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We encourage you to perform a real-time search of NLEBeta
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1

Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction  

E-Print Network [OSTI]

. Current weather radar detection and prediction sys- tems primarily rely on numerical models. We proposeOpen problem: Dynamic Relational Models for Improved Hazardous Weather Prediction Amy McGovern1, #12;Dynamic Relational Models for Improved Hazardous Weather Prediction Radar velocity Radar

McGovern, Amy

2

A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting  

E-Print Network [OSTI]

MultiscaleNumericalWeatherPredictionModel. Progressassimilatingnumericalweatherpredictionmodelforsolarcustomizable numericalweatherpredictionmodelthatis

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

3

Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction  

E-Print Network [OSTI]

Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction Supervisors). Background: Numerical Weather Prediction (NWP) has seen significant gains in accuracy in recent years due is directed at achieving real-world impact in numerical weather prediction by addressing fundamental issues

Wirosoetisno, Djoko

4

Forecasting wave height probabilities with numerical weather prediction models  

E-Print Network [OSTI]

Forecasting wave height probabilities with numerical weather prediction models Mark S. Roulstona; Numerical weather prediction 1. Introduction Wave forecasting is now an integral part of operational weather methods for generating such forecasts from numerical model output from the European Centre for Medium

Stevenson, Paul

5

Weather Regime Prediction Using Statistical Learning  

E-Print Network [OSTI]

most advanced numerical weather prediction models still havefor numerical weather prediction models. Acknowledgements It

A. Deloncle; R. Berk; F. D'Andrea; M. Ghil

2011-01-01T23:59:59.000Z

6

Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation  

E-Print Network [OSTI]

Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation Cyril a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly@gmail.com #12;Abstract. We propose in this paper an original technique to predict global radiation using

Paris-Sud XI, Université de

7

24 More Years of Numerical Weather Prediction: A Model Performance Model  

E-Print Network [OSTI]

24 More Years of Numerical Weather Prediction: A Model Performance Model Gerard Cats May 26, 2008 Abstract For two formulations of currently usual numerical weather prediction models the evolution in such a model is much 1 #12;24 More Years of Numerical Weather Prediction Gerard Cats higher than in a sis

Stoffelen, Ad

8

The Dynamics of Deterministic Chaos in Numerical Weather Prediction Models  

E-Print Network [OSTI]

Atmospheric weather systems are coherent structures consisting of discrete cloud cells forming patterns of rows/streets, mesoscale clusters and spiral bands which maintain their identity for the duration of their appreciable life times in the turbulent shear flow of the planetary Atmospheric Boundary Layer. The existence of coherent structures (seemingly systematic motion) in turbulent flows has been well established during the last 20 years of research in turbulence. Numerical weather prediction models based on the inherently non-linear Navier-Stokes equations do not give realistic forecasts because of the following inherent limitations: (1) the non-linear governing equations for atmospheric flows do not have exact analytic solutions and being sensitive to initial conditions give chaotic solutions characteristic of deterministic chaos (2) the governing equations do not incorporate the dynamical interactions and co-existence of the complete spectrum of turbulent fluctuations which form an integral part of the large coherent weather systems (3) limitations of available computer capacity necessitates severe truncation of the governing equations, thereby generating errors of approximations (4) the computer precision related roundoff errors magnify the earlier mentioned uncertainties exponentially with time and the model predictions become unrealistic. The accurate modelling of weather phenomena therefore requires alternative concepts and computational techniques. In this paper a universal theory of deterministic chaos applicable to the formation of coherent weather structures in the ABL is presented.

A. Mary Selvam

2003-10-07T23:59:59.000Z

9

EVALUATION OF NUMERICAL WEATHER PREDICTION IN MODELING CLOUD-RADIATION INTERACTIONS OVER THE SOUTHERN GREAT PLAINS  

E-Print Network [OSTI]

EVALUATION OF NUMERICAL WEATHER PREDICTION IN MODELING CLOUD- RADIATION INTERACTIONS OVER.bnl.gov ABSTRACT Numerical weather prediction (NWP) is the basis for present-day weather forecasts, and NWP for Medium-Range Weather Forecasts, the US North American Model, and the US Global Forecast System. Attempts

Johnson, Peter D.

10

Evaluating the ability of a numerical weather prediction model to forecast tracer concentrations during ETEX 2  

E-Print Network [OSTI]

Evaluating the ability of a numerical weather prediction model to forecast tracer concentrations an operational numerical weather prediction model to forecast air quality are also investigated. These potential a numerical weather prediction (NWP) model independently of the CTM. The NWP output is typically archived

Dacre, Helen

11

The origins of computer weather prediction and climate modeling  

SciTech Connect (OSTI)

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

Lynch, Peter [Meteorology and Climate Centre, School of Mathematical Sciences, University College Dublin, Belfield (Ireland)], E-mail: Peter.Lynch@ucd.ie

2008-03-20T23:59:59.000Z

12

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

Multiscale numerical weather prediction model. Progress inassimilating numerical weather prediction model for solarwith numerical weather prediction models. In: Solar Energy

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

13

USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS,  

E-Print Network [OSTI]

USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS to develop a methodology to generate solar radiation maps using information from different sources. First with conclusions and next works in the last section. Keywords: Solar Radiation maps, Numerical Weather Predictions

Paris-Sud XI, Université de

14

Prediction versus Projection: How weather forecasting and  

E-Print Network [OSTI]

Prediction versus Projection: How weather forecasting and climate models differ. Aaron B. Wilson Context: Global http://data.giss.nasa.gov/ #12;Numerical Weather Prediction Collect Observations alters associated weather patterns. Models used to predict weather depend on the current observed state

Howat, Ian M.

15

Estimation of the mean depth of boreal lakes for use in numerical weather prediction and climate modelling  

E-Print Network [OSTI]

in the numerical weather prediction (NWP) and climate models through parameterisation. For parameterisation, data. The effect of lakes should be parameterised in numerical weather prediction (NWP) and climate modellingEstimation of the mean depth of boreal lakes for use in numerical weather prediction and climate

Paris-Sud XI, Université de

16

Amending Numerical Weather Prediction forecasts using GPS  

E-Print Network [OSTI]

to validate the amounts of humidity in Numerical Weather Prediction (NWP) model forecasts. This paper presents. Satellite images and Numerical Weather Prediction (NWP) models are used together with the synoptic surface. In this paper, a case is presented for which the operational Numerical Weather Prediction Model (NWP) HIRLAM

Stoffelen, Ad

17

EXPLICIT SIMULATION OF ICE PARTICLE HABITS IN A NUMERICAL WEATHER PREDICTION MODEL  

E-Print Network [OSTI]

EXPLICIT SIMULATION OF ICE PARTICLE HABITS IN A NUMERICAL WEATHER PREDICTION MODEL by Tempei This study develops a scheme for explicit simulation of ice particle habits in Cloud Resolving Models (CRMs is called Spectral Ice Habit Prediction System (SHIPS), which represents a continuous-property approach

Wisconsin at Madison, University of

18

Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation  

E-Print Network [OSTI]

We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly look at the Multi-Layer Perceptron. After optimizing our architecture with ALADIN and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model ANN/ARMA is 14.9% compared to 26.2% for the na\\"ive persistence predictor. Note that in the stand alone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposed

Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure

2012-01-01T23:59:59.000Z

19

Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts  

E-Print Network [OSTI]

Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts Hlne of the shocks on the volatility by estimating a structural model with a periodic threshold GARCH. We show model, Markov chain, threshold GARCH, Monte- Carlo simulations, pricing, Value-at-Risk. JEL

Paris-Sud XI, Universit de

20

Satellite Application Facility for Numerical Weather Prediction  

E-Print Network [OSTI]

into Numerical Weather Prediction (NWP) models. However, the impact of such observations often critNWP SAF Satellite Application Facility for Numerical Weather Prediction Document NWPSAF-KN-VS-002 Stoffelen KNMI #12;NWP SAF Satellite Application Facility for Numerical Weather Prediction Report

Stoffelen, Ad

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States  

E-Print Network [OSTI]

fornumericalweatherpredictionandclimatemodels. Abstract: Numericalweatherprediction(NWP)modelsareModeloutputstatistics(MOS),NumericalWeatherPrediction(

Mathiesen, Patrick; Kleissl, Jan

2011-01-01T23:59:59.000Z

22

DREAM tool increases space weather predictions  

E-Print Network [OSTI]

- 1 - DREAM tool increases space weather predictions April 13, 2012 Predicting space weather improved by new DREAM modeling tool Earth's radiation belts can now be studied with a new modeling tool DREAM comes into play. Radiation belt structure and dynamics revealed DREAM is a modeling tool

23

The Quality of a 48-Hours Wind Power Forecast Using the German and Danish Weather Prediction Model  

E-Print Network [OSTI]

numerical weather prediction models operated by the weather services are refined by taking into account stock exchange. The typical predic- tion time horizon which is needed for these purposes is 3 to 48 are applied taking into account the effects from lo- cal roughness, thermal stratification of the atmosphere

Heinemann, Detlev

24

Every cloud has a silver lining: Weather forecasting models could predict brain tumor  

E-Print Network [OSTI]

, and combine them with incoming data streams from weather stations and satellites. Now, an innovative new study methodology used to assimilate data for weather forecasting could be used to predict the spread of brain. Synthetic magnetic resonance images of a hypothetical tumor were used for this purpose. Data assimilation

Kuang, Yang

25

AMPS, a real-time mesoscale modeling system, has provided a decade of service for scientific and logistical needs and has helped advance polar numerical weather prediction  

E-Print Network [OSTI]

and logistical needs and has helped advance polar numerical weather prediction as well as understanding support for the USAP. The concern at the time was the numerical weather prediction (NWP) guidance-time implementation of the Weather Research and Forecasting model (WRF; Skamarock et al. 2008) to support the U

Howat, Ian M.

26

Coupling a Mesoscale Numerical Weather Prediction Model with Large-Eddy Simulation for Realistic Wind Plant Aerodynamics Simulations (Poster)  

SciTech Connect (OSTI)

Wind plant aerodynamics are influenced by a combination of microscale and mesoscale phenomena. Incorporating mesoscale atmospheric forcing (e.g., diurnal cycles and frontal passages) into wind plant simulations can lead to a more accurate representation of microscale flows, aerodynamics, and wind turbine/plant performance. Our goal is to couple a numerical weather prediction model that can represent mesoscale flow [specifically the Weather Research and Forecasting model] with a microscale LES model (OpenFOAM) that can predict microscale turbulence and wake losses.

Draxl, C.; Churchfield, M.; Mirocha, J.; Lee, S.; Lundquist, J.; Michalakes, J.; Moriarty, P.; Purkayastha, A.; Sprague, M.; Vanderwende, B.

2014-06-01T23:59:59.000Z

27

CSU ATS703 Fall 2012 Numerical Weather Prediction  

E-Print Network [OSTI]

CSU ATS703 Fall 2012 Numerical Weather Prediction ATS703 is based on the course notes and papers method. A crucial element of accurate weather prediction is initialization, which is briefly discussed in Chapter 11. In the next decade, numerical weather prediction will expe- rience a revolution in model

28

Multigrid methods for improving the variational data assimilation in numerical weather prediction  

E-Print Network [OSTI]

conditions are needed to solve numerical weather prediction models: initial condition and boundary conditionMultigrid methods for improving the variational data assimilation in numerical weather prediction: numerical weather prediction, variational data assimilation, minimization procedure, multigrid methods, cell

Kwak, Do Young

29

Adjoint Sensitivity Analysis for Numerical Weather Prediction  

E-Print Network [OSTI]

Sep 2, 2011 ... Adjoint Sensitivity Analysis for Numerical Weather Prediction: Applications to Power Grid Optimization. Alexandru Cioaca(alexgc ***at*** vt.edu)

Alexandru Cioaca

2011-09-02T23:59:59.000Z

30

Temporal Changes in Wind as Objects for Evaluating Mesoscale Numerical Weather Prediction  

E-Print Network [OSTI]

a method of evaluating numerical weather prediction models by comparing the characteristics of temporal for biases in features forecast by the model. 1. Introduction Verification of numerical weather predictionTemporal Changes in Wind as Objects for Evaluating Mesoscale Numerical Weather Prediction DARAN L

Knievel, Jason Clark

31

WeatherSeptember2009,Vol.64,No.9 Can dispersion model predictions  

E-Print Network [OSTI]

into the atmosphere, with each particle representing a fixed mass of pollutant. Particles are transported due Office, Exeter 2 University of Reading Introduction In the case of a major pollution incident, terrorist attack, or a radioactive event such as the Chernobyl disaster in 1986, dispersion models are used

Dacre, Helen

32

Soil moisture in complex terrain: quantifying effects on atmospheric boundary layer flow and providing improved surface boundary conditions for mesoscale models  

E-Print Network [OSTI]

compressible numerical weather prediction model incompressible numerical weather prediction model withcompressible numerical weather prediction model in

Daniels, Megan Hanako

2010-01-01T23:59:59.000Z

33

Unified Surface Analysis Manual Weather Prediction Center  

E-Print Network [OSTI]

-bone in stage IV. The stages in the respective cyclone evolutions are separated by approximately 6 24 h's) National Weather Service (NWS) were generally based on the Norwegian Cyclone Model (Bjerknes 1919) over below shows a typical evolution according to both models of cyclone development. Conceptual models

34

Predicting Solar Generation from Weather Forecasts Using Machine Learning  

E-Print Network [OSTI]

of smart grid initiatives is significantly increasing the fraction of grid energy contributed by renewables existing forecast-based models. I. INTRODUCTION A key goal of smart grid efforts is to substantially-based prediction models built using seven distinct weather forecast metrics are 27% more accurate for our site than

Shenoy, Prashant

35

Tropical and subtropical cloud transitions in weather and climate prediction models: the GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)  

SciTech Connect (OSTI)

A model evaluation approach is proposed where weather and climate prediction models are analyzed along a Pacific Ocean cross-section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade-winds, to the deep convection regions of the ITCZ: the GCSS/WGNE Pacific Cross-section Intercomparison (GPCI). The main goal of GPCI is to evaluate, and help understand and improve the representation of tropical and sub-tropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross-section from the sub-tropics to the tropics for the season JJA of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the ECMWF Re-Analysis (ERA40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical crosssections of cloud properties (in particular), vertical velocity and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA40 in the stratocumulus regions (as compared to ISCCP) is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade-wind Lagrangian trajectory. Histograms of cloud cover along the cross-section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

Teixeira, J.; Cardoso, S.; Bonazzola, M.; Cole, Jason N.; DelGenio, Anthony D.; DeMott, C.; Franklin, A.; Hannay, Cecile; Jakob, Christian; Jiao, Y.; Karlsson, J.; Kitagawa, H.; Koehler, M.; Kuwano-Yoshida, A.; LeDrian, C.; Lock, Adrian; Miller, M.; Marquet, P.; Martins, J.; Mechoso, C. R.; Meijgaard, E. V.; Meinke, I.; Miranda, P.; Mironov, D.; Neggers, Roel; Pan, H. L.; Randall, David A.; Rasch, Philip J.; Rockel, B.; Rossow, William B.; Ritter, B.; Siebesma, A. P.; Soares, P.; Turk, F. J.; Vaillancourt, P.; Von Engeln, A.; Zhao, M.

2011-11-01T23:59:59.000Z

36

On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model  

SciTech Connect (OSTI)

This is a conference proceeding that is now being put together as a book. This is chapter 2 of the book: "INTEGRATED SYSTEMS OF MESO-METEOROLOGICAL AND CHEMICAL TRANSPORT MODELS" published by Springer. The chapter title is "On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model." The original conference was the COST-728/NetFAM workshop on Integrated systems of meso-meteorological and chemical transport models, Danish Meteorological Institute, Copenhagen, May 21-23, 2007.

Grell, Georg; Fast, Jerome D.; Gustafson, William I.; Peckham, Steven E.; McKeen, Stuart A.; Salzmann, Marc; Freitas, Saulo

2010-01-01T23:59:59.000Z

37

ATS 680 A6: Applied Numerical Weather Prediction MW, 1:00-1:50 PM, ACRC Room 212B  

E-Print Network [OSTI]

experiments using a state-of-the-art numerical weather prediction model · Discuss the strengths and weaknesses, Parameterization Schemes: Keys to Understanding Numerical Weather Prediction Models, Cambridge University PressATS 680 A6: Applied Numerical Weather Prediction Fall 2013 MW, 1:00-1:50 PM, ACRC Room 212B Course

38

Metr 6803: Numerical Weather Prediction Syllabus: Spring 2013 M / W 10:00-11:15, NWC 5930  

E-Print Network [OSTI]

Metr 6803: Numerical Weather Prediction Syllabus: Spring 2013 M / W ­ 10:00-11:15, NWC 5930 weather analysis (NWA) and numerical weather prediction (NWP)? - why are they important? - how "good of numerics of GFS, RUC/RAP, CAPS, MM5, WRF models 11. Atmospheric Predictability - basic concepts

Droegemeier, Kelvin K.

39

MOUNTAIN WEATHER PREDICTION: PHENOMENOLOGICAL CHALLENGES AND FORECAST METHODOLOGY  

E-Print Network [OSTI]

MOUNTAIN WEATHER PREDICTION: PHENOMENOLOGICAL CHALLENGES AND FORECAST METHODOLOGY Michael P. Meyers of the American Meteorological Society Mountain Weather and Forecasting Monograph Draft from Friday, May 21, 2010 of weather analysis and forecasting in complex terrain with special emphasis placed on the role of humans

Steenburgh, Jim

40

HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson  

E-Print Network [OSTI]

and decision makers strongly rely on Numerical Weather Prediction (NWP) models, for example on the forecasted on forecasted precipitation. KEYWORDS: Numerical weather prediction models, validation, precipitation 1. INTRODUCTION Numerical Weather Prediction (NWP) models are widely used by avalanche practitioners. Their de

Jamieson, Bruce

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Fixed points, stable manifolds, weather regimes, and their predictability  

DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the models fixed points in phase space. The model dynamics is characterized by the coexistence of multiple weather regimes. To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, bred vectors and singular vectors. These results are then verified in the framework of ensemble forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael [Univ. of California, Los Angeles, CA (United Staes). Atmospheric and Oceanic Sciences and Institute of Geophysics and Planetary Physics

2009-10-27T23:59:59.000Z

42

Predicting the Energy Output of Wind Farms Based on Weather Data: Important Variables and their Correlation  

E-Print Network [OSTI]

Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy suppliers can coordinate the collaborative production of different energy sources more efficiently to avoid costly overproductions. With this paper, we take a computer science perspective on energy prediction based on weather data and analyze the important parameters as well as their correlation on the energy output. To deal with the interaction of the different parameters we use symbolic regression based on the genetic programming tool DataModeler. Our studies are carried out on publicly available weather and energy data for a wind farm in Australia. We reveal the correlation of the different variables for the energy output. The model obtained for energy prediction gives a very reliable prediction of the energy output for newly given weather data.

Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

2011-01-01T23:59:59.000Z

43

PREDICTIVE MODELS  

SciTech Connect (OSTI)

PREDICTIVE MODELS is a collection of five models - CFPM, CO2PM, ICPM, PFPM, and SFPM - used in the 1982-1984 National Petroleum Council study of enhanced oil recovery (EOR) potential. Each pertains to a specific EOR process designed to squeeze additional oil from aging or spent oil fields. The processes are: 1) chemical flooding; 2) carbon dioxide miscible flooding; 3) in-situ combustion; 4) polymer flooding; and 5) steamflood. CFPM, the Chemical Flood Predictive Model, models micellar (surfactant)-polymer floods in reservoirs, which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option allows a rough estimate of oil recovery by caustic or caustic-polymer processes. CO2PM, the Carbon Dioxide miscible flooding Predictive Model, is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO2 injection or water-alternating gas processes. ICPM, the In-situ Combustion Predictive Model, computes the recovery and profitability of an in-situ combustion project from generalized performance predictive algorithms. PFPM, the Polymer Flood Predictive Model, is switch-selectable for either polymer or waterflooding, and an option allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. SFPM, the Steamflood Predictive Model, is applicable to the steam drive process, but not to cyclic steam injection (steam soak) processes. The IBM PC/AT version includes a plotting capability to produces a graphic picture of the predictive model results.

Ray, R.M. (DOE Bartlesville Energy Technology Center, Bartlesville, OK (United States))

1988-10-01T23:59:59.000Z

44

Special issue of Terrestrial, Atmospheric and Oceanic Science, 11(1), 157-186, March 2000. Assimilation of GPS Radio Occultation Data for Numerical Weather Prediction  

E-Print Network [OSTI]

Assimilation of GPS Radio Occultation Data for Numerical Weather Prediction Y-H. Kuo1 , S. Sokolovskiy2, 3 , R, water vapor), and to effectively assimilate them into weather prediction models is a challenging task assimilation, GPS/MET, numerical weather prediction, COSMIC) 1. INTRODUCTION The lack of data over the oceans

45

PREDICTIVE MODELS  

SciTech Connect (OSTI)

PREDICTIVE MODELS is a collection of five models - CFPM, CO2PM, ICPM, PFPM, and SFPM - used in the 1982-1984 National Petroleum Council study of enhanced oil recovery (EOR) potential. Each pertains to a specific EOR process designed to squeeze additional oil from aging or spent oil fields. The processes are: 1) chemical flooding, where soap-like surfactants are injected into the reservoir to wash out the oil; 2) carbon dioxide miscible flooding, where carbon dioxide mixes with the lighter hydrocarbons making the oil easier to displace; 3) in-situ combustion, which uses the heat from burning some of the underground oil to thin the product; 4) polymer flooding, where thick, cohesive material is pumped into a reservoir to push the oil through the underground rock; and 5) steamflood, where pressurized steam is injected underground to thin the oil. CFPM, the Chemical Flood Predictive Model, models micellar (surfactant)-polymer floods in reservoirs, which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option allows a rough estimate of oil recovery by caustic or caustic-polymer processes. CO2PM, the Carbon Dioxide miscible flooding Predictive Model, is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO2 injection or water-alternating gas processes. ICPM, the In-situ Combustion Predictive Model, computes the recovery and profitability of an in-situ combustion project from generalized performance predictive algorithms. PFPM, the Polymer Flood Predictive Model, is switch-selectable for either polymer or waterflooding, and an option allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. SFPM, the Steamflood Predictive Model, is applicable to the steam drive process, but not to cyclic steam injection (steam soak) processes.

Ray, R.M. (DOE Bartlesville Energy Technology Technology Center, Bartlesville, OK (United States))

1986-12-01T23:59:59.000Z

46

Numerical Prediction of High-Impact Local Weather: A  

E-Print Network [OSTI]

Chapter 6 Numerical Prediction of High-Impact Local Weather: A Driver for Petascale Computing Ming winds, lightning, hurricanes and winter storms, cause hundreds of deaths and average annual economic of mitigating the impacts of such events on the economy and society is obvious, our ability to do so

Xue, Ming

47

Weather  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and the variations in atmospheric conditions that produce weather. The Weather Machine, LANL's meteorological monitoring program, supports Laboratory operations and...

48

The Uncoordinated Giant: Why U.S. Weather Research and Prediction  

E-Print Network [OSTI]

1 The Uncoordinated Giant: Why U.S. Weather Research and Prediction Are Not Achieving.S. meteorological community has made significant strides in weather diagnosis and prediction, progress has been such problems in a number of areas, ranging from numerical weather prediction to forecast dissemination

Mass, Clifford F.

49

The Uncoordinated Giant: Why U.S. Weather Research and Prediction  

E-Print Network [OSTI]

1 The Uncoordinated Giant: Why U.S. Weather Research and Prediction Are Not Achieving.S. meteorological community has made significant strides in weather diagnosis and prediction, progress has been research and operations, that might facilitate improvement in our ability to understand and predict

Mass, Clifford F.

50

On the Use of QuikSCAT Scatterometer Measurements of Surface Winds for Marine Weather Prediction  

E-Print Network [OSTI]

the accuracies of surface wind fields in the National Centers for Envi- ronmental Prediction (NCEP) and EuropeanOn the Use of QuikSCAT Scatterometer Measurements of Surface Winds for Marine Weather Prediction ocean vector winds for marine weather prediction is investigated from two Northern Hemisphere case

Kurapov, Alexander

51

An improved lake model for climate simulations: Model structure, evaluation, and sensitivity analyses in CESM1  

E-Print Network [OSTI]

into the numerical weather prediction model COSMO, BorealCurrent numerical weather prediction (NWP) models, regionalof lakes in numerical weather prediction and climate models:

Subin, Z.M.

2013-01-01T23:59:59.000Z

52

Optimization Online - Economic Impacts of Advanced Weather ...  

E-Print Network [OSTI]

Mar 5, 2010 ... Economic Impacts of Advanced Weather Forecasting on Energy System ... that state-of-the-art numerical weather prediction (NWP) models can...

Victor M. Zavala

2010-03-05T23:59:59.000Z

53

Model error in weather forecasting D. Orrell 1,2 , L. Smith 1,3 , J. Barkmeijer 4 , and T. Palmer 4  

E-Print Network [OSTI]

numerical weather prediction mod­ els. A simple law is derived to relate model error to likely shadowingModel error in weather forecasting D. Orrell 1,2 , L. Smith 1,3 , J. Barkmeijer 4 , and T. Palmer 4 in the model, and inac­ curate initial conditions (Bjerknes, 1911). Because weather models are thought

Smith, Leonard A

54

ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS  

SciTech Connect (OSTI)

During the year 2008, the United States National Weather Service (NWS) completed an eight fold increase in sampling capability for weather radars to 250 m resolution. This increase is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current NWS operational model domains utilize grid spacing an order of magnitude larger than the radar data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of radar reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution was investigated under a Laboratory Directed Research and Development (LDRD) 'quick hit' grant to determine the impact of improved data resolution on model predictions with specific initial proof of concept application to daily Savannah River Site operations and emergency response. Development of software to process NWS radar reflectivity and radial velocity data was undertaken for assimilation of observations into numerical models. Data values within the radar data volume undergo automated quality control (QC) analysis routines developed in support of this project to eliminate empty/missing data points, decrease anomalous propagation values, and determine error thresholds by utilizing the calculated variances among data values. The Weather Research and Forecasting model (WRF) three dimensional variational data assimilation package (WRF-3DVAR) was used to incorporate the QC'ed radar data into input and boundary conditions. The lack of observational data in the vicinity of SRS available to NWS operational models signifies an important data void where radar observations can provide significant input. These observations greatly enhance the knowledge of storm structures and the environmental conditions which influence their development. As the increase in computational power and availability has made higher resolution real-time model simulations possible, the need to obtain observations to both initialize numerical models and verify their output has become increasingly important. The assimilation of high resolution radar observations therefore provides a vital component in the development and utility of numerical model forecasts for both weather forecasting and contaminant transport, including future opportunities to improve wet deposition computations explicitly.

Chiswell, S.; Buckley, R.

2009-01-15T23:59:59.000Z

55

Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill  

SciTech Connect (OSTI)

We investigated the contribution of medium range weather forecasts with lead times up to 14 days to seasonal hydrologic prediction skill over the Conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP)-based experiments were performed for the period 1980-2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980-2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts, for runoff (SM) forecasts generally varies from 0 to 0.8 (0 to 0.5) as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

Shukla, Shraddhanand; Voisin, Nathalie; Lettenmaier, D. P.

2012-08-15T23:59:59.000Z

56

Weather  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste and Materials Disposition3 WaterFebruary 18,theWeather Weather We

57

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)  

E-Print Network [OSTI]

, Paris, France e Canadian Centre for Climate Modelling and Analysis, Victoria, British Columbia, Canada f, Melbourne, Victoria, Australia i Monash University, Melbourne, Victoria, Australia j Department of Earth for the season June­July­August

Randall, David A.

58

Accurately Estimating the State of a Geophysical System with Sparse Observations: Predicting the Weather  

E-Print Network [OSTI]

Utilizing the information in observations of a complex system to make accurate predictions through a quantitative model when observations are completed at time $T$, requires an accurate estimate of the full state of the model at time $T$. When the number of measurements $L$ at each observation time within the observation window is larger than a sufficient minimum value $L_s$, the impediments in the estimation procedure are removed. As the number of available observations is typically such that $L \\ll L_s$, additional information from the observations must be presented to the model. We show how, using the time delays of the measurements at each observation time, one can augment the information transferred from the data to the model, removing the impediments to accurate estimation and permitting dependable prediction. We do this in a core geophysical fluid dynamics model, the shallow water equations, at the heart of numerical weather prediction. The method is quite general, however, and can be utilized in the analysis of a broad spectrum of complex systems where measurements are sparse. When the model of the complex system has errors, the method still enables accurate estimation of the state of the model and thus evaluation of the model errors in a manner separated from uncertainties in the data assimilation procedure.

Zhe An; Daniel Rey; Henry D. I. Abarbanel

2014-05-11T23:59:59.000Z

59

Weather Research and Forecasting Model 2.2 Documentation  

E-Print Network [OSTI]

................................................................................................. 20 3.1.2 Integrate's Flow of ControlWeather Research and Forecasting Model 2.2 Documentation: A Step-by-step guide of a Model Run .......................................................................................................................... 19 3.1 The Integrate Subroutine

Sadjadi, S. Masoud

60

A framework for predicting global silicate weathering and CO2 drawdown rates over geologic time-scales  

E-Print Network [OSTI]

A framework for predicting global silicate weathering and CO2 drawdown rates over geologic time (received for review February 15, 2008) Global silicate weathering drives long-time-scale fluctuations in atmospheric CO2. While tectonics, climate, and rock-type influence silicate weathering, it is unclear how

Hilley, George

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Interactive Weather Simulation and Visualization on a Display Wall  

E-Print Network [OSTI]

.hoai.ha,john.markus.bjorndalen,otto.anshus}@uit.no, {tormsh,daniels}@cs.uit.no Abstract. Numerical Weather Prediction models (NWP) used for op- erational Weather Model, WRF, Tiled Display Walls, Live Data Sets, On-Demand Computation. 1 Introduction Numerical Weather Prediction models for use in weather forecasting centers are often computed for a fixed static

Ha, Phuong H.

62

American Solar Energy Society Proc. ASES Annual Conference, Raleigh, NC, EVALUATION OF NUMERICAL WEATHER PREDICTION  

E-Print Network [OSTI]

© American Solar Energy Society ­ Proc. ASES Annual Conference, Raleigh, NC, EVALUATION;© American Solar Energy Society ­ Proc. ASES Annual Conference, Raleigh, NC, irradiance forecasts over OF NUMERICAL WEATHER PREDICTION SOLAR IRRADIANCE FORECASTS IN THE US Richard Perez ASRC, Albany, NY, Perez

Perez, Richard R.

63

E-Print Network 3.0 - area prediction models Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

for: area prediction models Page: << < 1 2 3 4 5 > >> 1 The Quality of a 48-Hours Wind Power Forecast Using the German and Danish Weather Prediction Model Summary: The Quality...

64

Lessons from Deploying NLG Technology for Marine Weather Forecast Text Generation  

E-Print Network [OSTI]

weather under the guidance of weather data generated by Numerical Weather Prediction (NWP) models Numerical Weather Prediction (NWP) data. It has been used for the past year by Weathernews (UK) Ltd weather prediction information fulfilling the needs of the end user. This task requires them to use NWP

Sripada, Yaji

65

Spatial predictive distribution for precipitation based on numerical weather predictions (NWP)  

E-Print Network [OSTI]

for precipitation based on NWP #12;Motivation, hydro power production How much water comes when? With uncertainty Precipitation Data Meteorological model NWP Short term optimalization Run off Hydrological model Past Future

Steinsland, Ingelin

66

Warm weather's a comin'! Performance Dependence on Closure  

E-Print Network [OSTI]

contributed also by Aaron Rosenberg!! #12;Wind Forecasting using Numerical Weather Prediction (NWP) Mesoscale weather models often predict the height of the LLJ too high and the magnitude too low Overwhelming 18-hr.forecasts initialized at 18Z Weather Research and Forecast (WRF) Model #12;Dissipation

McCalley, James D.

67

P2.3 DEVELOPMENT OF A COMPREHENSIVE SEVERE WEATHER FORECAST VERIFICATION SYSTEM AT THE STORM PREDICTION CENTER  

E-Print Network [OSTI]

: Andrew R. Dean, CIMMS, Univ. of Oklahoma, National Weather Center, Suite 2300, Norman, OK 73072-7268; e PREDICTION CENTER Andrew R. Dean*1,2 , Russell S. Schneider 2 , and Joseph T. Schaefer 2 1 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, OK 2 NOAA/NWS Storm

68

AFFILIATIONS: HULTQUIST--NOAA/National Weather Service, Marquette, Michigan; DUTTER--NOAA/National Weather Service,  

E-Print Network [OSTI]

with modern numerical weather prediction models to provide detailed hindcasts of conditions throughoutAFFILIATIONS: HULTQUIST--NOAA/National Weather Service, Marquette, Michigan; DUTTER--NOAA/National Weather Service, Cleveland, Ohio; SCHWAB--NOAA/Great Lakes Environmental Research Laboratory, Ann Arbor

69

Copula Based Stochastic Weather Generator as an Application for Crop Growth Models and Crop Insurance  

E-Print Network [OSTI]

INTRODUCTION .............................................................................. 1 CHAPTER II THE MODELING OF WEATHER VARIABLES WITH COPULA APPROACH..................................................................... 3 Introduction... 1 CHAPTER I INTRODUCTION Stochastic Weather Generators (SWG) are numerical models that try to reproduce the statistical properties from observed historical climate series. Climatological variables are complex systems, characterized by high...

Juarez Torres, Miriam 77-

2012-08-31T23:59:59.000Z

70

Mountain Weather Research and Forecasting Chapter 12: Bridging the Gap between Operations and Research to  

E-Print Network [OSTI]

and Research to Improve Weather Prediction in Mountainous Regions W. James Steenburgh Department of Atmospheric tools, and numerical models, and inhibits researchers from fully evaluating weaknesses in current integrated collaboration to address critical challenges for weather prediction in mountainous regions

Steenburgh, Jim

71

Model prediction for reactor control  

SciTech Connect (OSTI)

Model prediction is offered as a substitute to lengthy analysis of sample procedures to control product properties not amendable to direct measurement during chemical processing. A computer model of a reactor is set up, and control actions, based on current predicted values, are established. The control is based on predicted ''measurements'' which are derived using a dynamic process model solved on-line. The model is corrected by real measurements in the process operation. A two phase exothermic catalyzed reaction, with the objective of producing material with specified properties, is tested in this paper. The model prediction performance was very good. Model systems enable a more effective control to be exercised than the sample method.

Ardell, G.G.; Gumowski, B.

