the static models and 85.7% to 94.5% for the dynamic models. Beaked whale habitat prediction has been...submerged for such long periods of time that there is a high probability that they will never surface within the visual range of observers aboard a

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

NASA Astrophysics Data System (ADS)

Simmer, C.

2015-12-01

An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

Thermal Pollution Mathematical Model. Volume 6; Verification of Three-Dimensional Free-Surface Model at Anclote Anchorage; [environment impact of thermal discharges from power plants

NASA Technical Reports Server (NTRS)

Lee, S. S.; Sengupta, S.; Tuann, S. Y.; Lee, C. R.

1980-01-01

The free-surface model presented is for tidal estuaries and coastal regions where ambient tidal forces play an important role in the dispersal of heated water. The model is time dependent, three dimensional, and can handle irregular bottom topography. The vertical stretching coordinate is adopted for better treatment of kinematic condition at the water surface. The results include surface elevation, velocity, and temperature. The model was verified at the Anclote Anchorage site of Florida Power Company. Two data bases at four tidal stages for winter and summer conditions were used to verify the model. Differences between measured and predicted temperatures are on an average of less than 1 C.

Model parameter-related optimal perturbations and their contributions to El Niño prediction errors

NASA Astrophysics Data System (ADS)

Tao, Ling-Jiang; Gao, Chuan; Zhang, Rong-Hua

2018-04-01

Errors in initial conditions and model parameters (MPs) are the main sources that limit the accuracy of ENSO predictions. In addition to exploring the initial error-induced prediction errors, model errors are equally important in determining prediction performance. In this paper, the MP-related optimal errors that can cause prominent error growth in ENSO predictions are investigated using an intermediate coupled model (ICM) and a conditional nonlinear optimal perturbation (CNOP) approach. Two MPs related to the Bjerknes feedback are considered in the CNOP analysis: one involves the SST-surface wind coupling ({α _τ } ), and the other involves the thermocline effect on the SST ({α _{Te}} ). The MP-related optimal perturbations (denoted as CNOP-P) are found uniformly positive and restrained in a small region: the {α _τ } component is mainly concentrated in the central equatorial Pacific, and the {α _{Te}} component is mainly located in the eastern cold tongue region. This kind of CNOP-P enhances the strength of the Bjerknes feedback and induces an El Niño- or La Niña-like error evolution, resulting in an El Niño-like systematic bias in this model. The CNOP-P is also found to play a role in the spring predictability barrier (SPB) for ENSO predictions. Evidently, such error growth is primarily attributed to MP errors in small areas based on the localized distribution of CNOP-P. Further sensitivity experiments firmly indicate that ENSO simulations are sensitive to the representation of SST-surface wind coupling in the central Pacific and to the thermocline effect in the eastern Pacific in the ICM. These results provide guidance and theoretical support for the future improvement in numerical models to reduce the systematic bias and SPB phenomenon in ENSO predictions.

Modeling of Thickness and Profile Uniformity of Thermally Sprayed Coatings Deposited on Cylinders

NASA Astrophysics Data System (ADS)

Yanjun, Zhang; Wenbo, Li; Dayu, Li; Jinkun, Xiao; Chao, Zhang

2018-02-01

In thermal spraying processes, kinematic parameters of the robot play a decisive role in the coating thickness and profile. In this regard, some achievements have been made to optimize the spray trajectory on flat surfaces. However, few reports have focused on nonholonomic or variable-curvature cylindrical surfaces. The aim of this study is to investigate the correlation between the coating profile, coating thickness, and scanning step, which is determined by the radius of curvature and scanning angle. A mathematical simulation model was developed to predict the thickness of thermally sprayed coatings. Experiments were performed on cylinders with different radiuses of curvature to evaluate the predictive ability of the model.

Seasonal prediction of US summertime ozone using statistical analysis of large scale climate patterns.

