National Library of Energy BETA

Sample records for weather prediction models

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

    E-Print Network [OSTI]

    McGovern, Amy

    Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction Amy McGovern1 dis- covery methods for use on mesoscale weather data. Severe weather phenomena such as tornados, thun, current techniques for predicting severe weather are tied to specific characteristics of the radar systems

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of numerical weather prediction solar irradiance forecasts numerical weather prediction model for solar irradiance weather prediction for intra?day solar  forecasting in the 

  3. Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction

    E-Print Network [OSTI]

    Wirosoetisno, Djoko

    Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction Supervisors). Background: Numerical Weather Prediction (NWP) has seen significant gains in accuracy in recent years due in weather dynamics, e.g., the asymptotic balance seen in high and low pressure systems. Aims of the project

  4. 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

    2008-03-20

    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.

  5. Passive millimeter-wave retrieval of global precipitation utilizing satellites and a numerical weather prediction model

    E-Print Network [OSTI]

    Surussavadee, Chinnawat

    2007-01-01

    This thesis develops and validates the MM5/TBSCAT/F([lambda]) model, composed of a mesoscale numerical weather prediction (NWP) model (MM5), a two-stream radiative transfer model (TBSCAT), and electromagnetic models for ...

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    of numerical weather prediction solar irradiance forecastsof numerical weather prediction solar irradiance forecastsnumerical weather prediction model for solar irradiance

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    cycle:  The RUC.  Monthly Weather  Review.   132, 495?518.  th  Conference on  Numerical Weather Prediction.   American closure schemes.   Monthly Weather Review.   122, 927?945.  

  8. Optimizing Computations in Weather and Climate Prediction Models* F. BAER, BANGLIN ZHANG, AND BING ZHANG

    E-Print Network [OSTI]

    Baer, Ferdinand

    Optimizing Computations in Weather and Climate Prediction Models* F. BAER, BANGLIN ZHANG, AND BING scenarios for many time scales, more computer power than is currently available will be needed. One and sometimes with a biosphere included, are very complex and require so much computing power on available

  9. Precipitation sensitivity to autoconversion rate in a Numerical Weather Prediction model

    E-Print Network [OSTI]

    Marsham, John

    1 Precipitation sensitivity to autoconversion rate in a Numerical Weather Prediction model Céline;2 Summary Aerosols are known to significantly affect cloud and precipitation patterns and intensity. The impact of changing cloud droplet number concentration (CDNC), on cloud and precipitation evolution can

  10. Combining Weather Data for a Dataset Sufficient for Generating High-Resolution Weather Prediction Models

    SciTech Connect (OSTI)

    Fox, Jared B.; Ghan, Steven J.

    2004-03-01

    Assessments of the effects of climate change typically require information at scales of 10 km or less. In regions with complex terrain, much of the spatial variability in climate (temperature, precipitation, and snow water) occurs on scales below 10 km. Since the typical global climate model simulations grid size is more than 200 km, it is necessary to develop models with much higher resolution. Unfortunately, no datasets currently produced are both highly accurate and provide data at a sufficiently high resolution. As a result, current global climate models are forced to ignore the important climate variations that occur below the 200 km scale. This predicament prompted the creation of a global hybrid dataset with information for precipitation, temperature, and relative humidity. The resulting dataset illustrated the importance of having high-resolution datasets and gives clear proof that regions with complex terrain require a fine resolution grid to give an accurate represent at ion of their climatology. For example, the Andes Mountains in Chile cause a temperature shift of more than 25C within the same area as a single 2.5 grid cell from the NCEP dataset. Fortunately the CRU, U.D., GPCP, and NCEP datasets, when hybridized, are able to provide both precision and satisfactory resolution with global coverage. This composite will enable the development of both high-resolution models and quality empirical downscaling methods--both of which are necessary for scientists to more accurately predict the effects of global climate change. Without accurate long-term forecasts, climatologists and policy makers will not have the tools they need to effectively reduce the negative effects human activity have on the earth.

  11. Model predicts space weather and protects satellite hardware

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete7 AssessmentBusinessAlternativeModel Verification

  12. Evaluating Parameterizations in General Circulation Models: Climate Simulation Meets Weather Prediction

    SciTech Connect (OSTI)

    Phillips, T J; Potter, G L; Williamson, D L; Cederwall, R T; Boyle, J S; Fiorino, M; Hnilo, J J; Olson, J G; Xie, S; Yio, J J

    2004-05-06

    To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands that the GCM parameterizations of unresolved processes, in particular, should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provided that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by a realistically initialized climate GCM, and the application of six-hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be tested in the same framework. In order to further this method for evaluating and analyzing parameterizations in climate GCMs, the U.S. Department of Energy is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM.

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

    E-Print Network [OSTI]

    Heinemann, Detlev

    In countries showing high wind energy shares in the elec- trical power supply grid, a "wind power weatherThe Quality of a 48-Hours Wind Power Forecast Using the German and Danish Weather Prediction Model Laboratory, P.O. box 49, DK-4000 Roskilde, Tel/Fax: +45 4677 5095 / 5970 Gregor.Giebel@Risoe.DK Wind power

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

    E-Print Network [OSTI]

    G. Michalek; N. Gopalswamy; S. Yashiro

    2007-10-24

    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.

  15. 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.

    2014-06-01

    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.

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

    E-Print Network [OSTI]

    Kwak, Do Young

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

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

    E-Print Network [OSTI]

    Wehner, Michael; Oliker, Leonid; Shalf, John

    2008-01-01

    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

  18. Computational Models for Understanding Weather

    E-Print Network [OSTI]

    Muraki, David J.

    Computational Models for Understanding Weather Mathematics for Atmospheric Science http://weather-S migration Dutton Conway zonal jetstream in unstable weather 6 #12;Baroclinic Instability Vortices

  19. Discussion of long-range weather prediction

    SciTech Connect (OSTI)

    Canavan, G.H.

    1998-09-10

    A group of scientists at Los Alamos have held a series of discussions of the issues in and prospects for improvements in Long-range Weather Predictions Enabled by Proving of the Atmosphere at High Space-Time Resolution. The group contained the requisite skills for a full evaluation, although this report presents only an informal discussion of the main technical issues. The group discussed all aspects of the proposal, which are grouped below into the headings: (1) predictability; (2) sensors and satellites, (3) DIAL and atmospheric sensing; (4) localized transponders; and (5) summary and integration. Briefly, the group agreed that the relative paucity of observations of the state of the atmosphere severely inhibits the accuracy of weather forecasts, and any program that leads to a more dense and uniform observational network is welcome. As shown in Long-range Weather more dense and uniform observational network is welcome. As shown in Long-range Weather Predictions, the pay-back of accurate long-range forecasts should more than justify the expenditure associated with improved observations and forecast models required. The essential step is to show that the needed technologies are available for field test and space qualification.

  20. Predicting weather-related emergency blackspots

    E-Print Network [OSTI]

    Predicting weather-related emergency blackspots The STFC Hartree Centre's high-calibre data types of emergency occurring in specific places under specific weather conditions. Focusing initially on Hampshire, this solution ­ known as WUDoWUD (Weather You Do or Whether You Don't) ­ has clear potential

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

    E-Print Network [OSTI]

    Xue, Y; Fennessy, M; Sellers, P

    1996-01-01

    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,

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

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

  3. Downscaling Extended Weather Forecasts for Hydrologic Prediction

    SciTech Connect (OSTI)

    Leung, Lai-Yung R.; Qian, Yun

    2005-03-01

    Weather and climate forecasts are critical inputs to hydrologic forecasting systems. The National Center for Environmental Prediction (NCEP) issues 8-15 days outlook daily for the U.S. based on the Medium Range Forecast (MRF) model, which is a global model applied at about 2? spatial resolution. Because of the relatively coarse spatial resolution, weather forecasts produced by the MRF model cannot be applied directly to hydrologic forecasting models that require high spatial resolution to represent land surface hydrology. A mesoscale atmospheric model was used to dynamically downscale the 1-8 day extended global weather forecasts to test the feasibility of hydrologic forecasting through this model nesting approach. Atmospheric conditions of each 8-day forecast during the period 1990-2000 were used to provide initial and boundary conditions for the mesoscale model to produce an 8-day atmospheric forecast for the western U.S. at 30 km spatial resolution. To examine the impact of initialization of the land surface state on forecast skill, two sets of simulations were performed with the land surface state initialized based on the global forecasts versus land surface conditions from a continuous mesoscale simulation driven by the NCEP reanalysis. Comparison of the skill of the global and downscaled precipitation forecasts in the western U.S. showed higher skill for the downscaled forecasts at all precipitation thresholds and increasingly larger differences at the larger thresholds. Analyses of the surface temperature forecasts show that the mesoscale forecasts generally reduced the root-mean-square error by about 1.5 C compared to the global forecasts, because of the much better resolved topography at 30 km spatial resolution. In addition, initialization of the land surface states has large impacts on the temperature forecasts, but not the precipitation forecasts. The improvements in forecast skill using downscaling could be potentially significant for improving hydrologic forecasts for managing river basins.

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

    E-Print Network [OSTI]

    Jamieson, Bruce

    HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson and decision makers strongly rely on Numerical Weather Prediction (NWP) models, for example on the forecasted on forecasted precipitation. KEYWORDS: Numerical weather prediction models, validation, precipitation 1

  5. Space Weather Forecasting Identifying periodic block-structured models to predict

    E-Print Network [OSTI]

    lines, which can overwhelm and destroy transform- ers and electrical networks [2]. Figure 7 shows damage in the ionosphere. To predict these large ejections of magnetic and plasma energy, satellites monitor the solar past the Earth and the other planets in the form of the solar wind. The Sun's magnetic field, which

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of the WRF model solar irradiance forecasts in Andalusia (Beyer, H. , 2009.    Irradiance forecasting for the power dependent probabilistic irradiance  forecasts for coastal 

  7. Global weather prediction -Possible developments in the next decades -

    E-Print Network [OSTI]

    Begstsson, Lennart

    Global weather prediction -Possible developments in the next decades - Professor Lennart Bengtsson) It is by now almost fifty years since I first read L. F. Richardsons book ,,Weather prediction by numerical in weather and weather prediction I found the book all in all exciting, although quite a bit eccentric

  8. Predicting Weather Regime Transitions in Northern Hemisphere Datasets

    E-Print Network [OSTI]

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

    2011-01-01

    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

  9. Predicting Weather Regime Transitions in Northern Hemisphere Datasets

    E-Print Network [OSTI]

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

    2006-01-01

    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

  10. Predicting Weather Regime Transitions in Northern Hemisphere Datasets

    E-Print Network [OSTI]

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

    2006-01-01

    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

  11. Space Weather Prediction with Exascale Computing

    E-Print Network [OSTI]

    Lapenta, Giovanni

    2011-01-01

    Space weather refers to conditions on the Sun, in the interplanetary space and in the Earth space environment that can influence the performance and reliability of space-borne and ground-based technological systems and can endanger human life or health. Adverse conditions in the space environment can cause disruption of satellite operations, communications, navigation, and electric power distribution grids, leading to a variety of socioeconomic losses. The conditions in space are also linked to the Earth climate. The activity of the Sun affects the total amount of heat and light reaching the Earth and the amount of cosmic rays arriving in the atmosphere, a phenomenon linked with the amount of cloud cover and precipitation. Given these great impacts on society, space weather is attracting a growing attention and is the subject of international efforts worldwide. We focus here on the steps necessary for achieving a true physics-based ability to predict the arrival and consequences of major space weather storms....

  12. Weather regime prediction using statistical learning

    E-Print Network [OSTI]

    Deloncle, A.; Berk, Richard; D’Andrea, F.; Ghil, M.

    2005-01-01

    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

  13. Weather Regime Prediction Using Statistical Learning

    E-Print Network [OSTI]

    Deloncle, A.; Berk, Richard A.; D'Andrea, F.; Ghil, M.

    2005-01-01

    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

  14. Weather Regime Prediction Using Statistical Learning

    E-Print Network [OSTI]

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

    2011-01-01

    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

  15. A Deep Hybrid Model for Weather Forecasting Aditya Grover

    E-Print Network [OSTI]

    Horvitz, Eric

    @microsoft.com ABSTRACT Weather forecasting is a canonical predictive challenge that has depended primarily on model-based methods. We ex- plore new directions with forecasting weather as a data- intensive challenge that involves the joint statistics of a set of weather-related vari- ables. We show how the base model can be enhanced

  16. 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.

    2011-11-01

    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.

  17. 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

    2010-01-01

    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.

  18. Weather Forecasting -Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting - Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, "weather forecasts" are created such that selected wireless LAN performance indicators might be used to evaluate the effec- tiveness of individual weather forecasts. The paper evaluates six distinct weather

  19. Weather Forecasting Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting ­ Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, ``weather forecasts'' are created such that selected wireless LAN performance indicators might be used to evaluate the e#ec­ tiveness of individual weather forecasts. The paper evaluates six distinct weather

  20. 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 .................................................. 116 6.4 Numerical Weather Prediction Challenges and Requirements .......... 119 6.5 Summary The so-called mesoscale and convective scale weather events, including floods, tornadoes, hail, strong

  1. 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

    2009-01-01

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

  2. Quadratic hedging of weather and catastrophe risk by using short term climate predictions

    E-Print Network [OSTI]

    Imkeller, Peter

    Quadratic hedging of weather and catastrophe risk by using short term climate predictions Stefan 10099 Berlin Germany February 12, 2008 Abstract The extent to which catastrophic weather events occur into account in any reasonable management of weather related risk. In this paper we first set up a risk model

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

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

  4. 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

    2009-10-27

    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

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

    SciTech Connect (OSTI)

    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

    2009-10-27

    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.

  6. 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

    2009-01-01

    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.

  7. 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

    2011-01-01

    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.

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

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01

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

  9. A New Scheme for Predicting Fair-Weather Cumulus

    SciTech Connect (OSTI)

    Berg, Larry K.; Stull, Roland B.

    2007-04-01

    A new parameterization for boundary layer cumulus clouds, called the cumulus potential (CuP) scheme, is introduced. Unlike many other parameterizations, the CuP scheme explicitly links the fair-weather clouds to the boundary-layer turbulence and accounts for the non-local nature of the turbulence. This scheme uses joint probability density functions (JPDFs) of virtual potential temperature and water-vapor mixing ratio, as well as the mean vertical profiles of virtual potential temperature, to predict the amount and size distribution of boundary layer cloud cover. This model considers the diversity of air parcels over a heterogeneous surface, and recognizes that some parcels rise above their lifting condensation level to become cumulus, while other parcels might rise as clear updrafts. This model has several unique features: 1) surface heterogeneity and boundary-layer turbulence is represented using the boundary layer JPDF of virtual potential temperature versus water-vapor mixing ratio, 2) clear and cloudy thermals are allowed to coexist at the same altitude, and 3) a range of cloud-base heights, cloud-top heights, and cloud thicknesses are predicted within any one cloud field, as observed. Using data from Boundary Layer Experiment 1996 and a model intercomparsion study using large eddy simulation (LES) based on the Barbados Oceanographic and Meteorological Experiment (BOMEX), the CuP scheme is compared to three other cumulus parameterizations: one based on relative humidity, a statistical scheme based on the saturation deficit, and a slab model. It is shown that the CuP model does a better job predicting the cloud-base height and the cloud-top height than three other parameterizations. The model also shows promise in predicting cloud cover, and is found to give better cloud-cover estimates than the three other cumulus parameterizations. In ongoing work supported by the US Department of Energy¹s Atmospheric Radiation Measurement Program, the CuP scheme is being implemented in the Weather Research and Forecasting (WRF) model, in which it replaces the ad-hoc trigger function in an existing cumulus parameterization.

  10. Evaluation of the Weather Research and Forecasting Model on

    E-Print Network [OSTI]

    Basu, Sukanta

    are thus needed for precise assessment of wind resources, reliable prediction of power generation and robust design of wind turbines. However, mesoscale numerical weather prediction models face a chal- lenge: Implications for Wind Energy Brandon Storm*, Wind Science and Engineering Research Center, Texas Tech

  11. Regional weather modeling on parallel computers.

    SciTech Connect (OSTI)

    Baillie, C.; Michalakes, J.; Skalin, R.; Mathematics and Computer Science; NOAA Forecast Systems Lab.; Norwegian Meteorological Inst.

    1997-01-01

    This special issue on 'regional weather models' complements the October 1995 special issue on 'climate and weather modeling', which focused on global models. In this introduction we review the similarities and differences between regional and global atmospheric models. Next, the structure of regional models is described and we consider how the basic algorithms applied in these models influence the parallelization strategy. Finally, we give a brief overview of the eight articles in this issue and discuss some remaining challenges in the area of adapting regional weather models to parallel computers.

  12. A Fourier series model to predict hourly heating and cooling energy use in commercial buildings with outdoor temperature as the only weather variable

    SciTech Connect (OSTI)

    Dhar, A. [Enron Corp., Houston, TX (United States); Reddy, T.A. [Drexel Univ., Philadelphia, PA (United States). Civil and Architectural Engineering Dept.; Claridge, D.E. [Texas A and M Univ., College Station, TX (United States). Energy Systems Lab.

    1999-02-01

    Accurate modeling of hourly heating and cooling energy use in commercial buildings can be achieved by a Generalized Fourier Series (GFS) approach involving weather variables such as dry-bulb temperature, specific humidity and horizontal solar flux. However, there are situations when only temperature data is available. The objective of this paper is to (i) describe development of a variant of the GFS approach which allows modeling both heating and cooling hourly energy use in commercial buildings with outdoor temperature as the only weather variable and (ii) illustrate its application with monitored hourly data from several buildings in Texas. It is found that the new Temperature based Fourier Series (TFS) approach (1) provides better approximation to heating energy use than the existing GFS approach, (ii) can indirectly account for humidity and solar effects in the cooling energy use, (iii) offers physical insight into the operating pattern of a building HVAC system and (iv) can be used for diagnostic purposes.

  13. ADAPTIVE GRIDS IN WEATHER AND CLIMATE MODELING

    E-Print Network [OSTI]

    Jablonowski, Christiane

    ADAPTIVE GRIDS IN WEATHER AND CLIMATE MODELING by Christiane Jablonowski A dissertation submitted adaptive grid library that he wrote for his Ph.D. thesis in the Electrical Engineering and Computer Science as a postdoctoral researcher. In addition, thanks to Detlev Majewski from the German Weather Service DWD

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    Numerical Weather Prediction (NWP), Solar Forecasting  1.   to more accurate prediction of solar  irradiance, given a to create daily solar electricity predictions accurate to 

  15. A probabilistic approach to the prediction of area weather events, applied to precipitation

    E-Print Network [OSTI]

    Schmidt, Volker

    A probabilistic approach to the prediction of area weather events, applied to precipitation Bjoern in the context of estimating the probability of the meteorological event `occurrence of precipitation'. We treat roughly be interpreted as precipitation cells. The germ-grain model is completely characterized

  16. Weather

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

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

  17. The CCPP-ARM Parameterization Testbed (CAPT): Where Climate Simulation Meets Weather Prediction

    SciTech Connect (OSTI)

    Phillips, T J; Potter, G L; Williamson, D L; Cederwall, R T; Boyle, J S; Fiorino, M; Hnilo, J J; Olson, J G; Xie, S; Yio, J J

    2003-11-21

    To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands, in particular, that the GCM parameterizations of unresolved processes should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provied that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by realistically initialized climate GCM, and the application of six-hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be similarly tested. In order to further this method for evaluating and analyzing parameterizations in climate GCMs, the USDOE is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM. Numerical weather prediction methods show promise for improving parameterizations in climate GCMs.

  18. Where do Weather Forecasts and Climate Predictions Come From?

    E-Print Network [OSTI]

    Anderson, Charles W.

    on some aspect of the atmosphere. One sub-model is the solar flux model. Observations Prediction #12;3 The Solar Flux Model Public1.f Solar Flux Model The Public1.f Solar Flux Model is a Fortran program How do we get cloud properties from the spectrum BUT Cloud Observations #12;5 Inverting the Solar Flux

  19. System implementation for US Air Force Global Theater Weather Analysis and Prediction System (GTWAPS)

    SciTech Connect (OSTI)

    Simunich, K.L.; Pinkerton, S.C.; Michalakes, J.G.; Christiansen, J.H.

    1997-03-01

    The Global Theater Weather Analysis and Prediction System (GTWAPS) is intended to provide war fighters and decision makers with timely, accurate, and tailored meteorological and oceanographic (METOC) information to enhance effective employment of battlefield forces. Of critical importance to providing METOC theater information is the generation of meteorological parameters produced by numerical prediction models and application software at the Air Force Global Weather Central (AFGWC), Offutt Air Force Base, Nebraska. Ultimately, application-derived data will be produced by the regional Joint METOC Forecast Units and by the deployed teams within a theater. The USAF Air Staff contracted with Argonne National Laboratory (ANL) for assistance in defining a hardware and software solution using off-the-shelf technology that would give the USAF the flexibility of testing various meteorological models and the ability to use the system within their daily operational constraints.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    weather prediction solar irradiance forecasts in the US.2013: Review of solar irradiance forecasting methods and asatellite-derived irradiances: Description and validation.

  1. Adaptive Grids for Weather and Climate Models C. Jablonowski

    E-Print Network [OSTI]

    Stout, Quentin F.

    Adaptive Grids for Weather and Climate Models C. Jablonowski National Center for Atmospheric have been discussed in the literature. Nested-grid approaches are widely used at National Weather.: ADAPTIVE GRIDS FOR WEATHER AND CLIMATE MODELS two grids coincide. Other variable-resolution models

  2. Weather Forecasting Spring 2014

    E-Print Network [OSTI]

    Hennon, Christopher C.

    ATMS 350 Weather Forecasting Spring 2014 Professor : Dr. Chris Hennon Office : RRO 236C Phone : 232 of atmospheric physics and the ability to include this understanding into modern numerical weather prediction agencies, forecast tools, numerical weather prediction models, model output statistics, ensemble

  3. Environmental Physics Group Newsletter September 2013 Weather and Climate Modelling

    E-Print Network [OSTI]

    Williams, Paul

    Environmental Physics Group Newsletter September 2013 9 Weather and Climate Modelling Imperial and the Grantham Institute for Climate Change A half-day meeting on the topic of 'Should weather and climate increasingly common to represent subgrid-scale features in weather and climate models by including random noise

  4. Modeling Weather Impact on a Secondary Electrical Grid

    E-Print Network [OSTI]

    Wang, Dingquan

    Weather can cause problems for underground electrical grids by increasing the probability of serious “manhole events” such as fires and explosions. In this work, we compare a model that incorporates weather features ...

  5. 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

  6. Modeling Field-level Irrigation Demands with Changing Weather and Crop Choices

    E-Print Network [OSTI]

    MardanDoost, Babak

    2015-05-31

    . The presented water budget model is capable of estimate daily water demand over space and time under predicted climate and land-use change. The model-predicted irrigation demand was developed based on crop-specific evapotranspiration, weather data, and with 2007...

  7. ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS

    SciTech Connect (OSTI)

    Chiswell, S.; Buckley, R.

    2009-01-15

    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.

  8. Dynamic prediction of terminal-area severe convective weather penetration

    E-Print Network [OSTI]

    Schonfeld, Daniel (Daniel Ryan)

    2015-01-01

    Despite groundbreaking technology and revised operating procedures designed to improve the safety of air travel, numerous aviation accidents still occur every year. According to a recent report by the FAA's Aviation Weather ...

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

    SciTech Connect (OSTI)

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

    2012-08-15

    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.