1983-06-01T23:59:59.000Z

72

State space models, filtering and environmental applications  

E-Print Network [OSTI]

;Section 1 Introductory Examples Postprocessing of numerical weather predictions Data assimilation for weather prediction Stochastic reaction networks Rare event estimation Basics of state space models Numerical weather predictions (MWP) are deterministic with high spatial and temporal resolution. Statistical

Künsch, Hans Rudolf

73

Weather Radar and Hydrology 1 Influence of rainfall spatial variability on hydrological modelling: a  

E-Print Network [OSTI]

Weather Radar and Hydrology 1 Influence of rainfall spatial variability on hydrological modelling variability as well as characteristics and hydrological behavior of catchments, we have proceeded simulator and a distributed hydrological model (with four production functions and a distributed transfer

Paris-Sud XI, Université de

74

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect (OSTI)

Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18T23:59:59.000Z

75

PREDICTIVE MODELS. Enhanced Oil Recovery Model  

SciTech Connect (OSTI)

PREDICTIVE MODELS is a collection of five models - CFPM, CO2PM, ICPM, PFPM, and SFPM - used in the 1982-1984 National Petroleum Council study of enhanced oil recovery (EOR) potential. Each pertains to a specific EOR process designed to squeeze additional oil from aging or spent oil fields. The processes are: 1 chemical flooding; 2 carbon dioxide miscible flooding; 3 in-situ combustion; 4 polymer flooding; and 5 steamflood. CFPM, the Chemical Flood Predictive Model, models micellar (surfactant)-polymer floods in reservoirs, which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option allows a rough estimate of oil recovery by caustic or caustic-polymer processes. CO2PM, the Carbon Dioxide miscible flooding Predictive Model, is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO2 injection or water-alternating gas processes. ICPM, the In-situ Combustion Predictive Model, computes the recovery and profitability of an in-situ combustion project from generalized performance predictive algorithms. PFPM, the Polymer Flood Predictive Model, is switch-selectable for either polymer or waterflooding, and an option allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. SFPM, the Steamflood Predictive Model, is applicable to the steam drive process, but not to cyclic steam injection (steam soak) processes. The IBM PC/AT version includes a plotting capability to produces a graphic picture of the predictive model results.

Ray, R.M. [DOE Bartlesville Energy Technology Center, Bartlesville, OK (United States)

1992-02-26T23:59:59.000Z

76

Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model  

E-Print Network [OSTI]

Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model of Technology Bhubaneswar, Odisha, India A. ROUTRAY National Centre for Medium Range Weather Forecasting, Noida The performance of the Advanced Research version of the Weather Research and Forecasting (ARW) model in real

77

Using Weather Data and Climate Model Output in Economic Analyses of Climate Change  

SciTech Connect (OSTI)

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

Auffhammer, Maximilian [University of California at Berkeley; Hsiang, Solomon M. [Princeton University; Schlenker, Wolfram [Columbia University; Sobel, Adam H. [Columbia University

2013-06-28T23:59:59.000Z

78

Weather Radar and Hydrology (Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 3XX, 2011).  

E-Print Network [OSTI]

refractivity changes in Numerical Weather Prediction models could help improve the representation of near new data source for assimilation into Numerical Weather Prediction models, particularly with respect Weather Prediction J. C. NICOL1 , K. BARTHOLEMEW1 , T. DARLINGTON2 , A. J. ILLINGWORTH1 , & M. KITCHEN2 1

Reading, University of

79

SUMTIME-MOUSAM: Configurable Marine Weather Forecast Generator Somayajulu G. Sripada and Ehud Reiter  

E-Print Network [OSTI]

Weathernews (UK) Ltd. Aberdeen iand@wni.com Abstract Numerical weather prediction (NWP) models produce time is done using guidance from Numerical Weather Prediction (NWP) models; time series data from the NWPSUMTIME-MOUSAM: Configurable Marine Weather Forecast Generator Somayajulu G. Sripada and Ehud

Reiter, Ehud

80

Model Predictive Control Wind Turbines  

E-Print Network [OSTI]

Model Predictive Control of Wind Turbines Martin Klauco Kongens Lyngby 2012 IMM-MSc-2012-65 #12;Summary Wind turbines are the biggest part of the green energy industry. Increasing interest control strategies. Control strategy has a significant impact on the wind turbine operation on many levels

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

PREDICTIVE MODELS. Enhanced Oil Recovery Model  

SciTech Connect (OSTI)

PREDICTIVE MODELS is a collection of five models - CFPM, CO2PM, ICPM, PFPM, and SFPM - used in the 1982-1984 National Petroleum Council study of enhanced oil recovery (EOR) potential. Each pertains to a specific EOR process designed to squeeze additional oil from aging or spent oil fields. The processes are: 1 chemical flooding, where soap-like surfactants are injected into the reservoir to wash out the oil; 2 carbon dioxide miscible flooding, where carbon dioxide mixes with the lighter hydrocarbons making the oil easier to displace; 3 in-situ combustion, which uses the heat from burning some of the underground oil to thin the product; 4 polymer flooding, where thick, cohesive material is pumped into a reservoir to push the oil through the underground rock; and 5 steamflood, where pressurized steam is injected underground to thin the oil. CFPM, the Chemical Flood Predictive Model, models micellar (surfactant)-polymer floods in reservoirs, which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option allows a rough estimate of oil recovery by caustic or caustic-polymer processes. CO2PM, the Carbon Dioxide miscible flooding Predictive Model, is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO2 injection or water-alternating gas processes. ICPM, the In-situ Combustion Predictive Model, computes the recovery and profitability of an in-situ combustion project from generalized performance predictive algorithms. PFPM, the Polymer Flood Predictive Model, is switch-selectable for either polymer or waterflooding, and an option allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. SFPM, the Steamflood Predictive Model, is applicable to the steam drive process, but not to cyclic steam injection (steam soak) processes.

Ray, R.M. [DOE Bartlesville Energy Technology Technology Center, Bartlesville, OK (United States)

1992-02-26T23:59:59.000Z

82

WEATHER HAZARDS Basic Climatology  

E-Print Network [OSTI]

Prediction Center (SPC) Watch Atmospheric conditions are right for hazardous weather ­ hazardous weather is likely to occur Issued by SPC Warning Hazardous weather is either imminent or occurring Issued by local NWS office #12;Outlooks--SPC Storm Prediction Center (SPC) Outlook=Convective Outlook Day 1 Day 2

83

GPU Acceleration of Numerical Weather John Michalakes  

E-Print Network [OSTI]

GPU Acceleration of Numerical Weather Prediction John Michalakes National Center for Atmospheric parallelism will prove ineffective for many scenarios. We present an alternative method of scaling model Exponentially increasing processor power has fueled fifty years of continuous improvement in weather and climate

Colorado at Boulder, University of

84

Upper Air Wind Measurements by Weather Radar Iwan Holleman, Henk Benschop, and Jitze van der Meulen  

E-Print Network [OSTI]

or assimilated into numerical weather prediction (NWP) models. Un- der the assumption of a linear wind field background statistics of the weather radar wind profiles against the Hirlam NWP model are at least as good of the VVP wind profiles against the Hirlam NWP model demonstrate the high quality of weather radar wind

Stoffelen, Ad

85

Developing Models for Predictive Climate Science  

SciTech Connect (OSTI)

The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strong tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The collaborative SciDAC team--including over a dozen researchers at institutions around the country--developed, validated, documented, and optimized the performance of CCSM using the latest software engineering approaches, computational technology, and scientific knowledge. Many of the factors that must be accounted for in a comprehensive model of the climate system are illustrated in figure 1.

Drake, John B [ORNL; Jones, Philip W [Los Alamos National Laboratory (LANL)

2007-01-01T23:59:59.000Z

86

The temporal cascade structure of reanalyses and Global Circulation models  

E-Print Network [OSTI]

and stochastic forecasting. 1. Introduction "Weather prediction by Numerical Process" (Richardson, 1922 equations. While these equations are deterministic, numerical weather prediction has been increasingly of the deterministic models. Interestingly, Richardson is not only the father of numerical weather forecasting, he

Lovejoy, Shaun

87

Predicting Improved Chiller Performance Through Thermodynamic Modeling  

E-Print Network [OSTI]

This paper presents two case studies in which thermodynamic modeling was used to predict improved chiller performance. The model predicted the performance (COP and total energy consumption) of water-cooled centrifugal chillers as a function...

Figueroa, I. E.; Cathey, M.; Medina, M. A.; Nutter, D. W.

88

Calibrating DOE-2 to weather and non-weather-dependent loads for a commercial building  

E-Print Network [OSTI]

6. 1. 1 Predicted Chilled Water and Hot Water Consumption. . . . . . . . , . . . 102 6. 1. 2 Whole-building Electricity Consumption . . . 6. 2 Base Model Results Using Austin, TX TMY Weather Data. . . . 104 106 vnt CHAPTl'R VII WHOLE...

Bronson, John Douglas

2012-06-07T23:59:59.000Z

89

The calculation of climatically relevant singular vectors in the presence of weather  

E-Print Network [OSTI]

and Kleeman, 1996). As in numerical weather prediction, singular vectors have proven useful for predictability to the analysis of coupled general cir- culation models where the fastest growing modes are connected with weather to a relatively complete coupled general circulation model which has been shown to have skill in the prediction

Tang, Youmin

90

VALIDATION OF RAIN RATE RETRIEVALS FROM SEVIRI USING WEATHER RADAR OBSERVATIONS  

E-Print Network [OSTI]

and for improving parameterization cloud processes in numerical weather prediction (NWP) models or assimilation in these models. Although operational networks of Weather Radars are expanding over Europe and the United StatesVALIDATION OF RAIN RATE RETRIEVALS FROM SEVIRI USING WEATHER RADAR OBSERVATIONS R. A. Roebeling

Stoffelen, Ad

91

Developing a TeraGrid Based Land Surface Hydrology and Weather Modeling Interface  

E-Print Network [OSTI]

Developing a TeraGrid Based Land Surface Hydrology and Weather Modeling Interface Hsin-I Chang1 iclimate@purdue.edu -------------------- -------------------- 1 INTRODUCTION Real world hydrologic cyberinfrastructure (CI) has been articulated in many workshops and meetings of the environmental and hydrologic

Jiang, Wen

92

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications  

E-Print Network [OSTI]

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications DEV NIYOGI Department of Agronomy, and Department form 13 May 2008) ABSTRACT Current land surface schemes used for mesoscale weather forecast models use

Niyogi, Dev

93

Probabilistic Wind Speed Forecasting using Ensembles and Bayesian Model Averaging  

E-Print Network [OSTI]

is to issue deterministic forecasts based on numerical weather prediction models. Uncertainty canProbabilistic Wind Speed Forecasting using Ensembles and Bayesian Model Averaging J. Mc discretization than is seen in other weather quantities. The prevailing paradigm in weather forecasting

Washington at Seattle, University of

94

The impact of Greenland on the predictability of European weather systems Supervisors: Sue Gray (U. Reading), Ian Renfrew (U. East Anglia) and Richard Swinbank (Met  

E-Print Network [OSTI]

The impact of Greenland on the predictability of European weather systems Supervisors: Sue Gray (U-to-high latitude of Greenland means it has a major influence on the atmospheric circulation of the North Atlantic by the presence of Greenland as is the atmosphere well downstream, for example over the British Isles

Renfrew, Ian

95

Benefit of astronomy to ancient cultures Usefulness as a tool to predict the weather  

E-Print Network [OSTI]

Model · Tycho Brahe (1546-1601): Made accurate measurements of the positions of stars & planets · Johannes Kepler (1571-1630): interpreted Tycho's data #12;Phases of Venus Old

Walter, Frederick M.

96

Modeling High-Impact Weather and Climate: Lessons From a Tropical Cyclone Perspective  

SciTech Connect (OSTI)

Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding of the underlying physical processes. This challenge is driving fresh approaches to assess high-impact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias in the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be guided by the need to: include relevant regional climate physical processes; resolve key impact parameters; and to accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters. Finally, through the example of a tropical cyclone damage index, direct impact assessments are resented as powerful tools that distill complex datasets into concise statements on likely impact, and as highly effective communication devices.

Done, James; Holland, Greg; Bruyere, Cindy; Leung, Lai-Yung R.; Suzuki-Parker, Asuka

2013-10-19T23:59:59.000Z

97

Prediction Markets Partition model of knowledge  

E-Print Network [OSTI]

Prediction Markets Partition model of knowledge Distributed information markets Convergence time bounds Computational Aspects of Prediction Markets David M. Pennock and Rahul Sami December 5, 2012 Presented by: Rami Eitan David M. Pennock and Rahul Sami Computational Aspects of Prediction Markets #12

Fiat, Amos

98

EFFICIENT ASSIMILATION OF RADAR DATA AT HIGH RESOLUTION FOR SHORT-RANGE NUMERICAL WEATHER PREDICTION  

E-Print Network [OSTI]

-hydrostatic models, the rapid increase of computer power, and the avail- ability of full-precision radar data in real system must assimilate Doppler radar data including radial velocity and reflectivity, and combine that information with data from satellites, surface stations, and other meso- and micro-scale sensor networks

Xue, Ming

99

semble Prediction Lizzie S. R. Froude1  

E-Print Network [OSTI]

by numerical weather prediction (NWP). Operational NWP models are based on a set of equations known for Medium Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP will grow rapidly, resulting in a total loss of predictability at higher forecast times. Today's models

Froude, Lizzie

100

Latent feature models for dyadic prediction /  

E-Print Network [OSTI]

prediction . . . . . . . . . . . . . . . . . . . . . . . . .Response prediction . . . . . . . . . . . . . . . . . . .2.4.3 Weighted link prediction . . . . . .

Menon, Aditya Krishna

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Towards Ultra-High Resolution Models of Climate and Weather To appear in the International Journal of High Performance Computing Applications, 2008.  

E-Print Network [OSTI]

affordable cost and power considerations. The major conceptual changes required by a kilometer scale climate climate change and weather prediction is one of the most important challenges facing computa- tional fidelity in both short term weather prediction and long term climate change estimates will be better met

Oliker, Leonid

102

Introduction An important goal in operational weather forecasting  

E-Print Network [OSTI]

sensitive areas. To answer these questions simulation experiments with state-of-the-art numerical weather prediction (NWP) models have proved great value to test future meteorological observing systems a priori102 Introduction An important goal in operational weather forecasting is to reduce the number

Haak, Hein

103

Model accurately predicts directional borehole trajectory  

SciTech Connect (OSTI)

Theoretical investigations and field data analyses helped develop a new method of predicting the rate of inclination change in a deviated well bore to help reduce the frequency and magnitude of doglegs. Predicting borehole dogleg severity is one of the main problems in directional drilling. Predicting the tendency and magnitude of borehole deviation and comparing them to the planned well path makes it possible to improve bottom hole assembly (BHA) design and to reduce the number of correction runs. The application of adaptation models for predicting the rate of inclination change if measurement-while-drilling systems are used results in improved accuracy of prediction, and therefore a reduction in correction runs.

Mamedbekov, O.K. (Azerbaijan State Petroleum Academy, Baku (Azerbaijan))

1994-08-29T23:59:59.000Z

104

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

towers water pumps thermal storage tank water supply water loop system weather low-level MPC Setpoints Solar

Ma, Yudong

2012-01-01T23:59:59.000Z

105

ASSESSMENT OF ECONOMIC PERFORMANCE OF MODEL PREDICTIVE  

E-Print Network [OSTI]

ASSESSMENT OF ECONOMIC PERFORMANCE OF MODEL PREDICTIVE CONTROL THROUGH VARIANCE/CONSTRAINT TUNING advanced process control (APC) strategies to deal with multivariable constrained control problems with an ultimate objective towards economic optimization. Any attempt to evaluate MPC performance should therefore

Huang, Biao

106

DOE Workshop; Pan-Gass Conference on the Representation of Atmospheric Processes in Weather and Climate Models  

SciTech Connect (OSTI)

This is the first meeting of the whole new GEWEX (Global Energy and Water Cycle Experiment) Atmospheric System Study (GASS) project that has been formed from the merger of the GEWEX Cloud System Study (GCSS) Project and the GEWEX Atmospheric Boundary Layer Studies (GABLS). As such, this meeting will play a major role in energizing GEWEX work in the area of atmospheric parameterizations of clouds, convection, stable boundary layers, and aerosol-cloud interactions for the numerical models used for weather and climate projections at both global and regional scales. The representation of these processes in models is crucial to GEWEX goals of improved prediction of the energy and water cycles at both weather and climate timescales. This proposal seeks funds to be used to cover incidental and travel expenses for U.S.-based graduate students and early career scientists (i.e., within 5 years of receiving their highest degree). We anticipate using DOE funding to support 5-10 people. We will advertise the availability of these funds by providing a box to check for interested participants on the online workshop registration form. We will also send a note to our participants' mailing lists reminding them that the funds are available and asking senior scientists to encourage their more junior colleagues to participate. All meeting participants are encouraged to submit abstracts for oral or poster presentations. The science organizing committee (see below) will base funding decisions on the relevance and quality of these abstracts, with preference given to under-represented populations (especially women and minorities) and to early career scientists being actively mentored at the meeting (e.g. students or postdocs attending the meeting with their advisor).

Morrison, PI Hugh

2012-09-21T23:59:59.000Z

107

Predictive modelling of boiler fouling  

SciTech Connect (OSTI)

In this reporting period, efforts were initiated to supplement the comprehensive flow field description obtained from the RNG-Spectral Element Simulations by incorporating, in a general framework, appropriate modules to model particle and condensable species transport to the surface. Specifically, a brief survey of the literature revealed the following possible mechanisms for transporting different ash constituents from the host gas to boiler tubes as deserving prominence in building the overall comprehensive model: (1) Flame-volatilized species, chiefly sulfates, are deposited on cooled boiler tubes via the mechanism of classical vapor diffusion. This mechanism is more efficient than the particulate ash deposition, and as a result there is usually an enrichment of condensable salts, chiefly sulfates, in boiler deposits; (2) Particle diffusion (Brownian motion) may account for deposition of some fine particles below 0. 1 mm in diameter in comparison with the mechanism of vapor diffusion and particle depositions, however, the amount of material transported to the tubes via this route is probably small. (3) Eddy diffusion, thermophoretic and electrophoretic deposition mechanisms are likely to have a marked influence in transporting 0.1 to 5[mu]m particles from the host gas to cooled boiler tubes; (4) Inertial impaction is the dominant mechanism in transporting particles above 5[mu]m in diameter to water and steam tubes in pulverized coal fired boiler, where the typical flue gas velocity is between 10 to 25 m/s. Particles above 10[mu]m usually have kinetic energies in excess of what can be dissipated at impact (in the absence of molten sulfate or viscous slag deposit), resulting in their entrainment in the host gas.

Not Available

1992-01-01T23:59:59.000Z

108

Predictive modelling of boiler fouling  

SciTech Connect (OSTI)

As this study incorporates in a general framework, appropriate modules to model condensable species transport to the surface along with particles, the need for a suitable solver for the reaction component of the species equations with regard to issues of stability, stiffness, economy, etc. becomes obvious. It is generally agreed in the literature that the major problem associated with the simultaneous integration of large sets of chemical kinetic rate equations is that of stiffness. Although stiffness does not have a simple definition, it is characterized by widely varying time constants. For example, in hydrogen-air combustion, the induction time is of the order of microseconds whereas the nitric oxide formation time is of the order of milliseconds. These widely different time constants present classical methods (such as the popular explicit Runge-Kutta method) with the following difficulty: to ensure stability of the numerical solution, these methods are restricted to using very short time steps that are determined by the smallest time constant. However, the time for all chemical species to reach near-equilibrium values is determined by the longest time constant. As a result, classical methods require excessive amounts of computer time to solve stiff systems of ordinary differential equations (ODE's). Several approaches for the solution of stiff ODE's have been proposed. Of all these techniques, the general purpose codes EPISODE and LSODE are regarded as the best available packaged'' codes for the solution of stiff systems of ODE'S. However, although these codes may be the best available for solving an arbitrary systems ODE'S, it may be possible to construct superior methods for solving a particular system of ODE's governing the behavior of a specific problem. In this view, an exponentially fitted method, CREK1D, deserves a special mention and is described briefly.

Not Available

1992-01-01T23:59:59.000Z

109

Eulerian CFD Models to Predict Thermophoretic Deposition of Soot...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Eulerian CFD Models to Predict Thermophoretic Deposition of Soot Particles in EGR Coolers Eulerian CFD Models to Predict Thermophoretic Deposition of Soot Particles in EGR Coolers...

110

Combining Modeling and Gaming for Predictive Analytics  

SciTech Connect (OSTI)

Many of our most significant challenges involve people. While human behavior has long been studied, there are recent advances in computational modeling of human behavior. With advances in computational capabilities come increases in the volume and complexity of data that humans must understand in order to make sense of and capitalize on these modeling advances. Ultimately, models represent an encapsulation of human knowledge. One inherent challenge in modeling is efficient and accurate transfer of knowledge from humans to models, and subsequent retrieval. The simulated real-world environment of games presents one avenue for these knowledge transfers. In this paper we describe our approach of combining modeling and gaming disciplines to develop predictive capabilities, using formal models to inform game development, and using games to provide data for modeling.

Riensche, Roderick M.; Whitney, Paul D.

2012-08-22T23:59:59.000Z

111

Autonomous Helicopter Formation using Model Predictive Control  

E-Print Network [OSTI]

Autonomous Helicopter Formation using Model Predictive Control Hoam Chung and S. Shankar Sastry are required to fly in tight formations and under harsh conditions. The starting point for safe autonomous into a formation, so that each vehicle can safely maintain sufficient space between it and all other vehicles

Sastry, S. Shankar

112

Tuning Methods for Model Predictive Controllers  

E-Print Network [OSTI]

methods for tuning of a Gas-Oil Furnace, a Wood-Berry Distillation Column and a Cement Mill Circuit. #12-M.Sc.-2012-69 #12;Summary (English) Model Predictive Control (MPC) is an optimal control strategy, and can-Berry distillations kolonne og en cement mølle proces. #12;iv #12;Preface This M. Sc. thesis was prepared

113

Global Ensemble Predictions of 2009's Tropical Cyclones Initialized with an Ensemble Kalman Filter  

E-Print Network [OSTI]

to the general improvements in numerical weather prediction (NWP) models, such as increased resolution, improved) from two experimental global numerical weather prediction ensemble prediction systems (EPSs). The first model was a high-resolution version (T382L64) of the National Centers for Environmental Prediction (NCEP

Hamill, Tom

114

Can Fault Prediction Models and Metrics be Used for Vulnerability Prediction? Yonghee Shin and Laurie Williams  

E-Print Network [OSTI]

Can Fault Prediction Models and Metrics be Used for Vulnerability Prediction? Yonghee Shin to prioritize security inspection and testing efforts may be better served by a prediction model that indicates commonalities that may allow development teams to use traditional fault prediction models and metrics

Young, R. Michael

115

11.1 DEVELOPMENT OF AN IMMERSED BOUNDARY METHOD TO RESOLVE COMPLEX TERRAIN IN THE WEATHER RESEARCH AND FORECASTING MODEL  

E-Print Network [OSTI]

11.1 DEVELOPMENT OF AN IMMERSED BOUNDARY METHOD TO RESOLVE COMPLEX TERRAIN IN THE WEATHER RESEARCH AND FORECASTING MODEL Katherine A. Lundquist1 , Fotini K. Chow 2 , Julie K. Lundquist 3 , and Jeffery D. Mirocha 3 in urban areas are profoundly influenced by the presence of build- ings which divert mean flow, affect

Chow, Fotini Katopodes

116

Using Mesoscale Weather Model Output as Boundary Conditions for Atmospheric Large-Eddy Simulations and Wind-Plant Aerodynamic Simulations (Presentation)  

SciTech Connect (OSTI)

Wind plant aerodynamics are directly affected by the microscale weather, which is directly influenced by the mesoscale weather. Microscale weather refers to processes that occur within the atmospheric boundary layer with the largest scales being a few hundred meters to a few kilometers depending on the atmospheric stability of the boundary layer. Mesoscale weather refers to large weather patterns, such as weather fronts, with the largest scales being hundreds of kilometers wide. Sometimes microscale simulations that capture mesoscale-driven variations (changes in wind speed and direction over time or across the spatial extent of a wind plant) are important in wind plant analysis. In this paper, we present our preliminary work in coupling a mesoscale weather model with a microscale atmospheric large-eddy simulation model. The coupling is one-way beginning with the weather model and ending with a computational fluid dynamics solver using the weather model in coarse large-eddy simulation mode as an intermediary. We simulate one hour of daytime moderately convective microscale development driven by the mesoscale data, which are applied as initial and boundary conditions to the microscale domain, at a site in Iowa. We analyze the time and distance necessary for the smallest resolvable microscales to develop.

Churchfield, M. J.; Michalakes, J.; Vanderwende, B.; Lee, S.; Sprague, M. A.; Lundquist, J. K.; Moriarty, P. J.

2013-10-01T23:59:59.000Z

117

Grid-based modeling in "Wissensnetz Energiemeteorologie" Jan Ploski1  

E-Print Network [OSTI]

-Grid) for running numerical weather prediction models. Based on experience with our introductory implementation resources of the German Grid [3] for running NWP (Numerical Weather Prediction) models. This paper its prediction quality and on overcoming the technical challenges to establish numerical weather

Heinemann, Detlev

118

MODELLING SURFACE HOAR FORMATION AND EVOLUTION ON MOUNTAIN SLOPES Simon Horton1  

E-Print Network [OSTI]

. Weather station data and forecasted data from the GEM15 numerical weather prediction model were used evaluates surface hoar size predictions made with empirical weather based models and discusses how buried and south facing slopes in the Columbia Mountains. Two models were developed to predict crystal size, one

Jamieson, Bruce

119

Disease Prediction Models and Operational Readiness  

SciTech Connect (OSTI)

INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNLs IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the results are presented in this analysis.

Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.

2014-03-19T23:59:59.000Z

120

Predicting Time-Delays under Real-Time Scheduling for Linear Model Predictive Control  

E-Print Network [OSTI]

Predicting Time-Delays under Real-Time Scheduling for Linear Model Predictive Control Zhenwu Shi prediction of time-delays caused by real-time scheduling. Then, a model predictive controller is designed, the interaction between real-time scheduling and control design has received interest in the literature

Zhang, Fumin

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Prediction Intervals in Generalized Linear Mixed Models  

E-Print Network [OSTI]

3.1. BLP Based Prediction Intervals..3.2. BP Based Prediction Intervals....4.1.1. BLP Based Prediction Interval. 4.1.2.

Yang, Cheng-Hsueh

2013-01-01T23:59:59.000Z

122

Developing hourly weather data for locations having only daily weather data  

SciTech Connect (OSTI)

A methodology was developed to modify an hourly TMY weather tape to be representative of a location for which only average daily weather parameters were avilable. Typical hourly and daily variations in solar flux, and other parameters, were needed to properly exercise a computer model to predict the transient performance of a solar controlled greenhouse being designed for Riyadh, Saudi Arabia. The starting point was a TMY tape for Yuma, Arizona, since the design temperatures for summer and winter are nearly identical for Yuma and Riyadh. After comparing six of the most important weather variables, the hourly values on the Yuma tape were individually adjusted to give the same overall daily average conditions as existed in the long-term Riyadh data. Finally, a statistical analysis was used to confirm quantitatively that the daily variations between the long term average values for Riyadh and the modified TMY weather tape for Yuma matched satisfactorily.

Talbert, S.G.; Herold, K.E.; Jakob, F.E.; Lundstrom, D.K.

1983-06-01T23:59:59.000Z

123

The Los Alamos dynamic radiation environment assimilation model (DREAM) for space weather specification and forecasting  

SciTech Connect (OSTI)

The Dynamic Radiation Environment Assimilation Model (DREAM) was developed at Los Alamos National Laboratory to assess, quantify, and predict the hazards from the natural space environment and the anthropogenic environment produced by high altitude nuclear explosions (HANE). DREAM was initially developed as a basic research activity to understand and predict the dynamics of the Earth's Van Allen radiation belts. It uses Kalman filter techniques to assimilate data from space environment instruments with a physics-based model of the radiation belts. DREAM can assimilate data from a variety of types of instruments and data with various levels of resolution and fidelity by assigning appropriate uncertainties to the observations. Data from any spacecraft orbit can be assimilated but DREAM was designed to function with as few as two spacecraft inputs: one from geosynchronous orbit and one from GPS orbit. With those inputs, DREAM can be used to predict the environment at any satellite in any orbit whether space environment data are available in those orbits or not. Even with very limited data input and relatively simple physics models, DREAM specifies the space environment in the radiation belts to a high level of accuracy. DREAM has been extensively tested and evaluated as we transition from research to operations. We report here on one set of test results in which we predict the environment in a highly-elliptical polar orbit. We also discuss long-duration reanalysis for spacecraft design, using DREAM for real-time operations, and prospects for 1-week forecasts of the radiation belt environment.

Reeves, Geoffrey D [Los Alamos National Laboratory; Friedel, Reiner H W [Los Alamos National Laboratory; Chen, Yue [Los Alamos National Laboratory; Koller, Josef [Los Alamos National Laboratory; Henderson, Michael G [Los Alamos National Laboratory

2008-01-01T23:59:59.000Z

124

Commercial Weatherization  

Broader source: Energy.gov [DOE]

Commercial buildings consume 19 percent of the energy used in the U.S. Learn how the Energy Department is supporting research and deployment on commercial weatherization.

125

A Better Way to ID Extreme Weather Events in Climate Models  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

to do just that. "We're using state-of-the-art methods in data mining and high performance computing to locate and quantify extreme weather phenomena in the very large datasets...

126

MODEL ANALYSES AND GUIDANCE (MAG) APPLICATION MAG User's Manual  

E-Print Network [OSTI]

the National Weather Service's (NWS) Numerical Weather Prediction computer models. The website offers Guidance: Provides a path to view products created from the National Weather Service's (NWS) numerical Weather Service's Tropical Cyclone models. These products are only available when tropical cyclones

127

Improved forecasts of extreme weather events by future space borne Doppler wind lidar  

E-Print Network [OSTI]

sensitive areas. To answer these questions simulation experiments with state-of-the-art numerical weather prediction (NWP) models have proved great value to test future meteorological observing systems a prioriImproved forecasts of extreme weather events by future space borne Doppler wind lidar Gert

Marseille, Gert-Jan

128

Predictive modelling of boiler fouling. Final report.  

SciTech Connect (OSTI)

A spectral element method embodying Large Eddy Simulation based on Re- Normalization Group theory for simulating Sub Grid Scale viscosity was chosen for this work. This method is embodied in a computer code called NEKTON. NEKTON solves the unsteady, 2D or 3D,incompressible Navier Stokes equations by a spectral element method. The code was later extended to include the variable density and multiple reactive species effects at low Mach numbers, and to compute transport of large particles governed by inertia. Transport of small particles is computed by treating them as trace species. Code computations were performed for a number of test conditions typical of flow past a deep tube bank in a boiler. Results indicate qualitatively correct behavior. Predictions of deposition rates and deposit shape evolution also show correct qualitative behavior. These simulations are the first attempts to compute flow field results at realistic flow Reynolds numbers of the order of 10{sup 4}. Code validation was not done; comparison with experiment also could not be made as many phenomenological model parameters, e.g., sticking or erosion probabilities and their dependence on experimental conditions were not known. The predictions however demonstrate the capability to predict fouling from first principles. Further work is needed: use of large or massively parallel machine; code validation; parametric studies, etc.

Chatwani, A

1990-12-31T23:59:59.000Z

129

Global Ensemble Predictions of 2009's Tropical Cyclones Initialized with an Ensemble Kalman Filter  

E-Print Network [OSTI]

). In part, this can be attributed to the general improvements in numerical weather prediction (NWP) models summer tropical cyclones (TCs) from two experimental global numerical weather prediction ensemble prediction systems (EPSs). The first model was a highresolution version (T382L64) of the National Centers

Hamill, Tom

130

Weatherization Roundup  

Broader source: Energy.gov [DOE]

More than 750 thousand homes were weatherized by the Departments Weatherization Assistance Program in the past three years. Secretary Chu spoke with governors and members of Congress around the country to celebrate this huge accomplishment -- which was finished ahead of schedule and is saving the average household $400 annually on their heating and cooling bills.

131

Development of an Adjoint for a Complex Atmospheric Model, the ARPS, using TAF  

E-Print Network [OSTI]

, such as operational weather predictions models, pose challenges on the applicability of AD tools. We report- ational weather prediction models are much more complex, and the problem sizes tend to be much larger as a system for mesoscale and storm-scale numerical weather prediction as well as a wide range of idealized

Gao, Jidong

132

Statistical hadronization model predictions for charmed hadrons at LHC  

E-Print Network [OSTI]

We present predictions of the statistical hadronization model for charmed hadrons production in Pb+Pb collisions at LHC.

A Andronic; P Braun-Munzinger; K Redlich; J Stachel

2007-07-27T23:59:59.000Z

133

ReseaRch at the University of Maryland Climate Modeling and Prediction  

E-Print Network [OSTI]

between the familiar seven-day weather forecast and the century-long global-warming projection, Maryland-Rabinovitz's work is leading to improved predictions of extreme weather events such as monsoons, intense storms-use patterns and their contribution to climate change. Ning Zeng investigates how ice sheets store carbon

Hill, Wendell T.

134

Near quantitative agreement of model free DFT- MD predictions...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Near quantitative agreement of model free DFT- MD predictions with XAFS observations of the hydration structure of highly Near quantitative agreement of model free DFT- MD...

135

Settlement Prediction, Gas Modeling and Slope Stability Analysis  

E-Print Network [OSTI]

Settlement Prediction, Gas Modeling and Slope Stability Analysis in Coll Cards Landfill Li Yu UNIVERSIDAD POLITCNICA DE CATALUA April, 2007 GEOMODELS #12;Introduction to Coll Cards landfill Prediction of settlement in Coll Cards landfill 1) Settlement prediction by empirical method 2) Settlement prediction

Politcnica de Catalunya, Universitat

136

Bayesian Models and Algorithms for Protein Beta-Sheet Prediction  

E-Print Network [OSTI]

0 Bayesian Models and Algorithms for Protein Beta-Sheet Prediction Zafer Aydin, Student Member, IEEE, Yucel Altunbasak, Senior Member, IEEE, and Hakan Erdogan, Member, IEEE Abstract--Prediction of -sheet prediction defined as the prediction of -strand pairings, interaction types (parallel or anti

Erdogan, Hakan

137

Weatherizing America  

Broader source: Energy.gov [DOE]

As Recovery Act money arrives to expand home weatherization programs across the country, Zachary Stewart of Phoenix, Ariz., and others have found an exciting opportunity not only to start working...

138

Weatherizing America  

ScienceCinema (OSTI)

As Recovery Act money arrives to expand home weatherization programs across the country, Zachary Stewart of Phoenix, Ariz., and others have found an exciting opportunity not only to start working again, but also to find a calling.

Stewart, Zachary; Bergeron, T.J.; Barth, Dale; Qualis, Xavier; Sewall, Travis; Fransen, Richard; Gill, Tony;

2013-05-29T23:59:59.000Z

139

A case model for predictive maintenance  

E-Print Network [OSTI]

This project is to respond to a need by Varian Semiconductor Equipment Associates, Inc. (VSEA) to help predict failure of ion implanters. Predictive maintenance would help to reduce the unscheduled downtime of ion implanters, ...

