Locating helicopter emergency medical service bases to optimise population coverage versus average response time.

PubMed

Garner, Alan A; van den Berg, Pieter L

2017-10-16

New South Wales (NSW), Australia has a network of multirole retrieval physician staffed helicopter emergency medical services (HEMS) with seven bases servicing a jurisdiction with population concentrated along the eastern seaboard. The aim of this study was to estimate optimal HEMS base locations within NSW using advanced mathematical modelling techniques. We used high resolution census population data for NSW from 2011 which divides the state into areas containing 200-800 people. Optimal HEMS base locations were estimated using the maximal covering location problem facility location optimization model and the average response time model, exploring the number of bases needed to cover various fractions of the population for a 45 min response time threshold or minimizing the overall average response time to all persons, both in green field scenarios and conditioning on the current base structure. We also developed a hybrid mathematical model where average response time was optimised based on minimum population coverage thresholds. Seven bases could cover 98% of the population within 45mins when optimised for coverage or reach the entire population of the state within an average of 21mins if optimised for response time. Given the existing bases, adding two bases could either increase the 45 min coverage from 91% to 97% or decrease the average response time from 21mins to 19mins. Adding a single specialist prehospital rapid response HEMS to the area of greatest population concentration decreased the average state wide response time by 4mins. The optimum seven base hybrid model that was able to cover 97.75% of the population within 45mins, and all of the population in an average response time of 18 mins included the rapid response HEMS model. HEMS base locations can be optimised based on either percentage of the population covered, or average response time to the entire population. We have also demonstrated a hybrid technique that optimizes response time for a given number of bases and minimum defined threshold of population coverage. Addition of specialized rapid response HEMS services to a system of multirole retrieval HEMS may reduce overall average response times by improving access in large urban areas.

The role of heterogeneity in contact timing and duration in network models of influenza spread in schools

PubMed Central

Toth, Damon J. A.; Leecaster, Molly; Pettey, Warren B. P.; Gundlapalli, Adi V.; Gao, Hongjiang; Rainey, Jeanette J.; Uzicanin, Amra; Samore, Matthew H.

2015-01-01

Influenza poses a significant health threat to children, and schools may play a critical role in community outbreaks. Mathematical outbreak models require assumptions about contact rates and patterns among students, but the level of temporal granularity required to produce reliable results is unclear. We collected objective contact data from students aged 5–14 at an elementary school and middle school in the state of Utah, USA, and paired those data with a novel, data-based model of influenza transmission in schools. Our simulations produced within-school transmission averages consistent with published estimates. We compared simulated outbreaks over the full resolution dynamic network with simulations on networks with averaged representations of contact timing and duration. For both schools, averaging the timing of contacts over one or two school days caused average outbreak sizes to increase by 1–8%. Averaging both contact timing and pairwise contact durations caused average outbreak sizes to increase by 10% at the middle school and 72% at the elementary school. Averaging contact durations separately across within-class and between-class contacts reduced the increase for the elementary school to 5%. Thus, the effect of ignoring details about contact timing and duration in school contact networks on outbreak size modelling can vary across different schools. PMID:26063821

An empirical investigation on different methods of economic growth rate forecast and its behavior from fifteen countries across five continents

NASA Astrophysics Data System (ADS)

Yin, Yip Chee; Hock-Eam, Lim

2012-09-01

Our empirical results show that we can predict GDP growth rate more accurately in continent with fewer large economies, compared to smaller economies like Malaysia. This difficulty is very likely positively correlated with subsidy or social security policies. The stage of economic development and level of competiveness also appears to have interactive effects on this forecast stability. These results are generally independent of the forecasting procedures. Countries with high stability in their economic growth, forecasting by model selection is better than model averaging. Overall forecast weight averaging (FWA) is a better forecasting procedure in most countries. FWA also outperforms simple model averaging (SMA) and has the same forecasting ability as Bayesian model averaging (BMA) in almost all countries.

The phenotypic equilibrium of cancer cells: From average-level stability to path-wise convergence.

PubMed

Niu, Yuanling; Wang, Yue; Zhou, Da

2015-12-07

The phenotypic equilibrium, i.e. heterogeneous population of cancer cells tending to a fixed equilibrium of phenotypic proportions, has received much attention in cancer biology very recently. In the previous literature, some theoretical models were used to predict the experimental phenomena of the phenotypic equilibrium, which were often explained by different concepts of stabilities of the models. Here we present a stochastic multi-phenotype branching model by integrating conventional cellular hierarchy with phenotypic plasticity mechanisms of cancer cells. Based on our model, it is shown that: (i) our model can serve as a framework to unify the previous models for the phenotypic equilibrium, and then harmonizes the different kinds of average-level stabilities proposed in these models; and (ii) path-wise convergence of our model provides a deeper understanding to the phenotypic equilibrium from stochastic point of view. That is, the emergence of the phenotypic equilibrium is rooted in the stochastic nature of (almost) every sample path, the average-level stability just follows from it by averaging stochastic samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Comparison of Averaged and Full Models to Study the Third-Body Perturbation

PubMed Central

Solórzano, Carlos Renato Huaura; Prado, Antonio Fernando Bertachini de Almeida

2013-01-01

The effects of a third-body travelling in a circular orbit around a main body on a massless satellite that is orbiting the same main body are studied under two averaged models, single and double, where expansions of the disturbing function are made, and the full restricted circular three-body problem. The goal is to compare the behavior of these two averaged models against the full problem for long-term effects, in order to have some knowledge of their differences. The single averaged model eliminates the terms due to the short period of the spacecraft. The double average is taken over the mean motion of the satellite and the mean motion of the disturbing body, so removing both short period terms. As an example of the methods, an artificial satellite around the Earth perturbed by the Moon is used. A detailed study of the effects of different initial conditions in the orbit of the spacecraft is made. PMID:24319348

A comparison of averaged and full models to study the third-body perturbation.

PubMed

Solórzano, Carlos Renato Huaura; Prado, Antonio Fernando Bertachini de Almeida

2013-01-01

The effects of a third-body travelling in a circular orbit around a main body on a massless satellite that is orbiting the same main body are studied under two averaged models, single and double, where expansions of the disturbing function are made, and the full restricted circular three-body problem. The goal is to compare the behavior of these two averaged models against the full problem for long-term effects, in order to have some knowledge of their differences. The single averaged model eliminates the terms due to the short period of the spacecraft. The double average is taken over the mean motion of the satellite and the mean motion of the disturbing body, so removing both short period terms. As an example of the methods, an artificial satellite around the Earth perturbed by the Moon is used. A detailed study of the effects of different initial conditions in the orbit of the spacecraft is made.

Macroscopic neural mass model constructed from a current-based network model of spiking neurons.

PubMed

Umehara, Hiroaki; Okada, Masato; Teramae, Jun-Nosuke; Naruse, Yasushi

2017-02-01

Neural mass models (NMMs) are efficient frameworks for describing macroscopic cortical dynamics including electroencephalogram and magnetoencephalogram signals. Originally, these models were formulated on an empirical basis of synaptic dynamics with relatively long time constants. By clarifying the relations between NMMs and the dynamics of microscopic structures such as neurons and synapses, we can better understand cortical and neural mechanisms from a multi-scale perspective. In a previous study, the NMMs were analytically derived by averaging the equations of synaptic dynamics over the neurons in the population and further averaging the equations of the membrane-potential dynamics. However, the averaging of synaptic current assumes that the neuron membrane potentials are nearly time invariant and that they remain at sub-threshold levels to retain the conductance-based model. This approximation limits the NMM to the non-firing state. In the present study, we newly propose a derivation of a NMM by alternatively approximating the synaptic current which is assumed to be independent of the membrane potential, thus adopting a current-based model. Our proposed model releases the constraint of the nearly constant membrane potential. We confirm that the obtained model is reducible to the previous model in the non-firing situation and that it reproduces the temporal mean values and relative power spectrum densities of the average membrane potentials for the spiking neurons. It is further ensured that the existing NMM properly models the averaged dynamics over individual neurons even if they are spiking in the populations.

Evaluation of the accuracy of an offline seasonally-varying matrix transport model for simulating ideal age

DOE PAGES

Bardin, Ann; Primeau, Francois; Lindsay, Keith; ...

2016-07-21

Newton-Krylov solvers for ocean tracers have the potential to greatly decrease the computational costs of spinning up deep-ocean tracers, which can take several thousand model years to reach equilibrium with surface processes. One version of the algorithm uses offline tracer transport matrices to simulate an annual cycle of tracer concentrations and applies Newton’s method to find concentrations that are periodic in time. Here we present the impact of time-averaging the transport matrices on the equilibrium values of an ideal-age tracer. We compared annually-averaged, monthly-averaged, and 5-day-averaged transport matrices to an online simulation using the ocean component of the Community Earthmore » System Model (CESM) with a nominal horizontal resolution of 1° × 1° and 60 vertical levels. We found that increasing the time resolution of the offline transport model reduced a low age bias from 12% for the annually-averaged transport matrices, to 4% for the monthly-averaged transport matrices, and to less than 2% for the transport matrices constructed from 5-day averages. The largest differences were in areas with strong seasonal changes in the circulation, such as the Northern Indian Ocean. As a result, for many applications the relatively small bias obtained using the offline model makes the offline approach attractive because it uses significantly less computer resources and is simpler to set up and run.« less

An empirical investigation on the forecasting ability of mallows model averaging in a macro economic environment

NASA Astrophysics Data System (ADS)

Yin, Yip Chee; Hock-Eam, Lim

2012-09-01

This paper investigates the forecasting ability of Mallows Model Averaging (MMA) by conducting an empirical analysis of five Asia countries, Malaysia, Thailand, Philippines, Indonesia and China's GDP growth rate. Results reveal that MMA has no noticeable differences in predictive ability compared to the general autoregressive fractional integrated moving average model (ARFIMA) and its predictive ability is sensitive to the effect of financial crisis. MMA could be an alternative forecasting method for samples without recent outliers such as financial crisis.

Solar-QBO Interaction and Its Impact on Stratospheric Ozone in a Zonally Averaged Photochemical Transport Model of the Middle Atmosphere

DTIC Science & Technology

2007-08-28

Solar- QBO interaction and its impact on stratospheric ozone in a zonally averaged photochemical transport model of the middle atmosphere J. P...investigate the solar cycle modulation of the quasi-biennial oscillation ( QBO ) in stratospheric zonal winds and its impact on stratospheric ozone with an...updated version of the zonally averaged CHEM2D middle atmosphere model. We find that the duration of the westerly QBO phase at solar maximum is 3 months

Bayesian Model Averaging of Artificial Intelligence Models for Hydraulic Conductivity Estimation

NASA Astrophysics Data System (ADS)

Nadiri, A.; Chitsazan, N.; Tsai, F. T.; Asghari Moghaddam, A.

2012-12-01

This research presents a Bayesian artificial intelligence model averaging (BAIMA) method that incorporates multiple artificial intelligence (AI) models to estimate hydraulic conductivity and evaluate estimation uncertainties. Uncertainty in the AI model outputs stems from error in model input as well as non-uniqueness in selecting different AI methods. Using one single AI model tends to bias the estimation and underestimate uncertainty. BAIMA employs Bayesian model averaging (BMA) technique to address the issue of using one single AI model for estimation. BAIMA estimates hydraulic conductivity by averaging the outputs of AI models according to their model weights. In this study, the model weights were determined using the Bayesian information criterion (BIC) that follows the parsimony principle. BAIMA calculates the within-model variances to account for uncertainty propagation from input data to AI model output. Between-model variances are evaluated to account for uncertainty due to model non-uniqueness. We employed Takagi-Sugeno fuzzy logic (TS-FL), artificial neural network (ANN) and neurofuzzy (NF) to estimate hydraulic conductivity for the Tasuj plain aquifer, Iran. BAIMA combined three AI models and produced better fitting than individual models. While NF was expected to be the best AI model owing to its utilization of both TS-FL and ANN models, the NF model is nearly discarded by the parsimony principle. The TS-FL model and the ANN model showed equal importance although their hydraulic conductivity estimates were quite different. This resulted in significant between-model variances that are normally ignored by using one AI model.

Development of a modal emissions model using data from the Cooperative Industry/Government Exhaust Emission test program

DOT National Transportation Integrated Search

2003-06-22

The Environmental Protection Agencys (EPAs) recommended model, MOBILE5a, has been : used extensively to predict emission factors based on average speeds for each fleet type. : Because average speeds are not appropriate in modeling intersections...

Measured values of coal mine stopping resistance

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

Oswald, N.; Prosser, B.; Ruckman, R.

2008-12-15

As coal mines become larger, the number of stoppings in the ventilation system increases. Each stopping represents a potential leakage path which must be adequately represented in the ventilation model. Stopping resistance can be calculated using two methods, the USBM method, used to determine a resistance for a single stopping, and the MVS technique, in which an average resistance is calculated for multiple stoppings. Through MVS data collected from ventilation surveys of different subsurface coal mines, average resistances for stoppings were determined for stopping in poor, average, good, and excellent conditions. The calculated average stoppings resistance were determined for concretemore » block and Kennedy stopping. Using the average stopping resistance, measured and calculated using the MVS method, provides a ventilation modeling tool which can be used to construct more accurate and useful ventilation models. 3 refs., 3 figs.« less

An averaging battery model for a lead-acid battery operating in an electric car

NASA Technical Reports Server (NTRS)

Bozek, J. M.

1979-01-01

A battery model is developed based on time averaging the current or power, and is shown to be an effective means of predicting the performance of a lead acid battery. The effectiveness of this battery model was tested on battery discharge profiles expected during the operation of an electric vehicle following the various SAE J227a driving schedules. The averaging model predicts the performance of a battery that is periodically charged (regenerated) if the regeneration energy is assumed to be converted to retrievable electrochemical energy on a one-to-one basis.

Forecasting coconut production in the Philippines with ARIMA model

NASA Astrophysics Data System (ADS)

Lim, Cristina Teresa

2015-02-01

The study aimed to depict the situation of the coconut industry in the Philippines for the future years applying Autoregressive Integrated Moving Average (ARIMA) method. Data on coconut production, one of the major industrial crops of the country, for the period of 1990 to 2012 were analyzed using time-series methods. Autocorrelation (ACF) and partial autocorrelation functions (PACF) were calculated for the data. Appropriate Box-Jenkins autoregressive moving average model was fitted. Validity of the model was tested using standard statistical techniques. The forecasting power of autoregressive moving average (ARMA) model was used to forecast coconut production for the eight leading years.

Parameter regionalisation methods for a semi-distributed rainfall-runoff model: application to a Northern Apennine region

NASA Astrophysics Data System (ADS)

Neri, Mattia; Toth, Elena

2017-04-01

The study presents the implementation of different regionalisation approaches for the transfer of model parameters from similar and/or neighbouring gauged basin to an ungauged catchment, and in particular it uses a semi-distributed continuously-simulating conceptual rainfall-runoff model for simulating daily streamflows. The case study refers to a set of Apennine catchments (in the Emilia-Romagna region, Italy), that, given the spatial proximity, are assumed to belong to the same hydrologically homogeneous region and are used, alternatively, as donors and regionalised basins. The model is a semi-distributed version of the HBV model (TUWien model) in which the catchment is divided in zones of different altitude that contribute separately to the total outlet flow. The model includes a snow module, whose application in the Apennine area has been, so far, very limited, even if snow accumulation and melting phenomena do have an important role in the study basins. Two methods, both widely applied in the recent literature, are applied for regionalising the model: i) "parameters averaging", where each parameter is obtained as a weighted mean of the parameters obtained, through calibration, on the donor catchments ii) "output averaging", where the model is run over the ungauged basin using the entire set of parameters of each donor basin and the simulated outputs are then averaged. In the first approach, the parameters are regionalised independently from each other, in the second one, instead, the correlation among the parameters is maintained. Since the model is a semi-distributed one, where each elevation zone contributes separately, the study proposes to test also a modified version of the second approach ("output averaging"), where each zone is considered as an autonomous entity, whose parameters are transposed to the ungauged sub-basin corresponding to the same elevation zone. The study explores also the choice of the weights to be used for averaging the parameters (in the "parameters averaging" approach) or for averaging the simulated streamflow (in the "output averaging" approach): in particular, weights are estimated as a function of the similarity/distance of the ungauged basin/zone to the donors, on the basis of a set of geo-morphological catchment descriptors. The predictive accuracy of the different regionalisation methods is finally assessed by jack-knife cross-validation against the observed daily runoff for all the study catchments.

Study on characteristics of the aperture-averaging factor of atmospheric scintillation in terrestrial optical wireless communication

NASA Astrophysics Data System (ADS)

Shen, Hong; Liu, Wen-xing; Zhou, Xue-yun; Zhou, Li-ling; Yu, Long-Kun

2018-02-01

In order to thoroughly understand the characteristics of the aperture-averaging effect of atmospheric scintillation in terrestrial optical wireless communication and provide references for engineering design and performance evaluation of the optics system employed in the atmosphere, we have theoretically deduced the generally analytic expression of the aperture-averaging factor of atmospheric scintillation, and numerically investigated characteristics of the apertureaveraging factor under different propagation conditions. The limitations of the current commonly used approximate calculation formula of aperture-averaging factor have been discussed, and the results showed that the current calculation formula is not applicable for the small receiving aperture under non-uniform turbulence link. Numerical calculation has showed that aperture-averaging factor of atmospheric scintillation presented an exponential decline model for the small receiving aperture under non-uniform turbulent link, and the general expression of the model was given. This model has certain guiding significance for evaluating the aperture-averaging effect in the terrestrial optical wireless communication.

Modeling the Zeeman effect in high altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

NASA Astrophysics Data System (ADS)

Larsson, R.; Milz, M.; Rayer, P.; Saunders, R.; Bell, W.; Booton, A.; Buehler, S. A.; Eriksson, P.; John, V.

2015-10-01

We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Same channel, there is 1.2 K in average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Same channel, there is 1.3 K in average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies causing up to ± 7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

Modeling the Zeeman effect in high-altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

NASA Astrophysics Data System (ADS)

Larsson, Richard; Milz, Mathias; Rayer, Peter; Saunders, Roger; Bell, William; Booton, Anna; Buehler, Stefan A.; Eriksson, Patrick; John, Viju O.

2016-03-01

We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high-altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Concerning the same channel, there is 1.2 K on average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Regarding the same channel, there is 1.3 K on average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies, causing up to ±7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

Model averaging, optimal inference, and habit formation

PubMed Central

FitzGerald, Thomas H. B.; Dolan, Raymond J.; Friston, Karl J.

2014-01-01

Postulating that the brain performs approximate Bayesian inference generates principled and empirically testable models of neuronal function—the subject of much current interest in neuroscience and related disciplines. Current formulations address inference and learning under some assumed and particular model. In reality, organisms are often faced with an additional challenge—that of determining which model or models of their environment are the best for guiding behavior. Bayesian model averaging—which says that an agent should weight the predictions of different models according to their evidence—provides a principled way to solve this problem. Importantly, because model evidence is determined by both the accuracy and complexity of the model, optimal inference requires that these be traded off against one another. This means an agent's behavior should show an equivalent balance. We hypothesize that Bayesian model averaging plays an important role in cognition, given that it is both optimal and realizable within a plausible neuronal architecture. We outline model averaging and how it might be implemented, and then explore a number of implications for brain and behavior. In particular, we propose that model averaging can explain a number of apparently suboptimal phenomena within the framework of approximate (bounded) Bayesian inference, focusing particularly upon the relationship between goal-directed and habitual behavior. PMID:25018724

49 CFR 537.7 - Pre-model year and mid-model year reports.

Code of Federal Regulations, 2010 CFR

2010-10-01

... TRAFFIC SAFETY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AUTOMOTIVE FUEL ECONOMY REPORTS § 537.7 Pre... manufacturer's light trucks for the current model year. (b) Projected average and required fuel economy. (1) State the projected average fuel economy for the manufacturer's automobiles determined in accordance...

49 CFR 537.7 - Pre-model year and mid-model year reports.

Code of Federal Regulations, 2012 CFR

2012-10-01

... TRAFFIC SAFETY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AUTOMOTIVE FUEL ECONOMY REPORTS § 537.7 Pre... manufacturer's light trucks for the current model year. (b) Projected average and required fuel economy. (1) State the projected average fuel economy for the manufacturer's automobiles determined in accordance...

49 CFR 537.7 - Pre-model year and mid-model year reports.

Code of Federal Regulations, 2011 CFR

2011-10-01

... TRAFFIC SAFETY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AUTOMOTIVE FUEL ECONOMY REPORTS § 537.7 Pre... manufacturer's light trucks for the current model year. (b) Projected average and required fuel economy. (1) State the projected average fuel economy for the manufacturer's automobiles determined in accordance...

49 CFR 537.7 - Pre-model year and mid-model year reports.

Code of Federal Regulations, 2014 CFR

2014-10-01

.... List the model types in order of increasing average inertia weight from top to bottom down the left... form. List the model types in order of increasing average inertia weight from top to bottom down the... trucks in your fleet that meet the mild and strong hybrid vehicle definitions. For each mild and strong...

49 CFR 537.7 - Pre-model year and mid-model year reports.

Code of Federal Regulations, 2013 CFR

2013-10-01

.... List the model types in order of increasing average inertia weight from top to bottom down the left... form. List the model types in order of increasing average inertia weight from top to bottom down the... trucks in your fleet that meet the mild and strong hybrid vehicle definitions. For each mild and strong...

Climate modeling for Yamal territory using supercomputer atmospheric circulation model ECHAM5-wiso

NASA Astrophysics Data System (ADS)

Denisova, N. Y.; Gribanov, K. G.; Werner, M.; Zakharov, V. I.

2015-11-01

Dependences of monthly means of regional averages of model atmospheric parameters on initial and boundary condition remoteness in the past are the subject of the study. We used atmospheric general circulation model ECHAM5-wiso for simulation of monthly means of regional averages of climate parameters for Yamal region and different periods of premodeling. Time interval was varied from several months to 12 years. We present dependences of model monthly means of regional averages of surface temperature, 2 m air temperature and humidity for December of 2000 on duration of premodeling. Comparison of these results with reanalysis data showed that best coincidence with true parameters could be reached if duration of pre-modelling is approximately 10 years.

The Crossover Time as an Evaluation of Ocean Models Against Persistence

NASA Astrophysics Data System (ADS)

Phillipson, L. M.; Toumi, R.

2018-01-01

A new ocean evaluation metric, the crossover time, is defined as the time it takes for a numerical model to equal the performance of persistence. As an example, the average crossover time calculated using the Lagrangian separation distance (the distance between simulated trajectories and observed drifters) for the global MERCATOR ocean model analysis is found to be about 6 days. Conversely, the model forecast has an average crossover time longer than 6 days, suggesting limited skill in Lagrangian predictability by the current generation of global ocean models. The crossover time of the velocity error is less than 3 days, which is similar to the average decorrelation time of the observed drifters. The crossover time is a useful measure to quantify future ocean model improvements.

Water quality characterization and mathematical modeling of dissolved oxygen in the East and West Ponds, Jamaica Bay Wildlife Refuge.

PubMed

Maillacheruvu, Krishnanand; Roy, D; Tanacredi, J

2003-09-01

The current study was undertaken to characterize the East and West Ponds and develop a mathematical model of the effects of nutrient and BOD loading on dissolved oxygen (DO) concentrations in these ponds. The model predicted that both ponds will recover adequately given the average expected range of nutrient and BOD loading due to waste from surface runoff and migratory birds. The predicted dissolved oxygen levels in both ponds were greater than 5.0 mg/L, and were supported by DO levels in the field which were typically above 5.0 mg/L during the period of this study. The model predicted a steady-state NBOD concentration of 12.0-14.0 mg/L in the East Pond, compared to an average measured value of 3.73 mg/L in 1994 and an average measured value of 12.51 mg/L in a 1996-97 study. The model predicted that the NBOD concentration in the West Pond would be under 3.0 mg/L compared to the average measured values of 7.50 mg/L in 1997, and 8.51 mg/L in 1994. The model predicted that phosphorus (as PO4(3-)) concentration in the East Pond will approach 4.2 mg/L in 4 months, compared to measured average value of 2.01 mg/L in a 1994 study. The model predicted that phosphorus concentration in the West Pond will approach 1.00 mg/L, compared to a measured average phosphorus (as PO4(3-)) concentration of 1.57 mg/L in a 1994 study.

Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-05-29

Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final globalmore » uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.« less

Modeling particle number concentrations along Interstate 10 in El Paso, Texas

PubMed Central

Olvera, Hector A.; Jimenez, Omar; Provencio-Vasquez, Elias

2014-01-01

Annual average daily particle number concentrations around a highway were estimated with an atmospheric dispersion model and a land use regression model. The dispersion model was used to estimate particle concentrations along Interstate 10 at 98 locations within El Paso, Texas. This model employed annual averaged wind speed and annual average daily traffic counts as inputs. A land use regression model with vehicle kilometers traveled as the predictor variable was used to estimate local background concentrations away from the highway to adjust the near-highway concentration estimates. Estimated particle number concentrations ranged between 9.8 × 103 particles/cc and 1.3 × 105 particles/cc, and averaged 2.5 × 104 particles/cc (SE 421.0). Estimates were compared against values measured at seven sites located along I10 throughout the region. The average fractional error was 6% and ranged between -1% and -13% across sites. The largest bias of -13% was observed at a semi-rural site where traffic was lowest. The average bias amongst urban sites was 5%. The accuracy of the estimates depended primarily on the emission factor and the adjustment to local background conditions. An emission factor of 1.63 × 1014 particles/veh-km was based on a value proposed in the literature and adjusted with local measurements. The integration of the two modeling techniques ensured that the particle number concentrations estimates captured the impact of traffic along both the highway and arterial roadways. The performance and economical aspects of the two modeling techniques used in this study shows that producing particle concentration surfaces along major roadways would be feasible in urban regions where traffic and meteorological data are readily available. PMID:25313294

Instantaneous and time-averaged dispersion and measurement models for estimation theory applications with elevated point source plumes

NASA Technical Reports Server (NTRS)

Diamante, J. M.; Englar, T. S., Jr.; Jazwinski, A. H.

1977-01-01

Estimation theory, which originated in guidance and control research, is applied to the analysis of air quality measurements and atmospheric dispersion models to provide reliable area-wide air quality estimates. A method for low dimensional modeling (in terms of the estimation state vector) of the instantaneous and time-average pollutant distributions is discussed. In particular, the fluctuating plume model of Gifford (1959) is extended to provide an expression for the instantaneous concentration due to an elevated point source. Individual models are also developed for all parameters in the instantaneous and the time-average plume equations, including the stochastic properties of the instantaneous fluctuating plume.

A model for closing the inviscid form of the average-passage equation system

NASA Technical Reports Server (NTRS)

Adamczyk, J. J.; Mulac, R. A.; Celestina, M. L.

1985-01-01

A mathematical model is proposed for closing or mathematically completing the system of equations which describes the time average flow field through the blade passages of multistage turbomachinery. These equations referred to as the average passage equation system govern a conceptual model which has proven useful in turbomachinery aerodynamic design and analysis. The closure model is developed so as to insure a consistency between these equations and the axisymmetric through flow equations. The closure model was incorporated into a computer code for use in simulating the flow field about a high speed counter rotating propeller and a high speed fan stage. Results from these simulations are presented.

The Case of Effort Variables in Student Performance.

ERIC Educational Resources Information Center

Borg, Mary O.; And Others

1989-01-01

Tests the existence of a structural shift between above- and below-average students in the econometric models that explain students' grades in principles of economics classes. Identifies a structural shift and estimates separate models for above- and below-average students. Concludes that separate models as well as educational policies are…

Time Series ARIMA Models of Undergraduate Grade Point Average.

ERIC Educational Resources Information Center

Rogers, Bruce G.

The Auto-Regressive Integrated Moving Average (ARIMA) Models, often referred to as Box-Jenkins models, are regression methods for analyzing sequential dependent observations with large amounts of data. The Box-Jenkins approach, a three-stage procedure consisting of identification, estimation and diagnosis, was used to select the most appropriate…

Estimation of open water evaporation using land-based meteorological data

NASA Astrophysics Data System (ADS)

Li, Fawen; Zhao, Yong

2017-10-01

Water surface evaporation is an important process in the hydrologic and energy cycles. Accurate simulation of water evaporation is important for the evaluation of water resources. In this paper, using meteorological data from the Aixinzhuang reservoir, the main factors affecting water surface evaporation were determined by the principal component analysis method. To illustrate the influence of these factors on water surface evaporation, the paper first adopted the Dalton model to simulate water surface evaporation. The results showed that the simulation precision was poor for the peak value zone. To improve the model simulation's precision, a modified Dalton model considering relative humidity was proposed. The results show that the 10-day average relative error is 17.2%, assessed as qualified; the monthly average relative error is 12.5%, assessed as qualified; and the yearly average relative error is 3.4%, assessed as excellent. To validate its applicability, the meteorological data of Kuancheng station in the Luan River basin were selected to test the modified model. The results show that the 10-day average relative error is 15.4%, assessed as qualified; the monthly average relative error is 13.3%, assessed as qualified; and the yearly average relative error is 6.0%, assessed as good. These results showed that the modified model had good applicability and versatility. The research results can provide technical support for the calculation of water surface evaporation in northern China or similar regions.

Forecast of Frost Days Based on Monthly Temperatures

NASA Astrophysics Data System (ADS)

Castellanos, M. T.; Tarquis, A. M.; Morató, M. C.; Saa-Requejo, A.

2009-04-01

Although frost can cause considerable crop damage and mitigation practices against forecasted frost exist, frost forecasting technologies have not changed for many years. The paper reports a new method to forecast the monthly number of frost days (FD) for several meteorological stations at Community of Madrid (Spain) based on successive application of two models. The first one is a stochastic model, autoregressive integrated moving average (ARIMA), that forecasts monthly minimum absolute temperature (tmin) and monthly average of minimum temperature (tminav) following Box-Jenkins methodology. The second model relates these monthly temperatures to minimum daily temperature distribution during one month. Three ARIMA models were identified for the time series analyzed with a stational period correspondent to one year. They present the same stational behavior (moving average differenced model) and different non-stational part: autoregressive model (Model 1), moving average differenced model (Model 2) and autoregressive and moving average model (Model 3). At the same time, the results point out that minimum daily temperature (tdmin), for the meteorological stations studied, followed a normal distribution each month with a very similar standard deviation through years. This standard deviation obtained for each station and each month could be used as a risk index for cold months. The application of Model 1 to predict minimum monthly temperatures showed the best FD forecast. This procedure provides a tool for crop managers and crop insurance companies to asses the risk of frost frequency and intensity, so that they can take steps to mitigate against frost damage and estimated the damage that frost would cost. This research was supported by Comunidad de Madrid Research Project 076/92. The cooperation of the Spanish National Meteorological Institute and the Spanish Ministerio de Agricultura, Pesca y Alimentation (MAPA) is gratefully acknowledged.

Validation of a spatial model used to locate fish spawning reef construction sites in the St. Clair–Detroit River system

USGS Publications Warehouse

Fischer, Jason L.; Bennion, David; Roseman, Edward F.; Manny, Bruce A.

2015-01-01

Lake sturgeon (Acipenser fulvescens) populations have suffered precipitous declines in the St. Clair–Detroit River system, following the removal of gravel spawning substrates and overfishing in the late 1800s to mid-1900s. To assist the remediation of lake sturgeon spawning habitat, three hydrodynamic models were integrated into a spatial model to identify areas in two large rivers, where water velocities were appropriate for the restoration of lake sturgeon spawning habitat. Here we use water velocity data collected with an acoustic Doppler current profiler (ADCP) to assess the ability of the spatial model and its sub-models to correctly identify areas where water velocities were deemed suitable for restoration of fish spawning habitat. ArcMap 10.1 was used to create raster grids of water velocity data from model estimates and ADCP measurements which were compared to determine the percentage of cells similarly classified as unsuitable, suitable, or ideal for fish spawning habitat remediation. The spatial model categorized 65% of the raster cells the same as depth-averaged water velocity measurements from the ADCP and 72% of the raster cells the same as surface water velocity measurements from the ADCP. Sub-models focused on depth-averaged velocities categorized the greatest percentage of cells similar to ADCP measurements where 74% and 76% of cells were the same as depth-averaged water velocity measurements. Our results indicate that integrating depth-averaged and surface water velocity hydrodynamic models may have biased the spatial model and overestimated suitable spawning habitat. A model solely integrating depth-averaged velocity models could improve identification of areas suitable for restoration of fish spawning habitat.

Using Discrete Event Simulation to predict KPI's at a Projected Emergency Room.

PubMed

Concha, Pablo; Neriz, Liliana; Parada, Danilo; Ramis, Francisco

2015-01-01

Discrete Event Simulation (DES) is a powerful factor in the design of clinical facilities. DES enables facilities to be built or adapted to achieve the expected Key Performance Indicators (KPI's) such as average waiting times according to acuity, average stay times and others. Our computational model was built and validated using expert judgment and supporting statistical data. One scenario studied resulted in a 50% decrease in the average cycle time of patients compared to the original model, mainly by modifying the patient's attention model.

The effect of the behavior of an average consumer on the public debt dynamics

NASA Astrophysics Data System (ADS)

De Luca, Roberto; Di Mauro, Marco; Falzarano, Angelo; Naddeo, Adele

2017-09-01

An important issue within the present economic crisis is understanding the dynamics of the public debt of a given country, and how the behavior of average consumers and tax payers in that country affects it. Starting from a model of the average consumer behavior introduced earlier by the authors, we propose a simple model to quantitatively address this issue. The model is then studied and analytically solved under some reasonable simplifying assumptions. In this way we obtain a condition under which the public debt steadily decreases.

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

USGS Publications Warehouse

Tillman, Fred D.; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-01-01

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

Bootstrap-after-bootstrap model averaging for reducing model uncertainty in model selection for air pollution mortality studies.

PubMed

Roberts, Steven; Martin, Michael A

2010-01-01

Concerns have been raised about findings of associations between particulate matter (PM) air pollution and mortality that have been based on a single "best" model arising from a model selection procedure, because such a strategy may ignore model uncertainty inherently involved in searching through a set of candidate models to find the best model. Model averaging has been proposed as a method of allowing for model uncertainty in this context. To propose an extension (double BOOT) to a previously described bootstrap model-averaging procedure (BOOT) for use in time series studies of the association between PM and mortality. We compared double BOOT and BOOT with Bayesian model averaging (BMA) and a standard method of model selection [standard Akaike's information criterion (AIC)]. Actual time series data from the United States are used to conduct a simulation study to compare and contrast the performance of double BOOT, BOOT, BMA, and standard AIC. Double BOOT produced estimates of the effect of PM on mortality that have had smaller root mean squared error than did those produced by BOOT, BMA, and standard AIC. This performance boost resulted from estimates produced by double BOOT having smaller variance than those produced by BOOT and BMA. Double BOOT is a viable alternative to BOOT and BMA for producing estimates of the mortality effect of PM.

40 CFR 60.3042 - How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units?

Code of Federal Regulations, 2012 CFR

2012-07-01

... averages into the appropriate averaging times and units? 60.3042 Section 60.3042 Protection of Environment... Construction On or Before December 9, 2004 Model Rule-Monitoring § 60.3042 How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units? (a) Use Equation 1 in § 60.3076 to...

40 CFR 60.3042 - How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units?

Code of Federal Regulations, 2010 CFR

2010-07-01

... averages into the appropriate averaging times and units? 60.3042 Section 60.3042 Protection of Environment... Construction On or Before December 9, 2004 Model Rule-Monitoring § 60.3042 How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units? (a) Use Equation 1 in § 60.3076 to...

40 CFR 60.3042 - How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units?

Code of Federal Regulations, 2013 CFR

2013-07-01

... averages into the appropriate averaging times and units? 60.3042 Section 60.3042 Protection of Environment... Construction On or Before December 9, 2004 Model Rule-Monitoring § 60.3042 How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units? (a) Use Equation 1 in § 60.3076 to...

40 CFR 60.3042 - How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units?

Code of Federal Regulations, 2011 CFR

2011-07-01

... averages into the appropriate averaging times and units? 60.3042 Section 60.3042 Protection of Environment... Construction On or Before December 9, 2004 Model Rule-Monitoring § 60.3042 How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units? (a) Use Equation 1 in § 60.3076 to...

40 CFR 60.3042 - How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units?

Code of Federal Regulations, 2014 CFR

2014-07-01

... averages into the appropriate averaging times and units? 60.3042 Section 60.3042 Protection of Environment... Construction On or Before December 9, 2004 Model Rule-Monitoring § 60.3042 How do I convert my 1-hour arithmetic averages into the appropriate averaging times and units? (a) Use Equation 1 in § 60.3076 to...

Multi-Model Combination techniques for Hydrological Forecasting: Application to Distributed Model Intercomparison Project Results

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

Ajami, N K; Duan, Q; Gao, X

2005-04-11

This paper examines several multi-model combination techniques: the Simple Multi-model Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniquesmore » affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction.« less

Testing averaged cosmology with type Ia supernovae and BAO data

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

Santos, B.; Alcaniz, J.S.; Coley, A.A.

An important problem in precision cosmology is the determination of the effects of averaging and backreaction on observational predictions, particularly in view of the wealth of new observational data and improved statistical techniques. In this paper, we discuss the observational viability of a class of averaged cosmologies which consist of a simple parametrized phenomenological two-scale backreaction model with decoupled spatial curvature parameters. We perform a Bayesian model selection analysis and find that this class of averaged phenomenological cosmological models is favored with respect to the standard ΛCDM cosmological scenario when a joint analysis of current SNe Ia and BAO datamore » is performed. In particular, the analysis provides observational evidence for non-trivial spatial curvature.« less

[Influence of trabecular microstructure modeling on finite element analysis of dental implant].

