Sample records for weather prediction models

  1. The origins of computer weather prediction and climate modeling

    SciTech Connect (OSTI)

    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

    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.

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    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

  3. Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction

    E-Print Network [OSTI]

    McGovern, Amy

    dis- covery methods for use on mesoscale weather data. Severe weather phenomena such as tornados, thun of the transportation systems. The annual economic impact of these mesoscale storms is estimated to be greater than $13B

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  5. 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

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

    E-Print Network [OSTI]

    Heinemann, Detlev

    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

  7. Prediction Space Weather Using an Asymmetric Cone Model for Halo CMEs

    E-Print Network [OSTI]

    G. Michalek; N. Gopalswamy; S. Yashiro

    2007-10-24T23:59:59.000Z

    Halo coronal mass ejections (HCMEs) are responsible of the most severe geomagnetic storms. A prediction of their geoeffectiveness and travel time to Earth's vicinity is crucial to forecast space weather. Unfortunately coronagraphic observations are subjected to projection effects and do not provide true characteristics of CMEs. Recently, Michalek (2006, {\\it Solar Phys.}, {\\bf237}, 101) developed an asymmetric cone model to obtain the space speed, width and source location of HCMEs. We applied this technique to obtain the parameters of all front-sided HCMEs observed by the SOHO/LASCO experiment during a period from the beginning of 2001 until the end of 2002 (solar cycle 23). These parameters were applied for the space weather forecast. Our study determined that the space speeds are strongly correlated with the travel times of HCMEs within Earth's vicinity and with the magnitudes related to geomagnetic disturbances.

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

    SciTech Connect (OSTI)

    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

    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.

  9. 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

  10. Towards Ultra-High Resolution Models of Climate and Weather

    E-Print Network [OSTI]

    Wehner, Michael; Oliker, Leonid; Shalf, John

    2008-01-01T23:59:59.000Z

    Models of Climate and Weather Michael Wehner, Leonid Oliker,modeling climate change and weather prediction is one of thedelity in both short term weather prediction and long term

  11. Adjoint Sensitivity Analysis for Numerical Weather Prediction

    E-Print Network [OSTI]

    Alexandru Cioaca

    2011-09-02T23:59:59.000Z

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

  12. A real time model to forecast 24 hours ahead, ozone peaks and exceedance levels. Model based on artificial neural networks, neural classifier and weather predictions.

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    on artificial neural networks, neural classifier and weather predictions. Application in an urban atmosphere - will be solved. Keywords: Artificial neural network; Multilayer Perceptron; ozone modelling; statistical stepwise and Software 22, 9 (2007) 1261-1269" DOI : 10.1016/j.envsoft.2006.08.002 #12;Abstract A neural network combined

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    transport and  numerical weather modeling.   J.  Applied cross correlations.    Weather and Forecasting, 8:4, 401?of radiation for numerical weather prediction and climate 

  14. Impact of vegetation properties on U.S. summer weather prediction

    E-Print Network [OSTI]

    Xue, Y; Fennessy, M; sellers, P

    2015-01-01T23:59:59.000Z

    Meteorological Center, Mon. Weather Rev. , 108, 1279-1292,VEGETATION IN U.S. SUMMER WEATHER model (SIB) for use withinConference on Numerical Weather Prediction, pp. 726 -733,

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

    E-Print Network [OSTI]

    Dacre, Helen

    Office, Exeter 2 University of Reading Introduction In the case of a major pollution incident, terrorist to predict the transport of pollution away from its source, so allowing potentially affected areas predicting the spread of the smoke plume caused by the Buncefield Oil Depot fire in December 2005 (Webster et

  16. Predicting Weather Regime Transitions in Northern Hemisphere Datasets

    E-Print Network [OSTI]

    Kondrashov, D.; Shen, J.; Berk, R.; D., F

    2006-01-01T23:59:59.000Z

    R, D’Andrea F, Ghil M (2007) Weather regime prediction usingA case study. Mon. Weather Rev. , 120, 1616–1627. Kimoto M,D, Ide K, Ghil M (2004) Weather regimes and preferred

  17. Predicting Weather Regime Transitions in Northern Hemisphere Datasets

    E-Print Network [OSTI]

    D. Kondrashov; J. Shen; R. Berk; F. D

    2011-01-01T23:59:59.000Z

    R, D’Andrea F, Ghil M (2007) Weather regime prediction usingA case study. Mon. Weather Rev. , 120, 1616–1627. Kimoto M,D, Ide K, Ghil M (2004) Weather regimes and preferred

  18. Predicting Weather Regime Transitions in Northern Hemisphere Datasets

    E-Print Network [OSTI]

    Kondrashov, Dmitri; Shen, Jie; Berk, Richard; D'Andrea, F.; Ghil, M.

    2006-01-01T23:59:59.000Z

    R, D'Andrea F, Ghil M (2007) Weather regime prediction usingA case study. Mon. Weather Rev. , 120, 1616-1627. Kimoto M ,D, Ide K , Ghil M (2004) Weather regimes and preferred

  19. Geometric Numerical Methods for Numerical Weather Prediction

    E-Print Network [OSTI]

    Langdon, Stephen

    -Mesh (HPM) Method · Label space is discretised into N particles with coordinates on the momentum phase space and Sij = (1 - ^2xx)-1. Geometric Numerical Methods for Numerical Weather Prediction ­ p. 8/28 #12;HPM Equations of shallow water motions · The canonical HPM equations of 1D shallow water motion on TS1 are P

  20. 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

  1. Weather Regime Prediction Using Statistical Learning

    E-Print Network [OSTI]

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

    2011-01-01T23:59:59.000Z

    and B. Legras, 1995: Weather regimes: Recurrence and quasi10952. Molteni, F. , 2002: Weather regimes and multipleK. Ide, and M. Ghil, 2004: Weather regimes and preferred

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

    SciTech Connect (OSTI)

    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

    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.

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

    SciTech Connect (OSTI)

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

    2010-01-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Zhou, Shujia

    2009-01-01T23:59:59.000Z

    Acceleration of Numerical Weather Prediction,” ProceedingsComputer Systems for Climate and Weather Models Shujia Zhouprocesses in climate and weather models demands a continual

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

    E-Print Network [OSTI]

    , Parameterization Schemes: Keys to Understanding Numerical Weather Prediction Models, Cambridge University Press in class. Numerical model The primary numerical model that will be u

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    Evaluation of numerical weather prediction solar irradiancecycle: The RUC. Monthly Weather Review, 132 (2), 495-518.representations. Monthly Weather Review, 139 (6), 1972-1995.

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

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

    Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

    2009-01-01T23:59:59.000Z

    In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s 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 ensemblemore »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.« less

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

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

    Deremble, Bruno [Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Paris (France); D'Andrea, Fabio [Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Paris (France); Ghil, Michael [Univ. of California, Los Angeles, CA (United Staes). Atmospheric and Oceanic Sciences and Inst. of Geophysics and Planetary Physics

    2009-01-01T23:59:59.000Z

    In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s 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.

  9. Observations and simulations improve space weather models

    E-Print Network [OSTI]

    - 1 - Observations and simulations improve space weather models June 25, 2014 Los Alamos with fast-moving particles and a space weather system that varies in response to incoming energy computer simulations of the space weather that can affect vital technology, communication and navigation

  10. A Multi-period Equilibrium Pricing Model of Weather Derivatives

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01T23:59:59.000Z

    2002). On modelling and pricing weather derivatives. Applied2003). Arbitrage-fee pricing of weather derivatives based onfects and valuation of weather derivatives. The Financial

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

    E-Print Network [OSTI]

    Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

    2011-01-01T23:59:59.000Z

    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.

  12. Numerical Prediction of High-Impact Local Weather: A

    E-Print Network [OSTI]

    Xue, Ming

    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

  13. Weather

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

    Weather Weather We provide access to the latest meteorological observations, climatological information, and weather forecast products for the Los Alamos area. December 14, 2011...

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

    E-Print Network [OSTI]

    Mass, Clifford F.

    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

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

    E-Print Network [OSTI]

    Kurapov, Alexander

    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

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

    E-Print Network [OSTI]

    Mass, Clifford F.

    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

  17. EXTENSIONS OF GENERALIZED LINEAR MODELING APPROACH TO STOCHASTIC WEATHER GENERATORS

    E-Print Network [OSTI]

    Katz, Richard

    weather) -- Software R open source statistical programming language: Function glm "Family;(2) Generalized Linear Models Statistical Framework -- Multiple Regression Analysis (Linear model or LM) Response

  18. ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS

    SciTech Connect (OSTI)

    Chiswell, S.; Buckley, R.

    2009-01-15T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2012-08-15T23:59:59.000Z

    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.

  20. Surface Pressure Observations from Smartphones:3 A Potential Revolution for High-Resolution Weather Prediction?4

    E-Print Network [OSTI]

    Mass, Clifford F.

    -Resolution Weather Prediction?4 5 Clifford F. Mass1 and Luke E. Madaus6 Department of Atmospheric Sciences7 1 Corresponding author Professor Clifford F. Mass Department of Atmospheric Sciences Box 351640 about three-dimensional55 atmosph

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

    E-Print Network [OSTI]

    Randall, David A.

    , 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

  2. GENERALIZED LINEAR MODELING APPROACH TO STOCHASTIC WEATHER GENERATORS

    E-Print Network [OSTI]

    Katz, Richard

    ) Multisites (Spatial dependence of daily weather) -- Software R open source statistical programming language (Capable of "reproducing" any desired statistic) -- Disadvantages Synthetic weather looks too much like") Not amenable to uncertainty analysis #12;#12;#12;(2) Generalized Linear Models · Statistical Framework

  3. 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron SpinPrincetonUsing Maps1DOETHE FUTURE LOOKSofthe Geeks:WeaponsWeather

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

    E-Print Network [OSTI]

    Hilley, George

    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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    Model uncertainty in a mesoscale ensemble prediction system:monsoon experiment using a mesoscale two-dimensional model.Prediction operational mesoscale Eta model. Journal of

  6. Practical and Intrinsic Predictability of Severe and Convective Weather at the Mesoscales

    E-Print Network [OSTI]

    Practical and Intrinsic Predictability of Severe and Convective Weather at the Mesoscales at the mesoscales using convection-permitting ensemble simulations of a squall line and bow echo event during the Bow Echo and Mesoscale Convective Vortex (MCV) Experiment (BAMEX) on 9­10 June 2003. Although most

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

    E-Print Network [OSTI]

    Perez, Richard R.

    © 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

  8. Secular Changes in Solar Magnetic Flux Amplification Factor and Prediction of Space Weather

    E-Print Network [OSTI]

    T. E. Girish; G. Gopkumar

    2010-11-21T23:59:59.000Z

    We could infer a secular decreasing trend in the poloidal to toroidal solar magnetic flux amplification factor ( Af) using geomagnetic observations ( classic and IHV corrected aa indices) during the sunspot cycles 9-23. A similar decreasing trend is also observed for the solar equatorial rotation (W) which imply possibly a decrease in the efficiency of the solar dynamo during the above period. We could show correlated changes of Af and extreme space weather activity variations near earth since the middle of the 19th century. Indirect solar observations ( solar proton fluence estimates) suggests that the distinct enhancements in extreme space weather activity , Af and W found during sunspot cycles 10 to 15 is probably largest of that kind during the past 400 years. We find that the sunspot activity can reach an upper limit (Rweather conditions is most probable to occur during this cycle. Key words: Flux amplification,solar dynamo, space weather, predictions,cycle 24

  9. A multi-period equilibrium pricing model of weather derivatives

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2010-01-01T23:59:59.000Z

    Y. : Valuation and hedging of weather derivatives on monthlyJ. Risk 31. Yoo, S. : Weather derivatives and seasonaleffects and valuation of weather derivatives. Financ. Rev.

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

    E-Print Network [OSTI]

    Steinsland, Ingelin

    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

  11. Prediction of Terminal-Area Weather Penetration Based on Operational Factors

    E-Print Network [OSTI]

    Lin, Yi-Hsin

    Convective weather is known to reduce airspace capacity, but the extent of the impact is not well understood. Understanding how weather affects terminal area capacity is essential for quantification of the uncertainty in ...

  12. Prediction of terminal-area weather penetration based on operational factors

    E-Print Network [OSTI]

    Lin, Yi-Hsin, S.M. Massachusetts Institute of Technology

    2013-01-01T23:59:59.000Z

    As demand for air transportation grows, the existing air traffic control system is being pushed to capacity. This is especially true during weather events. However, the degree to which weather impacts airspace capacity, ...

  13. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output Perturbation

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output. This is typically not feasible for mesoscale weather prediction carried out locally by organizations without by simulating realizations of the geostatistical model. The method is applied to 48-hour mesoscale forecasts

  14. 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

  15. THE ROLE OF STORM PREDICTION CENTER PRODUCTS IN DECISION MAKING LEADING UP TO SEVERE WEATHER EVENTS

    E-Print Network [OSTI]

    to ultimately protect the lives and property of the American people. First-order users of SPC services, which responsibility is to release a suite of severe weather forecast and watch products for the #12;2 protection play key societal roles of efficiently relaying hazardous weather information to the public through

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    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

  17. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18T23:59:59.000Z

    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.

  18. Model prediction for reactor control

    SciTech Connect (OSTI)

    Ardell, G.G.; Gumowski, B.

    1983-06-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Niyogi, Dev

    (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 model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM

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

    SciTech Connect (OSTI)

    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

    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.

  1. Wet-Weather Flow Characterization for the Rock Creek through Monitoring and Modeling

    E-Print Network [OSTI]

    District of Columbia, University of the

    support of the following organizations: ­ DC Water Resources Research Institute ­ U.S. Geological Survey..................................................................16 Modeling of Urban Stormwater Management discharged to receiving waters demand that wet-weather flow control systems be planned and engineered

  2. 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

  3. 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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    to  predict daily solar radiation.   Agriculture and Forest and Chuo, S.   2008.  Solar radiation forecasting using Short?term forecasting of solar radiation:   A statistical 

  5. Developing Models for Predictive Climate Science

    SciTech Connect (OSTI)

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

    2007-01-01T23:59:59.000Z

    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.

  6. Developing a TeraGrid Based Land Surface Hydrology and Weather Modeling Interface

    E-Print Network [OSTI]

    Jiang, Wen

    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

  7. Predicting Improved Chiller Performance Through Thermodynamic Modeling

    E-Print Network [OSTI]

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

    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...

  8. 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]

    Renfrew, Ian

    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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    of variability for solar power plants.   While  NWP model operation of solar thermal power  plants, the management of 

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

    SciTech Connect (OSTI)

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

    2013-10-19T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Walter, Frederick M.

    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

  12. An Equilibrium Pricing Model for Weather Derivatives in a Multi-commodity Setting

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01T23:59:59.000Z

    e?ects and valuation of weather derivatives. The FinancialWei, J. (1999). Pricing weather derivative: an equilibrium2005). An introduction to cme weather products. www.cme.com/

  13. Monthly Weather Review Seamless precipitation prediction skill in the tropics and extratropics from a global

    E-Print Network [OSTI]

    Sobel, Adam

    (including the verification and validation of newly developed models) is essential, and goes hand in hand#12;National Power Grid Simulator Workshop b #12;1 Chartered in 1946 as the nation's first national are essential to maintain a competitive edge. This is particularly true for the complex transportation system

  14. Optimization Online - Nonlinear Model Predictive Control via ...

    E-Print Network [OSTI]

    M. J. Tenny

    2002-08-15T23:59:59.000Z

    Aug 15, 2002 ... Nonlinear Model Predictive Control via Feasibility-Perturbed Sequential Quadratic Programming. M. J. Tenny (tenny ***at*** bevo.che.wisc.edu)

  15. Prediction Markets Partition model of knowledge

    E-Print Network [OSTI]

    Fiat, Amos

    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

  16. Latent feature models for dyadic prediction /

    E-Print Network [OSTI]

    Menon, Aditya Krishna

    2013-01-01T23:59:59.000Z

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

  17. Solid phase evolution in the Biosphere 2 hillslope experiment as predicted by modeling of hydrologic and geochemical fluxes

    SciTech Connect (OSTI)

    Dontsova, K.; Steefel, C.I.; Desilets, S.; Thompson, A.; Chorover, J.

    2009-07-15T23:59:59.000Z

    A reactive transport geochemical modeling study was conducted to help predict the mineral transformations occurring over a ten year time-scale that are expected to impact soil hydraulic properties in the Biosphere 2 (B2) synthetic hillslope experiment. The modeling sought to predict the rate and extent of weathering of a granular basalt (selected for hillslope construction) as a function of climatic drivers, and to assess the feedback effects of such weathering processes on the hydraulic properties of the hillslope. Flow vectors were imported from HYDRUS into a reactive transport code, CrunchFlow2007, which was then used to model mineral weathering coupled to reactive solute transport. Associated particle size evolution was translated into changes in saturated hydraulic conductivity using Rosetta software. We found that flow characteristics, including velocity and saturation, strongly influenced the predicted extent of incongruent mineral weathering and neo-phase precipitation on the hillslope. Results were also highly sensitive to specific surface areas of the soil media, consistent with surface reaction controls on dissolution. Effects of fluid flow on weathering resulted in significant differences in the prediction of soil particle size distributions, which should feedback to alter hillslope hydraulic conductivities.

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

    SciTech Connect (OSTI)

    Morrison, PI Hugh

    2012-09-21T23:59:59.000Z

    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).

  19. Weather-based yield forecasts developed for 12 California crops

    E-Print Network [OSTI]

    Lobell, David; Cahill, Kimberly Nicholas; Field, Christopher

    2006-01-01T23:59:59.000Z

    RESEARCH ARTICLE Weather-based yield forecasts developed fordepend largely on the weather, measurements from existingpredictions. We developed weather-based models of statewide

  20. Predictive modelling of boiler fouling

    SciTech Connect (OSTI)

    Not Available

    1992-01-01T23:59:59.000Z

    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.

  1. Calibrating DOE-2 to Weather and Non-Weather-Dependent Loads for a Commercial Building: Data Processing Routines to Calibrate a DOE-2 Model, Volume II 

    E-Print Network [OSTI]

    Bronson, J. D.

