National Library of Energy BETA

Sample records for fuels model capital

  1. Electroweak stars: how nature may capitalize on the standard model's ultimate fuel

    E-Print Network [OSTI]

    De-Chang Dai; Arthur Lue; Glenn Starkman; Dejan Stojkovic

    2011-01-19

    We study the possible existence of an electroweak star - a compact stellar-mass object whose central core temperature is higher than the electroweak symmetry restoration temperature. We found a solution to the Tolman-Oppenheimer-Volkoff equations describing such an object. The parameters of such a star are not substantially different from a neutron star - its mass is around 1.3 Solar masses while its radius is around 8 km. What is different is the existence of a small electroweak core. The source of energy in the core that can at least temporarily balance gravity are standard-model non-perturbative baryon number (B) and lepton number (L) violating processes that allow the chemical potential of $B+L$ to relax to zero. The energy released at the core is enormous, but gravitational redshift and the enhanced neutrino interaction cross section at these energies make the energy release rate moderate at the surface of the star. The lifetime of this new quasi-equilibrium can be more than ten million years. This is long enough to represent a new stage in the evolution of a star if stellar evolution can take it there.

  2. CAPITAL FOR ENERGY AND INTER-FUEL ELASTICITIES OF SUBSTITUTION

    E-Print Network [OSTI]

    CAPITAL FOR ENERGY AND INTER- FUEL ELASTICITIES OF SUBSTITUTION FROM A TECHNOLOGY SIMULATION MODEL: Christopher G.F. Bataille Energy Research Group School of Resource and Environmental Management Simon Fraser to make a cost comparison of potential greenhouse gas (GHG) abatement policies. Our primary tools

  3. Fuel costs and the retirement of capital goods

    E-Print Network [OSTI]

    Goolsbee, Austan Dean

    1993-01-01

    This paper explores the effect that energy prices and market conditions have on the retirement rates of capital goods using new micro data on aircraft lifetimes and fuel costs. The oil shocks of the 1970s made fuel intensive ...

  4. The Capital Asset Pricing Model: Theory and Evidence

    E-Print Network [OSTI]

    Thomas, Anne

    is still widely used in applications, such as estimating the cost of capital for firms and evaluatingThe Capital Asset Pricing Model: Theory and Evidence Eugene F. Fama and Kenneth R. French T he capital asset pricing model (CAPM) of William Sharpe (1964) and John Lintner (1965) marks the birth

  5. Capital requirements and fuel-cycle energy and emissions impacts of potential PNGV fuels.

    SciTech Connect (OSTI)

    Johnson, L.; Mintz, M.; Singh, M.; Stork, K.; Vyas, A.; Wang, M.

    1999-03-11

    Our study reveals that supplying gasoline-equivalent demand for the low-market-share scenario requires a capital investment of less than $40 billion for all fuels except H{sub 2}, which will require a total cumulative investment of $150 billion. By contrast, cumulative capital investments under the high-market-share scenario are $50 billion for LNG, $90 billion for ethanol, $100 billion for methanol, $160 billion for CNG and DME, and $560 billion for H{sub 2}. Although these substantial capital requirements are spread over many years, their magnitude could pose a challenge to the widespread introduction of 3X vehicles. Fossil fuel use by US light-duty vehicles declines significantly with introduction of 3X vehicles because of fuel-efficiency improvements for 3X vehicles and because of fuel substitution (which applies to the nonpetroleum-fueled alternatives). Petroleum use for light-duty vehicles in 2030 is reduced by as much as 45% relative to the reference scenario. GHG emissions follow a similar pattern. Total GHG emissions decline by 25-30% with most of the propulsion system/fuel alternatives. For those using renewable fuels (i.e., ethanol and H{sub 2} from solar energy), GHG emissions drop by 33% (H{sub 2}) and 45% (ethanol). Among urban air pollutants, urban NOX emissions decline slightly for 3X vehicles using CIDI and SIDI engines and drop substantially for fuel-cell vehicles. Urban CO emissions decline for CIDI and FCV alternatives, while VOC emissions drop significantly for all alternatives except RFG-, methanol-, and ethanol-fueled SIDI engines. With the exception of CIDI engines fueled by RFD, FT50, or B20 (which increase urban PM{sub 10} emissions by over 30%), all propulsion system/fuel alternatives reduce urban PM{sub 10} emissions. Reductions are approximately 15-20% for fuel cells and for methanol-, ethanol-, CNG-, or LPG-fueled SIDI engines. Table 3 qualitatively summarizes impacts of the 13 alternatives on capital requirements and on energy use and emissions relative to the reference scenario. The table clearly shows the trade-off between costs and benefits. For example, while H{sub 2} FCVs have the greatest incremental capital needs, they offer the largest energy and emissions benefits. On the basis of the cost and benefit changes shown, methanol and gasoline FCVs appear to have particularly promising benefits-to-costs ratios.

  6. Assessment of capital requirements for alternative fuels infrastructure under the PNGV program

    SciTech Connect (OSTI)

    Stork, K.; Singh, M.; Wang, M.; Vyas, A.

    1998-12-31

    This paper presents an assessment of the capital requirements of using six different fuels in the vehicles with tripled fuel economy (3X vehicles) that the Partnership for a new Generation of Vehicles is currently investigating. The six fuels include two petroleum-based fuels (reformulated gasoline and low-sulfur diesel) and four alternative fuels (methanol, ethanol, dimethyl ether, and hydrogen). This study develops estimates of cumulative capital needs for establishing fuels production and distribution infrastructure to accommodate 3X vehicle fuel needs. Two levels of fuel volume-70,000 barrels per day and 1.6 million barrels per day-were established for meeting 3X-vehicle fuel demand. As expected, infrastructure capital needs for the high fuel demand level are much higher than for the low fuel demand level. Between fuel production infrastructure and distribution infrastructure, capital needs for the former far exceed those for the latter. Among the four alternative fuels, hydrogen bears the largest capital needs for production and distribution infrastructure.

  7. Assessment of PNGV fuels infrastructure. Phase 1 report: Additional capital needs and fuel-cycle energy and emissions impacts

    SciTech Connect (OSTI)

    Wang, M.; Stork, K.; Vyas, A.; Mintz, M.; Singh, M.; Johnson, L.

    1997-01-01

    This report presents the methodologies and results of Argonne`s assessment of additional capital needs and the fuel-cycle energy and emissions impacts of using six different fuels in the vehicles with tripled fuel economy (3X vehicles) that the Partnership for a New Generation of Vehicles is currently investigating. The six fuels included in this study are reformulated gasoline, low-sulfur diesel, methanol, ethanol, dimethyl ether, and hydrogen. Reformulated gasoline, methanol, and ethanol are assumed to be burned in spark-ignition, direct-injection engines. Diesel and dimethyl ether are assumed to be burned in compression-ignition, direct-injection engines. Hydrogen and methanol are assumed to be used in fuel-cell vehicles. The authors have analyzed fuels infrastructure impacts under a 3X vehicle low market share scenario and a high market share scenario. The assessment shows that if 3X vehicles are mass-introduced, a considerable amount of capital investment will be needed to build new fuel production plants and to establish distribution infrastructure for methanol, ethanol, dimethyl ether, and hydrogen. Capital needs for production facilities will far exceed those for distribution infrastructure. Among the four fuels, hydrogen will bear the largest capital needs. The fuel efficiency gain by 3X vehicles translates directly into reductions in total energy demand, fossil energy demand, and CO{sub 2} emissions. The combination of fuel substitution and fuel efficiency results in substantial petroleum displacement and large reductions in emissions of nitrogen oxide, carbon monoxide, volatile organic compounds, sulfur oxide, and particulate matter of size smaller than 10 microns.

  8. Integrated models of capital adequacy Why banks are undercapitalised

    E-Print Network [OSTI]

    McNeil, Alexander J.

    applied to the design of financial regulation...the crisis which began in the US sub-prime mortgage market sheet of a representative Eurobank using an economic scenario generation model calibrated to conditions. The introduction of integrated economic-scenario-based models in future can improve capital adequacy, enhance

  9. DYNAMIC MODELING FUEL PROCESSORS

    E-Print Network [OSTI]

    Mease, Kenneth D.

    turbine module (compressor and turbine sub-modules) Catalytic oxidizer Combustor module Heat exchanger, PEM, Gas Turbine General Model Assumptions · 1D process flow · Well-stirred within nodal volume · Slow reactants #12;Steam Reformation ­ Occurs in Reformer and Fuel Cells Methane reformation reaction Water Gas

  10. A credit risk model for agricultural loan portfolios under the new Basel Capital Accord 

    E-Print Network [OSTI]

    Kim, Juno

    2005-08-29

    The New Basel Capital Accord (Basel II) provides added emphasis to the development of portfolio credit risk models. An important regulatory change in Basel II is the differentiated treatment in measuring capital requirements for the corporate...

  11. Fuel Model | NISAC

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverse (Journal Article)Forthcoming UpgradesArea: PADD 1 toCells Fuel CellsFuel

  12. Discrete Event Modeling of Algae Cultivation and Harvesting at Commercial Scale: Capital Costs, Operating Costs, and System Bottlenecks

    SciTech Connect (OSTI)

    Lacey, Ph.D, P.E., Ronald E.

    2012-07-16

    Discrete Event Modeling of Algae Cultivation and Harvesting at Commercial Scale: Capital Costs, Operating Costs, and System Bottlenecks

  13. Modeling the Nuclear Fuel Cycle

    SciTech Connect (OSTI)

    Jacob J. Jacobson; A. M. Yacout; G. E. Matthern; S. J. Piet; A. Moisseytsev

    2005-07-01

    The Advanced Fuel Cycle Initiative is developing a system dynamics model as part of their broad systems analysis of future nuclear energy in the United States. The model will be used to analyze and compare various proposed technology deployment scenarios. The model will also give a better understanding of the linkages between the various components of the nuclear fuel cycle that includes uranium resources, reactor number and mix, nuclear fuel type and waste management. Each of these components is tightly connected to the nuclear fuel cycle but usually analyzed in isolation of the other parts. This model will attempt to bridge these components into a single model for analysis. This work is part of a multi-national laboratory effort between Argonne National Laboratory, Idaho National Laboratory and United States Department of Energy. This paper summarizes the basics of the system dynamics model and looks at some results from the model.

  14. High Burnup Fuel Behavior Modeling

    SciTech Connect (OSTI)

    Jahingir, M.; Rand, R.; Stachowski, R.; Miles, B.; Kusagaya, K.

    2007-07-01

    This paper discusses the development and qualification of the PRIME03 code to address high burnup mechanisms and to improve uranium utilization in current and new reactor designs. Materials properties and behavioral models have been updated from previous thermal-mechanical codes to reflect the effects of burnup on fuel pellet thermal conductivity, Zircaloy creep, fuel pellet relocation, and fission gas release. These new models are based on results of in-pool and post irradiation examination (PIE) of commercial boiling water reactor (BWR) fuel rods at high burnup and results from international experimental programs. The new models incorporated into PRIME03 also address specific high burnup effects associated with formation of pellet rim porosity at high exposure. The PRIME03 code is qualified by comparison of predicted and measured fuel performance parameters for a large number of high, low, and moderate burnup test and commercial reactor rod. The extensive experimental qualification of the PRIME03 prediction capabilities confirms that it is a reliable best-estimate predictor of fuel rod thermal-mechanical performance over a wide range of design and operating conditions. (authors)

  15. Spent nuclear fuel reprocessing modeling

    SciTech Connect (OSTI)

    Tretyakova, S.; Shmidt, O.; Podymova, T.; Shadrin, A.; Tkachenko, V. [Bochvar Institute, 5 Rogova str., Moscow 123098 (Russian Federation); Makeyeva, I.; Tkachenko, V.; Verbitskaya, O.; Schultz, O.; Peshkichev, I. [Russian Federal Nuclear Center - VNIITF E.I. Zababakhin, p.o.box 245, Snezhinsk, 456770 (Russian Federation)

    2013-07-01

    The long-term wide development of nuclear power requires new approaches towards the realization of nuclear fuel cycle, namely, closed nuclear fuel cycle (CNFC) with respect to fission materials. Plant nuclear fuel cycle (PNFC), which is in fact the reprocessing of spent nuclear fuel unloaded from the reactor and the production of new nuclear fuel (NF) at the same place together with reactor plant, can be one variant of CNFC. Developing and projecting of PNFC is a complicated high-technology innovative process that requires modern information support. One of the components of this information support is developed by the authors. This component is the programme conducting calculations for various variants of process flow sheets for reprocessing SNF and production of NF. Central in this programme is the blocks library, where the blocks contain mathematical description of separate processes and operations. The calculating programme itself has such a structure that one can configure the complex of blocks and correlations between blocks, appropriate for any given flow sheet. For the ready sequence of operations balance calculations are made of all flows, i.e. expenses, element and substance makeup, heat emission and radiation rate are determined. The programme is open and the block library can be updated. This means that more complicated and detailed models of technological processes will be added to the library basing on the results of testing processes using real equipment, in test operating mode. The development of the model for the realization of technical-economic analysis of various variants of technologic PNFC schemes and the organization of 'operator's advisor' is expected. (authors)

  16. Where might I find simplified Data on Capital, O&M, and fuel costs? |

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Information Serbia-EnhancingEtGeorgia: EnergyMaryland: EnergyWexfordSouth BrowardTexas:OpenEI

  17. Alternative Liquid Fuels Simulation Model (AltSim).

    SciTech Connect (OSTI)

    Baker, Arnold Barry; Williams, Ryan (Hobart and William Smith Colleges, Geneva, NY); Drennen, Thomas E.; Klotz, Richard (Hobart and William Smith Colleges, Geneva, NY)

    2007-10-01

    The Alternative Liquid Fuels Simulation Model (AltSim) is a high-level dynamic simulation model which calculates and compares the production costs, carbon dioxide emissions, and energy balances of several alternative liquid transportation fuels. These fuels include: corn ethanol, cellulosic ethanol, biodiesel, and diesels derived from natural gas (gas to liquid, or GTL) and coal (coal to liquid, or CTL). AltSim allows for comprehensive sensitivity analyses on capital costs, operation and maintenance costs, renewable and fossil fuel feedstock costs, feedstock conversion efficiency, financial assumptions, tax credits, CO{sub 2} taxes, and plant capacity factor. This paper summarizes the preliminary results from the model. For the base cases, CTL and cellulosic ethanol are the least cost fuel options, at $1.60 and $1.71 per gallon, respectively. Base case assumptions do not include tax or other credits. This compares to a $2.35/gallon production cost of gasoline at September, 2007 crude oil prices ($80.57/barrel). On an energy content basis, the CTL is the low cost alternative, at $12.90/MMBtu, compared to $22.47/MMBtu for cellulosic ethanol. In terms of carbon dioxide emissions, a typical vehicle fueled with cellulosic ethanol will release 0.48 tons CO{sub 2} per year, compared to 13.23 tons per year for coal to liquid.

  18. Fuel Cell Power (FCPower) Model

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:Financing Tool Fits the Bill Financing Tool Fits theSunShot Prize: Race

  19. Vehicle Technologies Office Merit Review 2014: Alternative Fueling Diversity in the Energy Capital of the World

    Broader source: Energy.gov [DOE]

    Presentation given by City of Houston-Galveston Council at 2014 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Office Annual Merit Review and Peer Evaluation Meeting about alternative...

  20. Full-fuel-cycle modeling for alternative transportation fuels

    SciTech Connect (OSTI)

    Bell, S.R.; Gupta, M. [Univ. of Alabama, Tuscaloosa, AL (United States); Greening, L.A. [Lawrence Berkeley National Lab., CA (United States). Energy and Environment Div.

    1995-12-01

    Utilization of alternative fuels in the transportation sector has been identified as a potential method for mitigation of petroleum-based energy dependence and pollutant emissions from mobile sources. Traditionally, vehicle tailpipe emissions have served as sole data when evaluating environmental impact. However, considerable differences in extraction and processing requirements for alternative fuels makes evident the need to consider the complete fuel production and use cycle for each fuel scenario. The work presented here provides a case study applied to the southeastern region of the US for conventional gasoline, reformulated gasoline, natural gas, and methanol vehicle fueling. Results of the study demonstrate the significance of the nonvehicle processes, such as fuel refining, in terms of energy expenditure and emissions production. Unique to this work is the application of the MOBILE5 mobile emissions model in the full-fuel-cycle analysis. Estimates of direct and indirect greenhouse gas production are also presented and discussed using the full-cycle-analysis method.

  1. Chemical Kinetic Modeling of Advanced Transportation Fuels

    SciTech Connect (OSTI)

    PItz, W J; Westbrook, C K; Herbinet, O

    2009-01-20

    Development of detailed chemical kinetic models for advanced petroleum-based and nonpetroleum based fuels is a difficult challenge because of the hundreds to thousands of different components in these fuels and because some of these fuels contain components that have not been considered in the past. It is important to develop detailed chemical kinetic models for these fuels since the models can be put into engine simulation codes used for optimizing engine design for maximum efficiency and minimal pollutant emissions. For example, these chemistry-enabled engine codes can be used to optimize combustion chamber shape and fuel injection timing. They also allow insight into how the composition of advanced petroleum-based and non-petroleum based fuels affect engine performance characteristics. Additionally, chemical kinetic models can be used separately to interpret important in-cylinder experimental data and gain insight into advanced engine combustion processes such as HCCI and lean burn engines. The objectives are: (1) Develop detailed chemical kinetic reaction models for components of advanced petroleum-based and non-petroleum based fuels. These fuels models include components from vegetable-oil-derived biodiesel, oil-sand derived fuel, alcohol fuels and other advanced bio-based and alternative fuels. (2) Develop detailed chemical kinetic reaction models for mixtures of non-petroleum and petroleum-based components to represent real fuels and lead to efficient reduced combustion models needed for engine modeling codes. (3) Characterize the role of fuel composition on efficiency and pollutant emissions from practical automotive engines.

  2. National Transportation Fuels Model | NISAC

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shinesSolar Photovoltaic Solar

  3. Used Fuel Testing Transportation Model

    SciTech Connect (OSTI)

    Ross, Steven B.; Best, Ralph E.; Maheras, Steven J.; Jensen, Philip J.; England, Jeffery L.; LeDuc, Dan

    2014-09-24

    This report identifies shipping packages/casks that might be used by the Used Nuclear Fuel Disposition Campaign Program (UFDC) to ship fuel rods and pieces of fuel rods taken from high-burnup used nuclear fuel (UNF) assemblies to and between research facilities for purposes of evaluation and testing. Also identified are the actions that would need to be taken, if any, to obtain U.S. Nuclear Regulatory (NRC) or other regulatory authority approval to use each of the packages and/or shipping casks for this purpose.

  4. Model Year 2012 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2011-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  5. Model Year 2011 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2010-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  6. Model Year 2013 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2012-12-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  7. Capital Requirements Estimating Model (CREMOD) for electric utilities. Volume I. Methodology description, model, description, and guide to model applications. [For each year up to 1990

    SciTech Connect (OSTI)

    Collins, D E; Gammon, J; Shaw, M L

    1980-01-01

    The Capital Requirements Estimating Model for the Electric Utilities (CREMOD) is a system of programs and data files used to estimate the capital requirements of the electric utility industry for each year between the current one and 1990. CREMOD disaggregates new electric plant capacity levels from the Mid-term Energy Forecasting System (MEFS) Integrating Model solution over time using actual projected commissioning dates. It computes the effect on aggregate capital requirements of dispersal of new plant and capital expenditures over relatively long construction lead times on aggregate capital requirements for each year. Finally, it incorporates the effects of real escalation in the electric utility construction industry on these requirements and computes the necessary transmission and distribution expenditures. This model was used in estimating the capital requirements of the electric utility sector. These results were used in compilation of the aggregate capital requirements for the financing of energy development as published in the 1978 Annual Report to Congress. This volume, Vol. I, explains CREMOD's methodology, functions, and applications.

  8. DYNAMIC MODELING PROTON EXCHANGE MEMBRANE FUEL CELL

    E-Print Network [OSTI]

    Mease, Kenneth D.

    DYNAMIC MODELING PROTON EXCHANGE MEMBRANE FUEL CELL OVERVIEW Current/Completed Plug Power to garner SCAQMD funding for fuel cell testing GenCore system is sensitive to diluents · As built design stream to compensate for removal of EGR · Functionality of the modified GenCore Fuel Cell system

  9. VISION: Verifiable Fuel Cycle Simulation Model

    SciTech Connect (OSTI)

    Jacob J. Jacobson; Abdellatif M. Yacout; Gretchen E. Matthern; Steven J. Piet; David E. Shropshire

    2009-04-01

    The nuclear fuel cycle is a very complex system that includes considerable dynamic complexity as well as detail complexity. In the nuclear power realm, there are experts and considerable research and development in nuclear fuel development, separations technology, reactor physics and waste management. What is lacking is an overall understanding of the entire nuclear fuel cycle and how the deployment of new fuel cycle technologies affects the overall performance of the fuel cycle. The Advanced Fuel Cycle Initiative’s systems analysis group is developing a dynamic simulation model, VISION, to capture the relationships, timing and delays in and among the fuel cycle components to help develop an understanding of how the overall fuel cycle works and can transition as technologies are changed. This paper is an overview of the philosophy and development strategy behind VISION. The paper includes some descriptions of the model and some examples of how to use VISION.

  10. Capital Markets and the Pricing

    E-Print Network [OSTI]

    Schubart, Christoph

    Portfolios 10.7 Measuring Systematic Risk 10.8 Beta and the Cost of Capital #12;Copyright ©2014 Pearson Asset Pricing Model to calculate the cost of capital for a particular project. 12.Explain why in an efficient capital market the cost of capital depends on systematic risk rather than diversifiable risk. #12

  11. Model Year 2006 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2005-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  12. Model Year 2005 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2004-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  13. Model Year 2010 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2009-10-14

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  14. Model Year 2007 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2007-10-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  15. Model Year 2015 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2014-12-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  16. Model Year 2009 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2008-10-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  17. Model Year 2008 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2007-10-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  18. Model Year 2016 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2015-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  19. Model Year 2014 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect (OSTI)

    2013-12-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  20. Empirical modeling of uranium nitride fuels 

    E-Print Network [OSTI]

    Brozak, Daniel Edward

    1987-01-01

    of this work was to develop an irradiation performance data base for nitride fuels and to provide empirical modeling capabilities for fuel swelling and fission gas release in nitride fuels. The nitride fuels data base represents the most extensive effort... the formation of a empirical fit based upon consistent data. The forms of the recommended correlations for fuel swelling and fission gas release are shown on the following page; AV/V = a(Tb) (BUc)(FDd) (SDe) FGR = a(T )(BU )(FD ) where: AV/V FGR T BU FD...

  1. Interaction model of private equity and venture capital developing factors in Chile and Latin America

    E-Print Network [OSTI]

    Sevil Esteban, Ángel

    2012-01-01

    Private equity and venture capital (PE/VC) are efficient resource allocation systems that provide equity capital to selected entrepreneurs, industries or firms that contribute to advance the economic welfare of society. ...

  2. Modeling of solid oxide fuel cells

    E-Print Network [OSTI]

    Lee, Won Yong, S.M. Massachusetts Institute of Technology

    2006-01-01

    A comprehensive membrane-electrode assembly (MEA) model of Solid Oxide Fuel Cell (SOFC)s is developed to investigate the effect of various design and operating conditions on the cell performance and to examine the underlying ...

  3. Fuel Conditioning Facility Electrorefiner Process Model

    SciTech Connect (OSTI)

    DeeEarl Vaden

    2005-10-01

    The Fuel Conditioning Facility at the Idaho National Laboratory processes spent nuclear fuel from the Experimental Breeder Reactor II using electro-metallurgical treatment. To process fuel without waiting for periodic sample analyses to assess process conditions, an electrorefiner process model predicts the composition of the electrorefiner inventory and effluent streams. For the chemical equilibrium portion of the model, the two common methods for solving chemical equilibrium problems, stoichiometric and non stoichiometric, were investigated. In conclusion, the stoichiometric method produced equilibrium compositions close to the measured results whereas the non stoichiometric method did not.

  4. Capital Reporting Company

    National Nuclear Security Administration (NNSA)

    of certain 21 materials for non-fuel cycle use, such as deuterium gas 22 for fiber-optic production, heavy water for deuterated *Added by DOENNSA for clarification. Capital...

  5. Mathematical modeling of solid oxide fuel cells using hydrocarbon fuels

    E-Print Network [OSTI]

    Lee, Won Yong, Ph. D. Massachusetts Institute of Technology

    2012-01-01

    Solid oxide fuel cells (SOFCs) are high efficiency conversion devices that use hydrogen or light hydrocarbon (HC) fuels in stationary applications to produce quiet and clean power. While successful, HC-fueled SOFCs face ...

  6. On a Pioneering Polymer Electrolyte Fuel Cell Model

    E-Print Network [OSTI]

    Weber, Adam Z.

    2013-01-01

    polymer electrolyte fuel cell, in, USPTO Editor, UnitedRenewable Energy, Office of Fuel Cell Technologies, of thePolymer Electrolyte Fuel Cell Model Adam Z Weber Lawrence

  7. Advancement in Fuel Spray and Combustion Modeling for Compression...

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

    Advancement in Fuel Spray and Combustion Modeling for Compression Ignition Engine Applications Advancement in Fuel Spray and Combustion Modeling for Compression Ignition Engine...

  8. Supercomputers Fuel Global High-Resolution Climate Models

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

    Supercomputers Fuel Global High-Resolution Climate Models Supercomputers Fuel Global High-Resolution Climate Models Berkeley Lab Researcher Says Climate Science is Entering New...

  9. Evaluation of fuel rod characterization for transient fuel modeling 

    E-Print Network [OSTI]

    Bechler, Eric Wayne

    1989-01-01

    Design parameters for Maine Yankee Unit I and Oconee Unit 2 fuel rods 23 Zircaloy cladding properties for Maine Yankee Unit I and Oconee Unit 2 fuel rods 26 Integral fission gas release of Maine Yankee Unit 1 and Oconee Unit 2 fuel rods 29 Cladding... parameters from COMETHE III-L steady state analyses for transient FREY-01 calculations 48 14 End-of-life fission gas release results for the Over-Ramp test fuel rodlet A20/3 49 15 Description of fuel diametral changes during the base irradiation...

  10. Sustainable World Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Information Serbia-Enhancing CapacityVectren)Model forTechnologies Ltd Jump to:PowerSystemsWorld Capital

  11. Essays in capital markets

    E-Print Network [OSTI]

    Makarov, Igor, 1976-

    2006-01-01

    This thesis consists of three essays in capital markets. The first essay presents a dynamic asset pricing model with heterogeneously informed agents. Unlike previous research, the general case where differential information ...

  12. Modeling Deep Burn TRISO Particle Nuclear Fuel

    SciTech Connect (OSTI)

    Besmann, Theodore M [ORNL; Stoller, Roger E [ORNL; Samolyuk, German D [ORNL; Schuck, Paul C [ORNL; Rudin, Sven [Los Alamos National Laboratory (LANL); Wills, John [Los Alamos National Laboratory (LANL); Wirth, Brian D. [University of California, Berkeley; Kim, Sungtae [University of Wisconsin, Madison; Morgan, Dane [University of Wisconsin, Madison; Szlufarska, Izabela [University of Wisconsin, Madison

    2012-01-01

    Under the DOE Deep Burn program TRISO fuel is being investigated as a fuel form for consuming plutonium and minor actinides, and for greater efficiency in uranium utilization. The result will thus be to drive TRISO particulate fuel to very high burn-ups. In the current effort the various phenomena in the TRISO particle are being modeled using a variety of techniques. The chemical behavior is being treated utilizing thermochemical analysis to identify phase formation/transformation and chemical activities in the particle, including kernel migration. First principles calculations are being used to investigate the critical issue of fission product palladium attack on the SiC coating layer. Density functional theory is being used to understand fission product diffusion within the plutonia oxide kernel. Kinetic Monte Carlo techniques are shedding light on transport of fission products, most notably silver, through the carbon and SiC coating layers. The diffusion of fission products through an alternative coating layer, ZrC, is being assessed via DFT methods. Finally, a multiscale approach is being used to understand thermal transport, including the effect of radiation damage induced defects, in a model SiC material.

  13. Boron-10 ABUNCL Models of Fuel Testing

    SciTech Connect (OSTI)

    Siciliano, Edward R.; Lintereur, Azaree T.; Kouzes, Richard T.; Ely, James H.

    2013-10-01

    The Department of Energy Office of Nuclear Safeguards and Security (NA-241) is supporting the project Coincidence Counting With Boron-Based Alternative Neutron Detection Technology at Pacific Northwest National Laboratory (PNNL) for the development of a 3He proportional counter alternative neutron coincidence counter. The goal of this project is to design, build and demonstrate a system based upon 10B-lined proportional tubes in a configuration typical for 3He-based coincidence counter applications. This report provides results from MCNP simulations of the General Electric Reuter-Stokes Alternative Boron-Based Uranium Neutron Coincidence Collar (ABUNCL) active configuration model with fuel pins previously measured at Los Alamos National Laboratory. A comparison of the GE-ABUNCL simulations and simulations of 3He based UNCL-II active counter (the system for which the GE-ABUNCL was targeted to replace) with the same fuel pin assemblies is also provided.

  14. Fuel Puddle Model and AFR Compensator for Gasoline-Ethanol Blends in Flex-Fuel Engines*

    E-Print Network [OSTI]

    Stefanopoulou, Anna

    Fuel Puddle Model and AFR Compensator for Gasoline-Ethanol Blends in Flex-Fuel Engines* Kyung as an alternative fuel to petroleum-based gasoline and diesel derivatives. Currently available flexible fuel the closed-loop air-to-fuel ratio (AFR) control which maintains automatically operation around

  15. Fuel Cell System Improvement for Model-Based Diagnosis Analysis

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Fuel Cell System Improvement for Model-Based Diagnosis Analysis Philippe Fiani & Michel Batteux of a model of a fuel cell system, in order to make it usable for model- based diagnosis methods. A fuel cell for the fuel cell stack but also for the system environment. In this paper, we present an adapted library which

  16. Water Transport in PEM Fuel Cells: Advanced Modeling, Material...

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

    Testing and Design Optimization Water Transport in PEM Fuel Cells: Advanced Modeling, Material Selection, Testing and Design Optimization Part of a 100 million fuel cell award...

  17. Progress in Chemical Kinetic Modeling for Surrogate Fuels

    SciTech Connect (OSTI)

    Pitz, W J; Westbrook, C K; Herbinet, O; Silke, E J

    2008-06-06

    Gasoline, diesel, and other alternative transportation fuels contain hundreds to thousands of compounds. It is currently not possible to represent all these compounds in detailed chemical kinetic models. Instead, these fuels are represented by surrogate fuel models which contain a limited number of representative compounds. We have been extending the list of compounds for detailed chemical models that are available for use in fuel surrogate models. Detailed models for components with larger and more complicated fuel molecular structures are now available. These advancements are allowing a more accurate representation of practical and alternative fuels. We have developed detailed chemical kinetic models for fuels with higher molecular weight fuel molecules such as n-hexadecane (C16). Also, we can consider more complicated fuel molecular structures like cyclic alkanes and aromatics that are found in practical fuels. For alternative fuels, the capability to model large biodiesel fuels that have ester structures is becoming available. These newly addressed cyclic and ester structures in fuels profoundly affect the reaction rate of the fuel predicted by the model. Finally, these surrogate fuel models contain large numbers of species and reactions and must be reduced for use in multi-dimensional models for spark-ignition, HCCI and diesel engines.

  18. Fuel Used for Off-Road Recreation: A Reassessment of the Fuel Use Model

    E-Print Network [OSTI]

    Fuel Used for Off-Road Recreation: A Reassessment of the Fuel Use Model Stacy C. Davis Lorena F. Truett Patricia S. Hu #12;ORNL/TM-1999/100 Fuel Used for Off-Road Recreation: A Reassessment of the Fuel.S. Department of Energy under Contract No. DE-AC05-96OR22464 #12;#12;Fuel Used for Off-Road Recreation

  19. MODELING AND EXPERIMENTAL STUDIES TO OPTIMIZE THE PERFORMANCE OF A HYDROGEN – BROMINE FUEL CELL

    E-Print Network [OSTI]

    Yarlagadda, Venkata Raviteja

    2015-08-31

    The regenerative Hydrogen-Bromine (H2-Br2) fuel cells are considered to be one of the viable systems for large scale energy storage because of their high energy conversion efficiency, flexible operation, highly reversible reactions and low capital...