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

    E-Print Network [OSTI]

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

    2014-05-11

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

  11. Stochastic Parameterization: Towards a new view of Weather and Climate Models

    E-Print Network [OSTI]

    Berner, Judith; Batte, Lauriane; De La Camara, Alvaro; Crommelin, Daan; Christensen, Hannah; Colangeli, Matteo; Dolaptchiev, Stamen; Franzke, Christian L E; Friederichs, Petra; Imkeller, Peter; Jarvinen, Heikki; Juricke, Stephan; Kitsios, Vassili; Lott, Franois; Lucarini, Valerio; Mahajan, Salil; Palmer, Timothy N; Penland, Cecile; Von Storch, Jin-Song; Sakradzija, Mirjana; Weniger, Michael; Weisheimer, Antje; Williams, Paul D; Yano, Jun-Ichi

    2015-01-01

    The last decade has seen the success of stochastic parameterizations in short-term, medium-range and seasonal ensembles: operational weather centers now routinely use stochastic parameterization schemes to better represent model inadequacy and improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides more skillful estimates of uncertainty, but is also extremely promising for reducing longstanding climate biases and relevant for determining the climate response to forcings such as e.g., an increase of CO2. This article highlights recent results from different research groups which show that the stochastic representation of unresolved processes in the atmosphere, oceans, land surface and cryosphere of comprehensive weather and climate models a) gives rise to more reliable probabilistic forecasts of weather and climate and b) reduces systematic model bias. We make a case that the use of mathematically ...

  12. 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

  13. ASSESSING THE UNCERTAINTY OF WIND POWER PREDICTIONS WITH REGARD TO SPECIFIC WEATHER SITUATIONS

    E-Print Network [OSTI]

    Heinemann, Detlev

    The growing share of wind energy in electrical grids de- mands new strategies to improve the integrationASSESSING THE UNCERTAINTY OF WIND POWER PREDICTIONS WITH REGARD TO SPECIFIC WEATHER SITUATIONS.lange@mail.uni-oldenburg.de, www.physik.uni-oldenburg.de/ehf The uncertainty of a short term wind power prediction is commonly

  14. Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia

    E-Print Network [OSTI]

    Evans, Jason

    Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south, Australia. D Corresponding author. Email: h.clarke@student.unsw.edu.au Abstract. The fire weather of south of the McArthur Forest Fire Danger Index (FFDI) using probability density function skill scores, annual

  15. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired SolarAbout /Two0Photos and Videos/01/2012 Page| National NuclearWeather

  16. Nonlinear Dynamics and Chaos: Applications for Prediction of Weather and Climate

    E-Print Network [OSTI]

    J. S. Pethkar; A. M. Selvam

    2001-04-19

    Turbulence, namely, irregular fluctuations in space and time characterize fluid flows in general and atmospheric flows in particular.The irregular,i.e., nonlinear space-time fluctuations on all scales contribute to the unpredictable nature of both short-term weather and long-term climate.It is of importance to quantify the total pattern of fluctuations for predictability studies. The power spectra of temporal fluctuations are broadband and exhibit inverse power law form with different slopes for different scale ranges. Inverse power-law form for power spectra implies scaling (self similarity) for the scale range over which the slope is constant. Atmospheric flows therefore exhibit multiple scaling or multifractal structure.Standard meteorological theory cannot explain satisfactorily the observed multifractal structure of atmospheric flows.Selfsimilar spatial pattern implies long-range spatial correlations. Atmospheric flows therefore exhibit long-range spatiotemporal correlations, namely,self-organized criticality,signifying order underlying apparent chaos. A recently developed non-deterministic cell dynamical system model for atmospheric flows predicts the observed self-organized criticality as intrinsic to quantumlike mechanics governing flow dynamics.The model predictions are in agreement with continuous periodogram spectral analysis of meteorological data sets.

  17. 1944 IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 28, NO. 6, DECEMBER 2000 System Identification, Modeling, and Prediction for

    E-Print Network [OSTI]

    Vassiliadis, Dimitrios

    , Modeling, and Prediction for Space Weather Environments Dimitris Vassiliadis Abstract--By now nonlinear dynamical models and neural net- works have been used to predict and model a wide variety of space weather. These developments have prompted the establishment of national space weather programs in the U.S. [21], [22

  18. Resolution dependence in modeling extreme weather events.

    SciTech Connect (OSTI)

    Taylor, J.; Larson, J.

    2001-04-13

    At Argonne National Laboratory we have developed a high performance regional climate modeling simulation capability based on the NCAR MM5v3.4. The regional climate simulation system at Argonne currently includes a Java-based interface to allow rapid selection and generation of initial and boundary conditions, a high-performance version of MM5v3.4 modified for long climate simulations on our 512-processor Beowulf cluster (Chiba City), an interactive Web-based analysis tool to facilitate analysis and collaboration via the Web, and an enhanced version of the CAVE5d software capable of working with large climate data sets. In this paper we describe the application of this modeling system to investigate the role of model resolution in predicting extreme events such as the ''Hurricane Huron'' event of 11-15 September 1996. We have performed a series of ''Hurricane Huron'' experiments at 80, 40, 20, and 10 km grid resolution over an identical spatiotemporal domain. We conclude that increasing model resolution leads to dramatic changes in the vertical structure of the simulated atmosphere producing significantly different representations of rainfall and other parameters critical to the assessment of impacts of climate change.

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

    E-Print Network [OSTI]

    Droegemeier, Kelvin K.

    ) and of real radar data by Dowell et al. (2003). All three studies used the same anelastic cloud model of Sun

  20. 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

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

    E-Print Network [OSTI]

    Knievel, Jason Clark

    Temporal Changes in Wind as Objects for Evaluating Mesoscale Numerical Weather Prediction DARAN L changes in simulated and observed 10-m (AGL) winds. The method is demon- strated on a 1-yr collection of 1-day simulations by the fifth-generation Pennsylvania State University­ National Center for Atmospheric

  2. Implementation of the Immersed Boundary Method in the Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, K A

    2006-12-07

    Accurate simulations of atmospheric boundary layer flow are vital for predicting dispersion of contaminant releases, particularly in densely populated urban regions where first responders must react within minutes and the consequences of forecast errors are potentially disastrous. Current mesoscale models do not account for urban effects, and conversely urban scale models do not account for mesoscale weather features or atmospheric physics. The ultimate goal of this research is to develop and implement an immersed boundary method (IBM) along with a surface roughness parameterization into the mesoscale Weather Research and Forecasting (WRF) model. IBM will be used in WRF to represent the complex boundary conditions imposed by urban landscapes, while still including forcing from regional weather patterns and atmospheric physics. This document details preliminary results of this research, including the details of three distinct implementations of the immersed boundary method. Results for the three methods are presented for the case of a rotation influenced neutral atmospheric boundary layer over flat terrain.

  3. Evaluating climate models: Should we use weather or climate observations?

    SciTech Connect (OSTI)

    Oglesby, Robert J [ORNL; Erickson III, David J [ORNL

    2009-12-01

    Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their ability to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.

  4. Long-range weather prediction and prevention of climate catastrophes: a status report

    SciTech Connect (OSTI)

    Caldeira, K; Caravan, G; Govindasamy, B; Grossman, A; Hyde, R; Ishikawa, M; Ledebuhr, A; Leith, C; Molenkamp, C; Teller, E; Wood, L

    1999-08-18

    As the human population of Earth continues to expand and to demand an ever-higher quality-of-life, requirements for ever-greater knowledge--and then control--of the future of the state of the terrestrial biosphere grow apace. Convenience of living--and, indeed, reliability of life itself--become ever more highly ''tuned'' to the future physical condition of the biosphere being knowable and not markedly different than the present one, Two years ago, we reported at a quantitative albeit conceptual level on technical ways-and-means of forestalling large-scale changes in the present climate, employing practical means of modulating insolation and/or the Earth's mean albedo. Last year, we reported on early work aimed at developing means for creating detailed, high-fidelity, all-Earth weather forecasts of two weeks duration, exploiting recent and anticipated advances in extremely high-performance digital computing and in atmosphere-observing Earth satellites bearing high-technology instrumentation. This year, we report on recent progress in both of these areas of endeavor. Preventing the commencement of large-scale changes in the current climate presently appears to be a considerably more interesting prospect than initially realized, as modest insolation reductions are model-predicted to offset the anticipated impacts of ''global warming'' surprisingly precisely, in both space and time. Also, continued study has not revealed any fundamental difficulties in any of the means proposed for insolation modulation and, indeed, applicability of some of these techniques to other planets in the inner Solar system seems promising. Implementation of the high-fidelity, long-range weather-forecasting capability presently appears substantially easier with respect to required populations of Earth satellites and atmospheric transponders and data-processing systems, and more complicated with respect to transponder lifetimes in the actual atmosphere; overall, the enterprise seems more technically feasible than originally anticipated.

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

    E-Print Network [OSTI]

    T. E. Girish; G. Gopkumar

    2010-11-21

    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 (Rsolar dynamo, space weather, predictions,cycle 24

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

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2010-01-01

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

  7. Monthly Weather Review EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    Monthly Weather Review EARLY ONLINE RELEASE This is a preliminary PDF of the author into numerical weather4 prediction models can improve precipitation forecasts and extend prediction capabilities5 that assimilates precipitation-affected microwave radiances into the7 Weather Research and Forecasting (WRF) model

  8. Long Range Weather Prediction III: Miniaturized Distributed Sensors for Global Atmospheric Measurements

    SciTech Connect (OSTI)

    Teller, E; Leith, C; Canavan, G; Wood, L

    2001-11-13

    We continue consideration of ways-and-means for creating, in an evolutionary, ever-more-powerful manner, a continually-updated data-base of salient atmospheric properties sufficient for finite differenced integration-based, high-fidelity weather prediction over intervals of 2-3 weeks, leveraging the 10{sup 14} FLOPS digital computing systems now coming into existence. A constellation comprised of 10{sup 6}-10{sup 9} small atmospheric sampling systems--high-tech superpressure balloons carrying early 21st century semiconductor devices, drifting with the local winds over the meteorological spectrum of pressure-altitudes--that assays all portions of the troposphere and lower stratosphere remains the central feature of the proposed system. We suggest that these devices should be active-signaling, rather than passive-transponding, as we had previously proposed only for the ground- and aquatic-situated sensors of this system. Instead of periodic interrogation of the intra-atmospheric transponder population by a constellation of sophisticated small satellites in low Earth orbit, we now propose to retrieve information from the instrumented balloon constellation by existing satellite telephony systems, acting as cellular tower-nodes in a global cellular telephony system whose ''user-set'' is the atmospheric-sampling and surface-level monitoring constellations. We thereby leverage the huge investment in cellular (satellite) telephony and GPS technologies, with large technical and economic gains. This proposal minimizes sponsor forward commitment along its entire programmatic trajectory, and moreover may return data of weather-predictive value soon after field activities commence. We emphasize its high near-term value for making better mesoscale, relatively short-term weather predictions with computing-intensive means, and its great long-term utility in enhancing the meteorological basis for global change predictive studies. We again note that adverse impacts of weather involve continuing costs of the order of 1% of GDP, a large fraction of which could be retrieved if high-fidelity predictions of two weeks forward applicability were available. These {approx}$10{sup 2} B annual savings dwarf the <$1 B costs of operating a rational, long-range weather prediction system of the type proposed.

  9. Coupled Weather and Wildfire Behavior Modeling at Los Alamos: An Overview

    SciTech Connect (OSTI)

    Bossert, James E.; Harlow, Francis H.; Linn, Rodman R.; Reisner, Jon M.; White, Andrew B.; Winterkamp, Judith L.

    1997-12-31

    Over the past two years, researchers at Los Alamos National Laboratory (LANL) have been engaged in coupled weather/wildfire modeling as part of a broader initiative to predict the unfolding of crisis events. Wildfire prediction was chosen for the following reasons: (1) few physics-based wild-fire prediction models presently exist; (2) LANL has expertise in the fields required to develop such a capability; and (3) the development of this predictive capability would be enhanced by LANL`s strength in high performance computing. Wildfire behavior models have historically been used to predict fire spread and heat release for a prescribed set of fuel, slope, and wind conditions (Andrews 1986). In the vicinity of a fire, however, atmospheric conditions are constantly changing due to non-local weather influences and the intense heat of the fire itself. This non- linear process underscores the need for physics-based models that treat the atmosphere-fire feedback. Actual wildfire prediction with full-physics models is both time-critical and computationally demanding, since it must include regional- to local-scale weather forecasting together with the capability to accurately simulate both intense gradients across a fireline, and atmosphere/fire/fuel interactions. Los Alamos has recently (January 1997) acquired a number of SGI/Cray Origin 2000 machines, each presently having 32 to 64 processors. These high performance computing systems are part of the Department of Energy`s Accelerated Strategic Computing Initiative (ASCI). While offering impressive performance now, upgrades to the system promise to deliver over 1 Teraflop (10(12) floating point operations per second) at peak performance before the turn of the century.

  10. Design of a next-generation regional weather research and forecast model.

    SciTech Connect (OSTI)

    Michalakes, J.

    1999-01-13

    The Weather Research and Forecast (WRF) model is a new model development effort undertaken jointly by the National Center for Atmospheric Research (NCAR), the National Oceanic and Atmospheric Administration (NOAA), and a number of collaborating institutions and university scientists. The model is intended for use by operational NWP and university research communities, providing a common framework for idealized dynamical studies, fill physics numerical weather prediction, air-quality simulation, and regional climate. It will eventually supersede large, well-established but aging regional models now maintained by the participating institutions. The WRF effort includes re-engineering the underlying software architecture to produce a modular, flexible code designed from the outset to provide portable performance across diverse computing architectures. This paper outlines key elements of the WRF software design.

  11. USE OF A STOCHASTIC WEATHER GENERATOR IN A WATERSHED MODEL FOR STREAMFLOW SIMULATION

    E-Print Network [OSTI]

    USE OF A STOCHASTIC WEATHER GENERATOR IN A WATERSHED MODEL FOR STREAMFLOW SIMULATION by ADAM N OF A STOCHASTIC WEATHER GENERATOR IN A WATERSHED MODEL FOR STREAMFLOW SIMULATION written by Adam N. Hobson has and Architectural Engineering) Use of a Stochastic Weather Generator in a Watershed Model for Streamflow Simulation

  12. ESTIMATING POTENTIAL SEVERE WEATHER SOCIETAL IMPACTS USING PROBABILISTIC FORECASTS ISSUED BY THE NWS STORM PREDICTION CENTER

    E-Print Network [OSTI]

    effort to estimate potential severe weather societal impacts based on a combination of probabilistic forecasts and high resolution population data. For equal severe weather threat, events that occur over1 ESTIMATING POTENTIAL SEVERE WEATHER SOCIETAL IMPACTS USING PROBABILISTIC FORECASTS ISSUED

  13. Predicting yearly energy savings using BIN weather data with heat-pipe heat exchangers

    SciTech Connect (OSTI)

    Mathur, G.D. [Zexel USA Corp., Decatur, IL (United States)

    1997-12-31

    In an earlier paper, the author had investigated the impact that a heat pipe heat exchanger (HPHE) has on the energy consumption and the peak demand on an existing air conditioning system. A detailed performance investigation was carried out for a number of cities for year round operation of the HVAC system with HPHE. Heating degree days and cooling hours were used for predicting the energy savings with the HPHE. In order to calculate the true energy savings, a more realistic approach is to use the BIN weather data. The author has developed a simulation program that can predict the energy savings by using the BIN weather data. The investigation has been carried out for 33 US cities with widely different climactic conditions and the results are presented in this paper. Economic analysis reveals that a simple retrofit on an existing HVAC system can pay for itself in less than a year. Based on this investigation, it is recommended that electric utilities use this technology as a demand side management strategy for reducing energy and peak demand.

  14. A Kernel-Based Spatio-Temporal Dynamical Model for Nowcasting Weather Radar Reflectivities

    E-Print Network [OSTI]

    A Kernel-Based Spatio-Temporal Dynamical Model for Nowcasting Weather Radar Reflectivities Ke Xu of the technique and its potential for nowcasting weather radar reflectivities. Key Words: Bayesian, dilation to nowcasting weather radar reflectivities into two general categories. The first is the use of simple

  15. Application of a new phenomenological coronal mass ejection model to space weather forecasting

    E-Print Network [OSTI]

    Howard, Tim

    to space weather forecasting T. A. Howard1 and S. J. Tappin2 Received 15 October 2009; revised 27 April with the Earth. Hence the model can be used for space weather forecasting. We present a preliminary evaluation to fully validate it for integration with existing tools for space weather forecasting. Citation: Howard, T

  16. How GIS and fire indices can be used in developing a fire prediction model for Scotland 

    E-Print Network [OSTI]

    MacKinnon, Frances

    2008-12-05

    This project looks at how GIS and the six fire indices from the Canadian Forest Fire Weather Index System (FWI) could be used to aid in developing a fire prediction model for Scotland. Information on land cover type, ...

  17. Edwards, Paul N. 2013. "Predicting the Weather: A Knowledge Commons for Europe and the World," in Cornelis Disco & Eda Kranakis (eds), Cosmopolitan

    E-Print Network [OSTI]

    Edwards, Paul N.

    Edwards, Paul N. 2013. "Predicting the Weather: A Knowledge Commons for Europe and the World Press: Cambridge, MA), pp. 155-184. #12;Weather affects virtually everything people do: where of temperature. Weather affects agriculture, urban planning, government, insurance, and much else. It even gets

  18. 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 ...

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

    E-Print Network [OSTI]

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

    2013-01-01

    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, ...

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    electric grid. Chapter 2 Marine Layer Meteorology 2.1 Marine Layer Stratocumulus Overview In coastal California, the dominant weather

  1. Comparison of the prediction accuracy of daily and monthly regression models for energy consumption in commercial buildings 

    E-Print Network [OSTI]

    Wang, Jinrong

    1996-01-01

    -retrofit weather is generally different from the weather used for model development, the prediction error of the baseline model may be different from the fitting error. Daily and monthly baseline models were developed for a midsize commercial building with (i) dual...

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

    E-Print Network [OSTI]

    Raftery, Adrian

    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

  3. A baseline model for utility bill analysis using both weather and non-weather-related variables

    SciTech Connect (OSTI)

    Sonderegger, R.C. [SRC Systems, Inc., Berkeley, CA (United States)

    1998-12-31

    Many utility bill analyses in the literature rely only on weather-based correlations. While often the dominant cause of seasonal variations in utility consumption, weather variables are far from the only determinant factors. Vacation shutdowns, plug creep, changes in building operation and square footage, and plain poor correlation are all too familiar to the practicing performance contractor. This paper presents a generalized baseline equation, consistent with prior results by others but extended to include other, non-weather-related independent variables. Its compatibility with extensive prior research by others is shown, as well as its application to several types of facilities. The baseline equation, as presented, can accommodate up to five simultaneous independent variables for a maximum of eight free parameters. The use of two additional, empirical degree-day threshold parameters is also discussed. The baseline equation presented here is at the base of a commercial utility accounting software program. All case studies presented to illustrate the development of the baseline equation for each facility are drawn from real-life studies performed by users of this program.

  4. Development and initial application of a sub-grid scale plume treatment in a state-of-the-art online Multi-scale Air Quality and Weather Prediction Model

    E-Print Network [OSTI]

    Zhang, Yang

    grid models applies to both "off- line" models, in which externally derived meteorology is usedDevelopment and initial application of a sub-grid scale plume treatment in a state of plume-in-grid (PinG) treatment in online-coupled WRF/Chem. grid

  5. 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 Laboratory (NSSL), the Storm Prediction Center (SPC), and the NWS Oklahoma City/Norman Weather Forecast

  6. Lateral boundary errors in regional numerical weather

    E-Print Network [OSTI]

    ?umer, Slobodan

    Lateral boundary errors in regional numerical weather prediction models Author: Ana Car Advisor, they describe evolution of atmospher - weather forecast. Every NWP model solves the same system of equations (1: assoc. prof. dr. Nedjeljka Zagar January 5, 2015 Abstract Regional models are used in many national

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    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.

  8. 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

  9. 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

  10. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Reiter, Ehud

    summarisation. We found three alternative ways in which we could model data summarisation. One approach is based turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from

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

    SciTech Connect (OSTI)

    Auffhammer, Maximilian; Hsiang, Solomon M.; Schlenker, Wolfram; Sobel, Adam H.

    2013-06-28

    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.

  12. Interactive Weather Simulation and Visualization on a Display Wall

    E-Print Network [OSTI]

    Ha, Phuong H.

    Interactive Weather Simulation and Visualization on a Display Wall with Many-Core Compute Nodes B.hoai.ha,john.markus.bjorndalen,otto.anshus}@uit.no, {tormsh,daniels}@cs.uit.no Abstract. Numerical Weather Prediction models (NWP) used for op- erational weather forecasting are typically run at predetermined times at a predetermined resolution and a fixed

  13. Predictability of PV power grid performance on insular sites without weather stations: use of artificial neural networks

    E-Print Network [OSTI]

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

    2009-01-01

    The official meteorological network is poor on the island of Corsica: only three sites being about 50 km apart are equipped with pyranometers which enable measurements by hourly and daily step. These sites are Ajaccio (seaside), Bastia (seaside) and Corte (average altitude of 486 meters). This lack of weather station makes difficult the predictability of PV power grid performance. This work intends to study a methodology which can predict global solar irradiation using data available from another location for daily and hourly horizon. In order to achieve this prediction, we have used Artificial Neural Network which is a popular artificial intelligence technique in the forecasting domain. A simulator has been obtained using data available for the station of Ajaccio that is the only station for which we have a lot of data: 16 years from 1972 to 1987. Then we have tested the efficiency of this simulator in two places with different geographical features: Corte, a mountainous region and Bastia, a coastal region. ...

  14. Effect of Weather on the Predicted PMN Landmine Chemical Signature for Kabul, Afghanistan

    SciTech Connect (OSTI)

    WEBB, STEPHEN W.; PHELAN, JAMES M.

    2002-11-01

    Buried landmines are often detected through the chemical signature in the air above the soil surface by mine detection dogs. Environmental processes play a significant role in the chemical signature available for detection. Due to the shallow burial depth of landmines, the weather influences the release of chemicals from the landmine, transport through the soil to the surface, and degradation processes in the soil. The effect of weather on the landmine chemical signature from a PMN landmine was evaluated with the T2TNT code for Kabul, Afghanistan. Results for TNT and DNT gas-phase and soil solid-phase concentrations are presented as a function of time of the day and time of the year.

  15. Atmospheric test models and numerical experiments for the simulation of the global distribution of weather data transponders

    SciTech Connect (OSTI)

    Grossman, A; Molenkamp, C R

    1999-08-25

    A proposal has been made to establish a high density global network of atmospheric micro transponders to record time, temperature, and wind data with time resolution of {le} 1 minute, temperature accuracy of {+-} 1 K, spatial resolution no poorer than {approx}3km horizontally and {approx}0.1km vertically, and 2-D speed accuracy of {le} 1m/s. This data will be used in conjunction with advanced numerical weather prediction models to provide increases in the reliability of long range weather forecasts. Major advances in data collection technology will be required to provide the proposed high-resolution data collection network. Systems studies must be undertaken to determine insertion requirements, spacing, and evolution of the transponder ensemble, which will be used to collect the data. Numerical models which provide realistic global weather pattern simulations must be utilized in order to perform these studies. A global circulation model with a 3{sup o} horizontal resolution has been used for initial simulations of the generation and evolution of transponder distributions. These studies indicate that reasonable global coverage of transponders can be achieved by a launch scenario consisting of the sequential launch of transponders at specified heights from a globally distributed set of launch sites.

