National Library of Energy BETA

Sample records for weather prediction models

  1. The origins of computer weather prediction and climate modeling

    SciTech Connect (OSTI)

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

    2008-03-20

    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.

  2. DREAM tool increases space weather predictions

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

    DREAM tool increases space weather predictions Model addresses radiation hazards of the space environment on space systems. April 13, 2012 Scientists studying Earth's radiation ...

  3. 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.

  4. Evaluation of cloud prediction and determination of critical relative humidity for a mesoscale numerical weather prediction model

    SciTech Connect (OSTI)

    Seaman, N.L.; Guo, Z.; Ackerman, T.P.

    1996-04-01

    Predictions of cloud occurrence and vertical location from the Pennsylvannia State University/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) were evaluated statistically using cloud observations obtained at Coffeyville, Kansas, as part of the Second International satellite Cloud Climatology Project Regional Experiment campaign. Seventeen cases were selected for simulation during a November-December 1991 field study. MM5 was used to produce two sets of 36-km simulations, one with and one without four-dimensional data assimilation (FDDA), and a set of 12-km simulations without FDDA, but nested within the 36-km FDDA runs.

  5. 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.

  6. 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

  7. Observations and simulations improve space weather models

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

    Observations improve space weather models Observations and simulations improve space weather models Researchers used data from the Van Allen Probes to improve a three-dimensional model created by Los Alamos scientists called DREAM3D. June 25, 2014 NASA's Van Allen Probes sample the Earth's magnetosphere. NASA's Van Allen Probes sample the Earth's magnetosphere. The work demonstrated that DREAM3D accurately simulated the behavior of a complex and dynamic event in the radiation belt that was

  8. Observations and simulations improve space weather models

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

    Observations improve space weather models Observations and simulations improve space weather models Researchers used data from the Van Allen Probes to improve a three-dimensional model created by Los Alamos scientists called DREAM3D. June 25, 2014 NASA's Van Allen Probes sample the Earth's magnetosphere. NASA's Van Allen Probes sample the Earth's magnetosphere. The work demonstrated that DREAM3D accurately simulated the behavior of a complex and dynamic event in the radiation belt that was

  9. 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...

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

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

    develop ever-more sophisticated computer models to predict the effects of climate change, one of the things they'll look for are changes in the frequency of extreme weather...

  11. 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

  12. Battery Life Predictive Model

    Energy Science and Technology Software Center (OSTI)

    2009-12-31

    The Software consists of a model used to predict battery capacity fade and resistance growth for arbitrary cycling and temperature profiles. It allows the user to extrapolate from experimental data to predict actual life cycle.

  13. Weather Research and Forecasting Model with the Immersed Boundary Method

    Energy Science and Technology Software Center (OSTI)

    2012-05-01

    The Weather Research and Forecasting (WRF) Model with the immersed boundary method is an extension of the open-source WRF Model available for wwww.wrf-model.org. The new code modifies the gridding procedure and boundary conditions in the WRF model to improve WRF's ability to simutate the atmosphere in environments with steep terrain and additionally at high-resolutions.

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

    SciTech Connect (OSTI)

    Oglesby, Robert J; Erickson III, David J

    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.

  15. Long-range Weather Prediction and Prevention of Climate Catastrophes: A Status Report

    DOE R&D Accomplishments [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

  16. Lidar-measured winds from space: A key component for weather and climate prediction

    SciTech Connect (OSTI)

    Baker, W.E.; Emmitt, G.D.; Robertson, F.

    1995-06-01

    The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate. This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds. Observing system simulation experiments, conducted using two different general circulation models, have shown (1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and (2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone. 99 refs., 10 figs., 3 tabs.

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

    DOE R&D Accomplishments [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

  18. 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

  19. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center (OSTI)

    2014-08-01

    The Weather Research and Forecasting (WRF) model with vertical nesting capability is an extension of the WRF model, which is available in the public domain, from www.wrf-model.org. The new code modifies the nesting procedure, which passes lateral boundary conditions between computational domains in the WRF model. Previously, the same vertical grid was required on all domains, while the new code allows different vertical grids to be used on concurrently run domains. This new functionality improvesmore » WRF's ability to produce high-resolution simulations of the atmosphere by allowing a wider range of scales to be efficiently resolved and more accurate lateral boundary conditions to be provided through the nesting procedure.« less

  20. 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.

  1. Model predicts space weather and protects satellite hardware

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

    | Department of Energy Mobilizing $4 Billion in Private-Sector Support for Clean Energy Innovation Mobilizing $4 Billion in Private-Sector Support for Clean Energy Innovation June 16, 2015 - 9:00am Addthis Innovations in clean energy like wind power are a crucial part of fighting climate change. | Photo courtesy of the Department of Energy Loan Programs Office. Innovations in clean energy like wind power are a crucial part of fighting climate change. | Photo courtesy of the Department of

  2. 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.

  3. predictive modeling | National Nuclear Security Administration

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

    Apply for Our Jobs Our Jobs Working at NNSA Blog Home predictive modeling predictive modeling Fukushima: Five Years Later After the March 11, 2011, Japan earthquake, tsunami, and ...

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

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

    A Better Way to ID Extreme Weather Events in Climate Models A Better Way to ID Extreme Weather Events in Climate Models Berkeley Lab scientists help automate the search for hurricanes and other storms in huge datasets December 7, 2011 Dan Krotz, dakrotz@lbl.gov, +1 510-486-4019 You'd think that spotting a category 5 hurricane would never be difficult. But when the hurricane is in a global climate model that spans several decades, it becomes a fleeting wisp among mountains of data. That's a

  5. 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

  6. predictive-models | netl.doe.gov

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

    predictive-models DOE/BC-88/1/SP. EOR Predictive Models: Handbook for Personal Computer Versions of Enhanced Oil Recovery Predictive Models. BPO Staff. February 1988. 76 pp. NTIS Order No. DE89001204. FORTRAN source code and executable programs for the five EOR Predictive Models shown below are available. The five recovery processes modeled are Steamflood, In-Situ Combustion, Polymer, Chemical Flooding, and CO2 Miscible Flooding. The models are available individually. Min Req.: IBM PC/XT, PS-2,

  7. 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."

  8. 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.

  9. Enhancing Cloud Radiative Processes and Radiation Efficiency in the Advanced Research Weather Research and Forecasting (WRF) Model

    SciTech Connect (OSTI)

    Iacono, Michael J.

    2015-03-09

    The objective of this research has been to evaluate and implement enhancements to the computational performance of the RRTMG radiative transfer option in the Advanced Research version of the Weather Research and Forecasting (WRF) model. Efficiency is as essential as accuracy for effective numerical weather prediction, and radiative transfer is a relatively time-consuming component of dynamical models, taking up to 30-50 percent of the total model simulation time. To address this concern, this research has implemented and tested a version of RRTMG that utilizes graphics processing unit (GPU) technology (hereinafter RRTMGPU) to greatly improve its computational performance; thereby permitting either more frequent simulation of radiative effects or other model enhancements. During the early stages of this project the development of RRTMGPU was completed at AER under separate NASA funding to accelerate the code for use in the Goddard Space Flight Center (GSFC) Goddard Earth Observing System GEOS-5 global model. It should be noted that this final report describes results related to the funded portion of the originally proposed work concerning the acceleration of RRTMG with GPUs in WRF. As a k-distribution model, RRTMG is especially well suited to this modification due to its relatively large internal pseudo-spectral (g-point) dimension that, when combined with the horizontal grid vector in the dynamical model, can take great advantage of the GPU capability. Thorough testing under several model configurations has been performed to ensure that RRTMGPU improves WRF model run time while having no significant impact on calculated radiative fluxes and heating rates or on dynamical model fields relative to the RRTMG radiation. The RRTMGPU codes have been provided to NCAR for possible application to the next public release of the WRF forecast model.

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

    SciTech Connect (OSTI)

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

    2013-10-19

    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.

  11. Validation of Global Weather Forecast and Climate Models Over the North

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

    Slope of Alaska Validation of Global Weather Forecast and Climate Models Over the North Slope of Alaska Xie, Shaocheng Lawrence Livermore National Laboratory Klein, Stephen Lawrence Livermore National Laboratory Boyle, Jim Lawrence Livermore National Laboratory Fiorino, Michael DOE/Lawrence Livermore National Laboratory Hnilo, Justin DOE/Lawrence Livermore National Laboratory Phillips, Thomas PCMDI/LLNL Potter, Gerald Lawrence Livermore National Laboratory Beljaars, Anton ECMWF Category:

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

    SciTech Connect (OSTI)

    Dben, 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

  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.

    2015-02-13

    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 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. Road Weather Predictions

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

    Road Tripping through the Geothermal Frontier Road Tripping through the Geothermal Frontier November 18, 2015 - 9:58am Addthis Geothermal Well Head, Utah 1 of 5 Geothermal Well Head, Utah This geothermal well head is located near the University of Utah's FORGE candidate site. The area is already renewables-friendly, with a wind farm nearby. Image: Elisabet Metcalfe, EERE Snake River Plain, Idaho 2 of 5 Snake River Plain, Idaho The mountainous view captures INL's Snake River Plain candidate site

  15. 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

  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. 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.

  18. Severe Weather

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

    1 Severe Weather Preparedness - StormReady To help communities guard against the devastation that can result from severe weather, the National Weather Service (NWS) has developed a new program called StormReady. The aim is to build, at the community level, the communication and safety skills necessary to prevent loss of life and property in the event of severe weather. Each year weather-related disasters lead to 500 deaths and $14 billion in damage. The NWS hopes that prepared communities

  19. Predictive Models for Target Response During Penetration (Technical...

    Office of Scientific and Technical Information (OSTI)

    Predictive Models for Target Response During Penetration Citation Details In-Document Search Title: Predictive Models for Target Response During Penetration You are accessing a...

  20. Computational Tools for Predictive Modeling of Properties in...

    Office of Scientific and Technical Information (OSTI)

    Book: Computational Tools for Predictive Modeling of Properties in Complex Actinide Systems Citation Details In-Document Search Title: Computational Tools for Predictive Modeling ...

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

    Office of Scientific and Technical Information (OSTI)

    Prediction Models at Los Alamos National Lab Technical Area 54 Citation Details In-Document Search Title: Comparison of Uncertainty of Two Precipitation Prediction Models ...

  2. A predictive standard model for heavy electron systems (Conference...

    Office of Scientific and Technical Information (OSTI)

    A predictive standard model for heavy electron systems Citation Details In-Document Search Title: A predictive standard model for heavy electron systems You are accessing a ...

  3. Simplified Protein Models: Predicting Folding Pathways and Structure...

    Office of Scientific and Technical Information (OSTI)

    Simplified Protein Models: Predicting Folding Pathways and Structure Using Amino Acid Sequences Title: Simplified Protein Models: Predicting Folding Pathways and Structure Using ...

  4. Testing model for predicting spillway cavitation damage

    SciTech Connect (OSTI)

    Lee, W.; Hoopes, J.A.

    1995-12-31

    Using fuzzy mathematics a comprehensive model has been developed to predict the time, location and level (intensity) of spillway cavitation damage. Five damage levels and four factors affecting damage are used. Membership functions express the degree that each factor effects damage, and weights express the relative importance of each factor. The model has been calibrated and tested with operating data and experience from the Glen Canyon Dam left tunnel spillway, which had major cavitation damage in 1983. An error analysis for the Glen Canyon Dam left tunnel spillway gave the best ranges for model weights. Prediction of damage at other spillways (4 tunnels, 3 chutes) with functions and parameters as for the Glen Canyon Dam left tunnel spillway gave reasonable predictions of damage intensity and location and poor estimates of occurrence time in the tunnels. Chute predictions were in poor agreement with observations, indicating need for different parameter values. Finally, two membership functions with constant or time varying parameters are compared with observed results from the Glen Canyon Dam left tunnel spillway.

