Sample records for gdp industrial output

  1. U.S. Motor Vehicle Output and Other GDP, 1968-2007 Danilo J. Santini, Ph. D.

    E-Print Network [OSTI]

    Kemner, Ken

    U.S. Motor Vehicle Output and Other GDP, 1968-2007 Danilo J. Santini, Ph. D. Senior Economist, and perform publicly and display publicly, by or on behalf of the Government. 1 #12;U.S. Motor Vehicle Output of motor vehicle output" on the rest of the economy over the period 1968-2007. We statistically assess

  2. The effects of energy policies in China on GDP, industrial output and new energy profits1

    E-Print Network [OSTI]

    Lin, C.-Y. Cynthia

    include those involving environmental protection or financial incentives. Ever since the 1978 reform

  3. New Contract Helps Portsmouth GDP Cleanup

    Broader source: Energy.gov [DOE]

    To accelerate the Portsmouth GDP cleanup efforts left over from the Cold War, the Department of Energy made a huge step forward in our nuclear environmental cleanup efforts.

  4. Alternative methods for forecasting GDP Dominique Gugan

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    analysis. Better forecast performance for macroeconomic variables will lead to Paris School of Economics the speed of computers that can develop search algorithms from appropriate selection criteria, Devroye. 1 Introduction Forecasting macroeconomic variables such as GDP and inflation play an important role

  5. AEO2014: Preliminary Industrial Output

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I'26,282.1chemical7Host and Presentor3 Oil andFor AEO

  6. Comparisons of four categories of waste recycling in China's paper industry based on physical input-output life-cycle assessment model

    SciTech Connect (OSTI)

    Liang Sai [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Zhang, Tianzhu, E-mail: zhangtz@mail.tsinghua.edu.cn [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Xu Yijian [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); China Academy of Urban Planning and Design, Beijing 100037 (China)

    2012-03-15T23:59:59.000Z

    Highlights: Black-Right-Pointing-Pointer Using crop straws and wood wastes for paper production should be promoted. Black-Right-Pointing-Pointer Bagasse and textile waste recycling should be properly limited. Black-Right-Pointing-Pointer Imports of scrap paper should be encouraged. Black-Right-Pointing-Pointer Sensitivity analysis, uncertainties and policy implications are discussed. - Abstract: Waste recycling for paper production is an important component of waste management. This study constructs a physical input-output life-cycle assessment (PIO-LCA) model. The PIO-LCA model is used to investigate environmental impacts of four categories of waste recycling in China's paper industry: crop straws, bagasse, textile wastes and scrap paper. Crop straw recycling and wood utilization for paper production have small total intensity of environmental impacts. Moreover, environmental impacts reduction of crop straw recycling and wood utilization benefits the most from technology development. Thus, using crop straws and wood (including wood wastes) for paper production should be promoted. Technology development has small effects on environmental impacts reduction of bagasse recycling, textile waste recycling and scrap paper recycling. In addition, bagasse recycling and textile waste recycling have big total intensity of environmental impacts. Thus, the development of bagasse recycling and textile waste recycling should be properly limited. Other pathways for reusing bagasse and textile wastes should be explored and evaluated. Moreover, imports of scrap paper should be encouraged to reduce large indirect impacts of scrap paper recycling on domestic environment.

  7. Industry

    E-Print Network [OSTI]

    Bernstein, Lenny

    2008-01-01T23:59:59.000Z

    SHIP - Solar heat for industrial processes. Internationalsolar power could be used to provide process heat for

  8. Constraining Energy Consumption of China's Largest Industrial Enterprises Through the Top-1000 Energy-Consuming Enterprise Program

    E-Print Network [OSTI]

    Price, Lynn; Wang, Xuejun

    2007-01-01T23:59:59.000Z

    Industry Constraining Energy Consumption of China’s Largestone-to-one ratio of energy consumption to GDP – given China’goal of reducing energy consumption per unit of GDP by 20%

  9. External research and energy efficiency in the process industries

    SciTech Connect (OSTI)

    Kaarsberg, T.M.; Foust, T.D.

    1997-07-01T23:59:59.000Z

    The process industries in the US are under enormous pressure. These industries, even more than US industry on average, face skyrocketing environmental costs, a rapidly changing electricity market, potential climate change policies, aging infrastructure and strong international competition. To be profitable they must reduce their costs and environmental impacts while increasing their product quality, turnaround time, productivity and output. Most of these industries have already cut costs and labor as much as possible. Therefore, to survive, these industries must innovate. History shows that industries that are the most innovative are the most successful. These industries are vital to the US economy. For example, the metals, pulp and paper, chemicals and the petroleum refining industries account for more than $800 billion in products shipped and employ more than three million workers. Although the US has shifted dramatically toward services with 77% of workers and 74% of GDP now in the service sector, what many have missed is that the process industries are important customers for many of these new services. ServOnly the last two years of NSF industrial R and D data provide any breakout of non-manufacturing R and D. This paper discusses the past, current and possible future role of eternal research and development (R and D)--much of which is now in the service sector--in fostering innovation and thus energy efficiency in these industries. The authors suggest that these industries are more innovative than previously thought because of external research.

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -2.

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -2.3.

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA. Net

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.A.

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.A.B.

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997Million

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor U.S.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor U.S.

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable Coal Reserves

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable Coal

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverableRecoverable

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of Employees at

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of Employees

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3. Coal

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3. Coal4.

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6. U.S.

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.8.

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.8.9.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average Sales

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average Sales1.

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.4.

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.4.Coal

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.Coal Production

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.Coal

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.CoalCoal

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.CoalCoalMajor

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835 2.812Average

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average Price

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average Steam

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835AverageU.S.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9,

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. Coal

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. CoalAverage

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. CoalAverageCoal

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S. Coke

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2. Coal

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2. CoalU.S.

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2.

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2.Quantity

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.Average Price of

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.Average Price of

  14. GDP Jobs Direct Structure of Australian economy, employment and

    E-Print Network [OSTI]

    Pezzey, Jack

    0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% GDP Jobs Direct emissions Inclusive emissions Structure Geothermal On-shore wind Afforestation, cropland Coal-to-gas shift Agriculture, waste Coal CCS retrofit are not additive to those of previous years Source: McKinsey Australia Climate Change Initiative #12;What might

  15. Industry

    E-Print Network [OSTI]

    Bernstein, Lenny

    2008-01-01T23:59:59.000Z

    oil, starch and corn refining, since these can be a source of fuel products. The sugar cane industry

  16. EPICS : input / output controller (IOC) application developer's guide. EPICS release 3.12 specific documentation.[Experimental Physics and Industrial Control System

    SciTech Connect (OSTI)

    Kraimer, M. R.

    2002-01-30T23:59:59.000Z

    This document describes the core software that resides in an Input/Output Controller (IOC), one of the major components of EPICS. EPICS consists of a set of software components and tools that Application Developers use to create a control system. The basic components are: OPI--Operator Interface. This is a UNIX based workstation which can run various EPICS tools; IOC--Input/Output Controller. This is a VME/VXI based chassis containing a processor, various I/O modules and VME modules that provide access to other I/O buses such as GPIB; and LAN--Local Area Network. This is the communication network which allows the IOCs and OPIs to communicate. EPICS provides a software component, Channel Access, which provides network transparent communication between a Channel Access client and an arbitrary number of Channel Access servers. This report is intended for anyone developing EPICS IOC databases and/or new record/device/driver support.

  17. Industry

    E-Print Network [OSTI]

    Bernstein, Lenny

    2008-01-01T23:59:59.000Z

    of its electricity requirements in the USA (US DOE, 2002)USA, where motor-driven systems account for 63% of industrial electricity

  18. Beyond GDP: Measuring and achieving global genuine progress Ida Kubiszewski a,

    E-Print Network [OSTI]

    Vermont, University of

    's overall performance (Kuznets, 1934; Marcuss and Kane, 2007; McCulla and Smith, 2007). GDP's current role

  19. Industry

    E-Print Network [OSTI]

    Bernstein, Lenny

    2008-01-01T23:59:59.000Z

    iron and steel production. IEA Greenhouse Gas R&D Programme,tempera- ture range. IEA/Caddet, Sittard, The Netherlands.industry. Cheltenham, UK, IEA Greenhouse Gas R&D Programme,

  20. Industry

    E-Print Network [OSTI]

    Bernstein, Lenny

    2008-01-01T23:59:59.000Z

    process residual like bagasse are now available (Cornland etsugar in- dustry uses bagasse and the edible oils industrySection 7.4.7. ). The use of bagasse for energy is likely to

  1. Industry

    SciTech Connect (OSTI)

    Bernstein, Lenny; Roy, Joyashree; Delhotal, K. Casey; Harnisch, Jochen; Matsuhashi, Ryuji; Price, Lynn; Tanaka, Kanako; Worrell, Ernst; Yamba, Francis; Fengqi, Zhou; de la Rue du Can, Stephane; Gielen, Dolf; Joosen, Suzanne; Konar, Manaswita; Matysek, Anna; Miner, Reid; Okazaki, Teruo; Sanders, Johan; Sheinbaum Parado, Claudia

    2007-12-01T23:59:59.000Z

    This chapter addresses past, ongoing, and short (to 2010) and medium-term (to 2030) future actions that can be taken to mitigate GHG emissions from the manufacturing and process industries. Globally, and in most countries, CO{sub 2} accounts for more than 90% of CO{sub 2}-eq GHG emissions from the industrial sector (Price et al., 2006; US EPA, 2006b). These CO{sub 2} emissions arise from three sources: (1) the use of fossil fuels for energy, either directly by industry for heat and power generation or indirectly in the generation of purchased electricity and steam; (2) non-energy uses of fossil fuels in chemical processing and metal smelting; and (3) non-fossil fuel sources, for example cement and lime manufacture. Industrial processes also emit other GHGs, e.g.: (1) Nitrous oxide (N{sub 2}O) is emitted as a byproduct of adipic acid, nitric acid and caprolactam production; (2) HFC-23 is emitted as a byproduct of HCFC-22 production, a refrigerant, and also used in fluoroplastics manufacture; (3) Perfluorocarbons (PFCs) are emitted as byproducts of aluminium smelting and in semiconductor manufacture; (4) Sulphur hexafluoride (SF{sub 6}) is emitted in the manufacture, use and, decommissioning of gas insulated electrical switchgear, during the production of flat screen panels and semiconductors, from magnesium die casting and other industrial applications; (5) Methane (CH{sub 4}) is emitted as a byproduct of some chemical processes; and (6) CH{sub 4} and N{sub 2}O can be emitted by food industry waste streams. Many GHG emission mitigation options have been developed for the industrial sector. They fall into three categories: operating procedures, sector-wide technologies and process-specific technologies. A sampling of these options is discussed in Sections 7.2-7.4. The short- and medium-term potential for and cost of all classes of options are discussed in Section 7.5, barriers to the application of these options are addressed in Section 7.6 and the implication of industrial mitigation for sustainable development is discussed in Section 7.7. Section 7.8 discusses the sector's vulnerability to climate change and options for adaptation. A number of policies have been designed either to encourage voluntary GHG emission reductions from the industrial sector or to mandate such reductions. Section 7.9 describes these policies and the experience gained to date. Co-benefits of reducing GHG emissions from the industrial sector are discussed in Section 7.10. Development of new technology is key to the cost-effective control of industrial GHG emissions. Section 7.11 discusses research, development, deployment and diffusion in the industrial sector and Section 7.12, the long-term (post-2030) technologies for GHG emissions reduction from the industrial sector. Section 7.13 summarizes gaps in knowledge.

  2. Determinants of energy intensity in industrialized countries : a comparison of China and India

    E-Print Network [OSTI]

    Huang, Feiya

    2006-01-01T23:59:59.000Z

    The amount of final energy per unit of economic output (usually in terms of gross domestic product, or GDP), known as energy intensity, is often used to measure the effectiveness of energy use and the consumption patterns ...

  3. Enabling long term value added partnership in the healthcare industry

    E-Print Network [OSTI]

    Duarte Oliveira, Jorge Miguel dos Santos Fradinho

    2005-01-01T23:59:59.000Z

    The USA healthcare industry has recently undergone significant pressure to become competitive and think innovatively due to its increased growth as a percentage of the GDP, which was as much as 14. 1% in 2001. Additionally ...

  4. Temporal Causality between House Prices and Output in the U. S.: A Bootstrap Rolling-Window Approach

    E-Print Network [OSTI]

    Ahmad, Sajjad

    1 Temporal Causality between House Prices and Output in the U. S.: A Bootstrap Rolling price index and real GDP per capita in the U.S., using the bootstrap Granger (temporal) non-sample bootstrap non-Granger causality test result suggests the existence of a unidirectional causality running

  5. Crystal structure of a tetrameric GDP-D-mannose 4,6-dehydratase from a bacterial GDP-D-rhamnose biosynthetic pathway

    SciTech Connect (OSTI)

    Webb, N.A.; Mulichak, A.M.; Lam, J.S.; Rocchetta, H.L.; Garavito, R.M. (MSU); (Guelph); (PG)

    2010-03-08T23:59:59.000Z

    D-Rhamnose is a rare 6-deoxy monosaccharide primarily found in the lipopolysaccharide of pathogenic bacteria, where it is involved in host-bacterium interactions and the establishment of infection. The biosynthesis of D-rhamnose proceeds through the conversion of GDP-D-mannose by GDP-D-mannose 4,6-dehydratase (GMD) to GDP-4-keto-6-deoxymannose, which is subsequently reduced to GDP-D-rhamnose by a reductase. We have determined the crystal structure of GMD from Pseudomonas aeruginosa in complex with NADPH and GDP. GMD belongs to the NDP-sugar modifying subfamily of the short-chain dehydrogenase/reductase (SDR) enzymes, all of which exhibit bidomain structures and a conserved catalytic triad (Tyr-XXX-Lys and Ser/Thr). Although most members of this enzyme subfamily display homodimeric structures, this bacterial GMD forms a tetramer in the same fashion as the plant MUR1 from Arabidopsis thaliana. The cofactor binding sites are adjoined across the tetramer interface, which brings the adenosyl phosphate moieties of the adjacent NADPH molecules to within 7 {angstrom} of each other. A short peptide segment (Arg35-Arg43) stretches into the neighboring monomer, making not only protein-protein interactions but also hydrogen bonding interactions with the neighboring cofactor. The interface hydrogen bonds made by the Arg35-Arg43 segment are generally conserved in GMD and MUR1, and the interacting residues are highly conserved among the sequences of bacterial and eukaryotic GMDs. Outside of the Arg35-Arg43 segment, residues involved in tetrameric contacts are also quite conserved across different species. These observations suggest that a tetramer is the preferred, and perhaps functionally relevant, oligomeric state for most bacterial and eukaryotic GMDs.

  6. Industrial policy and the Indian electronics industry

    E-Print Network [OSTI]

    Love, Robert (Robert Eric)

    2008-01-01T23:59:59.000Z

    Recently, production within India's Electronics sector amounted to a low $12 billion when compared to the global output of $1400 billion. The slow growth in the local industry is often judged to be the result of late ...

  7. Energy-GDP decoupling in a second best world -A case study on India Cline Guivarcha,*

    E-Print Network [OSTI]

    Boyer, Edmond

    1 Energy-GDP decoupling in a second best world - A case study on India Céline Guivarcha best world ­ A case study on India. Climatic Change, Volume 113, Number 2, pages 339­ 356. Abstract India, energy intensity, second-best world, power sector, reference scenario. Introduction Reference

  8. Multiple Structural Breaks in India's GDP: Evidence from India's Service Sector

    E-Print Network [OSTI]

    Bandyopadhyay, Antar

    of economists and policy makers. India was designated as an agricultural country with a highest share1 Multiple Structural Breaks in India's GDP: Evidence from India's Service Sector Purba Roy Choudhury1 Abstract: This paper takes a comprehensive investigation into India's service sector, the main

  9. The effects of energy policies in China on energy consumption and GDP1

    E-Print Network [OSTI]

    Lin, C.-Y. Cynthia

    policies have significant impacts on diesel oil, gasoline and natural gas consumption. However, some energy The effects of energy policies in China on energy consumption and GDP1 Ming-Jie Lu, C.-Y. Cynthia Lin and Song Chen Abstract This paper examines the effects of energy policies in China on energy

  10. GDP Formulation of a segmented CDU Swing Cut Model for Refinery Planning

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    1 GDP Formulation of a segmented CDU Swing Cut Model for Refinery Planning (Performance Analysis. Grossmann #12;2 Motivation · Refinery planning is an active area in process systems that strongly relies HF REFINERY FUEL RG LPG LN HN KN GO1 GO2 VGO VR1 VR2 C1 LPG LIGHT NAPHTHA PMS 98 MOGAS 95 JET FUEL

  11. The Long-Run Relationship between Money, Nominal GDP, and the Price Level in Venezuela: 1950 to 1996

    E-Print Network [OSTI]

    Ahmad, Sajjad

    The Long-Run Relationship between Money, Nominal GDP, and the Price Level in Venezuela: 1950 that structural breaks may be important. Since the economy depends heavily on oil revenue, oil price shocks have whether a significant long-run relationship exists between money and nominal GDP and between money

  12. Current Directions in Freight and Logistics Industry

    E-Print Network [OSTI]

    Minnesota, University of

    Current Directions in Freight and Logistics Industry CTS Freight and Logistics Symposium November- the-box #12;Perspective Be sure to look-up from time-to-time #12;Why Discuss Freight and Logistics....Large Part of the Economy Logistics Cost As A Percent of GDP ­ 10% Source: CSCMP State of Logistics 2007 #12

  13. GDP Formulation of a segmented CDU Swing Cut Model for Refinery Planning

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    1 GDP Formulation of a segmented CDU Swing Cut Model for Refinery Planning Department of Chemical · Refinery planning is an active area in process systems that strongly relies on the accuracy of the CDU REFINERY FUEL RG LPG LN HN KN GO1 GO2 VGO VR1 VR2 C1 LPG LIGHT NAPHTHA PMS 98 MOGAS 95 JET FUEL AGO HGO HFO

  14. Serial Input Output

    SciTech Connect (OSTI)

    Waite, Anthony; /SLAC

    2011-09-07T23:59:59.000Z

    Serial Input/Output (SIO) is designed to be a long term storage format of a sophistication somewhere between simple ASCII files and the techniques provided by inter alia Objectivity and Root. The former tend to be low density, information lossy (floating point numbers lose precision) and inflexible. The latter require abstract descriptions of the data with all that that implies in terms of extra complexity. The basic building blocks of SIO are streams, records and blocks. Streams provide the connections between the program and files. The user can define an arbitrary list of streams as required. A given stream must be opened for either reading or writing. SIO does not support read/write streams. If a stream is closed during the execution of a program, it can be reopened in either read or write mode to the same or a different file. Records represent a coherent grouping of data. Records consist of a collection of blocks (see next paragraph). The user can define a variety of records (headers, events, error logs, etc.) and request that any of them be written to any stream. When SIO reads a file, it first decodes the record name and if that record has been defined and unpacking has been requested for it, SIO proceeds to unpack the blocks. Blocks are user provided objects which do the real work of reading/writing the data. The user is responsible for writing the code for these blocks and for identifying these blocks to SIO at run time. To write a collection of blocks, the user must first connect them to a record. The record can then be written to a stream as described above. Note that the same block can be connected to many different records. When SIO reads a record, it scans through the blocks written and calls the corresponding block object (if it has been defined) to decode it. Undefined blocks are skipped. Each of these categories (streams, records and blocks) have some characteristics in common. Every stream, record and block has a name with the condition that each stream, record or block name must be unique in its category (i.e. all streams must have different names, but a stream can have the same name as a record). Each category is an arbitrary length list which is handled by a 'manager' and there is one manager for each category.