  16. Development of an Immersed Boundary Method to Resolve Complex Terrain in the Weather Research and Forecasting Model

    SciTech Connect (OSTI)

    Lunquist, K A; Chow, F K; Lundquist, J K; Mirocha, J D

    2007-09-04

    Flow and dispersion processes in urban areas are profoundly influenced by the presence of buildings which divert mean flow, affect surface heating and cooling, and alter the structure of turbulence in the lower atmosphere. Accurate prediction of velocity, temperature, and turbulent kinetic energy fields are necessary for determining the transport and dispersion of scalars. Correct predictions of scalar concentrations are vital in densely populated urban areas where they are used to aid in emergency response planning for accidental or intentional releases of hazardous substances. Traditionally, urban flow simulations have been performed by computational fluid dynamics (CFD) codes which can accommodate the geometric complexity inherent to urban landscapes. In these types of models the grid is aligned with the solid boundaries, and the boundary conditions are applied to the computational nodes coincident with the surface. If the CFD code uses a structured curvilinear mesh, then time-consuming manual manipulation is needed to ensure that the mesh conforms to the solid boundaries while minimizing skewness. If the CFD code uses an unstructured grid, then the solver cannot be optimized for the underlying data structure which takes an irregular form. Unstructured solvers are therefore often slower and more memory intensive than their structured counterparts. Additionally, urban-scale CFD models are often forced at lateral boundaries with idealized flow, neglecting dynamic forcing due to synoptic scale weather patterns. These CFD codes solve the incompressible Navier-Stokes equations and include limited options for representing atmospheric processes such as surface fluxes and moisture. Traditional CFD codes therefore posses several drawbacks, due to the expense of either creating the grid or solving the resulting algebraic system of equations, and due to the idealized boundary conditions and the lack of full atmospheric physics. Meso-scale atmospheric boundary layer simulations, on the other hand, are performed by numerical weather prediction (NWP) codes, which cannot handle the geometry of the urban landscape, but do provide a more complete representation of atmospheric physics. NWP codes typically use structured grids with terrain-following vertical coordinates, include a full suite of atmospheric physics parameterizations, and allow for dynamic synoptic scale lateral forcing through grid nesting. Terrain following grids are unsuitable for urban terrain, as steep terrain gradients cause extreme distortion of the computational cells. In this work, we introduce and develop an immersed boundary method (IBM) to allow the favorable properties of a numerical weather prediction code to be combined with the ability to handle complex terrain. IBM uses a non-conforming structured grid, and allows solid boundaries to pass through the computational cells. As the terrain passes through the mesh in an arbitrary manner, the main goal of the IBM is to apply the boundary condition on the interior of the domain as accurately as possible. With the implementation of the IBM, numerical weather prediction codes can be used to explicitly resolve urban terrain. Heterogeneous urban domains using the IBM can be nested into larger mesoscale domains using a terrain-following coordinate. The larger mesoscale domain provides lateral boundary conditions to the urban domain with the correct forcing, allowing seamless integration between mesoscale and urban scale models. Further discussion of the scope of this project is given by Lundquist et al. [2007]. The current paper describes the implementation of an IBM into the Weather Research and Forecasting (WRF) model, which is an open source numerical weather prediction code. The WRF model solves the non-hydrostatic compressible Navier-Stokes equations, and employs an isobaric terrain-following vertical coordinate. Many types of IB methods have been developed by researchers; a comprehensive review can be found in Mittal and Iaccarino [2005]. To the authors knowledge, this is the first IBM approach that is able to

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

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

  18. 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

    2012-06-01

    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 presented as powerful tools that distill complex datasets into concise statements on likely impact, and as highly effective communication devices. Capsule: "Combining dynamical modeling of high-impact weather using traditional regional climate models with statistical techniques allows for comprehensive sampling of the full distribution, uncertainty estimation, direct assessment of impacts, and increased confidence in future changes."

  19. Model Predictive Control for Energy Efficient Buildings

    E-Print Network [OSTI]

    Ma, Yudong

    2012-01-01

    Model Predictive Control and Thermal Storage: a Simple 3.3of Building Thermal Storage”. In: ASHRAE Transactions 96.2 (and Passive Building Thermal Storage”. In: International

  20. Predictability of PV power grid performance on insular sites without weather stations: use of artificial neural networks

    E-Print Network [OSTI]

    Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure; Poggi, Philippe; Haurant, P; 10.4229/24thEUPVSEC2009-5BV.2.35

    2010-01-01

    The official meteorological network is poor on the island of Corsica: only three sites being about 50 km apart are equipped with pyranometers which enable measurements by hourly and daily step. These sites are Ajaccio (41\\degree 55'N and 8\\degree 48'E, seaside), Bastia (42\\degree 33'N, 9\\degree 29'E, seaside) and Corte (42\\degree 30'N, 9\\degree 15'E average altitude of 486 meters). This lack of weather station makes difficult the predictability of PV power grid performance. This work intends to study a methodology which can predict global solar irradiation using data available from another location for daily and hourly horizon. In order to achieve this prediction, we have used Artificial Neural Network which is a popular artificial intelligence technique in the forecasting domain. A simulator has been obtained using data available for the station of Ajaccio that is the only station for which we have a lot of data: 16 years from 1972 to 1987. Then we have tested the efficiency of this simulator in two places w...

  1. Weather Data Gamification 

    E-Print Network [OSTI]

    Gargate, Rohit

    2013-07-25

    . With the huge amount of weather data available, we have designed and developed a fantasy weather game. People manage a team of cities with the goal of predicting weather better than other players in their league, and in the process gain an understanding...

  2. Sun-to-thermosphere simulation of the 28--30 October 2003 storm with the Space Weather Modeling Framework

    E-Print Network [OSTI]

    De Zeeuw, Darren L.

    pipelines, and the electric power grid have all become facts of life; however, they all rely on technologiesSun-to-thermosphere simulation of the 28--30 October 2003 storm with the Space Weather Modeling was carried out with the newly developed Space Weather Modeling Framework (SWMF, see http

  3. Development and initial application of the global-through-urban weather research and forecasting model with chemistry

    E-Print Network [OSTI]

    Zhang, Yang

    Development and initial application of the global-through-urban weather research and forecasting application of the global-through-urban weather research and forecasting model with chemistry (GU-WRF/Chem), J. In this work, a global-through-urban WRF/Chem model (i.e., GU-WRF/Chem) has been developed to provide

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

    SciTech Connect (OSTI)

    Wehner, Michael; Oliker, Leonid; Shalf, John

    2007-01-01

    We present a speculative extrapolation of the performance aspects of an atmospheric general circulation model to ultra-high resolution and describe alternative technological paths to realize integration of such a model in the relatively near future. Due to a superlinear scaling of the computational burden dictated by stability criterion, the solution of the equations of motion dominate the calculation at ultra-high resolutions. From this extrapolation, it is estimated that a credible kilometer scale atmospheric model would require at least a sustained ten petaflop computer to provide scientifically useful climate simulations. Our design study portends an alternate strategy for practical power-efficient implementations of petaflop scale systems. Embedded processor technology could be exploited to tailor a custom machine designed to ultra-high climate model specifications at relatively affordable cost and power considerations. The major conceptual changes required by a kilometer scale climate model are certain to be difficult to implement. Although the hardware, software, and algorithms are all equally critical in conducting ultra-high climate resolution studies, it is likely that the necessary petaflop computing technology will be available in advance of a credible kilometer scale climate model.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

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

  6. The use of imprecise processing to improve accuracy in weather and climate prediction

    SciTech Connect (OSTI)

    Düben, Peter D.; McNamara, Hugh; Palmer, T.N.

    2014-08-15

    The use of stochastic processing hardware and low precision arithmetic in atmospheric models is investigated. Stochastic processors allow hardware-induced faults in calculations, sacrificing bit-reproducibility and precision in exchange for improvements in performance and potentially accuracy of forecasts, due to a reduction in power consumption that could allow higher resolution. A similar trade-off is achieved using low precision arithmetic, with improvements in computation and communication speed and savings in storage and memory requirements. As high-performance computing becomes more massively parallel and power intensive, these two approaches may be important stepping stones in the pursuit of global cloud-resolving atmospheric modelling. The impact of both hardware induced faults and low precision arithmetic is tested using the Lorenz '96 model and the dynamical core of a global atmosphere model. In the Lorenz '96 model there is a natural scale separation; the spectral discretisation used in the dynamical core also allows large and small scale dynamics to be treated separately within the code. Such scale separation allows the impact of lower-accuracy arithmetic to be restricted to components close to the truncation scales and hence close to the necessarily inexact parametrised representations of unresolved processes. By contrast, the larger scales are calculated using high precision deterministic arithmetic. Hardware faults from stochastic processors are emulated using a bit-flip model with different fault rates. Our simulations show that both approaches to inexact calculations do not substantially affect the large scale behaviour, provided they are restricted to act only on smaller scales. By contrast, results from the Lorenz '96 simulations are superior when small scales are calculated on an emulated stochastic processor than when those small scales are parametrised. This suggests that inexact calculations at the small scale could reduce computation and power costs without adversely affecting the quality of the simulations. This would allow higher resolution models to be run at the same computational cost.

  7. 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

  8. Model Predictive Control for Energy Efficient Buildings

    E-Print Network [OSTI]

    Ma, Yudong

    2012-01-01

    solar radiation, occupancy, and electrical devices in the buildings as a function of weather information, time, and date.solar radiation, occupancy, and electrical devices in the buildings as a function of weather information, time, and date.

  9. 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

    2013-10-19

    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.

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

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01

    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/

  11. 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.

    2009-07-15

    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.

  12. Severe Weather on the Web: Computer Lab for WEST Severe Weather Module

    E-Print Network [OSTI]

    Jiang, Haiyan

    Severe Weather on the Web: Computer Lab for WEST Severe Weather Module Summary: Students Weather Service-- National Weather Hazards Website: http://www.weather.gov/view/largemap.php --This termforecasts in the lower 48 USstates. Definitions Forecast--The prediction of what the weather

  13. HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

    SciTech Connect (OSTI)

    Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin; Pereira, Jose M.; Hurtt, George C.

    2015-01-01

    Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spread over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.

  14. Incorporation of 3D Shortwave Radiative Effects within the Weather Research and Forecasting Model

    SciTech Connect (OSTI)

    O'Hirok, W.; Ricchiazzi, P.; Gautier, C.

    2005-03-18

    A principal goal of the Atmospheric Radiation Measurement (ARM) Program is to understand the 3D cloud-radiation problem from scales ranging from the local to the size of global climate model (GCM) grid squares. For climate models using typical cloud overlap schemes, 3D radiative effects are minimal for all but the most complicated cloud fields. However, with the introduction of ''superparameterization'' methods, where sub-grid cloud processes are accounted for by embedding high resolution 2D cloud system resolving models within a GCM grid cell, the impact of 3D radiative effects on the local scale becomes increasingly relevant (Randall et al. 2003). In a recent study, we examined this issue by comparing the heating rates produced from a 3D and 1D shortwave radiative transfer model for a variety of radar derived cloud fields (O'Hirok and Gautier 2005). As demonstrated in Figure 1, the heating rate differences for a large convective field can be significant where 3D effects produce areas o f intense local heating. This finding, however, does not address the more important question of whether 3D radiative effects can alter the dynamics and structure of a cloud field. To investigate that issue we have incorporated a 3D radiative transfer algorithm into the Weather Research and Forecasting (WRF) model. Here, we present very preliminary findings of a comparison between cloud fields generated from a high resolution non-hydrostatic mesoscale numerical weather model using 1D and 3D radiative transfer codes.

  15. The Management and Mining of Multiple Predictive Models Using the Predictive Modeling Markup Language (PMML)

    E-Print Network [OSTI]

    Grossman, Robert

    The Management and Mining of Multiple Predictive Models Using the Predictive Modeling Markup Language (PMML) Robert Grossman National Center for Data Mining, University of Illinois at Chicago & Magnify, Inc. Stuart Bailey, Ashok Ramu and Balinder Malhi National Center for Data Mining University

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

    SciTech Connect (OSTI)

    Morrison, PI Hugh

    2012-09-21

    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).

  17. 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 for teams of helicopters. However, the potential for accidents is greatly increased when helicopter teams to the problem of helicopter formations comprised of heterogenous vehicles. The disturbance attenuation property

  18. HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

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

    Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin; Pereira, Jose M.; Hurtt, George C.

    2015-02-13

    Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spreadmore »over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.« less

  19. Weather Research and Forecasting Model's Community Variational/Ensemble Data Assimilation System: WRFDA

    SciTech Connect (OSTI)

    Barker, D.; Huang, X. Y.; Liu, Z. Q.; Auligne, T.; Zhang, X.; Rugg, S.; Ajjaji, R.; Bourgeois, A.; Bray, J.; Chen, Y. S.; Demirtas, M.; Guo, Y. R.; Henderson, T.; Huang, W.; Lin, H. C.; Michalakes, J.; Rizvi, S.; Zhang, X. Y.

    2012-06-01

    Data assimilation is the process by which observations are combined with short-range NWP model output to produce an analysis of the state of the atmosphere at a specified time. Since its inception in the late 1990s, the multiagency Weather Research and Forecasting (WRF) model effort has had a strong data assimilation component, dedicating two working groups to the subject. This article documents the history of the WRF data assimilation effort, and discusses the challenges associated with balancing academic, research, and operational data assimilation requirements in the context of the WRF effort to date. The WRF Model's Community Variational/Ensemble Data Assimilation System (WRFDA) has evolved over the past 10 years, and has resulted in over 30 refereed publications to date, as well as implementation in a wide range of real-time and operational NWP systems.

  20. Comparison of Uncertainty of Two Precipitation Prediction Models

    E-Print Network [OSTI]

    Shield, Stephen

    2015-01-01

    Meteorological inputs are an important part of subsurface flow and transport modeling. The choice of source for meteorological data used as inputs has significant impacts on the results of subsurface flow and transport studies. One method to obtain the meteorological data required for flow and transport studies is the use of weather generating models. This paper compares the difference in performance of two weather generating models at Technical Area 54 of Los Alamos National Lab. Technical Area 54 is contains several waste pits for low-level radioactive waste and is the site for subsurface flow and transport studies. This makes the comparison of the performance of the two weather generators at this site particularly valuable.

  1. 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.

    2014-03-19

    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.

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

    E-Print Network [OSTI]

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

    2006-01-01

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

  3. Progress towards a PETN Lifetime Prediction Model

    SciTech Connect (OSTI)

    Burnham, A K; Overturf III, G E; Gee, R; Lewis, P; Qiu, R; Phillips, D; Weeks, B; Pitchimani, R; Maiti, A; Zepeda-Ruiz, L; Hrousis, C

    2006-09-11

    Dinegar (1) showed that decreases in PETN surface area causes EBW detonator function times to increase. Thermal aging causes PETN to agglomerate, shrink, and densify indicating a ''sintering'' process. It has long been a concern that the formation of a gap between the PETN and the bridgewire may lead to EBW detonator failure. These concerns have led us to develop a model to predict the rate of coarsening that occurs with age for thermally driven PETN powder (50% TMD). To understand PETN contributions to detonator aging we need three things: (1) Curves describing function time dependence on specific surface area, density, and gap. (2) A measurement of the critical gap distance for no fire as a function of density and surface area for various wire configurations. (3) A model describing how specific surface area, density and gap change with time and temperature. We've had good success modeling high temperature surface area reduction and function time increase using a phenomenological deceleratory kinetic model based on a distribution of parallel nth-order reactions having evenly spaced activation energies where weighing factors of the reactions follows a Gaussian distribution about the reaction with the mean activation energy (Figure 1). Unfortunately, the mean activation energy derived from this approach is high (typically {approx}75 kcal/mol) so that negligible sintering is predicted for temperatures below 40 C. To make more reliable predictions, we've established a three-part effort to understand PETN mobility. First, we've measured the rates of step movement and pit nucleation as a function of temperature from 30 to 50 C for single crystals. Second, we've measured the evaporation rate from single crystals and powders from 105 to 135 C to obtain an activation energy for evaporation. Third, we've pursued mechanistic kinetic modeling of surface mobility, evaporation, and ripening.

  4. Gamma-Ray Pulsars: Models and Predictions

    E-Print Network [OSTI]

    Alice K. Harding

    2000-12-12

    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.

  5. Predicting Protein Folding Kinetics via Temporal Logic Model Checking: Extended

    E-Print Network [OSTI]

    Langmead, Christopher James

    Predicting Protein Folding Kinetics via Temporal Logic Model Checking: Extended Abstract Abstract. We present a novel approach for predicting protein folding kinetics using techniques from checking. We tested our method on 19 test proteins. The quantitative predictions regarding folding rates

  6. Predicting Solar Flares by Data Assimilation in Avalanche Models. I. Model Design and Validation

    E-Print Network [OSTI]

    Eric Bélanger; Alain Vincent; Paul Charbonneau

    2007-08-14

    Data assimilation techniques, developed in the last two decades mainly for weather prediction, produce better forecasts by taking advantage of both theoretical/numerical models and real-time observations. In this paper, we explore the possibility of applying the data-assimilation techniques known as 4D-VAR to the prediction of solar flares. We do so in the context of a continuous version of the classical cellular-automaton-based self-organized critical avalanche models of solar flares introduced by Lu and Hamilton (Astrophys. J., 380, L89, 1991). Such models, although a priori far removed from the physics of magnetic reconnection and magneto-hydrodynamical evolution of coronal structures, nonetheless reproduce quite well the observed statistical distribution of flare characteristics. We report here on a large set of data assimilation runs on synthetic energy release time series. Our results indicate that, despite the unpredictable (and unobservable) stochastic nature of the driving/triggering mechanism within the avalanche model, 4D-VAR succeeds in producing optimal initial conditions that reproduce adequately the time series of energy released by avalanches/flares. This is an essential first step towards forecasting real flares.

  7. The Santa Ana Winds of Southern California in the context of Fire Weather

    E-Print Network [OSTI]

    Cao, Yang

    2015-01-01

    LFP w (red line) is the weather component of the total LFP (Prediction Systems, Monthly Weather Review, 133, 1076–1097,Administration, National Weather Service Scientific Services

  8. MODELLING SURFACE HOAR FORMATION AND EVOLUTION ON MOUNTAIN SLOPES Simon Horton1

    E-Print Network [OSTI]

    Jamieson, Bruce

    evaluates surface hoar size predictions made with empirical weather based models and discusses how buried. Weather station data and forecasted data from the GEM15 numerical weather prediction model were used. The surface energy balance model made good predictions of crystal size with real station data (r2 = 0

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

    E-Print Network [OSTI]

    Oren, Shmuel S.

    -day ice storm in February 2003 electricity prices spiked to $990/MWh causing a retail energy provider, representing some three trillion dollars annually, bears some degree of weather and climate risk. Energy be affected by weather. For example, the profit function of energy distribution companies, which are obligated

  10. 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.

    2013-10-01

    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.

  11. Impact of a Revised Convective Triggering Mechanism on CAM2 Model Simulations: Results from Short-Range Weather Forecasts

    SciTech Connect (OSTI)

    Xie, S; Boyle, J S; Cederwall, R T; Potter, G L; Zhang, M; Lin, W

    2004-02-19

    This study implements a revised convective triggering condition in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM2) model to reduce its excessive warm season daytime precipitation over land. The new triggering mechanism introduces a simple dynamic constraint on the initiation of convection that emulates the collective effects of lower level moistening and upward motion of the large-scale circulation. It requires a positive contribution from the large-scale advection of temperature and moisture to the existing positive Convective Available Potential Energy (CAPE) for model convection to start. In contrast, the original convection triggering function in CAM2 assumes that convection is triggered whenever there is positive CAPE, which results in too frequent warm season convection over land arising from strong diurnal variation of solar radiation. We examine the impact of the new trigger on CAM2 simulations by running the climate model in Numerical Weather Prediction (NWP) mode so that more available observations and high-frequency NWP analysis data can be used to evaluate model performance. We show that the modified triggering mechanism has led to considerable improvements in the simulation of precipitation, temperature, moisture, clouds, radiations, surface temperature, and surface sensible and latent heat fluxes when compared to the data collected from the Atmospheric Radiation Measurement (ARM) program at its South Great Plains (SGP) site. Similar improvements are also seen over other parts of the globe. In particular, the surface precipitation simulation has been significantly improved over both the continental United States and around the globe; the overestimation of high clouds in the equatorial tropics has been substantially reduced; and the temperature, moisture, and zonal wind are more realistically simulated. Results from this study also show that some systematic errors in the CAM2 climate simulations can be detected in the early stage of model integration. Examples are the extremely overestimated high clouds in the tropics in the vicinity of ITCZ and the spurious precipitation maximum in the east of the Rockies. This has important implications in studies of these model errors since running the climate model in NWP mode allows us to perform a more in-depth analysis during a short time period where more observations are available and different model errors from various processes have not compensated for the systematic errors.

  12. Predictive Capability Maturity Model for computational modeling and simulation.

    SciTech Connect (OSTI)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  13. A statistically predictive model for future monsoon failure in India

    E-Print Network [OSTI]

    Levermann, Anders

    A statistically predictive model for future monsoon failure in India Jacob Schewe1,2 and Anders Information #12;A statistically predictive model for future monsoon failure in India 2 mm/day numberofyears 0 statistically predictive model for future monsoon failure in India 4 30 o S 15o S 0 o 15o N 30o N A dry May B

  14. A resampling procedure for generating conditioned daily weather Martyn P. Clark,1

    E-Print Network [OSTI]

    Balaji, Rajagopalan

    A resampling procedure for generating conditioned daily weather sequences Martyn P. Clark,1 the observed spatial (intersite) and temporal correlation statistics. The weather generator model is applied weather sequence. The weather generator model is extended to produce sequences of weather

  15. Statistical surrogate models for prediction of high-consequence...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Statistical surrogate models for prediction of high-consequence climate change. Citation Details In-Document Search Title: Statistical surrogate models for...

  16. Sensitivity analysis of the MM5 weather model using automatic differentiation

    SciTech Connect (OSTI)

    Bischof, C.H. [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439 (United States)] [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439 (United States); Pusch, G.D. [Physics Department, Michigan State University, East Lansing, Michigan 48842 (United States)] [Physics Department, Michigan State University, East Lansing, Michigan 48842 (United States); Knoesel, R. [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439 (United States)] [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439 (United States)

    1996-11-01

    We present a general method for using automatic differentiation to facilitate model sensitivity analysis. Automatic differentiation techniques augment, in a completely mechanical fashion, an existing code such that it also simultaneously and efficiently computes derivatives. Our method allows the sensitivities of the code{close_quote}s outputs to its parameters and inputs to be determined with minimal human effort by exploiting the relationship between differentiation and formal perturbation theory. Employing this methodology, we performed a sensitivity study of the MM5 code, a mesoscale weather model jointly developed by Penn State University and the National Center for Atmospheric Research, that is composed of roughly 40,000 lines of Fortran 77 code. Our results show that automatic differentiation-computed sensitivities exhibit superior accuracy compared to divided difference approximations computed from finite-amplitude perturbations. We also comment on a numerically induced precursor wave that would almost certainly have been undetectable if one used a divided difference method. {copyright} {ital 1996 American Institute of Physics.}

  17. 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

    2008-01-01

    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.

  18. Predicting the past: archaeological predictive modeling in Central Texas 

    E-Print Network [OSTI]

    Werner, Corey M

    2002-01-01

    Texas has a well-stratified assemblage of Clovis artifacts. The discovery of additional sites like the Gault site could provide valuable information to resolve the debate. Two logistic regression models are created to locate areas with a high...

  19. 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 UNIVERSIDAD POLITÉCNICA DE CATALUÑA April, 2007 GEOMODELS #12;Introduction to Coll Cardús landfill Prediction of settlement in Coll Cardús landfill 1) Settlement prediction by empirical method 2) Settlement prediction

  20. A Better Way to ID Extreme Weather Events in Climate Models

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

    developing techniques 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...

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

    E-Print Network [OSTI]

    Juarez Torres, Miriam 77-

    2012-08-31

    Stochastic Weather Generators (SWG) try to reproduce the stochastic patterns of climatological variables characterized by high dimensionality, non-normal probability density functions and non-linear dependence relationships. However, conventional...

  2. Atmospheric Test Models and Numerical Experiments for the Simulation of the Global Distributions of Weather Data Transponders III. Horizontal Distributions

    SciTech Connect (OSTI)

    Molenkamp, C.R.; Grossman, A.