  5. 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.

  6. New model accurately predicts reformate composition

    SciTech Connect (OSTI)

    Ancheyta-Juarez, J.; Aguilar-Rodriguez, E. )

    1994-01-31

    Although naphtha reforming is a well-known process, the evolution of catalyst formulation, as well as new trends in gasoline specifications, have led to rapid evolution of the process, including: reactor design, regeneration mode, and operating conditions. Mathematical modeling of the reforming process is an increasingly important tool. It is fundamental to the proper design of new reactors and revamp of existing ones. Modeling can be used to optimize operating conditions, analyze the effects of process variables, and enhance unit performance. Instituto Mexicano del Petroleo has developed a model of the catalytic reforming process that accurately predicts reformate composition at the higher-severity conditions at which new reformers are being designed. The new AA model is more accurate than previous proposals because it takes into account the effects of temperature and pressure on the rate constants of each chemical reaction.

  7. 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.

  8. ARM - Weather

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

    TeachersTopic ListWeather Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Weather Weather refers to short-term changes in atmospheric conditions or elements. Here, short-term means that the changes taking place over a matter of seconds, minutes, or hours, or from day to day. It is a term

  9. 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.

  10. Weatherization Program

    Broader source: Energy.gov [DOE]

    Residences participating in the Home Energy Rebate or New Home Rebate Program may not also participate in the Weatherization Program. 

  11. An Anisotropic Hardening Model for Springback Prediction

    SciTech Connect (OSTI)

    Zeng, Danielle; Xia, Z. Cedric

    2005-08-05

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.

  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. 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.

  14. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1. Wind and Turbulence

    SciTech Connect (OSTI)

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-25

    We found that numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed wind speed, wind direction, turbulent kinetic energy (e), friction velocity (u* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (θ ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35° and 1.9 m s-1 , respectively. Then, using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model’s MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a θ gradient method whether using observed or modelled θ profiles.

  15. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1. Wind and Turbulence

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

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-25

    We found that numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed windmore » speed, wind direction, turbulent kinetic energy (e), friction velocity (u* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (θ ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35° and 1.9 m s-1 , respectively. Then, using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model’s MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a θ gradient method whether using observed or modelled θ profiles.« less

  16. Weather - Hanford Site

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

    Weather Weather Calendar Hanford Blog Archive Search Site Feeds Site Index Weather What's New Weather Email Email Page | Print Print Page |Text Increase Font Size Decrease Font...

  17. 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...

  18. 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.

  19. Weatherization Update

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

    weatherization 600,000 homes - Income eligibility was raised from 150% to 200% of the poverty level - Increased WAP training dollars (from 10% to 20%) - Dollars per house increased ...

  20. ARM - Weather

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

    SitesWeather Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Weather Air Quality Meteorology This website features a course for environmental decision-makers, scientists, technical advisors, and educators. The course is introduces basic concepts of meteorology and air quality necessary to

  1. Stimulation Prediction Models | Open Energy Information

    Open Energy Info (EERE)

    Predictive Simulator for Enhanced Geothermal Systems California Science Applications International Corporation Recovery Act: Enhanced Geothermal Systems Component Research and...

  2. Application of global weather and climate model output to the design and operation of wind-energy systems

    SciTech Connect (OSTI)

    Curry, Judith

    2015-05-21

    This project addressed the challenge of providing weather and climate information to support the operation, management and planning for wind-energy systems. The need for forecast information is extending to longer projection windows with increasing penetration of wind power into the grid and also with diminishing reserve margins to meet peak loads during significant weather events. Maintenance planning and natural gas trading is being influenced increasingly by anticipation of wind generation on timescales of weeks to months. Future scenarios on decadal time scales are needed to support assessment of wind farm siting, government planning, long-term wind purchase agreements and the regulatory environment. The challenge of making wind forecasts on these longer time scales is associated with a wide range of uncertainties in general circulation and regional climate models that make them unsuitable for direct use in the design and planning of wind-energy systems. To address this challenge, CFAN has developed a hybrid statistical/dynamical forecasting scheme for delivering probabilistic forecasts on time scales from one day to seven months using what is arguably the best forecasting system in the world (European Centre for Medium Range Weather Forecasting, ECMWF). The project also provided a framework to assess future wind power through developing scenarios of interannual to decadal climate variability and change. The Phase II research has successfully developed an operational wind power forecasting system for the U.S., which is being extended to Europe and possibly Asia.

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

    Office of Scientific and Technical Information (OSTI)

    SciTech Connect Predictive Models of Li-ion Battery Lifetime (Presentation) Citation Details In-Document Search Title: Predictive Models of Li-ion Battery Lifetime (Presentation) Predictive models of Li-ion battery reliability must consider a multiplicity of electrochemical, thermal and mechanical degradation modes experienced by batteries in application environments. Complicating matters, Li-ion batteries can experience several path dependent degradation trajectories dependent on storage

  4. 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...

  5. Weather | Princeton Plasma Physics Lab

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

    Weather Princeton, New Jersey, weather forecast Click here for more extensive PPPL weather information....

  6. PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in...

    Open Energy Info (EERE)

    San Francisco, CA, A41F-01. Fast JD, JC Doran, JC Barnard, S Springs ton, L Klein man, L Emmons, C Wiedinmyer. 2007. "Predictions of aerosols downwind of Mexico City using a...

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

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

    Degradation Mechanisms for Advanced Reflector Materials | Department of Energy Predictive Physico-Chemical Modeling of Intrinsic Degradation Mechanisms for Advanced Reflector Materials Project Profile: Predictive Physico-Chemical Modeling of Intrinsic Degradation Mechanisms for Advanced Reflector Materials NREL logo NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing a physics-based computational

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

    SciTech Connect (OSTI)

    Hemez, Francois M; Unal, Cetin; Atamturktur, Huriye S

    2010-01-01

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

  9. 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.

  10. Dynamic model predicts well bore surge and swab pressures

    SciTech Connect (OSTI)

    Bing, Z.; Kaiji, Z.

    1996-12-30

    A dynamic well control model predicts surge and swab pressures more accurately than a steady-state model, thereby providing better estimates of pressure fluctuations when pipe is tripped. Pressure fluctuations from tripping pipe into a well can contribute to lost circulation, kicks,and well control problems. This dynamic method of predicting surge and swab pressures was verified in a full-scale test well in the Zhong Yuan oil field in China. Both the dynamic model and steady state model were verified through the test data. The test data showed the dynamic model can correctly predict downhole pressures from running or pulling pipe in a well; steady state models may result in relatively large prediction errors, especially in deeper wells.

  11. New model predicts once-mysterious chemical reactions

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

    New model predicts once-mysterious chemical reactions New model predicts once-mysterious chemical reactions Results will also be used to understand basic questions about nature such as the cooling mechanisms of the early universe and the formation of planets and stars. June 28, 2016 Mark Zammit, of Los Alamos' Physics and Chemistry of Materials group, is part of a team that developed a theoretical model to forecast the fundamental chemical reactions involving molecular hydrogen. Photo credit

  12. 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.

  13. Today's Forecast: Improved Wind Predictions

    Broader source: Energy.gov [DOE]

    Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable.

  14. SimTable helps firefighters model and predict fire direction

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

    SimTable models and predicts fire path SimTable helps firefighters model and predict fire direction In 2009, SimTable received $100,000 from the LANS Venture Acceleration Fund to improve the user interface and seed firefighting academies with customized set ups. April 3, 2012 Stephen Guerin (L) and Chip Garner (R) with SimTable Stephen Guerin (L), and Chip Garner (R), with SimTable, a Santa Fe company helping firefighters model and predict where a fire is most likely to spread, received support

  15. In silico modeling to predict drug-induced phospholipidosis

    SciTech Connect (OSTI)

    Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G. 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 structureactivity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the construction and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 8081% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ? 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. The training set data in the models is derived from the FDA's phospholipidosis database. We find excellent predictivity values of the models based on external validation. The models can support drug screening and regulatory decision-making on DIPL.

  16. Statistical thermodynamics model and empirical correlations for predicting

    Office of Scientific and Technical Information (OSTI)

    mixed hydrate phase equilibria (Journal Article) | SciTech Connect Statistical thermodynamics model and empirical correlations for predicting mixed hydrate phase equilibria Citation Details In-Document Search Title: Statistical thermodynamics model and empirical correlations for predicting mixed hydrate phase equilibria Authors: Garapati, Nagasree ; Anderson, Brian J Publication Date: 2014-07-01 OSTI Identifier: 1165558 Report Number(s): A-UNIV-PUB-100 Journal ID: ISSN 0378-3812 DOE Contract

  17. Prediction of cloud droplet number in a general circulation model

    SciTech Connect (OSTI)

    Ghan, S.J.; Leung, L.R.

    1996-04-01

    We have applied the Colorado State University Regional Atmospheric Modeling System (RAMS) bulk cloud microphysics parameterization to the treatment of stratiform clouds in the National Center for Atmospheric Research Community Climate Model (CCM2). The RAMS predicts mass concentrations of cloud water, cloud ice, rain and snow, and number concnetration of ice. We have introduced the droplet number conservation equation to predict droplet number and it`s dependence on aerosols.

  18. Using a Simple Binomial Model to Assess Improvement in Predictive

    Office of Scientific and Technical Information (OSTI)

    Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis (Technical Report) | SciTech Connect Technical Report: Using a Simple Binomial Model to Assess Improvement in Predictive Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis Citation Details In-Document Search Title: Using a Simple Binomial Model to Assess Improvement in Predictive Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis We present a

  19. A thermodynamic model to predict the aqueous solubility of hydrocarbon

    Office of Scientific and Technical Information (OSTI)

    mixtures at two-phase hydrate-liquid water equilibrium (Journal Article) | SciTech Connect Journal Article: A thermodynamic model to predict the aqueous solubility of hydrocarbon mixtures at two-phase hydrate-liquid water equilibrium Citation Details In-Document Search This content will become publicly available on March 30, 2018 Title: A thermodynamic model to predict the aqueous solubility of hydrocarbon mixtures at two-phase hydrate-liquid water equilibrium Authors: Velaga, Srinath C.

  20. PV Module Intraconnect Thermomechanical Durability Damage Prediction Model

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

    | Department of Energy Module Intraconnect Thermomechanical Durability Damage Prediction Model PV Module Intraconnect Thermomechanical Durability Damage Prediction Model Presented at the PV Module Reliability Workshop, February 26 - 27 2013, Golden, Colorado pvmrw13_ps2_dow_gaston.pdf (1.26 MB) More Documents & Publications FY2015 Status Report: CIRFT Testing of High-Burnup Used Nuclear Fuel Rods from Pressurized Water Reactor and BWR Environments 2014 Propulsion Materials R&D Annual

  1. 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.