  15. China's Pathways to Achieving 40% ~ 45% Reduction in CO{sub 2} Emissions per Unit of GDP in 2020: Sectoral Outlook and Assessment of Savings Potential

    SciTech Connect (OSTI)

    Zheng, Nina; Fridley, David; Zhou, Nan; Levine, Mark; Price, Lynn; Ke, Jing

    2011-09-30T23:59:59.000Z

    Achieving China’s goal of reducing its carbon intensity (CO{sub 2} per unit of GDP) by 40% to 45% percent below 2005 levels by 2020 will require the strengthening and expansion of energy efficiency policies across the buildings, industries and transport sectors. This study uses a bottom-up, end-use model and two scenarios -- an enhanced energy efficiency (E3) scenario and an alternative maximum technically feasible energy efficiency improvement (Max Tech) scenario – to evaluate what policies and technical improvements are needed to achieve the 2020 carbon intensity reduction target. The findings from this study show that a determined approach by China can lead to the achievement of its 2020 goal. In particular, with full success in deepening its energy efficiency policies and programs but following the same general approach used during the 11th Five Year Plan, it is possible to achieve 49% reduction in CO{sub 2} emissions per unit of GDP (CO{sub 2} emissions intensity) in 2020 from 2005 levels (E3 case). Under the more optimistic but feasible assumptions of development and penetration of advanced energy efficiency technology (Max Tech case), China could achieve a 56% reduction in CO{sub 2} emissions intensity in 2020 relative to 2005 with cumulative reduction of energy use by 2700 Mtce and of CO{sub 2} emissions of 8107 Mt CO{sub 2} between 2010 and 2020. Energy savings and CO{sub 2} mitigation potential varies by sector but most of the energy savings potential is found in energy-intensive industry. At the same time, electricity savings and the associated emissions reduction are magnified by increasing renewable generation and improving coal generation efficiency, underscoring the dual importance of end-use efficiency improvements and power sector decarbonization.

  16. NEMS industrial module documentation report

    SciTech Connect (OSTI)

    Not Available

    1994-01-01T23:59:59.000Z

    The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2010) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of output of industrial activity. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

  17. Golgi GDP-mannose Uptake Requires Leishmania LPG2 A MEMBER OF A EUKARYOTIC FAMILY OF PUTATIVE NUCLEOTIDE-SUGAR TRANSPORTERS*

    E-Print Network [OSTI]

    Beverley, Stephen M.

    and mammalian cells lack a Golgi GDP-Man transporter, this activity may offer a new tar- get for chemotherapy include those for UDP-Gal, UDP-Glc, UDP-GlcNAc, UDP-glucuronic acid, UDP-xylose, UDP-GalNAc, GDP-fucose, GDP-Man, and CMP-sialic acid (1). Three candidate NST genes have been reported recently: one

  18. Reliable Gas Turbine Output: Attaining Temperature Independent Performance

    E-Print Network [OSTI]

    Neeley, J. E.; Patton, S.; Holder, F.

    % of the electric system, could create reliability and operational problems. This paper explores the potential for maintaining constant, reliable outputs from gas turbines by cooling ambient air temperatures before the air is used in the compressor section... strides have been made in the development of both aircraft, aircraft-derivative, and industrial gas turbines. The Basic Cycle The basic gas turbine engine consists of a compressor, a combustor, and a turbine in series. The intake air is compressed...

  19. Overload protection circuit for output driver

    DOE Patents [OSTI]

    Stewart, Roger G. (Neshanic Station, NJ)

    1982-05-11T23:59:59.000Z

    A protection circuit for preventing excessive power dissipation in an output transistor whose conduction path is connected between a power terminal and an output terminal. The protection circuit includes means for sensing the application of a turn on signal to the output transistor and the voltage at the output terminal. When the turn on signal is maintained for a period of time greater than a given period without the voltage at the output terminal reaching a predetermined value, the protection circuit decreases the turn on signal to, and the current conduction through, the output transistor.

  20. DUAL-OUTPUT HOLA FIRMWARE AND TESTS

    E-Print Network [OSTI]

    another channel (thus, "dual-output" HOLA) · Another LDC+ROMB block was added to receive data from side S32PCI64 "SOLAR" mezzanine card: Provides access to S-LINK via PCI bus The first prototype of dual-outputDUAL-OUTPUT HOLA FIRMWARE AND TESTS Anton Kapliy Mel Shochet Fukun Tang Daping Weng #12;Summary

  1. Industrial Permit

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

    Protection Obeying Environmental Laws Industrial Permit Industrial Permit The Industrial Permit authorizes the Laboratory to discharge point-source effluents under the...

  2. Water Power Calculator Temperature and Analog Input/Output Module Ambient Temperature Testing

    SciTech Connect (OSTI)

    Mark D. McKay

    2011-02-01T23:59:59.000Z

    Water Power Calculator Temperature and Analog input/output Module Ambient Temperature Testing A series of three ambient temperature tests were conducted for the Water Power Calculator development using the INL Calibration Laboratory’s Tenney Environmental Chamber. The ambient temperature test results demonstrate that the Moore Industries Temperature Input Modules, Analog Input Module and Analog Output Module, ambient temperature response meet or exceed the manufactures specifications

  3. OUTPUT REGULATION OF NONLINEAR NEUTRAL SYSTEMS

    E-Print Network [OSTI]

    Fridman, Emilia

    OUTPUT REGULATION OF NONLINEAR NEUTRAL SYSTEMS Emilia Fridman1 Department of Electrical Engineering, Tel-Aviv University Ramat-Aviv, Tel-Aviv 69978, Israel emilia@eng.tau.ac.il Summary. Output regulation regulation, regulator equations, center manifold 1 Introduction One of the most important problems in control

  4. Bayesian Learning of unobservable output 1 Bayesian Learning of unobservable output

    E-Print Network [OSTI]

    Provence Aix-Marseille I, Université de

    Bayesian Learning of unobservable output 1 Bayesian Learning of unobservable output aggregating the consistency of our method and illustrate its efficiency using simulations. Although up to our knowledge there are no similar algorithms for unobservable output, we compared in our simulations to supervised approaches

  5. The Structure of the MUR1 GDP-mannose 4,67-deydratase from A. thaliana: Implications for Ligand Binding Specificity

    SciTech Connect (OSTI)

    Mulichak, A.M.; Bonin, C.P.; Reiter, W.-D.; Garavito, R.M. (Michigan State University)

    2010-03-08T23:59:59.000Z

    GDP-D-mannose 4,6-dehydratase catalyzes the first step in the de novo synthesis of GDP-L-fucose, the activated form of L-fucose, which is a component of glycoconjugates in plants known to be important to the development and strength of stem tissues. We have determined the three-dimensional structure of the MUR1 dehydratase isoform from Arabidopsis thaliana complexed with its NADPH cofactor as well as with the ligands GDP and GDP-D-rhamnose. MUR1 is a member of the nucleoside-diphosphosugar modifying subclass of the short-chain dehydrogenase/reductase enzyme family, having homologous structures and a conserved catalytic triad of Lys, Tyr, and Ser/Thr residues. MUR1 is the first member of this subfamily to be observed as a tetramer, the interface of which reveals a close and intimate overlap of neighboring NADP{sup +}-binding sites. The GDP moiety of the substrate also binds in an unusual syn conformation. The protein-ligand interactions around the hexose moiety of the substrate support the importance of the conserved triad residues and an additional Glu side chain serving as a general base for catalysis. Phe and Arg side chains close to the hexose ring may serve to confer substrate specificity at the O2 position. In the MUR1/GDP-D-rhamnose complex, a single unique monomer within the protein tetramer that has an unoccupied substrate site highlights the conformational changes that accompany substrate binding and may suggest the existence of negative cooperativity in MUR1 function.

  6. Industrial Engineering Industrial Advisory Board

    E-Print Network [OSTI]

    Gelfond, Michael

    Industrial Engineering Industrial Advisory Board (IAB) #12;PURPOSE: The Texas Tech University - Industrial Engineering Industrial Ad- visory Board (IAB) is an association of professionals with a com- mon goal - promoting and developing the Texas Tech Department of Industrial Engineering and its students

  7. PETROLEUM INDUSTRY INFORMATION REPORTING ACT

    E-Print Network [OSTI]

    compliance. The Energy Commission uses the new refinery reports when creating the Weekly Fuels Watch Report refinery production and inventories. Monthly data of refinery inputs and outputs have a variety of regular use data by refineries to support analyses of total energy use by industry type within the state

  8. POLE PLACEMENT BY STATIC OUTPUT FEEDBACK FOR ...

    E-Print Network [OSTI]

    SIAM (#1) 1035 2001 Apr 10 12:32:38

    2002-06-04T23:59:59.000Z

    topology) subset U of such systems, where the real pole placement map is not surjective. It follows that, for ... Key words. linear systems, static output control feedback, pole placement. AMS subject .... is an integral power of 2. In the opposite ...

  9. Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs

    E-Print Network [OSTI]

    Venditti, David A.

    Anisotropic grid–adaptive strategies are presented for viscous flow simulations in which the accurate prediction of multiple aerodynamic outputs (such as the lift, drag, and moment coefficients) is required from a single ...

  10. SOLAR ENERGY (conditionally accepted 1/2010) QUANTIFYING PV POWER OUTPUT VARIABILITY

    E-Print Network [OSTI]

    Perez, Richard R.

    SOLAR ENERGY (conditionally accepted 1/2010) QUANTIFYING PV POWER OUTPUT VARIABILITY Thomas E create major problems that will require major mitigation efforts. #12;SOLAR ENERGY (conditionally industry believe it could constrain the penetration of gridconnected PV. The U.S. Department of Energy

  11. Emerging energy-efficient technologies for industry

    SciTech Connect (OSTI)

    Worrell, Ernst; Martin, Nathan; Price, Lynn; Ruth, Michael; Elliott, Neal; Shipley, Anna; Thorne, Jennifer

    2004-01-01T23:59:59.000Z

    U.S. industry consumes approximately 37 percent of the nation's energy to produce 24 percent of the nation's GDP. Increasingly, society is confronted with the challenge of moving toward a cleaner, more sustainable path of production and consumption, while increasing global competitiveness. Technology is essential in achieving these challenges. We report on a recent analysis of emerging energy-efficient technologies for industry, focusing on over 50 selected technologies. The technologies are characterized with respect to energy efficiency, economics and environmental performance. This paper provides an overview of the results, demonstrating that we are not running out of technologies to improve energy efficiency, economic and environmental performance, and neither will we in the future. The study shows that many of the technologies have important non-energy benefits, ranging from reduced environmental impact to improved productivity, and reduced capital costs compared to current technologies.

  12. PV output smoothing with energy storage.

    SciTech Connect (OSTI)

    Ellis, Abraham; Schoenwald, David Alan

    2012-03-01T23:59:59.000Z

    This report describes an algorithm, implemented in Matlab/Simulink, designed to reduce the variability of photovoltaic (PV) power output by using a battery. The purpose of the battery is to add power to the PV output (or subtract) to smooth out the high frequency components of the PV power that that occur during periods with transient cloud shadows on the PV array. The control system is challenged with the task of reducing short-term PV output variability while avoiding overworking the battery both in terms of capacity and ramp capability. The algorithm proposed by Sandia is purposely very simple to facilitate implementation in a real-time controller. The control structure has two additional inputs to which the battery can respond. For example, the battery could respond to PV variability, load variability or area control error (ACE) or a combination of the three.

  13. Single Inductor Dual Output Buck Converter

    E-Print Network [OSTI]

    Eachempatti, Haritha

    2010-07-14T23:59:59.000Z

    of value 3V. The main focus areas are low cross regulation between the outputs and supply of completely independent load current levels while maintaining desired values (1.2V,1.5V) within well controlled ripple levels. Dynamic hysteresis control is used...

  14. Porous radiant burners having increased radiant output

    DOE Patents [OSTI]

    Tong, Timothy W. (Tempe, AZ); Sathe, Sanjeev B. (Tempe, AZ); Peck, Robert E. (Tempe, AZ)

    1990-01-01T23:59:59.000Z

    Means and methods for enhancing the output of radiant energy from a porous radiant burner by minimizing the scattering and increasing the adsorption, and thus emission of such energy by the use of randomly dispersed ceramic fibers of sub-micron diameter in the fabrication of ceramic fiber matrix burners and for use therein.

  15. Bioenergy technology balancing energy output with environmental

    E-Print Network [OSTI]

    Levi, Ran

    E2.3 Bioenergy technology ­ balancing energy output with environmental benefitsbenefits John bioenergy Farmers historically used 25% land for horse feed #12;Energy crops are `solar panels' Solar energy° 50° #12;Same climate data (A1F1 scenario for 2050 - 2080) but the genotype is one which is less

  16. Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs

    E-Print Network [OSTI]

    Peraire, Jaime

    Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs David A. Venditti and David L Anisotropic grid­adaptive strategies are presented for viscous flow simulations in which the accurate estimation and Hessian-based anisotropic grid adaptation. Airfoil test cases are presented to demonstrate

  17. UFO - The Universal FeynRules Output

    E-Print Network [OSTI]

    Céline Degrande; Claude Duhr; Benjamin Fuks; David Grellscheid; Olivier Mattelaer; Thomas Reiter

    2012-07-31T23:59:59.000Z

    We present a new model format for automatized matrix-element generators, the so- called Universal FeynRules Output (UFO). The format is universal in the sense that it features compatibility with more than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a Python module that can easily be linked to other computer codes. We then describe an interface for the Mathematica package FeynRules that allows for an automatic output of models in the UFO format.

  18. UFO - The Universal FeynRules Output

    E-Print Network [OSTI]

    Degrande, Céline; Fuks, Benjamin; Grellscheid, David; Mattelaer, Olivier; Reiter, Thomas

    2011-01-01T23:59:59.000Z

    We present a new model format for automatized matrix-element generators, the so- called Universal FeynRules Output (UFO). The format is universal in the sense that it features compatibility with more than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a Python module that can easily be linked to other computer codes. We then describe an interface for the Mathematica package FeynRules that allows for an automatic output of models in the UFO format.

  19. Boosting America's Hydropower Output | 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 DataDepartment of Energy Your Density Isn't Your Destiny: The FutureCommentsEnergyandapproximatelyBoosting America's Hydropower Output

  20. Characterizing detonator output using dynamic witness plates

    SciTech Connect (OSTI)

    Murphy, Michael John [Los Alamos National Laboratory; Adrian, Ronald J [Los Alamos National Laboratory

    2009-01-01T23:59:59.000Z

    A sub-microsecond, time-resolved micro-particle-image velocimetry (PIV) system is developed to investigate the output of explosive detonators. Detonator output is directed into a transparent solid that serves as a dynamic witness plate and instantaneous shock and material velocities are measured in a two-dimensional plane cutting through the shock wave as it propagates through the solid. For the case of unloaded initiators (e.g. exploding bridge wires, exploding foil initiators, etc.) the witness plate serves as a surrogate for the explosive material that would normally be detonated. The velocity-field measurements quantify the velocity of the shocked material and visualize the geometry of the shocked region. Furthermore, the time-evolution of the velocity-field can be measured at intervals as small as 10 ns using the PIV system. Current experimental results of unloaded exploding bridge wire output in polydimethylsiloxane (PDMS) witness plates demonstrate 20 MHz velocity-field sampling just 300 ns after initiation of the wire.

  1. Comparison of CAISO-run Plexos output with LLNL-run Plexos output

    SciTech Connect (OSTI)

    Schmidt, A; Meyers, C; Smith, S

    2011-12-20T23:59:59.000Z

    In this report we compare the output of the California Independent System Operator (CAISO) 33% RPS Plexos model when run on various computing systems. Specifically, we compare the output resulting from running the model on CAISO's computers (Windows) and LLNL's computers (both Windows and Linux). We conclude that the differences between the three results are negligible in the context of the entire system and likely attributed to minor differences in Plexos version numbers as well as the MIP solver used in each case.

  2. OTHER INDUSTRIES

    Broader source: Energy.gov [DOE]

    AMO funded research results in novel technologies in diverse industries beyond the most energy intensive ones within the U.S. Manufacturing sector. These technologies offer quantifiable energy...

  3. Steady-state bumpless transfer under controller uncertainty using the state/output feedback topology

    SciTech Connect (OSTI)

    Zheng, K.; Lee, A.H.; Bentsman, J.; Taft, C.W. [University of Illinois, Urbana, IL (United States)

    2006-01-15T23:59:59.000Z

    Linear quadratic (LQ) bumpless transfer design introduced recently by Turner and Walker gives a very convenient and straightforward computational procedure for the steady-state bumpless transfer operator synthesis. It is, however, found to be incapable of providing convergence of the output of the offline controller to that of the online controller in several industrial applications, producing bumps in the plant output in the wake of controller transfer. An examination of this phenomenon reveals that the applications in question are characterized by a significant mismatch, further referred to as controller uncertainty, between the dynamics of the implemented controllers and their models used in the transfer operator computation. To address this problem, while retaining the convenience of the Turner and Walker design, a novel state/output feedback bumpless transfer topology is introduced that employs the nominal state of the offline controller and, through the use of an additional controller/model mismatch compensator, also the offline controller output. A corresponding steady-state bumpless transfer design procedure along with the supporting theory is developed for a large class of systems. Due to these features, it is demonstrated to solve a long-standing problem of high-quality steady-state bumpless transfer from the industry standard low-order nonlinear multiloop PID-based controllers to the modern multiinput-multioutput (MIMO) robust controllers in the megawatt/throttle pressure control of a typical coal-fired boiler/turbine unit.

  4. Assessment of Energy Efficiency Improvement and CO2 Emission Reduction Potentials in the Cement Industry in China

    E-Print Network [OSTI]

    Hasanbeigi, Ali

    2013-01-01T23:59:59.000Z

    Economic Output in Chinese Cement Kilns,” Proceedings of thereduction of China’s cement industry. Energy Policy 45 (751. Kong, Xiangzhong (China Cement Association, CCA), 2009.

  5. Steam Path Audits on Industrial Steam Turbines

    E-Print Network [OSTI]

    Mitchell, D. R.

    in sellable power output as a result of improved turbine efficiency. The Lyondell facility is a combined cycle power plant where a gas turbine: heat recovery system supplies steam to the steam turbine. Since this steam is a bypropuct of the gas turbine...steam Path Audits on Industrial steam Turbines DOUGLAS R. MITCHELL. ENGINEER. ENCOTECH, INC., SCHENECTADY, NEW YORK ABSTRACT The electric utility industry has benefitted from steam path audits on steam turbines for several years. Benefits...

  6. World crude output overcomes Persian Gulf disruption

    SciTech Connect (OSTI)

    Not Available

    1992-02-01T23:59:59.000Z

    Several OPEC producers made good on their promises to replace 2.7 MMbpd of oil exports that vanished from the world market after Iraq took over Kuwait. Even more incredibly, they accomplished this while a breathtaking 1.2- MMbopd reduction in Soviet output took place during the course of 1991. After Abu Dhabi, Indonesia, Iran, Libya, Nigeria, Saudi Arabia and Venezuela turned the taps wide open, their combined output rose 2.95 MMbopd. Put together with a 282,000-bopd increase by Norway and contributions from smaller producers, this enabled world oil production to remain within 400,000 bopd of its 1990 level. The 60.5-MMbopd average was off by just 0.7%. This paper reports that improvement took place in five of eight regions. Largest increases were in Western Europe and Africa. Greatest reductions occurred in Eastern Europe and the Middle East. Fifteen nations produced 1 MMbopd or more last year, compared with 17 during 1990.

  7. Soft-Input Soft-Output Sphere Decoding Christoph Studer

    E-Print Network [OSTI]

    Soft-Input Soft-Output Sphere Decoding Christoph Studer Integrated Systems Laboratory ETH Zurich Soft-input soft-output (SISO) detection in multiple-input multiple-output (MIMO) systems constitutes Laboratory ETH Zurich, 8092 Zurich, Switzerland Email: boelcskei@nari.ee.ethz.ch Abstract--Soft-input soft

  8. Output error identification of hydrogenerator conduit dynamics

    SciTech Connect (OSTI)

    Vogt, M.A.; Wozniak, L. (Illinois Univ., Urbana, IL (USA)); Whittemore, T.R. (Bureau of Reclamation, Denver, CO (USA))

    1989-09-01T23:59:59.000Z

    Two output error model reference adaptive identifiers are considered for estimating the parameters in a reduced order gate position to pressure model for the hydrogenerator. This information may later be useful in an adaptive controller. Gradient and sensitivity functions identifiers are discussed for the hydroelectric application and connections are made between their structural differences and relative performance. Simulations are presented to support the conclusion that the latter algorithm is more robust, having better disturbance rejection and less plant model mismatch sensitivity. For identification from recorded plant data from step gate inputs, the other algorithm even fails to converge. A method for checking the estimated parameters is developed by relating the coefficients in the reduced order model to head, an externally measurable parameter.