    1999-12-20

    A network of small balloon-borne transponders which gather very high resolution wind and temperature data for use by modern numerical weather predication models has been proposed to improve the reliability of long-range weather forecasts. The global distribution of an array of such transponders is simulated using LLNL's atmospheric parcel transport model (GRANTOUR) with winds supplied by two different general circulation models. An initial study used winds from CCM3 with a horizontal resolution of about 3 degrees in latitude and longitude, and a second study used winds from NOGAPS with a 0.75 degree horizontal resolution. Results from both simulations show that reasonable global coverage can be attained by releasing balloons from an appropriate set of launch sites.

  3. 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

  4. On-line economic optimization of energy systems using weather forecast information.

    SciTech Connect (OSTI)

    Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

    2009-01-01

    We establish an on-line optimization framework to exploit weather forecast information in the operation of energy systems. We argue that anticipating the weather conditions can lead to more proactive and cost-effective operations. The framework is based on the solution of a stochastic dynamic real-time optimization (D-RTO) problem incorporating forecasts generated from a state-of-the-art weather prediction model. The necessary uncertainty information is extracted from the weather model using an ensemble approach. The accuracy of the forecast trends and uncertainty bounds are validated using real meteorological data. We present a numerical simulation study in a building system to demonstrate the developments.

  5. 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.

  6. TAJE_A_754793.3d (TAJE) 02-05-2013 23:56 Towards a predictive model for opal exploration using

    E-Print Network [OSTI]

    Müller, Dietmar

    TAJE_A_754793.3d (TAJE) 02-05-2013 23:56 Towards a predictive model for opal exploration using produces over 90% of the world's precious opal from highly weathered Cretaceous sedimen- tary rocks within the Great Artesian Basin. Since opal was first discovered around 1870 until the present day, opal mining has

  7. 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.

    1992-01-01

    that extract hourly end-use energy consumption and weather data from DOE-2's hourly output reports and process the data into three-dimensional plots and temperature-specific humidity carpet plots....

  8. Predicting yearly energy savings using BIN weather data with heat-pipe heat exchangers with indirect evaporative cooling

    SciTech Connect (OSTI)

    Mathur, G.D.

    1998-07-01

    Heat-Pipe Heat-Exchangers (HPHE) are passive systems that have recently seen application in energy recovery (Mathur, 1997). A HPHE consists of individual closed end heat pipe tubes that are charged with a suitable working fluid. In these systems, the working fluid evaporates on one side of the heat exchanger and condenses over the other end of the heat exchanger. The condensed fluid returns back to the evaporator section through the capillary action of the wick. The performance of a HPHE system can be improved by the raising the condenser portion of the heat exchanger which facilitates effective return of the condensate back to the evaporator. HPHE can be used with air conditioning systems as retrofits and in new applications. For retrofit applications, the operating costs are reduced because of the reduction in the energy (kWh) and peak demand (kW) consumptions. For new installations, the heating and cooling equipment can be of smaller capacity which will result in lower equipment and operating costs. During the summer season, indirect evaporative cooling can also be used to further enhance the performance of the air conditioning system. When operated during both the heating and cooling seasons, a HPHE yields four types of savings: (i) Heating equipment savings (ii) Cooling equipment savings (iii) Heating operating savings (iv) Cooling operating savings. Savings in the energy consumption for both heating and cooling were calculated with the HPHE for 30 cities with widely different climactic conditions. The payback periods for most of the cities were less than 1 year. If indirect evaporative cooling is used during the summer season, more energy savings would be realized on an yearly basis along with further reductions in the peak demand. In this paper, the author has simulated the performance of a HPHE with indirect evaporative cooling using the BIN weather data.

  9. Two way coupling RAM-SCB to the space weather modeling framework

    SciTech Connect (OSTI)

    Welling, Daniel T [Los Alamos National Laboratory; Jordanova, Vania K [Los Alamos National Laboratory; Zaharia, Sorin G [Los Alamos National Laboratory; Toth, Gabor [UNIV OF MICHIGAN

    2010-12-03

    The Ring current Atmosphere interaction Model with Self-Consistently calculated 3D Magnetic field (RAM-SCB) has been used to successfully study inner magnetosphere dynamics during different solar wind and magnetosphere conditions. Recently, one way coupling of RAM-SCB with the Space Weather Modeling Framework (SWMF) has been achieved to replace all data or empirical inputs with those obtained through first-principles-based codes: magnetic field and plasma flux outer boundary conditions are provided by the Block Adaptive Tree Solar wind Roe-type Upwind Scheme (BATS-R-US) MHO code, convection electric field is provided by the Ridley Ionosphere Model (RIM), and ion composition is provided by the Polar Wind Outflow Model (PWOM) combined with a multi-species MHO approach. These advances, though creating a powerful inner magnetosphere virtual laboratory, neglect the important mechanisms through which the ring current feeds back into the whole system, primarily the stretching of the magnetic field lines and shielding of the convection electric field through strong region two Field Aligned Currents (FACs). In turn, changing the magnetosphere in this way changes the evolution of the ring current. To address this shortcoming, the coupling has been expanded to include feedback from RAM-SCB to the other coupled codes: region two FACs are returned to the RIM while total plasma pressure is used to nudge the MHO solution towards the RAMSCB values. The impacts of the two way coupling are evaluated on three levels: the global magnetospheric level, focusing on the impact on the ionosphere and the shape of the magnetosphere, the regional level, examining the impact on the development of the ring current in terms of energy density, anisotropy, and plasma distribution, and the local level to compare the new results to in-situ measurements of magnetic and electric field and plasma. The results will also be compared to past simulations using the one way coupling and no coupling whatsoever. This work is the first to fully couple an anisotropic kinetic ring current code with a selfconsistently calculated magnetic field to a set of global models.

  10. MODEL PREDICTIVE CONTROL OF A MICROGRID WITH PLUG-IN VEHICLES: ERROR MODELING AND THE ROLE OF PREDICTION HORIZON

    E-Print Network [OSTI]

    Papalambros, Panos

    MODEL PREDICTIVE CONTROL OF A MICROGRID WITH PLUG-IN VEHICLES: ERROR MODELING AND THE ROLE) for a microgrid with plug-in vehicles. A predictive model is de- veloped based on a hub model of the microgrid INTRODUCTION Recently, the control of electrical microgrids has been the focus of research efforts. A microgrid

  11. The myth of science-based predictive modeling.

    SciTech Connect (OSTI)

    Hemez, F. M. (François M.)

    2004-01-01

    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.

  12. 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.

  13. 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

  14. Recent forecasts from the National Weather Service and other Hurricane watchers predict an active Hurricane Season for the U.S. Connecticut has been severely affected many times by Hurricanes. Individuals, businesses and communities can take some basic st

    E-Print Network [OSTI]

    Post, David M.

    Recent forecasts from the National Weather Service and other Hurricane watchers predict an active Hurricane Season for the U.S. Connecticut has been severely affected many times by Hurricanes. Individuals, businesses and communities can take some basic steps to be better informed about and prepared for Hurricanes

  15. Predictive Models of Li-ion Battery Lifetime (Presentation) Smith...

    Office of Scientific and Technical Information (OSTI)

    Predictive Models of Li-ion Battery Lifetime (Presentation) Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Shi, Y.; Pesaran, A. 25 ENERGY STORAGE; 33 ADVANCED PROPULSION...

  16. A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

    E-Print Network [OSTI]

    Hong, Tianzhen

    2014-01-01

    DB. Weather data for building performance simulation.forecast models, weather data, and building prototypes havethe TMY3 weather data in building simulations to evaluate

  17. 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 ...

  18. On Predicting the Solar Cycle using Mean-Field Models

    E-Print Network [OSTI]

    Paul J. Bushby; Steven M. Tobias

    2007-04-18

    We discuss the difficulties of predicting the solar cycle using mean-field models. Here we argue that these difficulties arise owing to the significant modulation of the solar activity cycle, and that this modulation arises owing to either stochastic or deterministic processes. We analyse the implications for predictability in both of these situations by considering two separate solar dynamo models. The first model represents a stochastically-perturbed flux transport dynamo. Here even very weak stochastic perturbations can give rise to significant modulation in the activity cycle. This modulation leads to a loss of predictability. In the second model, we neglect stochastic effects and assume that generation of magnetic field in the Sun can be described by a fully deterministic nonlinear mean-field model -- this is a best case scenario for prediction. We designate the output from this deterministic model (with parameters chosen to produce chaotically modulated cycles) as a target timeseries that subsequent deterministic mean-field models are required to predict. Long-term prediction is impossible even if a model that is correct in all details is utilised in the prediction. Furthermore, we show that even short-term prediction is impossible if there is a small discrepancy in the input parameters from the fiducial model. This is the case even if the predicting model has been tuned to reproduce the output of previous cycles. Given the inherent uncertainties in determining the transport coefficients and nonlinear responses for mean-field models, we argue that this makes predicting the solar cycle using the output from such models impossible.

  19. Switching Between Discrete and Continuous Models To Predict Genetic Activity

    E-Print Network [OSTI]

    Weld, Daniel S.

    Molecular biologists use a variety of models when they predict the behavior of genetic systems. A discrete model of the behavior of individual macromolecular elements forms the foundation for their theory of each system. ...

  20. Weatherizing America

    ScienceCinema (OSTI)

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

    2013-05-29

    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.

  1. 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...

  2. A DETERMINISTIC PREDICTION MODEL FOR THE AMERICAN GAME OF FOOTBALL

    E-Print Network [OSTI]

    Weaver, Adam Lee

    A DETERMINISTIC PREDICTION MODEL FOR THE AMERICAN GAME OF FOOTBALL John Am Trono, Saint Michael's College Introduction This article describes a simulation model of the sport known as footballs It was created to predict results of post season football games, most notably college bowl games. By constructing

  3. Predicting Protein Folding Kinetics via Temporal Logic Model Checking

    E-Print Network [OSTI]

    Predicting Protein Folding Kinetics via Temporal Logic Model Checking Christopher James Langmead award from the U.S. Department of Energy. #12;Keywords: protein folding, model checking, temporal logic #12;Abstract We present a novel approach for predicting protein folding kinetics using techniques from

  4. PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer

    E-Print Network [OSTI]

    Wishart, Gordon C.; Azzato, Elizabeth M.; Greenberg, David C.; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D. P.

    2010-01-06

    Abstract Introduction The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Methods Using the Eastern Cancer Registration...

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

    E-Print Network [OSTI]

    Ganguly, Auroop Ratan

    2002-01-01

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

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

    E-Print Network [OSTI]

    Surussavadee, Chinnawat

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

  7. LHC diphoton Higgs signal predicted by little Higgs models

    SciTech Connect (OSTI)

    Wang Lei; Yang Jinmin

    2011-10-01

    Little Higgs theory naturally predicts a light Higgs boson whose most important discovery channel at the LHC is the diphoton signal pp{yields}h{yields}{gamma}{gamma}. In this work, we perform a comparative study for this signal in some typical little Higgs models, namely, the littlest Higgs model, two littlest Higgs models with T-parity (named LHT-I and LHT-II), and the simplest little Higgs models. We find that compared with the standard model prediction, the diphoton signal rate is always suppressed and the suppression extent can be quite different for different models. The suppression is mild (< or approx. 10%) in the littlest Higgs model but can be quite severe ({approx_equal}90%) in other three models. This means that discovering the light Higgs boson predicted by the little Higgs theory through the diphoton channel at the LHC will be more difficult than discovering the standard model Higgs boson.

  8. Modeling probability distributions with predictive state representations

    E-Print Network [OSTI]

    Wiewiora, Eric Walter

    2008-01-01

    Discovery is the process of choosing the core tests, whose success probabilities will become the state of the learned model.

  9. Evidences for and the models of self-similar skeletal structures in fusion devices, severe weather phenomena and space

    E-Print Network [OSTI]

    Kukushkin, A B

    2005-01-01

    The paper briefly reviews (i) the evidences for self-similar structures of a skeletal form (namely, tubules and cartwheels, and their simplest combinations), called the Universal Skeletal Structures (USS), observed in the range 10-5 cm - 1023 cm. in the high-current electric discharges in various fusion devices, severe weather phenomena, and space, (ii) the models for interpreting the phenomenon of skeletal structures, including the hypothesis for a fractal condensed matter (FCM), assembled from nanotubular dust, and (iii) probable role of FCM, which might be responsible for the USS phenomenon, in tornado, ball lightning, and waterspout.

  10. Development of a next-generation regional weather research and forecast model.

    SciTech Connect (OSTI)

    Michalakes, J.; Chen, S.; Dudhia, J.; Hart, L.; Klemp, J.; Middlecoff, J.; Skamarock, W.

    2001-02-05

    The Weather Research and Forecast (WRF) project is a multi-institutional effort to develop an advanced mesoscale forecast and data assimilation system that is accurate, efficient, and scalable across a range of scales and over a host of computer platforms. The first release, WRF 1.0, was November 30, 2000, with operational deployment targeted for the 2004-05 time frame. This paper provides an overview of the project and current status of the WRF development effort in the areas of numerics and physics, software and data architecture, and single-source parallelism and performance portability.

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

    E-Print Network [OSTI]

    Neumaier, Arnold

    MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE ARNOLD NEUMAIER­called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary) structure of a protein, given its sequence of amino acids. The dynamic aspect asks about the possible

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

    E-Print Network [OSTI]

    Neumaier, Arnold

    MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE ARNOLD NEUMAIER-called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary) structure of a protein, given its sequence of amino acids. The dynamic aspect asks about the possible

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

    E-Print Network [OSTI]

    for the simulated firing of an NSI into 1) a pin puller device, 2) a 10 cm3 closed vessel, and 3) an apparatus known as the Dynamic Test Device. The predictions are compared with experiments. The pressure magnitudes and time scales of pressure rise and decay are predicted well by the model. Introduction Pyrotechnically actuated

  14. High Level antitative Hardware Prediction Modeling using Statistical methods

    E-Print Network [OSTI]

    Bertels, Koen

    essential to have efficient prediction models to drive early HW-SW partitioning and co-design. In this paper development and HW-SW co-design. Given an application composed of different kernels, in order to map one-level language description as input, enabling hardware prediction in the early design stages. We calibrate

  15. A predictive ocean oil spill model

    SciTech Connect (OSTI)

    Sanderson, J.; Barnette, D.; Papodopoulos, P.; Schaudt, K.; Szabo, D.

    1996-07-01

    This is the final report of a two-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). Initially, the project focused on creating an ocean oil spill model and working with the major oil companies to compare their data with the Los Alamos global ocean model. As a result of this initial effort, Los Alamos worked closely with the Eddy Joint Industry Project (EJIP), a consortium oil and gas producing companies in the US. The central theme of the project was to use output produced from LANL`s global ocean model to look in detail at ocean currents in selected geographic areas of the world of interest to consortium members. Once ocean currents are well understood this information could be used to create oil spill models, improve offshore exploration and drilling equipment, and aid in the design of semi-permanent offshore production platforms.

  16. Colliding cascades model for earthquake prediction

    E-Print Network [OSTI]

    2000-10-12

    on a direct cascade that would deliver energy from the largest size scales ... The general objective of the colliding cascades model has been to reproduce the ..... earthquake and critical phase transitions studied in statistical physics, where the

  17. Conformal Higgs model: predicted dark energy density

    E-Print Network [OSTI]

    R. K. Nesbet

    2014-11-03

    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.

  18. Tracking tropical cloud systems for the diagnosis of simulations by the weather research and forecasting (WRF) model

    SciTech Connect (OSTI)

    Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E. P.; Jensen, M. P.; Zhang, M. H.; Boer, E.

    2010-06-27

    To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the tropical warm pool. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, J. Geophys. Res., 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest that the organization of the mesoscale convective systems is particularly sensitive to the cloud microphysics parameterization used.

  19. Tracking tropical cloud systems - Observations for the diagnosis of simulations by the Weather Research and Forecasting (WRF) Model

    SciTech Connect (OSTI)

    Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E.; Jensen, M.; Zhang, M.

    2010-03-15

    To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the vicinity of the ARM Tropical Western Pacific sites. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest a computational paradox where, even though the size of the simulated systems are about half of that observed, their longevities are still similar. The explanation for this seeming incongruity will be explored.

  20. Predictive capacity planning modeling with tactical and strategic applications

    E-Print Network [OSTI]

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

    2004-01-01

    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 ...

  1. Land Surface Model Data Assimilation for Atmospheric Prediction

    E-Print Network [OSTI]

    Walker, Jeff

    predictions from different models even when using the same parameters, inputs, and initial conditions (Houser remote sensing studies, using visible, thermal infrared (surface temperature) and microwave (passive and active) electromagnetic radiation. Of these, passive microwave soil moisture measurement has been

  2. 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

  3. QMC Simulations DataBase for Predictive Theory and Modeling ...

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

    CO monoxide adsorbs on the Pt (111) surface CO monoxide adsorbs on the Pt (111) surface. One application of the QMC Simulations Database for the Predictive Modeling and Theory...

  4. Interactive software for model predictive control with simultaneous identification 

    E-Print Network [OSTI]

    Echeverria Del Rio, Pablo

    2000-01-01

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

  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

    2013-06-01

    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. Predicting species invasions using ecological niche modeling

    E-Print Network [OSTI]

    Peterson, A. Townsend; Vieglais, David A.

    2001-05-01

    ) and commission (including niche space not ,lctually occupied by the 'pecies). Each algorithm for modeling specIes' ecological niches involves a specific com binatiol1 of errors of omission ,md commission. A rel.ltively new approach, called the (;enetic...

  7. Iterative Multivariate Regression Model for Correlated Responses Prediction S. Tom Au, Guangqin Ma, Rensheng Wang

    E-Print Network [OSTI]

    Greenberg, Albert

    Iterative Multivariate Regression Model for Correlated Responses Prediction S. Tom Au, Guangqin Ma- tive procedure to model multiple responses prediction into correlated multivariate predicting scheme, which is always favorable for responses separations in our multivariate prediction. We also point out

  8. Predictive models of circulating fluidized bed combustors

    SciTech Connect (OSTI)

    Gidaspow, D.

    1992-07-01

    Steady flows influenced by walls cannot be described by inviscid models. Flows in circulating fluidized beds have significant wall effects. Particles in the form of clusters or layers can be seen to run down the walls. Hence modeling of circulating fluidized beds (CFB) without a viscosity is not possible. However, in interpreting Equations (8-1) and (8-2) it must be kept in mind that CFB or most other two phase flows are never in a true steady state. Then the viscosity in Equations (8-1) and (8-2) may not be the true fluid viscosity to be discussed next, but an Eddy type viscosity caused by two phase flow oscillations usually referred to as turbulence. In view of the transient nature of two-phase flow, the drag and the boundary layer thickness may not be proportional to the square root of the intrinsic viscosity but depend upon it to a much smaller extent. As another example, liquid-solid flow and settling of colloidal particles in a lamella electrosettler the settling process is only moderately affected by viscosity. Inviscid flow with settling is a good first approximation to this electric field driven process. The physical meaning of the particulate phase viscosity is described in detail in the chapter on kinetic theory. Here the conventional derivation resented in single phase fluid mechanics is generalized to multiphase flow.

  9. Modeling Social Cues: Effective Features for Predicting Listener Nods

    E-Print Network [OSTI]

    Zhu, Xiaojin "Jerry"

    Modeling Social Cues: Effective Features for Predicting Listener Nods Faisal Khan, Bilge Mutlu, we present preliminary work in modeling a particular communicative mechanism--listener nods observations of verbal and nonverbal cues from the speaker and listener nods and a hidden sub- structure

  10. Chemical and Biological Engineering Model Predictive Control: Background

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    == - - = -- --- = DC C V F CC B k V F k Ckk V F A Bs s AsAfs s As s = f1 = f2 etcCAux Asss C f x f A , 1 ,1 1 11Chemical and Biological Engineering Model Predictive Control: Background B. Wayne Bequette "windup" problems Does not explicitly require a process model #12;Chemical and Biological Engineering

  11. Classical Cepheid Pulsation Models. III. The Predictable Scenario

    E-Print Network [OSTI]

    G. Bono; V. Castellani; M. Marconi

    1999-08-02

    Within the current uncertainties in the treatment of the coupling between pulsation and convection, limiting amplitude, nonlinear, convective models appear the only viable approach for providing theoretical predictions about the intrinsic properties of radial pulsators. In this paper we present the results of a comprehensive set of Cepheid models computed within such theoretical framework for selected assumptions on their original chemical composition.

  12. 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.

    2013-03-19

    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.

  13. Social Media: Space Weather #SpaceWeather

    E-Print Network [OSTI]

    ://www.swpc.noaa.gov/impacts/spaceweatherandgpssystems #SpaceWeather #12;Space Weather Impacts on the Power Grid Facebook The electric power grid. To learn about space weather and impacts to the electric grid visit http on the Power Grid Space Weather and the Aurora Borealis What are Solar Flares? What are Coronal Mass

  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)

    1997-12-31

    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. Improving understanding, modelImproving understanding, model simulations, and prediction of thesimulations, and prediction of the

    E-Print Network [OSTI]

    Wood, Robert

    GMAO Clouds in Global Models Annual mean Control run Atmospheric models #12;CGCM Problems: NOAA CFS Model CFS Errors SST Prec CLD · The CFS model has significant errors in the SEP · There is a meridional) · These errors adversely affect the skill of CFS climate forecasts (ENSO). What model developments are required

  16. INTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev

    E-Print Network [OSTI]

    , discourse and semantic. They are based on a conceptual model underlying weather forecasts as well situations represented in the form of texts in NL, weather maps, data tables or combined information objectsINTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev I n s t i t u t e of Mathematics Acad

  17. Understanding space weather to shield society

    E-Print Network [OSTI]

    Schrijver, Karel

    Understanding space weather to shield society An international, interdisciplinary roadmap to advance the scientific understanding of the Sun-Earth connections leading to space weather, on behalf observatory along with models and innovative approaches to data incorporation;! b) Understand space weather

  18. SPACE WEATHER RISKS FROM AN INSURANCE PERSPECTIVE

    E-Print Network [OSTI]

    Schrijver, Karel

    SPACE WEATHER RISKS FROM AN INSURANCE PERSPECTIVE 26.04.2011 Jan Eichner ­ Geo Risks Research #12, including geophysical hazards, weather-related hazards and potential consequences of climate change weather). · Linking geo-scientific research with business expertise in risk assessment, risk modeling

  19. Lepton Flavor Violation in Predictive SUSY-GUT Models

    SciTech Connect (OSTI)

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

    2008-02-01

    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.

  20. Development and Initial Application of the Global-Through-Urban Weather Research1 and Forecasting Model with Chemistry (GU-WRF/Chem)2

    E-Print Network [OSTI]

    Nenes, Athanasios

    1 Development and Initial Application of the Global-Through-Urban Weather Research1 and Forecasting-cloud-radiation-precipitation-climate interactions. In this work, a global-through-urban33 WRF/Chem model (i.e., GU-WRF/Chem) has been developed photolysis rate, near-surface temperature, wind speed at 10-m, planetary boundary layer height,40

  1. USING A PHYSIOLOGICAL MODEL FOR PREDICTION OF THERAPY EFFECTS IN

    E-Print Network [OSTI]

    Long, William J.