  2. Coupling WRF double-moment 6-class microphysics schemes to RRTMG radiation scheme in weather research forecasting model

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

    Bae, Soo Ya; Hong, Song -You; Lim, Kyo-Sun Sunny

    2016-01-01

    A method to explicitly calculate the effective radius of hydrometeors in the Weather Research Forecasting (WRF) double-moment 6-class (WDM6) microphysics scheme is designed to tackle the physical inconsistency in cloud properties between the microphysics and radiation processes. At each model time step, the calculated effective radii of hydrometeors from the WDM6 scheme are linked to the Rapid Radiative Transfer Model for GCMs (RRTMG) scheme to consider the cloud effects in radiative flux calculation. This coupling effect of cloud properties between the WDM6 and RRTMG algorithms is examined for a heavy rainfall event in Korea during 25–27 July 2011, and itmore » is compared to the results from the control simulation in which the effective radius is prescribed as a constant value. It is found that the derived radii of hydrometeors in the WDM6 scheme are generally larger than the prescribed values in the RRTMG scheme. Consequently, shortwave fluxes reaching the ground (SWDOWN) are increased over less cloudy regions, showing a better agreement with a satellite image. The overall distribution of the 24-hour accumulated rainfall is not affected but its amount is changed. In conclusion, a spurious rainfall peak over the Yellow Sea is alleviated, whereas the local maximum in the central part of the peninsula is increased.« less

  3. The selection of turbulence models for prediction of room airflow

    SciTech Connect (OSTI)

    Nielsen, P.V.

    1998-10-01

    The airflow in buildings involves a combination of many different flow elements. It is, therefore, difficult to find an adequate, all-round turbulence model covering all aspects. Consequently, it is appropriate and economical to choose turbulence models according to the situation that is to be predicted. This paper discusses the use of different turbulence models and their advantages in given situations. As an example, it is shown that a simple zero-equation model can be used for the prediction of special situations as flow with a low level of turbulence. A zero-equation model with compensation for room dimensions and velocity level also is discussed. A {kappa}-{epsilon} model expanded by damping functions is used to improve the prediction of the flow in a room ventilated by displacement ventilation. The damping functions especially take into account the turbulence level and the vertical temperature gradient. Low Reynolds number models (LNR models) are used to improve the prediction of evaporation-controlled emissions from building material, which is shown by an example. Finally, large eddy simulation (LES) of room airflow is discussed and demonstrated.

  4. 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.

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

    SciTech Connect (OSTI)

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

    1991-12-01

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

  6. Predictive Models of Li-ion Battery Lifetime

    SciTech Connect (OSTI)

    Smith, Kandler; Wood, Eric; Santhanagopalan, Shriram; Kim, Gi-heon; Shi, Ying; Pesaran, Ahmad

    2015-06-15

    It remains an open question how best to predict real-world battery lifetime based on accelerated calendar and cycle aging data from the laboratory. Multiple degradation mechanisms due to (electro)chemical, thermal, and mechanical coupled phenomena influence Li-ion battery lifetime, each with different dependence on time, cycling and thermal environment. The standardization of life predictive models would benefit the industry by reducing test time and streamlining development of system controls.

  7. 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.

  8. Cathy Zoi on Weatherization

    Broader source: Energy.gov [DOE]

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

  9. Sandia's ice sheet modeling of Greenland, Antarctica helps predict

    National Nuclear Security Administration (NNSA)

    sea-level rise | National Nuclear Security Administration | (NNSA) Sandia's ice sheet modeling of Greenland, Antarctica helps predict sea-level rise Wednesday, March 2, 2016 - 12:00am Sandia California researchers Irina Tezaur and Ray Tuminaro analyze a model of Antarctica. They are part of a Sandia team working to improve the reliability and efficiency of computational models that describe ice sheet behavior and dynamics. The Greenland and Antarctic ice sheets will make a dominant

  10. Lepton Flavor Violation in Predictive SUSY-GUT Models

    SciTech Connect (OSTI)

    Albright, Carl H.; 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.

  11. Mathematical modeling to predict residential solid waste generation

    SciTech Connect (OSTI)

    Ojeda Benitez, Sara; Vega, Carolina Armijo de

    2008-07-01

    One of the challenges faced by waste management authorities is determining the amount of waste generated by households in order to establish waste management systems, as well as trying to charge rates compatible with the principle applied worldwide, and design a fair payment system for households according to the amount of residential solid waste (RSW) they generate. The goal of this research work was to establish mathematical models that correlate the generation of RSW per capita to the following variables: education, income per household, and number of residents. This work was based on data from a study on generation, quantification and composition of residential waste in a Mexican city in three stages. In order to define prediction models, five variables were identified and included in the model. For each waste sampling stage a different mathematical model was developed, in order to find the model that showed the best linear relation to predict residential solid waste generation. Later on, models to explore the combination of included variables and select those which showed a higher R{sup 2} were established. The tests applied were normality, multicolinearity and heteroskedasticity. Another model, formulated with four variables, was generated and the Durban-Watson test was applied to it. Finally, a general mathematical model is proposed to predict residential waste generation, which accounts for 51% of the total.

  12. Product component genealogy modeling and field-failure prediction

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

    King, Caleb; Hong, Yili; Meeker, William Q.

    2016-04-13

    Many industrial products consist of multiple components that are necessary for system operation. There is an abundance of literature on modeling the lifetime of such components through competing risks models. During the life-cycle of a product, it is common for there to be incremental design changes to improve reliability, to reduce costs, or due to changes in availability of certain part numbers. These changes can affect product reliability but are often ignored in system lifetime modeling. By incorporating this information about changes in part numbers over time (information that is readily available in most production databases), better accuracy can bemore » achieved in predicting time to failure, thus yielding more accurate field-failure predictions. This paper presents methods for estimating parameters and predictions for this generational model and a comparison with existing methods through the use of simulation. Our results indicate that the generational model has important practical advantages and outperforms the existing methods in predicting field failures.« less

  13. Predictive RANS simulations via Bayesian Model-Scenario Averaging

    SciTech Connect (OSTI)

    Edeling, W.N.; Cinnella, P.; Dwight, R.P.

    2014-10-15

    The turbulence closure model is the dominant source of error in most Reynolds-Averaged Navier–Stokes simulations, yet no reliable estimators for this error component currently exist. Here we develop a stochastic, a posteriori error estimate, calibrated to specific classes of flow. It is based on variability in model closure coefficients across multiple flow scenarios, for multiple closure models. The variability is estimated using Bayesian calibration against experimental data for each scenario, and Bayesian Model-Scenario Averaging (BMSA) is used to collate the resulting posteriors, to obtain a stochastic estimate of a Quantity of Interest (QoI) in an unmeasured (prediction) scenario. The scenario probabilities in BMSA are chosen using a sensor which automatically weights those scenarios in the calibration set which are similar to the prediction scenario. The methodology is applied to the class of turbulent boundary-layers subject to various pressure gradients. For all considered prediction scenarios the standard-deviation of the stochastic estimate is consistent with the measurement ground truth. Furthermore, the mean of the estimate is more consistently accurate than the individual model predictions.

  14. 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.

  15. Weatherization and Intergovernmental Activities

    Broader source: Energy.gov [DOE]

    Weatherization and Intergovernmental Activities Annual Performance Results and Targets FY 2008 Congressional Budget

  16. 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.

  17. Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models

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

    Lu, Dan; Ye, Ming; Curtis, Gary P.

    2015-08-01

    While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. Our study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict themore » reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. Moreover, these reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Finally

  18. Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models

    SciTech Connect (OSTI)

    Lu, Dan; Ye, Ming; Curtis, Gary P.

    2015-08-01

    While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. Our study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict the reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. Moreover, these reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Finally, limitations of

  19. Weatherize | Department of Energy

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

    Weatherize Weatherize Proper insulation is just one element of weatherization that can save you money and improve the comfort and efficiency of your home. | Photo courtesy of Dennis Schroeder, NREL. Proper insulation is just one element of weatherization that can save you money and improve the comfort and efficiency of your home. | Photo courtesy of Dennis Schroeder, NREL. Weatherizing your home helps you save money by saving energy, and it can also improve the comfort of your home. Conduct a

  20. Improving models to predict phenological responses to global change

    SciTech Connect (OSTI)

    Richardson, Andrew D.

    2015-11-25

    The term phenology describes both the seasonal rhythms of plants and animals, and the study of these rhythms. Plant phenological processes, including, for example, when leaves emerge in the spring and change color in the autumn, are highly responsive to variation in weather (e.g. a warm vs. cold spring) as well as longer-term changes in climate (e.g. warming trends and changes in the timing and amount of rainfall). We conducted a study to investigate the phenological response of northern peatland communities to global change. Field work was conducted at the SPRUCE experiment in northern Minnesota, where we installed 10 digital cameras. Imagery from the cameras is being used to track shifts in plant phenology driven by elevated carbon dioxide and elevated temperature in the different SPRUCE experimental treatments. Camera imagery and derived products (“greenness”) is being posted in near-real time on a publicly available web page (http://phenocam.sr.unh.edu/webcam/gallery/). The images will provide a permanent visual record of the progression of the experiment over the next 10 years. Integrated with other measurements collected as part of the SPRUCE program, this study is providing insight into the degree to which phenology may mediate future shifts in carbon uptake and storage by peatland ecosystems. In the future, these data will be used to develop improved models of vegetation phenology, which will be tested against ground observations collected by a local collaborator.

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

    SciTech Connect (OSTI)

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

    2014-09-01

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

  2. Comparison of Uncertainty of Two Precipitation Prediction Models at Los Alamos National Lab Technical Area 54

    SciTech Connect (OSTI)

    Shield, Stephen Allan; Dai, Zhenxue

    2015-08-18

    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.

  3. NREL: Transportation Research - NREL's Battery Life Predictive Model Helps

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

    Companies Take Charge NREL's Battery Life Predictive Model Helps Companies Take Charge October 26, 2015 A series of batteries hooked together next to a monitor. An example of a stationary, grid-connected battery is the NREL project from Erigo/EaglePicher Technologies, LLC Technologies. Inverters and nickel cadmium batteries inside of a utility scale 300 kW battery storage system will support Department of Defense micro-grids. Photo by Dennis Schroeder / NREL 32696 Companies that rely on

  4. Predictive Materials Modeling for Li-Air Battery Systems | Argonne

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

    Leadership Computing Facility electron density obtained from a density functional theory Shown here is the electron density obtained from a density functional theory (DFT) calculation of lithium oxide (Li2O) performed with the GPAW code. This visualization was the result of a simulation run on Intrepid, a supercomputer at the Argonne Leadership Computing Facility. Kah Chun Lau, Aaron Knoll and Larry A. Curtiss, Argonne National Laboratory Predictive Materials Modeling for Li-Air Battery

  5. Predictive Materials Modeling for Li-Air Battery Systems | Argonne

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

    Leadership Computing Facility Predictive Materials Modeling for Li-Air Battery Systems PI Name: Larry Curtiss PI Email: curtiss@anl.gov Institution: Argonne National Laboratory Allocation Program: INCITE Allocation Hours at ALCF: 50 Million Year: 2015 Research Domain: Materials Science A rechargeable lithium-air (Li-air) battery can potentially store five to ten times the energy of a lithium-ion (Li-ion) battery of the same weight. Realizing this enormous potential presents a challenging

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

    SciTech Connect (OSTI)

    Ying, Khor Chia; Hin, Pooi Ah

    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 φ{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 φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{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.

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

    SciTech Connect (OSTI)

    Ma, Yudong; Borrelli, Francesco; Hencey, Brandon; Coffey, Brian; Bengea, Sorin; Haves, Philip

    2010-06-29

    A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reduction in the central plant electricity cost and improvement of its efficiency.