  9. Commissioning of output factors for uniform scanning proton beams

    SciTech Connect (OSTI)

    Zheng Yuanshui; Ramirez, Eric; Mascia, Anthony; Ding Xiaoning; Okoth, Benny; Zeidan, Omar; Hsi Wen; Harris, Ben; Schreuder, Andries N.; Keole, Sameer [ProCure Proton Therapy Center, 5901 West Memorial Road, Oklahoma City, Oklahoma 73142 (United States); ProCure Treatment Centers, 420 North Walnut Street, Bloomington, Indiana 47404 (United States); ProCure Proton Therapy Center, 5901 West Memorial Road, Oklahoma City, Oklahoma 73142 (United States)

    2011-04-15T23:59:59.000Z

    Purpose: Current commercial treatment planning systems are not able to accurately predict output factors and calculate monitor units for proton fields. Patient-specific field output factors are thus determined by either measurements or empirical modeling based on commissioning data. The objective of this study is to commission output factors for uniform scanning beams utilized at the ProCure proton therapy centers. Methods: Using water phantoms and a plane parallel ionization chamber, the authors first measured output factors with a fixed 10 cm diameter aperture as a function of proton range and modulation width for clinically available proton beams with ranges between 4 and 31.5 cm and modulation widths between 2 and 15 cm. The authors then measured the output factor as a function of collimated field size at various calibration depths for proton beams of various ranges and modulation widths. The authors further examined the dependence of the output factor on the scanning area (i.e., uncollimated proton field), snout position, and phantom material. An empirical model was developed to calculate the output factor for patient-specific fields and the model-predicted output factors were compared to measurements. Results: The output factor increased with proton range and field size, and decreased with modulation width. The scanning area and snout position have a small but non-negligible effect on the output factors. The predicted output factors based on the empirical modeling agreed within 2% of measurements for all prostate treatment fields and within 3% for 98.5% of all treatment fields. Conclusions: Comprehensive measurements at a large subset of available beam conditions are needed to commission output factors for proton therapy beams. The empirical modeling agrees well with the measured output factor data. This investigation indicates that it is possible to accurately predict output factors and thus eliminate or reduce time-consuming patient-specific output measurements for proton treatments.

  10. Regulatory Reform to Promote Clean Energy: The Potential of Output-Based Emissions Standards

    SciTech Connect (OSTI)

    Cox, Matthew [Georgia Institute of Technology] [Georgia Institute of Technology; Brown, Dr. Marilyn Ann [Georgia Institute of Technology] [Georgia Institute of Technology; Jackson, Roderick K [ORNL] [ORNL

    2011-01-01T23:59:59.000Z

    Barriers to industrial energy-efficient technologies hinder their use. A number of EPA analyses and industrial experts have found that the utilization of input-based emissions standards (measured in parts-per-million or pounds/MMBtu) in the Clean Air Act creates a regulatory barrier to the installation and deployment of technologies that emit fewer criteria pollutants and use energy more efficiently. Changing emission management strategies to an output-based emissions standard (measured in tons of pollutant emitted) is a way to ameliorate some of these barriers. Combined heat and power (CHP) is one of the key technologies that would see increased industrial application if the emissions standards were modified. Many states have made this change since the EPA first approved it in 2000, although direction from the Federal government could speed implementation modifications. To analyze the national impact of accelerated state adoption of output-based standards on CHP technologies, this paper uses detailed National Energy Modeling System (NEMS) and spreadsheet analysis illustrating two phased-in adoption scenarios for output-based emissions standards in the industrial sector. Benefit/cost metrics are calculated from a private and public perspective, and also a social perspective that considers the criteria and carbon air pollution emissions. These scenarios are compared to the reference case of AEO 2010 and are quite favorable, with a social benefit-cost ratio of 16.0 for a five-year phase-in scenario. In addition, the appropriateness of the Federal role, applicability, technology readiness, and administrative feasibility are discussed.

  11. Output power characteristics and performance of TOPAZ II Thermionic Fuel Element No. 24

    SciTech Connect (OSTI)

    Luchau, D.W.; Bruns, D.R. [Team Specialty Services, Inc., TOPAZ International Program, 901 University Blvd., SE, Albuquerque, New Mexico 87106 (United States); Izhvanov, O.; Androsov, V. [JV INERTEK, Scientific Industrial Association ``Luch``, 24 Zheleznodorozhnaya, Podolsk, (Russia) 142100

    1996-03-01T23:59:59.000Z

    A final report on the output power characteristics and capabilities of single cell TOPAZ II Thermionic Fuel Element (TFE) No. 24 is presented. Thermal power tests were conducted for over 3000 hours to investigate converter performance under normal and adverse operating conditions. Experiments conducted include low power testing, high power testing, air introduction to the interelectrode gap, collector temperature optimization, thermal modeling, and output power characteristic measurements. During testing, no unexpected degradation in converter performance was observed. The TFE has been removed from the test stand and returned to Scientific Industrial Association {open_quote}{open_quote}LUCH{close_quote}{close_quote} for materials analysis and report. This research was conducted at the Thermionic System Evaluation Test (TSET) Facility at the New Mexico Engineering Research Institute (NMERI) as a part of the Topaz International Program (TIP) by the Air Force Phillips Laboratory (PL). {copyright} {ital 1996 American Institute of Physics.}

  12. Method and apparatus for varying accelerator beam output energy

    DOE Patents [OSTI]

    Young, Lloyd M. (Los Alamos, NM)

    1998-01-01T23:59:59.000Z

    A coupled cavity accelerator (CCA) accelerates a charged particle beam with rf energy from a rf source. An input accelerating cavity receives the charged particle beam and an output accelerating cavity outputs the charged particle beam at an increased energy. Intermediate accelerating cavities connect the input and the output accelerating cavities to accelerate the charged particle beam. A plurality of tunable coupling cavities are arranged so that each one of the tunable coupling cavities respectively connect an adjacent pair of the input, output, and intermediate accelerating cavities to transfer the rf energy along the accelerating cavities. An output tunable coupling cavity can be detuned to variably change the phase of the rf energy reflected from the output coupling cavity so that regions of the accelerator can be selectively turned off when one of the intermediate tunable coupling cavities is also detuned.

  13. China's Pathways to Achieving 40percent 45percent Reduction in CO2 Emissions per Unit of GDP in 2020: Sectoral Outlook and Assessment of Savings Potential

    E-Print Network [OSTI]

    Zheng, Nina

    2013-01-01T23:59:59.000Z

    Generation Growth Demand Side Management Industrial Sectortechnology and demand side management. For electricity

  14. average power output: Topics by E-print Network

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

    in the bucket). For low Carroll, David L. 7 High power multi-output piezoelectric transformers. Open Access Theses and Dissertations Summary: ??Piezoelectric transformers have...

  15. action potential output: Topics by E-print Network

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

    HF efficiency, but does not necessarily yield a higher measurable power (power in the bucket). For low Carroll, David L. 376 A Spatial Analysis of Multivariate Output from...

  16. advisory capability output: Topics by E-print Network

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

    HF efficiency, but does not necessarily yield a higher measurable power (power in the bucket). For low Carroll, David L. 453 A Spatial Analysis of Multivariate Output from...

  17. Sandia National Laboratories: simulating solar-power-plant output...

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

    simulating solar-power-plant output variability Sandia PV Team Publishes Book Chapter On January 21, 2014, in Computational Modeling & Simulation, Energy, Modeling & Analysis,...

  18. MIT and Automotive Industries MIT Industry Brief

    E-Print Network [OSTI]

    Ceder, Gerbrand

    MIT and Automotive Industries MIT Industry Brief MIT's Industrial Liaison Program (ILP) can bring@ilp.mit.edu, or visit http://ilp-www.mit.edu. MIT and Automotive Industries The Massachusetts Institute of Technology (MIT) is a leading center of research and education on topics important to the automotive industry

  19. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

    A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

  20. EIA Energy Efficiency-Table 3e. Gross Output by Selected Industries, 1998,

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOrigin State GlossaryEnergy )and 2002 e

  1. EIA Energy Efficiency-Table 4e. Gross Output by Selected Industries, 1998,

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOrigin State GlossaryEnergy )andand 2002

  2. Interactive Computing 1 Input/Output and Complex Arithmetic

    E-Print Network [OSTI]

    Verschelde, Jan

    Interactive Computing 1 Input/Output and Complex Arithmetic interactive Python scripts complex Software (MCS 507 L-3) Interactive Computing 30 August 2013 1 / 33 #12;Interactive Computing 1 Input/Output and Complex Arithmetic interactive Python scripts complex arithmetic 2 Python Coding Style and pylint coding

  3. A Note on Platt's Probabilistic Outputs for Support Vector Machines

    E-Print Network [OSTI]

    Abu-Mostafa, Yaser S.

    A Note on Platt's Probabilistic Outputs for Support Vector Machines Hsuan-Tien Lin (htlin, National Chengchi University, Taipei 116, Taiwan Abstract. Platt's probabilistic outputs for Support Vector Machines (Platt, 2000) has been popular for applications that require posterior class probabilities

  4. Output regulation problem for differentiable families of linear systems

    E-Print Network [OSTI]

    Politècnica de Catalunya, Universitat

    The output regulation problem arose as one of the main research topics in linear control theory in the 1970s regulation when modeled by a global or a local differentiable family. Partially supported by DGICYT n.PB97Output regulation problem for differentiable families of linear systems Albert Compta and Marta Pe

  5. Challenges in Predicting Power Output from Offshore Wind Farms

    E-Print Network [OSTI]

    Pryor, Sara C.

    Challenges in Predicting Power Output from Offshore Wind Farms R. J. Barthelmie1 and S. C. Pryor2 Abstract: Offshore wind energy is developing rapidly in Europe and the trend is towards large wind farms an offshore wind farm, accurate assessment of the wind resource/power output from the wind farm is a necessity

  6. A Counterexample to Additivity of Minimum Output Entropy

    E-Print Network [OSTI]

    M. B. Hastings

    2009-12-30T23:59:59.000Z

    We present a random construction of a pair of channels which gives, with non-zero probability for sufficiently large dimensions, a counterexample to the minimum output entropy conjecture. As shown by Shor, this implies a violation of the additivity conjecture for the classical capacity of quantum channels. The violation of the minimum output entropy conjecture is relatively small.

  7. Industrial Users

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > The Energy Materials Center at CornellOf SmartIndustrial Users The

  8. Industry @ ALS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > The Energy Materials Center at CornellOf SmartIndustrial Users

  9. Industrial Users

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC) EnvironmentalGyroSolé(tm)HydrogenRFP »summerlectures [ICO]default Sign InIndustrial

  10. Most efficient quantum thermoelectric at finite power output

    E-Print Network [OSTI]

    Robert S. Whitney

    2014-03-13T23:59:59.000Z

    Machines are only Carnot efficient if they are reversible, but then their power output is vanishingly small. Here we ask, what is the maximum efficiency of an irreversible device with finite power output? We use a nonlinear scattering theory to answer this question for thermoelectric quantum systems; heat engines or refrigerators consisting of nanostructures or molecules that exhibit a Peltier effect. We find that quantum mechanics places an upper bound on both power output, and on the efficiency at any finite power. The upper bound on efficiency equals Carnot efficiency at zero power output, but decays with increasing power output. It is intrinsically quantum (wavelength dependent), unlike Carnot efficiency. This maximum efficiency occurs when the system lets through all particles in a certain energy window, but none at other energies. A physical implementation of this is discussed, as is the suppression of efficiency by a phonon heat flow.

  11. Saving Output to a File (Using Codeblocks or Dev-C++) Saving Your Output to a File

    E-Print Network [OSTI]

    Sokol, Dina

    Saving Output to a File (Using Codeblocks or Dev-C++) Saving Your Output to a File To save | New | Source File. d. In the new window, right-click and select Paste. e. Then select "File | Save as" to save and name the file. i. In the window that pops up, the bottom fill-in box is labelled "Save as type

  12. Mechanical & Industrial Engineering

    E-Print Network [OSTI]

    Mountziaris, T. J.

    Mechanical & Industrial Engineering 1 Welcome MIE Industrial Advisory Board October 15, 2010 #12;Mechanical & Industrial Engineering 2 MIE Dorothy Adams Undergraduate/Graduate Secretary David Schmidt Associate Professor & Graduate Program Director #12;Mechanical & Industrial Engineering 3 MIE James Rinderle

  13. Industrial Decision Making 

    E-Print Network [OSTI]

    Elliott, R. N.; McKinney, V.; Shipley, A.

    2008-01-01T23:59:59.000Z

    and industrial investment decision-making. The paper will also address several important questions: • Why has industrial investment declined? • What is the outlook for industrial investment? • How can programs engage industry for future opportunities?...

  14. China's Pathways to Achieving 40percent 45percent Reduction in CO2 Emissions per Unit of GDP in 2020: Sectoral Outlook and Assessment of Savings Potential

    E-Print Network [OSTI]

    Zheng, Nina

    2013-01-01T23:59:59.000Z

    heater Residential CO2 Emissions (Mt CO2) 2020 ResidentialEnergy Industrial Sector CO2 Emissions (Mt CO2) IndustrialFigure 5. Power Sector CO2 Emissions by Scenario E3 Max Tech

  15. INDUSTRIAL ENGINEERING Industrial engineering is concerned

    E-Print Network [OSTI]

    INDUSTRIAL ENGINEERING Industrial engineering is concerned with looking at the "big picture" of systems that allow organizations and individuals to perform at their best. Industrial engineers bridge should be used and how they should be used. The focus of industrial engineering is on process improvement

  16. INDUSTRIAL ENGINEERING Industrial engineering is concerned

    E-Print Network [OSTI]

    INDUSTRIAL ENGINEERING Industrial engineering is concerned with looking at the "big picture" of systems that allow organizations and individuals to perform at their best. Industrial engineers bridge should be used and how they should be used. Industrial engineers design and run the factories and systems

  17. System for monitoring an industrial or biological process

    DOE Patents [OSTI]

    Gross, Kenneth C. (Argonne, IL); Wegerich, Stephan W. (Argonne, IL); Vilim, Rick B. (Argonne, IL); White, Andrew M. (Skokie, IL)

    1998-01-01T23:59:59.000Z

    A method and apparatus for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT.

  18. Correction method for in-air output ratio for output variations occurring with changes in backscattered radiation

    SciTech Connect (OSTI)

    Tajiri, Minoru; Tokiya, Yuji; Watanabe, Kazuhiro [Research Center Hospital for Charged Particle Therapy, National Institute of Radiological Sciences, 4-9-1, Anagawa, Inage-ku, Chiba 263-8555 (Japan); International University of Health and Welfare, 1-4-3, Mita, Minato-ku, Tokyo 108-8329 (Japan); Research Center Hospital for Charged Particle Therapy, National Institute of Radiological Sciences, 4-9-1, Anagawa, Inage-ku, Chiba 263-8555 (Japan)

    2012-02-15T23:59:59.000Z

    Purpose: The in-air output ratio (S{sub c}) for a rectangular field is usually obtained using an equivalent square field formula. However, it is well-known that S{sub c} obtained using an equivalent square field formula differs slightly from the measured S{sub c}. Though several correction methods have been suggested for the monitor-backscatter effect, the authors propose a more simple correction method for a rectangular field. Methods: For rectangular fields and equivalent square fields, the authors assumed that the output variation was the product of six output variations for each backscattering area at the top of the collimator jaws, and the correction factor was the ratio of the output variation for a rectangular field to the output variation for an equivalent square field. The output variation was measured by using a telescope measurement. Results: The differences between the measured and corrected S{sub c} ranged from -0.20% to 0.28% for symmetric rectangular fields by applying the correction factor to S{sub c} obtained using an equivalent square field formula. This correction method is also available for asymmetric rectangular fields. Conclusions: The authors propose a method to correct S{sub c} obtained using an equivalent square field formula, and a method to obtain the output variation for a field defined by collimator jaws.

  19. Community Climate System Model (CCSM) Experiments and Output Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The CCSM web makes the source code of various versions of the model freely available and provides access to experiments that have been run and the resulting output data.

  20. The Effect of Signal Quality on Six Cardiac Output Estimators

    E-Print Network [OSTI]

    Mark, Roger Greenwood

    The effect of signal quality on the accuracy of cardiac output (CO) estimation from arterial blood pressure (ABP) was evaluated using data from the MIMIC II database. Thermodilution CO (TCO) was the gold standard. A total ...

  1. Development of Regional Wind Resource and Wind Plant Output Datasets...

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

    50-47676 March 2010 Development of Regional Wind Resource and Wind Plant Output Datasets Final Subcontract Report 15 October 2007 - 15 March 2009 3TIER Seattle, Washington National...

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

    E-Print Network [OSTI]

    Washington at Seattle, University of

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

  3. Corticospinal Output to Hindlimb Muscles in the Primate

    E-Print Network [OSTI]

    Hudson, Heather M

    2011-05-31T23:59:59.000Z

    The overall goal of this study was to investigate the properties of corticospinal output to a wide range of hindlimb muscles in the primate and to map the representation of individual muscles in hindlimb motor cortex. ...

  4. Grid adaptation for functional outputs of compressible flow simulations

    E-Print Network [OSTI]

    Venditti, David Anthony, 1973-

    2002-01-01T23:59:59.000Z

    An error correction and grid adaptive method is presented for improving the accuracy of functional outputs of compressible flow simulations. The procedure is based on an adjoint formulation in which the estimated error in ...

  5. Process and Intermediate Calculations User AccessInputs Outputs

    E-Print Network [OSTI]

    Process and Intermediate Calculations User AccessInputs Outputs Fire Behavior & Probability STARFire System Flow Valuation Processing Temporal Schedules Smoke · Zones · Zone impact · Emissions Fire and compare Valuation (Structured Elicit Process) 1) Value Layers: · Point (housing, cultural trees, etc

  6. Emerging energy-efficient industrial technologies

    SciTech Connect (OSTI)

    Martin, N.; Worrell, E.; Ruth, M.; Price, L.; Elliott, R.N.; Shipley, A.M.; Thorne, J.

    2000-10-01T23:59:59.000Z

    U.S. industry consumes approximately 37 percent of the nation's energy to produce 24 percent of the nation's GDP. Increasingly, industry is confronted with the challenge of moving toward a cleaner, more sustainable path of production and consumption, while increasing global competitiveness. Technology will be essential for meeting these challenges. At some point, businesses are faced with investment in new capital stock. At this decision point, new and emerging technologies compete for capital investment alongside more established or mature technologies. Understanding the dynamics of the decision-making process is important to perceive what drives technology change and the overall effect on industrial energy use. The assessment of emerging energy-efficient industrial technologies can be useful for: (1) identifying R&D projects; (2) identifying potential technologies for market transformation activities; (3) providing common information on technologies to a broad audience of policy-makers; and (4) offering new insights into technology development and energy efficiency potentials. With the support of PG&E Co., NYSERDA, DOE, EPA, NEEA, and the Iowa Energy Center, staff from LBNL and ACEEE produced this assessment of emerging energy-efficient industrial technologies. The goal was to collect information on a broad array of potentially significant emerging energy-efficient industrial technologies and carefully characterize a sub-group of approximately 50 key technologies. Our use of the term ''emerging'' denotes technologies that are both pre-commercial but near commercialization, and technologies that have already entered the market but have less than 5 percent of current market share. We also have chosen technologies that are energy-efficient (i.e., use less energy than existing technologies and practices to produce the same product), and may have additional ''non-energy benefits.'' These benefits are as important (if not more important in many cases) in influencing the decision on whether to adopt an emerging technology. The technologies were characterized with respect to energy efficiency, economics, and environmental performance. The results demonstrate that the United States is not running out of technologies to improve energy efficiency and economic and environmental performance, and will not run out in the future. We show that many of the technologies have important non-energy benefits, ranging from reduced environmental impact to improved productivity and worker safety, and reduced capital costs.

