National Library of Energy BETA

Sample records for barrels actual base

  1. U.S. Natural Gas Plant Liquids, Reserves Based Production (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Based Production (Million Barrels) U.S. Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 580 1980's 572 580 564 568 597 585 569 585 592 566 1990's 574 601 626 635 634 646 688 690 655 697 2000's 710 675 677 611 645 614 629 650 667 714 2010's 745 784 865 931 1,124 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  2. Secretary Bodman Announces Sale of 11 Million Barrels of Crude...

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

    Sale of 11 Million Barrels of Crude Oil from the Nation's Strategic Petroleum Reserve Secretary Bodman Announces Sale of 11 Million Barrels of Crude Oil from the Nation's Strategic ...

  3. Kansas Natural Gas Plant Liquids, Proved Reserves (Million Barrels...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Proved Reserves (Million Barrels) Kansas Natural Gas Plant Liquids, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  4. Texas Crude Oil + Lease Condensate Proved Reserves (Million Barrels...

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Texas Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 ...

  5. Table 4. Total Petroleum Consumption, Projected vs. Actual

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

    Total Petroleum Consumption, Projected vs. Actual" "Projected" " (million barrels)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",6449.55,6566.35,6643,6723.3,6810.9,6880.25,6956.9,7059.1,7124.8,7205.1,7296.35,7376.65,7446,7522.65,7595.65,7665,7712.45,7774.5 "AEO

  6. Table 6. Petroleum Net Imports, Projected vs. Actual

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

    Petroleum Net Imports, Projected vs. Actual" "Projected" " (million barrels)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",2934.6,3201.05,3361.65,3504,3657.3,3737.6,3879.95,3993.1,4098.95,4212.1,4303.35,4398.25,4474.9,4540.6,4584.4,4639.15,4668.35,4672 "AEO

  7. New Mexico Natural Gas Liquids Lease Condensate, Reserves Based...

    Gasoline and Diesel Fuel Update (EIA)

    Reserves Based Production (Million Barrels) New Mexico Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

  8. Kansas Natural Gas Liquids Lease Condensate, Reserves Based Production...

    Gasoline and Diesel Fuel Update (EIA)

    Reserves Based Production (Million Barrels) Kansas Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

  9. BARRELING THROUGH THE VACUUM OF SPACE at

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

    1663 October 2015 1663 October 2015 19 BARRELING THROUGH THE VACUUM OF SPACE at over 17,000 miles per hour, Earth's reflection glinting off its solar panels, the satellite is fiercely efficient and mission driven. It has hard edges and cold surfaces. It is brand new and state-of-the-art. It is an engineering masterpiece. And it's roughly the size of an electric pencil sharpener. Satellites are generally thought of as hulking beasts of instrumentation. They are billion-dollar machines capable of

  10. Utah Crude Oil + Lease Condensate Proved Reserves (Million Barrels...

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

    Utah Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 ... Release Date: 11192015 Next Release Date: 12312016 Referring Pages: Crude Oil plus ...

  11. Ohio Crude Oil + Lease Condensate Proved Reserves (Million Barrels...

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

    Ohio Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 ... Release Date: 11192015 Next Release Date: 12312016 Referring Pages: Crude Oil plus ...

  12. Beam test of the SDC barrel EM calorimeter test module

    SciTech Connect (OSTI)

    Balka, L.; Guarino, V.; Hill, N.

    1994-05-01

    The SDC barrel electromagnetic calorimeter test module was exposed to beams of high energy pions and electrons in the MP9 test beam at Fermilab in the fall of 1991. Data were collected on resolution, light yield, signal timing and hermiticity. These data demonstrated that the design met the specifications for the barrel electromagnetic calorimeter of the Solenoidal Detector collaboration (SDC).

  13. Modeling of gun barrel surface erosion: Historic perspective

    SciTech Connect (OSTI)

    Buckingham, A.C.

    1996-08-01

    Results and interpretations of numerical simulations of some dominant processes influencing gun barrel propellant combustion and flow-induced erosion are presented. Results include modeled influences of erosion reduction techniques such as solid additives, vapor phase chemical modifications, and alteration of surface solid composition through use of thin coatings. Precedents and historical perspective are provided with predictions from traditional interior ballistics compared to computer simulations. Accelerating reactive combustion flow, multiphase and multicomponent transport, flow-to-surface thermal/momentum/phase change/gas-surface chemical exchanges, surface and micro-depth subsurface heating/stress/composition evolution and their roles in inducing surface cracking, spall, ablation, melting, and vaporization are considered. Recognition is given to cyclic effects of previous firing history on material preconditioning. Current perspective and outlook for future are based on results of a US Army-LLNL erosion research program covering 7 y in late 1970s. This is supplemented by more recent research on hypervelocity electromagnetic projectile launchers.