    1992-01-01T23:59:59.000Z

    DOE-2 yields hourly data on specific variables provided the user specifies the HOURLY-REPORT instruction. Analyzing the simulation results with hourly data gives a more detailed picture of how well the model is predicting the monitored energy...

  2. Predictive modelling of boiler fouling

    SciTech Connect (OSTI)

    Not Available

    1992-01-01T23:59:59.000Z

    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.

  3. 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...

  4. area 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 159 Model predictive...

  5. An Equilibrium Pricing Model for Weather Derivatives in a Multi-commodity Setting

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01T23:59:59.000Z

    derivatives and risk management. Energy, 31. [Dutton, 2002]exposed to weather risk because the energy demand is highlyin the energy industry showing that volumetric risk caused

  6. Impact of rainstorm and runoff modeling on predicted consequences of atmospheric releases from nuclear reactor accidents

    SciTech Connect (OSTI)

    Ritchie, L.T.; Brown, W.D.; Wayland, J.R.

    1980-05-01T23:59:59.000Z

    A general temperate latitude cyclonic rainstorm model is presented which describes the effects of washout and runoff on consequences of atmospheric releases of radioactive material from potential nuclear reactor accidents. The model treats the temporal and spatial variability of precipitation processes. Predicted air and ground concentrations of radioactive material and resultant health consequences for the new model are compared to those of the original WASH-1400 model under invariant meteorological conditions and for realistic weather events using observed meteorological sequences. For a specific accident under a particular set of meteorological conditions, the new model can give significantly different results from those predicted by the WASH-1400 model, but the aggregate consequences produced for a large number of meteorological conditions are similar.

  7. 11.1 DEVELOPMENT OF AN IMMERSED BOUNDARY METHOD TO RESOLVE COMPLEX TERRAIN IN THE WEATHER RESEARCH AND FORECASTING MODEL

    E-Print Network [OSTI]

    Chow, Fotini Katopodes

    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

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

    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.

  9. Combining Modeling and Gaming for Predictive Analytics

    SciTech Connect (OSTI)

    Riensche, Roderick M.; Whitney, Paul D.

    2012-08-22T23:59:59.000Z

    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.

  10. Autonomous Helicopter Formation using Model Predictive Control

    E-Print Network [OSTI]

    Sastry, S. Shankar

    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

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

    E-Print Network [OSTI]

    Young, R. Michael

    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

  12. 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.

  13. Disease Prediction Models and Operational Readiness

    SciTech Connect (OSTI)

    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

    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, PNNL’s 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.

  14. 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...

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

    E-Print Network [OSTI]

    Juarez Torres, Miriam 77-

    2012-08-31T23:59:59.000Z

    , or even conclusive criterion (Genest and Favre 2007a). Data from three weather stations located in Montana, Washington and Texas are used for this research. 5 Background and Motivation Climatological and meteorological phenomena are complex...: [ )| ), ), ? , ) = ), Montana, one...

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

    SciTech Connect (OSTI)

    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

    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.

  17. Prediction Intervals in Generalized Linear Mixed Models

    E-Print Network [OSTI]

    Yang, Cheng-Hsueh

    2013-01-01T23:59:59.000Z

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

  18. Weatherization Roundup

    Broader source: Energy.gov [DOE]

    More than 750 thousand homes were weatherized by the Department’s 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.

  19. Gamma-Ray Pulsars: Models and Predictions

    E-Print Network [OSTI]

    Alice K. Harding

    2000-12-12T23:59:59.000Z

    Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. Next-generation gamma-ray telescopes sensitive to GeV-TeV emission will provide critical tests of pulsar acceleration and emission mechanisms.

  20. Model Predictive Control of Variable Density Multiphase Flows Governed by

    E-Print Network [OSTI]

    Hinze, Michael

    of model predictive control (MPC) consists in steering or keeping the state of a dynamical systemModel Predictive Control of Variable Density Multiphase Flows Governed by Diffuse Interface Models appearing in the model predictive control strategy. The resulting control concept is known as instantaneous

  1. Stimulation Prediction Models | Open Energy Information

    Open Energy Info (EERE)

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries Pvt LtdShawangunk,SoutheastSt.SteepStimulation Prediction Models Jump to:

  2. Predictive modelling of boiler fouling. Final report.

    SciTech Connect (OSTI)

    Chatwani, A

    1990-12-31T23:59:59.000Z

    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.

  3. Weatherizing America

    ScienceCinema (OSTI)

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

    2013-05-29T23:59:59.000Z

    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.

  4. 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...

  5. Model Predictive Control for Smooth Distributed Power Adaptation

    E-Print Network [OSTI]

    Boyer, Edmond

    1 Model Predictive Control for Smooth Distributed Power Adaptation Virgile Garcia1,2,3 , Nikolai the variations of other BS powers. The trajectories are then updated using a Model Predictive Control (MPC-based power control, no inter-cell cooperation, power trajectory, model predictive control, smooth power

  6. An Equilibrium Pricing Model for Weather Derivatives in a Multi-commodity Setting

    E-Print Network [OSTI]

    Oren, Shmuel S.

    . There- fore, energy companies face two types of risk, price risk in the spot market and 1 Manuscript weather changes will affect energy demand and sudden de- mand increases result in spot price spikes-day ice storm in February 2003 electricity prices spiked to $990/MWh causing a retail energy provider

  7. Interactive dust-radiation modeling: A step to improve weather Carlos Perez,1

    E-Print Network [OSTI]

    radiative effects could lead to a significant improvement in the radiation balance of numerical weather 2002 is selected to assess the radiative dust effects on the atmosphere at a regional level. A strong unresolved and depend on the optical properties of dust, its vertical distribution, cloud cover, and albedo

  8. Bayesian Models and Algorithms for Protein Beta-Sheet Prediction

    E-Print Network [OSTI]

    Erdogan, Hakan

    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

  9. A case model for predictive maintenance

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    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, ...

  10. Colliding cascades model for earthquake prediction

    E-Print Network [OSTI]

    2000-10-12T23:59:59.000Z

    3 International Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences, Moscow, Russia. 4 Department of Earth ...

  11. Model Predictability-Form Lorenz System to Operational Ocean and

    E-Print Network [OSTI]

    Chu, Peter C.

    Model Predictability- Form Lorenz System to Operational Ocean and Atmospheric Models Peter C Chu. Poberezhny, 2002: Power law decay in model predictability skill. Geophysical Research Letters, 29 (15), 10 Six Months Four-Times Daily Data From July 9, 1998 for Verification #12;Model Generated Velocity

  12. 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]

    Hiroi, Takahiro

    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

  13. The myth of science-based predictive modeling.

    SciTech Connect (OSTI)

    Hemez, F. M. (François M.)

    2004-01-01T23:59:59.000Z

    A key aspect of science-based predictive modeling is the assessment of prediction credibility. This publication argues that the credibility of a family of models and their predictions must combine three components: (1) the fidelity of predictions to test data; (2) the robustness of predictions to variability, uncertainty, and lack-of-knowledge; and (3) the prediction accuracy of models in cases where measurements are not available. Unfortunately, these three objectives are antagonistic. A recently published Theorem that demonstrates the irrevocable trade-offs between fidelity-to-data, robustness-to-uncertainty, and confidence in prediction is summarized. High-fidelity models cannot be made increasingly robust to uncertainty and lack-of-knowledge. Similarly, robustness-to-uncertainty can only be improved at the cost of reducing the confidence in prediction. The concept of confidence in prediction relies on a metric for total uncertainty, capable of aggregating different representations of uncertainty (probabilistic or not). The discussion is illustrated with an engineering application where a family of models is developed to predict the acceleration levels obtained when impacts of varying levels propagate through layers of crushable hyper-foam material of varying thicknesses. Convex modeling is invoked to represent a severe lack-of-knowledge about the constitutive material behavior. The analysis produces intervals of performance metrics from which the total uncertainty and confidence levels are estimated. Finally, performance, robustness and confidence are extrapolated throughout the validation domain to assess the predictive power of the family of models away from tested configurations.

  14. Model Predictive Control for Energy Efficient Buildings

    E-Print Network [OSTI]

    Ma, Yudong

    2012-01-01T23:59:59.000Z

    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

  15. Markovian Models for Electrical Load Prediction in Smart Buildings

    E-Print Network [OSTI]

    California at Santa Barbara, University of

    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

  16. NONLINEAR MODEL PREDICTIVE CONTROL VIA FEASIBILITYPERTURBED SEQUENTIAL QUADRATIC

    E-Print Network [OSTI]

    Wright, Steve

    NONLINEAR MODEL PREDICTIVE CONTROL VIA FEASIBILITY­PERTURBED SEQUENTIAL QUADRATIC PROGRAMMING­06, AUGUST 2002, COMPUTER SCIENCES DEPT, UNIV. OF WISCONSIN TEXAS­WISCONSIN MODELING AND CONTROL CONSORTIUM REPORT TWMCC­2002­02 Abstract. Model predictive control requires the solution of a sequence of continuous

  17. THE NOAA HAZARDOUS WEATHER TESTBED: COLLABORATIVE TESTING OF ENSEMBLE AND CONVECTION-ALLOWING WRF MODELS AND SUBSEQUENT

    E-Print Network [OSTI]

    Xue, Ming

    THE NOAA HAZARDOUS WEATHER TESTBED: COLLABORATIVE TESTING OF ENSEMBLE AND CONVECTION-ALLOWING WRF NOAA's Hazardous Weather Testbed (HWT) is a joint facility managed by the National Severe Storms and technologies into advances in forecasting and warning for hazardous mesoscale weather events throughout

  18. Regional-seasonal weather forecasting

    SciTech Connect (OSTI)

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

    1980-08-01T23:59:59.000Z

    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)

  19. age 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 162 On biases in the...

  20. 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...

  1. 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...

  2. 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...

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  4. Hospital Readmission in General Medicine Patients: A Prediction Model

    E-Print Network [OSTI]

    2010-01-01T23:59:59.000Z

    to the department of medicine as a screening tool forquality of care problems. Medicine. 2008;87:294–300. 3.Readmission in General Medicine Patients: A Prediction Model

  5. Climate Prediction: The Limits of Ocean Models

    E-Print Network [OSTI]

    Stone, Peter H.

    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 ...

  6. Mathematical Modeling Arnold Neumaier

    E-Print Network [OSTI]

    Neumaier, Arnold

    · Blood circulation models 4 #12;Meteorology · Weather prediction · Climate prediction (global warming (genetic variability) Chemical engineering · Chemical equilibrium · Planning of production units Chemistry recognition · Face recognition Economics · Labor data analysis Electrical engineering · Stability of electric

  7. Bootstrap Prediction for Returns and Volatilities in GARCH Models

    E-Print Network [OSTI]

    Ortega, Esther Ruiz

    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

  8. Model Predictive Control of a Kaibel Distillation Column

    E-Print Network [OSTI]

    Skogestad, Sigurd

    Model Predictive Control of a Kaibel Distillation Column Martin Kvernland Ivar Halvorsen Sigurd (e-mail: skoge@ntnu.no) Abstract: This is a simulation study on controlling a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared

  9. Nonlinear Model Predictive Control of an Omnidirectional Mobile Robot

    E-Print Network [OSTI]

    Zell, Andreas

    , University of Tübingen, Sand 1, 72076 Tübingen, Germany Abstract. This paper focuses on motion controlNonlinear Model Predictive Control of an Omnidirectional Mobile Robot Xiang LI a,1 , Kiattisin problems of an omnidirectional robot based on the Nonlinear Model Predictive Control (NMPC) method

  10. Plug-and-Play Decentralized Model Predictive Control Stefano Riverso

    E-Print Network [OSTI]

    Ferrari-Trecate, Giancarlo

    Plug-and-Play Decentralized Model Predictive Control Stefano Riverso , Marcello Farina. When this is possible, we show how to automatize the design of local controllers so that it can information with neighboring subsystems. In particular, local controllers exploit tube-based Model Predictive

  11. Chance Constrained Model Predictive Control Alexander T. Schwarm

    E-Print Network [OSTI]

    Nikolaou, Michael

    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

  12. Demonstrating the improvement of predictive maturity of a computational model

    SciTech Connect (OSTI)

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

    2010-01-01T23:59:59.000Z

    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.

  13. Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants

    E-Print Network [OSTI]

    Van den Hof, Paul

    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

  14. PV powering a weather station for severe weather

    SciTech Connect (OSTI)

    Young, W. Jr. [Florida Solar Energy Center, Cocoa, FL (United States); Schmidt, J. [Joe Schmidt, Inc., Miami, FL (United States)

    1997-12-31T23:59:59.000Z

    A natural disaster, such as Hurricane Andrew, destroys thousands of homes and businesses. The destruction from this storm left thousands of people without communications, potable water, and electrical power. This prompted the Florida Solar Energy Center to study the application of solar electric power for use in disasters. During this same period, volunteers at the Tropical Prediction Center at the National Hurricane Center (NHC), Miami, Florida and the Miami Office of the National Weather Service (NWS) were working to increase the quantity and quality of observations received from home weather stations. Forecasters at NHC have found surface reports from home weather stations a valuable tool in determining the size, strength and course of hurricanes. Home weather stations appear able to record the required information with an adequate level of accuracy. Amateur radio, utilizing the Automatic Packet Report System, (APRS) can be used to transmit this data to weather service offices in virtually real time. Many weather data collecting stations are at remote sites which are not readily serviced by dependable commercial power. Photovoltaic (solar electric) modules generate electricity and when connected to a battery can operate as a stand alone power system. The integration of these components provides an inexpensive standalone system. The system is easy to install, operates automatically and has good communication capabilities. This paper discusses the design criteria, operation, construction and deployment of a prototype solar powered weather station.

  15. Program evaluation: Weatherization Residential Assistance Partnership (WRAP) Program

    SciTech Connect (OSTI)

    Jacobson, Bonnie B.; Lundien, Barbara; Kaufman, Jeffrey; Kreczko, Adam; Ferrey, Steven; Morgan, Stephen

    1991-12-01T23:59:59.000Z

    The Weatherization Residential Assistance Partnership,'' or WRAP program, is a fuel-blind conservation program designed to assist Northeast Utilities' low-income customers to use energy safely and efficiently. Innovative with respect to its collaborative approach and its focus on utilizing and strengthening the existing low-income weatherization service delivery network, the WRAP program offers an interesting model to other utilities which traditionally have relied on for-profit energy service contractors and highly centralized program implementation structures. This report presents appendices with surveys, participant list, and computers program to examine and predict potential energy savings.

  16. Weather Forecast Data an Important Input into Building Management Systems

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    it can generate as much or more energy that it needs ? Building activities need N kWhrs per day (solar panels, heating, etc) ? Harvested from solar panels & passive solar. Amount depends on weather ? NWP models forecast DSWRF @ surface (MJ/m2...://collaboration.cmc.ec.gc.ca/cmc/cmoi/SolarScribe/SolarScribe/ CMC NWP datasets for Day 2 Forecasts ? Regional Deterministic Prediction System (RDPS) ? RDPS raw model data ? 10 km resolution, North America, 000-054 forecasts ? Data at: http...

  17. A two-timescale approach to nonlinear Model Predictive Control

    SciTech Connect (OSTI)

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

    1994-10-01T23:59:59.000Z

    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.

  18. Estimation and prediction in spatial models with block composite likelihoods

    E-Print Network [OSTI]

    Reich, Brian J.

    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

  19. 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

  20. Model Predictive Control based Real Time Power System Protection Schemes

    E-Print Network [OSTI]

    Kumar, Ratnesh

    1 Model Predictive Control based Real Time Power System Protection Schemes Licheng Jin, Member by controlling the production, absorption as well as flow of reactive power at various locations in the system predictive control, trajectory sensitivity, voltage stabilization, switching control, power system I

  1. 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

  2. Predictive capacity planning modeling with tactical and strategic applications

    E-Print Network [OSTI]

    Zeppieri, Michael A. (Michael Anthony), 1975-

    2004-01-01T23:59:59.000Z

    The focus of my internship was the development of a predictive capacity planning model to characterize the storage requirements and space utilization for Amazon's Campbellsville (SDF) Fulfillment Center (FC). Amazon currently ...

  3. On the predictive capability and stability of rubber material models

    E-Print Network [OSTI]

    Zheng, Haining

    2008-01-01T23:59:59.000Z

    Due to the high non-linearity and incompressibility constraint of rubber materials, the predictive capability and stability of rubber material models require specific attention for practical engineering analysis. In this ...

  4. Productivity prediction model based on Bayesian analysis and productivity console

    E-Print Network [OSTI]

    Yun, Seok Jun

    2005-08-29T23:59:59.000Z

    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...

  5. In silico modeling to predict drug-induced phospholipidosis

    SciTech Connect (OSTI)

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

    2013-06-01T23:59:59.000Z

    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 structure–activity 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 80–81% 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.

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

    E-Print Network [OSTI]

    Schiavon, Stefano; Lee, Kwang Ho

    2012-01-01T23:59:59.000Z

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

  7. Settlement Prediction, Gas Modeling and Slope Stability Analysis

    E-Print Network [OSTI]

    Politècnica de Catalunya, Universitat

    Settlement Prediction, Gas Modeling and Slope Stability Analysis in Coll Cardús Landfill Li Yu using mechanical models Simulation of gas generation, transport and extraction in MSW landfill 1 models Simulation of gas generation, transport and extraction in MSW landfill 1) Analytical solution

  8. Conformal Higgs model: predicted dark energy density

    E-Print Network [OSTI]

    R. K. Nesbet

    2014-11-03T23:59:59.000Z

    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.

  9. Model Predictive Control for Energy Efficient Buildings

    E-Print Network [OSTI]

    Ma, Yudong

    2012-01-01T23:59:59.000Z

    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

  10. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Sripada, Yaji

    for generating textual summaries. Our algorithm has been implemented in a weather forecast generation system. 1 presentation, aid human understanding of the underlying data sets. SUMTIME is a research project aiming turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP

  11. 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.

  12. Cathy Zoi on Weatherization

    ScienceCinema (OSTI)

    Zoi, Cath

    2013-05-29T23:59:59.000Z

    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.