  20. TRANSMISSION AND DISTRIBUTION; POWER SUBSTATIONS; CAPITALIZED...

    Office of Scientific and Technical Information (OSTI)

    AND DISTRIBUTION; POWER SUBSTATIONS; CAPITALIZED COST; CALCULATION METHODS; PLANNING; COST ESTIMATION; MATHEMATICAL MODELS The displacement or deferral of substation...

  1. COMPUTATIONAL FLUID DYNAMICS MODELING OF SOLID OXIDE FUEL CELLS

    E-Print Network [OSTI]

    COMPUTATIONAL FLUID DYNAMICS MODELING OF SOLID OXIDE FUEL CELLS Ugur Pasaogullari and Chao-dimensional model has been developed to simulate solid oxide fuel cells (SOFC). The model fully couples current density operation. INTRODUCTION Solid oxide fuel cells (SOFC) are among possible candidates

  2. Solid Oxide Fuel Cell: Perspective of Dynamic Modeling and Control

    E-Print Network [OSTI]

    Huang, Biao

    Solid Oxide Fuel Cell: Perspective of Dynamic Modeling and Control Biao Huang Yutong Qi Monjur: This paper presents a review of state-of-the-art solid oxide fuel cells (SOFC), from perspective of dynamic. Keywords: Solid Oxide Fuel Cell, Control Relevant Model, Model Predictive Control 1. INTRODUCTION Today

  3. Fuel Cell Power Model for CHHP System Economics and Performance...

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

    Model for CHHP System Economics and Performance Analysis Fuel Cell Power Model for CHHP System Economics and Performance Analysis Presented at the Renewable Hydrogen Workshop, Nov....

  4. Connecticut Fuel Cell Activities: Markets, Programs, and Models...

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

    Activities: Markets, Programs, and Models Connecticut Fuel Cell Activities: Markets, Programs, and Models Presented by the Connecticut Center for Advanced Technology, Inc. at the...

  5. Design optimization and analysis of coated particle fuel using advanced fuel performance modeling techniques

    E-Print Network [OSTI]

    Soontrapa, Chaiyod

    2005-01-01

    Modifying material properties provides another approach to optimize coated particle fuel used in pebble bed reactors. In this study, the MIT fuel performance model (TIMCOAT) was applied after benchmarking against the ...

  6. Alternative Liquid Fuels Simulation Model (AltSim).

    SciTech Connect (OSTI)

    Williams, Ryan; Baker, Arnold Barry; Drennen, Thomas E.

    2009-12-01

    The Alternative Liquid Fuels Simulation Model (AltSim) is a high-level dynamic simulation model which calculates and compares the production and end use costs, greenhouse gas emissions, and energy balances of several alternative liquid transportation fuels. These fuels include: corn ethanol, cellulosic ethanol from various feedstocks (switchgrass, corn stover, forest residue, and farmed trees), biodiesel, and diesels derived from natural gas (gas to liquid, or GTL), coal (coal to liquid, or CTL), and coal with biomass (CBTL). AltSim allows for comprehensive sensitivity analyses on capital costs, operation and maintenance costs, renewable and fossil fuel feedstock costs, feedstock conversion ratio, financial assumptions, tax credits, CO{sub 2} taxes, and plant capacity factor. This paper summarizes the structure and methodology of AltSim, presents results, and provides a detailed sensitivity analysis. The Energy Independence and Security Act (EISA) of 2007 sets a goal for the increased use of biofuels in the U.S., ultimately reaching 36 billion gallons by 2022. AltSim's base case assumes EPA projected feedstock costs in 2022 (EPA, 2009). For the base case assumptions, AltSim estimates per gallon production costs for the five ethanol feedstocks (corn, switchgrass, corn stover, forest residue, and farmed trees) of $1.86, $2.32, $2.45, $1.52, and $1.91, respectively. The projected production cost of biodiesel is $1.81/gallon. The estimates for CTL without biomass range from $1.36 to $2.22. With biomass, the estimated costs increase, ranging from $2.19 per gallon for the CTL option with 8% biomass to $2.79 per gallon for the CTL option with 30% biomass and carbon capture and sequestration. AltSim compares the greenhouse gas emissions (GHG) associated with both the production and consumption of the various fuels. EISA allows fuels emitting 20% less greenhouse gases (GHG) than conventional gasoline and diesels to qualify as renewable fuels. This allows several of the CBTL options to be included under the EISA mandate. The estimated GHG emissions associated with the production of gasoline and diesel are 19.80 and 18.40 kg of CO{sub 2} equivalent per MMBtu (kgCO{sub 2}e/MMBtu), respectively (NETL, 2008). The estimated emissions are significantly higher for several alternatives: ethanol from corn (70.6), GTL (51.9), and CTL without biomass or sequestration (123-161). Projected emissions for several other alternatives are lower; integrating biomass and sequestration in the CTL processes can even result in negative net emissions. For example, CTL with 30% biomass and 91.5% sequestration has estimated production emissions of -38 kgCO{sub 2}e/MMBtu. AltSim also estimates the projected well-to-wheel, or lifecycle, emissions from consuming each of the various fuels. Vehicles fueled with conventional diesel or gasoline and driven 12,500 miles per year emit 5.72-5.93 tons of CO{sub 2} equivalents per year (tCO{sub 2}e/yr). Those emissions are significantly higher for vehicles fueled with 100% ethanol from corn (8.03 tCO{sub 2}e/yr) or diesel from CTL without sequestration (10.86 to 12.85 tCO{sub 2}/yr). Emissions could be significantly lower for vehicles fueled with diesel from CBTL with various shares of biomass. For example, for CTL with 30% biomass and carbon sequestration, emissions would be 2.21 tCO{sub 2}e per year, or just 39% of the emissions for a vehicle fueled with conventional diesel. While the results presented above provide very specific estimates for each option, AltSim's true potential is as a tool for educating policy makers and for exploring 'what if?' type questions. For example, AltSim allows one to consider the affect of various levels of carbon taxes on the production cost estimates, as well as increased costs to the end user on an annual basis. Other sections of AltSim allow the user to understand the implications of various polices in terms of costs to the government or land use requirements. AltSim's structure allows the end user to explore each of these alternatives and understand the sensitivities implications a

  7. CAPITAL PROJECT PROPOSAL

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L OBransenBusiness networkingFleetPuget Dr.HomeGas ReserveCAPITAL

  8. Access to Capital Roundtable

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirley Ann JacksonDepartment| DepartmentAL/FAL 99-01 More5, 2014Nonproliferation |is anCapital

  9. CMEA Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButte County, California: Energy Resources JumpEmissionCapitalCMEA Capital Jump to:

  10. Modelling Microscale Fuel Cells Aimy Ming Jii Bazylak

    E-Print Network [OSTI]

    Victoria, University of

    Modelling Microscale Fuel Cells by Aimy Ming Jii Bazylak B.E., University of Saskatchewan, 2003 cell designs using computational fluid dynamics (CFD). Two microscale fuel cell systems are considered in this work: the membraneless microfluidic fuel cell and a planar array of integrated fuel cells. A concise

  11. 2011 Strategic Capital Discussions

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

    2010 IPR 2009 IPR 2008 Capital Investment Review CIR 2012 Quarterly Business Review 2011 Strategic Capital Discussions Access to Capital Debt Optimization Asset Management Cost...

  12. Modelling and control strategy development for fuel cell electric vehicles

    E-Print Network [OSTI]

    Peng, Huei

    Modelling and control strategy development for fuel cell electric vehicles Andreas Schell b , Huei applicable to the development of fuel cell electric vehicles (FCEVs) and hybrid electric vehicles (HEVs reserved. Keywords: Fuel cell electric vehicle; Hybrid vehicles; Modelling 1. Introduction Advanced

  13. Liquid Fuels Market Model (LFMM) Unveiling LFMM

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245YearYear

  14. Greenview Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History View New PagesSustainableGlynn County,Solar Jump to: navigation,Capital Advisors GCAGreenview

  15. Model Compound Studies of Fuel Cell Membrane Degradation

    Broader source: Energy.gov [DOE]

    Presentation on Model Compound Studies of Fuel Cell Membrane Degradation to the High Temperature Membrane Working Group Meeting held in Arlington, Virginia, May 26,2005.

  16. Analysis Models and Tools: Systems Analysis of Hydrogen and Fuel...

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

    and individual summaries of the models and tools used for systems analysis of hydrogen and fuel cells. View the Overview Fact Sheet and Individual Summaries Overview Fact...

  17. Water Transport in PEM Fuel Cells: Advanced Modeling, Material...

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

    Testing, and Design Optimization Water Transport in PEM Fuel Cells: Advanced Modeling, Material Selection, Testing, and Design Optimization This presentation, which focuses on...

  18. Mesoscale Modeling of Fuel Swelling and Restructuring: Coupling...

    Office of Scientific and Technical Information (OSTI)

    Conference: Mesoscale Modeling of Fuel Swelling and Restructuring: Coupling Microstructure evolution and Mechanical Localization. Citation Details In-Document Search Title:...

  19. A methodology for assessing the market benefits of alternative motor fuels: The Alternative Fuels Trade Model

    SciTech Connect (OSTI)

    Leiby, P.N.

    1993-09-01

    This report describes a modeling methodology for examining the prospective economic benefits of displacing motor gasoline use by alternative fuels. The approach is based on the Alternative Fuels Trade Model (AFTM). AFTM development was undertaken by the US Department of Energy (DOE) as part of a longer term study of alternative fuels issues. The AFTM is intended to assist with evaluating how alternative fuels may be promoted effectively, and what the consequences of substantial alternative fuels use might be. Such an evaluation of policies and consequences of an alternative fuels program is being undertaken by DOE as required by Section 502(b) of the Energy Policy Act of 1992. Interest in alternative fuels is based on the prospective economic, environmental and energy security benefits from the substitution of these fuels for conventional transportation fuels. The transportation sector is heavily dependent on oil. Increased oil use implies increased petroleum imports, with much of the increase coming from OPEC countries. Conversely, displacement of gasoline has the potential to reduce US petroleum imports, thereby reducing reliance on OPEC oil and possibly weakening OPEC`s ability to extract monopoly profits. The magnitude of US petroleum import reduction, the attendant fuel price changes, and the resulting US benefits, depend upon the nature of oil-gas substitution and the supply and demand behavior of other world regions. The methodology applies an integrated model of fuel market interactions to characterize these effects.

  20. Computational Modeling and Optimization of Proton Exchange Membrane Fuel Cells

    E-Print Network [OSTI]

    Victoria, University of

    Computational Modeling and Optimization of Proton Exchange Membrane Fuel Cells by Marc Secanell and Optimization of Proton Exchange Membrane Fuel Cells by Marc Secanell Gallart Bachelor in Engineering cells. In this thesis, a computational framework for fuel cell analysis and optimization is presented

  1. Direct Methanol Fuel Cell Experimental and Model Validation Study

    E-Print Network [OSTI]

    Wang, Chao-Yang

    Direct Methanol Fuel Cell Experimental and Model Validation Study M. Mench, J. Scott, S. Thynell boundary Fuel cell performance Current density distribution measurements Conclusions #12;3 Method, flow rate, species inlet and fuel cell temperature, and humidity. Transparent polycarbonate windows

  2. Dynamic Modelling for Control of Fuel Cells Federico Zenith

    E-Print Network [OSTI]

    Skogestad, Sigurd

    Dynamic Modelling for Control of Fuel Cells Federico Zenith Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Technology ( ntnu) Trondheim Abstract Fuel-cell dynamics have been investigated with a variable-resistance board applied to a high temperature polymer fuel cell

  3. Stochastic Programming Model for Fuel Treatment Management 

    E-Print Network [OSTI]

    Kabli, Mohannad Reda A

    2014-04-28

    Due to the increased number and intensity of wild fires, the need for solutions that minimize the impact of fire are needed. Fuel treatment is one of the methods used to mitigate the effects of fire at a certain area. In this thesis, a two...

  4. Dynamic Modeling in Solid-Oxide Fuel Cells Controller Design

    SciTech Connect (OSTI)

    Lu, Ning; Li, Qinghe; Sun, Xin; Khaleel, Mohammad A.

    2007-06-28

    In this paper, a dynamic model of the solid-oxide fuel cell (SOFC) power unit is developed for the purpose of designing a controller to regulate fuel flow rate, fuel temperature, air flow rate, and air temperature to maintain the SOFC stack temperature, fuel utilization rate, and voltage within operation limits. A lumped model is used to consider the thermal dynamics and the electro-chemial dynamics inside an SOFC power unit. The fluid dynamics at the fuel and air inlets are considered by using the in-flow ramp-rates.

  5. Model Year 2006: Alternative Fuel and Advanced Technology Vehicles

    Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels Data Center Home PageBlender PumpVehiclesThe Heat Letter to Science of 2Model

  6. Model of U3Si2 Fuel System using BISON Fuel Code

    SciTech Connect (OSTI)

    K. E. Metzger; T. W. Knight; R. L. Williamson

    2014-04-01

    This research considers the proposed advanced fuel system: U3Si2 combined with an advanced cladding. U3Si2 has a number of advantageous thermophysical properties, which motivate its use as an accident tolerant fuel. This preliminary model evaluates the behavior of U3Si2 using available thermophysical data to predict the cladding-fuel pellet temperature and stress using the fuel performance code: BISON. The preliminary results obtained from the U3Si2 fuel model describe the mechanism of Pellet-Clad Mechanical Interaction for this system while more extensive testing including creep testing of U3Si2 is planned for improved understanding of thermophysical properties for predicting fuel performance.

  7. Sustainable Energy Capital Partners SECP | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Information Serbia-Enhancing CapacityVectren)Model for theSunLanSuperDriveEconomiesNewSustainCapital

  8. Distributed parameter model simulation tool for PEM fuel cells

    E-Print Network [OSTI]

    Batlle, Carles

    for proton exchange membrane fuel cells (PEMFC) has been developed, based on a distributed parameter model and durability of PEMFC. Keywords: PEMFC, distributed parameter modeling, dynamic simulation 1. Introduction The proton exchange membrane fuel cells (PEMFC) technology has been incorporated to a wide range of portable

  9. Renewable Fuels Module of the National Energy Modeling System

    U.S. Energy Information Administration (EIA) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearby the(Dollars1.840 2.318 3.1195) Model8) Model

  10. Model documentation: Electricity Market Module, Electricity Fuel Dispatch Submodule

    SciTech Connect (OSTI)

    Not Available

    1994-04-08

    This report documents the objectives, analytical approach and development of the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

  11. Office of the Chief Human Capital Officer | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.Theory of rare Kaonforsupernovae model (JournalHearingsHuman Capital Officer Search

  12. Foundation Capital

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i nA Guide to Tapping into FundingCommittee on AppropriationsFuels Study

  13. Fuel cycle assessment: A compendium of models, methodologies, and approaches

    SciTech Connect (OSTI)

    Not Available

    1994-07-01

    The purpose of this document is to profile analytical tools and methods which could be used in a total fuel cycle analysis. The information in this document provides a significant step towards: (1) Characterizing the stages of the fuel cycle. (2) Identifying relevant impacts which can feasibly be evaluated quantitatively or qualitatively. (3) Identifying and reviewing other activities that have been conducted to perform a fuel cycle assessment or some component thereof. (4) Reviewing the successes/deficiencies and opportunities/constraints of previous activities. (5) Identifying methods and modeling techniques/tools that are available, tested and could be used for a fuel cycle assessment.

  14. VHTR Prismatic Super Lattice Model for Equilibrium Fuel Cycle Analysis

    SciTech Connect (OSTI)

    G. S. Chang

    2006-09-01

    The advanced Very High Temperature gas-cooled Reactor (VHTR), which is currently being developed, achieves simplification of safety through reliance on innovative features and passive systems. One of the VHTRs innovative features is the reliance on ceramic-coated fuel particles to retain the fission products under extreme accident conditions. The effect of the random fuel kernel distribution in the fuel prismatic block is addressed through the use of the Dancoff correction factor in the resonance treatment. However, if the fuel kernels are not perfect black absorbers, the Dancoff correction factor is a function of burnup and fuel kernel packing factor, which requires that the Dancoff correction factor be updated during Equilibrium Fuel Cycle (EqFC) analysis. An advanced Kernel-by-Kernel (K-b-K) hexagonal super lattice model can be used to address and update the burnup dependent Dancoff effect during the EqFC analysis. The developed Prismatic Super Homogeneous Lattice Model (PSHLM) is verified by comparing the calculated burnup characteristics of the double-heterogeneous Prismatic Super Kernel-by-Kernel Lattice Model (PSK-b-KLM). This paper summarizes and compares the PSHLM and PSK-b-KLM burnup analysis study and results. This paper also discusses the coupling of a Monte-Carlo code with fuel depletion and buildup code, which provides the fuel burnup analysis tool used to produce the results of the VHTR EqFC burnup analysis.

  15. Kinetic Modeling of Combustion Characteristics of Real Biodiesel Fuels

    SciTech Connect (OSTI)

    Naik, C V; Westbrook, C K

    2009-04-08

    Biodiesel fuels are of much interest today either for replacing or blending with conventional fuels for automotive applications. Predicting engine effects of using biodiesel fuel requires accurate understanding of the combustion characteristics of the fuel, which can be acquired through analysis using reliable detailed reaction mechanisms. Unlike gasoline or diesel that consists of hundreds of chemical compounds, biodiesel fuels contain only a limited number of compounds. Over 90% of the biodiesel fraction is composed of 5 unique long-chain C{sub 18} and C{sub 16} saturated and unsaturated methyl esters. This makes modeling of real biodiesel fuel possible without the need for a fuel surrogate. To this end, a detailed chemical kinetic mechanism has been developed for determining the combustion characteristics of a pure biodiesel (B100) fuel, applicable from low- to high-temperature oxidation regimes. This model has been built based on reaction rate rules established in previous studies at Lawrence Livermore National Laboratory. Computed results are compared with the few fundamental experimental data that exist for biodiesel fuel and its components. In addition, computed results have been compared with experimental data for other long-chain hydrocarbons that are similar in structure to the biodiesel components.

  16. LG Solid Oxide Fuel Cell (SOFC) Model Development

    SciTech Connect (OSTI)

    Haberman, Ben; Martinez-Baca, Carlos; Rush, Greg

    2013-03-31

    This report presents a summary of the work performed by LG Fuel Cell Systems Inc. during the project LG Solid Oxide Fuel Cell (SOFC) Model Development (DOE Award Number: DE-FE0000773) which commenced on October 1, 2009 and was completed on March 31, 2013. The aim of this project is for LG Fuel Cell Systems Inc. (formerly known as Rolls-Royce Fuel Cell Systems (US) Inc.) (?LGFCS?) to develop a multi-physics solid oxide fuel cell (SOFC) computer code (MPC) for performance calculations of the LGFCS fuel cell structure to support fuel cell product design and development. A summary of the initial stages of the project is provided which describes the MPC requirements that were developed and the selection of a candidate code, STAR-CCM+ (CD-adapco). This is followed by a detailed description of the subsequent work program including code enhancement and model verification and validation activities. Details of the code enhancements that were implemented to facilitate MPC SOFC simulations are provided along with a description of the models that were built using the MPC and validated against experimental data. The modeling work described in this report represents a level of calculation detail that has not been previously available within LGFCS.

  17. CAPITAL REGION

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p a l DeInsulation at04-86) (All Previous EditionsOffice of2, thet

  18. Market Share Elasticities for Fuel and Technology Choice in Home Heating and Cooling

    E-Print Network [OSTI]

    Wood, D.J.

    2010-01-01

    Data. Both fuel prices and capital costs are taken for the2 Price, Income, and Capital Cost Elasticities for Marketby operating and capital costs (or which are otherwise

  19. A Model Fuels Consortium to Promote Engine Modeling | Department...

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

    Detroit, Michigan. Sponsored by the U.S. DOE's EERE FreedomCar and Fuel Partnership and 21st Century Truck Programs. 2006deerdeur.pdf More Documents & Publications Kinetics,...

  20. CONTROL-ORIENTED MODEL OF AN INTEGRATED FUEL CELL STACK AND FUEL

    E-Print Network [OSTI]

    Stefanopoulou, Anna

    -oriented dynamic model of a catalytic partial oxidation-based fuel processor is developed using physics gas to hydrogen in- clude steam reforming and partial oxidation. The most common method, steam reforming, which is endothermic, is well suited for steady-state operation and can deliver a relatively high

  1. Venture Capital Finance

    Broader source: Energy.gov [DOE]

    Plenary III: Project Finance and Investment Venture Capital Finance Brian Baynes, Partner, Flagship Ventures

  2. Note on "Venture Capital"

    E-Print Network [OSTI]

    Kenney, Martin

    2000-01-01

    venture capital excludes buyouts, loans, and other financialconcentrating upon management buyouts, bridge financing,

  3. Greenworld Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History View New PagesSustainableGlynn County,Solar Jump to:Resources Jump to:Greenworld Capital Jump to:

  4. Hazel Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History View NewTexas: Energy Resources Jump to: navigation, search Equivalent| Open EnergyCapital Jump to:

  5. Nite Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo, Maryland:NPI VenturesNew Hampshire: Energy ResourcesNiigataNiobraraNite Capital Jump to:

  6. Greentech Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar2-0057-EA Jump to:ofEniaElectricHydro ElectricGreenLtd JumpCapital Jump to:

  7. Ardour Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EAandAmminex A S JumpArchuleta County, Colorado:Ardentown, Delaware:Capital

  8. Greener Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsource History View New Pages RecentPlantMagmaIncentivesEnergyGreenVoltsGreener Capital

  9. Yellowstone Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop IncIowa (UtilityMichigan) Jump to: Name:XinjiangPupingYanyuanValley ElecCapital

  10. Earthrise Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButtePower VenturesInformation9)askDoubleEERE -ESolarEarthrise Capital Jump to:

  11. Osmosis Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsourceII JumpQuarterly Smart Grid DataInformationOpenOsmosis Capital Jump to:

  12. VISION -- A Dynamic Model of the Nuclear Fuel Cycle

    SciTech Connect (OSTI)

    J. J. Jacobson; A. M. Yacout; S. J. Piet; D. E. Shropshire; G. E. Matthern

    2006-02-01

    The Advanced Fuel Cycle Initiative’s (AFCI) fundamental objective is to provide technology options that – if implemented – would enable long-term growth of nuclear power while improving sustainability and energy security. The AFCI organization structure consists of four areas; Systems Analysis, Fuels, Separations and Transmutations. The Systems Analysis Working Group is tasked with bridging the program technical areas and providing the models, tools, and analyses required to assess the feasibility of design and deploy¬ment options and inform key decision makers. An integral part of the Systems Analysis tool set is the development of a system level model that can be used to examine the implications of the different mixes of reactors, implications of fuel reprocessing, impact of deployment technologies, as well as potential “exit” or “off ramp” approaches to phase out technologies, waste management issues and long-term repository needs. The Verifiable Fuel Cycle Simulation Model (VISION) is a computer-based simulation model that allows performing dynamic simulations of fuel cycles to quantify infrastructure requirements and identify key trade-offs between alternatives. VISION is intended to serve as a broad systems analysis and study tool applicable to work conducted as part of the AFCI (including costs estimates) and Generation IV reactor development studies.

  13. Performance modelling of a proton exchange membrane fuel cell

    SciTech Connect (OSTI)

    Marr, C.; Li, X.

    1998-12-31

    This paper presents a performance model of a proton exchange membrane fuel cell that has sufficient accuracy for engineering applications with reduced computational requirements. The model includes electrochemical reaction in the catalyst layers and formulation for electrical resistance in the membrane, electrodes and bipolar plates, and employs engineering correlation for the reactant gas transport in the flow channels and through the electrodes. It is shown that the present model predictions are in reasonable agreement with known experimental observations, indicating that the present model can be employed for fuel cell stack and system modeling. The effect of various operating and design parameters on the cell performance has been investigated. It is found that mass transport limitations are the largest cause of performance loss in the cell when graphite is used as the material for bipolar plates and electrodes. If conducting polymers are substituted as construction materials, cell performance is expected to suffer considerably at high current densities due to their reduced electrical conductivity.

  14. Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles

    E-Print Network [OSTI]

    Zhao, Hengbing; Burke, Andy

    2008-01-01

    Polymer Electrolyte Fuel Cell Model, J. Electrochem. Soc. ,in Polymer Electrolyte Fuel Cells, J. Electrochem. Soc. ,Solid-Polymer- Electrolyte Fuel Cell, J. Electrochem. Soc. ,

  15. Modeling Constituent Redistribution in U-Pu-Zr Metallic Fuel Using the Advanced Fuel Performance Code BISON

    SciTech Connect (OSTI)

    Douglas Porter; Steve Hayes; Various

    2014-06-01

    The Advanced Fuels Campaign (AFC) metallic fuels currently being tested have higher zirconium and plutonium concentrations than those tested in the past in EBR reactors. Current metal fuel performance codes have limitations and deficiencies in predicting AFC fuel performance, particularly in the modeling of constituent distribution. No fully validated code exists due to sparse data and unknown modeling parameters. Our primary objective is to develop an initial analysis tool by incorporating state-of-the-art knowledge, constitutive models and properties of AFC metal fuels into the MOOSE/BISON (1) framework in order to analyze AFC metallic fuel tests.

  16. The FIT Model - Fuel-cycle Integration and Tradeoffs

    SciTech Connect (OSTI)

    Steven J. Piet; Nick R. Soelberg; Samuel E. Bays; Candido Pereira; Layne F. Pincock; Eric L. Shaber; Meliisa C Teague; Gregory M Teske; Kurt G Vedros

    2010-09-01

    All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010] are an initial step by the FCR&D program toward a global analysis that accounts for the requirements and capabilities of each component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. The question originally posed to the “system losses study” was the cost of separation, fuel fabrication, waste management, etc. versus the separation efficiency. In other words, are the costs associated with marginal reductions in separations losses (or improvements in product recovery) justified by the gains in the performance of other systems? We have learned that that is the wrong question. The right question is: how does one adjust the compositions and quantities of all mass streams, given uncertain product criteria, to balance competing objectives including cost? FIT is a method to analyze different fuel cycles using common bases to determine how chemical performance changes in one part of a fuel cycle (say used fuel cooling times or separation efficiencies) affect other parts of the fuel cycle. FIT estimates impurities in fuel and waste via a rough estimate of physics and mass balance for a set of technologies. If feasibility is an issue for a set, as it is for “minimum fuel treatment” approaches such as melt refining and AIROX, it can help to make an estimate of how performances would have to change to achieve feasibility.

  17. Fuel Performance Experiments and Modeling: Fission Gas Bubble Nucleation and Growth in Alloy Nuclear Fuels

    SciTech Connect (OSTI)

    McDeavitt, Sean; Shao, Lin; Tsvetkov, Pavel; Wirth, Brian; Kennedy, Rory

    2014-04-07

    Advanced fast reactor systems being developed under the DOE's Advanced Fuel Cycle Initiative are designed to destroy TRU isotopes generated in existing and future nuclear energy systems. Over the past 40 years, multiple experiments and demonstrations have been completed using U-Zr, U-Pu-Zr, U-Mo and other metal alloys. As a result, multiple empirical and semi-empirical relationships have been established to develop empirical performance modeling codes. Many mechanistic questions about fission as mobility, bubble coalescience, and gas release have been answered through industrial experience, research, and empirical understanding. The advent of modern computational materials science, however, opens new doors of development such that physics-based multi-scale models may be developed to enable a new generation of predictive fuel performance codes that are not limited by empiricism.

  18. Order Reduction of a Distributed Parameter PEM Fuel Cell Model

    E-Print Network [OSTI]

    Batlle, Carles

    reduction of the PEMFC 5 Conclusions and outlook 2 / 17 iberconappice2014 #12;Introduction Distributed and durability of the Proton Exchange Membrane Fuel Cells (PEMFC). Large number of differential algebraic dimension DAE system obtained from a first principles, PDE model of the PEMFC. Both the original full order

  19. Developing a Cost Model and Methodology to Estimate Capital Costs for Thermal Energy Storage

    SciTech Connect (OSTI)

    Glatzmaier, G.

    2011-12-01

    This report provides an update on the previous cost model for thermal energy storage (TES) systems. The update allows NREL to estimate the costs of such systems that are compatible with the higher operating temperatures associated with advanced power cycles. The goal of the Department of Energy (DOE) Solar Energy Technology Program is to develop solar technologies that can make a significant contribution to the United States domestic energy supply. The recent DOE SunShot Initiative sets a very aggressive cost goal to reach a Levelized Cost of Energy (LCOE) of 6 cents/kWh by 2020 with no incentives or credits for all solar-to-electricity technologies.1 As this goal is reached, the share of utility power generation that is provided by renewable energy sources is expected to increase dramatically. Because Concentrating Solar Power (CSP) is currently the only renewable technology that is capable of integrating cost-effective energy storage, it is positioned to play a key role in providing renewable, dispatchable power to utilities as the share of power generation from renewable sources increases. Because of this role, future CSP plants will likely have as much as 15 hours of Thermal Energy Storage (TES) included in their design and operation. As such, the cost and performance of the TES system is critical to meeting the SunShot goal for solar technologies. The cost of electricity from a CSP plant depends strongly on its overall efficiency, which is a product of two components - the collection and conversion efficiencies. The collection efficiency determines the portion of incident solar energy that is captured as high-temperature thermal energy. The conversion efficiency determines the portion of thermal energy that is converted to electricity. The operating temperature at which the overall efficiency reaches its maximum depends on many factors, including material properties of the CSP plant components. Increasing the operating temperature of the power generation system leads to higher thermal-to-electric conversion efficiency. However, in a CSP system, higher operating temperature also leads to greater thermal losses. These two effects combine to give an optimal system-level operating temperature that may be less than the upper operating temperature limit of system components. The overall efficiency may be improved by developing materials, power cycles, and system-integration strategies that enable operation at elevated temperature while limiting thermal losses. This is particularly true for the TES system and its components. Meeting the SunShot cost target will require cost and performance improvements in all systems and components within a CSP plant. Solar collector field hardware will need to decrease significantly in cost with no loss in performance and possibly with performance improvements. As higher temperatures are considered for the power block, new working fluids, heat-transfer fluids (HTFs), and storage fluids will all need to be identified to meet these new operating conditions. Figure 1 shows thermodynamic conversion efficiency as a function of temperature for the ideal Carnot cycle and 75% Carnot, which is considered to be the practical efficiency attainable by current power cycles. Current conversion efficiencies for the parabolic trough steam cycle, power tower steam cycle, parabolic dish/Stirling, Ericsson, and air-Brayton/steam Rankine combined cycles are shown at their corresponding operating temperatures. Efficiencies for supercritical steam and carbon dioxide (CO{sub 2}) are also shown for their operating temperature ranges.

  20. fuel

    National Nuclear Security Administration (NNSA)

    4%2A en Cheaper catalyst may lower fuel costs for hydrogen-powered cars http:www.nnsa.energy.govblogcheaper-catalyst-may-lower-fuel-costs-hydrogen-powered-cars

  1. Modeling and cold start in alcohol-fueled engines

    SciTech Connect (OSTI)

    Markel, A.J.; Bailey, B.K.

    1998-05-01

    Neat alcohol fuels offer several benefits over conventional gasoline in automotive applications. However, their low vapor pressure and high heat of vaporization make it difficult to produce a flammable vapor composition from a neat alcohol fuel during a start under cold ambient conditions. Various methods have been introduced to compensate for this deficiency. In this study, the authors applied computer modeling and simulation to evaluate the potential of four cold-start technologies for engines fueled by near-neat alcohol. The four technologies were a rich combustor device, a partial oxidation reactor, a catalytic reformer, and an enhanced ignition system. The authors ranked the competing technologies by their ability to meet two primary criteria for cold starting an engine at {minus}25 deg C and also by several secondary parameters related to commercialization. Their analysis results suggest that of the four technologies evaluated, the enhanced ignition system is the best option for further development.