  14. Table 3b. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual

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

    b. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual" "Projected Price in Nominal Dollars" " (nominal dollars per barrel)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO

  15. Small arms mini-fire control system: fiber-optic barrel deflection sensor

    Office of Scientific and Technical Information (OSTI)

    (Conference) | SciTech Connect Conference: Small arms mini-fire control system: fiber-optic barrel deflection sensor Citation Details In-Document Search Title: Small arms mini-fire control system: fiber-optic barrel deflection sensor Traditionally the methods to increase firearms accuracy, particularly at distance, have concentrated on barrel isolation (free floating) and substantial barrel wall thickening to gain rigidity. This barrel stiffening technique did not completely eliminate barrel

  16. Table 4. Total Petroleum Consumption, Projected vs. Actual

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

    Total Petroleum Consumption, Projected vs. Actual Projected (million barrels) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 6450 6566 6643 6723 6811 6880 6957 7059 7125 7205 7296 7377 7446 7523 7596 7665 7712 7775 AEO 1995 6398 6544 6555 6676 6745 6822 6888 6964 7048 7147 7245 7337 7406 7472 7537 7581 7621 AEO 1996 6490 6526 6607 6709 6782 6855 6942 7008 7085 7176 7260 7329 7384 7450 7501 7545 7581 7632 7676 AEO 1997 6636 6694

  17. Table 5. Domestic Crude Oil Production, Projected vs. Actual

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

    Domestic Crude Oil Production, Projected vs. Actual" "Projected" " (million barrels)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",2507.55,2372.5,2255.7,2160.8,2087.8,2022.1,1952.75,1890.7,1850.55,1825,1799.45,1781.2,1766.6,1759.3,1777.55,1788.5,1806.75,1861.5 "AEO

  18. Table 5. Domestic Crude Oil Production, Projected vs. Actual

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

    Domestic Crude Oil Production, Projected vs. Actual Projected (million barrels) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 2508 2373 2256 2161 2088 2022 1953 1891 1851 1825 1799 1781 1767 1759 1778 1789 1807 1862 AEO 1995 2402 2307 2205 2095 2037 1967 1953 1924 1916 1905 1894 1883 1887 1887 1920 1945 1967 AEO 1996 2387 2310 2248 2172 2113 2062 2011 1978 1953 1938 1916 1920 1927 1949 1971 1986 2000 2018 2055 AEO 1997 2362 2307

  19. Table 6. Petroleum Net Imports, Projected vs. Actual Projected

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

    Petroleum Net Imports, Projected vs. Actual Projected (million barrels) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 2935 3201 3362 3504 3657 3738 3880 3993 4099 4212 4303 4398 4475 4541 4584 4639 4668 4672 AEO 1995 2953 3157 3281 3489 3610 3741 3818 3920 4000 4103 4208 4303 4362 4420 4442 4460 4460 AEO 1996 3011 3106 3219 3398 3519 3679 3807 3891 3979 4070 4165 4212 4260 4289 4303 4322 4325 4347 4344 AEO 1997 3099 3245 3497

  20. Biomass 2011: Replace the Whole Barrel, Supply the Whole Market |

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

    Department of Energy 1: Replace the Whole Barrel, Supply the Whole Market Biomass 2011: Replace the Whole Barrel, Supply the Whole Market The New Horizons of Bioenergy Biomass 2011 July 26-27, 2011 Gaylord National Resort and Convention Center 201 Waterfront Street National Harbor, MD 20745 Thank you to everyone who attended and participated to help make Biomass 2011 a remarkable success. More than 600 speakers, moderators, sponsors, exhibitors, and attendees were able to listen to

  1. Emissions of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans from the open burning of household waste in barrels

    SciTech Connect (OSTI)

    Lemieux, P.M.; Lutes, C.C.; Abbott, J.A.; Aldous, K.M.

    2000-02-01

    Backyard burning of household waste in barrels is a common waste disposal practice for which pollutant emissions have not been well characterized. This study measured the emissions of several pollutants, including polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDDs/PCDFs), from burning mixtures designed to simulate waste generated by a recycling and a nonrecycling family in a 208-L (55-gal) burn barrel at the EPA's Open Burning Test Facility. This paper focuses on the PCDD/PCDF emissions and discusses the factors influencing PCDD/PCDF formation for different test burns. Four test burns were made in which the amount of waste placed in the barrel varied from 6.4 to 13.6 kg and the amount actually burned varied from 46.6% to 68.1%. Emissions of total PCDDs/PCDFs ranged between 0.0046 and 0.48 mg/kg of waste burned. Emissions are also presented in terms of 2,3,7,8-TCDD toxic equivalents. Emissions of PCDDs/PCDFs appear to correlate with both copper and hydrochloric acid emissions. The results of this study indicate that backyard burning emits more PCDDs/PCDFs on a mass of refuse burned basis than various types of municipal waste combustors (MWCs). Comparison of burn barrel emissions to emissions from a hypothetical modern MWC equipped with high-efficiency flue gas cleaning technology indicates that about 2--40 households burning their trash daily in barrels can produce average PCDD/PCDF emissions comparable to a 182,000 kg/day (200 ton/day) MWC facility. This study provides important data on a potentially significant source of emissions of PCDDs/PCDFs.