  7. An Electricity-focused Economic Input-output Model: Life-cycle Assessment and Policy Implications of Future Electricity Generation Scenarios

    E-Print Network [OSTI]

    , and the different means of generating power. We build a flexible framework for creating new industry sectors, supply of Future Electricity Generation Scenarios Joe Marriott Submitted in Partial Fulfillment of the Requirements in the input- output model of the U.S. economy, the power generation sector is an excellent candidate

  8. China's Top-1000 Energy-Consuming Enterprises Program:Reducing Energy Consumption of the 1000 Largest Industrial Enterprises in China

    SciTech Connect (OSTI)

    Price, Lynn; Price, Lynn; Wang, Xuejun; Yun, Jiang

    2008-06-02T23:59:59.000Z

    In 2005, the Chinese government announced an ambitious goal of reducing energy consumption per unit of GDP by 20% between 2005 and 2010. One of the key initiatives for realizing this goal is the Top-1000 Energy-Consuming Enterprises program. The energy consumption of these 1000 enterprises accounted for 33% of national and 47% of industrial energy usage in 2004. Under the Top-1000 program, 2010 energy consumption targets were determined for each enterprise. The objective of this paper is to evaluate the program design and initial results, given limited information and data, in order to understand the possible implications of its success in terms of energy and carbon dioxide emissions reductions and to recommend future program modifications based on international experience with similar target-setting agreement programs. Even though the Top-1000 Program was designed and implemented rapidly, it appears that--depending upon the GDP growth rate--it could contribute to somewhere between approximately 10% and 25% of the savings required to support China's efforts to meet a 20% reduction in energy use per unit of GDP by 2010.

  9. Nonlinear quantum input-output analysis using Volterra series

    E-Print Network [OSTI]

    Jing Zhang; Yu-xi Liu; Re-Bing Wu; Kurt Jacobs; Sahin Kaya Ozdemir; Lan Yang; Tzyh-Jong Tarn; Franco Nori

    2014-08-04T23:59:59.000Z

    Quantum input-output theory plays a very important role for analyzing the dynamics of quantum systems, especially large-scale quantum networks. As an extension of the input-output formalism of Gardiner and Collet, we develop a new approach based on the quantum version of the Volterra series which can be used to analyze nonlinear quantum input-output dynamics. By this approach, we can ignore the internal dynamics of the quantum input-output system and represent the system dynamics by a series of kernel functions. This approach has the great advantage of modelling weak-nonlinear quantum networks. In our approach, the number of parameters, represented by the kernel functions, used to describe the input-output response of a weak-nonlinear quantum network, increases linearly with the scale of the quantum network, not exponentially as usual. Additionally, our approach can be used to formulate the quantum network with both nonlinear and nonconservative components, e.g., quantum amplifiers, which cannot be modelled by the existing methods, such as the Hudson-Parthasarathy model and the quantum transfer function model. We apply our general method to several examples, including Kerr cavities, optomechanical transducers, and a particular coherent feedback system with a nonlinear component and a quantum amplifier in the feedback loop. This approach provides a powerful way to the modelling and control of nonlinear quantum networks.

  10. The world of quantum noise and the fundamental output process

    E-Print Network [OSTI]

    V. P. Belavkin; O. Hirota; R. Hudson

    2005-10-04T23:59:59.000Z

    A stationary theory of quantum stochastic processes of second order is outlined. It includes KMS processes in wide sense like the equilibrium finite temperature quantum noise given by the Planck's spectral formula. It is shown that for each stationary noise there exists a natural output process output process which is identical to the noise in the infinite temperature limit, and flipping with the noise if the time is reversed at finite temperature. A canonical Hilbert space representation of the quantum noise and the fundamental output process is established and a decomposition of their spectra is found. A brief explanation of quantum stochastic integration with respect to the input-output processes is given using only correlation functions. This provides a mathematical foundation for linear stationary filtering transformations of quantum stochastic processes. It is proved that the colored quantum stationary noise and its time-reversed version can be obtained in the second order theory by a linear nonadapted filtering of the standard vacuum noise uniquely defined by the canonical creation and annihilation operators on the spectrum of the input-output pair.

  11. New Industrial Park Energy Supply for Economical Energy Conservation

    E-Print Network [OSTI]

    Scott, D.; Marda, R. S.; Hodson, J. S.; Williams, M.

    1982-01-01T23:59:59.000Z

    steam inlet conditions of 550 psig and 825?~. The gross output from this machine is 11.6 MW(ej. Process steam for the industrial users is rdmoved from the turbine cycle at the topping turbi~e exhaust. Approximately 840,000 lb/hr of prdcess steam...

  12. Optimal Scheduling of Industrial Combined Heat and Power Plants

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    -output relationships that are thermodynamically sound, such as the Willans line for steam turbines. Furthermore, we-switching for boilers and supplementary firing for gas turbines, and transitional behavior. Transitional behavior economies such as India and China. Many of the CHP plants are industrial CHP plants that supply steam

  13. Electric Utility Industry Update

    Broader source: Energy.gov [DOE]

    Presentation—given at the April 2012 Federal Utility Partnership Working Group (FUPWG) meeting—covers significant electric industry trends and industry priorities with federal customers.

  14. Uranium industry annual 1997

    SciTech Connect (OSTI)

    NONE

    1998-04-01T23:59:59.000Z

    This report provides statistical data on the U.S. uranium industry`s activities relating to uranium raw materials and uranium marketing.

  15. CASL Industry Council Meeting

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

    IndustryCouncil.shtml The new members that joined the Industry Council include NPP owneroperators with analysis capability: Tyrone Stevens of Exelon, and SMR vendors:...

  16. Microwave generated electrodeless lamp for producing bright output

    SciTech Connect (OSTI)

    Wood, Ch. H.; Ury, M. G.

    1985-03-26T23:59:59.000Z

    A microwave generated electrodeless light source for producing a bright output comprising a lamp structure including a microwave chamber and a plasma medium-containing lamp envelope having a maximum dimension which is substantially less than a wavelength disposed therein. To provide the desired radiation output the interior of the chamber is coated with a UV-reflective material and the chamber has an opening for allowing UV radiation to exit, which is covered with a metallic mesh. The chamber is arranged to be near-resonant at a single wavelength, and the lamp envelope has a fill including mercury at an operating pressure of 1-2 atmospheres, while a power density of at least 250-300 (watts/cm/sup 3/) is coupled to the envelope to result in a relatively high deep UV output at a relatively high brightness.

  17. Changing Trends in the Bulk Chemicals and Pulp and Paper Industries (released in AEO2005)

    Reports and Publications (EIA)

    2005-01-01T23:59:59.000Z

    Compared with the experience of the 1990s, rising energy prices in recent years have led to questions about expectations of growth in industrial output, particularly in energy-intensive industries. Given the higher price trends, a review of expected growth trends in selected industries was undertaken as part of the production of Annual Energy Outlook 2005 (AEO). In addition, projections for the industrial value of shipments, which were based on the Standard Industrial Classification (SIC) system in AEO2004, are based on the North American Industry Classification System (NAICS) in AEO2005. The change in industrial classification leads to lower historical growth rates for many industrial sectors. The impacts of these two changes are highlighted in this section for two of the largest energy-consuming industries in the U.S. industrial sector-bulk chemicals and pulp and paper.

  18. Self-consistent input-output formulation of quantum feedback

    SciTech Connect (OSTI)

    Yanagisawa, M. [Department of Engineering, The Australian National University, Canberra, ACT 0200 (Australia); Hope, J. J. [Department of Quantum Science, The Australian National University, Canberra, ACT 0200 (Australia)

    2010-12-15T23:59:59.000Z

    A simple method of analyzing quantum feedback circuits is presented. The classical analysis of feedback circuits can be generalized to apply to quantum systems by mapping the field operators of various outputs to other inputs via the standard input-output formalism. Unfortunately, this has led to unphysical results such as the violation of the Heisenberg uncertainty principle for in-loop fields. This paper shows that this general approach can be redeemed by ensuring a self-consistently Hermitian Hamiltonian. The calculations are based on a noncommutative calculus of operator derivatives. A full description of several examples of quantum linear and nonlinear feedback for optical systems is presented.

  19. Motor-output variability in a ballistic task

    E-Print Network [OSTI]

    Weeks, Douglas Lane

    1981-01-01T23:59:59.000Z

    MOTOR-OUTPUT VARIABILIT'f IN A BALLISTIC TASK A Thesis by DOUGLAS LANE WEEKS Submitted to the Graduate College of Texas ASM University in partsal fulfillment of the requirement for the degree of MASTER OF SCIENCE August 1981 Major Subject...: Physical Education MOTOR-OUTPUT VARIABILITY IN A BALLISTIC TASK A Thesis by DOUGLAS LANE WEEKS Approved as to style and content by: Chairman of Committee , ember C ee. yc ace Member )g p~ Head of Department August 1981 ADS!RACT !Notor...

  20. Making Industry Part of the Climate Solution

    SciTech Connect (OSTI)

    Lapsa, Melissa Voss [ORNL; Brown, Dr. Marilyn Ann [Georgia Institute of Technology; Jackson, Roderick K [ORNL; Cox, Matthew [Georgia Institute of Technology; Cortes, Rodrigo [Georgia Institute of Technology; Deitchman, Benjamin H [ORNL

    2011-06-01T23:59:59.000Z

    Improving the energy efficiency of industry is essential for maintaining the viability of domestic manufacturing, especially in a world economy where production is shifting to low-cost, less regulated developing countries. Numerous studies have shown the potential for significant cost-effective energy-savings in U.S. industries, but the realization of this potential is hindered by regulatory, information, workforce, and financial obstacles. This report evaluates seven federal policy options aimed at improving the energy efficiency of industry, grounded in an understanding of industrial decision-making and the barriers to efficiency improvements. Detailed analysis employs the Georgia Institute of Technology's version of the National Energy Modeling System and spreadsheet calculations, generating a series of benefit/cost metrics spanning private and public costs and energy bill savings, as well as air pollution benefits and the social cost of carbon. Two of the policies would address regulatory hurdles (Output-Based Emissions Standards and a federal Energy Portfolio Standard with Combined Heat and Power); three would help to fill information gaps and workforce training needs (the Superior Energy Performance program, Implementation Support Services, and a Small Firm Energy Management program); and two would tackle financial barriers (Tax Lien Financing and Energy-Efficient Industrial Motor Rebates). The social benefit-cost ratios of these policies appear to be highly favorable based on a range of plausible assumptions. Each of the seven policy options has an appropriate federal role, broad applicability across industries, utilizes readily available technologies, and all are administratively feasible.

  1. Output Growth and Its Volatility: The Gold Standard through the Great Moderation

    E-Print Network [OSTI]

    Ahmad, Sajjad

    of real GDP growth and some form of a generalized autoregressive conditional heteroskedasticity (GARCH GARCH or exponential GARCH (EGARCH) process, capturing the movement in volatility. The neglect persistence in the conditional volatility or integrated GARCH (IGARCH). That is, typically all persistence

  2. INTRODUCTION The power industry is at the dawn of a new era

    E-Print Network [OSTI]

    Shihada, Basem

    that there may be almost 81 percent drop in output power over the span of just five minutes in a solar photoINTRODUCTION The power industry is at the dawn of a new era of transformation, triggered witnessed an increasing focus on the next gener- ation power grid from both industry and research. The goals

  3. A 350 MHz, 200 kW CW, Multiple Beam Inductive Output Tube - Final Report

    SciTech Connect (OSTI)

    R.Lawrece Ives; George Collins; David Marsden Michael Read; Edward Eisen; Takuchi Kamura, Philipp Borchard

    2012-11-28T23:59:59.000Z

    This program developed a 200 kW CW, 350 MHz, multiple beam inductive output tube (MBIOT) for driving accelerator cavities. The MBIOT operates at 30 kV with a gain of 23 dB. The estimated efficiency is 70%. The device uses seven electron beams, each transmitting 1.4 A of current. The tube is approximately six feet long and weighs approximately 400 lbs. The prototype device will be evaluated as a potential RF source for the Advanced Photon Source at Argonne National Laboratory (ANL). Because of issues related to delivery of the electron guns, it was not possible to complete assembly and test of the MBIOT during the Phase II program. The device is being completed with support from Calabazas Creek Research, Inc., Communications & Power Industries, LLC. and the Naval Surface Weapons Center (NSWC) in Dahlgren, VA. The MBIOT will be initially tested at NSWC before delivery to ANL. The testing at NSWC is scheduled for February 2013.

  4. Industry Analysis February 2013

    E-Print Network [OSTI]

    Abolmaesumi, Purang

    technology ­ Clean tech/ clean technology #12;7 Industry Studies · IbisWorld ­ U.S. and global industry-Industries · Biodiesel ­ Biofuel ­ Alternate fuels ­ Green fuels ­ Renewable fuels/energy ­ Green energy ­ Green Canada, Census, Industry Canada, the OECD, European Union, IMF, World Bank, UN . . . Never pay for stats

  5. INDUSTRIAL ENGINEERING GRADUATE PROGRAMS

    E-Print Network [OSTI]

    Gelfond, Michael

    : Occupational biomechanics, work physiology, industrial ergonomics, environmental hygiene, cognitive engineeringINDUSTRIAL ENGINEERING GRADUATE PROGRAMS The Master of Science in Industrial Engineering (M Systems and Engineering (M.S.M.S.E.), the Doctor of Philosophy in Industrial Engineering, and the Doctor

  6. Control of fuel cell power output Federico Zenith, Sigurd Skogestad *

    E-Print Network [OSTI]

    Skogestad, Sigurd

    Control of fuel cell power output Federico Zenith, Sigurd Skogestad * Department of Chemical A simplified dynamic model for fuel cells is developed, based on the concept of instantaneous characteristic, which is the set of values of current and voltage that a fuel cell can reach instantaneously

  7. On Optimal Distributed Output-Feedback Control over Acyclic Graphs

    E-Print Network [OSTI]

    Gattami, Ather

    2012-01-01T23:59:59.000Z

    In this paper, we consider the problem of distributed optimal control of linear dynamical systems with a quadratic cost criterion. We study the case of output feedback control for two interconnected dynamical systems, and show that the linear optimal solution can be obtained from a combination of two uncoupled Riccati equations and two coupled Riccati equations.

  8. TRICOLOR LIGHT EMITTING DIODE DOT MATRIX DISPLAY SYSTEM WITHAUDIO OUTPUT

    E-Print Network [OSTI]

    Pang, Grantham

    1 TRICOLOR LIGHT EMITTING DIODE DOT MATRIX DISPLAY SYSTEM WITHAUDIO OUTPUT Grantham Pang, Chi emitting diodes; tricolor display; audio communication. I. Introduction This paper relates to a tricolor broadcasting through the visible light rays transmitted by the display panel or assembly. Keywords: light

  9. The effects of output transformers on distortion in audio amplifiers

    E-Print Network [OSTI]

    Lanier, Ross Edwin

    1949-01-01T23:59:59.000Z

    Introduction ~. . . . . . . . , . . . . . . ~. . . . . 7 Frequency Discrimination. . . . . . . . . . . . . . . . 9 Harmonic Distortion. ~ ~. . . . ~ 21 Distortion by the Intermodulationmethod. . . . . . . . 47 Comparison of Harmonic and Intermodulation... current in the primary as a function of frequency . 19 Output voltage of transformer 3 without direct current in the primary as a function of frequency 20 Block diagram for measuring distortion by the harmonic method 26 Per cent harmonic distortion...

  10. ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE CO

    E-Print Network [OSTI]

    Groppi, Christopher

    Initialization Program - ADIOS INITB Appendix 2 Test Program - ADIOS TEST Appendix 3 AND9513 Utilization Appendix HI-506A. Multiplexer F. Sprague UHP -507 Relay Driver G. Teledyne Solid-State Relays H. Advanced bus driver, a 4-bit relay driver, or two solid-state relays. Three of the digital output bits can

  11. Convergent relaxations of polynomial matrix inequalities and static output feedback

    E-Print Network [OSTI]

    Henrion, Didier

    (LMI) relaxations to solve non-convex polynomial matrix in- equality (PMI) optimization problems minimizers that satisfy the PMI. The approach is successfully applied to PMIs arising from static output- mulated as polynomial matrix inequality (PMI) optimization problems in the controller parameters

  12. Observer-Controllers for Output Regulation: the Internal Model Principle Revisited

    E-Print Network [OSTI]

    Pao, Lucy Y.

    Observer-Controllers for Output Regulation: the Internal Model Principle Revisited Jason H. Laks rejection;tracking;model predictive control;output feedback control 1 Introduction Output regulation, the design of an output regulating observer-controller is less clear. This latter approach is based

  13. On Hastings' counterexamples to the minimum output entropy additivity conjecture

    E-Print Network [OSTI]

    Fernando G. S. L. Brandao; Michal Horodecki

    2009-07-19T23:59:59.000Z

    Hastings recently reported a randomized construction of channels violating the minimum output entropy additivity conjecture. Here we revisit his argument, presenting a simplified proof. In particular, we do not resort to the exact probability distribution of the Schmidt coefficients of a random bipartite pure state, as in the original proof, but rather derive the necessary large deviation bounds by a concentration of measure argument. Furthermore, we prove non-additivity for the overwhelming majority of channels consisting of a Haar random isometry followed by partial trace over the environment, for an environment dimension much bigger than the output dimension. This makes Hastings' original reasoning clearer and extends the class of channels for which additivity can be shown to be violated.

  14. Optical device with conical input and output prism faces

    DOE Patents [OSTI]

    Brunsden, Barry S. (Chicago, IL)

    1981-01-01T23:59:59.000Z

    A device for radially translating radiation in which a right circular cylinder is provided at each end thereof with conical prism faces. The faces are oppositely extending and the device may be severed in the middle and separated to allow access to the central part of the beam. Radiation entering the input end of the device is radially translated such that radiation entering the input end at the perimeter is concentrated toward the output central axis and radiation at the input central axis is dispersed toward the output perimeter. Devices are disclosed for compressing beam energy to enhance drilling techniques, for beam manipulation of optical spatial frequencies in the Fourier plane and for simplification of dark field and color contrast microscopy. Both refracting and reflecting devices are disclosed.

  15. An Advanced simulation Code for Modeling Inductive Output Tubes

    SciTech Connect (OSTI)

    Thuc Bui; R. Lawrence Ives

    2012-04-27T23:59:59.000Z

    During the Phase I program, CCR completed several major building blocks for a 3D large signal, inductive output tube (IOT) code using modern computer language and programming techniques. These included a 3D, Helmholtz, time-harmonic, field solver with a fully functional graphical user interface (GUI), automeshing and adaptivity. Other building blocks included the improved electrostatic Poisson solver with temporal boundary conditions to provide temporal fields for the time-stepping particle pusher as well as the self electric field caused by time-varying space charge. The magnetostatic field solver was also updated to solve for the self magnetic field caused by time changing current density in the output cavity gap. The goal function to optimize an IOT cavity was also formulated, and the optimization methodologies were investigated.

  16. Simple SPICE model for comparison of CMOS output driver circuits

    E-Print Network [OSTI]

    Hermann, John Karl

    1993-01-01T23:59:59.000Z

    to monitor the ground nodes of output driver circuits for noise. Both relative performance and noise levels are generated through the simulations. A test device was built to confirm that the model was effective in speed and noise comparisons. Values were... on CMOS technologies. Journal model is IEEE 'I?ansactions on Automatic Control. A. Literature Survey Research has been done in the past concerning noise generated by digital logic de- vices. In particular, Advanced CMOS Logic (ACL) integrated circuits...

  17. Input-output multiplier distributions from probabilistic production paths

    SciTech Connect (OSTI)

    Konecny, R.T.

    1987-01-01T23:59:59.000Z

    In the standard Leontief input-output model, a single dominant technology is assumed in the production of a particular commodity. However, in the real world, quite similar commodities are produced by firms with vastly different technologies. In addressing this limitation, the Probabilistic Production Path model (PPP) is used to investigate both the method of production and identity of the producer. An important feature of the PPP model is the consideration of the effects that heterogeneous technologies and dissimilar trade patterns have on the properties of the distribution of input-output multipliers. The derivation of the distribution of output multipliers is generalized for discrete probabilities based on market shares. Due to the complexity of the generalized solution, a simulation model is used to approximate the multiplier distribution. Results of the model show that the distributional properties of the multipliers are unpredictable, with the majority of the distributions being multimodal. Typically, the mean of the multipliers lies in a trough between two modes. Multimodal multiplier distributions were found to have a tighter symmetric interval than the corresponding standard normal confidence interval. Therefore, the use of the normal confidence interval appears to be sufficient, though overstated, for the construction of confidence intervals in the PPP model.