  8. Weather-Resistive Barriers

    SciTech Connect (OSTI)

    2000-10-01

    How to select and install housewrap and other types of weather-resistive barriers: Building Technology Fact Sheet

  9. Weatherization Assistance Program

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

    Weatherization Assistance Program State Energy Advisory Board Meeting Washington, DC Robert C. Adams DOE Weatherization Assistance Program 1 | WAP Training & Technical Assistance Tools and Resources eere.energy.gov Weatherization Assistance Program Background * The WAP leads the nation in advancing technology, research and work practices related to making residential energy upgrades cost effective, safe and comprehensive * Over 7.3 million low-income dwelling units have been weatherized

  10. Weatherization Assistance Program

    Broader source: Energy.gov [DOE]

    This fact sheet provides an overview of the U.S. Department of Energys Weatherization Assistance Program.

  11. The Impact of Weatherization

    Broader source: Energy.gov [DOE]

    The Weatherization Assistance Program under the Recovery Act is making a serious impact in savings this summer.

  12. 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.

  13. QMC Simulations Database for Predictive Modeling and Theory | Argonne

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

    Leadership Computing Facility DMC spin densities for antiferromagnetic states AF1 (left) and AF3 (right) DMC spin densities for antiferromagnetic states AF1 (left) and AF3 (right). Shown only atoms with a non-null spin. The picture shows the localization of the spins in d-orbital. Blue is a spin down, while yellow is a spin up. Anouar Benali, Argonne National Laboratory QMC Simulations Database for Predictive Modeling and Theory PI Name: David Ceperley PI Email: ceperley@illinois.edu

  14. 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.

  15. 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

  16. Aleutian Pribilof Islands Weatherization Project

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

    Weatherization Energy conservation education ... Native Village of Sand Point, AK Focus Communities Unanagx ... core competencies for the Weatherization Assistance Program. ...

  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. Predicting laser weld reliability with stochastic reduced-order models. Predicting laser weld reliability

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

    Emery, John M.; Field, Richard V.; Foulk, James W.; Karlson, Kyle N.; Grigoriu, Mircea D.

    2015-05-26

    Laser welds are prevalent in complex engineering systems and they frequently govern failure. The weld process often results in partial penetration of the base metals, leaving sharp crack-like features with a high degree of variability in the geometry and material properties of the welded structure. Furthermore, accurate finite element predictions of the structural reliability of components containing laser welds requires the analysis of a large number of finite element meshes with very fine spatial resolution, where each mesh has different geometry and/or material properties in the welded region to address variability. We found that traditional modeling approaches could not bemore » efficiently employed. Consequently, a method is presented for constructing a surrogate model, based on stochastic reduced-order models, and is proposed to represent the laser welds within the component. Here, the uncertainty in weld microstructure and geometry is captured by calibrating plasticity parameters to experimental observations of necking as, because of the ductility of the welds, necking – and thus peak load – plays the pivotal role in structural failure. The proposed method is exercised for a simplified verification problem and compared with the traditional Monte Carlo simulation with rather remarkable results.« less

  19. Predicting laser weld reliability with stochastic reduced-order models. Predicting laser weld reliability

    SciTech Connect (OSTI)

    Emery, John M.; Field, Richard V.; Foulk, James W.; Karlson, Kyle N.; Grigoriu, Mircea D.

    2015-05-26

    Laser welds are prevalent in complex engineering systems and they frequently govern failure. The weld process often results in partial penetration of the base metals, leaving sharp crack-like features with a high degree of variability in the geometry and material properties of the welded structure. Furthermore, accurate finite element predictions of the structural reliability of components containing laser welds requires the analysis of a large number of finite element meshes with very fine spatial resolution, where each mesh has different geometry and/or material properties in the welded region to address variability. We found that traditional modeling approaches could not be efficiently employed. Consequently, a method is presented for constructing a surrogate model, based on stochastic reduced-order models, and is proposed to represent the laser welds within the component. Here, the uncertainty in weld microstructure and geometry is captured by calibrating plasticity parameters to experimental observations of necking as, because of the ductility of the welds, necking – and thus peak load – plays the pivotal role in structural failure. The proposed method is exercised for a simplified verification problem and compared with the traditional Monte Carlo simulation with rather remarkable results.

  20. 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.

  1. Differential Angstrom model for predicting insolation from hours of sunshine

    SciTech Connect (OSTI)

    Yeboah-Amankwah, D.; Agyeman, K.

    1990-01-01

    The Angstrom model for predicting insolation is limited in scope because it gives equal weighting to sunshine hours recorded at any time of the day. The differential Angstrom model presented in this paper removes this limitation and relates insolation, q{sub j}, in the j{sup th} hour to the sunshine duration, n{sub j}, of the same period by the equation: q{sub j} = a{sub j} + b{sub j}. By regression analysis of monthly data, the set of constants a{sub j} and b{sub j} for each hour of each month of the year can be determined. Thus, using the appropriate set of a and b regression coefficients, any sunshine data can be transformed to insolation. The sum of the equation over a day gives the daily insolation from which monthly means can be calculated. The method has been applied to the 1986 and 1988 sunshine data recorded at the University of Papua New Guinea to predict the observed insolation to within 3.5%. The differential Angstrom method has applications in places which have much recorded data on hours of sunshine but have limited observed insolation data.

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

    SciTech Connect (OSTI)

    DelSole, Timothy

    2015-08-31

    The purpose of the proposed research was to identify unforced predictable components on decadal time scales, distinguish these components from forced predictable components, and to assess the reliability of model predictions of these components. The question of whether anthropogenic forcing changes decadal predictability, or gives rise to new forms of decadal predictability, also will be

  3. Development of a land ice core for the Model for Prediction Across...

    Office of Scientific and Technical Information (OSTI)

    a land ice core for the Model for Prediction Across Scales (MPAS) Citation Details In-Document Search Title: Development of a land ice core for the Model for Prediction Across Scales ...

  4. Development of a land ice core for the Model for Prediction Across...

    Office of Scientific and Technical Information (OSTI)

    for the Model for Prediction Across Scales (MPAS) Citation Details In-Document Search Title: Development of a land ice core for the Model for Prediction Across Scales (MPAS) No ...

  5. Land-ice modeling for sea-level prediction (Technical Report...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Land-ice modeling for sea-level prediction Citation Details In-Document Search Title: Land-ice modeling for sea-level prediction Authors: Lipscomb, William H 1 ...

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

    SciTech Connect (OSTI)

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

    2002-05-01

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

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

    SciTech Connect (OSTI)

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

    2012-07-22

    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. 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.

  9. Practical model for predicting pressure in gas-storage reservoirs

    SciTech Connect (OSTI)

    Mollnard, J.E.; Le Bitoux, P.; Pelce, V. ); Tek, M.R. )

    1990-11-01

    Optional planning, design, and operation of gas fields in production or storage critically depends on reliable models for predicting pressures that are often based on sophisticated numerical and mathematical concepts. The pressure that prevails at a given time is a direct function of production/injection schedules, past history, and surface equipment as related to reserves and reservoir characteristics. Maintaining the pressure within prescribed limits is particularly important in underground storage to avoid pressures above a maximum for reasons of safety and migration and below a minimum for surface-equipment and contracted-deliverability considerations. This paper presents a way to calculate the convolution integral on which the pressure variations depend. The classic methods were long and costly to run and seldom used. The author's method, which identifies this convolution integral with a finite sum of exponential terms, is much quicker and has been implemented in a program called PREPRE, usable on microcomputers. Based on a production/pressure schedule, the model is capable of forecasting the evolution of pressures in main zones of interest, such as wellbores, gathering systems, and surface equipment. The data required for the model-past production/pressure history-are matched by a special algorithm that automatically calculates the main reservoir parameters used as bases for future projections.

  10. Adaptive model predictive process control using neural networks

    DOE Patents [OSTI]

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    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.

  11. 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.

  12. Aquatic pathways model to predict the fate of phenolic compounds

    SciTech Connect (OSTI)

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

    1983-04-01

    Organic materials released from energy-related activities could affect human health and the environment. To better assess possible impacts, we developed a model to predict the fate of spills or discharges of pollutants into flowing or static bodies of fresh water. A computer code, Aquatic Pathways Model (APM), was written to implement the model. The computer programs use compartmental analysis to simulate aquatic ecosystems. The APM estimates the concentrations of chemicals in fish tissue, water and sediment, and is therefore useful for assessing exposure to humans through aquatic pathways. The APM will consider any aquatic pathway for which the user has transport data. Additionally, APM will estimate transport rates from physical and chemical properties of chemicals between several key compartments. The major pathways considered are biodegradation, fish and sediment uptake, photolysis, and evaporation. The model has been implemented with parameters for distribution of phenols, an important class of compounds found in the water-soluble fractions of coal liquids. Current modeling efforts show that, in comparison with many pesticides and polyaromatic hydrocarbons (PAH), the lighter phenolics (the cresols) are not persistent in the environment. The properties of heavier molecular weight phenolics (indanols, naphthols) are not well enough understood at this time to make similar judgements. For the twelve phenolics studied, biodegradation appears to be the major pathway for elimination from aquatic environments. A pond system simulation (using APM) of a spill of solvent refined coal (SRC-II) materials indicates that phenol, cresols, and other single cyclic phenolics are degraded to 16 to 25 percent of their original concentrations within 30 hours. Adsorption of these compounds into sediments and accumulation by fish was minor.

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

    SciTech Connect (OSTI)

    Hoffman, E.; Skidmore, E.

    2009-11-24

    The Savannah River Site (SRS) is currently storing plutonium materials in the K-Area Materials Storage (KAMS) facility. The materials are packaged per the DOE 3013 Standard and transported and stored in KAMS in Model 9975 shipping packages, which include double containment vessels sealed with dual O-rings made of Parker Seals compound V0835-75 (based on Viton{reg_sign} GLT). The outer O-ring of each containment vessel is credited for leaktight containment per ANSI N14.5. O-ring service life depends on many factors, including the failure criterion, environmental conditions, overall design, fabrication quality and assembly practices. A preliminary life prediction model has been developed for the V0835-75 O-rings in KAMS. The conservative model is based primarily on long-term compression stress relaxation (CSR) experiments and Arrhenius accelerated-aging methodology. For model development purposes, seal lifetime is defined as a 90% loss of measurable sealing force. Thus far, CSR experiments have only reached this target level of degradation at temperatures {ge} 300 F. At lower temperatures, relaxation values are more tolerable. Using time-temperature superposition principles, the conservative model predicts a service life of approximately 20-25 years at a constant seal temperature of 175 F. This represents a maximum payload package at a constant ambient temperature of 104 F, the highest recorded in KAMS to date. This is considered a highly conservative value as such ambient temperatures are only reached on occasion and for short durations. The presence of fiberboard in the package minimizes the impact of such temperature swings, with many hours to several days required for seal temperatures to respond proportionately. At 85 F ambient, a more realistic but still conservative value, bounding seal temperatures are reduced to {approx}158 F, with an estimated seal lifetime of {approx}35-45 years. The actual service life for O-rings in a maximum wattage package likely lies

  14. Estimating vehicle roadside encroachment frequency using accident prediction models

    SciTech Connect (OSTI)

    Miaou, S.-P.

    1996-07-01

    The existing data to support the development of roadside encroachment- based accident models are extremely limited and largely outdated. Under the sponsorship of the Federal Highway Administration and Transportation Research Board, several roadside safety projects have attempted to address this issue by providing rather comprehensive data collection plans and conducting pilot data collection efforts. It is clear from the results of these studies that the required field data collection efforts will be expensive. Furthermore, the validity of any field collected encroachment data may be questionable because of the technical difficulty to distinguish intentional from unintentional encroachments. This paper proposes an alternative method for estimating the basic roadside encroachment data without actually field collecting them. The method is developed by exploring the probabilistic relationships between a roadside encroachment event and a run-off-the-road event With some mild assumptions, the method is capable of providing a wide range of basic encroachment data from conventional accident prediction models. To illustrate the concept and use of such a method, some basic encroachment data are estimated for rural two-lane undivided roads. In addition, the estimated encroachment data are compared with the existing collected data. The illustration shows that the method described in this paper can be a viable approach to estimating basic encroachment data without actually collecting them which can be very costly.