PubMed

Shen, M J; Wang, G G; Zhu, X H; Ding, X

2016-09-01

To analyze the influence of trabecular microstructure modeling on the biomechanical distribution of implant-bone interface with a three-dimensional finite element mandible model of trabecular structure. Dental implants were embeded in the mandibles of a beagle dog. After three months of the implant installation, the mandibles with dental implants were harvested and scaned by micro-CT and cone-beam CT. Two three-dimensional finite element mandible models, trabecular microstructure(precise model) and macrostructure(simplified model), were built. The values of stress and strain of implant-bone interface were calculated using the software of Ansys 14.0. Compared with the simplified model, the precise models' average values of the implant bone interface stress increased obviously and its maximum values did not change greatly. The maximum values of quivalent stress of the precise models were 80% and 110% of the simplified model and the average values were 170% and 290% of simplified model. The maximum and average values of equivalent strain of precise models were obviously decreased, and the maximum values of the equivalent effect strain were 17% and 26% of simplified model and the average ones were 21% and 16% of simplified model respectively. Stress and strain concentrations at implant-bone interface were obvious in the simplified model. However, the distributions of stress and strain were uniform in the precise model. The precise model has significant effect on the distribution of stress and strain at implant-bone interface.

The Stagger-grid: A grid of 3D stellar atmosphere models. II. Horizontal and temporal averaging and spectral line formation

NASA Astrophysics Data System (ADS)

Magic, Z.; Collet, R.; Hayek, W.; Asplund, M.

2013-12-01

Aims: We study the implications of averaging methods with different reference depth scales for 3D hydrodynamical model atmospheres computed with the Stagger-code. The temporally and spatially averaged (hereafter denoted as ⟨3D⟩) models are explored in the light of local thermodynamic equilibrium (LTE) spectral line formation by comparing spectrum calculations using full 3D atmosphere structures with those from ⟨3D⟩ averages. Methods: We explored methods for computing mean ⟨3D⟩ stratifications from the Stagger-grid time-dependent 3D radiative hydrodynamical atmosphere models by considering four different reference depth scales (geometrical depth, column-mass density, and two optical depth scales). Furthermore, we investigated the influence of alternative averages (logarithmic, enforced hydrostatic equilibrium, flux-weighted temperatures). For the line formation we computed curves of growth for Fe i and Fe ii lines in LTE. Results: The resulting ⟨3D⟩ stratifications for the four reference depth scales can be very different. We typically find that in the upper atmosphere and in the superadiabatic region just below the optical surface, where the temperature and density fluctuations are highest, the differences become considerable and increase for higher Teff, lower log g, and lower [Fe / H]. The differential comparison of spectral line formation shows distinctive differences depending on which ⟨3D⟩ model is applied. The averages over layers of constant column-mass density yield the best mean ⟨3D⟩ representation of the full 3D models for LTE line formation, while the averages on layers at constant geometrical height are the least appropriate. Unexpectedly, the usually preferred averages over layers of constant optical depth are prone to increasing interference by reversed granulation towards higher effective temperature, in particular at low metallicity. Appendix A is available in electronic form at http://www.aanda.orgMean ⟨3D⟩ models are available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/560/A8 as well as at http://www.stagger-stars.net

Effects of whole spine alignment patterns on neck responses in rear end impact.

PubMed

Sato, Fusako; Odani, Mamiko; Miyazaki, Yusuke; Yamazaki, Kunio; Östh, Jonas; Svensson, Mats

2017-02-17

The aim of this study was to investigate the whole spine alignment in automotive seated postures for both genders and the effects of the spinal alignment patterns on cervical vertebral motion in rear impact using a human finite element (FE) model. Image data for 8 female and 7 male subjects in a seated posture acquired by an upright open magnetic resonance imaging (MRI) system were utilized. Spinal alignment was determined from the centers of the vertebrae and average spinal alignment patterns for both genders were estimated by multidimensional scaling (MDS). An occupant FE model of female average size (162 cm, 62 kg; the AF 50 size model) was developed by scaling THUMS AF 05. The average spinal alignment pattern for females was implemented in the model, and model validation was made with respect to female volunteer sled test data from rear end impacts. Thereafter, the average spinal alignment pattern for males and representative spinal alignments for all subjects were implemented in the validated female model, and additional FE simulations of the sled test were conducted to investigate effects of spinal alignment patterns on cervical vertebral motion. The estimated average spinal alignment pattern was slight kyphotic, or almost straight cervical and less-kyphotic thoracic spine for the females and lordotic cervical and more pronounced kyphotic thoracic spine for the males. The AF 50 size model with the female average spinal alignment exhibited spine straightening from upper thoracic vertebra level and showed larger intervertebral angular displacements in the cervical spine than the one with the male average spinal alignment. The cervical spine alignment is continuous with the thoracic spine, and a trend of the relationship between cervical spine and thoracic spinal alignment was shown in this study. Simulation results suggested that variations in thoracic spinal alignment had a potential impact on cervical spine motion as well as cervical spinal alignment in rear end impact condition.

Partially-Averaged Navier Stokes Model for Turbulence: Implementation and Validation

NASA Technical Reports Server (NTRS)

Girimaji, Sharath S.; Abdol-Hamid, Khaled S.

2005-01-01

Partially-averaged Navier Stokes (PANS) is a suite of turbulence closure models of various modeled-to-resolved scale ratios ranging from Reynolds-averaged Navier Stokes (RANS) to Navier-Stokes (direct numerical simulations). The objective of PANS, like hybrid models, is to resolve large scale structures at reasonable computational expense. The modeled-to-resolved scale ratio or the level of physical resolution in PANS is quantified by two parameters: the unresolved-to-total ratios of kinetic energy (f(sub k)) and dissipation (f(sub epsilon)). The unresolved-scale stress is modeled with the Boussinesq approximation and modeled transport equations are solved for the unresolved kinetic energy and dissipation. In this paper, we first present a brief discussion of the PANS philosophy followed by a description of the implementation procedure and finally perform preliminary evaluation in benchmark problems.

Statistical Ensemble of Large Eddy Simulations

NASA Technical Reports Server (NTRS)

Carati, Daniele; Rogers, Michael M.; Wray, Alan A.; Mansour, Nagi N. (Technical Monitor)

2001-01-01

A statistical ensemble of large eddy simulations (LES) is run simultaneously for the same flow. The information provided by the different large scale velocity fields is used to propose an ensemble averaged version of the dynamic model. This produces local model parameters that only depend on the statistical properties of the flow. An important property of the ensemble averaged dynamic procedure is that it does not require any spatial averaging and can thus be used in fully inhomogeneous flows. Also, the ensemble of LES's provides statistics of the large scale velocity that can be used for building new models for the subgrid-scale stress tensor. The ensemble averaged dynamic procedure has been implemented with various models for three flows: decaying isotropic turbulence, forced isotropic turbulence, and the time developing plane wake. It is found that the results are almost independent of the number of LES's in the statistical ensemble provided that the ensemble contains at least 16 realizations.

Redshift drift in an inhomogeneous universe: averaging and the backreaction conjecture

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

Koksbang, S.M.; Hannestad, S., E-mail: koksbang@phys.au.dk, E-mail: sth@phys.au.dk

2016-01-01

An expression for the average redshift drift in a statistically homogeneous and isotropic dust universe is given. The expression takes the same form as the expression for the redshift drift in FLRW models. It is used for a proof-of-principle study of the effects of backreaction on redshift drift measurements by combining the expression with two-region models. The study shows that backreaction can lead to positive redshift drift at low redshifts, exemplifying that a positive redshift drift at low redshifts does not require dark energy. Moreover, the study illustrates that models without a dark energy component can have an average redshiftmore » drift observationally indistinguishable from that of the standard model according to the currently expected precision of ELT measurements. In an appendix, spherically symmetric solutions to Einstein's equations with inhomogeneous dark energy and matter are used to study deviations from the average redshift drift and effects of local voids.« less

Expected indoor 222Rn levels in counties with very high and very low lung cancer rates.

PubMed

Cohen, B L

1989-12-01

Counties in the U.S. with high lung cancer rates should have higher average 222Rn levels than counties with low lung cancer rates, assuming the average 222Rn level in a county is not correlated with other factors that cause lung cancer. The magnitude of this effect was calculated, using the absolute risk model, the relative risk model, and an intermediate model, for females who died in 1950-1969. The results were similar for all three models. We concluded that, ignoring migration, the average Rn level in the highest lung cancer counties should be about three times higher than in the lowest lung cancer counties according to the theory. Preliminary data are presented indicating that the situation is quite the opposite: The average Rn level in the highest lung cancer counties was only about one-half that in the lowest lung cancer counties.

Accuracy of three-dimensional dental resin models created by fused deposition modeling, stereolithography, and Polyjet prototype technologies: A comparative study.

PubMed

Rebong, Raymund E; Stewart, Kelton T; Utreja, Achint; Ghoneima, Ahmed A

2018-05-01

The aim of this study was to assess the dimensional accuracy of fused deposition modeling (FDM)-, Polyjet-, and stereolithography (SLA)-produced models by comparing them to traditional plaster casts. A total of 12 maxillary and mandibular posttreatment orthodontic plaster casts were selected from the archives of the Orthodontic Department at the Indiana University School of Dentistry. Plaster models were scanned, saved as stereolithography files, and printed as physical models using three different three-dimensional (3D) printers: Makerbot Replicator (FDM), 3D Systems SLA 6000 (SLA), and Objet Eden500V (Polyjet). A digital caliper was used to obtain measurements on the original plaster models as well as on the printed resin models. Comparison between the 3D printed models and the plaster casts showed no statistically significant differences in most of the parameters. However, FDM was significantly higher on average than were plaster casts in maxillary left mixed plane (MxL-MP) and mandibular intermolar width (Md-IMW). Polyjet was significantly higher on average than were plaster casts in maxillary intercanine width (Mx-ICW), mandibular intercanine width (Md-ICW), and mandibular left mixed plane (MdL-MP). Polyjet was significantly lower on average than were plaster casts in maxillary right vertical plane (MxR-vertical), maxillary left vertical plane (MxL-vertical), mandibular right anteroposterior plane (MdR-AP), mandibular right vertical plane (MdR-vertical), and mandibular left vertical plane (MdL-vertical). SLA was significantly higher on average than were plaster casts in MxL-MP, Md-ICW, and overbite. SLA was significantly lower on average than were plaster casts in MdR-vertical and MdL-vertical. Dental models reconstructed by FDM technology had the fewest dimensional measurement differences compared to plaster models.

Assessing the Resolution Adaptability of the Zhang-McFarlane Cumulus Parameterization With Spatial and Temporal Averaging: RESOLUTION ADAPTABILITY OF ZM SCHEME

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

Yun, Yuxing; Fan, Jiwen; Xiao, Heng

Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32more » km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.« less

77 FR 17219 - Patient Protection and Affordable Care Act; Standards Related to Reinsurance, Risk Corridors and...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-23

... parts of the risk adjustment process--the risk adjustment model, the calculation of plan average... risk adjustment process. The risk adjustment model calculates individual risk scores. The calculation...'' to mean all data that are used in a risk adjustment model, the calculation of plan average actuarial...

National Snow Analyses - NOHRSC - The ultimate source for snow information

Science.gov Websites

Equivalent Thumbnail image of Modeled Snow Water Equivalent Animate: Season --- Two weeks --- One Day Snow Depth Thumbnail image of Modeled Snow Depth Animate: Season --- Two weeks --- One Day Average Snowpack Temp Thumbnail image of Modeled Average Snowpack Temp Animate: Season --- Two weeks --- One Day SWE

Recommendations for the U.S. Coast Guard Survival Prediction Tool

DTIC Science & Technology

2009-04-01

model. Not enough data to support modeling of how alcohol impairs swimming ability. Experimental evidence shows no significant cooling effect 50...equation. When matched for physical attributes, females cool more quickly than males due to lower metabolic response and greater surface-area-to-mass...April 2009 However, the average female has about 10% more body fat than the average male so, on average, males cool faster than females. (Tipton

40 CFR 91.1304 - Averaging.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Averaging. (a) A manufacturer may use averaging across engine families to demonstrate a zero or positive... credits obtained through trading. (b) Beginning in model year 2004, credits used to demonstrate a zero or...

40 CFR 91.1304 - Averaging.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Averaging. (a) A manufacturer may use averaging across engine families to demonstrate a zero or positive... credits obtained through trading. (b) Beginning in model year 2004, credits used to demonstrate a zero or...

40 CFR 91.1304 - Averaging.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Averaging. (a) A manufacturer may use averaging across engine families to demonstrate a zero or positive... credits obtained through trading. (b) Beginning in model year 2004, credits used to demonstrate a zero or...

40 CFR 91.1304 - Averaging.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Averaging. (a) A manufacturer may use averaging across engine families to demonstrate a zero or positive... credits obtained through trading. (b) Beginning in model year 2004, credits used to demonstrate a zero or...

40 CFR 91.1304 - Averaging.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Averaging. (a) A manufacturer may use averaging across engine families to demonstrate a zero or positive... credits obtained through trading. (b) Beginning in model year 2004, credits used to demonstrate a zero or...

Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method

NASA Astrophysics Data System (ADS)

Tsai, F. T. C.; Elshall, A. S.

2014-12-01

Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using the hierarchical Bayesian model averaging (HBMA) method [1], this study shows that segregating different uncertain model components through a BMA tree of posterior model probabilities, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool [2]. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater modeling of a siliciclastic aquifer-fault system. The sources of uncertainty considered are from geological architecture, formation dip, boundary conditions and model parameters. The study shows that the HBMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models. [1] Tsai, F. T.-C., and A. S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation. Water Resources Research, 49, 5520-5536, doi:10.1002/wrcr.20428. [2] Elshall, A.S., and F. T.-C. Tsai (2014). Constructive epistemic modeling of groundwater flow with geological architecture and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119, doi: 10.1016/j.jhydrol.2014.05.027.

Occupational exposure assessment of magnetic fields generated by induction heating equipment-the role of spatial averaging.

PubMed

Kos, Bor; Valič, Blaž; Kotnik, Tadej; Gajšek, Peter

2012-10-07

Induction heating equipment is a source of strong and nonhomogeneous magnetic fields, which can exceed occupational reference levels. We investigated a case of an induction tempering tunnel furnace. Measurements of the emitted magnetic flux density (B) were performed during its operation and used to validate a numerical model of the furnace. This model was used to compute the values of B and the induced in situ electric field (E) for 15 different body positions relative to the source. For each body position, the computed B values were used to determine their maximum and average values, using six spatial averaging schemes (9-285 averaging points) and two averaging algorithms (arithmetic mean and quadratic mean). Maximum and average B values were compared to the ICNIRP reference level, and E values to the ICNIRP basic restriction. Our results show that in nonhomogeneous fields, the maximum B is an overly conservative predictor of overexposure, as it yields many false positives. The average B yielded fewer false positives, but as the number of averaging points increased, false negatives emerged. The most reliable averaging schemes were obtained for averaging over the torso with quadratic averaging, with no false negatives even for the maximum number of averaging points investigated.

A novel convolution-based approach to address ionization chamber volume averaging effect in model-based treatment planning systems

NASA Astrophysics Data System (ADS)

Barraclough, Brendan; Li, Jonathan G.; Lebron, Sharon; Fan, Qiyong; Liu, Chihray; Yan, Guanghua

2015-08-01

The ionization chamber volume averaging effect is a well-known issue without an elegant solution. The purpose of this study is to propose a novel convolution-based approach to address the volume averaging effect in model-based treatment planning systems (TPSs). Ionization chamber-measured beam profiles can be regarded as the convolution between the detector response function and the implicit real profiles. Existing approaches address the issue by trying to remove the volume averaging effect from the measurement. In contrast, our proposed method imports the measured profiles directly into the TPS and addresses the problem by reoptimizing pertinent parameters of the TPS beam model. In the iterative beam modeling process, the TPS-calculated beam profiles are convolved with the same detector response function. Beam model parameters responsible for the penumbra are optimized to drive the convolved profiles to match the measured profiles. Since the convolved and the measured profiles are subject to identical volume averaging effect, the calculated profiles match the real profiles when the optimization converges. The method was applied to reoptimize a CC13 beam model commissioned with profiles measured with a standard ionization chamber (Scanditronix Wellhofer, Bartlett, TN). The reoptimized beam model was validated by comparing the TPS-calculated profiles with diode-measured profiles. Its performance in intensity-modulated radiation therapy (IMRT) quality assurance (QA) for ten head-and-neck patients was compared with the CC13 beam model and a clinical beam model (manually optimized, clinically proven) using standard Gamma comparisons. The beam profiles calculated with the reoptimized beam model showed excellent agreement with diode measurement at all measured geometries. Performance of the reoptimized beam model was comparable with that of the clinical beam model in IMRT QA. The average passing rates using the reoptimized beam model increased substantially from 92.1% to 99.3% with 3%/3 mm and from 79.2% to 95.2% with 2%/2 mm when compared with the CC13 beam model. These results show the effectiveness of the proposed method. Less inter-user variability can be expected of the final beam model. It is also found that the method can be easily integrated into model-based TPS.

Comparative evaluation of a new lactation curve model for pasture-based Holstein-Friesian dairy cows.

PubMed

Adediran, S A; Ratkowsky, D A; Donaghy, D J; Malau-Aduli, A E O

2012-09-01

Fourteen lactation models were fitted to average and individual cow lactation data from pasture-based dairy systems in the Australian states of Victoria and Tasmania. The models included a new "log-quadratic" model, and a major objective was to evaluate and compare the performance of this model with the other models. Nine empirical and 5 mechanistic models were first fitted to average test-day milk yield of Holstein-Friesian dairy cows using the nonlinear procedure in SAS. Two additional semiparametric models were fitted using a linear model in ASReml. To investigate the influence of days to first test-day and the number of test-days, 5 of the best-fitting models were then fitted to individual cow lactation data. Model goodness of fit was evaluated using criteria such as the residual mean square, the distribution of residuals, the correlation between actual and predicted values, and the Wald-Wolfowitz runs test. Goodness of fit was similar in all but one of the models in terms of fitting average lactation but they differed in their ability to predict individual lactations. In particular, the widely used incomplete gamma model most displayed this failing. The new log-quadratic model was robust in fitting average and individual lactations, and was less affected by sampled data and more parsimonious in having only 3 parameters, each of which lends itself to biological interpretation. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Thomson scattering in the average-atom approximation.

PubMed

Johnson, W R; Nilsen, J; Cheng, K T

2012-09-01

The average-atom model is applied to study Thomson scattering of x-rays from warm dense matter with emphasis on scattering by bound electrons. Parameters needed to evaluate the dynamic structure function (chemical potential, average ionic charge, free electron density, bound and continuum wave functions, and occupation numbers) are obtained from the average-atom model. The resulting analysis provides a relatively simple diagnostic for use in connection with x-ray scattering measurements. Applications are given to dense hydrogen, beryllium, aluminum, and titanium plasmas. In the case of titanium, bound states are predicted to modify the spectrum significantly.

Free-free opacity in dense plasmas with an average atom model

DOE PAGES

Shaffer, Nathaniel R.; Ferris, Natalie G.; Colgan, James Patrick; ...

2017-02-28

A model for the free-free opacity of dense plasmas is presented. The model uses a previously developed average atom model, together with the Kubo-Greenwood model for optical conductivity. This, in turn, is used to calculate the opacity with the Kramers-Kronig dispersion relations. Furthermore, comparisons to other methods for dense deuterium results in excellent agreement with DFT-MD simulations, and reasonable agreement with a simple Yukawa screening model corrected to satisfy the conductivity sum rule.

Free-free opacity in dense plasmas with an average atom model

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

Shaffer, Nathaniel R.; Ferris, Natalie G.; Colgan, James Patrick

A model for the free-free opacity of dense plasmas is presented. The model uses a previously developed average atom model, together with the Kubo-Greenwood model for optical conductivity. This, in turn, is used to calculate the opacity with the Kramers-Kronig dispersion relations. Furthermore, comparisons to other methods for dense deuterium results in excellent agreement with DFT-MD simulations, and reasonable agreement with a simple Yukawa screening model corrected to satisfy the conductivity sum rule.

Multi-Model Ensemble Wake Vortex Prediction

NASA Technical Reports Server (NTRS)

Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

2015-01-01

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Averaging and Adding in Children's Worth Judgements

ERIC Educational Resources Information Center

Schlottmann, Anne; Harman, Rachel M.; Paine, Julie

2012-01-01

Under the normative Expected Value (EV) model, multiple outcomes are additive, but in everyday worth judgement intuitive averaging prevails. Young children also use averaging in EV judgements, leading to a disordinal, crossover violation of utility when children average the part worths of simple gambles involving independent events (Schlottmann,…

Kumaraswamy autoregressive moving average models for double bounded environmental data

NASA Astrophysics Data System (ADS)

Bayer, Fábio Mariano; Bayer, Débora Missio; Pumi, Guilherme

2017-12-01

In this paper we introduce the Kumaraswamy autoregressive moving average models (KARMA), which is a dynamic class of models for time series taking values in the double bounded interval (a,b) following the Kumaraswamy distribution. The Kumaraswamy family of distribution is widely applied in many areas, especially hydrology and related fields. Classical examples are time series representing rates and proportions observed over time. In the proposed KARMA model, the median is modeled by a dynamic structure containing autoregressive and moving average terms, time-varying regressors, unknown parameters and a link function. We introduce the new class of models and discuss conditional maximum likelihood estimation, hypothesis testing inference, diagnostic analysis and forecasting. In particular, we provide closed-form expressions for the conditional score vector and conditional Fisher information matrix. An application to environmental real data is presented and discussed.

Mean-field velocity difference model considering the average effect of multi-vehicle interaction

NASA Astrophysics Data System (ADS)

Guo, Yan; Xue, Yu; Shi, Yin; Wei, Fang-ping; Lü, Liang-zhong; He, Hong-di

2018-06-01

In this paper, a mean-field velocity difference model(MFVD) is proposed to describe the average effect of multi-vehicle interactions on the whole road. By stability analysis, the stability condition of traffic system is obtained. Comparison with stability of full velocity-difference (FVD) model and the completeness of MFVD model are discussed. The mKdV equation is derived from MFVD model through nonlinear analysis to reveal the traffic jams in the form of the kink-antikink density wave. Then the numerical simulation is performed and the results illustrate that the average effect of multi-vehicle interactions plays an important role in effectively suppressing traffic jam. The increase strength of the mean-field velocity difference in MFVD model can rapidly reduce traffic jam and enhance the stability of traffic system.

A Framework for Validating Traffic Simulation Models at the Vehicle Trajectory Level

DOT National Transportation Integrated Search

2017-03-01

Based on current practices, traffic simulation models are calibrated and validated using macroscopic measures such as 15-minute averages of traffic counts or average point-to-point travel times. For an emerging number of applications, including conne...

A modeling study of the impact of urban trees on ozone

Treesearch

David J. Nowak; Kevin L. Civerolo; S. Trivikrama Rao; Gopal Sistla; Christopher J. Luley; Daniel E. Crane

2000-01-01

Modeling the effects of increased urban tree cover on ozone concentrations (July 13-15, 1995) from Washington, DC, to central Massachusetts reveals that urban trees generally reduce ozone concentrations in cities, but tend to increase average ozone concentrations in the overall modeling domain. During the daytime, average ozone reductions in urban areas (1 ppb) were...

Evaluation of average daily gain predictions by the integrated farm system model for forage-finished beef steers

USDA-ARS?s Scientific Manuscript database

Representing the performance of cattle finished on an all forage diet in process-based whole farm system models has presented a challenge. To address this challenge, a study was done to evaluate average daily gain (ADG) predictions of the Integrated Farm System Model (IFSM) for steers consuming all-...

Parental and interpersonal relationships of transsexual and masculine and feminine homosexual men.

PubMed

Sípová, I; Brzek, A

1983-01-01

A group of transsexual and homosexual men was examined using the Leary Test as a psycho-sociogram, and findings were compared to those from a group of heterosexual men. It was found that the fathers of homosexuals and transsexuals were more hostile and less dominant than the fathers of the control group and hence less desirable identification models. The average mothers of transsexuals were close to the ideal person in our culture, e.g., dominant, strong and kindly, and thus an imposing identification model. Heterosexual men and transsexuals, in their behavior towards their wives, on the average identified with the models set by their fathers. Effeminate homosexuals in relations towards their male partners on the average identified with their mothers. Non-effeminate homosexuals modeled their behavior somewhere between both parents. Heterosexual men tended to choose wives modelled on their mothers and modelled their behavior towards their wives on their fathers' behavior. Non-effeminate homosexuals tended to choose their male partners according to the model set by their mothers and behaved toward them in a more dominant manner than any of the other groups studied (effeminate homosexuals, non-effeminate homosexuals and transsexuals). Effeminate homosexuals on average chose the most dominant male partners and modelled their behavior toward them on that of their mothers. The wives of transsexuals were rated as the most hostile. The self-esteem of all the groups studied suffered from lack of dominance. On the average, non-effeminate homosexuals were found to be closest to the heterosexual norms, transsexuals the furthest.

Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis

NASA Astrophysics Data System (ADS)

Xu, Feinan; Wang, Weizhen; Wang, Jiemin; Xu, Ziwei; Qi, Yuan; Wu, Yueru

2017-08-01

The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be extended to the water balance study of the whole Heihe River basin.

Forecasting Instability Indicators in the Horn of Africa

DTIC Science & Technology

2008-03-01

further than 2 (Makridakis, et al, 1983, 359). 2-32 Autoregressive Integrated Moving Average ( ARIMA ) Model . Similar to the ARMA model except for...stationary process. ARIMA models are described as ARIMA (p,d,q), where p is the order of the autoregressive process, d is the degree of the...differential process, and q is the order of the moving average process. The ARMA (1,1) model shown above is equivalent to an ARIMA (1,0,1) model . An ARIMA

Simulation of multistage turbine flows

NASA Technical Reports Server (NTRS)

Adamczyk, John J.; Mulac, Richard A.

1987-01-01

A flow model has been developed for analyzing multistage turbomachinery flows. This model, referred to as the average passage flow model, describes the time-averaged flow field with a typical passage of a blade row embedded within a multistage configuration. Computer resource requirements, supporting empirical modeling, formulation code development, and multitasking and storage are discussed. Illustrations from simulations of the space shuttle main engine (SSME) fuel turbine performed to date are given.

Creating "Intelligent" Climate Model Ensemble Averages Using a Process-Based Framework

NASA Astrophysics Data System (ADS)

Baker, N. C.; Taylor, P. C.

2014-12-01

The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is often used to add value to model projections: consensus projections have been shown to consistently outperform individual models. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, certain models reproduce climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables—e.g., outgoing longwave radiation and surface temperature. Metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument and surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing weighted and unweighted model ensembles. For example, one tested metric weights the ensemble by how well models reproduce the time-series probability distribution of the cloud forcing component of reflected shortwave radiation. The weighted ensemble for this metric indicates lower simulated precipitation (up to .7 mm/day) in tropical regions than the unweighted ensemble: since CMIP5 models have been shown to overproduce precipitation, this result could indicate that the metric is effective in identifying models which simulate more realistic precipitation. Ultimately, the goal of the framework is to identify performance metrics for advising better methods for ensemble averaging models and create better climate predictions.

Modeling level of urban taxi services using neural network

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

Xu, J.; Wong, S.C.; Tong, C.O.

1999-05-01

This paper is concerned with the modeling of the complex demand-supply relationship in urban taxi services. A neural network model is developed, based on a taxi service situation observed in the urban area of Hong Kong. The input consists of several exogenous variables including number of licensed taxis, incremental charge of taxi fare, average occupied taxi journey time, average disposable income, and population and customer price index; the output consists of a set of endogenous variables including daily taxi passenger demand, passenger waiting time, vacant taxi headway, average percentage of occupied taxis, taxi utilization, and average taxi waiting time. Comparisonsmore » of the estimation accuracy are made between the neural network model and the simultaneous equations model. The results show that the neural network-based macro taxi model can obtain much more accurate information of the taxi services than the simultaneous equations model does. Although the data set used for training the neural network is small, the results obtained thus far are very encouraging. The neural network model can be used as a policy tool by regulator to assist with the decisions concerning the restriction over the number of taxi licenses and the fixing of the taxi fare structure as well as a range of service quality control.« less

Application of scl - pbl method to increase quality learning of industrial statistics course in department of industrial engineering pancasila university

NASA Astrophysics Data System (ADS)

Darmawan, M.; Hidayah, N. Y.

2017-12-01

Currently, there has been a change of new paradigm in the learning model in college, ie from Teacher Centered Learning (TCL) model to Student Centered Learing (SCL). It is generally assumed that the SCL model is better than the TCL model. The Courses of 2nd Industrial Statistics in the Department Industrial Engineering Pancasila University is the subject that belongs to the Basic Engineering group. So far, the applied learning model refers more to the TCL model, and field facts show that the learning outcomes are less satisfactory. Of the three consecutive semesters, ie even semester 2013/2014, 2014/2015, and 2015/2016 obtained grade average is equal to 56.0; 61.1, and 60.5. In the even semester of 2016/2017, Classroom Action Research (CAR) is conducted for this course through the implementation of SCL model with Problem Based Learning (PBL) methods. The hypothesis proposed is that the SCL-PBL model will be able to improve the final grade of the course. The results shows that the average grade of the course can be increased to 73.27. This value was then tested using the ANOVA and the test results concluded that the average grade was significantly different from the average grade value in the previous three semesters.

Forecasting Dust Storms Using the CARMA-Dust Model and MM5 Weather Data

NASA Astrophysics Data System (ADS)

Barnum, B. H.; Winstead, N. S.; Wesely, J.; Hakola, A.; Colarco, P.; Toon, O. B.; Ginoux, P.; Brooks, G.; Hasselbarth, L. M.; Toth, B.; Sterner, R.

2002-12-01

An operational model for the forecast of dust storms in Northern Africa, the Middle East and Southwest Asia has been developed for the United States Air Force Weather Agency (AFWA). The dust forecast model uses the 5th generation Penn State Mesoscale Meteorology Model (MM5), and a modified version of the Colorado Aerosol and Radiation Model for Atmospheres (CARMA). AFWA conducted a 60 day evaluation of the dust model to look at the model's ability to forecast dust storms for short, medium and long range (72 hour) forecast periods. The study used satellite and ground observations of dust storms to verify the model's effectiveness. Each of the main mesoscale forecast theaters was broken down into smaller sub-regions for detailed analysis. The study found the forecast model was able to forecast dust storms in Saharan Africa and the Sahel region with an average Probability of Detection (POD)exceeding 68%, with a 16% False Alarm Rate (FAR). The Southwest Asian theater had average POD's of 61% with FAR's averaging 10%.

Spatial averaging of a dissipative particle dynamics model for active suspensions

NASA Astrophysics Data System (ADS)

Panchenko, Alexander; Hinz, Denis F.; Fried, Eliot

2018-03-01

Starting from a fine-scale dissipative particle dynamics (DPD) model of self-motile point particles, we derive meso-scale continuum equations by applying a spatial averaging version of the Irving-Kirkwood-Noll procedure. Since the method does not rely on kinetic theory, the derivation is valid for highly concentrated particle systems. Spatial averaging yields stochastic continuum equations similar to those of Toner and Tu. However, our theory also involves a constitutive equation for the average fluctuation force. According to this equation, both the strength and the probability distribution vary with time and position through the effective mass density. The statistics of the fluctuation force also depend on the fine scale dissipative force equation, the physical temperature, and two additional parameters which characterize fluctuation strengths. Although the self-propulsion force entering our DPD model contains no explicit mechanism for aligning the velocities of neighboring particles, our averaged coarse-scale equations include the commonly encountered cubically nonlinear (internal) body force density.

A new type of exact arbitrarily inhomogeneous cosmology: evolution of deceleration in the flat homogeneous-on-average case

NASA Astrophysics Data System (ADS)

Hellaby, Charles

2012-01-01

A new method for constructing exact inhomogeneous universes is presented, that allows variation in 3 dimensions. The resulting spacetime may be statistically uniform on average, or have random, non-repeating variation. The construction utilises the Darmois junction conditions to join many different component spacetime regions. In the initial simple example given, the component parts are spatially flat and uniform, but much more general combinations should be possible. Further inhomogeneity may be added via swiss cheese vacuoles and inhomogeneous metrics. This model is used to explore the proposal, that observers are located in bound, non-expanding regions, while the universe is actually in the process of becoming void dominated, and thus its average expansion rate is increasing. The model confirms qualitatively that the faster expanding components come to dominate the average, and that inhomogeneity results in average parameters which evolve differently from those of any one component, but more realistic modelling of the effect will need this construction to be generalised.

Upscaling the Navier-Stokes Equation for Turbulent Flows in Porous Media Using a Volume Averaging Method

NASA Astrophysics Data System (ADS)

Wood, Brian; He, Xiaoliang; Apte, Sourabh

2017-11-01

Turbulent flows through porous media are encountered in a number of natural and engineered systems. Many attempts to close the Navier-Stokes equation for such type of flow have been made, for example using RANS models and double averaging. On the other hand, Whitaker (1996) applied volume averaging theorem to close the macroscopic N-S equation for low Re flow. In this work, the volume averaging theory is extended into the turbulent flow regime to posit a relationship between the macroscale velocities and the spatial velocity statistics in terms of the spatial averaged velocity only. Rather than developing a Reynolds stress model, we propose a simple algebraic closure, consistent with generalized effective viscosity models (Pope 1975), to represent the spatial fluctuating velocity and pressure respectively. The coefficients (one 1st order, two 2nd order and one 3rd order tensor) of the linear functions depend on averaged velocity and gradient. With the data set from DNS, performed with inertial and turbulent flows (pore Re of 300, 500 and 1000) through a periodic face centered cubic (FCC) unit cell, all the unknown coefficients can be computed and the closure is complete. The macroscopic quantity calculated from the averaging is then compared with DNS data to verify the upscaling. NSF Project Numbers 1336983, 1133363.

Two-Component Modeling of the Solar IR CO Lines

NASA Astrophysics Data System (ADS)

Avrett, E. H.

One-dimensional hydrostatic models of quiet and active solar regions can be constructed that generally account for the observed intensities of lines and continua throughout the spectrum, except for the infrared CO lines. There is an apparent conflict between a) observations of the strongest infrared CO lines formed in LTE at low-chromospheric heights but at temperatures much cooler than the average chromospheric values, and b) observations of Ca II, UV, and microwave intensities that originate from the same chromospheric heights but at the much higher temperatures characteristic of the average chromosphere. A model M_CO has been constructed which gives a good fit to the full range of mean CO line profiles (averaged over the central area of the solar disk and over time) but this model conflicts with other observations of average quiet regions. A model L_CO which is approximately 100 K cooler than M_CO combined with a very bright network model F in the proportions 0.6L_CO+0.4F is found to be generally consistent with the CO, Ca II, UV, and microwave observations. Ayres, Testerman, and Brault found that models COOLC and FLUXT in the proportions 0.925 and 0.075 account for the CO and Ca II lines, but these combined models give an average UV intensity at 140 nm about 20 times larger than observed. The 0.6L_CO+0.4F result may give a better description of the cool and hot components that produce the space- and time-averaged spectra. Recent observations carried out by Uitenbroek, Noyes, and Rabin with high spatial and temporal resolution indicate that the faintest intensities in the strong CO lines measured at given locations usually become much brighter within 1 to 3 minutes. The cool regions thus seem to be mostly the low- temperature portions of oscillatory waves rather than cool structures that are stationary.

Two-component modeling of the solar IR CO lines

NASA Technical Reports Server (NTRS)

Avrett, Eugene H.

1995-01-01

One-dimensional hydrostatic models of quiet and active solar regions can be constructed that generally account for the observed intensities of lines and continue throughout the spectrum, except for the infrared CO lines. There is an apparent conflict between: (1) observations of the strongest infrared CO lines formed in LTE at low-chromospheric heights but at temperatures much cooler than the average chromospheric values; and (2) observations of Ca II, UV (ultraviolet), and microwave intensities that originate from the same chromospheric heights but at the much higher temperatures characteristic of the average chromosphere. A model M(sub CO) has been constructed which gives a good fit to the full range of mean CO line profiles (averaged over the central area of the solar disk and over time) but this model conflicts with other observations of average quiet regions. A model L(sub CO) which is approximately 100 K cooler than M(sub CO) combined with a very bright network model F in the proportions 0.6 L(sub CO) + 0.4 F is found to be generally consistent with the CO, Ca II, UV, and microwave observations. Ayres, Testerman, and Brault found that models COOLC and FLUXT in the proportions 0.925 and 0.075 account for the CO and Ca II lines, but these combined models give an average UV intensity at 140 nm about 20 times larger than observed. The 0.6 L(sub CO) + 0.4 F result may give a better description of the cool and hot components that produce the space- and time-averaged spectra. Recent observations carried out by Uitenbroek, Noyes, and Rabine with high spatial and temporal resolution indicate that the faintest intensities in the strong CO lines measured at given locations usually become much brighter within 1 to 3 minutes. The cool regions thus seem to be mostly the low-temperature portions of oscillatory waves rather than cool structures that are stationary.

Proof of Concept for the Trajectory-Level Validation Framework for Traffic Simulation Models

DOT National Transportation Integrated Search

2017-10-30

Based on current practices, traffic simulation models are calibrated and validated using macroscopic measures such as 15-minute averages of traffic counts or average point-to-point travel times. For an emerging number of applications, including conne...

40 CFR 600.512-86 - Model year report.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 1978 Passenger Automobiles and for 1979 and Later Model Year Automobiles (Light Trucks and Passenger Automobiles)-Procedures for Determining Manufacturer's Average Fuel Economy and Manufacturer's Average Carbon... submitted. (3) Separate reports shall be submitted for passenger automobiles and light trucks (as identified...

40 CFR 600.512-01 - Model year report.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 1978 Passenger Automobiles and for 1979 and Later Model Year Automobiles (Light Trucks and Passenger Automobiles)-Procedures for Determining Manufacturer's Average Fuel Economy and Manufacturer's Average Carbon... report must be submitted. (3) Separate reports shall be submitted for passenger automobiles and light...

40 CFR 600.512-08 - Model year report.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 1978 Passenger Automobiles and for 1979 and Later Model Year Automobiles (Light Trucks and Passenger Automobiles)-Procedures for Determining Manufacturer's Average Fuel Economy and Manufacturer's Average Carbon... report must be submitted. (3) Separate reports shall be submitted for passenger automobiles and light...