    . Long, Shapur Naimi, M. G. Criscitiello, Robert Jayes M.I.T. Laboratory for Computer Science, Cambridge, based on signal flow analysis, for predicting hemodynamic changes using a model of physiological Library of Medicine. 2 #12; 1 Introduction As the variety of diagnostic and therapeutic modalities

  2. What is the Recent Controversy in Evaluating Risk Prediction Models

    E-Print Network [OSTI]

    Brent, Roger

    What is the Recent Controversy in Evaluating Risk Prediction Models All About? Margaret Sullivan Pepe #12;Controversy about Risk Reclassification Techniques · Purpose: To evaluate the addition cases controls C-index = P(riskevent > risknonevent) · Should not be used to evaluate or compare risk

  3. 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

  4. 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

  5. Model Predictive Control of Residential Energy Systems Using

    E-Print Network [OSTI]

    Knobloch,Jürgen

    network infrastructure and can lead to a degradation of power quality and even outages. In responseModel Predictive Control of Residential Energy Systems Using Energy Storage & Controllable Loads degree of freedom leads to improved performance. 1 Introduction Widespread uptake of local electricity

  6. Flood Prevention of the Demer using Model Predictive Control

    E-Print Network [OSTI]

    Flood Prevention of the Demer using Model Predictive Control Toni Barjas Blanco, ,1 Patrick Willems Abstract: In order to prevent flooding of a river system the local water administration of the Demer reduced the damage and frequency of flooding events, simulations have shown that a better usage

  7. A distributed accelerated gradient algorithm for distributed model predictive

    E-Print Network [OSTI]

    Como, Giacomo

    is applied to the power reference tracking problem of a hydro power valley (HPV) system. The applied, Distributed model predictive control 1. Introduction Hydro power plants generate electricity from potential river or a water body system to generate the power at different stages. Currently, hydro power is one

  8. Predictive modeling of thermoelastic energy dissipation in tunable MEMS mirrors

    E-Print Network [OSTI]

    Yi, Yun-Bo

    Predictive modeling of thermoelastic energy dissipation in tunable MEMS mirrors Houwen Tang is of significant importance in many microelectromechanical sys- tem MEMS applications. Thermoelastic damping can such as MEMS mirrors. We deal with the simulation and analysis of thermoelastic damping of MEMS mirrors based

  9. 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 in drilling research is a fall of pene- tration rate for higher static loads. This is known both

  10. 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, Massachusetts Institute of Technology, Cambridge, MA 02139, USA Two different approaches are described

  11. Building a Weather-Ready Nation Winter Weather Safety

    E-Print Network [OSTI]

    Building a Weather-Ready Nation Winter Weather Safety NOAA/NWS Winter Weather Safety Seasonal Campaign www.weather.gov #12;Building a Weather-Ready Nation Winter Weather Hazards Winter Weather Safety www.weather.gov · Snow/Ice · Blizzards · Flooding · Cold Temperatures #12;Building a Weather

  12. Predicting solar cycle 24 with a solar dynamo model

    E-Print Network [OSTI]

    Arnab Rai Choudhuri; Piyali Chatterjee; Jie Jiang

    2007-01-18

    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.

  13. ScoPred--Scalable User-Directed Performance Prediction Using Complexity Modeling and Historical Data

    E-Print Network [OSTI]

    Feitelson, Dror

    complexity models, good prediction accuracy can be obtained. 1 Introduction The typical approach in parallel, partic

  14. A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

    E-Print Network [OSTI]

    Hong, Tianzhen

    2014-01-01

    vs. synthesized energy modeling weather files. Journal ofHong TZ, Jiang Y. Stochastic weather model for building HVAC1. [9] Crawley DB. Which weather data should you use for

  15. 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.

  16. Solar cycle prediction using precursors and flux transport models

    E-Print Network [OSTI]

    R. Cameron; M. Schuessler

    2006-12-22

    We study the origin of the predictive skill of some methods to forecast the strength of solar activity cycles. A simple flux transport model for the azimuthally averaged radial magnetic field at the solar surface is used, which contains a source term describing the emergence of new flux based on observational sunspot data. We consider the magnetic flux diffusing over the equator as a predictor, since this quantity is directly related to the global dipole field from which a Babcock-Leighton dynamo generates the toroidal field for the next activity cycle. If the source is represented schematically by a narrow activity belt drifting with constant speed over a fixed range of latitudes between activity minima, our predictor shows considerable predictive skill with correlation coefficients up to 0.95 for past cycles. However, the predictive skill is completely lost when the actually observed emergence latitudes are used. This result originates from the fact that the precursor amplitude is determined by the sunspot activity a few years before solar minimum. Since stronger cycles tend to rise faster to their maximum activity (known as the Waldmeier effect), the temporal overlapping of cycles leads to a shift of the minimum epochs that depends on the strength of the following cycle. This information is picked up by precursor methods and also by our flux transport model with a schematic source. Therefore, their predictive skill does not require a memory, i.e., a physical connection between the surface manifestations of subsequent activity cycles.

  17. Cathy Zoi on Weatherization

    ScienceCinema (OSTI)

    Zoi, Cath

    2013-05-29

    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.

  18. On the Predictiveness of Single-Field Inflationary Models

    E-Print Network [OSTI]

    C. P. Burgess; Subodh P. Patil; Michael Trott

    2015-07-20

    We re-examine the predictiveness of single-field inflationary models and discuss how an unknown UV completion can complicate determining inflationary model parameters from observations, even from precision measurements. Besides the usual naturalness issues associated with having a shallow inflationary potential, we describe another issue for inflation, namely, unknown UV physics modifies the running of Standard Model (SM) parameters and thereby introduces uncertainty into the potential inflationary predictions. We illustrate this point using the minimal Higgs Inflationary scenario, which is arguably the most predictive single-field model on the market, because its predictions for $A_s$, $r$ and $n_s$ are made using only one new free parameter beyond those measured in particle physics experiments, and run up to the inflationary regime. We find that this issue can already have observable effects. At the same time, this UV-parameter dependence in the Renormalization Group allows Higgs Inflation to occur (in principle) for a slightly larger range of Higgs masses. We comment on the origin of the various UV scales that arise at large field values for the SM Higgs, clarifying cut off scale arguments by further developing the formalism of a non-linear realization of $\\rm SU_L(2) \\times U(1)$ in curved space. We discuss the interesting fact that, outside of Higgs Inflation, the effect of a non-minimal coupling to gravity, even in the SM, results in a non-linear EFT for the Higgs sector. Finally, we briefly comment on post BICEP2 attempts to modify the Higgs Inflation scenario.

  19. 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)

    2014-06-19

    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.

  20. Early View (EV): 1-EV Nice weather for bettongs: using weather events, not climate

    E-Print Network [OSTI]

    Turner, Monica G.

    distribution using temporally matched observations of the species with weather data (includ- ing extremeEarly View (EV): 1-EV Nice weather for bettongs: using weather events, not climate means applications of species distribution models (SDM) are typically static, in that they are based on correlations

  1. SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity

    E-Print Network [OSTI]

    Bejerano, Gill

    SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity Qingyuan Zhao Stanford: Algorithms; Experimentation. Keywords: information diffusion; cascade prediction; self-exciting point process

  2. 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)

    2005-10-01

    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

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

    E-Print Network [OSTI]

    Bourg, Brandi Marie

    2009-05-15

    energy (ME) value was conducted. A meta-analysis of growing and finishing steers evaluated to model’s accuracy in predicting DMR of individually fed steers, and the relationships between several model-predicted variables and actual performance...

  4. Exploiting weather forecast data for cloud detection 

    E-Print Network [OSTI]

    Mackie, Shona

    2009-01-01

    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 ...

  5. Weather Photos - Hanford Site

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

    weather Mammatus clouds Mammatus clouds Mammatus Clouds Mammatus Clouds Mammatus clouds Mammatus clouds Downburst Downburst...

  6. 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

  7. Internally Electrodynamic Particle Model: Its Experimental Basis and Its Predictions

    E-Print Network [OSTI]

    Zheng-Johansson, J X

    2008-01-01

    The internally electrodynamic (IED) particle model was derived based on overall experimental observations, with the IED process itself being built directly on three experimental facts, a) electric charges present with all material particles, b) an accelerated charge generates electromagnetic waves according to Maxwell's equations and Planck energy equation and c)source motion produces Doppler effect. A set of well-known basic particle equations and properties become predictable based on first-principles solutions for the IED particles; several key solutions achieved will be outlined, including the de Broglie phase wave, de Broglie relations, Schr\\"odinger equation, mass, mass-energy relation, Newton's law of gravity, single particle self interference, and electromagnetic radiation and absorption; these equations or properties have long been broadly experimentally validated or demonstrated. The IED solution also predicts the Doebner-Goldin equation which emerges to represent a form of long-sought quantum wave ...

  8. 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

    2010-03-03

    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.

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

    SciTech Connect (OSTI)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    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.

  10. Predictive modeling of reactive wetting and metal joining.

    SciTech Connect (OSTI)

    van Swol, Frank B.

    2013-09-01

    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.

  11. Building a Weather-Ready Nation Fall Weather Safety

    E-Print Network [OSTI]

    Building a Weather-Ready Nation Fall Weather Safety www.weather.gov/safety Wildfire ­ Drought ­ Hurricanes ­ Wind ­ Early Season Winter ­ Flood #12;Building a Weather-Ready Nation Wildfire Safety smoking materials. weather.gov/wildfire www.weather.gov/safety #12;Building a Weather-Ready Nation

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

    SciTech Connect (OSTI)

    Dowding, Kevin J.; Rutherford, Brian Milne

    2003-07-01

    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

  13. Weather-based forecasts of California crop yields

    SciTech Connect (OSTI)

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

    2005-09-26

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

  14. Integration of traffic congestion and predictive modeling offers

    E-Print Network [OSTI]

    Bustamante, Fabián E.

    are far fewer issues when products are flown or driven across the country, but getting them to your home interacting more intimately with traffic congestion, the weather, and other day-to-day variants." To combat, and that is a major motivation," says Mahmassani. "Companies may also want to do the right thing, but we live

  15. 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

  16. 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

    2013-09-01

    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.

  17. Ocean-ice/oil-weathering computer program user's manual. Final report

    SciTech Connect (OSTI)

    Kirstein, B.E.; Redding, R.T.

    1987-10-01

    The ocean-ice/oil-weathering code is written in FORTRAN as a series of stand-alone subroutines that can easily be installed on most any computer. All of the trial-and-error routines, integration routines, and other special routines are written in the code so that nothing more than the normal system functions such as EXP are required. The code is user-interactive and requests input by prompting questions with suggested input. Therefore, the user can actually learn about the nature of crude oil and oil weathering by using this code. The ocean-ice oil-weathering model considers the following weathering processes: evaporation; dispersion (oil into water); moussee (water into oil); and spreading; These processes are used to predict the mass balance and composition of oil remaining in the slick as a function of time and environmental parameters.

  18. SNO+: predictions from standard solar models and spin flavour precession

    E-Print Network [OSTI]

    Marco Picariello; João Pulido; S. Andringa; N. F. Barros; J. Maneira

    2007-10-22

    Time variability of the solar neutrino flux especially in the low and intermediate energy sector remains an open question and, if it exists, it is likely to be originated from the magnetic moment transition from active to light sterile neutrinos at times of intense solar activity and magnetic field. We examine the prospects for the SNO+ experiment to address this important issue and to distinguish between the two classes of solar models which are currently identified as corresponding to a high (SSM I) and a low (SSM II) heavy element abundance. We also evaluate the predictions from these two models for the Chlorine experiment event rate in the standard LMA and LMA+Spin Flavour Precession (SFP) scenarios. It is found that after three years of SNO+ data taking, the pep flux measurement will be able to discriminate between the standard LMA and LMA+SFP scenarios, independently of which is the correct solar model. If the LMA rate is measured, SFP with $B_0 \\sim 280kG$ for the resonant $\\Delta m^2_{01}$ can be excluded at more than $4\\sigma$. A low rate would signal new physics, excluding all the 90% allowed range of the standard LMA solution at 3$\\sigma$, and a time variability would be a strong signature of the SFP model. The CNO fluxes are the ones for which the two SSM predictions exhibit the largest differences, so their measurement at SNO+ will be important to favour one or the other. The distinction will be clearer after LMA or SFP are confirmed with pep, but still, a CNO measurement at the level of SSM I/LMA will disfavour SSM II at about $3 \\sigma$. We conclude that consistency between future pep and CNO flux measurements at SNO+ and Chlorine would either favour an LMA+SFP scenario or favour SSM II over SSM I.

  19. How Computational Models Predict the Behavior of Complex Systems John Symons 1

    E-Print Network [OSTI]

    Boschetti, Fabio

    How Computational Models Predict the Behavior of Complex Systems John Symons 1 Fabio Boschetti2,3 1 of prediction in the use of computational models in science. We focus on the consequences of the irreversibility of computational models and on the conditional or ceteris paribus, nature of the kinds of their predictions

  20. Beating the bookie: A look at statistical models for prediction of football matches

    E-Print Network [OSTI]

    Langseth, Helge

    Beating the bookie: A look at statistical models for prediction of football matches Helge LANGSETH, Norway Abstract. In this paper we look at statistical models for predicting the outcome of football. Keywords. Association football, statistical models, predictions, betting 1. Introduction Association

  1. Colliding cascades model for earthquake prediction Andrei Gabrielov,1,2

    E-Print Network [OSTI]

    Gabrielov, Andrei

    Colliding cascades model for earthquake prediction Andrei Gabrielov,1,2 Ilya Zaliapin,3 William I Lafayette, IN 47907-1395, USA 3 International Institute of Earthquake Prediction Theory and Mathematical model of seismicity, and their performance in the prediction of major model earthquakes is evaluated

  2. Climate predictions: the chaos and complexity in climate models

    E-Print Network [OSTI]

    Dragutin T. Mihailovi?; Gordan Mimi?; Ilija Arseni?

    2013-10-15

    Some issues which are relevant for the recent state in climate modeling have been considered. A detailed overview of literature related to this subject is given. The concept in modeling of climate, as a complex system, seen through Godel's Theorem and Rosen's definition of complexity and predictability is discussed. It is pointed out to occurrence of chaos in computing the environmental interface temperature from the energy balance equation given in a difference form. A coupled system of equations, often used in climate models is analyzed. It is shown that the Lyapunov exponent mostly has positive values allowing presence of chaos in this systems. The horizontal energy exchange between environmental interfaces, which is described by the dynamics of driven coupled oscillators, is analyzed. Their behavior and synchronization, when a perturbation is introduced in the system, as a function of the coupling parameters, the logistic parameter and the parameter of exchange, was studied calculating the Lyapunov exponent under simulations with the closed contour of N=100 environmental interfaces. Finally, we have explored possible differences in complexities of two global and two regional climate models using their output time series by applying the algorithm for calculating the Kolmogorov complexity.

  3. Social Media: Space Weather #SpaceWeather

    E-Print Network [OSTI]

    causing blackouts in rare cases. To learn about space weather and impacts to the electric grid visit on the Power Grid Space Weather and the Aurora Borealis What are Solar Flares? What are Coronal Mass we do. Satellite communications, GPS applications, and the electric power grid provide the backbone

  4. Prerequisites Control Systems, System Modeling, Optimal Control, Model Predictive Control, (Engine Systems).

    E-Print Network [OSTI]

    Lygeros, John

    of High Performance Hybrid Race Cars Background The power unit of a high performance hybrid race carPrerequisites Control Systems, System Modeling, Optimal Control, Model Predictive Control, (Engine consists of an internal combustion engine (ICE) and a kinetic energy recovery system (KERS). The time

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

    E-Print Network [OSTI]

    Hsieh, William

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

  6. Internally Electrodynamic Particle Model: Its Experimental Basis and Its Predictions

    E-Print Network [OSTI]

    J. X. Zheng-Johansson

    2010-07-13

    The internally electrodynamic (IED) particle model was derived based on overall experimental observations, with the IED process itself being built directly on three experimental facts, a) electric charges present with all material particles, b) an accelerated charge generates electromagnetic waves according to Maxwell's equations and Planck energy equation and c) source motion produces Doppler effect. A set of well-known basic particle equations and properties become predictable based on first principles solutions for the IED process; several key solutions achieved are outlined, including the de Broglie phase wave, de Broglie relations, Schr\\"odinger equation, mass, Einstein mass-energy relation, Newton's law of gravity, single particle self interference, and electromagnetic radiation and absorption; these equations and properties have long been broadly experimentally validated or demonstrated. A specific solution also predicts the Doebner-Goldin equation which emerges to represent a form of long-sought quantum wave equation including gravity. A critical review of the key experiments is given which suggests that the IED process underlies the basic particle equations and properties not just sufficiently but also necessarily.

  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

    2012-07-22

    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. Weatherization Assistance Program

    Broader source: Energy.gov [DOE]

    This fact sheet provides an overview of the U.S. Department of Energys Weatherization Assistance Program.

  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)

    1997-01-01

    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.

    1997-08-19

    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. Weather Effects on European Agricultural Output 1850-1913

    E-Print Network [OSTI]

    Solomou, Solomos; Wu, Weike

    2004-06-16

    This paper compares the effects of weather shocks on agricultural production in Britain, France and Germany during the late nineteenth century. Using semi- parametric models to estimate the non-linear agro-weather relationship, we find...

  12. Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization

    E-Print Network [OSTI]

    Nocedal, Jorge

    Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization M. Fisher J weather prediction centers to produce the initial conditions for 7- to 10-day weather fore- casts, with particular reference to the system in operation at the European Centre for Medium-Range Weather Forecasts. 1

  13. Paintball Summer Weather

    E-Print Network [OSTI]

    Sin, Peter

    Highlights · Paintball · Summer Weather · Birthdays · Manners TheELIWeekly Paintball! Come out Turkey United States Venezuela Summer Weather Safety We've come to realize in the past that not all of our students are aware of our unique weather problems in Central Florida. One hazard that you should

  14. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    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

  15. WEATHER HAZARDS Basic Climatology

    E-Print Network [OSTI]

    WEATHER HAZARDS Basic Climatology Colorado Climate Center Funding provided by NOAA Sectoral) Wildfires (Jun 02) Recent Declared Disasters in Colorado No Map from FEMA provided #12;National Weather and Warnings Outlook Indicates that hazardous weather may develop ­ useful to those who need considerable

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

    E-Print Network [OSTI]

    Young, R. Michael

    are built with traditional metrics of complexity, code churn, and fault history. We have performed to the code [17]. Hence, complexity metrics and code churn metrics have been used for fault prediction [5, 17 fault prediction metrics ­ complexity, code churn, and fault history metrics for vulnerability

  17. Numerical and analytical modeling of sanding onset prediction 

    E-Print Network [OSTI]

    Yi, Xianjie

    2004-09-30

    To provide technical support for sand control decision-making, it is necessary to predict the production condition at which sand production occurs. Sanding onset prediction involves simulating the stress state on the surface of an oil/gas producing...

  18. The Dark Gravity model predictions for Gravity Probe B

    E-Print Network [OSTI]

    Frederic Henry-Couannier

    2007-10-23

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

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

    E-Print Network [OSTI]

    models and methods for predicting the wind power output from wind farms. The system is being developed are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions farms ­ the Prediktor model developed at Risø and the Wind Power Prediction Tool (WPPT) developed at IMM

  20. Selection of Ground Motion Prediction Equations for the Global Earthquake Model

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Selection of Ground Motion Prediction Equations for the Global Earthquake Model Jonathan P are developed. Keywords: Engineering seismology, ground-motion prediction, site effects, Global Earthquake Model.EERI, and Peter J. Stafford, h) M.EERI Ground-motion prediction equations (GMPEs) relate ground-motion intensity

  1. Building risk prediction models -with a focus on Genome-Wide Association Studies

    E-Print Network [OSTI]

    Brent, Roger

    Kooperberg Charles Kooperberg Predictive models for GWAS #12;Risk prediction models Based on data: (Di , Xi1;Selection of predictors. Selection of predictors on the same data as training and/or evaluating models can data to evaluate your model as is part of your cross-validation procedure biases your results

  2. 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

  3. 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'Ã?Â?Ã?Â?Day, University of California, Merced; Karl Mueller, Penn State University; Wooyong Um, Pacific Northwest National Laboratory; Carl Steefel, Lawrence Berkeley National Laboratory

    2012-10-01

    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.

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

    E-Print Network [OSTI]

    Virginia, University of

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

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

    E-Print Network [OSTI]

    Rodriguez-Escobar, Olga Lydia

    2009-05-15

    This study investigates the degree to which the cumulative risk index predicted school readiness in a Head Start population. In general, the reviewed studies indicated the cumulative risk model was efficacious in predicting adverse developmental...

  6. Scatterometer-Based Assessment of 10-m Wind Analyses from the Operational ECMWF and NCEP Numerical Weather Prediction Models

    E-Print Network [OSTI]

    Kurapov, Alexander

    .75 and 1.5 m s 1 for the along-wind and crosswind components, respectively. The NSCAT and QuikSCAT datasets

  7. Predictive models of safety based on audit findings: Part 1: Model development and reliability

    E-Print Network [OSTI]

    Wu, Changxu (Sean)

    tools to carry out an ergonomic evaluation of maintenance and inspection operations. It was validated, we developed a Human Factors/Ergonomics classifi- cation framework based on HFACS model (Shappell to proceed with prediction validity testing in Part 2. Ó 2012 Elsevier Ltd and The Ergonomics Society. All

  8. Diagnosis of the summertime warm and dry bias over the U. S. Southern Great Plains in the GFDL climate model using a weather forecasting approach

    SciTech Connect (OSTI)

    Klein, S A; Jiang, X; Boyle, J; Malyshev, S; Xie, S

    2006-07-11

    Weather forecasts started from realistic initial conditions are used to diagnose the large warm and dry bias over the United States Southern Great Plains simulated by the GFDL climate model. The forecasts exhibit biases in surface air temperature and precipitation within 3 days which appear to be similar to the climate bias. With the model simulating realistic evaporation but underestimated precipitation, a deficit in soil moisture results which amplifies the initial temperature bias through feedbacks with the land surface. The underestimate of precipitation is associated with an inability of the model to simulate the eastward propagation of convection from the front-range of the Rocky Mountains and is insensitive to an increase of horizontal resolution from 2{sup o} to 0.5{sup o} latitude.

  9. 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 ...

  10. 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 ...

  11. 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 ...

  12. Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling

    SciTech Connect (OSTI)

    Valerio, Luis G. . E-mail: luis.valerio@FDA.HHS.gov; Arvidson, Kirk B.; Chanderbhan, Ronald F.; Contrera, Joseph F.

    2007-07-01

    Consistent with the U.S. Food and Drug Administration (FDA) Critical Path Initiative, predictive toxicology software programs employing quantitative structure-activity relationship (QSAR) models are currently under evaluation for regulatory risk assessment and scientific decision support for highly sensitive endpoints such as carcinogenicity, mutagenicity and reproductive toxicity. At the FDA's Center for Food Safety and Applied Nutrition's Office of Food Additive Safety and the Center for Drug Evaluation and Research's Informatics and Computational Safety Analysis Staff (ICSAS), the use of computational SAR tools for both qualitative and quantitative risk assessment applications are being developed and evaluated. One tool of current interest is MDL-QSAR predictive discriminant analysis modeling of rodent carcinogenicity, which has been previously evaluated for pharmaceutical applications by the FDA ICSAS. The study described in this paper aims to evaluate the utility of this software to estimate the carcinogenic potential of small, organic, naturally occurring chemicals found in the human diet. In addition, a group of 19 known synthetic dietary constituents that were positive in rodent carcinogenicity studies served as a control group. In the test group of naturally occurring chemicals, 101 were found to be suitable for predictive modeling using this software's discriminant analysis modeling approach. Predictions performed on these compounds were compared to published experimental evidence of each compound's carcinogenic potential. Experimental evidence included relevant toxicological studies such as rodent cancer bioassays, rodent anti-carcinogenicity studies, genotoxic studies, and the presence of chemical structural alerts. Statistical indices of predictive performance were calculated to assess the utility of the predictive modeling method. Results revealed good predictive performance using this software's rodent carcinogenicity module of over 1200 chemicals, comprised primarily of pharmaceutical, industrial and some natural products developed under an FDA-MDL cooperative research and development agreement (CRADA). The predictive performance for this group of dietary natural products and the control group was 97% sensitivity and 80% concordance. Specificity was marginal at 53%. This study finds that the in silico QSAR analysis employing this software's rodent carcinogenicity database is capable of identifying the rodent carcinogenic potential of naturally occurring organic molecules found in the human diet with a high degree of sensitivity. It is the first study to demonstrate successful QSAR predictive modeling of naturally occurring carcinogens found in the human diet using an external validation test. Further test validation of this software and expansion of the training data set for dietary chemicals will help to support the future use of such QSAR methods for screening and prioritizing the risk of dietary chemicals when actual animal data are inadequate, equivocal, or absent.