  2. Renewable Fuels Module of the National Energy Modeling System: Model Documentation 2013

    U.S. Energy Information Administration (EIA) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearby the(Dollars1.840 2.318 3.1195) Model8) Model Model

  3. TRISO-Fuel Element Performance Modeling for the Hybrid LIFE Engine with Pu Fuel Blanket

    SciTech Connect (OSTI)

    DeMange, P; Marian, J; Caro, M; Caro, A

    2010-02-18

    A TRISO-coated fuel thermo-mechanical performance study is performed for the hybrid LIFE engine to test the viability of TRISO particles to achieve ultra-high burnup of a weapons-grade Pu blanket. Our methodology includes full elastic anisotropy, time and temperature varying material properties for all TRISO layers, and a procedure to remap the elastic solutions in order to achieve fast fluences up to 30 x 10{sup 25} n {center_dot} m{sup -2} (E > 0.18 MeV). In order to model fast fluences in the range of {approx} 7 {approx} 30 x 10{sup 25} n {center_dot} m{sup -2}, for which no data exist, careful scalings and extrapolations of the known TRISO material properties are carried out under a number of potential scenarios. A number of findings can be extracted from our study. First, failure of the internal pyrolytic carbon (PyC) layer occurs within the first two months of operation. Then, the particles behave as BISO-coated particles, with the internal pressure being withstood directly by the SiC layer. Later, after 1.6 years, the remaining PyC crumbles due to void swelling and the fuel particle becomes a single-SiC-layer particle. Unrestrained by the PyC layers, and at the temperatures and fluences in the LIFE engine, the SiC layer maintains reasonably-low tensile stresses until the end-of-life. Second, the PyC creep constant, K, has a striking influence on the fuel performance of TRISO-coated particles, whose stresses scale almost inversely proportional to K. Obtaining more reliable measurements, especially at higher fluences, is an imperative for the fidelity of our models. Finally, varying the geometry of the TRISO-coated fuel particles results in little differences in the scope of fuel performance. The mechanical integrity of 2-cm graphite pebbles that act as fuel matrix has also been studied and it is concluded that they can reliable serve the entire LIFE burnup cycle without failure.

  4. Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles

    E-Print Network [OSTI]

    Zhao, Hengbing; Burke, Andy

    2008-01-01

    In the original fuel cell optimization model [11], only theIn the original fuel cell optimization model, only the dryof the fuel cell system and optimization of the operating

  5. fuel

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3446 YEAR/%2Afissile4/%2A en

  6. TRISO Fuel Performance: Modeling, Integration into Mainstream Design Studies, and Application to a Thorium-fueled Fusion-Fission Hybrid Blanket

    E-Print Network [OSTI]

    Powers, Jeffrey

    2011-01-01

    Quantification in Fuel Performance Modeling . . . . . . .3.4 Integration with Fuel Performance Calculations ivmicroscopic image of a TRISO fuel particle cracked open to

  7. Modeling the Effect of Fuel Ethanol Concentration on Cylinder Pressure Evolution in Direct-Injection Flex-Fuel Engines

    E-Print Network [OSTI]

    Stefanopoulou, Anna

    Modeling the Effect of Fuel Ethanol Concentration on Cylinder Pressure Evolution in Direct the fuel vaporization pro- cess for ethanol-gasoline fuel blends and the associated charge cooling effect experimental cylinder pressure for different gasoline-ethanol blends and various speeds and loads on a 2.0 L

  8. Renewable Fuels Module of the National Energy Modeling System: Model Documentation 2012

    U.S. Energy Information Administration (EIA) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearby the(Dollars1.840 2.318 3.1195) Model8) Model

  9. Modeling Cold Start in a Polymer-Electrolyte Fuel Cell

    E-Print Network [OSTI]

    Balliet, Ryan

    2010-01-01

    conditions used for fuel—cell simulations. 3.12 Values usedFuel Cells . . . . . . . . . . . . . . . . . . . . . . 1.1.1in Polymer Electrolyte Fuel Cells — II. Parametric Study,”

  10. Modeling Cold Start in a Polymer-Electrolyte Fuel Cell

    E-Print Network [OSTI]

    Balliet, Ryan

    2010-01-01

    conditions used for fuel—cell simulations. 3.12 Values usedin Polymer Electrolyte Fuel Cells — II. Parametric Study,”of Polymer Electrolyte Fuel Cells,” Electrochimica Acta, 53,

  11. MSU CAPITAL ASSET POLICY 1. CAPITALIZATION POLICY and USEFUL LIFE: MSU records as capital assets those

    E-Print Network [OSTI]

    Maxwell, Bruce D.

    , museum and related items not meeting the above criteria are capitalized at cost or our best estimateMSU CAPITAL ASSET POLICY 1. CAPITALIZATION POLICY and USEFUL LIFE: MSU records as capital assets those assets that meet its formal capitalization policy. The capitalization policy is as follows: TYPE

  12. Fuel

    SciTech Connect (OSTI)

    NONE

    1999-10-01

    Two subjects are covered in this section. They are: (1) Health effects of possible contamination at Paducah Gaseous Diffusion Plant to be studied; and (2) DOE agrees on test of MOX fuel in Canada.

  13. Fuel-Cycle Analysis of Hydrogen-Powered Fuel-Cell Systems with the GREET Model

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum12, 2015ExecutiveFluorescentDanKathy LoftusFuelDepartmentUnveiled

  14. EIA model documentation: Electricity market module - electricity fuel dispatch

    SciTech Connect (OSTI)

    1997-01-01

    This report documents the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM) as it was used for EIA`s Annual Energy Outlook 1997. It replaces previous documentation dated March 1994 and subsequent yearly update revisions. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This document serves four purposes. First, it is a reference document providing a detailed description of the model for reviewers and potential users of the EFD including energy experts at the Energy Information Administration (EIA), other Federal agencies, state energy agencies, private firms such as utilities and consulting firms, and non-profit groups such as consumer and environmental groups. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports. Third, it facilitates continuity in model development by providing documentation which details model enhancements that were undertaken for AE097 and since the previous documentation. Last, because the major use of the EFD is to develop forecasts, this documentation explains the calculations, major inputs and assumptions which were used to generate the AE097.

  15. Modeling and Control of High-Velocity Oxygen-Fuel (HVOF) Thermal Spray: A Tutorial Review

    E-Print Network [OSTI]

    Li, Mingheng; Christofides, Panagiotis D.

    2009-01-01

    Fluid Dynamics Analysis of a Wire- Feed, High-Velocity Oxygen Fuel (Fluid Dynamic Modeling of Gas Flow Charac- teristics in a High-Velocity Oxy-Fuel

  16. MA3T Model Application at ORNL Assesses the Future of Fuel Cell...

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

    Leveraging funding from the Fuel Cell Technologies Office, Oak Ridge National Lab (ORNL) has developed a model for simulating the market potential of fuel cell electric vehicles...

  17. The Effect of Energy Prices on Operation and Investment in OECD Countries: Evidence from the Vintage Capital Model

    E-Print Network [OSTI]

    Steinbuks, J.; Meshreky, A.; Neuhoff, Karsten

    by 2020. This analysis, however, excludes the rebound e¤ect27. To quantify the rebound e¤ect, we predict an increase in the share of energy service consumption Sji;t due to greenhouse tax induced improvements in energy e¢ ciency of capital stock (holding... other factors constant), and convert these changes in level terms. The rebound e¤ect is the di¤erence in price-induced energy consumption with and without adjustments for changes in share of energy service. Our calculations show a long-run rebound e...

  18. Chemical Kinetic Modeling of Fuels | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based Fuels|Programs |Chart of breakout of funds by major FSCCheckout,Fuels

  19. Integrating repositories with fuel cycles: The airport authority model

    SciTech Connect (OSTI)

    Forsberg, C. [Massachusetts Inst. of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139-4307 (United States)

    2012-07-01

    The organization of the fuel cycle is a legacy of World War II and the cold war. Fuel cycle facilities were developed and deployed without consideration of the waste management implications. This led to the fuel cycle model of a geological repository site with a single owner, a single function (disposal), and no other facilities on site. Recent studies indicate large economic, safety, repository performance, nonproliferation, and institutional incentives to collocate and integrate all back-end facilities. Site functions could include geological disposal of spent nuclear fuel (SNF) with the option for future retrievability, disposal of other wastes, reprocessing with fuel fabrication, radioisotope production, other facilities that generate significant radioactive wastes, SNF inspection (navy and commercial), and related services such as SNF safeguards equipment testing and training. This implies a site with multiple facilities with different owners sharing some facilities and using common facilities - the repository and SNF receiving. This requires a different repository site institutional structure. We propose development of repository site authorities modeled after airport authorities. Airport authorities manage airports with government-owned runways, collocated or shared public and private airline terminals, commercial and federal military facilities, aircraft maintenance bases, and related operations - all enabled and benefiting the high-value runway asset and access to it via taxi ways. With a repository site authority the high value asset is the repository. The SNF and HLW receiving and storage facilities (equivalent to the airport terminal) serve the repository, any future reprocessing plants, and others with needs for access to SNF and other wastes. Non-public special-built roadways and on-site rail lines (equivalent to taxi ways) connect facilities. Airport authorities are typically chartered by state governments and managed by commissions with members appointed by the state governor, county governments, and city governments. This structure (1) enables state and local governments to work together to maximize job and tax benefits to local communities and the state, (2) provides a mechanism to address local concerns such as airport noise, and (3) creates an institutional structure with large incentives to maximize the value of the common asset, the runway. A repository site authority would have a similar structure and be the local interface to any national waste management authority. (authors)

  20. Short-Term Energy Outlook Model Documentation: Electricity Generation and Fuel Consumption Models

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7, 2013 MEMORANDUM Model

  1. Capital Reporting Company Quadrennial ...

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

    3 05-27-2014 (866) 448 - DEPO www.CapitalReportingCompany.com 2014 1 QUADRENNIAL ENERGY REVIEW STAKEHOLDER MEETING 3 PETROLEUM TRANSMISSION, STORAGE AND DISTRIBUTION ISSUES...

  2. Capital Reporting Company Quadrennial ...

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

    - DEPO www.CapitalReportingCompany.com 2014 1 UNITED STATE OF AMERICA DEPARTMENT OF ENERGY ---: : IN RE: : : QUADRENNIAL ENERGY REVIEW : : NEW...

  3. Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles

    E-Print Network [OSTI]

    Zhao, Hengbing; Burke, Andy

    2008-01-01

    H. Peng, Control of Fuel Cell Power Systems, Springer, 2004an arbitrary size (power) fuel cell. Finally, the model ison the rated fuel cell stack power. The rated stack power is

  4. Fire Behavior Modeling - Experiment on Surface Fire Transition to the Elevated Live Fuel

    E-Print Network [OSTI]

    Omodan, Sunday

    2015-01-01

    of FDS to recognize two fuels of different materials in theFire Behavior Prediction and Fuel Modeling System, BURN -K.P. Combustion of forest fuels in Forest Fire: Control and

  5. Modeling Cold Start in a Polymer-Electrolyte Fuel Cell

    E-Print Network [OSTI]

    Balliet, Ryan

    2010-01-01

    Polymer Electrolyte Fuel Cell Cross—Section Below Freezingstart—up of a fuel cell from below freezing. Because waterFreezing in a Polymer—Electrolyte—Membrane Fuel Cell,” ECS

  6. Modeling Water Management in Polymer-Electrolyte Fuel Cells

    E-Print Network [OSTI]

    Weber, Adam; Department of Chemical Engineering, University of California, Berkeley

    2008-01-01

    Newman, in Advances in Fuel Cells, Vol. 1, T. S. Zhao, K. -A. Uribe and B. S. Pivovar, Fuel Cells, 7, 153 (2007). R. C.and S. Srinivasan, Fuel Cells: Their Electrochemistry,

  7. Renewable Fuel Vehicle Modeling and Analysis | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankADVANCED MANUFACTURINGEnergy BillsNo. 195 - Oct. 7,DOERTIRegulatoryResidentialRenewable Fuel Vehicle

  8. Advancement in Fuel Spray and Combustion Modeling for Compression Ignition

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based Fuels Research at NREL Advanced PetroleumDepartment|Department

  9. Alternative Fuels Data Center: Clean Cities Helps National Parks Model

    Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

  10. CONTROL-ORIENTED MODELING OF A SOLID-OXIDE FUEL CELL STACK USING AN LPV MODEL STRUCTURE

    E-Print Network [OSTI]

    Sanandaji, Borhan M.

    CONTROL-ORIENTED MODELING OF A SOLID-OXIDE FUEL CELL STACK USING AN LPV MODEL STRUCTURE Borhan M. Sanandaji, Tyrone L. Vincent, Andrew Colclasure, and Robert J. Kee Colorado Fuel Cell Center Engineering dynamic model of a solid oxide fuel cell stack. Using a detailed physical model as a starting point, we

  11. DOE Announces Webinars on Sandia Modeling Tool, Hydrogen Fueling...

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

    Register to attend the webinar. September 11: Live Webinar on Introduction to SAE Hydrogen Fueling Standardization Webinar Sponsors: Fuel Cell Technologies Office The...

  12. Aalborg Universitet Modeling of large-scale oxy-fuel combustion processes

    E-Print Network [OSTI]

    Yin, Chungen

    implementation into CFD simulations of various oxy- fuel combustion processes and experimental validation. Result-fuel flames (Yin et al., 2010). · Various combustion mechanisms implemented in CFD of oxy-fuel combustion of gray gases model applicable to CFD modeling of oxy-fuel combustion: Derivation, validation

  13. MATHEMATICAL MODELING OF CHANNEL POROUS LAYER INTERFACES IN PEM FUEL CELLS

    E-Print Network [OSTI]

    Ehrhardt, Matthias

    MATHEMATICAL MODELING OF CHANNEL ­ POROUS LAYER INTERFACES IN PEM FUEL CELLS M. EHRHARDT, J, Germany ABSTRACT In proton exchange membrane (PEM) fuel cells, the transport of the fuel to the active diffusion layers. In order to improve existing mathematical and numerical models of PEM fuel cells, a deeper

  14. Sensitivity of economic performance of the nuclear fuel cycle to simulation modeling assumptions

    E-Print Network [OSTI]

    Bonnet, Nicéphore

    2007-01-01

    Comparing different nuclear fuel cycles and assessing their implications require a fuel cycle simulation model as complete and realistic as possible. In this thesis, methodological implications of modeling choices are ...

  15. KINETIC MODELING OF FUEL EFFECTS OVER A WIDE RANGE OF CHEMISTRY...

    Office of Scientific and Technical Information (OSTI)

    KINETIC MODELING OF FUEL EFFECTS OVER A WIDE RANGE OF CHEMISTRY, PROPERTIES, AND SOURCES Citation Details In-Document Search Title: KINETIC MODELING OF FUEL EFFECTS OVER A WIDE...

  16. Connecticut Fuel Cell Activities: Markets, Programs, and Models

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based Fuels|ProgramsLake Paiute ReservationResourcesMarch2 DOE1 Connecticut Fuel

  17. CAPITAL ASSET DOCUMENT TRAINING

    E-Print Network [OSTI]

    KUALI CAPITAL ASSET MANAGEMENT DOCUMENT TRAINING Business and Financial Services, Property Definitions of Asset Management roles What is a CAM Processor and why do we designate that authority? Department Property Contact role What is a movable capital asset? #12;Property Management We are here

  18. Water Transport in PEM Fuel Cells: Advanced Modeling, Material Selection,

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on DeliciousMathematics And Statistics » USAJobs SearchAMERICA'S FUTURE.Projects at ArmyusingPeerTesting and Design

  19. Water Transport in PEM Fuel Cells: Advanced Modeling, Material Selection,

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on DeliciousMathematics And Statistics » USAJobs SearchAMERICA'S FUTURE.Projects at ArmyusingPeerTesting and

  20. Computer Modeling Illuminates Degradation Pathways of Cations in Alkaline Membrane Fuel Cells (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2012-08-01

    Cation degradation insights obtained by computational modeling could result in better performance and longer lifetime for alkaline membrane fuel cells.

  1. MODELING THE PERFORMANCE OF HIGH BURNUP THORIA AND URANIA PWR FUEL

    E-Print Network [OSTI]

    Long, Y.

    Fuel performance models have been developed to assess the performance of ThO[subscript 2]-UO[subscript 2]

  2. Advanced Fuel Performance: Modeling and Simulation Light Water Reactor Fuel Performance:

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room News Publications Traditional Knowledge KiosksAboutHelp & Reference UsersAdvanced 63 No. 8

  3. MicroScale Modeling of an AnodeSupported Planar Solid Oxide Fuel Cell

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Micro­Scale Modeling of an Anode­Supported Planar Solid Oxide Fuel Cell P. Chinda1 , W. Wechsatol A micro ­ scale model of a Solid Oxide Fuel Cell (SOFC) involving the mass transfer together the available literatures. Keywords: Solid Oxide Fuel Cells, Micro ­ Scale Model, Mass Transfer, Electrochemical

  4. Aalborg Universitet Thermal modeling and temperature control of a PEM fuel cell system for forklift

    E-Print Network [OSTI]

    Berning, Torsten

    Aalborg Universitet Thermal modeling and temperature control of a PEM fuel cell system for forklift., & Mortensen, H. H. (2014). Thermal modeling and temperature control of a PEM fuel cell system for forklift.aau.dk on: juli 07, 2015 #12;Thermal modeling and temperature control of a PEM fuel cell system for forklift

  5. DOE Announces Webinars on Sandia Modeling Tool, Hydrogen Fueling

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergy Webinar:IAbout Us »Buildings Resource, and MoreBiomass

  6. Lessons Learned from Alternative Transportation Fuels: Modeling Transition Dynamics

    Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

  7. Validation of an Integrated System for a Hydrogen-Fueled Power Park

    E-Print Network [OSTI]

    simulation ­ Efficiency ­ Waste heat availability Develop cost of operation models ­ Capital ­ Fuel costs reformer with equal loads All waste heat can be utilized 3-5 kW commercially available PEM fuel cells Heat and Power Has the Potential to Lower Power Cost by ~$0.01/kWh · CHP Requires Reformer and Fuel

  8. An economic feasibility analysis of distributed electric power generation based upon the natural gas-fired fuel cell: a model of a central utility plant.

    SciTech Connect (OSTI)

    Not Available

    1993-06-30

    This central utilities plant model details the major elements of a central utilities plant for several classes of users. The model enables the analyst to select optional, cost effective, plant features that are appropriate to a fuel cell application. These features permit the future plant owner to exploit all of the energy produced by the fuel cell, thereby reducing the total cost of ownership. The model further affords the analyst an opportunity to identify avoided costs of the fuel cell-based power plant. This definition establishes the performance and capacity information, appropriate to the class of user, to support the capital cost model and the feasibility analysis. It is detailed only to the depth required to identify the major elements of a fuel cell-based system. The model permits the choice of system features that would be suitable for a large condominium complex or a residential institution such as a hotel, boarding school or prison. The user may also select large office buildings that are characterized by 12 to 16 hours per day of operation or industrial users with a steady demand for thermal and electrical energy around the clock.

  9. Modeling Cold Start in a Polymer-Electrolyte Fuel Cell

    E-Print Network [OSTI]

    Balliet, Ryan

    2010-01-01

    Boundary conditions used for fuel—cell simulations. 3.12to the Problem of Cold Start 1.1 Polymer—Electrolyte Fuelin Polymer Electrolyte Fuel Cells — II. Parametric Study,”

  10. Mesoscale Modeling of Fuel Swelling and Restructuring: Coupling

    Office of Scientific and Technical Information (OSTI)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfate Reducing(JournalspectroscopyReport) | SciTechelement methodbyoxide embeddedtwo

  11. Mesoscale modeling of fuel restructuring. (Conference) | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfate Reducing(JournalspectroscopyReport) | SciTechelement methodbyoxide

  12. Development of custom fire behavior fuel models from FCCS fuelbeds for the Savannah River fuel assessment project.

    SciTech Connect (OSTI)

    Scott, Joe, H.

    2009-07-23

    The purpose of this project is to create fire behavior fuel models that replicate the fire behavior characteristics (spread rate and fireline intensity) produced by 23 candidate FCCS fuelbeds developed for the Savannah River National Wildlife Refuge. These 23 fuelbeds were created by FERA staff in consultation with local fuel managers. The FCCS produces simulations of surface fire spread rate and flame length (and therefore fireline intensity) for each of these fuelbeds, but it does not produce maps of those fire behavior characteristics or simulate fire growth—those tasks currently require the use of the FARSITE and/or FlamMap software systems. FARSITE and FlamMap do not directly use FCCS fuelbeds, but instead use standard or custom fire behavior fuel models to describe surface fuel characteristics for fire modeling. Therefore, replicating fire growth and fire behavior potential calculations using FCCS?simulated fire characteristics requires the development of custom fuel models that mimic, as closely as possible, the fire behavior characteristics produced by the FCCS for each fuelbed, over a range of fuel moisture and wind speeds.

  13. VISION Model for Vehicle Technologies and Alternative Fuels | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Information Serbia-EnhancingEt Al.,Turin, New York:PowerNewPumatyUvalde County, Texas:EnergyVELOcar

  14. Fuel Cell Power (FCPower) Model | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History View New PagesSustainable Urban TransportFortistar LLCNorthIdaho:FroniusFruitdale,FryeBio OnePower

  15. Connecticut Fuel Cell Activities: Markets, Programs, and Models |

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative FuelsofProgram:Y-12Power,5Energy Works' SuccessOil, and GasWorking

  16. Supercomputers Fuel Global High-Resolution Climate Models

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired Solar Fuel Production 1: Total systemsSuccess

  17. Used Fuel Degradation: Experimental and Modeling Report | Department of

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LIST OF APPLICABLEStatutoryin theNuclear EnergyPotomacCool RoofDepartment ofEnergy

  18. Recent Advances in Detailed Chemical Kinetic Models for Large Hydrocarbon and Biodiesel Transportation Fuels

    SciTech Connect (OSTI)

    Westbrook, C K; Pitz, W J; Curran, H J; Herbinet, O; Mehl, M

    2009-03-30

    n-Hexadecane and 2,2,4,4,6,8,8-heptamethylnonane represent the primary reference fuels for diesel that are used to determine cetane number, a measure of the ignition property of diesel fuel. With the development of chemical kinetics models for these two primary reference fuels for diesel, a new capability is now available to model diesel fuel ignition. Also, we have developed chemical kinetic models for a whole series of large n-alkanes and a large iso-alkane to represent these chemical classes in fuel surrogates for conventional and future fuels. Methyl decanoate and methyl stearate are large methyl esters that are closely related to biodiesel fuels, and kinetic models for these molecules have also been developed. These chemical kinetic models are used to predict the effect of the fuel molecule size and structure on ignition characteristics under conditions found in internal combustion engines.

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  20. Recent advances in single-chamber fuel-cells: Experiment and modeling , Zongping Shao b

    E-Print Network [OSTI]

    Haile, Sossina M.

    Recent advances in single-chamber fuel-cells: Experiment and modeling Yong Hao a , Zongping Shao b; accepted 6 May 2006 Abstract Single-chamber fuel cells (SCFC) are ones in which the fuel and oxidizer is discussed. © 2006 Elsevier B.V. All rights reserved. Keywords: Solid oxide fuel cell; Single chamber

  1. Capital Reporting Company Quadrenntial ...

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

    Quadrenntial Energy Review 04-21-2014 (866) 448 - DEPO www.CapitalReportingCompany.com 2014 1 NEW ENGLAND REGIONAL INFRASTRUCTURE CONSTRAINTS A Public Meeting on the Quadrennial...

  2. Capital Reporting Company Quadrennial ...

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

    07-21-2014 (866) 448 - DEPO www.CapitalReportingCompany.com 2014 1 QUADRENNIAL ENERGY REVIEW PUBLIC MEETING 6 MONDAY, JULY 21, 2014 HELD AT: RASHID AUDITORIUM-HILLMAN CENTER...

  3. Capital Reporting Company Quadrennial ...

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

    11-2014 (866) 448 - DEPO www.CapitalReportingCompany.com 2014 1 QUADRENNIAL ENERGY REVIEW PUBLIC MEETING 10: Infrastructure Constraints Monday, August 11, 2014 New Mexico State...

  4. Understanding Global Capitalism

    E-Print Network [OSTI]

    Robinson, William I.

    2008-01-01

    where-have-you, and they buy Lula panicked and said “well,on the basis it wasn’t that Lula and his faction of of thethat it could pressure Lula because transnational capital

  5. A Planar Anode -Supported Solid Oxide Fuel Cell Model with Internal Reforming of Natural Gas

    E-Print Network [OSTI]

    Boyer, Edmond

    1 A Planar Anode - Supported Solid Oxide Fuel Cell Model with Internal Reforming of Natural Gas.brault@univ-orleans.fr Abstract Solid Oxide Fuel Cells (SOFCs) are of great interest due to their high energy efficiency, low, a mathematical model of a co - flow planar anode - supported solid oxide fuel cell with internal reforming

  6. Analysis of Molten Carbonate Fuel Cell Performance Using a Three-Phase Homogeneous Model

    E-Print Network [OSTI]

    Popov, Branko N.

    Analysis of Molten Carbonate Fuel Cell Performance Using a Three-Phase Homogeneous Model N-phase homogeneous model was developed to simulate the performance of the molten carbonate fuel cell MCFC cathode received June 18, 2002. Available electronically November 15, 2002. Molten carbonate fuel cells MCFCs

  7. P0906-090-Chnani Macroscopic Model of Solid Oxide Fuel Cell Stack for

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 P0906-090-Chnani Macroscopic Model of Solid Oxide Fuel Cell Stack for Integrating in a Generator fuel cell (SOFC) with the aim to perform a simulation of the whole generator. Three sub-models have at the catalytic sites and gas flows at fuel cell input and output. The electrical response is based

  8. A non-isothermal PEM fuel cell model including two water transport mechanisms in the

    E-Print Network [OSTI]

    Münster, Westfälische Wilhelms-Universität

    A non-isothermal PEM fuel cell model including two water transport mechanisms in the membrane K Freiburg Germany A dynamic two-phase flow model for proton exchange mem- brane (PEM) fuel cells and the species concentrations. In order to describe the charge transport in the fuel cell the Poisson equations

  9. Liquid Water Dynamics in a Model Polymer Electrolyte Fuel Cell Flow Channel

    E-Print Network [OSTI]

    Victoria, University of

    Liquid Water Dynamics in a Model Polymer Electrolyte Fuel Cell Flow Channel by Chris Miller in a Model Polymer Electrolyte Fuel Cell Flow Channel by Chris Miller Bachelors of Engineering, University in a polymer electrolyte fuel cell is a critical issue in ensuring high cell performance. The water production

  10. A NEW APPROACH TO MODELING LARGE-SCALE ALTERNATIVE FUEL AND VEHICLE TRANSITIONS

    E-Print Network [OSTI]

    Lin, C.-Y. Cynthia

    counter-intuitive dynamic: high energy prices can discourage wide scale adoption of alternative fueled 1 A NEW APPROACH TO MODELING LARGE-SCALE ALTERNATIVE FUEL AND VEHICLE TRANSITIONS by Joel to alternative fuels and vehicles will be challenging. New modeling approaches are necessary to supplement

  11. Aalborg Universitet Development of a 400 W High Temperature PEM Fuel Cell Power Pack -Modelling and

    E-Print Network [OSTI]

    Berning, Torsten

    Aalborg Universitet Development of a 400 W High Temperature PEM Fuel Cell Power Pack - Modelling., Korsgaard, A., Nielsen, M. P., & Kær, S. K. (2006). Development of a 400 W High Temperature PEM Fuel Cell Power Pack - Modelling and System Control. Poster session presented at Fuel Cell Seminar 2006 Conference

  12. Aalborg Universitet Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data and

    E-Print Network [OSTI]

    Berning, Torsten

    Aalborg Universitet Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data Reza Published in: Journal of Fuel Cell Science and Technology DOI (link to publication from Publisher. K., Andreasen, S. J., & Shaker, H. R. (2014). Dynamic Modeling of a Reformed Methanol Fuel Cell

  13. GENERAL TECHNICAL REPORT PSW-GTR-245 Fuel Load Modeling From Mensuration

    E-Print Network [OSTI]

    of this study was to model a dead fuel load based on forest mensuration attributes from forest management from management programs are an efficient and low-cost alternative for estimating forest fuel loadsGENERAL TECHNICAL REPORT PSW-GTR-245 274 Fuel Load Modeling From Mensuration Attributes

  14. Thermo-chemical Modelling of Uranium-free Nitride Fuels Mikael JOLKKONEN1;;y

    E-Print Network [OSTI]

    Haviland, David

    be applied to modelling of oxide and carbide fuels as well. In this paper we give a brief introductionThermo-chemical Modelling of Uranium-free Nitride Fuels Mikael JOLKKONEN1;Ã;y , Marco STREIT2 and accepted December 22, 2003) A production process for americium-bearing, uranium-free nitride fuels

  15. Aalborg Universitet Modelling and Validation of Water Hydration of PEM Fuel Cell Membrane in Dynamic

    E-Print Network [OSTI]

    Liso, Vincenzo

    Aalborg Universitet Modelling and Validation of Water Hydration of PEM Fuel Cell Membrane of Water Hydration of PEM Fuel Cell Membrane in Dynamic Operations. In ECS Transactions. (Vol. 68). ECS from vbn.aau.dk on: november 29, 2015 #12;Modelling and Validation of Water Hydration of PEM Fuel Cell

  16. Model of the Air System Transients in a Fuel Cell Vehicle

    E-Print Network [OSTI]

    Kochersberger, Kevin

    Model of the Air System Transients in a Fuel Cell Vehicle by John P. Bird Thesis submitted W. Ellis January 30, 2002 Blacksburg, Virginia Keywords: Fuel Cell, System Modeling, Simulation, Fuel Cell Vehicle #12;1 Abstract This thesis describes a procedure to measure the transient effects

  17. Greentech Capital Advisors GCA | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History View New PagesSustainableGlynn County,Solar Jump to: navigation,Capital Advisors GCA Jump to:

  18. Long Branch Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History View NewTexas:Montezuma, Arizona:Oregon: EnergyLloyd, NewBranch Capital Jump to: navigation, search

  19. Jane Capital Partners | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History View NewTexas: Energy ResourcesOrder at 8,OpenKentucky: EnergyFacility |Jane Capital Partners Jump

  20. Eco Drive Capital Partners | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar2-0057-EA Jump to:of the NationalDynetek EuropeEPG|ElecSolutions JumpCapital

  1. Black Coral Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar Energy LLC JumpBiossence Jump to: navigation, searchBirahi GangaCoral Capital

  2. Capital Electric Coop, Inc | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar Energy LLC JumpBiossenceBrunswick,CalendarFork ElectricCapara EnergiaCapital

  3. Chestnut Capital LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar Energy LLCLtd Jump to:Changing World TechnologiesChartsCapital LLC Jump to:

  4. Ambata Capital Partners | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar Energy LLC Jump to: navigation, search Name:Ambata Capital Partners Jump to:

  5. Sequoia Capital Ltda | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop Inc Jump to:Newberg,EnergyEastCarbonOpenSchulthessENDA ProjectsCapital Ltda Jump

  6. Solution Capital Partners | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop Inc JumpHeter BatterySolarfin Jump to:Solkar Solar Industry LtdSolution Capital

  7. Strategic Capital Investments LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop Inc JumpHeter BatterySolarfinMarket Studies JumpSteinbineCycles IncCapital

  8. Sustainable Development Capital LLP | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS ReportEuropeEnergySustainability Center of the Rockies JumpCapital

  9. Ethanol Capital Funding | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButtePowerEdisto Electric Coop,Erosion Flume Jump to:Ethanol Capital Funding Jump

  10. Ethanol Capital Management | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButtePowerEdisto Electric Coop,Erosion Flume Jump to:Ethanol Capital Funding

  11. Hereford Capital Advisors | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsource History View NewGuam: Energyarea, California |Sysop deletingHereford Capital

  12. MVP Capital Partners | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsource HistoryScenarios Towards 2050Enermar <OMISPowerTurbine forMHKMP2MSEMVP Capital

  13. Mont Vista Capital LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsourceII Jump to: navigation, searchsource History ViewMoe WindJump to:Vista Capital LLC

  14. Carbon Credit Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButte County,Camilla, Georgia: Energy ResourcesRanch Jump to:Capital Jump to:

  15. New Energy Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsourceII Jump to: navigation,National MarineUSAIDCanaan, Connecticut:New EarthCapital

  16. CASL-U-2015-0015-000 Modeling Integral Fuel

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room News PublicationsAudits &Bradbury Science Museum6 Shares CraigUser Guidelines

  17. A Statistical Model of Vehicle Emissions and Fuel Consumption

    E-Print Network [OSTI]

    Cappiello, Alessandra

    2002-09-17

    A number of vehicle emission models are overly simple, such as static speed-dependent models widely used in

  18. Modeling the transient operation of an endothermic fuel cooling system for high Mach number vehicle missions 

    E-Print Network [OSTI]

    Williams, Mark Robert

    1993-01-01

    A computer model was developed to simulate the transient operation of a hypothetical endothermic fuel cooling system. The model simulated the performance of a cross-flow, shell and tube heat exchanger. This model was applied to a representative...