Li, Jiawei, M. Eng. Massachusetts Institute of Technology

2008-01-01T23:59:59.000Z

140

Introduction. Stochastic physics and climate modelling  

E-Print Network [OSTI]

become a backbone of numerical weather prediction and is used not only by weather forecasters but also. Stochastic physics schemes within weather and climate models have the potential to represent the dynamical history, the present era, whereby predictions are made from numerical solutions of the underlying dynamic

Williams, Paul

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Extreme events in solutions of hydrostatic and non-hydrostatic climate models  

E-Print Network [OSTI]

the assumptions made in applying them to operational numerical weather prediction (NWP), climate modelling-hydrostatic (NPE) primitive equations that have been used extensively in numerical weather prediction and climate weather, climate and global ocean circulation predictions for many decades. The HPE govern incompressible

Gibbon, J. D.

142

Wind Speed Prediction Via Time Series Modeling.  

E-Print Network [OSTI]

??Projected construction of nearby wind farms motivates this study of statistical forecasting of wind speed, for which accurate prediction is critically important to the fluid (more)

Alexander, Daniel

2009-01-01T23:59:59.000Z

143

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

Learning Control for Thermal Energy Storage Systems. In:Predictive Control of Thermal Energy Storage in Buildingmaking use of building thermal energy storage, and this work

Ma, Yudong

2012-01-01T23:59:59.000Z

144

The NOAA National Operational Model Archive and Distribution System -NOMADS  

E-Print Network [OSTI]

for access to real-time and retrospective high volume numerical weather prediction and climate models been on weather and reanalysis. Plans to support climate models and associated observational data a unified climate and weather model archive providing format independent access to retrospective models

145

Markovian Models for Electrical Load Prediction in Smart Buildings  

E-Print Network [OSTI]

Markovian Models for Electrical Load Prediction in Smart Buildings Muhammad Kumail Haider, Asad,13100004,ihsan.qazi}@lums.edu.pk Abstract. Developing energy consumption models for smart buildings is important develop parsimo- nious Markovian models of smart buildings for different periods in a day for predicting

California at Santa Barbara, University of

146

EXPANDING THE MODIFIED GAUSSIAN MODEL TO INCLUDE THE SPACE WEATHERING EFFECTS: ESTIMATION OF THE WEATHERING DEGREES OF PULSE-LASER TREATED OLIVINE SAMPLES. Y.  

E-Print Network [OSTI]

OF THE WEATHERING DEGREES OF PULSE-LASER TREATED OLIVINE SAMPLES. Y. Ueda1, 2 , T. Hiroi2 , C. M. Pieters2 and M creating the npFe0 by treating olivine (Fo91) pow- der samples with pulse laser at 1064 nm in wavelength of their olivine samples treated with laser energies of 0, 15, and 30 mJ. The refractive index spectra of Fe

Hiroi, Takahiro

147

TROPICAL DEFORESTATION MODELLING: A COMPARATIVE ANALYSIS OF DIFFERENT PREDICTIVE APPROACHES.  

E-Print Network [OSTI]

TROPICAL DEFORESTATION MODELLING: A COMPARATIVE ANALYSIS OF DIFFERENT PREDICTIVE APPROACHES-time discretisation; Remote Sensing; Neural Networks; Markov Chains; MCE; Dinamica; Risk management; Deforestation

Paris-Sud XI, Université de

148

Economic and Distributed Model Predictive Control of Nonlinear Systems  

E-Print Network [OSTI]

R. Amrit. Optimizing process economic performance us- ing2 Economic Model Predictive Control of Nonlinear Processof MPC and economic optimization of processes (e.g. , [2,

Heidarinejad, Mohsen

2012-01-01T23:59:59.000Z

149

accident prediction models: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 136 Title: Development of...

150

animal models predictive: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 222 Title: Development of...

151

accident prediction model: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 136 Title: Development of...

152

Global precipitation retrieval algorithm trained for SSMIS using a numerical weather prediction model: Design and evaluation  

E-Print Network [OSTI]

This paper presents and evaluates a global precipitation retrieval algorithm for the Special Sensor Microwave Imager/Sounder (SSMIS). It is based on those developed earlier for the Advanced Microwave Sounding Unit (AMSU) ...

Surussavadee, Chinnawat

153

Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs  

E-Print Network [OSTI]

Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. ...

Ganguly, Auroop Ratan

2002-01-01T23:59:59.000Z

154

A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting  

E-Print Network [OSTI]

iscriticalforcoastalCaliforniasolarforecasting. affectingsolarirradianceinsouthernCalifornia. solar photovoltaicgeneration(thesouthernCalifornia

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

155

Effects of vegetation and soil moisture on the simulated land surface processes from the coupled WRF/Noah model  

E-Print Network [OSTI]

simulations. Meso- scale models, which have been used not only for numerical weather prediction but also surface and atmosphere into numerical weather or climate prediction. This study describes coupled WRF [Chen et al., 1997; Pielke et al., 1997]. Numerical weather prediction with high spatial and tempo- ral

Small, Eric

156

Climate Prediction: The Limits of Ocean Models  

E-Print Network [OSTI]

We identify three major areas of ignorance which limit predictability in current ocean GCMs. One is the very crude representation of subgrid-scale mixing processes. These processes are parameterized with coefficients whose ...

Stone, Peter H.

157

Bootstrap Prediction for Returns and Volatilities in GARCH Models  

E-Print Network [OSTI]

Bootstrap Prediction for Returns and Volatilities in GARCH Models Lorenzo Pascuala , Juan Romob of GARCH processes is proposed. Financial market participants have shown an increasing interest Autoregressive Conditionally Heteroscedastic (GARCH) models, originally introduced by Bollerslev (1986), provide

Ortega, Esther Ruiz

158

Standard Model Predictions for the Muon $(g-2)/2$  

E-Print Network [OSTI]

The current status of the Standard Model predictions for the muon anomalous magnetic moment is described. Various contributions expected in the Standard Model are discussed. After the reevaluation of the leading-order hadronic term based on the new \\ep data, the theoretical prediction is more than three standard deviations lower than the experimental value.

S. I. Eidelman

2009-04-21T23:59:59.000Z

159

Web Page Rank Prediction with Markov Models Michalis Vazirgiannis  

E-Print Network [OSTI]

Web Page Rank Prediction with Markov Models Michalis Vazirgiannis INRIA Futurs Orsay, France a method for predicting the rank- ing position of a Web page. Assuming a set of successive past top-k rankings, we study the evolution of Web pages in terms of ranking trend sequences used for Markov Models

Paris-Sud XI, Université de

160

Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants  

E-Print Network [OSTI]

Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants M. Leskens , R.h.Bosgra@tudelft.nl, p.m.j.vandenhof@tudelft.nl Keywords : nonlinear model predictive control, municipal solid waste combus- tion Abstract : Combustion of municipal solid waste (MSW; = household waste) is used to reduce

Van den Hof, Paul

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Chance Constrained Model Predictive Control Alexander T. Schwarm  

E-Print Network [OSTI]

through a simulation case study on a high-purity distillation column. Suggestions for further improvements@uh.edu #12;2 Abstract This work focuses on robustness of model predictive control (MPC) with respect such property, particularly important for constrained model predictive control (MPC) systems

Nikolaou, Michael

162

Model Predictive Control of a Kaibel Distillation Column  

E-Print Network [OSTI]

column with model predictive control (MPC). A Kaibel distillation column has several advantages comparedModel Predictive Control of a Kaibel Distillation Column Martin Kvernland Ivar Halvorsen Sigurd only a single column shell. The distillation process is a multivariable process which leads

Skogestad, Sigurd

163

Demonstrating the improvement of predictive maturity of a computational model  

SciTech Connect (OSTI)

We demonstrate an improvement of predictive capability brought to a non-linear material model using a combination of test data, sensitivity analysis, uncertainty quantification, and calibration. A model that captures increasingly complicated phenomena, such as plasticity, temperature and strain rate effects, is analyzed. Predictive maturity is defined, here, as the accuracy of the model to predict multiple Hopkinson bar experiments. A statistical discrepancy quantifies the systematic disagreement (bias) between measurements and predictions. Our hypothesis is that improving the predictive capability of a model should translate into better agreement between measurements and predictions. This agreement, in turn, should lead to a smaller discrepancy. We have recently proposed to use discrepancy and coverage, that is, the extent to which the physical experiments used for calibration populate the regime of applicability of the model, as basis to define a Predictive Maturity Index (PMI). It was shown that predictive maturity could be improved when additional physical tests are made available to increase coverage of the regime of applicability. This contribution illustrates how the PMI changes as 'better' physics are implemented in the model. The application is the non-linear Preston-Tonks-Wallace (PTW) strength model applied to Beryllium metal. We demonstrate that our framework tracks the evolution of maturity of the PTW model. Robustness of the PMI with respect to the selection of coefficients needed in its definition is also studied.

Hemez, Francois M [Los Alamos National Laboratory; Unal, Cetin [Los Alamos National Laboratory; Atamturktur, Huriye S [CLEMSON UNIV.

2010-01-01T23:59:59.000Z

164

Regional-seasonal weather forecasting  

SciTech Connect (OSTI)

In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

1980-08-01T23:59:59.000Z

165

Severe Hail Prediction within a Spatiotemporal Relational Data Mining Framework  

E-Print Network [OSTI]

by incorporating output from an ensemble of storm scale numerical weather prediction models into a spatiotemporal within higher resolution numerical models can explicitly predict the size distributions of graupel, which relational data mining model that would produce probabilistic predictions of severe hail. The spatiotemporal

McGovern, Amy

166

Analysis of the singular vectors of the full-physics FSU Global Spectral Model  

E-Print Network [OSTI]

for the numerical weather prediction models has been the subject of numerous studies. For the barotropic atmosphere-growth estimation in numerical weather prediction and atmospheric predictability (Molteni and Palmer, 1993 predictability of an idealized model. However, singular vector analysis was carried out for the realistic meteo

Aluffi, Paolo

167

A two-timescale approach to nonlinear Model Predictive Control  

SciTech Connect (OSTI)

Model Predictive Control (MPC) schemes generate controls by using a model to predict the plant`s response to various control strategies. A problem arises when the underlying model is obtained by fitting a general nonlinear function, such as a neural network, to data: an exorbitant amount of data may be required to obtain accurate enough predictions. We describe a means of avoiding this problem that involves a simplified plant model which bases its predictions on averages of past control inputs. This model operates on a timescale slower than- the rate at which the controls are updated and the plant outputs are sampled. Not only does this technique give better closed-loop performance from the same amount of open-loop data, but it requires far less on-line computation as well. We illustrate the usefulness of this two-timescale approach by applying it to a simulated exothermic continuously stirred tank reactor with jacket dynamics.

Buescher, K.L.; Baum, C.C.

1994-10-01T23:59:59.000Z

168

Residential Weatherization  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared atEffectquestionnairesU.S. EnergyEnergy53 2.370Weatherization

169

Ensemble climate predictions using climate models and observational constraints  

E-Print Network [OSTI]

REVIEW Ensemble climate predictions using climate models and observational constraints BY PETER A. STOTT 1,* AND CHRIS E. FOREST 2 1 Hadley Centre for Climate Change (Reading Unit), Meteorology Building for constraining climate predictions based on observations of past climate change. The first uses large ensembles

170

Estimation and prediction in spatial models with block composite likelihoods  

E-Print Network [OSTI]

Estimation and prediction in spatial models with block composite likelihoods Jo Eidsvik1 , Benjamin, IA 50011, U.S.A. (niemi@iastate.edu) 1 #12;Abstract A block composite likelihood is developed for estimation and prediction in large spatial datasets. The composite likelihood is constructed from the joint

Reich, Brian J.

171

Conformal Higgs model: predicted dark energy density  

E-Print Network [OSTI]

Postulated universal Weyl conformal scaling symmetry provides an alternative to the $\\Lambda$CDM paradigm for cosmology. Recent applications to galactic rotation velocities, Hubble expansion, and a model of dark galactic halos explain qualitative phenomena and fit observed data without invoking dark matter. Significant revision of theory relevant to galactic collisions and clusters is implied, but not yet tested. Dark energy is found to be a consequence of conformal symmetry for the Higgs scalar field of electroweak physics. The present paper tests this implication. The conformal Higgs model acquires a gravitational effect described by a modified Friedmann cosmic evolution equation, shown to fit cosmological data going back to the cosmic microwave background epoch. The tachyonic mass parameter of the Higgs model becomes dark energy in the Friedmann equation. A dynamical model of this parameter, analogous to the Higgs mechanism for gauge boson mass, is derived and tested here. An approximate calculation yields a result consistent with the empirical magnitude inferred from Hubble expansion.

R. K. Nesbet

2014-11-03T23:59:59.000Z

172

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

T mixed T amb d OA ?T supply Cooling Fan Heating 20 Time (models for supply fan (5.6), cooling and heating coils (5.7)Solar radiation u cooling/heating coils supply fan dampers

Ma, Yudong

2012-01-01T23:59:59.000Z

173

Interactive software for model predictive control with simultaneous identification  

E-Print Network [OSTI]

This thesis is a unified practical framework in the theory of Model Predictive Control with Simultaneous Identification. The ability to change and visualize parameters on-line makes this toolbox attractive for control engineers, and for anyone...

Echeverria Del Rio, Pablo

2000-01-01T23:59:59.000Z

174

Standard Model Prediction of the Muon Anomalous Magnetic Moment  

E-Print Network [OSTI]

I review the present Standard Model prediction of the muon anomalous magnetic moment. The discrepancy with its experimental determination is (25.5 +- 8.0) x 10^-10, i.e., 3.2 standard deviations.

Joaquim Prades

2010-02-18T23:59:59.000Z

175

Hospital Readmission in General Medicine Patients: A Prediction Model  

E-Print Network [OSTI]

J Med. 1985;313: JGIM Hasan et al. : Hospital ReadmissionA Prediction Model Omar Hasan, MBBS, MPH 1,2 , David O.online December 15, 2009 Hasan et al. : Hospital Readmission

2010-01-01T23:59:59.000Z

176

Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes  

E-Print Network [OSTI]

Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes Christopher K. Wikle Department of Statistics, University of Missouri To appear: Ecology June 10, 2002 Key Words: Bayesian, Diffusion, Forecast, Hierarchical, House Finch, Invasive, Malthu- sian, State Space, Uncertainty Abstract

177

Productivity prediction model based on Bayesian analysis and productivity console  

E-Print Network [OSTI]

in poor planning and defies effective control of time and budgets in project management. In this research, we have built a productivity prediction model which uses productivity data from an ongoing project to reevaluate the initial productivity estimate...

Yun, Seok Jun

2005-08-29T23:59:59.000Z

178

In silico modeling to predict drug-induced phospholipidosis  

SciTech Connect (OSTI)

Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structureactivity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the construction and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 8081% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ? 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. The training set data in the models is derived from the FDA's phospholipidosis database. We find excellent predictivity values of the models based on external validation. The models can support drug screening and regulatory decision-making on DIPL.

Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov; Sadrieh, Nakissa

2013-06-01T23:59:59.000Z

179

Predictive clothing insulation model based on outdoor air and indoor operative temperatures  

E-Print Network [OSTI]

2012) Predictive clothing insulation model based on outdoorPredictive clothing insulation model based on outdoor airpredictive models of clothing insulation have been developed

Schiavon, Stefano; Lee, Kwang Ho

2012-01-01T23:59:59.000Z

180

Predictive modeling of pedestal structure in KSTAR using EPED model  

SciTech Connect (OSTI)

A predictive calculation is given for the structure of edge pedestal in the H-mode plasma of the KSTAR (Korea Superconducting Tokamak Advanced Research) device using the EPED model. Particularly, the dependence of pedestal width and height on various plasma parameters is studied in detail. The two codes, ELITE and HELENA, are utilized for the stability analysis of the peeling-ballooning and kinetic ballooning modes, respectively. Summarizing the main results, the pedestal slope and height have a strong dependence on plasma current, rapidly increasing with it, while the pedestal width is almost independent of it. The plasma density or collisionality gives initially a mild stabilization, increasing the pedestal slope and height, but above some threshold value its effect turns to a destabilization, reducing the pedestal width and height. Among several plasma shape parameters, the triangularity gives the most dominant effect, rapidly increasing the pedestal width and height, while the effect of elongation and squareness appears to be relatively weak. Implication of these edge results, particularly in relation to the global plasma performance, is discussed.

Han, Hyunsun; Kim, J. Y. [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of)] [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of); Kwon, Ohjin [Department of Physics, Daegu University, Gyeongbuk 712-714 (Korea, Republic of)] [Department of Physics, Daegu University, Gyeongbuk 712-714 (Korea, Republic of)

2013-10-15T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

The Isospin Model prediction for multi-pion tau decays  

E-Print Network [OSTI]

The predictions of an isospin model are compared with the branching ratios of the 5 and 6 pion decays of the tau lepton. In both cases, the isospin model suggests that the tau favours decays in which there is an omega resonance. Recent measurements of such tau decays confirm this hypothesis. If the decay of the tau to 7 pions also proceeds through an intermediate omega, then the isospin model predicts that the branching ratio of the tau to seven charged pions should be small when compared with other 7 pion decays. New limits on this mode appear to support this argument.

Randall J. Sobie

1998-10-19T23:59:59.000Z

182

Predicting Vehicle Crashworthiness: Validation of Computer Models for  

E-Print Network [OSTI]

Predicting Vehicle Crashworthiness: Validation of Computer Models for Functional and Hierarchical. Cafeo, Chin-Hsu Lin, and Jian Tu Abstract The CRASH computer model simulates the effect of a vehicle colliding against different barrier types. If it accurately represents real vehicle crash- worthiness

Berger, Jim

183

Weatherization Training for South Carolina's Muggy Weather  

Broader source: Energy.gov [DOE]

Why it makes sense for one technical college in Charleston, South Carolina is adding weatherization programs to their curriculum.

184

Cathy Zoi on Weatherization  

ScienceCinema (OSTI)

Right now, the Weatherization Assistance Program is now weatherizing 25,000 homes each month. So far 10,000 jobs have been created under the Recovery Act.

Zoi, Cath

2013-05-29T23:59:59.000Z

185

Cathy Zoi on Weatherization  

SciTech Connect (OSTI)

Right now, the Weatherization Assistance Program is now weatherizing 25,000 homes each month. So far 10,000 jobs have been created under the Recovery Act.

Zoi, Cath

2010-01-01T23:59:59.000Z

186

Lepton Flavor Violation in Predictive SUSY-GUT Models  

SciTech Connect (OSTI)

There have been many theoretical models constructed which aim to explain the neutrino masses and mixing patterns. While many of the models will be eliminated once more accurate determinations of the mixing parameters, especially sin{sup 2} 2{theta}{sub 13}, are obtained, charged lepton flavor violation (LFV) experiments are able to differentiate even further among the models. In this paper, they investigate various rare LFV processes, such as {ell}{sub i} {yields} {ell}{sub j} + {gamma} and {mu} - e conversion, in five predictive SUSY SO(10) models and their allowed soft SUSY breaking parameter space in the constrained minimal SUSY standard model (CMSSM). Utilizing the WMAP dark matter constraints, they obtain lower bounds on the branching ratios of these rare processes and find that at least three of the five models they consider give rise to predictions for {mu} {yields} e + {gamma} that will be tested by the MEG collaboration at PSI. in addition, the next generation {mu} - e conversion experiment has sensitivity to the predictions of all five models, making it an even more robust way to test these models. While generic studies have emphasized the dependence of the branching ratios of these rare processes on the reactor neutrino angle, {theta}{sub 13}, and the mass of the heaviest right-handed neutrino, M{sub 3}, they find very massive M{sub 3} is more significant than large {theta}{sub 13} in leading to branching ratios near to the present upper limits.

Albright, Carl H.; /Northern Illinois U. /Fermilab; Chen, Mu-Chun; /UC, Irvine

2008-02-01T23:59:59.000Z

187

Exploiting weather forecast data for cloud detection  

E-Print Network [OSTI]

Accurate, fast detection of clouds in satellite imagery has many applications, for example Numerical Weather Prediction (NWP) and climate studies of both the atmosphere and of the Earths surface temperature. Most ...

Mackie, Shona

2009-01-01T23:59:59.000Z

188

Reference wind farm selection for regional wind power prediction models  

E-Print Network [OSTI]

1 Reference wind farm selection for regional wind power prediction models Nils Siebert George.siebert@ensmp.fr, georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting is recognized today as a major requirement for a secure and economic integration of wind generation in power systems. This paper deals

Paris-Sud XI, Université de

189

A distributed accelerated gradient algorithm for distributed model predictive  

E-Print Network [OSTI]

of hydro power plants is to manage the available water resources efficiently, while following an optimal is applied to the power reference tracking problem of a hydro power valley (HPV) system. The applied power control, Distributed optimization, Accelerated gradient algorithm, Model predictive control

Como, Giacomo

190

RESEARCH ARTICLE Climate change model predicts 33 % rice yield decrease  

E-Print Network [OSTI]

RESEARCH ARTICLE Climate change model predicts 33 % rice yield decrease in 2100 in Bangladesh parameters on rice. The effects of climate change on yield of a popular winter rice cultivar in Bangladesh online: 12 June 2012 # INRA and Springer-Verlag, France 2012 Abstract In Bangladesh, projected climate

Boyer, Edmond

191

Model to predict the mechanical behaviour of oriented rigid PVC  

E-Print Network [OSTI]

Model to predict the mechanical behaviour of oriented rigid PVC D. J. Hitt*1 and D. Miroshnychenko2 The mechanical properties of PVC sheets can be modified substantially by both uniaxial and biaxial stretching pattern in the relationship between tensile properties of oriented PVC products and imposed strains

Miroshnychenko, Dmitri

192

Vehicle Trajectory Prediction based on Motion Model and Maneuver Recognition  

E-Print Network [OSTI]

Vehicle Trajectory Prediction based on Motion Model and Maneuver Recognition Adam Houenou, Philippe is a crucial task for an autonomous vehicle, in order to avoid collisions on its planned trajectory. It is also necessary for many Advanced Driver Assistance Systems, where the ego- vehicle's trajectory has

Paris-Sud XI, Universit de

193

Application of Sampling Based Model Predictive Control to an Autonomous  

E-Print Network [OSTI]

Unmanned Underwater Vehicles (UUVs) can be utilized to perform difficult tasks in cluttered environments55 Application of Sampling Based Model Predictive Control to an Autonomous Underwater Vehicle for an autonomous underwater vehicle (AUV). The algorithm combines the benefits of sampling-based motion planning

Collins, Emmanuel

194

Predicting solar cycle 24 with a solar dynamo model  

E-Print Network [OSTI]

Whether the upcoming cycle 24 of solar activity will be strong or not is being hotly debated. The solar cycle is produced by a complex dynamo mechanism. We model the last few solar cycles by `feeding' observational data of the Sun's polar magnetic field into our solar dynamo model. Our results fit the observed sunspot numbers of cycles 21-23 extremely well and predict that cycle~24 will be about 35% weaker than cycle~23.

Arnab Rai Choudhuri; Piyali Chatterjee; Jie Jiang

2007-01-18T23:59:59.000Z

195

A minimal and predictive $T_7$ lepton flavor 331 model  

E-Print Network [OSTI]

We present a model based on the $SU(3)_{C}\\otimes SU(3)_{L}\\otimes U(1)_{X}$ gauge group having an extra $T_{7}\\otimes Z_{3}\\otimes Z_{14}$ flavor group, where the light active neutrino masses arise via double seesaw mechanism and the observed charged lepton mass hierarchy is a consequence of the $Z_{14}$ symmetry breaking at very high energy. In our minimal and predictive $T_7$ lepton flavor 331 model, the spectrum of neutrinos includes very light active neutrinos and heavy and very heavy sterile neutrinos. The obtained neutrino mixing parameters and neutrino mass squared splittings are compatible with the neutrino oscillation experimental data, for both normal and inverted hierarchies. The model predicts CP conservation in neutrino oscillations.

Hernndez, A E Crcamo

2015-01-01T23:59:59.000Z

196

Prediction of Leptonic CP Phase in $A_4$ symmetric model  

E-Print Network [OSTI]

We consider minimal modifications to tribimaximal (TBM) mixing matrix which accommodate non-zero mixing angle $\\theta_{13}$ and CP violation. We derive four possible forms for the minimal modifications to TBM mixing in a model with $A_4$ flavor symmetry by incorporating symmetry breaking terms appropriately. We show how possible values of the Dirac-type CP phase $\\delta_D$ can be predicted with regards to two neutrino mixing angles in the standard parametrization of the neutrino mixing matrix. Carrying out numerical analysis based on the recent updated experimental results for neutrino mixing angles, we predict the values of the CP phase for all possible cases. We also confront our predictions of the CP phase with the updated fit.

Sin Kyu Kang; Morimitsu Tanimoto

2015-01-29T23:59:59.000Z

197

Probabilistic Forecasts of Wind Speed: Ensemble Model Output Statistics  

E-Print Network [OSTI]

. Over the past two decades, ensembles of numerical weather prediction (NWP) models have been developed and phrases: Continuous ranked probability score; Density forecast; Ensem- ble system; Numerical weather prediction; Heteroskedastic censored regression; Tobit model; Wind energy. 1 #12;1 Introduction Accurate

Washington at Seattle, University of

198

Predictive Models of Li-ion Battery Lifetime (Presentation)  

SciTech Connect (OSTI)

Predictive models of Li-ion battery reliability must consider a multiplicity of electrochemical, thermal and mechanical degradation modes experienced by batteries in application environments. Complicating matters, Li-ion batteries can experience several path dependent degradation trajectories dependent on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. Lacking accurate models and tests, lifetime uncertainty must be absorbed by overdesign and warranty costs. Degradation models are needed that predict lifetime more accurately and with less test data. Models should also provide engineering feedback for next generation battery designs. This presentation reviews both multi-dimensional physical models and simpler, lumped surrogate models of battery electrochemical and mechanical degradation. Models are compared with cell- and pack-level aging data from commercial Li-ion chemistries. The analysis elucidates the relative importance of electrochemical and mechanical stress-induced degradation mechanisms in real-world operating environments. Opportunities for extending the lifetime of commercial battery systems are explored.

Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Shi, Y.; Pesaran, A.

2014-09-01T23:59:59.000Z

199

The Numerical Modelling Research and Development Division is responsible for research into and develop-  

E-Print Network [OSTI]

into and develop- ment of numerical weather prediction models and other meteorological applications, that are opera in the field of numerical weather prediction: atmospheric and oceanographic modelling, physical and statistical132 The Numerical Modelling Research and Development Division is responsible for research

Haak, Hein

200

Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction  

E-Print Network [OSTI]

from numerical weather prediction models, which is based on a state-of-the-art circular-processing techniques for forecasts from numerical weather prediction models tend to become ineffective or inapplicableBias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction Le

Washington at Seattle, University of

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Weather-based forecasts of California crop yields  

SciTech Connect (OSTI)

Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over the 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.

Lobell, D B; Cahill, K N; Field, C B

2005-09-26T23:59:59.000Z

202

Stochastic Models Predict User Behavior in Social Media  

E-Print Network [OSTI]

User response to contributed content in online social media depends on many factors. These include how the site lays out new content, how frequently the user visits the site, how many friends the user follows, how active these friends are, as well as how interesting or useful the content is to the user. We present a stochastic modeling framework that relates a user's behavior to details of the site's user interface and user activity and describe a procedure for estimating model parameters from available data. We apply the model to study discussions of controversial topics on Twitter, specifically, to predict how followers of an advocate for a topic respond to the advocate's posts. We show that a model of user behavior that explicitly accounts for a user transitioning through a series of states before responding to an advocate's post better predicts response than models that fail to take these states into account. We demonstrate other benefits of stochastic models, such as their ability to identify users who a...

Hogg, Tad; Smith, Laura M

2013-01-01T23:59:59.000Z

203

DECENTRALIZED ROBUST NONLINEAR MODEL PREDICTIVE CONTROLLER FOR UNMANNED AERIAL SYSTEMS  

E-Print Network [OSTI]

Measurement Unit LFT : Linear Fractional Transformation LPV : Linear Parameter-Varying LTI : Linear Time-Invariant LTV : Linear Time-Varying NED : North-East-Down (N)MPC : (Nonlinear) Model Predictive Controller MIMO : Multi Input Multi Output..., showing superior tracking performance over conventional multi-loop proportional-derivative controllers. Ref. [50] applied linear MPC to a small helicopter, easily incorporating control and state constraints, and reducing the typical computational burden...

Garcia, Gonzalo Andres

2013-05-31T23:59:59.000Z

204

Prediction of interest rate using CKLS model with stochastic parameters  

SciTech Connect (OSTI)

The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector ?{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j?-th time point where j?j??j+n. To model the variation of ?{sup (j)}, we assume that ?{sup (j)} depends on ?{sup (j?m)}, ?{sup (j?m+1)},, ?{sup (j?1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d?2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.

Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)

2014-06-19T23:59:59.000Z

205

Fuel Conditioning Facility Electrorefiner Model Predictions versus Measurements  

SciTech Connect (OSTI)

Electrometallurgical treatment of spent nuclear fuel is performed in the Fuel Conditioning Facility (FCF) at the Idaho National Laboratory (INL) by electrochemically separating uranium from the fission products and structural materials in a vessel called an electrorefiner (ER). To continue processing without waiting for sample analyses to assess process conditions, an ER process model predicts the composition of the ER inventory and effluent streams via multicomponent, multi-phase chemical equilibrium for chemical reactions and a numerical solution to differential equations for electro-chemical transport. The results of the process model were compared to the electrorefiner measured data.

D Vaden

2007-10-01T23:59:59.000Z

206

Intelligent weather agent for aircraft severe weather avoidance  

E-Print Network [OSTI]

avoidance capability has increased. In this thesis, an intelligent weather agent is developed for general aviation aircraft. Using a radar image from an onboard weather radar, the intelligent weather agent determines the safest path around severe weather...

Bokadia, Sangeeta

2002-01-01T23:59:59.000Z

207

Fast prediction and evaluation of gravitational waveforms using surrogate models  

E-Print Network [OSTI]

[Abridged] We propose a solution to the problem of quickly and accurately predicting gravitational waveforms within any given physical model. The method is relevant for both real-time applications and in more traditional scenarios where the generation of waveforms using standard methods can be prohibitively expensive. Our approach is based on three offline steps resulting in an accurate reduced-order model that can be used as a surrogate for the true/fiducial waveform family. First, a set of m parameter values is determined using a greedy algorithm from which a reduced basis representation is constructed. Second, these m parameters induce the selection of m time values for interpolating a waveform time series using an empirical interpolant. Third, a fit in the parameter dimension is performed for the waveform's value at each of these m times. The cost of predicting L waveform time samples for a generic parameter choice is of order m L + m c_f online operations where c_f denotes the fitting function operation count and, typically, m standard ways. Surrogate model building for other waveform models follow the same steps and have the same low online scaling cost. For expensive numerical simulations of binary black hole coalescences we thus anticipate large speedups in generating new waveforms with a surrogate. As waveform generation is one of the dominant costs in parameter estimation algorithms and parameter space exploration, surrogate models offer a new and practical way to dramatically accelerate such studies without impacting accuracy.

Scott E. Field; Chad R. Galley; Jan S. Hesthaven; Jason Kaye; Manuel Tiglio

2014-02-28T23:59:59.000Z

208

Development of a scalable model for predicting arsenic transport coupled with oxidation and adsorption reactions  

E-Print Network [OSTI]

modeling; Contaminant transport; Scaling; Numerical modeling 1. Introduction Management of groundwaterDevelopment of a scalable model for predicting arsenic transport coupled with oxidation is critical for predicting its transport dynamics in groundwater systems. We completed batch experiments

Clement, Prabhakar

209

Virtual Models for Prediction of Wind Turbine Parameters  

E-Print Network [OSTI]

AbstractIn this paper, a data-driven methodology for the development of virtual models of a wind turbine is presented. To demonstrate the proposed methodology, two parameters of the wind turbine have been selected for modeling, namely, power output and rotor speed. A virtual model for each of the two parameters is developed and tested with data collected at a wind farm. Both models consider controllable and noncontrollable parameters of the wind turbine, as well as the delay effect of wind speed and other parameters. To mitigate data bias of each virtual model and ensure its robustness, a training set is assembled from ten randomly selected turbines. The performance of a virtual model is largely determined by the input parameters selected and the data mining algorithms used to extract the model. Several data mining algorithms for parameter selection and model extraction are analyzed. The research presented in the paper is illustrated with computational results. Index TermsData mining, parameter selection, power prediction, virtual model, wind turbine. I.

Andrew Kusiak

210

Supporting technology for enhanced oil recovery: Polymer predictive model  

SciTech Connect (OSTI)

The Polymer Flood Predictive Model (PFPM) was developed by Scientific Software-Intercomp for the National Petroleum Council's (NPC) 1984 survey of US enhanced oil recovery potential (NPC, 1984). The PFPM is switch-selectable for either polymer or waterflooding, and an option in the model allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. The architecture of the PFPM is similar to that of the other predictive models in the series: in-situ combustion, steam drive (Aydelotte and Pope, 1983), chemical flooding (Paul et al., 1982) and CO/sub 2/ miscible flooding (Paul et al., 1984). In the PFPM, an oil rate versus time function for a single pattern is computed and then is passed to the economic calculations. Data for reservoir and process development, operating costs, and a pattern schedule (if multiple patterns are desired) allow the computation of discounted cash flow and other measures of profitability. The PFPM is a three-dimensional (stratified, five-spot), two-phase (water and oil) model which computes water from breakthrough and oil recovery using fractional flow theory, and models areal and vertical sweeps using a streamtube approach. A correlation based on numerical simulation results is used to model the polymer slug size effect. The physical properties of polymer fluids, such as adsorption, permeability reduction, and non-Newtonian effects, are included in the model. Pressure drop between the injector and producer is kept constant, and the injectivity at each time step is calculated based on the mobility in each streamtube. Heterogeneity is accounted for by either entering detailed layer data or using the Dykstra-Parsons coefficient for a reservoir with a log-normal permeability distribution. 24 refs., 27 figs., 59 tabs.

Not Available

1986-12-01T23:59:59.000Z

211

Quarterly Journal of the Royal Meteorological Society Q. J. R. Meteorol. Soc. 00: 115 (0000) Controlling model error of underdamped forecast models in  

E-Print Network [OSTI]

-dependent predictability, ensemble methods have become popular for producing numerical weather forecasts (Molteni weather prediction or climate dynamics. In such simulations numerical codes tend to produce large errors of the forecast model and a numerical model error due to the choice of the numerical method used to simulate those

Gottwald, Georg A.