  13. Cathy Zoi on Weatherization

    Broader source: Energy.gov [DOE]

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

  14. Spatiotemporal discrimination model predicts temporal masking functions

    E-Print Network [OSTI]

    CA 94035 a b Institute for Optical Research, Stockholm, Sweden W ABSTRACT e present a simplified dual, and masking based on local spatio­temporal contrast energy. The contras ensitivity filter parameters for the lack of space­time l s separability in contrast detection, the model has separate sustained

  15. Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms

    SciTech Connect (OSTI)

    Hou, Zhangshuan; Makarov, Yuri V.; Samaan, Nader A.; Etingov, Pavel V.

    2013-03-19T23:59:59.000Z

    Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (‘stochastic’) model with the weather forecast model (‘deterministic’) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

  16. Predictive modeling of pedestal structure in KSTAR using EPED model

    SciTech Connect (OSTI)

    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

    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.

  17. ReseaRch at the University of Maryland Climate Modeling and Prediction

    E-Print Network [OSTI]

    Hill, Wendell T.

    for farmers and agricultural policy makers Antonio Busalacchi studies tropical ocean circulation to refine, and drought. Eugenia Kalnay uses chaos theory to improve weather forecasting. She also documents land to predict the complex atmospheric effects of polar ice loss. Improving Rainfall Forecasts for Farmers Rapid

  18. Exploiting weather forecast data for cloud detection 

    E-Print Network [OSTI]

    Mackie, Shona

    2009-01-01T23:59:59.000Z

    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 Earth’s surface temperature. Most ...

  19. Predicting Vehicle Crashworthiness: Validation of Computer Models for

    E-Print Network [OSTI]

    Berger, Jim

    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

  20. Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD

    E-Print Network [OSTI]

    Plale, Beth

    "mesoscale" weather events. In this paper we discuss an architectural framework that is forming our thinking "mesoscale" weather events. This is accomplished by middleware that facilitates adaptive uti- lization. The meteorology goal of the project is improved prediction of mesoscale weather phenomena; that is, regional scale

  1. accelerated weathering tests: Topics by E-print Network

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

    managed by the National Severe Storms Laboratory (NSSL), the Storm Prediction Center (SPC), and the NWS Oklahoma CityNorman Weather Forecast Xue, Ming 30 Testing General...

  2. Lepton Flavor Violation in Predictive SUSY-GUT Models

    SciTech Connect (OSTI)

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

    2008-02-01T23:59:59.000Z

    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.

  3. CROPS AND SOILS RESEARCH PAPER Improved weather-based late blight risk management

    E-Print Network [OSTI]

    Douches, David S.

    CROPS AND SOILS RESEARCH PAPER Improved weather-based late blight risk management: comparing models infestans) risk at 26 locations in the Great Lakes region. Accuracies of predictions made using an early number of early warning systems for crop disease risk that integrate with crop- specific decision support

  4. Model to predict the mechanical behaviour of oriented rigid PVC

    E-Print Network [OSTI]

    Miroshnychenko, Dmitri

    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

  5. Penetration rate prediction for percussive drilling via dry friction model

    E-Print Network [OSTI]

    Krivtsov, Anton M.

    Penetration rate prediction for percussive drilling via dry friction model Anton M. Krivtsov a of percussive drilling assuming a dry friction mechanism to explain the experimentally observed drop in pene as a frictional pair, and this can generate the pattern of the impact forces close to reality. Despite quite

  6. Reference wind farm selection for regional wind power prediction models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    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

  7. Model Predictive Control of a Wind Lars Christian Henriksen

    E-Print Network [OSTI]

    wind turbines is on the sea as their is a more stable wind. These water based wind farms are confined locations to become potential wind farms. This thesis investigates control of both wind turbines mountedModel Predictive Control of a Wind Turbine Lars Christian Henriksen Kongens Lyngby 2007 IMM

  8. Fast Nonconvex Model Predictive Control for Commercial Refrigeration

    E-Print Network [OSTI]

    Fast Nonconvex Model Predictive Control for Commercial Refrigeration Tobias Gybel Hovgard , Lars F multi-zone refrigeration system, consisting of several cooling units that share a common compressor. This corresponds roughly to 2% of the entire electricity consumption in the country. Refrigerated goods constitute

  9. Application of Sampling Based Model Predictive Control to an Autonomous

    E-Print Network [OSTI]

    Collins, Emmanuel

    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

  10. Model Predictive Control For Wind Excited Buildings: A Benchmark Problem

    E-Print Network [OSTI]

    Kareem, Ahsan

    control force; W is the wind excitation vector of dimension 24; and are control output vec- tor , , , , , , , and were given by Yang et al (1999) and have appropriate dimensions. The wind force data acting1 Model Predictive Control For Wind Excited Buildings: A Benchmark Problem Gang Mei, Student M

  11. A distributed accelerated gradient algorithm for distributed model predictive

    E-Print Network [OSTI]

    Como, Giacomo

    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

  12. Vehicle Trajectory Prediction based on Motion Model and Maneuver Recognition

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    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

  13. Predicting solar cycle 24 with a solar dynamo model

    E-Print Network [OSTI]

    Arnab Rai Choudhuri; Piyali Chatterjee; Jie Jiang

    2007-01-18T23:59:59.000Z

    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.

  14. Implementation and assessment of turbine wake models in the Weather Research and Forecasting model for both mesoscale and large-eddy simulation

    SciTech Connect (OSTI)

    Singer, M; Mirocha, J; Lundquist, J; Cleve, J

    2010-03-03T23:59:59.000Z

    Flow dynamics in large wind projects are influenced by the turbines located within. The turbine wakes, regions characterized by lower wind speeds and higher levels of turbulence than the surrounding free stream flow, can extend several rotor diameters downstream, and may meander and widen with increasing distance from the turbine. Turbine wakes can also reduce the power generated by downstream turbines and accelerate fatigue and damage to turbine components. An improved understanding of wake formation and transport within wind parks is essential for maximizing power output and increasing turbine lifespan. Moreover, the influence of wakes from large wind projects on neighboring wind farms, agricultural activities, and local climate are all areas of concern that can likewise be addressed by wake modeling. This work describes the formulation and application of an actuator disk model for studying flow dynamics of both individual turbines and arrays of turbines within wind projects. The actuator disk model is implemented in the Weather Research and Forecasting (WRF) model, which is an open-source atmospheric simulation code applicable to a wide range of scales, from mesoscale to large-eddy simulation. Preliminary results demonstrate the applicability of the actuator disk model within WRF to a moderately high-resolution large-eddy simulation study of a small array of turbines.

  15. A minimal and predictive $T_7$ lepton flavor 331 model

    E-Print Network [OSTI]

    Hernández, A E Cárcamo

    2015-01-01T23:59:59.000Z

    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.

  16. Model Predictability Depends on Model Fidelity: Challenges in...

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

    and climate, and projections of climate change, show that current climate and Earth-system models continue to have stubborn irreducible errors. It is unlikely that the...

  17. Prediction of Leptonic CP Phase in $A_4$ symmetric model

    E-Print Network [OSTI]

    Sin Kyu Kang; Morimitsu Tanimoto

    2015-01-29T23:59:59.000Z

    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.

  18. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary and interpretation of information from National Weather Service watches and warnings by10 decision makers such an outlier to the regional severe weather climatology. An analysis of the synoptic and13 mesoscale

  19. Winter Weather Introduction

    E-Print Network [OSTI]

    Taylor, Jerry

    Winter Weather Management #12;Introduction · Campus Facilities Staff · Other Campus Organizations #12;Purpose · Organize and coordinate the campus response to winter weather events to maintain campus for use by 7 AM. · Response will be modified depending upon forecast and current weather conditions. #12

  20. Stochastic Models Predict User Behavior in Social Media

    E-Print Network [OSTI]

    Hogg, Tad; Smith, Laura M

    2013-01-01T23:59:59.000Z

    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...

  1. Risk prediction models for melanoma: A systematic review

    E-Print Network [OSTI]

    Usher-Smith, Juliet A.; Emery, Jon; Kassianos, Angelos P.; Walter, Fiona M.

    2014-06-03T23:59:59.000Z

    of Cambridge, Cambridge, UK. 2 General Practice and Primary Care Academic Centre, University of Melbourne, Australia. 3 School of Primary, Aboriginal and Rural Health Care, University of Western Australia, Australia. Running title: Risk prediction models... :1000129. 35. English, DR, Armstrong, BK. Identifying people at high risk of cutaneous malignant melanoma: Results from a case-control study in Western Australia. Br. Med. J. (Clin. Res. Ed). 1988; 296: 1285–1288. 36. Amir, E, Freedman, OC, Seruga...

  2. Carbon-cycle models for better long-term predictions | EMSL

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

    Carbon-cycle models for better long-term predictions Carbon-cycle models for better long-term predictions Released: November 04, 2014 Reduced variation among models should improve...

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

    E-Print Network [OSTI]

    Clement, Prabhakar

    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

  4. Prediction of interest rate using CKLS model with stochastic parameters

    SciTech Connect (OSTI)

    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

    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.

  5. Neutrino minimal standard model predictions for neutrinoless double beta decay

    SciTech Connect (OSTI)

    Bezrukov, F. [Institute for Nuclear Research of the Russian Academy of Sciences, 60th October Anniversary prospect 7a, Moscow 117312 (Russian Federation) and Institut de Theorie des Phenomenes Physiques, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland)

    2005-10-01T23:59:59.000Z

    Prediction of the effective Majorana mass for neutrinoless double {beta} decay in a simple extension of the standard model ({nu}MSM) is given. The model adds three right-handed neutrinos with masses smaller than the electroweak scale and explains dark matter of the Universe. This leads to constraints 1.3

  6. Fuel Conditioning Facility Electrorefiner Model Predictions versus Measurements

    SciTech Connect (OSTI)

    D Vaden

    2007-10-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    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

    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.

  8. Virtual Models for Prediction of Wind Turbine Parameters

    E-Print Network [OSTI]

    Andrew Kusiak

    Abstract—In 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 Terms—Data mining, parameter selection, power prediction, virtual model, wind turbine. I.

  9. Weather-Corrected Performance Ratio

    SciTech Connect (OSTI)

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

    2013-04-01T23:59:59.000Z

    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.

  10. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    SciTech Connect (OSTI)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31T23:59:59.000Z

    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.

  11. 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]

    Zhu, Kehui

    2013-04-04T23:59:59.000Z

    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...

  12. Critical Fire Weather Patterns

    E-Print Network [OSTI]

    Clements, Craig

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

  13. Predictive modeling of reactive wetting and metal joining.

    SciTech Connect (OSTI)

    van Swol, Frank B.

    2013-09-01T23:59:59.000Z

    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.

  14. Large-Scale Errors and Mesoscale Predictability in Pacific Northwest Snowstorms DALE R. DURRAN

    E-Print Network [OSTI]

    Large-Scale Errors and Mesoscale Predictability in Pacific Northwest Snowstorms DALE R. DURRAN The development of mesoscale numerical weather prediction (NWP) models over the last two decades has made- search communities. Nevertheless, the predictability of the mesoscale features captured in such forecasts

  15. The Weatherization Training program at Pennsylvania College

    SciTech Connect (OSTI)

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

    2010-01-01T23:59:59.000Z

    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.

  16. The Weatherization Training program at Pennsylvania College

    ScienceCinema (OSTI)

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

    2013-05-29T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Dowding, Kevin J.; Rutherford, Brian Milne

    2003-07-01T23:59:59.000Z

    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

  18. 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

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

    E-Print Network [OSTI]

    Cecconi, Fabio

    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

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

    E-Print Network [OSTI]

    Haves, Phillip

    2010-01-01T23:59:59.000Z

    heat  exchangers,  the  models  calibrated  using  the  manufacturer  performance  curves  predicted  power  consumption  within 10%.  The data 

  1. Development of a fourth generation predictive capability maturity model.

    SciTech Connect (OSTI)

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

    2013-09-01T23:59:59.000Z

    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.

  2. Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong of the dynamics of the robot and propose a new Linear Model Predictive Control scheme which is an improvement are unfortunately severely limited. Model Predictive Control, also known as Receding Horizon Control, is a general

  3. Home Weatherization Visit

    ScienceCinema (OSTI)

    Chu, Steven

    2013-05-29T23:59:59.000Z

    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.

  4. Today's Space Weather Space Weather Case Studies

    E-Print Network [OSTI]

    ], and grounding is difficult Hydro-Quebec's power grid is, within 90-sec of storm onset interference was thought to be due to Russian radio jamming ! GOES weather satellites, knocked out Power outage lasted 9-hours #12;What We Focus on Regarding This Storm: Power Grids

  5. Modelling Monsoons: Understanding and Predicting Current and Future Behaviour

    SciTech Connect (OSTI)

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

    2008-09-16T23:59:59.000Z

    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.

  6. RESIDUA UPGRADING EFFICIENCY IMPROVEMENT MODELS: COKE FORMATION PREDICTABILITY MAPS

    SciTech Connect (OSTI)

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

    2002-05-01T23:59:59.000Z

    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.

  7. Optimal Control of Distributed Energy Resources using Model Predictive Control

    SciTech Connect (OSTI)

    Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.; Zhang, Wei; Lu, Shuai; Samaan, Nader A.; Butler-Purry, Karen

    2012-07-22T23:59:59.000Z

    In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.

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

    E-Print Network [OSTI]

    Schrijver, Karel

    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

  9. Adaptive model predictive process control using neural networks

    DOE Patents [OSTI]

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

    1997-01-01T23:59:59.000Z

    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.

  10. Adaptive model predictive process control using neural networks

    DOE Patents [OSTI]

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

    1997-08-19T23:59:59.000Z

    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.

  11. LIFETIME PREDICTION FOR MODEL 9975 O-RINGS IN KAMS

    SciTech Connect (OSTI)

    Hoffman, E.; Skidmore, E.

    2009-11-24T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    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

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

    E-Print Network [OSTI]

    Cao, Quang V.

    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

  14. Predictability and reduced order modeling in stochastic reaction networks.

    SciTech Connect (OSTI)

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

    2008-10-01T23:59:59.000Z

    Many systems involving chemical reactions between small numbers of molecules exhibit inherent stochastic variability. Such stochastic reaction networks are at the heart of processes such as gene transcription, cell signaling or surface catalytic reactions, which are critical to bioenergy, biomedical, and electrical storage applications. The underlying molecular reactions are commonly modeled with chemical master equations (CMEs), representing jump Markov processes, or stochastic differential equations (SDEs), rather than ordinary differential equations (ODEs). As such reaction networks are often inferred from noisy experimental data, it is not uncommon to encounter large parametric uncertainties in these systems. Further, a wide range of time scales introduces the need for reduced order representations. Despite the availability of mature tools for uncertainty/sensitivity analysis and reduced order modeling in deterministic systems, there is a lack of robust algorithms for such analyses in stochastic systems. In this talk, we present advances in algorithms for predictability and reduced order representations for stochastic reaction networks and apply them to bistable systems of biochemical interest. To study the predictability of a stochastic reaction network in the presence of both parametric uncertainty and intrinsic variability, an algorithm was developed to represent the system state with a spectral polynomial chaos (PC) expansion in the stochastic space representing parametric uncertainty and intrinsic variability. Rather than relying on a non-intrusive collocation-based Galerkin projection [1], this PC expansion is obtained using Bayesian inference, which is ideally suited to handle noisy systems through its probabilistic formulation. To accommodate state variables with multimodal distributions, an adaptive multiresolution representation is used [2]. As the PC expansion directly relates the state variables to the uncertain parameters, the formulation lends itself readily to sensitivity analysis. Reduced order modeling in the time dimension is accomplished using a Karhunen-Loeve (KL) decomposition of the stochastic process in terms of the eigenmodes of its covariance matrix. Subsequently, a Rosenblatt transformation relates the random variables in the KL decomposition to a set of independent random variables, allowing the representation of the system state with a PC expansion in those independent random variables. An adaptive clustering method is used to handle multimodal distributions efficiently, and is well suited for high-dimensional spaces. The spectral representation of the stochastic reaction networks makes these systems more amenable to analysis, enabling a detailed understanding of their functionality, and robustness under experimental data uncertainty and inherent variability.

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

    E-Print Network [OSTI]

    Schiavon, Stefano; Lee, Kwang Ho

    2013-01-01T23:59:59.000Z

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

  16. VISUALIZING MODEL-BASED PREDICTIVE CONTROLLERS StephanieGuerlain Greg JamjesonandPeter Bullemer

    E-Print Network [OSTI]

    Virginia, University of

    -based predictive controllers (MPC) are becoming very popular in petrochemical refineries, as they simultaneously control ayd optimize large sections of a petrochemical process;yqng a predictive model. However, current

  17. Weatherizing Wilkes-Barre

    ScienceCinema (OSTI)

    Calore, Joe

    2013-05-29T23:59:59.000Z

    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.

  18. 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.

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

    SciTech Connect (OSTI)

    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

    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.

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

    E-Print Network [OSTI]

    Babiker, Mustafa M.H.

    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 ...

  1. The MIT Emissions Prediction and Policy Analysis (EPPA) model : revisions, sensitivities, and comparisons of results

    E-Print Network [OSTI]

    Babiker, Mustafa H.M.; Reilly, John M.; Mayer, Monika.; Eckaus, Richard S.; Sue Wing, Ian.; Hyman, Robert C.

    The Emissions Prediction and Policy Analysis (EPPA) model is a component of the MIT Integrated Earth Systems Model (IGSM). Here, we provide an overview of the model accessible to a broad audience and present the detailed ...

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

    E-Print Network [OSTI]

    Paltsev, Sergey.

    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 ...

  3. Predicting the microbial "weather" | Argonne National Laboratory

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

    Argonne and the University of Chicago; other authors on the paper are Argonne's Peter Larsen and Dawn Field at the U.K.'s Natural Environment Research Council. The research was...