  18. Development of output user interface software to support analysis

    SciTech Connect (OSTI)

    Wahanani, Nursinta Adi, E-mail: sintaadi@batan.go.id; Natsir, Khairina, E-mail: sintaadi@batan.go.id; Hartini, Entin, E-mail: sintaadi@batan.go.id [Center for Development of Nuclear Informatics - National Nuclear Energy Agency, PUSPIPTEK, Serpong, Tangerang, Banten (Indonesia)

    2014-09-30T23:59:59.000Z

    Data processing software packages such as VSOP and MCNPX are softwares that has been scientifically proven and complete. The result of VSOP and MCNPX are huge and complex text files. In the analyze process, user need additional processing like Microsoft Excel to show informative result. This research develop an user interface software for output of VSOP and MCNPX. VSOP program output is used to support neutronic analysis and MCNPX program output is used to support burn-up analysis. Software development using iterative development methods which allow for revision and addition of features according to user needs. Processing time with this software 500 times faster than with conventional methods using Microsoft Excel. PYTHON is used as a programming language, because Python is available for all major operating systems: Windows, Linux/Unix, OS/2, Mac, Amiga, among others. Values that support neutronic analysis are k-eff, burn-up and mass Pu{sup 239} and Pu{sup 241}. Burn-up analysis used the mass inventory values of actinide (Thorium, Plutonium, Neptunium and Uranium). Values are visualized in graphical shape to support analysis.

  19. Ring laser having an output at a single frequency

    DOE Patents [OSTI]

    Hackell, Lloyd A. (Livermore, CA)

    1991-01-01T23:59:59.000Z

    A ring laser is disclosed that produces a single frequency of laser radiation in either the pulsed mode of operation or the continuous waveform (cw) mode of operation. The laser comprises a ring laser in a bowtie configuration, a birefringent gain material such as Nd:YLF, an improved optical diode that supports laser oscillation having a desired direction of travel and linear polarization, and a Q-switch. An output coupler (mirror) having a high reflectivity, such as 94%, is disclosed. Also disclosed is a self-seeded method of operation in which the laser can provide a pulse or a series of pulses of high power laser radiation at a consistent single frequency with a high degree of amplitude stability and temporal stability. In operation, the laser is operated in continuous waveform (cw) at a low power output with the Q-switch introducing a loss into the resonating cavity. Pumping is continued at a high level, causing the gain material to store energy. When a pulse is desired, the Q-switch is actuated to substantially reduce the losses so that a pulse can build up based on the low level cw oscillation. The pulse quickly builds, using the stored energy in the gain medium to provide a high power output pulse. The process may be repeated to provide a series of high power pulses of a consistent single frequency.

  20. The Industrial Electrification Program

    E-Print Network [OSTI]

    Harry, I. L.

    1982-01-01T23:59:59.000Z

    EPRI's role as the research organization of the electric power industry, in coordination with potential user industries, is to 1) define the viability of candidate electrification technologies by monitoring the state-of-the-art and continuously...

  1. Electrotechnologies in Process Industries

    E-Print Network [OSTI]

    Amarnath, K. R.

    The Industrial Program at the Electric Power Research Institute (EPRI) promotes the efficient use of electricity to improve the competitive position of the American industry. Electrotechnologies that improve productivity, improve quality...

  2. and Industrial Engineering

    E-Print Network [OSTI]

    Mountziaris, T. J.

    technologicalandlogisticssystemsbygathering, structuring, and managing information. Indus- trial engineers apply their knowledge not only45 Mechanical and Industrial Engineering 220 Engineering Lab Degrees: Bachelor of Science in Mechanical Engineering Bachelor of Science in Industrial Engineering Contact: James R. Rinderle

  3. Demographics and industry returns

    E-Print Network [OSTI]

    Pollet, Joshua A.; DellaVigna, Stefano

    2007-01-01T23:59:59.000Z

    Industry category Child care Children’s books Children’s clothing Toysindustry Child care Children’s books Children’s clothing ToysIndustries are associated with high demand by children (child care, toys) and

  4. INDUSTRIAL ENGINEER APPRENTICE OPPORTUNITY

    E-Print Network [OSTI]

    Pohl, Karsten

    INDUSTRIAL ENGINEER APPRENTICE OPPORTUNITY SUMMER 2013 Industrial Engineering COOP Student needed-Fri, for summer 2013. Student must be enrolled in BS Engineering program. (Preferably completed 2-3 yrs

  5. Industry Analysis October 2010

    E-Print Network [OSTI]

    Abolmaesumi, Purang

    Different regulations for some industries in Canada, the U.S. and Europe ie. telecommunications, energy of energy, materials, industrial waste, byproducts #12;Contact Constance Adamson Stauffer Library adamsonc

  6. Geothermal Industry Partnership Opportunities

    Broader source: Energy.gov [DOE]

    Here you'll find links to information about partnership opportunities and programs for the geothermal industry.

  7. Mechanical & Industrial Engineering

    E-Print Network [OSTI]

    Mountziaris, T. J.

    Mechanical & Industrial Engineering Mario A. Rotea Professor and Department Head #12;2Mechanical & Industrial Engineering Outline · Undergraduate Degree Programs · Graduate Degree Programs · The Faculty · The Research · Summary #12;3Mechanical & Industrial Engineering Undergraduate Programs ­ BSME & BSIE 0 20 40 60

  8. Industrial Dojo Program Fosters Industrial Internet Development...

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

    share on LinkedIn (Opens in new window) Click to share on Tumblr (Opens in new window) GE Launches Cloud Foundry 'Industrial Dojo,' Contributes to Open Source to Foster Continued...

  9. LANSCE | Lujan Center | Industrial Users

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

    Industrial Users The Lujan Neutron Scattering Center offers a diverse set of capabilities and instruments for industrial projects. Industrial users are invited to contact Fredrik...

  10. Uranium industry annual 1998

    SciTech Connect (OSTI)

    NONE

    1999-04-22T23:59:59.000Z

    The Uranium Industry Annual 1998 (UIA 1998) provides current statistical data on the US uranium industry`s activities relating to uranium raw materials and uranium marketing. It contains data for the period 1989 through 2008 as collected on the Form EIA-858, ``Uranium Industry Annual Survey.`` Data provides a comprehensive statistical characterization of the industry`s activities for the survey year and also include some information about industry`s plans and commitments for the near-term future. Data on uranium raw materials activities for 1989 through 1998, including exploration activities and expenditures, EIA-estimated reserves, mine production of uranium, production of uranium concentrate, and industry employment, are presented in Chapter 1. Data on uranium marketing activities for 1994 through 2008, including purchases of uranium and enrichment services, enrichment feed deliveries, uranium fuel assemblies, filled and unfilled market requirements, and uranium inventories, are shown in Chapter 2. The methodology used in the 1998 survey, including data edit and analysis, is described in Appendix A. The methodologies for estimation of resources and reserves are described in Appendix B. A list of respondents to the ``Uranium Industry Annual Survey`` is provided in Appendix C. The Form EIA-858 ``Uranium Industry Annual Survey`` is shown in Appendix D. For the readers convenience, metric versions of selected tables from Chapters 1 and 2 are presented in Appendix E along with the standard conversion factors used. A glossary of technical terms is at the end of the report. 24 figs., 56 tabs.

  11. Uranium industry annual 1994

    SciTech Connect (OSTI)

    NONE

    1995-07-05T23:59:59.000Z

    The Uranium Industry Annual 1994 (UIA 1994) provides current statistical data on the US uranium industry`s activities relating to uranium raw materials and uranium marketing during that survey year. The UIA 1994 is prepared for use by the Congress, Federal and State agencies, the uranium and nuclear electric utility industries, and the public. It contains data for the 10-year period 1985 through 1994 as collected on the Form EIA-858, ``Uranium Industry Annual Survey.`` Data collected on the ``Uranium Industry Annual Survey`` (UIAS) provide a comprehensive statistical characterization of the industry`s activities for the survey year and also include some information about industry`s plans and commitments for the near-term future. Where aggregate data are presented in the UIA 1994, care has been taken to protect the confidentiality of company-specific information while still conveying accurate and complete statistical data. A feature article, ``Comparison of Uranium Mill Tailings Reclamation in the United States and Canada,`` is included in the UIA 1994. Data on uranium raw materials activities including exploration activities and expenditures, EIA-estimated resources and reserves, mine production of uranium, production of uranium concentrate, and industry employment are presented in Chapter 1. Data on uranium marketing activities, including purchases of uranium and enrichment services, and uranium inventories, enrichment feed deliveries (actual and projected), and unfilled market requirements are shown in Chapter 2.

  12. INDUSTRIAL&SYSTEMS Industrial and Systems engineers use engineering

    E-Print Network [OSTI]

    Rohs, Remo

    78 INDUSTRIAL&SYSTEMS Industrial and Systems engineers use engineering and business principles companies compete in today's global marketplace. The Industrial and Systems engineer's task is to take of industries including consulting, technology development, software, supply chain manufacturing, engineering

  13. Method and system for managing an electrical output of a turbogenerator

    DOE Patents [OSTI]

    Stahlhut, Ronnie Dean (Bettendorf, IA); Vuk, Carl Thomas (Denver, IA)

    2009-06-02T23:59:59.000Z

    The system and method manages an electrical output of a turbogenerator in accordance with multiple modes. In a first mode, a direct current (DC) bus receives power from a turbogenerator output via a rectifier where turbogenerator revolutions per unit time (e.g., revolutions per minute (RPM)) or an electrical output level of a turbogenerator output meet or exceed a minimum threshold. In a second mode, if the turbogenerator revolutions per unit time or electrical output level of a turbogenerator output are less than the minimum threshold, the electric drive motor or a generator mechanically powered by the engine provides electrical energy to the direct current bus.

  14. Method and system for managing an electrical output of a turbogenerator

    DOE Patents [OSTI]

    Stahlhut, Ronnie Dean (Bettendorf, IA); Vuk, Carl Thomas (Denver, IA)

    2010-08-24T23:59:59.000Z

    The system and method manages an electrical output of a turbogenerator in accordance with multiple modes. In a first mode, a direct current (DC) bus receives power from a turbogenerator output via a rectifier where turbogenerator revolutions per unit time (e.g., revolutions per minute (RPM)) or an electrical output level of a turbogenerator output meet or exceed a minimum threshold. In a second mode, if the turbogenerator revolutions per unit time or electrical output level of a turbogenerator output are less than the minimum threshold, the electric drive motor or a generator mechanically powered by the engine provides electrical energy to the direct current bus.

  15. Energy Efficiency in the Pulp and Paper Industry: Simulation of Steam Challenge and CHP Incentives with ITEMS

    E-Print Network [OSTI]

    Roop, J. M.

    in manufacturing as reported in the 1991 Manufacturing Energy Consumption Survey (MECS) (6). For simulation of the model, the major drivers are industry output and fuel prices (the latter may be taken from any of a number of publications; the simulations... for this paper use [7]). Output forecasts are derived from the technical appendix to the same source. The MECS data are used to calibrate the end uses for each industry and the fuel types for each industry. This is done with varying success. Food processing...

  16. Spatial Interference Mitigation for Multiple Input Multiple Output Ad Hoc Networks: MISO Gains

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Spatial Interference Mitigation for Multiple Input Multiple Output Ad Hoc Networks: MISO Gains beamforming for a multiple input single output (MISO) ad hoc network to increase the density of successful

  17. Design of a 3.3 V analog video line driver with controlled output impedance

    E-Print Network [OSTI]

    Ramachandran, Narayan Prasad

    2004-09-30T23:59:59.000Z

    impedance of the line. The main requirements for design are high output swing, high linearity, matched impedance to the line and power efficiency. These requirements are addressed by a class AB amplifier whose output impedance can be controlled through...

  18. Predicting the Power Output of Distributed Renewable Energy Resources within a Broad Geographical Region

    E-Print Network [OSTI]

    Chalkiadakis, Georgios

    Predicting the Power Output of Distributed Renewable Energy Resources within a Broad Geographical potentially dis- tributed renewable energy resources (su years, estimating the power output of in- herently intermittent and potentially distributed renewable

  19. Industrial Retrofits are Possible

    E-Print Network [OSTI]

    Stobart, E. W.

    . In April of 1987, the provincial government initiated a program to assist industrial energy users to reduce their energy usage. This program was designed to concentrate on an in-depth analysis of the complete operations of industrial plants... with the analyses being performed by specialist, private sector, engineering consultants. The program is in 3 phases providing an Ontario industrial plant with an Energy Analysis, a Feasibility Analysis Grant and a Project Engineering Design Grant...

  20. Sector trends and driving forces of global energy use and greenhouse gas emissions: focus in industry and buildings

    SciTech Connect (OSTI)

    Price, Lynn; Worrell, Ernst; Khrushch, Marta

    1999-09-01T23:59:59.000Z

    Disaggregation of sectoral energy use and greenhouse gas emissions trends reveals striking differences between sectors and regions of the world. Understanding key driving forces in the energy end-use sectors provides insights for development of projections of future greenhouse gas emissions. This report examines global and regional historical trends in energy use and carbon emissions in the industrial, buildings, transport, and agriculture sectors, with a more detailed focus on industry and buildings. Activity and economic drivers as well as trends in energy and carbon intensity are evaluated. The authors show that macro-economic indicators, such as GDP, are insufficient for comprehending trends and driving forces at the sectoral level. These indicators need to be supplemented with sector-specific information for a more complete understanding of future energy use and greenhouse gas emissions.

  1. Presentations for Industry

    Broader source: Energy.gov [DOE]

    Learn energy-saving strategies from leading manufacturing companies and energy experts. The presentations are organized below by topic area. In addition, industrial energy managers, utilities, and...

  2. About Industrial Distributed Energy

    Broader source: Energy.gov [DOE]

    The Advanced Manufacturing Office's (AMO's) Industrial Distributed Energy activities build on the success of predecessor DOE programs on distributed energy and combined heat and power (CHP) while...

  3. Industrial Demand Module

    Gasoline and Diesel Fuel Update (EIA)

    Boiler, Steam, and Cogeneration (BSC) Component. The BSC Component satisfies the steam demand from the PA and BLD Components. In some industries, the PA Component produces...

  4. Soft-Input Soft-Output King Decoder for Coded MIMO Wireless Communications

    E-Print Network [OSTI]

    Soft-Input Soft-Output King Decoder for Coded MIMO Wireless Communications Giuseppe PAPA, Domenico,{domenico.ciuonzo,gianmarco.romano,pierluigi.salvorossi}@unina2.it Abstract--This paper presents a Soft-Input Soft-Output (SISO) version of the King Decoder (KD for Multiple-Input Multiple-Output (MIMO) communication systems. More specifically, four versions of the KD

  5. A Framework to Determine the Probability Density Function for the Output Power of Wind Farms

    E-Print Network [OSTI]

    Liberzon, Daniel

    A Framework to Determine the Probability Density Function for the Output Power of Wind Farms Sairaj to the power output of a wind farm while factoring in the availability of the wind turbines in the farm availability model for the wind turbines, we propose a method to determine the wind-farm power output pdf

  6. The electrical and lumen output characteristics of an RF lamp

    SciTech Connect (OSTI)

    Alexandrovich, B.M.; Godyak, V.A.; Piejak, R.B. [Osram Sylvania Inc., Beverly, MA (United States)

    1996-12-31T23:59:59.000Z

    Low pressure rf discharges have been studied for over a century. Their first practical application for lighting was proposed by Tesla in 1891. Since then hundreds of patents have been published attempting to implement rf lighting. However, progress in understanding rf discharge phenomena (mostly driven by plasma processing needs) and dramatic improvement in the performance/cost ratio of rf power sources have recently opened the door for development of rf light sources. Today commercial inductively coupled electrodeless lamps are offered by Matsuhita, Philips and GE. In this work the authors present measurements of the electrical characteristics and lumen output from a 2.65 MHz driven inductively coupled light source. Measurements were made on a spherical lamp of 3.125 inch diameter with a re-entrant cavity that houses a cylindrical ferrite core around which is wrapped the primary coil.

  7. Growing Hawaii's agriculture industry,

    E-Print Network [OSTI]

    Program Overview Growing Hawaii's agriculture industry, one business at a time Website: http-3547 agincubator@ctahr.hawaii.edu Grow Your Business If you are looking to start an agriculture-related business with our program · Positively impact the agriculture industry in Hawaii with their success

  8. Geothermal industry assessment

    SciTech Connect (OSTI)

    Not Available

    1980-07-01T23:59:59.000Z

    An assessment of the geothermal industry is presented, focusing on industry structure, corporate activities and strategies, and detailed analysis of the technological, economic, financial, and institutional issues important to government policy formulation. The study is based principally on confidential interviews with executives of 75 companies active in the field. (MHR)

  9. Industrial Optimization Compact Course

    E-Print Network [OSTI]

    Kirches, Christian

    Industrial Optimization Compact Course and Challenge Workshop Optimization plays a crucial role of the processes are typically nonlinear and dyna- mic. Thus, complex dynamic optimization or optimal control in industrial optimization. February 17­20, 2014 ·9.00­17.00 IWR ·Im Neuenheimer Feld 368 ·69120 Heidelberg www

  10. Uranium industry annual 1996

    SciTech Connect (OSTI)

    NONE

    1997-04-01T23:59:59.000Z

    The Uranium Industry Annual 1996 (UIA 1996) provides current statistical data on the US uranium industry`s activities relating to uranium raw materials and uranium marketing. The UIA 1996 is prepared for use by the Congress, Federal and State agencies, the uranium and nuclear electric utility industries, and the public. Data on uranium raw materials activities for 1987 through 1996 including exploration activities and expenditures, EIA-estimated reserves, mine production of uranium, production of uranium concentrate, and industry employment are presented in Chapter 1. Data on uranium marketing activities for 1994 through 2006, including purchases of uranium and enrichment services, enrichment feed deliveries, uranium fuel assemblies, filled and unfilled market requirements, uranium imports and exports, and uranium inventories are shown in Chapter 2. A feature article, The Role of Thorium in Nuclear Energy, is included. 24 figs., 56 tabs.

  11. INDUSTRIAL&SYSTEMS Industrial and Systems engineers use

    E-Print Network [OSTI]

    Rohs, Remo

    78 INDUSTRIAL&SYSTEMS Industrial and Systems engineers use engineering and business principles companies compete in today's global marketplace. The Industrial and Systems engineer's task is to take · Industrial and Systems Engineering Bachelor of Science 128 units · Industrial and Systems Engineering

  12. Update to industrial drivers in the AEO2015 as a result of new input-output data

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I'26,282.1 26,672.1MonthFeet) Year Jan Feb Mar AprUpdate

  13. Uranium industry annual 1995

    SciTech Connect (OSTI)

    NONE

    1996-05-01T23:59:59.000Z

    The Uranium Industry Annual 1995 (UIA 1995) provides current statistical data on the U.S. uranium industry`s activities relating to uranium raw materials and uranium marketing. The UIA 1995 is prepared for use by the Congress, Federal and State agencies, the uranium and nuclear electric utility industries, and the public. It contains data for the period 1986 through 2005 as collected on the Form EIA-858, ``Uranium Industry Annual Survey``. Data collected on the ``Uranium Industry Annual Survey`` provide a comprehensive statistical characterization of the industry`s plans and commitments for the near-term future. Where aggregate data are presented in the UIA 1995, care has been taken to protect the confidentiality of company-specific information while still conveying accurate and complete statistical data. Data on uranium raw materials activities for 1986 through 1995 including exploration activities and expenditures, EIA-estimated reserves, mine production of uranium, production of uranium concentrate, and industry employment are presented in Chapter 1. Data on uranium marketing activities for 1994 through 2005, including purchases of uranium and enrichment services, enrichment feed deliveries, uranium fuel assemblies, filled and unfilled market requirements, uranium imports and exports, and uranium inventories are shown in Chapter 2. The methodology used in the 1995 survey, including data edit and analysis, is described in Appendix A. The methodologies for estimation of resources and reserves are described in Appendix B. A list of respondents to the ``Uranium Industry Annual Survey`` is provided in Appendix C. For the reader`s convenience, metric versions of selected tables from Chapters 1 and 2 are presented in Appendix D along with the standard conversion factors used. A glossary of technical terms is at the end of the report. 14 figs., 56 tabs.

  14. Industrial process surveillance system

    DOE Patents [OSTI]

    Gross, K.C.; Wegerich, S.W.; Singer, R.M.; Mott, J.E.