49 CFR 536.3 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... manufactured by a manufacturer in that compliance category in a particular model year have greater average fuel.... 32905) than that manufacturer's fuel economy standard for that compliance category and model year... year have lower average fuel economy (calculated in a manner that reflects the incentives for...

49 CFR 536.3 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... manufactured by a manufacturer in that compliance category in a particular model year have greater average fuel.... 32905) than that manufacturer's fuel economy standard for that compliance category and model year... year have lower average fuel economy (calculated in a manner that reflects the incentives for...

Spatial Interpretation of Tower, Chamber and Modelled Terrestrial Fluxes in a Tropical Forest Plantation

NASA Astrophysics Data System (ADS)

Whidden, E.; Roulet, N.

2003-04-01

Interpretation of a site average terrestrial flux may be complicated in the presence of inhomogeneities. Inhomogeneity may invalidate the basic assumptions of aerodynamic flux measurement. Chamber measurement may miss or misinterpret important temporal or spatial anomalies. Models may smooth over important nonlinearities depending on the scale of application. Although inhomogeneity is usually seen as a design problem, many sites have spatial variance that may have a large impact on net flux, and in many cases a large homogeneous surface is unrealistic. The sensitivity and validity of a site average flux are investigated in the presence of an inhomogeneous site. Directional differences are used to evaluate the validity of aerodynamic methods and the computation of a site average tower flux. Empirical and modelling methods are used to interpret the spatial controls on flux. An ecosystem model, Ecosys, is used to assess spatial length scales appropriate to the ecophysiologic controls. A diffusion model is used to compare tower, chamber, and model data, by spatially weighting contributions within the tower footprint. Diffusion model weighting is also used to improve tower flux estimates by producing footprint averaged ecological parameters (soil moisture, soil temperature, etc.). Although uncertainty remains in the validity of measurement methods and the accuracy of diffusion models, a detailed spatial interpretation is required at an inhomogeneous site. Flux estimation between methods improves with spatial interpretation, showing the importance to an estimation of a site average flux. Small-scale temporal and spatial anomalies may be relatively unimportant to overall flux, but accounting for medium-scale differences in ecophysiological controls is necessary. A combination of measurements and modelling can be used to define the appropriate time and length scales of significant non-linearity due to inhomogeneity.

MAX-DOAS tropospheric nitrogen dioxide column measurements compared with the Lotos-Euros air quality model

NASA Astrophysics Data System (ADS)

Vlemmix, T.; Eskes, H. J.; Piters, A. J. M.; Schaap, M.; Sauter, F. J.; Kelder, H.; Levelt, P. F.

2015-02-01

A 14-month data set of MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) tropospheric NO2 column observations in De Bilt, the Netherlands, has been compared with the regional air quality model Lotos-Euros. The model was run on a 7×7 km2 grid, the same resolution as the emission inventory used. A study was performed to assess the effect of clouds on the retrieval accuracy of the MAX-DOAS observations. Good agreement was found between modeled and measured tropospheric NO2 columns, with an average difference of less than 1% of the average tropospheric column (14.5 · 1015 molec cm-2). The comparisons show little cloud cover dependence after cloud corrections for which ceilometer data were used. Hourly differences between observations and model show a Gaussian behavior with a standard deviation (σ) of 5.5 · 1015 molec cm-2. For daily averages of tropospheric NO2 columns, a correlation of 0.72 was found for all observations, and 0.79 for cloud free conditions. The measured and modeled tropospheric NO2 columns have an almost identical distribution over the wind direction. A significant difference between model and measurements was found for the average weekly cycle, which shows a much stronger decrease during the weekend for the observations; for the diurnal cycle, the observed range is about twice as large as the modeled range. The results of the comparison demonstrate that averaged over a long time period, the tropospheric NO2 column observations are representative for a large spatial area despite the fact that they were obtained in an urban region. This makes the MAX-DOAS technique especially suitable for validation of satellite observations and air quality models in urban regions.

A computer model of long-term salinity in San Francisco Bay: Sensitivity to mixing and inflows

USGS Publications Warehouse

Uncles, R.J.; Peterson, D.H.

1995-01-01

A two-level model of the residual circulation and tidally-averaged salinity in San Francisco Bay has been developed in order to interpret long-term (days to decades) salinity variability in the Bay. Applications of the model to biogeochemical studies are also envisaged. The model has been used to simulate daily-averaged salinity in the upper and lower levels of a 51-segment discretization of the Bay over the 22-y period 1967–1988. Observed, monthly-averaged surface salinity data and monthly averages of the daily-simulated salinity are in reasonable agreement, both near the Golden Gate and in the upper reaches, close to the delta. Agreement is less satisfactory in the central reaches of North Bay, in the vicinity of Carquinez Strait. Comparison of daily-averaged data at Station 5 (Pittsburg, in the upper North Bay) with modeled data indicates close agreement with a correlation coefficient of 0.97 for the 4110 daily values. The model successfully simulates the marked seasonal variability in salinity as well as the effects of rapidly changing freshwater inflows. Salinity variability is driven primarily by freshwater inflow. The sensitivity of the modeled salinity to variations in the longitudinal mixing coefficients is investigated. The modeled salinity is relatively insensitive to the calibration factor for vertical mixing and relatively sensitive to the calibration factor for longitudinal mixing. The optimum value of the longitudinal calibration factor is 1.1, compared with the physically-based value of 1.0. Linear time-series analysis indicates that the observed and dynamically-modeled salinity-inflow responses are in good agreement in the lower reaches of the Bay.

Synchronized Trajectories in a Climate "Supermodel"

NASA Astrophysics Data System (ADS)

Duane, Gregory; Schevenhoven, Francine; Selten, Frank

2017-04-01

Differences in climate projections among state-of-the-art models can be resolved by connecting the models in run-time, either through inter-model nudging or by directly combining the tendencies for corresponding variables. Since it is clearly established that averaging model outputs typically results in improvement as compared to any individual model output, averaged re-initializations at typical analysis time intervals also seems appropriate. The resulting "supermodel" is more like a single model than it is like an ensemble, because the constituent models tend to synchronize even with limited inter-model coupling. Thus one can examine the properties of specific trajectories, rather than averaging the statistical properties of the separate models. We apply this strategy to a study of the index cycle in a supermodel constructed from several imperfect copies of the SPEEDO model (a global primitive-equation atmosphere-ocean-land climate model). As with blocking frequency, typical weather statistics of interest like probabilities of heat waves or extreme precipitation events, are improved as compared to the standard multi-model ensemble approach. In contrast to the standard approach, the supermodel approach provides detailed descriptions of typical actual events.

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

NASA Astrophysics Data System (ADS)

Braman, Kalen; Raman, Venkat

2011-11-01

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

EMC Global Climate And Weather Modeling Branch Personnel

Science.gov Websites

Comparison Statistics which includes: NCEP Raw and Bias-Corrected Ensemble Domain Averaged Bias NCEP Raw and Bias-Corrected Ensemble Domain Averaged Bias Reduction (Percents) CMC Raw and Bias-Corrected Control Forecast Domain Averaged Bias CMC Raw and Bias-Corrected Control Forecast Domain Averaged Bias Reduction

49 CFR 525.11 - Termination of exemption; amendment of alternative average fuel economy standard.

Code of Federal Regulations, 2013 CFR

2013-10-01

... average fuel economy standard. 525.11 Section 525.11 Transportation Other Regulations Relating to... EXEMPTIONS FROM AVERAGE FUEL ECONOMY STANDARDS § 525.11 Termination of exemption; amendment of alternative average fuel economy standard. (a) Any exemption granted under this part for an affected model year does...

49 CFR 525.11 - Termination of exemption; amendment of alternative average fuel economy standard.

Code of Federal Regulations, 2011 CFR

2011-10-01

... average fuel economy standard. 525.11 Section 525.11 Transportation Other Regulations Relating to... EXEMPTIONS FROM AVERAGE FUEL ECONOMY STANDARDS § 525.11 Termination of exemption; amendment of alternative average fuel economy standard. (a) Any exemption granted under this part for an affected model year does...

49 CFR 525.11 - Termination of exemption; amendment of alternative average fuel economy standard.

Code of Federal Regulations, 2014 CFR

2014-10-01

... average fuel economy standard. 525.11 Section 525.11 Transportation Other Regulations Relating to... EXEMPTIONS FROM AVERAGE FUEL ECONOMY STANDARDS § 525.11 Termination of exemption; amendment of alternative average fuel economy standard. (a) Any exemption granted under this part for an affected model year does...

49 CFR 525.11 - Termination of exemption; amendment of alternative average fuel economy standard.

Code of Federal Regulations, 2012 CFR

2012-10-01

... average fuel economy standard. 525.11 Section 525.11 Transportation Other Regulations Relating to... EXEMPTIONS FROM AVERAGE FUEL ECONOMY STANDARDS § 525.11 Termination of exemption; amendment of alternative average fuel economy standard. (a) Any exemption granted under this part for an affected model year does...

Prediction of dosage-based parameters from the puff dispersion of airborne materials in urban environments using the CFD-RANS methodology

NASA Astrophysics Data System (ADS)

Efthimiou, G. C.; Andronopoulos, S.; Bartzis, J. G.

2018-02-01

One of the key issues of recent research on the dispersion inside complex urban environments is the ability to predict dosage-based parameters from the puff release of an airborne material from a point source in the atmospheric boundary layer inside the built-up area. The present work addresses the question of whether the computational fluid dynamics (CFD)-Reynolds-averaged Navier-Stokes (RANS) methodology can be used to predict ensemble-average dosage-based parameters that are related with the puff dispersion. RANS simulations with the ADREA-HF code were, therefore, performed, where a single puff was released in each case. The present method is validated against the data sets from two wind-tunnel experiments. In each experiment, more than 200 puffs were released from which ensemble-averaged dosage-based parameters were calculated and compared to the model's predictions. The performance of the model was evaluated using scatter plots and three validation metrics: fractional bias, normalized mean square error, and factor of two. The model presented a better performance for the temporal parameters (i.e., ensemble-average times of puff arrival, peak, leaving, duration, ascent, and descent) than for the ensemble-average dosage and peak concentration. The majority of the obtained values of validation metrics were inside established acceptance limits. Based on the obtained model performance indices, the CFD-RANS methodology as implemented in the code ADREA-HF is able to predict the ensemble-average temporal quantities related to transient emissions of airborne material in urban areas within the range of the model performance acceptance criteria established in the literature. The CFD-RANS methodology as implemented in the code ADREA-HF is also able to predict the ensemble-average dosage, but the dosage results should be treated with some caution; as in one case, the observed ensemble-average dosage was under-estimated slightly more than the acceptance criteria. Ensemble-average peak concentration was systematically underpredicted by the model to a degree higher than the allowable by the acceptance criteria, in 1 of the 2 wind-tunnel experiments. The model performance depended on the positions of the examined sensors in relation to the emission source and the buildings configuration. The work presented in this paper was carried out (partly) within the scope of COST Action ES1006 "Evaluation, improvement, and guidance for the use of local-scale emergency prediction and response tools for airborne hazards in built environments".

A depth-averaged 2-D shallow water model for breaking and non-breaking long waves affected by rigid vegetation

USDA-ARS?s Scientific Manuscript database

This paper presents a depth-averaged two-dimensional shallow water model for simulating long waves in vegetated water bodies under breaking and non-breaking conditions. The effects of rigid vegetation are modelled in the form of drag and inertia forces as sink terms in the momentum equations. The dr...

Maximum stress estimation model for multi-span waler beams with deflections at the supports using average strains.

PubMed

Park, Sung Woo; Oh, Byung Kwan; Park, Hyo Seon

2015-03-30

The safety of a multi-span waler beam subjected simultaneously to a distributed load and deflections at its supports can be secured by limiting the maximum stress of the beam to a specific value to prevent the beam from reaching a limit state for failure or collapse. Despite the fact that the vast majority of accidents on construction sites occur at waler beams in retaining wall systems, no safety monitoring model that can consider deflections at the supports of the beam is available. In this paper, a maximum stress estimation model for a waler beam based on average strains measured from vibrating wire strain gauges (VWSGs), the most frequently used sensors in construction field, is presented. The model is derived by defining the relationship between the maximum stress and the average strains measured from VWSGs. In addition to the maximum stress, support reactions, deflections at supports, and the magnitudes of distributed loads for the beam structure can be identified by the estimation model using the average strains. Using simulation tests on two multi-span beams, the performance of the model is evaluated by estimating maximum stress, deflections at supports, support reactions, and the magnitudes of distributed loads.

Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data.

PubMed

Bateman, Brooke L; Pidgeon, Anna M; Radeloff, Volker C; Flather, Curtis H; VanDerWal, Jeremy; Akçakaya, H Resit; Thogmartin, Wayne E; Albright, Thomas P; Vavrus, Stephen J; Heglund, Patricia J

2016-12-01

Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species' potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs. © 2016 by the Ecological Society of America.

Modeling aboveground biomass of Tamarix ramosissima in the Arkansas River Basin of Southeastern Colorado, USA

USGS Publications Warehouse

Evangelista, P.; Kumar, S.; Stohlgren, T.J.; Crall, A.W.; Newman, G.J.

2007-01-01

Predictive models of aboveground biomass of nonnative Tamarix ramosissima of various sizes were developed using destructive sampling techniques on 50 individuals and four 100-m2 plots. Each sample was measured for average height (m) of stems and canopy area (m2) prior to cutting, drying, and weighing. Five competing regression models (P < 0.05) were developed to estimate aboveground biomass of T. ramosissima using average height and/or canopy area measurements and were evaluated using Akaike's Information Criterion corrected for small sample size (AICc). Our best model (AICc = -148.69, ??AICc = 0) successfully predicted T. ramosissima aboveground biomass (R2 = 0.97) and used average height and canopy area as predictors. Our 2nd-best model, using the same predictors, was also successful in predicting aboveground biomass (R2 = 0.97, AICc = -131.71, ??AICc = 16.98). A 3rd model demonstrated high correlation between only aboveground biomass and canopy area (R2 = 0.95), while 2 additional models found high correlations between aboveground biomass and average height measurements only (R2 = 0.90 and 0.70, respectively). These models illustrate how simple field measurements, such as height and canopy area, can be used in allometric relationships to accurately predict aboveground biomass of T. ramosissima. Although a correction factor may be necessary for predictions at larger scales, the models presented will prove useful for many research and management initiatives.

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

MacDonald, G.; Abarbanel, H.; Carruthers, P.

The questions of the sources of atmospheric carbon dioxide are addressed; distribution of the present carbon dioxide among the atmospheric, oceanic, and biospheric reservoirs is considered; and the impact on climate as reflected by the average ground temperature at each latitude of significant increases in atmospheric carbon dioxide is assessed. A new model for the mixing of carbon dioxide in the oceans is proposed. The proposed model explicitly takes into account the flow of colder and/or saltier water to great depths. We have constructed two models for the case of radiative equilibrium treating the atmosphere as gray and dividing themore » infrared emission region into nine bands. The gray atmosphere model predicts an increase of average surface temperature of 2.8/sup 0/K for a doubling of CO/sub 2/, a result about a degree less than the nine band model. An analytic model of the atmosphere was constructed (JASON Climate Model). Calculation with this zonally averaged model shows an increase of average surface temperature of 2.4/sup 0/ for a doubling of CO/sub 2/. The equatorial temperature increases by 0.7/sup 0/K while the poles warm up by 10 to 12/sup 0/K. The JASON climate model suffers from a number of fundamental weaknesses. The role of clouds in determining the albedo is not adequately taken into account nor are the asymmetries between the northern and southern hemisphere. (JGB)« less

Predictability of weather and climate in a coupled ocean-atmosphere model: A dynamical systems approach. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Nese, Jon M.

1989-01-01

A dynamical systems approach is used to quantify the instantaneous and time-averaged predictability of a low-order moist general circulation model. Specifically, the effects on predictability of incorporating an active ocean circulation, implementing annual solar forcing, and asynchronously coupling the ocean and atmosphere are evaluated. The predictability and structure of the model attractors is compared using the Lyapunov exponents, the local divergence rates, and the correlation, fractal, and Lyapunov dimensions. The Lyapunov exponents measure the average rate of growth of small perturbations on an attractor, while the local divergence rates quantify phase-spatial variations of predictability. These local rates are exploited to efficiently identify and distinguish subtle differences in predictability among attractors. In addition, the predictability of monthly averaged and yearly averaged states is investigated by using attractor reconstruction techniques.

Statistical Models for Averaging of the Pump–Probe Traces: Example of Denoising in Terahertz Time-Domain Spectroscopy

NASA Astrophysics Data System (ADS)

Skorobogatiy, Maksim; Sadasivan, Jayesh; Guerboukha, Hichem

2018-05-01

In this paper, we first discuss the main types of noise in a typical pump-probe system, and then focus specifically on terahertz time domain spectroscopy (THz-TDS) setups. We then introduce four statistical models for the noisy pulses obtained in such systems, and detail rigorous mathematical algorithms to de-noise such traces, find the proper averages and characterise various types of experimental noise. Finally, we perform a comparative analysis of the performance, advantages and limitations of the algorithms by testing them on the experimental data collected using a particular THz-TDS system available in our laboratories. We conclude that using advanced statistical models for trace averaging results in the fitting errors that are significantly smaller than those obtained when only a simple statistical average is used.

40 CFR 600.512-12 - Model year report.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 1978 Passenger Automobiles and for 1979 and Later Model Year Automobiles (Light Trucks and Passenger Automobiles)-Procedures for Determining Manufacturer's Average Fuel Economy and Manufacturer's Average Carbon... reports shall be submitted for passenger automobiles and light trucks (as identified in § 600.510). (c...

40 CFR 600.513-08 - Gas Guzzler Tax.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 1978 Passenger Automobiles and for 1979 and Later Model Year Automobiles (Light Trucks and Passenger Automobiles)-Procedures for Determining Manufacturer's Average Fuel Economy and Manufacturer's Average Carbon... automobiles sold after December 27, 1991, regardless of the model year of those vehicles. For alcohol dual...

40 CFR 600.513-91 - Gas Guzzler Tax.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 1978 Passenger Automobiles and for 1979 and Later Model Year Automobiles (Light Trucks and Passenger Automobiles)-Procedures for Determining Manufacturer's Average Fuel Economy and Manufacturer's Average Carbon... automobiles sold after December 27, 1991, regardless of the model year of those vehicles. For alcohol dual...

Sources and Trends of Nitrogen Loading to New England Estuaries

EPA Science Inventory

A database of nitrogen (N) loading components to estuaries of the conterminous United States has been developed through application of regional SPARROW models. The original SPARROW models predict average detrended loads by source based on average flow conditions and 2002 source t...

Validation of a mixture-averaged thermal diffusion model for premixed lean hydrogen flames

NASA Astrophysics Data System (ADS)

Schlup, Jason; Blanquart, Guillaume

2018-03-01

The mixture-averaged thermal diffusion model originally proposed by Chapman and Cowling is validated using multiple flame configurations. Simulations using detailed hydrogen chemistry are done on one-, two-, and three-dimensional flames. The analysis spans flat and stretched, steady and unsteady, and laminar and turbulent flames. Quantitative and qualitative results using the thermal diffusion model compare very well with the more complex multicomponent diffusion model. Comparisons are made using flame speeds, surface areas, species profiles, and chemical source terms. Once validated, this model is applied to three-dimensional laminar and turbulent flames. For these cases, thermal diffusion causes an increase in the propagation speed of the flames as well as increased product chemical source terms in regions of high positive curvature. The results illustrate the necessity for including thermal diffusion, and the accuracy and computational efficiency of the mixture-averaged thermal diffusion model.

Learning Instance-Specific Predictive Models

PubMed Central

Visweswaran, Shyam; Cooper, Gregory F.

2013-01-01

This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algorithm learns Markov blanket models, carries out Bayesian model averaging over a set of models to predict a target variable of the instance at hand, and employs an instance-specific heuristic to locate a set of suitable models to average over. We call this method the instance-specific Markov blanket (ISMB) algorithm. The ISMB algorithm was evaluated on 21 UCI data sets using five different performance measures and its performance was compared to that of several commonly used predictive algorithms, including nave Bayes, C4.5 decision tree, logistic regression, neural networks, k-Nearest Neighbor, Lazy Bayesian Rules, and AdaBoost. Over all the data sets, the ISMB algorithm performed better on average on all performance measures against all the comparison algorithms. PMID:25045325

A FEniCS-based programming framework for modeling turbulent flow by the Reynolds-averaged Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Mortensen, Mikael; Langtangen, Hans Petter; Wells, Garth N.

2011-09-01

Finding an appropriate turbulence model for a given flow case usually calls for extensive experimentation with both models and numerical solution methods. This work presents the design and implementation of a flexible, programmable software framework for assisting with numerical experiments in computational turbulence. The framework targets Reynolds-averaged Navier-Stokes models, discretized by finite element methods. The novel implementation makes use of Python and the FEniCS package, the combination of which leads to compact and reusable code, where model- and solver-specific code resemble closely the mathematical formulation of equations and algorithms. The presented ideas and programming techniques are also applicable to other fields that involve systems of nonlinear partial differential equations. We demonstrate the framework in two applications and investigate the impact of various linearizations on the convergence properties of nonlinear solvers for a Reynolds-averaged Navier-Stokes model.

Dynamics of a prey-predator system under Poisson white noise excitation

NASA Astrophysics Data System (ADS)

Pan, Shan-Shan; Zhu, Wei-Qiu

2014-10-01

The classical Lotka-Volterra (LV) model is a well-known mathematical model for prey-predator ecosystems. In the present paper, the pulse-type version of stochastic LV model, in which the effect of a random natural environment has been modeled as Poisson white noise, is investigated by using the stochastic averaging method. The averaged generalized Itô stochastic differential equation and Fokker-Planck-Kolmogorov (FPK) equation are derived for prey-predator ecosystem driven by Poisson white noise. Approximate stationary solution for the averaged generalized FPK equation is obtained by using the perturbation method. The effect of prey self-competition parameter ɛ2 s on ecosystem behavior is evaluated. The analytical result is confirmed by corresponding Monte Carlo (MC) simulation.

Distributional behavior of diffusion coefficients obtained by single trajectories in annealed transit time model

NASA Astrophysics Data System (ADS)

Akimoto, Takuma; Yamamoto, Eiji

2016-12-01

Local diffusion coefficients in disordered systems such as spin glass systems and living cells are highly heterogeneous and may change over time. Such a time-dependent and spatially heterogeneous environment results in irreproducibility of single-particle-tracking measurements. Irreproducibility of time-averaged observables has been theoretically studied in the context of weak ergodicity breaking in stochastic processes. Here, we provide rigorous descriptions of equilibrium and non-equilibrium diffusion processes for the annealed transit time model, which is a heterogeneous diffusion model in living cells. We give analytical solutions for the mean square displacement (MSD) and the relative standard deviation of the time-averaged MSD for equilibrium and non-equilibrium situations. We find that the time-averaged MSD grows linearly with time and that the time-averaged diffusion coefficients are intrinsically random (irreproducible) even in the long-time measurements in non-equilibrium situations. Furthermore, the distribution of the time-averaged diffusion coefficients converges to a universal distribution in the sense that it does not depend on initial conditions. Our findings pave the way for a theoretical understanding of distributional behavior of the time-averaged diffusion coefficients in disordered systems.

Average male and female virtual dummy model (BioRID and EvaRID) simulations with two seat concepts in the Euro NCAP low severity rear impact test configuration.

PubMed

Linder, Astrid; Holmqvist, Kristian; Svensson, Mats Y

2018-05-01

Soft tissue neck injuries, also referred to as whiplash injuries, which can lead to long term suffering accounts for more than 60% of the cost of all injuries leading to permanent medical impairment for the insurance companies, with respect to injuries sustained in vehicle crashes. These injuries are sustained in all impact directions, however they are most common in rear impacts. Injury statistics have since the mid-1960s consistently shown that females are subject to a higher risk of sustaining this type of injury than males, on average twice the risk of injury. Furthermore, some recently developed anti-whiplash systems have revealed they provide less protection for females than males. The protection of both males and females should be addresses equally when designing and evaluating vehicle safety systems to ensure maximum safety for everyone. This is currently not the case. The norm for crash test dummies representing humans in crash test laboratories is an average male. The female part of the population is not represented in tests performed by consumer information organisations such as NCAP or in regulatory tests due to the absence of a physical dummy representing an average female. Recently, the world first virtual model of an average female crash test dummy was developed. In this study, simulations were run with both this model and an average male dummy model, seated in a simplified model of a vehicle seat. The results of the simulations were compared to earlier published results from simulations run in the same test set-up with a vehicle concepts seat. The three crash pulse severities of the Euro NCAP low severity rear impact test were applied. The motion of the neck, head and upper torso were analysed in addition to the accelerations and the Neck Injury Criterion (NIC). Furthermore, the response of the virtual models was compared to the response of volunteers as well as the average male model, to that of the response of a physical dummy model. Simulations with the virtual male and female dummy models revealed differences in dynamic response related to the crash severity, as well as between the two dummies in the two different seat models. For the comparison of the response of the virtual models to the response of the volunteers and the physical dummy model, the peak angular motion of the first thoracic vertebra as found in the volunteer tests and mimicked by the physical dummy were not of the same magnitude in the virtual models. The results of the study highlight the need for an extended test matrix that includes an average female dummy model to evaluate the level of occupant protection different seats provide in vehicle crashes. This would provide developers with an additional tool to ensure that both male and female occupants receive satisfactory protection and promote seat concepts that provide the best possible protection for the whole adult population. This study shows that using the mathematical models available today can provide insights suitable for future testing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hybrid Reynolds-Averaged/Large-Eddy Simulations of a Co-Axial Supersonic Free-Jet Experiment

NASA Technical Reports Server (NTRS)

Baurle, R. A.; Edwards, J. R.

2009-01-01

Reynolds-averaged and hybrid Reynolds-averaged/large-eddy simulations have been applied to a supersonic coaxial jet flow experiment. The experiment utilized either helium or argon as the inner jet nozzle fluid, and the outer jet nozzle fluid consisted of laboratory air. The inner and outer nozzles were designed and operated to produce nearly pressure-matched Mach 1.8 flow conditions at the jet exit. The purpose of the computational effort was to assess the state-of-the-art for each modeling approach, and to use the hybrid Reynolds-averaged/large-eddy simulations to gather insight into the deficiencies of the Reynolds-averaged closure models. The Reynolds-averaged simulations displayed a strong sensitivity to choice of turbulent Schmidt number. The baseline value chosen for this parameter resulted in an over-prediction of the mixing layer spreading rate for the helium case, but the opposite trend was noted when argon was used as the injectant. A larger turbulent Schmidt number greatly improved the comparison of the results with measurements for the helium simulations, but variations in the Schmidt number did not improve the argon comparisons. The hybrid simulation results showed the same trends as the baseline Reynolds-averaged predictions. The primary reason conjectured for the discrepancy between the hybrid simulation results and the measurements centered around issues related to the transition from a Reynolds-averaged state to one with resolved turbulent content. Improvements to the inflow conditions are suggested as a remedy to this dilemma. Comparisons between resolved second-order turbulence statistics and their modeled Reynolds-averaged counterparts were also performed.

Climate, soil water storage, and the average annual water balance

USGS Publications Warehouse

Milly, P.C.D.

1994-01-01

This paper describes the development and testing of the hypothesis that the long-term water balance is determined only by the local interaction of fluctuating water supply (precipitation) and demand (potential evapotranspiration), mediated by water storage in the soil. Adoption of this hypothesis, together with idealized representations of relevant input variabilities in time and space, yields a simple model of the water balance of a finite area having a uniform climate. The partitioning of average annual precipitation into evapotranspiration and runoff depends on seven dimensionless numbers: the ratio of average annual potential evapotranspiration to average annual precipitation (index of dryness); the ratio of the spatial average plant-available water-holding capacity of the soil to the annual average precipitation amount; the mean number of precipitation events per year; the shape parameter of the gamma distribution describing spatial variability of storage capacity; and simple measures of the seasonality of mean precipitation intensity, storm arrival rate, and potential evapotranspiration. The hypothesis is tested in an application of the model to the United States east of the Rocky Mountains, with no calibration. Study area averages of runoff and evapotranspiration, based on observations, are 263 mm and 728 mm, respectively; the model yields corresponding estimates of 250 mm and 741 mm, respectively, and explains 88% of the geographical variance of observed runoff within the study region. The differences between modeled and observed runoff can be explained by uncertainties in the model inputs and in the observed runoff. In the humid (index of dryness <1) parts of the study area, the dominant factor producing runoff is the excess of annual precipitation over annual potential evapotranspiration, but runoff caused by variability of supply and demand over time is also significant; in the arid (index of dryness >1) parts, all of the runoff is caused by variability of forcing over time. Contributions to model runoff attributable to small-scale spatial variability of storage capacity are insignificant throughout the study area. The consistency of the model with observational data is supportive of the supply-demand-storage hypothesis, which neglects infiltration excess runoff and other finite-permeability effects on the soil water balance.

[The impact of exposure to images of ideally thin models on body dissatisfaction in young French and Italian women].

PubMed

Rodgers, R; Chabrol, H

2009-06-01

The thin-ideal of feminine beauty has a strong impact on body image and plays a central part in eating disorders. This ideal is widely promoted by the media images that flood western societies. Although the harmful effects of exposure to thin-ideal media images have been repeatedly demonstrated experimentally in English-speaking western countries, no such studies exist in southern Europe. There is evidence to suggest that the use of average-size models could reduce these negative effects. This study investigates body image amongst French and Italian students following exposure to media images of thin or average-size models, with a neutral or supportive slogan. The data were gathered in three locations: the psychology departments of the Universities of Padua, Italy, and Toulouse, France, and lastly high schools in the Toulouse area. A total of 299 girls took part in the study; their average age was 19.9 years old (S.D.=2.54) In order to investigate the effects of media images, we created three fake advertisements, allegedly promoting body-cream. The first advertisement displayed an ideally-thin model accompanied by a neutral slogan. In the second, the model was average-size with the same neutral slogan. The last advertisement also contained the average-size model, but with a supportive slogan designed to convey acceptance of deviations from the social norms of thinness. The participants first graded themselves on a VAS of body dissatisfaction (0 to 10). On the basis of this score, we created a first group containing girls reporting body dissatisfaction (VAS>or=5), the second with those reporting no body dissatisfaction (VAS<5). Participants were then randomly exposed to one of the three advertisements, after which they filled in the body dissatisfaction sub-scale of the Eating Disorders Inventory (EDI-2). The results showed that girls with initial body dissatisfaction reported higher body dissatisfaction after being exposed to images of ideally thin models than images of average-size models (F(1.32)=4.64, p=0.039). However, there was no significant difference between body dissatisfaction scores reported after exposure to images of average-size models accompanied by neutral or supportive slogans (F(1.39)=0.093, p=0.76). This study illustrates the negative effects of exposure to thin-ideal media images among students with body dissatisfaction. The use of average-size models in the media and advertising might help reduce these effects. No improvement was obtained via the use of a supportive slogan. These results highlight the importance of media literacy campaigns in the prevention of eating disorders.

Scattering in infrared radiative transfer: A comparison between the spectrally averaging model JURASSIC and the line-by-line model KOPRA

NASA Astrophysics Data System (ADS)

Griessbach, Sabine; Hoffmann, Lars; Höpfner, Michael; Riese, Martin; Spang, Reinhold

2013-09-01

The viability of a spectrally averaging model to perform radiative transfer calculations in the infrared including scattering by atmospheric particles is examined for the application of infrared limb remote sensing measurements. Here we focus on the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard the European Space Agency's Envisat. Various spectra for clear air and cloudy conditions were simulated with a spectrally averaging radiative transfer model and a line-by-line radiative transfer model for three atmospheric window regions (825-830, 946-951, 1224-1228 cm-1) and compared to each other. The results are rated in terms of the MIPAS noise equivalent spectral radiance (NESR). The clear air simulations generally agree within one NESR. The cloud simulations neglecting the scattering source term agree within two NESR. The differences between the cloud simulations including the scattering source term are generally below three and always below four NESR. We conclude that the spectrally averaging approach is well suited for fast and accurate infrared radiative transfer simulations including scattering by clouds. We found that the main source for the differences between the cloud simulations of both models is the cloud edge sampling. Furthermore we reasoned that this model comparison for clouds is also valid for atmospheric aerosol in general.

Reproducing the Ensemble Average Polar Solvation Energy of a Protein from a Single Structure: Gaussian-Based Smooth Dielectric Function for Macromolecular Modeling.

PubMed

Chakravorty, Arghya; Jia, Zhe; Li, Lin; Zhao, Shan; Alexov, Emil

2018-02-13

Typically, the ensemble average polar component of solvation energy (ΔG polar solv ) of a macromolecule is computed using molecular dynamics (MD) or Monte Carlo (MC) simulations to generate conformational ensemble and then single/rigid conformation solvation energy calculation is performed on each snapshot. The primary objective of this work is to demonstrate that Poisson-Boltzmann (PB)-based approach using a Gaussian-based smooth dielectric function for macromolecular modeling previously developed by us (Li et al. J. Chem. Theory Comput. 2013, 9 (4), 2126-2136) can reproduce that ensemble average (ΔG polar solv ) of a protein from a single structure. We show that the Gaussian-based dielectric model reproduces the ensemble average ΔG polar solv (⟨ΔG polar solv ⟩) from an energy-minimized structure of a protein regardless of the minimization environment (structure minimized in vacuo, implicit or explicit waters, or crystal structure); the best case, however, is when it is paired with an in vacuo-minimized structure. In other minimization environments (implicit or explicit waters or crystal structure), the traditional two-dielectric model can still be selected with which the model produces correct solvation energies. Our observations from this work reflect how the ability to appropriately mimic the motion of residues, especially the salt bridge residues, influences a dielectric model's ability to reproduce the ensemble average value of polar solvation free energy from a single in vacuo-minimized structure.

A kinetic model for estimating net photosynthetic rates of cos lettuce leaves under pulsed light.

PubMed

Jishi, Tomohiro; Matsuda, Ryo; Fujiwara, Kazuhiro

2015-04-01

Time-averaged net photosynthetic rate (P n) under pulsed light (PL) is known to be affected by the PL frequency and duty ratio, even though the time-averaged photosynthetic photon flux density (PPFD) is unchanged. This phenomenon can be explained by considering that photosynthetic intermediates (PIs) are pooled during light periods and then consumed by partial photosynthetic reactions during dark periods. In this study, we developed a kinetic model to estimate P n of cos lettuce (Lactuca sativa L. var. longifolia) leaves under PL based on the dynamics of the amount of pooled PIs. The model inputs are average PPFD, duty ratio, and frequency; the output is P n. The rates of both PI accumulation and consumption at a given moment are assumed to be dependent on the amount of pooled PIs at that point. Required model parameters and three explanatory variables (average PPFD, frequency, and duty ratio) were determined for the simulation using P n values under PL based on several combinations of the three variables. The model simulation for various PL levels with a wide range of time-averaged PPFDs, frequencies, and duty ratios further demonstrated that P n under PL with high frequencies and duty ratios was comparable to, but did not exceed, P n under continuous light, and also showed that P n under PL decreased as either frequency or duty ratio was decreased. The developed model can be used to estimate P n under various light environments where PPFD changes cyclically.

Instantaneous-to-daily GPP upscaling schemes based on a coupled photosynthesis-stomatal conductance model: correcting the overestimation of GPP by directly using daily average meteorological inputs.

PubMed

Wang, Fumin; Gonsamo, Alemu; Chen, Jing M; Black, T Andrew; Zhou, Bin

2014-11-01

Daily canopy photosynthesis is usually temporally upscaled from instantaneous (i.e., seconds) photosynthesis rate. The nonlinear response of photosynthesis to meteorological variables makes the temporal scaling a significant challenge. In this study, two temporal upscaling schemes of daily photosynthesis, the integrated daily model (IDM) and the segmented daily model (SDM), are presented by considering the diurnal variations of meteorological variables based on a coupled photosynthesis-stomatal conductance model. The two models, as well as a simple average daily model (SADM) with daily average meteorological inputs, were validated using the tower-derived gross primary production (GPP) to assess their abilities in simulating daily photosynthesis. The results showed IDM closely followed the seasonal trend of the tower-derived GPP with an average RMSE of 1.63 g C m(-2) day(-1), and an average Nash-Sutcliffe model efficiency coefficient (E) of 0.87. SDM performed similarly to IDM in GPP simulation but decreased the computation time by >66%. SADM overestimated daily GPP by about 15% during the growing season compared to IDM. Both IDM and SDM greatly decreased the overestimation by SADM, and improved the simulation of daily GPP by reducing the RMSE by 34 and 30%, respectively. The results indicated that IDM and SDM are useful temporal upscaling approaches, and both are superior to SADM in daily GPP simulation because they take into account the diurnally varying responses of photosynthesis to meteorological variables. SDM is computationally more efficient, and therefore more suitable for long-term and large-scale GPP simulations.

Influence of Averaging Preprocessing on Image Analysis with a Markov Random Field Model

NASA Astrophysics Data System (ADS)

Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato

2018-02-01

This paper describes our investigations into the influence of averaging preprocessing on the performance of image analysis. Averaging preprocessing involves a trade-off: image averaging is often undertaken to reduce noise while the number of image data available for image analysis is decreased. We formulated a process of generating image data by using a Markov random field (MRF) model to achieve image analysis tasks such as image restoration and hyper-parameter estimation by a Bayesian approach. According to the notions of Bayesian inference, posterior distributions were analyzed to evaluate the influence of averaging. There are three main results. First, we found that the performance of image restoration with a predetermined value for hyper-parameters is invariant regardless of whether averaging is conducted. We then found that the performance of hyper-parameter estimation deteriorates due to averaging. Our analysis of the negative logarithm of the posterior probability, which is called the free energy based on an analogy with statistical mechanics, indicated that the confidence of hyper-parameter estimation remains higher without averaging. Finally, we found that when the hyper-parameters are estimated from the data, the performance of image restoration worsens as averaging is undertaken. We conclude that averaging adversely influences the performance of image analysis through hyper-parameter estimation.