212

Model Predictive Control of Integrated Gasification Combined Cycle Power Plants  

SciTech Connect (OSTI)

The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

B. Wayne Bequette; Priyadarshi Mahapatra

2010-08-31T23:59:59.000Z

213

Time Step Sensitivity of Nonlinear Atmospheric Models: Numerical Convergence, Truncation Error Growth, and Ensemble Design  

E-Print Network [OSTI]

1973; Oran and Boris 1987; Murray 1989; Gershenfeld 1999). Weather and climate prediction models, which to the initial conditions, which is a major source of uncertainty in Numerical Weather Prediction (NWP; eTime Step Sensitivity of Nonlinear Atmospheric Models: Numerical Convergence, Truncation Error

Judd, Kevin

214

A perfectly matched layer formulation for the nonlinear shallow water equations models: The split  

E-Print Network [OSTI]

In a limited-area numerical weather prediction model, the lateral boundaries are not physical boundaries interest since the early days of numerical weather prediction. Several good reviews are availableA perfectly matched layer formulation for the nonlinear shallow water equations models: The split

Navon, Michael

215

Predictive Modeling of fMRI Brain States using Functional Canonical Correlation Analysis  

E-Print Network [OSTI]

Predictive Modeling of fMRI Brain States using Functional Canonical Correlation Analysis S Abstract. We present a novel method for predictive modeling of human brain states from functional for prediction of naturalistic stimuli from unknown fMRI data shows that the method nds highly predictive brain

Smeulders, Arnold

216

Predictive modeling of reactive wetting and metal joining.  

SciTech Connect (OSTI)

The performance, reproducibility and reliability of metal joints are complex functions of the detailed history of physical processes involved in their creation. Prediction and control of these processes constitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy and reactive wetting. Understanding this process requires coupling strong molecularscale chemistry at the interface with microscopic (diffusion) and macroscopic mass transport (flow) inside the liquid followed by subsequent cooling and solidification of the new metal mixture. The final joint displays compositional heterogeneity and its resulting microstructure largely determines the success or failure of the entire component. At present there exists no computational tool at Sandia that can predict the formation and success of a braze joint, as current capabilities lack the ability to capture surface/interface reactions and their effect on interface properties. This situation precludes us from implementing a proactive strategy to deal with joining problems. Here, we describe what is needed to arrive at a predictive modeling and simulation capability for multicomponent metals with complicated phase diagrams for melting and solidification, incorporating dissolutive and composition-dependent wetting.

van Swol, Frank B.

2013-09-01T23:59:59.000Z

217

An approach to model validation and model-based prediction -- polyurethane foam case study.  

SciTech Connect (OSTI)

Enhanced software methodology and improved computing hardware have advanced the state of simulation technology to a point where large physics-based codes can be a major contributor in many systems analyses. This shift toward the use of computational methods has brought with it new research challenges in a number of areas including characterization of uncertainty, model validation, and the analysis of computer output. It is these challenges that have motivated the work described in this report. Approaches to and methods for model validation and (model-based) prediction have been developed recently in the engineering, mathematics and statistical literatures. In this report we have provided a fairly detailed account of one approach to model validation and prediction applied to an analysis investigating thermal decomposition of polyurethane foam. A model simulates the evolution of the foam in a high temperature environment as it transforms from a solid to a gas phase. The available modeling and experimental results serve as data for a case study focusing our model validation and prediction developmental efforts on this specific thermal application. We discuss several elements of the ''philosophy'' behind the validation and prediction approach: (1) We view the validation process as an activity applying to the use of a specific computational model for a specific application. We do acknowledge, however, that an important part of the overall development of a computational simulation initiative is the feedback provided to model developers and analysts associated with the application. (2) We utilize information obtained for the calibration of model parameters to estimate the parameters and quantify uncertainty in the estimates. We rely, however, on validation data (or data from similar analyses) to measure the variability that contributes to the uncertainty in predictions for specific systems or units (unit-to-unit variability). (3) We perform statistical analyses and hypothesis tests as a part of the validation step to provide feedback to analysts and modelers. Decisions on how to proceed in making model-based predictions are made based on these analyses together with the application requirements. Updating modifying and understanding the boundaries associated with the model are also assisted through this feedback. (4) We include a ''model supplement term'' when model problems are indicated. This term provides a (bias) correction to the model so that it will better match the experimental results and more accurately account for uncertainty. Presumably, as the models continue to develop and are used for future applications, the causes for these apparent biases will be identified and the need for this supplementary modeling will diminish. (5) We use a response-modeling approach for our predictions that allows for general types of prediction and for assessment of prediction uncertainty. This approach is demonstrated through a case study supporting the assessment of a weapons response when subjected to a hydrocarbon fuel fire. The foam decomposition model provides an important element of the response of a weapon system in this abnormal thermal environment. Rigid foam is used to encapsulate critical components in the weapon system providing the needed mechanical support as well as thermal isolation. Because the foam begins to decompose at temperatures above 250 C, modeling the decomposition is critical to assessing a weapons response. In the validation analysis it is indicated that the model tends to ''exaggerate'' the effect of temperature changes when compared to the experimental results. The data, however, are too few and to restricted in terms of experimental design to make confident statements regarding modeling problems. For illustration, we assume these indications are correct and compensate for this apparent bias by constructing a model supplement term for use in the model-based predictions. Several hypothetical prediction problems are created and addressed. Hypothetical problems are used because no guidance was provided concern

Dowding, Kevin J.; Rutherford, Brian Milne

2003-07-01T23:59:59.000Z

218

EnKF Assimilation of High-Resolution, Mobile Doppler Radar Data of the 4 May 2007 Greensburg, Kansas, Supercell into a Numerical Cloud Model  

E-Print Network [OSTI]

Kalman filter (EnKF) technique into a non- hydrostatic, compressible numerical weather prediction model weather prediction (NWP) models to improve under- standing of convective storm dynamics is now a fairly, Kansas, Supercell into a Numerical Cloud Model ROBIN L. TANAMACHI,*,1,# LOUIS J. WICKER,@ DAVID C. DOWELL

Xue, Ming

219

Final Project Report: Release of aged contaminants from weathered sediments: Effects of sorbate speciation on scaling of reactive transport  

SciTech Connect (OSTI)

Hanford sediments impacted by hyperalkaline high level radioactive waste have undergone incongruent silicate mineral weathering concurrent with contaminant uptake. In this project, we studied the impact of background pore water (BPW) on strontium, cesium and iodine desorption and transport in Hanford sediments that were experimentally weathered by contact with simulated hyperalkaline tank waste leachate (STWL) solutions. Using those lab-weathered Hanford sediments (HS) and model precipitates formed during nucleation from homogeneous STWL solutions (HN), we (i) provided detailed characterization of reaction products over a matrix of field-relevant gradients in contaminant concentration, PCO2, and reaction time; (ii) improved molecular-scale understanding of how sorbate speciation controls contaminant desorption from weathered sediments upon removal of caustic sources; and (iii) developed a mechanistic, predictive model of meso- to field-scale contaminant reactive transport under these conditions.

Jon Chorover, University of Arizona; Peggy O'‚ € ‚ ™ Day, University of California, Merced; Karl Mueller, Penn State University; Wooyong Um, Pacific Northwest National Laboratory; Carl Steefel, Lawrence Berkeley National Laboratory

2012-10-01T23:59:59.000Z

220

Development of a fourth generation predictive capability maturity model.  

SciTech Connect (OSTI)

The Predictive Capability Maturity Model (PCMM) is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated for an intended application. The primary application of this tool at Sandia National Laboratories (SNL) has been for physics-based computational simulations in support of nuclear weapons applications. The two main goals of a PCMM evaluation are 1) the communication of computational simulation capability, accurately and transparently, and 2) the development of input for effective planning. As a result of the increasing importance of computational simulation to SNL's mission, the PCMM has evolved through multiple generations with the goal to provide more clarity, rigor, and completeness in its application. This report describes the approach used to develop the fourth generation of the PCMM.

Hills, Richard Guy; Witkowski, Walter R.; Urbina, Angel; Rider, William J.; Trucano, Timothy Guy

2013-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
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to obtain the most current and comprehensive results.


221

Crucial stages of protein folding through a solvable model: Predicting target sites  

E-Print Network [OSTI]

Crucial stages of protein folding through a solvable model: Predicting target sites for enzyme. Keywords: Protein-folding modeling; prediction of key folding sites; HIV-1 protease; drug resistance One

Cecconi, Fabio

222

A Model to Predict Work-Related Fatigue Based on Hours of Work  

E-Print Network [OSTI]

A Model to Predict Work-Related Fatigue Based on Hours of Work Gregory D. Roach, Adam Fletcher, and Drew Dawson ROACH GD, FLETCHER A, DAWSON D. A model to predict work- related fatigue based on hours

223

Supporting technology for enhanced oil recovery: Chemical flood predictive model  

SciTech Connect (OSTI)

The Chemical Flood Predictive Model (CFPM) was developed by Scientific Software-Intercomp for the US Department of Energy and was used in the National Petroleum Council's (NPC) 1984 survey of US enhanced oil recovery potential (NPC, 1984). The CFPM models micellar (surfactant)-polymer (MP) floods in reservoirs which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option is available in the model which allows a rough estimate of oil recovery by caustic (alkaline) or caustic-polymer processes. This ''caustic'' option, added for the NPC survey, is not modeled as a separate process. Rather, the caustic and caustic-polymer oil recoveries are computed simply as 15% and 40%, respectively, of the MP oil recovery. In the CFPM, an oil rate versus time function for a single pattern is computed and the results are passed to the economic routines. To estimate multi-pattern project behavior, a pattern development schedule must be specified. After-tax cash flow is computed by combining revenues with capital costs for drilling, conversion and upgrading of wells, chemical handling costs, fixed and variable operating costs, injectant costs, depreciation, royalties, severance, state, federal, and windfall profit taxes, cost and price inflation rates, and the discount rate. A lumped parameter uncertainty routine is used to estimate risk, and allows for variation in computed project performance within an 80% confidence interval. The CFPM uses theory and the results of numerical simulation to predict MP oil recovery in five-spot patterns. Oil-bank and surfactant breakthrough and project life are determined from fractional flow theory. A Koval-type factor, based on the Dykstra-Parsons (1950) coefficient, is used to account for the effects of reservoir heterogeneity on surfactant and oil bank velocities. 18 refs., 17 figs., 27 tabs.

Ray, R.M.; Munoz, J.D.

1986-12-01T23:59:59.000Z

224

Predicting the Texas Windstorm Insurance Association Payout for Commercial Property Loss Due to Ike Based on Weather, Geographical, and Building Variables  

E-Print Network [OSTI]

Payout Ratio Model ........................................................................................ 5? Importance and Expected Benefits ................................................................................. 8? Assumptions... 5. Parcel Information (2008 Improvement Value) ................................................ 30? Figure 6. Method of Analysis ........................................................................................... 34? Figure 7. Locations...

Zhu, Kehui

2013-04-04T23:59:59.000Z

225

Weather-Corrected Performance Ratio  

SciTech Connect (OSTI)

Photovoltaic (PV) system performance depends on both the quality of the system and the weather. One simple way to communicate the system performance is to use the performance ratio (PR): the ratio of the electricity generated to the electricity that would have been generated if the plant consistently converted sunlight to electricity at the level expected from the DC nameplate rating. The annual system yield for flat-plate PV systems is estimated by the product of the annual insolation in the plane of the array, the nameplate rating of the system, and the PR, which provides an attractive way to estimate expected annual system yield. Unfortunately, the PR is, again, a function of both the PV system efficiency and the weather. If the PR is measured during the winter or during the summer, substantially different values may be obtained, making this metric insufficient to use as the basis for a performance guarantee when precise confidence intervals are required. This technical report defines a way to modify the PR calculation to neutralize biases that may be introduced by variations in the weather, while still reporting a PR that reflects the annual PR at that site given the project design and the project weather file. This resulting weather-corrected PR gives more consistent results throughout the year, enabling its use as a metric for performance guarantees while still retaining the familiarity this metric brings to the industry and the value of its use in predicting actual annual system yield. A testing protocol is also presented to illustrate the use of this new metric with the intent of providing a reference starting point for contractual content.

Dierauf, T.; Growitz, A.; Kurtz, S.; Cruz, J. L. B.; Riley, E.; Hansen, C.

2013-04-01T23:59:59.000Z

226

Modelling Monsoons: Understanding and Predicting Current and Future Behaviour  

SciTech Connect (OSTI)

The global monsoon system is so varied and complex that understanding and predicting its diverse behaviour remains a challenge that will occupy modellers for many years to come. Despite the difficult task ahead, an improved monsoon modelling capability has been realized through the inclusion of more detailed physics of the climate system and higher resolution in our numerical models. Perhaps the most crucial improvement to date has been the development of coupled ocean-atmosphere models. From subseasonal to interdecadal timescales, only through the inclusion of air-sea interaction can the proper phasing and teleconnections of convection be attained with respect to sea surface temperature variations. Even then, the response to slow variations in remote forcings (e.g., El Nino-Southern Oscillation) does not result in a robust solution, as there are a host of competing modes of variability that must be represented, including those that appear to be chaotic. Understanding the links between monsoons and land surface processes is not as mature as that explored regarding air-sea interactions. A land surface forcing signal appears to dominate the onset of wet season rainfall over the North American monsoon region, though the relative role of ocean versus land forcing remains a topic of investigation in all the monsoon systems. Also, improved forecasts have been made during periods in which additional sounding observations are available for data assimilation. Thus, there is untapped predictability that can only be attained through the development of a more comprehensive observing system for all monsoon regions. Additionally, improved parameterizations - for example, of convection, cloud, radiation, and boundary layer schemes as well as land surface processes - are essential to realize the full potential of monsoon predictability. Dynamical considerations require ever increased horizontal resolution (probably to 0.5 degree or higher) in order to resolve many monsoon features including, but not limited to, the Mei-Yu/Baiu sudden onset and withdrawal, low-level jet orientation and variability, and orographic forced rainfall. Under anthropogenic climate change many competing factors complicate making robust projections of monsoon changes. Without aerosol effects, increased land-sea temperature contrast suggests strengthened monsoon circulation due to climate change. However, increased aerosol emissions will reflect more solar radiation back to space, which may temper or even reduce the strength of monsoon circulations compared to the present day. A more comprehensive assessment is needed of the impact of black carbon aerosols, which may modulate that of other anthropogenic greenhouse gases. Precipitation may behave independently from the circulation under warming conditions in which an increased atmospheric moisture loading, based purely on thermodynamic considerations, could result in increased monsoon rainfall under climate change. The challenge to improve model parameterizations and include more complex processes and feedbacks pushes computing resources to their limit, thus requiring continuous upgrades of computational infrastructure to ensure progress in understanding and predicting the current and future behavior of monsoons.

Turner, A; Sperber, K R; Slingo, J M; Meehl, G A; Mechoso, C R; Kimoto, M; Giannini, A

2008-09-16T23:59:59.000Z

227

Critical Fire Weather Patterns  

E-Print Network [OSTI]

.1 Sundowner Winds FAT -- 1.1 Southeastern U.S. Fire Weather LIT -- 1.1 East Winds MFR -- 1.1 East Winds OLM

Clements, Craig

228

RESIDUA UPGRADING EFFICIENCY IMPROVEMENT MODELS: COKE FORMATION PREDICTABILITY MAPS  

SciTech Connect (OSTI)

The dispersed particle solution model of petroleum residua structure was used to develop predictors for pyrolytic coke formation. Coking Indexes were developed in prior years that measure how near a pyrolysis system is to coke formation during the coke formation induction period. These have been demonstrated to be universally applicable for residua regardless of the source of the material. Coking onset is coincidental with the destruction of the ordered structure and the formation of a multiphase system. The amount of coke initially formed appears to be a function of the free solvent volume of the original residua. In the current work, three-dimensional coke make predictability maps were developed at 400 C, 450 C, and 500 C (752 F, 842 F, and 932 F). These relate residence time and free solvent volume to the amount of coke formed at a particular pyrolysis temperature. Activation energies for two apparent types of zero-order coke formation reactions were estimated. The results provide a new tool for ranking residua, gauging proximity to coke formation, and predicting initial coke make tendencies.

John F. Schabron; A. Troy Pauli; Joseph F. Rovani Jr.

2002-05-01T23:59:59.000Z

229

ZEPHYR THE PREDICTION MODELS T.S. Nielsen, H. Madsen, H. Aa. Nielsen  

E-Print Network [OSTI]

models and methods for predicting the wind power output from wind farms. The system is being developed Modelling (IMM) as the modelling team and all the Danish utilities as partners and users. The new models INTRODUCTION Historically there has been two models used in Denmark to predict the power production from wind

230

Hybrid coupled models of the tropical Paci c | II ENSO prediction  

E-Print Network [OSTI]

Hybrid coupled models of the tropical Paci#12;c | II ENSO prediction by Youmin Tang 1 , William W: ytang@cims.nyu.edu #12; Abstract Two hybrid coupled models (HCMs), a dynamical ocean model coupled Introduction Models for ENSO prediction can be categorized into purely statistical models, hybrid coupled

Hsieh, William

231

The Weatherization Training program at Pennsylvania College  

SciTech Connect (OSTI)

A look into some of the remarkable work being done in the Weatherization Training program at Pennsylvania College. Penn College's program has served as the model for six other training centers in Pennsylvania alone.

Meville, Jeff; Wilson, Jack; Manz, John; Gannett, Kirk; Smith, Franzennia

2010-01-01T23:59:59.000Z

232

The Weatherization Training program at Pennsylvania College  

ScienceCinema (OSTI)

A look into some of the remarkable work being done in the Weatherization Training program at Pennsylvania College. Penn College's program has served as the model for six other training centers in Pennsylvania alone.

Meville, Jeff; Wilson, Jack; Manz, John; Gannett, Kirk; Smith, Franzennia;

2013-05-29T23:59:59.000Z

233

Adaptive model predictive process control using neural networks  

DOE Patents [OSTI]

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

Buescher, Kevin L. (Los Alamos, NM); Baum, Christopher C. (Mazomanie, WI); Jones, Roger D. (Espanola, NM)

1997-01-01T23:59:59.000Z

234

Adaptive model predictive process control using neural networks  

DOE Patents [OSTI]

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

Buescher, K.L.; Baum, C.C.; Jones, R.D.

1997-08-19T23:59:59.000Z

235

LIFETIME PREDICTION FOR MODEL 9975 O-RINGS IN KAMS  

SciTech Connect (OSTI)

The Savannah River Site (SRS) is currently storing plutonium materials in the K-Area Materials Storage (KAMS) facility. The materials are packaged per the DOE 3013 Standard and transported and stored in KAMS in Model 9975 shipping packages, which include double containment vessels sealed with dual O-rings made of Parker Seals compound V0835-75 (based on Viton{reg_sign} GLT). The outer O-ring of each containment vessel is credited for leaktight containment per ANSI N14.5. O-ring service life depends on many factors, including the failure criterion, environmental conditions, overall design, fabrication quality and assembly practices. A preliminary life prediction model has been developed for the V0835-75 O-rings in KAMS. The conservative model is based primarily on long-term compression stress relaxation (CSR) experiments and Arrhenius accelerated-aging methodology. For model development purposes, seal lifetime is defined as a 90% loss of measurable sealing force. Thus far, CSR experiments have only reached this target level of degradation at temperatures {ge} 300 F. At lower temperatures, relaxation values are more tolerable. Using time-temperature superposition principles, the conservative model predicts a service life of approximately 20-25 years at a constant seal temperature of 175 F. This represents a maximum payload package at a constant ambient temperature of 104 F, the highest recorded in KAMS to date. This is considered a highly conservative value as such ambient temperatures are only reached on occasion and for short durations. The presence of fiberboard in the package minimizes the impact of such temperature swings, with many hours to several days required for seal temperatures to respond proportionately. At 85 F ambient, a more realistic but still conservative value, bounding seal temperatures are reduced to {approx}158 F, with an estimated seal lifetime of {approx}35-45 years. The actual service life for O-rings in a maximum wattage package likely lies higher than the estimates due to the conservative assumptions used for the model. For lower heat loads at similar ambient temperatures, seal lifetime is further increased. The preliminary model is based on several assumptions that require validation with additional experiments and longer exposures at more realistic conditions. The assumption of constant exposure at peak temperature is believed to be conservative. Cumulative damage at more realistic conditions will likely be less severe but is more difficult to assess based on available data. Arrhenius aging behavior is expected, but non-Arrhenius behavior is possible. Validation of Arrhenius behavior is ideally determined from longer tests at temperatures closer to actual service conditions. CSR experiments will therefore continue at lower temperatures to validate the model. Ultrasensitive oxygen consumption analysis has been shown to be useful in identifying non-Arrhenius behavior within reasonable test periods. Therefore, additional experiments are recommended and planned to validate the model.

Hoffman, E.; Skidmore, E.

2009-11-24T23:59:59.000Z

236

Cathy Zoi on Weatherization | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Weatherization Cathy Zoi on Weatherization Addthis Description The Weatherization Assistance Program is now weatherizing 25,000 homes each month. So far 10,000 jobs have been...

237

Paintball Summer Weather  

E-Print Network [OSTI]

Highlights · Paintball · Summer Weather · Birthdays · Manners TheELIWeekly Paintball! Come out France Iraq Japan Korea Kuwait Libya Netherlands Niger Peru Qatar Saudi Arabia Spain Taiwan Thailand Turkey United States Venezuela Summer Weather Safety We've come to realize in the past that not all

Pilyugin, Sergei S.

238

Home Weatherization Visit  

ScienceCinema (OSTI)

Secretary Steven Chu visits a home that is in the process of being weatherized in Columbus, OH, along with Ohio Governor Ted Strickland and Columbus Mayor Michael Coleman. They discuss the benefits of weatherization and how funding from the recovery act is having a direct impact in communities across America.

Chu, Steven

2013-05-29T23:59:59.000Z

239

The Dark Gravity model predictions for Gravity Probe B  

E-Print Network [OSTI]

The previous version of this article gave erroneous predictions. The correct uptodate predictions can be found in the section devoted to gravitomagnetism in the living review of the Dark Gravity theory: gr-qc/0610079 The most natural prediction is zero frame dragging and the same geodetic effect as predicted by GR. However, a straightforward extension of the theory could lead to the same frame-dragging as in GR.

Frederic Henry-Couannier

2007-10-23T23:59:59.000Z

240

Prediction of Physico-Chemical Properties for REACH Based on QSPR Models  

E-Print Network [OSTI]

Prediction of Physico-Chemical Properties for REACH Based on QSPR Models Guillaume Fayeta models have been developed for the prediction of flash points of two families of organic compounds respected all OECD validation principles with excellent performances in predictivity, the one dedicated

Paris-Sud XI, Universit de

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Prediction of tree diameter growth using quantile regression and mixed-effects models  

E-Print Network [OSTI]

Prediction of tree diameter growth using quantile regression and mixed-effects models Som B. Bohora diameter predictions for the same tree in the future. Another approach considered in this study involved and mixed-effects models in predicting tree diameter growth. Tree diameter at the end of each growth period

Cao, Quang V.

242

Influence Of Three Dynamic Predictive Clothing Insulation Models On Building Energy Use, HVAC Sizing And Thermal Comfort  

E-Print Network [OSTI]

Predictive Clothing Insulation Models based on Outdoor AirPREDICTIVE CLOTHING INSULATION MODELS ON BUILDING ENERGYthat the clothing insulation is equal to a constant value of

Schiavon, Stefano; Lee, Kwang Ho

2013-01-01T23:59:59.000Z

243

SPACE WEATHER, VOL. 11, 529541, doi:10.1002/swe.20092, 2013 A survey of customers of space  

E-Print Network [OSTI]

SPACE WEATHER, VOL. 11, 529541, doi:10.1002/swe.20092, 2013 A survey of customers of space weather August 2013; published 24 September 2013. [1] We present an analysis of the users of space weather information based on 2783 responses to an online survey among subscribers of NOAA's Space Weather Prediction

Schrijver, Karel

244

The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4  

E-Print Network [OSTI]

The Emissions Prediction and Policy Analysis (EPPA) model is the part of the MIT Integrated Global Systems Model (IGSM) that represents the human systems. EPPA is a recursive-dynamic multi-regional general equilibrium model ...

Paltsev, Sergey.

245

A Forward Looking Version of the MIT Emissions Prediction and Policy Analysis (EPPA) Model  

E-Print Network [OSTI]

This paper documents a forward looking multi-regional general equilibrium model developed from the latest version of the recursive-dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model. The model represents ...

Babiker, Mustafa M.H.

246

Toward understanding predictability of climate: a linear stochastic modeling approach  

E-Print Network [OSTI]

(E?) ? ; (2.29) which represents the predictable information(Schneider and Gri?es, 1999). In our case here, it is convenient to work with a derived quantity which we call predictive power loss (PPL) PPL(?) = e? 2nI(?x; x) = det ?E?C?1?1=n (2.30) after... the predictive power (PP) of Schneider and Gri?es (1999). Using the properties of positive de?nite matrix, one can show 0 6 PPL 6 1. It is consistent with ?(?) in the sense that PPL(0) = 0 and PPL(?1) = 1. The predictive power loss has some nice mathematical...

Wang, Faming

2004-11-15T23:59:59.000Z

247

Model Predictive Control for the Operation of Building Cooling Systems  

E-Print Network [OSTI]

predictive control of thermal energy storage in buildingpredictive control of thermal energy storage in buildingsystems which use thermal energy storage. In particular the

Ma, Yudong

2010-01-01T23:59:59.000Z

248

Wavelets, Self-organizing Maps and Artificial Neural Nets for Predicting Energy Use and Estimating Uncertainties in Energy Savings in Commercial Buildings  

E-Print Network [OSTI]

This dissertation develops a "neighborhood" based neural network model utilizing wavelet analysis and Self-organizing Map (SOM) to predict building baseline energy use. Wavelet analysis was used for feature extraction of the daily weather profiles...

Lei, Yafeng

2010-01-14T23:59:59.000Z

249

An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries  

E-Print Network [OSTI]

An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries Peng cycle-life tends to shrink significantly. The capacities of commercial lithium-ion batteries fade by 10 prediction model to estimate the remaining capacity of a Lithium-Ion battery. The proposed analytical model

Pedram, Massoud

250

IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 8, NO. 6, DECEMBER 2000 665 Fuzzy Model Predictive Control  

E-Print Network [OSTI]

. Index Terms--Control system design, fuzzy logic, model predic- tive control. I. INTRODUCTION MODELIEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 8, NO. 6, DECEMBER 2000 665 Fuzzy Model Predictive Control computational effort that may prohibit its on-line applications. In this paper, a fuzzy model predictive control

Huang, Yinlun

251

Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations  

E-Print Network [OSTI]

Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Buster is a stochastic, spatially explicit simulation model of Aedes aegypti populations, designed of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations. PLoS ONE 6(7): e

Lloyd, Alun

252

Weatherizing Wilkes-Barre  

Broader source: Energy.gov [DOE]

Ride along with some weatherizers in Wilkes-Barre, PA, as they blower door test, manage z-doors, and dense pack their way to an energy efficient future one house at a time.

253

Weatherizing Wilkes-Barre  

ScienceCinema (OSTI)

Ride along with some weatherizers in Wilkes-Barre, PA, as they blower door test, manage z-doors, and dense pack their way to an energy efficient future one house at a time.

Calore, Joe

2013-05-29T23:59:59.000Z

254

Weatherizing Wilkes-Barre  

SciTech Connect (OSTI)

Ride along with some weatherizers in Wilkes-Barre, PA, as they blower door test, manage z-doors, and dense pack their way to an energy efficient future one house at a time.

Calore, Joe

2010-01-01T23:59:59.000Z

255

Understanding the strengths and weaknesses of a new-generation numerical weather prediction model for application to short-term wind energy prediction.  

E-Print Network [OSTI]

??Wind power is a growing economy and science. It has far reaching consequences in all aspects of society and if goals of energy sustainability and (more)

Fowler, Padriac

2012-01-01T23:59:59.000Z

256

Satellite Application Facility for Numerical Weather Prediction  

E-Print Network [OSTI]

region (traffic, off-shore, tourism, wind parks), and most pollutants are released into the environment

Stoffelen, Ad

257

WEATHER PREDICTIONS AND SURFACE RADIATION ESTIMATES  

Office of Legacy Management (LM)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "ofEarlyEnergyDepartment ofDepartment ofof EnergyYou$0.C.Greentnv~ronmenrar ivronrrorrng L V ~ / O Ui

258

DREAM tool increases space weather predictions  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation Proposed Newcatalyst phases onOrganizationElectronic2005-2007 Budget Dear2, 2011DREAM tool

259

Dynamic predictive clothing insulation models based on outdoor air and indoor operative temperatures  

E-Print Network [OSTI]

predictive clothing insulation models based on outdoor airrange of the clothing insulation calculated for eachbuilding). Figure 8 Clothing insulation versus dress code [

Schiavon, Stefano; Lee, Kwang Ho

2012-01-01T23:59:59.000Z

260

Influence of two dynamic predictive clothing insulation models on building energy performance  

E-Print Network [OSTI]

Predictive Clothing Insulation Models on Building Energyunnecessarily higher clothing insulation and lower heatingthat the constant clothing insulation assumption lead to the

Lee, Kwang Ho; Schiavon, Stefano

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Modeling Metal Fatigue As a Key Step in PV Module Life Time Prediction (Presentation)  

SciTech Connect (OSTI)

This presentation covers modeling metal fatigue as a key step in photovoltaic (PV) module lifetime predictions. Described are time-dependent and time-independent case studies.

Bosco, N.

2012-02-01T23:59:59.000Z

262

Model Predictive Control of HVAC Systems: Implementation and Testing at the University of California, Merced  

E-Print Network [OSTI]

ModelPredictiveControlofHVACSystems: Implementationand air conditioning (HVAC) account for 27% of thereductionpotentialofHVACsystemswith activethermal

Haves, Phillip

2010-01-01T23:59:59.000Z

263

The rapidly evolving field of decadal climate prediction, using initialized climate models to produce time-evolving predictions of regional climate, is producing new results for  

E-Print Network [OSTI]

, and it is on those time scales of interest to water managers that decadal climate prediction is being appliedThe rapidly evolving field of decadal climate prediction, using initialized climate models to produce time-evolving predictions of regional climate, is producing new results for predictions

264

Prediction of Channel State for Cognitive Radio Using Higher-Order Hidden Markov Model  

E-Print Network [OSTI]

Prediction of Channel State for Cognitive Radio Using Higher-Order Hidden Markov Model Zhe Chen implementation. Prediction can be utilized to diminish the negative effect of such latency. In this paper, this latency is illustrated, and an approach for prediction of channel state using higher-order hidden Markov

Qiu, Robert Caiming

265

Where fast weathering creates thin regolith and slow weathering creates thick regolith  

SciTech Connect (OSTI)

Weathering disaggregates rock into regolith the fractured or granular earthmaterial that sustains life on the continental land surface. Here, we investigate what controls the depth of regolith formed on ridges of two rock compositions with similar initial porosities in Virginia (USA).A priori, we predicted that the regolith on diabasewould be thicker than on granite because the dominant mineral (feldspar) in the diabase weathers faster than its granitic counterpart. However, weathering advanced 20deeper into the granite than the diabase. The 20-thicker regolith is attributed mainly to connected micron-sized pores, microfractures formed around oxidizing biotite at 20m depth, and the lower iron (Fe) content in the felsic rock. Such porosity allows pervasive advection and deep oxidation in the granite. These observations may explainwhy regolithworldwide is thicker on felsic compared tomafic rock under similar conditions. To understand regolith formationwill require better understanding of such deep oxidation reactions and how they impact fluid flow during weathering.

Bazilevskaya, Ekaterina [Pennsylvania State University, University Park, PA; Lebedeva, Marina [Pennsylvania State University, University Park, PA; Pavich, Milan [U.S. Geological Survey, Reston, VA; Rother, Gernot [ORNL; Parkinson, D. Y. [Advanced Light Source, LBNL; Cole, David [Ohio State University; Brantley, S. L. [Pennsylvania State University, University Park, PA

2012-01-01T23:59:59.000Z

266

Locating Pleistocene refugia: Comparing phylogeographic and ecological niche model predictions  

E-Print Network [OSTI]

, American Museum of Natural History, New York, New York, United States of America, 2 International Rice Research Institute, Los Banos, Laguna, Philippines, 3Natural History Museum & Biodiversity Research Center, University of Kansas, Lawrence, Kansas.... Refugia identified in phylogeographic studies are shown as black outlines. Areas predicted to be refugia are in green, areas not predicted are in gray, and hatching indicates approximate locations of ice sheets [68]. Gray lines indicate present day...

Waltari, Eric; Hijmans, Robert J.; Peterson, A. Townsend; Nyá ri, Á rpá d S.; Perkins, Susan L.; Guralnick, Robert P.

2007-07-11T23:59:59.000Z

267

The Impact of IBM Cell Technology on the Programming Paradigm in the Context of Computer Systems for Climate and Weather Models  

SciTech Connect (OSTI)

The call for ever-increasing model resolutions and physical processes in climate and weather models demands a continual increase in computing power. The IBM Cell processor's order-of-magnitude peak performance increase over conventional processors makes it very attractive to fulfill this requirement. However, the Cell's characteristics, 256KB local memory per SPE and the new low-level communication mechanism, make it very challenging to port an application. As a trial, we selected the solar radiation component of the NASA GEOS-5 climate model, which: (1) is representative of column physics components (half the total computational time), (2) has an extremely high computational intensity: the ratio of computational load to main memory transfers, and (3) exhibits embarrassingly parallel column computations. In this paper, we converted the baseline code (single-precision Fortran) to C and ported it to an IBM BladeCenter QS20. For performance, we manually SIMDize four independent columns and include several unrolling optimizations. Our results show that when compared with the baseline implementation running on one core of Intel's Xeon Woodcrest, Dempsey, and Itanium2, the Cell is approximately 8.8x, 11.6x, and 12.8x faster, respectively. Our preliminary analysis shows that the Cell can also accelerate the dynamics component (~;;25percent total computational time). We believe these dramatic performance improvements make the Cell processor very competitive as an accelerator.

Zhou, Shujia; Duffy, Daniel; Clune, Thomas; Suarez, Max; Williams, Samuel; Halem, Milton

2009-01-10T23:59:59.000Z

268

A Mathematical Model for Predicting the Life of PEM Fuel Cell Membranes Subjected to Hydration Cycling  

E-Print Network [OSTI]

Under typical PEM fuel cell operating conditions, part of membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEM FC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane life-time. Short descriptions of the model components along with overall framework are presented in the paper. The model was used...

Burlatsky, S F; O'Neill, J; Atrazhev, V V; Varyukhin, A N; Dmitriev, D V; Erikhman, N S

2013-01-01T23:59:59.000Z

269

Collaborative Research: Separating Forced and Unforced Decadal Predictability in Models and Observations  

SciTech Connect (OSTI)

This report is a progress report of the accomplishments of the research grant Collaborative Research: Separating Forced and Unforced Decadal Predictability in Models and Observa- tions during the period 1 May 2011- 31 August 2013. This project is a collaborative one between Columbia University and George Mason University. George Mason University will submit a final technical report at the conclusion of their no-cost extension. The purpose of the proposed research is to identify unforced predictable components on decadal time scales, distinguish these components from forced predictable components, and to assess the reliability of model predictions of these components. Components of unforced decadal predictability will be isolated by maximizing the Average Predictability Time (APT) in long, multimodel control runs from state-of-the-art climate models. Components with decadal predictability have large APT, so maximizing APT ensures that components with decadal predictability will be detected. Optimal fingerprinting techniques, as used in detection and attribution analysis, will be used to separate variations due to natural and anthropogenic forcing from those due to unforced decadal predictability. This methodology will be applied to the decadal hindcasts generated by the CMIP5 project to assess the reliability of model projections. The question of whether anthropogenic forcing changes decadal predictability, or gives rise to new forms of decadal predictability, also will be investigated.