    1998-06-09T23:59:59.000Z

    A system and method are disclosed for monitoring an industrial process and/or industrial data source. The system includes generating time varying data from industrial data sources, processing the data to obtain time correlation of the data, determining the range of data, determining learned states of normal operation and using these states to generate expected values, comparing the expected values to current actual values to identify a current state of the process closest to a learned, normal state; generating a set of modeled data, and processing the modeled data to identify a data pattern and generating an alarm upon detecting a deviation from normalcy. 96 figs.

  15. Fail safe controllable output improved version of the Electromechanical battery

    DOE Patents [OSTI]

    Post, Richard F. (Walnut Creek, CA)

    1999-01-01T23:59:59.000Z

    Mechanical means are provided to control the voltages induced in the windings of a generator/motor. In one embodiment, a lever is used to withdraw or insert the entire stator windings from the cavity where the rotating field exists. In another embodiment, voltage control and/or switching off of the output is achievable with a variable-coupling generator/motor. A stator is made up of two concentric layers of windings, with a larger number of turns on the inner layer of windings than the outer layer of windings. The windings are to be connected in series electrically, that is, their voltages add vectorially. The mechanical arrangement is such that one or both of the windings can be rotated with respect to the other winding about their common central axis. Another improved design for the stator assembly of electromechanical batteries provides knife switch contacts that are in electrical contact with the stator windings. The operation of this embodiment depends on the fact that an abnormally large torque will be exerted on the stator structure during any short-circuit condition.

  16. Fail safe controllable output improved version of the electromechanical battery

    DOE Patents [OSTI]

    Post, R.F.

    1999-01-19T23:59:59.000Z

    Mechanical means are provided to control the voltages induced in the windings of a generator/motor. In one embodiment, a lever is used to withdraw or insert the entire stator windings from the cavity where the rotating field exists. In another embodiment, voltage control and/or switching off of the output is achievable with a variable-coupling generator/motor. A stator is made up of two concentric layers of windings, with a larger number of turns on the inner layer of windings than the outer layer of windings. The windings are to be connected in series electrically, that is, their voltages add vectorially. The mechanical arrangement is such that one or both of the windings can be rotated with respect to the other winding about their common central axis. Another improved design for the stator assembly of electromechanical batteries provides knife switch contacts that are in electrical contact with the stator windings. The operation of this embodiment depends on the fact that an abnormally large torque will be exerted on the stator structure during any short-circuit condition. 4 figs.

  17. SARAH 3.2: Dirac Gauginos, UFO output, and more

    E-Print Network [OSTI]

    Florian Staub

    2013-02-12T23:59:59.000Z

    SARAH is a Mathematica package optimized for the fast, efficient and precise study of supersymmetric models beyond the MSSM: a new model can be defined in a short form and all vertices are derived. This allows SARAH to create model files for FeynArts/FormCalc, CalcHep/CompHep and WHIZARD/OMEGA. The newest version of SARAH now provides the possibility to create model files in the UFO format which is supported by MadGraph 5, MadAnalysis, GoSam, and soon by Herwig++. Furthermore, SARAH also calculates the mass matrices, RGEs and one-loop corrections to the mass spectrum. This information is used to write source code for SPheno in order to create a precision spectrum generator for the given model. This spectrum-generator-generator functionality as well as the output of WHIZARD and CalcHep model files have seen further improvement in this version. Also models including Dirac Gauginos are supported with the new version of SARAH, and additional checks for the consistency of model implementations have been created.

  18. Industrial Decision Making

    E-Print Network [OSTI]

    Elliott, R. N.; McKinney, V.; Shipley, A.

    2008-01-01T23:59:59.000Z

    Domestic industrial investment has declined due to unfavorable energy prices, and external markets. Investment behavior has changed over the past few years, and will continue due to high labor costs, tight markets and an unstable U.S. economy...

  19. AI Industrial Engineering 

    E-Print Network [OSTI]

    Unknown

    2011-08-17T23:59:59.000Z

    This paper describes the California Energy Commission’s (Commission) energy policies and programs that save energy and money for California’s manufacturing and food processing industries to help retain businesses in-state and reduce greenhouse gases...

  20. Uranium Industry Annual, 1992

    SciTech Connect (OSTI)

    Not Available

    1993-10-28T23:59:59.000Z

    The Uranium Industry Annual provides current statistical data on the US uranium industry for the Congress, Federal and State agencies, the uranium and electric utility industries, and the public. The feature article, ``Decommissioning of US Conventional Uranium Production Centers,`` is included. Data on uranium raw materials activities including exploration activities and expenditures, resources and reserves, mine production of uranium, production of uranium concentrate, and industry employment are presented in Chapter 1. Data on uranium marketing activities including domestic uranium purchases, commitments by utilities, procurement arrangements, uranium imports under purchase contracts and exports, deliveries to enrichment suppliers, inventories, secondary market activities, utility market requirements, and uranium for sale by domestic suppliers are presented in Chapter 2.

  1. Industrial energy use indices 

    E-Print Network [OSTI]

    Hanegan, Andrew Aaron

    2008-10-10T23:59:59.000Z

    Energy use index (EUI) is an important measure of energy use which normalizes energy use by dividing by building area. Energy use indices and associated coefficients of variation are computed for major industry categories ...

  2. Animal Industries Building 

    E-Print Network [OSTI]

    Unknown

    2011-08-17T23:59:59.000Z

    Plant managers around the world are interested in improving the energy efficiency of their facilities while both growing and modernizing their manufacturing capabilities. Emerging industrial technologies, both at the ...

  3. Animal Industries Building 

    E-Print Network [OSTI]

    Unknown

    2011-08-17T23:59:59.000Z

    Industrial steam users recognize the need to reduce system cost in order to remain internationally competitive. Steam systems are a key utility that influence cost significantly, and represent a high value opportunity ...

  4. Utility and Industrial Partnerships

    E-Print Network [OSTI]

    Sashihara, T. F.

    In the past decade, many external forces have shocked both utilities and their large industrial customers into seeking more effective ways of coping and surviving. One such way is to develop mutually beneficial partnerships optimizing the use...

  5. Engineering Industrial & Systems

    E-Print Network [OSTI]

    Berdichevsky, Victor

    powerful tool sets used in industry today. -Brent Gillett, BSIE 2007 Advanced Planning Engineer at BMW I the skills necessary to be successful in today's global environment. EDGE exposes and trains engineering

  6. Challenges for implementing industrial policy in Mexico

    E-Print Network [OSTI]

    Leith, Kendra Sawyer

    2009-01-01T23:59:59.000Z

    Although Mexico experienced high growth rates in the 1960s, 1970s, and early 1980s, the country has not fared well in terms of improvements in poverty and equality, growth in GDP, and job growth in some sectors in the last ...

  7. Clean Energy Manufacturing Initiative Industrial Efficiency and...

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

    Industrial Efficiency and Energy Productivity Video Clean Energy Manufacturing Initiative Industrial Efficiency and Energy Productivity Video Addthis Description Industrial...

  8. Industrial Development Fund (North Carolina)

    Broader source: Energy.gov [DOE]

    The Industrial Development Fund provides financing grants and loans through designated municipalities and counties to assist in infrastructure improvements for targeted industrial projects. The...

  9. Industrial Energy Efficiency: Designing Effective State Programs...

    Energy Savers [EERE]

    Industrial Energy Efficiency: Designing Effective State Programs for the Industrial Sector Industrial Energy Efficiency: Designing Effective State Programs for the Industrial...

  10. Iron and steel industry process model

    SciTech Connect (OSTI)

    Sparrow, F.T.; Pilati, D.; Dougherty, T.; McBreen, E.; Juang, L.L.

    1980-01-01T23:59:59.000Z

    The iron and steel industry process model depicts expected energy-consumption characteristics of the iron and steel industry and ancillary industries for the next 25 years by means of a process model of the major steps in steelmaking, from ore mining and scrap recycling to the final finishing of carbon, alloy, and stainless steel into steel products such as structural steel, slabs, plates, tubes, and bars. Two plant types are modeled: fully integrated mills and mini-mills. User-determined inputs into the model are as follows: projected energy and materials prices; projected costs of capacity expansion and replacement; energy-conserving options, both operating modes and investments; the internal rate of return required on investment; and projected demand for finished steel. Nominal input choices in the model for the inputs listed above are as follows: National Academy of Sciences Committee on Nuclear and Alternative Energy Systems Demand Panel nominal energy-price projections for oil, gas, distillates, residuals, and electricity and 1975 actual prices for materials; actual 1975 costs; new technologies added; 15% after taxes; and 1975 actual demand with 1.5%/y growth. The model reproduces the base-year (1975) actual performance of the industry; then, given the above nominal input choices, it projects modes of operation and capacity expansion that minimize the cost of meeting the given final demands for each of 5 years, each year being the midpoint of a 5-year interval. The output of the model includes the following: total energy use and intensity (Btu/ton) by type, by process, and by time period; energy conservation options chosen; utilization rates for existing capacity; capital-investment decisions for capacity expansion.

  11. Mechanical and Industrial Engineering Industry Advisory Board University of Massachusetts Amherst

    E-Print Network [OSTI]

    Mountziaris, T. J.

    9/13/2007 Mechanical and Industrial Engineering Industry Advisory Board University of Massachusetts Amherst Department of Mechanical and Industrial Engineering About the Mechanical and Industrial Engineering Industry Advisory Board The purpose of the Mechanical and Industrial Engineering Industry Advisory

  12. Data error detection and device controller failure detection in an input/output system

    SciTech Connect (OSTI)

    Katzman, J.A.; Bartlett, J.F.; Bixler, R.M.; Davidow, W.H.; Despotakis, J.A.; Graziano, P.J.; Green, M.D.; Greig, D.A.; Hayashi, S.J.; Mackie, D.R.

    1987-06-09T23:59:59.000Z

    This patent describes an input/output system for a multiprocessor system of the kind in which separate processor modules are interconnected for parallel processing, each of the processor modules having a central processing unit and a memory, at least some of the processor modules having an input/output channel, the input/output system comprising, at least one device controller for controlling the transfer of data between multiple different ones of the processor modules and a peripheral device.

  13. INTRODUCTION The power output of insect flight muscles is proportional to muscle

    E-Print Network [OSTI]

    Nieh, James

    #12;2239 INTRODUCTION The power output of insect flight muscles is proportional to muscle polaris) to forage in suboptimal thermal conditions (Heinrich, 1993). Recently, bumble bee (Bombus

  14. Fault-Tolerant Resynthesis with Dual-Output LUTs Ju-Yueh Lee1

    E-Print Network [OSTI]

    He, Lei

    utilization rate in real designs motivates us to utilize non-occupied SRAM bits of dual-output LUTs for fault

  15. Policies on Japan's Space Industry

    E-Print Network [OSTI]

    with space emerging countries 3. Step up leading-edge science and technology as an innovation engine (1Policies on Japan's Space Industry Shuichi Kaneko Director, Space Industry Office Manufacturing Industries Bureau Ministry of Economy, Trade and Industry (METI) #12;Japan's Space Policy is based

  16. Emulsified industrial oils recycling

    SciTech Connect (OSTI)

    Gabris, T.

    1982-04-01T23:59:59.000Z

    The industrial lubricant market has been analyzed with emphasis on current and/or developing recycling and re-refining technologies. This task has been performed for the United States and other industrialized countries, specifically France, West Germany, Italy and Japan. Attention has been focused at emulsion-type fluids regardless of the industrial application involved. It was found that emulsion-type fluids in the United States represent a much higher percentage of the total fluids used than in other industrialized countries. While recycling is an active matter explored by the industry, re-refining is rather a result of other issues than the mere fact that oil can be regenerated from a used industrial emulsion. To extend the longevity of an emulsion is a logical step to keep expenses down by using the emulsion as long as possible. There is, however, another important factor influencing this issue: regulations governing the disposal of such fluids. The ecological question, the respect for nature and the natural balances, is often seen now as everybody's task. Regulations forbid dumping used emulsions in the environment without prior treatment of the water phase and separation of the oil phase. This is a costly procedure, so recycling is attractive since it postpones the problem. It is questionable whether re-refining of these emulsions - as a business - could stand on its own if these emulsions did not have to be taken apart for disposal purposes. Once the emulsion is separated into a water and an oil phase, however, re-refining of the oil does become economical.

  17. ARM: ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Coulter, Richard; Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen; Martin, Timothy

    ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

  18. Developing an energy efficiency service industry in Shanghai

    SciTech Connect (OSTI)

    Lin, Jiang; Goldman, Charles; Levine, Mark; Hopper, Nicole

    2004-02-10T23:59:59.000Z

    The rapid development of the Chinese economy over the past two decades has led to significant growth in China's energy consumption and greenhouse gas (GHG) emissions. Between 1980 and 2000, China's energy consumption more than doubled from 602 million to 1.3 billion tons of coal-equivalent (NBS, 2003). In 2000, China's GHG emissions were about 12% of the global total, ranked second behind only the US. According to the latest national development plan issued by the Chinese government, China's energy demand is likely to double again by 2020 (DRC, 2004), based on a quadrupling of its gross domestic product (GDP). The objectives of the national development plan imply that China needs to significantly raise the energy efficiency of its economy, i.e., cutting the energy intensity of its economy by half. Such goals are extremely ambitious, but not infeasible. China has achieved such reductions in the past, and its current overall level of energy efficiency remains far behind those observed in other developed economies. However, challenges remain whether China can put together an appropriate policy framework and the institutions needed to improve the energy efficiency of its economy under a more market-based economy today. Shanghai, located at the heart of the Yangtze River Delta, is the most dynamic economic and financial center in the booming Chinese economy. With 1% of Chinese population (13 million inhabitants), its GDP in 2000 stood at 455 billion RMB yuan (5% of the national total), with an annual growth rate of 12%--much higher than the national average. It is a major destination for foreign as well as Chinese domestic investment. In 2003, Shanghai absorbed 10% of actual foreign investment in all China (''Economist'', January 17-23, 2004). Construction in Shanghai continues at a breakneck pace, with an annual addition of approximately 200 million square foot of residential property and 100 million square foot of commercial and industrial space over the last 5 years. It is one reason that China consumed over 60% of the world's cement production in 2003 (NBS 2004). Energy consumption in Shanghai has been growing at 6-8% annually, with the growth of electricity demand at over 10% per year. Shanghai, with very limited local energy resources, relies heavily on imported coal, oil, natural gas, and electricity. While coal still constitutes over half of Shanghai's energy consumption, oil and natural gas use have been growing in importance. Shanghai is the major market for China's West to East (natural gas) Pipeline (WEP). With the input from WEP and off-shore pipelines, it is expected that natural gas consumption will grow from 250 million cubic meters in 2000 to 3000-3500 million cubic meters in 2005. In order to secure energy supply to power Shanghai's fast-growing economy, the Shanghai government has set three priorities in its energy strategy: (1) diversification of its energy structure, (2) improving its energy efficiency, and (3) developing renewable and other cleaner forms of energy. Efficiency improvements are likely to be most critical, particularly in the near future, in addressing Shanghai's energy security, especially the recent electricity shortage in Shanghai. Commercial buildings and industries consume the majority of Shanghai's, as well as China's, commercial energy. In the building sector, Shanghai has been very active implementing energy efficiency codes for commercial and residential buildings. Following a workshop on building codes implementation held at LBNL for senior Shanghai policy makers in 2001, the Shanghai government recently introduced an implementation guideline on residential building energy code compliance for the downtown area of Shanghai to commence in April, 2004, with other areas of the city to follow in 2005. A draft code for commercial buildings has been developed as well. In the industrial sector, the Shanghai government started an ambitious initiative in 2002 to induce private capital to invest in energy efficiency improvements via energy management/services companies (EMC/ESCOs). In partic

  19. Industrial Assessment Center

    SciTech Connect (OSTI)

    Dr. Diane Schaub

    2007-03-05T23:59:59.000Z

    Since its inception, the University of Florida Industrial Assessment Center has successfully completed close to 400 energy assessments of small to medium manufacturing facilities in Florida, southern Georgia and southern Alabama. Through these efforts, recommendations were made that would result in savings of about $5 million per year, with an implementation rate of 20-25%. Approximately 80 engineering students have worked for the UF-IAC, at least 10 of whom went on to work in energy related fields after graduation. Additionally, through the popular course in Industrial Energy Management, many students have graduated from the University of Florida with a strong understanding and support of energy conservation methods.

  20. Libyan oil industry

    SciTech Connect (OSTI)

    Waddams, F.C.

    1980-01-01T23:59:59.000Z

    Three aspects of the growth and progress of Libya's oil industry since the first crude oil discovery in 1961 are: (1) relations between the Libyan government and the concessionary oil companies; (2) the impact of Libyan oil and events in Libya on the petroleum markets of Europe and the world; and (3) the response of the Libyan economy to the development of its oil industry. The historical review begins with Libya's becoming a sovereign nation in 1951 and traces its subsequent development into a position as a leading world oil producer. 54 references, 10 figures, 55 tables.

  1. Solar industrial process heat

    SciTech Connect (OSTI)

    Lumsdaine, E.

    1981-04-01T23:59:59.000Z

    The aim of the assessment reported is to candidly examine the contribution that solar industrial process heat (SIPH) is realistically able to make in the near and long-term energy futures of the United States. The performance history of government and privately funded SIPH demonstration programs, 15 of which are briefly summarized, and the present status of SIPH technology are discussed. The technical and performance characteristics of solar industrial process heat plants and equipment are reviewed, as well as evaluating how the operating experience of over a dozen SIPH demonstration projects is influencing institutional acceptance and economoc projections. Implications for domestic energy policy and international implications are briefly discussed. (LEW)

  2. Industrial Equipment Impacts Infrastructure

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed offOCHCO2: FinalOffers3.pdf0-45.pdf05 IdentifiedPathways to SustainedIndustrial AssessmentIndustrial

  3. Ontario's Industrial Energy Services Program

    E-Print Network [OSTI]

    Ploeger, L. K.

    .8%! ! ! ! OTHER 8.4%! l4.9%! l4.0%! ! ! ! TOTAL 100.0%! 100.0%! 100.0%! ! PROGRAM STRATEGY Ontario's Industrial Energy Services Program was designed to: lead industrial energy consumers to the realization that increased energy efficiency generates... ONTARIO'S INDUSTRIAL ENERGY SERVICES PROGRAM LINDA K. PLOEGER, GENERAL MANAGER, INDUSTRY PROGRAMS ONTARIO MINISTRY OF ENERGY TORONTO, ONTARIO, ABSTRACT The Ontario Ministry of Energy began offering its new Industrial Energy Services Program...

  4. Estimating Solar PV Output Using Modern Space/Time Geostatistics (Presentation)

    SciTech Connect (OSTI)

    Lee, S. J.; George, R.; Bush, B.

    2009-04-29T23:59:59.000Z

    This presentation describes a project that uses mapping techniques to predict solar output at subhourly resolution at any spatial point, develop a methodology that is applicable to natural resources in general, and demonstrate capability of geostatistical techniques to predict the output of a potential solar plant.

  5. Experimental Results on Multiple-Input Single-Output (MISO) Time Reversal for UWB

    E-Print Network [OSTI]

    Qiu, Robert Caiming

    Experimental Results on Multiple-Input Single-Output (MISO) Time Reversal for UWB Systems with multiple-input single- output (MISO) antennas over ultra-wideband (UWB) channels. In particular, temporal and spatial focusing as well as array gain are studied based on a (4 × 1) MISO scheme in an office environment

  6. Mechanism of low-frequency fluctuations of the output power of gas-discharge lasers

    SciTech Connect (OSTI)

    Melekhin, G.V.; Stepanov, V.A.; Chirkin, M.V.

    1984-08-01T23:59:59.000Z

    Fluctuations of the output power of gas-discharge lasers arising on account of the random character of the processes of ionization and electron-impact excitation of atomic levels are described. Low-frequency fluctuations of the output power of a cataphoretic He--Cd laser are examined as an example.

  7. Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu

    E-Print Network [OSTI]

    Lavaei, Javad

    Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu January 1, 2013 1 Introduction of solar panel: Routing the configuration between solar cells with a switch matrix. However, their result models and control policies for the optimal output of solar panels. The smallest unit on a solar panel

  8. Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization and Integrated Control

    E-Print Network [OSTI]

    Potkonjak, Miodrag

    1 Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization mechanical energy from human foot-strikes and explore its configuration and control towards optimized energy output. Dielectric Elastomers (DEs) are high-energy density, soft, rubber-like material

  9. Non-Additivity of Minimum Output p-$\\mathbf{R\\acute{e}nyi}$ Entropy

    E-Print Network [OSTI]

    Nengkun Yu; Mingsheng Ying

    2012-12-24T23:59:59.000Z

    Hastings disproved additivity conjecture for minimum output entropy by using random unitary channels. In this note, we employ his approach to show that minimum output $p-$R\\'{e}nyi entropy is non-additive for $p\\in(0,p_0)\\cup(1-p_0,1)$ where $p_0\\approx 0.2855$.