  4. 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power Administration wouldDECOMPOSITION OFSupplemental Technology TestingDiscussionRESPONSE

  5. 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilA groupTuba City, Arizona, DisposalFourthN V4100 DOE/EA-1452Di ..I WAR

  6. Model Predictive Control for the Operation of Building Cooling Systems

    E-Print Network [OSTI]

    Ma, Yudong

    2010-01-01T23:59:59.000Z

    predictive control of thermal energy storage in buildingsystems which use thermal energy storage. In particular thepredictive control of thermal energy storage in building

  7. Toward understanding predictability of climate: a linear stochastic modeling approach

    E-Print Network [OSTI]

    Wang, Faming

    2004-11-15T23:59:59.000Z

    (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...

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

    E-Print Network [OSTI]

    Pedram, Massoud

    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

  9. Model for the prediction of 3D surface topography in 5-axis milling

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Model for the prediction of 3D surface topography in 5-axis milling Sylvain Lavernhe LURPA - ENS surface topography obtained in 5-axis milling in function of the machining conditions. For this purpose to a feed rate prediction model. Thanks to the simulation model of 3D surface topography, the influence

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

    SciTech Connect (OSTI)

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

    2009-01-10T23:59:59.000Z

    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.

  11. Program evaluation: Weatherization Residential Assistance Partnership (WRAP) Program. Volume 3, Appendices D, E, F, and G: [Final Report

    SciTech Connect (OSTI)

    Not Available

    1991-12-01T23:59:59.000Z

    The ``Weatherization Residential Assistance Partnership,`` or WRAP program, is a fuel-blind conservation program designed to assist Northeast Utilities` low-income customers to use energy safely and efficiently. Innovative with respect to its collaborative approach and its focus on utilizing and strengthening the existing low-income weatherization service delivery network, the WRAP program offers an interesting model to other utilities which traditionally have relied on for-profit energy service contractors and highly centralized program implementation structures. This report presents appendices with surveys, participant list, and computers program to examine and predict potential energy savings.

  12. OPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING

    E-Print Network [OSTI]

    Virginia, University of

    OPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING Greg A success in the petrochemical industry, they have introduced new challenges for the operators and engineers

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

    SciTech Connect (OSTI)

    Bosco, N.

    2012-02-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Schiavon, Stefano; Lee, Kwang Ho

    2012-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Lee, Kwang Ho; Schiavon, Stefano

    2013-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Haves, Phillip

    2010-01-01T23:59:59.000Z

    Model Predictive Control of HVAC Systems:    Implementation and  air  conditioning  (HVAC)  account  for  27%  of  the reduction potential of HVAC systems with  active thermal 

  17. 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

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

    E-Print Network [OSTI]

    Qiu, Robert Caiming

    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

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

    E-Print Network [OSTI]

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

    2013-01-01T23:59:59.000Z

    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...

  20. Locating Pleistocene refugia: Comparing phylogeographic and ecological niche model predictions

    E-Print Network [OSTI]

    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

    , American Museum of Natural History, New York, New York, United States of America, 2 International Rice Research Institute, Los Ban˜os, 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...

  1. THE SPATIAL AGGREGATION LANGUAGE FOR MODELING AND CONTROLLING DISTRIBUTED

    E-Print Network [OSTI]

    Bailey-Kellogg, Chris

    THE SPATIAL AGGREGATION LANGUAGE FOR MODELING AND CONTROLLING DISTRIBUTED PHYSICAL SYSTEMS study novel approaches to decentralized control de- sign, in the context of thermal regulation important science and engineering applications, such as predicting weather patterns, controlling

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

    SciTech Connect (OSTI)

    Tippett, Michael K. [Columbia University

    2014-04-09T23:59:59.000Z

    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.

  3. Intelligent weather agent for aircraft severe weather avoidance

    E-Print Network [OSTI]

    Bokadia, Sangeeta

    2002-01-01T23:59:59.000Z

    Severe weather conditions pose a large threat to the safety of aircraft, since they are responsible for a large percentage of aviation related accidents. With the advent of the free flight environment, the exigency for an autonomous severe weather...

  4. A Benchmark of Computational Models of Saliency to Predict Human Fixations

    E-Print Network [OSTI]

    Judd, Tilke

    2012-01-13T23:59:59.000Z

    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 ...

  5. Predicting regeneration establishment with the prognosis model. Forest Service research paper

    SciTech Connect (OSTI)

    Ferguson, D.E.; Carlson, C.E.

    1993-08-01T23:59:59.000Z

    The conifer establishment following regeneration timber harvests is predicted by version 2 of the Regeneration Establishment Model, a submodel of the Prognosis Model. The regeneration model covers 10 species for forests in Montana, central Idaho, and northern Idaho. Most harvest and site preparation methods can be simulated so that alternative treatments can be evaluated. Also included in the model is the influence of western spruce budworm (Choristoneura occidentalis) on regeneration success. The model predicts the probability of stocking, seedling density, species composition, and seedling heights 2 to 20 years after harvest. The paper describes the study design, equation development, model formulation, and model behavior for the Regeneration Establishment Model.

  6. Distributed state estimation and model predictive control of linear interconnected system

    E-Print Network [OSTI]

    Boyer, Edmond

    requirements, modern control systems are becoming more and more complex. For these processes, different controlDistributed state estimation and model predictive control of linear interconnected system: In this paper, a distributed and networked control system architecture based on independent Model Predictive

  7. A New Empirical Model for Predicting Single-Sided, Wind-Driven Natural Ventilation in Buildings

    E-Print Network [OSTI]

    Chen, Qingyan "Yan"

    A New Empirical Model for Predicting Single-Sided, Wind-Driven Natural Ventilation in Buildings-sided natural ventilation is difficult due to the bi-directional flow at the opening and the complex flow around buildings. A new empirical model was developed that can predict the mean ventilation rate and fluctuating

  8. Statistical prediction of aircraft trajectory: regression methods vs point-mass model

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    the altitude of climbing aircraft. In addition to the standard linear regression model, two common non-linear, BADA, linear regression, neural networks, Loess. INTRODUCTION Predicting aircraft trajectoriesStatistical prediction of aircraft trajectory: regression methods vs point-mass model M. Ghasemi

  9. Model Predictive Tracking Control for a Head-Positioning in a Hard-Disk-Drive

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Model Predictive Tracking Control for a Head-Positioning in a Hard-Disk-Drive M. Taktak-Meziou, A generated from Model Predictive Control (MPC). The first approach consists of a classical linear MPC without/Write (R/W) head of a Hard-Disk-Drive (HDD) servo-system, which is resolved with two control algorithms

  10. Axis control using model predictive control: identification and friction effect reduction

    E-Print Network [OSTI]

    Boyer, Edmond

    Axis control using model predictive control: identification and friction effect reduction Pedro this numerical model is used to synthetize a predictive GPC controller reducing the impact of the friction Rodriguez-Ayerbe, Didier Dumur, Sylvain Lavernhe** * SUPELEC- E3S, Automatic Control, 3 rue Joliot Curie

  11. Plug-and-play decentralized model predictive control for linear systems

    E-Print Network [OSTI]

    Ferrari-Trecate, Giancarlo

    1 Plug-and-play decentralized model predictive control for linear systems Stefano Riverso, Graduate to automatize the design of local controllers so that it can be carried out in parallel by smart actuators. In particular, local controllers exploit tube-based Model Predictive Control (MPC) in order to guarantee

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

    E-Print Network [OSTI]

    Todorov, Emanuel

    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

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

    E-Print Network [OSTI]

    Langmead, Christopher James

    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

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

    E-Print Network [OSTI]

    Hazas, Mike

    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

  15. A Predictive Model for Slip Resistance Using Artificial Neural Networks Janet M. Twomey, IIE Student Member

    E-Print Network [OSTI]

    Smith, Alice E.

    A Predictive Model for Slip Resistance Using Artificial Neural Networks Janet M. Twomey, IIE Artificial Neural Networks Why This Paper is Important Slips and falls are a serious ergonomic problem a slip resistance testing device were used to develop an artificial neural network model which predicts

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

    E-Print Network [OSTI]

    Emmerich, Michael

    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

  17. Fault-tolerant model predictive control of a wind turbine benchmark

    E-Print Network [OSTI]

    Cambridge, University of

    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

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

    E-Print Network [OSTI]

    Oxford, University of

    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

  19. Prediction Models for a Smart Home based Health Care System Vikramaditya R. Jakkula1

    E-Print Network [OSTI]

    Cook, Diane J.

    Prediction Models for a Smart Home based Health Care System Vikramaditya R. Jakkula1 , Diane J health care. Smart health care systems at home can be used to provide such solutions. A technology a prediction model in an intelligent smart home system can be used for identifying health trends over time

  20. The US National Multi-Model Ensemble ISI Prediction System Ben Kirtman (University of Miami)

    E-Print Network [OSTI]

    Miami, University of

    The US National Multi-Model Ensemble ISI Prediction System Ben Kirtman (University of Miami) The newly emerging US National Multi-Model Ensemble (NMME) sub-seasonal to interannual (ISI) prediction includes experimental real-time ISI forecasting that leverages existing CTB partner activities. The NMME

  1. 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...

  2. 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.

  3. Weatherization Innovation Pilot Program (WIPP): Technical Assistance Summary

    SciTech Connect (OSTI)

    Hollander, A.

    2014-09-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2012-11-05T23:59:59.000Z

    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.

  5. QUANTIFICATION OF WEATHERING Robert Hack

    E-Print Network [OSTI]

    Hack, Robert

    sandstone, limestone and dolomites, slates, shales, and in- Weathering and especially future weathering 40 60 80 H slate medium H slate v.thin H slate tick lam. Tg21 thick Tg21 medium Tg21 thin Tg21 v

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

    E-Print Network [OSTI]

    Martin, A; Venkatesan, Dr V Prasanna

    2011-01-01T23:59:59.000Z

    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.

  7. Overview of Neutrino Mixing Models and Their Mixing Angle Predictions

    SciTech Connect (OSTI)

    Albright, Carl H.

    2009-11-01T23:59:59.000Z

    An overview of neutrino-mixing models is presented with emphasis on the types of horizontal flavor and vertical family symmetries that have been invoked. Distributions for the mixing angles of many models are displayed. Ways to differentiate among the models and to narrow the list of viable models are discussed.

  8. Numerical and analytical modeling of sanding onset prediction

    E-Print Network [OSTI]

    Yi, Xianjie

    2004-09-30T23:59:59.000Z

    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...

  9. Predictive Linear Regression Model for Microinverter Internal Temperature

    E-Print Network [OSTI]

    Rollins, Andrew M.

    , 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

  10. MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE

    E-Print Network [OSTI]

    Neumaier, Arnold

    ­called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary at solutions to the protein folding problem. Key words. protein folding, molecular mechanics, transition states. This so­called protein folding problem is one of the most challenging problems in current bio­ chemistry

  11. MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE

    E-Print Network [OSTI]

    Neumaier, Arnold

    -called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary at solutions to the protein folding problem. Key words. protein folding, molecular mechanics, transition states. This so-called protein folding problem is one of the most challenging problems in current bio- chemistry

  12. Road Weather and Transportation Systems

    E-Print Network [OSTI]

    Bertini, Robert L.

    Road Weather and Transportation Systems Rhonda Young, P.E., PhD Associate Professor Dept. of Civil & Arch. Engineering Portland State University April 18, 2014 #12;Engineering Perspective of Road Weather · How does weather impact transportation systems? · As engineers, is there anything we can do

  13. 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

  14. Predictive Simulation of Bidirectional Glenn Shunt Using a Hybrid Blood Vessel Model

    E-Print Network [OSTI]

    Leow, Wee Kheng

    Predictive Simulation of Bidirectional Glenn Shunt Using a Hybrid Blood Vessel Model Hao Li1 to model the deformation of blood vessels. The hybrid blood vessel model consists of a reference Cosserat rod and a surface mesh. The reference Cosserat rod models the blood vessel's global bending

  15. 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...

  16. 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...

  17. Human walking model predicts joint mechanics, electromyography and mechanical economy

    E-Print Network [OSTI]

    Endo, Ken

    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, ...

  18. On the Predictive Uncertainty of a Distributed Hydrologic Model

    E-Print Network [OSTI]

    Cho, Huidae

    2009-05-15T23:59:59.000Z

    .2.2. Sampling strategy for high diversity . . . . . . . . . . 34 3.2.3. Isolated speciation . . . . . . . . . . . . . . . . . . . 36 3.2.4. Fitness assimilation . . . . . . . . . . . . . . . . . . . 39 3.2.5. Nesting criteria for global and local optima... unique optimal solution Beven (2006a). There may exist even mathematically inferior solutions, often referred to as local optima, that provide more realistic predictions. However, it is not straight- forward to find local optima using global optimization...

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

    SciTech Connect (OSTI)

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

    2013-12-18T23:59:59.000Z

    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.

  20. Predicting hurricane regional landfall rates: comparing local and basin-wide track model approaches

    E-Print Network [OSTI]

    Hall, T; Hall, Tim; Jewson, Stephen

    2006-01-01T23:59:59.000Z

    We compare two methods for making predictions of the climatological distribution of the number of hurricanes making landfall along short sections of the North American coastline. The first method uses local data, and the second method uses a basin-wide track model. Using cross-validation we show that the basin-wide track model gives better predictions for almost all parts of the coastline. This is the first time such a comparison has been made, and is the first rigourous justification for the use of basin-wide track models for predicting hurricane landfall rates and hurricane risk.

  1. Model Predictive Control for the Operation of Building Cooling Systems

    E-Print Network [OSTI]

    Ma, Yudong

    2010-01-01T23:59:59.000Z

    of the cooling towers while consuming less energy. Duringtowers, the thermal storage tank and the electricity energytowers, the thermal storage tank, the campus model and the electricity energy

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

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

    large domain size and multiple realizations. * Model calibration and verification (End of project) - We will collect data from literature, extrapolate existing data and conduct...

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model of solid polycyclic aromatic hydrocarbons in water. For this purpose, we first validate our methodology for fluid phase equilibria predictions of aromatic hydrocarbons and gas (CO2, C2H6) mixtures. Finally, we

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

    E-Print Network [OSTI]

    Boyer, Edmond

    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

  5. Ventilation performance prediction for buildings: Model Assessment Qingyan Chena,b,*

    E-Print Network [OSTI]

    Chen, Qingyan "Yan"

    1 Ventilation performance prediction for buildings: Model Assessment Qingyan Chena,b,* , Kisup Leeb ventilation systems for buildings requires a suitable tool to assess the system performance-scale experimental, multizone network, zonal, and CFD) for predicting ventilation performance in buildings, which can

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

    E-Print Network [OSTI]

    Cerpa, Alberto E.

    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

  7. Non-asymptotic Adaptive Prediction in Functional Linear Models Elodie Brunel, Andre Mas, and Angelina Roche

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Non-asymptotic Adaptive Prediction in Functional Linear Models ´Elodie Brunel, Andr´e Mas, and Angelina Roche I3M, Universit´e Montpellier II Abstract Functional linear regression has recently attracted. Functional linear regression, functional principal components analysis, mean squared prediction error

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

    E-Print Network [OSTI]

    Hornof, Anthony

    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

  9. `TVLSI-00029-2003.R1 An Analytical Model for Predicting the Remaining Battery

    E-Print Network [OSTI]

    Pedram, Massoud

    . Reference [7] studied the battery discharge efficiency under different loading conditions and approximated`TVLSI-00029-2003.R1 1 An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries Peng Rong, Student Member, IEEE and Massoud Pedram, Fellow, IEEE Abstract -- Predicting

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

    E-Print Network [OSTI]

    Zhao, Xuepu

    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

  11. Model Formulation and Predictions for a Pyrotechnically Actuated Pin Puller*

    E-Print Network [OSTI]

    ) actuated pin puller. The conservation principles are written as a set of ordinary differential equations-stirred reactor is simulated. These assumptions generally restrict the validity of the model to regimes near a formulation of the model in terms of the mass, momentum, and energy principles supplemented by appropriate

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

    SciTech Connect (OSTI)

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

    2013-01-01T23:59:59.000Z

    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 DOE’s 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.

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

    E-Print Network [OSTI]

    Webster, Peter J.

    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

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

    E-Print Network [OSTI]

    Ruiz, Jose Pedro, 1980-

    2004-01-01T23:59:59.000Z

    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 ...

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

    E-Print Network [OSTI]

    Rodriguez-Escobar, Olga Lydia

    2009-05-15T23:59:59.000Z

    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...

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

    E-Print Network [OSTI]

    McDonald, Jennifer Nicole

    2012-07-16T23:59:59.000Z

    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...

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

    E-Print Network [OSTI]

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

    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...

  18. Image Segmentation for the Application of the Neugebauer Colour Prediction Model on Inkjet Printed

    E-Print Network [OSTI]

    Figueiredo, Mário A. T.

    are reported in Section 5. The paper is concluded in Section 6. 2 The Neugebauer Color Prediction Model overlaps (CM, CY, MY, CK, MK, YK); all ternary overlaps (CMY, CMK, CYK, MYK), the single full overlap (CMYK

  19. PREDICTIVE THERMAL MODEL FOR INDIRECT TEMPERATURE MEASUREMENT INSIDE ATOMIC CELL OF NUCLEAR MAGNETIC RESONANCE GYROSCOPE

    E-Print Network [OSTI]

    Tang, William C

    , atomic MEMS, compact thermal model. INTRODUCTION We present a two-step process for predicting and the VCSEL, active heating and cooling was included in the presented prototype through an external heater

  20. Application of the Gebhart-Block Model for Predicting Vertical Temperature Distribution in a Large Space Building with Natural Ventilation

    E-Print Network [OSTI]

    Huang, C.; Song, Y.; Luo, X.

    2006-01-01T23:59:59.000Z

    Based on the Block model for predicting vertical temperature distribution in a large space, this paper describes an improved Gebhart-Block model for predicting vertical temperature distribution of a large space with natural ventilation...

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

    E-Print Network [OSTI]

    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

    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.