  2. Simulation and testing of pyramid and barrel vault skylights

    SciTech Connect (OSTI)

    McGowan, A.G.; Desjarlais, A.O.; Wright, J.L.

    1998-10-01

    The thermal performance of fenestration in commercial buildings can have a significant effect on building loads--yet there is little information on the performance of these products. With this in mind, ASHRAE TC 4.5, Fenestration, commissioned a research project involving test and simulation of commercial fenestration systems. The objectives of ASHRAE Research Project 877 were: to evaluate the thermal performance (U-factors) of commonly used commercial glazed roof and wall assemblies; to obtain a better fundamental understanding of the heat transfer processes that occur in these specialty fenestration products; to develop correlations for natural-convection heat transfer in complex glazing cavities; to develop a methodology for evaluating complex fenestration products, suitable for inclusion in ASHRAE Standard 142P (ASHRAE 1996); and to generate U-factors for common commercial fenestration products, suitable for inclusion in the ASHRAE Handbook--Fundamentals. This paper describes testing and simulation of pyramid and barrel vault skylight specimens and provides guidelines for modeling these systems based on the validated results.

  3. Ohio Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Ohio Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 0 17 2000's 10 6 8 8 7 7 8 8 7 5 2010's 1 1 2 7 3 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves of Crude Oil

  4. Oklahoma Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Oklahoma Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 98 80 2000's 111 109 105 92 92 101 90 118 129 138 2010's 143 244 279 292 444 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved

  5. Michigan Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Michigan Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 3 1 2000's 4 6 4 14 10 17 15 2 9 6 2010's 0 0 0 4 3 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves of

  6. Montana Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Montana Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 6 83 2000's 36 43 65 79 104 88 91 90 50 42 2010's 74 59 95 104 155 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing

  7. New Mexico Crude Oil + Lease Condensate Proved Reserves (Million Barrels)

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

    + Lease Condensate Proved Reserves (Million Barrels) New Mexico Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 780 2010's 922 960 1,069 1,277 1,558 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate Proved Reserves, as of

  8. New Mexico Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) New Mexico Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 97 157 2000's 91 161 146 133 142 171 159 147 136 149 2010's 180 185 232 314 489 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages:

  9. Arkansas Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Arkansas Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 2 5 2000's 7 4 5 2 3 2 1 0 0 0 2010's 1 0 11 10 8 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves of Crude

  10. Colorado Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Colorado Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 26 30 2000's 49 44 56 61 62 74 102 122 123 42 2010's 180 208 283 607 765 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved

  11. Florida Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Florida Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 6 12 2000's 9 7 7 6 6 2 1 12 0 2 2010's 2 4 3 9 6 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves of Crude

  12. Illinois Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Illinois Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 4 11 2000's 4 15 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves of Crude Oil Illinois Proved

  13. Kansas Crude Oil + Lease Condensate Proved Reserves (Million Barrels)

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

    + Lease Condensate Proved Reserves (Million Barrels) Kansas Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 264 2010's 302 350 382 390 451 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate Proved Reserves, as of Dec. 31

  14. Kansas Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Kansas Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 11 12 2000's 13 21 23 18 11 16 17 9 11 3 2010's 2 4 6 11 34 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves

  15. Kentucky Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Kentucky Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 0 0 2000's 0 0 4 4 5 5 0 0 1 3 2010's 0 0 0 1 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves of Crude

  16. Utah Natural Gas Liquids Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Million Barrels) Utah Natural Gas Liquids Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 59 1980's 127 277 2000's 108 116 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Natural Gas Liquids Proved Reserves as of Dec. 31 Utah Natural Gas Liquids Proved Reserves

  17. Wyoming Natural Gas Liquids Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Million Barrels) Wyoming Natural Gas Liquids Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 285 1980's 341 384 2000's 1,032 1,121 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Natural Gas Liquids Proved Reserves as of Dec. 31 Wyoming Natural Gas Liquids Proved

  18. Utah Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Utah Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 36 58 2000's 91 100 91 76 61 52 164 174 140 235 2010's 257 258 368 312 261 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved

  19. Wyoming Crude Oil + Lease Condensate Proved Reserves (Million Barrels)

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

    + Lease Condensate Proved Reserves (Million Barrels) Wyoming Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 855 2010's 823 919 932 955 1,137 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate Proved Reserves, as of Dec. 31

  20. Wyoming Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Reserves in Nonproducing Reservoirs (Million Barrels) Wyoming Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 31 52 2000's 63 74 69 61 45 249 258 208 162 144 2010's 152 188 233 219 362 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved

  1. Apparatus and method for quantitative assay of samples of transuranic waste contained in barrels in the presence of matrix material

    DOE Patents [OSTI]

    Caldwell, J.T.; Herrera, G.C.; Hastings, R.D.; Shunk, E.R.; Kunz, W.E.