Equity venture capital platform model based on complex network

NASA Astrophysics Data System (ADS)

Guo, Dongwei; Zhang, Lanshu; Liu, Miao

2018-05-01

This paper uses the small-world network and the random-network to simulate the relationship among the investors, construct the network model of the equity venture capital platform to explore the impact of the fraud rate and the bankruptcy rate on the robustness of the network model while observing the impact of the average path length and the average agglomeration coefficient of the investor relationship network on the income of the network model. The study found that the fraud rate and bankruptcy rate exceeded a certain threshold will lead to network collapse; The bankruptcy rate has a great influence on the income of the platform; The risk premium exists, and the average return is better under a certain range of bankruptcy risk; The structure of the investor relationship network has no effect on the income of the investment model.

Translating landfill methane generation parameters among first-order decay models.

PubMed

Krause, Max J; Chickering, Giles W; Townsend, Timothy G

2016-11-01

Landfill gas (LFG) generation is predicted by a first-order decay (FOD) equation that incorporates two parameters: a methane generation potential (L 0 ) and a methane generation rate (k). Because non-hazardous waste landfills may accept many types of waste streams, multiphase models have been developed in an attempt to more accurately predict methane generation from heterogeneous waste streams. The ability of a single-phase FOD model to predict methane generation using weighted-average methane generation parameters and tonnages translated from multiphase models was assessed in two exercises. In the first exercise, waste composition from four Danish landfills represented by low-biodegradable waste streams was modeled in the Afvalzorg Multiphase Model and methane generation was compared to the single-phase Intergovernmental Panel on Climate Change (IPCC) Waste Model and LandGEM. In the second exercise, waste composition represented by IPCC waste components was modeled in the multiphase IPCC and compared to single-phase LandGEM and Australia's Solid Waste Calculator (SWC). In both cases, weight-averaging of methane generation parameters from waste composition data in single-phase models was effective in predicting cumulative methane generation from -7% to +6% of the multiphase models. The results underscore the understanding that multiphase models will not necessarily improve LFG generation prediction because the uncertainty of the method rests largely within the input parameters. A unique method of calculating the methane generation rate constant by mass of anaerobically degradable carbon was presented (k c ) and compared to existing methods, providing a better fit in 3 of 8 scenarios. Generally, single phase models with weighted-average inputs can accurately predict methane generation from multiple waste streams with varied characteristics; weighted averages should therefore be used instead of regional default values when comparing models. Translating multiphase first-order decay model input parameters by weighted average shows that single-phase models can predict cumulative methane generation within the level of uncertainty of many of the input parameters as defined by the Intergovernmental Panel on Climate Change (IPCC), which indicates that decreasing the uncertainty of the input parameters will make the model more accurate rather than adding multiple phases or input parameters.

49 CFR 537.4 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., DEPARTMENT OF TRANSPORTATION AUTOMOTIVE FUEL ECONOMY REPORTS § 537.4 Definitions. (a) Statutory terms. (1) The terms average fuel economy standard, fuel, manufacture, and model year are used as defined in... accordance with part 529 of this chapter. (3) The terms average fuel economy, fuel economy, and model type...

Detectability of planetary characteristics in disk-averaged spectra. I: The Earth model.

PubMed

Tinetti, Giovanna; Meadows, Victoria S; Crisp, David; Fong, William; Fishbein, Evan; Turnbull, Margaret; Bibring, Jean-Pierre

2006-02-01

Over the next 2 decades, NASA and ESA are planning a series of space-based observatories to detect and characterize extrasolar planets. This first generation of observatories will not be able to spatially resolve the terrestrial planets detected. Instead, these planets will be characterized by disk-averaged spectroscopy. To assess the detectability of planetary characteristics in disk-averaged spectra, we have developed a spatially and spectrally resolved model of the Earth. This model uses atmospheric and surface properties from existing observations and modeling studies as input, and generates spatially resolved high-resolution synthetic spectra using the Spectral Mapping Atmospheric Radiative Transfer model. Synthetic spectra were generated for a variety of conditions, including cloud coverage, illumination fraction, and viewing angle geometry, over a wavelength range extending from the ultraviolet to the farinfrared. Here we describe the model and validate it against disk-averaged visible to infrared observations of the Earth taken by the Mars Global Surveyor Thermal Emission Spectrometer, the ESA Mars Express Omega instrument, and ground-based observations of earthshine reflected from the unilluminated portion of the Moon. The comparison between the data and model indicates that several atmospheric species can be identified in disk-averaged Earth spectra, and potentially detected depending on the wavelength range and resolving power of the instrument. At visible wavelengths (0.4-0.9 microm) O3, H2O, O2, and oxygen dimer [(O2)2] are clearly apparent. In the mid-infrared (5-20 microm) CO2, O3, and H2O are present. CH4, N2O, CO2, O3, and H2O are visible in the near-infrared (1-5 microm). A comprehensive three-dimensional model of the Earth is needed to produce a good fit with the observations.

Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

PubMed

Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

2018-01-01

When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Financial modelling of femtosecond laser-assisted cataract surgery within the National Health Service using a 'hub and spoke' model for the delivery of high-volume cataract surgery.

PubMed

Roberts, H W; Ni, M Z; O'Brart, D P S

2017-03-16

To develop financial models which offset additional costs associated with femtosecond laser (FL)-assisted cataract surgery (FLACS) against improvements in productivity and to determine important factors relating to its implementation into the National Health Service (NHS). FL platforms are expensive, in initial purchase and running costs. The additional costs associated with FL technology might be offset by an increase in surgical efficiency. Using a 'hub and spoke' model to provide high-volume cataract surgery, we designed a financial model, comparing FLACS against conventional phacoemulsification surgery (CPS). The model was populated with averaged financial data from 4 NHS foundation trusts and 4 commercial organisations manufacturing FL platforms. We tested our model with sensitivity and threshold analyses to allow for variations or uncertainties. The averaged weekly workload for cataract surgery using our hub and spoke model required either 8 or 5.4 theatre sessions with CPS or FLACS, respectively. Despite reduced theatre utilisation, CPS (average £433/case) was still found to be 8.7% cheaper than FLACS (average £502/case). The greatest associated cost of FLACS was the patient interface (PI) (average £135/case). Sensitivity analyses demonstrated that FLACS could be less expensive than CPS, but only if increased efficiency, in terms of cataract procedures per theatre list, increased by over 100%, or if the cost of the PI was reduced by almost 70%. The financial viability of FLACS within the NHS is currently precluded by the cost of the PI and the lack of knowledge regarding any gains in operational efficiency. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Geohydrology of the French Creek basin and simulated effects of droughtand ground-water withdrawals, Chester County, Pennsylvania

USGS Publications Warehouse

Sloto, Ronald A.

2004-01-01

This report describes the results of a study by the U.S. Geological Survey, in cooperation with the Delaware River Basin Commission, to develop a regional ground-water-flow model of the French Creek Basin in Chester County, Pa. The model was used to assist water-resource managers by illustrating the interconnection between ground-water and surface-water systems. The 70.7-mi2 (square mile) French Creek Basin is in the Piedmont Physiographic Province and is underlain by crystalline and sedimentary fractured-rock aquifers. Annual water budgets were calculated for 1969-2001 for the French Creek Basin upstream of streamflow measurement station French Creek near Phoenixville (01472157). Average annual precipitation was 46.28 in. (inches), average annual streamflow was 20.29 in., average annual base flow determined by hydrograph separation was 12.42 in., and estimated average annual ET (evapotranspiration) was 26.10 in. Estimated average annual recharge was 14.32 in. and is equal to 31 percent of the average annual precipitation. Base flow made up an average of 61 percent of streamflow. Ground-water flow in the French Creek Basin was simulated using the finite-difference MODFLOW-96 computer program. The model structure is based on a simplified two-dimensional conceptualization of the ground-water-flow system. The modeled area was extended outside the French Creek Basin to natural hydrologic boundaries; the modeled area includes 40 mi2 of adjacent areas outside the basin. The hydraulic conductivity for each geologic unit was calculated from reported specific-capacity data determined from aquifer tests and was adjusted during model calibration. The model was calibrated for aboveaverage conditions by simulating base-flow and water-level measurements made on May 1, 2001, using a recharge rate of 20 in/yr (inches per year). The model was calibrated for below-average conditions by simulating base-flow and water-level measurements made on September 11 and 17, 2001, using a recharge rate of 6.2 in/yr. Average conditions were simulated by adjusting the recharge rate until simulated streamflow at streamflow-measurement station 01472157 matched the long-term (1968-2001) average base flow of 54.1 cubic feet per second. The recharge rate used for average conditions was 15.7 in/yr. The effect of drought in the French Creek Basin was simulated using a drought year recharge rate of 8 in/yr for 3 months. After 3 months of drought, the simulated streamflow of French Creek at streamflow-measurement station 01472157 decreased 34 percent. The simulations show that after 6 months of average recharge (15.7 in/yr) following drought, streamflow and water levels recovered almost to pre-drought conditions. The effect of increased ground-water withdrawals on stream base flow in the South Branch French Creek Subbasin was simulated under average and drought conditions with pumping rates equal to 50, 75, and 100 percent of the Delaware River Basin Commission Ground Water Protected Area (GWPA) withdrawal limit (1,393 million gallons per year) with all pumped water removed from the basin. For average recharge conditions, the simulated streamflow of South Branch French Creek at the mouth decreased 18, 28, and 37 percent at a withdrawal rate equal to 50, 75, and 100 percent of the GWPA limit, respectively. After 3 months of drought recharge conditions, the simulated streamflow of South Branch French Creek at the mouth decreased 27, 40, and 52 percent at a withdrawal rate equal to 50, 75, and 100 percent of the GWPA limit, respectively. The effect of well location on base flow, water levels, and the sources of water to the well was simulated by locating a hypothetical well pumping 200 gallons per minute in different places in the Beaver Run Subbasin with all pumped water removed from the basin. The smallest reduction in the base flow of Beaver Run was from a well on the drainage divide

Constructing optimal ensemble projections for predictive environmental modelling in Northern Eurasia

NASA Astrophysics Data System (ADS)

Anisimov, Oleg; Kokorev, Vasily

2013-04-01

Large uncertainties in climate impact modelling are associated with the forcing climate data. This study is targeted at the evaluation of the quality of GCM-based climatic projections in the specific context of predictive environmental modelling in Northern Eurasia. To accomplish this task, we used the output from 36 CMIP5 GCMs from the IPCC AR-5 data base for the control period 1975-2005 and calculated several climatic characteristics and indexes that are most often used in the impact models, i.e. the summer warmth index, duration of the vegetation growth period, precipitation sums, dryness index, thawing degree-day sums, and the annual temperature amplitude. We used data from 744 weather stations in Russia and neighbouring countries to analyze the spatial patterns of modern climatic change and to delineate 17 large regions with coherent temperature changes in the past few decades. GSM results and observational data were averaged over the coherent regions and compared with each other. Ultimately, we evaluated the skills of individual models, ranked them in the context of regional impact modelling and identified top-end GCMs that "better than average" reproduce modern regional changes of the selected meteorological parameters and climatic indexes. Selected top-end GCMs were used to compose several ensembles, each combining results from the different number of models. Ensembles were ranked using the same algorithm and outliers eliminated. We then used data from top-end ensembles for the 2000-2100 period to construct the climatic projections that are likely to be "better than average" in predicting climatic parameters that govern the state of environment in Northern Eurasia. The ultimate conclusions of our study are the following. • High-end GCMs that demonstrate excellent skills in conventional atmospheric model intercomparison experiments are not necessarily the best in replicating climatic characteristics that govern the state of environment in Northern Eurasia, and independent model evaluation on regional level is necessary to identify "better than average" GCMs. • Each of the ensembles combining results from several "better than average" models replicate selected meteorological parameters and climatic indexes better than any single GCM. The ensemble skills are parameter-specific and depend on models it consists of. The best results are not necessarily those based on the ensemble comprised by all "better than average" models. • Comprehensive evaluation of climatic scenarios using specific criteria narrows the range of uncertainties in environmental projections.

Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data

Treesearch

Brooke L. Bateman; Anna M. Pidgeon; Volker C. Radeloff; Curtis H. Flather; Jeremy VanDerWal; H. Resit Akcakaya; Wayne E. Thogmartin; Thomas P. Albright; Stephen J. Vavrus; Patricia J. Heglund

2016-01-01

Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in...

How Reliable is Bayesian Model Averaging Under Noisy Data? Statistical Assessment and Implications for Robust Model Selection

NASA Astrophysics Data System (ADS)

Schöniger, Anneli; Wöhling, Thomas; Nowak, Wolfgang

2014-05-01

Bayesian model averaging ranks the predictive capabilities of alternative conceptual models based on Bayes' theorem. The individual models are weighted with their posterior probability to be the best one in the considered set of models. Finally, their predictions are combined into a robust weighted average and the predictive uncertainty can be quantified. This rigorous procedure does, however, not yet account for possible instabilities due to measurement noise in the calibration data set. This is a major drawback, since posterior model weights may suffer a lack of robustness related to the uncertainty in noisy data, which may compromise the reliability of model ranking. We present a new statistical concept to account for measurement noise as source of uncertainty for the weights in Bayesian model averaging. Our suggested upgrade reflects the limited information content of data for the purpose of model selection. It allows us to assess the significance of the determined posterior model weights, the confidence in model selection, and the accuracy of the quantified predictive uncertainty. Our approach rests on a brute-force Monte Carlo framework. We determine the robustness of model weights against measurement noise by repeatedly perturbing the observed data with random realizations of measurement error. Then, we analyze the induced variability in posterior model weights and introduce this "weighting variance" as an additional term into the overall prediction uncertainty analysis scheme. We further determine the theoretical upper limit in performance of the model set which is imposed by measurement noise. As an extension to the merely relative model ranking, this analysis provides a measure of absolute model performance. To finally decide, whether better data or longer time series are needed to ensure a robust basis for model selection, we resample the measurement time series and assess the convergence of model weights for increasing time series length. We illustrate our suggested approach with an application to model selection between different soil-plant models following up on a study by Wöhling et al. (2013). Results show that measurement noise compromises the reliability of model ranking and causes a significant amount of weighting uncertainty, if the calibration data time series is not long enough to compensate for its noisiness. This additional contribution to the overall predictive uncertainty is neglected without our approach. Thus, we strongly advertise to include our suggested upgrade in the Bayesian model averaging routine.

Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia.

PubMed

Ansari, Mozafar; Othman, Faridah; Abunama, Taher; El-Shafie, Ahmed

2018-04-01

The function of a sewage treatment plant is to treat the sewage to acceptable standards before being discharged into the receiving waters. To design and operate such plants, it is necessary to measure and predict the influent flow rate. In this research, the influent flow rate of a sewage treatment plant (STP) was modelled and predicted by autoregressive integrated moving average (ARIMA), nonlinear autoregressive network (NAR) and support vector machine (SVM) regression time series algorithms. To evaluate the models' accuracy, the root mean square error (RMSE) and coefficient of determination (R 2 ) were calculated as initial assessment measures, while relative error (RE), peak flow criterion (PFC) and low flow criterion (LFC) were calculated as final evaluation measures to demonstrate the detailed accuracy of the selected models. An integrated model was developed based on the individual models' prediction ability for low, average and peak flow. An initial assessment of the results showed that the ARIMA model was the least accurate and the NAR model was the most accurate. The RE results also prove that the SVM model's frequency of errors above 10% or below - 10% was greater than the NAR model's. The influent was also forecasted up to 44 weeks ahead by both models. The graphical results indicate that the NAR model made better predictions than the SVM model. The final evaluation of NAR and SVM demonstrated that SVM made better predictions at peak flow and NAR fit well for low and average inflow ranges. The integrated model developed includes the NAR model for low and average influent and the SVM model for peak inflow.

Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere

NASA Astrophysics Data System (ADS)

Ostler, Andreas; Sussmann, Ralf; Patra, Prabir K.; Houweling, Sander; De Bruine, Marko; Stiller, Gabriele P.; Haenel, Florian J.; Plieninger, Johannes; Bousquet, Philippe; Yin, Yi; Saunois, Marielle; Walker, Kaley A.; Deutscher, Nicholas M.; Griffith, David W. T.; Blumenstock, Thomas; Hase, Frank; Warneke, Thorsten; Wang, Zhiting; Kivi, Rigel; Robinson, John

2016-09-01

The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model-TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH4 fields in place of model simulations improves the model-TCCON XCH4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 to 4.3 ppb) and LMDz (Laboratoire de Météorologie Dynamique model with zooming capability; from 6.8 to 4.3 ppb). Replacing model simulations with MIPAS stratospheric CH4 fields adjusted to ACE-FTS reduces the average XCH4 bias for ACTM (3.3 ppb), but increases the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH4 to sufficient accuracy to eliminate these biases. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH4 and, hence, its contribution to XCH4. Therefore, it would be worthwhile to analyze how individual model components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) impact the simulation of stratospheric CH4 and XCH4.

Climatic Models Ensemble-based Mid-21st Century Runoff Projections: A Bayesian Framework

NASA Astrophysics Data System (ADS)

Achieng, K. O.; Zhu, J.

2017-12-01

There are a number of North American Regional Climate Change Assessment Program (NARCCAP) climatic models that have been used to project surface runoff in the mid-21st century. Statistical model selection techniques are often used to select the model that best fits data. However, model selection techniques often lead to different conclusions. In this study, ten models are averaged in Bayesian paradigm to project runoff. Bayesian Model Averaging (BMA) is used to project and identify effect of model uncertainty on future runoff projections. Baseflow separation - a two-digital filter which is also called Eckhardt filter - is used to separate USGS streamflow (total runoff) into two components: baseflow and surface runoff. We use this surface runoff as the a priori runoff when conducting BMA of runoff simulated from the ten RCM models. The primary objective of this study is to evaluate how well RCM multi-model ensembles simulate surface runoff, in a Bayesian framework. Specifically, we investigate and discuss the following questions: How well do ten RCM models ensemble jointly simulate surface runoff by averaging over all the models using BMA, given a priori surface runoff? What are the effects of model uncertainty on surface runoff simulation?

Analysis and comparison of safety models using average daily, average hourly, and microscopic traffic.

PubMed

Wang, Ling; Abdel-Aty, Mohamed; Wang, Xuesong; Yu, Rongjie

2018-02-01

There have been plenty of traffic safety studies based on average daily traffic (ADT), average hourly traffic (AHT), or microscopic traffic at 5 min intervals. Nevertheless, not enough research has compared the performance of these three types of safety studies, and seldom of previous studies have intended to find whether the results of one type of study is transferable to the other two studies. First, this study built three models: a Bayesian Poisson-lognormal model to estimate the daily crash frequency using ADT, a Bayesian Poisson-lognormal model to estimate the hourly crash frequency using AHT, and a Bayesian logistic regression model for the real-time safety analysis using microscopic traffic. The model results showed that the crash contributing factors found by different models were comparable but not the same. Four variables, i.e., the logarithm of volume, the standard deviation of speed, the logarithm of segment length, and the existence of diverge segment, were positively significant in the three models. Additionally, weaving segments experienced higher daily and hourly crash frequencies than merge and basic segments. Then, each of the ADT-based, AHT-based, and real-time models was used to estimate safety conditions at different levels: daily and hourly, meanwhile, the real-time model was also used in 5 min intervals. The results uncovered that the ADT- and AHT-based safety models performed similar in predicting daily and hourly crash frequencies, and the real-time safety model was able to provide hourly crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.

DEVELOMENT AND EVALUATION OF A MODEL FOR ESTIMATING LONG-TERM AVERAGE OZONE EXPOSURES TO CHILDREN

EPA Science Inventory

Long-term average exposures of school-age children can be modelled using longitudinal measurements collected during the Harvard Southern California Chronic Ozone Exposure Study over a 12-month period: June, 1995-May, 1996. The data base contains over 200 young children with perso...

Estimating effective soil properties of heterogeneous areas for modeling infiltration and redistribution

USDA-ARS?s Scientific Manuscript database

Field scale water infiltration and soil-water and solute transport models require spatially-averaged “effective” soil hydraulic parameters to represent the average flux and storage. The values of these effective parameters vary for different conditions, processes, and component soils in a field. For...

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

Marra, Valerio; Kolb, Edward W.; Matarrese, Sabino

We analyze a toy Swiss-cheese cosmological model to study the averaging problem. In our Swiss-cheese model, the cheese is a spatially flat, matter only, Friedmann-Robertson-Walker solution (i.e., the Einstein-de Sitter model), and the holes are constructed from a Lemaitre-Tolman-Bondi solution of Einstein's equations. We study the propagation of photons in the Swiss-cheese model, and find a phenomenological homogeneous model to describe observables. Following a fitting procedure based on light-cone averages, we find that the expansion scalar is unaffected by the inhomogeneities (i.e., the phenomenological homogeneous model is the cheese model). This is because of the spherical symmetry of the model;more » it is unclear whether the expansion scalar will be affected by nonspherical voids. However, the light-cone average of the density as a function of redshift is affected by inhomogeneities. The effect arises because, as the universe evolves, a photon spends more and more time in the (large) voids than in the (thin) high-density structures. The phenomenological homogeneous model describing the light-cone average of the density is similar to the {lambda}CDM concordance model. It is interesting that, although the sole source in the Swiss-cheese model is matter, the phenomenological homogeneous model behaves as if it has a dark-energy component. Finally, we study how the equation of state of the phenomenological homogeneous model depends on the size of the inhomogeneities, and find that the equation-of-state parameters w{sub 0} and w{sub a} follow a power-law dependence with a scaling exponent equal to unity. That is, the equation of state depends linearly on the distance the photon travels through voids. We conclude that, within our toy model, the holes must have a present size of about 250 Mpc to be able to mimic the concordance model.« less

A mathematical model of reservoir sediment quality prediction based on land-use and erosion processes in watershed

NASA Astrophysics Data System (ADS)

Junakova, N.; Balintova, M.; Junak, J.

2017-10-01

The aim of this paper is to propose a mathematical model for determining of total nitrogen (N) and phosphorus (P) content in eroded soil particles with emphasis on prediction of bottom sediment quality in reservoirs. The adsorbed nutrient concentrations are calculated using the Universal Soil Loss Equation (USLE) extended by the determination of the average soil nutrient concentration in top soils. The average annual vegetation and management factor is divided into five periods of the cropping cycle. For selected plants, the average plant nutrient uptake divided into five cropping periods is also proposed. The average nutrient concentrations in eroded soil particles in adsorbed form are modified by sediment enrichment ratio to obtain the total nutrient content in transported soil particles. The model was designed for the conditions of north-eastern Slovakia. The study was carried out in the agricultural basin of the small water reservoir Klusov.

Modeling the effect of control on the wake of a utility-scale turbine via large-eddy simulation

NASA Astrophysics Data System (ADS)

Yang, Xiaolei; Annoni, Jennifer; Seiler, Pete; Sotiropoulos, Fotis

2014-06-01

A model of the University of Minnesota EOLOS research turbine (Clipper Liberty C96) is developed, integrating the C96 torque control law with a high fidelity actuator line large- eddy simulation (LES) model. Good agreement with the blade element momentum theory is obtained for the power coefficient curve under uniform inflow. Three different cases, fixed rotor rotational speed ω, fixed tip-speed ratio (TSR) and generator torque control, have been simulated for turbulent inflow. With approximately the same time-averaged ω, the time- averaged power is in good agreement with measurements for all three cases. Although the time-averaged aerodynamic torque is nearly the same for the three cases, the root-mean-square (rms) of the aerodynamic torque fluctuations is significantly larger for the case with fixed ω. No significant differences have been observed for the time-averaged flow fields behind the turbine for these three cases.

Derivation and calibration of a gas metal arc welding (GMAW) dynamic droplet model

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

Reutzel, E.W.; Einerson, C.J.; Johnson, J.A.

1996-12-31

A rudimentary, existing dynamic model for droplet growth and detachment in gas metal arc welding (GMAW) was improved and calibrated to match experimental data. The model simulates droplets growing at the end of an imaginary spring. Mass is added to the drop as the electrode melts, the droplet grows, and the spring is displaced. Detachment occurs when one of two criteria is met, and the amount of mass that is detached is a function of the droplet velocity at the time of detachment. Improvements to the model include the addition of a second criterion for drop detachment, a more sophisticatedmore » model of the power supply and secondary electric circuit, and the incorporation of a variable electrode resistance. Relevant physical parameters in the model were adjusted during model calibration. The average current, droplet frequency, and parameter-space location of globular-to-streaming mode transition were used as criteria for tuning the model. The average current predicted by the calibrated model matched the experimental average current to within 5% over a wide range of operating conditions.« less

[Comparison of predictive effect between the single auto regressive integrated moving average (ARIMA) model and the ARIMA-generalized regression neural network (GRNN) combination model on the incidence of scarlet fever].

PubMed

Zhu, Yu; Xia, Jie-lai; Wang, Jing

2009-09-01

Application of the 'single auto regressive integrated moving average (ARIMA) model' and the 'ARIMA-generalized regression neural network (GRNN) combination model' in the research of the incidence of scarlet fever. Establish the auto regressive integrated moving average model based on the data of the monthly incidence on scarlet fever of one city, from 2000 to 2006. The fitting values of the ARIMA model was used as input of the GRNN, and the actual values were used as output of the GRNN. After training the GRNN, the effect of the single ARIMA model and the ARIMA-GRNN combination model was then compared. The mean error rate (MER) of the single ARIMA model and the ARIMA-GRNN combination model were 31.6%, 28.7% respectively and the determination coefficient (R(2)) of the two models were 0.801, 0.872 respectively. The fitting efficacy of the ARIMA-GRNN combination model was better than the single ARIMA, which had practical value in the research on time series data such as the incidence of scarlet fever.

Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere

DOE PAGES

Ostler, Andreas; Sussmann, Ralf; Patra, Prabir K.; ...

2016-09-28

The distribution of methane (CH 4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH 4 mixing ratio (XCH 4), which is being measured increasingly for the assessment of CH 4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH 4 accurately for estimating surface emissions from XCH 4. Simulations from three CTMs are tested against XCH 4 observations from the Total Carbon Column Network (TCCON). We analyze how the model–TCCON agreement in XCH 4 depends on the model representation of stratospheric CH 4 distributions.more » Model equivalents of TCCON XCH 4 are computed with stratospheric CH 4 fields from both the model simulations and from satellite-based CH 4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH 4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH 4 fields in place of model simulations improves the model–TCCON XCH 4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH 4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 to 4.3 ppb) and LMDz (Laboratoire de Météorologie Dynamique model with zooming capability; from 6.8 to 4.3 ppb). Replacing model simulations with MIPAS stratospheric CH 4 fields adjusted to ACE-FTS reduces the average XCH 4 bias for ACTM (3.3 ppb), but increases the average XCH 4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH 4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH 4 to sufficient accuracy to eliminate these biases. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH 4 and, hence, its contribution to XCH 4. Furthermore, it would be worthwhile to analyze how individual model components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) impact the simulation of stratospheric CH 4 and XCH 4.« less

Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere

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

Ostler, Andreas; Sussmann, Ralf; Patra, Prabir K.

The distribution of methane (CH 4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH 4 mixing ratio (XCH 4), which is being measured increasingly for the assessment of CH 4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH 4 accurately for estimating surface emissions from XCH 4. Simulations from three CTMs are tested against XCH 4 observations from the Total Carbon Column Network (TCCON). We analyze how the model–TCCON agreement in XCH 4 depends on the model representation of stratospheric CH 4 distributions.more » Model equivalents of TCCON XCH 4 are computed with stratospheric CH 4 fields from both the model simulations and from satellite-based CH 4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH 4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH 4 fields in place of model simulations improves the model–TCCON XCH 4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH 4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 to 4.3 ppb) and LMDz (Laboratoire de Météorologie Dynamique model with zooming capability; from 6.8 to 4.3 ppb). Replacing model simulations with MIPAS stratospheric CH 4 fields adjusted to ACE-FTS reduces the average XCH 4 bias for ACTM (3.3 ppb), but increases the average XCH 4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH 4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH 4 to sufficient accuracy to eliminate these biases. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH 4 and, hence, its contribution to XCH 4. Furthermore, it would be worthwhile to analyze how individual model components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) impact the simulation of stratospheric CH 4 and XCH 4.« less

Identification of coffee bean varieties using hyperspectral imaging: influence of preprocessing methods and pixel-wise spectra analysis.

PubMed

Zhang, Chu; Liu, Fei; He, Yong

2018-02-01

Hyperspectral imaging was used to identify and to visualize the coffee bean varieties. Spectral preprocessing of pixel-wise spectra was conducted by different methods, including moving average smoothing (MA), wavelet transform (WT) and empirical mode decomposition (EMD). Meanwhile, spatial preprocessing of the gray-scale image at each wavelength was conducted by median filter (MF). Support vector machine (SVM) models using full sample average spectra and pixel-wise spectra, and the selected optimal wavelengths by second derivative spectra all achieved classification accuracy over 80%. Primarily, the SVM models using pixel-wise spectra were used to predict the sample average spectra, and these models obtained over 80% of the classification accuracy. Secondly, the SVM models using sample average spectra were used to predict pixel-wise spectra, but achieved with lower than 50% of classification accuracy. The results indicated that WT and EMD were suitable for pixel-wise spectra preprocessing. The use of pixel-wise spectra could extend the calibration set, and resulted in the good prediction results for pixel-wise spectra and sample average spectra. The overall results indicated the effectiveness of using spectral preprocessing and the adoption of pixel-wise spectra. The results provided an alternative way of data processing for applications of hyperspectral imaging in food industry.

Average capacity of the ground to train communication link of a curved track in the turbulence of gamma-gamma distribution

NASA Astrophysics Data System (ADS)

Yang, Yanqiu; Yu, Lin; Zhang, Yixin

2017-04-01

A model of the average capacity of optical wireless communication link with pointing errors for the ground-to-train of the curved track is established based on the non-Kolmogorov. By adopting the gamma-gamma distribution model, we derive the average capacity expression for this channel. The numerical analysis reveals that heavier fog reduces the average capacity of link. The strength of atmospheric turbulence, the variance of pointing errors, and the covered track length need to be reduced for the larger average capacity of link. The normalized beamwidth and the average signal-to-noise ratio (SNR) of the turbulence-free link need to be increased. We can increase the transmit aperture to expand the beamwidth and enhance the signal intensity, thereby decreasing the impact of the beam wander accordingly. As the system adopting the automatic tracking of beam at the receiver positioned on the roof of the train, for eliminating the pointing errors caused by beam wander and train vibration, the equivalent average capacity of the channel will achieve a maximum value. The impact of the non-Kolmogorov spectral index's variation on the average capacity of link can be ignored.

The electrostatics of a dusty plasma

NASA Technical Reports Server (NTRS)

Whipple, E. C.; Mendis, D. A.; Northrop, T. G.

1986-01-01

The potential distribution in a plasma containing dust grains were derived where the Debye length can be larger or smaller than the average intergrain spacing. Three models were treated for the grain-plasma system, with the assumption that the system of dust and plasma is charge-neutral: a permeable grain model, an impermeable grain model, and a capacitor model that does not require the nearest neighbor approximation of the other two models. A gauge-invariant form of Poisson's equation was used which is linearized about the average potential in the system. The charging currents to a grain are functions of the difference between the grain potential and this average potential. Expressions were obtained for the equilibrium potential of the grain and for the gauge-invariant capacitance between the grain and the plasma. The charge on a grain is determined by the product of this capacitance and the grain-plasma potential difference.

Modeling of Density-Dependent Flow based on the Thermodynamically Constrained Averaging Theory

NASA Astrophysics Data System (ADS)

Weigand, T. M.; Schultz, P. B.; Kelley, C. T.; Miller, C. T.; Gray, W. G.

2016-12-01

The thermodynamically constrained averaging theory (TCAT) has been used to formulate general classes of porous medium models, including new models for density-dependent flow. The TCAT approach provides advantages that include a firm connection between the microscale, or pore scale, and the macroscale; a thermodynamically consistent basis; explicit inclusion of factors such as a diffusion that arises from gradients associated with pressure and activity and the ability to describe both high and low concentration displacement. The TCAT model is presented and closure relations for the TCAT model are postulated based on microscale averages and a parameter estimation is performed on a subset of the experimental data. Due to the sharpness of the fronts, an adaptive moving mesh technique was used to ensure grid independent solutions within the run time constraints. The optimized parameters are then used for forward simulations and compared to the set of experimental data not used for the parameter estimation.

Financial Incentives and Cervical Cancer Screening Participation in Ontario's Primary Care Practice Models.

PubMed

Pendrith, Ciara; Thind, Amardeep; Zaric, Gregory S; Sarma, Sisira

2016-08-01

The primary objective of this paper is to compare cervical cancer screening rates of family physicians in Ontario's two dominant reformed practice models, Family Health Group (FHG) and Family Health Organization (FHO), and traditional fee-for-service (FFS) model. Both reformed models formally enrol patients and offer extensive pay-for-performance incentives; however, they differ by remuneration for core services (FHG is FFS; FHO is capitated). The secondary objective is to estimate the average and marginal costs of screening in each model. Using administrative data on 7,298 family physicians and their 2,083,633 female patients aged 35-69 eligible for cervical cancer screening in 2011, we assessed screening rates after adjusting for patient and physician characteristics. Predicted screening rates, fees and bonus payments were used to estimate the average and marginal costs of cervical cancer screening. Adjusted screening rates were highest in the FHG (81.9%), followed by the FHO (79.6%), and then the traditional FFS model (74.2%). The cost of a cervical cancer screening was $18.30 in the FFS model. The estimated average cost of screening in the FHGs and FHOs were $29.71 and $35.02, respectively, while the corresponding marginal costs were $33.05 and $39.06. We found significant differences in cervical cancer screening rates across Ontario's primary care practice models. Cervical screening rates were significantly higher in practice models eligible for incentives (FHGs and FHOs) than the traditional FFS model. However, the average and marginal cost of screening were lowest in the traditional FFS model and highest in the FHOs. Copyright © 2016 Longwoods Publishing.

Comparing Satellite Rainfall Estimates with Rain-Gauge Data: Optimal Strategies Suggested by a Spectral Model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Lau, William K. M. (Technical Monitor)

2002-01-01

Validation of satellite remote-sensing methods for estimating rainfall against rain-gauge data is attractive because of the direct nature of the rain-gauge measurements. Comparisons of satellite estimates to rain-gauge data are difficult, however, because of the extreme variability of rain and the fact that satellites view large areas over a short time while rain gauges monitor small areas continuously. In this paper, a statistical model of rainfall variability developed for studies of sampling error in averages of satellite data is used to examine the impact of spatial and temporal averaging of satellite and gauge data on intercomparison results. The model parameters were derived from radar observations of rain, but the model appears to capture many of the characteristics of rain-gauge data as well. The model predicts that many months of data from areas containing a few gauges are required to validate satellite estimates over the areas, and that the areas should be of the order of several hundred km in diameter. Over gauge arrays of sufficiently high density, the optimal areas and averaging times are reduced. The possibility of using time-weighted averages of gauge data is explored.

Frequentist Model Averaging in Structural Equation Modelling.

PubMed

Jin, Shaobo; Ankargren, Sebastian

2018-06-04

Model selection from a set of candidate models plays an important role in many structural equation modelling applications. However, traditional model selection methods introduce extra randomness that is not accounted for by post-model selection inference. In the current study, we propose a model averaging technique within the frequentist statistical framework. Instead of selecting an optimal model, the contributions of all candidate models are acknowledged. Valid confidence intervals and a [Formula: see text] test statistic are proposed. A simulation study shows that the proposed method is able to produce a robust mean-squared error, a better coverage probability, and a better goodness-of-fit test compared to model selection. It is an interesting compromise between model selection and the full model.

Neural net forecasting for geomagnetic activity

NASA Technical Reports Server (NTRS)

Hernandez, J. V.; Tajima, T.; Horton, W.

1993-01-01

We use neural nets to construct nonlinear models to forecast the AL index given solar wind and interplanetary magnetic field (IMF) data. We follow two approaches: (1) the state space reconstruction approach, which is a nonlinear generalization of autoregressive-moving average models (ARMA) and (2) the nonlinear filter approach, which reduces to a moving average model (MA) in the linear limit. The database used here is that of Bargatze et al. (1985).

40 CFR 600.510-12 - Calculation of average fuel economy and average carbon-related exhaust emissions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... nearest 0.1 mpg; or (iii) For natural gas-fueled model types, the fuel economy value calculated for that... as determined in § 600.208-12(b)(5)(i). (vi) For natural gas dual fuel model types, for model years... natural gas as determined in § 600.208-12(b)(5)(ii) divided by 0.15 provided the requirements of paragraph...

40 CFR 600.510-12 - Calculation of average fuel economy and average carbon-related exhaust emissions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... nearest 0.1 mpg; or (iii) For natural gas-fueled model types, the fuel economy value calculated for that... as determined in § 600.208-12(b)(5)(i). (vi) For natural gas dual fuel model types, for model years... natural gas as determined in § 600.208-12(b)(5)(ii) divided by 0.15 provided the requirements of paragraph...

An Investigation of the Fit of Linear Regression Models to Data from an SAT[R] Validity Study. Research Report 2011-3

ERIC Educational Resources Information Center

Kobrin, Jennifer L.; Sinharay, Sandip; Haberman, Shelby J.; Chajewski, Michael

2011-01-01

This study examined the adequacy of a multiple linear regression model for predicting first-year college grade point average (FYGPA) using SAT[R] scores and high school grade point average (HSGPA). A variety of techniques, both graphical and statistical, were used to examine if it is possible to improve on the linear regression model. The results…

The pitch of short-duration fundamental frequency glissandos.