  10. Generating Isolated Outputs in a Multilevel Modular Capacitor Clamped DC-DC Converter

    E-Print Network [OSTI]

    Tolbert, Leon M.

    balance between the fuel cell and any energy storage inside the vehicle, and provides continuous power) for Hybrid Electric and Fuel Cell Vehicles Faisal H. Khan1 , Leon M. Tolbert2 1 Electric Power Research transformers to generate isolated ac outputs. These isolated outputs can be rectified and filtered to obtain

  11. Selection of Output Function in Nonlinear Feedback Linearizing Excitation Control for Power Systems

    E-Print Network [OSTI]

    Pota, Himanshu Roy

    Selection of Output Function in Nonlinear Feedback Linearizing Excitation Control for Power Systems for power systems. Depending on the relative degree of the system which depends on the output function Power systems are large, complex, and highly nonlinear interconnected dynamic systems. The power demand

  12. Statistical post processing of model output from the air quality model LOTOS-EUROS

    E-Print Network [OSTI]

    Stoffelen, Ad

    are calculated with R, a language for statistical computing. The routine STEP in R is used to remove variablesStatistical post processing of model output from the air quality model LOTOS-EUROS Annemiek Pijnappel De Bilt, 2011 | Stageverslag #12;#12;Statistical post processing of model output from the air

  13. Modeling of passive microwave responses in convective situations using output from mesoscale models

    E-Print Network [OSTI]

    Pardo-Carrión, Juan R.

    Modeling of passive microwave responses in convective situations using output from mesoscale models using output from nonhydrostatic mesoscale atmospheric model, Meso-NH, simulations. The radiative for a systematic evaluation of the mesoscale cloud models. An overall good agreement is obtained for both

  14. Fine-grained Photovoltaic Output Prediction using a Bayesian Ensemble Prithwish Chakraborty1,2

    E-Print Network [OSTI]

    Ramakrishnan, Naren

    generation is increasingly reliant on renewable power sources, e.g., solar (pho- tovoltaic or PV) and wind Increasingly, local and distributed power generation e.g., through solar (photovoltaic or PV), wind, fuel cells and intermittent in their energy output, which makes integration with the power grid challenging. PV output

  15. Quality assurance of solar thermal systems with the ISFH-Input/Output-Procedure

    E-Print Network [OSTI]

    Quality assurance of solar thermal systems with the ISFH- Input/Output-Procedure Peter Paerisch different solar systems. The simulation model was validated with measured data. The deviation between meas * Tel. +49 (0)5151-999503, Fax: +49 (0)5151-999500, Email: paerisch@isfh.de Abstract Input/Output

  16. Industry Partners Panel

    Broader source: Energy.gov [DOE]

    Industry Panel presenters include: Michael G. Andrew, Director - Academic and Technical Programs, Advanced Products and Materials, Johnson Controls Power Solutions Michael A. Fetcenko, Vice President and Managing Director, BASF Battery Materials – Ovonic, BASF Corporation Adam Kahn, Founder and CEO, AKHAN Technologies, Inc. Stephen E. Zimmer, Executive Director, United States Council for Automotive Research (USCAR)

  17. Industrial Energy Use Indices

    E-Print Network [OSTI]

    Hanegan, A.; Heffington, W. M.

    2007-01-01T23:59:59.000Z

    of variations for all industry types in warm versus cold regions of the U.S. generally is greater than unity. Data scatter may have several explanations, including climate, plant area accounting, the influence of low cost energy and low cost buildings used...

  18. INTERMOUNTAIN INDUSTRIAL ASSESSMENT CENTER

    SciTech Connect (OSTI)

    MELINDA KRAHENBUHL

    2010-05-28T23:59:59.000Z

    The U. S. Department of Energy’s Intermountain Industrial Assessment Center (IIAC) at the University of Utah has been providing eligible small- and medium-sized manufacturers with no-cost plant assessments since 2001, offering cost-effective recommendations for improvements in the areas of energy efficiency, pollution prevention, and productivity improvement.

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

    E-Print Network [OSTI]

    Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

    2011-01-01T23:59:59.000Z

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

  20. Method for leveling the power output of an electromechanical battery as a function of speed

    DOE Patents [OSTI]

    Post, Richard F. (Walnut Creek, CA)

    1999-01-01T23:59:59.000Z

    The invention is a method of leveling the power output of an electromechanical battery during its discharge, while at the same time maximizing its power output into a given load. The method employs the concept of series resonance, employing a capacitor the parameters of which are chosen optimally to achieve the desired near-flatness of power output over any chosen charged-discharged speed ratio. Capacitors are inserted in series with each phase of the windings to introduce capacitative reactances that act to compensate the inductive reactance of these windings. This compensating effect both increases the power that can be drawn from the generator before inductive voltage drops in the windings become dominant and acts to flatten the power output over a chosen speed range. The values of the capacitors are chosen so as to optimally flatten the output of the generator over the chosen speed range.

  1. Method for leveling the power output of an electromechanical battery as a function of speed

    DOE Patents [OSTI]

    Post, R.F.

    1999-03-16T23:59:59.000Z

    The invention is a method of leveling the power output of an electromechanical battery during its discharge, while at the same time maximizing its power output into a given load. The method employs the concept of series resonance, employing a capacitor the parameters of which are chosen optimally to achieve the desired near-flatness of power output over any chosen charged-discharged speed ratio. Capacitors are inserted in series with each phase of the windings to introduce capacitative reactances that act to compensate the inductive reactance of these windings. This compensating effect both increases the power that can be drawn from the generator before inductive voltage drops in the windings become dominant and acts to flatten the power output over a chosen speed range. The values of the capacitors are chosen so as to optimally flatten the output of the generator over the chosen speed range. 3 figs.

  2. Model documentation report: Industrial sector demand module of the National Energy Modeling System

    SciTech Connect (OSTI)

    NONE

    1997-01-01T23:59:59.000Z

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

  3. Modular industrial solar retrofit project (MISR)

    SciTech Connect (OSTI)

    Alvis, R.L.

    1980-01-01T23:59:59.000Z

    The intent of this paper is to describe a major Department of Energy (DOE) thrust to bring line-focus solar thermal technology to commercial readiness. This effort is referred to as the MISR Project. The project is based upon the premise that thermal energy is the basic solar thermal system output and that low-temperature, fossil fuel applications are technically the first that should be retrofitted. Experience has shown that modularity in system design and construction offers potential for reducing engineering design costs, reduces manufacturing costs, reduces installation time and expense, and improves system operational reliability. The modular design effort will be sponsored by Sandia National Laboratories with industry doing the final designs. The operational credibility of the systems will be established by allowing selected industrial thermal energy users to purchase MISR systems from suppliers and operate them for two years. Industries will be solicited by DOE/Albuquerque Operations Office to conduct these experiments on a cost sharing basis. The MISR system allowed in the experiments will have been previously qualified for the application. The project is divided into three development phases which represent three design and experiment cycles. The first cycle will use commercially available trough-type solar collectors and will incorporate 5 to 10 experiments of up to 5000 m/sup 2/ of collectors each. The project effort began in March 1980, and the first cycle is to be completed in 1985. Subsequent cycles will begin at 3-year intervals. The project is success oriented, and if the first cycle reaches commercial readiness, the project will be terminated. If not, a second, and possibly a third, development cycle will be conducted.

  4. Transforming the Oil Industry into the Energy Industry

    E-Print Network [OSTI]

    Sperling, Daniel; Yeh, Sonia

    2009-01-01T23:59:59.000Z

    Transforming the Oil Industry into the Energy Industry BYculprit. It consumes half the oil used in the world andconsuming two thirds of the oil and causing about one third

  5. Innovative New Industrial Technologies: An Industry/DOE Joint Endeavor

    E-Print Network [OSTI]

    Gross, T. J.

    The Department of Energy’s Office of Industrial Programs supports research and development leading to improved energy efficiency and greater overall productivity in the industrial sector. Its basic strategy is a program of cost-shared R...

  6. INDUSTRIAL ASSOCIATESHIP SCHEME Centre for Industrial Consultancy and Sponsored Research

    E-Print Network [OSTI]

    Bhashyam, Srikrishna

    this scheme: #12;(i) Energy Energy Storage (1990) Strategies for Energy Saving in Industry (1993) Pollution Control Equipment (2001) Acoustics and Noise Control for Industry (2005) Urban Air Quality

  7. Energy efficiency opportunities in China. Industrial equipment and small cogeneration

    SciTech Connect (OSTI)

    NONE

    1995-02-01T23:59:59.000Z

    A quick glance at comparative statistics on energy consumption per unit of industrial output reveals that China is one of the least energy efficient countries in the world. Energy waste not only impedes economic growth, but also creates pollution that threatens human health, regional ecosystems, and the global climate. China`s decision to pursue economic reform and encourage technology transfer from developed countries has created a window of opportunity for significant advances in energy efficiency. Policy changes, technical training, public education, and financing can help China realize its energy conservation potential.

  8. INDUSTRIAL & SYSTEMS Industrial and Systems engineers use engineering

    E-Print Network [OSTI]

    Rohs, Remo

    78 INDUSTRIAL & SYSTEMS Industrial and Systems engineers use engineering and business principles of physical and human resources. These engineers are involved in developing manufacturing systems to help companies compete in todays global marketplace. The Industrial and Systems engineers task is to take limited

  9. Finding the quantum thermoelectric with maximal efficiency and minimal entropy production at given power output

    E-Print Network [OSTI]

    Robert S. Whitney

    2015-03-16T23:59:59.000Z

    We investigate the nonlinear scattering theory for quantum systems with strong Seebeck and Peltier effects, and consider their use as heat-engines and refrigerators with finite power outputs. This article gives detailed derivations of the results summarized in Phys. Rev. Lett. 112, 130601 (2014). It shows how to use the scattering theory to find (i) the quantum thermoelectric with maximum possible power output, and (ii) the quantum thermoelectric with maximum efficiency at given power output. The latter corresponds to a minimal entropy production at that power output. These quantities are of quantum origin since they depend on system size over electronic wavelength, and so have no analogue in classical thermodynamics. The maximal efficiency coincides with Carnot efficiency at zero power output, but decreases with increasing power output. This gives a fundamental lower bound on entropy production, which means that reversibility (in the thermodynamic sense) is impossible for finite power output. The suppression of efficiency by (nonlinear) phonon and photon effects is addressed in detail; when these effects are strong, maximum efficiency coincides with maximum power. Finally, we show in particular limits (typically without magnetic fields) that relaxation within the quantum system does not allow the system to exceed the bounds derived for relaxation-free systems, however, a general proof of this remains elusive.

  10. Coal industry annual 1997

    SciTech Connect (OSTI)

    NONE

    1998-12-01T23:59:59.000Z

    Coal Industry Annual 1997 provides comprehensive information about US coal production, number of mines, prices, productivity, employment, productive capacity, and recoverable reserves. US Coal production for 1997 and previous years is based on the annual survey EIA-7A, Coal Production Report. This report presents data on coal consumption, coal distribution, coal stocks, coal prices, and coal quality for Congress, Federal and State agencies, the coal industry, and the general public. Appendix A contains a compilation of coal statistics for the major coal-producing States. This report includes a national total coal consumption for nonutility power producers that are not in the manufacturing, agriculture, mining, construction, or commercial sectors. 14 figs., 145 tabs.

  11. Coal industry annual 1993

    SciTech Connect (OSTI)

    Not Available

    1994-12-06T23:59:59.000Z

    Coal Industry Annual 1993 replaces the publication Coal Production (DOE/FIA-0125). This report presents additional tables and expanded versions of tables previously presented in Coal Production, including production, number of mines, Productivity, employment, productive capacity, and recoverable reserves. This report also presents data on coal consumption, coal distribution, coal stocks, coal prices, coal quality, and emissions for a wide audience including the Congress, Federal and State agencies, the coal industry, and the general public. In addition, Appendix A contains a compilation of coal statistics for the major coal-producing States. This report does not include coal consumption data for nonutility Power Producers who are not in the manufacturing, agriculture, mining, construction, or commercial sectors. This consumption is estimated to be 5 million short tons in 1993.

  12. BTU Accounting for Industry

    E-Print Network [OSTI]

    Redd, R. O.

    1979-01-01T23:59:59.000Z

    , salesmen cars, over the highway trucks, facilities startup, waste used as fuel and fuels received for storage. This is a first step in the DOE's effort to establish usage guidelines for large industrial users and, we note, it requires BTU usage data...-generated electricity, heating, ventilating, air conditioning, in-plant transportation, ore hauling, raw material storage and finished product warehousing. Categories which are excluded are corporate and divisional offices, basic research, distribution centers...

  13. Industrial Waste Heat Recovery

    E-Print Network [OSTI]

    Ward, M. E.; Solomon, N. G.; Tabb, E. S.

    1980-01-01T23:59:59.000Z

    INDUSTRIAL WASTE HEAT RECOVREY M. E. Ward and N. G. Solomon E. S. Tabb Solar Turbines International and Gas Research Institute San Diego, California Chicago, Illinois ABSTRACT i I One hundred fifty reports were reviewed along with interviews... tests, promising low temperature heat exchanger tube alloys and coated surfaces were identified. 1INTROUCTION of advanced technology heat recovery techniques 1_ Recovering waste heat from the flue gases of the pr~ary objective. Specific objectives...

  14. Industrial Energy Efficiency Assessments

    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 DataDepartment of Energy Your Density Isn't YourTransport(Fact Sheet),EnergyImprovementINDIAN COUNTRYBarriers to Industrial

  15. The impact of government policies on industrial evolution : the case of China's automotive industry

    E-Print Network [OSTI]

    Luo, Jianxi

    2006-01-01T23:59:59.000Z

    Governmental industrial policies have great influence on industrial performances and development trajectories. The infant industry theory has been the dominating theoretical foundation of the industrial policies in developing ...

  16. Industrial Heat Pump Design Options

    E-Print Network [OSTI]

    Gilbert, J. S.

    There are numerous industries that can incorporate heat pumps into their operations to save energy costs and payoff the investment in well under two years. Many of these industries can cut energy costs associated with evaporation by over 75...

  17. Industrial Heat Pump Design Options 

    E-Print Network [OSTI]

    Gilbert, J. S.

    1985-01-01T23:59:59.000Z

    There are numerous industries that can incorporate heat pumps into their operations to save energy costs and payoff the investment in well under two years. Many of these industries can cut energy costs associated with evaporation by over 75...

  18. A National Resource for Industry

    E-Print Network [OSTI]

    alloys, and metal matrix composite products carbon fibe's manufacturing industries. These industries call upon ORNL's expertise in materials synthesis, characterization-efficient manufacturing processes and materials targeting products of the future. The Department of Energy's first

  19. Electrotechnologies and Industrial Pollution Control

    E-Print Network [OSTI]

    Schmidt, P. S.

    The role of electrotechnologies in the control of emissions and effluents from industrial processes is discussed. Matrices are presented identifying those electrotechnologies which impact pollution in various industries. Specific examples...

  20. Deaerators in Industrial Steam Systems

    SciTech Connect (OSTI)

    Not Available

    2006-01-01T23:59:59.000Z

    This revised ITP tip sheet on deaerators in industrial steam systems provides how-to advice for improving industrial steam systems using low-cost, proven practices and technologies.

  1. Modeling the semiconductor industry dynamics

    E-Print Network [OSTI]

    Wu, Kailiang

    2008-01-01T23:59:59.000Z

    The semiconductor industry is an exciting and challenging industry. Strong demand at the application end, plus the high capital intensity and rapid technological innovation in manufacturing, makes it difficult to manage ...

  2. Texas Industries of the Future

    E-Print Network [OSTI]

    Ferland, K.

    The purpose of the Texas Industries of the Future program is to facilitate the development, demonstration and adoption of advanced technologies and adoption of best practices that reduce industrial energy usage, emissions, and associated costs...

  3. Fracking: An Industry Under Pressure

    E-Print Network [OSTI]

    Melville, Jo

    2013-01-01T23:59:59.000Z

    is able to squeeze out of oil and gas wells, it is a hugehugely to the local oil and gas industries, household incomeMore importantly, the oil and gas industry -- mostly through

  4. X-ray source assembly having enhanced output stability, and fluid stream analysis applications thereof

    DOE Patents [OSTI]

    Radley, Ian (Glenmont, NY); Bievenue, Thomas J. (Delmar, NY); Burdett, John H. (Charlton, NY); Gallagher, Brian W. (Guilderland, NY); Shakshober, Stuart M. (Hudson, NY); Chen, Zewu (Schenectady, NY); Moore, Michael D. (Alplaus, NY)

    2008-06-08T23:59:59.000Z

    An x-ray source assembly and method of operation are provided having enhanced output stability. The assembly includes an anode having a source spot upon which electrons impinge and a control system for controlling position of the anode source spot relative to an output structure. The control system can maintain the anode source spot location relative to the output structure notwithstanding a change in one or more operating conditions of the x-ray source assembly. One aspect of the disclosed invention is most amenable to the analysis of sulfur in petroleum-based fuels.

  5. X-ray source assembly having enhanced output stability, and fluid stream analysis applications thereof

    DOE Patents [OSTI]

    Radley, Ian; Bievenue, Thomas J.; Burdett Jr., John H.; Gallagher, Brian W.; Shakshober, Stuart M.; Chen, Zewu; Moore, Michael D.

    2007-04-24T23:59:59.000Z

    An x-ray source assembly (2700) and method of operation are provided having enhanced output stability. The assembly includes an anode (2125) having a source spot upon which electrons (2120) impinge and a control system (2715/2720) for controlling position of the anode source spot relative to an output structure. The control system can maintain the anode source spot location relative to the output structure (2710) notwithstanding a change in one or more operating conditions of the x-ray source assembly. One aspect of the disclosed invention is most amenable to the analysis of sulfur in petroleum-based fuels.

  6. Innovative Utility Pricing for Industry

    E-Print Network [OSTI]

    Ross, J. A.

    tariffs can re a market for power during the time when it has sult in benefits to industry, to the electric abundant capacity available. From the other rate utility, and to other ratepayers on the electric payers' perspective, there will be a continued...INNOVATIVE UTILITY PRICING FOR INDUSTRY James A. Ross Drazen-Brubaker &Associates, Inc. St. Louis, Missouri ABSTRACT The electric utility industry represents only one source of power available to industry. Al though the monopolistic...

  7. Study of domestic social and economic impacts of ocean thermal energy conversion (OTEC) commercial development. Volume II. Industry profiles

    SciTech Connect (OSTI)

    None

    1981-12-22T23:59:59.000Z

    Econoimc profiles of the industries most affected by the construction, deployment, and operation of Ocean Thermal Energy Conversion (OTEC) powerplants are presented. Six industries which will contribute materials and/or components to the construction of OTEC plants have been identified and are profiled here. These industries are: steel industry, concrete industry, titanium metal industry, fabricated structural metals industry, fiber glass-reinforced plastics industry, and electrical transmission cable industry. The economic profiles for these industries detail the industry's history, its financial and economic characteristics, its technological and production traits, resource constraints that might impede its operation, and its relation to OTEC. Some of the historical data collected and described in the profile include output, value of shipments, number of firms, prices, employment, imports and exports, and supply-demand forecasts. For most of the profiled industries, data from 1958 through 1980 were examined. In addition, profiles are included on the sectors of the economy which will actualy construct, deploy, and supply the OTEC platforms.

  8. Industrial Energy Audit Guidebook: Guidelines for Conducting...

    Open Energy Info (EERE)

    Industry Resource Type: Guidemanual Website: china.lbl.govsiteschina.lbl.govfilesLBNL-3991E.Industrial%20Energy Industrial Energy Audit Guidebook: Guidelines for Conducting...

  9. Local Option- Industrial Facilities and Development Bonds

    Broader source: Energy.gov [DOE]

    Under the Utah Industrial Facilities and Development Act, counties, municipalities, and state universities in Utah may issue Industrial Revenue Bonds (IRBs) or Industrial Development Bonds (IDBs)...