    1987-08-28

    Apparatus and method for performing corrections for matrix material effects on the neutron measurements generated from analysis of transuranic waste drums using the differential-dieaway technique. By measuring the absorption index and the moderator index for a particular drum, correction factors can be determined for the effects of matrix materials on the ''observed'' quantity of fissile and fertile material present therein in order to determine the actual assays thereof. A barrel flux monitor is introduced into the measurement chamber to accomplish these measurements as a new contribution to the differential-dieaway technology. 9 figs.

  2. U.S. crude oil production expected to top 8 million barrels per...

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

    U.S. crude oil production expected to top 8 million barrels per day, highest output since 1988 U.S. crude oil production in 2014 is now expected to top 8 million barrels per day ...

  3. U.S. monthly oil production tops 8 million barrels per day for...

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

    barrels per day for the first time since 1988 Estimated U.S. crude oil production in November topped 8 million barrels per day for the first time in 25 years, according to the ...

  4. U.S. Natural Gas Total Liquids Extracted (Thousand Barrels)

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

    Total Liquids Extracted (Thousand Barrels) U.S. Natural Gas Total Liquids Extracted (Thousand Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 569,968 599,518 584,160 571,256 587,502 594,306 569,913 1990's 573,054 602,734 626,320 634,481 635,983 649,149 689,314 690,999 668,011 686,862 2000's 721,895 682,873 681,646 622,291 657,032 619,884 637,635 658,291 673,677 720,612 2010's 749,095 792,481 873,563 937,591 1,124,416 - = No Data Reported; -- = Not

  5. Utah Natural Gas Plant Liquids, Reserves Based Production (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 48,965 46,151 46,733 1970's 42,781 42,418 39,474 42,715 50,522 55,354 57,416 60,696 58,416 58,605 1980's 87,766 91,191 94,255 63,158 74,698 83,405 90,013 87,158 101,372 120,089 1990's 145,875 144,817 171,293 225,401 270,858 241,290 250,767 257,139 277,340 262,614 2000's 269,285 283,913 274,739 268,058 277,969 301,223 348,320 376,409 433,566 444,162 2010's 432,045 457,525 490,393 470,863 453,207 422,423

    Year

  6. New Mexico Natural Gas Plant Liquids, Reserves Based Production...

    Gasoline and Diesel Fuel Update (EIA)

    Reserves Based Production (Million Barrels) New Mexico Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  7. Kansas Natural Gas Plant Liquids, Reserves Based Production ...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Reserves Based Production (Million Barrels) Kansas Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

  8. Nebraska Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 0 0 2000's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves of Crude Oil Nebraska Proved Nonproducing Reserves

  9. New York Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves of Crude Oil New York Proved Nonproducing Reserves

  10. Indiana Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Indiana Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's NA NA 0 0 2000's 0 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Proved Nonproducing Reserves of Crude Oil Indiana Proved Nonproducing Reserves

  11. Master plate production for the tile calorimeter extended barrel modules.

    SciTech Connect (OSTI)

    Guarino, V.J.; Hill, N.; Petereit, E.; Price, L.E.; Proudfoot, J.; Wood, K.

    1999-03-10

    Approximately 41,000 master plates (Fig. 1) are required for the Extended Barrel Hadronic Calorimeter for the ATLAS experiment at the LHC. Early in the R&D program associated with the detector, it was recognized that the fabrication of these steel laminations was a significant issue, both in terms of the cost to produce these high precision formed plates, as well as the length of time required to produce all plates for the calorimeter. Two approaches were given serious consideration: laser cutting and die stamping. The Argonne group was a strong supporter of the latter approach and in late 1995 initiated an R&D program to demonstrate the feasibility and cost effectiveness of die stamping these plates by constructing a die and stamping approximately 2000 plates for use in construction of three full size prototype modules. This was extremely successful and die stamping was selected by the group for production of these plates. When the prototype die was constructed it was matched to the calorimeter envelope at that time. This subsequently changed. However with some minor adjustments in the design envelope and a small compromise in terms of instrumented volume, it became possible to use this same die for the production of all master plates for the Tile Calorimeter. Following an extensive series of discussions and an evaluation of the performance of the stamping presses available to our collaborators in Europe, it was decided to ship the US die to CERN for use in stamping master plates for the barrel section of the calorimeter. This was done under the supervision of CERN and JINR, Dubna, and carried out at the TATRA truck plant at Koprivinice, Czech Republic. It was a great success. Approximately 41,000 plates were stamped and fully met specification. Moreover, the production time was significantly reduced by avoiding the need of constructing and then qualifying a second die for use in Europe. This also precluded small geometrical differences between the barrel and extended barrel plates (and therefore submodules) being an issue, with the result that standard submodules are fully exchangeable between the two types of module.