  19. Fundamental Models for Fuel Cell Engineering Chao-Yang Wang*

    E-Print Network [OSTI]

    Cell Dynamics Fuel cell science and technology cuts across mul- tiple disciplines, including materials and Materials Science and Engineering, Electrochemical Engine Center (ECEC), The Pennsylvania State University and Parallel Computing 4730 2.3. Material Property Characterization 4730 3. Polymer Electrolyte Fuel Cells 4732

  20. Mapping surface fuel models using lidar and multispectral data fusion for fire behavior

    E-Print Network [OSTI]

    ) producing spatially explicit digital fuel maps. Estimates of fuel models were compared with in-situ data to improve the overall accuracy of image classification. Supervised image classification methods provided

  1. Mapping surface fuels using LIDAR and multispectral data fusion for fire behavior modeling 

    E-Print Network [OSTI]

    Mutlu, Muge

    2009-05-15

    Fires have become intense and more frequent in the United States. Improving the accuracy of mapping fuel models is essential for fuel management decisions and explicit fire behavior prediction for real-time support of suppression tactics...

  2. An integrated performance model for high temperature gas cooled reactor coated particle fuel

    E-Print Network [OSTI]

    Wang, Jing, 1976-

    2004-01-01

    The performance of coated fuel particles is essential for the development and deployment of High Temperature Gas Reactor (HTGR) systems for future power generation. Fuel performance modeling is indispensable for understanding ...

  3. Fact #624: May 24, 2010 Corporate Average Fuel Economy Standards, Model Years 2012-2016

    Broader source: Energy.gov [DOE]

    The final rule for the Corporate Average Fuel Economy (CAFE) Standards was published in March 2010. Under this rule, each light vehicle model produced for sale in the United States will have a fuel...

  4. Webinar: DOE Updates JOBS and Economic Impacts of Fuel Cells (JOBS FC1.1) Model

    Broader source: Energy.gov [DOE]

    Video recording of the Fuel Cell Technologies Office webinar, DOE Updates JOBS and Economic Impacts of Fuel Cells (JOBS FC1.1) Model, originally presented on December 11, 2012.

  5. Determination of the proper operating range for the CAFCA IIB fuel cycle model

    E-Print Network [OSTI]

    Warburton, Jamie (Jamie L.)

    2007-01-01

    The fuel cycle simulation tool, CAFCA II was previously modified to produce the most recent version, CAFCA IIB. The code tracks the mass distribution of transuranics in the fuel cycle in one model and also projects costs ...

  6. Liquid Fuels Market Model of the National Energy Modeling System: Model Documentation 2013

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr 2012 2013 2014Thousand343DecadeFeet) Decade

  7. Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests.

    SciTech Connect (OSTI)

    Parresol, Bernard, R.; Scott, Joe, H.; Andreu, Anne; Prichard, Susan; Kurth, Laurie

    2012-01-01

    Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or thousands of measured surface fuelbeds representing the fine scale variation in fire behavior on the landscape is constrained in terms of creating compatible custom fire behavior fuel models. In this study, we demonstrate an objective method for taking ecologically complex fuelbeds from inventory observations and converting those into a set of custom fuel models that can be mapped to the original landscape. We use an original set of 629 fuel inventory plots measured on an 80,000 ha contiguous landscape in the upper Atlantic Coastal Plain of the southeastern United States. From models linking stand conditions to component fuel loads, we impute fuelbeds for over 6000 stands. These imputed fuelbeds were then converted to fire behavior parameters under extreme fuel moisture and wind conditions (97th percentile) using the fuel characteristic classification system (FCCS) to estimate surface fire rate of spread, surface fire flame length, shrub layer reaction intensity (heat load), non-woody layer reaction intensity, woody layer reaction intensity, and litter-lichen-moss layer reaction intensity. We performed hierarchical cluster analysis of the stands based on the values of the fire behavior parameters. The resulting 7 clusters were the basis for the development of 7 custom fire behavior fuel models from the cluster centroids that were calibrated against the FCCS point data for wind and fuel moisture. The latter process resulted in calibration against flame length as it was difficult to obtain a simultaneous calibration against both rate of spread and flame length. The clusters based on FCCS fire behavior parameters represent reasonably identifiable stand conditions, being: (1) pine dominated stands with more litter and down woody debriscomponents than other stands, (2) hardwood and pine stands with no shrubs, (3) hardwood dominated stands with low shrub and high non-woody biomass and high down woody debris, (4) stands with high grass and forb (i.e., non-woody) biomass as well as substantial shrub biomass, (5) stands with both high shrub and litter biomass, (6) pine-mixed hardwood stands with moderate litter biomass and low shrub biomass, and (7) baldcypress-tupelo stands. Models representing these stand clusters generated flame lengths from 0.6 to 2.3 musing a 30 km h{sub 1} wind speed and fireline intensities of 100-1500 kW m{sub 1} that are typical within the range of experience on this landscape. The fuel models ranked 1 < 2 < 7 < 5 < 4 < 3 < 6 in terms of both flame length and fireline intensity. The method allows for ecologically complex data to be utilized in order to create a landscape representative of measured fuel conditions and to create models that interface with geospatial fire models.

  8. A Three-Dimensional Computational Model of PEM Fuel Cell with Serpentine Gas Channels

    E-Print Network [OSTI]

    Victoria, University of

    A Three-Dimensional Computational Model of PEM Fuel Cell with Serpentine Gas Channels by Phong ABSTRACT A three-dimensional computational fluid dynamics model of a Polymer Electrolyte Membrane (PEM) fuel cell with serpentine gas flow channels is presented in this thesis. This comprehensive model

  9. Analytical model for transient gas flow in nuclear fuel rods. [PWR; BWR

    SciTech Connect (OSTI)

    Rowe, D.S.; Oehlberg, R.N.

    1981-08-01

    An analytical model for calculating gas flow and pressure inside a nuclear fuel rod is presented. Such a model is required to calculate the pressure loading of cladding during ballooning that could occur for postulated reactor accidents. The mathematical model uses a porous media (permeability) concept to define the resistance to gas flow along the fuel rod. 7 refs.

  10. Model documentation: Renewable Fuels Module of the National Energy Modeling System

    SciTech Connect (OSTI)

    Not Available

    1994-04-01

    This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it related to the production of the 1994 Annual Energy Outlook (AEO94) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves two purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. Of these six, four are documented in the following chapters: municipal solid waste, wind, solar and biofuels. Geothermal and wood are not currently working components of NEMS. The purpose of the RFM is to define the technological and cost characteristics of renewable energy technologies, and to pass these characteristics to other NEMS modules for the determination of mid-term forecasted renewable energy demand.

  11. Far-field dispersal modeling for fuel-air-explosive devices

    SciTech Connect (OSTI)

    Glass, M.W.

    1990-05-01

    A computer model for simulating the explosive dispersal of a fuel agent in the far-field regime is described and is applied to a wide variety of initial conditions to judge their effect upon the resulting fuel/air cloud. This work was directed toward modeling the dispersal process associated with Fuel-Air-Explosives devices. The far-field dispersal regime is taken to be that time after the initial burster charge detonation in which the shock forces no longer dominate the flow field and initial canister and fuel mass breakup has occurred. The model was applied to a low vapor pressure fuel, a high vapor pressure fuel and a solid fuel. A strong dependence of the final cloud characteristics upon the initial droplet size distribution was demonstrated. The predicted fuel-air clouds were highly non-uniform in concentration. 18 refs., 86 figs., 4 tabs.

  12. Capital Equipment Validation Form | The Ames Laboratory

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B LReports from the CloudGEGR-NOperatorsCan'tPower | ArgonneCapital

  13. Working Capital for Contractors | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal Gas &SCE-Sessions |discussed how saving energy5 Worker Righs, Issue 2 Working Capital for

  14. Demonstrating Fuel Consumption and Emissions Reductions with Next Generation Model-Based Diesel Engine Control

    Office of Energy Efficiency and Renewable Energy (EERE)

    Presents a next generation model-based engine controller that incorporates real-time fuel efficiency optimization and tested under fully transient engine and vehicle operating conditions.

  15. Fuel Cell Power Model for CHHP System Economics and Performance Analysis (Presentation)

    SciTech Connect (OSTI)

    Steward, D.

    2009-11-16

    Presentation about Fuel Cell Power (FCPower) Model used to analyze the economics and performance of combined heat, hydrogen, and power (CHHP) systems.

  16. Heavy Duty Diesel Particulate Matter and Fuel Consumption Modeling for Transportation Analysis

    E-Print Network [OSTI]

    Scora, George Alexander

    2011-01-01

    Model for Heavy Duty Diesel Vehicles. TransportationAir Contaminant Emissions from Diesel- fueled Engines. Factfor Measuring Emissions from Diesel Engines. 1. Regulated

  17. Webinar: DOE Launches JOBS and Economic Impacts of Fuel Cells (JOBS FC) Analysis Model

    Broader source: Energy.gov [DOE]

    Video recording and text version of the webinar titled, DOE Launches JOBS and Economic Impacts of Fuel Cells (JOBS FC) Analysis Model, originally presented on May 22, 2012.

  18. CO2e Capital Limited | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButte County, California: Energy Resources JumpEmissionCapitalCMEA CapitalTech

  19. MODELING AND CONTROL OF A HIGH PRESSURE COMBINED AIR/FUEL INJECTION SYSTEM

    E-Print Network [OSTI]

    Barth, Eric J.

    MODELING AND CONTROL OF A HIGH PRESSURE COMBINED AIR/FUEL INJECTION SYSTEM Chao Yong Eric J. Barth.j.barth@vanderbilt.edu ABSTRACT A high pressure combined air-fuel injection system is designed and tested for an experimental free the compressor's reservoir, and high pressure fuel to mix and then inject into a combustion chamber. This paper

  20. MODELING THE EFFECT OF FLOW FIELD DESIGN ON PEM FUEL CELL PERFORMANCE

    E-Print Network [OSTI]

    Van Zee, John W.

    and transportation applications. One aspect that is crucial to optimizing the performance of PEM fuel cellsMODELING THE EFFECT OF FLOW FIELD DESIGN ON PEM FUEL CELL PERFORMANCE Jeffrey Glandt, Sirivatch Shimpalee, Woo-kum Lee, and John W. Van Zee Fuel Cell Research Laboratory Department of Chemical Engineering

  1. Water Transport in PEM Fuel Cells: Advanced Modeling, Material Selection, Testing,

    E-Print Network [OSTI]

    Optimization J. Vernon Cole and Ashok Gidwani CFDRC Prepared for: DOE Hydrogen Fuel Cell Kickoff MeetingWater Transport in PEM Fuel Cells: Advanced Modeling, Material Selection, Testing, and Design fuel cell design and operation; Demonstrate improvements in water management resulting in improved

  2. Designing a Component-Based Architecture for the Modeling and Simulation of Nuclear Fuels and Reactors

    E-Print Network [OSTI]

    Pennycook, Steve

    interest in nuclear energy in the U. S. Applications for 26 new reactors have been sub- mitted to the U. S. The NEAMS program is organized around four technical areas of the nuclear fuel cycle: fuels, reactorsDesigning a Component-Based Architecture for the Modeling and Simulation of Nuclear Fuels

  3. CONTROL-ORIENTED MODELING AND ANALYSIS FOR AUTOMOTIVE FUEL CELL SYSTEMS

    E-Print Network [OSTI]

    Peng, Huei

    CONTROL-ORIENTED MODELING AND ANALYSIS FOR AUTOMOTIVE FUEL CELL SYSTEMS Jay T. Pukrushpan Huei Peng of Michigan Ann Arbor, Michigan 48109-2125 Email: pukrushp@umich.edu Abstract Fuel Cells are electrochemical regarded as a potential future stationary and mobile power source. The response of a fuel cell system

  4. Performance modeling and cell design for high concentration methanol fuel cells

    E-Print Network [OSTI]

    Chapter 50 Performance modeling and cell design for high concentration methanol fuel cells C. E The direct methanol fuel cell (DMFC) has become a lead- ing contender to replace the lithium-ion (Li density of liquid methanol (CH3OH) fuel is 4800 Wh l-1 , whereas the theoretical energy density of Li

  5. Aalborg Universitet Modeling of a HTPEM Fuel Cell using Adaptive NeuroFuzzy Inference Systems

    E-Print Network [OSTI]

    Berning, Torsten

    Aalborg Universitet Modeling of a HTPEM Fuel Cell using Adaptive NeuroFuzzy Inference Systems of a HTPEM Fuel Cell using Adaptive Neuro Fuzzy Inference Systems. Poster session presented at 4th CARISMA from vbn.aau.dk on: juli 05, 2015 #12;Introduction HTPEM fuel cells can with great benefit be used

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

    E-Print Network [OSTI]

    Stefanopoulou, Anna

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

  7. Phase-field modeling of three-phase electrode microstructures in solid oxide fuel cells

    E-Print Network [OSTI]

    Chen, Long-Qing

    Phase-field modeling of three-phase electrode microstructures in solid oxide fuel cells Qun Li, mechanical deformation, and heterogeneous damage accumulation in solid oxide fuel cell anodes J. Appl. Phys oxide fuel cell/gas turbine cycle J. Renewable Sustainable Energy 4, 043115 (2012) Electric

  8. Stochastic Modeling and Direct Simulation of the Diffusion Media for Polymer Electrolyte Fuel Cells

    E-Print Network [OSTI]

    Schmidt, Volker

    Cells Yun Wang* and Xuhui Feng Renewable Energy Resources Lab (RERL) and National Fuel Cell Research the stochastic-model-based reconstruction of the gas diffusion layer (GDL) of polymer electrolyte fuel cells on pore-level transport and scrutinize the macroscopic approach vastly adopted in current fuel cell

  9. Heat and Mass Transfer Modeling of Dry Gases in the Cathode of PEM Fuel Cells

    E-Print Network [OSTI]

    Stockie, John

    Heat and Mass Transfer Modeling of Dry Gases in the Cathode of PEM Fuel Cells M.J. Kermani1 J and N2, through the cathode of a proton exchange membrane (PEM) fuel cell is studied numerically) an energy equation, written in a form that has enthalpy as the dependent variable. Keywords: PEM fuel cells

  10. The Hybrid Solid Oxide Fuel Cell (SOFC) and Gas Turbine (GT) Systems Steady State Modeling

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    The Hybrid Solid Oxide Fuel Cell (SOFC) and Gas Turbine (GT) Systems Steady State Modeling Penyarat plants offer high cycle efficiencies. In this work a hybrid solid oxide fuel cell and gas turbine power, Gas turbine, Hybrid, Solid Oxide Fuel Cell hal-00703135,version1-31May2012 Author manuscript

  11. Pinhole Breaches in Spent Fuel Containers: Some Modeling Considerations

    SciTech Connect (OSTI)

    Casella, Andrew M.; Loyalka, Sudarsham K.; Hanson, Brady D.

    2006-06-04

    This paper replaces PNNL-SA-48024 and incorporates the ANS reviewer's comments, including the change in the title. Numerical methods to solve the equations for gas diffusion through very small breaches in spent fuel containers are presented and compared with previous literature results.

  12. Fuel Efficient Diesel Particulate Filter (DPF) Modeling and Development

    SciTech Connect (OSTI)

    Stewart, Mark L.; Gallant, Thomas R.; Kim, Do Heui; Maupin, Gary D.; Zelenyuk, Alla

    2010-08-01

    The project described in this report seeks to promote effective diesel particulate filter technology with minimum fuel penalty by enhancing fundamental understanding of filtration mechanisms through targeted experiments and computer simulations. The overall backpressure of a filtration system depends upon complex interactions of particulate matter and ash with the microscopic pores in filter media. Better characterization of these phenomena is essential for exhaust system optimization. The acicular mullite (ACM) diesel particulate filter substrate is under continuing development by Dow Automotive. ACM is made up of long mullite crystals which intersect to form filter wall framework and protrude from the wall surface into the DPF channels. ACM filters have been demonstrated to effectively remove diesel exhaust particles while maintaining relatively low backpressure. Modeling approaches developed for more conventional ceramic filter materials, such as silicon carbide and cordierite, have been difficult to apply to ACM because of properties arising from its unique microstructure. Penetration of soot into the high-porosity region of projecting crystal structures leads to a somewhat extended depth filtration mode, but with less dramatic increases in pressure drop than are normally observed during depth filtration in cordierite or silicon carbide filters. Another consequence is greater contact between the soot and solid surfaces, which may enhance the action of some catalyst coatings in filter regeneration. The projecting crystals appear to provide a two-fold benefit for maintaining low backpressures during filter loading: they help prevent soot from being forced into the throats of pores in the lower porosity region of the filter wall, and they also tend to support the forming filter cake, resulting in lower average cake density and higher permeability. Other simulations suggest that soot deposits may also tend to form at the tips of projecting crystals due to the axial velocity component of exhaust moving down the filter inlet channel. Soot mass collected in this way would have a smaller impact on backpressure than soot forced into the flow restrictions deeper in the porous wall structure. This project has focused on the development of computational, analytical, and experimental techniques that are generally applicable to a wide variety of exhaust aftertreatment technologies. By helping to develop improved fundamental understanding pore-scale phenomena affecting filtration, soot oxidation, and NOX abatement, this cooperative research and development agreement (CRADA) has also assisted Dow Automotive in continuing development and commercialization of the ACM filter substrate. Over the course of this research project, ACM filters were successfully deployed on the Audi R10 TDI racecar which won the 24 Hours of LeMans endurance race in 2006, 2007, and 2008; and the 12 Hours of Sebring endurance race in 2006 and 2007. It would not have been possible for the R10 to compete in these traditionally gasoline-dominated events without reliable and effective exhaust particulate filtration. These successes demonstrated not only the performance of automotive diesel engines, but the efficacy of DPF technology as it was being deployed around the world to meet new emissions standards on consumer vehicles. During the course of this CRADA project, Dow Automotive commercialized their ACM DPF technology under the AERIFYTM DPF brand.

  13. Generation IV benchmarking of TRISO fuel performance models under accident conditions. Modeling input data

    SciTech Connect (OSTI)

    Blaise Collin

    2014-09-01

    This document presents the benchmark plan for the calculation of particle fuel performance on safety testing experiments that are representative of operational accidental transients. The benchmark is dedicated to the modeling of fission product release under accident conditions by fuel performance codes from around the world, and the subsequent comparison to post-irradiation experiment (PIE) data from the modeled heating tests. The accident condition benchmark is divided into three parts: the modeling of a simplified benchmark problem to assess potential numerical calculation issues at low fission product release; the modeling of the AGR-1 and HFR-EU1bis safety testing experiments; and, the comparison of the AGR-1 and HFR-EU1bis modeling results with PIE data. The simplified benchmark case, thereafter named NCC (Numerical Calculation Case), is derived from ''Case 5'' of the International Atomic Energy Agency (IAEA) Coordinated Research Program (CRP) on coated particle fuel technology [IAEA 2012]. It is included so participants can evaluate their codes at low fission product release. ''Case 5'' of the IAEA CRP-6 showed large code-to-code discrepancies in the release of fission products, which were attributed to ''effects of the numerical calculation method rather than the physical model''[IAEA 2012]. The NCC is therefore intended to check if these numerical effects subsist. The first two steps imply the involvement of the benchmark participants with a modeling effort following the guidelines and recommendations provided by this document. The third step involves the collection of the modeling results by Idaho National Laboratory (INL) and the comparison of these results with the available PIE data. The objective of this document is to provide all necessary input data to model the benchmark cases, and to give some methodology guidelines and recommendations in order to make all results suitable for comparison with each other. The participants should read this document thoroughly to make sure all the data needed for their calculations is provided in the document. Missing data will be added to a revision of the document if necessary.

  14. Fact #718: March 12, 2012 Number of Flex-Fuel Models Offered...

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

    (GM), Ford, and Chrysler have produced many different models of flex-fuel vehicles (cars and light trucks) over the last five years. In 2011, the number of models offered by...

  15. An improved structural mechanics model for the FRAPCON nuclear fuel performance code

    E-Print Network [OSTI]

    Mieloszyk, Alexander James

    2012-01-01

    In order to provide improved predictions of Pellet Cladding Mechanical Interaction (PCMI) for the FRAPCON nuclear fuel performance code, a new model, the FRAPCON Radial-Axial Soft Pellet (FRASP) model, was developed. This ...

  16. Fact #718: March 12, 2012 Number of Flex-Fuel Models Offered Increased in 2011

    Broader source: Energy.gov [DOE]

    General Motors (GM), Ford, and Chrysler have produced many different models of flex-fuel vehicles (cars and light trucks) over the last five years. In 2011, the number of models offered by those...

  17. MELCOR model for an experimental 17x17 spent fuel PWR assembly.

    SciTech Connect (OSTI)

    Cardoni, Jeffrey

    2010-11-01

    A MELCOR model has been developed to simulate a pressurized water reactor (PWR) 17 x 17 assembly in a spent fuel pool rack cell undergoing severe accident conditions. To the extent possible, the MELCOR model reflects the actual geometry, materials, and masses present in the experimental arrangement for the Sandia Fuel Project (SFP). The report presents an overview of the SFP experimental arrangement, the MELCOR model specifications, demonstration calculation results, and the input model listing.

  18. Modeling of constituent redistribution in U-Pu-Zr metallic fuel.

    SciTech Connect (OSTI)

    Kim, Y. S.; Hofman, G. L.; Hayes, S. L.; Yacout, A. M.; Nuclear Engineering Division; INL

    2006-12-01

    A computer model was developed to analyze constituent redistribution in U-Pu-Zr metallic nuclear fuels. Diffusion and thermochemical properties were parametrically determined to fit the postirradiation data from a fuel test performed in the Experimental Breeder Reactor II (EBR-II). The computer model was used to estimate redistribution profiles of fuels proposed for the conceptual designs of small modular fast reactors. The model results showed that the level of redistribution of the fuel constituents of the designs was similar to the measured data from EBR-II.

  19. Waste generation process modeling and analysis for fuel reprocessing technologies

    SciTech Connect (OSTI)

    Kornreich, D. E. (Drew E.); Koehler, A. C. (Andrew C.); Farman, Richard F.

    2002-01-01

    Estimates of electric power generation requirements for the next century, even when taking the most conservative tack, indicate that the United States will have to increase its production capacity significantly. If the country determines that nuclear power will not be a significant component of this production capacity, the nuclear industry will have to die, as maintaining a small nuclear component will not be justifiable. However, if nuclear power is to be a significant component, it will probably require some form of reprocessing technology. The once-through fuel cycle is only feasible for a relatively small number of nuclear power plants. If we are maintaining several hundred reactors, the once-through fuel cycle is more expensive and ethically questionable.

  20. Modeling hazardous fire potential within a completed fuel treatment network in the northern Sierra Nevada

    E-Print Network [OSTI]

    Stephens, Scott L.

    fuel models in treated areas had much less impact on hazardous fire potential, indicating a robust in untreated areas over time, result- ing in an increase in overall fire hazard. This suggests additionalModeling hazardous fire potential within a completed fuel treatment network in the northern Sierra

  1. GREET 1.0 -- Transportation fuel cycles model: Methodology and use

    SciTech Connect (OSTI)

    Wang, M.Q.

    1996-06-01

    This report documents the development and use of the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The model, developed in a spreadsheet format, estimates the full fuel-cycle emissions and energy use associated with various transportation fuels for light-duty vehicles. The model calculates fuel-cycle emissions of five criteria pollutants (volatile organic compounds, Co, NOx, SOx, and particulate matter measuring 10 microns or less) and three greenhouse gases (carbon dioxide, methane, and nitrous oxide). The model also calculates the total fuel-cycle energy consumption, fossil fuel consumption, and petroleum consumption using various transportation fuels. The GREET model includes 17 fuel cycles: petroleum to conventional gasoline, reformulated gasoline, clean diesel, liquefied petroleum gas, and electricity via residual oil; natural gas to compressed natural gas, liquefied petroleum gas, methanol, hydrogen, and electricity; coal to electricity; uranium to electricity; renewable energy (hydropower, solar energy, and wind) to electricity; corn, woody biomass, and herbaceous biomass to ethanol; and landfill gases to methanol. This report presents fuel-cycle energy use and emissions for a 2000 model-year car powered by each of the fuels that are produced from the primary energy sources considered in the study.

  2. FRAPCON-3: Modifications to fuel rod material properties and performance models for high-burnup application

    SciTech Connect (OSTI)

    Lanning, D.D.; Beyer, C.E.; Painter, C.L.

    1997-12-01

    This volume describes the fuel rod material and performance models that were updated for the FRAPCON-3 steady-state fuel rod performance code. The property and performance models were changed to account for behavior at extended burnup levels up to 65 Gwd/MTU. The property and performance models updated were the fission gas release, fuel thermal conductivity, fuel swelling, fuel relocation, radial power distribution, solid-solid contact gap conductance, cladding corrosion and hydriding, cladding mechanical properties, and cladding axial growth. Each updated property and model was compared to well characterized data up to high burnup levels. The installation of these properties and models in the FRAPCON-3 code along with input instructions are provided in Volume 2 of this report and Volume 3 provides a code assessment based on comparison to integral performance data. The updated FRAPCON-3 code is intended to replace the earlier codes FRAPCON-2 and GAPCON-THERMAL-2. 94 refs., 61 figs., 9 tabs.

  3. Fuel Cell Power Model Version 2: Startup Guide, System Designs, and Case Studies. Modeling Electricity, Heat, and Hydrogen Generation from Fuel Cell-Based Distributed Energy Systems

    SciTech Connect (OSTI)

    Steward, D.; Penev, M.; Saur, G.; Becker, W.; Zuboy, J.

    2013-06-01

    This guide helps users get started with the U.S. Department of Energy/National Renewable Energy Laboratory Fuel Cell Power (FCPower) Model Version 2, which is a Microsoft Excel workbook that analyzes the technical and economic aspects of high-temperature fuel cell-based distributed energy systems with the aim of providing consistent, transparent, comparable results. This type of energy system would provide onsite-generated heat and electricity to large end users such as hospitals and office complexes. The hydrogen produced could be used for fueling vehicles or stored for later conversion to electricity.

  4. Modeling Water Management in Polymer-Electrolyte Fuel Cells

    E-Print Network [OSTI]

    Weber, Adam; Department of Chemical Engineering, University of California, Berkeley

    2008-01-01

    model can be used in a full-cell simulation. For example, itinterfaces are since in a full cell the CLs contain membranecannot be used in a full-cell simulations. The current

  5. On a Pioneering Polymer Electrolyte Fuel Cell Model

    E-Print Network [OSTI]

    Weber, Adam Z.

    2013-01-01

    systems. Both the testing of PEFC’s and the complexity ofrate can affect another. The PEFC modeling literature hasmembrane at the center of the PEFC. It focuses on analyzing

  6. RockPort Capital Partners (California) | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/ColoradoRemsenburg-Speonk, NewMichigan: Energy Resources JumpMtSamplingRockPort Capital

  7. A Venture Capital Perspective on Technology Transfer and Alternative Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative FuelsofProgram:Y-12 Beta-3 Racetracks25 AMOSystem for UtilizingVenture Capital

  8. JOBS Models: JOBS FC (Fuel Cells) and JOBS H2 (Hydrogen)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:Financing Tool Fits the BillDepartment ofEnergy Introduction SCADAPlanIs the18,16, 2013Models

  9. MA3T Model Application at ORNL Assesses the Future of Fuel Cell Markets |

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuelsof EnergyApril 2014 |Department of Energy MA3T Model Application at ORNL

  10. Modeling Water Management in Polymer-Electrolyte Fuel Cells

    SciTech Connect (OSTI)

    Department of Chemical Engineering, University of California, Berkeley; Weber, Adam; Weber, Adam Z.; Balliet, Ryan; Gunterman, Haluna P.; Newman, John

    2007-09-07

    Fuel cells may become the energy-delivery devices of the 21st century with realization of a carbon-neutral energy economy. Although there are many types of fuel cells, polymerelectrolyte fuel cells (PEFCs) are receiving the most attention for automotive and small stationary applications. In a PEFC, hydrogen and oxygen are combined electrochemically to produce water, electricity, and waste heat. During the operation of a PEFC, many interrelated and complex phenomena occur. These processes include mass and heat transfer, electrochemical reactions, and ionic and electronic transport. Most of these processes occur in the through-plane direction in what we term the PEFC sandwich as shown in Figure 1. This sandwich comprises multiple layers including diffusion media that can be composite structures containing a macroporous gas-diffusion layer (GDL) and microporous layer (MPL), catalyst layers (CLs), flow fields or bipolar plates, and a membrane. During operation fuel is fed into the anode flow field, moves through the diffusion medium, and reacts electrochemically at the anode CL to form hydrogen ions and electrons. The oxidant, usually oxygen in air, is fed into the cathode flow field, moves through the diffusion medium, and is electrochemically reduced at the cathode CL by combination with the generated protons and electrons. The water, either liquid or vapor, produced by the reduction of oxygen at the cathode exits the PEFC through either the cathode or anode flow field. The electrons generated at the anode pass through an external circuit and may be used to perform work before they are consumed at the cathode. The performance of a PEFC is most often reported in the form of a polarization curve, as shown in Figure 2. Roughly speaking, the polarization curve can be broken down into various regions. First, it should be noted that the equilibrium potential differs from the open-circuit voltage due mainly to hydrogen crossover through the membrane (i.e., a mixed potential on the cathode) and the resulting effects of the kinetic reactions. Next, at low currents, the behavior of a PEFC is dominated by kinetic losses. These losses mainly stem from the high overpotential of the oxygen-reduction reaction (ORR). As the current is increased, ohmic losses become a factor in lowering the overall cell potential. These ohmic losses are mainly from ionic losses in the electrodes and separator. At high currents, mass-transport limitations become increasingly important. These losses are due to reactants not being able to reach the electrocatalytic sites. Key among the issues facing PEFCs today is water management. Due to their low operating temperature (< 100 C), water exists in both liquid and vapor phases. Furthermore, state-of-the-art membranes require the use of water to provide high conductivity and fast proton transport. Thus, there is a tradeoff between having enough water for proton conduction (ohmic losses), but not too much or else the buildup of liquid water will cause a situation in which the reactant-gas-transport pathways are flooded (mass-transfer limitations). Figure 3 displays experimental evidence of the effects of water management on performance. In Figure 3(a), a neutron image of water content displays flooding near the outlet of the cell due to accumulation of liquid water and a decrease in the gas flowrates. The serpentine flow field is clearly visible with the water mainly underneath the ribs. Figure 3(b) shows polarization performance at 0.4 and 0.8 V and high-frequency resistance at 0.8 V as a function of cathode humidification temperature. At low current densities, as the inlet air becomes more humid, the membrane resistance decreases, and the performance increases. At higher current densities, the same effect occurs; however, the higher temperatures and more humid air also results in a lower inlet oxygen partial pressure.

  11. Ab Initio Enhanced calphad Modeling of Actinide-Rich Nuclear Fuels

    SciTech Connect (OSTI)

    Morgan, Dane; Yang, Yong Austin

    2013-10-28

    The process of fuel recycling is central to the Advanced Fuel Cycle Initiative (AFCI), where plutonium and the minor actinides (MA) Am, Np, and Cm are extracted from spent fuel and fabricated into new fuel for a fast reactor. Metallic alloys of U-Pu-Zr-MA are leading candidates for fast reactor fuels and are the current basis for fast spectrum metal fuels in a fully recycled closed fuel cycle. Safe and optimal use of these fuels will require knowledge of their multicomponent phase stability and thermodynamics (Gibbs free energies). In additional to their use as nuclear fuels, U-Pu-Zr-MA contain elements and alloy phases that pose fundamental questions about electronic structure and energetics at the forefront of modern many-body electron theory. This project will validate state-of-the-art electronic structure approaches for these alloys and use the resulting energetics to model U-Pu-Zr-MA phase stability. In order to keep the work scope practical, researchers will focus on only U-Pu-Zr-{Np,Am}, leaving Cm for later study. The overall objectives of this project are to: Provide a thermodynamic model for U-Pu-Zr-MA for improving and controlling reactor fuels; and, Develop and validate an ab initio approach for predicting actinide alloy energetics for thermodynamic modeling.

  12. Advanced Pellet Cladding Interaction Modeling Using the US DOE CASL Fuel Performance Code: Peregrine

    SciTech Connect (OSTI)

    Jason Hales; Various

    2014-06-01

    The US DOE’s Consortium for Advanced Simulation of LWRs (CASL) program has undertaken an effort to enhance and develop modeling and simulation tools for a virtual reactor application, including high fidelity neutronics, fluid flow/thermal hydraulics, and fuel and material behavior. The fuel performance analysis efforts aim to provide 3-dimensional capabilities for single and multiple rods to assess safety margins and the impact of plant operation and fuel rod design on the fuel thermomechanical- chemical behavior, including Pellet-Cladding Interaction (PCI) failures and CRUD-Induced Localized Corrosion (CILC) failures in PWRs. [1-3] The CASL fuel performance code, Peregrine, is an engineering scale code that is built upon the MOOSE/ELK/FOX computational FEM framework, which is also common to the fuel modeling framework, BISON [4,5]. Peregrine uses both 2-D and 3-D geometric fuel rod representations and contains a materials properties and fuel behavior model library for the UO2 and Zircaloy system common to PWR fuel derived from both open literature sources and the FALCON code [6]. The primary purpose of Peregrine is to accurately calculate the thermal, mechanical, and chemical processes active throughout a single fuel rod during operation in a reactor, for both steady state and off-normal conditions.