Tippett, Michael K. [Columbia University

2014-04-09T23:59:59.000Z

270

A Benchmark of Computational Models of Saliency to Predict Human Fixations  

E-Print Network [OSTI]

Many computational models of visual attention have been created from a wide variety of different approaches to predict where people look in images. Each model is usually introduced by demonstrating performances on new ...

Judd, Tilke

2012-01-13T23:59:59.000Z

271

Matchstick: A Room-to-Room Thermal Model for Predicting Indoor Temperature from Wireless Sensor Data  

E-Print Network [OSTI]

that our model can predict future indoor temperature trends with a 90th percentile aggregate error between thermo- stat actuates the heating, ventilation, and air condition- ing (HVAC) infrastructure to bring and these energy approaches, a heating model could allow future temperature trends to be predicted using

Hazas, Mike

272

Genetic Algorithm for Predicting Protein Folding in the 2D HP Model  

E-Print Network [OSTI]

Genetic Algorithm for Predicting Protein Folding in the 2D HP Model A Parameter Tuning Case Study of a protein, predicting its tertiary structure is known as the protein folding problem. This problem has been. The protein folding problem in the HP model is to find a conformation (a folded sequence) with the lowest

Emmerich, Michael

273

Fault-tolerant model predictive control of a wind turbine benchmark  

E-Print Network [OSTI]

Fault-tolerant model predictive control of a wind turbine benchmark X. Yang J.M. Maciejowski tolerant control problem of a wind turbine benchmark. A hierarchical controller with model predictive pre component of the wind turbine. The global MPC is used to schedule the operation of the components

Cambridge, University of

274

A forward microphysical model to predict the size-distribution parameters of laboratory generated (mimic)  

E-Print Network [OSTI]

A forward microphysical model to predict the size- distribution parameters of laboratory generated Interactions ­ Condensational Growth and Coagulation, Submitted for Indian Aerosol Science and Technology Microphysical Model for the UTLS (FAMMUS) is applied to predict the size-distribution parameters of laboratory

Oxford, University of

275

An integrated system for real-time Model Predictive Control of humanoid robots  

E-Print Network [OSTI]

this goal. The automatic controller is based on real-time model-predictive control (MPC) applied to the full. The resulting composite cost is sent to the MPC machinery which constructs a new locally-optimal time- varying-based optimal control is called Model-Predictive Control (MPC), an approach that relies on real-time trajectory

Todorov, Emanuel

276

A graphical model approach for predicting free energies of association for protein-protein  

E-Print Network [OSTI]

A graphical model approach for predicting free energies of association for protein University, Pittsburgh, PA 1 Corresponding Author: cjl@cs.cmu.edu #12;Keywords: Graphical Models, Free Energy in free energy, and the ability to predict binding free energies provides both better understanding

Langmead, Christopher James

277

A LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL  

E-Print Network [OSTI]

-FATIGUE-OXIDATION DAMAGE A. M. ALAM1 and L. REMY2 1 ALSTOM (Power), Gas Turbine Design Department, Brown Boveri Strasse 7A LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL CREEP 91003, Evry, France ABSTRACT This paper contains a brief description of a lifetime prediction model

Paris-Sud XI, Université de

278

Predictive Linear Regression Model for Microinverter Internal Temperature  

E-Print Network [OSTI]

, photovoltaic (PV) module temperature, irradiance and AC power data. Time-series environmental, temperature prediction, reliabil- ity, photovoltaic systems. I. INTRODUCTION PV modules equipped with microinverters have system. Reliability of microinverters in harsh and extreme real- world outdoor operating conditions has

Rollins, Andrew M.

279

Numerical and analytical modeling of sanding onset prediction  

E-Print Network [OSTI]

results vary with the selection of one or another rock strength criterion. In this work, we present four commonly used rock strength criteria in sanding onset prediction and wellbore stability studies: Mohr-Coulomb, Hoek-Brown, Drucker-Prager, and Modified...

Yi, Xianjie

2004-09-30T23:59:59.000Z

280

A Business Intelligence Model to Predict Bankruptcy using Financial Domain Ontology with Association Rule Mining Algorithm  

E-Print Network [OSTI]

Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement of a business. One of the best bankruptcy prediction models is Altman Z-score model. Altman Z-score method uses financial rations to predict bankruptcy. From the financial ontological model the relation between financial data is discovered by using data mining algorithm. By combining financial domain ontological model with association rule mining algorithm and Zscore model a new business intelligence model is developed to predict the bankruptcy.

Martin, A; Venkatesan, Dr V Prasanna

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Segmenting Time Series for Weather Forecasting  

E-Print Network [OSTI]

) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from an operational gas turbine is summarised for the maintenance engineers. More details on SUMTIME have been to develop a generic model for summarisation of time series data. Initially, we have applied standard

Sripada, Yaji

282

Proceedings: US Hydrographic Conference 2013, New Orleans, LA, 25-28 March 2013 Oceanographic Weather Maps: Using Oceanographic Models to Improve Seabed  

E-Print Network [OSTI]

: · Designing survey layout and prescribing line spacing and/or orientation. · Determining when to conduct the operation based on traffic, weather, and other environmental factors. · Selecting calibration sites

New Hampshire, University of

283

Human walking model predicts joint mechanics, electromyography and mechanical economy  

E-Print Network [OSTI]

In this paper, we present an under-actuated model of human walking, comprising only a soleus muscle and flexion/extension monoarticular hip muscles. The remaining muscle groups of the human leg are modeled using quasi-passive, ...

Endo, Ken

284

Weatherization Works!: Weatherization Assistance Program Close-Up Fact Sheet  

SciTech Connect (OSTI)

The United States demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes.

D& R International

2001-10-10T23:59:59.000Z

285

Abstract--Eventually, prediction of transformer thermal performance for dynamic loading will be made using models  

E-Print Network [OSTI]

1 Abstract--Eventually, prediction of transformer thermal performance for dynamic loading will be made using models distilled from measure data, rather than models derived from transformer heat for measuring the acceptability of transformer thermal models. For a model to be acceptable, it must have

286

Portland Diversifying Weatherization Workforce  

Broader source: Energy.gov [DOE]

An agreement signed by a diverse group of stakeholders ensures that those in disadvantaged communities have access to some of the weatherization jobs stemming from the pilot phase of the Clean Energy Works Portland program, which has almost 500 homes receiving retrofits through the summer with the help of federal dollars.

287

accelerated weathering: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Winter Weather Safety www.weather.gov SnowIce Blizzards Flooding Cold Temperatures 12;Building a Weather 5 Weather Theory Weather Reports, Forcasts and...

288

Injection-Molded Long-Fiber Thermoplastic Composites: From Process Modeling to Prediction of Mechanical Properties  

SciTech Connect (OSTI)

This article illustrates the predictive capabilities for long-fiber thermoplastic (LFT) composites that first simulate the injection molding of LFT structures by Autodesk Simulation Moldflow Insight (ASMI) to accurately predict fiber orientation and length distributions in these structures. After validating fiber orientation and length predictions against the experimental data, the predicted results are used by ASMI to compute distributions of elastic properties in the molded structures. In addition, local stress-strain responses and damage accumulation under tensile loading are predicted by an elastic-plastic damage model of EMTA-NLA, a nonlinear analysis tool implemented in ABAQUS via user-subroutines using an incremental Eshelby-Mori-Tanaka approach. Predicted stress-strain responses up to failure and damage accumulations are compared to the experimental results to validate the model.

Nguyen, Ba Nghiep; Kunc, Vlastimil; Jin, Xiaoshi; Tucker III, Charles L.; Costa, Franco

2013-12-18T23:59:59.000Z

289

Useful Weather Links Nolan Doesken  

E-Print Network [OSTI]

Useful Weather Links Nolan Doesken Odie Bliss Colorado Climate Center Presented at Professional://www.weather.gov/nwr/ #12;City of Fort Collins Alert Network ­ Rainfall and Streamflow http

290

Weatherization Innovation Pilot Program (WIPP): Technical Assistance Summary  

SciTech Connect (OSTI)

The U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy (EERE) Weatherization and Intergovernmental Programs Office (WIPO) launched the Weatherization Innovation Pilot Program (WIPP) to accelerate innovations in whole-house weatherization and advance DOE's goal of increasing the energy efficiency and health and safety of low-income residences without the utilization of additional taxpayer funding. Sixteen WIPP grantees were awarded a total of $30 million in Weatherization Assistance Program (WAP) funds in September 2010. These projects focused on: including nontraditional partners in weatherization service delivery; leveraging significant non-federal funding; and improving the effectiveness of low-income weatherization through the use of new materials, technologies, behavior-change models, and processes.

Hollander, A.

2014-09-01T23:59:59.000Z

291

Release of aged contaminants from weathered sediments: Effects of sorbate speciation on scaling of reactive transport  

SciTech Connect (OSTI)

Hanford sediments impacted by hyperalkaline high level radioactive waste have undergone incongruent silicate mineral weathering concurrent with contaminant uptake. In this project, we studied the impact of background pore water (BPW) on strontium, cesium and iodine desorption and transport in Hanford sediments that were experimentally weathered by contact with simulated hyperalkaline tank waste leachate (STWL) solutions. Using those lab-weathered Hanford sediments (HS) and model precipitates formed during nucleation from homogeneous STWL solutions (HN), we (i) provided thorough characterization of reaction products over a matrix of field-relevant gradients in contaminant concentration, partial pressure of carbon dioxide, and reaction time; (ii) improved molecular-scale understanding of how sorbate speciation controls contaminant desorption from weathered sediments upon removal of caustic sources; and (iii) developed a mechanistic, predictive model of meso- to field-scale contaminant reactive transport under these conditions. In this final report, we provide detailed descriptions of our results from this three-year study, completed in 2012 following a one-year no cost extension.

Chorover, Jon; Perdrial, Nico; Mueller, Karl; Strepka, Caleb; Oƒ ƒ ‚ ¢ƒ ‚ ‚ € ƒ ‚ ‚ ™ Day, Peggy; Rivera, Nelson; Um, Wooyong; Chang, Hyun-Shik; Steefel, Carl; Thompson, Aaron

2012-11-05T23:59:59.000Z

292

Putting Nonlinear Model Predictive Control Bjarne A. Foss1  

E-Print Network [OSTI]

estimation. Finally, we consider the design of the optimization problem itself and implementation issues. 1 for optimization of suspension PVC polymerization processes has been implemented on two large (140 m3) autoclaves: It contains a rather detailed nonlinear model of the polymerization reactor. The reactor model includes

Foss, Bjarne A.

293

Occupancy Modeling and Prediction for Building Energy Varick L. Erickson, University of California, Merced  

E-Print Network [OSTI]

A Occupancy Modeling and Prediction for Building Energy Management Varick L. Erickson, University.Cerpa, University of California, Merced Heating, cooling and ventilation accounts for 35% energy usage in the United and Prediction for Building Energy Management and Auditing. ACM Trans. Sensor Netw. V, N, Article A (August 2012

Cerpa, Alberto E.

294

Towards Accurate and Practical Predictive Models of Active-Vision-Based Visual Search  

E-Print Network [OSTI]

which permit increasingly realistic and accurate predictions for visual human-computer interaction tasks not practical. For as long as human-computer interaction has been studied, researchers have been working@cs.uoregon.edu ABSTRACT Being able to predict the performance of interface designs using models of human cognition

Hornof, Anthony

295

Discrepancies in the Prediction of Solar Wind using Potential Field Source Surface Model: An  

E-Print Network [OSTI]

Discrepancies in the Prediction of Solar Wind using Potential Field Source Surface Model. This inverse relation has been made use of in the prediction of solar wind speed at 1 AU using a potential between the magnetic flux tube expansion factor (FTE) at the source surface and the solar wind speed

Zhao, Xuepu

296

Predicting the net carbon exchanges of crop rotations in Europe with an agro-ecosystem model  

E-Print Network [OSTI]

Predicting the net carbon exchanges of crop rotations in Europe with an agro-ecosystem model S.Lehuger@art.admin.ch. Fax: (+41) 44 377 72 01. Phone: (+41) 44 377 75 13. hal-00414342,version2-1Sep2010 #12;Abstract Carbon and measuring land-atmosphere carbon exchanges from arable lands are important tasks to predict the influence

Boyer, Edmond

297

Predictive models for power dissipation in optical transceivers  

E-Print Network [OSTI]

Power dissipation in optical networks is a significant problem for the telecommunications industry. The optical transceiver was selected as a representative device of the network, and a component based power model is ...

Butler, Katherine, 1981-

2004-01-01T23:59:59.000Z

298

Development of Chemical Model to Predict the Interactions between...  

Broader source: Energy.gov (indexed) [DOE]

- TOUGH family codes have been widely used in modeling EGS and CCS processes. The fracture-matrix feature can be handled through the MINC module; however, at considerable cost....

299

Application of the cumulative risk model in predicting school readiness in Head Start children  

E-Print Network [OSTI]

outcomes. This study built on this literature by investigating how child, parent, and family risk factors predicted school readiness in Head Start children using two statistical models. Specific aims of this study included identifying 1) to what degree...

Rodriguez-Escobar, Olga Lydia

2009-05-15T23:59:59.000Z

300

Model predictive control with application to real-time hardware and guided parafoil  

E-Print Network [OSTI]

Model Predictive Control (MPC) is a control strategy that is suitable for optimizing the performance of constrained systems. Constraints are present in all control systems due to the physical and environmental limits on ...

Alaniz, Abran, 1980-

2004-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Evaluating Importance Ratings as an Alternative to Mental Models in Predicting Driving Crashes and Moving Violations  

E-Print Network [OSTI]

The present study investigated the extent to which importance ratings (i.e., a measure of perceived importance for driving-related concepts) are a viable alternative to traditional mental model assessment methods in predicting driving performance...

McDonald, Jennifer Nicole

2012-07-16T23:59:59.000Z

302

Sensors and Actuators B 106 (2005) 122127 Eulerian-Lagrangian model for predicting odor dispersion using  

E-Print Network [OSTI]

Sensors and Actuators B 106 (2005) 122­127 Eulerian-Lagrangian model for predicting odor dispersion-level heating from solar short wave radiation, and (2) during the evening when deep surface cooling through long

Katul, Gabriel

303

Evaluation of short-term climate change prediction in multi-model CMIP5 decadal hindcasts  

E-Print Network [OSTI]

events such as trop- ical cyclone activity. On decadal timescales, some aspects of internal climate skill of individual models have been analyzed separately for multi-year prediction horizons over

Webster, Peter J.

304

Connecting Peptide Physicochemical and Antimicrobial Properties by a Rational Prediction Model  

E-Print Network [OSTI]

Connecting Peptide Physicochemical and Antimicrobial Properties by a Rational Prediction Model Marc network approach, based on the AMP's physicochemical characteristics, that is able not only to identify active peptides but also to assess its antimicrobial potency. The physicochemical properties considered

Pompeu Fabra, Universitat

305

Reconfigurable autopilot design for a high performance aircraft using model predictive control  

E-Print Network [OSTI]

The losses of military and civilian aircraft due to control surface failures have prompted research into controllers with a degree of reconfiguration. This thesis will describe a design approach incorporating Model Predictive ...

Ruiz, Jose Pedro, 1980-

2004-01-01T23:59:59.000Z

306

Validated Model-Based Performance Prediction of Multi-Core Software Routers  

E-Print Network [OSTI]

Terms--measurement, simulation, intra-node model, re- source contention, model validation, software components. Leveraged by high flexibility and low costs of software developments in comparison with hardwareValidated Model-Based Performance Prediction of Multi-Core Software Routers Torsten Meyer1

Carle, Georg

307

An Advanced Induction Machine Model for Predicting Inverter-Machine Interaction  

E-Print Network [OSTI]

An Advanced Induction Machine Model for Predicting Inverter-Machine Interaction [31 [41 [51 [6] [7 saturntion d d d d d d d d d d d d d d d d d d d d d d d Leakage inductance saturation as a function of flux- tion machine model specifically designed for use with inverter models to study machin

Chapman, Patrick

308

Modeling, Analysis, Predictions, and Projections Email: oar.cpo.mapp@noaa.gov  

E-Print Network [OSTI]

Earth system models to better simulate the climate system? Can we improve intraseasonal to seasonal mission, MAPP supports the development of advanced Earth system models that can predict climate variations, and the external research community. MAPP Objectives · Improve Earth system models · Achieve an integrated Earth

309

A Mathematical Model for Predicting the Life of PEM Fuel Cell Membranes Subjected to Hydration Cycling  

E-Print Network [OSTI]

Under typical PEM fuel cell operating conditions, part of membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEM FC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane life-time. Short descriptions of the model components along with overall framework are presented in the paper. The model was used for lifetime prediction of a GORE-SELECT membrane.

S. F. Burlatsky; M. Gummalla; J. O'Neill; V. V. Atrazhev; A. N. Varyukhin; D. V. Dmitriev; N. S. Erikhman

2013-06-19T23:59:59.000Z

310

Accelerating Clean Energy Adoption (Fact Sheet), Weatherization...  

Broader source: Energy.gov (indexed) [DOE]

Accelerating Clean Energy Adoption (Fact Sheet), Weatherization and Intergovernmental Program (WIP) Accelerating Clean Energy Adoption (Fact Sheet), Weatherization and...

311

Weatherization Assistance Program: Spurring Innovation, Increasing...  

Energy Savers [EERE]

Weatherization Assistance Program: Spurring Innovation, Increasing Home Energy Efficiency Weatherization Assistance Program: Spurring Innovation, Increasing Home Energy Efficiency...

312

Connecticut's Health Impact Study Rapidly Increasing Weatherization...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

of Weatherization Assistance Program Technical Assistance Center Donna Hawkins Technology Transfer Specialist, Weatherization Assistance Program Floris Weston Project Officer,...

313

Leveraging Resources for the Weatherization Innovation Pilot...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

the Weatherization Innovation Pilot Program (WIPP) - Webinar Transcript Leveraging Resources for the Weatherization Innovation Pilot Program (WIPP) - Webinar Transcript This...

314

Leveraging Resources for Weatherization Innovation Pilot Projects...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Weatherization Innovation Pilot Projects (WIPP) Presentation Leveraging Resources for Weatherization Innovation Pilot Projects (WIPP) Presentation As a WIPP agency, reporting...

315

Subscribe to Weatherization and Intergovernmental Program Office...  

Broader source: Energy.gov (indexed) [DOE]

Subscribe to Weatherization and Intergovernmental Program Office Newsletters Subscribe to Weatherization and Intergovernmental Program Office Newsletters You can subscribe to...

316

Development of a new model for predicting sucker-rod pumping system performance  

E-Print Network [OSTI]

DEVELOPMENT OF A NEW MODEL FOR PREDICTING SUCKER-ROD PUMPING SYSTEM PERFORMANCE A Thesis by JULIAN PEREZ GARCIA, JR. Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirements for the degree... of MASTER OF SCIENCE August 1988 Major Subject: Petroleum Engineering DEVELOPMENT OF A NEW MODEL FOR PREDICTING SUCKER-ROD PUMPING SYSTEM PERFORMANCE A Thesis by JULIAN PEREZ GARCIA, JR. Approved as to style and content by: J. . Jen in s (Cha...

Garcia, Julian Perez

1988-01-01T23:59:59.000Z

317

A quantitative model to predict the cost of quality nonconformance in the construction industry  

E-Print Network [OSTI]

A QUANTITATIVE MODEL TO PREDICT THE COST OF QUALITY NONCONFORMANCE IN THE CONSTRUCTION INDUSTRY A Thesis by ETHELBERT OKECHUKWU OPARA Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of requirements... for the degree of MASTER OF SCIENCE August 1993 Major Subject: Construction Management A QUANTITATIVE MODEL TO PREDICT THE COST OF QUALITY NONCONFORMANCE IN THE CONSTRUCTION INDUSTRY A Thesis by ETHELBERT OKECHUKWU OPARA Submitted to Texas A&M University...

Opara, Ethelbert Okechukwu

1993-01-01T23:59:59.000Z

318

Weatherization Assistance Program  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:YearRound-Up from theDepartment of Dept.| DepartmentVolvoWaterWeatherization Assistance Program

319

Lurking Pathway Prediction And Pathway ODE Model Dynamic Analysis  

E-Print Network [OSTI]

regulated proteins in the transduction pro- cess. And by modeling the CCL2 pathway in MTB infected cells, J N K , cM Y C and P LC showed as the most significant modules. Hence, the drug treatments inhibit- ing J N K , cM Y C and P LC would effectively...

Zhang, Rengjing

2013-11-18T23:59:59.000Z

320

Single-Pass Flow-Through Test Elucidation of Weathering Behavior and Evaluation of Contaminant Release Models for Hanford Tank Residual Radioactive Waste  

SciTech Connect (OSTI)

Contaminant release models are required to evaluate and predict long-term environmental impacts of even residual amounts of high-level radioactive waste after cleanup and closure of radioactively contaminated sites such as the DOEs Hanford Site. More realistic and representative models have been developed for release of uranium, technetium, and chromium from Hanford Site tanks C-202, C-203, and C-103 residual wastes using data collected with a single-pass flow-through test (SPFT) method. These revised models indicate that contaminant release concentrations from these residual wastes will be considerably lower than previous estimates based on batch experiments. For uranium, a thermodynamic solubility model provides an effective description of uranium release, which can account for differences in pore fluid chemistry contacting the waste that could occur through time and as a result of different closure scenarios. Under certain circumstances in the SPFT experiments various calcium rich precipitates (calcium phosphates and calcite) form on the surfaces of the waste particles, inhibiting dissolution of the underlying uranium phases in the waste. This behavior was not observed in previous batch experiments. For both technetium and chromium, empirical release models were developed. In the case of technetium, release from all three wastes was modeled using an equilibrium Kd model. For chromium release, a constant concentration model was applied for all three wastes.

Cantrell, Kirk J.; Carroll, Kenneth C.; Buck, Edgar C.; Neiner, Doinita; Geiszler, Keith N.

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)  

SciTech Connect (OSTI)

Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.

Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Pesaran, A.

2014-02-01T23:59:59.000Z

322

A soil moisture availability model for crop stress prediction  

E-Print Network [OSTI]

is composed of three major components, which are, a) calcul ation of evapotranspiration, b) infiltration of moisture into the soil, c) redistribution of the soil moisture. Other edaphic models have been developed by Hill [1974], Bai er and Robertson... inputs could result in the development of moist layers in the lower soil layer that would not be accounted for if the moisture were uniformly redistributed. As the cycle progesses, redistribution and moisture depletion do occur, until there 1s less...

Gay, Roger Franklin

1983-01-01T23:59:59.000Z

323

Subsidence prediction for the forthcoming TONO UCG project. [Rubble model and block model  

SciTech Connect (OSTI)

The motion of the strata that overlie the TONO UCG Project partial-seam test is calculated using the analyses that have been developed for the prediction of subsidence above coal mines. This purely mechanical analysis of the overburden response to the formation of a void in the underlying coal seam is based on the analysis of two codes. The first is a finite-element code that uses a nonlinear rubble model to describe both the kinematics of roof fall and the continuum behavior of broken and unbroken strata. The second is a block code that treats the overburden as an assemblage of blocks. The equations of motion are solved for each block using an explicit integration operator. As both of these calculations are two-dimensional in nature, they are used to calibrate the semi-empirical, complementary influence function model. This model permits the extension of the two-dimensional analyses to three dimensions by using computationally efficient algorithms. These techniques are calibrated to UCG projects by analyzing the Hoe Creek 3 burn. Their application to the TONO project required the estimation of the lateral extent of the cavity for the partial-seam test. The estimates utilized the projected tons of coal to be removed and two scenarios for the burn sequence. The subsidence analytical techniques were combined with the expected patterns of coal removal to place an upper bound on the surface subsidence that can be anticipated at the TONO UCG site. 9 figures.

Sutherland, H.R.; Hommert, P.J.; Taylor, L.M.; Benzley, S.E.

1983-01-01T23:59:59.000Z

324

Bayesian methods for discontinuity detection in climate model predictions.  

SciTech Connect (OSTI)

Discontinuity detection is an important component in many fields: Image recognition, Digital signal processing, and Climate change research. Current methods shortcomings are: Restricted to one- or two-dimensional setting, Require uniformly spaced and/or dense input data, and Give deterministic answers without quantifying the uncertainty. Spectral methods for Uncertainty Quantification with global, smooth bases are challenged by discontinuities in model simulation results. Domain decomposition reduces the impact of nonlinearities and discontinuities. However, while gaining more smoothness in each subdomain, the current domain refinement methods require prohibitively many simulations. Therefore, detecting discontinuities up front and refining accordingly provides huge improvement to the current methodologies.

Safta, Cosmin; Debusschere, Bert J.; Najm, Habib N.; Sargsyan, Khachik

2010-06-01T23:59:59.000Z

325

Gamma-ray Burst Models: General Requirements and Predictions  

E-Print Network [OSTI]

Whatever the ultimate energy source of gamma-ray bursts turns out to be, the resulting sequence of physical events is likely to lead to a fairly generic, almost unavoidable scenario: a relativistic fireball that dissipates its energy after it has become optically thin. This is expected both for cosmological and halo distances. Here we explore the observational motivation of this scenario, and the consequences of the resulting models for the photon production in different wavebands, the energetics and the time structure of classical gamma-ray bursters.

P. Meszaros

1995-02-21T23:59:59.000Z

326

SimTable helps firefighters model and predict fire direction  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassiveSubmitted forHighlightsSeminarsSilicon sponge improvesSimTable models and

327

A Hierarchical Bayesian Model for Improving Short-Term Forecasting of Hospital Demand by Including Meteorological  

E-Print Network [OSTI]

A Hierarchical Bayesian Model for Improving Short-Term Forecasting of Hospital Demand by Including Sarran4 Abstract The effect of weather on health has been widely researched, and the ability to forecast, better predictions of hospital demand that are more sensitive to fluctuations in weather can allow

Sahu, Sujit K

328

Hamiltonian-based numerical methods for forced-dissipative climate prediction  

E-Print Network [OSTI]

Hamiltonian-based numerical methods for forced-dissipative climate prediction Bob Peeters1 , Onno long-term weather forecast models fail at this point. But the question remains, however: Question: Is it advantageous to use numerical schemes with a Hamil- tonian core for realistic climate modeling? The primitive

Al Hanbali, Ahmad

329

Air Leakage of U.S. Homes: Model Prediction  

SciTech Connect (OSTI)

Air tightness is an important property of building envelopes. It is a key factor in determining infiltration and related wall-performance properties such as indoor air quality, maintainability and moisture balance. Air leakage in U.S. houses consumes roughly 1/3 of the HVAC energy but provides most of the ventilation used to control IAQ. The Lawrence Berkeley National Laboratory has been gathering residential air leakage data from many sources and now has a database of more than 100,000 raw measurements. This paper uses a model developed from that database in conjunction with US Census Bureau data for estimating air leakage as a function of location throughout the US.

Sherman, Max H.; McWilliams, Jennifer A.

2007-01-01T23:59:59.000Z

330

FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake Erie  

E-Print Network [OSTI]

weather prediction step-coordinate Eta Model are able to forecast winds for the Great Lakes region, using Administration (NOAA) Coastal Ocean Program, the output of NCEP numerical atmospheric prediction models is being used as the forcing for numerical ocean prediction models for several U.S. coastal regions

331

Water Research 38 (2004) 33313339 Testing a surface tension-based model to predict the salting  

E-Print Network [OSTI]

Water Research 38 (2004) 3331­3339 Testing a surface tension-based model to predict the salting out associated with transferring solutes from water to a salt solution to the difference in surface tensions likely reflects the inability of the simple surface tension model to account for all interactions among

Herbert, Bruce

332

A Two Step Model for Linear Prediction, with Connections to PLS  

E-Print Network [OSTI]

A Two Step Model for Linear Prediction, with Connections to PLS Ying Li Faculty of Natural ISSN, 1654-9406 ISBN, 978-91-576-9055-5 c 2011 Ying Li, Uppsala Print: SLU Service/Repro, Uppsala 2011 Model, Krylov Space, MLE, PLS. Author's address: Ying Li SLU, Department of Energy and Technology, Box

333

Development of a new model to predict indoor daylighting : integration in CODYRUN software and validation  

E-Print Network [OSTI]

1 Development of a new model to predict indoor daylighting : integration in CODYRUN software in the scientific literature for determining indoor daylighting values. They are classified in three categories. The originality of our paper relies on the coupling of several simplified models of indoor daylighting

Paris-Sud XI, Université de

334

A Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water Quality: Evidence  

E-Print Network [OSTI]

A Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water carrying capacity. Keywords Visitation model Á Recreation management Á Water quality Á River visitation Á Clark, Fort Collins, Colorado 80523, USA 123 Environmental Management DOI 10.1007/s00267-008-9079-5 #12

335

User-click Modeling for Understanding and Predicting Search-behavior  

E-Print Network [OSTI]

. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: General Terms AlgorithmsUser-click Modeling for Understanding and Predicting Search-behavior Yuchen Zhang1 , Weizhu Chen1 advances in search users' click modeling consider both users' search queries and click/skip behavior

Yang, Qiang

336

Critical Fracture Stress and Fracture Strain Models for the Prediction of Lower and  

E-Print Network [OSTI]

Critical Fracture Stress and Fracture Strain Models for the Prediction of Lower and Upper Shelf fracture stress and stress modified fracture strain models are utilized to describe the variation of lower and upper shelf fracture toughness with temperature and strain rate for two alloy steels used

Ritchie, Robert

337

Project Profile: Predictive Physico-Chemical Modeling of Intrinsic Degradation Mechanisms for Advanced Reflector Materials  

Broader source: Energy.gov [DOE]

NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing a physics-based computational degradation model to assess the kinetic oxidation rates; realistic model light attenuation and transport; and multi-layer treatment with variable properties Simulation based experimental design.

338

Atomistic Modeling of Macromolecular Crowding Predicts Modest Increases in Protein Folding and Binding Stability  

E-Print Network [OSTI]

Atomistic Modeling of Macromolecular Crowding Predicts Modest Increases in Protein Folding that macromolecular crowding can increase protein folding stability, but depending on details of the models (e.g., how on the effects of macro- molecular crowding on protein folding and binding stability has been reached. Crowders

Weston, Ken

339

Predictive Modeling of Transient Storage and Nutrient Uptake: Implications for Stream Restoration  

E-Print Network [OSTI]

Predictive Modeling of Transient Storage and Nutrient Uptake: Implications for Stream Restoration of reactive transport modeling for stream restoration purposes: the accuracy of the nutrient spiraling geomorphology and hydraulics influence nu- trient uptake is vital for stream restoration projects that modify

340

Nonlinear Model Predictive Control of an Aircraft Gas Turbine Engine Brent. J. Brunell  

E-Print Network [OSTI]

Nonlinear Model Predictive Control of an Aircraft Gas Turbine Engine Brent. J. Brunell , Robert R the potential to achieve better performance than the production controller. 1 Introduction Gas turbines can turbine model considered is a low bypass, two rotor, turbojet with a variable exhaust area typical

Bitmead, Bob

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

An Efficient Genetic Algorithm for Predicting Protein Tertiary Structures in the 2D HP Model  

E-Print Network [OSTI]

, predicting its tertiary structure is known as the protein folding problem. This problem has been widely genetic algo- rithm for the protein folding problem under the HP model in the two-dimensional square Genetic Algorithm, Protein Folding Problem, 2D HP Model 1. INTRODUCTION Amino acids are the building

Istrail, Sorin

342

Weather Photos - Hanford Site  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste and Materials Disposition3 WaterFebruary 18,theWeather

343

Weather Photos - Hanford Site  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste and Materials Disposition3 WaterFebruary 18,theWeather

344

Weather Photos - Hanford Site  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste and Materials Disposition3 WaterFebruary 18,theWeather

345

Weather Photos - Hanford Site  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste and Materials Disposition3 WaterFebruary 18,theWeather

346

A Physically Based Analytical Model to Predict Quantized Eigen Energies and Wave Functions Incorporating Penetration Effect  

E-Print Network [OSTI]

We propose a physically based analytical compact model to calculate Eigen energies and Wave functions which incorporates penetration effect. The model is applicable for a quantum well structure that frequently appears in modern nano-scale devices. This model is equally applicable for both silicon and III-V devices. Unlike other models already available in the literature, our model can accurately predict all the eigen energies without the inclusion of any fitting parameters. The validity of our model has been checked with numerical simulations and the results show significantly better agreement compared to the available methods.

Nadim Chowdhury; Imtiaz Ahmed; Zubair Al Azim; Md. Hasibul Alam; Iftikhar Ahmad Niaz; Quazi D. M. Khosru

2014-04-14T23:59:59.000Z

347

Optimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model Predictive Control  

E-Print Network [OSTI]

is shown by applying it to a case study involving composition control of a binary distillation column. I is demonstrated in a binary high-purity distillation column case study by Weischedel and McAvoy [7], a demanding nonlinear and strongly interactive process application. A Model-on-Demand Model Predictive Control (MoD-MPC

Mittelmann, Hans D.

348

Northerly surface wind events over the eastern North Pacific Ocean : spatial distribution, seasonality, atmospheric circulation, and forcing  

E-Print Network [OSTI]

ECMWF and NCEP numerical weather prediction models, Mon.atmospheric numerical weather prediction model. The

Taylor, Stephen V.

2006-01-01T23:59:59.000Z

349

Deriving cloud velocity from an array of solar radiation measurements  

E-Print Network [OSTI]

trajectory and numerical weather prediction models. Proc.ration cause Numerical Weather Prediction (NWP) models to

Bosch, J.L.; Zheng, Y.; Kleissl, J.

2013-01-01T23:59:59.000Z

350

Bishop Paiute Weatherization Training Program  

SciTech Connect (OSTI)

The DOE Weatherization Training Grant assisted Native American trainees in developing weatherization competencies, creating employment opportunities for Bishop Paiute tribal members in a growing field. The trainees completed all the necessary training and certification requirements and delivered high-quality weatherization services on the Bishop Paiute Reservation. Six tribal members received all three certifications for weatherization; four of the trainees are currently employed. The public benefit includes (1) development of marketable skills by low-income Native individuals, (2) employment for low-income Native individuals in a growing industry, and (3) economic development opportunities that were previously not available to these individuals or the Tribe.

Carlos Hernandez

2010-01-28T23:59:59.000Z

351

Weatherization Apprenticeship Program  

SciTech Connect (OSTI)

Weatherization improvement services will be provided to Native people by Native people. The proposed project will recruit, train and hire two full-time weatherization technicians who will improve the energy efficiency of homes of Alaska Natives/American Indians residing in the Indian areas, within the Cook Inlet Region of Alaska. The Region includes Anchorage as well as 8 small tribal villages: The Native Villages of Eklutna, Knik, Chickaloon, Seldovia, Ninilchik, Kenaitze, Salamatof, and Tyonek. This project will be a partnership between three entities, with Cook Inlet Tribal Council (CITC) as the lead agency: CITCA's Employment and Training Services Department, Cook Inlet Housing Authority and Alaska Works Partnership. Additionally, six of the eight tribal villages within the Cook Inlet Region of Alaska have agreed to work with the project in order to improve the energy efficiency of their tribally owned buildings and homes. The remaining three villages will be invited to participate in the establishment of an intertribal consortium through this project. Tribal homes and buildings within Anchorage fall under Cook Inlet Region, Inc. (CIRI) tribal authority.