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

    E-Print Network [OSTI]

    Daraio, Chiara

    ·Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms. ·Wake measurements in the ETHZ facility compare well with measurements at the Horns Rev offshore wind farm models take account of the effects of wakes on downstream wind turbines. ·Wake models used in the wind

  3. Detection and Prediction of Errors in EPCs of the SAP Reference Model

    E-Print Network [OSTI]

    van der Aalst, Wil

    as a blueprint for roll-out projects of SAP's ERP system. It reflects Version18 4.6 of SAP R/3 which was marketedDetection and Prediction of Errors in EPCs of the SAP Reference Model J. Mendling a, H.M.W. Verbeek provide empirical evidence for these questions based on the SAP reference model. This model collection

  4. Power law decay in model predictability skill Peter C. Chu,1

    E-Print Network [OSTI]

    Chu, Peter C.

    Power law decay in model predictability skill Peter C. Chu,1 Leonid M. Ivanov,1,2 Lakshmi H. Kantha a Gulf of Mexico nowcast/forecast model. Power law scaling is found in the mean square error of displacement between drifting buoy and model trajectories (both at 50 m depth). The probability density

  5. Artificial Neural Networks and Hidden Markov Models for Predicting the Protein Structures: The Secondary Structure

    E-Print Network [OSTI]

    1 Artificial Neural Networks and Hidden Markov Models for Predicting the Protein Structures advice on the development of this project #12;2 Artificial Neural Networks and Hidden Markov Models learning methods: artificial neural networks (ANN) and hidden Markov models (HMM) (Rost 2002; Karplus et al

  6. 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

  7. An Advanced Induction Machine Model for Predicting Inverter-Machine Interaction

    E-Print Network [OSTI]

    Chapman, Patrick

    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

  8. Evaluation of SWAT model - subdaily runoff prediction in Texas watersheds

    E-Print Network [OSTI]

    Palanisamy, Bakkiyalakshmi

    2007-09-17T23:59:59.000Z

    Spatial variability of rainfall is a significant factor in hydrologic and water quality modeling. In recent years, characterizing and analyzing the effect of spatial variability of rainfall in hydrologic applications has become vital with the advent...

  9. DECENTRALIZED ROBUST NONLINEAR MODEL PREDICTIVE CONTROLLER FOR UNMANNED AERIAL SYSTEMS

    E-Print Network [OSTI]

    Garcia, Gonzalo Andres

    2013-05-31T23:59:59.000Z

    that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2 A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3 An artificial neural network...

  10. Predictive models for power dissipation in optical transceivers

    E-Print Network [OSTI]

    Butler, Katherine, 1981-

    2004-01-01T23:59:59.000Z

    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 ...

  11. How predictable : modeling rates of change in individuals and populations

    E-Print Network [OSTI]

    Krumme, Katherine

    2013-01-01T23:59:59.000Z

    This thesis develops methodologies to measure rates of change in individual human behavior, and to capture statistical regularities in change at the population level, in three pieces: i) a model of individual rate of change ...

  12. Robust Constrained Model Predictive Control using Linear Matrix Inequalities \\Lambda

    E-Print Network [OSTI]

    Balakrishnan, Venkataramanan "Ragu"

    dynamical systems, such as those encountered in chemical process control in the petrochemical, pulp process models as well as many performance criteria of significance to the process industries can

  13. Robust Constrained Model Predictive Control using Linear Matrix Inequalities

    E-Print Network [OSTI]

    Balakrishnan, Venkataramanan "Ragu"

    , such as those encountered in chemical process control in the petrochemical, pulp and paper industries, several process models as well as many performance criteria of significance to the process industries can

  14. Dispersion modeling for prediction of emission factors for cattle feedyards

    E-Print Network [OSTI]

    Parnell, Sarah Elizabeth

    1994-01-01T23:59:59.000Z

    of state air pollution regulatory agencies will require accurate EPA AP-42 emission factors. A protocol was developed so that accurate emission factors can be determined using both source sampling data and dispersion modeling. In this study, an emission...

  15. Flow Control of Real Time Multimedia Applications Using Model Predictive Control with a Feed Forward Term

    E-Print Network [OSTI]

    Duong, Thien Chi

    2011-02-22T23:59:59.000Z

    FLOW CONTROL OF REAL TIME MULTIMEDIA APPLICATIONS USING MODEL PREDICTIVE CONTROL WITH A FEED FORWARD TERM A Thesis by THIEN CHI DUONG 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 2010 Major Subject: Mechanical Engineering Flow Control of Real Time Multimedia Applications Using Model Predictive Control with Feed Forward Term...

  16. Evaluation of a mathematical model in predicting intake of growing and finishing cattle

    E-Print Network [OSTI]

    Bourg, Brandi Marie

    2009-05-15T23:59:59.000Z

    EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG 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 2007 Major Subject: Animal Science EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted...

  17. Evaluation of a mathematical model in predicting intake of growing and finishing cattle

    E-Print Network [OSTI]

    Bourg, Brandi Marie

    2008-10-10T23:59:59.000Z

    EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG 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 2007 Major Subject: Animal Science EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted...

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

    E-Print Network [OSTI]

    Opara, Ethelbert Okechukwu

    1993-01-01T23:59:59.000Z

    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...

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

    E-Print Network [OSTI]

    Garcia, Julian Perez

    1988-01-01T23:59:59.000Z

    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...

  20. A computer simulation model for the prediction of temperature distributions in radiofrequency hyperthermia treatment

    E-Print Network [OSTI]

    Rothe, Jeanne Marie

    1983-01-01T23:59:59.000Z

    A COMPUTER SIMULATION MODEL FOR THE PREDICTION OF . EMPERATURE DISTRIBUTIONS IN RADIOFREQUENCY HYPERTHERMIA TREATMENT A Thesis by JEANNE MARIE ROTHE Submitted to the Graduate College of Texas ASM University in Partial fulfillment... of the requirement for the degree of MASTER OF SCIENCE DECEMBER 1983 Major Subject: Bioengineering A COMPUTER SIMULATION MODEL FOR THE PREDICTION OF TEMPERATURE DISTRIBUTIONS IN RADIOFREQUENCY HYPERTHERMIA TREATMENT A Thesis by JEANNE MARIE ROTHE Approved...

  1. A new, efficient computational model for the prediction of fluid seal flowfields

    E-Print Network [OSTI]

    Hibbs, Robert Irwin

    1988-01-01T23:59:59.000Z

    A NEW) EFFICIENT COMPUTATIONAL MODEL FOR THE PREDICTION OF FLUID SEAL FLOWFIELDS A Thesis by ROBERT IRWIN HIBBS, JR. Submitted to the Office of Graduate Studies of Texas ASM University in partial fulfillment of the requirement for the degree... of MASTER OF SCIENCE December 1988 Major Subject: Mechanical Engineering A NEW, EFFICIENT COMPUTATIONAL MODEL FOR THE PREDICTION OF FLUID SEAL FLOWFIELDS A Thesis by ROBERT IRWIN HIBBS, JR. Approved as to style and content by: David L. Rhode...

  2. Model Refinement Needs A model developed by Peters and Marmorek (2003) will be used to generate predictions for

    E-Print Network [OSTI]

    449 Model Refinement Needs A model developed by Peters and Marmorek (2003) will be used to generate primarily an energy sink or primarily a source of food? More information is needed as to interactions predictions for comparison with observed variations in kokanee production. As with most models

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

    SciTech Connect (OSTI)

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

    2014-02-01T23:59:59.000Z

    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.

  4. 3D Rigid Body Impact Burial Prediction Model

    E-Print Network [OSTI]

    Chu, Peter C.

    -fixed coordinate (E-coordinate) · cylinder's main-axis following coordinate (M-coordinate) · hydrodynamic force-Coordiante Hydrodynamic forces (drag and lift) are easily calculated. #12;Moment of Momentum Equations #12;Interfacial;Experiment · Hydrodynamic Model Development · Behavior of Falling Cylinder in Water Column (Chaotic

  5. Prediction under uncertainty in reservoir modeling S. Subbeya,*, M. Christiea

    E-Print Network [OSTI]

    Sambridge, Malcolm

    a Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh EH14 4AS, UK b Research School to production data, is obtained. The model is then used to forecast future production profiles. Because the history match is non-unique, the forecast production profiles are therefore uncertain, although

  6. Crowdtuning: systematizing auto-tuning using predictive modeling and

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    in a public repository to initiate systematic, reproducible and collaborative R&D with a new publication model, reliability and cost. We present our novel long-term holistic and practical solution to this problem basedTuning.org for collaborative explanation, top-down complexity reduction, incremental problem decomposition and detection

  7. A NEW MODEL FOR PERFORMANCE PREDICTION OF HARD ROCK TBMS.

    E-Print Network [OSTI]

    TBMs. The model uses information on the rock properties and cutting geometry to calculate TBM rate on data collected in the field and is merely a regression between machine parameters, rock properties is introduced to provide an estimate of disc cutting forces as a function of rock properties and the cutting

  8. Bishop Paiute Weatherization Training Program

    SciTech Connect (OSTI)

    Carlos Hernandez

    2010-01-28T23:59:59.000Z

    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.

  9. Interactive software for model predictive control with simultaneous identification

    E-Print Network [OSTI]

    Echeverria Del Rio, Pablo

    2000-01-01T23:59:59.000Z

    and Internal Model Control (IMC) by Garcia and Morari (Garcia and Morari, 1982); the other one was about the stability of constrained MPC by Rawlings and Muske (Rawlings and Muske, 1993). Among the research papers and thesis that have been written about MPC... making process (Garcia, Prett and Morari, 1989). In order to obtain the maximum benefit from a process, several performance objectives should be specified and attained in the design and actual implementation of the plant. However, this condition...

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

    SciTech Connect (OSTI)

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

    1983-01-01T23:59:59.000Z

    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.

  11. Weatherization Apprenticeship Program

    SciTech Connect (OSTI)

    Watson, Eric J

    2012-12-18T23:59:59.000Z

    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.

  12. A soil moisture availability model for crop stress prediction

    E-Print Network [OSTI]

    Gay, Roger Franklin

    1983-01-01T23:59:59.000Z

    wet so11 profile [Ritch1e et al. , 1972] . . . . . . . . . . . . . . 12 Relationships between the ratio of actual evaporation (Ea) to pan evaporat1on (E an) as a function of the available soil water in Rule and Bragg soybean [Burch et al. , 1978...] F1gure Interact1ons between soil-moisture status and other components of a general crop yield model . . . . . . . . . . . . . . . 16 Figure Root densit1es for ra1nfed Ruse and Bragg soybean, 98 days after planting [Burch et al. , 1978...

  13. Gamma-ray Burst Models: General Requirements and Predictions

    E-Print Network [OSTI]

    P. Meszaros

    1995-02-21T23:59:59.000Z

    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.

  14. Development and Validation of an Advanced Stimulation Prediction Model for

    Open Energy Info (EERE)

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE Facility DatabaseMichigan: EnergyKansas:DetroitOpen Energy1987)

  15. Development of Chemical Model to Predict the Interactions between

    Open Energy Info (EERE)

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE Facility DatabaseMichigan: EnergyKansas:DetroitOpen

  16. Air Leakage of U.S. Homes: Model Prediction

    SciTech Connect (OSTI)

    Sherman, Max H.; McWilliams, Jennifer A.

    2007-01-01T23:59:59.000Z

    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.

  17. Prediction of oxy-coal flame stand-off using high-fidelity thermochemical models

    E-Print Network [OSTI]

    Prediction of oxy-coal flame stand-off using high-fidelity thermochemical models and the one Abstract An Eulerian one-dimensional turbulence (ODT) model is applied to simulate oxy-coal combustion temperature and mixing rate on oxy-coal flame is simulated and discussed where flame stand-off is used

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

    E-Print Network [OSTI]

    Istrail, Sorin

    , 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

  19. User-click Modeling for Understanding and Predicting Search-behavior

    E-Print Network [OSTI]

    Yang, Qiang

    . 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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    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

  1. Predicting Response to Political Blog Posts with Topic Models Language Technologies Institute

    E-Print Network [OSTI]

    Cohen, William W.

    - tent Dirichlet Allocation, introduced by Blei et al. (2003), in various ways to capture different char a blog site. The model is an extension of Latent Dirichlet Allocation (LDA) introduced by Blei et al for learning and/or prediction (Blei et al., 2003). Different models can be compared to explore

  2. PAVEMENT PREDICTION PERFORMANCE MODELS AND RELATION WITH TRAFFIC FATALITIES AND INJURIES

    E-Print Network [OSTI]

    Boyer, Edmond

    PAVEMENT PREDICTION PERFORMANCE MODELS AND RELATION WITH TRAFFIC FATALITIES AND INJURIES V. CEREZO.gothie@developpement-durable.gouv.fr ABSTRACT This paper presents some results of a study, which aimed at modelling pavement evolution, pavement characteristics and age. In a second part, non-linear regressions were used in view of obtaining

  3. 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

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

    E-Print Network [OSTI]

    carrying capacity. Keywords Visitation model Á Recreation management Á Water quality Á River visitation ÁA Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water Quality: Evidence from Two Rivers in Puerto Rico Luis E. Santiago � Armando Gonzalez-Caban � John Loomis

  5. A simplified approach to quantifying predictive and parametric uncertainty in artificial neural network hydrologic models

    E-Print Network [OSTI]

    Chaubey, Indrajeet

    considerable interest in developing methods for uncertainty analysis of artificial neural network (ANN) models and parametric uncertainty in artificial neural network hydrologic models, Water Resour. Res., 43, W10407, doi:10A simplified approach to quantifying predictive and parametric uncertainty in artificial neural

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

    E-Print Network [OSTI]

    Huang, Yinlun

    and petrochemical industries during the past decade. In MPC, a process dynamic model is used to predict future (FMPC) approach is introduced to design a control system for a highly nonlinear process. In this approach, a process system is described by a fuzzy convolution model that consists of a number of quasi

  7. 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.

  8. Bayesian calibration of a k -turbulence model for predictive jet-in-crossflow simulations

    E-Print Network [OSTI]

    Ray, Jaideep

    Bayesian calibration of a k - turbulence model for predictive jet-in-crossflow simulations Jaideep skill in jet-in-crossflow simulations. The method is based on the hypotheses that (1) informative features of jet-in-crossflow interactions and (2) one can construct surrogates of RANS models

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

    E-Print Network [OSTI]

    Weston, Ken

    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

  10. The 1D Iterative Model for Predicting Thermal Radiation from a Jet Fire

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    manuscript, published in "6. International Seminar on Fire and Explosion Hazards (FEH), Leeds : UnitedThe 1D Iterative Model for Predicting Thermal Radiation from a Jet Fire Leroy, G.* and Duplantier of the current jet fire models used in the accidental fire risks department are semi- empirical. They depend

  11. 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....

  12. SpaceWeather RESEARCH ARTICLE

    E-Print Network [OSTI]

    Lockwood, Mike

    ), The Solar Stormwatch CME catalogue: Results from the first space weather citizen science project, Space is properly cited. The Solar Stormwatch CME catalogue: Results from the first space weather citizen science citizen science project, the aim of which is to identify and track coronal mass ejections (CMEs) observed

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

    E-Print Network [OSTI]

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

    2014-04-14T23:59:59.000Z

    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.

  14. Evaluation of Transport and Dispersion Models: A Controlled Comparison of HPAC and NARAC Predictions

    SciTech Connect (OSTI)

    Warner, S; Heagy, J F; Platt, N; Larson, D; Sugiyama, G; Nasstrom, J S; Foster, K T; Bradley, S; Bieberbach, G

    2001-05-01T23:59:59.000Z

    During fiscal year 2000, a series of studies in support of the Defense Threat Reduction Agency (DTRA) was begun. The goal of these studies is to improve the verification, validation, and accreditation (VV&A) of hazard prediction and assessment models and capabilities. These studies are part of a larger joint VV&A collaborative effort that DTRA and the Department of Energy (DOE), via the Lawrence Livermore National Laboratory (LLNL), are conducting. This joint effort includes comparisons of the LLNL and DTRA transport and dispersion (T&D) modeling systems, NARAC and HPAC, respectively. The purpose of this work is to compare, in a systematic way, HPAC and NARAC model predictions for a set of controlled hypothetical release scenarios. Only ''model-versus-model'' comparisons are addressed in this work. Model-to-field trial comparisons for HPAC and NARAC have been addressed in a recent companion study, in support of the same joint VV&A effort.

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

    SciTech Connect (OSTI)

    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

    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.

  16. Weatherization Formula Grants - American Recovery and Reinvestment...

    Energy Savers [EERE]

    Weatherization Formula Grants - American Recovery and Reinvestment Act (ARRA) Weatherization Formula Grants - American Recovery and Reinvestment Act (ARRA) U.S. Department of...

  17. New York: Weatherizing Westbeth Reduces Energy Consumption |...

    Energy Savers [EERE]

    New York: Weatherizing Westbeth Reduces Energy Consumption New York: Weatherizing Westbeth Reduces Energy Consumption August 21, 2013 - 12:00am Addthis The New York State Homes and...

  18. 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...

  19. The application of a chemical equilibrium model, SOLTEQ, to predict the chemical speciations in stabilized/solidified waste forms 

    E-Print Network [OSTI]

    Park, Joo-Yang

    1994-01-01T23:59:59.000Z

    . . . . . . . . . . . . . . . . . ?. .. , . . . . . . . . . . . . 55 10 Prediction of porewater pH . 11 Effects of pH on predictions of various species . . . 12 Prediction of Al concentration 13 Prediction of Fe concentration 14 Prediction of SO4 concentration . 15 Prediction of Ca concentration . 16...A hydration (16). However, Reardon (9) indicated that equilibrium models using current K, ?values of these minerals tend to predict the thermodynamic stability of ettringite over monosulfate. Because the hydration of C4AF is analogous to that of CsA, C4AF...

  20. Observations, dynamics and predictability of the mesoscale convective vortex event of 10-13 June 2003

    E-Print Network [OSTI]

    Hawblitzel, Daniel Patrick

    2006-08-16T23:59:59.000Z

    with varying resolutions. It is determined that the ability of a forecast model to accurately predict this MCV event is directly related to its ability to simulate convection. It is also shown that the convective-resolving Weather Research and Forecast (WRF...