PubMed

d'Alessandro, C; Rosset, S; Rossi, J P

1998-10-01

Pitch perception for short-duration fundamental frequency (F0) glissandos was studied. In the first part, new measurements using the method of adjustment are reported. Stimuli were F0 glissandos centered at 220 Hz. The parameters under study were: F0 glissando extents (0, 0.8, 1.5, 3, 6, and 12 semitones, i.e., 0, 10.17, 18.74, 38.17, 76.63, and 155.56 Hz), F0 glissando durations (50, 100, 200, and 300 ms), F0 glissando directions (rising or falling), and the extremity of F0 glissandos matched (beginning or end). In the second part, the main results are discussed: (1) perception seems to correspond to an average of the frequencies present in the vicinity of the extremity matched; (2) the higher extremities of the glissando seem more important; (3) adjustments at the end are closer to the extremities than adjustments at the beginning. In the third part, numerical models accounting for the experimental data are proposed: a time-average model and a weighted time-average model. Optimal parameters for these models are derived. The weighted time-average model achieves a 94% accurate prediction rate for the experimental data. The numerical model is successful in predicting the pitch of short-duration F0 glissandos.

Maximum Stress Estimation Model for Multi-Span Waler Beams with Deflections at the Supports Using Average Strains

PubMed Central

Park, Sung Woo; Oh, Byung Kwan; Park, Hyo Seon

2015-01-01

The safety of a multi-span waler beam subjected simultaneously to a distributed load and deflections at its supports can be secured by limiting the maximum stress of the beam to a specific value to prevent the beam from reaching a limit state for failure or collapse. Despite the fact that the vast majority of accidents on construction sites occur at waler beams in retaining wall systems, no safety monitoring model that can consider deflections at the supports of the beam is available. In this paper, a maximum stress estimation model for a waler beam based on average strains measured from vibrating wire strain gauges (VWSGs), the most frequently used sensors in construction field, is presented. The model is derived by defining the relationship between the maximum stress and the average strains measured from VWSGs. In addition to the maximum stress, support reactions, deflections at supports, and the magnitudes of distributed loads for the beam structure can be identified by the estimation model using the average strains. Using simulation tests on two multi-span beams, the performance of the model is evaluated by estimating maximum stress, deflections at supports, support reactions, and the magnitudes of distributed loads. PMID:25831087

Competition model for aperiodic stochastic resonance in a Fitzhugh-Nagumo model of cardiac sensory neurons.

PubMed

Kember, G C; Fenton, G A; Armour, J A; Kalyaniwalla, N

2001-04-01

Regional cardiac control depends upon feedback of the status of the heart from afferent neurons responding to chemical and mechanical stimuli as transduced by an array of sensory neurites. Emerging experimental evidence shows that neural control in the heart may be partially exerted using subthreshold inputs that are amplified by noisy mechanical fluctuations. This amplification is known as aperiodic stochastic resonance (ASR). Neural control in the noisy, subthreshold regime is difficult to see since there is a near absence of any correlation between input and the output, the latter being the average firing (spiking) rate of the neuron. This lack of correlation is unresolved by traditional energy models of ASR since these models are unsuitable for identifying "cause and effect" between such inputs and outputs. In this paper, the "competition between averages" model is used to determine what portion of a noisy, subthreshold input is responsible, on average, for the output of sensory neurons as represented by the Fitzhugh-Nagumo equations. A physiologically relevant conclusion of this analysis is that a nearly constant amount of input is responsible for a spike, on average, and this amount is approximately independent of the firing rate. Hence, correlation measures are generally reduced as the firing rate is lowered even though neural control under this model is actually unaffected.

Queues with Choice via Delay Differential Equations

NASA Astrophysics Data System (ADS)

Pender, Jamol; Rand, Richard H.; Wesson, Elizabeth

Delay or queue length information has the potential to influence the decision of a customer to join a queue. Thus, it is imperative for managers of queueing systems to understand how the information that they provide will affect the performance of the system. To this end, we construct and analyze two two-dimensional deterministic fluid models that incorporate customer choice behavior based on delayed queue length information. In the first fluid model, customers join each queue according to a Multinomial Logit Model, however, the queue length information the customer receives is delayed by a constant Δ. We show that the delay can cause oscillations or asynchronous behavior in the model based on the value of Δ. In the second model, customers receive information about the queue length through a moving average of the queue length. Although it has been shown empirically that giving patients moving average information causes oscillations and asynchronous behavior to occur in U.S. hospitals, we analytically and mathematically show for the first time that the moving average fluid model can exhibit oscillations and determine their dependence on the moving average window. Thus, our analysis provides new insight on how operators of service systems should report queue length information to customers and how delayed information can produce unwanted system dynamics.

Simulated impacts of climate change on phosphorus loading to Lake Michigan

USGS Publications Warehouse

Robertson, Dale M.; Saad, David A.; Christiansen, Daniel E.; Lorenz, David J

2016-01-01

Phosphorus (P) loading to the Great Lakes has caused various types of eutrophication problems. Future climatic changes may modify this loading because climatic models project changes in future meteorological conditions, especially for the key hydrologic driver — precipitation. Therefore, the goal of this study is to project how P loading may change from the range of projected climatic changes. To project the future response in P loading, the HydroSPARROW approach was developed that links results from two spatially explicit models, the SPAtially Referenced Regression on Watershed attributes (SPARROW) transport and fate watershed model and the water-quantity Precipitation Runoff Modeling System (PRMS). PRMS was used to project changes in streamflow throughout the Lake Michigan Basin using downscaled meteorological data from eight General Circulation Models (GCMs) subjected to three greenhouse gas emission scenarios. Downscaled GCMs project a + 2.1 to + 4.0 °C change in average-annual air temperature (+ 2.6 °C average) and a − 5.1% to + 16.7% change in total annual precipitation (+ 5.1% average) for this geographic area by the middle of this century (2045–2065) and larger changes by the end of the century. The climatic changes by mid-century are projected to result in a − 21.2% to + 8.9% change in total annual streamflow (− 1.8% average) and a − 29.6% to + 17.2% change in total annual P loading (− 3.1% average). Although the average projected changes in streamflow and P loading are relatively small for the entire basin, considerable variability exists spatially and among GCMs because of their variability in projected future precipitation.

PIV measurements in the near wakes of hollow cylinders with holes

NASA Astrophysics Data System (ADS)

Firat, Erhan; Ozkan, Gokturk M.; Akilli, Huseyin

2017-05-01

The wake flows behind fixed, hollow, rigid circular cylinders with two rows of holes connecting the front and rear stagnation lines were investigated using particle image velocimetry (PIV) for various combinations of three hole diameters, d = 0.1 D, 0.15 D, and 0.20 D, six hole-to-hole distances, l = 2 d, 3 d, 4 d, 5 d, 6 d, and 7 d, and ten angles of incidence ( α), from 0° to 45° in steps of 5°, at a Reynolds number of Re = 6,900. Time-averaged velocity distributions, instantaneous and time-averaged vorticity patterns, time-averaged streamline topology, and hot spots of turbulent kinetic energy occurred through the interaction of shear layers from the models were presented to show how the wake flow was modified by the presence of the self-issuing jets with various momentums emanating from the downstream holes. In general, as hole diameter which is directly related to jet momentum increased, the values of time-averaged wake characteristics (length of time-averaged recirculation region, vortex formation length, length of shear layers, and gap between the shear layers) increased. Irrespective to d and l tested, the values of the vortex formation length of the models are greater than that of the cylinder without hole (reference model). That is, vortex formation process was shifted downstream by aid of jets. It was found that time-averaged wake characteristics were very sensitive to α. As α increased, the variation of these characteristics can be modeled by exponential decay functions. The effect of l on the three-dimensional vortex shedding patterns in the near wake of the models was also discussed.

Twelve-month, 12 km resolution North American WRF-Chem v3.4 air quality simulation: performance evaluation

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

Tessum, C. W.; Hill, J. D.; Marshall, J. D.

We present results from and evaluate the performance of a 12-month, 12 km horizontal resolution year 2005 air pollution simulation for the contiguous United States using the WRF-Chem (Weather Research and Forecasting with Chemistry) meteorology and chemical transport model (CTM). We employ the 2005 US National Emissions Inventory, the Regional Atmospheric Chemistry Mechanism (RACM), and the Modal Aerosol Dynamics Model for Europe (MADE) with a volatility basis set (VBS) secondary aerosol module. Overall, model performance is comparable to contemporary modeling efforts used for regulatory and health-effects analysis, with an annual average daytime ozone (O 3) mean fractional bias (MFB) ofmore » 12% and an annual average fine particulate matter (PM 2.5) MFB of −1%. WRF-Chem, as configured here, tends to overpredict total PM 2.5 at some high concentration locations and generally overpredicts average 24 h O 3 concentrations. Performance is better at predicting daytime-average and daily peak O 3 concentrations, which are more relevant for regulatory and health effects analyses relative to annual average values. Predictive performance for PM 2.5 subspecies is mixed: the model overpredicts particulate sulfate (MFB = 36%), underpredicts particulate nitrate (MFB = −110%) and organic carbon (MFB = −29%), and relatively accurately predicts particulate ammonium (MFB = 3%) and elemental carbon (MFB = 3%), so that the accuracy in total PM 2.5 predictions is to some extent a function of offsetting over- and underpredictions of PM 2.5 subspecies. Model predictive performance for PM 2.5 and its subspecies is in general worse in winter and in the western US than in other seasons and regions, suggesting spatial and temporal opportunities for future WRF-Chem model development and evaluation.« less

Twelve-month, 12 km resolution North American WRF-Chem v3.4 air quality simulation: performance evaluation

DOE PAGES

Tessum, C. W.; Hill, J. D.; Marshall, J. D.

2015-04-07

We present results from and evaluate the performance of a 12-month, 12 km horizontal resolution year 2005 air pollution simulation for the contiguous United States using the WRF-Chem (Weather Research and Forecasting with Chemistry) meteorology and chemical transport model (CTM). We employ the 2005 US National Emissions Inventory, the Regional Atmospheric Chemistry Mechanism (RACM), and the Modal Aerosol Dynamics Model for Europe (MADE) with a volatility basis set (VBS) secondary aerosol module. Overall, model performance is comparable to contemporary modeling efforts used for regulatory and health-effects analysis, with an annual average daytime ozone (O 3) mean fractional bias (MFB) ofmore » 12% and an annual average fine particulate matter (PM 2.5) MFB of −1%. WRF-Chem, as configured here, tends to overpredict total PM 2.5 at some high concentration locations and generally overpredicts average 24 h O 3 concentrations. Performance is better at predicting daytime-average and daily peak O 3 concentrations, which are more relevant for regulatory and health effects analyses relative to annual average values. Predictive performance for PM 2.5 subspecies is mixed: the model overpredicts particulate sulfate (MFB = 36%), underpredicts particulate nitrate (MFB = −110%) and organic carbon (MFB = −29%), and relatively accurately predicts particulate ammonium (MFB = 3%) and elemental carbon (MFB = 3%), so that the accuracy in total PM 2.5 predictions is to some extent a function of offsetting over- and underpredictions of PM 2.5 subspecies. Model predictive performance for PM 2.5 and its subspecies is in general worse in winter and in the western US than in other seasons and regions, suggesting spatial and temporal opportunities for future WRF-Chem model development and evaluation.« less

Simulated effects of irrigation on salinity in the Arkansas River Valley in Colorado

USGS Publications Warehouse

Goff, K.; Lewis, M.E.; Person, M.A.; Konikow, Leonard F.

1998-01-01

Agricultural irrigation has a substantial impact on water quantity and quality in the lower Arkansas River valley of southeastern Colorado. A two-dimensional flow and solute transport model was used to evaluate the potential effects of changes in irrigation on the quantity and quality of water in the alluvial aquifer and in the Arkansas River along an 17.7 km reach of the fiver. The model was calibrated to aquifer water level and dissolved solids concentration data collected throughout the 24 year study period (197195). Two categories of irrigation management were simulated with the calibrated model: (1) a decrease in ground water withdrawals for irrigation; and (2) cessation of all irrigation from ground water and surface water sources. In the modeled category of decreased irrigation from ground water pumping, there was a resulting 6.9% decrease in the average monthly ground water salinity, a 0.6% decrease in average monthly river salinity, and an 11.1% increase in ground water return flows to the river. In the modeled category of the cessation of all irrigation, average monthly ground water salinity decreased by 25%; average monthly river salinity decreased by 4.4%; and ground water return flows to the river decreased by an average of 64%. In all scenarios, simulated ground water salinity decreased relative to historical conditions for about 12 years before reaching a new dynamic equilibrium condition. Aquifer water levels were not sensitive to any of the modeled scenarios. These potential changes in salinity could result in improved water quality for irrigation purposes downstream from the affected area.

An analytical study of various telecomminication networks using markov models

NASA Astrophysics Data System (ADS)

Ramakrishnan, M.; Jayamani, E.; Ezhumalai, P.

2015-04-01

The main aim of this paper is to examine issues relating to the performance of various Telecommunication networks, and applied queuing theory for better design and improved efficiency. Firstly, giving an analytical study of queues deals with quantifying the phenomenon of waiting lines using representative measures of performances, such as average queue length (on average number of customers in the queue), average waiting time in queue (on average time to wait) and average facility utilization (proportion of time the service facility is in use). In the second, using Matlab simulator, summarizes the finding of the investigations, from which and where we obtain results and describing methodology for a) compare the waiting time and average number of messages in the queue in M/M/1 and M/M/2 queues b) Compare the performance of M/M/1 and M/D/1 queues and study the effect of increasing the number of servers on the blocking probability M/M/k/k queue model.

A state-based probabilistic model for tumor respiratory motion prediction

NASA Astrophysics Data System (ADS)

Kalet, Alan; Sandison, George; Wu, Huanmei; Schmitz, Ruth

2010-12-01

This work proposes a new probabilistic mathematical model for predicting tumor motion and position based on a finite state representation using the natural breathing states of exhale, inhale and end of exhale. Tumor motion was broken down into linear breathing states and sequences of states. Breathing state sequences and the observables representing those sequences were analyzed using a hidden Markov model (HMM) to predict the future sequences and new observables. Velocities and other parameters were clustered using a k-means clustering algorithm to associate each state with a set of observables such that a prediction of state also enables a prediction of tumor velocity. A time average model with predictions based on average past state lengths was also computed. State sequences which are known a priori to fit the data were fed into the HMM algorithm to set a theoretical limit of the predictive power of the model. The effectiveness of the presented probabilistic model has been evaluated for gated radiation therapy based on previously tracked tumor motion in four lung cancer patients. Positional prediction accuracy is compared with actual position in terms of the overall RMS errors. Various system delays, ranging from 33 to 1000 ms, were tested. Previous studies have shown duty cycles for latencies of 33 and 200 ms at around 90% and 80%, respectively, for linear, no prediction, Kalman filter and ANN methods as averaged over multiple patients. At 1000 ms, the previously reported duty cycles range from approximately 62% (ANN) down to 34% (no prediction). Average duty cycle for the HMM method was found to be 100% and 91 ± 3% for 33 and 200 ms latency and around 40% for 1000 ms latency in three out of four breathing motion traces. RMS errors were found to be lower than linear and no prediction methods at latencies of 1000 ms. The results show that for system latencies longer than 400 ms, the time average HMM prediction outperforms linear, no prediction, and the more general HMM-type predictive models. RMS errors for the time average model approach the theoretical limit of the HMM, and predicted state sequences are well correlated with sequences known to fit the data.

A highly detailed FEM volume conductor model based on the ICBM152 average head template for EEG source imaging and TCS targeting.

PubMed

Haufe, Stefan; Huang, Yu; Parra, Lucas C

2015-08-01

In electroencephalographic (EEG) source imaging as well as in transcranial current stimulation (TCS), it is common to model the head using either three-shell boundary element (BEM) or more accurate finite element (FEM) volume conductor models. Since building FEMs is computationally demanding and labor intensive, they are often extensively reused as templates even for subjects with mismatching anatomies. BEMs can in principle be used to efficiently build individual volume conductor models; however, the limiting factor for such individualization are the high acquisition costs of structural magnetic resonance images. Here, we build a highly detailed (0.5mm(3) resolution, 6 tissue type segmentation, 231 electrodes) FEM based on the ICBM152 template, a nonlinear average of 152 adult human heads, which we call ICBM-NY. We show that, through more realistic electrical modeling, our model is similarly accurate as individual BEMs. Moreover, through using an unbiased population average, our model is also more accurate than FEMs built from mismatching individual anatomies. Our model is made available in Matlab format.

EXPERIMENTAL AND MODEL-COMPUTED AREA AVERAGED VERTICAL PROFILES OF WIND SPEED FOR EVALUATION OF MESOSCALE URBAN CANOPY SCHEMES

EPA Science Inventory

Numerous urban canopy schemes have recently been developed for mesoscale models in order to approximate the drag and turbulent production effects of a city on the air flow. However, little data exists by which to evaluate the efficacy of the schemes since "area-averaged&quo...

77 FR 69924 - Request for Comments on a Renewal of a Previously Approved Information Collection: Production...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-21

...: Kenneth R. Katz, Fuel Economy Division, Office of International Policy, Fuel Economy and Consumer Programs... Parts 531 and 533 Passenger Car Average Fuel Economy Standards--Model Years 2016-2025; Light Truck Average Fuel Economy Standards--Model Years 2016-2025; Production Plan Data. OMB Control Number: 2127-0655...

49 CFR 526.5 - Earning offsetting monetary credits in future model years.

Code of Federal Regulations, 2010 CFR

2010-10-01

... each planned product action (e.g., new model, mix change) which will affect the average fuel economy of... Act must contain the following information: (a) Projected average fuel economy and production levels for the class of automobiles which may fail to comply with a fuel economy standard and for any other...

40 CFR 600.510-12 - Calculation of average fuel economy and average carbon-related exhaust emissions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... MOTOR VEHICLES Fuel Economy Regulations for Model Year 1978 Passenger Automobiles and for 1979 and Later Model Year Automobiles (Light Trucks and Passenger Automobiles)-Procedures for Determining Manufacturer... will be calculated to the nearest 0.1 mpg for the categories of automobiles identified in this section...

Flame-conditioned turbulence modeling for reacting flows

NASA Astrophysics Data System (ADS)

Macart, Jonathan F.; Mueller, Michael E.

2017-11-01

Conventional approaches to turbulence modeling in reacting flows rely on unconditional averaging or filtering, that is, consideration of the momentum equations only in physical space, implicitly assuming that the flame only weakly affects the turbulence, aside from a variation in density. Conversely, for scalars, which are strongly coupled to the flame structure, their evolution equations are often projected onto a reduced-order manifold, that is, conditionally averaged or filtered, on a flame variable such as a mixture fraction or progress variable. Such approaches include Conditional Moment Closure (CMC) and related variants. However, recent observations from Direct Numerical Simulation (DNS) have indicated that the flame can strongly affect turbulence in premixed combustion at low Karlovitz number. In this work, a new approach to turbulence modeling for reacting flows is investigated in which conditionally averaged or filtered equations are evolved for the momentum. The conditionally-averaged equations for the velocity and its covariances are derived, and budgets are evaluated from DNS databases of turbulent premixed planar jet flames. The most important terms in these equations are identified, and preliminary closure models are proposed.

Development of sustainable precision farming systems for swine: estimating real-time individual amino acid requirements in growing-finishing pigs.

PubMed

Hauschild, L; Lovatto, P A; Pomar, J; Pomar, C

2012-07-01

The objective of this study was to develop and evaluate a mathematical model used to estimate the daily amino acid requirements of individual growing-finishing pigs. The model includes empirical and mechanistic model components. The empirical component estimates daily feed intake (DFI), BW, and daily gain (DG) based on individual pig information collected in real time. Based on DFI, BW, and DG estimates, the mechanistic component uses classic factorial equations to estimate the optimal concentration of amino acids that must be offered to each pig to meet its requirements. The model was evaluated with data from a study that investigated the effect of feeding pigs with a 3-phase or daily multiphase system. The DFI and BW values measured in this study were compared with those estimated by the empirical component of the model. The coherence of the values estimated by the mechanistic component was evaluated by analyzing if it followed a normal pattern of requirements. Lastly, the proposed model was evaluated by comparing its estimates with those generated by the existing growth model (InraPorc). The precision of the proposed model and InraPorc in estimating DFI and BW was evaluated through the mean absolute error. The empirical component results indicated that the DFI and BW trajectories of individual pigs fed ad libitum could be predicted 1 d (DFI) or 7 d (BW) ahead with the average mean absolute error of 12.45 and 1.85%, respectively. The average mean absolute error obtained with the InraPorc for the average individual of the population was 14.72% for DFI and 5.38% for BW. Major differences were observed when estimates from InraPorc were compared with individual observations. The proposed model, however, was effective in tracking the change in DFI and BW for each individual pig. The mechanistic model component estimated the optimal standardized ileal digestible Lys to NE ratio with reasonable between animal (average CV = 7%) and overtime (average CV = 14%) variation. Thus, the amino acid requirements estimated by model are animal- and time-dependent and follow, in real time, the individual DFI and BW growth patterns. The proposed model can follow the average feed intake and feed weight trajectory of each individual pig in real time with good accuracy. Based on these trajectories and using classical factorial equations, the model makes it possible to estimate dynamically the AA requirements of each animal, taking into account the intake and growth changes of the animal.

The application of a geometric optical canopy reflectance model to semiarid shrub vegetation

NASA Technical Reports Server (NTRS)

Franklin, Janet; Turner, Debra L.

1992-01-01

Estimates are obtained of the average plant size and density of shrub vegetation on the basis of SPOT High Resolution Visible Multispectral imagery from Chihuahuan desert areas, using the Li and Strahler (1985) model. The aggregated predictions for a number of stands within a class were accurate to within one or two standard errors of the observed average value. Accuracy was highest for those classes of vegetation where the nonrandom scrub pattern was characterized for the class on the basis of the average coefficient of the determination of density.

A Lagrangian subgrid-scale model with dynamic estimation of Lagrangian time scale for large eddy simulation of complex flows

NASA Astrophysics Data System (ADS)

Verma, Aman; Mahesh, Krishnan

2012-08-01

The dynamic Lagrangian averaging approach for the dynamic Smagorinsky model for large eddy simulation is extended to an unstructured grid framework and applied to complex flows. The Lagrangian time scale is dynamically computed from the solution and does not need any adjustable parameter. The time scale used in the standard Lagrangian model contains an adjustable parameter θ. The dynamic time scale is computed based on a "surrogate-correlation" of the Germano-identity error (GIE). Also, a simple material derivative relation is used to approximate GIE at different events along a pathline instead of Lagrangian tracking or multi-linear interpolation. Previously, the time scale for homogeneous flows was computed by averaging along directions of homogeneity. The present work proposes modifications for inhomogeneous flows. This development allows the Lagrangian averaged dynamic model to be applied to inhomogeneous flows without any adjustable parameter. The proposed model is applied to LES of turbulent channel flow on unstructured zonal grids at various Reynolds numbers. Improvement is observed when compared to other averaging procedures for the dynamic Smagorinsky model, especially at coarse resolutions. The model is also applied to flow over a cylinder at two Reynolds numbers and good agreement with previous computations and experiments is obtained. Noticeable improvement is obtained using the proposed model over the standard Lagrangian model. The improvement is attributed to a physically consistent Lagrangian time scale. The model also shows good performance when applied to flow past a marine propeller in an off-design condition; it regularizes the eddy viscosity and adjusts locally to the dominant flow features.

Relationship between road traffic accidents and conflicts recorded by drive recorders.

PubMed

Lu, Guangquan; Cheng, Bo; Kuzumaki, Seigo; Mei, Bingsong

2011-08-01

Road traffic conflicts can be used to estimate the probability of accident occurrence, assess road safety, or evaluate road safety programs if the relationship between road traffic accidents and conflicts is known. To this end, we propose a model for the relationship between road traffic accidents and conflicts recorded by drive recorders (DRs). DRs were installed in 50 cars in Beijing to collect records of traffic conflicts. Data containing 1366 conflicts were collected in 193 days. The hourly distributions of conflicts and accidents were used to model the relationship between accidents and conflicts. To eliminate time series and base number effects, we defined and used 2 parameters: average annual number of accidents per 10,000 vehicles per hour and average number of conflicts per 10,000 vehicles per hour. A model was developed to describe the relationship between the two parameters. If A(i) = average annual number of accidents per 10,000 vehicles per hour at hour i, and E(i) = average number of conflicts per 10,000 vehicles per hour at hour i, the relationship can be expressed as [Formula in text] (α>0, β>0). The average number of traffic accidents increases as the number of conflicts rises, but the rate of increase decelerates as the number of conflicts increases further. The proposed model can describe the relationship between road traffic accidents and conflicts in a simple manner. According to our analysis, the model fits the present data.

Model selection and model averaging in phylogenetics: advantages of akaike information criterion and bayesian approaches over likelihood ratio tests.

PubMed

Posada, David; Buckley, Thomas R

2004-10-01

Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental concepts and techniques of model selection in the context of phylogenetics. We start by reviewing different aspects of the selection of substitution models in phylogenetics from a theoretical, philosophical and practical point of view, and summarize this comparison in table format. We argue that the most commonly implemented model selection approach, the hierarchical likelihood ratio test, is not the optimal strategy for model selection in phylogenetics, and that approaches like the Akaike Information Criterion (AIC) and Bayesian methods offer important advantages. In particular, the latter two methods are able to simultaneously compare multiple nested or nonnested models, assess model selection uncertainty, and allow for the estimation of phylogenies and model parameters using all available models (model-averaged inference or multimodel inference). We also describe how the relative importance of the different parameters included in substitution models can be depicted. To illustrate some of these points, we have applied AIC-based model averaging to 37 mitochondrial DNA sequences from the subgenus Ohomopterus(genus Carabus) ground beetles described by Sota and Vogler (2001).

49 CFR 531.5 - Fuel economy standards.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PASSENGER AUTOMOBILE AVERAGE FUEL ECONOMY STANDARDS § 531.5 Fuel... automobiles shall comply with the fleet average fuel economy standards in Table I, expressed in miles per... passenger automobile fleet shall comply with the fleet average fuel economy level calculated for that model...

49 CFR 531.5 - Fuel economy standards.

Code of Federal Regulations, 2013 CFR

2013-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PASSENGER AUTOMOBILE AVERAGE FUEL ECONOMY STANDARDS § 531.5 Fuel... automobiles shall comply with the fleet average fuel economy standards in Table I, expressed in miles per... passenger automobile fleet shall comply with the fleet average fuel economy level calculated for that model...

Calibration of a texture-based model of a ground-water flow system, western San Joaquin Valley, California

USGS Publications Warehouse

Phillips, Steven P.; Belitz, Kenneth

1991-01-01

The occurrence of selenium in agricultural drain water from the western San Joaquin Valley, California, has focused concern on the semiconfined ground-water flow system, which is underlain by the Corcoran Clay Member of the Tulare Formation. A two-step procedure is used to calibrate a preliminary model of the system for the purpose of determining the steady-state hydraulic properties. Horizontal and vertical hydraulic conductivities are modeled as functions of the percentage of coarse sediment, hydraulic conductivities of coarse-textured (Kcoarse) and fine-textured (Kfine) end members, and averaging methods used to calculate equivalent hydraulic conductivities. The vertical conductivity of the Corcoran (Kcorc) is an additional parameter to be evaluated. In the first step of the calibration procedure, the model is run by systematically varying the following variables: (1) Kcoarse/Kfine, (2) Kcoarse/Kcorc, and (3) choice of averaging methods in the horizontal and vertical directions. Root mean square error and bias values calculated from the model results are functions of these variables. These measures of error provide a means for evaluating model sensitivity and for selecting values of Kcoarse, Kfine, and Kcorc for use in the second step of the calibration procedure. In the second step, recharge rates are evaluated as functions of Kcoarse, Kcorc, and a combination of averaging methods. The associated Kfine values are selected so that the root mean square error is minimized on the basis of the results from the first step. The results of the two-step procedure indicate that the spatial distribution of hydraulic conductivity that best produces the measured hydraulic head distribution is created through the use of arithmetic averaging in the horizontal direction and either geometric or harmonic averaging in the vertical direction. The equivalent hydraulic conductivities resulting from either combination of averaging methods compare favorably to field- and laboratory-based values.

SU-F-BRD-01: A Logistic Regression Model to Predict Objective Function Weights in Prostate Cancer IMRT

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

Boutilier, J; Chan, T; Lee, T

2014-06-15

Purpose: To develop a statistical model that predicts optimization objective function weights from patient geometry for intensity-modulation radiotherapy (IMRT) of prostate cancer. Methods: A previously developed inverse optimization method (IOM) is applied retrospectively to determine optimal weights for 51 treated patients. We use an overlap volume ratio (OVR) of bladder and rectum for different PTV expansions in order to quantify patient geometry in explanatory variables. Using the optimal weights as ground truth, we develop and train a logistic regression (LR) model to predict the rectum weight and thus the bladder weight. Post hoc, we fix the weights of the leftmore » femoral head, right femoral head, and an artificial structure that encourages conformity to the population average while normalizing the bladder and rectum weights accordingly. The population average of objective function weights is used for comparison. Results: The OVR at 0.7cm was found to be the most predictive of the rectum weights. The LR model performance is statistically significant when compared to the population average over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and mean voxel dose to the bladder, rectum, CTV, and PTV. On average, the LR model predicted bladder and rectum weights that are both 63% closer to the optimal weights compared to the population average. The treatment plans resulting from the LR weights have, on average, a rectum V70Gy that is 35% closer to the clinical plan and a bladder V70Gy that is 43% closer. Similar results are seen for bladder V54Gy and rectum V54Gy. Conclusion: Statistical modelling from patient anatomy can be used to determine objective function weights in IMRT for prostate cancer. Our method allows the treatment planners to begin the personalization process from an informed starting point, which may lead to more consistent clinical plans and reduce overall planning time.« less

Evaluation of Near-Tropopause Ozone Distributions in the Global Modeling Initiative Combined Stratosphere/Troposphere Model with Ozonesonde Data

NASA Technical Reports Server (NTRS)

Considine, David B.; Logan, Jennifer A.; Olsen, Mark A.

2008-01-01

The NASA Global Modeling Initiative has developed a combined stratosphere/troposphere chemistry and transport model which fully represents the processes governing atmospheric composition near the tropopause. We evaluate model ozone distributions near the tropopause, using two high vertical resolution monthly mean ozone profile climatologies constructed with ozonesonde data, one by averaging on pressure levels and the other relative to the thermal tropopause. Model ozone is high biased at the SH tropical and NH midlatitude tropopause by approx. 45% in a 4 deg. latitude x 5 deg. longitude model simulation. Increasing the resolution to 2 deg. x 2.5 deg. increases the NH tropopause high bias to approx. 60%, but decreases the tropical tropopause bias to approx. 30%, an effect of a better-resolved residual circulation. The tropopause ozone biases appear not to be due to an overly vigorous residual circulation or excessive stratosphere/troposphere exchange, but are more likely due to insufficient vertical resolution or excessive vertical diffusion near the tropopause. In the upper troposphere and lower stratosphere, model/measurement intercomparisons are strongly affected by the averaging technique. NH and tropical mean model lower stratospheric biases are less than 20%. In the upper troposphere, the 2 deg. x 2.5 deg. simulation exhibits mean high biases of approx. 20% and approx. 35% during April in the tropics and NH midlatitudes, respectively, compared to the pressure averaged climatology. However, relative-to-tropopause averaging produces upper troposphere high biases of approx. 30% and 70% in the tropics and NH midlatitudes. This is because relative-to-tropopause averaging better preserves large cross-tropopause O3 gradients, which are seen in the daily sonde data, but not in daily model profiles. The relative annual cycle of ozone near the tropopause is reproduced very well in the model Northern Hemisphere midlatitudes. In the tropics, the model amplitude of the near tropopause annual cycle is weak. This is likely due to the annual amplitude of mean vertical upwelling near the tropopause, which analysis suggests is approx. 30% weaker than in the real atmosphere.

Light propagation in Swiss-cheese models of random close-packed Szekeres structures: Effects of anisotropy and comparisons with perturbative results

NASA Astrophysics Data System (ADS)

Koksbang, S. M.

2017-03-01

Light propagation in two Swiss-cheese models based on anisotropic Szekeres structures is studied and compared with light propagation in Swiss-cheese models based on the Szekeres models' underlying Lemaitre-Tolman-Bondi models. The study shows that the anisotropy of the Szekeres models has only a small effect on quantities such as redshift-distance relations, projected shear and expansion rate along individual light rays. The average angular diameter distance to the last scattering surface is computed for each model. Contrary to earlier studies, the results obtained here are (mostly) in agreement with perturbative results. In particular, a small negative shift, δ DA≔D/A-DA ,b g DA ,b g , in the angular diameter distance is obtained upon line-of-sight averaging in three of the four models. The results are, however, not statistically significant. In the fourth model, there is a small positive shift which has an especially small statistical significance. The line-of-sight averaged inverse magnification at z =1100 is consistent with 1 to a high level of confidence for all models, indicating that the area of the surface corresponding to z =1100 is close to that of the background.

A systematic comparison of two-equation Reynolds-averaged Navier-Stokes turbulence models applied to shock-cloud interactions

NASA Astrophysics Data System (ADS)

Goodson, Matthew D.; Heitsch, Fabian; Eklund, Karl; Williams, Virginia A.

2017-07-01

Turbulence models attempt to account for unresolved dynamics and diffusion in hydrodynamical simulations. We develop a common framework for two-equation Reynolds-averaged Navier-Stokes turbulence models, and we implement six models in the athena code. We verify each implementation with the standard subsonic mixing layer, although the level of agreement depends on the definition of the mixing layer width. We then test the validity of each model into the supersonic regime, showing that compressibility corrections can improve agreement with experiment. For models with buoyancy effects, we also verify our implementation via the growth of the Rayleigh-Taylor instability in a stratified medium. The models are then applied to the ubiquitous astrophysical shock-cloud interaction in three dimensions. We focus on the mixing of shock and cloud material, comparing results from turbulence models to high-resolution simulations (up to 200 cells per cloud radius) and ensemble-averaged simulations. We find that the turbulence models lead to increased spreading and mixing of the cloud, although no two models predict the same result. Increased mixing is also observed in inviscid simulations at resolutions greater than 100 cells per radius, which suggests that the turbulent mixing begins to be resolved.

Analyzing average and conditional effects with multigroup multilevel structural equation models

PubMed Central

Mayer, Axel; Nagengast, Benjamin; Fletcher, John; Steyer, Rolf

2014-01-01

Conventionally, multilevel analysis of covariance (ML-ANCOVA) has been the recommended approach for analyzing treatment effects in quasi-experimental multilevel designs with treatment application at the cluster-level. In this paper, we introduce the generalized ML-ANCOVA with linear effect functions that identifies average and conditional treatment effects in the presence of treatment-covariate interactions. We show how the generalized ML-ANCOVA model can be estimated with multigroup multilevel structural equation models that offer considerable advantages compared to traditional ML-ANCOVA. The proposed model takes into account measurement error in the covariates, sampling error in contextual covariates, treatment-covariate interactions, and stochastic predictors. We illustrate the implementation of ML-ANCOVA with an example from educational effectiveness research where we estimate average and conditional effects of early transition to secondary schooling on reading comprehension. PMID:24795668

The B-dot Earth Average Magnetic Field

NASA Technical Reports Server (NTRS)

Capo-Lugo, Pedro A.; Rakoczy, John; Sanders, Devon

2013-01-01

The average Earth's magnetic field is solved with complex mathematical models based on mean square integral. Depending on the selection of the Earth magnetic model, the average Earth's magnetic field can have different solutions. This paper presents a simple technique that takes advantage of the damping effects of the b-dot controller and is not dependent of the Earth magnetic model; but it is dependent on the magnetic torquers of the satellite which is not taken into consideration in the known mathematical models. Also the solution of this new technique can be implemented so easily that the flight software can be updated during flight, and the control system can have current gains for the magnetic torquers. Finally, this technique is verified and validated using flight data from a satellite that it has been in orbit for three years.

Brazil wheat yield covariance model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate wheat yields for the wheat growing states of Rio Grande do Sul, Parana, and Santa Catarina in Brazil. The meteorological data of these three states were pooled and the years 1972 to 1979 were used to develop the model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature.

Argentina soybean yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the soybean growing area. Predictor variables for the model were derived from monthly total precipitation and monthly average temperature. A trend variable was included for the years 1969 to 1978 since an increasing trend in yields due to technology was observed between these years.

Forecasting asthma-related hospital admissions in London using negative binomial models.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D; Sarran, Christophe

2013-05-01

Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.

Mass Function of Galaxy Clusters in Relativistic Inhomogeneous Cosmology

NASA Astrophysics Data System (ADS)

Ostrowski, Jan J.; Buchert, Thomas; Roukema, Boudewijn F.

The current cosmological model (ΛCDM) with the underlying FLRW metric relies on the assumption of local isotropy, hence homogeneity of the Universe. Difficulties arise when one attempts to justify this model as an average description of the Universe from first principles of general relativity, since in general, the Einstein tensor built from the averaged metric is not equal to the averaged stress-energy tensor. In this context, the discrepancy between these quantities is called "cosmological backreaction" and has been the subject of scientific debate among cosmologists and relativists for more than 20 years. Here we present one of the methods to tackle this problem, i.e. averaging the scalar parts of the Einstein equations, together with its application, the cosmological mass function of galaxy clusters.

Modelling the average velocity of propagation of the flame front in a gasoline engine with hydrogen additives

NASA Astrophysics Data System (ADS)

Smolenskaya, N. M.; Smolenskii, V. V.

2018-01-01

The paper presents models for calculating the average velocity of propagation of the flame front, obtained from the results of experimental studies. Experimental studies were carried out on a single-cylinder gasoline engine UIT-85 with hydrogen additives up to 6% of the mass of fuel. The article shows the influence of hydrogen addition on the average velocity propagation of the flame front in the main combustion phase. The dependences of the turbulent propagation velocity of the flame front in the second combustion phase on the composition of the mixture and operating modes. The article shows the influence of the normal combustion rate on the average flame propagation velocity in the third combustion phase.

40 CFR 86.449 - Averaging provisions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Later New Motorcycles, General Provisions § 86.449 Averaging provisions. (a) This section describes how... credits may not be banked for use in later model years, except as specified in paragraph (j) of this... average emission levels are at or below the applicable standards in § 86.410-2006. (2) Compliance with the...