  15. 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.

  16. 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...

  17. 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.

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

    SciTech Connect (OSTI)

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

    2012-10-01

    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.

  19. Stability of Ensemble Models Predicts Productivity of Enzymatic Systems

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

    Theisen, Matthew K.; Lafontaine Rivera, Jimmy G.; Liao, James C.

    2016-03-10

    Stability in a metabolic system may not be obtained if incorrect amounts of enzymes are used. Without stability, some metabolites may accumulate or deplete leading to the irreversible loss of the desired operating point. Even if initial enzyme amounts achieve a stable steady state, changes in enzyme amount due to stochastic variations or environmental changes may move the system to the unstable region and lose the steady-state or quasi-steady-state flux. This situation is distinct from the phenomenon characterized by typical sensitivity analysis, which focuses on the smooth change before loss of stability. Here we show that metabolic networks differ significantlymore » in their intrinsic ability to attain stability due to the network structure and kinetic forms, and that after achieving stability, some enzymes are prone to cause instability upon changes in enzyme amounts. We use Ensemble Modelling for Robustness Analysis (EMRA) to analyze stability in four cell-free enzymatic systems when enzyme amounts are changed. Loss of stability in continuous systems can lead to lower production even when the system is tested experimentally in batch experiments. The predictions of instability by EMRA are supported by the lower productivity in batch experimental tests. Finally, the EMRA method incorporates properties of network structure, including stoichiometry and kinetic form, but does not require specific parameter values of the enzymes.« less

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

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

    NREL logo NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing a physics-based computational ...

  1. 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 ...

  2. New climate model predicts likelihood of Greenland ice melt, sea level rise

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

    and dangerous temperatures New climate model predicts likelihood of Greenland ice melt New climate model predicts likelihood of Greenland ice melt, sea level rise and dangerous temperatures A new computer model of accumulated carbon emissions predicts the likelihood of crossing several dangerous climate change thresholds. November 20, 2015 Greenland ice loss. Greenland ice loss. Contact Kevin Roark Communications Office (505) 665-9202 Email "The model is based on idealized

  3. An Inupiat Weather Report

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

    An Iñupiat Weather Report Grades: 6 th - 8 th Duration: 2-3 hours of class time. Time for students to prepare their reports: 1 week. Objectives: The objective of this lesson is for students to correctly use the Iñupiat language using weather related vocabulary, numbers, and days of the week. Students will prepare a weather forecast and present it as if they were on a television news program. The forecast must be entirely in the Iñupiat language. Alaska State Content Standards:

  4. Cold Weather Hazards

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

    0 Cold Weather Hazards June 2010 NSA_cwh_Rev10.doc 1 Atmospheric Radiation Measurement Climate Research Facility/ North Slope of Alaska/Adjacent Arctic Ocean (ACRF/NSA/AAO) Cold Weather Hazards Winter Conditions at the North Slope of Alaska The North Slope of Alaska is north of the Arctic Circle at latitudes ranging from 69 to 72 degrees. Barrow, the largest town on the North Slope (pop. 4500), is the site of a National Weather Service Station, which has been active for several decades, so the

  5. 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.

  6. 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

  7. 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.

  8. 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...

  9. 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.

  10. Weatherization Assistance Program (WAP)

    Broader source: Energy.gov [DOE]

    Through the Weatherization Assistance Program (WAP), the U.S. Department of Energy (DOE) issues grants to states, territories, and some Indian tribes to improve the energy efficiency of low-income...

  11. Impact of heterogeneous chemistry on model predictions of ozone changes

    SciTech Connect (OSTI)

    Granier, C.; Brasseur, G. )

    1992-11-20

    A two-dimensional chemical/transport model of the middle atmosphere is used to assess the importance of chemical heterogeneous processes in the polar regions (on polar stratospheric clouds (PSCs)) and at other latitudes (on sulfate aerosols). When conversion on type I and type II PSCs of N[sub 2]O[sub 5] into HNO[sub 3] and of CIONO[sub 2] into reactive forms of chlorine is taken into account, enhanced CIO concentrations lead to the formation of a springtime ozone hole over the Antarctic continent; no such major reduction in the ozone column is found in the Arctic region. When conversion of nitrogen and chlorine compounds is assumed to occur on sulfate particles in the lower stratosphere, significant perturbations in the chemistry are also found. For background aerosol conditions, the concentration of nitric acid is enhanced and agrees with observed values, while that of nitrogen oxides is reduced and agrees less than if heterogeneous processes are ignored in the calculations. The concentration of the OH radical is significantly increased. Ozone number density appears to become larger between 16 and 30 km but smaller below 16 km, especially at high latitudes. The ozone column is only slightly modified, except at high latitudes where it is substantially reduced if the CIONO[sub 2] conversion into reactive chlorine is considered. After a large volcanic eruption these changes are further exacerbated. The ozone budget in the lower stratrosphere becomes less affected by nitrogen oxides but is largely controlled by the CIO[sub x] and HO[sub x] chemistries. A substantial decrease in the ozone column is predicted as a result of the Pinatubo volcanic eruption, mostly in winter at middle and high latitudes. 62 refs., 18 figs., 3 tabs.

  12. The quest to predict severe weather sooner

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

    MPAS's variable mesh enables smooth transitions from higher resolution (over North America in this example) to coarser resolution over the rest of the globe. (Credit: UCAR) "What's ...

  13. WEATHER PREDICTIONS AND SURFACE RADIATION ESTIMATES

    Office of Legacy Management (LM)

    RADIATION ESTIMATES for the RULISON EVENT Final Report Albert H . S t o u t , Ray E . ... f i c e U . ' S . Atomic Energy Commission January 1970 LEGAL NOTSCCE ; L *U . . . . . - . ...

  14. 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.

  15. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    SciTech Connect (OSTI)

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A; Ge, Y

    2014-06-15

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH/NCI under grant

  16. A Predictive Model of Fragmentation using Adaptive Mesh Refinement...

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

    A new arena for predictive simulations in high- powered laser systems "12 NIF" Or 96 ... Numerical simulations show how to mitigate damage from debris and shrapnel Damage prior to ...

  17. 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

  18. Attributing Changes in the Risk of Extreme Weather and Climate...

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

    150 Million Year: 2013 Research Domain: Earth Science The climate system is a naturally ... Modeling of the statistics of extreme weather is exceedingly computationally intensive. ...

  19. DOPPLER WEATHER SYSTEM

    Energy Science and Technology Software Center (OSTI)

    2002-08-05

    The SRS Doppler Weather System consists of a Doppler Server, A Master Server (also known as the Weather Server), several Doppler Slave Servers, and client-side software program called the Doppler Radar Client. This system is used to display near rel-time images taken from the SRS Weather Center's Doppler Radar computer. The Doppler Server is software that resides on the SRS Doppler Computer. It gathers raw data, 24-bit color weather images via screen scraping ever fivemore » minutes as requested by the Master Server. The Doppler Server then reduces the 24-bit color images to 8-bit color using a fixed color table for analysis and compression. This preserves the fidelity of the image color and arranges the colors in specific order for display. At the time of color reduction, the white color used for the city names on the background images are remapped to a different index (color) of white that the white on the weather scale. The Weather Server places a time stamp on the image, then compresses the image and passes it to all Doppler Slave servers. Each of the Doppler Slave servers mainitain a circular buffer of the eight most current images representing the last 40 minutes of weather data. As a new image is added, the oldest drops off. The Doppler Radar Client is an optional install program for any site-wide workstation. When a Client session is started, the Client requests Doppler Slave server assignment from the Master Server. Upon its initial request to the Slave Server, the Client obtains all eight current images and maintains its own circular buffer, updating its images every five minutes as the Doppler Slave is updated. Three background reference images are stored as part of the Client. The Client brings up the appropriate background image, decompresses the doppler data, and displays the doppler data on the background image.« less

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

    Office of Scientific and Technical Information (OSTI)

    existing coupled atmospheric models due to the high computational cost of each simulation. ... CLIMATES; DIAGNOSIS; DISTRIBUTION; FORECASTING; GENERAL CIRCULATION MODELS; METRICS; ...

  1. Final Technical Report: Increasing Prediction Accuracy.

    SciTech Connect (OSTI)

    King, Bruce Hardison; Hansen, Clifford; Stein, Joshua

    2015-12-01

    PV performance models are used to quantify the value of PV plants in a given location. They combine the performance characteristics of the system, the measured or predicted irradiance and weather at a site, and the system configuration and design into a prediction of the amount of energy that will be produced by a PV system. These predictions must be as accurate as possible in order for finance charges to be minimized. Higher accuracy equals lower project risk. The Increasing Prediction Accuracy project at Sandia focuses on quantifying and reducing uncertainties in PV system performance models.

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

    SciTech Connect (OSTI)

    Tippett, Michael K.

    2014-04-09

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

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

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

    Leadership Computing Facility 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 project is to model this important surface reaction which is poorly modeled by methods with static treatment of electron-electron interaction. Credit: William Parker, ALCF QMC Simulations DataBase for Predictive Theory and Modeling PI Name: David Ceperley PI Email: ceperley@illinois.ed

  4. SimTable helps firefighters model and predict fire direction

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

    for modeling lung cancer. In other news December, 1 2015 - Novel therapy for stomach cancer; grand opening of Manhattan Project National Historical Park; 2015 Northern New...

  5. Weather Photos - Hanford Site

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

    Hanford Meteorological Station Weather Photos Hanford Meteorological Station Photo Gallery Email Email Page | Print Print Page | Text Increase Font Size Decrease Font Size Hanford Meteorological Service Search Search Search Filter: Hanford Meteorological Service All Galleries 284 East Explosive Demolition Settlers B Reactor 100DX Groundwater Treatment Facility 100HX Groundwater Treatment Facility 200 West Groundwater Treatment Facility Construction 200 West Groundwater Treatment LEED Facility

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

    SciTech Connect (OSTI)

    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 adaptation 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.

  7. 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

  8. WEATHERIZATION PROGRAM NOTICE 16-XX EFFECTIVE DATE: SUBJECT: MULTIFAMILY WEATHERIZATION

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

    6-XX EFFECTIVE DATE: SUBJECT: MULTIFAMILY WEATHERIZATION PURPOSE: To provide Grantees with consolidated guidance on previously issued Weatherization Program Notices (WPNs) on weatherizing multifamily buildings in the Weatherization Assistance Program (WAP). This supersedes WPN 10-7 and WPN 11-9 SCOPE: The provisions of this guidance apply to Grantees applying for financial assistance under the Department of Energy (DOE) WAP. LEGAL AUTHORITY: Title IV, Energy Conservation and Production Act, as

  9. Weatherization Rules and Regulations Resources

    Broader source: Energy.gov [DOE]

    Federal regulations provide the framework for the Weatherization Assistance Program. These rules and regulations give state and local weatherization programs guidelines to provide the energy efficiency improvements to low-income dwellings.

  10. 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.