  1. WEATHER MODIFICATION BY CARBON DUST ABSORPTION OF SOLAR ENERGY

    E-Print Network [OSTI]

    Gray, William

    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

  2. Survey and Analysis of Weather Data for Building Energy Simulations

    SciTech Connect (OSTI)

    Bhandari, Mahabir S [ORNL; Shrestha, Som S [ORNL; New, Joshua Ryan [ORNL

    2012-01-01T23:59:59.000Z

    In recent years, calibrated energy modeling of residential and commercial buildings has gained importance in a retrofit-dominated market. Accurate weather data plays an important role in this calibration process and projected energy savings. It would be ideal to measure weather data at the building location to capture relevant microclimate variation but this is generally considered cost-prohibitive. There are data sources publicly available with high temporal sampling rates but at relatively poor geospatial sampling locations. To overcome this limitation, there are a growing number of service providers that claim to provide real time and historical weather data for 20-35 km2 grid across the globe. Unfortunately, there is limited documentation from 3rd-party sources attesting to the accuracy of this data. This paper compares provided weather characteristics with data collected from a weather station inaccessible to the service providers. Monthly average dry bulb temperature; relative humidity; direct, diffuse and horizontal solar radiation; and wind speed are statistically compared. Moreover, we ascertain the relative contributions of each weather variable and its impact on building loads. Annual simulations are calculated for three different building types, including a closely monitored and automated energy efficient research building. The comparison shows that the difference for an individual variable can be as high as 90%. In addition, annual building energy consumption can vary by 7% while monthly building loads can vary by 40% as a function of the provided location s weather data.

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

    SciTech Connect (OSTI)

    Lovley, Derek R.

    2012-10-31T23:59:59.000Z

    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.

  4. WeatherMaker: Weather file conversion and evaluation

    SciTech Connect (OSTI)

    Balcomb, J.D.

    1999-07-01T23:59:59.000Z

    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.

  5. Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling

    SciTech Connect (OSTI)

    Jaroslav Solc

    2009-06-01T23:59:59.000Z

    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.

  6. Dynamics of Cell Shape and Forces on Micropatterned Substrates Predicted by a Cellular Potts Model

    E-Print Network [OSTI]

    Philipp J. Albert; Ulrich S. Schwarz

    2014-05-19T23:59:59.000Z

    Micropatterned substrates are often used to standardize cell experiments and to quantitatively study the relation between cell shape and function. Moreover, they are increasingly used in combination with traction force microscopy on soft elastic substrates. To predict the dynamics and steady states of cell shape and forces without any a priori knowledge of how the cell will spread on a given micropattern, here we extend earlier formulations of the two-dimensional cellular Potts model. The third dimension is treated as an area reservoir for spreading. To account for local contour reinforcement by peripheral bundles, we augment the cellular Potts model by elements of the tension-elasticity model. We first parameterize our model and show that it accounts for momentum conservation. We then demonstrate that it is in good agreement with experimental data for shape, spreading dynamics, and traction force patterns of cells on micropatterned substrates. We finally predict shapes and forces for micropatterns that have not yet been experimentally studied.

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

    E-Print Network [OSTI]

    Chen, Long-Qing

    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

  8. Molecular Constraints on Synaptic Tagging and Maintenance of Long-Term Potentiation: A Predictive Model

    E-Print Network [OSTI]

    Paul Smolen; Douglas A. Baxter; John H. Byrne

    2012-08-03T23:59:59.000Z

    Protein synthesis-dependent, late long-term potentiation (LTP) and depression (LTD) at glutamatergic hippocampal synapses are well characterized examples of long-term synaptic plasticity. Persistent increased activity of the enzyme protein kinase M (PKM) is thought essential for maintaining LTP. Additional spatial and temporal features that govern LTP and LTD induction are embodied in the synaptic tagging and capture (STC) and cross capture hypotheses. Only synapses that have been "tagged" by an stimulus sufficient for LTP and learning can "capture" PKM. A model was developed to simulate the dynamics of key molecules required for LTP and LTD. The model concisely represents relationships between tagging, capture, LTD, and LTP maintenance. The model successfully simulated LTP maintained by persistent synaptic PKM, STC, LTD, and cross capture, and makes testable predictions concerning the dynamics of PKM. The maintenance of LTP, and consequently of at least some forms of long-term memory, is predicted to require continual positive feedback in which PKM enhances its own synthesis only at potentiated synapses. This feedback underlies bistability in the activity of PKM. Second, cross capture requires the induction of LTD to induce dendritic PKM synthesis, although this may require tagging of a nearby synapse for LTP. The model also simulates the effects of PKM inhibition, and makes additional predictions for the dynamics of CaM kinases. Experiments testing the above predictions would significantly advance the understanding of memory maintenance.

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

    E-Print Network [OSTI]

    Stryk, Oskar von

    . 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

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

    E-Print Network [OSTI]

    Julius, Anak Agung

    -- 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

  11. Three-Dimensional Hydrodynamic Model for Prediction of Falling Cylinder Through Water Column

    E-Print Network [OSTI]

    Chu, Peter C.

    1 1 Three-Dimensional Hydrodynamic Model for Prediction of Falling Cylinder Through Water Column-coordinate), cylinder's main-axis following coordinate (M-coordinate), and hydrodynamic force following coordinate (F-coordinate system. The hydrodynamic forces (such as the drag and lift forces) and their moments are easily computed

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    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

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

    E-Print Network [OSTI]

    Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving arising in the Airborne Wind Energy paradigm, an essential one is the control of the tethered airfoil], [3], the Airborne Wind Energy (AWE) paradigm shift proposes to get rid of the structural elements

  14. 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

  15. Predicting Protein Folds with Structural Repeats Using a Chain Graph Model

    E-Print Network [OSTI]

    Xing, Eric P.

    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

  16. Structural health monitoring with piezoelectric wafer active sensors predictive modeling and simulation

    E-Print Network [OSTI]

    Giurgiutiu, Victor

    Structural health monitoring with piezoelectric wafer active sensors ­ predictive modeling of the state of the art in structural health monitoring with piezoelectric wafer active sensors and follows with conclusions and suggestions for further work Key Words: structural health monitoring, SHM, nondestructive

  17. Towards a Generalized Regression Model for On-body Energy Prediction from Treadmill Walking

    E-Print Network [OSTI]

    Sukhatme, Gaurav S.

    Towards a Generalized Regression Model for On-body Energy Prediction from Treadmill Walking sensor data to energy expenditure is the ques- tion of normalizating across physiological parameters. Common approaches such as weight scaling require validation for each new population. An alternative

  18. A Prediction Model for Adiabatic and Diabatic Capillary Tubes with Alternative Refrigerants

    E-Print Network [OSTI]

    Zhang, Yupeng

    2014-12-05T23:59:59.000Z

    line) that exits the evaporator, which creates the so called capillary tube/suction line heat exchanger. Models to predict the mass flow in both adiabatic capillary tubes and capillary tube/suction line heat exchangers are developed in this thesis...

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

    E-Print Network [OSTI]

    Miami, University of

    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-induced internal wave energy in the world's oceans, J. Geophys. Res., 113, C09034, doi:10.1029/2008JC004768. 1

  20. Virtual Electrodes Mechanisms Predictions with a Current-Lifted Monodomain Model

    E-Print Network [OSTI]

    Boyer, Edmond

    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

  1. Predictive Modeling for Glass-Side Laser Scribing of Thin Film Photovoltaic Cells

    E-Print Network [OSTI]

    Yao, Y. Lawrence

    with reduced thermal effect. Film side laser scribing is governed by heating, melting and vaporizing of selective films. Glass side laser scribing is a thermal-mechanical process which involves stress inducedPredictive Modeling for Glass-Side Laser Scribing of Thin Film Photovoltaic Cells Hongliang Wang

  2. 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

  3. Supervisory hybrid model predictive control for voltage stability of power networks

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Supervisory hybrid model predictive control for voltage stability of power networks R.R. Negenborn voltage control problems in electric power networks have stimulated the interest for the imple- mentation dynamics to restore power consumption beyond the capability of the transmission and generation system

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

    E-Print Network [OSTI]

    Johansen, Tor Arne

    Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant Email: torstein.bo@itk.ntnu.no, tor.arne.johansen@itk.ntnu.no Abstract--Diesel-electric propulsion generation control, Ma- rine safety, Optimal control. I. INTRODUCTION Diesel electric propulsion is a system

  5. Prediction Intervals for NAR Model Structures Using a Bootstrap De Brabanter J.,

    E-Print Network [OSTI]

    Prediction Intervals for NAR Model Structures Using a Bootstrap Method De Brabanter J structure. Our approach relies on the external bootstrap procedure [1]. This method is contrasted. In this paper, an external bootstrap method will be proposed for this purpose. The bootstrap is a computer

  6. Predicting pesticide fate in the hive (part 2): development of a dynamic hive model

    E-Print Network [OSTI]

    .g. bees, wax and honey). The proposed model is validated using empirical data on -fluvalinate residues in bees, wax and honey. It predicts with good approximation both the trends over time to measured data. A honeybee hive is a micro-ecosystem com- posed of several components (e.g. bees, wax, honey

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

    E-Print Network [OSTI]

    Qiu, Qinru

    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

  8. Comparison of Machine Learning Techniques with Classical Statistical Models in Predicting Health Outcomes

    E-Print Network [OSTI]

    Mitnitski, Arnold B.

    ,5]. The aim of our report is to compare the performance of sev- eral well known machine learning techniquesComparison of Machine Learning Techniques with Classical Statistical Models in Predicting Health Faculty of Computer Science, Dalhousie University, Canada Abstract Several machine learning techniques

  9. Nonparametric Variable Selection for Predictive Models and Subpopulations in Clinical Trials

    E-Print Network [OSTI]

    Xie, Jun

    Introduction In most clinical trials, there is much heterogeneity among individual outcomes and the treat- mentNonparametric Variable Selection for Predictive Models and Subpopulations in Clinical Trials Jingyi, IN 47907 Abstract Most clinical trials have heterogeneous treatment effect among patient individuals

  10. 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

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

    E-Print Network [OSTI]

    Stephens, Matthew

    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

  12. Blood Glucose Level Prediction using Physiological Models and Support Vector Regression

    E-Print Network [OSTI]

    Bunescu, Razvan C.

    Blood Glucose Level Prediction using Physiological Models and Support Vector Regression Razvan continually monitor their blood glucose levels and adjust insulin doses, striving to keep blood glucose levels as close to normal as possible. Blood glucose levels that deviate from the normal range can lead to serious

  13. 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

  14. A LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    materials tensile, creep and LCF test data at different temperatures. Some parameters, independentA LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL CREEP for Single Crystal Superalloys operated at high temperatures and subjected to creep, fatigue and oxidation

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

    E-Print Network [OSTI]

    Fernandez, Thomas

    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

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

    E-Print Network [OSTI]

    Johansson, Karl Henrik

    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

  17. Trace-Based Analysis and Prediction of Cloud Computing User Behavior Using the Fractal Modeling Technique

    E-Print Network [OSTI]

    Pedram, Massoud

    Trace-Based Analysis and Prediction of Cloud Computing User Behavior Using the Fractal Modeling and technology. In this paper, we investigate the characteristics of the cloud computing requests received the alpha- stable distribution. Keywords- cloud computing; alpha-stable distribution; fractional order

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

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    / 24 #12;Natural Gas Industry Motivation Natural Gas Industry Globally increasing demand & production of natural gas. Demand distribution (as of 2008) 21 % residential, 13 % Commercial, 34 % Industrial, 29 - Regulated, Deregulated markets Applying Economic Model Predictive Control to gas transportation. 1Zheng et

  19. 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

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

    SciTech Connect (OSTI)

    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

    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.

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

    SciTech Connect (OSTI)

    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

    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)

  2. Arizona Foundation Expands Weatherization Training Center

    Broader source: Energy.gov [DOE]

    Read about one weatherization training center that's looking forward to an onslaught of new trainees.

  3. 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.

  4. Weatherization and Intergovernmental Program Success Stories

    Broader source: Energy.gov [DOE]

    Weatherization and Intergovernmental Programs Office (WIPO) success stories, news clips, and press releases.

  5. 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

  6. Attic or Roof? An Evaluation of Two Advanced Weatherization Packages

    SciTech Connect (OSTI)

    Neuhauser, K.

    2012-06-01T23:59:59.000Z

    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.

  7. Natural Priors, CMSSM Fits and LHC Weather Forecasts

    E-Print Network [OSTI]

    Allanach, B C; Cranmer, Kyle; Lester, Christopher G; Weber, Arne M

    2007-08-07T23:59:59.000Z

    ar X iv :0 70 5. 04 87 v3 [ he p- ph ] 5 J ul 20 07 Preprint typeset in JHEP style - HYPER VERSION DAMTP-2007-18 Cavendish-HEP-2007-03 MPP-2007-36 Natural Priors, CMSSM Fits and LHC Weather Forecasts Benjamin C Allanach1, Kyle Cranmer2... ’s likely discoveries. There are big differences between nature of the questions answered by a forecast, and the ques- tions that will be answered by the experiments themselves when they have acquired compelling data. A weather forecast predicting “severe...

  8. 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

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

    E-Print Network [OSTI]

    Street, Michael A. (Michael Anthony)

    2013-01-01T23:59:59.000Z

    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 ...

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

    E-Print Network [OSTI]

    Whipple, Sean David

    2014-01-01T23:59:59.000Z

    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 ...

  11. Predictions and measurements of isothermal airflow in a model once-through steam generator

    SciTech Connect (OSTI)

    Carter, H R; Promey, G J; Rush, G C

    1982-11-01T23:59:59.000Z

    Once-Through Steam Generators (OTSGs) are used in the Nuclear Steam Supply Systems marketed by The Babcock and Wilcox Company (B and W). To analytically predict the three-dimensional, steady-state thermohydraulic conditions in the OTSG, B and W has developed a proprietary code THEDA-1 and is working in cooperation with EPRI to develop an improved version, THEDA-2. Confident application of THEDA requires experimental verification to demonstrate that the code can accurately describe the thermohydraulic conditions in geometries characteristic of the OTSG. The first step in the THEDA verification process is the subject of this report. A full-scale, partial-section model of two OTSG spans was constructed and tested using isothermal air as the working fluid. Model local velocities and pressure profiles were measured and compared to THEDA prediction for five model configurations. Over 3000 velocity measurements were taken and the results were compared to THEDA predictions. Agreement between measured and predicted velocity data was generally better than +-12.5%.

  12. Elemental Solubility Tendency for the Phases of Uranium by Classical Models Used to Predict Alloy Behavior

    SciTech Connect (OSTI)

    Van Blackwood; Travis Koenig; Saleem Drera; Brajenda Mishra; Davis Olson; Doug Porter; Robert Mariani

    2012-03-01T23:59:59.000Z

    Traditional alloy theory models, specifically Darken-Gurry and Miedema’s analyses, that characterize solutes in solid solvents relative to physical properties of the elements have been used to assist in predicting alloy behavior. These models will be applied relative to the three solid phases of uranium: alpha (orthorhombic), beta (tetragonal), and gamma (bcc). These phases have different solubilities for specific alloy additions as a function of temperature. The Darken-Gurry and Miedema models, with modifications based on concepts of Waber, Gschneider, and Brewer will be used to predict the behavior of four types of solutes: 1) Transition metals that are used for various purposes associated with the containment as alloy additions in the uranium fuel 2) Transuranic elements in the uranium 3) Rare earth fission products (lanthanides) 4) Transition metals and other fission products Using these solute map criteria, elemental behavior will be predicted as highly soluble, marginally soluble, or immiscible (compound formers) and will be used to compare solute effects during uranium phase transformations. The overlapping of these solute maps are convenient first approximation tools for predicting alloy behavior.

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

    SciTech Connect (OSTI)

    Lipscomb, William [Los Alamos National Laboratory

    2012-06-19T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    M. K. Parida; Sudhanwa Patra

    2013-01-14T23:59:59.000Z

    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.

  15. A model for predicting the costs of research and development in the Post Office Department

    E-Print Network [OSTI]

    Watts, David Eli

    1970-01-01T23:59:59.000Z

    coefficients relating Y and 4. e is an n x 1 vector of the random errors c which are 2 normally distributed with mean 0 and variance a The least squares solution to this model is I ] I B ~ (K X) X Y Linear Cost Models The general philosophy behind linear... of Committee) ~ g QAr4 (Member) (Head of Department) ( er) January 1970 ABSTRACT A Model for Predicting the Costs of Research and Development in the Post Office Department. (January 1970) David E. Vatts, B. S. , Texas A&M University; Directed by: Dr...

  16. Interim Models Developed to Predict Key Hanford Waste Glass Properties Using Composition

    SciTech Connect (OSTI)

    Vienna, John D.; Kim, Dong-Sang; Hrma, Pavel R.

    2003-08-08T23:59:59.000Z

    Over the past several years the amount of waste glass property data available in the open literature has increased markedly. We have compiled the data from over 2000 glass compositions, evaluated the data for consistency, and fit glass property models to portions of this database.[1] The properties modeled include normalized releases of boron (rB), sodium (rNa), and lithium (rLi) from glass exposed to the product consistency test (PCT), liquidus temperature (TL) of glasses in the spinel and zircon primary phase field, viscosity (?) at 1150°C (?1150) and as a function of temperature (?T), and molar volume (V). These models were compared to some of the previously available models and were found to predict the properties of glasses not used in model fitting better and covered broader glass composition regions than the previous ones. This paper summarizes the data collected and the models that resulted from this effort.

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

    E-Print Network [OSTI]

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

    2015-01-01T23:59:59.000Z

    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...