  12. Replacing the Whole BarrelTo Reduce U.S. Dependence on Oil | Department of

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

    Energy Replacing the Whole BarrelTo Reduce U.S. Dependence on Oil Replacing the Whole BarrelTo Reduce U.S. Dependence on Oil Converting domestic biomass into affordable fuels, products, and power supports our national strategy to diversify energy resources and reduce dependence on imported oil. PDF icon replacing_barrel_overview.pdf More Documents & Publications Thermochemical Conversion: Using Heat and Catalysis to Make Biofuels and Bioproducts Bioenergy Technologies Office Conversion

  13. Secretary Bodman Announces Sale of 11 Million Barrels of Crude Oil from the

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

    Nation's Strategic Petroleum Reserve | Department of Energy Sale of 11 Million Barrels of Crude Oil from the Nation's Strategic Petroleum Reserve Secretary Bodman Announces Sale of 11 Million Barrels of Crude Oil from the Nation's Strategic Petroleum Reserve September 14, 2005 - 10:21am Addthis WASHINGTON, DC - Secretary Samuel W. Bodman announced that the Department of Energy has approved bids for the sale of 11 million barrels of crude oil from the Strategic Petroleum Reserve (SPR).

  14. The How's and Why's of Replacing the Whole Barrel | Department of Energy

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

    The How's and Why's of Replacing the Whole Barrel The How's and Why's of Replacing the Whole Barrel October 19, 2011 - 4:09pm Addthis A 42-U.S. gallon barrel of crude oil yields about 45 gallons of petroleum products. Source: Energy Information Administration, “Oil: Crude Oil and Petroleum Products Explained” and Annual Energy Outlook 2009 (Updated February 2010). A 42-U.S. gallon barrel of crude oil yields about 45 gallons of petroleum products. Source: Energy Information

  15. An analysis of increasing the size of the strategic petroleum reserve to one billion barrels

    SciTech Connect (OSTI)

    Not Available

    1990-01-01

    The Department of Energy's Office of Energy Emergency Policy and Evaluation requested that the Energy Information Administration complete an analysis of the proposed expansion in the Strategic Petroleum Reserve (SPR) from its currently planned size of 750 million barrels to 1000 million barrels. Because the SPR contains only 580 million barrels at this point in time, the benefits and costs of increasing the SPR from 600 to 750 million barrels were also estimated. This report documents the assumptions, methodology, and results of the analysis. 17 figs., 15 tabs.

  16. Table 3a. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual

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

    a. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual" "Projected Price in Constant Dollars" " (constant dollars per barrel in ""dollar year"" specific to each AEO)" ,"AEO $ Year",1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",1992,16.69,16.42999,16.9899,17.66,18.28,19.0599,19.89,20.72,21.65,22.61,23.51,24.29,24.9,25.6,26.3,27,27.64,28.16

  17. How People Actually Use Thermostats

    SciTech Connect (OSTI)

    Meier, Alan; Aragon, Cecilia; Hurwitz, Becky; Mujumdar, Dhawal; Peffer, Therese; Perry, Daniel; Pritoni, Marco

    2010-08-15

    Residential thermostats have been a key element in controlling heating and cooling systems for over sixty years. However, today's modern programmable thermostats (PTs) are complicated and difficult for users to understand, leading to errors in operation and wasted energy. Four separate tests of usability were conducted in preparation for a larger study. These tests included personal interviews, an on-line survey, photographing actual thermostat settings, and measurements of ability to accomplish four tasks related to effective use of a PT. The interviews revealed that many occupants used the PT as an on-off switch and most demonstrated little knowledge of how to operate it. The on-line survey found that 89% of the respondents rarely or never used the PT to set a weekday or weekend program. The photographic survey (in low income homes) found that only 30% of the PTs were actually programmed. In the usability test, we found that we could quantify the difference in usability of two PTs as measured in time to accomplish tasks. Users accomplished the tasks in consistently shorter times with the touchscreen unit than with buttons. None of these studies are representative of the entire population of users but, together, they illustrate the importance of improving user interfaces in PTs.

  18. Tapered laser rods as a means of minimizing the path length of trapped barrel mode rays

    DOE Patents [OSTI]

    Beach, Raymond J.; Honea, Eric C.; Payne, Stephen A.; Mercer, Ian; Perry, Michael D.