  13. Transistor roadmap projection using predictive full-band atomistic modeling

    SciTech Connect (OSTI)

    Salmani-Jelodar, M., E-mail: m.salmani@gmail.com; Klimeck, G. [Network for Computational Nanotechnology and School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States); Kim, S. [Intel Corporation, 2501 Northwest 229th Avenue, Hillsboro, Oregon 97124 (United States); Ng, K. [Semiconductor Research Corporation (SRC), 1101 Slater Rd, Durham, North Carolina 27703 (United States)

    2014-08-25

    In this letter, a full band atomistic quantum transport tool is used to predict the performance of double gate metal-oxide-semiconductor field-effect transistors (MOSFETs) over the next 15?years for International Technology Roadmap for Semiconductors (ITRS). As MOSFET channel lengths scale below 20?nm, the number of atoms in the device cross-sections becomes finite. At this scale, quantum mechanical effects play an important role in determining the device characteristics. These quantum effects can be captured with the quantum transport tool. Critical results show the ON-current degradation as a result of geometry scaling, which is in contrast to previous ITRS compact model calculations. Geometric scaling has significant effects on the ON-current by increasing source-to-drain (S/D) tunneling and altering the electronic band structure. By shortening the device gate length from 20?nm to 5.1?nm, the ratio of S/D tunneling current to the overall subthreshold OFF-current increases from 18% to 98%. Despite this ON-current degradation by scaling, the intrinsic device speed is projected to increase at a rate of at least 8% per year as a result of the reduction of the quantum capacitance.

  14. Project Profile: Predictive Physico-Chemical Modeling of Intrinsic...

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

    Advanced Reflector Materials NREL logo NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing...

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

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

    This paper describes an Eulerian axisymmetric method in Fluent(R) to predict the overall heat transfer reduction of a surrogate tube due to thermophoretic deposition of submicron...

  16. Weather-Corrected Performance Ratio

    SciTech Connect (OSTI)

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

    2013-04-01

    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.

  17. Preprints, 15th AMS Conference on Weather Analysis and Forecasting

    E-Print Network [OSTI]

    Doswell III, Charles A.

    ) models have substantially improved forecast skill. Recent and planned changes along these lines (e to delivering two kinds of weather products. The first is a day-to-day forecast of weather elements, e by the private sector. Improvements in automated techniques for the forecasting of basic weather elements

  18. The Ideal Evaluation of a Risk Prediction Model: A Randomized Clinical Trial

    E-Print Network [OSTI]

    Brent, Roger

    The Ideal Evaluation of a Risk Prediction Model: A Randomized Clinical Trial Holly Janes Fred Hutchinson Cancer Research Center 1/25 #12;Context Often a risk prediction model is developed to identify high risk subjects who can benefit from preventative therapy E.g. Framingham risk model to identify

  19. 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

  20. A Geologic Prediction Model For Tunneling By Photios G. Ioannou, A.M. ASCE

    E-Print Network [OSTI]

    A Geologic Prediction Model For Tunneling By Photios G. Ioannou, A.M. ASCE Abstract: Geologic to inflated costs. This paper presents a general model for the probabilistic prediction of tunnel geology. The geologic conditions along the tunnel alignment are modeled by a set of geologic parameters (such as rock

  1. Is Weather Chaotic?

    E-Print Network [OSTI]

    Ales Raidl

    1998-10-13

    The correlation dimension and K2-entropy are estimated from meteorological time- series. The results lead us to claim that seasonal variability of weather is under influence of low dimensional dynamics, whereas changes of weather from day to day are governed by high dimensional system(s). Error-doubling time of this system is less than 3 days. We suggest that the outstanding feature of the weather dynamics is deterministic chaos.

  2. Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data

    Broader source: Energy.gov [DOE]

    Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data Elizabeth J. Kelly and Raymond N. Tell

  3. Second International Workshop on Social Computing, Behavioral Modeling, and Prediction Phoenix, Arizona

    E-Print Network [OSTI]

    Liu, Huan

    Second International Workshop on Social Computing, Behavioral Modeling, and Prediction Phoenix, Arizona March 31 - April 1, 2009 Phoenix, Arizona Proceedings published by Springer Social computing

  4. Weather Charts - Hanford Site

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

    Meteorological Station > Met and Climate Data Summary Products > Historical Weather Charts Hanford Meteorological Station Real Time Met Data from Around the Site Current HMS...

  5. The Weatherization Training program at Pennsylvania College

    ScienceCinema (OSTI)

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

    2013-05-29

    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.

  6. The Weatherization Training program at Pennsylvania College

    SciTech Connect (OSTI)

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

    2010-01-01

    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.

  7. The Weatherization Training program at Pennsylvania College

    Broader source: Energy.gov [DOE]

    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...

  8. A System for Online Power Prediction in Virtualized Environments Using Gaussian Mixture Models

    E-Print Network [OSTI]

    Simunic, Tajana

    A System for Online Power Prediction in Virtualized Environments Using Gaussian Mixture Models In this paper we present a system for online power prediction in vir- tualized environments. It is based dynamically by our system to predict both the physical machine and per VM level power consumption. A real

  9. Parametric Urban Regulation Models for Predicting Development Performances 

    E-Print Network [OSTI]

    Kim, Jong Bum

    2014-12-23

    are significant indicators for predicting environmental footprints for the resource managements (Fischer and Guy, 2009; Lang, 1994; Punter, 1997). The prescriptive urban regulations such as FBC are less rigid in limiting density than the conventional zoning...

  10. 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

    2013-01-01

    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...

  11. Management of Weather and Climate Disputes

    E-Print Network [OSTI]

    Weiss, Edith Brown

    1983-01-01

    who may suffer harm from weather modification, efforts mustmitigating disputes over weather and cli- mate changes.Legal Implications of Weather Modification, in WEATHER

  12. Home Weatherization Visit

    ScienceCinema (OSTI)

    Chu, Steven

    2013-05-29

    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.

  13. Improving Computational Efficiency of Prediction in Model-based Prognostics Using the Unscented Transform

    E-Print Network [OSTI]

    Daigle, Matthew

    , and availability. Prognos- tics deals with determining the health state of compo- nents, and projecting) predictions. Model-based prognos- tics approaches perform these tasks with the aid of a model that captures

  14. Interval Methods for Sensitivity-Based Model-Predictive Control of

    E-Print Network [OSTI]

    Kearfott, R. Baker

    Interval Methods for Sensitivity-Based Model-Predictive Control of Solid Oxide Fuel Cell Systems and experiment for the thermal subprocess of a high-temperature solid oxide fuel cell system. Keywords: Interval analysis, model-predictive control, sensitivity analysis, tracking control, solid oxide fuel cells AMS

  15. 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

  16. Flood control of the Demer by using Model Predictive Control Maarten Breckpot a,n

    E-Print Network [OSTI]

    rainfall. Also hydraulic structures were built to control the discharges in the river and the water goingFlood control of the Demer by using Model Predictive Control Maarten Breckpot a,n , Oscar Mauricio 2013 Keywords: Model Predictive Control Flood control Kalman filter Open channel flow a b s t r a c

  17. 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

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

    E-Print Network [OSTI]

    Chen, Sheng

    A data-based approach for multivariate model predictive control performance monitoring$ Xuemin Tian of Petroleum (Hua Dong), Donying, Shandong 257061, China b School of Electronics and Computer Science by J. Zhang Available online 20 October 2010 Keywords: Model predictive control Performance monitoring

  19. ITER predictions using the GYRO verified and experimentally validated trapped gyro-Landau fluid transport model

    E-Print Network [OSTI]

    Budny, Robert

    predictions using the GYRO verified and experimentally validated trapped gyro-Landau fluid transport model JITER predictions using the GYRO verified and experimentally validated trapped gyro-Landau fluid transport model This article has been downloaded from IOPscience. Please scroll down to see the full text

  20. A Real-time Framework for Model Predictive Control of Continuous-Time Nonlinear Systems

    E-Print Network [OSTI]

    Sontag, Eduardo

    for piecewise constant NMPC of continuous-time processes. Index Terms-- nonlinear model predictive control, real-time optimization, optimal control, piecewise constant control I. INTRODUCTION Model predictive control (MPC horizon, open-loop optimal control problem. The unprecedented industrial success of MPC ap- proaches based

  1. 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

  2. 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

  3. Predictive Modeling of Large-Scale Commercial Water Desalination Plants: Data-Based Neural Network and Model-Based Process

    E-Print Network [OSTI]

    Liu, Y. A.

    Predictive Modeling of Large-Scale Commercial Water Desalination Plants: Data-Based Neural Network for developing predictive models for large-scale commercial water desalination plants by (1) a data (MSF) and reverse osmosis (RO) desalination plants in the world. Our resulting neural network

  4. 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

    2011-01-01

    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.

  5. MBGP IN MODELLING AND PREDICTION Carlos OliverMorales

    E-Print Network [OSTI]

    Fernandez, Thomas

    (MB­GP) encoding. Having multiple branches representing an individual allows us to get simpler), relative humidity (H), solar radiation (R) and wind speed (V) and direction (D) were recorded. The time). Cost function was predictive error­based metric. For each experiment, 20 runs were evaluated in order

  6. OCEAN PREDICTION WITH THE HYBRID COORDINATE OCEAN MODEL (HYCOM)

    E-Print Network [OSTI]

    . of South Florida, Fugro-GEOS, ROFFS, Orbimage, Shell, ExxonMobil #12;414 ERIC P. CHASSIGNET ET AL-resolving, real-time global and basin-scale ocean prediction system in the context of the Global Ocean Data Assimilation Experiment (GODAE). Keywords: HYCOM, GODAE, LAS, data assimilation, metrics. 1. Introduction

  7. 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

  8. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would like submit theCovalent Bonding Low-Cost2 DOE HQSiteo n n eDPFJ.D.

  9. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal Gas &SCE-SessionsSouthReport for the WeldonB10081278 United Statestnv~ronmenrar~

  10. Variable horizon model predictive control: robustness and optimality

    E-Print Network [OSTI]

    Shekhar, Rohan Chandra

    2012-07-03

    . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 6.3 Kinematic vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 6.4 Mechanism model showing generalised coordinates . . . . . . . . . . . . . . . . 109 6.5 Static balance of material failure forces... .1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 6.1.1 Nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 6.2 Mechanism Model...

  11. 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, ...

  12. 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 of weather data. Although many new digital weather and forecast datasets are gridded data, the current improvements made to an artificial neuralnetwork for forecasting weather-based potato late blight (Phytophthora

  13. Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar

    E-Print Network [OSTI]

    radar data. 1 Introduction The National Weather Service operates the WSR-88D (Weather Surveillance Radar, weather, and even airborne dust. Consequently, data must be interpreted manually by a highly information collected by Doppler radar. Our model is based on wind profiling algorithms from the weather

  14. 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

  15. NOAA's National Weather Service Building a Weather-Ready Nation

    E-Print Network [OSTI]

    NOAA's National Weather Service Building a Weather-Ready Nation For more information, please visit: www.noaa.gov and www.nws.noaa.gov NOAA's National Weather Service (NWS) is the Nation's official source for weather and water data, forecasts, and warnings. From information accessed on your smartphone

  16. Cointegration of the Daily Electric Power System Load and the Weather

    E-Print Network [OSTI]

    Stefanov, Stefan Z

    2007-01-01

    The paper examines the cointegration of the daily electric power system load and the weather by a field intelligent system. The daily load has been modelled by dynamic regressions. A "Daily Artificial Dispather" thermal intelligent system has been costructed. Time and energy tests have been obtained for this intelligent system. The improvement in the daily load forecast, achieved by this intelligent system, has been obtained. The predicted daily electricity price has been found.

  17. 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.

  18. Neighborhood Weatherization, Houston 

    E-Print Network [OSTI]

    Fowler, M.

    2011-01-01

    . Referrals http://www.click2houston.com/video/24501979/index.html 2010 CLEAResult. All rights reserved. Milestone Celebration 2010 CLEAResult. All rights reserved. 10,000 Homes Weatherized 2010 CLEAResult. All rights reserved. CATEE...

  19. Home Weatherization Visit

    Broader source: Energy.gov [DOE]

    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...

  20. Weatherizing Wilkes-Barre

    ScienceCinema (OSTI)

    Calore, Joe

    2013-05-29

    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.

  1. 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

    2013-12-18

    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.

  2. 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

    2009-01-10

    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.

  3. Comparison of Uncertainty of Two Precipitation Prediction Models...

    Office of Scientific and Technical Information (OSTI)

    Lab Technical Area 54 Meteorological inputs are an important part of subsurface flow and transport modeling. The choice of source for meteorological data used as inputs has...

  4. Predictive Models of Li-ion Battery Lifetime (Presentation) (Conference) |

    Office of Scientific and Technical Information (OSTI)

    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield MunicipalTechnical Report:Speeding access toSmall Reactor forPatents -SciTech Connect Predictive

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

    E-Print Network [OSTI]

    Hall, T; Hall, Tim; Jewson, Stephen

    2006-01-01

    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.

  6. Unbiased Statistical Comparison of Creep and Shrinkage Prediction Models

    E-Print Network [OSTI]

    , important for designing durable and safe concrete structures. Statistical methods of standard and several to improper data sampling in the database, and then examines Bazant and Baweja's model B3, ACI model, CEB of least squares, which is the standard and the only statistically correct method, dictated by the maximum

  7. Simulations of Clouds and Sensitivity Study by Weather Research and Forecast Model for Atmospheric Radiation Measurement Case 4

    SciTech Connect (OSTI)

    Wu, J.; Zhang, M.

    2005-03-18

    One of the large errors in general circulation models (GCMs) cloud simulations is from the mid-latitude, synoptic-scale frontal cloud systems. Now, with the availability of the cloud observations from Atmospheric Radiation Measurement (ARM) 2000 cloud Intensive Operational Period (IOP) and other observational datasets, the community is able to document the model biases in comparison with the observations and make progress in development of better cloud schemes in models. Xie et al. (2004) documented the errors in midlatitude frontal cloud simulations for ARM Case 4 by single-column models (SCMs) and cloud resolving models (CRMs). According to them, the errors in the model simulated cloud field might be caused by following reasons: (1) lacking of sub-grid scale variability; (2) lacking of organized mesoscale cyclonic advection of hydrometeors behind a moving cyclone which may play important role to generate the clouds there. Mesoscale model, however, can be used to better under stand these controls on the subgrid variability of clouds. Few studies have focused on applying mesoscale models to the forecasting of cloud properties. Weaver et al. (2004) used a mesoscale model RAMS to study the frontal clouds for ARM Case 4 and documented the dynamical controls on the sub-GCM-grid-scale cloud variability.

  8. Vulnerability and adaptation to severe weather events in the American southwest

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

    Boero, Riccardo; Bianchini, Laura; Pasqualini, Donatella

    2015-05-04

    Climate change can induce changes in the frequency of severe weather events representing a threat to socio-economic development. It is thus of uttermost importance to understand how the vulnerability to the weather of local communities is determined and how adaptation public policies can be effectively put in place. We focused our empirical analysis on the American Southwest. Results show that, consistently with the predictions of an investment model, economic characteristics signaling local economic growth in the near future decrease the level of vulnerability. We also show that federal governments transfers and grants neither work to support recovery from and adaptationmore »to weather events nor to distribute their costs over a broader tax base. Finally, we show that communities relying on municipal bonds to finance adaptation and recovery policies can benefit from local acknowledgment of the need for such policies and that they do not have to pay lenders a premium for the risk induced by weather events. In conclusion, our findings suggest that determinants of economic growth support lower vulnerability to the weather and increase options for financing adaptation and recovery policies, but also that only some communities are likely to benefit from those processes.« less

  9. 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

    2012-01-01

    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.

  10. 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 in process control to the more thoroughly studied Flight Management System (FMS) employed in airline cockpits and challenging task. Keywords: Cognitive task analysis; Process control; Predictive control; Optimization

  11. Ecological Modelling 185 (2005) 513529 Air quality prediction in Milan: feed-forward neural networks,

    E-Print Network [OSTI]

    Corani, Giorgio

    2005-01-01

    Ecological Modelling 185 (2005) 513­529 Air quality prediction in Milan: feed-forward neural December 2004; accepted 3 January 2005 Abstract Ozone and PM10 constitute the major concern for air quality of Milan. This paper addresses the problem of the prediction of such two pollutants, using to this end

  12. 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

  13. Mixtures of Predictive Linear Gaussian Models for Nonlinear Stochastic Dynamical Systems

    E-Print Network [OSTI]

    Baveja, Satinder Singh

    Mixtures of Predictive Linear Gaussian Models for Nonlinear Stochastic Dynamical Systems David dynamical systems. The primary contribution of this work is to extend the PLG to nonlinear, stochastic- proves upon traditional linear dynamical system mod- els by using a predictive representation of state

  14. Wind Speed Modelling and Short-term Predic-tion using Wavelets

    E-Print Network [OSTI]

    Nason, Guy

    prediction of the wind regime at a proposed wind farm site. Suppose a small amount of wind speed data hasWind Speed Modelling and Short-term Predic- tion using Wavelets Katherine Hunt and Guy P Nason@bristol.ac.uk Abstract The mathematical method of wavelets is explained and used to predict wind condi- tions using short

  15. Scientific Programming 11 (2003) 159176 159 A performance-prediction model for PIC

    E-Print Network [OSTI]

    Vlad, Gregorio

    2003-01-01

    Scientific Programming 11 (2003) 159­176 159 IOS Press A performance-prediction model for PIC hierarchical workload decomposition strategies for particle in cell (PIC) codes on Clusters of Symmetric Multi of parallelization efficiency are compared with the predicted results. 1. Introduction Particle-in-cell (PIC

  16. 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

  17. 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

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

    E-Print Network [OSTI]

    Pedram, Massoud

    `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 the residual energy of the battery source that powers a portable electronic device is imperative in designing

  19. 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

  20. 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

  1. 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

  2. Terminal Spacecraft Rendezvous and Capture with LASSO Model Predictive Control

    E-Print Network [OSTI]

    Hartley, Edward N.; Gallieri, Marco; Maciejowski, Jan M.

    2013-08-20

    . Int. Conf. Instrumentation, Communication Information Technology, and Biomedical Engineering, Badung, 23–25 Nov, pp. 435–439. Kawai, F., Ito, H., Nakazawa, C., Matsui, T., Fukuyama, Y., Suzuki, R., and Aiyoshi, E. (2007), “Automatic Tuning for Model...

  3. Predictive models for power dissipation in optical transceivers

    E-Print Network [OSTI]

    Butler, Katherine, 1981-

    2004-01-01

    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 ...

  4. Validity of the WEPP model for predicting infiltration on irrigated lands 

    E-Print Network [OSTI]

    Ngang, Fidelis Ndemah

    1995-01-01

    The objective of this research was to establish the validity of the hydrologic component of the YVEPP erosion model for predicting infiltration on irrigated lands. WEPP uses the Green and Ampt equation with ponding to compute infiltration...

  5. Switching Strategy for Direct Model Predictive Control in Power Converter and Drive Applications

    E-Print Network [OSTI]

    Noé, Reinhold

    of permanent magnet synchronous motors with interior magnets (IPMSM). Index Terms--Direct Model Predictive Direct-MPC approaches, a more flexible gate-signal generation method which enables switching during

  6. A predictive, size-dependent continuum model for dense granular flows

    E-Print Network [OSTI]

    Henann, David Lee

    Dense granular materials display a complicated set of flow properties, which differentiate them from ordinary fluids. Despite their ubiquity, no model has been developed that captures or predicts the complexities of granular ...

  7. Insights into Conventional and Low Temperature Diesel Combustion Using Combustion Trajectory Prediction Model 

    E-Print Network [OSTI]

    Bittle, Joshua A

    2014-04-18

    Attempting to bridge the gap between typical off-line engine simulations and online real-time control strategies a computationally efficient model has been created that predicts the combustion trajectory (path through the ?-T plane). To give...

  8. ECOLOGICAL NICHE MODELING AS A PREDICTIVE TOOL: ASIATIC FRESHWATER FISHES IN NORTH AMERICA

    E-Print Network [OSTI]

    Chen, Pingfu

    2008-05-30

    appropriately. After introduction, the most effective way is to predict their spread, to discover populations early, and to adopt measures to eradicate or at least contain them. This dissertation uses ecological niches modeling to estimate the ecological...

  9. Guidance and control using model predictive control for low altitude real-time terrain following flight

    E-Print Network [OSTI]

    Lapp, Tiffany Rae, 1979-

    2004-01-01

    This thesis presents the design and implementation of a model predictive control based trajectory optimization method for Nap-of-the-Earth (NOE) flight. A NOE trajectory reference is generated over a subspace of the terrain. ...

  10. Prediction Capabilities of Vulnerability Discovery Models Omar H. Alhazmi, Colorado State University

    E-Print Network [OSTI]

    Malaiya, Yashwant K.

    Prediction Capabilities of Vulnerability Discovery Models Omar H. Alhazmi, Colorado State Discovery Models (VDMs) have been proposed to model vulnerability discovery and have has been fitted discovery process, presenting a static approach to estimating the initial values of one of the VDM

  11. 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

  12. TESTS OF 1-D TRANSPORT MODELS, AND THEIR PREDICTIONS FOR ITER

    E-Print Network [OSTI]

    Vlad, Gregorio

    . INTRODUCTION Predictions of ITER based on validated 1-D transport models would provide: 1) a physical research programs. Many transport models have been partially tested against tokamak data [1]. In order to establish how well each model represents the wide range of existing tokamak data we have developed the ITER

  13. 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

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

    E-Print Network [OSTI]

    Cao, Quang V.

    of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA b School of Renewable Natural ResourcesPrediction of tree diameter growth using quantile regression and mixed-effects models Som B. Bohora is an important component of an individual-tree model. This function can be considered as a mixed-effects model

  15. 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

    2013-06-19

    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.

  16. 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.

    2006-01-01

    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...

  17. On the Predictive Uncertainty of a Distributed Hydrologic Model 

    E-Print Network [OSTI]

    Cho, Huidae

    2009-05-15

    of the San Jacinto River watershed. . . . . . . . . . . . . . 14 2 Barton Creek and Onion Creek watersheds. . . . . . . . . . . . . . . 15 3 Streamflow versus runoff for selected models out of the 54 cali- brated models...?99 SOL AWC Available water capacity of the soil layer (mm H2O/mm soil) 0.0?1.0 ESCO Soil evaporation compensation factor 0.01?1.0 GWQMN Threshold depth of water in the shallow aquifer re- quired for return flow to occur (mm H2O) 0?5000 GW REVAP...

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

    E-Print Network [OSTI]

    Wang, Faming

    2004-11-15

    in examining a dynamical system. The origin and growth of small perturbations are often attributed to the 10 existence of unstable modes. In the limit of long times, the ?rst normal mode (least damped mode) dominates the response. The above classical stability... for the linear case. Recently, Neumaier and Schneider (2001) developed a procedure to estimate eigen- modes of high order autoregressive (AR) models, while (2.3) is basically an AR(1) model. Traditionally, the least damped eigenmodes are considered to be the most...