Watson, Eric J

2012-12-18T23:59:59.000Z

352

Comparison of Model Forecast Skill of Sea-Level Pressure Along the East and West Coasts of the United States  

E-Print Network [OSTI]

1 Comparison of Model Forecast Skill of Sea-Level Pressure Along the East and West Coasts, University of Washington, Seattle, Washington Submitted to: Weather and Forecasting May 2008 Revised recent advances in numerical weather prediction, major errors in short-range forecasts still occur

Mass, Clifford F.

353

A predictive model for the combustion process in dual fuel engines  

SciTech Connect (OSTI)

A multi-zone model has been developed for the prediction of the combustion processes in dual fuel engines and some of their performance features. The consequences of the interaction between the gaseous and the diesel fuels and the resulting modification to the combustion processes are considered. A reacting zone has been incorporated in the model to describe the partial oxidation of the gaseous fuel-air mixture while detailed kinetic schemes are employed to describe the oxidation of the gaseous fuel, right from the start of compression to the end of the expansion process. The associated formation and concentrations of exhaust emissions are correspondingly established. The model can predict the onset of knock as well as the operating features and emissions for the more demanding case of light load performance. Predicted values for methane operation show good agreement with corresponding experimental values.

Liu, Z.; Karim, G.A. [Univ. of Calgary, Alberta (Canada)

1995-12-31T23:59:59.000Z

354

Comparison of model predicted to observed winds in the coastal zone  

SciTech Connect (OSTI)

Predictions of near-surface (10 to 100 m) wind velocities made by a mesoscale numerical model on a 10 km grid over and near the coastline are checked against observations. Two comparisons are made. The first is between observed and model-estimated mean annual wind power density at locations where surface observations exist in three coastal areas: the Chesapeake Bay, the Apalachee Bay and the South Texas coastal area. The second comparison is made between model predictions over the Delmarva Peninsula and adjacent ocean and observations made over a 120 x 30 km rectangle extending across the peninsula and out to sea. It is concluded that the unbiased error analysis skill ratings of 81% and 76% are attained for two days of prediction-observation comparisons. In the meantime, the skill of the model in duplicating individual coastal wind fields is taken as 78%. In addition, a qualitative comparison is made between the predicted fields of wind and the observed wind field. The predicted wind field unquestionably reproduces the observed field.

Garstang, M.; Pielke, R.A.; Snow, J.W.

1982-06-01T23:59:59.000Z

355

Mathematical approaches for complexity/predictivity trade-offs in complex system models : LDRD final report.  

SciTech Connect (OSTI)

The goal of this research was to examine foundational methods, both computational and theoretical, that can improve the veracity of entity-based complex system models and increase confidence in their predictions for emergent behavior. The strategy was to seek insight and guidance from simplified yet realistic models, such as cellular automata and Boolean networks, whose properties can be generalized to production entity-based simulations. We have explored the usefulness of renormalization-group methods for finding reduced models of such idealized complex systems. We have prototyped representative models that are both tractable and relevant to Sandia mission applications, and quantified the effect of computational renormalization on the predictive accuracy of these models, finding good predictivity from renormalized versions of cellular automata and Boolean networks. Furthermore, we have theoretically analyzed the robustness properties of certain Boolean networks, relevant for characterizing organic behavior, and obtained precise mathematical constraints on systems that are robust to failures. In combination, our results provide important guidance for more rigorous construction of entity-based models, which currently are often devised in an ad-hoc manner. Our results can also help in designing complex systems with the goal of predictable behavior, e.g., for cybersecurity.

Goldsby, Michael E.; Mayo, Jackson R.; Bhattacharyya, Arnab (Massachusetts Institute of Technology, Cambridge, MA); Armstrong, Robert C.; Vanderveen, Keith

2008-09-01T23:59:59.000Z

356

COBRA-WC model and predictions for a fast-reactor natural-circulation transient. [LMFBR  

SciTech Connect (OSTI)

The COBRA-WC (Whole Core) code has been used to predict the core-wide coolant and rod temperature distribution in a liquid metal fast reactor during the early part (first 220 seconds) of a natural circulation transient. Approximately one-sixth of the core was modeled including bypass flows and the pressure losses above and below the core region. Detailed temperature and flow distributions were obtained for the two test fuel assemblies. The COBRA-WC model, the approach, and predictions of core-wide transient coolant and rod temperatures during a natural circulation transient are presented in this paper.

George, T.L.; Basehore, K.L.; Prather, W.A.

1980-01-01T23:59:59.000Z

357

artificial weathering environment: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Nation Winter Weather Hazards Winter Weather Safety www.weather.gov SnowIce Blizzards Flooding Cold Temperatures 12;Building a Weather 37 4....

358

Final Report Coupling in silico microbial models with reactive transport models to predict the fate of contaminants in the subsurface.  

SciTech Connect (OSTI)

This project successfully accomplished its goal of coupling genome-scale metabolic models with hydrological and geochemical models to predict the activity of subsurface microorganisms during uranium bioremediation. Furthermore, it was demonstrated how this modeling approach can be used to develop new strategies to optimize bioremediation. The approach of coupling genome-scale metabolic models with reactive transport modeling is now well enough established that it has been adopted by other DOE investigators studying uranium bioremediation. Furthermore, the basic principles developed during our studies will be applicable to much broader investigations of microbial activities, not only for other types of bioremediation, but microbial metabolism in diversity of environments. This approach has the potential to make an important contribution to predicting the impact of environmental perturbations on the cycling of carbon and other biogeochemical cycles.

Lovley, Derek R.

2012-10-31T23:59:59.000Z

359

Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling  

SciTech Connect (OSTI)

The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.

Jaroslav Solc

2009-06-01T23:59:59.000Z

360

Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant  

E-Print Network [OSTI]

Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant where diesel gener- ator sets (a diesel engine connected to a generator) produce electrical power, which Email: torstein.bo@itk.ntnu.no, tor.arne.johansen@itk.ntnu.no Abstract--Diesel-electric propulsion

Johansen, Tor Arne

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

MRI based diffusion and perfusion predictive model to estimate stroke Stephen E. Rosea,  

E-Print Network [OSTI]

MRI based diffusion and perfusion predictive model to estimate stroke evolution Stephen E. Rosea and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs

McLachlan, Geoff

362

Adaptive Model Predictive Control of the Hybrid Dynamics of a Fuel Cell System.  

E-Print Network [OSTI]

Adaptive Model Predictive Control of the Hybrid Dynamics of a Fuel Cell System. M. Fiacchini, T operation of a fuel cell system is presented. The aim of the control design is to guarantee that the oxygen control to a fuel cell plant is presented. The fuel cell, located in the laboratory of the Department

Paris-Sud XI, Universit de

363

Accurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded Systems  

E-Print Network [OSTI]

Binghamton University, State University of New York Binghamton, New York, USA {jlu5, sliu5, qwu, qqiuAccurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded}@binghamton.edu Abstract -- Energy availability is the primary subject that drives the research innovations in energy

Qiu, Qinru

364

Predictive Inner-Outer Model for Turbulent Boundary Layers Applied to Hypersonic DNS Data  

E-Print Network [OSTI]

Predictive Inner-Outer Model for Turbulent Boundary Layers Applied to Hypersonic DNS Data Clara numerical simulation (DNS) data of supersonic and hypersonic turbulent boundaries with Mach 3 and Mach 7, and Martin12­14 on DNS of hypersonic turbulent boundary layers demonstrates the existence of large scale

Martín, Pino

365

Predictive Modeling of Mercury Speciation in Combustion Flue Gases Using GMDH-Based Abductive Networks  

E-Print Network [OSTI]

to develop. The use of modern data-based machine learning techniques has been recently introduced, including and boiler operating conditions. Prediction performance compares favourably with neural network models for future work to further improve performance. Index Terms: Mercury speciation, Flue gases, Boiler emissions

Abdel-Aal, Radwan E.

366

A Graphical Model for Predicting Protein Molecular Function Barbara E. Engelhardt bee@cs.berkeley.edu  

E-Print Network [OSTI]

function within the homologous proteins, despite the lack of a direct connection between sequenceA Graphical Model for Predicting Protein Molecular Function Barbara E. Engelhardt bee function evolves within a phylogenetic tree based on the proteins' sequence. Inputs are a phylogeny

367

A graphical model for predicting protein molecular function Barbara E Engelhardt bee@cs.berkeley.edu  

E-Print Network [OSTI]

function within the homologous proteins, despite the lack of a direct connection between sequenceA graphical model for predicting protein molecular function Barbara E Engelhardt bee function evolves within a phylogenetic tree based on the proteins' sequence. Inputs are a phylogeny

Stephens, Matthew

368

Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving Horizon Estimation  

E-Print Network [OSTI]

tethered to the ground at a high velocity across the wind direction. Power can be generated by a, the first option is considered. Because it involves a much lighter structure, a major advantage of powerControl of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving

369

Virtual Electrodes Mechanisms Predictions with a Current-Lifted Monodomain Model  

E-Print Network [OSTI]

Virtual Electrodes Mechanisms Predictions with a Current-Lifted Monodomain Model Yves Coudi`ere1 cost. The source term is derived from a lifting principle ap- plied to the resolution, and an excitation part, that remains unchanged. Equivalently, we make a lifting of the stimula- tion functions

Boyer, Edmond

370

Human Leg Model Predicts Ankle Muscle-Tendon Morphology, State, Roles and Energetics in Walking  

E-Print Network [OSTI]

Human Leg Model Predicts Ankle Muscle-Tendon Morphology, State, Roles and Energetics in Walking to be established. Here we develop a computational framework to address how the ankle joint actuation problem-tendon morphology and neural activations enable a metabolically optimal realization of biological ankle mechanics

Herr, Hugh

371

A probabilistic model to predict the formation and propagation of crack networks in thermal  

E-Print Network [OSTI]

. In the case of cooling systems in nuclear power plants, observations revealed the presence of thermal crazing loading even if thermal fatigue is multiaxial. However, the first simulations on a uniaxial mechanicalA probabilistic model to predict the formation and propagation of crack networks in thermal fatigue

372

A Novel Virtual Age Reliability Model for Time-to-Failure Prediction  

E-Print Network [OSTI]

counts, devices approaching physical feature size limits and nuclear plant comparable power densityA Novel Virtual Age Reliability Model for Time-to-Failure Prediction Yao Wang, Sorin Cotofana their relatively short operating lifetime. To overcome the MTTF weakness, this paper proposes a novel virtual age

Kuzmanov, Georgi

373

Randomized Model Predictive Control for HVAC Systems Alessandra Parisio, Damiano Varagnolo, Daniel Risberg,  

E-Print Network [OSTI]

Randomized Model Predictive Control for HVAC Systems Alessandra Parisio, Damiano Varagnolo, Daniel Conditioning (HVAC) sys- tems play a fundamental role in maintaining acceptable ther- mal comfort and Indoor. A possible solu- tion is to develop effective control strategies for HVAC sys- tems, but this is complicated

Johansson, Karl Henrik

374

Occupancy Modeling and Prediction for Building Energy Management VARICK L. ERICKSON, University of California, Merced  

E-Print Network [OSTI]

42 Occupancy Modeling and Prediction for Building Energy Management VARICK L. ERICKSON, University, University of California, Merced Heating, cooling and ventilation accounts for 35% energy usage in the United into building conditioning system for usage-based demand control conditioning strategies. Using strategies based

Carreira-Perpiñán, Miguel Á.

375

Model-predicted distribution of wind-induced internal wave energy in the world's oceans  

E-Print Network [OSTI]

Model-predicted distribution of wind-induced internal wave energy in the world's oceans Naoki 9 July 2008; published 30 September 2008. [1] The distribution of wind-induced internal wave energy-scaled kinetic energy are all consistent with the available observations in the regions of significant wind

Miami, University of

376

Predicting effective magnetoelectric response in magnetic-ferroelectric composites via phase-field modeling  

E-Print Network [OSTI]

Predicting effective magnetoelectric response in magnetic-ferroelectric composites via phase Articles you may be interested in Stress magnetization model for magnetostriction in multiferroic composite circular fibrous multiferroic composites J. Appl. Phys. 109, 104901 (2011); 10.1063/1.3583580 Effect

Chen, Long-Qing

377

Prediction of the tool displacement for robot milling applications using coupled models of an industrial  

E-Print Network [OSTI]

. INTRODUCTION The major fields of machining applications for industrial robots are automated pre- machining an industrial robot for milling applications inaccuracies of the serial robot kinematic, the low structuralPrediction of the tool displacement for robot milling applications using coupled models

Stryk, Oskar von

378

Motion Control of Tetrahymena pyriformis Cells with Artificial Magnetotaxis: Model Predictive Control (MPC) Approach  

E-Print Network [OSTI]

-- The use of live microbial cells as microscale robots is an attractive premise, primarily because eukaryotic cell. Whitesides et al [10] demonstrated the biological propul- sion of microscale loadsMotion Control of Tetrahymena pyriformis Cells with Artificial Magnetotaxis: Model Predictive

Julius, Anak Agung

379

Economic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks  

E-Print Network [OSTI]

Economic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks EWO University Oct 12, 2011 Ajit Gopalakrishnan (CMU) Economic NMPC for gas pipeline optimization Oct 12, 2011 1 Gopalakrishnan (CMU) Economic NMPC for gas pipeline optimization Oct 12, 2011 4 / 24 #12;Natural Gas Industry

Grossmann, Ignacio E.

380

PREDICTIONS FOR STRESS-STRAIN BEHAVIOR OF PANKI FLY-ASH USING MODIFIED CAM CLAY MODEL  

E-Print Network [OSTI]

the fact that fly-ash is a granular material and its mechanical response may be similar to that of soils) is based on critical state soil mechanics, and today it is one of the most widely used constitutive model for predicting the mechanical behavior of geo-materials. In critical state soil mechanics, it is proposed

Prashant, Amit

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Technical Report -DTU -Informatics and Mathematical Modeling (May 31, 2007) Temperature Prediction in District  

E-Print Network [OSTI]

Prediction in District Heating Systems with cFIR models Pierre Pinson , Torben S. Nielsen, Henrik Aa. Nielsen, Lyngby, Denmark Abstract Current methodologies for the optimal operation of district heating systems regularization. Results are given for the test case of the Roskilde district heating system, over a period

382

Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms.  

E-Print Network [OSTI]

deficit in the near field, Proceedings of the European Wind Energy Conference, Madrid, Spain, European, Boundary Layer Meteorology 132, pp. 129-149, 2009. [3] G. Larsen, H. Madsen and N. Sørensen, Mean wake·Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms. ·Wake

Daraio, Chiara

383

Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models  

E-Print Network [OSTI]

Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models Dragan Ivanovi´c Universidad Polit´ecnica de Madrid idragan@clip.dia.fi.upm.es Peerachai Kaowichakorn Universidad Polit´ecnica de Madrid p.kaowichakorn@gmail.com Manuel Carro Universidad Polit´ecnica de Madrid

Politécnica de Madrid, Universidad

384

Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model  

E-Print Network [OSTI]

processes of PAH with subcritical water [5,6] since it provides the extractability limit which can be used groups, for the representation of the solubility of solid PAH in subcritical water. These hal-00872639Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model

Paris-Sud XI, Université de

385

Model predictive control of a pilot-scale distillation column using a programmable automation controller  

E-Print Network [OSTI]

Model predictive control of a pilot-scale distillation column using a programmable automation). The controller is tested on a pilot-scale binary distillation column to track reference temperatures. A majorRIO) to control a pilot-scale binary distillation col- umn. Both the PI-controllers and the supervising online MPC

386

A data-based approach for multivariate model predictive control performance monitoring$  

E-Print Network [OSTI]

of the proposed methodology is demonstrated in a case study of the Wood­Berry distillation column system. & 2010 model predictive control (MPC) controller, which systematically integrates both the assessment'' user-predefined one, this method can properly evaluate the performance of an MPC controller

Chen, Sheng

387

Exploiting Two Intelligent Models to Predict Water Level: A field study of Urmia lake, Iran  

E-Print Network [OSTI]

Exploiting Two Intelligent Models to Predict Water Level: A field study of Urmia lake, Iran Shahab. The measurements from a single tide gauge at Urmia Lake, Northwest Iran, were used to train and validate the GP of Tabriz, Tabriz, Iran. Tel: 0098-411-3392786 Fax: 0098-411-3345332, (e-mail: sha- hab kvk66@yahoo

Fernandez, Thomas

388

2014Science About the cover: A new transcriptomics-based model accurately predicts how much  

E-Print Network [OSTI]

2014Science Frontiers #12;About the cover: A new transcriptomics-based model accurately predicts's Environmental Molecular Sciences Laboratory: Making Isoprene from Biomass Material Using Bacillus Species. Pacific Northwest National Laboratory (PNNL) is a U.S. Department of Energy (DOE), Office of Science

389

Predicting Protein Folds with Structural Repeats Using a Chain Graph Model  

E-Print Network [OSTI]

Predicting Protein Folds with Structural Repeats Using a Chain Graph Model Yan Liu yanliu, Carnegie Mellon University, Pittsburgh, PA 15213 USA Abstract Protein fold recognition is a key step to to accurately identify protein folds aris- ing from typical spatial arrangements of well-defined secondary

Xing, Eric P.

390

A comparison of various models in predicting ignition delay in single-particle coal combustion  

E-Print Network [OSTI]

A comparison of various models in predicting ignition delay in single-particle coal combustion November 2013 Accepted 7 January 2014 Available online xxxx Keywords: Coal Devolatilization Ignition delay a b s t r a c t In this paper, individual coal particle combustion under laminar conditions

391

Model-Inspired Research. TES research uses modeling, prediction, and synthesis to identify  

E-Print Network [OSTI]

in Earth system models (ESMs). TES supports research to advance fundamental understanding of terrestrial-process models, ecosystem models, and the Community Earth System Model). This emphasis on the capture of advanced in Earth system models to increase the quality of climate model projections and to provide the scientific

392

Reliability analysis and prediction of mixed mode load using Markov Chain Model  

SciTech Connect (OSTI)

The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading.

Nikabdullah, N. [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia and Institute of Space Science (ANGKASA), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); Singh, S. S. K.; Alebrahim, R.; Azizi, M. A. [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); K, Elwaleed A. [Institute of Space Science (ANGKASA), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); Noorani, M. S. M. [School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia (Malaysia)

2014-06-19T23:59:59.000Z

393

Probe measurements and numerical model predictions of evolving size distributions in premixed flames  

SciTech Connect (OSTI)

Particle size distributions (PSDs), measured with a dilution probe and a Differential Mobility Analyzer (DMA), and numerical predictions of these PSDs, based on a model that includes only coagulation or alternatively inception and coagulation, are compared to investigate particle growth processes and possible sampling artifacts in the post-flame region of a C/O = 0.65 premixed laminar ethylene-air flame. Inputs to the numerical model are the PSD measured early in the flame (the initial condition for the aerosol population) and the temperature profile measured along the flame's axial centerline. The measured PSDs are initially unimodal, with a modal mobility diameter of 2.2 nm, and become bimodal later in the post-flame region. The smaller mode is best predicted with a size-dependent coagulation model, which allows some fraction of the smallest particles to escape collisions without resulting in coalescence or coagulation through the size-dependent coagulation efficiency ({gamma}{sub SD}). Instead, when {gamma} = 1 and the coagulation rate is equal to the collision rate for all particles regardless of their size, the coagulation model significantly under predicts the number concentration of both modes and over predicts the size of the largest particles in the distribution compared to the measured size distributions at various heights above the burner. The coagulation ({gamma}{sub SD}) model alone is unable to reproduce well the larger particle mode (mode II). Combining persistent nucleation with size-dependent coagulation brings the predicted PSDs to within experimental error of the measurements, which seems to suggest that surface growth processes are relatively insignificant in these flames. Shifting measured PSDs a few mm closer to the burner surface, generally adopted to correct for probe perturbations, does not produce a better matching between the experimental and the numerical results. (author)

De Filippo, A.; Sgro, L.A.; Lanzuolo, G.; D'Alessio, A. [Dipartimento di Ingegneria Chimica, Universita degli Studi di Napoli Federico II, Piazzale Tecchio 80, 80125 Napoli (Italy)

2009-09-15T23:59:59.000Z

394

Tacoma Power- Residential Weatherization Rebate Program  

Broader source: Energy.gov [DOE]

Tacoma Power helps residential customers increase the energy efficiency of homes through the utility's residential weatherization program. Weatherization upgrades to windows are eligible for an...

395

Administration Announces Nearly $8 Billion in Weatherization...  

Office of Environmental Management (EM)

Administration Announces Nearly 8 Billion in Weatherization Funding and Energy Efficiency Grants Administration Announces Nearly 8 Billion in Weatherization Funding and Energy...

396

Monitoring Plan for Weatherization Assistance Program, State...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Monitoring Plan for Weatherization Assistance Program, State Energy Program and Energy Efficiency and Conservation Block Grants Monitoring Plan for Weatherization Assistance...

397

Demand Response-Enabled Model Predictive HVAC Load Control in Buildings using Real-Time Electricity Pricing.  

E-Print Network [OSTI]

??A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy (more)

Avci, Mesut

2013-01-01T23:59:59.000Z

398

Left-right models with light neutrino mass prediction and dominant neutrinoless double beta decay rate  

E-Print Network [OSTI]

In TeV scale left-right symmetric models, new dominant predictions to neutrinoless double beta decay and light neutrino masses are in mutual contradiction because of large contribution to the latter through popular seesaw mechanisms. We show that in a class of left-right models with high-scale parity restoration, these results coexist without any contravention with neutrino oscillation data and the relevant formula for light neutrino masses is obtained via gauged inverse seesaw mechanism. The most dominant contribution to the double beta decay is shown to be via $W^-_L- W^-_R$ mediation involving both light and heavy neutrino exchanges, and the model predictions are found to discriminate whether the Dirac neutrino mass is of quark-lepton symmetric origin or without it. We also discuss associated lepton flavor violating decays.

M. K. Parida; Sudhanwa Patra

2013-01-14T23:59:59.000Z

399

A Model for Predicting Magnetic Targeting of Multifunctional Particles in the Microvasculature  

E-Print Network [OSTI]

A mathematical model is presented for predicting magnetic targeting of multifunctional carrier particles that are designed to deliver therapeutic agents to malignant tissue in vivo. These particles consist of a nonmagnetic core material that contains embedded magnetic nanoparticles and therapeutic agents such as photodynamic sensitizers. For in vivo therapy, the particles are injected into the vascular system upstream from malignant tissue, and captured at the tumor using an applied magnetic field. The applied field couples to the magnetic nanoparticles inside the carrier particle and produces a force that attracts the particle to the tumor. In noninvasive therapy the applied field is produced by a permanent magnet positioned outside the body. In this paper a mathematical model is developed for predicting noninvasive magnetic targeting of therapeutic carrier particles in the microvasculature. The model takes into account the dominant magnetic and fluidic forces on the particles and leads to an analytical expr...

Furlani, E J

2006-01-01T23:59:59.000Z

400

Predicting Land-Ice Retreat and Sea-Level Rise with the Community Earth System Model  

SciTech Connect (OSTI)

Coastal stakeholders need defensible predictions of 21st century sea-level rise (SLR). IPCC assessments suggest 21st century SLR of {approx}0.5 m under aggressive emission scenarios. Semi-empirical models project SLR of {approx}1 m or more by 2100. Although some sea-level contributions are fairly well constrained by models, others are highly uncertain. Recent studies suggest a potential large contribution ({approx}0.5 m/century) from the marine-based West Antarctic Ice Sheet, linked to changes in Southern Ocean wind stress. To assess the likelihood of fast retreat of marine ice sheets, we need coupled ice-sheet/ocean models that do not yet exist (but are well under way). CESM is uniquely positioned to provide integrated, physics based sea-level predictions.

Lipscomb, William [Los Alamos National Laboratory

2012-06-19T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Predictive storm damage modeling and optimizing crew response to improve storm response operations  

E-Print Network [OSTI]

Utility infrastructures are constantly damaged by naturally occurring weather. Such damage results in customer service interruption and repairs are necessary to return the system to normal operation. In most cases these ...

Whipple, Sean David

2014-01-01T23:59:59.000Z

402

Comparison of simplified models of urban climate for improved prediction of building energy use in cities  

E-Print Network [OSTI]

Thermal simulation of buildings is a requisite tool in the design of low-energy buildings, yet, definition of weather boundary conditions during simulation of urban buildings suffers from a lack of data that accounts for ...

Street, Michael A. (Michael Anthony)

2013-01-01T23:59:59.000Z

403

WEATHER MODIFICATION BY CARBON DUST ABSORPTION OF SOLAR ENERGY  

E-Print Network [OSTI]

WEATHER MODIFICATION BY CARBON DUST ABSORPTION OF SOLAR ENERGY by WM. M. GRAY, WM. M. FRANK, M OF SOLAR ENERGY by w. M. Gray, W. M. Frank, M. L. Corrin and C. A. Stokes Department of Atmospheric Science interception of solar energy. Growing population pressures and predicted future global food shortages dictate

Gray, William

404

WeatherMaker: Weather file conversion and evaluation  

SciTech Connect (OSTI)

WeatherMaker is a weather-data utility for use with the ENERGY-10 design-tool computer program. The three main features are: Convert--Weather files can be converted from one format to another. For example, a TMY2 format file can be converted to an ENERGY-10 binary file that can be used in a simulation. This binary file can then be converted to a text format that allows it to be read and/or manipulated in WordPad or Excel. Evaluate--ENERGY-10 weather files can be studied in great detail. There are 8 graphical displays of the data that provide insight into the data, and a summary tables that presents results calculated from the hourly data. Adjust--Hourly temperature data can be adjusted starting with hourly data from a nearby TMY2 site. Dry-bulb and wet-bulb temperatures are adjusted up or down as required to match given monthly statistics. This feature can be used to generate weather files for any of 3,958 sites in the US where such monthly statistics are tabulated. The paper shows a variety of results, explains the methods used, and discusses the rationale for making the adjustments. It is anticipated that WeatherMaker will be released by the time of the ASES Solar 99 conference.

Balcomb, J.D.

1999-07-01T23:59:59.000Z

405

Fast and accurate prediction of numerical relativity waveforms from binary black hole mergers using surrogate models  

E-Print Network [OSTI]

Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. In this paper, we construct an accurate and fast-to-evaluate surrogate model for numerical relativity (NR) waveforms from non-spinning binary black hole coalescences with mass ratios from $1$ to $10$ and durations corresponding to about $15$ orbits before merger. Our surrogate, which is built using reduced order modeling techniques, is distinct from traditional modeling efforts. We find that the full multi-mode surrogate model agrees with waveforms generated by NR to within the numerical error of the NR code. In particular, we show that our modeling strategy produces surrogates which can correctly predict NR waveforms that were {\\em not} used for the surrogate's training. For all practical purposes, then, the surrogate waveform model is equivalent to the high-accuracy, large-scale simulation waveform but can be evaluated in a millisecond to a second dependin...

Blackman, Jonathan; Galley, Chad R; Szilagyi, Bela; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

2015-01-01T23:59:59.000Z

406

Oldest and Largest The Weather  

E-Print Network [OSTI]

MIT's Oldest and Largest Newspaper The Weather Today: Clear skies, 45°F (70C) Tonight: Clear, cool Eilts, former U.S. Ambassador to Saudi Arabia and Egypt and Professor Emeritus of Inter- national

407

Probabilistic fatigue life prediction model for alloys with defects: applied to A206  

SciTech Connect (OSTI)

Presented here is a model for the prediction of fatigue life based on the statistical distribution of pores, intermetallic particles and grains. This has been applied to a cast Al alloy A206, before and after friction stir processing (FSP). The model computes the probability to initiate a small crack based on the probability of finding combinations of defects and grains on the surface. The crack initiation and propagation life of small cracks due to these defect and grain combinations are computed and summed to obtain the total fatigue life. The defect and grain combinations are ranked according to total fatigue life and the failure probability computed. Bending fatigue experiments were carried out on A206 before and after FSP. FSP eliminated the porosity, broke down the particles and refined the microstructure. The model predicted the fatigue life of A206 before and after FSP well. The cumulative probability distribution vs. fatigue life was fitted to a three parameter Weibull distribution function. The scatter reduced after FSP and the threshold of fatigue life increased. The potential improvement in the fatigue life of A206 for a microstructure consisting of a finer distribution of particle sizes after FSP was predicted using the model.

Kapoor, Rajeev; Sree Hari Rao, V.; Mishra, Rajiv S.; Baumann, John A.; Grant, Glenn J.

2011-05-31T23:59:59.000Z

408

Evaluation of the Highway Safety Manual Crash Prediction Model for Rural Two-Lane Highway Segments in Kansas  

E-Print Network [OSTI]

for states other than those the model was developed for. To address this gap the Kansas Department of Transportation (KDOT) commissioned this study to analyze both the accuracy and the practicality of using these crash prediction models on Kansas highways...

Lubliner, Howard

2011-12-31T23:59:59.000Z

409

Impact of emissions, chemistry, and climate on atmospheric carbon monoxide : 100-year predictions from a global chemistry-climate model  

E-Print Network [OSTI]

The possible trends for atmospheric carbon monoxide in the next 100 yr have been illustrated using a coupled atmospheric chemistry and climate model driven by emissions predicted by a global economic development model. ...

Wang, Chien.; Prinn, Ronald G.

410

This Day in Weather History for southeast Minnesota, northeast Iowa, and western Wisconsin  

E-Print Network [OSTI]

this part of the Upper Mississippi River Valley, information for severe weather, and information and charts Regional Climate Center (MRCC), and Storm Prediction Center (SPC) archives; various newspaper archives

411

Low-Income Weatherization: The Human Dimension  

Broader source: Energy.gov [DOE]

This presentation focuses on how the human dimension saves energy within low-income weatherization programs.

412

Unified model of voltage/current mode control to predict subharmonic oscillation  

E-Print Network [OSTI]

A unified model of voltage mode control (VMC) and current mode control (CMC) is proposed to predict the subharmonic oscillation. In the unified model, based on the sampled-data slope-based analysis, the subharmonic oscillation boundary conditions for VMC/CMC have similar forms. The boundary conditions are exact, and can be further simplified in various approximate closed forms for design purpose. Harmonic balance analysis is also applied. Both the slope-based and harmonic balance analysis are applied to analyze five different VMC/CMC control schemes. A new "HB plot" and an equivalent "M plot" are proposed to accurately predict the subharmonic oscillation. The relation between the crossover frequency and the subharmonic oscillation is also analyzed.

Fang, Chung-Chieh

2012-01-01T23:59:59.000Z

413

Energy Savings Through Application of Model Predictive Control to an Air Separation Facility  

E-Print Network [OSTI]

Energy Savings Through Application of Model Predictive Control to an Air Separation Facility Thomas C. Hanson PauiF. Scharf Manager Senior Engineering Associate Process Development Process Control Technology Praxair, Inc., Tonawanda, New York...TM based operator interface was developed by Praxair to make the system usable in our operations. 174 ESL-IE-96-04-24 Proceedings from the Eighteenth Industrial Energy Technology Conference, Houston, TX, April 17-18, 1996 Benefits overview MPC has...

Hanson, T. C.; Scharf, P. F.

414

PREV'AIR, a modeling platform for the air quality predictability study , C. Honor2  

E-Print Network [OSTI]

PREV'AIR, a modeling platform for the air quality predictability study Menut L.1 , C. Honoré2 , L Ministère de l'écologie et du développement durable, Paris, France This platform is proposed by the PREV'AIR about PREV'AIR ? please send an e-mail to cecile.honore@ineris.fr 1. Introduction Since 2002, the PREV'AIR

Menut, Laurent

415

Statistical Model Predictions for p-p and Pb-Pb collisions at LHC  

E-Print Network [OSTI]

Predictions for particle production at LHC are discussed in the context of the statistical model. Moreover, the capability of particle ratios to determine the freeze-out point experimentally is studied, and the best suited ratios are specified. Finally, canonical suppression in p-p collisions at LHC energies is discussed in a cluster framework. Measurements with p-p collisions will allow us to estimate the strangeness correlation volume and to study its evolution over a large range of incident energies.

I Kraus; J Cleymans; H Oeschler; K Redlich; S Wheaton

2007-07-09T23:59:59.000Z

416

A new thermodynamic model to predict wax deposition from crude oils  

E-Print Network [OSTI]

Hydrocarbons 5 Comparison of Experimental and Predicted Onset Temperatures using this Model at 1 Atm. 30 31 37 6 Component Data for Oil Mixture l. 7 Characterization for Oil Mixture l. 8 Characterization for Oil Mixture 2. 9 Characterization for Oil... for Flash Calculations . . 34 4 Variation of Onset Temperature with Pressure for Oil Mixture l. . . 5 Variation of Onset Temperature with Pressure for Oil Mixture 2 . . 51 52 6 Wax Precipitation Curves for Oil Mixture 1 at 1 Atm. . . 7 Wax...

Loganathan, Narayanan

1993-01-01T23:59:59.000Z

417

Attic or Roof? An Evaluation of Two Advanced Weatherization Packages  

SciTech Connect (OSTI)

This project examines implementation of advanced retrofit measures in the context of a large-scale weatherization program and the archetypal Chicago brick bungalow. One strategy applies best practice air sealing methods and a standard insulation method to the attic floor. The other strategy creates an unvented roof assembly using materials and methods typically available to weatherization contractors. Through implementations of the retrofit strategies in a total of eight (8) test homes, the research found that the two different strategies achieve similar reductions in air leakage measurement (55%) and predicted energy performance (18%) relative to the pre-retrofit conditions.

Neuhauser, K.

2012-06-01T23:59:59.000Z

418

Earthquake prediction: Simple methods for complex phenomena  

E-Print Network [OSTI]

and predictions . . . . . . . . . . . . . . . . . . . . .6.1 Assessing models and predictions . . . . . . .What are earthquake predictions and forecasts? . . . . . .

Luen, Bradley

2010-01-01T23:59:59.000Z

419

Modeling and life prediction methodology for titanium matrix composites subjected to mission profiles  

SciTech Connect (OSTI)

Titanium matrix composites (TMCs) are being evaluated as structural materials for elevated temperature applications in future generation hypersonic vehicles. In such applications, TMC components are subjected to complex thermomechanical loading profiles at various elevated temperatures. Therefore, thermomechanical fatigue (TMF) testing, using a simulated mission profile, is essential for evaluation and development of life prediction methodologies. The objective of the research presented in this paper was to evaluate the TMF response of the [0/90]{sub 2s} SCS-6/TIMETAL-21S subjected to a generic hypersonic flight profile and its portions with a temperature ranging from {minus}130 to 816 C. It was found that the composite modulus, prior to rapid degradation, had consistent values for all the profiles tested. The accumulated minimum strain was also found to be the same for all the profiles tested. A micromechanics-based analysis was used to predict the stress-strain response of the laminate and of the constituents in each ply during thermomechanical loading conditions by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature-dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relationship. In the analysis, the composite modulus degradation was assumed to result from matrix cracking and was modeled by reducing the matrix modulus. Fatigue lives of the composite subjected to the complex generic hypersonic flight profiles were well correlated using the predicted stress in 0{degree} fibers.