    2005-08-30

    By tapering the diameter of a flanged barrel laser rod over its length, the maximum trapped path length of a barrel mode can be dramatically reduced, thereby reducing the ability of the trapped spontaneous emission to negatively impact laser performance through amplified spontaneous emission (ASE). Laser rods with polished barrels and flanged end caps have found increasing application in diode array end-pumped laser systems. The polished barrel of the rod serves to confine diode array pump light within the rod. In systems utilizing an end-pumping geometry and such polished barrel laser rods, the pump light that is introduced into one or both ends of the laser rod, is ducted down the length of the rod via the total internal reflections (TIRs) that occur when the light strikes the rod's barrel. A disadvantage of using polished barrel laser rods is that such rods are very susceptible to barrel mode paths that can trap spontaneous emission over long path lengths. This trapped spontaneous emission can then be amplified through stimulated emission resulting in a situation where the stored energy available to the desired lasing mode is effectively depleted, which then negatively impacts the laser's performance, a result that is effectively reduced by introducing a taper onto the laser rod.

  19. New Mexico--East Natural Gas Plant Liquids, Reserves Based Production...

    Gasoline and Diesel Fuel Update (EIA)

    Reserves Based Production (Million Barrels) New Mexico--East Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  20. New Mexico--West Natural Gas Plant Liquids, Reserves Based Production...

    Gasoline and Diesel Fuel Update (EIA)

    Reserves Based Production (Million Barrels) New Mexico--West Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  1. Caustic-Side Solvent Extraction: Prediction of Cesium Extraction for Actual Wastes and Actual Waste Simulants

    SciTech Connect (OSTI)

    Delmau, L.H.; Haverlock, T.J.; Sloop, F.V., Jr.; Moyer, B.A.

    2003-02-01

    This report presents the work that followed the CSSX model development completed in FY2002. The developed cesium and potassium extraction model was based on extraction data obtained from simple aqueous media. It was tested to ensure the validity of the prediction for the cesium extraction from actual waste. Compositions of the actual tank waste were obtained from the Savannah River Site personnel and were used to prepare defined simulants and to predict cesium distribution ratios using the model. It was therefore possible to compare the cesium distribution ratios obtained from the actual waste, the simulant, and the predicted values. It was determined that the predicted values agree with the measured values for the simulants. Predicted values also agreed, with three exceptions, with measured values for the tank wastes. Discrepancies were attributed in part to the uncertainty in the cation/anion balance in the actual waste composition, but likely more so to the uncertainty in the potassium concentration in the waste, given the demonstrated large competing effect of this metal on cesium extraction. It was demonstrated that the upper limit for the potassium concentration in the feed ought to not exceed 0.05 M in order to maintain suitable cesium distribution ratios.

  2. DOE to Sell 35,000 Barrels of Oil from the Northeast Home Heating Oil

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

    Reserve | Department of Energy Sell 35,000 Barrels of Oil from the Northeast Home Heating Oil Reserve DOE to Sell 35,000 Barrels of Oil from the Northeast Home Heating Oil Reserve May 24, 2007 - 4:16pm Addthis WASHINGTON, DC - The U.S. Department of Energy announced today that it will sell approximately 35,000 barrels of home heating oil from the Northeast Home Heating Oil Reserve (NEHHOR). The Reserve's current 5-year storage contracts expire on September 30, 2007 and market conditions have

  3. EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day

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

    EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day The forecast for U.S. crude oil production keeps going higher. The U.S. Energy Information Administration revised upward its projection for crude oil output in 2013 by 70,000 barrels per day and for next year by 190,000 barrels per day. U.S. oil production is now on track to average 7.5 million barrels per day this year and rise to 8.4 million barrels per day in 2014, according to EIA's latest monthly forecast.

  4. Replacing the Whole BarrelTo Reduce U.S. Dependence on Oil

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

    Replacing the Whole Barrel To Reduce U.S. Dependence on Oil July 2013 Biofuels are ... We've got to develop every source of American energy-not just oil and gas, but wind power ...

  5. U.S. crude oil production expected to top 9 million barrels per...

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

    In its new forecast, the U.S. Energy Information Administration said domestic crude oil production should average 9.3 million barrels per day in 2015. On-shore production in the ...

  6. U.S. crude oil production expected to top 9 million barrels per...

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

    In its new short-term forecast, the U.S. Energy Information Administration said monthly average oil production is on track to surpass 9 million barrels per day in December for the ...

  7. U.S. monthly oil production tops 8 million barrels per day for...

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

    high of 9.6 million barrels per day set in 1970. Most of the oil production growth will come from increased drilling in the shale formations in North Dakota, Texas and New Mexico. ...