  13. KINETIC MODELING OF FUEL EFFECTS OVER A WIDE RANGE OF CHEMISTRY, PROPERTIES, AND SOURCES

    SciTech Connect (OSTI)

    Bunting, Bruce G [ORNL] [ORNL; Bunce, Michael [ORNL] [ORNL; Niak, Chitralkumar [Reaction Design] [Reaction Design; Puduppakkam, Karthik [Reaction Design] [Reaction Design

    2012-01-01

    Kinetic modeling is an important tool for engine design and can also be used for engine tuning and to study response to fuel chemistry and properties before an engine configuration is physically built and tested. Methodologies needed for studying fuel effects include development of fuel kinetic mechanisms for pure compounds, tools for designing surrogate blends of pure compounds that mimic a desired market fuel, and tools for reducing kinetic mechanisms to a size that allows inclusion in complex CFD engine models. In this paper, we demonstrate the use of these tools to reproduce engine results for a series of research diesel fuels using surrogate fuels in an engine and then modeling results with a simple 2 component surrogate blend with physical properties adjusted to vary fuel volatility. Results indicate that we were reasonably successful in mimicking engine performance of real fuels with blends of pure compounds. We were also successful in spanning the range of the experimental data using CFD and kinetic modeling, but further tuning and matching will be needed to exactly match engine performance of the real and surrogate fuels.

  14. User Guide for VISION 3.4.7 (Verifiable Fuel Cycle Simulation) Model

    SciTech Connect (OSTI)

    Jacob J. Jacobson; Robert F. Jeffers; Gretchen E. Matthern; Steven J. Piet; Wendell D. Hintze

    2011-07-01

    The purpose of this document is to provide a guide for using the current version of the Verifiable Fuel Cycle Simulation (VISION) model. This is a complex model with many parameters and options; the user is strongly encouraged to read this user guide before attempting to run the model. This model is an R&D work in progress and may contain errors and omissions. It is based upon numerous assumptions. This model is intended to assist in evaluating 'what if' scenarios and in comparing fuel, reactor, and fuel processing alternatives at a systems level. The model is not intended as a tool for process flow and design modeling of specific facilities nor for tracking individual units of fuel or other material through the system. The model is intended to examine the interactions among the components of a fuel system as a function of time varying system parameters; this model represents a dynamic rather than steady-state approximation of the nuclear fuel system. VISION models the nuclear cycle at the system level, not individual facilities, e.g., 'reactor types' not individual reactors and 'separation types' not individual separation plants. Natural uranium can be enriched, which produces enriched uranium, which goes into fuel fabrication, and depleted uranium (DU), which goes into storage. Fuel is transformed (transmuted) in reactors and then goes into a storage buffer. Used fuel can be pulled from storage into either separation or disposal. If sent to separations, fuel is transformed (partitioned) into fuel products, recovered uranium, and various categories of waste. Recycled material is stored until used by its assigned reactor type. VISION is comprised of several Microsoft Excel input files, a Powersim Studio core, and several Microsoft Excel output files. All must be co-located in the same folder on a PC to function. You must use Powersim Studio 8 or better. We have tested VISION with the Studio 8 Expert, Executive, and Education versions. The Expert and Education versions work with the number of reactor types of 3 or less. For more reactor types, the Executive version is currently required. The input files are Excel2003 format (xls). The output files are macro-enabled Excel2007 format (xlsm). VISION 3.4 was designed with more flexibility than previous versions, which were structured for only three reactor types - LWRs that can use only uranium oxide (UOX) fuel, LWRs that can use multiple fuel types (LWR MF), and fast reactors. One could not have, for example, two types of fast reactors concurrently. The new version allows 10 reactor types and any user-defined uranium-plutonium fuel is allowed. (Thorium-based fuels can be input but several features of the model would not work.) The user identifies (by year) the primary fuel to be used for each reactor type. The user can identify for each primary fuel a contingent fuel to use if the primary fuel is not available, e.g., a reactor designated as using mixed oxide fuel (MOX) would have UOX as the contingent fuel. Another example is that a fast reactor using recycled transuranic (TRU) material can be designated as either having or not having appropriately enriched uranium oxide as a contingent fuel. Because of the need to study evolution in recycling and separation strategies, the user can now select the recycling strategy and separation technology, by year.

  15. The FIT 2.0 Model - Fuel-cycle Integration and Tradeoffs

    SciTech Connect (OSTI)

    Steven J. Piet; Nick R. Soelberg; Layne F. Pincock; Eric L. Shaber; Gregory M Teske

    2011-06-01

    All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010b] are steps by the Fuel Cycle Technology program toward an analysis that accounts for the requirements and capabilities of each fuel cycle component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. This report describes FIT 2, an update of the original FIT model.[Piet2010c] FIT is a method to analyze different fuel cycles; in particular, to determine how changes in one part of a fuel cycle (say, fuel burnup, cooling, or separation efficiencies) chemically affect other parts of the fuel cycle. FIT provides the following: Rough estimate of physics and mass balance feasibility of combinations of technologies. If feasibility is an issue, it provides an estimate of how performance would have to change to achieve feasibility. Estimate of impurities in fuel and impurities in waste as function of separation performance, fuel fabrication, reactor, uranium source, etc.

  16. Modeling of the performance of weapons MOX fuel in light water reactors

    SciTech Connect (OSTI)

    Alvis, J.; Bellanger, P.; Medvedev, P.G.; Peddicord, K.L.; Gellene, G.I.

    1999-05-01

    Both the Russian Federation and the US are pursing mixed uranium-plutonium oxide (MOX) fuel in light water reactors (LWRs) for the disposition of excess plutonium from disassembled nuclear warheads. Fuel performance models are used which describe the behavior of MOX fuel during irradiation under typical power reactor conditions. The objective of this project is to perform the analysis of the thermal, mechanical, and chemical behavior of weapons MOX fuel pins under LWR conditions. If fuel performance analysis indicates potential questions, it then becomes imperative to assess the fuel pin design and the proposed operating strategies to reduce the probability of clad failure and the associated release of radioactive fission products into the primary coolant system. Applying the updated code to anticipated fuel and reactor designs, which would be used for weapons MOX fuel in the US, and analyzing the performance of the WWER-100 fuel for Russian weapons plutonium disposition are addressed in this report. The COMETHE code was found to do an excellent job in predicting fuel central temperatures. Also, despite minor predicted differences in thermo-mechanical behavior of MOX and UO{sub 2} fuels, the preliminary estimate indicated that, during normal reactor operations, these deviations remained within limits foreseen by fuel pin design.

  17. Radiolysis Model Sensitivity Analysis for a Used Fuel Storage Canister

    SciTech Connect (OSTI)

    Wittman, Richard S.

    2013-09-20

    This report fulfills the M3 milestone (M3FT-13PN0810027) to report on a radiolysis computer model analysis that estimates the generation of radiolytic products for a storage canister. The analysis considers radiolysis outside storage canister walls and within the canister fill gas over a possible 300-year lifetime. Previous work relied on estimates based directly on a water radiolysis G-value. This work also includes that effect with the addition of coupled kinetics for 111 reactions for 40 gas species to account for radiolytic-induced chemistry, which includes water recombination and reactions with air.

  18. MODELING ASSUMPTIONS FOR THE ADVANCED TEST REACTOR FRESH FUEL SHIPPING CONTAINER

    SciTech Connect (OSTI)

    Rick J. Migliore

    2009-09-01

    The Advanced Test Reactor Fresh Fuel Shipping Container (ATR FFSC) is currently licensed per 10 CFR 71 to transport a fresh fuel element for either the Advanced Test Reactor, the University of Missouri Research Reactor (MURR), or the Massachusetts Institute of Technology Research Reactor (MITR-II). During the licensing process, the Nuclear Regulatory Commission (NRC) raised a number of issues relating to the criticality analysis, namely (1) lack of a tolerance study on the fuel and packaging, (2) moderation conditions during normal conditions of transport (NCT), (3) treatment of minor hydrogenous packaging materials, and (4) treatment of potential fuel damage under hypothetical accident conditions (HAC). These concerns were adequately addressed by modifying the criticality analysis. A tolerance study was added for both the packaging and fuel elements, full-moderation was included in the NCT models, minor hydrogenous packaging materials were included, and fuel element damage was considered for the MURR and MITR-II fuel types.

  19. Modeling and Analysis of FCM UN TRISO Fuel Using the PARFUME Code

    SciTech Connect (OSTI)

    Blaise Collin

    2013-09-01

    The PARFUME (PARticle Fuel ModEl) modeling code was used to assess the overall fuel performance of uranium nitride (UN) tri-structural isotropic (TRISO) ceramic fuel in the frame of the design and development of Fully Ceramic Matrix (FCM) fuel. A specific modeling of a TRISO particle with UN kernel was developed with PARFUME, and its behavior was assessed in irradiation conditions typical of a Light Water Reactor (LWR). The calculations were used to access the dimensional changes of the fuel particle layers and kernel, including the formation of an internal gap. The survivability of the UN TRISO particle was estimated depending on the strain behavior of the constituent materials at high fast fluence and burn-up. For nominal cases, internal gas pressure and representative thermal profiles across the kernel and layers were determined along with stress levels in the pyrolytic carbon (PyC) and silicon carbide (SiC) layers. These parameters were then used to evaluate fuel particle failure probabilities. Results of the study show that the survivability of UN TRISO fuel under LWR irradiation conditions might only be guaranteed if the kernel and PyC swelling rates are limited at high fast fluence and burn-up. These material properties are unknown at the irradiation levels expected to be reached by UN TRISO fuel in LWRs. Therefore, more effort is needed to determine them and positively conclude on the applicability of FCM fuel to LWRs.

  20. Computational Modeling of Electrolyte/Cathode Interfaces in Proton Exchange Membrane Fuel Cells

    E-Print Network [OSTI]

    Bjørnstad, Ottar Nordal

    Computational Modeling of Electrolyte/Cathode Interfaces in Proton Exchange Membrane Fuel Cells Dr Proton exchange membrane fuel cells (PEMFCs) are alternative energy conversion devices that efficiently. The fundamental relationship between operating conditions and device performance will help to optimize the device

  1. Modelling and Design Optimization of Low Speed Fuel Cell Hybrid Electric Vehicles

    E-Print Network [OSTI]

    Victoria, University of

    Modelling and Design Optimization of Low Speed Fuel Cell Hybrid Electric Vehicles by Matthew Blair of emissions to global climate change. Although electric cars and buses have been the focus of much of electric and utility purposes in many countries. In order to explore the viability of fuel cell - battery hybrid

  2. Modeling the performance of high burnup thoria and urania PWR fuel

    E-Print Network [OSTI]

    Long, Yun, 1972-

    2002-01-01

    Fuel performance models have been developed to assess the performance of ThO?-UO? fuels that can be operated to a high burnup up to 80-100MWd/kgHM in current and future Light Water Reactors (LWRs). Among the various issues ...

  3. Nonlinear modelling of polymer electrolyte membrane fuel cell stack using nonlinear cancellation technique

    SciTech Connect (OSTI)

    Barus, R. P. P.; Tjokronegoro, H. A.; Leksono, E.; Ismunandar

    2014-09-25

    Fuel cells are promising new energy conversion devices that are friendly to the environment. A set of control systems are required in order to operate a fuel cell based power plant system optimally. For the purpose of control system design, an accurate fuel cell stack model in describing the dynamics of the real system is needed. Currently, linear model are widely used for fuel cell stack control purposes, but it has limitations in narrow operation range. While nonlinear models lead to nonlinear control implemnetation whos more complex and hard computing. In this research, nonlinear cancellation technique will be used to transform a nonlinear model into a linear form while maintaining the nonlinear characteristics. The transformation is done by replacing the input of the original model by a certain virtual input that has nonlinear relationship with the original input. Then the equality of the two models is tested by running a series of simulation. Input variation of H2, O2 and H2O as well as disturbance input I (current load) are studied by simulation. The error of comparison between the proposed model and the original nonlinear model are less than 1 %. Thus we can conclude that nonlinear cancellation technique can be used to represent fuel cell nonlinear model in a simple linear form while maintaining the nonlinear characteristics and therefore retain the wide operation range.

  4. Modeling the Influence of Interaction Layer Formation on Thermal Conductivity of U–Mo Dispersion Fuel

    SciTech Connect (OSTI)

    Burkes, Douglas; Casella, Andrew M.; Huber, Tanja K.

    2015-01-01

    The Global Threat Reduction Initiative Program continues to develop existing and new plate- and rod-type research and test reactor fuels with maximum attainable uranium loadings capable of potentially converting a number of the world’s remaining high-enriched uranium fueled reactors to low-enriched uranium fuel. Currently, the program is focused on assisting with the development and qualification of an even higher density fuel type consisting of a uranium-molybdenum (U-Mo) alloy dispersed in an aluminum matrix. Thermal conductivity is an important consideration in determining the operational temperature of the fuel plate and can be influenced by interaction layer formation between the fuel and matrix, porosity that forms during fabrication of the fuel plates, and upon the concentration of the dispersed phase within the matrix. This paper develops and validates a simple model to study the influence of interaction layer formation and conductivity, fuel particle size, and volume fraction of fuel dispersed in the matrix on the effective conductivity of the composite. The model shows excellent agreement with results previously presented in the literature. In particular, the thermal conductivity of the interaction layer does not appear to be important in determining the overall conductivity of the composite, while formation of the interaction layer and subsequent consumption of the matrix reveals a rather significant effect. The effective thermal conductivity of the composite can be influenced by the fuel particle distribution by minimizing interaction layer formation and preserving the higher thermal conductivity matrix.

  5. Beryllium Impregnation of Uranium Fuel: Thermal Modeling of Cylindrical Objects for Efficiency Evaluation 

    E-Print Network [OSTI]

    Lynn, Nicholas

    2011-08-04

    With active research projects related to nuclear waste immobilization and high conductivity nuclear fuels, a thermal model has been developed to simulate the temperature profile within a heat generating cylinder in order to imitate the behavior...

  6. Influence of FRAPCON-1 evaluation models on fuel behavior calculations for commercial power reactors. [PWR; BWR

    SciTech Connect (OSTI)

    Chambers, R.; Laats, E.T.

    1981-01-01

    A preliminary set of nine evaluation models (EMs) was added to the FRAPCON-1 computer code, which is used to calculate fuel rod behavior in a nuclear reactor during steady-state operation. The intent was to provide an audit code to be used in the United States Nuclear Regulatory Commission (NRC) licensing activities when calculations of conservative fuel rod temperatures are required. The EMs place conservatisms on the calculation of rod temperature by modifying the calculation of rod power history, fuel and cladding behavior models, and materials properties correlations. Three of the nine EMs provide either input or model specifications, or set the reference temperature for stored energy calculations. The remaining six EMs were intended to add thermal conservatism through model changes. To determine the relative influence of these six EMs upon fuel behavior calculations for commercial power reactors, a sensitivity study was conducted. That study is the subject of this paper.

  7. Modeling the Fuel Spray and Combustion Process of the Ignition Quality Tester with KIVA-3V

    SciTech Connect (OSTI)

    Bogin, G. E. Jr.; DeFilippo, A.; Chen, J. Y.; Chin, G.; Luecke, J.; Ratcliff, M. A.; Zigler, B. T.; Dean, A. M.

    2010-05-01

    Discusses the use of KIVA-3V to develop a model that reproduces ignition behavior inside the Ignition Quality Tester, which measures the ignition delay of low-volatility fuels.

  8. A decision-support model for managing the fuel inventory of a Panamanian generating company

    E-Print Network [OSTI]

    Perez-Franco, Roberto, 1976-

    2004-01-01

    Bahia Las Minas Corp (BLM) is a fuelpowered generating company in the Panamanian power system. The purpose of this thesis is to design and evaluate a decision-support model for managing the fuel inventory of this company. ...

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

    E-Print Network [OSTI]

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

    2013-01-01

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

  10. An evaluation of thermal modeling techniques utilized for nuclear fuel rods 

    E-Print Network [OSTI]

    Simmons, Jeffrey Warren

    1989-01-01

    for open gap conditions or increases the interfacial pressure for closed gap conditions. Therefore, an accurate prediction of fission gas behavior is an essential part of a fuel rod performance code. Theory Development Xenon and krypton are noble gases... the different thermal modeling techniques employed therein. Differences in fuel centerline temperature predictions caused by these identified differences in thermal modeling techniques were then determined using the integral conductivity method. Fission gas...

  11. Development and use of the GREET model to estimate fuel-cycle energy use and emissions of various transportation technologies and fuels

    SciTech Connect (OSTI)

    Wang, M.Q.

    1996-03-01

    This report documents the development and use of the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The model, developed in a spreadsheet format, estimates the full fuel- cycle emissions and energy use associated with various transportation fuels for light-duty vehicles. The model calculates fuel-cycle emissions of five criteria pollutants (volatile organic compounds, carbon monoxide, nitrogen oxides, sulfur oxides, and particulate matter measuring 10 microns or less) and three greenhouse gases (carbon dioxide, methane, and nitrous oxide). The model also calculates the total fuel-cycle energy consumption, fossil fuel consumption, and petroleum consumption using various transportation fuels. The GREET model includes 17 fuel cycles: petroleum to conventional gasoline, reformulated gasoline, clean diesel, liquefied petroleum gas, and electricity via residual oil; natural gas to compressed natural gas, liquefied petroleum gas, methanol, hydrogen, and electricity; coal to electricity; uranium to electricity; renewable energy (hydrogen, solar energy, and wind) to electricity; corn, woody biomass, and herbaceous biomass to ethanol; and landfill gases to methanol. This report presents fuel-cycle energy use and emissions for a 2000 model-year car powered by each of the fuels that are produced from the primary energy sources considered in the study.

  12. The Modeling of a Standalone Solid-Oxide Fuel Cell Auxiliary Power Unit

    SciTech Connect (OSTI)

    Lu, Ning; Li, Qinghe; Sun, Xin; Khaleel, Mohammad A.

    2006-10-27

    In this research, a Simulink model of a standalone vehicular solid-oxide fuel cell (SOFC) auxiliary power unit (APU) is developed. The SOFC APU model consists of three major components: a controller model; a power electronics system model; and an SOFC plant model, including an SOFC stack module; two heat exchanger modules; and a combustor module. This paper discusses the development of the nonlinear dynamic models for the SOFC stacks, the heat exchangers and the combustors. When coupling with a controller model and a power electronic circuit model, the developed SOFC plant model is able to model the thermal dynamics and the electrochemical dynamics inside the SOFC APU components as well as the transient responses to the electric loading changes. It has been shown that having such a model for the SOFC APU will benefit design engineers to adjust design parameters to optimize the performance. The modeling results of the heat-up stage of an SOFC APU and the output voltage response to a sudden load change are presented in the paper. The fuel flow regulation based on fuel utilization is also briefly discussed.

  13. A Comparison of HCCI Engine Performance Data and Kinetic Modeling Results over a Wide Rangeof Gasoline Range Surrogate Fuel Blends

    Broader source: Energy.gov [DOE]

    Kinetic models of fuels are needed to allow the simulation of engine performance for research, design, or verification purposes.

  14. A Combustion Model for the TWA 800 Center-Wing Fuel Tank Explosion

    SciTech Connect (OSTI)

    Baer, M.R.; Gross, R.J.

    1998-10-02

    In support of the National Transportation Safety Board investigation of the TWA Flight 800 accident, a combined experimental/computational effort was conducted that focused on quarter-scale testing and simulation of the fuel-air explosion in the Boeing 747 center wing fuel tank. This report summarizes the modeling approach used at Sandia National Laboratories. In this approach approximations are introduced that capture the essential physics associated with turbulent flame propagation in multiple compartment fuel tanks. This model efficiently defines the pressure loading conditions during a jet-fuel air explosion in a fuel tank confinement. Modeling calculations compare favorably with a variety of experimental quarter-scale tests conducted in rigid confinement. The modeling describes well the overpressure history in several geometry configurations. Upon demonstrating a reasonable comparison to experimental observations, a parametric study of eight possible ignition sources is then discussed. Model calculations demonstrate that different loading conditions arise as the location of the ignition event is varied. By comparing the inferred damage and calculated impulses to that seen in the recovered tank, it maybe possible to reduce the number of likely sources. A possible extension of this work to better define tank damage includes coupling the combustion model as a pressure loading routine for structural failure analysis.

  15. A Low-Carbon Fuel Standard for California Part 1: Technical Analysis

    E-Print Network [OSTI]

    2007-01-01

    B. “Alternative Transportation Fuels and Vehicles: Energy,alternative fuels for market share, energy resources and capital. Though complex and dynamic alternative fuel vehicle

  16. A Low-Carbon Fuel Standard for California, Part 1: Technical Analysis

    E-Print Network [OSTI]

    Farrell, Alexander E.; Sperling, Dan

    2007-01-01

    B. “Alternative Transportation Fuels and Vehicles: Energy,alternative fuels for market share, energy resources and capital. Though complex and dynamic alternative fuel vehicle

  17. THETRIS: A MICRO-SCALE TEMPERATURE AND GAS RELEASE MODEL FOR TRISO FUEL

    SciTech Connect (OSTI)

    J. Ortensi; A.M. Ougouag

    2011-12-01

    The dominating mechanism in the passive safety of gas-cooled, graphite-moderated, high-temperature reactors (HTRs) is the Doppler feedback effect. These reactor designs are fueled with sub-millimeter sized kernels formed into TRISO particles that are imbedded in a graphite matrix. The best spatial and temporal representation of the feedback effect is obtained from an accurate approximation of the fuel temperature. Most accident scenarios in HTRs are characterized by large time constants and slow changes in the fuel and moderator temperature fields. In these situations a meso-scale, pebble and compact scale, solution provides a good approximation of the fuel temperature. Micro-scale models are necessary in order to obtain accurate predictions in faster transients or when parameters internal to the TRISO are needed. Since these coated particles constitute one of the fundamental design barriers for the release of fission products, it becomes important to understand the transient behavior inside this containment system. An explicit TRISO fuel temperature model named THETRIS has been developed and incorporated into the CYNOD-THERMIX-KONVEK suite of coupled codes. The code includes gas release models that provide a simple predictive capability of the internal pressure during transients. The new model yields similar results to those obtained with other micro-scale fuel models, but with the added capability to analyze gas release, internal pressure buildup, and effects of a gap in the TRISO. The analyses show the instances when the micro-scale models improve the predictions of the fuel temperature and Doppler feedback. In addition, a sensitivity study of the potential effects on the transient behavior of high-temperature reactors due to the presence of a gap is included. Although the formation of a gap occurs under special conditions, its consequences on the dynamic behavior of the reactor can cause unexpected responses during fast transients. Nevertheless, the strong Doppler feedback forces the reactor to quickly stabilize.

  18. Human Capital Management Accountability Program

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2008-08-01

    The Order establishes requirements, roles and responsibilities for the Human Capital Management Accountability Program (HCMAP) for human resources programs and personnel and ensures that human capital activities are regulatory and procedurally compliant with Federal statutes and Departmental policies. Does not cancel other directives.

  19. Access to Capital

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsicloudden Documentation DataStreamsTotalproposalsAboutAcceleratingthYour

  20. Information, Diversification, and Cost of Capital

    E-Print Network [OSTI]

    Hughes, John S; Liu, Jing; Liu, Jun

    2005-01-01

    insider trading and cost of capital. ” Working paper, UCLA,Information and the cost of capital. ” Journal of Finance,in Determining Cost of Equity Capital,” Review of Accounting

  1. Modeling the Integrated Performance of Dispersion and Monolithic U-Mo Based Fuels

    SciTech Connect (OSTI)

    Daniel M. Wachs; Douglas E. Burkes; Steven L. Hayes; Karen Moore; Greg Miller; Gerard Hofman; Yeon Soo Kim

    2006-10-01

    The evaluation and prediction of integrated fuel performance is a critical component of the Reduced Enrichment for Research and Test Reactors (RERTR) program. The PLATE code is the primary tool being developed and used to perform these functions. The code is being modified to incorporate the most recent fuel/matrix interaction correlations as they become available for both aluminum and aluminum/silicon matrices. The code is also being adapted to treat cylindrical and square pin geometries to enhance the validation database by including the results gathered from various international partners. Additional modeling work has been initiated to evaluate the thermal and mechanical performance requirements unique to monolithic fuels during irradiation.

  2. Renewable Fuels Module of the National Energy Modeling System: Model Documentation 2014

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand Cubic Feet)6984 ForRenewable

  3. Liquid Fuels Market Module of the National Energy Modeling System: Model Documentation 2014

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr 2012 2013 2014Thousand343DecadeFeet) DecadeModule

  4. Experimental and Modeling Study of the Flammability of Fuel Tank Headspace Vapors from High Ethanol Content Fuels

    SciTech Connect (OSTI)

    Gardiner, D.; Bardon, M.; Pucher, G.

    2008-10-01

    Study determined the flammability of fuel tank headspace vapors as a function of ambient temperature for seven E85 fuel blends, two types of gasoline, and denatured ethanol at a low tank fill level.

  5. Detailed Chemical Kinetic Modeling of Surrogate Fuels for Gasoline and Application to an HCCI Engine

    SciTech Connect (OSTI)

    Naik, C V; Pitz, W J; Sj?berg, M; Dec, J E; Orme, J; Curran, H J; Simmie, J M; Westbrook, C K

    2005-01-07

    Gasoline consists of many different classes of hydrocarbons, such as paraffins, olefins, aromatics, and cycloalkanes. In this study, a surrogate gasoline reaction mechanism is developed, and it has one representative fuel constituent from each of these classes. These selected constituents are iso-octane, n-heptane, 1-pentene, toluene, and methyl-cyclohexane. The mechanism was developed in a step-wise fashion, adding submechanisms to treat each fuel component. Reactions important for low temperature oxidation (<1000K) and cross-reactions among different fuels are incorporated into the mechanism. The mechanism consists of 1214 species and 5401 reactions. A single-zone engine model is used to evaluate how well the mechanism captures autoignition behavior for conditions corresponding to homogeneous charge compression ignition (HCCI) engine operation. Experimental data are available for both how the combustion phasing changes with fueling at a constant intake temperature, and also how the intake temperature has to be changed with pressure in order to maintain combustion phasing for a fixed equivalence ratio. Three different surrogate fuel mixtures are used for the modeling. Predictions are in reasonably good agreement with the engine data. In addition, the heat release rate is calculated and compared to the data from experiments. The model predicts less low-temperature heat release than that measured. It is found that the low temperature heat-release rate depends strongly on engine speed, reactions of RO{sub 2}+HO{sub 2}, fuel composition, and pressure boost.

  6. Nuclear fuel cycle system simulation tool based on high-fidelity component modeling

    SciTech Connect (OSTI)

    Ames, David E.

    2014-02-01

    The DOE is currently directing extensive research into developing fuel cycle technologies that will enable the safe, secure, economic, and sustainable expansion of nuclear energy. The task is formidable considering the numerous fuel cycle options, the large dynamic systems that each represent, and the necessity to accurately predict their behavior. The path to successfully develop and implement an advanced fuel cycle is highly dependent on the modeling capabilities and simulation tools available for performing useful relevant analysis to assist stakeholders in decision making. Therefore a high-fidelity fuel cycle simulation tool that performs system analysis, including uncertainty quantification and optimization was developed. The resulting simulator also includes the capability to calculate environmental impact measures for individual components and the system. An integrated system method and analysis approach that provides consistent and comprehensive evaluations of advanced fuel cycles was developed. A general approach was utilized allowing for the system to be modified in order to provide analysis for other systems with similar attributes. By utilizing this approach, the framework for simulating many different fuel cycle options is provided. Two example fuel cycle configurations were developed to take advantage of used fuel recycling and transmutation capabilities in waste management scenarios leading to minimized waste inventories.

  7. Modeling and Analysis of UN TRISO Fuel for LWR Application Using the PARFUME Code

    SciTech Connect (OSTI)

    Blaise Collin

    2014-08-01

    The Idaho National Laboraroty (INL) PARFUME (particle fuel model) code was used to assess the overall fuel performance of uranium nitride (UN) tristructural isotropic (TRISO) ceramic fuel under irradiation conditions typical of a Light Water Reactor (LWR). The dimensional changes of the fuel particle layers and kernel were calculated, including the formation of an internal gap. The survivability of the UN TRISO particle was estimated depending on the strain behavior of the constituent materials at high fast fluence and burn up. For nominal cases, internal gas pressure and representative thermal profiles across the kernel and layers were determined along with stress levels in the inner and outer pyrolytic carbon (IPyC/OPyC) and silicon carbide (SiC) layers. These parameters were then used to evaluate fuel particle failure probabilities. Results of the study show that the survivability of UN TRISO fuel under LWR irradiation conditions might only be guaranteed if the kernel and PyC swelling rates are limited at high fast fluence and burn up. These material properties have large uncertainties at the irradiation levels expected to be reached by UN TRISO fuel in LWRs. Therefore, a large experimental effort would be needed to establish material properties, including kernel and PyC swelling rates, under these conditions before definitive conclusions can be drawn on the behavior of UN TRISO fuel in LWRs.

  8. Grain Boundary Percolation Modeling of Fission Gas Release in Oxide Fuels

    SciTech Connect (OSTI)

    Paul C. Millett; Michael R. Tonks; S. B. Biner

    2012-05-01

    We present a new approach to fission gas release modeling in oxide fuels based on grain boundary network percolation. The method accounts for variability in the bubble growth and coalescence rates on individual grain boundaries, and the resulting effect on macroscopic fission gas release. Two-dimensional representa- tions of fuel pellet microstructures are considered, and the resulting gas release rates are compared with traditional two-stage Booth models, which do not account for long-range percolation on grain boundary net- works. The results show that the requirement of percolation of saturated grain boundaries can considerably reduce the total gas release rates, particularly when gas resolution is considered.

  9. Fuel Cell Power Model Elucidates Life-Cycle Costs for Fuel Cell-Based Combined Heat, Hydrogen, and Power (CHHP) Production Systems (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2010-11-01

    This fact sheet describes NREL's accomplishments in accurately modeling costs for fuel cell-based combined heat, hydrogen, and power systems. Work was performed by NREL's Hydrogen Technologies and Systems Center.

  10. TRISO Fuel Performance: Modeling, Integration into Mainstream Design Studies, and Application to a Thorium-fueled Fusion-Fission Hybrid Blanket

    E-Print Network [OSTI]

    Powers, Jeffrey

    2011-01-01

    Neutronics Models and Methodologies 3.1 Thorium LIFE DesignEngine. . .Design Parameters for Thorium-fueled LIFE TRISOburnup value for DU and Thorium hybrid LIFE engine designs

  11. Experimental and Modeling Study of the Flammability of Fuel Tank Headspace Vapors from Ethanol/Gasoline Fuels, Phase 2: Evaluations of Field Samples and Laboratory Blends

    SciTech Connect (OSTI)

    Gardiner, D. P.; Bardon, M. F.; LaViolette, M.

    2010-04-01

    Study to measure the flammability of gasoline/ethanol fuel vapors at low ambient temperatures and develop a mathematical model to predict temperatures at which flammable vapors were likely to form.