Mirdamadi, M. [Analytical Services and Materials Inc., Hampton, VA (United States); Johnson, W.S. [Georgia Inst. of Tech., Atlanta, GA (United States). School of Materials Science and Engineering

1996-12-31T23:59:59.000Z

420

Modeling and life prediction methodology for Titanium Matrix Composites subjected to mission profiles  

SciTech Connect (OSTI)

Titanium matrix composites (TMC) are being evaluated as structural materials for elevated temperature applications in future generation hypersonic vehicles. In such applications, TMC components are subjected to complex thermomechanical loading profiles at various elevated temperatures. Therefore, thermomechanical fatigue (TMF) testing, using a simulated mission profile, is essential for evaluation and development of life prediction methodologies. The objective of the research presented in this paper was to evaluate the TMF response of the (0/90)2s SCS-6/Timetal-21S subjected to a generic hypersonic flight profile and its portions with a temperature ranging from -130 C to 816 C. It was found that the composite modulus, prior to rapid degradation, had consistent values for all the profiles tested. A micromechanics based analysis was used to predict the stress-strain response of the laminate and of the constituents in each ply during thermomechanical loading conditions by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relation. In the analysis, the composite modulus degradation was assumed to result from matrix cracking and was modeled by reducing the matrix modulus. Fatigue lives of the composite subjected to the complex generic hypersonic flight profile were well correlated using the predicted stress in 0 degree fibers.

Mirdamadi, M.; Johnson, W.S.

1994-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Pressure vessel embrittlement predictions based on a composite model of copper precipitation and point defect clustering  

SciTech Connect (OSTI)

A theoretical model is used to investigate the relative importance of point defect clusters (PDC) and copper-rich precipitates in reactor pressure vessel (RPV) embrittlement and to examine the influence of a broad range of irradiation and material parameters on predicted yield strength changes. The results indicate that there are temperature and displacement rate regimes wherein either CRP or PDC can dominate the material`s response to irradiation, with both interstitial and vacancy type defects contributing to the PDC component. The different dependencies of the CRP and PDC on temperature and displacement rate indicate that simple data extrapolations could lead to poor predictions of RPV embrittlement. It is significant that the yield strength changes predicted by the composite PDC/CRP model exhibit very little dependence on displacement rate below about 10{sup {minus}9} dpa/s. If this result is confirmed, concerns about accelerated displacement rates in power reactor surveillance programs should be minimized. The sensitivity of the model to microstructural parameters highlights the need for more detailed microstructural characterization of RPV steels.

Stoller, R.E. [Oak Ridge National Lab., TN (United States). Metals and Ceramics Div.

1996-12-31T23:59:59.000Z

422

Predictive Reactor Pressure Vessel Steel Irradiation Embrittlement Models: Issues and Opportunities  

SciTech Connect (OSTI)

Nuclear plant life extension to 80 years will require accurate predictions of neutron irradiation-induced increases in the ductile-brittle transition temperature ( T) of reactor pressure vessel (RPV) steels at high fluence conditions that are far outside the existing database. Remarkable progress in mechanistic understanding of irradiation embrittlement has led to physically motivated T correlation models that provide excellent statistical fi ts to the existing surveillance database. However, an important challenge is developing advanced embrittlement models for low fl ux-high fl uence conditions pertinent to extended life. These new models must also provide better treatment of key variables and variable combinations and account for possible delayed formation of late blooming phases in low copper steels. Other issues include uncertainties in the compositions of actual vessel steels, methods to predict T attenuation away from the reactor core, verifi cation of the master curve method to directly measure the fracture toughness with small specimens and predicting T for vessel annealing remediation and re-irradiation cycles.

Odette, George Robert [UCSB; Nanstad, Randy K [ORNL

2009-01-01T23:59:59.000Z

423

Aquatic Pathways Model to predict the fate of phenolic compounds. Appendixes A through D  

SciTech Connect (OSTI)

Organic materials released from energy-related activities could affect human health and the environment. We have developed a model to predict the fate of spills or discharges of pollutants into flowing or static bodies of fresh water. A computer code, Aquatic Pathways Model (APM), was written to implement the model. The APM estimates the concentrations of chemicals in fish tissue, water and sediment, and is therefore useful for assessing exposure to humans through aquatic pathways. The major pathways considered are biodegradation, fish and sediment uptake, photolysis, and evaporation. The model has been implemented with parameters for the distribution of phenols, an important class of compounds found in the water-soluble fractions of coal liquids. The model was developed to estimate the fate of liquids derived from coal. Current modeling efforts show that, in comparison with many pesticides and polyaromatic hydrocarbons (PAH), the lighter phenolics (the cresols) are not persistent in the environment. For the twelve phenolics studied, biodegradation appears to be the major pathway for elimination from aquatic environments. A pond system simulation of a spill of solvent-refined coal (SRC-II) materials indicates that phenol, cresols, and other single cyclic phenolics are degraded to 16 to 25 percent of their original concentrations within 30 hours. Adsorption of these compounds into sediments and accumulation by fish was minor. Results of a simulated spill of a coal liquid (SRC-II) into a pond show that APM predicted the allocation of 12 phenolic components among six compartments at 30 hours after a small spill. The simulation indicated that most of the introduced phenolic compounds were biodegraded. The phenolics remaining in the aquatic system partitioned according to their molecular weight and structure. A substantial amount was predicted to remain in the water, with less than 0.01% distributed in sediment or fish.

Aaberg, R.L.; Peloquin, R.A.; Strenge, D.L.; Mellinger, P.L.

1983-04-01T23:59:59.000Z

424

Ecological Impacts of the Cerro Grande Fire: Predicting Elk Movement and Distribution Patterns in Response to Vegetative Recovery through Simulation Modeling October 2005  

SciTech Connect (OSTI)

In May 2000, the Cerro Grande Fire burned approximately 17,200 ha in north-central New Mexico as the result of an escaped prescribed burn initiated by Bandelier National Monument. The interaction of large-scale fires, vegetation, and elk is an important management issue, but few studies have addressed the ecological implications of vegetative succession and landscape heterogeneity on ungulate populations following large-scale disturbance events. Primary objectives of this research were to identify elk movement pathways on local and landscape scales, to determine environmental factors that influence elk movement, and to evaluate movement and distribution patterns in relation to spatial and temporal aspects of the Cerro Grande Fire. Data collection and assimilation reflect the collaborative efforts of National Park Service, U.S. Forest Service, and Department of Energy (Los Alamos National Laboratory) personnel. Geographic positioning system (GPS) collars were used to track 54 elk over a period of 3+ years and locational data were incorporated into a multi-layered geographic information system (GIS) for analysis. Preliminary tests of GPS collar accuracy indicated a strong effect of 2D fixes on position acquisition rates (PARs) depending on time of day and season of year. Slope, aspect, elevation, and land cover type affected dilution of precision (DOP) values for both 2D and 3D fixes, although significant relationships varied from positive to negative making it difficult to delineate the mechanism behind significant responses. Two-dimensional fixes accounted for 34% of all successfully acquired locations and may affect results in which those data were used. Overall position acquisition rate was 93.3% and mean DOP values were consistently in the range of 4.0 to 6.0 leading to the conclusion collar accuracy was acceptable for modeling purposes. SAVANNA, a spatially explicit, process-oriented ecosystem model, was used to simulate successional dynamics. Inputs to the SAVANNA included a land cover map, long-term weather data, soil maps, and a digital elevation model. Parameterization and calibration were conducted using field plots. Model predictions of herbaceous biomass production and weather were consistent with available data and spatial interpolations of snow were considered reasonable for this study. Dynamic outputs generated by SAVANNA were integrated with static variables, movement rules, and parameters developed for the individual-based model through the application of a habitat suitability index. Model validation indicated reasonable model fit when compared to an independent test set. The finished model was applied to 2 realistic management scenarios for the Jemez Mountains and management implications were discussed. Ongoing validation of the individual-based model presented in this dissertation provides an adaptive management tool that integrates interdisciplinary experience and scientific information, which allows users to make predictions about the impact of alternative management policies.

S.P. Rupp

2005-10-01T23:59:59.000Z

425

Figure 1. Day 1 SPC Fire Weather Outlook graphic showing a critical area over parts of the western U.S.,  

E-Print Network [OSTI]

Figure 1. Day 1 SPC Fire Weather Outlook graphic showing a critical area over parts of the western. INTRODUCTION The Storm Prediction Center (SPC) in Norman, OK prepares national Fire Weather Outlooks valid thunderstorms, result in a significant threat of wildfires. The SPC Fire Weather Outlook contains both a text

426

A model for predicting the evolution of damage in the plastic bonded explosive LX17  

E-Print Network [OSTI]

. Of particular interest, Chan et al. (1997a, 1997b) observed grain boundary fracture in argillaceous salt. Along the same lines, Helms et al. (1999) employed the Tvergaard (1990) cohesive zone model in an implicit finite element code to predict grain boundary... implemented into a finite element code. The model, developed in part by Yoon and Allen (1999) and Allen and Searcy (2000, 2001a, 2001b), will use material parameters for the plastic bonded explosive LX17 in order to compare computational results...

Seidel, Gary Don

2002-01-01T23:59:59.000Z

427

Phenomenological Model for Predicting the Energy Resolution of Neutron-Damaged Coaxial HPGe Detectors  

SciTech Connect (OSTI)

The peak energy resolution of germanium detectors deteriorates with increasing neutron fluence. This is due to hole capture at neutron-created defects in the crystal which prevents the full energy of the gamma-ray from being recorded by the detector. A phenomenological model of coaxial HPGe detectors is developed that relies on a single, dimensionless parameter that is related to the probability for immediate trapping of a mobile hole in the damaged crystal. As this trap parameter is independent of detector dimensions and type, the model is useful for predicting energy resolution as a function of neutron fluence.

C. DeW. Van Siclen; E. H. Seabury; C. J. Wharton; A. J. Caffrey

2012-10-01T23:59:59.000Z

428

A Bayesian Approach for Parameter Estimation and Prediction using a Computationally Intensive Model  

E-Print Network [OSTI]

Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model $\\eta(\\theta)$ where $\\theta$ denotes the uncertain, best input setting. Hence the statistical model is of the form $y = \\eta(\\theta) + \\epsilon$, where $\\epsilon$ accounts for measurement, and possibly other error sources. When non-linearity is present in $\\eta(\\cdot)$, the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and non-standard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. While quite generally applicable, MCMC requires thousands, or even millions of evaluations of the physics model $\\eta(\\cdot)$. This is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we present an approach adapted from Bayesian model calibration. This approach combines output from an ensemble of computational model runs with physical measurements, within a statistical formulation, to carry out inference. A key component of this approach is a statistical response surface, or emulator, estimated from the ensemble of model runs. We demonstrate this approach with a case study in estimating parameters for a density functional theory (DFT) model, using experimental mass/binding energy measurements from a collection of atomic nuclei. We also demonstrate how this approach produces uncertainties in predictions for recent mass measurements obtained at Argonne National Laboratory (ANL).

Dave Higdon; Jordan D. McDonnell; Nicolas Schunck; Jason Sarich; Stefan M. Wild

2014-09-17T23:59:59.000Z

429

Sensor and model integration for the rapid prediction of concurrent flow flame spread  

E-Print Network [OSTI]

Fire Safety Engineering is required at every stage in the life cycle of modern-day buildings. Fire safety design, detection and suppression, and emergency response are all vital components of Structural Fire Safety but are usually perceived...Issues of accuracy aside, these models demand heavy resources and computational time periods that are far greater than the time associated with the processes being simulated. To be of use to emergency responders, the output would need to be produced faster than the event itself with lead time to enable planning of an intervention strategy. Therefore in isolation, model output is not robust or fast enough to be implemented in an emergency response scenario. The concept of super-real time predictions steered by measurements is studied in the simple yet meaningful scenario of concurrent flow flame spread. Experiments have been conducted with PMMA slabs to feed sensor data into a simple analytical model. Numerous sensing techniques have been adapted to feed a simple algebraic expression from the literature linking flame spread, flame characteristics and pyrolysis evolution in order to model upward flame spread. The measurements are continuously fed to the computations so that projections of the flame spread velocity and flame characteristics can be established at each instant in time, ahead of the real flame. It was observed that as the input parameters in the analytical models were optimised to the scenario, rapid convergence between the evolving experiment and the predictions was attained....

Cowlard, Adam

430

Accuracy Test for Link Prediction in terms of Similarity Index: The Case of WS and BA Models  

E-Print Network [OSTI]

Link prediction is a technique that uses the topological information in a given network to infer the missing links in it. Since past research on link prediction has primarily focused on enhancing performance for given empirical systems, negligible attention has been devoted to link prediction with regard to network models. In this paper, we thus apply link prediction to two network models: The Watts-Strogatz (WS) model and Barab\\'asi-Albert (BA) model. We attempt to gain a better understanding of the relation between accuracy and each network parameter (mean degree, the number of nodes and the rewiring probability in the WS model) through network models. Six similarity indices are used, with precision and area under the ROC curve (AUC) value as the accuracy metrics. We observe a positive correlation between mean degree and accuracy, and size independence of the AUC value.

Ahn, Min-Woo

2015-01-01T23:59:59.000Z

431

Predicting Coupled Ocean-Atmosphere Modes with a Climate Modeling Hierarchy -- Final Report  

SciTech Connect (OSTI)

The goal of the project was to determine midlatitude climate predictability associated with tropical-extratropical interactions on interannual-to-interdecadal time scales. Our strategy was to develop and test a hierarchy of climate models, bringing together large GCM-based climate models with simple fluid-dynamical coupled ocean-ice-atmosphere models, through the use of advanced probabilistic network (PN) models. PN models were used to develop a new diagnostic methodology for analyzing coupled ocean-atmosphere interactions in large climate simulations made with the NCAR Parallel Climate Model (PCM), and to make these tools user-friendly and available to other researchers. We focused on interactions between the tropics and extratropics through atmospheric teleconnections (the Hadley cell, Rossby waves and nonlinear circulation regimes) over both the North Atlantic and North Pacific, and the oceans thermohaline circulation (THC) in the Atlantic. We tested the hypothesis that variations in the strength of the THC alter sea surface temperatures in the tropical Atlantic, and that the latter influence the atmosphere in high latitudes through an atmospheric teleconnection, feeding back onto the THC. The PN model framework was used to mediate between the understanding gained with simplified primitive equations models and multi-century simulations made with the PCM. The project team is interdisciplinary and built on an existing synergy between atmospheric and ocean scientists at UCLA, computer scientists at UCI, and climate researchers at the IRI.

Michael Ghil, UCLA; Andrew W. Robertson, IRI, Columbia Univ.; Sergey Kravtsov, U. of Wisconsin, Milwaukee; Padhraic Smyth, UC Irvine

2006-08-04T23:59:59.000Z

432

Fast and accurate prediction of numerical relativity waveforms from binary black hole mergers using surrogate models  

E-Print Network [OSTI]

Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. In this paper, we construct an accurate and fast-to-evaluate surrogate model for numerical relativity (NR) waveforms from non-spinning binary black hole coalescences with mass ratios from $1$ to $10$ and durations corresponding to about $15$ orbits before merger. Our surrogate, which is built using reduced order modeling techniques, is distinct from traditional modeling efforts. We find that the full multi-mode surrogate model agrees with waveforms generated by NR to within the numerical error of the NR code. In particular, we show that our modeling strategy produces surrogates which can correctly predict NR waveforms that were {\\em not} used for the surrogate's training. For all practical purposes, then, the surrogate waveform model is equivalent to the high-accuracy, large-scale simulation waveform but can be evaluated in a millisecond to a second depending on the number of output modes and the sampling rate. Our model includes all spherical-harmonic ${}_{-2}Y_{\\ell m}$ waveform modes that can be resolved by the NR code up to $\\ell=8$, including modes that are typically difficult to model with other approaches. We assess the model's uncertainty, which could be useful in parameter estimation studies seeking to incorporate model error. We anticipate NR surrogate models to be useful for rapid NR waveform generation in multiple-query applications like parameter estimation, template bank construction, and testing the fidelity of other waveform models.

Jonathan Blackman; Scott E. Field; Chad R. Galley; Bela Szilagyi; Mark A. Scheel; Manuel Tiglio; Daniel A. Hemberger

2015-02-26T23:59:59.000Z

433

SIMULATION-BASED WEATHER NORMALIZATION APPROACH TO STUDY THE IMPACT OF WEATHER ON ENERGY USE OF BUILDINGS IN THE U.S.  

SciTech Connect (OSTI)

Weather normalization is a crucial task in several applications related to building energy conservation such as retrofit measurements and energy rating. This paper documents preliminary results found from an effort to determine a set of weather adjustment coefficients that can be used to smooth out impacts of weather on energy use of buildings in 1020 weather location sites available in the U.S. The U.S. Department of Energy (DOE) commercial reference building models are adopted as hypothetical models with standard operations to deliver consistency in modeling. The correlation between building envelop design, HVAC system design and properties for different building types and the change in heating and cooling energy consumption caused by variations in weather is examined.

Makhmalbaf, Atefe; Srivastava, Viraj; Wang, Na

2013-08-05T23:59:59.000Z

434

Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs  

SciTech Connect (OSTI)

Reservoirs in the Lansing-Kansas City limestone result from complex interactions among paleotopography (deposition, concurrent structural deformation), sea level, and diagenesis. Analysis of reservoirs and surface and near-surface analogs has led to developing a {open_quotes}strandline grainstone model{close_quotes} in which relative sea-level stabilized during regressions, resulting in accumulation of multiple grainstone buildups along depositional strike. Resulting stratigraphy in these carbonate units are generally predictable correlating to inferred topographic elevation along the shelf. This model is a valuable predictive tool for (1) locating favorable reservoirs for exploration, and (2) anticipating internal properties of the reservoir for field development. Reservoirs in the Lansing-Kansas City limestones are developed in both oolitic and bioclastic grainstones, however, re-analysis of oomoldic reservoirs provides the greatest opportunity for developing bypassed oil. A new technique, the {open_quotes}Super{close_quotes} Pickett crossplot (formation resistivity vs. porosity) and its use in an integrated petrophysical characterization, has been developed to evaluate extractable oil remaining in these reservoirs. The manual method in combination with 3-D visualization and modeling can help to target production limiting heterogeneities in these complex reservoirs and moreover compute critical parameters for the field such as bulk volume water. Application of this technique indicates that from 6-9 million barrels of Lansing-Kansas City oil remain behind pipe in the Victory-Northeast Lemon Fields. Petroleum geologists are challenged to quantify inferred processes to aid in developing rationale geologically consistent models of sedimentation so that acceptable levels of prediction can be obtained.

Watney, W.L.

1994-12-01T23:59:59.000Z

435

Simulation of complex glazing products; from optical data measurements to model based predictive controls  

SciTech Connect (OSTI)

Complex glazing systems such as venetian blinds, fritted glass and woven shades require more detailed optical and thermal input data for their components than specular non light-redirecting glazing systems. Various methods for measuring these data sets are described in this paper. These data sets are used in multiple simulation tools to model the thermal and optical properties of complex glazing systems. The output from these tools can be used to generate simplified rating values or as an input to other simulation tools such as whole building annual energy programs, or lighting analysis tools. I also describe some of the challenges of creating a rating system for these products and which factors affect this rating. A potential future direction of simulation and building operations is model based predictive controls, where detailed computer models are run in real-time, receiving data for an actual building and providing control input to building elements such as shades.

Kohler, Christian

2012-08-01T23:59:59.000Z

436

Failure Predictions for VHTR Core Components using a Probabilistic Contiuum Damage Mechanics Model  

SciTech Connect (OSTI)

The proposed work addresses the key research need for the development of constitutive models and overall failure models for graphite and high temperature structural materials, with the long-term goal being to maximize the design life of the Next Generation Nuclear Plant (NGNP). To this end, the capability of a Continuum Damage Mechanics (CDM) model, which has been used successfully for modeling fracture of virgin graphite, will be extended as a predictive and design tool for the core components of the very high- temperature reactor (VHTR). Specifically, irradiation and environmental effects pertinent to the VHTR will be incorporated into the model to allow fracture of graphite and ceramic components under in-reactor conditions to be modeled explicitly using the finite element method. The model uses a combined stress-based and fracture mechanics-based failure criterion, so it can simulate both the initiation and propagation of cracks. Modern imaging techniques, such as x-ray computed tomography and digital image correlation, will be used during material testing to help define the baseline material damage parameters. Monte Carlo analysis will be performed to address inherent variations in material properties, the aim being to reduce the arbitrariness and uncertainties associated with the current statistical approach. The results can potentially contribute to the current development of American Society of Mechanical Engineers (ASME) codes for the design and construction of VHTR core components.

Fok, Alex

2013-10-30T23:59:59.000Z

437

The Prediction of Extratropical Storm Tracks by the ECMWF and NCEP Ensemble Prediction Systems  

E-Print Network [OSTI]

The Prediction of Extratropical Storm Tracks by the ECMWF and NCEP Ensemble Prediction Systems 2006) ABSTRACT The prediction of extratropical cyclones by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) ensemble prediction systems

Froude, Lizzie

438

Lagrangian and Control Volume Models for Prediction of Cooling Lake Performance at SRP  

SciTech Connect (OSTI)

The model validation described in this document indicates that the methods described here and by Cooper (1984) for predicting the performance of the proposed L-Area cooling lake are reliable. Extensive observations from the Par Pond system show that lake surface temperatures exceeding 32.2 degrees C (90 degrees F) are attained occasionally in the summer in areas where there is little or no heating from the P-Area Reactor. Regulations which restrict lake surface temperatures to less than 32.2 degrees C should be structured to allow for these naturally-occurring thermal excursions.

Garrett, A.J.

2001-06-26T23:59:59.000Z

439

Toward a Fully Lagrangian Atmospheric Modeling System JAHRUL M. ALAM AND JOHN C. LIN  

E-Print Network [OSTI]

weather prediction (NWP) models]. A better numerical treatment of the nonlinear advection process numerical model is, therefore, presented for calculating atmospheric flows. The model employs a Lagrangian). Such models require numerical simu- lation of advection-dominated flow problems. The re- alization

Lin, John Chun-Han

440

Discrepancies in the prediction of solar wind using potential field source surface model: An investigation of possible sources  

E-Print Network [OSTI]

Discrepancies in the prediction of solar wind using potential field source surface model expansion factor (FTE) at the source surface and the solar wind speed (SWS) observed at Earth, which has been made use of in the prediction of solar wind speed near the Earth with reasonable accuracy. However

California at Berkeley, University of

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Journal of Energy and Power Engineering 5 (2011) 554-561 Load Torque Compensator for Model Predictive Direct  

E-Print Network [OSTI]

Predictive Direct Current Control in High Power PMSM Drive Systems M. Preindl1, 2 and E. Schaltz2 1. Power Magnet Synchronous Machine (PMSM), it contains an inner current i.e. torque control loop and an outer for Model Predictive Direct Current Control in High Power PMSM Drive Systems 555 Fig. 1 Block diagram

Schaltz, Erik

442

Weather Data Gamification  

E-Print Network [OSTI]

to planning policies and strategies to counter the impact of climate change, and identifies a need for climate awareness in the public. This thesis explores using gamification to motivate people to learn about long term trends in climate data. As a model...

Gargate, Rohit

2013-07-25T23:59:59.000Z

443

Homes Weatherized by State March 2010 | Department of Energy  

Energy Savers [EERE]

March 2010 Homes Weatherized by State March 2010 Weatherization Assistance Program Homes Weatherized By State through 03312010 HomesWeatherizedbyStateQ12010.pdf More...

444

U.S. Department of Energy Weatherization Assistance Program Homes...  

Broader source: Energy.gov (indexed) [DOE]

S. Department of Energy Weatherization Assistance Program Homes Weatherized By State through 06302010 (Calendar Year) U.S. Department of Energy Weatherization Assistance Program...

445

The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.  

SciTech Connect (OSTI)

One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would therefore be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a laser altimetry remote sensing method, obtained from the USDA Forest Service at Savannah River Site. The specific DEM resolutions were chosen because they are common grid cell sizes (10m, 30m, and 50m) used in mapping for management applications and in research. The finer resolutions (2m and 5m) were chosen for the purpose of determining how finer resolutions performed compared with coarser resolutions at predicting wetness and related soil attributes. The wetness indices were compared across DEMs and with each other in terms of quantile and distribution differences, then in terms of how well they each correlated with measured soil attributes. Spatial and non-spatial analyses were performed, and predictions using regression and geostatistics were examined for efficacy relative to each DEM resolution. Trends in the raw data and analysis results were also revealed.

Drover, Damion, Ryan

2011-12-01T23:59:59.000Z

446

A Predictive Model of Fragmentation using Adaptive Mesh Refinement and a Hierarchical Material Model  

SciTech Connect (OSTI)

Fragmentation is a fundamental material process that naturally spans spatial scales from microscopic to macroscopic. We developed a mathematical framework using an innovative combination of hierarchical material modeling (HMM) and adaptive mesh refinement (AMR) to connect the continuum to microstructural regimes. This framework has been implemented in a new multi-physics, multi-scale, 3D simulation code, NIF ALE-AMR. New multi-material volume fraction and interface reconstruction algorithms were developed for this new code, which is leading the world effort in hydrodynamic simulations that combine AMR with ALE (Arbitrary Lagrangian-Eulerian) techniques. The interface reconstruction algorithm is also used to produce fragments following material failure. In general, the material strength and failure models have history vector components that must be advected along with other properties of the mesh during remap stage of the ALE hydrodynamics. The fragmentation models are validated against an electromagnetically driven expanding ring experiment and dedicated laser-based fragmentation experiments conducted at the Jupiter Laser Facility. As part of the exit plan, the NIF ALE-AMR code was applied to a number of fragmentation problems of interest to the National Ignition Facility (NIF). One example shows the added benefit of multi-material ALE-AMR that relaxes the requirement that material boundaries must be along mesh boundaries.

Koniges, A E; Masters, N D; Fisher, A C; Anderson, R W; Eder, D C; Benson, D; Kaiser, T B; Gunney, B T; Wang, P; Maddox, B R; Hansen, J F; Kalantar, D H; Dixit, P; Jarmakani, H; Meyers, M A

2009-03-03T23:59:59.000Z

447

The use of a distributed hydrologic model to predict dynamic landslide susceptibility for a humid basin in Puerto Rico  

E-Print Network [OSTI]

This thesis describes the use of a distributed hydrology model in conjunction with a Factor of Safety (FS) algorithm to predict dynamic landslide susceptibility for a humid basin in Puerto Rico. The Mameyes basin, located ...

Kamal, Sameer A. (Sameer Ahmed)

2009-01-01T23:59:59.000Z

448

Prediction of continental shelf sediment transport using a theoretical model of the wave-current boundary layer  

E-Print Network [OSTI]

This thesis presents an application of the Grant-Madsen-Glenn bottom boundary layer model (Grant and Madsen, 1979; Glenn and Grant, 1987) to predictions of sediment transport on the continental shelf. The analysis is a ...

Goud, Margaret R

1987-01-01T23:59:59.000Z

449

Utilization of Smart Materials and Predictive Modeling to Integrate Intracellular Dynamics with Cell Biomechanics and Collective Tissue Behavior  

E-Print Network [OSTI]

Utilization of Smart Materials and Predictive Modeling to Integrate Intracellular Dynamics important structures inside cells. New "smart" material will be used to trigger changes to cell movement Medical University Control of Cell Polarization by Smart Material Substrates Multiscale Imaging Multiscale

Mather, Patrick T.

450

Finite Mixture of ARMA-GARCH Model for Stock Price Prediction Him Tang, Kai-Chun Chiu and Lei Xu  

E-Print Network [OSTI]

Finite Mixture of ARMA-GARCH Model for Stock Price Prediction Him Tang, Kai-Chun Chiu and Lei Xu mixture of autore- gressive generalized autoregressive conditional het- eroscedasticity (AR-GARCH) models to extend the mixture of AR-GARCH model (W.C. Wong, F. Yip and L. Xu, 1998) to the mixture of ARMA- GARCH

Xu, Lei

451

BFEPM:Best Fit Energy Prediction Modeling Based on CPU Utilization Xiao Zhang, Jianjun Lu, Xiao Qin  

E-Print Network [OSTI]

different servers have different energy consumption characters even with same CPU. In this paper, we present BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark different machines to estimate the real-time energy consumption. The results show our model can get better

Qin, Xiao

452

Gas Metal Arc Welding Process Modeling and Prediction of Weld Microstructure in MIL A46100 Armor-Grade  

E-Print Network [OSTI]

Gas Metal Arc Welding Process Modeling and Prediction of Weld Microstructure in MIL A46100 Armor metal arc welding (GMAW) butt-joining process has been modeled using a two-way fully coupled, transient in the form of heat, and the mechanical material model of the workpiece and the weld is made temperature

Grujicic, Mica

453

Performance of corrosion inhibiting admixtures for structural concrete -- assessment methods and predictive modeling  

SciTech Connect (OSTI)

During the past fifteen years corrosion inhibiting admixtures (CIAs) have become increasingly popular for protection of reinforced components of highway bridges and other structures from damage induced by chlorides. However, there remains considerable debate about the benefits of CIAs in concrete. A variety of testing methods to assess the performance of CIA have been reported in the literature, ranging from tests in simulated pore solutions to long-term exposures of concrete slabs. The paper reviews the published techniques and recommends the methods which would make up a comprehensive CIA effectiveness testing program. The results of this set of tests would provide the data which can be used to rank the presently commercially available CIA and future candidate formulations utilizing a proposed predictive model. The model is based on relatively short-term laboratory testing and considers several phases of a service life of a structure (corrosion initiation, corrosion propagation without damage, and damage to the structure).

Yunovich, M.; Thompson, N.G. [CC Technologies Labs., Inc., Dublin, OH (United States)

1998-12-31T23:59:59.000Z

454

Standard Model Predictions and New Physics Sensitivity in B->DD Decays  

E-Print Network [OSTI]

An extensive model-independent analysis of B->DD decays is carried out employing SU(3) flavour symmetry, including symmetry-breaking corrections. Several theoretically clean observables are identified which allow for testing the Standard Model. These include the known time-dependent CP asymmetries, the penguin pollution of which can be controlled in this framework, but notably also quasi-isospin relations which are experimentally well accessible and unaffected by symmetry-breaking corrections. Theoretical assumptions can be kept to a minimum and controlled by additional sum rules. Available data are used in global fits to predict the branching ratio for the B0->DsDs decay as well as several CP asymmetries which have not been measured so far, and future prospects are analyzed.

Jung, Martin

2014-01-01T23:59:59.000Z

455

Predictions of monthly energy consumption and annual patterns of energy usage for convenience stores by using multiple and nonlinear regression models  

E-Print Network [OSTI]

Thirty convenience stores in College Station, Texas, have been selected as the samples for an energy consumption prediction. The predicted models assist facility energy managers for making decisions of energy demand/supply plans. The models...

Muendej, Krisanee

2004-11-15T23:59:59.000Z

456

Incorporating Single-nucleotide Polymorphisms Into the Lyman Model to Improve Prediction of Radiation Pneumonitis  

SciTech Connect (OSTI)

Purpose: To determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-{beta}, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). Methods and Materials: Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGF{beta}, TNF{alpha}, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk of severe (grade {>=}3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. Results: Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGF{beta}, VEGF, TNF{alpha}, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGF{beta}, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. Conclusions: This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.

Tucker, Susan L., E-mail: sltucker@mdanderson.org [Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Li Minghuan [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China)] [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Xu Ting; Gomez, Daniel [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Yuan Xianglin [Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (China)] [Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (China); Yu Jinming [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China)] [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Liu Zhensheng; Yin Ming; Guan Xiaoxiang; Wang Lie; Wei Qingyi [Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Mohan, Radhe [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Vinogradskiy, Yevgeniy [University of Colorado School of Medicine, Aurora, Colorado (United States)] [University of Colorado School of Medicine, Aurora, Colorado (United States); Martel, Mary [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Liao Zhongxing [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)

2013-01-01T23:59:59.000Z

457

The application of a chemical equilibrium model, SOLTEQ, to predict the chemical speciations in stabilized/solidified waste forms  

E-Print Network [OSTI]

THE APPLICATION OI' A CHEMICAL EQUILIBRIUM MODEL, SOLTEQ, TO PREDICT THK CHEMICAL SPKCIATIONS IN STABILIZED/SOLIDIFIED WASTE FORMS A Thesis by JOO-YANG PARK Submitted to the Office of Graduate Studies of Texas A&M University in partial... fulfillment of the requirements for the degree of MASTER OF SCIENCE December 1994 Major Subject: Civil Engineering THE APPLICATION OF A CHEMICAL EQUILIBRIUM MODEL, SOLTEQ, TO PREDICT THE CHEMICAL SPECIATIONS IN STABILIZED/SOLIDIFIED WASTE FORMS A Thesis...

Park, Joo-Yang

1994-01-01T23:59:59.000Z

458

Interface modeling to predict well casing damage for big hill strategic petroleum reserve.  

SciTech Connect (OSTI)

Oil leaks were found in well casings of Caverns 105 and 109 at the Big Hill Strategic Petroleum Reserve site. According to the field observations, two instances of casing damage occurred at the depth of the interface between the caprock and top of salt. This damage could be caused by interface movement induced by cavern volume closure due to salt creep. A three dimensional finite element model, which allows each cavern to be configured individually, was constructed to investigate shear and vertical displacements across each interface. The model contains interfaces between each lithology and a shear zone to examine the interface behavior in a realistic manner. This analysis results indicate that the casings of Caverns 105 and 109 failed by shear stress that exceeded shear strength due to the horizontal movement of the top of salt relative to the caprock, and tensile stress due to the downward movement of the top of salt from the caprock, respectively. The casings of Caverns 101, 110, 111 and 114, located at the far ends of the field, are predicted to be failed by shear stress in the near future. The casings of inmost Caverns 107 and 108 are predicted to be failed by tensile stress in the near future.