  19. Predicting carcinogenicity of diverse chemicals using probabilistic neural network modeling approaches

    SciTech Connect (OSTI)

    Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com [Academy of Scientific and Innovative Research, Council of Scientific and Industrial Research, New Delhi (India); Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow 226 001 (India); Gupta, Shikha; Rai, Premanjali [Academy of Scientific and Innovative Research, Council of Scientific and Industrial Research, New Delhi (India); Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow 226 001 (India)

    2013-10-15

    Robust global models capable of discriminating positive and non-positive carcinogens; and predicting carcinogenic potency of chemicals in rodents were developed. The dataset of 834 structurally diverse chemicals extracted from Carcinogenic Potency Database (CPDB) was used which contained 466 positive and 368 non-positive carcinogens. Twelve non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals and nonlinearity in the data were evaluated using Tanimoto similarity index and Brock–Dechert–Scheinkman statistics. Probabilistic neural network (PNN) and generalized regression neural network (GRNN) models were constructed for classification and function optimization problems using the carcinogenicity end point in rat. Validation of the models was performed using the internal and external procedures employing a wide series of statistical checks. PNN constructed using five descriptors rendered classification accuracy of 92.09% in complete rat data. The PNN model rendered classification accuracies of 91.77%, 80.70% and 92.08% in mouse, hamster and pesticide data, respectively. The GRNN constructed with nine descriptors yielded correlation coefficient of 0.896 between the measured and predicted carcinogenic potency with mean squared error (MSE) of 0.44 in complete rat data. The rat carcinogenicity model (GRNN) applied to the mouse and hamster data yielded correlation coefficient and MSE of 0.758, 0.71 and 0.760, 0.46, respectively. The results suggest for wide applicability of the inter-species models in predicting carcinogenic potency of chemicals. Both the PNN and GRNN (inter-species) models constructed here can be useful tools in predicting the carcinogenicity of new chemicals for regulatory purposes. - Graphical abstract: Figure (a) shows classification accuracies (positive and non-positive carcinogens) in rat, mouse, hamster, and pesticide data yielded by optimal PNN model. Figure (b) shows generalization and predictive abilities of the interspecies GRNN model to predict the carcinogenic potency of diverse chemicals. - Highlights: • Global robust models constructed for carcinogenicity prediction of diverse chemicals. • Tanimoto/BDS test revealed structural diversity of chemicals and nonlinearity in data. • PNN/GRNN successfully predicted carcinogenicity/carcinogenic potency of chemicals. • Developed interspecies PNN/GRNN models for carcinogenicity prediction. • Proposed models can be used as tool to predict carcinogenicity of new chemicals.

  20. Comparison between JET Profile Data and the Predictions of a Transport Model Based on ITG and Trapped Electron Modes

    E-Print Network [OSTI]

    Comparison between JET Profile Data and the Predictions of a Transport Model Based on ITG and Trapped Electron Modes

  1. 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

  2. Incorporating Control Performance Tuning into Economic Model Predictive Control

    E-Print Network [OSTI]

    Olanrewaju, Olumuyiwa I.; Maciejowski, Jan M.

    2015-01-01

    [1] A. Singh, J. Forbes, P. Vermeer, and S. Woo, “Model-based real-time optimization of automotive gasoline blending operations,” Journal of Process Control, vol. 10, no. 1, pp. 43 – 58, 2000. [2] A. Toumi and S. Engell, “Optimization-based control...

  3. Bayesian System Identification and Response Predictions Robust to Modeling Uncertainty

    E-Print Network [OSTI]

    Beck, James L.

    .g. system ID, structural health monitoring, robust control, state &/or parameter estimation ) #12;33 Outline of seismic ground acceleration Finite element model with uncertain parameters Posterior analysis: During;55 System performance measure in the presence of uncertainty: Failure probability + - "Failure" t(t)iy i b i

  4. Comparison of Thermal Properties Predicted by Interatomic Potential Models

    E-Print Network [OSTI]

    Cai, Wei

    ). The state-of-the-art free energy methods are used to determine the melting points of these models within]. In the "free-energy" method, the Gibbs free energies of the solid and liquid phases are computed as functions of temperature, and the melting point is determined by their intersection point. The free energy method has been

  5. NONLINEAR MODEL PREDICTIVE CONTROL WITH MOVING HORIZON STATE AND

    E-Print Network [OSTI]

    Van den Hof, Paul

    referred to as air pollution or "post-combustion" control systems). In this paper only the combustion - WITH APPLICATION TO MSW COMBUSTION M. Leskens , L.B.M. van Kessel , P.M.J. Van den Hof and O.H. Bosgra strategy are demonstrated by applying it to a model of a municipal solid waste (MSW) combustion plant under

  6. New Tools in Non-Linear Modelling and Prediction

    E-Print Network [OSTI]

    Jones, Antonia J.

    networks . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 5 A case study: Thames River Valley 28 5.1 The Thames river valley region . . . . . . . . . . . . . . . . . . . 28 5.2 Model identification of attributes, a single run of the Gamma test typically takes a few seconds. Around this essentially simple

  7. Experimental Validation of Stochastic Wireless Urban Channel Model: Estimation and Prediction

    SciTech Connect (OSTI)

    Kuruganti, Phani Teja [ORNL] [ORNL; Ma, Xiao [ORNL] [ORNL; Djouadi, Seddik M [ORNL] [ORNL

    2012-01-01

    Stochastic differential equations (SDE) can be used to describe the time-varying nature of wireless channels. This paper validates a long-term fading channel model for estimation and prediction from solely using measured received signal strength measurements. Such channel models can be used for optimizing wireless networks deployed for industrial automation, public access, and communication. This paper uses two different sets of received signal measurement data to estimate an predict the signal strength based on past measurements. The realworld performance of the estimation and prediction algorithm is demonstrated.

  8. 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.

    2014-02-01

    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.

  9. WORKSHOP ON RADIATION BELTS: MODELS & STANDARDS, BRUSSELS, 17{20 OCT., 1995 Los Alamos Geosynchronous Space Weather Data For

    E-Print Network [OSTI]

    Reeves, Geoffrey D.

    WORKSHOP ON RADIATION BELTS: MODELS & STANDARDS, BRUSSELS, 17{20 OCT., 1995 Los Alamos. Henderson, R. A. Christensen, P. S. McLachlan, and J. C. Ingraham Los Alamos National Laboratory, Mail Stop D436, Los Alamos, NM 87545, USA, reeves@lanl.gov Abstract. This paper presents an overview

  10. Inside-Out Infall Formation of Disk Galaxies: Do Predictions Differ from Models without Size Evolution?

    E-Print Network [OSTI]

    Rychard J. Bouwens; Laura Cayon; Joseph Silk

    1997-09-13

    We develop an idealized inside-out formation model for disk galaxies to include a realistic mix of galaxy types and luminosities that provides a fair match to the traditional observables. The predictions of our infall models are compared against identical models with no-size evolution by generating fully realistic simulations of the HDF, from which we recover the angular size distributions. We find that our infall models produce nearly identical angular size distributions to those of our no-size evolution models in the case of a Omega = 0 geometry but produce slightly smaller sizes in the case of a Omega = 1 geometry, a difference we associate with the fact that there is a different amount of cosmic time in our two models for evolving to relatively low redshifts (z \\approx 1-2). Our infall models also predict a slightly smaller (11% - 29%) number of large (disk scale lengths > 4 h_{50} ^{-1} kpc) galaxies at z \\approx 0.7 for the CFRS as well as different increases in the central surface brightness of the disks for early-type spirals, the infall model predicting an increase by 1.2 magnitudes out to z \\approx 2 (Omega = 0), 1 (Omega = 1), while our no-size evolution models predict an increase of only 0.5 magnitude. This result suggests that infall models could be important for explaining the 1.2-1.6 magnitude increase in surface brightness reported by Schade et al. (1995, 1996a, 1996b).

  11. Predictive modeling of synergistic effects in nanoscale ion track formation

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

    Zarkadoula, Eva; Pakarinen, Olli H.; Xue, Haizhou; Zhang, Yanwen; Weber, William J.

    2015-08-05

    Molecular dynamics techniques and the inelastic thermal spike model are used to study the coupled effects of inelastic energy loss due to 21 MeV Ni ion irradiation and pre-existing defects in SrTiO3. We determine the dependence on pre-existing defect concentration of nanoscale track formation occurring from the synergy between the inelastic energy loss and the pre-existing atomic defects. We show that the nanoscale ion tracks’ size can be controlled by the concentration of pre-existing disorder. This work identifies a major gap in fundamental understanding concerning the role played by defects in electronic energy dissipation and electron–lattice coupling.

  12. Setups for Weathering Tests 

    E-Print Network [OSTI]

    Unknown

    2011-08-17

    cotton. This Web-based decision support system, the Crop Weather Program for South Texas (CWP), is stationed out of the Texas AgriLife Research and Extension Center at Corpus Christi. The program provides easy access to his- torical and current... weather data as well as cal- culators and other tools that generate useful field-specific information about the crop and its environment, said Dr. Carlos J. Fern?ndez, associate professor and the Plant Physiology and Cropping Systems Program?s leader...

  13. Building a Statistical Model toBuilding a Statistical Model to Predict Reactor TemperaturesPredict Reactor Temperatures

    E-Print Network [OSTI]

    Scarrott, Carl

    ENGXT +++= )F( ­ Temperature at Channel (i,j) ­ Fuel Irradiation for Channel (r,s) ­ Direct and Neutron(.)?How to Model F(.)? l Effect of Fuel Irradiation on Temperatures l Direct Non-Linear Effect l Neutron Diffusion Region Cold Outer Region l Similar Behaviour ­ Sharp Increase ­ Constant l Weak Relationship l Scatter

  14. Intelligent weather agent for aircraft severe weather avoidance 

    E-Print Network [OSTI]

    Bokadia, Sangeeta

    2002-01-01

    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...

  15. Value of global weather sensors

    SciTech Connect (OSTI)

    Canavan, G.H.

    1998-12-23

    Long-range weather predictions have great scientific and economic potential, but require precise global observations. Small balloon transponders could serve as lagrangian trace particles to measure the vector wind, which is the primary input to long-range numerical forecasts. The wind field is difficult to measure; it is at present poorly sampled globally. Distance measuring equipment (DME) triangulation of signals from roughly a million transponders could sample it with sufficient accuracy to support {approximately} two week forecasts. Such forecasts would have great scientific and economic potential which is estimated below. DME uses small, low-power transmitters on each transponder to broadcast short, low-power messages that are detected by several small receivers and forwarded to the ground station for processing of position, velocity, and state information. Thus, the transponder is little more than a balloon with a small radio, which should only weigh a few grams and cost a few dollars.

  16. Comparison of LMA and LOW Solar Solution Predictions in an SO(10) GUT Model

    E-Print Network [OSTI]

    Carl H. Albright; S. Geer

    2002-02-15

    Within the framework of an SO(10) GUT model that can accommodate both the LMA and LOW solar neutrino mixing solutions by appropriate choice of the right-handed Majorana matrix elements, we present explicit predictions for the neutrino oscillation parameters \\Delta m^2_{21}, \\sin^2 2\\theta_{12}, \\sin^2 2\\theta_{23}, \\sin^2 2\\theta_{13}, and \\delta_{CP}. Given the observed near maximality of the atmospheric mixing, the model favors the LMA solution and predicts that \\delta_{CP} is small. The suitability of Neutrino Superbeams and Neutrino Factories for precision tests of the two model versions is discussed.

  17. Infiltration as Ventilation: Weather-Induced Dilution

    E-Print Network [OSTI]

    Sherman, Max H.

    2014-01-01

    LOGICS. 1999. Canadian Weather for Energy Calculations, In:natural ventilation rate with weather conditions, Renewablefor ASHRAE 136 [1/h] WSF Weather and Shielding Factor [1/h

  18. Particulate air quality model predictions using prognostic vs. diagnostic meteorology in central California

    E-Print Network [OSTI]

    Chen, Shu-Hua

    Particulate air quality model predictions using prognostic vs. diagnostic meteorology in central a , Michael J. Kleeman c,* a Department of Land, Air and Water Resources, University of California, Davis, 1 Prognostic meteorological fields Data assimilation UCD/CIT air quality model California Regional Particulate

  19. 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

  20. Prediction of Functional Sites Based on the Fuzzy Oil Drop Model

    E-Print Network [OSTI]

    Skolnick, Jeff

    Prediction of Functional Sites Based on the Fuzzy Oil Drop Model Michal Brylin´ski1,2 , Katarzyna, Astronomy and Applied Computer Science, Jagiellonian University, Krako´w, Poland, 4 Institute of Medical Oil Drop model. PLoS Comput Biol 3(5): e94. doi:10.1371/journal.pcbi.0030094 Introduction Because

  1. 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

  2. A Novel Industry Grade Dataset for Fault Prediction based on Model-Driven Developed

    E-Print Network [OSTI]

    A Novel Industry Grade Dataset for Fault Prediction based on Model-Driven Developed Automotive a novel industry dataset on static software and change metrics for Matlab/Simulink models and their corresponding auto-generated C source code. The data set comprises data of three automotive projects developed

  3. Intercomparison of Single-Column Numerical Models for the Prediction of Radiation Fog

    E-Print Network [OSTI]

    Intercomparison of Single-Column Numerical Models for the Prediction of Radiation Fog THIERRY-term forecasting of fog is a difficult issue that can have a large societal impact. Radiation fog appears layers of the atmosphere. Current NWP models poorly forecast the life cycle of fog, and improved NWP

  4. BIOMECHANICAL KIDNEY MODEL FOR PREDICTING TUMOR DISPLACEMENT IN THE PRESENCE OF EXTERNAL PRESSURE LOAD

    E-Print Network [OSTI]

    Hamarneh, Ghassan

    BIOMECHANICAL KIDNEY MODEL FOR PREDICTING TUMOR DISPLACEMENT IN THE PRESENCE OF EXTERNAL PRESSURE biomechanical model to simulate de- formations under additional external pressure load. A second CT scan that the biomechanical simula- tion improves by 29% the tumor localization. Index Terms-- Partial nephrectomy, image

  5. 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

  6. Temporal Models for Groundwater Level Prediction in Regions of Maharashtra Dissertation Report

    E-Print Network [OSTI]

    Sohoni, Milind

    Temporal Models for Groundwater Level Prediction in Regions of Maharashtra Dissertation Report In this project work we perform analysis of groundwater level data in three districts of Maha- rashtra - Thane of these districts and developed seasonal models to represent the groundwater be- havior. Three different type

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

    E-Print Network [OSTI]

    Ritchie, Robert

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

  9. 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

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

    E-Print Network [OSTI]

    Cohen, William W.

    Predicting Response to Political Blog Posts with Topic Models Tae Yano Language Technologies Language Technologies Institute Carnegie Mellon University Pittsburgh, PA 15213, USA nasmith@cs.cmu.edu Abstract In this paper we model discussions in online po- litical weblogs (blogs). To do this, we extend La

  11. 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

  12. PREDICTING HABITAT RESPONSE TO FLOW USING GENERALIZED HABITAT MODELS FOR TROUT IN ROCKY MOUNTAIN STREAMS

    E-Print Network [OSTI]

    Bledsoe, Brian

    The Nature Conservancy, Fort Collins, Colorado USA ABSTRACT Dams and water diversions can dramatically alter the hydraulic habitats of stream ecosystems. Predicting how water depth and velocity respond to flow alteration is possible using hydraulic models, such as Physical Habitat Simulation (PHABSIM); however, such models

  13. 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

  14. 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; O���¢��������Day, Peggy; Rivera, Nelson; Um, Wooyong; Chang, Hyun-Shik; Steefel, Carl; Thompson, Aaron

    2012-11-05

    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.

  15. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Rutledge, Steven

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary microbursts than in many previously documented microbursts. Alignment of Doppler radar data to reports of wind-related damage to electrical power infrastructure in Phoenix allowed a comparison of microburst wind damage

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

    SciTech Connect (OSTI)

    Hollander, A.

    2014-09-01

    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.

  17. 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.

    2013-01-01

    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.

  18. THE WEATHER VISUALIZER, JAVATM , HABANEROTM

    E-Print Network [OSTI]

    Wilhelmson, Robert

    13.19 THE WEATHER VISUALIZER, JAVATM , HABANEROTM , AND THE FUTURE Joel Plutchak* , Robert B Urbana-Champaign has developed a web-based visualization tool known as The Weather Visualizer (DAS, 1997 and images.__ Since its debut in 1995, the goals of the various versions of the Weather Visualizer have

  19. Summer Weather TheELIWeekly

    E-Print Network [OSTI]

    Sin, Peter

    Highlights · Midterms · Summer Weather · Manners · Grammar TheELIWeekly Midterms Good luck on your will be closed for the Independence Day Holiday. th th Summer Weather Safety We've come to realize in the past that not all of our students are aware of our unique weather problems in Central Florida. One hazard that you

  20. Useful Weather Links Nolan Doesken

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    Useful Weather Links Nolan Doesken Odie Bliss Colorado Climate Center Presented at ProfessionalAgMet (Colorado Agricultural Meteorological Network) · http://www.coagmet.com Weather data for agriculture #12://www.hprcc.unl.edu/index.php #12;BLM / Forest Service Remote Automated Weather Stations ­ RAWS · http://www.fs.fed.us/raws/ #12

  1. Does weather confound or modify the association of particulate air pollution with mortality? An analysis of the Philadelphia data, 1973--1980

    SciTech Connect (OSTI)

    Samet, J.; Zeger, S.; Kelsall, J.; Xu, J. [Johns Hopkins Univ. School of Public Health, Baltimore, MD (United States)] [Johns Hopkins Univ. School of Public Health, Baltimore, MD (United States); Kalkstein, L. [Univ. of Delaware, Newark, DE (United States). Center for Climatic Research] [Univ. of Delaware, Newark, DE (United States). Center for Climatic Research

    1998-04-01

    This report considers the consequences of using alternative approaches to controlling for weather and explores modification of air pollution effects by weather, as weather patterns could plausibly alter air pollution`s effect on health. The authors analyzed 1973--1980 total mortality data for Philadelphia using four weather models and compared estimates of the effects of TSP and SO{sub 2} on mortality using a Poisson regression model. Two synoptic categories developed by Kalkstein were selected--The Temporal Synoptic Index (TSI) and the Spatial Synoptic Classification (SSC)--and compared with (1) descriptive models developed by Schwartz and Dockery (S-D); and (2) LOESS, a nonparametric function of the previous day`s temperature and dew point. The authors considered model fit using Akaike`s Information Criterion (AIC) and changes in the estimated effects of TSP and SO{sub 2}. In the full-year analysis, S-D is better than LOESS at predicting mortality, and S-D and LOESS are better than TSI, as measured by AIC. When TSP or SO{sub 2} was fit alone, the results were qualitatively similar, regardless of how weather was controlled; when TSP and SO{sub 2} were fit simultaneously, the S-D and LOESS models give qualitatively different results than TSI, which attributes more of the pollution effect to SO{sub 2} than to TSP. Model fit is substantially poorer with TSI.

  2. 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; Armstrong, Robert C.; Vanderveen, Keith

    2008-09-01

    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.

  3. Statistical model selection for better prediction and discovering science mechanisms that affect reliability

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

    Anderson-Cook, Christine M.; Morzinski, Jerome; Blecker, Kenneth D.

    2015-08-19

    Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidatemore »inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.« less

  4. Weather Ready Nation: A Vital Conversation on

    E-Print Network [OSTI]

    Weather Ready Nation: A Vital Conversation on Tornadoes and Severe Weather A Community Report March;WeatherReady Nation: A Vital Conversation on Tornadoes and Severe Weather Report from the December 2011

  5. A comparison of rotordynamic-coefficient predictions for annular honeycomb gas seals using different friction-factor models 

    E-Print Network [OSTI]

    D'Sousa, Rohan Joseph

    2000-01-01

    Predictions of rotordynamic-coefficients for annular honeycomb gas seals are compared using different friction-factor models. Analysis shows that the fundamental improvement in predicting the rotordynamic-coefficients ...

  6. 7.5 Influence of Chemical Weathering on Hillslope Forms SM Mudd, University of Edinburgh, Edinburgh, UK

    E-Print Network [OSTI]

    Mudd, Simon Marius

    frequently, soil production is cast as a function of soil thickness. Abstract Chemical weathering affects7.5 Influence of Chemical Weathering on Hillslope Forms SM Mudd, University of Edinburgh, Edinburgh Model of Hillslope Evolution Including Chemical Weathering 56 7.5.2.1 The Chemical Weathering Mass

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

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01

    Implementation and Operational Services Section Canadian Meteorological Centre, Dorval, Qc National Prediction Operations Division ICEBO 2013, Montreal, Qc October 10 2013 Version 2013-09-27 Weather Forecast Data An Important Input into Building..., Martin Fradette Environment Canada RPN ? Recherche en Pr?vision num?rique Dr. Wei Yu, Dr. Paul Vaillancourt, Dr. Sylvie Leroyer Natural Resources Canada ? Canmet Energy Dr. Jos? A. Candanedo Overview ? Building management and weather information...

  8. 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...

  9. Mass-transport models to predict toxicity of inhaled gases in the upper respiratory tract

    SciTech Connect (OSTI)

    Hubal, E.A.C.; Fedkiw, P.S.; Kimbell, J.S. [North Carolina State Univ., Raleigh, NC (United States)

    1996-04-01

    Mass-transport (the movement of a chemical species) plays an important role in determining toxic responses of the upper respiratory tract (URT) to inhaled chemicals. Mathematical dosimetry models incorporate physical characteristics of mass transport and are used to predict quantitative uptake (absorption rate) and distribution of inhaled gases and vapors in the respiratory tract. Because knowledge of dose is an essential component of quantitative risk assessment, dosimetry modeling plays an important role in extrapolation of animal study results to humans. A survey of existing mathematical dosimetry models for the URT is presented, limitations of current models are discussed, and adaptations of existing models to produce a generally applicable model are suggested. Reviewed URT dosimetry models are categorized as early, lumped-parameter, and distributed-parameter models. Specific examples of other relevant modeling work are also presented. 35 refs., 11 figs., 1 tab.

  10. Weatherize | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels Data CenterFinancialInvestingRenewableTeachDevelopmentWaterAt-A-GlanceWeatherize

  11. Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models

    E-Print Network [OSTI]

    ALANQAR, ANAS WAEL

    2015-01-01

    optimization and feedback control since it is a predictive control scheme that is formulated with an objective function representing the processoptimization and feedback control since it is a predictive control scheme that is formulated with an objective function representing the process/

  12. Green Bank Weather Dana S. Balser

    E-Print Network [OSTI]

    Balser, Dana S.

    Green Bank Weather Dana S. Balser #12;Weather Resources 1. Weather Stations 2. Weather Forecasts (NOAA/Maddalena) 3. Pyrgeometer 4. 86 GHz Tipping Radiometer 5. 12 GHz Interferometer #12;Weather Parameters 1 May 2004 to 1 March 2007 speedwindousInstantaneV :Hz)(12StationWeather e

  13. Predicting ecological roles in the rhizosphere using metabolome and transportome modeling

    SciTech Connect (OSTI)

    Larsen, Peter E.; Collart, Frank R.; Dai, Yang; Blanchard, Jeffrey L.

    2015-09-02

    The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. New algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad’s ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism’s transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.

  14. Predicting ecological roles in the rhizosphere using metabolome and transportome modeling

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

    Larsen, Peter E.; Collart, Frank R.; Dai, Yang; Blanchard, Jeffrey L.

    2015-09-02

    The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. New algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad’s ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter ofmore »plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism’s transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.« less

  15. Linear Model-Based Predictive Control of the LHC 1.8 K Cryogenic Loop

    E-Print Network [OSTI]

    Blanco-Viñuela, E; De Prada-Moraga, C

    1999-01-01

    The LHC accelerator will employ 1800 superconducting magnets (for guidance and focusing of the particle beams) in a pressurized superfluid helium bath at 1.9 K. This temperature is a severely constrained control parameter in order to avoid the transition from the superconducting to the normal state. Cryogenic processes are difficult to regulate due to their highly non-linear physical parameters (heat capacity, thermal conductance, etc.) and undesirable peculiarities like non self-regulating process, inverse response and variable dead time. To reduce the requirements on either temperature sensor or cryogenic system performance, various control strategies have been investigated on a reduced-scale LHC prototype built at CERN (String Test). Model Based Predictive Control (MBPC) is a regulation algorithm based on the explicit use of a process model to forecast the plant output over a certain prediction horizon. This predicted controlled variable is used in an on-line optimization procedure that minimizes an approp...