Computational problems in autoregressive moving average (ARMA) models

NASA Technical Reports Server (NTRS)

Agarwal, G. C.; Goodarzi, S. M.; Oneill, W. D.; Gottlieb, G. L.

1981-01-01

The choice of the sampling interval and the selection of the order of the model in time series analysis are considered. Band limited (up to 15 Hz) random torque perturbations are applied to the human ankle joint. The applied torque input, the angular rotation output, and the electromyographic activity using surface electrodes from the extensor and flexor muscles of the ankle joint are recorded. Autoregressive moving average models are developed. A parameter constraining technique is applied to develop more reliable models. The asymptotic behavior of the system must be taken into account during parameter optimization to develop predictive models.

40 CFR 600.503-78 - Abbreviations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 1978 Passenger Automobiles and for 1979 and Later Model Year Automobiles (Light Trucks and Passenger Automobiles)-Procedures for Determining Manufacturer's Average Fuel Economy and Manufacturer's Average Carbon...

40 CFR 600.505-78 - Recordkeeping.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 1978 Passenger Automobiles and for 1979 and Later Model Year Automobiles (Light Trucks and Passenger Automobiles)-Procedures for Determining Manufacturer's Average Fuel Economy and Manufacturer's Average Carbon...

Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection

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

Zhao, Kaiguang; Valle, Denis; Popescu, Sorin

2013-05-15

Model specification remains challenging in spectroscopy of plant biochemistry, as exemplified by the availability of various spectral indices or band combinations for estimating the same biochemical. This lack of consensus in model choice across applications argues for a paradigm shift in hyperspectral methods to address model uncertainty and misspecification. We demonstrated one such method using Bayesian model averaging (BMA), which performs variable/band selection and quantifies the relative merits of many candidate models to synthesize a weighted average model with improved predictive performances. The utility of BMA was examined using a portfolio of 27 foliage spectral–chemical datasets representing over 80 speciesmore » across the globe to estimate multiple biochemical properties, including nitrogen, hydrogen, carbon, cellulose, lignin, chlorophyll (a or b), carotenoid, polar and nonpolar extractives, leaf mass per area, and equivalent water thickness. We also compared BMA with partial least squares (PLS) and stepwise multiple regression (SMR). Results showed that all the biochemicals except carotenoid were accurately estimated from hyerspectral data with R2 values > 0.80.« less

Metainference: A Bayesian inference method for heterogeneous systems.

PubMed

Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele

2016-01-01

Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called "metainference," that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors.

Elucidating fluctuating diffusivity in center-of-mass motion of polymer models with time-averaged mean-square-displacement tensor

NASA Astrophysics Data System (ADS)

Miyaguchi, Tomoshige

2017-10-01

There have been increasing reports that the diffusion coefficient of macromolecules depends on time and fluctuates randomly. Here a method is developed to elucidate this fluctuating diffusivity from trajectory data. Time-averaged mean-square displacement (MSD), a common tool in single-particle-tracking (SPT) experiments, is generalized to a second-order tensor with which both magnitude and orientation fluctuations of the diffusivity can be clearly detected. This method is used to analyze the center-of-mass motion of four fundamental polymer models: the Rouse model, the Zimm model, a reptation model, and a rigid rodlike polymer. It is found that these models exhibit distinctly different types of magnitude and orientation fluctuations of diffusivity. This is an advantage of the present method over previous ones, such as the ergodicity-breaking parameter and a non-Gaussian parameter, because with either of these parameters it is difficult to distinguish the dynamics of the four polymer models. Also, the present method of a time-averaged MSD tensor could be used to analyze trajectory data obtained in SPT experiments.

A Lagrangian stochastic model for aerial spray transport above an oak forest

USGS Publications Warehouse

Wang, Yansen; Miller, David R.; Anderson, Dean E.; McManus, Michael L.

1995-01-01

An aerial spray droplets' transport model has been developed by applying recent advances in Lagrangian stochastic simulation of heavy particles. A two-dimensional Lagrangian stochastic model was adopted to simulate the spray droplet dispersion in atmospheric turbulence by adjusting the Lagrangian integral time scale along the drop trajectory. The other major physical processes affecting the transport of spray droplets above a forest canopy, the aircraft wingtip vortices and the droplet evaporation, were also included in each time step of the droplets' transport.The model was evaluated using data from an aerial spray field experiment. In generally neutral stability conditions, the accuracy of the model predictions varied from run-to-run as expected. The average root-mean-square error was 24.61 IU cm−2, and the average relative error was 15%. The model prediction was adequate in two-dimensional steady wind conditions, but was less accurate in variable wind condition. The results indicated that the model can simulate successfully the ensemble; average transport of aerial spray droplets under neutral, steady atmospheric wind conditions.

Cosmological backreaction within the Szekeres model and emergence of spatial curvature

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

Bolejko, Krzysztof, E-mail: krzysztof.bolejko@sydney.edu.au

This paper discusses the phenomenon of backreaction within the Szekeres model. Cosmological backreaction describes how the mean global evolution of the Universe deviates from the Friedmannian evolution. The analysis is based on models of a single cosmological environment and the global ensemble of the Szekeres models (of the Swiss-Cheese-type and Styrofoam-type). The obtained results show that non-linear growth of cosmic structures is associated with the growth of the spatial curvature Ω{sub R} (in the FLRW limit Ω{sub R} → Ω {sub k} ). If averaged over global scales the result depends on the assumed global model of the Universe. Withinmore » the Swiss-Cheese model, which does have a fixed background, the volume average follows the evolution of the background, and the global spatial curvature averages out to zero (the background model is the ΛCDM model, which is spatially flat). In the Styrofoam-type model, which does not have a fixed background, the mean evolution deviates from the spatially flat ΛCDM model, and the mean spatial curvature evolves from Ω{sub R} =0 at the CMB to Ω{sub R} ∼ 0.1 at 0 z =. If the Styrofoam-type model correctly captures evolutionary features of the real Universe then one should expect that in our Universe, the spatial curvature should build up (local growth of cosmic structures) and its mean global average should deviate from zero (backreaction). As a result, this paper predicts that the low-redshift Universe should not be spatially flat (i.e. Ω {sub k} ≠ 0, even if in the early Universe Ω {sub k} = 0) and therefore when analysing low- z cosmological data one should keep Ω {sub k} as a free parameter and independent from the CMB constraints.« less

Regression modeling of gas-particle partitioning of atmospheric oxidized mercury from temperature data

NASA Astrophysics Data System (ADS)

Cheng, Irene; Zhang, Leiming; Blanchard, Pierrette

2014-10-01

Models describing the partitioning of atmospheric oxidized mercury (Hg(II)) between the gas and fine particulate phases were developed as a function of temperature. The models were derived from regression analysis of the gas-particle partitioning parameters, defined by a partition coefficient (Kp) and Hg(II) fraction in fine particles (fPBM) and temperature data from 10 North American sites. The generalized model, log(1/Kp) = 12.69-3485.30(1/T) (R2 = 0.55; root-mean-square error (RMSE) of 1.06 m3/µg for Kp), predicted the observed average Kp at 7 of the 10 sites. Discrepancies between the predicted and observed average Kp were found at the sites impacted by large Hg sources because the model had not accounted for the different mercury speciation profile and aerosol compositions of different sources. Site-specific equations were also generated from average Kp and fPBM corresponding to temperature interval data. The site-specific models were more accurate than the generalized Kp model at predicting the observations at 9 of the 10 sites as indicated by RMSE of 0.22-0.5 m3/µg for Kp and 0.03-0.08 for fPBM. Both models reproduced the observed monthly average values, except for a peak in Hg(II) partitioning observed during summer at two locations. Weak correlations between the site-specific model Kp or fPBM and observations suggest the role of aerosol composition, aerosol water content, and relative humidity factors on Hg(II) partitioning. The use of local temperature data to parameterize Hg(II) partitioning in the proposed models potentially improves the estimation of mercury cycling in chemical transport models and elsewhere.

Cosmological backreaction within the Szekeres model and emergence of spatial curvature

NASA Astrophysics Data System (ADS)

Bolejko, Krzysztof

2017-06-01

This paper discusses the phenomenon of backreaction within the Szekeres model. Cosmological backreaction describes how the mean global evolution of the Universe deviates from the Friedmannian evolution. The analysis is based on models of a single cosmological environment and the global ensemble of the Szekeres models (of the Swiss-Cheese-type and Styrofoam-type). The obtained results show that non-linear growth of cosmic structures is associated with the growth of the spatial curvature ΩScript R (in the FLRW limit ΩScript R → Ωk). If averaged over global scales the result depends on the assumed global model of the Universe. Within the Swiss-Cheese model, which does have a fixed background, the volume average follows the evolution of the background, and the global spatial curvature averages out to zero (the background model is the ΛCDM model, which is spatially flat). In the Styrofoam-type model, which does not have a fixed background, the mean evolution deviates from the spatially flat ΛCDM model, and the mean spatial curvature evolves from ΩScript R =0 at the CMB to ΩScript R ~ 0.1 at 0z =. If the Styrofoam-type model correctly captures evolutionary features of the real Universe then one should expect that in our Universe, the spatial curvature should build up (local growth of cosmic structures) and its mean global average should deviate from zero (backreaction). As a result, this paper predicts that the low-redshift Universe should not be spatially flat (i.e. Ωk ≠ 0, even if in the early Universe Ωk = 0) and therefore when analysing low-z cosmological data one should keep Ωk as a free parameter and independent from the CMB constraints.

Reformers, Batting Averages, and Malpractice: The Case for Caution in Value-Added Use

ERIC Educational Resources Information Center

Gleason, Daniel

2014-01-01

The essay considers two analogies that help to reveal the limitations of value-added modeling: the first, a comparison with batting averages, shows that the model's reliability is quite limited even though year-to-year correlation figures may seem impressive; the second, a comparison between medical malpractice and so-called educational…

Group-theoretical model of developed turbulence and renormalization of the Navier-Stokes equation.

PubMed

Saveliev, V L; Gorokhovski, M A

2005-07-01

On the basis of the Euler equation and its symmetry properties, this paper proposes a model of stationary homogeneous developed turbulence. A regularized averaging formula for the product of two fields is obtained. An equation for the averaged turbulent velocity field is derived from the Navier-Stokes equation by renormalization-group transformation.

The Effect on Non-Normal Distributions on the Integrated Moving Average Model of Time-Series Analysis.

ERIC Educational Resources Information Center

Doerann-George, Judith

The Integrated Moving Average (IMA) model of time series, and the analysis of intervention effects based on it, assume random shocks which are normally distributed. To determine the robustness of the analysis to violations of this assumption, empirical sampling methods were employed. Samples were generated from three populations; normal,…

40 CFR 86.1865-12 - How to comply with the fleet average CO2 standards.

Code of Federal Regulations, 2010 CFR

2010-07-01

... of § 86.1801-12(j), CO2 fleet average exhaust emission standards apply to: (i) 2012 and later model... businesses meeting certain criteria may be exempted from the greenhouse gas emission standards in § 86.1818... standards applicable in a given model year are calculated separately for passenger automobiles and light...

Initial Conditions in the Averaging Cognitive Model

ERIC Educational Resources Information Center

Noventa, S.; Massidda, D.; Vidotto, G.

2010-01-01

The initial state parameters s[subscript 0] and w[subscript 0] are intricate issues of the averaging cognitive models in Information Integration Theory. Usually they are defined as a measure of prior information (Anderson, 1981; 1982) but there are no general rules to deal with them. In fact, there is no agreement as to their treatment except in…

Mean-field theory for pedestrian outflow through an exit.

PubMed

Yanagisawa, Daichi; Nishinari, Katsuhiro

2007-12-01

The average pedestrian flow through an exit is one of the most important indices in evaluating pedestrian dynamics. In order to study the flow in detail, the floor field model, which is a crowd model using cellular automata, is extended by taking into account realistic behavior of pedestrians around the exit. The model is studied by both numerical simulations and cluster analysis to obtain a theoretical expression for the average pedestrian flow through the exit. It is found quantitatively that the effects of exit door width, the wall, and the pedestrian mood of competition or cooperation significantly influence the average flow. The results show that there is a suitable width and position of the exit according to the pedestrians' mood.

A Bayesian model averaging approach for estimating the relative risk of mortality associated with heat waves in 105 U.S. cities.

PubMed

Bobb, Jennifer F; Dominici, Francesca; Peng, Roger D

2011-12-01

Estimating the risks heat waves pose to human health is a critical part of assessing the future impact of climate change. In this article, we propose a flexible class of time series models to estimate the relative risk of mortality associated with heat waves and conduct Bayesian model averaging (BMA) to account for the multiplicity of potential models. Applying these methods to data from 105 U.S. cities for the period 1987-2005, we identify those cities having a high posterior probability of increased mortality risk during heat waves, examine the heterogeneity of the posterior distributions of mortality risk across cities, assess sensitivity of the results to the selection of prior distributions, and compare our BMA results to a model selection approach. Our results show that no single model best predicts risk across the majority of cities, and that for some cities heat-wave risk estimation is sensitive to model choice. Although model averaging leads to posterior distributions with increased variance as compared to statistical inference conditional on a model obtained through model selection, we find that the posterior mean of heat wave mortality risk is robust to accounting for model uncertainty over a broad class of models. © 2011, The International Biometric Society.

PAB3D: Its History in the Use of Turbulence Models in the Simulation of Jet and Nozzle Flows

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.; Pao, S. Paul; Hunter, Craig A.; Deere, Karen A.; Massey, Steven J.; Elmiligui, Alaa

2006-01-01

This is a review paper for PAB3D s history in the implementation of turbulence models for simulating jet and nozzle flows. We describe different turbulence models used in the simulation of subsonic and supersonic jet and nozzle flows. The time-averaged simulations use modified linear or nonlinear two-equation models to account for supersonic flow as well as high temperature mixing. Two multiscale-type turbulence models are used for unsteady flow simulations. These models require modifications to the Reynolds Averaged Navier-Stokes (RANS) equations. The first scheme is a hybrid RANS/LES model utilizing the two-equation (k-epsilon) model with a RANS/LES transition function, dependent on grid spacing and the computed turbulence length scale. The second scheme is a modified version of the partially averaged Navier-Stokes (PANS) formulation. All of these models are implemented in the three-dimensional Navier-Stokes code PAB3D. This paper discusses computational methods, code implementation, computed results for a wide range of nozzle configurations at various operating conditions, and comparisons with available experimental data. Very good agreement is shown between the numerical solutions and available experimental data over a wide range of operating conditions.

The Gaussian atmospheric transport model and its sensitivity to the joint frequency distribution and parametric variability.

PubMed

Hamby, D M

2002-01-01

Reconstructed meteorological data are often used in some form of long-term wind trajectory models for estimating the historical impacts of atmospheric emissions. Meteorological data for the straight-line Gaussian plume model are put into a joint frequency distribution, a three-dimensional array describing atmospheric wind direction, speed, and stability. Methods using the Gaussian model and joint frequency distribution inputs provide reasonable estimates of downwind concentration and have been shown to be accurate to within a factor of four. We have used multiple joint frequency distributions and probabilistic techniques to assess the Gaussian plume model and determine concentration-estimate uncertainty and model sensitivity. We examine the straight-line Gaussian model while calculating both sector-averaged and annual-averaged relative concentrations at various downwind distances. The sector-average concentration model was found to be most sensitive to wind speed, followed by horizontal dispersion (sigmaZ), the importance of which increases as stability increases. The Gaussian model is not sensitive to stack height uncertainty. Precision of the frequency data appears to be most important to meteorological inputs when calculations are made for near-field receptors, increasing as stack height increases.

Ergodicity Breaking in Geometric Brownian Motion

NASA Astrophysics Data System (ADS)

Peters, O.; Klein, W.

2013-03-01

Geometric Brownian motion (GBM) is a model for systems as varied as financial instruments and populations. The statistical properties of GBM are complicated by nonergodicity, which can lead to ensemble averages exhibiting exponential growth while any individual trajectory collapses according to its time average. A common tactic for bringing time averages closer to ensemble averages is diversification. In this Letter, we study the effects of diversification using the concept of ergodicity breaking.

Averaged head phantoms from magnetic resonance images of Korean children and young adults

NASA Astrophysics Data System (ADS)

Han, Miran; Lee, Ae-Kyoung; Choi, Hyung-Do; Jung, Yong Wook; Park, Jin Seo

2018-02-01

Increased use of mobile phones raises concerns about the health risks of electromagnetic radiation. Phantom heads are routinely used for radiofrequency dosimetry simulations, and the purpose of this study was to construct averaged phantom heads for children and young adults. Using magnetic resonance images (MRI), sectioned cadaver images, and a hybrid approach, we initially built template phantoms representing 6-, 9-, 12-, 15-year-old children and young adults. Our subsequent approach revised the template phantoms using 29 averaged items that were identified by averaging the MRI data from 500 children and young adults. In females, the brain size and cranium thickness peaked in the early teens and then decreased. This is contrary to what was observed in males, where brain size and cranium thicknesses either plateaued or grew continuously. The overall shape of brains was spherical in children and became ellipsoidal by adulthood. In this study, we devised a method to build averaged phantom heads by constructing surface and voxel models. The surface model could be used for phantom manipulation, whereas the voxel model could be used for compliance test of specific absorption rate (SAR) for users of mobile phones or other electronic devices.

Scaling laws and fluctuations in the statistics of word frequencies

NASA Astrophysics Data System (ADS)

Gerlach, Martin; Altmann, Eduardo G.

2014-11-01

In this paper, we combine statistical analysis of written texts and simple stochastic models to explain the appearance of scaling laws in the statistics of word frequencies. The average vocabulary of an ensemble of fixed-length texts is known to scale sublinearly with the total number of words (Heaps’ law). Analyzing the fluctuations around this average in three large databases (Google-ngram, English Wikipedia, and a collection of scientific articles), we find that the standard deviation scales linearly with the average (Taylor's law), in contrast to the prediction of decaying fluctuations obtained using simple sampling arguments. We explain both scaling laws (Heaps’ and Taylor) by modeling the usage of words using a Poisson process with a fat-tailed distribution of word frequencies (Zipf's law) and topic-dependent frequencies of individual words (as in topic models). Considering topical variations lead to quenched averages, turn the vocabulary size a non-self-averaging quantity, and explain the empirical observations. For the numerous practical applications relying on estimations of vocabulary size, our results show that uncertainties remain large even for long texts. We show how to account for these uncertainties in measurements of lexical richness of texts with different lengths.

FIFRELIN - TRIPOLI-4® coupling for Monte Carlo simulations with a fission model. Application to shielding calculations

NASA Astrophysics Data System (ADS)

Petit, Odile; Jouanne, Cédric; Litaize, Olivier; Serot, Olivier; Chebboubi, Abdelhazize; Pénéliau, Yannick

2017-09-01

TRIPOLI-4® Monte Carlo transport code and FIFRELIN fission model have been coupled by means of external files so that neutron transport can take into account fission distributions (multiplicities and spectra) that are not averaged, as is the case when using evaluated nuclear data libraries. Spectral effects on responses in shielding configurations with fission sampling are then expected. In the present paper, the principle of this coupling is detailed and a comparison between TRIPOLI-4® fission distributions at the emission of fission neutrons is presented when using JEFF-3.1.1 evaluated data or FIFRELIN data generated either through a n/g-uncoupled mode or through a n/g-coupled mode. Finally, an application to a modified version of the ASPIS benchmark is performed and the impact of using FIFRELIN data on neutron transport is analyzed. Differences noticed on average reaction rates on the surfaces closest to the fission source are mainly due to the average prompt fission spectrum. Moreover, when working with the same average spectrum, a complementary analysis based on non-average reaction rates still shows significant differences that point out the real impact of using a fission model in neutron transport simulations.

Flow over bedforms in a large sand-bed river: A field investigation

USGS Publications Warehouse

Holmes, Robert R.; Garcia, Marcelo H.

2008-01-01

An experimental field study of flows over bedforms was conducted on the Missouri River near St. Charles, Missouri. Detailed velocity data were collected under two different flow conditions along bedforms in this sand-bed river. The large river-scale data reflect flow characteristics similar to those of laboratory-scale flows, with flow separation occurring downstream of the bedform crest and flow reattachment on the stoss side of the next downstream bedform. Wave-like responses of the flow to the bedforms were detected, with the velocity decreasing throughout the flow depth over bedform troughs, and the velocity increasing over bedform crests. Local and spatially averaged velocity distributions were logarithmic for both datasets. The reach-wise spatially averaged vertical-velocity profile from the standard velocity-defect model was evaluated. The vertically averaged mean flow velocities for the velocity-defect model were within 5% of the measured values and estimated spatially averaged point velocities were within 10% for the upper 90% of the flow depth. The velocity-defect model, neglecting the wake function, was evaluated and found to estimate thevertically averaged mean velocity within 1% of the measured values.  

Comparison of cursive models for handwriting instruction.

PubMed

Karlsdottir, R

1997-12-01

The efficiency of four different cursive handwriting styles as model alphabets for handwriting instruction of primary school children was compared in a cross-sectional field experiment from Grade 3 to 6 in terms of the average handwriting speed developed by the children and the average rate of convergence of the children's handwriting to the style of their model. It was concluded that styles with regular entry stroke patterns give the steadiest rate of convergence to the model and styles with short ascenders and descenders and strokes with not too high curvatures give the highest handwriting speed.

Ergodicity of financial indices

NASA Astrophysics Data System (ADS)

Kolesnikov, A. V.; Rühl, T.

2010-05-01

We introduce the concept of the ensemble averaging for financial markets. We address the question of equality of ensemble and time averaging in their sequence and investigate if these averagings are equivalent for large amount of equity indices and branches. We start with the model of Gaussian-distributed returns, equal-weighted stocks in each index and absence of correlations within a single day and show that even this oversimplified model captures already the run of the corresponding index reasonably well due to its self-averaging properties. We introduce the concept of the instant cross-sectional volatility and discuss its relation to the ordinary time-resolved counterpart. The role of the cross-sectional volatility for the description of the corresponding index as well as the role of correlations between the single stocks and the role of non-Gaussianity of stock distributions is briefly discussed. Our model reveals quickly and efficiently some anomalies or bubbles in a particular financial market and gives an estimate of how large these effects can be and how quickly they disappear.

Statistical theory of nucleation in the presence of uncharacterized impurities

NASA Astrophysics Data System (ADS)

Sear, Richard P.

2004-08-01

First order phase transitions proceed via nucleation. The rate of nucleation varies exponentially with the free-energy barrier to nucleation, and so is highly sensitive to variations in this barrier. In practice, very few systems are absolutely pure, there are typically some impurities present which are rather poorly characterized. These interact with the nucleus, causing the barrier to vary, and so must be taken into account. Here the impurity-nucleus interactions are modelled by random variables. The rate then has the same form as the partition function of Derrida’s random energy model, and as in this model there is a regime in which the behavior is non-self-averaging. Non-self-averaging nucleation is nucleation with a rate that varies significantly from one realization of the random variables to another. In experiment this corresponds to variation in the nucleation rate from one sample to another. General analytic expressions are obtained for the crossover from a self-averaging to a non-self-averaging rate of nucleation.

Optimal weighted averaging of event related activity from acquisitions with artifacts.

PubMed

Vollero, Luca; Petrichella, Sara; Innello, Giulio

2016-08-01

In several biomedical applications that require the signal processing of biological data, the starting procedure for noise reduction is the ensemble averaging of multiple repeated acquisitions (trials). This method is based on the assumption that each trial is composed of two additive components: (i) a time-locked activity related to some sensitive/stimulation phenomenon (ERA, Event Related Activity in the following) and (ii) a sum of several other non time-locked background activities. The averaging aims at estimating the ERA activity under very low Signal to Noise and Interference Ratio (SNIR). Although averaging is a well established tool, its performance can be improved in the presence of high-power disturbances (artifacts) by a trials classification and removal stage. In this paper we propose, model and evaluate a new approach that avoids trials removal, managing trials classified as artifact-free and artifact-prone with two different weights. Based on the model, a weights tuning is possible and through modeling and simulations we show that, when optimally configured, the proposed solution outperforms classical approaches.

[The reentrant binomial model of nuclear anomalies growth in rhabdomyosarcoma RA-23 cell populations under increasing doze of rare ionizing radiation].

PubMed

Alekseeva, N P; Alekseev, A O; Vakhtin, Iu B; Kravtsov, V Iu; Kuzovatov, S N; Skorikova, T I

2008-01-01

Distributions of nuclear morphology anomalies in transplantable rabdomiosarcoma RA-23 cell populations were investigated under effect of ionizing radiation from 0 to 45 Gy. Internuclear bridges, nuclear protrusions and dumbbell-shaped nuclei were accepted for morphological anomalies. Empirical distributions of the number of anomalies per 100 nuclei were used. The adequate model of reentrant binomial distribution has been found. The sum of binomial random variables with binomial number of summands has such distribution. Averages of these random variables were named, accordingly, internal and external average reentrant components. Their maximum likelihood estimations were received. Statistical properties of these estimations were investigated by means of statistical modeling. It has been received that at equally significant correlation between the radiation dose and the average of nuclear anomalies in cell populations after two-three cellular cycles from the moment of irradiation in vivo the irradiation doze significantly correlates with internal average reentrant component, and in remote descendants of cell transplants irradiated in vitro - with external one.

The influence of averaging procedure on the accuracy of IVIVC predictions: immediate release dosage form case study.

PubMed

Ostrowski, Michalł; Wilkowska, Ewa; Baczek, Tomasz

2010-12-01

In vivo-in vitro correlation (IVIVC) is an effective tool to predict absorption behavior of active substances from pharmaceutical dosage forms. The model for immediate release dosage form containing amoxicillin was used in the presented study to check if the calculation method of absorption profiles can influence final results achieved. The comparison showed that an averaging of individual absorption profiles performed by Wagner-Nelson (WN) conversion method can lead to lose the discrimination properties of the model. The approach considering individual plasma concentration versus time profiles enabled to average absorption profiles prior WN conversion. In turn, that enabled to find differences between dispersible tablets and capsules. It was concluded that in the case of immediate release dosage form, the decision to use averaging method should be based on an individual situation; however, it seems that the influence of such a procedure on the discrimination properties of the model is then more significant. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Weighed scalar averaging in LTB dust models: part II. A formalism of exact perturbations

NASA Astrophysics Data System (ADS)

Sussman, Roberto A.

2013-03-01

We examine the exact perturbations that arise from the q-average formalism that was applied in the preceding article (part I) to Lemaître-Tolman-Bondi (LTB) models. By introducing an initial value parametrization, we show that all LTB scalars that take an FLRW ‘look-alike’ form (frequently used in the literature dealing with LTB models) follow as q-averages of covariant scalars that are common to FLRW models. These q-scalars determine for every averaging domain a unique FLRW background state through Darmois matching conditions at the domain boundary, though the definition of this background does not require an actual matching with an FLRW region (Swiss cheese-type models). Local perturbations describe the deviation from the FLRW background state through the local gradients of covariant scalars at the boundary of every comoving domain, while non-local perturbations do so in terms of the intuitive notion of a ‘contrast’ of local scalars with respect to FLRW reference values that emerge from q-averages assigned to the whole domain or the whole time slice in the asymptotic limit. We derive fluid flow evolution equations that completely determine the dynamics of the models in terms of the q-scalars and both types of perturbations. A rigorous formalism of exact spherical nonlinear perturbations is defined over the FLRW background state associated with the q-scalars, recovering the standard results of linear perturbation theory in the appropriate limit. We examine the notion of the amplitude and illustrate the differences between local and non-local perturbations by qualitative diagrams and through an example of a cosmic density void that follows from the numeric solution of the evolution equations.

Iterative Procedures for Exact Maximum Likelihood Estimation in the First-Order Gaussian Moving Average Model

DTIC Science & Technology

1990-11-01

1 = Q- 1 - 1 QlaaQ- 1.1 + a’Q-1a This is a simple case of a general formula called Woodbury’s formula by some authors; see, for example, Phadke and...1 2. The First-Order Moving Average Model ..... .................. 3. Some Approaches to the Iterative...the approximate likelihood function in some time series models. Useful suggestions have been the Cholesky decomposition of the covariance matrix and

Work-related accidents among the Iranian population: a time series analysis, 2000–2011

PubMed Central

Karimlou, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood

2015-01-01

Background Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. Objectives To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. Methods In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box–Jenkins modeling to develop a time series model of the total number of accidents. Results There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). Conclusions The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection. PMID:26119774

Work-related accidents among the Iranian population: a time series analysis, 2000-2011.

PubMed

Karimlou, Masoud; Salehi, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood

2015-01-01

Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box-Jenkins modeling to develop a time series model of the total number of accidents. There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection.

Climate model biases in seasonality of continental water storage revealed by satellite gravimetry

USGS Publications Warehouse

Swenson, Sean; Milly, P.C.D.

2006-01-01

Satellite gravimetric observations of monthly changes in continental water storage are compared with outputs from five climate models. All models qualitatively reproduce the global pattern of annual storage amplitude, and the seasonal cycle of global average storage is reproduced well, consistent with earlier studies. However, global average agreements mask systematic model biases in low latitudes. Seasonal extrema of low‐latitude, hemispheric storage generally occur too early in the models, and model‐specific errors in amplitude of the low‐latitude annual variations are substantial. These errors are potentially explicable in terms of neglected or suboptimally parameterized water stores in the land models and precipitation biases in the climate models.

Real time detection of farm-level swine mycobacteriosis outbreak using time series modeling of the number of condemned intestines in abattoirs.

PubMed

Adachi, Yasumoto; Makita, Kohei

2015-09-01

Mycobacteriosis in swine is a common zoonosis found in abattoirs during meat inspections, and the veterinary authority is expected to inform the producer for corrective actions when an outbreak is detected. The expected value of the number of condemned carcasses due to mycobacteriosis therefore would be a useful threshold to detect an outbreak, and the present study aims to develop such an expected value through time series modeling. The model was developed using eight years of inspection data (2003 to 2010) obtained at 2 abattoirs of the Higashi-Mokoto Meat Inspection Center, Japan. The resulting model was validated by comparing the predicted time-dependent values for the subsequent 2 years with the actual data for 2 years between 2011 and 2012. For the modeling, at first, periodicities were checked using Fast Fourier Transformation, and the ensemble average profiles for weekly periodicities were calculated. An Auto-Regressive Integrated Moving Average (ARIMA) model was fitted to the residual of the ensemble average on the basis of minimum Akaike's information criterion (AIC). The sum of the ARIMA model and the weekly ensemble average was regarded as the time-dependent expected value. During 2011 and 2012, the number of whole or partial condemned carcasses exceeded the 95% confidence interval of the predicted values 20 times. All of these events were associated with the slaughtering of pigs from three producers with the highest rate of condemnation due to mycobacteriosis.

Dimension reduction method for SPH equations

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

Tartakovsky, Alexandre M.; Scheibe, Timothy D.

2011-08-26

Smoothed Particle Hydrodynamics model of a complex multiscale processe often results in a system of ODEs with an enormous number of unknowns. Furthermore, a time integration of the SPH equations usually requires time steps that are smaller than the observation time by many orders of magnitude. A direct solution of these ODEs can be extremely expensive. Here we propose a novel dimension reduction method that gives an approximate solution of the SPH ODEs and provides an accurate prediction of the average behavior of the modeled system. The method consists of two main elements. First, effective equationss for evolution of averagemore » variables (e.g. average velocity, concentration and mass of a mineral precipitate) are obtained by averaging the SPH ODEs over the entire computational domain. These effective ODEs contain non-local terms in the form of volume integrals of functions of the SPH variables. Second, a computational closure is used to close the system of the effective equations. The computational closure is achieved via short bursts of the SPH model. The dimension reduction model is used to simulate flow and transport with mixing controlled reactions and mineral precipitation. An SPH model is used model transport at the porescale. Good agreement between direct solutions of the SPH equations and solutions obtained with the dimension reduction method for different boundary conditions confirms the accuracy and computational efficiency of the dimension reduction model. The method significantly accelerates SPH simulations, while providing accurate approximation of the solution and accurate prediction of the average behavior of the system.« less

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.

Test techniques for model development of repetitive service energy storage capacitors

NASA Astrophysics Data System (ADS)

Thompson, M. C.; Mauldin, G. H.

1984-03-01

The performance of the Sandia perfluorocarbon family of energy storage capacitors was evaluated. The capacitors have a much lower charge noise signature creating new instrumentation performance goals. Thermal response to power loading and the importance of average and spot heating in the bulk regions require technical advancements in real time temperature measurements. Reduction and interpretation of thermal data are crucial to the accurate development of an intelligent thermal transport model. The thermal model is of prime interest in the high repetition rate, high average power applications of power conditioning capacitors. The accurate identification of device parasitic parameters has ramifications in both the average power loss mechanisms and peak current delivery. Methods to determine the parasitic characteristics and their nonlinearities and terminal effects are considered. Meaningful interpretations for model development, performance history, facility development, instrumentation, plans for the future, and present data are discussed.

Toward {U}(N|M) knot invariant from ABJM theory

NASA Astrophysics Data System (ADS)

Eynard, Bertrand; Kimura, Taro

2017-06-01

We study {U}(N|M) character expectation value with the supermatrix Chern-Simons theory, known as the ABJM matrix model, with emphasis on its connection to the knot invariant. This average just gives the half-BPS circular Wilson loop expectation value in ABJM theory, which shall correspond to the unknot invariant. We derive the determinantal formula, which gives {U}(N|M) character expectation values in terms of {U}(1|1) averages for a particular type of character representations. This means that the {U}(1|1) character expectation value is a building block for the {U}(N|M) averages and also, by an appropriate limit, for the {U}(N) invariants. In addition to the original model, we introduce another supermatrix model obtained through the symplectic transform, which is motivated by the torus knot Chern-Simons matrix model. We obtain the Rosso-Jones-type formula and the spectral curve for this case.

Models of brachial to finger pulse wave distortion and pressure decrement.

PubMed

Gizdulich, P; Prentza, A; Wesseling, K H

1997-03-01

To model the pulse wave distortion and pressure decrement occurring between brachial and finger arteries. Distortion reversion and decrement correction were also our aims. Brachial artery pressure was recorded intra-arterially and finger pressure was recorded non-invasively by the Finapres technique in 53 adult human subjects. Mean pressure was subtracted from each pressure waveform and Fourier analysis applied to the pulsations. A distortion model was estimated for each subject and averaged over the group. The average inverse model was applied to the full finger pressure waveform. The pressure decrement was modelled by multiple regression on finger systolic and diastolic levels. Waveform distortion could be described by a general, frequency dependent model having a resonance at 7.3 Hz. The general inverse model has an anti-resonance at this frequency. It converts finger to brachial pulsations thereby reducing average waveform distortion from 9.7 (s.d. 3.2) mmHg per sample for the finger pulse to 3.7 (1.7) mmHg for the converted pulse. Systolic and diastolic level differences between finger and brachial arterial pressures changed from -4 (15) and -8 (11) to +8 (14) and +8 (12) mmHg, respectively, after inverse modelling, with pulse pressures correct on average. The pressure decrement model reduced both the mean and the standard deviation of systolic and diastolic level differences to 0 (13) and 0 (8) mmHg. Diastolic differences were thus reduced most. Brachial to finger pulse wave distortion due to wave reflection in arteries is almost identical in all subjects and can be modelled by a single resonance. The pressure decrement due to flow in arteries is greatest for high pulse pressures superimposed on low means.

Modelling radiative transfer through ponded first-year Arctic sea ice with a plane-parallel model

NASA Astrophysics Data System (ADS)

Taskjelle, Torbjørn; Hudson, Stephen R.; Granskog, Mats A.; Hamre, Børge

2017-09-01

Under-ice irradiance measurements were done on ponded first-year pack ice along three transects during the ICE12 expedition north of Svalbard. Bulk transmittances (400-900 nm) were found to be on average 0.15-0.20 under bare ice, and 0.39-0.46 under ponded ice. Radiative transfer modelling was done with a plane-parallel model. While simulated transmittances deviate significantly from measured transmittances close to the edge of ponds, spatially averaged bulk transmittances agree well. That is, transect-average bulk transmittances, calculated using typical simulated transmittances for ponded and bare ice weighted by the fractional coverage of the two surface types, are in good agreement with the measured values. Radiative heating rates calculated from model output indicates that about 20 % of the incident solar energy is absorbed in bare ice, and 50 % in ponded ice (35 % in pond itself, 15 % in the underlying ice). This large difference is due to the highly scattering surface scattering layer (SSL) increasing the albedo of the bare ice.

Digital flow model of the Chowan River estuary, North Carolina

USGS Publications Warehouse

Daniel, C.C.

1977-01-01

A one-dimensional deterministic flow model based on the continuity equation had been developed to provide estimates of daily flow past a number of points on the Chowan River estuary of northeast North Carolina. The digital model, programmed in Fortran IV, computes daily average discharge for nine sites; four of these represent inflow at the mouths of major tributaries, the five other sites are at stage stations along the estuary. Because flows within the Chowan River and the lower reaches of its tributaries are tidally affected, flows occur in both upstream and downstream directions. The period of record generated by the model extends from April 1, 1974, to March 31, 1976. During the two years of model operation the average discharge at Edenhouse near the mouth of the estuary was 5,830 cfs (cubic feet per second). Daily average flows during this period ranged from 55,900 cfs in the downstream direction on July 17, 1975, to 14,200 cfs in the upstream direction on November 30, 1974

Approximation to cutoffs of higher modes of Rayleigh waves for a layered earth model

USGS Publications Warehouse

Xu, Y.; Xia, J.; Miller, R.D.

2009-01-01

A cutoff defines the long-period termination of a Rayleigh-wave higher mode and, therefore is a key characteristic of higher mode energy relationship to several material properties of the subsurface. Cutoffs have been used to estimate the shear-wave velocity of an underlying half space of a layered earth model. In this study, we describe a method that replaces the multilayer earth model with a single surface layer overlying the half-space model, accomplished by harmonic averaging of velocities and arithmetic averaging of densities. Using numerical comparisons with theoretical models validates the single-layer approximation. Accuracy of this single-layer approximation is best defined by values of the calculated error in the frequency and phase velocity estimate at a cutoff. Our proposed method is intuitively explained using ray theory. Numerical results indicate that a cutoffs frequency is controlled by the averaged elastic properties within the passing depth of Rayleigh waves and the shear-wave velocity of the underlying half space. ?? Birkh??user Verlag, Basel 2009.