  12. Modeling and Control for PEM Fuel Cell Stack System I Jay T. Pukrushpan, Anna G. Stefanopoulou, Huei Peng

    E-Print Network [OSTI]

    Peng, Huei

    Modeling and Control for PEM Fuel Cell Stack System I Jay T. Pukrushpan, Anna G. Stefanopoulou~umich, edu, hpeng@umich, edu Abstract A nonlinear fuel cell system dynamic model that is suit- able, the reactant partial pres- sures. Characterization of the Fuel Cell polarization curves based on time varying

  13. Journal of Power Sources 162 (2006) 388399 Model-based condition monitoring of PEM fuel cell using

    E-Print Network [OSTI]

    Ding, Yu

    2006-01-01

    Journal of Power Sources 162 (2006) 388­399 Model-based condition monitoring of PEM fuel cell using of polymer electrolyte membrane (PEM) fuel cell systems, temporary faults in such systems still might occur/uncertainty of the fuel cell system, and the measurement noise. In this research, we propose a model-based condition

  14. Capital Project Authorization

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B LReports from the CloudGEGR-NOperatorsCan'tPower |

  15. Capital Project Prioritization

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B LReports from the CloudGEGR-NOperatorsCan'tPower

  16. 2011 Strategic Capital Discussions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-InspiredAtmosphericdevicesPPONe β+-DecayUpgrade P. May, G.J.11 News

  17. Capital Reporting Company

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia National 1 PAGE 1 OF2Guidance to the1 1 9B.|.© 2013 2 1

  18. Capital Reporting Company

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia National 1 PAGE 1 OF2Guidance to the1 1 9B.|.© 2013 2 1

  19. Capital Reporting Company

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p a lCarib Energy (USA) LLCAdministrationAward-LNG -07-11-2014 (866) 448

  20. Capital Reporting Company

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p a lCarib Energy (USA) LLCAdministrationAward-LNG -07-11-2014 (866) 448

  1. Capital Reporting Company

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p a lCarib Energy (USA) LLCAdministrationAward-LNG -07-11-2014 (866)

  2. Major Capital Projects

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport)Price (Dollars per Thousand CubicMaintaining6 $ 45.6 $

  3. Major Capital Projects

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport)Price (Dollars per Thousand CubicMaintaining6 $ 45.6 $0 $

  4. Major Capital Projects

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport)Price (Dollars per Thousand CubicMaintaining6 $ 45.6 $0

  5. Major Capital Projects

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport)Price (Dollars per Thousand CubicMaintaining6 $ 45.6 $06

  6. Major Capital Projects

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport)Price (Dollars per Thousand CubicMaintaining6 $ 45.6

  7. Major Capital Projects

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport)Price (Dollars per Thousand CubicMaintaining6 $ 45.6mile

  8. Major Capital Projects

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport)Price (Dollars per Thousand CubicMaintaining6 $

  9. Major Capital Projects

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport)Price (Dollars per Thousand CubicMaintaining6 $6 $ 46.2 $

  10. System Design Description and Requirements for Modeling the Off-Gas Systems for Fuel Recycling Facilities

    SciTech Connect (OSTI)

    Daryl R. Haefner; Jack D. Law; Troy J. Tranter

    2010-08-01

    This document provides descriptions of the off-gases evolved during spent nuclear fuel processing and the systems used to capture the gases of concern. Two reprocessing techniques are discussed, namely aqueous separations and electrochemical (pyrochemical) processing. The unit operations associated with each process are described in enough detail so that computer models to mimic their behavior can be developed. The document also lists the general requirements for the desired computer models.

  11. Benchmarking of the MIT High Temperature Gas-cooled Reactor TRISO-coated particle fuel performance model

    E-Print Network [OSTI]

    Stawicki, Michael A

    2006-01-01

    MIT has developed a Coated Particle Fuel Performance Model to study the behavior of TRISO nuclear fuels. The code, TIMCOAT, is designed to assess the mechanical and chemical condition of populations of coated particles and ...

  12. Control-relevant Modelling and Linear Analysis of Instabilities in Oxy-fuel Combustion

    E-Print Network [OSTI]

    Foss, Bjarne A.

    Control-relevant Modelling and Linear Analysis of Instabilities in Oxy-fuel Combustion Dagfinn combustion have been proposed as an alternative to conventional gas turbine cycles for achieving CO2-capture for CO2 sequestration purposes. While combustion instabilities is a problem in modern conventional gas

  13. Dynamic First-Principles Molecular-Scale Model for Solid Oxide Fuel Cells V. Hugo Schmidt

    E-Print Network [OSTI]

    vs. current density i characteristics applies both to the Solid Oxide Fuel Cell (SOFC) and Solid accurately the V(i) curves obtained by Jiang and Virkar (1). We will apply the model to other SOFC results from our laboratory and elsewhere, and use it to predict performance of proposed SOFC designs

  14. Development and validation of a combustion model for a fuel cell off-gas burner

    E-Print Network [OSTI]

    Collins, William Tristan

    2008-10-14

    Burner Details 164 C.1 Burner Inlet Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 C.2 Emission Indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 List of References 173 List of Figures 1.1 SOFC... Steady Laminar Flamelet Model . . . . . . . . . . . . . . . . . . . . . . 16 SOFC Solid Oxide Fuel Cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 UDF User De?ned Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73...

  15. A combustion model for IC engine combustion simulations with multi-component fuels

    SciTech Connect (OSTI)

    Ra, Youngchul; Reitz, Rolf D.

    2011-01-15

    Reduced chemical kinetic mechanisms for the oxidation of representative surrogate components of a typical multi-component automotive fuel have been developed and applied to model internal combustion engines. Starting from an existing reduced mechanism for primary reference fuel (PRF) oxidation, further improvement was made by including additional reactions and by optimizing reaction rate constants of selected reactions. Using a similar approach to that used to develop the reduced PRF mechanism, reduced mechanisms for the oxidation of n-tetradecane, toluene, cyclohexane, dimethyl ether (DME), ethanol, and methyl butanoate (MB) were built and combined with the PRF mechanism to form a multi-surrogate fuel chemistry (MultiChem) mechanism. The final version of the MultiChem mechanism consists of 113 species and 487 reactions. Validation of the present MultiChem mechanism was performed with ignition delay time measurements from shock tube tests and predictions by comprehensive mechanisms available in the literature. A combustion model was developed to simulate engine combustion with multi-component fuels using the present MultiChem mechanism, and the model was applied to simulate HCCI and DI engine combustion. The results show that the present multi-component combustion model gives reliable performance for combustion predictions, as well as computational efficiency improvements through the use of reduced mechanism for multi-dimensional CFD simulations. (author)

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

    E-Print Network [OSTI]

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

    2013-06-19

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

  17. Uncertainty and sensitivity analysis of fission gas behavior in engineering-scale fuel modeling

    SciTech Connect (OSTI)

    G. Pastore; L.P. Swiler; J.D. Hales; S.R. Novascone; D.M. Perez; B.W. Spencer; L. Luzzi; P. Van Uffelen; R.L. Williamson

    2014-10-01

    The role of uncertainties in fission gas behavior calculations as part of engineering-scale nuclear fuel modeling is investigated using the BISON fuel performance code and a recently implemented physics-based model for the coupled fission gas release and swelling. Through the integration of BISON with the DAKOTA software, a sensitivity analysis of the results to selected model parameters is carried out based on UO2 single-pellet simulations covering different power regimes. The parameters are varied within ranges representative of the relative uncertainties and consistent with the information from the open literature. The study leads to an initial quantitative assessment of the uncertainty in fission gas behavior modeling with the parameter characterization presently available. Also, the relative importance of the single parameters is evaluated. Moreover, a sensitivity analysis is carried out based on simulations of a fuel rod irradiation experiment, pointing out a significant impact of the considered uncertainties on the calculated fission gas release and cladding diametral strain. The results of the study indicate that the commonly accepted deviation between calculated and measured fission gas release by a factor of 2 approximately corresponds to the inherent modeling uncertainty at high fission gas release. Nevertheless, higher deviations may be expected for values around 10% and lower. Implications are discussed in terms of directions of research for the improved modeling of fission gas behavior for engineering purposes.

  18. Capital Project 2 | P a g e

    E-Print Network [OSTI]

    Pittendrigh, Barry

    construction. Facility additions, renovations, and/or capital improvement projects estimated to cost $2 millionCapital Project Planning Process #12;2 | P a g e Capital Planning Overview The planning process overview presented in this document combines work being conducted by both Physical and Capital Planning

  19. TianDi Growth Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Information Serbia-EnhancingEt Al., 2013)Open Energy Information ThreeTianDi Growth Capital Jump to:

  20. Mexico-Capital Markets Climate Initiative | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop Inc Jump to: navigation,Mereg GmbH Jump to: navigation,EnergyCapital Markets

  1. PvT Capital Gmbh | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop Inc Jump to:Newberg,Energy LLCALLETE Inc dEAPrysmianPvT Capital Gmbh Jump to:

  2. Carbon Credit Capital and Feedback Ventures JV | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmentalBowerbank,Cammack Village, Arkansas: EnergyCounty,NewHatteras2ConnectionsUtah:Capital

  3. MP2 CapitalLLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsource HistoryScenarios Towards 2050Enermar <OMISPowerTurbine forMHKMP2 CapitalLLC

  4. BioLogical Capital BLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop IncIowaWisconsin: EnergyYorkColoradoBelcherCarbonAlgeneBioLogical Capital BLC Jump

  5. CE2 Capital Partners LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButte County, California: Energy Resources JumpEmissionCapital Partners LLC Jump

  6. A general approach to develop reduced order models for simulation of solid oxide fuel cell stacks

    SciTech Connect (OSTI)

    Pan, Wenxiao; Bao, Jie; Lo, Chaomei; Lai, Canhai; Agarwal, Khushbu; Koeppel, Brian J.; Khaleel, Mohammad A.

    2013-06-15

    A reduced order modeling approach based on response surface techniques was developed for solid oxide fuel cell stacks. This approach creates a numerical model that can quickly compute desired performance variables of interest for a stack based on its input parameter set. The approach carefully samples the multidimensional design space based on the input parameter ranges, evaluates a detailed stack model at each of the sampled points, and performs regression for selected performance variables of interest to determine the responsive surfaces. After error analysis to ensure that sufficient accuracy is established for the response surfaces, they are then implemented in a calculator module for system-level studies. The benefit of this modeling approach is that it is sufficiently fast for integration with system modeling software and simulation of fuel cell-based power systems while still providing high fidelity information about the internal distributions of key variables. This paper describes the sampling, regression, sensitivity, error, and principal component analyses to identify the applicable methods for simulating a planar fuel cell stack.

  7. FATE Unified Modeling Method for Spent Nuclear Fuel and Sludge Processing, Shipping and Storage - 13405

    SciTech Connect (OSTI)

    Plys, Martin; Burelbach, James; Lee, Sung Jin; Apthorpe, Robert

    2013-07-01

    A unified modeling method applicable to the processing, shipping, and storage of spent nuclear fuel and sludge has been incrementally developed, validated, and applied over a period of about 15 years at the US DOE Hanford site. The software, FATE{sup TM}, provides a consistent framework for a wide dynamic range of common DOE and commercial fuel and waste applications. It has been used during the design phase, for safety and licensing calculations, and offers a graded approach to complex modeling problems encountered at DOE facilities and abroad (e.g., Sellafield). FATE has also been used for commercial power plant evaluations including reactor building fire modeling for fire PRA, evaluation of hydrogen release, transport, and flammability for post-Fukushima vulnerability assessment, and drying of commercial oxide fuel. FATE comprises an integrated set of models for fluid flow, aerosol and contamination release, transport, and deposition, thermal response including chemical reactions, and evaluation of fire and explosion hazards. It is one of few software tools that combine both source term and thermal-hydraulic capability. Practical examples are described below, with consideration of appropriate model complexity and validation. (authors)

  8. UC Merced -Capital Planning and Space Management (updated August 2012) Capital Planning Process

    E-Print Network [OSTI]

    Oviedo, Néstor J.

    Improvement Projects based on project cost: #12;UC Merced - Capital Planning and Space Management (updated with an estimated cost greater than $750,000. These projects are included in the Capital Financial Plan Capital Improvements varies based on the project cost. · Minor Capital Improvements Minor Capital

  9. Summary report on the fuel performance modeling of the AFC-2A, 2B irradiation experiments

    SciTech Connect (OSTI)

    Pavel G. Medvedev

    2013-09-01

    The primary objective of this work at the Idaho National Laboratory (INL) is to determine the fuel and cladding temperature history during irradiation of the AFC-2A, 2B transmutation metallic fuel alloy irradiation experiments containing transuranic and rare earth elements. Addition of the rare earth elements intends to simulate potential fission product carry-over from pyro-metallurgical reprocessing. Post irradiation examination of the AFC-2A, 2B rodlets revealed breaches in the rodlets and fuel melting which was attributed to the release of the fission gas into the helium gap between the rodlet cladding and the capsule which houses six individually encapsulated rodlets. This release is not anticipated during nominal operation of the AFC irradiation vehicle that features a double encapsulated design in which sodium bonded metallic fuel is separated from the ATR coolant by the cladding and the capsule walls. The modeling effort is focused on assessing effects of this unanticipated event on the fuel and cladding temperature with an objective to compare calculated results with the temperature limits of the fuel and the cladding.

  10. Development of Novel PEM Membrane and Multiphase CD Modeling of PEM Fuel Cell

    SciTech Connect (OSTI)

    K. J. Berry; Susanta Das

    2009-12-30

    To understand heat and water management phenomena better within an operational proton exchange membrane fuel cell's (PEMFC) conditions, a three-dimensional, two-phase computational fluid dynamic (CFD) flow model has been developed and simulated for a complete PEMFC. Both liquid and gas phases are considered in the model by taking into account the gas flow, diffusion, charge transfer, change of phase, electro-osmosis, and electrochemical reactions to understand the overall dynamic behaviors of species within an operating PEMFC. The CFD model is solved numerically under different parametric conditions in terms of water management issues in order to improve cell performance. The results obtained from the CFD two-phase flow model simulations show improvement in cell performance as well as water management under PEMFCs operational conditions as compared to the results of a single phase flow model available in the literature. The quantitative information obtained from the two-phase model simulation results helped to develop a CFD control algorithm for low temperature PEM fuel cell stacks which opens up a route in designing improvement of PEMFC for better operational efficiency and performance. To understand heat and water management phenomena better within an operational proton exchange membrane fuel cell's (PEMFC) conditions, a three-dimensional, two-phase computational fluid dynamic (CFD) flow model has been developed and simulated for a complete PEMFC. Both liquid and gas phases are considered in the model by taking into account the gas flow, diffusion, charge transfer, change of phase, electro-osmosis, and electrochemical reactions to understand the overall dynamic behaviors of species within an operating PEMFC. The CFD model is solved numerically under different parametric conditions in terms of water management issues in order to improve cell performance. The results obtained from the CFD two-phase flow model simulations show improvement in cell performance as well as water management under PEMFCs operational conditions as compared to the results of a single phase flow model available in the literature. The quantitative information obtained from the two-phase model simulation results helped to develop a CFD control algorithm for low temperature PEM fuel cell stacks which opens up a route in designing improvement of PEMFC for better operational efficiency and performance.

  11. Models for the Configuration and Integrity of Partially Oxidized Fuel Rod Cladding at High Temperatures

    SciTech Connect (OSTI)

    Siefken, L.J.

    1999-01-01

    Models were designed to resolve deficiencies in the SCDAP/RELAP5/MOD3.2 calculations of the configuration and integrity of hot, partially oxidized cladding. These models are expected to improve the calculations of several important aspects of fuel rod behavior. First, an improved mapping was established from a compilation of PIE results from severe fuel damage tests of the configuration of melted metallic cladding that is retained by an oxide layer. The improved mapping accounts for the relocation of melted cladding in the circumferential direction. Then, rules based on PIE results were established for calculating the effect of cladding that has relocated from above on the oxidation and integrity of the lower intact cladding upon which it solidifies. Next, three different methods were identified for calculating the extent of dissolution of the oxidic part of the cladding due to its contact with the metallic part. The extent of dissolution effects the stress and thus the integrity of the oxidic part of the cladding. Then, an empirical equation was presented for calculating the stress in the oxidic part of the cladding and evaluating its integrity based on this calculated stress. This empirical equation replaces the current criterion for loss of integrity which is based on temperature and extent of oxidation. Finally, a new rule based on theoretical and experimental results was established for identifying the regions of a fuel rod with oxidation of both the inside and outside surfaces of the cladding. The implementation of these models is expected to eliminate the tendency of the SCDAP/RELAP5 code to overpredict the extent of oxidation of the upper part of fuel rods and to underpredict the extent of oxidation of the lower part of fuel rods and the part with a high concentration of relocated material. This report is a revision and reissue of the report entitled, Improvements in Modeling of Cladding Oxidation and Meltdown.

  12. Evaluating health care programs by combining cost with quality of life measures: a case study comparing capitation and Fee for Service

    E-Print Network [OSTI]

    Sekhon, Jasjeet S.

    .10. Conclusions. A capitation model with a for profit element was more cost-effective for Medicaid patients with severe mental illness than not-for-profit capitation or FFS models. Key words: cost model. Some of these studies reported that reimbursement by capitation was associated with lower costs

  13. Transmission line capital costs

    SciTech Connect (OSTI)

    Hughes, K.R.; Brown, D.R.

    1995-05-01

    The displacement or deferral of conventional AC transmission line installation is a key benefit associated with several technologies being developed with the support of the U.S. Department of Energy`s Office of Energy Management (OEM). Previous benefits assessments conducted within OEM have been based on significantly different assumptions for the average cost per mile of AC transmission line. In response to this uncertainty, an investigation of transmission line capital cost data was initiated. The objective of this study was to develop a database for preparing preliminary estimates of transmission line costs. An extensive search of potential data sources identified databases maintained by the Bonneville Power Administration (BPA) and the Western Area Power Administration (WAPA) as superior sources of transmission line cost data. The BPA and WAPA data were adjusted to a common basis and combined together. The composite database covers voltage levels from 13.8 to 765 W, with cost estimates for a given voltage level varying depending on conductor size, tower material type, tower frame type, and number of circuits. Reported transmission line costs vary significantly, even for a given voltage level. This can usually be explained by variation in the design factors noted above and variation in environmental and land (right-of-way) costs, which are extremely site-specific. Cost estimates prepared from the composite database were compared to cost data collected by the Federal Energy Regulatory Commission (FERC) for investor-owned utilities from across the United States. The comparison was hampered because the only design specifications included with the FERC data were voltage level and line length. Working within this limitation, the FERC data were not found to differ significantly from the composite database. Therefore, the composite database was judged to be a reasonable proxy for estimating national average costs.

  14. WaterTransport in PEM Fuel Cells: Advanced Modeling, Material Selection, Testing and Design Optimization

    SciTech Connect (OSTI)

    J. Vernon Cole; Abhra Roy; Ashok Damle; Hari Dahr; Sanjiv Kumar; Kunal Jain; Ned Djilai

    2012-10-02

    Water management in Proton Exchange Membrane, PEM, Fuel Cells is challenging because of the inherent conflicts between the requirements for efficient low and high power operation. Particularly at low powers, adequate water must be supplied to sufficiently humidify the membrane or protons will not move through it adequately and resistance losses will decrease the cell efficiency. At high power density operation, more water is produced at the cathode than is necessary for membrane hydration. This excess water must be removed effectively or it will accumulate in the Gas Diffusion Layers, GDLs, between the gas channels and catalysts, blocking diffusion paths for reactants to reach the catalysts and potentially flooding the electrode. As power density of the cells is increased, the challenges arising from water management are expected to become more difficult to overcome simply due to the increased rate of liquid water generation relative to fuel cell volume. Thus, effectively addressing water management based issues is a key challenge in successful application of PEMFC systems. In this project, CFDRC and our partners used a combination of experimental characterization, controlled experimental studies of important processes governing how water moves through the fuel cell materials, and detailed models and simulations to improve understanding of water management in operating hydrogen PEM fuel cells. The characterization studies provided key data that is used as inputs to all state-of-the-art models for commercially important GDL materials. Experimental studies and microscopic scale models of how water moves through the GDLs showed that the water follows preferential paths, not branching like a river, as it moves toward the surface of the material. Experimental studies and detailed models of water and airflow in fuel cells channels demonstrated that such models can be used as an effective design tool to reduce operating pressure drop in the channels and the associated costs and weight of blowers and pumps to force air and hydrogen gas through the fuel cell. Promising improvements to materials structure and surface treatments that can potentially aid in managing the distribution and removal of liquid water were developed; and improved steady-state and freeze-thaw performance was demonstrated for a fuel cell stack under the self-humidified operating conditions that are promising for stationary power generation with reduced operating costs.

  15. A comparison of geospatially modeled fire behavior and potential application to fire and fuels management for the Savannah River Site.

    SciTech Connect (OSTI)

    Kurth, Laurie; Hollingsworth, LaWen; Shea, Dan

    2011-12-20

    This study evaluates modeled fire behavior for the Savannah River Site in the Atlantic Coastal Plain of the southeastern U.S. using three data sources: FCCS, LANDFIRE, and SWRA. The Fuel Characteristic Classification System (FCCS) was used to build fuelbeds from intensive field sampling of 629 plots. Custom fire behavior fuel models were derived from these fuelbeds. LANDFIRE developed surface fire behavior fuel models and canopy attributes for the U.S. using satellite imagery informed by field data. The Southern Wildfire Risk Assessment (SWRA) developed surface fire behavior fuel models and canopy cover for the southeastern U.S. using satellite imagery.

  16. Regional refining models for alternative fuels using shale and coal synthetic crudes: identification and evaluation of optimized alternative fuels. Annual report, March 20, 1979-March 19, 1980

    SciTech Connect (OSTI)

    Sefer, N.R.; Russell, J.A.

    1980-11-01

    The initial phase has been completed in the project to evaluate alternative fuels for highway transportation from synthetic crudes. Three refinery models were developed for Rocky Mountain, Mid-Continent and Great Lakes regions to make future product volumes and qualities forecast for 1995. Projected quantities of shale oil and coal oil syncrudes were introduced into the raw materials slate. Product slate was then varied from conventional products to evaluate maximum diesel fuel and broadcut fuel in all regions. Gasoline supplement options were evaluated in one region for 10% each of methanol, ethanol, MTBE or synthetic naphtha in the blends along with syncrude components. Compositions and qualities of the fuels were determined for the variation in constraints and conditions established for the study. Effects on raw materials, energy consumption and investment costs were reported. Results provide the basis to formulate fuels for laboratory and engine evaluation in future phases of the project.

  17. Coupling the Mixed Potential and Radiolysis Models for Used Fuel Degradation

    SciTech Connect (OSTI)

    Buck, Edgar C.; Jerden, James L.; Ebert, William L.; Wittman, Richard S.

    2013-08-30

    The primary purpose of this report is to describe the strategy for coupling three process level models to produce an integrated Used Fuel Degradation Model (FDM). The FDM, which is based on fundamental chemical and physical principals, provides direct calculation of radionuclide source terms for use in repository performance assessments. The G-value for H2O2 production (Gcond) to be used in the Mixed Potential Model (MPM) (H2O2 is the only radiolytic product presently included but others will be added as appropriate) needs to account for intermediate spur reactions. The effects of these intermediate reactions on [H2O2] are accounted for in the Radiolysis Model (RM). This report details methods for applying RM calculations that encompass the effects of these fast interactions on [H2O2] as the solution composition evolves during successive MPM iterations and then represent the steady-state [H2O2] in terms of an “effective instantaneous or conditional” generation value (Gcond). It is anticipated that the value of Gcond will change slowly as the reaction progresses through several iterations of the MPM as changes in the nature of fuel surface occur. The Gcond values will be calculated with the RM either after several iterations or when concentrations of key reactants reach threshold values determined from previous sensitivity runs. Sensitivity runs with RM indicate significant changes in G-value can occur over narrow composition ranges. The objective of the mixed potential model (MPM) is to calculate the used fuel degradation rates for a wide range of disposal environments to provide the source term radionuclide release rates for generic repository concepts. The fuel degradation rate is calculated for chemical and oxidative dissolution mechanisms using mixed potential theory to account for all relevant redox reactions at the fuel surface, including those involving oxidants produced by solution radiolysis and provided by the radiolysis model (RM). The RM calculates the concentration of species generated at any specific time and location from the surface of the fuel. Several options being considered for coupling the RM and MPM are described in the report. Different options have advantages and disadvantages based on the extent of coding that would be required and the ease of use of the final product.

  18. Covenant Community Capital Mission: Covenant Community Capital equips working families to thrive financially

    E-Print Network [OSTI]

    Aazhang, Behnaam

    Covenant Community Capital Mission: Covenant Community Capital equips developments. Since its establishment, Covenant Community Capital has helped over 600. Research and develop a strategy for Covenant to acquire donated and low-cost

  19. ESTIMATION OF ETHANOL CONTENT IN FLEX-FUEL VEHICLES USING AN EXHAUST GAS OXYGEN SENSOR: MODEL, TUNING AND SENSITIVITY

    E-Print Network [OSTI]

    Stefanopoulou, Anna

    ESTIMATION OF ETHANOL CONTENT IN FLEX-FUEL VEHICLES USING AN EXHAUST GAS OXYGEN SENSOR: MODEL periods of intense interest in using ethanol as an alternative fuel to petroleum-based gasoline and diesel derivatives. Currently available flexible fuel vehicles (FFVs) can operate on a blend of gasoline and ethanol

  20. A Computational Model of the Mark-IV Electrorefiner: Phase I -- Fuel Basket/Salt Interface

    SciTech Connect (OSTI)

    Robert Hoover; Supathorn Phongikaroon; Shelly Li; Michael Simpson; Tae-Sic Yoo

    2009-09-01

    Spent driver fuel from the Experimental Breeder Reactor-II (EBR-II) is currently being treated in the Mk-IV electrorefiner (ER) in the Fuel Conditioning Facility (FCF) at Idaho National Laboratory. The modeling approach to be presented here has been developed to help understand the effect of different parameters on the dynamics of this system. The first phase of this new modeling approach focuses on the fuel basket/salt interface involving the transport of various species found in the driver fuels (e.g. uranium and zirconium). This approach minimizes the guessed parameters to only one, the exchange current density (i0). U3+ and Zr4+ were the only species used for the current study. The result reveals that most of the total cell current is used for the oxidation of uranium, with little being used by zirconium. The dimensionless approach shows that the total potential is a strong function of i0 and a weak function of wt% of uranium in the salt system for initiation processes.

  1. RELAP5 model of the high flux isotope reactor with low enriched fuel thermal flux profiles

    SciTech Connect (OSTI)

    Banfield, J.; Mervin, B.; Hart, S.; Ritchie, J.; Walker, S.; Ruggles, A.; Maldonado, G. I. [Dept. of Nuclear Engineering, Univ. of Tennessee Knoxville, Knoxville, TN 37996-2300 (United States)

    2012-07-01

    The High Flux Isotope Reactor (HFIR) currently uses highly enriched uranium (HEU) fabricated into involute-shaped fuel plates. It is desired that HFIR be able to use low enriched uranium (LEU) fuel while preserving the current performance capability for its diverse missions in material irradiation studies, isotope production, and the use of neutron beam lines for basic research. Preliminary neutronics and depletion simulations of HFIR with LEU fuel have arrived to feasible fuel loadings that maintain the neutronics performance of the reactor. This article illustrates preliminary models developed for the analysis of the thermal-hydraulic characteristics of the LEU core to ensure safe operation of the reactor. The beginning of life (BOL) LEU thermal flux profile has been modeled in RELAP5 to facilitate steady state simulation of the core cooling, and of anticipated and unanticipated transients. Steady state results are presented to validate the new thermal power profile inputs. A power ramp, slow depressurization at the outlet, and flow coast down transients are also evaluated. (authors)

  2. A REVIEW OF ASSUMPTIONS AND ANALYSIS IN EPRI EA-3409, "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPS BEHAVIORAL MODELS"

    E-Print Network [OSTI]

    Wood, D.J.

    2010-01-01

    to separate fuel price and capital cost effects from non-for any household's heat pump capital costs, and replace theto own fuel prices, own capital costs, and household income.

  3. Fuel quality issues in stationary fuel cell systems.

    SciTech Connect (OSTI)

    Papadias, D.; Ahmed, S.; Kumar, R.

    2012-02-07

    Fuel cell systems are being deployed in stationary applications for the generation of electricity, heat, and hydrogen. These systems use a variety of fuel cell types, ranging from the low temperature polymer electrolyte fuel cell (PEFC) to the high temperature solid oxide fuel cell (SOFC). Depending on the application and location, these systems are being designed to operate on reformate or syngas produced from various fuels that include natural gas, biogas, coal gas, etc. All of these fuels contain species that can potentially damage the fuel cell anode or other unit operations and processes that precede the fuel cell stack. These detrimental effects include loss in performance or durability, and attenuating these effects requires additional components to reduce the impurity concentrations to tolerable levels, if not eliminate the impurity entirely. These impurity management components increase the complexity of the fuel cell system, and they add to the system's capital and operating costs (such as regeneration, replacement and disposal of spent material and maintenance). This project reviewed the public domain information available on the impurities encountered in stationary fuel cell systems, and the effects of the impurities on the fuel cells. A database has been set up that classifies the impurities, especially in renewable fuels, such as landfill gas and anaerobic digester gas. It documents the known deleterious effects on fuel cells, and the maximum allowable concentrations of select impurities suggested by manufacturers and researchers. The literature review helped to identify the impurity removal strategies that are available, and their effectiveness, capacity, and cost. A generic model of a stationary fuel-cell based power plant operating on digester and landfill gas has been developed; it includes a gas processing unit, followed by a fuel cell system. The model includes the key impurity removal steps to enable predictions of impurity breakthrough, component sizing, and utility needs. These data, along with process efficiency results from the model, were subsequently used to calculate the cost of electricity. Sensitivity analyses were conducted to correlate the concentrations of key impurities in the fuel gas feedstock to the cost of electricity.

  4. Economic feasibility analysis of distributed electric power generation based upon the natural gas-fired fuel cell. Final report

    SciTech Connect (OSTI)

    Not Available

    1994-03-01

    The final report provides a summary of results of the Cost of Ownership Model and the circumstances under which a distributed fuel cell is economically viable. The analysis is based on a series of micro computer models estimate the capital and operations cost of a fuel cell central utility plant configuration. Using a survey of thermal and electrical demand profiles, the study defines a series of energy user classes. The energy user class demand requirements are entered into the central utility plant model to define the required size the fuel cell capacity and all supporting equipment. The central plant model includes provisions that enables the analyst to select optional plant features that are most appropriate to a fuel cell application, and that are cost effective. The model permits the choice of system features that would be suitable for a large condominium complex or a residential institution such as a hotel, boarding school or prison. Other applications are also practical; however, such applications have a higher relative demand for thermal energy, a characteristic that is well-suited to a fuel cell application with its free source of hot water or steam. The analysis combines the capital and operation from the preceding models into a Cost of Ownership Model to compute the plant capital and operating costs as a function of capacity and principal features and compares these estimates to the estimated operating cost of the same central plant configuration without a fuel cell.

  5. Modelling of thermo-mechanical and irradiation behavior of metallic and oxide fuels for sodium fast reactors

    E-Print Network [OSTI]

    Karahan, Aydin

    2009-01-01

    A robust and reliable code to model the irradiation behavior of metal and oxide fuels in sodium cooled fast reactors is developed. Modeling capability was enhanced by adopting a non-empirical mechanistic approach to the ...

  6. Capital Projects Estimated >$7 Million in Direct Costs Business

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B LReports from the CloudGEGR-NOperatorsCan'tPowerCapital Projects

  7. EA-185 Morgan Stanley Capital Group Inc. | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergy A plug-in electricLaboratoryofNotices |DynegyPowerexMorgan Stanley Capital Group

  8. EM Capital Asset Project List | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergy A plug-inPPL EnergyPlus, LLC to5USC787StatementDepartment'sRead the EM Capital Asset

  9. Guide to IT Capital Planning and Investment Control

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i nA Guide to Tapping STD-1128-2013levelGUIDE TO FEDERAL REGULATION OFIT Capital

  10. Mathematical Modeling of Liquid-Feed Direct Methanol Fuel Z. H. Wang* and C. Y. Wang*,z

    E-Print Network [OSTI]

    Mathematical Modeling of Liquid-Feed Direct Methanol Fuel Cells Z. H. Wang* and C. Y. Wang for liquid-feed direct methanol fuel cells DMFC . In addition to the anode and cathode electrochemical-osmosis. This comprehensive model is solved numerically using computational fluid dynamics. The transport phenomena

  11. Journal of Power Sources 164 (2007) 189195 Modeling water transport in liquid feed direct methanol fuel cells

    E-Print Network [OSTI]

    2007-01-01

    Journal of Power Sources 164 (2007) 189­195 Modeling water transport in liquid feed direct methanol management in direct methanol fuel cells (DMFCs) is very critical and complicated because of many interacting rights reserved. Keywords: Direct methanol fuel cell; Water transport; Mathematical modeling; Three

  12. Deterministic contact mechanics model applied to electrode interfaces in polymer electrolyte fuel cells and interfacial water accumulation

    E-Print Network [OSTI]

    Litster, Shawn

    in polymer electrolyte fuel cells (PEFCs) to elucidate the interfacial morphology. The model employs measured Elsevier B.V. All rights reserved. 1. Introduction Polymer electrolyte fuel cells (PEFC) are promising, mathematical models are valuable tools often used in evaluating multiphase transport phenomena in PEFC

  13. Optimal Portfolio Management with Transactions Costs and Capital Gains Taxes

    E-Print Network [OSTI]

    Leland, Hayne E.