Ehgartner, Brian L.; Park, Byoung Yoon

2012-02-01T23:59:59.000Z

459

Weatherization Innovation Pilot Program: Program Overview and Philadelphia Project Highlight (Fact Sheet)  

SciTech Connect (OSTI)

Case Study with WIPP program overview, information regarding eligibility, and successes from Pennsylvania's Commission on Economic Opportunity (CEO) that demonstrate innovative approaches that maximize the benefit of the program. The Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) recently launched the Weatherization Innovation Pilot Program (WIPP) to accelerate innovations in whole-house weatherization and advance DOE's goal of increasing the energy efficiency and health and safety of homes of low-income families. Since 2010, WIPP has helped weatherization service providers as well as new and nontraditional partners leverage non-federal financial resources to supplement federal grants, saving taxpayer money. WIPP complements the Weatherization Assistance program (WAP), which operates nation-wide, in U.S. territories and in three Native American tribes. 16 grantees are implementing weatherization innovation projects using experimental approaches to find new and better ways to weatherize homes. They are using approaches such as: (1) Financial tools - by understanding a diverse range of financing mechanisms, grantees can maximize the impact of the federal grant dollars while providing high-quality work and benefits to eligible low-income clients; (2) Green and healthy homes - in addition to helping families reduce their energy costs, grantees can protect their health and safety. Two WIPP projects (Connecticut and Maryland) will augment standard weatherization services with a comprehensive green and healthy homes approach; (3) New technologies and techniques - following the model of continuous improvement in weatherization, WIPP grantees will continue to use new and better technologies and techniques to improve the quality of work; (4) Residential energy behavior change - Two grantees are rigorously testing home energy monitors (HEMs) that display energy used in kilowatt-hours, allowing residents to monitor and reduce their energy use, and another is examining best-practices for mobile home energy efficiency; (5) Workforce development and volunteers - with a goal of creating a self-sustaining weatherization model that does not require future federal investment, three grantees are adapting business models successful in other sectors of the home performance business to perform weatherization work. Youthbuild is training youth to perform home energy upgrades to eligible clients and Habitat for Humanity is developing a model for how to incorporate volunteer labor in home weatherization. These innovative approaches will improve key weatherization outcomes, such as: Increasing the total number of homes that are weatherized; Reducing the weatherization cost per home; Increasing the energy savings in each weatherized home; Increasing the number of weatherization jobs created and retained; and Reducing greenhouse gas emissions.

Not Available

2012-01-01T23:59:59.000Z

460

Coupling Sorption to Soil Weathering During Reactive Transport: Impacts of Mineral Transformation and Sorbent Aging on Contaminant Speciation and Mobility  

SciTech Connect (OSTI)

This project aimed for a predictive-mechanistic understanding of the coupling between mineral weathering and contaminant (Cs, Sr, I) transport/fate in caustic waste-impacted sediments. Based on our prior studies of model clay mineral systems, we postulated that contaminant uptake to Hanford sediments would reflect concurrent adsorption and co-precipitation effects. Our specific objectives were: (1) to assess the molecular-scale mechanisms responsible for time-dependent sequestration of contaminants (Cs, Sr and I) during penetration of waste-induced weathering fronts; (2) to determine the rate and extent of contaminant release from the sorbed state; (3) to develop a reactive transport model based on molecular mechanisms and macroscopic flow experiments [(1) and (2)] that simulates adsorption, aging, and desorption dynamics. Progress toward achieving each of these objectives is discussed below. We observed unique molecular mechanisms for sequestration of Sr, Cs and I during native silicate weathering in caustic waste. Product solids, which included poorly crystalline aluminosilicates and well-crystallized zeolites and feldspathoids, accumulate contaminant species during crystal growth.

Chorover, J.; Mueller, K. T.; O'Day, P. A.; Serne, R. J.; Steefel, C. I.

2009-10-30T23:59:59.000Z

Note: This page contains sample records for the topic "weather prediction models" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Transition Prediction for Scramjet Intakes Using the \\gamma-Re_\\theta_t Model Coupled to Two Turbulence Models  

E-Print Network [OSTI]

Due to the thick boundary layers in hypersonic flows, the state of the boundary layer significantly influences the whole flow field as well as surface heat loads. Hence, for engineering applications the efficient numerical prediction of laminar-to-turbulent transition is a challenging and important task. Within the framework of the Reynolds averaged Navier-Stokes equations, Langtry/Menter [1] proposed the -Re?t transition model using two transport equations for the intermittency and Re?t combined with the Shear Stress Transport turbulence model (SST) [2]. The transition model contains two empirical correlations for onset and length of transition. Langtry/Menter [1] designed and validated the correlations for the subsonic and transonic flow regime. For our applications in the hypersonic flow regime, the development of a new set of correlations proved necessary, even when using the same SST turbulence model [3]. Within this paper, we propose a next step and couple the transition model with the SSG/LRR-! Reynold...

Frauholz, Sarah; Mller, Siegfried; Behr, Marek

2014-01-01T23:59:59.000Z

462

A Simple Path Loss Prediction Model for HVAC Systems O. K. Tonguz, D. D. Stancil, A. E. Xhafa, A. G. Cepni, P. V. Nikitin  

E-Print Network [OSTI]

1 A Simple Path Loss Prediction Model for HVAC Systems O. K. Tonguz, D. D. Stancil, A. E. Xhafa, A, and air conditioning (HVAC) cylindrical ducts in 2.4-2.5 GHz frequency band. The model we propose predicts the average power loss between a transmitter-receiver pair in an HVAC duct network. This prediction model

Stancil, Daniel D.

463

Immersed Boundary Methods for High-Resolution Simulation of Atmospheric Boundary-Layer Flow Over Complex Terrain  

E-Print Network [OSTI]

in todays numerical weather prediction models is stillability of a numerical weather prediction model to predictthe context of numerical weather prediction models. The two-

Lundquist, Katherine Ann

2010-01-01T23:59:59.000Z

464

Solar forecasting review  

E-Print Network [OSTI]

of all Numerical Weather Prediction (NWP models). First aof all Numerical Weather Prediction (NWP models). First apersistence models, numerical weather predictions as well as

Inman, Richard Headen

2012-01-01T23:59:59.000Z

465

Assessing the Impacts of Different WRF Precipitation Physics in Hurricane Simulations  

E-Print Network [OSTI]

ABSTRACT Numerical weather prediction models play a majorthat numerical weather prediction models are particularlymodel with numerical weather prediction models (Olson et al.

Nasrollahi, Nasrin; AghaKouchak, Amir; Li, Jialun; Gao, Xiaogang; Hsu, Kuolin; Sorooshian, Soroosh

2012-01-01T23:59:59.000Z

466

Interactions of Water and Energy Mediate Responses of High-Latitude Terrestrial Ecosystems to Climate Change  

E-Print Network [OSTI]

into the numerical weather prediction model COSMO. Borealinto the numerical weather prediction model COSMO. BorealCurrent numerical weather prediction (NWP) models, regional

Subin, Zachary Marc

2012-01-01T23:59:59.000Z

467

Cluster analysis of cloud properties : a method for diagnosing cloud-climate feedbacks  

E-Print Network [OSTI]

from a numerical weather prediction model over approximatelyto analyses from numerical weather prediction models but isconstrains numerical weather prediction (NWP) model output

Gordon, Neil D.

2008-01-01T23:59:59.000Z

468

Prediction of buried mine-like target radar signatures using wideband electromagnetic modeling  

SciTech Connect (OSTI)

Current ground penetrating radars (GPR) have been tested for land mine detection, but they have generally been costly and have poor performance. Comprehensive modeling and experimentation must be done to predict the electromagnetic (EM) signatures of mines to access the effect of clutter on the EM signature of the mine, and to understand the merit and limitations of using radar for various mine detection scenarios. This modeling can provide a basis for advanced radar design and detection techniques leading to superior performance. Lawrence Livermore National Laboratory (LLNL) has developed a radar technology that when combined with comprehensive modeling and detection methodologies could be the basis of an advanced mine detection system. Micropower Impulse Radar (MIR) technology exhibits a combination of properties, including wideband operation, extremely low power consumption, extremely small size and low cost, array configurability, and noise encoded pulse generation. LLNL is in the process of developing an optimal processing algorithm to use with the MIR sensor. In this paper, we use classical numerical models to obtain the signature of mine-like targets and examine the effect of surface roughness on the reconstructed signals. These results are then qualitatively compared to experimental data.

Warrick, A.L.; Azevedo, S.G.; Mast, J.E.

1998-04-06T23:59:59.000Z

469

Explaining the road accident risk: weather effects Ruth Bergel-Hayat1*  

E-Print Network [OSTI]

1 Explaining the road accident risk: weather effects Ruth Bergel-Hayat1* , Mohammed Debbarh1 conditions and road accident risk at an aggregate level and on a monthly basis, in order to improve road accidents. Time series analysis models with explanatory variables that measure the weather quantitatively

Paris-Sud XI, Université de

470

200,000 homes weatherized under the Recovery Act  

Broader source: Energy.gov [DOE]

Today Vice President Biden announced that the Weatherization Assistance Program has weatherized 200,000 homes under the Recovery Act.

471

Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs (Annex 1)  

SciTech Connect (OSTI)

Interdisciplinary studies of the Upper Pennsylvanian Lansing and Kansas City groups have been undertaken in order to improve the geologic characterization of petroleum reservoirs and to develop a quantitative understanding of the processes responsible for formation of associated depositional sequences. To this end, concepts and methods of sequence stratigraphy are being used to define and interpret the three-dimensional depositional framework of the Kansas City Group. The investigation includes characterization of reservoir rocks in oil fields in western Kansas, description of analog equivalents in near-surface and surface sites in southeastern Kansas, and construction of regional structural and stratigraphic framework to link the site specific studies. Geologic inverse and simulation models are being developed to integrate quantitative estimates of controls on sedimentation to produce reconstructions of reservoir-bearing strata in an attempt to enhance our ability to predict reservoir characteristics.

Watney, W.L.

1992-01-01T23:59:59.000Z

472

Model predictive control system and method for integrated gasification combined cycle power generation  

DOE Patents [OSTI]

Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

2013-04-09T23:59:59.000Z

473

A COMPARATIVE ANALYSIS OF THE INFLUENCE OF WEATHER ON THE  

E-Print Network [OSTI]

conditions (Bouten et al. 2003). This model will be used by experts as a decision support tool to reduceA COMPARATIVE ANALYSIS OF THE INFLUENCE OF WEATHER ON THE FLIGHT ALTITUDES OF BIRDS Meteorological/Bash/stats.html). The International Civil Aviation Organization (ICAO) has long acknowledged the risk of bird hazards to civil

Loon, E. Emiel van

474

Modeling Stress Strain Relationships and Predicting Failure Probabilities For Graphite Core Components  

SciTech Connect (OSTI)

This project will implement inelastic constitutive models that will yield the requisite stress-strain information necessary for graphite component design. Accurate knowledge of stress states (both elastic and inelastic) is required to assess how close a nuclear core component is to failure. Strain states are needed to assess deformations in order to ascertain serviceability issues relating to failure, e.g., whether too much shrinkage has taken place for the core to function properly. Failure probabilities, as opposed to safety factors, are required in order to capture the bariability in failure strength in tensile regimes. The current stress state is used to predict the probability of failure. Stochastic failure models will be developed that can accommodate possible material anisotropy. This work will also model material damage (i.e., degradation of mechanical properties) due to radiation exposure. The team will design tools for components fabricated from nuclear graphite. These tools must readily interact with finite element software--in particular, COMSOL, the software algorithm currently being utilized by the Idaho National Laboratory. For the eleastic response of graphite, the team will adopt anisotropic stress-strain relationships available in COMSO. Data from the literature will be utilized to characterize the appropriate elastic material constants.

Duffy, Stephen

2013-09-09T23:59:59.000Z

475

Quasi-steady model for predicting temperature of aqueous foams circulating in geothermal wellbores  

SciTech Connect (OSTI)

A quasi-steady model has been developed for predicting the temperature profiles of aqueous foams circulating in geothermal wellbores. The model assumes steady one-dimensional incompressible flow in the wellbore; heat transfer by conduction from the geologic formation to the foam is one-dimensional radially and time-dependent. The vertical temperature distribution in the undisturbed geologic formation is assumed to be composed of two linear segments. For constant values of the convective heat-transfer coefficient, a closed-form analytical solution is obtained. It is demonstrated that the Prandtl number of aqueous foams is large (1000 to 5000); hence, a fully developed temperature profile may not exist for representative drilling applications. Existing convective heat-transfer-coefficient solutions are adapted to aqueous foams. The simplified quasi-steady model is successfully compared with a more-sophisticated finite-difference computer code. Sample temperature-profile calculations are presented for representative values of the primary parameters. For a 5000-ft wellbore with a bottom hole temperature of 375{sup 0}F, the maximum foam temperature can be as high as 300{sup 0}F.

Blackwell, B.F.; Ortega, A.

1983-01-01T23:59:59.000Z

476

Variance, Skewness & Kurtosis: results from the APM Cluster Redshift Survey and model predictions  

E-Print Network [OSTI]

We estimate the variance $\\xibar_2$, the skewness $\\xibar_3$ and the kurtosis $\\xibar_4$ in the distribution of density fluctuations in a complete sample from the APM Cluster Redshift Survey with 339 clusters and a mean depth $ \\sim 250\\Mpc$. We are able to measure the statistics of fluctuations in spheres of radius $R \\simeq 5-80 \\Mpc$, with reasonable errorbars. The statistics in the cluster distribution follow the hierarchical pattern $\\xibar_J=S_J~\\xibar_2^{J-1}$ with $S_J$ roughly constant, $S_3 \\simeq 2$ and $S_4 \\sim 8$. We analyse the distribution of clusters taken from N-body simulations of different dark matter models. The results are compared with an alternative method of simulating clusters which uses the truncated Zel'dovich approximation. We argue that this alternative method is not reliable enough for making quantitative predictions of $\\xibar$. The N-body simulation results follow similar hierarchical relations to the observations, with $S_J$ almost unaffected by redshift distortions from peculiar motions. The standard $\\Omega=1$ Cold Dark Matter (CDM) model is inconsistent with either the second, third or fourth order statistics at all scales. However both a hybrid Mixed Dark Matter model and a low density CDM variant agree with the $\\xibar_J$ observations.

Enrique Gaztaaga; Rupert Croft; Gavin Dalton

1995-01-31T23:59:59.000Z

477

Supporting technology for enhanced oil recovery: CO/sub 2/ miscible flood predictive model  

SciTech Connect (OSTI)

The CO/sub 2/ Miscible Flood Predictive Model (CO2PM) was developed by Scientific Software-Intercomp for the US Department of Energy and was used in the National Petroleum Council's (NPC) 1984 survey of US enhanced oil recovery potential (NPC, 1984). The CO2PM is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO/sub 2/ injection or water-alternating-gas (WAG) processes. In the CO2PM, an oil rate versus time function for a single pattern is computed, the results of which are passed to the economic calculations. To estimate multi-pattern project behavior a pattern development schedule is required. After-tax cash flow is computed by combining revenues with costs for drilling, conversion and well workovers, CO/sub 2/ compression and recycle, fixed and variable operating costs, water treating and disposal costs, depreciation, royalties, severance, state, federal and windfall profit taxes, cost and price inflation rates, and the discount rate. A lumped parameter uncertainty model is used to estimate risk, allowing for variation in computed project performance within an 80% confidence interval. The CO2PM is a three-dimensional (layered, five-spot), two-phase (aqueous and oleic), three component (oil, water, and CO/sub 2/) model. It computes oil and CO/sub 2/ breakthrough and recovery from fractional theory modified for the effects of viscous fingering, areal sweep, vertical heterogeneity and gravity segregation. 23 refs., 19 figs., 57 tabs.

Ray, R.M.; Munoz, J.D.

1986-12-01T23:59:59.000Z

478

Predictive Treatment Management: Incorporating a Predictive Tumor Response Model Into Robust Prospective Treatment Planning for Non-Small Cell Lung Cancer  

SciTech Connect (OSTI)

Purpose: We hypothesized that a treatment planning technique that incorporates predicted lung tumor regression into optimization, predictive treatment planning (PTP), could allow dose escalation to the residual tumor while maintaining coverage of the initial target without increasing dose to surrounding organs at risk (OARs). Methods and Materials: We created a model to estimate the geometric presence of residual tumors after radiation therapy using planning computed tomography (CT) and weekly cone beam CT scans of 5 lung cancer patients. For planning purposes, we modeled the dynamic process of tumor shrinkage by morphing the original planning target volume (PTV{sub orig}) in 3 equispaced steps to the predicted residue (PTV{sub pred}). Patients were treated with a uniform prescription dose to PTV{sub orig}. By contrast, PTP optimization started with the same prescription dose to PTV{sub orig} but linearly increased the dose at each step, until reaching the highest dose achievable to PTV{sub pred} consistent with OAR limits. This method is compared with midcourse adaptive replanning. Results: Initial parenchymal gross tumor volume (GTV) ranged from 3.6 to 186.5 cm{sup 3}. On average, the primary GTV and PTV decreased by 39% and 27%, respectively, at the end of treatment. The PTP approach gave PTV{sub orig} at least the prescription dose, and it increased the mean dose of the true residual tumor by an average of 6.0 Gy above the adaptive approach. Conclusions: PTP, incorporating a tumor regression model from the start, represents a new approach to increase tumor dose without increasing toxicities, and reduce clinical workload compared with the adaptive approach, although model verification using per-patient midcourse imaging would be prudent.

Zhang, Pengpeng, E-mail: zhangp@mskcc.org [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Yorke, Ellen; Hu, Yu-Chi; Mageras, Gig [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Rimner, Andreas [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States)

2014-02-01T23:59:59.000Z

479

ghMulti-Level Approach for Model-Based Predictive Control (MPC) in Buildings: A Preliminary Overview  

E-Print Network [OSTI]

Model-based predictive control (MPC) has emerged in recent years as a promising approach to building operation. MPC uses models of the system(s) under control -and knowledge about future disturbances- to select an optimal set of actions. Despite its...

Candanedo, J. A.; Dehkordi, V. R.

2013-01-01T23:59:59.000Z

480

Optimization of the GB/SA Solvation Model for Predicting the Structure of Surface Loops in Proteins  

E-Print Network [OSTI]

Optimization of the GB/SA Solvation Model for Predicting the Structure of Surface Loops in ProteinsVed: October 10, 2005; In Final Form: December 1, 2005 Implicit solvation models are commonly optimized the force field is sometimes not considered. In previous studies, we have developed an optimization

Meirovitch, Hagai

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481

Conclusions The results show that the models are able to predict the response of the FETi motor  

E-Print Network [OSTI]

Conclusions The results show that the models are able to predict the response of the FETi motor just one animal might over-fit the noise of that particular animal. However, a model designed strand transmit the movement to the sensory neurons in the FeCO, which excite the motor neurons. Design

Sóbester, András

482

Evaluation of Mixed-Phase Cloud Parameterizations in Short-Range Weather Forecasts with CAM3 and AM2 for Mixed-Phase Arctic Cloud Experiment  

SciTech Connect (OSTI)

By making use of the in-situ data collected from the recent Atmospheric Radiation Measurement Mixed-Phase Arctic Cloud Experiment, we have tested the mixed-phase cloud parameterizations used in the two major U.S. climate models, the National Center for Atmospheric Research Community Atmosphere Model version 3 (CAM3) and the Geophysical Fluid Dynamics Laboratory climate model (AM2), under both the single-column modeling framework and the U.S. Department of Energy Climate Change Prediction Program-Atmospheric Radiation Measurement Parameterization Testbed. An improved and more physically based cloud microphysical scheme for CAM3 has been also tested. The single-column modeling tests were summarized in the second quarter 2007 Atmospheric Radiation Measurement metric report. In the current report, we document the performance of these microphysical schemes in short-range weather forecasts using the Climate Chagne Prediction Program Atmospheric Radiation Measurement Parameterizaiton Testbest strategy, in which we initialize CAM3 and AM2 with realistic atmospheric states from numerical weather prediction analyses for the period when Mixed-Phase Arctic Cloud Experiment was conducted.

Xie, S; Boyle, J; Klein, S; Liu, X; Ghan, S

2007-06-01T23:59:59.000Z

483

Elements of a pragmatic approach for dealing with bias and uncertainty in experiments through predictions : experiment design and data conditioning; %22real space%22 model validation and conditioning; hierarchical modeling and extrapolative prediction.  

SciTech Connect (OSTI)

This report explores some important considerations in devising a practical and consistent framework and methodology for utilizing experiments and experimental data to support modeling and prediction. A pragmatic and versatile 'Real Space' approach is outlined for confronting experimental and modeling bias and uncertainty to mitigate risk in modeling and prediction. The elements of experiment design and data analysis, data conditioning, model conditioning, model validation, hierarchical modeling, and extrapolative prediction under uncertainty are examined. An appreciation can be gained for the constraints and difficulties at play in devising a viable end-to-end methodology. Rationale is given for the various choices underlying the Real Space end-to-end approach. The approach adopts and refines some elements and constructs from the literature and adds pivotal new elements and constructs. Crucially, the approach reflects a pragmatism and versatility derived from working many industrial-scale problems involving complex physics and constitutive models, steady-state and time-varying nonlinear behavior and boundary conditions, and various types of uncertainty in experiments and models. The framework benefits from a broad exposure to integrated experimental and modeling activities in the areas of heat transfer, solid and structural mechanics, irradiated electronics, and combustion in fluids and solids.

Romero, Vicente Jose

2011-11-01T23:59:59.000Z

484

Prediction of PWSCC in nickel base alloys using crack growth rate models  

SciTech Connect (OSTI)

The Ford/Andresen slip-dissolution SCC model, originally developed for stainless steel components in BWR environments, has been applied to Alloy 600 and Alloy X-750 tested in deaerated pure water chemistry. A method is described whereby the crack growth rates measured in compact tension specimens can be used to estimate crack growth in a component. Good agreement was found between model prediction and measured SCC in X-750 threaded fasteners over a wide range of temperatures, stresses, and material conditions. Most data support the basic assumption of this model that cracks initiate early in life. The evidence supporting a particular SCC mechanism is mixed. Electrochemical repassivation data and estimates of oxide fracture strain indicate that the slip-dissolution model can account for the observed crack growth rates, provided primary rather than secondary creep rates are used. However, approximately 100 cross-sectional TEM foils of SCC cracks including crack tips reveal no evidence of enhanced plasticity or unique dislocation patterns at the crack tip or along the crack to support a classic slip-dissolution mechanism. No voids, hydrides, or microcracks are found in the vicinity of the crack tips creating doubt about classic hydrogen related mechanisms. The bulk oxide films exhibit a surface oxide which is often different than the oxides found within a crack. Although bulk chromium concentration affects the rate of SCC, analytical data indicates the mechanism does not result from chromium depletion at the grain boundaries. The overall findings support a corrosion/dissolution mechanism but not one necessarily related to slip at the crack tip.

Thompson, C.D.; Krasodomski, H.T.; Lewis, N.; Makar, G.L. [Knolls Atomic Power Lab., Schenectady, NY (United States)

1995-12-31T23:59:59.000Z

485

SEISMIC RESPONSE PREDICTION OF NUPEC'S FIELD MODEL TESTS OF NPP STRUCTURES WITH ADJACENT BUILDING EFFECT.  

SciTech Connect (OSTI)

As part of a verification test program for seismic analysis computer codes for Nuclear Power Plant (NPP) structures, the Nuclear Power Engineering Corporation (NUPEC) of Japan has conducted a series of field model tests to address the dynamic cross interaction (DCI) effect on the seismic response of NPP structures built in close proximity to each other. The program provided field data to study the methodologies commonly associated with seismic analyses considering the DCI effect. As part of a collaborative program between the United States and Japan on seismic issues related to NPP applications, the U.S. Nuclear Regulatory Commission sponsored a program at Brookhaven National Laboratory (BNL) to perform independent seismic analyses which applied common analysis procedures to predict the building response to recorded earthquake events for the test models with DCI effect. In this study, two large-scale DCI test model configurations were analyzed: (1) twin reactor buildings in close proximity and (2) adjacent reactor and turbine buildings. This paper describes the NUPEC DCI test models, the BNL analysis using the SASSI 2000 program, and comparisons between the BNL analysis results and recorded field responses. To account for large variability in the soil properties, the conventional approach of computing seismic responses with the mean, mean plus and minus one-standard deviation soil profiles is adopted in the BNL analysis and the three sets of analysis results were used in the comparisons with the test data. A discussion is also provided in the paper to address (1) the capability of the analysis methods to capture the DCI effect, and (2) the conservatism of the practice for considering soil variability in seismic response analysis for adjacent NPP structures.

XU,J.COSTANTINO,C.HOFMAYER,C.ALI,S.

2004-03-04T23:59:59.000Z

486

NOAA Center for Weather and Climate Prediction NOAA Center for Weather and  

E-Print Network [OSTI]

for better insulation and protection. Rainwater bio-retention areas and a storm water cistern collect water for irrigation, and a four-story rainwater waterfall efficiently drains the non-green portion of the roof. NOAA

487

Extended Abstract, 20th Conf. Weather Analysis and Forecasting/ 16th Conf. Numerical Weather Prediction  

E-Print Network [OSTI]

. In the study, water and ice phase microphysical variables are first derived from the polariza- tion for an adjoint that should include detailed physics parameterizations and the high computational cost, 4DVAR,mxue@ou.edu. et al (2000) being one exception. In the latter, the ice mi- crophysics scheme used

Xue, Ming

488

MIT Big Data Challenge: Transportation in the City of Boston Model of Prediction Challenge  

E-Print Network [OSTI]

and for periods before and after the prediction interval. When available, the number of MBTA T rides at nearby

Oliva, Aude

489

Predictions of flow through an isothermal serpentine passage with linear eddy-viscosity Reynolds Averaged Navier Stokes models.  

SciTech Connect (OSTI)

Flows with strong curvature present a challenge for turbulence models, specifically eddy viscosity type models which assume isotropy and a linear and instantaneous equilibrium relation between stress and strain. Results obtained from three different codes and two different linear eddy viscosity turbulence models are compared to a DNS simulation in order to gain some perspective on the turbulence modeling capability of SIERRA/Fuego. The Fuego v2f results are superior to the more common two-layer k-e model results obtained with both a commercial and research code in terms of the concave near wall behavior predictions. However, near the convex wall, including the separated region, little improvement is gained using the v2f model and in general the turbulent kinetic energy prediction is fair at best.

Laskowski, Gregory Michael

2005-12-01T23:59:59.000Z

490

Autonomous Reactor Control Using Model Based Predictive Control for Space Propulsion Applications  

SciTech Connect (OSTI)

Reliable reactor control is important to reactor safety, both in terrestrial and space systems. For a space system, where the time for communication to Earth is significant, autonomous control is imperative. Based on feedback from reactor diagnostics, a controller must be able to automatically adjust to changes in reactor temperature and power level to maintain nominal operation without user intervention. Model-based predictive control (MBPC) (Clarke 1994; Morari 1994) is investigated as a potential control methodology for reactor start-up and transient operation in the presence of an external source. Bragg-Sitton and Holloway (2004) assessed the applicability of MBPC to reactor start-up from a cold, zero-power condition in the presence of a time-varying external radiation source, where large fluctuations in the external radiation source can significantly impact a reactor during start-up operations. The MBPC algorithm applied the point kinetics model to describe the reactor dynamics, using a single group of delayed neutrons; initial application considered a fast neutron lifetime (10-3 sec) to simplify calculations during initial controller analysis. The present study will more accurately specify the dynamics of a fast reactor, using a more appropriate fast neutron lifetime (10-7 sec) than in the previous work. Controller stability will also be assessed by carefully considering the dependencies of each component in the defined cost (objective) function and its subsequent effect on the selected 'optimal' control maneuvers.

Bragg-Sitton, Shannon M.; Holloway, James Paul [University of Michigan, Nuclear Engineering and Radiological Sciences, Ann Arbor, MI 48109 (United States)

2005-02-06T23:59:59.000Z

491

Impact of Pilot Light Modeling on the Predicted Annual Performance of Residential Gas Water Heaters: Preprint  

SciTech Connect (OSTI)

Modeling residential water heaters with dynamic simulation models can provide accurate estimates of their annual energy consumption, if the units? characteristics and use conditions are known. Most gas storage water heaters (GSWHs) include a standing pilot light. It is generally assumed that the pilot light energy will help make up standby losses and have no impact on the predicted annual energy consumption. However, that is not always the case. The gas input rate and conversion efficiency of a pilot light for a GSWH were determined from laboratory data. The data were used in simulations of a typical GSWH with and without a pilot light, for two cases: 1) the GSWH is used alone; and 2) the GSWH is the second tank in a solar water heating (SWH) system. The sensitivity of wasted pilot light energy to annual hot water use, climate, and installation location was examined. The GSWH used alone in unconditioned space in a hot climate had a slight increase in energy consumption. The GSWH with a pilot light used as a backup to an SWH used up to 80% more auxiliary energy than one without in hot, sunny locations, from increased tank losses.

Maguire, J.; Burch, J.

2013-08-01T23:59:59.000Z

492

Molecular adsorption of alkanes on platinum surfaces: A predictive theoretical model  

SciTech Connect (OSTI)

The adsorption probabilities of methane and propane on Pt(111), and propane on Pt(110)-(1{times}2) have been successfully predicted for a wide range of incident energies and angles with classical stochastic trajectory simulations, using a pairwise additive Morse methyl{endash}platinum potential previously developed from the measured trapping probabilities of ethane on Pt(111). These predictions, along with those for ethane adsorption on Pt(110){endash}(1{times}2), comprise a unified model for the molecular adsorption of alkanes on platinum surfaces. The simulations show the initial trapping probabilities of methane and propane on Pt(111) are determined to within approximately 10{percent} by the fate of the first bounce. They also indicate that at normal incidence on Pt(111) energy conversions from perpendicular translational motion to both cartwheeling rotation and lattice phonons play increasingly important roles in increasing the trapping probability as the alkane increases in size and molecular weight. For methane itself excitation of parallel translational momentum after the first bounce serves as the most effective energy storage mechanism which facilitates trapping, whereas for propane cartwheel rotational motion plays the dominant role. Excessive excitation of these modes of motion, however, can cause scattering on subsequent bounces by reconversion of the energy into perpendicular translational energy. Collisions of methane with the hollow and bridge sites on the Pt(111) surface appear less effective in trapping than do atop sites. The simulations also suggest excitation of the C{endash}C{endash}C bending mode of propane has little effect on the trapping of propane on platinum surfaces for beam energies below 55 kJ/mol. {copyright} {ital 1996 American Institute of Physics.}

Stinnett, J.A.; Madix, R.J. [Department of Chemical Engineering, Stanford University, Stanford, California 94305 (United States)] [Department of Chemical Engineering, Stanford University, Stanford, California 94305 (United States)

1996-07-01T23:59:59.000Z

493

Development and verification of simplified prediction models for enhanced oil recovery applications. CO/sub 2/ (miscible flood) predictive model. Final report  

SciTech Connect (OSTI)

A screening model for CO/sub 2/ miscible flooding has been developed consisting of a reservoir model for oil rate and recovery and an economic model. The reservoir model includes the effects of viscous fingering, reservoir heterogeneity, gravity segregation and areal sweep. The economic model includes methods to calculate various profitability indices, the windfall profits tax, and provides for CO/sub 2/ recycle. The model is applicable to secondary or tertiary floods, and to solvent slug or WAG processes. The model does not require detailed oil-CO/sub 2/ PVT data for execution, and is limited to five-spot patterns. A pattern schedule may be specified to allow economic calculations for an entire project to be made. Models of similar architecture have been developed for steam drive, in-situ combustion, surfactant-polymer flooding, polymer flooding and waterflooding. 36 references, 41 figures, 4 tables.

Paul, G.W.

1984-10-01T23:59:59.000Z

494

Diurnal to annual variations in the atmospheric water cycle  

E-Print Network [OSTI]

global numerical weather prediction models. Investigationsknown problem in numerical weather prediction models, wheremodel. Preprint, 11 th AMS Conference on Numerical Weather Prediction,

Ruane, Alexander C.

2007-01-01T23:59:59.000Z

495

REVIEW OF MECHANISTIC UNDERSTANDING AND MODELING AND UNCERTAINTY ANALYSIS METHODS FOR PREDICTING CEMENTITIOUS BARRIER PERFORMANCE  

SciTech Connect (OSTI)

Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various chapters contain both a description of the mechanism or and a discussion of the current approaches to modeling the phenomena.

Langton, C.; Kosson, D.

2009-11-30T23:59:59.000Z

496

Predicting the microbial "weather" | Argonne National Laboratory  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar Home Design PassivePostdoctoralKanareykin,U DPre-Combustion

497

Do Ecological Niche Model Predictions Reflect the Adaptive Landscape of Species?: A Test Using Myristica malabarica Lam., an Endemic Tree in the Western Ghats, India  

E-Print Network [OSTI]

Ecological niche models (ENM) have become a popular tool to define and predict the ecological niche of a species. An implicit assumption of the ENMs is that the predicted ecological niche of a species actually reflects ...

Nagaraju, Shivaprakash K.; Gudasalamani, Ravikanth; Barve, Narayani; Ghazoul, Jaboury; Narayangowda, Ganeshaiah Kotiganahalli; Ramanan, Uma Shaanker

2013-11-29T23:59:59.000Z

498

Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models  

SciTech Connect (OSTI)

Purpose: The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Methods: Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. Results: In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: ?11.6%23.8%) and 14.6% (range: ?7.3%27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: ?6.8%40.3%) and 13.1% (range: ?1.5%52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: ?11.1%20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. Conclusions: A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.

Yock, Adam D., E-mail: ADYock@mdanderson.org; Kudchadker, Rajat J. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)] [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States); Rao, Arvind [Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and the Graduate School of Biomedical Sciences, the University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)] [Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and the Graduate School of Biomedical Sciences, the University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States); Dong, Lei [Scripps Proton Therapy Center, San Diego, California 92121 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)] [Scripps Proton Therapy Center, San Diego, California 92121 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States); Beadle, Beth M.; Garden, Adam S. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States)] [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Court, Laurence E. [Department of Radiation Physics and Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)] [Department of Radiation Physics and Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)

2014-05-15T23:59:59.000Z

499

Five case studies of multifamily weatherization programs  

SciTech Connect (OSTI)

The multifamily case studies that are the subject of this report were conducted to provide a better understanding of the approach taken by program operators in weatherizing large buildings. Because of significant variations in building construction and energy systems across the country, five states were selected based on their high level of multifamily weatherization. This report summarizes findings from case studies conducted by multifamily weatherization operations in five cities. The case studies were conducted between January and November 1994. Each of the case studies involved extensive interviews with the staff of weatherization subgrantees conducting multifamily weatherization, the inspection of 4 to 12 buildings weatherized between 1991 and 1993, and the analysis of savings and costs. The case studies focused on innovative techniques which appear to work well.

Kinney, L; Wilson, T.; Lewis, G. [Synertech Systems Corp. (United States)] [Synertech Systems Corp. (United States); MacDonald, M. [Oak Ridge National Lab., TN (United States)] [Oak Ridge National Lab., TN (United States)

1997-12-31T23:59:59.000Z

500

Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model  

SciTech Connect (OSTI)

The primary research task completed for this project was the development of the Regional Arctic Climate Model (RACM). This involved coupling existing atmosphere, ocean, sea ice, and land models using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) coupler (CPL7). RACM is based on the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP) ocean model, the CICE sea ice model, and the Variable Infiltration Capacity (VIC) land model. A secondary research task for this project was testing and evaluation of WRF for climate-scale simulations on the large pan-Arctic model domain used in RACM. This involved identification of a preferred set of model physical parameterizations for use in our coupled RACM simulations and documenting any atmospheric biases present in RACM.

Cassano, John [Principal Investigator

2013-06-30T23:59:59.000Z