Using a GIS to link digital spatial data and the precipitation-runoff modeling system, Gunnison River Basin, Colorado

USGS Publications Warehouse

Battaglin, William A.; Kuhn, Gerhard; Parker, Randolph S.

1993-01-01

The U.S. Geological Survey Precipitation-Runoff Modeling System, a modular, distributed-parameter, watershed-modeling system, is being applied to 20 smaller watersheds within the Gunnison River basin. The model is used to derive a daily water balance for subareas in a watershed, ultimately producing simulated streamflows that can be input into routing and accounting models used to assess downstream water availability under current conditions, and to assess the sensitivity of water resources in the basin to alterations in climate. A geographic information system (GIS) is used to automate a method for extracting physically based hydrologic response unit (HRU) distributed parameter values from digital data sources, and for the placement of those estimates into GIS spatial datalayers. The HRU parameters extracted are: area, mean elevation, average land-surface slope, predominant aspect, predominant land-cover type, predominant soil type, average total soil water-holding capacity, and average water-holding capacity of the root zone.

49 CFR 535.7 - Averaging, banking, and trading (ABT) program.

Code of Federal Regulations, 2011 CFR

2011-10-01

... procedures of 40 CFR part 1065 or using the post-transmission test procedures. (2) Post-transmission hybrid...) Averaging. Averaging is the exchange of FCC among a manufacturer's engines or vehicle families or test... expiration date of five model years after the year in which the credits are earned. For example, credits...

40 CFR 86.1865-12 - How to comply with the fleet average CO2 standards.

Code of Federal Regulations, 2013 CFR

2013-07-01

... different strategies are and why they are used. (i) Calculating the fleet average carbon-related exhaust emissions. (1) Manufacturers must compute separate production-weighted fleet average carbon-related exhaust... as defined in § 86.1818-12. The model type carbon-related exhaust emission results determined...

40 CFR 86.1865-12 - How to comply with the fleet average CO2 standards.

Code of Federal Regulations, 2011 CFR

2011-07-01

... different strategies are and why they are used. (i) Calculating the fleet average carbon-related exhaust emissions. (1) Manufacturers must compute separate production-weighted fleet average carbon-related exhaust... as defined in § 86.1818-12. The model type carbon-related exhaust emission results determined...

40 CFR 86.1865-12 - How to comply with the fleet average CO2 standards.

Code of Federal Regulations, 2012 CFR

2012-07-01

... different strategies are and why they are used. (i) Calculating the fleet average carbon-related exhaust emissions. (1) Manufacturers must compute separate production-weighted fleet average carbon-related exhaust... as defined in § 86.1818-12. The model type carbon-related exhaust emission results determined...

Midwife-led continuity models versus other models of care for childbearing women.

PubMed

Sandall, Jane; Soltani, Hora; Gates, Simon; Shennan, Andrew; Devane, Declan

2016-04-28

Midwives are primary providers of care for childbearing women around the world. However, there is a lack of synthesised information to establish whether there are differences in morbidity and mortality, effectiveness and psychosocial outcomes between midwife-led continuity models and other models of care. To compare midwife-led continuity models of care with other models of care for childbearing women and their infants. We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (25 January 2016) and reference lists of retrieved studies. All published and unpublished trials in which pregnant women are randomly allocated to midwife-led continuity models of care or other models of care during pregnancy and birth. Two review authors independently assessed trials for inclusion and risk of bias, extracted data and checked them for accuracy. The quality of the evidence was assessed using the GRADE approach. We included 15 trials involving 17,674 women. We assessed the quality of the trial evidence for all primary outcomes (i.e. regional analgesia (epidural/spinal), caesarean birth, instrumental vaginal birth (forceps/vacuum), spontaneous vaginal birth, intact perineum, preterm birth (less than 37 weeks) and all fetal loss before and after 24 weeks plus neonatal death using the GRADE methodology: all primary outcomes were graded as of high quality.For the primary outcomes, women who had midwife-led continuity models of care were less likely to experience regional analgesia (average risk ratio (RR) 0.85, 95% confidence interval (CI) 0.78 to 0.92; participants = 17,674; studies = 14; high quality), instrumental vaginal birth (average RR 0.90, 95% CI 0.83 to 0.97; participants = 17,501; studies = 13; high quality), preterm birth less than 37 weeks (average RR 0.76, 95% CI 0.64 to 0.91; participants = 13,238; studies = eight; high quality) and less all fetal loss before and after 24 weeks plus neonatal death (average RR 0.84, 95% CI 0.71 to 0.99; participants = 17,561; studies = 13; high quality evidence). Women who had midwife-led continuity models of care were more likely to experience spontaneous vaginal birth (average RR 1.05, 95% CI 1.03 to 1.07; participants = 16,687; studies = 12; high quality). There were no differences between groups for caesarean births or intact perineum.For the secondary outcomes, women who had midwife-led continuity models of care were less likely to experience amniotomy (average RR 0.80, 95% CI 0.66 to 0.98; participants = 3253; studies = four), episiotomy (average RR 0.84, 95% CI 0.77 to 0.92; participants = 17,674; studies = 14) and fetal loss less than 24 weeks and neonatal death (average RR 0.81, 95% CI 0.67 to 0.98; participants = 15,645; studies = 11). Women who had midwife-led continuity models of care were more likely to experience no intrapartum analgesia/anaesthesia (average RR 1.21, 95% CI 1.06 to 1.37; participants = 10,499; studies = seven), have a longer mean length of labour (hours) (mean difference (MD) 0.50, 95% CI 0.27 to 0.74; participants = 3328; studies = three) and more likely to be attended at birth by a known midwife (average RR 7.04, 95% CI 4.48 to 11.08; participants = 6917; studies = seven). There were no differences between groups for fetal loss equal to/after 24 weeks and neonatal death, induction of labour, antenatal hospitalisation, antepartum haemorrhage, augmentation/artificial oxytocin during labour, opiate analgesia, perineal laceration requiring suturing, postpartum haemorrhage, breastfeeding initiation, low birthweight infant, five-minute Apgar score less than or equal to seven, neonatal convulsions, admission of infant to special care or neonatal intensive care unit(s) or in mean length of neonatal hospital stay (days).Due to a lack of consistency in measuring women's satisfaction and assessing the cost of various maternity models, these outcomes were reported narratively. The majority of included studies reported a higher rate of maternal satisfaction in midwife-led continuity models of care. Similarly, there was a trend towards a cost-saving effect for midwife-led continuity care compared to other care models. This review suggests that women who received midwife-led continuity models of care were less likely to experience intervention and more likely to be satisfied with their care with at least comparable adverse outcomes for women or their infants than women who received other models of care.Further research is needed to explore findings of fewer preterm births and fewer fetal deaths less than 24 weeks, and all fetal loss/neonatal death associated with midwife-led continuity models of care.

Midwife-led continuity models versus other models of care for childbearing women.

PubMed

Sandall, Jane; Soltani, Hora; Gates, Simon; Shennan, Andrew; Devane, Declan

2015-09-15

Midwives are primary providers of care for childbearing women around the world. However, there is a lack of synthesised information to establish whether there are differences in morbidity and mortality, effectiveness and psychosocial outcomes between midwife-led continuity models and other models of care. To compare midwife-led continuity models of care with other models of care for childbearing women and their infants. We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (31 May 2015) and reference lists of retrieved studies. All published and unpublished trials in which pregnant women are randomly allocated to midwife-led continuity models of care or other models of care during pregnancy and birth. Two review authors independently assessed trials for inclusion and risk of bias, extracted data and checked them for accuracy. We included 15 trials involving 17,674 women. We assessed the quality of the trial evidence for all primary outcomes (i.e., regional analgesia (epidural/spinal), caesarean birth, instrumental vaginal birth (forceps/vacuum), spontaneous vaginal birth, intact perineum, preterm birth (less than 37 weeks) and overall fetal loss and neonatal death (fetal loss was assessed by gestation using 24 weeks as the cut-off for viability in many countries) using the GRADE methodology: All primary outcomes were graded as of high quality.For the primary outcomes, women who had midwife-led continuity models of care were less likely to experience regional analgesia (average risk ratio (RR) 0.85, 95% confidence interval (CI) 0.78 to 0.92; participants = 17,674; studies = 14; high quality), instrumental vaginal birth (average RR 0.90, 95% CI 0.83 to 0.97; participants = 17,501; studies = 13; high quality), preterm birth less than 37 weeks (average RR 0.76, 95% CI 0.64 to 0.91; participants = 13,238; studies = 8; high quality) and less overall fetal/neonatal death (average RR 0.84, 95% CI 0.71 to 0.99; participants = 17,561; studies = 13; high quality evidence). Women who had midwife-led continuity models of care were more likely to experience spontaneous vaginal birth (average RR 1.05, 95% CI 1.03 to 1.07; participants = 16,687; studies = 12; high quality). There were no differences between groups for caesarean births or intact perineum.For the secondary outcomes, women who had midwife-led continuity models of care were less likely to experience amniotomy (average RR 0.80, 95% CI 0.66 to 0.98; participants = 3253; studies = 4), episiotomy (average RR 0.84, 95% CI 0.77 to 0.92; participants = 17,674; studies = 14) and fetal loss/neonatal death before 24 weeks (average RR 0.81, 95% CI 0.67 to 0.98; participants = 15,645; studies = 11). Women who had midwife-led continuity models of care were more likely to experience no intrapartum analgesia/anaesthesia (average RR 1.21, 95% CI 1.06 to 1.37; participants = 10,499; studies = 7), have a longer mean length of labour (hours) (mean difference (MD) 0.50, 95% CI 0.27 to 0.74; participants = 3328; studies = 3) and more likely to be attended at birth by a known midwife (average RR 7.04, 95% CI 4.48 to 11.08; participants = 6917; studies = 7). There were no differences between groups for fetal loss or neonatal death more than or equal to 24 weeks, induction of labour, antenatal hospitalisation, antepartum haemorrhage, augmentation/artificial oxytocin during labour, opiate analgesia, perineal laceration requiring suturing, postpartum haemorrhage, breastfeeding initiation, low birthweight infant, five-minute Apgar score less than or equal to seven, neonatal convulsions, admission of infant to special care or neonatal intensive care unit(s) or in mean length of neonatal hospital stay (days).Due to a lack of consistency in measuring women's satisfaction and assessing the cost of various maternity models, these outcomes were reported narratively. The majority of included studies reported a higher rate of maternal satisfaction in midwife-led continuity models of care. Similarly, there was a trend towards a cost-saving effect for midwife-led continuity care compared to other care models. This review suggests that women who received midwife-led continuity models of care were less likely to experience intervention and more likely to be satisfied with their care with at least comparable adverse outcomes for women or their infants than women who received other models of care.Further research is needed to explore findings of fewer preterm births and fewer fetal deaths less than 24 weeks, and overall fetal loss/neonatal death associated with midwife-led continuity models of care.

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.

Rainier Mesa CAU Infiltration Model using INFILv3

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

Levitt, Daniel G.; Kwicklis, Edward M.

The outline of this presentation are: (1) Model Inputs - DEM, Precipitation, Air temp, Soil props, Surface geology, Vegetation; (2) Model Pre-processing - Runoff Routing and sinks, Slope and Azimuth, Soil Ksat reduction with slope (to mitigate bathtub ring), Soil-Bedrock Interface permeabilities; (3) Model Calibration - ET using PEST, Chloride mass balance data, Streamflow using PEST; (4) Model Validation - Streamflow data not used for calibration; (5) Uncertainty Analysis; and (6) Results. Conclusions are: (1) Average annual infiltration rates =11 to 18 mm/year for RM domain; (2) Average annual infiltration rates = 7 to 11 mm/year for SM domain; (3)more » ET = 70% of precipitation for both domains; (4) Runoff = 8-9% for RM; and 22-24% for SM - Apparently high average runoff is caused by the truncation of the lowerelevation portions of watersheds where much of the infiltration of runoff waters would otherwise occur; (5) Model results are calibrated to measured ET, CMB data, and streamflow observations; (6) Model results are validated using streamflow observations discovered after model calibration was complete; (7) Use of soil Ksat reduction with slope to mitigate bathtub ring was successful (based on calibration results); and (8) Soil-bedrock K{_}interface is innovative approach.« less

Vehicle-specific emissions modeling based upon on-road measurements.

PubMed

Frey, H Christopher; Zhang, Kaishan; Rouphail, Nagui M

2010-05-01

Vehicle-specific microscale fuel use and emissions rate models are developed based upon real-world hot-stabilized tailpipe measurements made using a portable emissions measurement system. Consecutive averaging periods of one to three multiples of the response time are used to compare two semiempirical physically based modeling schemes. One scheme is based on internally observable variables (IOVs), such as engine speed and manifold absolute pressure, while the other is based on externally observable variables (EOVs), such as speed, acceleration, and road grade. For NO, HC, and CO emission rates, the average R(2) ranged from 0.41 to 0.66 for the former and from 0.17 to 0.30 for the latter. The EOV models have R(2) for CO(2) of 0.43 to 0.79 versus 0.99 for the IOV models. The models are sensitive to episodic events in driving cycles such as high acceleration. Intervehicle and fleet average modeling approaches are compared; the former account for microscale variations that might be useful for some types of assessments. EOV-based models have practical value for traffic management or simulation applications since IOVs usually are not available or not used for emission estimation.

The Effect of Inhibitory Neuron on the Evolution Model of Higher-Order Coupling Neural Oscillator Population

PubMed Central

Qi, Yi; Wang, Rubin; Jiao, Xianfa; Du, Ying

2014-01-01

We proposed a higher-order coupling neural network model including the inhibitory neurons and examined the dynamical evolution of average number density and phase-neural coding under the spontaneous activity and external stimulating condition. The results indicated that increase of inhibitory coupling strength will cause decrease of average number density, whereas increase of excitatory coupling strength will cause increase of stable amplitude of average number density. Whether the neural oscillator population is able to enter the new synchronous oscillation or not is determined by excitatory and inhibitory coupling strength. In the presence of external stimulation, the evolution of the average number density is dependent upon the external stimulation and the coupling term in which the dominator will determine the final evolution. PMID:24516505

Properties of bright solitons in averaged and unaveraged models for SDG fibres

NASA Astrophysics Data System (ADS)

Kumar, Ajit; Kumar, Atul

1996-04-01

Using the slowly varying envelope approximation and averaging over the fibre cross-section the evolution equation for optical pulses in semiconductor-doped glass (SDG) fibres is derived from the nonlinear wave equation. Bright soliton solutions of this equation are obtained numerically and their properties are studied and compared with those of the bright solitons in the unaveraged model.

The Performance of Multilevel Growth Curve Models under an Autoregressive Moving Average Process

ERIC Educational Resources Information Center

Murphy, Daniel L.; Pituch, Keenan A.

2009-01-01

The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…

PTM Modeling of Dredged Suspended Sediment at Proposed Polaris Point and Ship Repair Facility CVN Berthing Sites - Apra Harbor, Guam

DTIC Science & Technology

2017-09-01

ADCP locations used for model calibration. ......................................................................... 12 Figure 4-3. Sample water...Example of fine sediment sample [Set d, Sample B30]. (B) Example of coarse sediment sample [Set d, sample B05...Turning Basin average sediment size distribution curve. ................................................... 21 Figure 5-5. Turning Basin average size

The Use of Individualized Video Modeling to Enhance Positive Peer Interactions in Three Preschool Children

ERIC Educational Resources Information Center

Green, Vanessa A.; Prior, Tessa; Smart, Emily; Boelema, Tanya; Drysdale, Heather; Harcourt, Susan; Roche, Laura; Waddington, Hannah

2017-01-01

The study described in this article sought to enhance the social interaction skills of 3 preschool children using video modeling. All children had been assessed as having difficulties in their interactions with peers. Two were above average on internalizing problems and the third was above average on externalizing problems. The study used a…

Moisture transfer through the membrane of a cross-flow energy recovery ventilator: Measurement and simple data-driven modeling

Treesearch

CR Boardman; Samuel V. Glass

2015-01-01

The moisture transfer effectiveness (or latent effectiveness) of a cross-flow, membrane based energy recovery ventilator is measured and modeled. Analysis of in situ measurements for a full year shows that energy recovery ventilator latent effectiveness increases with increasing average relative humidity and surprisingly increases with decreasing average temperature. A...

Using Baidu Search Index to Predict Dengue Outbreak in China

NASA Astrophysics Data System (ADS)

Liu, Kangkang; Wang, Tao; Yang, Zhicong; Huang, Xiaodong; Milinovich, Gabriel J.; Lu, Yi; Jing, Qinlong; Xia, Yao; Zhao, Zhengyang; Yang, Yang; Tong, Shilu; Hu, Wenbiao; Lu, Jiahai

2016-12-01

This study identified the possible threshold to predict dengue fever (DF) outbreaks using Baidu Search Index (BSI). Time-series classification and regression tree models based on BSI were used to develop a predictive model for DF outbreak in Guangzhou and Zhongshan, China. In the regression tree models, the mean autochthonous DF incidence rate increased approximately 30-fold in Guangzhou when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 382. When the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 91.8, there was approximately 9-fold increase of the mean autochthonous DF incidence rate in Zhongshan. In the classification tree models, the results showed that when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 99.3, there was 89.28% chance of DF outbreak in Guangzhou, while, in Zhongshan, when the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 68.1, the chance of DF outbreak rose up to 100%. The study indicated that less cost internet-based surveillance systems can be the valuable complement to traditional DF surveillance in China.

Modelling gas dynamics in 1D ducts with abrupt area change

NASA Astrophysics Data System (ADS)

Menina, R.; Saurel, R.; Zereg, M.; Houas, L.

2011-09-01

Most gas dynamic computations in industrial ducts are done in one dimension with cross-section-averaged Euler equations. This poses a fundamental difficulty as soon as geometrical discontinuities are present. The momentum equation contains a non-conservative term involving a surface pressure integral, responsible for momentum loss. Definition of this integral is very difficult from a mathematical standpoint as the flow may contain other discontinuities (shocks, contact discontinuities). From a physical standpoint, geometrical discontinuities induce multidimensional vortices that modify the surface pressure integral. In the present paper, an improved 1D flow model is proposed. An extra energy (or entropy) equation is added to the Euler equations expressing the energy and turbulent pressure stored in the vortices generated by the abrupt area variation. The turbulent energy created by the flow-area change interaction is determined by a specific estimate of the surface pressure integral. Model's predictions are compared with 2D-averaged results from numerical solution of the Euler equations. Comparison with shock tube experiments is also presented. The new 1D-averaged model improves the conventional cross-section-averaged Euler equations and is able to reproduce the main flow features.

Variable diffusion in stock market fluctuations

NASA Astrophysics Data System (ADS)

Hua, Jia-Chen; Chen, Lijian; Falcon, Liberty; McCauley, Joseph L.; Gunaratne, Gemunu H.

2015-02-01

We analyze intraday fluctuations in several stock indices to investigate the underlying stochastic processes using techniques appropriate for processes with nonstationary increments. The five most actively traded stocks each contains two time intervals during the day where the variance of increments can be fit by power law scaling in time. The fluctuations in return within these intervals follow asymptotic bi-exponential distributions. The autocorrelation function for increments vanishes rapidly, but decays slowly for absolute and squared increments. Based on these results, we propose an intraday stochastic model with linear variable diffusion coefficient as a lowest order approximation to the real dynamics of financial markets, and to test the effects of time averaging techniques typically used for financial time series analysis. We find that our model replicates major stylized facts associated with empirical financial time series. We also find that ensemble averaging techniques can be used to identify the underlying dynamics correctly, whereas time averages fail in this task. Our work indicates that ensemble average approaches will yield new insight into the study of financial markets' dynamics. Our proposed model also provides new insight into the modeling of financial markets dynamics in microscopic time scales.

Customer focus level following implementation of quality improvement model in Tehran social security hospitals.

PubMed

Mehrabi, F; Nasiripour, A; Delgoshaei, B

2008-01-01

The key factor for the success of total quality management programs in an organization is focusing on the customer. The purpose of this paper is to assess customer focus level following implementation of a quality improvement model in social security hospitals in Tehran Province. This research was descriptive-comparative in nature. The study population consisted of the implementers of quality improvement model in four Tehran social security hospitals. The data were gathered through a checklist addressing customer knowledge and customer satisfaction. The research findings indicated that the average scores on customer knowledge in Shahriar, Alborz, Milad, and Varamin hospitals were 64.1, 61.2, 54.1, and 46.6, respectively. The average scores on customer satisfaction in Shahriar, Alborz, Milad, and Varamin hospitals were 67.7, 65, 59.4, and 50, respectively. The customer focus average scores in Shahriar, Alborz, Milad, and Varamin hospitals were 66.3, 63.3, 57.3, and 48.6, respectively. The total average scores on customer knowledge, satisfaction and customer focus in the investigated hospitals proved to be 56.4, 60.5, and 58.9, respectively. The paper is of value in showing that implementation of the quality improvement model could considerably improve customer focus level.

In-use activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks.

PubMed

Sandhu, Gurdas S; Frey, H Christopher; Bartelt-Hunt, Shannon; Jones, Elizabeth

2015-03-01

The objectives of this study were to quantify real-world activity, fuel use, and emissions for heavy duty diesel roll-off refuse trucks; evaluate the contribution of duty cycles and emissions controls to variability in cycle average fuel use and emission rates; quantify the effect of vehicle weight on fuel use and emission rates; and compare empirical cycle average emission rates with the U.S. Environmental Protection Agency's MOVES emission factor model predictions. Measurements were made at 1 Hz on six trucks of model years 2005 to 2012, using onboard systems. The trucks traveled 870 miles, had an average speed of 16 mph, and collected 165 tons of trash. The average fuel economy was 4.4 mpg, which is approximately twice previously reported values for residential trash collection trucks. On average, 50% of time is spent idling and about 58% of emissions occur in urban areas. Newer trucks with selective catalytic reduction and diesel particulate filter had NOx and PM cycle average emission rates that were 80% lower and 95% lower, respectively, compared to older trucks without. On average, the combined can and trash weight was about 55% of chassis weight. The marginal effect of vehicle weight on fuel use and emissions is highest at low loads and decreases as load increases. Among 36 cycle average rates (6 trucks×6 cycles), MOVES-predicted values and estimates based on real-world data have similar relative trends. MOVES-predicted CO2 emissions are similar to those of the real world, while NOx and PM emissions are, on average, 43% lower and 300% higher, respectively. The real-world data presented here can be used to estimate benefits of replacing old trucks with new trucks. Further, the data can be used to improve emission inventories and model predictions. In-use measurements of the real-world activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks can be used to improve the accuracy of predictive models, such as MOVES, and emissions inventories. Further, the activity data from this study can be used to generate more representative duty cycles for more accurate chassis dynamometer testing. Comparisons of old and new model year diesel trucks are useful in analyzing the effect of fleet turnover. The analysis of effect of haul weight on fuel use can be used by fleet managers to optimize operations to reduce fuel cost.

How well the Reliable Ensemble Averaging Method (REA) for 15 CMIP5 GCMs simulations works for Mexico?

NASA Astrophysics Data System (ADS)

Colorado, G.; Salinas, J. A.; Cavazos, T.; de Grau, P.

2013-05-01

15 CMIP5 GCMs precipitation simulations were combined in a weighted ensemble using the Reliable Ensemble Averaging (REA) method, obtaining the weight of each model. This was done for a historical period (1961-2000) and for the future emissions based on low (RCP4.5) and high (RCP8.5) radiating forcing for the period 2075-2099. The annual cycle of simple ensemble of the historical GCMs simulations, the historical REA average and the Climate Research Unit (CRU TS3.1) database was compared in four zones of México. In the case of precipitation we can see the improvements by using the REA method, especially in the two northern zones of México where the REA average is more close to the observations (CRU) that the simple average. However in the southern zones although there is an improvement it is not as good as it is in the north, particularly in the southeast where instead of the REA average is able to reproduce qualitatively good the annual cycle with the mid-summer drought it was greatly underestimated. The main reason is because the precipitation is underestimated for all the models and the mid-summer drought do not even exists in some models. In the REA average of the future scenarios, as we can expected, the most drastic decrease in precipitation was simulated using the RCP8.5 especially in the monsoon area and in the south of Mexico in summer and in winter. In the center and southern of Mexico however, the same scenario in autumn simulates an increase of precipitation.

Measuring coding intensity in the Medicare Advantage program.

PubMed

Kronick, Richard; Welch, W Pete

2014-01-01

In 2004, Medicare implemented a system of paying Medicare Advantage (MA) plans that gave them greater incentive than fee-for-service (FFS) providers to report diagnoses. Risk scores for all Medicare beneficiaries 2004-2013 and Medicare Current Beneficiary Survey (MCBS) data, 2006-2011. Change in average risk score for all enrollees and for stayers (beneficiaries who were in either FFS or MA for two consecutive years). Prevalence rates by Hierarchical Condition Category (HCC). Each year the average MA risk score increased faster than the average FFS score. Using the risk adjustment model in place in 2004, the average MA score as a ratio of the average FFS score would have increased from 90% in 2004 to 109% in 2013. Using the model partially implemented in 2014, the ratio would have increased from 88% to 102%. The increase in relative MA scores appears to largely reflect changes in diagnostic coding, not real increases in the morbidity of MA enrollees. In survey-based data for 2006-2011, the MA-FFS ratio of risk scores remained roughly constant at 96%. Intensity of coding varies widely by contract, with some contracts coding very similarly to FFS and others coding much more intensely than the MA average. Underpinning this relative growth in scores is particularly rapid relative growth in a subset of HCCs. Medicare has taken significant steps to mitigate the effects of coding intensity in MA, including implementing a 3.4% coding intensity adjustment in 2010 and revising the risk adjustment model in 2013 and 2014. Given the continuous relative increase in the average MA risk score, further policy changes will likely be necessary.

Stress drop inferred from dynamic rupture simulations consistent with Moment-Rupture area empirical scaling models: Effects of week shallow zone

NASA Astrophysics Data System (ADS)

Dalguer, L. A.; Miyake, H.; Irikura, K.; Wu, H., Sr.

2016-12-01

Empirical scaling models of seismic moment and rupture area provide constraints to parameterize source parameters, such as stress drop, for numerical simulations of ground motion. There are several scaling models published in the literature. The effect of the finite width seismogenic zone and the free-surface have been attributed to cause the breaking of the well know self-similar scaling (e.g. Dalguer et al, 2008) given origin to the so called L and W models for large faults. These models imply the existence of three-stage scaling relationship between seismic moment and rupture area (e.g. Irikura and Miyake, 2011). In this paper we extend the work done by Dalguer et al 2008, in which these authors calibrated fault models that match the observations showing that the average stress drop is independent of earthquake size for buried earthquakes, but scale dependent for surface-rupturing earthquakes. Here we have developed additional sets of dynamic rupture models for vertical strike slip faults to evaluate the effect of the weak shallow layer (WSL) zone for the calibration of stress drop. Rupture in the WSL zone is expected to operate with enhanced energy absorption mechanism. The set of dynamic models consists of fault models with width 20km and fault length L=20km, 40km, 60km, 80km, 100km, 120km, 200km, 300km and 400km and average stress drop values of 2.0MPa, 2.5MPa, 3.0MPa, 3.5MPa, 5.0MPa and 7.5MPa. For models that break the free-surface, the WSL zone is modeled assuming a 2km width with stress drop 0.0MPa or -2.0 MPa. Our results show that depending on the characterization of the WSL zone, the average stress drop at the seismogenic zone that fit the empirical models changes. If WSL zone is not considered, that is, stress drop at SL zone is the same as the seismogenic zone, average stress drop is about 20% smaller than models with WSL zone. By introducing more energy absorption at the SL zone, that could be the case of large mature faults, the average stress drop in the seismogenic zone increases. Suggesting that large earthquakes need higher stress drop to break the fault than buried and moderate earthquakes. Therefore, the value of the average stress drop for large events that break the free-source depend on the definition of the WSL. Suggesting that the WSL plays an important role on the prediction of final slip and fault displacement.

Hybrid Reynolds-Averaged/Large-Eddy Simulations of a Coaxial Supersonic Free-Jet Experiment

NASA Technical Reports Server (NTRS)

Baurle, Robert A.; Edwards, Jack R.

2010-01-01

Reynolds-averaged and hybrid Reynolds-averaged/large-eddy simulations have been applied to a supersonic coaxial jet flow experiment. The experiment was designed to study compressible mixing flow phenomenon under conditions that are representative of those encountered in scramjet combustors. The experiment utilized either helium or argon as the inner jet nozzle fluid, and the outer jet nozzle fluid consisted of laboratory air. The inner and outer nozzles were designed and operated to produce nearly pressure-matched Mach 1.8 flow conditions at the jet exit. The purpose of the computational effort was to assess the state-of-the-art for each modeling approach, and to use the hybrid Reynolds-averaged/large-eddy simulations to gather insight into the deficiencies of the Reynolds-averaged closure models. The Reynolds-averaged simulations displayed a strong sensitivity to choice of turbulent Schmidt number. The initial value chosen for this parameter resulted in an over-prediction of the mixing layer spreading rate for the helium case, but the opposite trend was observed when argon was used as the injectant. A larger turbulent Schmidt number greatly improved the comparison of the results with measurements for the helium simulations, but variations in the Schmidt number did not improve the argon comparisons. The hybrid Reynolds-averaged/large-eddy simulations also over-predicted the mixing layer spreading rate for the helium case, while under-predicting the rate of mixing when argon was used as the injectant. The primary reason conjectured for the discrepancy between the hybrid simulation results and the measurements centered around issues related to the transition from a Reynolds-averaged state to one with resolved turbulent content. Improvements to the inflow conditions were suggested as a remedy to this dilemma. Second-order turbulence statistics were also compared to their modeled Reynolds-averaged counterparts to evaluate the effectiveness of common turbulence closure assumptions.

Stand age and climate drive forest carbon balance recovery

NASA Astrophysics Data System (ADS)

Besnard, Simon; Carvalhais, Nuno; Clevers, Jan; Herold, Martin; Jung, Martin; Reichstein, Markus

2016-04-01

Forests play an essential role in the terrestrial carbon (C) cycle, especially in the C exchanges between the terrestrial biosphere and the atmosphere. Ecological disturbances and forest management are drivers of forest dynamics and strongly impact the forest C budget. However, there is a lack of knowledge on the exogenous and endogenous factors driving forest C recovery. Our analysis includes 68 forest sites in different climate zones to determine the relative influence of stand age and climate conditions on the forest carbon balance recovery. In this study, we only included forest regrowth after clear-cut stand replacement (e.g. harvest, fire), and afforestation/reforestation processes. We synthesized net ecosystem production (NEP), gross primary production (GPP), ecosystem respiration (Re), the photosynthetic respiratory ratio (GPP to Re ratio), the ecosystem carbon use efficiency (CUE), that is NEP to GPP ratio, and CUEclimax, where GPP is derived from the climate conditions. We implemented a non-linear regression analysis in order to identify the best model representing the C flux patterns with stand age. Furthermore, we showed that each C flux have a non-linear relationship with stand age, annual precipitation (P) and mean annual temperature (MAT), therefore, we proposed to use non-linear transformations of the covariates for C fluxes'estimates. Non-linear stand age and climate models were, therefore, used to establish multiple linear regressions for C flux predictions and for determining the contribution of stand age and climate in forest carbon recovery. Our findings depicted that a coupled stand age-climate model explained 33% (44%, average site), 62% (76%, average site), 56% (71%, average site), 41% (59%, average site), 50% (65%, average site) and 36% (50%, average site) of the variance of annual NEP, GPP, Re, photosynthetic respiratory ratio, CUE and CUEclimax across sites, respectively. In addition, we showed that gross fluxes (e.g. GPP and Re) are mainly climatically driven with 54.2% (68.4%, average site) and 54.1% (71.0%, average site) of GPP and Re variability, respectively, explained by the sum of MAT and P. However, annual NEP, GPP to Re ratio and CUEclimax are affected by both forest stand age and climate conditions, in particular MAT. The key result is that forest stand age plays a crucial role in determining CUE (36.4% and 48.2% for all years per site and average site, respectively), while climate conditions have less effect on CUE (13.6% and 15.4% for all years per site and average site, respectively). These findings are relevant for the implementation of Earth system models and imply that information both on forest stand age and climate conditions are critical to improve the accuracy of global terrestrial C models's estimates.

The effects of ground hydrology on climate sensitivity to solar constant variations

NASA Technical Reports Server (NTRS)

Chou, S. H.; Curran, R. J.; Ohring, G.

1979-01-01

The effects of two different evaporation parameterizations on the climate sensitivity to solar constant variations are investigated by using a zonally averaged climate model. The model is based on a two-level quasi-geostrophic zonally averaged annual mean model. One of the evaporation parameterizations tested is a nonlinear formulation with the Bowen ratio determined by the predicted vertical temperature and humidity gradients near the earth's surface. The other is the linear formulation with the Bowen ratio essentially determined by the prescribed linear coefficient.

An Universal and Easy-to-Use Model for the Pressure of Arbitrary-Shape 3D Multifunctional Integumentary Cardiac Membranes.

PubMed

Su, Yewang; Liu, Zhuangjian; Xu, Lizhi

2016-04-20

Recently developed concepts for 3D, organ-mounted electronics for cardiac applications require a universal and easy-to-use mechanical model to calculate the average pressure associated with operation of the device, which is crucial for evaluation of design efficacy and optimization. This work proposes a simple, accurate, easy-to-use, and universal model to quantify the average pressure for arbitrary-shape organs. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Channel Characterization for Free-Space Optical Communications

DTIC Science & Technology

2012-07-01

parameters. From the path- average parameters, a 2nC profile model, called the HAP model, was constructed so that the entire channel from air to ground...SR), both of which are required to estimate the Power in the Bucket (PIB) and Power in the Fiber (PIF) associated with the FOENEX data beam. UCF was...of the path-average values of 2nC , the resulting HAP 2nC profile model led to values of ground level 2 nC that compared very well with actual

Developing and Testing a Robust, Multi-Scale Framework for the Recovery of Longleaf Pine Understory Communities

DTIC Science & Technology

2015-05-01

Model averaging for species richness on post-agricultural sites (1000 m2) with a landscape radius of 150 m. Table 3.4.8. Model selection for species ... richness on post-agricultural sites (1000 m2) with a landscape radius of 150 m. Table 3.4.9. Model averaging for proportion of reference species on...Direct, indirect, and total standardized effects on species richness . Table 4.1.1. Species and number of seeds added to the experimental plots at

Time series forecasting using ERNN and QR based on Bayesian model averaging

NASA Astrophysics Data System (ADS)

Pwasong, Augustine; Sathasivam, Saratha

2017-08-01

The Bayesian model averaging technique is a multi-model combination technique. The technique was employed to amalgamate the Elman recurrent neural network (ERNN) technique with the quadratic regression (QR) technique. The amalgamation produced a hybrid technique known as the hybrid ERNN-QR technique. The potentials of forecasting with the hybrid technique are compared with the forecasting capabilities of individual techniques of ERNN and QR. The outcome revealed that the hybrid technique is superior to the individual techniques in the mean square error sense.

Applications of Analytical Self-Similar Solutions of Reynolds-Averaged Models for Instability-Induced Turbulent Mixing

NASA Astrophysics Data System (ADS)

Hartland, Tucker; Schilling, Oleg

2017-11-01

Analytical self-similar solutions to several families of single- and two-scale, eddy viscosity and Reynolds stress turbulence models are presented for Rayleigh-Taylor, Richtmyer-Meshkov, and Kelvin-Helmholtz instability-induced turbulent mixing. The use of algebraic relationships between model coefficients and physical observables (e.g., experimental growth rates) following from the self-similar solutions to calibrate a member of a given family of turbulence models is shown. It is demonstrated numerically that the algebraic relations accurately predict the value and variation of physical outputs of a Reynolds-averaged simulation in flow regimes that are consistent with the simplifying assumptions used to derive the solutions. The use of experimental and numerical simulation data on Reynolds stress anisotropy ratios to calibrate a Reynolds stress model is briefly illustrated. The implications of the analytical solutions for future Reynolds-averaged modeling of hydrodynamic instability-induced mixing are briefly discussed. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

The effect of inquiry-flipped classroom model toward students' achievement on chemical reaction rate

NASA Astrophysics Data System (ADS)

Paristiowati, Maria; Fitriani, Ella; Aldi, Nurul Hanifah

2017-08-01

The aim of this research is to find out the effect of Inquiry-Flipped Classroom Models toward Students' Achievement on Chemical Reaction Rate topic. This study was conducted at SMA Negeri 3 Tangerang in Eleventh Graders. The Quasi Experimental Method with Non-equivalent Control Group design was implemented in this study. 72 students as the sample was selected by purposive sampling. Students in experimental group were learned through inquiry-flipped classroom model. Meanwhile, in control group, students were learned through guided inquiry learning model. Based on the data analysis, it can be seen that there is significant difference in the result of the average achievement of the students. The average achievement of the students in inquiry-flipped classroom model was 83,44 and the average achievement of the students in guided inquiry learning model was 74,06. It can be concluded that the students' achievement with inquiry-flipped classroom better than guided inquiry. The difference of students' achievement were significant through t-test which is tobs 3.056 > ttable 1.994 (α = 0.005).