    1999-01-01

    with Transactions Costs and Capital Gains Taxes Hayne E.of Transactions Costs and Capital gains Taxes," SeptemberWITH TRANSACTIONS COSTS AND CAPITAL GAINS TAXES I.

  14. Fuel Cell Technologies Office Multi-Year Research, Development...

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

    Currently, hydrogen production is capital-intensive. Widespread adoption of hydrogen fuel cells requires consumers to have access to cost-competitive hydrogen. Steam methane...

  15. Modeling Low-Platinum-Loading Effects in Fuel-Cell Catalyst Layers

    E-Print Network [OSTI]

    Yoon, Wonseok

    2013-01-01

    of Low Pt- Loading Cathodes in PEM Fuel Cells, in8th International Fuel Cell Science, Engineeriung &Loading Effects in Fuel-Cell Catalyst Layers Wonseok Yoon*

  16. Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles

    E-Print Network [OSTI]

    Zhao, Hengbing; Burke, Andy

    2008-01-01

    for fuel cell systems for vehicle applications, Journal ofuse in fuel cell vehicles and other applications has beenin automotive applications, the fuel cell systems has to be

  17. Using a Quasipotential Transformation for Modeling Diffusion Media in Polymer-Electrolyte Fuel Cells

    E-Print Network [OSTI]

    Weber, Adam Z.

    2008-01-01

    Proton Exchange Membrane Fuel Cell , Numerical Heat Transferof Polymer Electrolyte Fuel Cells Using a Two-EquationLayers for Proton Exchange Membrane Fuel Cells 2. Absolute

  18. Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles

    E-Print Network [OSTI]

    Zhao, Hengbing; Burke, Andy

    2008-01-01

    operating conditions. Direct Hydrogen Fuel Cell System Modelconditions for a direct hydrogen fuel cell system Table 1simulation tool for hydrogen fuel cell vehicles, Journal of

  19. Incorporating stakeholders' perspectives into models of new technology diffusion: The case of fuel-cell vehicles

    E-Print Network [OSTI]

    Collantes, Gustavo O

    2007-01-01

    dual superiority of hydrogen fuel-cell vehicles (FCVs) hasneeded to position the hydrogen–fuel cell combination as avolume, accessibility to hydrogen fuel dispensing stations,

  20. Using a Quasipotential Transformation for Modeling Diffusion Media in Polymer-Electrolyte Fuel Cells

    E-Print Network [OSTI]

    Weber, Adam Z.

    2008-01-01

    Proton Exchange Membrane Fuel Cell , Numerical Heat Transferof Polymer Electrolyte Fuel Cells Using a Two-EquationExchange Membrane Fuel Cells 2. Absolute Permeability ,

  1. Using a Quasipotential Transformation for Modeling Diffusion Media in Polymer-Electrolyte Fuel Cells

    E-Print Network [OSTI]

    Weber, Adam Z.

    2008-01-01

    Exchange Membrane Fuel Cells , Journal of Power Sources,in Polymer-Electrolyte Fuel Cells , in M. Schlesinger, ed. ,in Polymer- Electrolyte Fuel Cells , Journal of the

  2. Fluid-Structure Interaction Modeling of High-Aspect Ratio Nuclear Fuel Plates Using COMSOL

    SciTech Connect (OSTI)

    Curtis, Franklin G [ORNL] [ORNL; Ekici, Kivanc [ORNL] [ORNL; Freels, James D [ORNL] [ORNL

    2013-01-01

    The High Flux Isotope Reactor at the Oak Ridge National Lab is in the research stage of converting its fuel from high-enriched uranium to low-enriched uranium. Due to different physical properties of the new fuel and changes to the internal fuel plate design, the current safety basis must be re-evaluated through rigorous computational analyses. One of the areas being explored is the fluid-structure interaction phenomenon due to the interaction of thin fuel plates (50 mils thickness) and the cooling fluid (water). Detailed computational fluid dynamics and fluid-structure interaction simulations have only recently become feasible due to improved numerical algorithms and advancements in computing technology. For many reasons including the already built-in fluid-structure interaction module, COMSOL has been chosen for this complex problem. COMSOL's ability to solve multiphysics problems using a fully-coupled and implicit solution algorithm is crucial in obtaining a stable and accurate solution. Our initial findings show that COMSOL can accurately model such problems due to its ability to closely couple the fluid dynamics and the structural dynamics problems.

  3. Improved Modeling and Understanding of Diffusion-Media Wettability on Polymer-Electrolyte-Fuel-Cell Performance

    SciTech Connect (OSTI)

    Weber, Adam

    2010-03-05

    A macroscopic-modeling methodology to account for the chemical and structural properties of fuel-cell diffusion media is developed. A previous model is updated to include for the first time the use of experimentally measured capillary pressure -- saturation relationships through the introduction of a Gaussian contact-angle distribution into the property equations. The updated model is used to simulate various limiting-case scenarios of water and gas transport in fuel-cell diffusion media. Analysis of these results demonstrate that interfacial conditions are more important than bulk transport in these layers, where the associated mass-transfer resistance is the result of higher capillary pressures at the boundaries and the steepness of the capillary pressure -- saturation relationship. The model is also used to examine the impact of a microporous layer, showing that it dominates the response of the overall diffusion medium. In addition, its primary mass-transfer-related effect is suggested to be limiting the water-injection sites into the more porous gas-diffusion layer.

  4. Modeling and simulation of hydrogen behavior in Zircaloy-4 fuel cladding

    SciTech Connect (OSTI)

    Jason D. Hales; Various

    2014-09-01

    As a result of corrosion during normal operation in nuclear reactors, hydrogen can enter the zirconium-alloy fuel cladding and precipitate as brittle hydride platelets, which can severely degrade the cladding ductility. Under a heterogeneous temperature distribution, hydrides tend to accumulate in the colder areas, creating local spots of degraded cladding that can favor crack initiation. Therefore, an estimation of the local hydride distribution is necessary to help predict the risk of cladding failure. The hydride distribution is governed by three competing phenomena. Hydrogen in solid solution diffuses under a concentration gradient due to Fick’s law and under a temperature gradient due to the Soret effect. Precipitation of the hydride platelets occurs once the hydrogen solubility limit is reached. A model of these phenomena was implemented in the 3D fuel performance code BISON in order to calculate the hydrogen distribution for arbitrary geometries, such as a nuclear fuel rod, and is now available for BISON users. Simulations have been performed on simple geometries to validate the model and its implementation. The simulations predict that before precipitation occurs, hydrogen tends to accumulate in the colder spots due to the Soret effect. Once the solubility limit is reached, hydrogen precipitates and forms a rim close to the outer edge of the cladding. The simulations also predict that the reactor shut down has little effect on already precipitated hydrides but causes the remaining hydrogen to precipitate homogeneously into hydrides.

  5. TRISO Fuel Performance: Modeling, Integration into Mainstream Design Studies, and Application to a Thorium-fueled Fusion-Fission Hybrid Blanket

    SciTech Connect (OSTI)

    Powers, J J

    2011-11-28

    This study focused on creating a new tristructural isotropic (TRISO) coated particle fuel performance model and demonstrating the integration of this model into an existing system of neutronics and heat transfer codes, creating a user-friendly option for including fuel performance analysis within system design optimization and system-level trade-off studies. The end product enables both a deeper understanding and better overall system performance of nuclear energy systems limited or greatly impacted by TRISO fuel performance. A thorium-fueled hybrid fusion-fission Laser Inertial Fusion Energy (LIFE) blanket design was used for illustrating the application of this new capability and demonstrated both the importance of integrating fuel performance calculations into mainstream design studies and the impact that this new integrated analysis had on system-level design decisions. A new TRISO fuel performance model named TRIUNE was developed and verified and validated during this work with a novel methodology established for simulating the actual lifetime of a TRISO particle during repeated passes through a pebble bed. In addition, integrated self-consistent calculations were performed for neutronics depletion analysis, heat transfer calculations, and then fuel performance modeling for a full parametric study that encompassed over 80 different design options that went through all three phases of analysis. Lastly, side studies were performed that included a comparison of thorium and depleted uranium (DU) LIFE blankets as well as some uncertainty quantification work to help guide future experimental work by assessing what material properties in TRISO fuel performance modeling are most in need of improvement. A recommended thorium-fueled hybrid LIFE engine design was identified with an initial fuel load of 20MT of thorium, 15% TRISO packing within the graphite fuel pebbles, and a 20cm neutron multiplier layer with beryllium pebbles in flibe molten salt coolant. It operated at a system power level of 2000 MW{sub th}, took about 3.5 years to reach full plateau power, and was capable of an End of Plateau burnup of 38.7 %FIMA if considering just the neutronic constraints in the system design; however, fuel performance constraints led to a maximum credible burnup of 12.1 %FIMA due to a combination of internal gas pressure and irradiation effects on the TRISO materials (especially PyC) leading to SiC pressure vessel failures. The optimal neutron spectrum for the thorium-fueled blanket options evaluated seemed to favor a hard spectrum (low but non-zero neutron multiplier thicknesses and high TRISO packing fractions) in terms of neutronic performance but the fuel performance constraints demonstrated that a significantly softer spectrum would be needed to decrease the rate of accumulation of fast neutron fluence in order to improve the maximum credible burnup the system could achieve.

  6. Understanding Global Capitalism

    E-Print Network [OSTI]

    Robinson, William I.

    2008-01-01

    the model emerging in Venezuela, and we could say with 21stBolivarian initiative, Venezuela. I was wondering how theand that's done by the way, Venezuela and Argentina are good

  7. Capturing the Impact of Fuel Price on Jet Aircraft Operating Costs with Engineering and Econometric Models

    E-Print Network [OSTI]

    Smirti Ryerson, Megan; Hansen, Mark

    2009-01-01

    Capturing the Impact of Fuel Price on Jet Aircraft OperatingCapturing the Impact of Fuel Price on Jet Aircraft Operatingsurges in the price of fuel as regional jets have lower fuel

  8. Radiation Damage in Nuclear Fuel for Advanced Burner Reactors: Modeling and Experimental Validation

    SciTech Connect (OSTI)

    Jensen, Niels Gronbech; Asta, Mark; Ozolins, Nigel Browning'Vidvuds; de Walle, Axel van; Wolverton, Christopher

    2011-12-29

    The consortium has completed its existence and we are here highlighting work and accomplishments. As outlined in the proposal, the objective of the work was to advance the theoretical understanding of advanced nuclear fuel materials (oxides) toward a comprehensive modeling strategy that incorporates the different relevant scales involved in radiation damage in oxide fuels. Approaching this we set out to investigate and develop a set of directions: 1) Fission fragment and ion trajectory studies through advanced molecular dynamics methods that allow for statistical multi-scale simulations. This work also includes an investigation of appropriate interatomic force fields useful for the energetic multi-scale phenomena of high energy collisions; 2) Studies of defect and gas bubble formation through electronic structure and Monte Carlo simulations; and 3) an experimental component for the characterization of materials such that comparisons can be obtained between theory and experiment.

  9. Kinetic modelling of a surrogate diesel fuel applied to 3D auto-ignition in HCCI engines

    E-Print Network [OSTI]

    Bounaceur, Roda; Fournet, René; Battin-Leclerc, Frédérique; Jay, S; Da Cruz, A Pires

    2007-01-01

    The prediction of auto-ignition delay times in HCCI engines has risen interest on detailed chemical models. This paper described a validated kinetic mechanism for the oxidation of a model Diesel fuel (n-decane and ?-methylnaphthalene). The 3D model for the description of low and high temperature auto-ignition in engines is presented. The behavior of the model fuel is compared with that of n-heptane. Simulations show that the 3D model coupled with the kinetic mechanism can reproduce experimental HCCI and Diesel engine results and that the correct modeling of auto-ignition in the cool flame region is essential in HCCI conditions.

  10. Development and Validation of a Slurry Model for Chemical Hydrogen Storage in Fuel Cell Applications

    SciTech Connect (OSTI)

    Brooks, Kriston P.; Pires, Richard P.; Simmons, Kevin L.

    2014-07-25

    The US Department of Energy's (DOE) Hydrogen Storage Engineering Center of Excellence (HSECoE) is developing models for hydrogen storage systems for fuel cell-based light duty vehicle applications for a variety of promising materials. These transient models simulate the performance of the storage system for comparison to the DOE’s Technical Targets and a set of four drive cycles. The purpose of this research is to describe the models developed for slurry-based chemical hydrogen storage materials. The storage systems of both a representative exothermic system based on ammonia borane and endothermic system based on alane were developed and modeled in Simulink®. Once complete the reactor and radiator components of the model were validated with experimental data. The model was then run using a highway cycle, an aggressive cycle, cold-start cycle and hot drive cycle. The system design was adjusted to meet these drive cycles. A sensitivity analysis was then performed to identify the range of material properties where these DOE targets and drive cycles could be met. Materials with a heat of reaction greater than 11 kJ/mol H2 generated and a slurry hydrogen capacity of greater than 11.4% will meet the on-board efficiency and gravimetric capacity targets, respectively.

  11. THERMODYNAMIC AND KINETIC MODELING OF ADVANCED NUCLEAR FUELS - FINAL LDRD-ER REPORT

    SciTech Connect (OSTI)

    Turchi, P

    2011-11-28

    This project enhanced our theoretical capabilities geared towards establishing the basic science of a high-throughput protocol for the development of advanced nuclear fuel that should couple modern computational materials modeling and simulation tools, fabrication and characterization capabilities, and targeted high throughput performance testing experiments. The successful conclusion of this ER project allowed us to upgrade state-of-the-art modeling codes, and apply these modeling tools to ab initio energetics and thermodynamic assessments of phase diagrams of various mixtures of actinide alloys, propose a tool for optimizing composition of complex alloys for specific properties, predict diffusion behavior in diffusion couples made of actinide and transition metals, include one new equation in the LLNL phase-field AMPE code, and predict microstructure evolution during alloy coring. In FY11, despite limited funding, the team also initiated an experimental activity, with collaboration from Texas A&M University by preparing samples of nuclear fuels in bulk forms and for diffusion couple studies and metallic matrices, and performing preliminary characterization.

  12. A Lifecycle Emissions Model (LEM): Lifecycle Emissions from Transportation Fuels, Motor Vehicles, Transportation Modes, Electricity Use, Heating and Cooking Fuels, and Materials

    E-Print Network [OSTI]

    Delucchi, Mark

    2003-01-01

    by crediting against full fuel cycle emissions from theuse” process fuel -- is the full fuel cycle emission factor,where the full fuel cycle includes emissions from

  13. Using a Quasipotential Transformation for Modeling Diffusion Media inPolymer-Electrolyte Fuel Cells

    SciTech Connect (OSTI)

    Weber, Adam Z.; Newman, John

    2008-08-29

    In this paper, a quasipotential approach along with conformal mapping is used to model the diffusion media of a polymer-electrolyte fuel cell. This method provides a series solution that is grid independent and only requires integration along a single boundary to solve the problem. The approach accounts for nonisothermal phenomena, two-phase flow, correct placement of the electronic potential boundary condition, and multilayer media. The method is applied to a cathode diffusion medium to explore the interplay between water and thermal management and performance, the impact of the rib-to-channel ratio, and the existence of diffusion under the rib and flooding phenomena.

  14. Comparison of Homogeneous and Heterogeneous CFD Fuel Models for Phase I of the IAEA CRP on HTR Uncertainties Benchmark

    SciTech Connect (OSTI)

    Gerhard Strydom; Su-Jong Yoon

    2014-04-01

    Computational Fluid Dynamics (CFD) evaluation of homogeneous and heterogeneous fuel models was performed as part of the Phase I calculations of the International Atomic Energy Agency (IAEA) Coordinate Research Program (CRP) on High Temperature Reactor (HTR) Uncertainties in Modeling (UAM). This study was focused on the nominal localized stand-alone fuel thermal response, as defined in Ex. I-3 and I-4 of the HTR UAM. The aim of the stand-alone thermal unit-cell simulation is to isolate the effect of material and boundary input uncertainties on a very simplified problem, before propagation of these uncertainties are performed in subsequent coupled neutronics/thermal fluids phases on the benchmark. In many of the previous studies for high temperature gas cooled reactors, the volume-averaged homogeneous mixture model of a single fuel compact has been applied. In the homogeneous model, the Tristructural Isotropic (TRISO) fuel particles in the fuel compact were not modeled directly and an effective thermal conductivity was employed for the thermo-physical properties of the fuel compact. On the contrary, in the heterogeneous model, the uranium carbide (UCO), inner and outer pyrolytic carbon (IPyC/OPyC) and silicon carbide (SiC) layers of the TRISO fuel particles are explicitly modeled. The fuel compact is modeled as a heterogeneous mixture of TRISO fuel kernels embedded in H-451 matrix graphite. In this study, a steady-state and transient CFD simulations were performed with both homogeneous and heterogeneous models to compare the thermal characteristics. The nominal values of the input parameters are used for this CFD analysis. In a future study, the effects of input uncertainties in the material properties and boundary parameters will be investigated and reported.

  15. Urban airshed modeling of air quality impacts of alternative transportation fuel use in Los Angeles and Atlanta

    SciTech Connect (OSTI)

    NONE

    1997-12-01

    The main objective of NREL in supporting this study is to determine the relative air quality impact of the use of compressed natural gas (CNG) as an alternative transportation fuel when compared to low Reid vapor pressure (RVP) gasoline and reformulated gasoline (RFG). A table lists the criteria, air toxic, and greenhouse gas pollutants for which emissions were estimated for the alternative fuel scenarios. Air quality impacts were then estimated by performing photochemical modeling of the alternative fuel scenarios using the Urban Airshed Model Version 6.21 and the Carbon Bond Mechanism Version IV (CBM-IV) (Geary et al., 1988) Using this model, the authors examined the formation and transport of ozone under alternative fuel strategies for motor vehicle transportation sources for the year 2007. Photochemical modeling was performed for modeling domains in Los Angeles, California, and Atlanta, Georgia.

  16. Toward Verifying Fossil Fuel CO2 Emissions with the CMAQ Model: Motivation, Model Description and Initial Simulation

    SciTech Connect (OSTI)

    Liu, Zhen; Bambha, Ray P.; Pinto, Joseph P.; Zeng, Tao; Boylan, Jim; Huang, Maoyi; Lei, Huimin; Zhao, Chun; Liu, Shishi; Mao, Jiafu; Schwalm, Christopher R.; Shi, Xiaoying; Wei, Yaxing; Michelsen, Hope A.

    2014-03-14

    Motivated by the urgent need for emission verification of CO2 and other greenhouse gases, we have developed regional CO2 simulation with CMAQ over the contiguous U.S. Model sensitivity experiments have been performed using three different sets of inputs for net ecosystem exchange (NEE) and two fossil fuel emission inventories, to understand the roles of fossil fuel emissions, atmosphere-biosphere exchange and transport in regulating the spatial and diurnal variability of CO2 near the surface, and to characterize the well-known ‘signal-to-noise’ problem, i.e. the interference from the biosphere on the interpretation of atmospheric CO2 observations. It is found that differences in the meteorological conditions for different urban areas strongly contribute to the contrast in concentrations. The uncertainty of NEE, as measured by the difference among the three different NEE inputs, has notable impact on regional distribution of CO2 simulated by CMAQ. Larger NEE uncertainty and impact are found over eastern U.S. urban areas than along the western coast. A comparison with tower CO2 measurements at Boulder Atmospheric Observatory (BAO) shows that the CMAQ model using hourly varied and high-resolution CO2 emission from the Vulcan inventory and CarbonTracker optimized NEE reasonably reproduce the observed diurnal profile, whereas switching to different NEE inputs significantly degrades the model performance. Spatial distribution of CO2 is found to correlate with NOx, SO2 and CO, due to their similarity in emission sources and transport processes. These initial results from CMAQ demonstrate the power of a state-of-the art CTM in helping interpret CO2 observations and verify fossil fuel emissions. The ability to simulate CO2 in CMAQ will also facilitate investigations of the utility of traditionally regulated pollutants and other species as tracers to CO2 source attribution.

  17. Modeling Heavy/Medium-Duty Fuel Consumption Based on Drive Cycle Properties

    SciTech Connect (OSTI)

    Wang, Lijuan; Duran, Adam; Gonder, Jeffrey; Kelly, Kenneth

    2015-10-13

    This paper presents multiple methods for predicting heavy/medium-duty vehicle fuel consumption based on driving cycle information. A polynomial model, a black box artificial neural net model, a polynomial neural network model, and a multivariate adaptive regression splines (MARS) model were developed and verified using data collected from chassis testing performed on a parcel delivery diesel truck operating over the Heavy Heavy-Duty Diesel Truck (HHDDT), City Suburban Heavy Vehicle Cycle (CSHVC), New York Composite Cycle (NYCC), and hydraulic hybrid vehicle (HHV) drive cycles. Each model was trained using one of four drive cycles as a training cycle and the other three as testing cycles. By comparing the training and testing results, a representative training cycle was chosen and used to further tune each method. HHDDT as the training cycle gave the best predictive results, because HHDDT contains a variety of drive characteristics, such as high speed, acceleration, idling, and deceleration. Among the four model approaches, MARS gave the best predictive performance, with an average absolute percent error of -1.84% over the four chassis dynamometer drive cycles. To further evaluate the accuracy of the predictive models, the approaches were first applied to real-world data. MARS outperformed the other three approaches, providing an average absolute percent error of -2.2% of four real-world road segments. The MARS model performance was then compared to HHDDT, CSHVC, NYCC, and HHV drive cycles with the performance from Future Automotive System Technology Simulator (FASTSim). The results indicated that the MARS method achieved a comparative predictive performance with FASTSim.

  18. Fundamental Study of the Oxidation Characteristics and Pollutant Emissions of Model Biodiesel Fuels

    SciTech Connect (OSTI)

    Feng, Q.; Wang, Y. L.; Egolfopoulos, Fokion N.; Tsotsis, T. T.

    2010-07-18

    In this study, the oxidation characteristics of biodiesel fuels are investigated with the goal of contributing toward the fundamental understanding of their combustion characteristics and evaluating the effect of using these alternative fuels on engine performance as well as on the environment. The focus of the study is on pure fatty acid methyl-esters (FAME,) that can serve as surrogate compounds for real biodiesels. The experiments are conducted in the stagnation-flow configuration, which allows for the systematic evaluation of fundamental combustion and emission characteristics. In this paper, the focus is primarily on the pollutant emission characteristics of two C{sub 4} FAMEs, namely, methyl-butanoate and methyl-crotonate, whose behavior is compared with that of n-butane and n-pentane. To provide insight into the mechanisms of pollutant formation for these fuels, the experimental data are compared with computed results using a model with consistent C1-C4 oxidation and NOx formation kinetics.

  19. Thermal performance sensitivity studies in support of material modeling for extended storage of used nuclear fuel

    SciTech Connect (OSTI)

    Cuta, Judith M.; Suffield, Sarah R.; Fort, James A.; Adkins, Harold E.

    2013-08-15

    The work reported here is an investigation of the sensitivity of component temperatures of a storage system, including fuel cladding temperatures, in response to age-related changes that could degrade the design-basis thermal behavior of the system. Three specific areas of interest were identified for this study. • degradation of the canister backfill gas from pure helium to a mixture of air and helium, resulting from postulated leakage due to stress corrosion cracking (SCC) of canister welds • changes in surface emissivity of system components, resulting from corrosion or other aging mechanisms, which could cause potentially significant changes in temperatures and temperature distributions, due to the effect on thermal radiation exchange between components • changes in fuel and basket temperatures due to changes in fuel assembly position within the basket cells in the canister The purpose of these sensitivity studies is to provide a realistic example of how changes in the physical properties or configuration of the storage system components can affect temperatures and temperature distributions. The magnitudes of these sensitivities can provide guidance for identifying appropriate modeling assumptions for thermal evaluations extending long term storage out beyond 50, 100, 200, and 300 years.

  20. Modeling Low-Platinum-Loading Effects in Fuel-Cell Catalyst Layers

    SciTech Connect (OSTI)

    Yoon, Wonseok; Weber, Adam Z.

    2011-01-20

    The cathode catalyst layer within a proton-exchange-membrane fuel cell is the most complex and critical, yet least understood, layer within the cell. The exact method and equations for modeling this layer are still being revised and will be discussed in this paper, including a 0.8 reaction order, existence of Pt oxides, possible non-isopotential agglomerates, and the impact of a film resistance towards oxygen transport. While the former assumptions are relatively straightforward to understand and implement, the latter film resistance is shown to be critically important in explaining increased mass-transport limitations with low Pt-loading catalyst layers. Model results demonstrate agreement with experimental data that the increased oxygen flux and/or diffusion pathway through the film can substantially decrease performance. Also, some scale-up concepts from the agglomerate scale to the more macroscopic porous-electrode scale are discussed and the resulting optimization scenarios investigated.

  1. Optics and Fluid Dynamics Department Intellectual Capital Accounts 1998

    E-Print Network [OSTI]

    Optics and Fluid Dynamics Department Intellectual Capital Accounts 1998 Resources, production and results RISØ-R-1108(EN) Risø National Laboratory Optics and Fluid Dynamics Department Building 128 P for optical information storage, · novel schemes for spatial cryptography, and · new models for surface

  2. DegreeinMasters CapitalProjectsSupplyChain

    E-Print Network [OSTI]

    Bolding, M. Chad

    and Logistics Application of model building and analytical techniques in the design, optimization, and control and optimizing the supply chain with specific applications in capital projects, a multidisciplinary approach has for improving supply chain processes today, and durable tools and concepts that will continue to serve

  3. Geant4 Model Validation of Compton Suppressed System for Process monitoring of Spent Fuel

    SciTech Connect (OSTI)

    Bender, Sarah; Unlu, Kenan; Orton, Christopher R.; Schwantes, Jon M.

    2013-05-01

    Nuclear material accountancy is of continuous concern for the regulatory, safeguards, and verification communities. In particular, spent nuclear fuel reprocessing facilities pose one of the most difficult accountancy challenges: monitoring highly radioactive, fluid sample streams in near real-time. The Multi-Isotope Process monitor will allow for near-real-time indication of process alterations using passive gamma-ray detection coupled with multivariate analysis techniques to guard against potential material diversion or to enhance domestic process monitoring. The Compton continuum from the dominant 661.7 keV 137Cs fission product peak obscures lower energy lines which could be used for spectral and multivariate analysis. Compton suppression may be able to mitigate the challenges posed by the high continuum caused by scattering. A Monte Carlo simulation using the Geant4 toolkit is being developed to predict the expected suppressed spectrum from spent fuel samples to estimate the reduction in the Compton continuum. Despite the lack of timing information between decay events in the particle management of Geant4, encouraging results were recorded utilizing only the information within individual decays without accounting for accidental coincidences. The model has been validated with single and cascade decay emitters in two steps: as an unsuppressed system and with suppression activated. Results of the Geant4 model validation will be presented.

  4. Waste Classification based on Waste Form Heat Generation in Advanced Nuclear Fuel Cycles Using the Fuel-Cycle Integration and Tradeoffs (FIT) Model

    SciTech Connect (OSTI)

    Denia Djokic; Steven J. Piet; Layne F. Pincock; Nick R. Soelberg

    2013-02-01

    This study explores the impact of wastes generated from potential future fuel cycles and the issues presented by classifying these under current classification criteria, and discusses the possibility of a comprehensive and consistent characteristics-based classification framework based on new waste streams created from advanced fuel cycles. A static mass flow model, Fuel-Cycle Integration and Tradeoffs (FIT), was used to calculate the composition of waste streams resulting from different nuclear fuel cycle choices. This analysis focuses on the impact of waste form heat load on waste classification practices, although classifying by metrics of radiotoxicity, mass, and volume is also possible. The value of separation of heat-generating fission products and actinides in different fuel cycles is discussed. It was shown that the benefits of reducing the short-term fission-product heat load of waste destined for geologic disposal are neglected under the current source-based radioactive waste classification system , and that it is useful to classify waste streams based on how favorable the impact of interim storage is in increasing repository capacity.

  5. Waste Classification based on Waste Form Heat Generation in Advanced Nuclear Fuel Cycles Using the Fuel-Cycle Integration and Tradeoffs (FIT) Model - 13413

    SciTech Connect (OSTI)

    Djokic, Denia [Department of Nuclear Engineering, University of California - Berkeley, 4149 Etcheverry Hall, Berkeley, CA 94720-1730 (United States)] [Department of Nuclear Engineering, University of California - Berkeley, 4149 Etcheverry Hall, Berkeley, CA 94720-1730 (United States); Piet, Steven J.; Pincock, Layne F.; Soelberg, Nick R. [Idaho National Laboratory - INL, 2525 North Fremont Avenue, Idaho Falls, ID 83415 (United States)] [Idaho National Laboratory - INL, 2525 North Fremont Avenue, Idaho Falls, ID 83415 (United States)

    2013-07-01

    This study explores the impact of wastes generated from potential future fuel cycles and the issues presented by classifying these under current classification criteria, and discusses the possibility of a comprehensive and consistent characteristics-based classification framework based on new waste streams created from advanced fuel cycles. A static mass flow model, Fuel-Cycle Integration and Tradeoffs (FIT), was used to calculate the composition of waste streams resulting from different nuclear fuel cycle choices. This analysis focuses on the impact of waste form heat load on waste classification practices, although classifying by metrics of radiotoxicity, mass, and volume is also possible. The value of separation of heat-generating fission products and actinides in different fuel cycles is discussed. It was shown that the benefits of reducing the short-term fission-product heat load of waste destined for geologic disposal are neglected under the current source-based radioactive waste classification system, and that it is useful to classify waste streams based on how favorable the impact of interim storage is in increasing repository capacity. (authors)

  6. KINETIC MODELING OF A SURROGATE DIESEL FUEL APPLIED TO 3D AUTO-IGNITION IN HCCI ENGINES

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    KINETIC MODELING OF A SURROGATE DIESEL FUEL APPLIED TO 3D AUTO-IGNITION IN HCCI ENGINES R OF A SURROGATE DIESEL FUEL APPLIED TO 3D AUTO-IGNITION IN HCCI ENGINES INTRODUCTION Engines running on HCCI combustion mode (Homogeneous Charge Compression Ignition) have the potential to provide both diesel

  7. An Integrated Electric Power Supply Chain and Fuel Market Network Framework: Theoretical Modeling with Empirical Analysis for New England

    E-Print Network [OSTI]

    Nagurney, Anna

    An Integrated Electric Power Supply Chain and Fuel Market Network Framework: Theoretical Modeling investigate how changes in the demand for electricity influence the electric power and the fuel markets from markets to quantify the interactions in electric power/energy supply chains and their effects on flows

  8. Modeling of autoignition and NO sensitization for the oxidation of IC engine surrogate fuels

    SciTech Connect (OSTI)

    Anderlohr, J.M. |; Bounaceur, R.; Battin-Leclerc, F.; Pires Da Cruz, A.

    2009-02-15

    This paper presents an approach for modeling with one single kinetic mechanism the chemistry of the autoignition and combustion processes inside an internal combustion engine, as well as the chemical kinetics governing the postoxidation of unburned hydrocarbons in engine exhaust gases. Therefore a new kinetic model was developed, valid over a wide range of temperatures including the negative temperature coefficient regime. The model simulates the autoignition and the oxidation of engine surrogate fuels composed of n-heptane, iso-octane, and toluene, which are sensitized by the presence of nitric oxides. The new model was obtained from previously published mechanisms for the oxidation of alkanes and toluene where the coupling reactions describing interactions between hydrocarbons and NO{sub x} were added. The mechanism was validated against a wide range of experimental data obtained in jet-stirred reactors, rapid compression machines, shock tubes, and homogeneous charge compression ignition engines. Flow rate and sensitivity analysis were performed in order to explain the low temperature chemical kinetics, especially the impact of NO{sub x} on hydrocarbon oxidation. (author)

  9. Modeling Gas-Phase Transport in Polymer-Electrolyte Fuel Cells

    E-Print Network [OSTI]

    Weber, A.Z.; Newman, J.

    2006-01-01

    Energy, Office of Hydrogen, Fuel Cell, and InfrastructureIN POLYMER-ELECTROLYTE FUEL CELLS A. Z. Weber and J. Newmandiffusion of gases in a fuel-cell gas-diffusion layer are

  10. Development of fission gas swelling and release models for metallic nuclear fuels

    E-Print Network [OSTI]

    Andrews, Nathan Christopher

    2012-01-01

    Fuel swelling and fission gas generation for fast reactor fuels are of high importance since they are among the main limiting factors in the development of metallic fast reactor fuel. Five new fission gas and swelling ...