  8. U.S. monthly oil production tops 8 million barrels per day for...

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

    monthly oil output in Texas recently topped 3 million barrels per day for the first time since the late 1970s and North Dakota's oil production reached a record 1 million ...

  9. U.S. monthly oil production tops 8 million barrels per day for...

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

    monthly crude oil production highest in nearly 26 year Estimated U.S. crude oil production in May averaged almost 8.4 million barrels per day, the highest output for any month ...

  10. U.S. monthly oil production tops 8 million barrels per day for...

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

    to account for 91% of the growth in world oil production in 2015 The United States is expected to provide nine out of every 10 barrels of new global oil supplies in 2015. In its ...

  11. Small arms mini-fire control system: fiber-optic barrel deflection...

    Office of Scientific and Technical Information (OSTI)

    Conference: Small arms mini-fire control system: fiber-optic barrel deflection sensor Citation Details In-Document Search Title: Small arms mini-fire control system: fiber-optic ...

  12. U.S. Natural Gas Plant Liquids, Reserves Sales (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Sales (Million Barrels) U.S. Natural Gas Plant Liquids, Reserves Sales (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 906 448 458 403 442 440 931 670 282 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Natural Gas Liquids Reserves Sales

  13. Could Material Defects Actually Improve Solar Cells?

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

    Could Material Defects Actually Improve Solar Cells? Could Material Defects Actually Improve Solar Cells? March 21, 2016 Contact: Kathy Kincade, kkincade@lbl.gov, +1 510 495 2124 NRELsolarcell Scientists at the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) are using supercomputers to study what may seem paradoxical: certain defects in silicon solar cells may actually improve their performance. The findings, published January 11, 2016 in Applied Physics Letters,

  14. Table 3a. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual

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

    a. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual Projected Price in Constant Dollars (constant dollars per barrel in "dollar year" specific to each AEO) AEO $ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1992 16.69 16.43 16.99 17.66 18.28 19.06 19.89 20.72 21.65 22.61 23.51 24.29 24.90 25.60 26.30 27.00 27.64 28.16 AEO 1995 1993 14.90 16.41 16.90 17.45 18.00 18.53 19.13 19.65 20.16 20.63

  15. Table 3b. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual

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

    b. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual Projected Price in Nominal Dollars (nominal dollars per barrel) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 17.06 17.21 18.24 19.43 20.64 22.12 23.76 25.52 27.51 29.67 31.86 34.00 36.05 38.36 40.78 43.29 45.88 48.37 AEO 1995 15.24 17.27 18.23 19.26 20.39 21.59 22.97 24.33 25.79 27.27 28.82 30.38 32.14 33.89 35.85 37.97 40.28 AEO 1996 17.16 17.74 18.59

  16. Quantitative/Statistical Approach to Bullet-to-Firearm Identification with Consecutively Manufactured Barrels

    SciTech Connect (OSTI)

    Peter Striupaitis; R.E. Gaensslen

    2005-01-30

    Efforts to use objective image comparison and bullet scanning technologies to distinguish bullets from consecutively manufactured handgun barrels from two manufacturers gave mixed results. The ability of a technology to reliably distinguish between matching and non-matching bullets, where the non-matching bullets were as close in pattern to the matching ones as is probably possible, would provide evidence that the distinctions could be made ''objectively'', and independently of human eyes. That evidence is identical or very close to what seems to be needed to satisfy Daubert standards. It is fair to say that the FTI IBIS image comparison technology correctly distinguished between all the Springfield barrel bullets, and between most but not all of the HiPoint barrel bullets. In the HiPoint cases that were not distinguished 100% of the time, they would he distinguished correctly at least 83% of the time. These results, although obviously limited to the materials used in the comparisons, provide strong evidence that barrel-to-bullet matching is objectively reliable. The results with SciClops were less compelling. The results do not mean that bullet-to-barrel matching is not objectively reliable--rather, they mean that this version of the particular technology could not quite distinguish between these extremely similar yet different bullets as well as the image comparison technology did. In a number of cases, the numerical results made the correct distinctions, although they were close to one another. It is hard to say from this data that this technology differs in its ability to make distinctions between the manufacturers, because the results are very similar with both. The human examiner results were as expected. We did not expect any misidentifications, and there were not any. It would have been preferable to have a higher return rate, and thus more comparisons in the overall sample. As noted, the ''consecutively manufactured barrel exercise'' has been done before, with the same outcome.