Monthly streamflow forecasting with auto-regressive integrated moving average

NASA Astrophysics Data System (ADS)

Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

2017-09-01

Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

Vertical profiles for SO2 and SO on Venus from different one-dimensional simulations

NASA Astrophysics Data System (ADS)

Mills, Franklin P.; Jessup, Kandis-Lea; Yung, Yuk

2017-10-01

Sulfur dioxide (SO2) plays many roles in Venus’ atmosphere. It is a precursor for the sulfuric acid that condenses to form the global cloud layers and is likely a precursor for the unidentified UV absorber, which, along with CO2 near the tops of the clouds, appears to be responsible for absorbing about half of the energy deposited in Venus’ atmosphere [1]. Most published simulations of Venus’ mesospheric chemistry have used one-dimensional numerical models intended to represent global-average or diurnal-average conditions [eg, 2, 3, 4]. Observations, however, have found significant variations of SO and SO2 with latitude and local time throughout the mesosphere [eg, 5, 6]. Some recent simulations have examined local time variations of SO and SO2 using analytical models [5], one-dimensional steady-state solar-zenith-angle-dependent numerical models [6], and three-dimensional general circulation models (GCMs) [7]. As an initial step towards a quantitative comparison among these different types of models, this poster compares simulated SO, SO2, and SO/SO2 from global-average, diurnal-average, and solar-zenith-angle (SZA) dependent steady-state models for the mesosphere.The Caltech/JPL photochemical model [8] was used with vertical transport via eddy diffusion set based on observations and observationally-defined lower boundary conditions for HCl, CO, and OCS. Solar fluxes are based on SORCE SOLSTICE and SORCE SIM measurements from 26 December 2010 [9, 10]. The results indicate global-average and diurnal-average models may have significant limitations when used to interpret latitude- and local-time-dependent observations of SO2 and SO.[1] Titov D et al (2007) in Exploring Venus as a Terrestrial Planet, 121-138. [2] Zhang X et al (2012) Icarus, 217, 714-739. [3] Krasnopolsky V A (2012) Icarus, 218, 230-246. [4] Parkinson C D et al (2015) Planet Space Sci, 113-114, 226-236. [5] Sandor B J et al (2010) Icarus, 208, 49-60. [6] Jessup K-L et al (2015) Icarus, 258, 309-336. [7] Stolzenbach A et al (2014) EGU General Assembly 2014, 16, EGU2014-5315. [8] Allen M et al (1981) J Geophys Res, 86, 3617-3627. [9] Harder J W et al (2010) Sol Phys, 263, 3-24. [10] Snow M et al (2005) Sol Phys, 230, 295-324.

Isolating the cow-specific part of residual energy intake in lactating dairy cows using random regressions.

PubMed

Fischer, A; Friggens, N C; Berry, D P; Faverdin, P

2018-07-01

The ability to properly assess and accurately phenotype true differences in feed efficiency among dairy cows is key to the development of breeding programs for improving feed efficiency. The variability among individuals in feed efficiency is commonly characterised by the residual intake approach. Residual feed intake is represented by the residuals of a linear regression of intake on the corresponding quantities of the biological functions that consume (or release) energy. However, the residuals include both, model fitting and measurement errors as well as any variability in cow efficiency. The objective of this study was to isolate the individual animal variability in feed efficiency from the residual component. Two separate models were fitted, in one the standard residual energy intake (REI) was calculated as the residual of a multiple linear regression of lactation average net energy intake (NEI) on lactation average milk energy output, average metabolic BW, as well as lactation loss and gain of body condition score. In the other, a linear mixed model was used to simultaneously fit fixed linear regressions and random cow levels on the biological traits and intercept using fortnight repeated measures for the variables. This method split the predicted NEI in two parts: one quantifying the population mean intercept and coefficients, and one quantifying cow-specific deviations in the intercept and coefficients. The cow-specific part of predicted NEI was assumed to isolate true differences in feed efficiency among cows. NEI and associated energy expenditure phenotypes were available for the first 17 fortnights of lactation from 119 Holstein cows; all fed a constant energy-rich diet. Mixed models fitting cow-specific intercept and coefficients to different combinations of the aforementioned energy expenditure traits, calculated on a fortnightly basis, were compared. The variance of REI estimated with the lactation average model represented only 8% of the variance of measured NEI. Among all compared mixed models, the variance of the cow-specific part of predicted NEI represented between 53% and 59% of the variance of REI estimated from the lactation average model or between 4% and 5% of the variance of measured NEI. The remaining 41% to 47% of the variance of REI estimated with the lactation average model may therefore reflect model fitting errors or measurement errors. In conclusion, the use of a mixed model framework with cow-specific random regressions seems to be a promising method to isolate the cow-specific component of REI in dairy cows.

Numerical investigation of airflow in an idealised human extra-thoracic airway: a comparison study

PubMed Central

Chen, Jie; Gutmark, Ephraim

2013-01-01

Large eddy simulation (LES) technique is employed to numerically investigate the airflow through an idealised human extra-thoracic airway under different breathing conditions, 10 l/min, 30 l/min, and 120 l/min. The computational results are compared with single and cross hot-wire measurements, and with time-averaged flow field computed by standard k-ω and k-ω-SST Reynolds averaged Navier-Stokes (RANS) models and the Lattice-Boltzmann method (LBM). The LES results are also compared to root-mean-square (RMS) flow field computed by the Reynolds stress model (RSM) and LBM. LES generally gives better prediction of the time-averaged flow field than RANS models and LBM. LES also provides better estimation of the RMS flow field than both the RSM and the LBM. PMID:23619907

Optimal firing rate estimation

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

2001-01-01

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

Quantifying predictability variations in a low-order ocean-atmosphere model - A dynamical systems approach

NASA Technical Reports Server (NTRS)

Nese, Jon M.; Dutton, John A.

1993-01-01

The predictability of the weather and climatic states of a low-order moist general circulation model is quantified using a dynamic systems approach, and the effect of incorporating a simple oceanic circulation on predictability is evaluated. The predictability and the structure of the model attractors are compared using Liapunov exponents, local divergence rates, and the correlation and Liapunov dimensions. It was found that the activation of oceanic circulation increases the average error doubling time of the atmosphere and the coupled ocean-atmosphere system by 10 percent and decreases the variance of the largest local divergence rate by 20 percent. When an oceanic circulation develops, the average predictability of annually averaged states is improved by 25 percent and the variance of the largest local divergence rate decreases by 25 percent.

Averaged model to study long-term dynamics of a probe about Mercury

NASA Astrophysics Data System (ADS)

Tresaco, Eva; Carvalho, Jean Paulo S.; Prado, Antonio F. B. A.; Elipe, Antonio; de Moraes, Rodolpho Vilhena

2018-02-01

This paper provides a method for finding initial conditions of frozen orbits for a probe around Mercury. Frozen orbits are those whose orbital elements remain constant on average. Thus, at the same point in each orbit, the satellite always passes at the same altitude. This is very interesting for scientific missions that require close inspection of any celestial body. The orbital dynamics of an artificial satellite about Mercury is governed by the potential attraction of the main body. Besides the Keplerian attraction, we consider the inhomogeneities of the potential of the central body. We include secondary terms of Mercury gravity field from J_2 up to J_6, and the tesseral harmonics \\overline{C}_{22} that is of the same magnitude than zonal J_2. In the case of science missions about Mercury, it is also important to consider third-body perturbation (Sun). Circular restricted three body problem can not be applied to Mercury-Sun system due to its non-negligible orbital eccentricity. Besides the harmonics coefficients of Mercury's gravitational potential, and the Sun gravitational perturbation, our average model also includes Solar acceleration pressure. This simplified model captures the majority of the dynamics of low and high orbits about Mercury. In order to capture the dominant characteristics of the dynamics, short-period terms of the system are removed applying a double-averaging technique. This algorithm is a two-fold process which firstly averages over the period of the satellite, and secondly averages with respect to the period of the third body. This simplified Hamiltonian model is introduced in the Lagrange Planetary equations. Thus, frozen orbits are characterized by a surface depending on three variables: the orbital semimajor axis, eccentricity and inclination. We find frozen orbits for an average altitude of 400 and 1000 km, which are the predicted values for the BepiColombo mission. Finally, the paper delves into the orbital stability of frozen orbits and the temporal evolution of the eccentricity of these orbits.

Maximum likelihood estimation for periodic autoregressive moving average models

USGS Publications Warehouse

Vecchia, A.V.

1985-01-01

A useful class of models for seasonal time series that cannot be filtered or standardized to achieve second-order stationarity is that of periodic autoregressive moving average (PARMA) models, which are extensions of ARMA models that allow periodic (seasonal) parameters. An approximation to the exact likelihood for Gaussian PARMA processes is developed, and a straightforward algorithm for its maximization is presented. The algorithm is tested on several periodic ARMA(1, 1) models through simulation studies and is compared to moment estimation via the seasonal Yule-Walker equations. Applicability of the technique is demonstrated through an analysis of a seasonal stream-flow series from the Rio Caroni River in Venezuela.

Evaluation of Observation-Fused Regional Air Quality Model Results for Population Air Pollution Exposure Estimation

PubMed Central

Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

2014-01-01

In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRR regions are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

The impact of reforestation in the northeast United States on precipitation and surface temperature

NASA Astrophysics Data System (ADS)

Clark, Allyson

Since the 1920s, forest coverage in the northeastern United States has recovered from disease, clearing for agricultural and urban development, and the demands of the timber industry. Such a dramatic change in ground cover can influence heat and moisture fluxes to the atmosphere, as measured in altered landscapes in Australia, Israel, and the Amazon. In this study, the impacts of recent reforestation in the northeastern United States on summertime precipitation and surface temperature were quantified by comparing average modern values to 1950s values. Weak positive (negative) relationships between reforestation and average monthly precipitation and daily minimum temperatures (average daily maximum surface temperature) were found. There was no relationship between reforestation and average surface temperature. Results of the observational analysis were compared with results obtained from reforestation scenarios simulated with the BUGS5 global climate model. The single difference between the model runs was the amount of forest coverage in the northeast United States; three levels of forest were defined - a grassland state, with 0% forest coverage, a completely forested state, with approximately 100% forest coverage, and a control state, with forest coverage closely resembling modern forest coverage. The three simulations were compared, and had larger magnitude average changes in precipitation and in all temperature variables. The difference in magnitudes between the model simulations observations was much larger than the difference in the amount of reforestation in each case. Additionally, unlike in observations, a negative relationship was found between average daily minimum temperature and amount of forest coverage, implying that additional factors influence temperature and precipitation in the real world that are not accounted for in the model.

An Interactive Multi-Model for Consensus on Climate Change

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

Kocarev, Ljupco

This project purports to develop a new scheme for forming consensus among alternative climate models, that give widely divergent projections as to the details of climate change, that is more intelligent than simply averaging the model outputs, or averaging with ex post facto weighting factors. The method under development effectively allows models to assimilate data from one another in run time with weights that are chosen in an adaptive training phase using 20th century data, so that the models synchronize with one another as well as with reality. An alternate approach that is being explored in parallel is the automatedmore » combination of equations from different models in an expert-system-like framework.« less

Quantification of errors induced by temporal resolution on Lagrangian particles in an eddy-resolving model

NASA Astrophysics Data System (ADS)

Qin, Xuerong; van Sebille, Erik; Sen Gupta, Alexander

2014-04-01

Lagrangian particle tracking within ocean models is an important tool for the examination of ocean circulation, ventilation timescales and connectivity and is increasingly being used to understand ocean biogeochemistry. Lagrangian trajectories are obtained by advecting particles within velocity fields derived from hydrodynamic ocean models. For studies of ocean flows on scales ranging from mesoscale up to basin scales, the temporal resolution of the velocity fields should ideally not be more than a few days to capture the high frequency variability that is inherent in mesoscale features. However, in reality, the model output is often archived at much lower temporal resolutions. Here, we quantify the differences in the Lagrangian particle trajectories embedded in velocity fields of varying temporal resolution. Particles are advected from 3-day to 30-day averaged fields in a high-resolution global ocean circulation model. We also investigate whether adding lateral diffusion to the particle movement can compensate for the reduced temporal resolution. Trajectory errors reveal the expected degradation of accuracy in the trajectory positions when decreasing the temporal resolution of the velocity field. Divergence timescales associated with averaging velocity fields up to 30 days are faster than the intrinsic dispersion of the velocity fields but slower than the dispersion caused by the interannual variability of the velocity fields. In experiments focusing on the connectivity along major currents, including western boundary currents, the volume transport carried between two strategically placed sections tends to increase with increased temporal averaging. Simultaneously, the average travel times tend to decrease. Based on these two bulk measured diagnostics, Lagrangian experiments that use temporal averaging of up to nine days show no significant degradation in the flow characteristics for a set of six currents investigated in more detail. The addition of random-walk-style diffusion does not mitigate the errors introduced by temporal averaging for large-scale open ocean Lagrangian simulations.

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

Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo; Craig, Tim

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and appliedmore » three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR weight prediction methodologies perform comparably to the LR model and can produce clinical quality treatment plans by simultaneously predicting multiple weights that capture trade-offs associated with sparing multiple OARs.« less

Combining NMR spectral and structural data to form models of polychlorinated dibenzodioxins, dibenzofurans, and biphenyls binding to the AhR

NASA Astrophysics Data System (ADS)

Beger, Richard D.; Buzatu, Dan A.; Wilkes, Jon G.

2002-10-01

A three-dimensional quantitative spectrometric data-activity relationship (3D-QSDAR) modeling technique which uses NMR spectral and structural information that is combined in a 3D-connectivity matrix has been developed. A 3D-connectivity matrix was built by displaying all possible assigned carbon NMR chemical shifts, carbon-to-carbon connections, and distances between the carbons. Two-dimensional 13C-13C COSY and 2D slices from the distance dimension of the 3D-connectivity matrix were used to produce a relationship among the 2D spectral patterns for polychlorinated dibenzofurans, dibenzodioxins, and biphenyls (PCDFs, PCDDs, and PCBs respectively) binding to the aryl hydrocarbon receptor (AhR). We refer to this technique as comparative structural connectivity spectral analysis (CoSCoSA) modeling. All CoSCoSA models were developed using forward multiple linear regression analysis of the predicted 13C NMR structure-connectivity spectral bins. A CoSCoSA model for 26 PCDFs had an explained variance (r2) of 0.93 and an average leave-four-out cross-validated variance (q4 2) of 0.89. A CoSCoSA model for 14 PCDDs produced an r2 of 0.90 and an average leave-two-out cross-validated variance (q2 2) of 0.79. One CoSCoSA model for 12 PCBs gave an r2 of 0.91 and an average q2 2 of 0.80. Another CoSCoSA model for all 52 compounds had an r2 of 0.85 and an average q4 2 of 0.52. Major benefits of CoSCoSA modeling include ease of development since the technique does not use molecular docking routines.

Mantle structure and composition to 800-km depth beneath southern Africa and surrounding oceans from broadband body waves

NASA Astrophysics Data System (ADS)

Simon, R. E.; Wright, C.; Kwadiba, M. T. O.; Kgaswane, E. M.

2003-12-01

Average one-dimensional P and S wavespeed models from the surface to depths of 800 km were derived for the southern African region using travel times and waveforms from earthquakes recorded at stations of the Kaapvaal and South African seismic networks. The Herglotz-Wiechert method combined with ray tracing was used to derive a preliminary P wavespeed model, followed by refinements using phase-weighted stacking and synthetic seismograms to yield the final model. Travel times combined with ray tracing were used to derive the S wavespeed model, which was also refined using phase-weighted stacking and synthetic seismograms. The presence of a high wavespeed upper mantle lid in the S model overlying a low wavespeed zone (LWZ) around 210- to ˜345-km depth that is not observed in the P wavespeed model was inferred. The 410-km discontinuity shows similar characteristics to that in other continental regions, but occurs slightly deeper at 420 km. Depletion of iron and/or enrichment in aluminium relative to other regions are the preferred explanation, since the P wavespeeds throughout the transition zone are slightly higher than average. The average S wavespeed structure beneath southern Africa within and below the transition zone is similar to that of the IASP91 model. There is no evidence for discontinuity at 520-km depth. The 660-km discontinuity also appears to be slightly deeper than average (668 km), although the estimated thickness of the transition zone is 248 km, similar to the global average of 241 km. The small size of the 660-km discontinuity for P waves, compared with many other regions, suggests that interpretation of the discontinuity as the transformation of spinel to perovskite and magnesiowüstite may require modification. Alternative explanations include the presence of garnetite-rich material or ilmenite-forming phase transformations above the 660-km discontinuity, and the garnet-perovskite transformation as the discontinuity.

Physical Models of Layered Polar Firn Brightness Temperatures from 0.5 to 2 GHz

NASA Technical Reports Server (NTRS)

Tan, Shurun; Aksoy, Mustafa; Brogioni, Marco; Macelloni, Giovanni; Durand, Michael; Jezek, Kenneth C.; Wang, Tian-Lin; Tsang, Leung; Johnson, Joel T.; Drinkwater, Mark R.;

Ensemble Averaged Probability Density Function (APDF) for Compressible Turbulent Reacting Flows

NASA Technical Reports Server (NTRS)

Shih, Tsan-Hsing; Liu, Nan-Suey

2012-01-01

In this paper, we present a concept of the averaged probability density function (APDF) for studying compressible turbulent reacting flows. The APDF is defined as an ensemble average of the fine grained probability density function (FG-PDF) with a mass density weighting. It can be used to exactly deduce the mass density weighted, ensemble averaged turbulent mean variables. The transport equation for APDF can be derived in two ways. One is the traditional way that starts from the transport equation of FG-PDF, in which the compressible Navier- Stokes equations are embedded. The resulting transport equation of APDF is then in a traditional form that contains conditional means of all terms from the right hand side of the Navier-Stokes equations except for the chemical reaction term. These conditional means are new unknown quantities that need to be modeled. Another way of deriving the transport equation of APDF is to start directly from the ensemble averaged Navier-Stokes equations. The resulting transport equation of APDF derived from this approach appears in a closed form without any need for additional modeling. The methodology of ensemble averaging presented in this paper can be extended to other averaging procedures: for example, the Reynolds time averaging for statistically steady flow and the Reynolds spatial averaging for statistically homogeneous flow. It can also be extended to a time or spatial filtering procedure to construct the filtered density function (FDF) for the large eddy simulation (LES) of compressible turbulent reacting flows.

The abundances of hydrogen, helium, oxygen, and iron accelerated in large solar particle events

NASA Technical Reports Server (NTRS)

Mazur, J. E.; Mason, G. M.; Klecker, B.; Mcguire, R. E.

1993-01-01

Energy spectra measured in 10 large flares with the University of Maryland/Max-Planck-Institut sensors on ISEE I and Goddard Space Flight Center sensors on IMP 8 allowed us to determine the average H, He, O, and Fe abundances as functions of energy in the range of about 0.3-80 MeV/nucleon. Model fits to the spectra of individual events using the predictions of a steady state stochastic acceleration model with rigidity-dependent diffusion provided a means of interpolating small portions of the energy spectra not measured with the instrumentation. Particles with larger mass-to-charge ratios were relatively less abundant at higher energies in the flare-averaged composition. The Fe/O enhancement at low SEP energies was less than the Fe/O ratios observed in He-3-rich flares. Unlike the SEP composition averaged above 5 MeV/nucleon, the average SEP abundances above 0.3 MeV/nucleon were similar to the average solar wind.

Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions

DOE PAGES

Syamlal, Madhava; Celik, Ismail B.; Benyahia, Sofiane

2017-07-12

The two-fluid model (TFM) has become a tool for the design and troubleshooting of industrial fluidized bed reactors. To use TFM for scale up with confidence, the uncertainty in its predictions must be quantified. Here, we study two sources of uncertainty: discretization and time-averaging. First, we show that successive grid refinement may not yield grid-independent transient quantities, including cross-section–averaged quantities. Successive grid refinement would yield grid-independent time-averaged quantities on sufficiently fine grids. A Richardson extrapolation can then be used to estimate the discretization error, and the grid convergence index gives an estimate of the uncertainty. Richardson extrapolation may not workmore » for industrial-scale simulations that use coarse grids. We present an alternative method for coarse grids and assess its ability to estimate the discretization error. Second, we assess two methods (autocorrelation and binning) and find that the autocorrelation method is more reliable for estimating the uncertainty introduced by time-averaging TFM data.« less

Planning and Management of Faculty Resources. AIR Forum 1981 Paper.

ERIC Educational Resources Information Center

Montgomery, James R.; And Others

A computerized faculty allocation and reallocation model is presented to aid the decision maker in evaluating the outcomes of various strategies. A unique goal can be computed for each department based on the average index of the institution, the average of the college, the preceding average of the department, and a goal established by management…

A benefit-cost analysis of ten tree species in Modesto, California, U.S.A

Treesearch

E.G. McPherson

2003-01-01

Tree work records for ten species were analyzed to estimate average annual management costs by dbh class for six activity areas. Average annual benefits were calculated by dbh class for each species with computer modeling. Average annual net benefits per tree were greatest for London plane (Platanus acerifolia) ($178.57), hackberry (...

Pricing and Enrollment Planning.

ERIC Educational Resources Information Center

Martin, Robert E.

2003-01-01

Presents a management model for pricing and enrollment planning that yields optimal pricing decisions relative to student fees and average scholarship, the institution's financial ability to support students, and an average cost-pricing rule. (SLD)

Predicting top-of-atmosphere radiance for arbitrary viewing geometries from the visible to thermal infrared: generalization to arbitrary average scene temperatures

NASA Astrophysics Data System (ADS)

Florio, Christopher J.; Cota, Steve A.; Gaffney, Stephanie K.

2010-08-01

In a companion paper presented at this conference we described how The Aerospace Corporation's Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) may be used in conjunction with a limited number of runs of AFRL's MODTRAN4 radiative transfer code, to quickly predict the top-of-atmosphere (TOA) radiance received in the visible through midwave IR (MWIR) by an earth viewing sensor, for any arbitrary combination of solar and sensor elevation angles. The method is particularly useful for large-scale scene simulations where each pixel could have a unique value of reflectance/emissivity and temperature, making the run-time required for direct prediction via MODTRAN4 prohibitive. In order to be self-consistent, the method described requires an atmospheric model (defined, at a minimum, as a set of vertical temperature, pressure and water vapor profiles) that is consistent with the average scene temperature. MODTRAN4 provides only six model atmospheres, ranging from sub-arctic winter to tropical conditions - too few to cover with sufficient temperature resolution the full range of average scene temperatures that might be of interest. Model atmospheres consistent with intermediate temperature values can be difficult to come by, and in any event, their use would be too cumbersome for use in trade studies involving a large number of average scene temperatures. In this paper we describe and assess a method for predicting TOA radiance for any arbitrary average scene temperature, starting from only a limited number of model atmospheres.

Comparing CT perfusion with oxygen partial pressure in a rabbit VX2 soft-tissue tumor model.

PubMed

Sun, Chang-Jin; Li, Chao; Lv, Hai-Bo; Zhao, Cong; Yu, Jin-Ming; Wang, Guang-Hui; Luo, Yun-Xiu; Li, Yan; Xiao, Mingyong; Yin, Jun; Lang, Jin-Yi

2014-01-01

The aim of this study was to evaluate the oxygen partial pressure of the rabbit model of the VX2 tumor using a 64-slice perfusion CT and to compare the results with that obtained using the oxygen microelectrode method. Perfusion CT was performed for 45 successfully constructed rabbit models of a VX2 brain tumor. The perfusion values of the brain tumor region of interest, the blood volume (BV), the time to peak (TTP) and the peak enhancement intensity (PEI) were measured. The results were compared with the partial pressure of oxygen (PO2) of that region of interest obtained using the oxygen microelectrode method. The perfusion values of the brain tumor region of interest in 45 successfully constructed rabbit models of a VX2 brain tumor ranged from 1.3-127.0 (average, 21.1 ± 26.7 ml/min/ml); BV ranged from 1.2-53.5 ml/100g (average, 22.2 ± 13.7 ml/100g); PEI ranged from 8.7-124.6 HU (average, 43.5 ± 28.7 HU); and TTP ranged from 8.2-62.3 s (average, 38.8 ± 14.8 s). The PO2 in the corresponding region ranged from 0.14-47 mmHg (average, 16 ± 14.8 mmHg). The perfusion CT positively correlated with the tumor PO2, which can be used for evaluating the tumor hypoxia in clinical practice.

A geometrical optics approach for modeling aperture averaging in free space optical communication applications

NASA Astrophysics Data System (ADS)

Yuksel, Heba; Davis, Christopher C.

2006-09-01

Intensity fluctuations at the receiver in free space optical (FSO) communication links lead to a received power variance that depends on the size of the receiver aperture. Increasing the size of the receiver aperture reduces the power variance. This effect of the receiver size on power variance is called aperture averaging. If there were no aperture size limitation at the receiver, then there would be no turbulence-induced scintillation. In practice, there is always a tradeoff between aperture size, transceiver weight, and potential transceiver agility for pointing, acquisition and tracking (PAT) of FSO communication links. We have developed a geometrical simulation model to predict the aperture averaging factor. This model is used to simulate the aperture averaging effect at given range by using a large number of rays, Gaussian as well as uniformly distributed, propagating through simulated turbulence into a circular receiver of varying aperture size. Turbulence is simulated by filling the propagation path with spherical bubbles of varying sizes and refractive index discontinuities statistically distributed according to various models. For each statistical representation of the atmosphere, the three-dimensional trajectory of each ray is analyzed using geometrical optics. These Monte Carlo techniques have proved capable of assessing the aperture averaging effect, in particular, the quantitative expected reduction in intensity fluctuations with increasing aperture diameter. In addition, beam wander results have demonstrated the range-cubed dependence of mean-squared beam wander. An effective turbulence parameter can also be determined by correlating beam wander behavior with the path length.

A model-averaging method for assessing groundwater conceptual model uncertainty.

PubMed

Ye, Ming; Pohlmann, Karl F; Chapman, Jenny B; Pohll, Greg M; Reeves, Donald M

2010-01-01

This study evaluates alternative groundwater models with different recharge and geologic components at the northern Yucca Flat area of the Death Valley Regional Flow System (DVRFS), USA. Recharge over the DVRFS has been estimated using five methods, and five geological interpretations are available at the northern Yucca Flat area. Combining the recharge and geological components together with additional modeling components that represent other hydrogeological conditions yields a total of 25 groundwater flow models. As all the models are plausible given available data and information, evaluating model uncertainty becomes inevitable. On the other hand, hydraulic parameters (e.g., hydraulic conductivity) are uncertain in each model, giving rise to parametric uncertainty. Propagation of the uncertainty in the models and model parameters through groundwater modeling causes predictive uncertainty in model predictions (e.g., hydraulic head and flow). Parametric uncertainty within each model is assessed using Monte Carlo simulation, and model uncertainty is evaluated using the model averaging method. Two model-averaging techniques (on the basis of information criteria and GLUE) are discussed. This study shows that contribution of model uncertainty to predictive uncertainty is significantly larger than that of parametric uncertainty. For the recharge and geological components, uncertainty in the geological interpretations has more significant effect on model predictions than uncertainty in the recharge estimates. In addition, weighted residuals vary more for the different geological models than for different recharge models. Most of the calibrated observations are not important for discriminating between the alternative models, because their weighted residuals vary only slightly from one model to another.

Metainference: A Bayesian inference method for heterogeneous systems

PubMed Central

Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele

2016-01-01

Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called “metainference,” that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors. PMID:26844300

Impact of Bias-Correction Type and Conditional Training on Bayesian Model Averaging over the Northeast United States

Treesearch

Michael J. Erickson; Brian A. Colle; Joseph J. Charney

2012-01-01

The performance of a multimodel ensemble over the northeast United States is evaluated before and after applying bias correction and Bayesian model averaging (BMA). The 13-member Stony Brook University (SBU) ensemble at 0000 UTC is combined with the 21-member National Centers for Environmental Prediction (NCEP) Short-Range Ensemble Forecast (SREF) system at 2100 UTC....

Predicting Student Grade Point Average at a Community College from Scholastic Aptitude Tests and from Measures Representing Three Constructs in Vroom's Expectancy Theory Model of Motivation.

ERIC Educational Resources Information Center

Malloch, Douglas C.; Michael, William B.

1981-01-01

This study was designed to determine whether an unweighted linear combination of community college students' scores on standardized achievement tests and a measure of motivational constructs derived from Vroom's expectance theory model of motivation was predictive of academic success (grade point average earned during one quarter of an academic…

Implementation of ICARE learning model using visualization animation on biotechnology course

NASA Astrophysics Data System (ADS)

Hidayat, Habibi

2017-12-01

ICARE is a learning model that directly ensure the students to actively participate in the learning process using animation media visualization. ICARE have five key elements of learning experience from children and adult that is introduction, connection, application, reflection and extension. The use of Icare system to ensure that participants have opportunity to apply what have been they learned. So that, the message delivered by lecture to students can be understood and recorded by students in a long time. Learning model that was deemed capable of improving learning outcomes and interest to learn in following learning process Biotechnology with applying the ICARE learning model using visualization animation. This learning model have been giving motivation to participate in the learning process and learning outcomes obtained becomes more increased than before. From the results of student learning in subjects Biotechnology by applying the ICARE learning model using Visualization Animation can improving study results of student from the average value of middle test amounted to 70.98 with the percentage of 75% increased value of final test to be 71.57 with the percentage of 68.63%. The interest to learn from students more increasing visits of student activities at each cycle, namely the first cycle obtained average value by 33.5 with enough category. The second cycle is obtained an average value of 36.5 to good category and third cycle the average value of 36.5 with a student activity to good category.

Local and average structure of Mn- and La-substituted BiFeO3

NASA Astrophysics Data System (ADS)

Jiang, Bo; Selbach, Sverre M.

2017-06-01

The local and average structure of solid solutions of the multiferroic perovskite BiFeO3 is investigated by synchrotron X-ray diffraction (XRD) and electron density functional theory (DFT) calculations. The average experimental structure is determined by Rietveld refinement and the local structure by total scattering data analyzed in real space with the pair distribution function (PDF) method. With equal concentrations of La on the Bi site or Mn on the Fe site, La causes larger structural distortions than Mn. Structural models based on DFT relaxed geometry give an improved fit to experimental PDFs compared to models constrained by the space group symmetry. Berry phase calculations predict a higher ferroelectric polarization than the experimental literature values, reflecting that structural disorder is not captured in either average structure space group models or DFT calculations with artificial long range order imposed by periodic boundary conditions. Only by including point defects in a supercell, here Bi vacancies, can DFT calculations reproduce the literature results on the structure and ferroelectric polarization of Mn-substituted BiFeO3. The combination of local and average structure sensitive experimental methods with DFT calculations is useful for illuminating the structure-property-composition relationships in complex functional oxides with local structural distortions.

Quantifying the association between obesity, automobile travel, and caloric intake.

PubMed

Behzad, Banafsheh; King, Douglas M; Jacobson, Sheldon H

2013-02-01

The objective of this study is to assess the association between average adult body mass index (BMI), automobile travel, and caloric intake in the US in order to predict future trends of adult obesity. Annual BMI data (1984-2010) from the Behavioral Risk Factor Surveillance System (BRFSS), vehicle miles traveled data (1970-2009) from the Federal Highway Administration, licensed drivers data (1970-2009) from the Federal Highway Administration, and adult average daily caloric intake data (1970-2009) from the US Department of Agriculture were collected. A statistical model is proposed to capture multicollinearity across the independent variables. The proposed statistical model provides an estimate of changes in the average adult BMI associated with changes in automobile travel and caloric intake. According to this model, reducing daily automobile travel by one mile per driver would be associated with a 0.21 kg/m(2) reduction in the national average BMI after six years. Reducing daily caloric intake by 100 calories per person would be associated with a 0.16 kg/m(2) reduction in the national average BMI after three years. Making small changes in travel or diet choices may lead to comparable obesity interventions, implying that travel-based interventions may be as effective as dietary interventions. Copyright © 2012 Elsevier Inc. All rights reserved.

Econophysics of adaptive power markets: When a market does not dampen fluctuations but amplifies them

NASA Astrophysics Data System (ADS)

Krause, Sebastian M.; Börries, Stefan; Bornholdt, Stefan

2015-07-01

The average economic agent is often used to model the dynamics of simple markets, based on the assumption that the dynamics of a system of many agents can be averaged over in time and space. A popular idea that is based on this seemingly intuitive notion is to dampen electric power fluctuations from fluctuating sources (as, e.g., wind or solar) via a market mechanism, namely by variable power prices that adapt demand to supply. The standard model of an average economic agent predicts that fluctuations are reduced by such an adaptive pricing mechanism. However, the underlying assumption that the actions of all agents average out on the time axis is not always true in a market of many agents. We numerically study an econophysics agent model of an adaptive power market that does not assume averaging a priori. We find that when agents are exposed to source noise via correlated price fluctuations (as adaptive pricing schemes suggest), the market may amplify those fluctuations. In particular, small price changes may translate to large load fluctuations through catastrophic consumer synchronization. As a result, an adaptive power market may cause the opposite effect than intended: Power demand fluctuations are not dampened but amplified instead.

Local and average structure of Mn- and La-substituted BiFeO 3

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

Jiang, Bo; Selbach, Sverre M.

2017-06-01

The local and average structure of solid solutions of the multiferroic perovskite BiFeO 3 is investigated by synchrotron X-ray diffraction (XRD) and electron density functional theory (DFT) calculations. The average experimental structure is determined by Rietveld refinement and the local structure by total scattering data analyzed in real space with the pair distribution function (PDF) method. With equal concentrations of La on the Bi site or Mn on the Fe site, La causes larger structural distortions than Mn. Structural models based on DFT relaxed geometry give an improved fit to experimental PDFs compared to models constrained by the space groupmore » symmetry. Berry phase calculations predict a higher ferroelectric polarization than the experimental literature values, reflecting that structural disorder is not captured in either average structure space group models or DFT calculations with artificial long range order imposed by periodic boundary conditions. Only by including point defects in a supercell, here Bi vacancies, can DFT calculations reproduce the literature results on the structure and ferroelectric polarization of Mn-substituted BiFeO 3. The combination of local and average structure sensitive experimental methods with DFT calculations is useful for illuminating the structure-property-composition relationships in complex functional oxides with local structural distortions.« less

A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China

PubMed Central

Li, Huashan; Cao, Fei; Wang, Xianlong; Ma, Weibin

2014-01-01

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China. PMID:24605046

Model uncertainty and multimodel inference in reliability estimation within a longitudinal framework.

PubMed

Alonso, Ariel; Laenen, Annouschka

2013-05-01

Laenen, Alonso, and Molenberghs (2007) and Laenen, Alonso, Molenberghs, and Vangeneugden (2009) proposed a method to assess the reliability of rating scales in a longitudinal context. The methodology is based on hierarchical linear models, and reliability coefficients are derived from the corresponding covariance matrices. However, finding a good parsimonious model to describe complex longitudinal data is a challenging task. Frequently, several models fit the data equally well, raising the problem of model selection uncertainty. When model uncertainty is high one may resort to model averaging, where inferences are based not on one but on an entire set of models. We explored the use of different model building strategies, including model averaging, in reliability estimation. We found that the approach introduced by Laenen et al. (2007, 2009) combined with some of these strategies may yield meaningful results in the presence of high model selection uncertainty and when all models are misspecified, in so far as some of them manage to capture the most salient features of the data. Nonetheless, when all models omit prominent regularities in the data, misleading results may be obtained. The main ideas are further illustrated on a case study in which the reliability of the Hamilton Anxiety Rating Scale is estimated. Importantly, the ambit of model selection uncertainty and model averaging transcends the specific setting studied in the paper and may be of interest in other areas of psychometrics. © 2012 The British Psychological Society.

Sources of secondary organic aerosols over North China Plain in winter

NASA Astrophysics Data System (ADS)

Xing, L.; Li, G.; Tie, X.; Junji, C.; Long, X.

2017-12-01

Organic aerosol (OA) concentrations are simulated over the North China Plain (NCP) from 10th to 26th January, 2014 using the Weather Research and Forecasting model coupled to chemistry (WRF-CHEM), with the goal of examining the impact of heterogeneous HONO sources on atmospheric oxidation capacity and consequently on SOA formation and SOA formation from different pathways in winter. Generally, the model well reproduced the spatial and temporal distribution of PM2.5, SO2, NO2, and O3 concentrations. The heterogeneous HONO formation contributed a major part of atmospheric HONO concentrations in Beijing. The heterogeneous HONO sources significantly increased the daily maximum OH concentrations by 260% on average in Beijing, which enhanced the atmospheric oxidation capacity and consequently SOA concentrations by 80% in Beijing on average. Under severe haze pollution on January 16th 2014, the regional average HONO concentration over NCP was 0.86 ppb, which increased SOA concentration by 68% on average. The average mass fractions of ASOA (SOA from oxidation of anthropogenic VOCs), BSOA (SOA from oxidation of biogenic VOCs), PSOA (SOA from oxidation of evaporated POA), and GSOA (SOA from irreversible uptake of glyoxal and methylglyoxal) during the simulation period over NCP were 24%, 5%, 26% and 45%, respectively. GSOA contributed most to the total SOA mass over NCP in winter. The model sensitivity simulation revealed that GSOA in winter was mainly from primary residential sources. The regional average of GSOA from primary residential sources constituted 87% of total GSOA mass.

Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties

NASA Astrophysics Data System (ADS)

Exbrayat, Jean-François; Bloom, A. Anthony; Falloon, Pete; Ito, Akihiko; Smallman, T. Luke; Williams, Mathew

2018-02-01

Multi-model averaging techniques provide opportunities to extract additional information from large ensembles of simulations. In particular, present-day model skill can be used to evaluate their potential performance in future climate simulations. Multi-model averaging methods have been used extensively in climate and hydrological sciences, but they have not been used to constrain projected plant productivity responses to climate change, which is a major uncertainty in Earth system modelling. Here, we use three global observationally orientated estimates of current net primary productivity (NPP) to perform a reliability ensemble averaging (REA) method using 30 global simulations of the 21st century change in NPP based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) business as usual emissions scenario. We find that the three REA methods support an increase in global NPP by the end of the 21st century (2095-2099) compared to 2001-2005, which is 2-3 % stronger than the ensemble ISIMIP mean value of 24.2 Pg C y-1. Using REA also leads to a 45-68 % reduction in the global uncertainty of 21st century NPP projection, which strengthens confidence in the resilience of the CO2 fertilization effect to climate change. This reduction in uncertainty is especially clear for boreal ecosystems although it may be an artefact due to the lack of representation of nutrient limitations on NPP in most models. Conversely, the large uncertainty that remains on the sign of the response of NPP in semi-arid regions points to the need for better observations and model development in these regions.