  16. The impact of global nuclear mass model uncertainties on $r$-process abundance predictions

    E-Print Network [OSTI]

    M. Mumpower; R. Surman; A. Aprahamian

    2014-11-14

    Rapid neutron capture or `$r$-process' nucleosynthesis may be responsible for half the production of heavy elements above iron on the periodic table. Masses are one of the most important nuclear physics ingredients that go into calculations of $r$-process nucleosynthesis as they enter into the calculations of reaction rates, decay rates, branching ratios and Q-values. We explore the impact of uncertainties in three nuclear mass models on $r$-process abundances by performing global monte carlo simulations. We show that root-mean-square (rms) errors of current mass models are large so that current $r$-process predictions are insufficient in predicting features found in solar residuals and in $r$-process enhanced metal poor stars. We conclude that the reduction of global rms errors below $100$ keV will allow for more robust $r$-process predictions.

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

    SciTech Connect (OSTI)

    Jaroslav Solc

    2009-06-01

    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.

  18. 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

    2014-05-19

    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.

  19. Flood regulation using nonlinear model predictive control Toni Barjas Blanco a,, Patrick Willems b

    E-Print Network [OSTI]

    Flood regulation using nonlinear model predictive control Toni Barjas Blanco a,Ã, Patrick Willems b t In this paper the flood problem of the river Demer, a river located in Belgium, is discussed. First a simplified. & 2010 Elsevier Ltd. All rights reserved. 1. Introduction Flooding of rivers are a worldwide cause

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

    E-Print Network [OSTI]

    Daraio, Chiara

    measurements in the ETHZ facility compare well with measurements at the Horns Rev offshore wind farm·Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms. ·Wake and wind turbine wakes in large windfarms offshore, Wind Energy 12, pp. 431-444, 2009. [2] L.P. Chamorro

  1. A predictive analytical friction model from basic theories of interfaces, contacts and dislocations

    E-Print Network [OSTI]

    Marks, Laurence D.

    A predictive analytical friction model from basic theories of interfaces, contacts and dislocations of dislocation drag, contact mechanics, and interface theory. An analytic expression for the friction force still see use in basic discus- sions of the phenomenon [1]. Three basic observations have persisted

  2. 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

  3. 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

  4. Linear-quadratic model predictive control for urban traffic , Hai L. Vu a

    E-Print Network [OSTI]

    Nazarathy, Yoni

    Accepted 30 June 2013 Keywords: Model predictive control Intelligent transport system Congestion control- tion systems are driving the field of intelligent transport systems (ITS) into the twenty first century for large urban networks containing thousands of sensors and actuators. We demonstrate the essence of our

  5. Variable Selection in Data Mining: Building a Predictive Model for Bankruptcy

    E-Print Network [OSTI]

    Stine, Robert A.

    Variable Selection in Data Mining: Building a Predictive Model for Bankruptcy Dean P. Foster and Robert A. Stine Department of Statistics The Wharton School of the University of Pennsylvania consequences of over-fitting (e.g. ?). Many in- teresting problems, particularly classification problems

  6. World Congress on Industrial Process Tomography, Aizu, Japan Modelling and predicting flow regimes using wavelet

    E-Print Network [OSTI]

    Barber, Stuart

    4 th World Congress on Industrial Process Tomography, Aizu, Japan Modelling and predicting flow of Statistics, University of Leeds, Leeds, LS2 9JT, UK, robert@maths.leeds.ac.uk ABSTRACT The aim of industrial without intruding into the industrial process, but produce highly correlated and noisy data, and hence

  7. 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

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

    E-Print Network [OSTI]

    by the varying properties and chemical structure of different coal types [2], and by the fact that the coal properties change significantly throughout a coal particle's lifetime in a combustor [3­5]. The coal particleA comparison of various models in predicting ignition delay in single-particle coal combustion

  9. Flood Control with Model Predictive Control for River Systems with Water Reservoirs

    E-Print Network [OSTI]

    Flood Control with Model Predictive Control for River Systems with Water Reservoirs Maarten consisting of multiple channels, gates, and a water reservoir. One controller is used in combination of measured water levels. It was observed that the influence of this estimator on the control performance

  10. Flood control of rivers with nonlinear model predictive control and moving horizon estimation

    E-Print Network [OSTI]

    ]. Several studies can be found in literature where MPC is used to control water systems [15], [16] and [5Flood control of rivers with nonlinear model predictive control and moving horizon estimation control (MPC) in combination with moving horizon estimation (MHE) can more effectively be used for flood

  11. 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

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

    E-Print Network [OSTI]

    Cotofana, Sorin

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

  13. 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

  14. 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-scaled kinetic energy are all consistent with the available observations in the regions of significant wind

  15. PREDICTION OF FOG EPISODES AT THE AIRPORT OF MADRID-BARAJAS USING DIFFERENT MODELING APPROACHES

    E-Print Network [OSTI]

    Politècnica de Catalunya, Universitat

    PREDICTION OF FOG EPISODES AT THE AIRPORT OF MADRID-BARAJAS USING DIFFERENT MODELING APPROACHES Meteorología (INM) has been investigating for some time the phenomena related to the formation of fog episodes between the development of fog and the establishment of katabatic flows in the region, generally under

  16. 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

  17. Voltage Utilization in Model Predictive Control for Michael Leuer, Joachim Bocker

    E-Print Network [OSTI]

    Noé, Reinhold

    Voltage Utilization in Model Predictive Control for IPMSM Michael Leuer, Joachim B¨ocker Power (IPMSM). Besides the good dynamics, the utilization of the DC link voltage is important for these motor types. Since the MPC is able to utilize the available DC link voltage optimally, the MPC is superior

  18. 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

  19. 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

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

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    Compressor 4 Commercial Industry Power Plant LDC 3 Suppliers, 12 Demand nodes, 5 Compressors Sinusoidal Flowrates Industry: N6,12,13,19,21 Commercial: N30,32,34,35 Power Plant: N4,25 LDC: N23 Pcontract = 500 kEconomic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks EWO

  1. 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

  2. Hybrid Model Predictive Control Based on Wireless Sensor Feedback: An Experimental Study

    E-Print Network [OSTI]

    Johansson, Karl Henrik

    Hybrid Model Predictive Control Based on Wireless Sensor Feedback: An Experimental Study Alberto based on measurements collected by a wireless sensor network. The proposed setup is the prototype of an industrial application in which a remote station controls the process via wireless network links

  3. 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

    2012-08-03

    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.

  4. Model Predictive Control for Starvation Prevention in a Hybrid Fuel Cell System1

    E-Print Network [OSTI]

    Stefanopoulou, Anna

    Model Predictive Control for Starvation Prevention in a Hybrid Fuel Cell System1 Ardalan Vahidi 2 current is drawn from a fuel cell, it is critical that the reacted oxygen is replenished rapidly. We formulate distribution of current demand between the fuel cell and the auxiliary source

  5. 2014Science About the cover: A new transcriptomics-based model accurately predicts how much

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Carbonell, Jaime

    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

  7. Three-body interactions improve the prediction of rate and mechanism in protein folding models

    E-Print Network [OSTI]

    Plotkin, Steven S.

    Three-body interactions improve the prediction of rate and mechanism in protein folding models M. R-body interactions on rate and mechanism in protein folding by using the results of molecular dynamics simulations that stabilize protein structures and govern protein folding mechanisms is a fundamental problem in molecular

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

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    and boiler operating conditions. Prediction performance compares favourably with neural network models for future work to further improve performance. Index Terms: Mercury speciation, Flue gases, Boiler emissions activities are coal-fired electric utility boilers, where speciation depends on the operating conditions

  9. Modeling Ideology and Predicting Policy Change with Social Media: Case of Same-Sex Marriage

    E-Print Network [OSTI]

    Modeling Ideology and Predicting Policy Change with Social Media: Case of Same-Sex Marriage Amy X of important policy decisions. Focus- ing on the issue of same-sex marriage legalization, we exam- ine almost 2 million public Twitter posts related to same-sex marriage in the U.S. states over the course of 4 years

  10. ARSA: A Sentiment-Aware Model for Predicting Sales Performance Using Blogs

    E-Print Network [OSTI]

    Huang, Jimmy

    ARSA: A Sentiment-Aware Model for Predicting Sales Performance Using Blogs Yang Liu1 , Xiangji, Toronto, Canada 2 School of Information Technology York University, Toronto, Canada yliu@cse.yorku.ca, jhuang@yorku.ca, aan@cse.yorku.ca, xhyu@yorku.ca ABSTRACT Due to its high popularity, Weblogs (or blogs

  11. Model to Predict Temperature and Capillary Pressure Driven Water Transport in PEFCs After Shutdown

    E-Print Network [OSTI]

    Mench, Matthew M.

    Model to Predict Temperature and Capillary Pressure Driven Water Transport in PEFCs After Shutdown-912 Korea To enhance durability and cold-start performance of polymer electrolyte fuel cells PEFCs in the PEFC components after shutdown, which for the first time includes thermo-osmotic flow in the membrane

  12. 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

  13. Physically Based Model-Predictive Control for SOFC Stacks and Systems Tyrone L. Vincent, Borhan Sanandaji

    E-Print Network [OSTI]

    Sanandaji, Borhan M.

    Physically Based Model-Predictive Control for SOFC Stacks and Systems Tyrone L. Vincent, Borhan output tra- jectory. The process is demonstrated for a tubular SOFC stack that could be used, solid-oxide fuel cells (SOFC) must deliver power profiles that meet the demands of transient loads

  14. Towards a Predictive Model for Opal Exploration using a Spatio-temporal Data Mining Approach

    E-Print Network [OSTI]

    Müller, Dietmar

    Towards a Predictive Model for Opal Exploration using a Spatio-temporal Data Mining Approach Andrew depositional, unclassified Opal deposit 140°E120°E 20°S 40°S Winton Opalton Jundah Eromanga Quilpie Lightning Ridge White Cliffs Stuart Creek LambinaMintabie Coober Pedy Surat Basin Eromanga Basin Opal mining town

  15. 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

  16. Conditional Spectrum Computation Incorporating Multiple Causal Earthquakes and Ground-Motion Prediction Models

    E-Print Network [OSTI]

    Baker, Jack W.

    Conditional Spectrum Computation Incorporating Multiple Causal Earthquakes and Ground-Motion Prediction Models by Ting Lin, Stephen C. Harmsen, Jack W. Baker, and Nicolas Luco Abstract The conditional uncertainties in all earthquake scenarios and resulting ground motions, as well as the epistemic uncertainties

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

    E-Print Network [OSTI]

    Qin, Xiao

    BFEPM:Best Fit Energy Prediction Modeling Based on CPU Utilization Xiao Zhang, Jianjun Lu, Xiao Qin BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark Engineering Auburn University Auburn, AL USA 36849-5347 Email: xqin@auburn.edu Abstract--Energy cost becomes

  18. Analysis and prediction of hazard risks caused by tropical cyclones in Southern China with fuzzy mathematical and grey models

    E-Print Network [OSTI]

    Zhang, Da-Lin

    Analysis and prediction of hazard risks caused by tropical cyclones in Southern China with fuzzy 2011 Keywords: Combined weights Fuzzy mathematical models Hazard risk analysis Exceeded probability Tropical cyclones Grey prediction model a b s t r a c t A hazard-risk assessment model and a grey hazard

  19. Understanding space weather to shield society: A global road map for 2015-2025 commissioned by COSPAR and ILWS

    E-Print Network [OSTI]

    Schrijver, Karel

    Understanding space weather to shield society: A global road map for 2015-2025 commissionedSpace Weather and Environment Informatics Lab., National Inst. of Information and Communications Techn., Tokyo Corporation, Chantilly, VA 20151, USA vNOAA Space Weather Prediction Center, USA wSwedish Institute of Space

  20. The Dirac Form Factor Predicts the Pauli Form Factor in the Endpoint Model

    E-Print Network [OSTI]

    Sumeet Dagaonkar; Pankaj Jain; John P. Ralston

    2015-03-24

    We compute the momentum-transfer dependence of the proton Pauli form factor $F_{2}$ in the endpoint overlap model. We find the model correctly reproduces the scaling of the ratio of $F_{2}$ with the Dirac Form factor $F_{1}$ observed at the Jefferson Laboratory. The calculation uses the leading-power, leading twist Dirac structure of the quark light-cone wave function, and the same endpoint dependence previously determined from the Dirac form factor $F_{1}$. There are no parameters and no adjustable functions in the endpoint model's prediction for $F_{2}$. The model's predicted ratio $F_{2}(Q^{2})/F_{1}(Q^{2})$ is quite insensitive to the endpoint wave function, which explains why the observed ratio scales like $1/Q$ down to rather low momentum transfers. The endpoint model appears to be the only comprehensive model consistent with all form factor information as well as reproducing fixed-angle proton-proton scattering at large momentum transfer. Any one of the processes is capable of predicting the others.

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

    SciTech Connect (OSTI)

    Nikabdullah, N.; Singh, S. S. K.; Alebrahim, R.; Azizi, M. A.; K, Elwaleed A.; Noorani, M. S. M.

    2014-06-19

    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.

  2. Long-Fiber Thermoplastic Injection Molded Composites: from Process Modeling to Property Prediction

    SciTech Connect (OSTI)

    Nguyen, Ba Nghiep; Holbery, Jim D.; Johnson, Kenneth I.; Smith, Mark T.

    2005-09-01

    Recently, long-fiber filled thermoplastics have become a great interest to the automotive industry since these materials offer much better property performance (e.g. elastic moduli, strength, durability…) than their short-fiber analogues, and they can be processed through injection molding with some specific tool design. However, in order that long-fiber thermoplastic injection molded composites can be used efficiently for automotive applications, there is a tremendous need to develop process and constitutive models as well as computational tools to predict the microstructure of the as-formed composite, and its resulting properties and macroscopic responses from processing to the final product. The microstructure and properties of such a composite are governed by i) flow-induced fiber orientation, ii) fiber breakage during injection molding, and iii) processing conditions (e,g. pressure, mold and melt temperatures, mold geometries, injection speed, etc.). This paper highlights our efforts to address these challenging issues. The work is an integrated part of a research program supported by the US Department of Energy, which includes • The development of process models for long-fiber filled thermoplastics, • The construction of an interface between process modeling and property prediction as well as the development of new constitutive models to perform linear and nonlinear structural analyses, • Experimental characterization of model parameters and verification of the model predictions.

  3. 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

  4. Nonlinear dynamics of the magnetosphere and space weather

    SciTech Connect (OSTI)

    Sharma, A.S. [Univ. of Maryland, College Park, MD (United States). Dept. of Astronomy

    1996-12-31

    The solar wind-magnetosphere-ionosphere system exhibits coherence on the global scale and such behavior can arise from nonlinearity in the dynamics. The observational time series data have been used extensively to analyze the magnetospheric dynamics by using the techniques of phase space reconstruction. Analyses of the solar wind and auroral electrojet and Dst indices have shown low dimensionality of the dynamics and accurate prediction can be made with an input-output model. The predictability of the magnetosphere in spite of the apparent complexity arises form its being synchronized, in the dynamical sense, to the solar wind. The AE and Dst data are used to analyze the storm-substorm relationship based on the input-output model. This shows differences between the storm-time and non-storm substorms, and is interpreted in terms of loading-unloading and directly driven processes. The strong electrodynamic coupling between the different regions of the magnetosphere yields its coherent and thus low dimensional behavior. The data from multiple satellites and ground stations are used to develop a spatio-temporal model that identifies the coupling between the different regions. These nonlinear dynamical models provide forecasting tools for space weather.

  5. Localized customized mortality prediction modeling for patients with acute kidney injury admitted to the intensive care unit

    E-Print Network [OSTI]

    Celi, Leo Anthony G

    2009-01-01

    Introduction. Models for mortality prediction are traditionally developed from prospective multi-center observational studies involving a heterogeneous group of patients to optimize external validity. We hypothesize that ...

  6. The use of a new logistic regression model for predicting the outcome of pregnancies of unknown location

    E-Print Network [OSTI]

    .8, a positive predictive value of 27.5% and a negative predictive value of 99.4%. CONCLUSIONS: The logisticThe use of a new logistic regression model for predicting the outcome of pregnancies of unknown, London UK. E-mail: gcondous@hotmail.com BACKGROUND: The aim of this study was to generate and evaluate

  7. Shedding Light on the Weather Srinivasa G. Narasimhan and Shree K. Nayar

    E-Print Network [OSTI]

    Nayar, Shree K.

    Shedding Light on the Weather Srinivasa G. Narasimhan and Shree K. Nayar Computer Science Dept in image processing and computer vision, for removing weather effects from images, as- sume single in bad weather. Modeling multiple scattering is critical to un- derstanding the complex effects

  8. "WEATHER IN A TANK" exploiting Laboratory experiments in the Teaching of

    E-Print Network [OSTI]

    Lee, Sukyoung

    "WEATHER IN A TANK" exploiting Laboratory experiments in the Teaching of meteorology, oceanography revealing midlatitude weather systems (the North Pole is in the middle) "stirring" properties between that govern atmospheric synoptic-scale weather systems. The laboratory model is a simplified system

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

    SciTech Connect (OSTI)

    Lipscomb, William

    2012-06-19

    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.

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

    E-Print Network [OSTI]

    M. K. Parida; Sudhanwa Patra

    2013-01-14

    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.

  11. Winter Weather Outlook

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubictheThe U.S. Department ofWinners0 Winter Weather

  12. Winter Weather Outlook

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubictheThe U.S. Department ofWinners0 Winter Weather1

  13. Monte Carlo and analytical model predictions of leakage neutron exposures from passively scattered proton therapy

    SciTech Connect (OSTI)

    Pérez-Andújar, Angélica [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 (United States)] [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 (United States); Zhang, Rui; Newhauser, Wayne [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 and The University of Texas Graduate School of Biomedical Sciences at Houston, 6767 Bertner Avenue, Houston, Texas 77030 (United States)] [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 and The University of Texas Graduate School of Biomedical Sciences at Houston, 6767 Bertner Avenue, Houston, Texas 77030 (United States)

    2013-12-15

    Purpose: Stray neutron radiation is of concern after radiation therapy, especially in children, because of the high risk it might carry for secondary cancers. Several previous studies predicted the stray neutron exposure from proton therapy, mostly using Monte Carlo simulations. Promising attempts to develop analytical models have also been reported, but these were limited to only a few proton beam energies. The purpose of this study was to develop an analytical model to predict leakage neutron equivalent dose from passively scattered proton beams in the 100-250-MeV interval.Methods: To develop and validate the analytical model, the authors used values of equivalent dose per therapeutic absorbed dose (H/D) predicted with Monte Carlo simulations. The authors also characterized the behavior of the mean neutron radiation-weighting factor, w{sub R}, as a function of depth in a water phantom and distance from the beam central axis.Results: The simulated and analytical predictions agreed well. On average, the percentage difference between the analytical model and the Monte Carlo simulations was 10% for the energies and positions studied. The authors found that w{sub R} was highest at the shallowest depth and decreased with depth until around 10 cm, where it started to increase slowly with depth. This was consistent among all energies.Conclusion: Simple analytical methods are promising alternatives to complex and slow Monte Carlo simulations to predict H/D values. The authors' results also provide improved understanding of the behavior of w{sub R} which strongly depends on depth, but is nearly independent of lateral distance from the beam central axis.

  14. Model predictive adaptive control of process systems using recurrent neural networks 

    E-Print Network [OSTI]

    Parthasarathy, Sanjay

    1993-01-01

    ) controller structure is used for the simulations. The feasibility of the approach is first demonstrated on a, piece-wise linearized model of the UTSG. It is found that the proposed model predictive adaptive PI controller significantly reduces the system set... Summary 41 41 42 45 49 53 54 V CASE-STUDY: THE U-TUBE STEAM GENERATOR LEVEL CONTROL PROBLEM WATER o6 V. 1 Introduction V. 2 Current Practice: The PID Controller 56 60 CHAPTER Page V. 3 Development of the Piece-wise Linearized Model ol...

  15. Bishop Paiute Weatherization Training Program

    SciTech Connect (OSTI)

    Carlos Hernandez

    2010-01-28

    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.

  16. Weatherization Apprenticeship Program

    SciTech Connect (OSTI)

    Watson, Eric J

    2012-12-18

    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.

  17. PREDICTING WATER ACTIVITY IN ELECTROLYTE SOLUTIONS WITH THE CISTERNAS-LAM MODEL

    SciTech Connect (OSTI)

    REYNOLDS JG; GREER DA; DISSELKAMP RL

    2011-03-01

    Water activity is an important parameter needed to predict the solubility of hydrated salts in Hanford nuclear waste supernatants. A number of models available in the scientific literature predict water activity from electrolyte solution composition. The Cisternas-Lam model is one of those models and has several advantages for nuclear waste application. One advantage is that it has a single electrolyte specific parameter that is temperature independent. Thus, this parameter can be determined from very limited data and extrapolated widely. The Cisternas-Lam model has five coefficients that are used for all aqueous electrolytes. The present study aims to determine if there is a substantial improvement in making all six coefficients electrolyte specific. The Cisternas-Lam model was fit to data for six major electrolytes in Hanford nuclear waste supernatants. The model was first fit to all data to determine the five global coefficients, when they were held constant for all electrolytes it yielded a substantially better fit. Subsequently, the model was fit to each electrolyte dataset separately, where all six coefficients were allowed to be electrolyte specific. Treating all six coefficients as electrolyte specific did not make sufficient difference, given the complexity of applying the electrolyte specific parameters to multi-solute systems. Revised water specific parameters, optimized to the electrolytes relevant to Hanford waste, are also reported.

  18. Adsorption of selected pharmaceuticals and an endocrine disrupting compound by granular activated carbon. 2. Model prediction

    SciTech Connect (OSTI)

    Yu, Z.; Peldszus, S.; Huck, P.M. [University of Waterloo, Waterloo, ON (Canada). NSERC Chair in Water Treatment

    2009-03-01

    The adsorption of two representative pharmaceutically active compounds (PhACs) naproxen and carbamazepine and one endocrine disrupting compound (EDC) nonylphenol was studied in pilot-scale granular activated carbon (GAC) adsorbers using post-sedimentation (PS) water from a full-scale drinking water treatment plant. The GAC adsorbents were coal-based Calgon Filtrasorb 400 and coconut shell-based PICA CTIF TE. Acidic naproxen broke through fastest while nonylphenol was removed best, which was consistent with the degree to which fouling affected compound removals. Model predictions and experimental data were generally in good agreement for all three compounds, which demonstrated the effectiveness and robustness of the pore and surface diffusion model (PSDM) used in combination with the time-variable parameter approach for predicting removals at environmentally relevant concentrations (i.e., ng/L range). Sensitivity analyses suggested that accurate determination of film diffusion coefficients was critical for predicting breakthrough for naproxen and carbamazepine, in particular when high removals are targeted. Model simulations demonstrated that GAC carbon usage rates (CURs) for naproxen were substantially influenced by the empty bed contact time (EBCT) at the investigated conditions. Model-based comparisons between GAC CURs and minimum CURs for powdered activated carbon (PAC) applications suggested that PAC would be most appropriate for achieving 90% removal of naproxen, whereas GAC would be more suitable for nonylphenol. 25 refs., 4 figs., 1 tab.

  19. 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)

    2013-01-01

    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 ...

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

    E-Print Network [OSTI]

    Whipple, Sean David

    2014-01-01

    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 ...