  11. Grandma's House (Weatherization) | Department of Energy

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

    Grandma's House (Weatherization) Grandma's House (Weatherization) Addthis When you weatherize a home it needs to work as a system. Learn more here

  12. Predictive Modeling of Terrestrial Radiation Exposure from Geologic Materials

    SciTech Connect (OSTI)

    Malchow, Russell L.; Haber, Daniel University of Nevada, Las Vegas; Burnley, Pamela; Marsac, Kara; Hausrath, Elisabeth; Adcock, Christopher

    2015-01-01

    Aerial gamma ray surveys are important for those working in nuclear security and industry for determining locations of both anthropogenic radiological sources and natural occurrences of radionuclides. During an aerial gamma ray survey, a low flying aircraft, such as a helicopter, flies in a linear pattern across the survey area while measuring the gamma emissions with a sodium iodide (NaI) detector. Currently, if a gamma ray survey is being flown in an area, the only way to correct for geologic sources of gamma rays is to have flown the area previously. This is prohibitively expensive and would require complete national coverage. This project’s goal is to model the geologic contribution to radiological backgrounds using published geochemical data, GIS software, remote sensing, calculations, and modeling software. K, U and Th are the three major gamma emitters in geologic material. U and Th are assumed to be in secular equilibrium with their daughter isotopes. If K, U, and Th abundance values are known for a given geologic unit the expected gamma ray exposure rate can be calculated using the Grasty equation or by modeling software. Monte Carlo N-Particle Transport software (MCNP), developed by Los Alamos National Laboratory, is modeling software designed to simulate particles and their interactions with matter. Using this software, models have been created that represent various lithologies. These simulations randomly generate gamma ray photons at energy levels expected from natural radiologic sources. The photons take a random path through the simulated geologic media and deposit their energy at the end of their track. A series of nested spheres have been created and filled with simulated atmosphere to record energy deposition. Energies deposited are binned in the same manner as the NaI detectors used during an aerial survey. These models are used in place of the simplistic Grasty equation as they take into account absorption properties of the lithology which the

  13. Prediction of turbulent buoyant flow using an RNG {kappa}-{epsilon} model

    SciTech Connect (OSTI)

    Gan, G.

    1998-02-06

    Buoyant flows occur in various engineering practices such as heating, ventilation, and air-conditioning of buildings. This phenomenon is particularly important in rooms with displacement ventilation, where supply air velocities are generally very low (< 0.2 m/s) so that the predominant indoor airflow is largely due to thermal buoyancy created by internal heat sources such as occupants and equipment. This type of ventilation system has been shown to be an effective means to remove excess heat and achieve good indoor air quality. Here, numerical predictions were carried out for turbulent natural convection in two tall air cavities. The standard and RNG {kappa}-{epsilon} turbulence models were used for the predictions. The predicted results were compared with experimental data from the literature, and good agreement between prediction and measurement was obtained. Improved prediction was achieved using the RNG {kappa}-{epsilon} model in comparison with the standard {kappa}-{epsilon} model. The principal parameters for the improvement were investigated.

  14. weather | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    weather NNSA & Nuclear Security Enterprise support nation's preparedness Scientists at NNSA facilities study climate and meteorology. Other sites are key players in weather preparedness. Today, on National Weatherperson Day, NNSA recognizes numerous contributions to the nation's climate and weather readiness in any situation. With emergency response as one of its core

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

    SciTech Connect (OSTI)

    Not Available

    1991-12-01

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

  16. Method for quantifying the prediction uncertainties associated with water quality models

    SciTech Connect (OSTI)

    Summers, J.K.; Wilson, H.T.; Kou, J.

    1993-01-01

    Many environmental regulatory agencies depend on models to organize, understand, and utilize the information for regulatory decision making. A general analytical protocol was developed to quantify prediction error associated with commonly used surface water quality models. Its application is demonstrated by comparing water quality models configured to represent different levels of spatial, temporal, and mechanistic complexity. This comparison can be accomplished by fitting the models to a benchmark data set. Once the models are successfully fitted to the benchmark data, the prediction errors associated with each application can be quantified using the Monte Carlo simulation techniques.

  17. Red Lake Weatherization Project

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

    REVIEW RED LAKE WEATHERIZATION PROJECT BERT VAN WERT ENERGY ACTIVITIES COORDINATOR Project Overview To develop the capacity to conduct energy audits Implement energy efficiency measures into Tribal homes Develop a Tribally administered Energy Efficiency Program and business PROJECT LOCATION Our project is located at Red Lake Housing Authority Red Lake Band of Chippewa Indians Red Lake , MN Red Lake Band of Chippewas Area overview Reservation (Diminished Lands) and Surroundings Red Lake Band of

  18. Modelling hepatitis C therapy—predicting effects of treatment

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

    Perelson, Alan S.; Guedj, Jeremie

    2015-06-30

    Mathematically modelling changes in HCV RNA levels measured in patients who receive antiviral therapy has yielded many insights into the pathogenesis and effects of treatment on the virus. By determining how rapidly HCV is cleared when viral replication is interrupted by a therapy, one can deduce how rapidly the virus is produced in patients before treatment. This knowledge, coupled with estimates of the HCV mutation rate, enables one to estimate the frequency with which drug resistant variants arise. Modelling HCV also permits the deduction of the effectiveness of an antiviral agent at blocking HCV replication from the magnitude of themore » initial viral decline. One can also estimate the lifespan of an HCV-infected cell from the slope of the subsequent viral decline and determine the duration of therapy needed to cure infection. The original understanding of HCV RNA decline under interferon-based therapies obtained by modelling needed to be revised in order to interpret the HCV RNA decline kinetics seen when using direct-acting antiviral agents (DAAs). In addition, there also exist unresolved issues involving understanding therapies with combinations of DAAs, such as the presence of detectable HCV RNA at the end of therapy in patients who nonetheless have a sustained virologic response.« less

  19. Maintenance personnel performance simulation (MAPPS): a model for predicting maintenance performance reliability in nuclear power plants

    SciTech Connect (OSTI)

    Knee, H.E.; Krois, P.A.; Haas, P.M.; Siegel, A.I.; Ryan, T.G.

    1983-01-01

    The NRC has developed a structured, quantitative, predictive methodology in the form of a computerized simulation model for assessing maintainer task performance. Objective of the overall program is to develop, validate, and disseminate a practical, useful, and acceptable methodology for the quantitative assessment of NPP maintenance personnel reliability. The program was organized into four phases: (1) scoping study, (2) model development, (3) model evaluation, and (4) model dissemination. The program is currently nearing completion of Phase 2 - Model Development.

  20. 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.

  1. Modeling predicts which counties could store more carbon in soil by growing

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

    bioenergy crops | Argonne National Laboratory Modeling predicts which counties could store more carbon in soil by growing bioenergy crops By Katie Elyce Jones * July 13, 2016 Tweet EmailPrint To help stakeholders in government and business make smart decisions about the best types of land and local climates for planting bioenergy crops, researchers at the U.S. Department of Energy's (DOE's) Argonne National Laboratory are using computational modeling to predict which counties could see

  2. 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.

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

    SciTech Connect (OSTI)

    Singh, Kunwar P.; Gupta, Shikha; Rai, Premanjali

    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 BrockDechertScheinkman 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

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

    SciTech Connect (OSTI)

    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.

  5. 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.

  6. Leveraging Resources for the Weatherization Innovation Pilot...

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

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

  7. 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.

  8. National Weatherization Assistance Program Impact Evaluation: Weatherization Staff Survey

    SciTech Connect (OSTI)

    Carroll, David; Berger, Jacqueline; Miller, Carolyn; Johnson, Daya Bill

    2015-02-01

    This report presents results from a national survey of a representative sample of local weatherization staff -- auditors, crew chiefs, crew members.

  9. 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.

  10. First Steps Toward Tribal Weatherization

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

    weatherization program Lac Courte Oreilles Ojibwe Community College Reserve 16-Plex Elderly complex Leslie Isham LCO Development LCO Housing Authority LCOOCC LCO K-12 The ...

  11. 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

  12. 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.

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

    SciTech Connect (OSTI)

    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 candidate 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.

  14. Development of a land ice core for the Model for Prediction Across Scales

    Office of Scientific and Technical Information (OSTI)

    (MPAS) (Conference) | SciTech Connect Development of a land ice core for the Model for Prediction Across Scales (MPAS) Citation Details In-Document Search Title: Development of a land ice core for the Model for Prediction Across Scales (MPAS) No abstract prepared. Authors: Hoffman, Matthew J [1] + Show Author Affiliations Los Alamos National Laboratory Publication Date: 2012-06-25 OSTI Identifier: 1044843 Report Number(s): LA-UR-12-22469 TRN: US201214%%525 DOE Contract Number: AC52-06NA25396

  15. Towards the Prediction of Decadal to Centennial Climate Processes in the Coupled Earth System Model

    SciTech Connect (OSTI)

    Liu, Zhengyu; Kutzbach, J.; Jacob, R.; Prentice, C.

    2011-12-05

    In this proposal, we have made major advances in the understanding of decadal and long term climate variability. (a) We performed a systematic study of multidecadal climate variability in FOAM-LPJ and CCSM-T31, and are starting exploring decadal variability in the IPCC AR4 models. (b) We develop several novel methods for the assessment of climate feedbacks in the observation. (c) We also developed a new initialization scheme DAI (Dynamical Analogue Initialization) for ensemble decadal prediction. (d) We also studied climate-vegetation feedback in the observation and models. (e) Finally, we started a pilot program using Ensemble Kalman Filter in CGCM for decadal climate prediction.

  16. 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.

  17. 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.

  18. 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.

  19. A comparison of simulation models for predicting soil water dynamics in bare and vegetated lysimeters

    SciTech Connect (OSTI)

    Link, S.O.; Kickert, R.N.; Fayer, M.J.; Gee, G.W.

    1993-06-01

    This report describes the results of simulation models used to predict soil water storage dynamics at the Field Lysimeter Test Facility (FLTF) weighing lysimeters. The objectives of this research is to develop the capability to predict soil water storage dynamics with plants in support of water infiltration control studies for the Hanford Permanent Isolation Barrier Development Program. It is important to gain confidence in one`s ability to simulate soil water dynamics over long time periods to assess the barrier`s ability to prevent drainage. Two models were compared for their ability to simulate soil water storage dynamics with and without plants in weighing lysimeters, the soil water infiltration and movement (SWIM) and the simulation of production and utilization of rangelands (SPUR-91) models. These models adequately simulated soil water storage dynamics for the weighing lysimeters. The range of root mean square error values for the two models was 7.0 to 19.8. This compares well with the range reported by Fayer et al. (1992) for the bare soil data sets of 8.1 to 22.1. Future research will test the predictive capability of these models for longer term lysimeter data sets and for historical data sets collected in various plant community types.

  20. 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.

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

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

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

  3. Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT

    SciTech Connect (OSTI)

    Depeursinge, Adrien; Yanagawa, Masahiro; Leung, Ann N.; Rubin, Daniel L.