  10. Federal Utility Partnership Working Group Industry Commitment...

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

    Industry Commitment Federal Utility Partnership Working Group Industry Commitment Investor-owned electric utility industry members of the Edison Electric Institute pledge to assist...

  11. Design of Dual-Output Alternators With Switched-Mode Rectification

    E-Print Network [OSTI]

    Hassan, Gimba

    The push to introduce dual-voltage (42 V/14 V) automotive electrical systems necessitates power generation solutions capable of supplying power to multiple outputs. A number of approaches for implementing dual-voltage ...

  12. Limitation of the output power of cw electric-discharge CO{sub 2} lasers

    SciTech Connect (OSTI)

    Nevdakh, Vladimir V [B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk (Belarus)

    1999-04-30T23:59:59.000Z

    The output power of a sealed-off tunable cw CO{sub 2} laser was optimised. The dependences of the small-signal gain for the 10P(20) line and of the output powers for different transmittances of the cavity on the discharge current were determined. The distributed loss coefficient and the saturation parameter were measured. The saturation parameter increased continuously with increase in the discharge current, leading to a mismatch between the output power and gain maxima. It was established that the principal factor limiting the output power of cw electric-discharge CO{sub 2} lasers is not an increase in the temperature of the active medium but the dissociation of CO{sub 2} molecules. When the latter is minimised in order to achieve the maximum laser power, low gas temperatures are not required. (lasers)

  13. Output dominance as a predictor of humor content in verbal productions

    E-Print Network [OSTI]

    Hull, Rachel Gayle

    2000-01-01T23:59:59.000Z

    -dominance-ordered feature lists generated for each of the concepts. It was hypothesized that juxtapositions judged funny would rely more often on properties with significantly different output dominance scores per concept, while those judged not funny would involve fewer...

  14. Examining the Variability of Wind Power Output in the Regulation Time Frame: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Shedd, S.; Florita, A.

    2012-08-01T23:59:59.000Z

    This work examines the distribution of changes in wind power for different time scales in the regulation time frame as well as the correlation of changes in power output for individual wind turbines in a wind plant.

  15. Motor output in a bimanual continuation-tapping task is independent of visual cues 

    E-Print Network [OSTI]

    Miller, Louisa

    2009-07-03T23:59:59.000Z

    Presented are two studies examining the role of vision on motor output in the continuation-tapping paradigm (Stevens, 1886). The role of vision is measured by comparisons of motor performance under three visual feedback conditions: freeview...

  16. Multilevel Cascade H-bridge Inverter DC Voltage Estimation Through Output Voltage Sensing

    E-Print Network [OSTI]

    Tolbert, Leon M.

    system as the inverter power supply may vary. For example, interface of solar panels or fuel cell. The output voltage is then processed by a DSP unit that uses the signals that command the switches

  17. Primate Motor Cortex: Individual and Ensemble Neuron-Muscle Output Relationships

    E-Print Network [OSTI]

    Griffin, Darcy Michelle

    2008-07-30T23:59:59.000Z

    The specific aims of this study were to: 1) investigate the encoding of forelimb muscle activity timing and magnitude by corticomotoneuronal (CM) cells, 2) test the stability of primary motor cortex (M1) output to forelimb ...

  18. Augmentation of Power Output of Axisymmetric Ducted Wind Turbines by Porous Trailing Edge Disks

    E-Print Network [OSTI]

    widnall, sheila

    2014-06-30T23:59:59.000Z

    This paper presents analytical and experimental results that demonstrated that the power output from a ducted wind turbine can be dramatically increased by the addition of a trailing edge device such as a porous disk. In ...

  19. Input-Output as a Method of Evaluahon of the Economic Impact of Water Resources Development

    E-Print Network [OSTI]

    Canion, R. L.; Trock, W. L.

    In this report the results of a study of the use of input-output analysis to evaluate the economic impact of water resources development are presented. Blackburn Crossing reservoir on the Upper Neches river was the subject development...

  20. Code design for multiple-input multiple-output broadcast channels

    E-Print Network [OSTI]

    Uppal, Momin Ayub

    2009-06-02T23:59:59.000Z

    Recent information theoretical results indicate that dirty-paper coding (DPC) achieves the entire capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This thesis presents practical code designs for Gaussian...

  1. Concatenated codes for the multiple-input multiple-output quasi-static fading channel

    E-Print Network [OSTI]

    Gulati, Vivek

    2005-02-17T23:59:59.000Z

    CONCATENATED CODES FOR THE MULTIPLE-INPUT MULTIPLE-OUTPUT QUASI-STATIC FADING CHANNEL A Dissertation by VIVEK GULATI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree... of DOCTOR OF PHILOSOPHY December 2004 Major Subject: Electrical Engineering CONCATENATED CODES FOR THE MULTIPLE-INPUT MULTIPLE-OUTPUT QUASI-STATIC FADING CHANNEL A Dissertation by VIVEK GULATI Submitted to Texas A&M University in partial fulfillment...

  2. Exploring the circadian outputs and function of HPT-1 in Neurospora crassa

    E-Print Network [OSTI]

    Vickery, Justin Wayde

    2013-09-28T23:59:59.000Z

    EXPLORING THE CIRCADIAN OUTPUTS AND FUNCTIONS OF HTP-1 IN NEUROSPORA CRASSA An Undergraduate Research Scholars Thesis by JUSTIN WAYDE VICKERY Submitted to Honors and Undergraduate Research Texas A&M University in partial fulfillment... ......................................................................................................................... 25 1 ABSTRACT Exploring the circadian outputs and functions of HPT-1 in N. crassa. (May 2014) Justin Wayde Vickery Department of Biology Texas A&M University Research Advisor: Dr. Deborah Bell-Pedersen Department of Biology...

  3. Coal Industry Annual 1995

    SciTech Connect (OSTI)

    NONE

    1996-10-01T23:59:59.000Z

    This report presents data on coal consumption, coal distribution, coal stocks, coal prices, coal quality, and emissions for Congress, Federal and State agencies, the coal industry, and the general public. Appendix A contains a compilation of coal statistics for the major coal-producing States. This report does not include coal consumption data for nonutility power producers that are not in the manufacturing, agriculture, mining, construction, or commercial sectors. Consumption for nonutility power producers not included in this report is estimated to be 21 million short tons for 1995.

  4. Industrial Cogeneration Application

    E-Print Network [OSTI]

    Mozzo, M. A.

    INDUSTRIAL COGENERATION APLLICATION Martin A. Mozzo, Jr., P.E. American Standard, Inc. New York,New York ABSTRACT Cogeneration is the sequential use of a single fuel source to generate electrical and thermal energy. It is not a new technology... been reviewing the potential of cogeneration at some of our key facilities. Our plan is to begin with a Pilot Plant 500 KW steam turbine generator to be install~d and operating in 1986. Key points to be discuss~d in the paper are: 1...

  5. Coal industry annual 1996

    SciTech Connect (OSTI)

    NONE

    1997-11-01T23:59:59.000Z

    This report presents data on coal consumption, coal distribution, coal stocks, coal prices, and coal quality, and emissions for Congress, Federal and State agencies, the coal industry, and the general public. Appendix A contains a compilation of coal statistics for the major coal-producing States.This report does not include coal consumption data for nonutility power producers that are not in the manufacturing, agriculture, mining, construction, or commercial sectors. Consumption for nonutility power producers not included in this report is estimated to be 24 million short tons for 1996. 14 figs., 145 tabs.

  6. Industrial energy use indices

    E-Print Network [OSTI]

    Hanegan, Andrew Aaron

    2008-10-10T23:59:59.000Z

    and colder are determined by annual average temperature weather data). Data scatter may have several explanations, including climate, plant area accounting, the influence of low cost energy and low cost buildings used in the south of the U.S. iv... the average EUI for an energy type. The combined CoV from all of the industries considered, which accounts for 8,200 plants from all areas of the continental U.S., is 290%. This paper discusses EUIs and their variations based on electricity and natural...

  7. Natural Gas Industrial Price

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBG 0 20Year Jan Feb2009 20103 5.53

  8. Industrial Green | Jefferson Lab

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn Other News link to facebook link to04948Industrial Green

  9. CASL - Industry Council

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWPSuccess Stories Siteandscience, and8 FY0Link to Resources Industry

  10. CASL - Industry Council Resources

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWPSuccess Stories Siteandscience, and8 FY0Link to Resources IndustryCASL

  11. Industrial Energy Efficiency

    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 DataDepartment of Energy Your Density Isn't YourTransport(Fact Sheet),EnergyImprovementINDIAN COUNTRYBarriers to Industrial Energy

  12. Industrial Energy Efficiency Assessments

    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 DataDepartment of Energy Your Density Isn't YourTransport(Fact Sheet),EnergyImprovementINDIAN COUNTRYBarriers to IndustrialEnergy

  13. Flow boiling test of GDP replacement coolants

    SciTech Connect (OSTI)

    Park, S.H. [comp.

    1995-08-01T23:59:59.000Z

    The tests were part of the CFC replacement program to identify and test alternate coolants to replace CFC-114 being used in the uranium enrichment plants at Paducah and Portsmouth. The coolants tested, C{sub 4}F{sub 10} and C{sub 4}F{sub 8}, were selected based on their compatibility with the uranium hexafluoride process gas and how well the boiling temperature and vapor pressure matched that of CFC-114. However, the heat of vaporization of both coolants is lower than that of CFC-114 requiring larger coolant mass flow than CFC-114 to remove the same amount of heat. The vapor pressure of these coolants is higher than CFC-114 within the cascade operational range, and each coolant can be used as a replacement coolant with some limitation at 3,300 hp operation. The results of the CFC-114/C{sub 4}F{sub 10} mixture tests show boiling heat transfer coefficient degraded to a minimum value with about 25% C{sub 4}F{sub 10} weight mixture in CFC-114 and the degree of degradation is about 20% from that of CFC-114 boiling heat transfer coefficient. This report consists of the final reports from Cudo Technologies, Ltd.

  14. Optimization of the LCLS X-ray FEL output performance in the presence of strong undulator wakefields

    E-Print Network [OSTI]

    Reiche, S; Emma, P; Fawley, W M; Huang, Z; Nuhn, H D; Stupakov, G V

    2005-01-01T23:59:59.000Z

    Optimization of the LCLS X-ray FEL output performance in the presence of strong undulator wakefields

  15. Output Harmonic Termination Techniques for AlGaN/GaN HEMT Power Amplifiers Using Active Integrated Antenna Approach

    E-Print Network [OSTI]

    Itoh, Tatsuo

    Output Harmonic Termination Techniques for AlGaN/GaN HEMT Power Amplifiers Using Active Integrated 1200, Los Angeles, CA 90045 Abstract -- In this paper, effects of output harmonic terminations on PAE termination, we observe a substantial increase in PAE and output power. Further, we demonstrate the high

  16. Whitacre College of Engineering Industrial Engineering Department

    E-Print Network [OSTI]

    Gelfond, Michael

    Whitacre College of Engineering Industrial Engineering Department Department Chair and Professor of Industrial Engineering. The Industrial Engineering Department at Texas Tech University has a distinguished industrial engineering education and provide appropriate service to the department, university

  17. Faculty of Engineering & Design Industrial Placements

    E-Print Network [OSTI]

    Burton, Geoffrey R.

    Faculty of Engineering & Design Industrial Placements A guide for industry #12;Industrial placements The Faculty of Engineering & Design has built close links with engineering companies through research, projects, placements and graduate employees. We know that working with industry ensures our

  18. Competitive developments in the electric supply industry

    SciTech Connect (OSTI)

    Bruder, G.F.; Lively, M.

    1996-12-31T23:59:59.000Z

    Competition in the electric supply industry is outlined. The following topics are discussed: six impending major developments in the electric industry; recent and projected developments in the industry; where is the industry headed?; and what the future holds.

  19. Research Projects in Industrial Technology.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration. Industrial Technology Section.

    1990-06-01T23:59:59.000Z

    The purpose of this booklet is to briefly describe ongoing and completed projects being carried out by Bonneville Power Administration's (BPA) Industrial Technology Section. In the Pacific Northwest, the industrial sector is the largest of the four consuming sectors. It accounted for thirty-nine percent of the total firm demand in the region in 1987. It is not easy to asses the conservation potential in the industrial sector. Recognizing this, the Northwest Power Planning Council established an objective to gain information on the size, cost, and availability of the conservation resource in the industrial sector, as well as other sectors, in its 1986 Power Plan. Specifically, the Council recommended that BPA operate a research and development program in conjunction with industry to determine the potential costs and savings from efficiency improvements in industrial processes which apply to a wide array of industrial firms.'' The section, composed of multidisciplinary engineers, provides technical support to the Industrial Programs Branch by designing and carrying out research relating to energy conservation in the industrial sector. The projects contained in this booklet are arranged by sector --industrial, utility, and agricultural -- and, within each sector, chronologically from ongoing to completed, with those projects completed most recently falling first. For each project the following information is given: its objective approach, key findings, cost, and contact person. Completed projects also include the date of completion, a report title, and report number.

  20. Biomedical | Chemical & Biomolecular | Civil & Environmental | Electrical & Computer | Industrial | Mechanical | Petroleum Careers in Industrial Engineering

    E-Print Network [OSTI]

    Glowinski, Roland

    | Mechanical | Petroleum Careers in Industrial Engineering Manufacturing, service and retail industries hireBiomedical | Chemical & Biomolecular | Civil & Environmental | Electrical & Computer | Industrial a significant number of industrial engineers. Specific industries include automobile manufacturers, electronics

  1. The Industrialization of Thermoelectric Power Generation Technology...

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

    The Industrialization of Thermoelectric Power Generation Technology The Industrialization of Thermoelectric Power Generation Technology Presents module and system requirements for...

  2. ITP Industrial Materials: Development and Commercialization of...

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

    Industrial Materials: Development and Commercialization of Alternative Carbon Fiber Precursors and Conversion Technologies ITP Industrial Materials: Development and...

  3. SPIDERS Joint Capability Technology Demonstration Industry Day...

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

    SPIDERS Joint Capability Technology Demonstration Industry Day Presentations SPIDERS Joint Capability Technology Demonstration Industry Day Presentations Presentations from the...

  4. Office of Industry Research and Technology Programs Greetings to Industry

    E-Print Network [OSTI]

    Ginzel, Matthew

    Assistant Vice President, Corporate & Foundation Relations Inside this issue... Greetings to Industry. The founding members are American Axle and Manufacturing, Eaton Corpora- tion and John Deere. This applied

  5. Modeling the Energy Output from an In-Stream Tidal Turbine Farm

    E-Print Network [OSTI]

    Ye Li; Barbara J. Lence; Sander M. Calisal

    Abstract—This paper is based on a recent paper presented in the 2007 IEEE SMC conference by the same authors [1], discussing an approach to predicting energy output from an instream tidal turbine farm. An in-stream tidal turbine is a device for harnessing energy from tidal currents in channels, and functions in a manner similar to a wind turbine. A group of such turbines distributed in a site is called an in-stream tidal turbine farm which is similar to a wind farm. Approaches to estimating energy output from wind farms cannot be fully transferred to study tidal farms, however, because of the complexities involved in modeling turbines underwater. In this paper, we intend to develop an approach for predicting energy output of an in-stream tidal turbine farm. The mathematical formulation and basic procedure for predicting power output of a stand-alone turbine 1 is presented, which includes several highly nonlinear terms. In order to facilitate the computation and utilize the formulation for predicting power output from a turbine farm, a simplified relationship between turbine distribution and turbine farm energy output is derived. A case study is then conducted by applying the numerical procedure to predict the energy output of the farms. Various scenarios are implemented according to the environmental conditions in Seymour Narrows, British Columbia, Canada. Additionally, energy cost results are presented as an extension. Index Terms—renewable energy, in-stream turbine, tidal current, tidal power, vertical axis turbine, farm system modeling, in-stream tidal turbine farm 1 A stand-alone turbine refers to a turbine around which there is no other turbine that might potentially affect the performance of this turbine.

  6. System and method for cancelling the effects of stray magnetic fields from the output of a variable reluctance sensor

    DOE Patents [OSTI]

    Chen, Chingchi (Ann Arbor, MI); Degner, Michael W. (Farmington Hills, MI)

    2002-11-19T23:59:59.000Z

    A sensor system for sensing a rotation of a sensing wheel is disclosed. The sensor system has a sensing coil in juxtaposition with the sensing wheel. Moreover, the sensing coil has a sensing coil output signal indicative of the rotational speed of the sensing wheel. Further, a cancellation coil is located remotely from the sensing coil and connected in series therewith. Additionally, the cancellation coil has a cancellation coil output signal indicative of an environmental disturbance which is effecting the sensing coil output signal. The cancellation coil output signal operates to cancel the effects of the environmental disturbance on the sensing coil output signal.

  7. A combined compensation method for the output voltage of an insulated core transformer power supply

    SciTech Connect (OSTI)

    Yang, L.; Yang, J., E-mail: jyang@mail.hust.edu.cn; Liu, K. F.; Qin, B.; Chen, D. Z. [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2014-06-15T23:59:59.000Z

    An insulated core transformer (ICT) power supply is an ideal high-voltage generator for irradiation accelerators with energy lower than 3 MeV. However, there is a significant problem that the structure of the segmented cores leads to an increase in the leakage flux and voltage differences between rectifier disks. A high level of consistency in the output of the disks helps to achieve a compact structure by improving the utilization of both the rectifier components and the insulation distances, and consequently increase the output voltage of the power supply. The output voltages of the disks which are far away from the primary coils need to be improved to reduce their inhomogeneity. In this study, by investigating and comparing the existing compensation methods, a new combined compensation method is proposed, which increases the turns on the secondary coils and employs parallel capacitors to improve the consistency of the disks, while covering the entire operating range of the power supply. This method turns out to be both feasible and effective during the development of an ICT power supply. The non-uniformity of the output voltages of the disks is less than 3.5% from no-load to full-load, and the power supply reaches an output specification of 350 kV/60 mA.

  8. Industry Supply Chain Development (Ohio)

    Broader source: Energy.gov [DOE]

    Supply Chain Development programs are focused on targeted industries that have significant growth opportunities for Ohio's existing manufacturing sector from emerging energy resources and...

  9. FAQS Reference Guide – Industrial Hygiene

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the November 2007 edition of DOE-STD-1138-2007, Industrial Hygiene Functional Area Qualification Standard.

  10. China's Nuclear Industry After Fukushima

    E-Print Network [OSTI]

    YUAN, Jingdong

    2013-01-01T23:59:59.000Z

    s Nuclear Industry After Fukushima Jingdong YUAN SummaryT he March 2011 Fukushima nuclear accident has had aand speedy responses to Fukushima-like and other unexpected

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.3.

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.3..

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3. Revenue

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.8.

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.8.9.

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. Net

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. Net

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. NetB.

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. NetB.A.

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6. Net

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6. Net7.

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9. Net

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.1.

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.1.2.

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5. Net

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5. Net6.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8. Net

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.0.

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.0.1.

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful4.

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful4..

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.5.

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.5.6.

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer Capacity

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9. Total

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.2.

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.2.3.

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B. Coal:

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.E.

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.E.F.

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B. Petroleum

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B. PetroleumC.

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E. Petroleum

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.D.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.D.E.

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:B.

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:B.C.

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE. Natural

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D. Wood

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.A.

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.A.B.

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill Gas:

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill Gas:E.

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.B.

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.B.C.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. Biogenic

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. BiogenicF.

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. BiogenicF.D.

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other Waste

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.1.

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.1.2.

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1. Stocks

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1. Stocks2

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4.

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..3.

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..3.4.

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost, and

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost, and7

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,9.

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,9.0.

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.5.

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.5.6.

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost of

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost0.

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost0.1.

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.5.

  20. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.5.1.

  1. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.

  2. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity and

  3. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity and4.

  4. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity

  5. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.

  6. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.2.

  7. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.2.3.

  8. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.

  9. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5. Demand-Side

  10. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.

  11. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy

  12. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy8.

  13. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy8.9.

  14. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.

  15. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1. Sulfur

  16. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1. Sulfur2.

  17. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.

  18. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.4.

  19. SAS Output

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.4.5. Unit

  20. SAS Output

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3. Revenue