  18. Earthquake prediction: Simple methods for complex phenomena

    E-Print Network [OSTI]

    Luen, Bradley

    2010-01-01T23:59:59.000Z

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

  19. Predictions for the abundance and colours of galaxies in high redshift clusters in hierarchical models

    E-Print Network [OSTI]

    Merson, Alexander I; Abdalla, Filipe B; Gonzalez-Perez, Violeta; Lagos, Claudia del P; Mei, Simona

    2015-01-01T23:59:59.000Z

    High redshift galaxy clusters allow us to examine galaxy formation in extreme environments. Here we compile data for $z>1$ galaxy clusters to test the predictions from one of the latest semi-analytical models of galaxy formation. The model gives a good match to the slope and zero-point of the cluster red sequence. The model is able to match the cluster galaxy luminosity function at faint and bright magnitudes, but under-estimates the number of galaxies around the break in the luminosity function. We find that simply assuming a weaker dust attenuation improves the model predictions for the cluster galaxy luminosity function, but worsens the predictions for the red sequence at bright magnitudes. Examination of the properties of the bright cluster galaxies suggests that the default dust attenuation is very large due to these galaxies having large reservoirs of cold gas as well as small radii. We find that matching the luminosity function and colours of high redshift cluster galaxies, whilst remaining consistent ...

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

    E-Print Network [OSTI]

    Lubliner, Howard

    2011-12-31T23:59:59.000Z

    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...

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

    E-Print Network [OSTI]

    Wang, Chien.; Prinn, Ronald G.

    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. ...

  2. Combined Experimental and Computational Approach to Predict the...

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

    rates measured in laboratory experiments to predict the weathering of primary minerals and volcanic and nuclear waste glasses in field studies requires the construction of...

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

    SciTech Connect (OSTI)

    Makhmalbaf, Atefe; Srivastava, Viraj; Wang, Na

    2013-08-05T23:59:59.000Z

    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.

  4. 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)

    S.P. Rupp

    2005-10-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Fang, Chung-Chieh

    2012-01-01T23:59:59.000Z

    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.

  6. Predicting bid prices in construction projects using non-parametric statistical models

    E-Print Network [OSTI]

    Pawar, Roshan

    2009-05-15T23:59:59.000Z

    of Department, David Rosowsky August 2007 Major Subject: Civil Engineering iii ABSTRACT Predicting Bid Prices in Construction Projects Using Non-parametric Statistical Models. (August 2007) Roshan Pawar, B.E., University of Mumbai Chair... neural networks. v DEDICATION Dedicated to my parents Suresh and Sharayu Pawar and brother Abhishek Pawar. vi ACKNOWLEDGEMENTS I would like to thank the committee chair Dr. Seth Guikema for providing his assistance...

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

    E-Print Network [OSTI]

    Menut, Laurent

    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

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

    SciTech Connect (OSTI)

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

    1996-12-31T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2009-01-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    1983-04-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Seidel, Gary Don

    2002-01-01T23:59:59.000Z

    . 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...

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

    SciTech Connect (OSTI)

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

    2012-10-01T23:59:59.000Z

    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.

  13. Predicting spin of compact objects from their QPOs: A global QPO model

    E-Print Network [OSTI]

    Banibrata Mukhopadhyay

    2008-09-19T23:59:59.000Z

    We establish a unified model to explain Quasi-Periodic-Oscillation (QPO) observed from black hole and neutron star systems globally. This is based on the accreting systems thought to be damped harmonic oscillators with higher order nonlinearity. The model explains multiple properties parallelly independent of the nature of the compact object. It describes QPOs successfully for several compact sources. Based on it, we predict the spin frequency of the neutron star Sco X-1 and the specific angular momentum of black holes GRO J1655-40, GRS 1915+105.

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

    E-Print Network [OSTI]

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

    2014-09-17T23:59:59.000Z

    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).

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

    E-Print Network [OSTI]

    Froude, Lizzie

    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

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

    E-Print Network [OSTI]

    Cowlard, Adam

    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....

  17. Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation

    SciTech Connect (OSTI)

    Gershgorin, B. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States); Harlim, J. [Department of Mathematics, North Carolina State University, NC 27695 (United States)], E-mail: jharlim@ncsu.edu; Majda, A.J. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States)

    2010-01-01T23:59:59.000Z

    The filtering and predictive skill for turbulent signals is often limited by the lack of information about the true dynamics of the system and by our inability to resolve the assumed dynamics with sufficiently high resolution using the current computing power. The standard approach is to use a simple yet rich family of constant parameters to account for model errors through parameterization. This approach can have significant skill by fitting the parameters to some statistical feature of the true signal; however in the context of real-time prediction, such a strategy performs poorly when intermittent transitions to instability occur. Alternatively, we need a set of dynamic parameters. One strategy for estimating parameters on the fly is a stochastic parameter estimation through partial observations of the true signal. In this paper, we extend our newly developed stochastic parameter estimation strategy, the Stochastic Parameterization Extended Kalman Filter (SPEKF), to filtering sparsely observed spatially extended turbulent systems which exhibit abrupt stability transition from time to time despite a stable average behavior. For our primary numerical example, we consider a turbulent system of externally forced barotropic Rossby waves with instability introduced through intermittent negative damping. We find high filtering skill of SPEKF applied to this toy model even in the case of very sparse observations (with only 15 out of the 105 grid points observed) and with unspecified external forcing and damping. Additive and multiplicative bias corrections are used to learn the unknown features of the true dynamics from observations. We also present a comprehensive study of predictive skill in the one-mode context including the robustness toward variation of stochastic parameters, imperfect initial conditions and finite ensemble effect. Furthermore, the proposed stochastic parameter estimation scheme applied to the same spatially extended Rossby wave system demonstrates high predictive skill, comparable with the skill of the perfect model for a duration of many eddy turnover times especially in the unstable regime.

  18. U.S. Department of Energy Weatherization Assistance Program Homes...

    Energy Savers [EERE]

    U.S. Department of Energy Weatherization Assistance Program Homes Weatherized By State through 06302010 (Calendar Year) U.S. Department of Energy Weatherization Assistance...

  19. Essays on Weather Indexed Insurance and Energy Use in Mexico

    E-Print Network [OSTI]

    Fuchs, Alan

    2011-01-01T23:59:59.000Z

    and O. Mahul, 2007. “Weather Index Insurance for Agricultureand J. Vickery, 2005. “Weather Insurance in Semi-AridBinswanger, 1993. “Wealth, Weather Risk and the Composition

  20. Identification of High Collision Concentration Locations Under Wet Weather Conditions

    E-Print Network [OSTI]

    Hwang, Taesung; Chung, Koohong; Ragland, David; Chan, Chin-Yao

    2008-01-01T23:59:59.000Z

    conducted under wet weather conditions. Observations fromLeahy, M. , and Suggett, J. Weather as a Chronic Hazard forLocations Under Wet Weather Conditions Taesung Hwang,

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

    E-Print Network [OSTI]

    Ahn, Min-Woo

    2015-01-01T23:59:59.000Z

    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.

  2. 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]

    Oliker, Leonid

    of anthropogenic climate change are highly dependent on cloud-radiation interactions. In this paper, we Keywords Climate model, atmospheric general circulation model, finite volume model, global warming scientists today, with economic ramifications in the trillions of dollars. Effectively performing

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

    SciTech Connect (OSTI)

    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

    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 ocean’s 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.

  4. The Microwave Thermal Emission from the Zodiacal Dust Cloud Predicted with Contemporary Meteoroid Models

    E-Print Network [OSTI]

    Dikarev, Valery V

    2015-01-01T23:59:59.000Z

    Predictions of the microwave thermal emission from the interplanetary dust cloud are made using several contemporary meteoroid models to construct the distributions of cross-section area of dust in space, and applying the Mie light-scattering theory to estimate the temperatures and emissivities of dust particles in broad size and heliocentric distance ranges. In particular, the model of the interplanetary dust cloud by Kelsall et al. (1998, ApJ 508: 44-73), the five populations of interplanetary meteoroids of Divine (1993, JGR 98(E9): 17,029-17,048) and the Interplanetary Meteoroid Engineering Model (IMEM) by Dikarev et al. (2004, EMP 95: 109-122) are used in combination with the optical properties of olivine, carbonaceous and iron spherical particles. The Kelsall model has been widely accepted by the Cosmic Microwave Background (CMB) community. We show, however, that it predicts the microwave emission from interplanetary dust remarkably different from the results of application of the meteoroid engineering m...

  5. Rolling Process Modeling Report: Finite-Element Prediction of Roll Separating Force and Rolling Defects

    SciTech Connect (OSTI)

    Soulami, Ayoub; Lavender, Curt A.; Paxton, Dean M.; Burkes, Douglas

    2014-04-23T23:59:59.000Z

    Pacific Northwest National Laboratory (PNNL) has been investigating manufacturing processes for the uranium-10% molybdenum (U-10Mo) alloy plate-type fuel for the U.S. high-performance research reactors. This work supports the Convert Program of the U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) Global Threat Reduction Initiative. This report documents modeling results of PNNL’s efforts to perform finite-element simulations to predict roll separating forces and rolling defects. Simulations were performed using a finite-element model developed using the commercial code LS-Dyna. Simulations of the hot rolling of U-10Mo coupons encapsulated in low-carbon steel have been conducted following two different schedules. Model predictions of the roll-separation force and roll-pack thicknesses at different stages of the rolling process were compared with experimental measurements. This report discusses various attributes of the rolled coupons revealed by the model (e.g., dog-boning and thickness non-uniformity).

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

    E-Print Network [OSTI]

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

    2015-02-26T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Watney, W.L.

    1994-12-01T23:59:59.000Z

    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.

  8. Winter Weather FAQs | Argonne National Laboratory

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

    Winter Weather FAQs As Argonne prepares for the winter season, employees should be aware of the laboratory's procedures and policies in severe weather events. Below are some of the...

  9. Weatherization Innovation Pilot Program: Program Overview and Philadelphia Project Highlight (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2012-01-01T23:59:59.000Z

    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.

  10. Pantex receives National Weather Service recognition | National...

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

    receives National Weather Service recognition | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS People Mission Managing the Stockpile Preventing...

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

    SciTech Connect (OSTI)

    Kohler, Christian

    2012-08-01T23:59:59.000Z

    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.

  12. A Comparison of Measured Crab and Vela Glitch Healing Parameters with Predictions of Neutron Star Models

    E-Print Network [OSTI]

    Fronefield Crawford; Marek Demianski

    2003-06-11T23:59:59.000Z

    There are currently two well-accepted models that explain how pulsars exhibit glitches, sudden changes in their regular rotational spin-down. According to the starquake model, the glitch healing parameter, Q, which is measurable in some cases from pulsar timing, should be equal to the ratio of the moment of inertia of the superfluid core of a neutron star (NS) to its total moment of inertia. Measured values of the healing parameter from pulsar glitches can therefore be used in combination with realistic NS structure models as one test of the feasibility of the starquake model as a glitch mechanism. We have constructed NS models using seven representative equations of state of superdense matter to test whether starquakes can account for glitches observed in the Crab and Vela pulsars, for which the most extensive and accurate glitch data are available. We also present a compilation of all measured values of Q for Crab and Vela glitches to date which have been separately published in the literature. We have computed the fractional core moment of inertia for stellar models covering a range of NS masses and find that for stable NSs in the realistic mass range 1.4 +/- 0.2 solar masses, the fraction is greater than 0.55 in all cases. This range is not consistent with the observational restriction Q 0.7) are consistent with the starquake model predictions and support previous conclusions that starquakes can be the cause of Crab glitches.

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

    SciTech Connect (OSTI)

    Fok, Alex

    2013-10-30T23:59:59.000Z

    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.

  14. Karimar Ledesma Puerto Rico Weather Camp 2009

    E-Print Network [OSTI]

    Gilbes, Fernando

    Karimar Ledesma Puerto Rico Weather Camp 2009 Me llamo Karimar Ledesma Maldonado y soy una "Weather Camper 2009". Mi participación en el Puerto Rico Weather Camp fue lo que finalmente me convenció y motivo Física Teórica en adición a la certificación de meteorología en la Universidad de Puerto Rico en Mayagüez

  15. Internship opportunity with National Weather Service

    E-Print Network [OSTI]

    Internship opportunity with National Weather Service Pacific Regional Headquarters Fall 2008 deadline: August 8, 2008 The Pacific Region of the National Weather Service administers the programs and the general public. The Pacific Regional Headquarters of the National Weather Service, located in downtown

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

    E-Print Network [OSTI]

    California at Berkeley, University of

    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

  17. Journal of Energy and Power Engineering 5 (2011) 554-561 Load Torque Compensator for Model Predictive Direct

    E-Print Network [OSTI]

    Schaltz, Erik

    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

  18. Evaluating uncertainty in stochastic simulation models

    SciTech Connect (OSTI)

    McKay, M.D.

    1998-02-01T23:59:59.000Z

    This paper discusses fundamental concepts of uncertainty analysis relevant to both stochastic simulation models and deterministic models. A stochastic simulation model, called a simulation model, is a stochastic mathematical model that incorporates random numbers in the calculation of the model prediction. Queuing models are familiar simulation models in which random numbers are used for sampling interarrival and service times. Another example of simulation models is found in probabilistic risk assessments where atmospheric dispersion submodels are used to calculate movement of material. For these models, randomness comes not from the sampling of times but from the sampling of weather conditions, which are described by a frequency distribution of atmospheric variables like wind speed and direction as a function of height above ground. A common characteristic of simulation models is that single predictions, based on one interarrival time or one weather condition, for example, are not nearly as informative as the probability distribution of possible predictions induced by sampling the simulation variables like time and weather condition. The language of model analysis is often general and vague, with terms having mostly intuitive meaning. The definition and motivations for some of the commonly used terms and phrases offered in this paper lead to an analysis procedure based on prediction variance. In the following mathematical abstraction the authors present a setting for model analysis, relate practical objectives to mathematical terms, and show how two reasonable premises lead to a viable analysis strategy.

  19. Watching ColoradoWatching Colorado WeatherWeather

    E-Print Network [OSTI]

    ­ Evapotranspiration #12;CoAgMet Southeast Colorado #12;Hoehne CoAgMet Weather Station #12;Hoehne Daily Temperatures #12;Hoehne Relative Humidity #12;Hoehne Solar Radiation #12;Hoehne Wind Speed #12;Hoehne ET Reference Hoehne ET Reference 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Jan-04 Jan-04 Feb-04 M ar-04 M

  20. Procedures for Filling Short Gaps in Energy Use and Weather Data

    E-Print Network [OSTI]

    Chen, H.; Claridge, D. E.

    2000-01-01T23:59:59.000Z

    data. Single variable regression, polynomial models, Lagrange interpolation, and linear interpolation models are developed, demonstrated, and used to fill 1-6 hour gaps in weather data, heating data and cooling data for commercial buildings...

  1. Models for the Prediction of Fouling in Crude Oil Pre-Heat Trains

    E-Print Network [OSTI]

    Yeap, B. L.; Wilson, D. I.; Polley, G. T.

    Models for the Prediction of Fouling in Crude Oil Pre-Heat Trains B.L. Yeap D.I. Wilson G.T. PoUey Dept. of Chern. Engng. Dept. of Chern. Engng. ESDU International Ltd University of Cambridge University of Cambridge Fouling has two significant... across a unit. Extended fouling can affect the throughput of the train. The impetus behind exchanger cleaning is often the need to maintain throughput rather than save energy. If we are to be able to consider fouling in the design of crude oil pre...

  2. Explaining the road accident risk: weather effects Ruth Bergel-Hayat1*

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    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

  3. 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.

  4. The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.

    SciTech Connect (OSTI)

    Drover, Damion, Ryan

    2011-12-01T23:59:59.000Z

    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.

  5. Application of a spatially referenced water quality model to predict E. coli flux in two Texas river basins

    E-Print Network [OSTI]

    , Deepti

    2009-05-15T23:59:59.000Z

    Water quality models are applied to assess the various processes affecting the concentrations of contaminants in a watershed. SPAtially Referenced Regression On Watershed attributes (SPARROW) is a nonlinear regression based approach to predict...

  6. The use of a distributed hydrologic model to predict dynamic landslide susceptibility for a humid basin in Puerto Rico

    E-Print Network [OSTI]

    Kamal, Sameer A. (Sameer Ahmed)

    2009-01-01T23:59:59.000Z

    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 ...

  7. Prediction of continental shelf sediment transport using a theoretical model of the wave-current boundary layer

    E-Print Network [OSTI]

    Goud, Margaret R

    1987-01-01T23:59:59.000Z

    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 ...

  8. Evaluation of the accuracy of the EPA model for BOD5 prediction in various climatic regions of Texas

    E-Print Network [OSTI]

    Koutny, Jessica Leigh

    2000-01-01T23:59:59.000Z

    This project focused on evaluating the effectiveness of the EPA's first-order BOD? removal model for predicting BOD? reductions in residential constructed wetlands. Monthly grab sample data from nine constructed wetlands designed using the EPA BOD5...

  9. 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]

    Muendej, Krisanee

    2004-11-15T23:59:59.000Z

    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...

  10. IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 7, NO. 3, JUNE 1999 319 Model Predictive Satisficing Fuzzy Logic Control

    E-Print Network [OSTI]

    Goodrich, Michael A.

    Logic Control Michael A. Goodrich, Wynn C. Stirling, and Richard L. Frost Abstract-- Model constrained and nonlinear control problems. However, even when a good model is available, it may be necessary employs a fuzzy description of system consequences via model predictions. This controller considers

  11. Gas Metal Arc Welding Process Modeling and Prediction of Weld Microstructure in MIL A46100 Armor-Grade

    E-Print Network [OSTI]

    Grujicic, Mica

    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

  12. Finite Mixture of ARMA-GARCH Model for Stock Price Prediction Him Tang, Kai-Chun Chiu and Lei Xu

    E-Print Network [OSTI]

    Xu, Lei

    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

  13. Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

    SciTech Connect (OSTI)

    Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov [Science and Research Staff, Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993–0002 (United States); Cross, Kevin P. [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)] [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)

    2012-05-01T23:59:59.000Z

    Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ? We characterize a new in silico model to predict mutagenicity of drug impurities. ? The model predicts Salmonella mutagenicity and will be useful for safety assessment. ? We examine toxicity fingerprints and toxicophores of this Ames assay model. ? We compare these attributes to those found in drug impurities known to FDA/CDER. ? We validate the model and find it has a desired predictive performance.