  11. 2015 Hydrogen Student Design Contest Challenges Students to Develop Innovative Hydrogen Fueling Station Business and Financing Models

    Broader source: Energy.gov [DOE]

    The Hydrogen Education Foundation announced the 11th annual Hydrogen Student Design Contest, which will challenge student teams to develop business and financing models for hydrogen fueling stations. Registration for the Contest is open until January 16, 2015.

  12. Chemical Kinetic Modeling of Non-Petroleum Based Fuels | Department of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based Fuels|Programs |Chart of breakout of funds by major

  13. Fuel Cell Power Model for CHHP System Economics and Performance Analysis |

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum12, 2015ExecutiveFluorescentDanKathy Loftus GlobalEfficient Fuel Cells

  14. Incorporating stakeholders' perspectives into models of new technology diffusion: The case of fuel-cell vehicles

    E-Print Network [OSTI]

    Collantes, Gustavo O

    2007-01-01

    include on-board hydrogen storage and fuel cell durability.drive Hydrogen production Hydrogen storage Hydrogen fuelingnecessary are on-board hydrogen storage and fuel cells. The

  15. MODELING HEAT TRANSFER IN SPENT FUEL TRANSFER CASK NEUTRON SHIELDS – A CHALLENGING PROBLEM IN NATURAL CONVECTION

    SciTech Connect (OSTI)

    Fort, James A.; Cuta, Judith M.; Bajwa, C.; Baglietto, E.

    2010-07-18

    In the United States, commercial spent nuclear fuel is typically moved from spent fuel pools to outdoor dry storage pads within a transfer cask system that provides radiation shielding to protect personnel and the surrounding environment. The transfer casks are cylindrical steel enclosures with integral gamma and neutron radiation shields. Since the transfer cask system must be passively cooled, decay heat removal from spent nuclear fuel canister is limited by the rate of heat transfer through the cask components, and natural convection from the transfer cask surface. The primary mode of heat transfer within the transfer cask system is conduction, but some cask designs incorporate a liquid neutron shield tank surrounding the transfer cask structural shell. In these systems, accurate prediction of natural convection within the neutron shield tank is an important part of assessing the overall thermal performance of the transfer cask system. The large-scale geometry of the neutron shield tank, which is typically an annulus approximately 2 meters in diameter but only 10-15 cm in thickness, and the relatively small scale velocities (typically less than 5 cm/s) represent a wide range of spatial and temporal scales that contribute to making this a challenging problem for computational fluid dynamics (CFD) modeling. Relevant experimental data at these scales are not available in the literature, but some recent modeling studies offer insights into numerical issues and solutions; however, the geometries in these studies, and for the experimental data in the literature at smaller scales, all have large annular gaps that are not prototypic of the transfer cask neutron shield. This paper proposes that there may be reliable CFD approaches to the transfer cask problem, specifically coupled steady-state solvers or unsteady simulations; however, both of these solutions take significant computational effort. Segregated (uncoupled) steady state solvers that were tested did not accurately capture the flow field and heat transfer distribution in this application. Mesh resolution, turbulence modeling, and the tradeoff between steady state and transient solutions are addressed. Because of the critical nature of this application, the need for new experiments at representative scales is clearly demonstrated.

  16. A three-dimensional numerical model of a micro laminar flow fuel cell with a bridge-shaped microchannel cross-section

    E-Print Network [OSTI]

    Kenis, Paul J. A.

    A three-dimensional numerical model of a micro laminar flow fuel cell with a bridge: Membraneless fuel cell Laminar flow fuel cell Numerical model Convection-diffusion equations Electrode kinetics equations COMSOL a b s t r a c t The operation of a laminar flow fuel cell (LFFC) involves complex interplay

  17. Model-based control strategies in the dynamic interaction of air supply and fuel cell

    E-Print Network [OSTI]

    Grujicic, Mica

    to the type of membrane (polymer electrolyte membrane fuel cells, solid oxide fuel cells, molten carbonate to analyse and optimize the transient behaviour of a polymer electrolyte membrane (PEM) fuel cell system such as a battery. Keywords: polymer electrolyte membrane, fuel cells NOTATION a water vapour activity cv water

  18. Evaluation of fuel consumption potential of medium and heavy duty vehicles through modeling and simulation.

    SciTech Connect (OSTI)

    Delorme, A.; Karbowski, D.; Sharer, P.; Energy Systems

    2010-03-31

    The main objective of this report is to provide quantitative data to support the Committee in its task of establishing a report to support rulemaking on medium- and heavy-duty fuel efficiency improvement. In particular, it is of paramount importance for the Committee to base or illustrate their conclusions on established models and actual state-of-the art data. The simulations studies presented in the report have been defined and requested by the members of the National Academy committee to provide quantitative inputs to support their recommendations. As such, various technologies and usage scenarios were considered for several applications. One of the objective is to provide the results along with their associated assumptions (both vehicle and drive cycles), information generally missing from public discussions on literature search. Finally, the advantages and limitations of using simulation will be summarized. The study addresses several of the committee tasks, including: (1) Discussion of the implication of metric selection; (2) Assessing the impact of existing technologies on fuel consumption through energy balance analysis (both steady-state and standard cycles) as well as real world drive cycles; and (3) Impact of future technologies, both individually and collectively.

  19. Fuel Cell Tri-Generation System Case Study using the H2A Stationary Model |

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum12, 2015ExecutiveFluorescentDanKathy LoftusFuel CellFuel CellMaterialsDepartment

  20. Mesoscopic modeling of liquid water transport in polymer electrolyte fuel cells

    SciTech Connect (OSTI)

    Mukherjee, Partha P [Los Alamos National Laboratory; Wang, Chao Yang [PENNSTATE UNIV.

    2008-01-01

    A key performance limitation in polymer electrolyte fuel cells (PEFC), manifested in terms of mass transport loss, originates from liquid water transport and resulting flooding phenomena in the constituent components. Liquid water leads to the coverage of the electrochemically active sites in the catalyst layer (CL) rendering reduced catalytic activity and blockage of the available pore space in the porous CL and fibrous gas diffusion layer (GDL) resulting in hindered oxygen transport to the active reaction sites. The cathode CL and the GDL therefore playa major role in the mass transport loss and hence in the water management of a PEFC. In this article, we present the development of a mesoscopic modeling formalism coupled with realistic microstructural delineation to study the profound influence of the pore structure and surface wettability on liquid water transport and interfacial dynamics in the PEFC catalyst layer and gas diffusion layer.

  1. DOE Updates JOBS and Economic Impacts of Fuel Cells (JOBS FC1.1) Model |

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: AlternativeCommunication & EngagementFishers Circle byEnergy ProudUnder

  2. A Total Cost of Ownership Model for Low Temperature PEM Fuel Cells in

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:Financing ToolInternationalReportOffice | DepartmentVery1, in:QuarterlyA Solar

  3. 184 IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 26, NO. 1, MARCH 2011 PEM Fuel Cell Stack Modeling for Real-Time

    E-Print Network [OSTI]

    Simões, Marcelo Godoy

    184 IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 26, NO. 1, MARCH 2011 PEM Fuel Cell Stack Modeling, IEEE Abstract--In this paper, a multiphysical proton exchange mem- brane fuel cell stack model, which, fluidic, and thermal. A Ballard 1.2 kW 47 cells fuel cell stack model is introduced. The corresponding

  4. Assessment of a mechanistic model in U-Pu-Zr metallic alloy fuel fission-gas behavior simulations

    SciTech Connect (OSTI)

    Yun, D.; Rest, J.; Yacout, A. M.

    2012-07-01

    A mechanistic kinetic rate theory model originally developed for the prediction of fission gas behavior in oxide nuclear fuels under steady-state and transient conditions has been assessed to look at its applicability to model fission gas behavior in U-Pu-Zr metallic alloy fuel. In order to capture and validate the underlying physics for irradiated U-Pu-Zr fuels, the mechanistic model was applied to the simulation of fission gas release, fission gas and fission product induced swelling, and the evolution of the gas bubble size distribution in three different fuel zones: the outer {alpha}-U, the intermediate, and the inner {gamma}-U zones. Due to its special microstructural features, the {alpha}-U zone in U-Pu-Zr fuels is believed to contribute the largest fraction of fission gas release among the different fuel zones. It is shown that with the use of small effective grain sizes, the mechanistic model can predict fission gas release that is consistent with (though slightly lower than) experimentally measured data. These simulation results are comparable to the experimentally measured fission gas release since the mechanism of fission gas transport through the densely distributed laminar porosity in the {alpha}-U zone is analogous to the mechanism of fission gas transport through the interconnected gas bubble porosity utilized in the mechanistic model. Detailed gas bubble size distributions predicted with the mechanistic model in both the intermediate zone and the high temperature {gamma}-U zone of U-Pu-Zr fuel are also compared to experimental measurements from available SEM micrographs. These comparisons show good agreements between the simulation results and experimental measurements, and therefore provide crucial guidelines for the selection of key physical parameters required for modeling these two zones. In addition, the results of parametric studies for several key parameters are presented for both the intermediate zone and the {gamma}-U zone simulations. (authors)

  5. A Fission Gas Release Model for High-Burnup LWR ThO{sub 2}-UO{sub 2} Fuel

    SciTech Connect (OSTI)

    Long, Yun; Yi Yuan; Kazimi, Mujid S.; Ballinger, Ronald G.; Pilat, Edward E.

    2002-06-15

    Fission gas release in thoria-urania fuel has been investigated by creating a specially modified FRAPCON-3 code. Because of the reduced buildup of {sup 239}Pu and a flatter distribution of {sup 233}U, the new model THUPS (Thoria-Urania Power Shape) was developed to calculate the radial power distribution, including the effects of both plutonium and {sup 233}U. Additionally, a new porosity model for the rim region was introduced at high burnup. The mechanisms of fission gas release in ThO{sub 2}-UO{sub 2} fuel are expected to be essentially similar to those of UO{sub 2} fuel; therefore, the general formulations of the existing fission gas release models in FRAPCON-3 were retained. However, the gas diffusion coefficient was adjusted to a lower level to account for the smaller observed release fraction in the thoria-based fuel. To model the accelerated fission gas release at high burnup properly, a new athermal fission gas release model was introduced. The modified version of FRAPCON-3 was calibrated using the measured fission gas release data from the light water breeder reactor. Using the new model to calculate the gas release in typical pressurized water reactor hot pins gives data that indicate that the ThO{sub 2}-UO{sub 2} fuel will have considerably lower fission gas release above a burnup of 50 MWd/kg HM.

  6. An Integrated Electric Power Supply Chain and Fuel Market Network Framework: Theoretical Modeling with Empirical Analysis for New England

    E-Print Network [OSTI]

    Nagurney, Anna

    An Integrated Electric Power Supply Chain and Fuel Market Network Framework: Theoretical Modeling regions and multiple electricity markets under deregulation to quantify the interactions in electric power an oligopolistic electricity market model with a nitrogen ox- ide permit market, and provided examples based

  7. Modeling the natural attenuation of benzene in groundwater impacted by ethanol-blended fuels: Effect of ethanol content

    E-Print Network [OSTI]

    Alvarez, Pedro J.

    Modeling the natural attenuation of benzene in groundwater impacted by ethanol-blended fuels: Effect of ethanol content on the lifespan and maximum length of benzene plumes Diego E. Gomez1 and Pedro 10 March 2009. [1] A numerical model was used to evaluate how the concentration of ethanol

  8. Development of aircraft fuel burn modeling techniques with applications to global emissions modeling and assessment of the benefits of reduced vertical separation minimums

    E-Print Network [OSTI]

    Yoder, Tim (Tim Alan)

    2007-01-01

    Given the current level of concern over anthropogenic climate change and the role of commercial aviation in this process, the ability to adequately model and quantify fuel burn and emissions on a system wide scale is of ...

  9. Chemical Kinetic Modeling of Non-Petroleum Based Fuels | Department of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based Fuels|Programs |Chart of breakout of funds by majorEnergy 1 DOE

  10. Fuel-Cycle Energy and Emissions Analysis with the GREET Model | Department

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum12, 2015ExecutiveFluorescentDanKathy LoftusFuelDepartmentUnveiledof Energy

  11. Analysis Models and Tools: Systems Analysis of Hydrogen and Fuel Cells |

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergy Webinar:I Due Date Adv.Alison MarkovitzAmped Up! VolumeDepartment

  12. A Semi-Empirical Two Step Carbon Corrosion Reaction Model in PEM Fuel Cells

    SciTech Connect (OSTI)

    Young, Alan; Colbow, Vesna; Harvey, David; Rogers, Erin; Wessel, Silvia

    2013-01-01

    The cathode CL of a polymer electrolyte membrane fuel cell (PEMFC) was exposed to high potentials, 1.0 to 1.4 V versus a reversible hydrogen electrode (RHE), that are typically encountered during start up/shut down operation. While both platinum dissolution and carbon corrosion occurred, the carbon corrosion effects were isolated and modeled. The presented model separates the carbon corrosion process into two reaction steps; (1) oxidation of the carbon surface to carbon-oxygen groups, and (2) further corrosion of the oxidized surface to carbon dioxide/monoxide. To oxidize and corrode the cathode catalyst carbon support, the CL was subjected to an accelerated stress test cycled the potential from 0.6 VRHE to an upper potential limit (UPL) ranging from 0.9 to 1.4 VRHE at varying dwell times. The reaction rate constants and specific capacitances of carbon and platinum were fitted by evaluating the double layer capacitance (Cdl) trends. Carbon surface oxidation increased the Cdl due to increased specific capacitance for carbon surfaces with carbon-oxygen groups, while the second corrosion reaction decreased the Cdl due to loss of the overall carbon surface area. The first oxidation step differed between carbon types, while both reaction rate constants were found to have a dependency on UPL, temperature, and gas relative humidity.

  13. Vehicle Technologies Office Merit Review 2015: Improve Fuel Economy through Formulation Design and Modeling

    Broader source: Energy.gov [DOE]

    Presentation given by Ashland Inc. at 2015 DOE Hydrogen and Fuel Cells Program and vehicle technologies office annual merit review and peer evaluation meeting about improve fuel economy through...

  14. Advancement in Fuel Spray and Combustion Modeling for Compression Ignition Engine Applications

    Broader source: Energy.gov [DOE]

    2013 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting

  15. KINETIC MODELING OF FUEL EFFECTS OVER A WIDE RANGE OF CHEMISTRY,

    Office of Scientific and Technical Information (OSTI)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfate Reducing(Journalspectroscopy of aerosols in(JournalTechnical

  16. Aalborg Universitet Experimental study and modeling of degradation phenomena in HTPEM fuel cell stacks

    E-Print Network [OSTI]

    Andreasen, Søren Juhl

    Fuel cell based combined heat and power production (CHP) systems fuel with natural gas fuel can 1 Serenergy A/S, Denmark, http://serenergy.dk , 2 Aalborg University, Department of Energy Technology, Denmark, http://www.iet.aau.dk ­ * Corresponding author: mpn@iet.aau.dk Abstract: Degradation

  17. Experimental identification of turbulent fluid forces applied to fuel assemblies using an uncertain model and

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Experimental identification of turbulent fluid forces applied to fuel assemblies using an uncertain with an experimental setup which is constituted of a half fuel assembly which bathes in a turbulent fluid This paper is devoted to the identification of stochastic loads applied to fuel assemblies using an uncertain

  18. Science Highlight December 2010 Electrochemical Surface Science: Hard X-rays Probe Fuel Cell Model Catalyst

    E-Print Network [OSTI]

    Wechsler, Risa H.

    Science Highlight ­ December 2010 Electrochemical Surface Science: Hard X-rays Probe Fuel Cell. Proton exchange membrane fuel cells (PEMFCs) are promising power sources since they can generate distribution network. Large-scale deployment of fuel cells, however, has been hampered by cost and performance

  19. Phase field modeling of microstructure evolution of electrocatalyst-infiltrated solid oxide fuel cell cathodes

    E-Print Network [OSTI]

    Chen, Long-Qing

    instability and mechanical damage in solid oxide fuel cell anodes J. Appl. Phys. 114, 183519 (2013); 10-phase electrode microstructures in solid oxide fuel cells Appl. Phys. Lett. 101, 033909 (2012); 10.1063/1.4738230 Synthesis and calorimetric studies of oxide multilayer systems: Solid oxide fuel cell cathode

  20. A Multi-Stage Wear Model for Grid-to-Rod Fretting of Nuclear Fuel Rods

    SciTech Connect (OSTI)

    Blau, Peter Julian

    2014-01-01

    The wear of fuel rod cladding against the supporting structures in the cores of pressurized water nuclear reactors (PWRs) is an important and potentially costly tribological issue. Grid-to-rod fretting (GTRF), as it is known, involves not only time-varying contact conditions, but also elevated temperatures, flowing hot water, aqueous tribo-corrosion, and the embrittling effects of neutron fluences. The multi-stage, closed-form analytical model described in this paper relies on published out-of-reactor wear and corrosion data and a set of simplifying assumptions to portray the conversion of frictional work into wear depth. The cladding material of interest is a zirconium-based alloy called Zircaloy-4, and the grid support is made of a harder and more wear-resistant material. Focus is on the wear of the cladding. The model involves an incubation stage, a surface oxide wear stage, and a base alloy wear stage. The wear coefficient, which is a measure of the efficiency of conversion of frictional work into wear damage, can change to reflect the evolving metallurgical condition of the alloy. Wear coefficients for Zircaloy-4 and for a polyphase zirconia layer were back-calculated for a range of times required to wear to a critical depth. Inputs for the model, like the friction coefficient, are taken from the tribology literature in lieu of in-reactor tribological data. Concepts of classical fretting were used as a basis, but are modified to enable the model to accommodate the complexities of the PWR environment. Factors like grid spring relaxation, pre-oxidation of the cladding, multiple oxide phases, gap formation, impact, and hydrogen embrittlement are part of the problem definition but uncertainties in their relative roles limits the ability to validate the model. Sample calculations of wear depth versus time in the cladding illustrate how GTRF wear might occur in a discontinuous fashion during months-long reactor operating cycles. A means to account for grid/rod gaps and repetitive impact effects on GTRF wear is proposed

  1. Renewable Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/ColoradoRemsenburg-Speonk, New York: Energy Resources Jump to:Alternatives LLC Jump

  2. Capital E | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmentalBowerbank,Cammack Village, Arkansas: EnergyCounty,NewHatteras Elec

  3. EPA and DOE Release Annual Fuel Economy Guide with 2014 Models | Department

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based|DepartmentStatementof EnergyQuality'Lean'1401of Energy EPA and DOE

  4. EPA and DOE Release Annual Fuel Economy Guide with 2014 Models | Department

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based|DepartmentStatementof EnergyQuality'Lean'1401of Energy EPA and

  5. Fact #764: January 28, 2013 Model Year 2013 Brings More Fuel Efficient

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum12, 2015Executive Order14, 20111,FY 2007 FeeFederalFirst2Decisions RMChoices for

  6. Analysis Models and Tools: Systems Analysis of Hydrogen and Fuel Cells

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative FuelsofProgram:Y-12 Beta-3AUDITLeslieAlgae BiomassServicesWindAmy KiddOctoberPage1

  7. Sustainable Investments Capital SI Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS ReportEuropeEnergySustainability Center of theEuropeInvestments

  8. Scalable Nonlinear Solvers for Fully Implicit Coupled Nuclear Fuel Modeling. Final Report

    SciTech Connect (OSTI)

    Cai, Xiao-Chuan; Keyes, David; Yang, Chao; Zheng, Xiang; Pernice, Michael

    2014-09-29

    The focus of the project is on the development and customization of some highly scalable domain decomposition based preconditioning techniques for the numerical solution of nonlinear, coupled systems of partial differential equations (PDEs) arising from nuclear fuel simulations. These high-order PDEs represent multiple interacting physical fields (for example, heat conduction, oxygen transport, solid deformation), each is modeled by a certain type of Cahn-Hilliard and/or Allen-Cahn equations. Most existing approaches involve a careful splitting of the fields and the use of field-by-field iterations to obtain a solution of the coupled problem. Such approaches have many advantages such as ease of implementation since only single field solvers are needed, but also exhibit disadvantages. For example, certain nonlinear interactions between the fields may not be fully captured, and for unsteady problems, stable time integration schemes are difficult to design. In addition, when implemented on large scale parallel computers, the sequential nature of the field-by-field iterations substantially reduces the parallel efficiency. To overcome the disadvantages, fully coupled approaches have been investigated in order to obtain full physics simulations.

  9. A Thermal Model to Evaluate Sub-Freezing Startup for a Direct Hydrogen Hybrid Fuel Cell Vehicle Polymer Electrolyte Fuel Cell Stack and System

    E-Print Network [OSTI]

    Sundaresan, Meena

    2004-01-01

    fuel cell electric power generation system below the freezingthe fuel cell stack and system during the sub-freezingbelow the freezing point of water the fuel cell must be

  10. Taxation and Capital Spending Alan J. Auerbach

    E-Print Network [OSTI]

    Sadoulet, Elisabeth

    of new capital, r is the firm's nominal cost of funds (presumably a weighted average of debt and equity system of capital income taxation is so complex, leading to misallocation and hence effective reductions the object of frequent tax policy initiatives, the most recent being the temporary "bonus depreciation

  11. Housing market report Capital city market report

    E-Print Network [OSTI]

    Peters, Richard

    Housing market report Capital city market report Prepared February 2014 Dr Andrew Wilson, Senior mortgage interest rates, the current, once in a decade energy of the Sydney housing market is set house price growth since 2009 with the median house price increasing by 9.8 percent. All capital cities

  12. A Lifecycle Emissions Model (LEM): Lifecycle Emissions from Transportation Fuels, Motor Vehicles, Transportation Modes, Electricity Use, Heating and Cooking Fuels, and Materials

    E-Print Network [OSTI]

    Delucchi, Mark

    2003-01-01

    C (data from DME, 2001). EF E = the fuel cycle emissionDME = dimethyl ether. The feedstocks from which the fuels

  13. EPA and DOE Release Annual Fuel Economy Guide with 2014 Models...

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

    of the guide, available through www.fueleconomy.gov, allows consumers to enter local gasoline prices and typical driving habits to receive a personalized fuel cost estimate....

  14. Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles

    E-Print Network [OSTI]

    Zhao, Hengbing; Burke, Andy

    2008-01-01

    and Optimization of PEMFC Systems and its Application toand Optimization of PEMFC Systems and its Application onExchange Membrane fuel cell (PEMFC) technology for use in

  15. Fact #764: January 28, 2013 Model Year 2013 Brings More Fuel...

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

    available to consumers in several size classes. For a consumer purchasing a new large car in 2008, the highest combined cityhighway fuel economy available was 25 miles per...

  16. EPA and DOE Release Annual Fuel Economy Guide with 2014 Models | Department

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergy A plug-inPPL EnergyPlus, LLCConfidentialityOnline HostedIt is theStates |of

  17. DOE/EIA-M069(2010) Model Documentation Renewable Fuels Module

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul AugAdditions1 0 0 0 09)6)8) The9)

  18. DOE/EIA-M069(2011) Model Documentation Renewable Fuels Module

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul AugAdditions1 0 0 0 09)6)8) The9)69(2011)

  19. Model for Simulation of Hydride Precipitation in Zr-Based Used Fuel

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i nAand DOE SafetyofDepartment.Efficiency RebateDepartmentCladdings: A Status

  20. MELCOR Model of the Spent Fuel Pool of Fukushima Dai-ichi Unit 4

    Office of Scientific and Technical Information (OSTI)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfate Reducing(Journalspectroscopy ofArticle) |management (Patent)SciTechSciTech Connect

  1. RELAP5 Model of a Two-phase ThermoSyphon Experimental Facility for Fuels

    Office of Scientific and Technical Information (OSTI)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTech ConnectSpeedingConnect Pulse energy(Conference) |SciTech ConnectPROPOSING

  2. Annual Fuel Economy Guide with 2014 Models Released | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p a l De p u t yWaste | DepartmentEnergyEnergyEnergy Department

  3. Theory, modeling and evaluations for the fuel cycle (Conference) | SciTech

    Office of Scientific and Technical Information (OSTI)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.Theory of rare Kaon and Pion decays Citation Details In-Document Search Title:

  4. Theory, modeling and evaluations for the fuel cycle (Conference) | SciTech

    Office of Scientific and Technical Information (OSTI)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.Theory of rare Kaon and Pion decays Citation Details In-Document Search

  5. DOE and EPA Release Annual Fuel Economy Guide with 2013 Models | Department

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirley Ann JacksonDepartment ofOffice of Headquarters1,784-square-footEnergyHomeLLCParkWells |of

  6. Table 5.5. U.S. Vehicle Fuel Efficiency by Model Year, 1994

    U.S. Energy Information Administration (EIA) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearbyWithdrawalsHome6,672 7,2060 0 1 02. U.S.8. U.S..

  7. Table 5.6. U.S. Average Vehicle Fuel Consumption by Model Year, 1994

    U.S. Energy Information Administration (EIA) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearbyWithdrawalsHome6,672 7,2060 0 1 02. U.S.8. U.S... U.S.

  8. Survey Results and Analysis of the Cost and Efficiency of Various Operating Hydrogen Fueling Stations

    SciTech Connect (OSTI)

    Cornish, John

    2011-03-05

    Existing Hydrogen Fueling Stations were surveyed to determine capital and operational costs. Recommendations for cost reduction in future stations and for research were developed.

  9. Atrium Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar Energy LLC Jump to:Greece: Energy Resources Jump to:AtlanticaAtria

  10. Capital Connections | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar Energy LLC JumpBiossenceBrunswick,CalendarFork ElectricCapara Energia

  11. Peony Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop Inc Jump to:Newberg,Energy LLC Jump to:3 ofAltosPenoyer Valley ElectricPeony

  12. Riba Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop Inc Jump to:Newberg,EnergyEast Jump to: navigation,ReportVelho

  13. Gaian Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar2-0057-EA Jump to:ofEnia SpAFlexStock CoGTO Home

  14. Swiftsure Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS ReportEuropeEnergySustainability CenterSvayaSweco JumpaJump

  15. Arborview Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EAandAmminex A S Jump to:AngolaEnergyAquaAratua Central

  16. BG Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EAandAmminex AAustria Geothermal RegionAvraPáginasSolarBBBFC SolutionsBG

  17. Capital Point | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmentalBowerbank,Cammack Village, Arkansas: EnergyCounty,NewHatteras ElecPoint Jump to:

  18. Carbon Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmentalBowerbank,Cammack Village, Arkansas: EnergyCounty,NewHatteras2 Geothermal

  19. Commons Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTIONRobertsdale, Alabama (Utility Company)| Open EnergyColoradoBiomass EnergyCity,CommercialCommons

  20. GGV Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButtePowerEdistoWhiskeyFootprintGEXA Corp. (Delaware) Jump to: navigation,GGV

  1. Greencore Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsource History View New Pages RecentPlantMagmaIncentivesEnergyGreenVolts

  2. Greenrock Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsource History View New PagesInformation Regional Inventory ProtocolGreenpeace

  3. Infield Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsource History View NewGuam:on Openei |sourceAnd CentralWorld BankTerms

  4. BEV Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop IncIowaWisconsin: EnergyYork Jump|LineMaine:Ayuda:NavegacionBARC Electric CoopBEV

  5. Dragonfly Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButtePower VenturesInformation9)askDouble Oak, Texas: EnergyCo Jump

  6. Cascadia Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButte County,Camilla, Georgia: Energy014771°, -77.1888704°Cascade

  7. Clarey Capital | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButte County,Camilla,ThermalCubaParker,Georgia (UtilityWilliams -Centre, |

  8. Capital Solar | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LIST OFAMERICA'SHeavy Electricals Ltd BHEL JumpCMNA Power JumpWindSL Jump to:Solar

  9. Methodology for modeling the devolatilization of refuse-derived fuel from thermogravimetric analysis of municipal solid waste components

    SciTech Connect (OSTI)

    Fritsky, K.J.; Miller, D.L.; Cernansky, N.P.

    1994-09-01

    A methodology was introduced for modeling the devolatilization characteristics of refuse-derived fuel (RFD) in terms of temperature-dependent weight loss. The basic premise of the methodology is that RDF is modeled as a combination of select municipal solid waste (MSW) components. Kinetic parameters are derived for each component from thermogravimetric analyzer (TGA) data measured at a specific set of conditions. These experimentally derived parameters, along with user-derived parameters, are inputted to model equations for the purpose of calculating thermograms for the components. The component thermograms are summed to create a composite thermogram that is an estimate of the devolatilization for the as-modeled RFD. The methodology has several attractive features as a thermal analysis tool for waste fuels. 7 refs., 10 figs., 3 tabs.

  10. Mr. Walter Huber, Director Capital Improvements Division National Capital Region

    Office of Legacy Management (LM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal Gas &SCE-SessionsSouth DakotaRobbins and MyersHr.EvaluationJune~of theOfll s'_665

  11. Maryland-National Capital Building Industry Association Regulatory...

    Office of Environmental Management (EM)

    Maryland-National Capital Building Industry Association Regulatory Burden RFI (Federal Register August 8, 2012) Maryland-National Capital Building Industry Association Regulatory...

  12. Best Practices for Controlling Capital Costs in Net Zero Energy...

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

    Best Practices for Controlling Capital Costs in Net Zero Energy Design and Construction - 2014 BTO Peer Review Best Practices for Controlling Capital Costs in Net Zero Energy...

  13. Accessing Low-Cost Capital Through Securitization (Poster)

    SciTech Connect (OSTI)

    Mendelsohn, M.

    2014-10-01

    Poster for Solar Power International conference presents information on NREL's effort to open capital markets through securitization via Solar Access to Public Capital (SAPC) working group's efforts.

  14. A Multiphase Model for Cold Start of Polymer Electrolyte Fuel Leng Mao, Chao-Yang Wang,*,z

    E-Print Network [OSTI]

    interactions. The governing equations of mass, momentum, species, heat, and charge transport under coldA Multiphase Model for Cold Start of Polymer Electrolyte Fuel Cells Leng Mao, Chao-Yang Wang is presented to describe transport and electrochemical processes with ice formation during startup of polymer

  15. Modeling the natural attenuation of benzene in groundwater impacted by ethanol-blended fuels: Effect of ethanol content

    E-Print Network [OSTI]

    Alvarez, Pedro J.

    -source simulations imply that high-ethanol blends (e.g., E85) pose a lower risk of benzene reaching a receptor via gasoline, 15 years for E10, 9 years for E50, and 3 years for E85), indicating greater natural attenuationModeling the natural attenuation of benzene in groundwater impacted by ethanol-blended fuels

  16. Report: EM Human Capital Initiatives

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (BillionProvedTravelInformationCollectionGridReno Roundtable SummaryEM Communications August 24,HUMAN

  17. Principal Associate Director - Capital Projects

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservation of Fe(II) by Carbon-Rich Matrices in HydrothermalMagneticAiter

  18. Pore Scale Modeling of the Reactive Transport of Chromium in the Cathode of a Solid Oxide Fuel Cell

    SciTech Connect (OSTI)

    Ryan, Emily M.; Tartakovsky, Alexandre M.; Recknagle, Kurtis P.; Khaleel, Mohammad A.; Amon, Cristina

    2011-01-01

    We present a pore scale model of a solid oxide fuel cell (SOFC) cathode. Volatile chromium species are known to migrate from the current collector of the SOFC into the cathode where over time they decrease the voltage output of the fuel cell. A pore scale model is used to investigate the reactive transport of chromium species in the cathode and to study the driving forces of chromium poisoning. A multi-scale modeling approach is proposed which uses a cell level model of the cathode, air channel and current collector to determine the boundary conditions for a pore scale model of a section of the cathode. The pore scale model uses a discrete representation of the cathode to explicitly model the surface reactions of oxygen and chromium with a cathode material. The pore scale model is used to study the reaction mechanisms of chromium by considering the effects of reaction rates, diffusion coefficients, chromium vaporization, and oxygen consumption on chromium’s deposition in the cathode. The study shows that chromium poisoning is most significantly affected by the chromium reaction rates in the cathode and that the reaction rates are a function of the local current density in the cathode.

  19. Environmental Aspects of Advanced Nuclear Fuel Cycles: Parametric Modeling and Preliminary Analysis 

    E-Print Network [OSTI]

    Yancey, Kristina D.

    2010-07-14

    Nuclear power has the potential to help reduce rising carbon emissions, but to be considered sustainable, it must also demonstrate the availability of an indefinite fuel supply as well as not produce any significant negative environmental effects...

  20. Development of an Experimental Database and Kinetic Models for Surrogate Jet Fuels

    E-Print Network [OSTI]

    Pitsch, Heinz

    90089 Peter Lindstedt, Imperial College, London, UK SW72BX Kalyanasundaram Seshadri, University on the development of databases for real transportation fuels. As part of the discussions, the need for surrogate