PubMed

Shen, Lu; Mickley, Loretta J

2017-03-07

We develop a statistical model to predict June-July-August (JJA) daily maximum 8-h average (MDA8) ozone concentrations in the eastern United States based on large-scale climate patterns during the previous spring. We find that anomalously high JJA ozone in the East is correlated with these springtime patterns: warm tropical Atlantic and cold northeast Pacific sea surface temperatures (SSTs), as well as positive sea level pressure (SLP) anomalies over Hawaii and negative SLP anomalies over the Atlantic and North America. We then develop a linear regression model to predict JJA MDA8 ozone from 1980 to 2013, using the identified SST and SLP patterns from the previous spring. The model explains ∼45% of the variability in JJA MDA8 ozone concentrations and ∼30% variability in the number of JJA ozone episodes (>70 ppbv) when averaged over the eastern United States. This seasonal predictability results from large-scale ocean-atmosphere interactions. Warm tropical Atlantic SSTs can trigger diabatic heating in the atmosphere and influence the extratropical climate through stationary wave propagation, leading to greater subsidence, less precipitation, and higher temperatures in the East, which increases surface ozone concentrations there. Cooler SSTs in the northeast Pacific are also associated with more summertime heatwaves and high ozone in the East. On average, models participating in the Atmospheric Model Intercomparison Project fail to capture the influence of this ocean-atmosphere interaction on temperatures in the eastern United States, implying that such models would have difficulty simulating the interannual variability of surface ozone in this region.

Predicting residential exposure to phthalate plasticizer emitted from vinyl flooring: a mechanistic analysis.

PubMed

Xu, Ying; Hubal, Elaine A Cohen; Clausen, Per A; Little, John C

2009-04-01

A two-room model is developed to estimate the emission rate of di-2-ethylhexyl phthalate (DEHP) from vinyl flooring and the evolving gas-phase and adsorbed surface concentrations in a realistic indoor environment. Because the DEHP emission rate measured in a test chamber may be quite different from the emission rate from the same material in the indoor environment the model provides a convenient means to predict emissions and transport in a more realistic setting. Adsorption isotherms for phthalates and plasticizers on interior surfaces, such as carpet, wood, dust, and human skin, are derived from previous field and laboratory studies. Log-linear relationships between equilibrium parameters and chemical vapor pressure are obtained. The predicted indoor air DEHP concentration at steady state is 0.15 microg/m3. Room 1 reaches steady state within about one year, while the adjacent room reaches steady state about three months later. Ventilation rate has a strong influence on DEHP emission rate while total suspended particle concentration has a substantial impact on gas-phase concentration. Exposure to DEHP via inhalation, dermal absorption, and oral ingestion of dust is evaluated. The model clarifies the mechanisms that govern the release of DEHP from vinyl flooring and the subsequent interactions with interior surfaces, airborne particles, dust, and human skin. Although further model development, parameter identification, and model validation are needed, our preliminary model provides a mechanistic framework that elucidates exposure pathways for phthalate plasticizers, and can most likely be adapted to predict emissions and transport of other semivolatile organic compounds, such as brominated flame retardants and biocides, in a residential environment.

Seasonal prediction of US summertime ozone using statistical analysis of large scale climate patterns

PubMed Central

Mickley, Loretta J.

2017-01-01

We develop a statistical model to predict June–July–August (JJA) daily maximum 8-h average (MDA8) ozone concentrations in the eastern United States based on large-scale climate patterns during the previous spring. We find that anomalously high JJA ozone in the East is correlated with these springtime patterns: warm tropical Atlantic and cold northeast Pacific sea surface temperatures (SSTs), as well as positive sea level pressure (SLP) anomalies over Hawaii and negative SLP anomalies over the Atlantic and North America. We then develop a linear regression model to predict JJA MDA8 ozone from 1980 to 2013, using the identified SST and SLP patterns from the previous spring. The model explains ∼45% of the variability in JJA MDA8 ozone concentrations and ∼30% variability in the number of JJA ozone episodes (>70 ppbv) when averaged over the eastern United States. This seasonal predictability results from large-scale ocean–atmosphere interactions. Warm tropical Atlantic SSTs can trigger diabatic heating in the atmosphere and influence the extratropical climate through stationary wave propagation, leading to greater subsidence, less precipitation, and higher temperatures in the East, which increases surface ozone concentrations there. Cooler SSTs in the northeast Pacific are also associated with more summertime heatwaves and high ozone in the East. On average, models participating in the Atmospheric Model Intercomparison Project fail to capture the influence of this ocean–atmosphere interaction on temperatures in the eastern United States, implying that such models would have difficulty simulating the interannual variability of surface ozone in this region. PMID:28223483