  14. A COMPARATIVE ANALYSIS OF THE INFLUENCE OF WEATHER ON THE

    E-Print Network [OSTI]

    Loon, E. Emiel van

    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

  15. A voxel-based finite element model for the prediction of bladder deformation

    SciTech Connect (OSTI)

    Chai Xiangfei; Herk, Marcel van; Hulshof, Maarten C. C. M.; Bel, Arjan [Radiation Oncology Department, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam (Netherlands); Radiation Oncology Department, Netherlands Cancer Institute, 1066 CX Amsterdam (Netherlands); Radiation Oncology Department, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam (Netherlands)

    2012-01-15T23:59:59.000Z

    Purpose: A finite element (FE) bladder model was previously developed to predict bladder deformation caused by bladder filling change. However, two factors prevent a wide application of FE models: (1) the labor required to construct a FE model with high quality mesh and (2) long computation time needed to construct the FE model and solve the FE equations. In this work, we address these issues by constructing a low-resolution voxel-based FE bladder model directly from the binary segmentation images and compare the accuracy and computational efficiency of the voxel-based model used to simulate bladder deformation with those of a classical FE model with a tetrahedral mesh. Methods: For ten healthy volunteers, a series of MRI scans of the pelvic region was recorded at regular intervals of 10 min over 1 h. For this series of scans, the bladder volume gradually increased while rectal volume remained constant. All pelvic structures were defined from a reference image for each volunteer, including bladder wall, small bowel, prostate (male), uterus (female), rectum, pelvic bone, spine, and the rest of the body. Four separate FE models were constructed from these structures: one with a tetrahedral mesh (used in previous study), one with a uniform hexahedral mesh, one with a nonuniform hexahedral mesh, and one with a low-resolution nonuniform hexahedral mesh. Appropriate material properties were assigned to all structures and uniform pressure was applied to the inner bladder wall to simulate bladder deformation from urine inflow. Performance of the hexahedral meshes was evaluated against the performance of the standard tetrahedral mesh by comparing the accuracy of bladder shape prediction and computational efficiency. Results: FE model with a hexahedral mesh can be quickly and automatically constructed. No substantial differences were observed between the simulation results of the tetrahedral mesh and hexahedral meshes (<1% difference in mean dice similarity coefficient to manual contours and <0.02 cm difference in mean standard deviation of residual errors). The average equation solving time (without manual intervention) for the first two types of hexahedral meshes increased to 2.3 h and 2.6 h compared to the 1.1 h needed for the tetrahedral mesh, however, the low-resolution nonuniform hexahedral mesh dramatically decreased the equation solving time to 3 min without reducing accuracy. Conclusions: Voxel-based mesh generation allows fast, automatic, and robust creation of finite element bladder models directly from binary segmentation images without user intervention. Even the low-resolution voxel-based hexahedral mesh yields comparable accuracy in bladder shape prediction and more than 20 times faster in computational speed compared to the tetrahedral mesh. This approach makes it more feasible and accessible to apply FE method to model bladder deformation in adaptive radiotherapy.

  16. Interface modeling to predict well casing damage for big hill strategic petroleum reserve.

    SciTech Connect (OSTI)

    Ehgartner, Brian L.; Park, Byoung Yoon

    2012-02-01T23:59:59.000Z

    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.

  17. Incorporating Single-nucleotide Polymorphisms Into the Lyman Model to Improve Prediction of Radiation Pneumonitis

    SciTech Connect (OSTI)

    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

    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.

  18. A Predictive Model of Fragmentation using Adaptive Mesh Refinement and a Hierarchical Material Model

    SciTech Connect (OSTI)

    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

    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.

  19. Evaluation of Mixed-Phase Cloud Parameterizations in Short-Range Weather Forecasts with CAM3 and AM2 for Mixed-Phase Arctic Cloud Experiment

    SciTech Connect (OSTI)

    Xie, S; Boyle, J; Klein, S; Liu, X; Ghan, S

    2007-06-01T23:59:59.000Z

    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.

  20. Predicted impacts of future water level decline on monitoring wells using a ground-water model of the Hanford Site

    SciTech Connect (OSTI)

    Wurstner, S.K.; Freshley, M.D.

    1994-12-01T23:59:59.000Z

    A ground-water flow model was used to predict water level decline in selected wells in the operating areas (100, 200, 300, and 400 Areas) and the 600 Area. To predict future water levels, the unconfined aquifer system was stimulated with the two-dimensional version of a ground-water model of the Hanford Site, which is based on the Coupled Fluid, Energy, and Solute Transport (CFEST) Code in conjunction with the Geographic Information Systems (GIS) software package. The model was developed using the assumption that artificial recharge to the unconfined aquifer system from Site operations was much greater than any natural recharge from precipitation or from the basalt aquifers below. However, artificial recharge is presently decreasing and projected to decrease even more in the future. Wells currently used for monitoring at the Hanford Site are beginning to go dry or are difficult to sample, and as the water table declines over the next 5 to 10 years, a larger number of wells is expected to be impacted. The water levels predicted by the ground-water model were compared with monitoring well completion intervals to determine which wells will become dry in the future. Predictions of wells that will go dry within the next 5 years have less uncertainty than predictions for wells that will become dry within 5 to 10 years. Each prediction is an estimate based on assumed future Hanford Site operating conditions and model assumptions.

  1. Prediction of buried mine-like target radar signatures using wideband electromagnetic modeling

    SciTech Connect (OSTI)

    Warrick, A.L.; Azevedo, S.G.; Mast, J.E.

    1998-04-06T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Haves, Phillip; Hencey, Brandon; Borrell, Francesco; Elliot, John; Ma, Yudong; Coffey, Brian; Bengea, Sorin; Wetter, Michael

    2010-06-29T23:59:59.000Z

    A Model Predictive Control algorithm was developed for the UC Merced campus chilled water plant. Model predictive control (MPC) is an advanced control technology that has proven successful in the chemical process industry and other industries. The main goal of the research was to demonstrate the practical and commercial viability of MPC for optimization of building energy systems. The control algorithms were developed and implemented in MATLAB, allowing for rapid development, performance, and robustness assessment. The UC Merced chilled water plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during the night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. The control algorithms determined the optimal chilled water plant operation including chilled water supply (CHWS) temperature set-point, condenser water supply (CWS) temperature set-point and the charging start and stop times to minimize a cost function that includes energy consumption and peak electrical demand over a 3-day prediction horizon. A detailed model of the chilled water plant and simplified models of the buildings served by the plant were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers performance data, and calibrated using measured data collected and archived by the control system. A detailed dynamic model of the chilled water storage tank was also developed and calibrated. Simple, semi-empirical models were developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a model predictive control algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The report describes the development and testing of the algorithm and evaluates the resulting performance, concluding with a discussion of next steps in further research. The experimental results show a small improvement in COP over the baseline policy but it is difficult to draw any strong conclusions about the energy savings potential for MPC with this system only four days of suitable experimental data were obtained once correct operation of the MPC system had been achieved. These data show an improvement in COP of 3.1% {+-} 2.2% relative to a baseline established immediately prior to the period when the MPC was run in its final form. This baseline includes control policy improvements that the plant operators learned by observing the earlier implementations of MPC, including increasing the temperature of the water supplied to the chiller condensers from the cooling towers. The process of data collection and model development, necessary for any MPC project, resulted in the team uncovering various problems with the chilled water system. Although it is difficult to quantify the energy savings resulting from these problems being remedied, they were likely on the same order as the energy savings from the MPC itself. Although the types of problems uncovered and the level of energy savings may differ significantly from other projects, some of the benefits of detecting and diagnosing problems are expected from the use of MPC for any chilled water plant. The degree of chiller loading was found to be a key factor for efficiency. It is more efficient to operate the chillers at or near full load. In order to maximize the chiller load, one would maximize the temperature difference across chillers and the chilled water flow rate through the chillers. Thus, the CHWS set-point and the chilled water flow-rate can be used to limit the chiller loading to prevent chiller surging. Since the flow rate has an upper bound and the CHWS set point has a lower bound, the chiller loading is constrained and often determined by the chilled water return temperature (CHWR). The CHWR temperature

  3. Extended Abstract, 20th Conf. Weather Analysis and Forecasting/ 16th Conf. Numerical Weather Prediction

    E-Print Network [OSTI]

    Xue, Ming

    . 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

  4. Predictive Treatment Management: Incorporating a Predictive Tumor Response Model Into Robust Prospective Treatment Planning for Non-Small Cell Lung Cancer

    SciTech Connect (OSTI)

    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

    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.

  5. Model predictive control system and method for integrated gasification combined cycle power generation

    DOE Patents [OSTI]

    Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

    2013-04-09T23:59:59.000Z

    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.

  6. Predictive Modelling of Toxicity Resulting from Radiotherapy Treatments of Head and Neck Cancer

    E-Print Network [OSTI]

    Dean, Jamie A; Harrington, Kevin J; Nutting, Christopher M; Gulliford, Sarah L

    2014-01-01T23:59:59.000Z

    In radiotherapy for head and neck cancer, the radiation dose delivered to the pharyngeal mucosa (mucosal lining of the throat) is thought to be a major contributing factor to dysphagia (swallowing dysfunction), the most commonly reported severe toxicity. There is a variation in the severity of dysphagia experienced by patients. Understanding the role of the dose distribution in dysphagia would allow improvements in the radiotherapy technique to be explored. The 3D dose distributions delivered to the pharyngeal mucosa of 249 patients treated as part of clinical trials were reconstructed. Pydicom was used to extract DICOM (digital imaging and communications in medicine) data (the standard file formats for medical imaging and radiotherapy data). NumPy and SciPy were used to manipulate the data to generate 3D maps of the dose distribution delivered to the pharyngeal mucosa and calculate metrics describing the dose distribution. Multivariate predictive modelling of severe dysphagia, including descriptions of the d...

  7. Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs (Annex 1)

    SciTech Connect (OSTI)

    Watney, W.L.

    1992-01-01T23:59:59.000Z

    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.

  8. Supporting technology for enhanced oil recovery: CO/sub 2/ miscible flood predictive model

    SciTech Connect (OSTI)

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

    1986-12-01T23:59:59.000Z

    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.

  9. Modeling Stress Strain Relationships and Predicting Failure Probabilities For Graphite Core Components

    SciTech Connect (OSTI)

    Duffy, Stephen

    2013-09-09T23:59:59.000Z

    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.

  10. Development of a model for predicting transient hydrogen venting in 55-gallon drums

    SciTech Connect (OSTI)

    Apperson, Jason W [Los Alamos National Laboratory; Clemmons, James S [Los Alamos National Laboratory; Garcia, Michael D [Los Alamos National Laboratory; Sur, John C [Los Alamos National Laboratory; Zhang, Duan Z [Los Alamos National Laboratory; Romero, Michael J [Los Alamos National Laboratory

    2008-01-01T23:59:59.000Z

    Remote drum venting was performed on a population of unvented high activity drums (HAD) in the range of 63 to 435 plutonium equivalent Curies (PEC). These 55-gallon Transuranic (TRU) drums will eventually be shipped to the Waste Isolation Pilot Plant (WIPP). As a part of this process, the development of a calculational model was required to predict the transient hydrogen concentration response of the head space and polyethylene liner (if present) within the 55-gallon drum. The drum and liner were vented using a Remote Drum Venting System (RDVS) that provided a vent sampling path for measuring flammable hydrogen vapor concentrations and allow hydrogen to diffuse below lower flammability limit (LFL) concentrations. One key application of the model was to determine the transient behavior of hydrogen in the head space, within the liner, and the sensitivity to the number of holes made in the liner or number of filters. First-order differential mass transport equations were solved using Laplace transformations and numerically to verify the results. the Mathematica 6.0 computing tool was also used as a validation tool and for examining larger than two chamber systems. Results will be shown for a variety of configurations, including 85-gallon and 110-gallon overpack drums. The model was also validated against hydrogen vapor concentration assay measurements.

  11. Use of roof temperature modeling to predict necessary conditions for locating wet insulation with infrared thermography

    SciTech Connect (OSTI)

    Childs, K.W.

    1985-11-01T23:59:59.000Z

    In low-sloped roofing systems using porous insulation, the presence of water can significantly degrade thermal performance. For this reason, it is desirable to develop a reliable method for detecting the presence of water in a roofing system. Because of the different thermal characteristics of wet and dry insulation, there is often a surface temperature differential between areas containing wet insulation and areas containing dry insulation. Under the right circumstances, the areas of wet insulation can be detected by means of infrared sensing techniques. These techniques have already gained widespread acceptance, but there is still some uncertainty as to what are appropriate environmental conditions for viewing. To better define the conditions under which infrared techniques can distinguish between areas of wet and dry insulation, a one-dimensional, transient heat transfer model of a roofing system was developed. The model considers conduction through the roof, insolation on the surface, radiant exchange between the roof and sky, convective heat transfer between the roof and air, and the influence of trapped moisture on the thermal properties of the insulation. A study was undertaken using this model to develop an easily-applied technique for prediction of necessary conditions for locating wet roof insulation using infrared thermography.

  12. Quasi-steady model for predicting temperature of aqueous foams circulating in geothermal wellbores

    SciTech Connect (OSTI)

    Blackwell, B.F.; Ortega, A.

    1983-01-01T23:59:59.000Z

    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.

  13. Computer modeling of arc welds to predict effects of critical variables on weld penetration

    SciTech Connect (OSTI)

    Zacharia, T.; David, S.A.

    1991-01-01T23:59:59.000Z

    In recent years, there have been several attempts to study the effect of critical variables on welding by computational modeling. It is widely recognized that temperature distributions and weld pool shapes are keys to quality weldments. It would be very useful to obtain relevant information about the thermal cycle experienced by the weld metal, the size and shape of the weld pool, and the local solidification rates, temperature distributions in the heat-affected zone (HAZ), and associated phase transformations. The solution of moving boundary problems, such as weld pool fluid flow and heat transfer, that involve melting and/or solidification is inherently difficult because the location of the solid-liquid interface is not known a priori and must be obtained as a part of the solution. Because of non-linearity of the governing equations, exact analytical solutions can be obtained only for a limited number of idealized cases. Therefore, considerable interest has been directed toward the use of numerical methods to obtain time-dependant solutions for theoretical models that describe the welding process. Numerical methods can be employed to predict the transient development of the weld pool as an integral part of the overall heat transfer conditions. The structure of the model allows each phenomenon to be addressed individually, thereby gaining more insight into their competing interactions. 19 refs., 6 figs., 1 tab.

  14. Conclusions The results show that the models are able to predict the response of the FETi motor

    E-Print Network [OSTI]

    Sóbester, András

    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

  15. ghMulti-Level Approach for Model-Based Predictive Control (MPC) in Buildings: A Preliminary Overview

    E-Print Network [OSTI]

    Candanedo, J. A.; Dehkordi, V. R.

    2013-01-01T23:59:59.000Z

    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...

  16. BFEPM:Best Fit Energy Prediction Modeling Based on CPU Utilization Xiao Zhang, Jianjun Lu, Xiao Qin

    E-Print Network [OSTI]

    Qin, Xiao

    Engineering Auburn University Auburn, AL USA 36849-5347 Email: xqin@auburn.edu Abstract--Energy cost becomes 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

  17. Optimization of the GB/SA Solvation Model for Predicting the Structure of Surface Loops in Proteins

    E-Print Network [OSTI]

    Meirovitch, Hagai

    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

  18. Quantification and prediction of extreme events in a one-dimensional nonlinear dispersive wave model

    E-Print Network [OSTI]

    Will Cousins; Themistoklis P. Sapsis

    2014-01-15T23:59:59.000Z

    The aim of this work is the quantification and prediction of rare events characterized by extreme intensity in nonlinear waves with broad spectra. We consider a one-dimensional non- linear model with deep-water waves dispersion relation, the Majda-McLaughlin-Tabak (MMT) model, in a dynamical regime that is characterized by broadband spectrum and strong non- linear energy transfers during the development of intermittent events with finite-lifetime. To understand the energy transfers that occur during the development of an extreme event we perform a spatially localized analysis of the energy distribution along different wavenumbers by means of the Gabor transform. A stochastic analysis of the Gabor coefficients reveals i) the low-dimensionality of the intermittent structures, ii) the interplay between non-Gaussian statis- tical properties and nonlinear energy transfers between modes, as well as iii) the critical scales (or critical Gabor coefficients) where a critical amount of energy can trigger the formation of an extreme event. We analyze the unstable character of these special localized modes directly through the system equation and show that these intermittent events are due to the interplay of the system nonlinearity, the wave dispersion, and the wave dissipation which mimics wave breaking. These localized instabilities are triggered by random localizations of energy in space, created by the dispersive propagation of low-amplitude waves with random phase. Based on these properties, we design low-dimensional functionals of these Gabor coefficients that allow for the prediction of the extreme event well before the nonlinear interactions begin to occur.

  19. Five case studies of multifamily weatherization programs

    SciTech Connect (OSTI)

    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

    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.

  20. Clay formation and metal fixation during weathering of coal fly ash

    SciTech Connect (OSTI)

    Zevenbergen, C.; Bradley, J.P.; Reeuwijk, L.P. Van; Shyam, A.K.; Hjelmar, O.; Comans, R.N.J.

    1999-10-01T23:59:59.000Z

    The enormous and worldwide production of coal fly ash cannot be durably isolated from the weathering cycle, and the weathering characteristics of fly ash must be known to understand the long-term environmental impact. The authors studied the weathering of two coal fly ashes and compared them with published data from weathered volcanic ash, it's closest natural analogue. Both types of ash contain abundant aluminosilicate glass, which alters to noncrystalline clay. However, this study reveals that the kinetics of coal fly ash weathering are more rapid than those of volcanic ash because the higher pH of fresh coal fly ash promotes rapid dissolution of the glass. After about 10 years of weathering, the noncrystalline clay content of coal fly ash is higher than that of 250-year-old volcanic ash. The observed rapid clay formation together with heavy metal fixation imply that the long-term environmental impact of coal fly ash disposal may be less severe and the benefits more pronounced than predicted from previous studies on unweathered ash. Their findings suggest that isolating coal fly ash from the weathering cycle may be counterproductive because, in the long-term under conditions of free drainage, fly ash is converted into fertile soil capable of supporting agriculture.