    2015-04-15

    Purpose: To investigate the importance of presurgical computed tomography (CT) intensity and texture information from ground-glass opacities (GGO) and solid nodule components for the prediction of adenocarcinoma recurrence. Methods: For this study, 101 patients with surgically resected stage I adenocarcinoma were selected. During the follow-up period, 17 patients had disease recurrence with six associated cancer-related deaths. GGO and solid tumor components were delineated on presurgical CT scans by a radiologist. Computational texture models of GGO and solid regions were built using linear combinations of steerable Riesz wavelets learned with linear support vector machines (SVMs). Unlike other traditional texture attributes, the proposed texture models are designed to encode local image scales and directions that are specific to GGO and solid tissue. The responses of the locally steered models were used as texture attributes and compared to the responses of unaligned Riesz wavelets. The texture attributes were combined with CT intensities to predict tumor recurrence and patient hazard according to disease-free survival (DFS) time. Two families of predictive models were compared: LASSO and SVMs, and their survival counterparts: Cox-LASSO and survival SVMs. Results: The best-performing predictive model of patient hazard was associated with a concordance index (C-index) of 0.81 ± 0.02 and was based on the combination of the steered models and CT intensities with survival SVMs. The same feature group and the LASSO model yielded the highest area under the receiver operating characteristic curve (AUC) of 0.8 ± 0.01 for predicting tumor recurrence, although no statistically significant difference was found when compared to using intensity features solely. For all models, the performance was found to be significantly higher when image attributes were based on the solid components solely versus using the entire tumors (p < 3.08 × 10{sup −5}). Conclusions: This study

  4. Runtime System Library for Parallel Weather Modules

    Energy Science and Technology Software Center (OSTI)

    1997-07-22

    RSL is a Fortran-callable runtime library for use in implementing regular-grid weather forecast models, with nesting, on scalable distributed memory parallel computers. It provides high-level routines for finite-difference stencil communications and inter-domain exchange of data for nested forcing and feedback. RSL supports a unique point-wise domain-decomposition strategy to facilitate load-balancing.

  5. WEATHERIZATION ANNUAL FILE WORKSHEET | Department of Energy

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

    WEATHERIZATION ANNUAL FILE WORKSHEET WEATHERIZATION ANNUAL FILE WORKSHEET Form is designed to gather specific detail related to the expenditures of the Weatherization grant. WEATHERIZATION ANNUAL FILE WORKSHEET (134.96 KB) More Documents & Publications DOE F 540.3 WPN 06-3: Revised Weatherization Assistance Program Application Instructions and Forms WPN 04-4: Revised Weatherization Assistance Program Application Package and Reporting Format

  6. What is Weatherization | Department of Energy

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

    What is Weatherization What is Weatherization Weatherization as defined by the Weatherization Assistance Program (WAP) differs in many ways from what is commonly called "weatherizing your home." The latter involves low-cost improvements like adding weatherstripping to doors and windows to save energy. These measures made up the services WAP provided in its early years and are likely responsible for the program's name. Today, WAP's weatherization services consist of cost-effective

  7. WeatherMaker: Weather file conversion and evaluation

    SciTech Connect (OSTI)

    Balcomb, J.D.

    1999-07-01

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

  8. Monitoring Plan for Weatherization Assistance Program, State...

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

    WPN 16-4: Weatherization Assistance Program Monitoring Guidance WPN 12-5: Updated Weatherization Assistance Program Monitoring Guidance WAP Memorandum 010: Quality Management Plan ...

  9. Los Alamos Space Weather Summer School

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

    Mentors, Projects Lectures Papers, Reports Photos NSEC CSES Space Weather Summer School Los Alamos Space Weather Summer School June 6 - July 29, 2016 Contacts Director Misa ...

  10. Incorporating Weather Data into Energy Savings Calculations ...

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

    Incorporating Weather Data into Energy Savings Calculations Incorporating Weather Data into Energy Savings Calculations Better Buildings Residential Network Peer Exchange Call...

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

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

    Connecticut's Health Impact Study Rapidly Increasing Weatherization Efforts Connecticut's Health Impact Study Rapidly Increasing Weatherization Efforts June 18, 2014 - 10:49am ...

  12. Weatherization and Intergovernmental Programs Office FY 2015...

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

    5 Budget At-A-Glance Weatherization and Intergovernmental Programs Office FY 2015 Budget At-A-Glance Weatherization and Intergovernmental Programs (WIP) is part of EERE's balanced ...

  13. Weatherization and Intergovernmental Programs Office FY 2016...

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

    KB) More Documents & Publications Weatherization and Intergovernmental Programs Office FY 2017 Budget At-A-Glance Weatherization and Intergovernmental Programs Office FY 2015

  14. Weather Services International Corporation WSI | Open Energy...

    Open Energy Info (EERE)

    Weather Services International Corporation WSI Jump to: navigation, search Name: Weather Services International Corporation (WSI) Place: Andover, Massachusetts Zip: 1810 Product:...

  15. HUD Multifamily Property Listings Eligible for Weatherization...

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

    HUD Multifamily Property Listings Eligible for Weatherization Assistance HUD Multifamily Property Listings Eligible for Weatherization Assistance February 23, 2016 - 4:29pm Addthis ...

  16. Incorporating Weather Data into Energy Savings Calculations ...

    Energy Savers [EERE]

    Weather Data into Energy Savings Calculations Incorporating Weather Data into Energy Savings Calculations Better Buildings Residential Network Peer Exchange Call Series: ...

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

    SciTech Connect (OSTI)

    Prez-Andjar, Anglica [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.

  18. Winter Weather Outlook

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

    2. Use of a human face as the modeled target. 3. Incorporation of modern heat transfer theory to model heat loss from the body and its surroundings on cold, windy days. 4. A...

  19. Weatherization Technical and Management Resources

    Broader source: Energy.gov [DOE]

    The technical and management resources serve as a toolkit for weatherization professionals to access the key program processes, and tools and materials that will assist in the implementation of state and local programs.

  20. 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.

    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.

  1. 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

  2. Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

    SciTech Connect (OSTI)

    Xavier, MA; Trimboli, MS

    2015-07-01

    This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.

  3. An Elastic-Plastic and Strength Prediction Model for Injection-Molded Long-Fiber Thermoplastics

    SciTech Connect (OSTI)

    Nguyen, Ba Nghiep; Kunc, Vlastimil; Phelps, Jay; Tucker III, Charles L.; Bapanapalli, Satish K.

    2008-09-01

    This paper applies a recently developed model to predict the elastic-plastic stress/strain response and strength of injection-molded long-fiber thermoplastics (LFTs). The model combines a micro-macro constitutive modeling approach with experimental characterization and modeling of the composite microstructure to determine the composite stress/strain response and strength. Specifically, it accounts for elastic fibers embedded in a thermoplastic resin that exhibits the elastic-plastic behavior obeying the Ramberg-Osgood relation and J-2 deformation theory of plasticity. It also accounts for fiber length, orientation and volume fraction distributions in the composite formed by the injection-molding process. Injection-molded-long-glass-fiber/polypropylene (PP) specimens were prepared for mechanical characterization and testing. Fiber length, orientation, and volume fraction distributions were then measured at some selected locations for use in the computation. Fiber orientations in these specimens were also predicted using an anisotropic rotary diffusion model developed for LFTs. The stress-strain response of the as-formed composite was computed by an incremental procedure that uses the Eshelbys equivalent inclusion method, the Mori-Tanaka assumption and a fiber orientation averaging technique. The model has been validated against the experimental stress-strain results obtained for these long-glass-fiber/PP specimens.

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

    SciTech Connect (OSTI)

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

    2012-01-01

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

  5. A comparison of general circulation model predictions to sand drift and dune orientations

    SciTech Connect (OSTI)

    Blumberg, D.G.; Greeley, R.

    1996-12-01

    The growing concern over climate change and decertification stresses the importance of aeolian process prediction. In this paper the use of a general circulation model to predict current aeolian features is examined. A GCM developed at NASA/Goddard Space Flight Center was used in conjunction with White`s aeolian sand flux model to produce a global potential aeolian transport map. Surface wind shear stress predictions were used from the output of a GCM simulation that was performed as part of the Atmospheric Model Intercomparison Project on 1979 climate conditions. The spatial resolution of this study (as driven by the GCM) is 4{degrees} X 5{degrees}; instantaneous 6-hourly wind stress data were saved by the GCM and used in this report. A global map showing potential sand transport was compared to drift potential directions as inferred from Landsat images from the 1980s for several sand seas and a coastal dune field. Generally, results show a good correlation between the simulated sand drift direction and the drift direction inferred for dune forms. Discrepancies between the drift potential and the drift inferred from images were found in the North American deserts and the Arabian peninsula. An attempt to predict the type of dune that would be formed in specific regions was not successful. The model could probably be further improved by incorporating soil moisture, surface roughness, and vegetation information for a better assessment of sand threshold conditions. The correlation may permit use of a GCM to analyze {open_quotes}fossil{close_quotes} dunes or to forecast aeolian processes. 48 refs., 8 figs.

  6. Results from baseline tests of the SPRE I and comparison with code model predictions

    SciTech Connect (OSTI)

    Cairelli, J.E.; Geng, S.M.; Skupinski, R.C.

    1994-09-01

    The Space Power Research Engine (SPRE), a free-piston Stirling engine with linear alternator, is being tested at the NASA Lewis Research Center as part of the Civil Space Technology Initiative (CSTI) as a candidate for high capacity space power. This paper presents results of base-line engine tests at design and off-design operating conditions. The test results are compared with code model predictions.

  7. Predictive Theory and Modeling| U.S. DOE Office of Science (SC)

    Office of Science (SC) Website

    Predictive Theory and Modeling Basic Energy Sciences (BES) BES Home About Research Facilities Science Highlights Benefits of BES Funding Opportunities Closed Funding Opportunity Announcements (FOAs) Closed Lab Announcements Award Search / Public Abstracts Additional Requirements and Guidance for Digital Data Management Peer Review Policies EFRCs FOA Applications from Universities and Other Research Institutions Construction Review EPSCoR DOE Office of Science Graduate Fellowship (DOE SCGF)

  8. Controlling Bimetallic Nanostructures by the Microemulsion Method with Subnanometer Resolution Using a Prediction Model

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

    Buceta, D.; Tojo, C.; Vukmirovic, M.; Deepak, F. L.; Arturo Lopez-Quintela, M.

    2015-07-14

    We present a theoretical model to predict the atomic structure of Au/Pt nanoparticles synthesized in microemulsions. Excellent concordance with the experimental results shows that the structure of the nanoparticles can be controlled at sub-nanometer resolution simply by changing the reactants concentration. The results of this study not only offer a better understanding of the complex mechanisms governing reactions in microemulsions, but open up a simple new way to synthesize bimetallic nanoparticles with ad-hoc controlled nanostructures.

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

    SciTech Connect (OSTI)

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

    1983-04-01

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

  10. Low-Income Weatherization: The Human Dimension

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  11. Weatherization Assistance Program National Evaluation | Department of

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

    Energy Weatherization Assistance Program National Evaluation Weatherization Assistance Program National Evaluation The Weatherization and Intergovernmental Programs Office authorized the Oak Ridge National Laboratory to implement the national evaluation of the Weatherization Assistance Program. This evaluation addressed energy and cost savings, non-energy benefits, program cost-effectiveness, and program operations for program year 2008, called the Retrospective Evaluation, and for program

  12. Weatherization and Intergovernmental Program Success Stories

    Broader source: Energy.gov [DOE]

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

  13. Weatherization Assistance Program: Spurring Innovation, Increasing Home

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

    Energy Efficiency | Department of Energy Weatherization Assistance Program: Spurring Innovation, Increasing Home Energy Efficiency Weatherization Assistance Program: Spurring Innovation, Increasing Home Energy Efficiency October 31, 2013 - 5:01pm Addthis The Intermountain Weatherization Training Center in Clearfield, Utah. Weatherization Training Centers throughout the nation teach workers valuable skills needed to improve energy efficiency of homes. | Photo courtesy of Intermountain

  14. Nevada Weatherizes Large-Scale Complex

    Broader source: Energy.gov [DOE]

    Increased energy efficiency is translating into increased productivity for one Nevada weatherization organization.

  15. Arizona Foundation Expands Weatherization Training Center

    Broader source: Energy.gov [DOE]

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

  16. Weatherization Assistance Program National Evaluation | Department of

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

    Energy Weatherization Assistance Program National Evaluation Weatherization Assistance Program National Evaluation The Weatherization and Intergovernmental Programs Office authorized the Oak Ridge National Laboratory to implement the national evaluation of the Weatherization Assistance Program. This evaluation addressed energy and cost savings, non-energy benefits, program cost-effectiveness, and program operations for program year 2008, called the Retrospective Evaluation, and for program

  17. Explore Careers in Weatherization | Department of Energy

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

    Weatherization Explore Careers in Weatherization EERE's Weatherization and Intergovernmental Program provides grants, technical assistance, and information tools to the state energy offices of states, local governments, community action agencies, utility companies, tribal governments, and overseas U.S. territories. These programs aim to reduce market barriers to the adoption of energy efficiency and renewable energy technologies while also reducing petroleum consumption. EERE's Weatherization

  18. Predicting individual action switching in covert and continuous interactive tasks using the fluid events model

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

    Radvansky, Gabriel A.; D’Mello, Sidney K.; Abbott, Robert G.; Bixler, Robert E.

    2016-01-27

    The Fluid Events Model is aimed at predicting changes in the actions people take on a moment-by-moment basis. In contrast with other research on action selection, this work does not investigate why some course of action was selected, but rather the likelihood of discontinuing the current course of action and selecting another in the near future. This is done using both task-based and experience-based factors. Prior work evaluated this model in the context of trial-by-trial, independent, interactive events, such as choosing how to copy a figure of a line drawing. In this paper, we extend this model to more covertmore » event experiences, such as reading narratives, as well as to continuous interactive events, such as playing a video game. To this end, the model was applied to existing data sets of reading time and event segmentation for written and picture stories. It was also applied to existing data sets of performance in a strategy board game, an aerial combat game, and a first person shooter game in which a participant’s current state was dependent on prior events. The results revealed that the model predicted behavior changes well, taking into account both the theoretically defined structure of the described events, as well as a person’s prior experience. Hence, theories of event cognition can benefit from efforts that take into account not only how events in the world are structured, but also how people experience those events.« less

  19. Stem thrust prediction model for W-K-M double wedge parallel expanding gate valves

    SciTech Connect (OSTI)

    Eldiwany, B.; Alvarez, P.D.; Wolfe, K.

    1996-12-01

    An analytical model for determining the required valve stem thrust during opening and closing strokes of W-K-M parallel expanding gate valves was developed as part of the EPRI Motor-Operated Valve Performance Prediction Methodology (EPRI MOV PPM) Program. The model was validated against measured stem thrust data obtained from in-situ testing of three W-K-M valves. Model predictions show favorable, bounding agreement with the measured data for valves with Stellite 6 hardfacing on the disks and seat rings for water flow in the preferred flow direction (gate downstream). The maximum required thrust to open and to close the valve (excluding wedging and unwedging forces) occurs at a slightly open position and not at the fully closed position. In the nonpreferred flow direction, the model shows that premature wedging can occur during {Delta}P closure strokes even when the coefficients of friction at different sliding surfaces are within the typical range. This paper summarizes the model description and comparison against test data.

  20. In-Service Design & Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation

    SciTech Connect (OSTI)

    G. R. Odette; G. E. Lucas

    2005-11-15

    This final report on "In-Service Design & Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation" (DE-FG03-01ER54632) consists of a series of summaries of work that has been published, or presented at meetings, or both. It briefly describes results on the following topics: 1) A Transport and Fate Model for Helium and Helium Management; 2) Atomistic Studies of Point Defect Energetics, Dynamics and Interactions; 3) Multiscale Modeling of Fracture consisting of: 3a) A Micromechanical Model of the Master Curve (MC) Universal Fracture Toughness-Temperature Curve Relation, KJc(T - To), 3b) An Embrittlement DTo Prediction Model for the Irradiation Hardening Dominated Regime, 3c) Non-hardening Irradiation Assisted Thermal and Helium Embrittlement of 8Cr Tempered Martensitic Steels: Compilation and Analysis of Existing Data, 3d) A Model for the KJc(T) of a High Strength NFA MA957, 3e) Cracked Body Size and Geometry Effects of Measured and Effective Fracture Toughness-Model Based MC and To Evaluations of F82H and Eurofer 97, 3-f) Size and Geometry Effects on the Effective Toughness of Cracked Fusion Structures; 4) Modeling the Multiscale Mechanics of Flow Localization-Ductility Loss in Irradiation Damaged BCC Alloys; and 5) A Universal Relation Between Indentation Hardness and True Stress-Strain Constitutive Behavior. Further details can be found in the cited references or presentations that generally can be accessed on the internet, or provided upon request to the authors. Finally, it is noted that this effort was integrated with our base program in fusion materials, also funded by the DOE OFES.

  1. WEATHERIZATION PROGRAM NOTICE 16-XX EFFECTIVE DATE:

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

    WEATHERIZATION PROGRAM NOTICE 16-XX EFFECTIVE DATE: SUBJECT: WEATHERIZATION OF RENTAL UNITS - Applicable to single family and multifamily dwellings PURPOSE: To provide Grantees with updated guidance on weatherizing rental units in the Weatherization Assistance Program (WAP). DOE has answered specific questions from Grantees related to the weatherization of rental units, whether single family building or multifamily dwellings, over a number of years. However, the responses to these questions have

  2. Response to Weatherization Questions | Department of Energy

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

    Response to Weatherization Questions Response to Weatherization Questions August 30, 2010 - 4:53pm Addthis Andy Oare Andy Oare Former New Media Strategist, Office of Public Affairs Last week as part of Vice President Biden's announcement of 200,000 homes weatherized under the Recovery act, we asked you to send us your questions and comments about the weatherization process. Today, we're following up with answers experts from the Department's Weatherization and Intergovernmental Program: 1) From

  3. Weatherization Program Guidance | Department of Energy

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

    Program Guidance Weatherization Program Guidance The U.S. Department of Energy's (DOE's) Weatherization Assistance Program (WAP) is governed by various federal regulations designed to help manage and account for the resources provided by DOE. Each year, Congress passes a Weatherization Assistance Program Appropriation. Find active and archived weatherization program notices and memorandums in the table below, which establish the framework for administering WAP funds. Type Topic Weatherization

  4. Connecticut's Health Impact Study Rapidly Increasing Weatherization

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

    Efforts | Department of Energy Connecticut's Health Impact Study Rapidly Increasing Weatherization Efforts Connecticut's Health Impact Study Rapidly Increasing Weatherization Efforts June 18, 2014 - 10:49am Addthis Weatherization workers are trained in the house as a system approach. The Energy Department's Weatherization Assistance Program funded technical assistance as part of Connecticut's Health Impact Assessment project. | Photo courtesy of Weatherization Assistance Program Technical

  5. A Screening Model to Predict Microalgae Biomass Growth in Photobioreactors and Raceway Ponds

    SciTech Connect (OSTI)

    Huesemann, Michael H.; Van Wagenen, Jonathan M.; Miller, Tyler W.; Chavis, Aaron R.; Hobbs, Watts B.; Crowe, Braden J.

    2013-06-01

    A microalgae biomass growth model was developed for screening novel strains for their potential to exhibit high biomass productivities under nutrient-replete conditions in photobioreactors or outdoor ponds. Growth is modeled by first estimating the light attenuation by biomass according to Beer-Lamberts law, and then calculating the specific growth rate in discretized culture volume slices that receive declining light intensities due to attenuation. The model requires only two physical and two species-specific biological input parameters, all of which are relatively easy to determine: incident light intensity, culture depth, as well as the biomass light absorption coefficient and the specific growth rate as a function of light intensity. Roux bottle culture experiments were performed with Nannochloropsis salina at constant temperature (23 C) at six different incident light intensities (5, 10, 25, 50, 100, 250, and 850 ?mol/m2? sec) to determine both the specific growth rate under non-shading conditions and the biomass light absorption coefficient as a function of light intensity. The model was successful in predicting the biomass growth rate in these Roux bottle cultures during the light-limited linear phase at different incident light intensities. Model predictions were moderately sensitive to minor variations in the values of input parameters. The model was also successful in predicting the growth performance of Chlorella sp. cultured in LED-lighted 800 L raceway ponds operated at constant temperature (30 C) and constant light intensity (1650 ?mol/m2? sec). Measurements of oxygen concentrations as a function of time demonstrated that following exposure to darkness, it takes at least 5 seconds for cells to initiate dark respiration. As a result, biomass loss due to dark respiration in the aphotic zone of a culture is unlikely to occur in highly mixed small-scale photobioreactors where cells move rapidly in and out of the light. By contrast, as supported also by

  6. Lumped Parameter Modeling as a Predictive Tool for a Battery Status Monitor

    SciTech Connect (OSTI)

    Jon P. Christophersen; Chester G. Motloch; Chinh D. Ho; John L. Morrison; Ronald C. Fenton; Vincent S. Battaglia; Tien Q. Duong

    2003-10-01

    The Advanced Technology Development Program is currently evaluating the performance of the second generation of lithium-ion cells (i.e., Gen 2 cells). Both the Gen 2 Baseline and Variant C cells are tested in accordance with the cell-specific test plan, and are removed at roughly equal power fade increments and sent for destructive diagnostic analysis. The diagnostic laboratories did not need all test cells for analysis, and returned five spare cells to the Idaho National Engineering and Environmental Laboratory (INEEL). INEEL used these cells for special pulse testing at various duty cycles, amplitudes, and durations to investigate the usefulness of the lumped parameter model (LPM) as a predictive tool in a battery status monitor (BSM). The LPM is a simplified linear model that accurately predicts the voltage response during certain pulse conditions. A database of parameter trends should enable dynamic predictions of state-of-charge and state-of-health conditions during in-vehicle pulsing. This information could be used by the BSM to provide accurate information to the vehicle control system.

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

    SciTech Connect (OSTI)

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

    2014-04-23

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

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

    SciTech Connect (OSTI)

    S.P. Rupp

    2005-10-01

    SAVANNA included a land cover map, long-term weather data, soil maps, and a digital elevation model. Parameterization and calibration were conducted using field plots. Model predictions of herbaceous biomass production and weather were consistent with available data and spatial interpolations of snow were considered reasonable for this study. Dynamic outputs generated by SAVANNA were integrated with static variables, movement rules, and parameters developed for the individual-based model through the application of a habitat suitability index. Model validation indicated reasonable model fit when compared to an independent test set. The finished model was applied to 2 realistic management scenarios for the Jemez Mountains and management implications were discussed. Ongoing validation of the individual-based model presented in this dissertation provides an adaptive management tool that integrates interdisciplinary experience and scientific information, which allows users to make predictions about the impact of alternative management policies.

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

    SciTech Connect (OSTI)

    Neuhauser, K.

    2012-06-01

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

  10. EAC Meeting Cancelled Due to Weather | Department of Energy

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

    Cancelled Due to Weather EAC Meeting Cancelled Due to Weather March 5, 2013 - 3:06pm Addthis This week's Electricity Advisory Committee (EAC) meeting has been cancelled due to a strong winter storm which is predicted to impact the Washington DC area on Wednesday. Originally scheduled to be held March 6 and March 7 in Arlington, Virginia, the EAC meeting may possibly be rescheduled for a later date. If the meeting is rescheduled, details will be posted online and will be published in a new