  17. U.S. Crude Oil + Lease Condensate Reserves Acquisitions (Million Barrels)

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

    Acquisitions (Million Barrels) U.S. Crude Oil + Lease Condensate Reserves Acquisitions (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 344 2010's 1,470 1,561 1,234 1,925 2,828 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate Reserves Acquisitions

  18. U.S. Crude Oil + Lease Condensate Reserves Adjustments (Million Barrels)

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

    Adjustments (Million Barrels) U.S. Crude Oil + Lease Condensate Reserves Adjustments (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 46 2010's 188 207 137 -595 440 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate Proved Reserves

  19. U.S. Crude Oil + Lease Condensate Reserves Extensions (Million Barrels)

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

    Extensions (Million Barrels) U.S. Crude Oil + Lease Condensate Reserves Extensions (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 1,305 2010's 1,766 3,107 5,191 4,973 5,021 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate Reserves Extensions

  20. U.S. Crude Oil + Lease Condensate Reserves Sales (Million Barrels)

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

    Sales (Million Barrels) U.S. Crude Oil + Lease Condensate Reserves Sales (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 249 2010's 803 1,024 819 1,536 2,475 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate Reserves Sales

  1. Video: SuperTruck Barreling Down the Road of Sustainability | Department of

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

    Energy SuperTruck Barreling Down the Road of Sustainability Video: SuperTruck Barreling Down the Road of Sustainability May 14, 2015 - 4:30pm Addthis New Energy 101 video shows how the Energy Department's SuperTruck initiative is making Class 8 trucks more fuel efficient and less expensive to operate. | Office of Energy Efficiency and Renewable Energy video. Paul Lester Paul Lester Digital Content Specialist, Office of Public Affairs KEY FACTS SuperTruck initiative helping make Class 8

  2. U.S. Natural Gas Plant Liquids, Reserves Acquisitions (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Acquisitions (Million Barrels) U.S. Natural Gas Plant Liquids, Reserves Acquisitions (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 1,051 550 512 433 554 596 1,048 771 332 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Natural Gas Liquids Reserves Acquisitions

  3. U.S. Natural Gas Plant Liquids, Reserves Adjustments (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Adjustments (Million Barrels) U.S. Natural Gas Plant Liquids, Reserves Adjustments (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 64 1980's 153 231 299 849 -123 426 367 231 11 -277 1990's -83 233 225 102 43 192 474 -15 -361 99 2000's -83 -429 62 -338 273 -89 173 -139 76 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date:

  4. U.S. Natural Gas Plant Liquids, Reserves Extensions (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Extensions (Million Barrels) U.S. Natural Gas Plant Liquids, Reserves Extensions (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 364 1980's 418 542 375 321 348 337 263 213 268 259 1990's 299 189 190 245 314 432 451 535 383 313 2000's 645 717 612 629 734 863 924 1,030 956 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date:

  5. ,"Louisiana--State Offshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--State Offshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  6. ,"Louisiana--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  7. ,"Lower 48 States Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Lower 48 States Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  8. ,"Michigan Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  9. ,"Miscellaneous States Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Miscellaneous States Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  10. ,"Montana Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  11. ,"Nebraska Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  12. ,"New Mexico Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  13. ,"New Mexico Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel

  14. ,"New Mexico Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  15. ,"New Mexico Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  16. ,"New Mexico--East Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico--East Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  17. ,"New Mexico--West Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico--West Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  18. ,"North Dakota Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  19. ,"Oklahoma Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  20. ,"Oklahoma Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  1. ,"Texas State Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas State Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  2. ,"Texas--State Offshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--State Offshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  3. ,"Texas--State Offshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--State Offshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  4. ,"Texas--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  5. ,"U.S. Federal Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Federal Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  6. ,"U.S. Federal Offshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Federal Offshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  7. ,"U.S. Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  8. ,"U.S. Total Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Total Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel

  9. ,"Utah Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  10. ,"Wyoming Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  11. ,"Alabama Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  12. ,"Alaska Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel

  13. ,"Arkansas Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  14. ,"Arkansas Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  15. ,"Arkansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  16. ,"Calif--Coastal Region Onshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Calif--Coastal Region Onshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  17. ,"California - Coastal Region Onshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California - Coastal Region Onshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  18. ,"California Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  19. ,"California Federal Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Federal Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  20. ,"California State Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California State Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  1. ,"California--State Offshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--State Offshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  2. ,"California--State Offshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--State Offshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  3. ,"California--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  4. ,"Colorado Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  5. ,"Colorado Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  6. ,"Colorado Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  7. ,"Federal Offshore--California Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--California Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  8. ,"Florida Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  9. ,"Florida Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  10. ,"Florida Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  11. ,"Illinois Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  12. ,"Indiana Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  13. ,"Kansas Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  14. ,"Kansas Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  15. ,"Kansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  16. ,"Kentucky Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  17. ,"Kentucky Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  18. ,"Kentucky Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  19. ,"Louisiana Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  20. ,"Louisiana State Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana State Offshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  1. ,"Louisiana--North Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--North Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  2. ,"Louisiana--North Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--North Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  3. ,"Louisiana--South Onshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--South Onshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  4. ,"Louisiana--South Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--South Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  5. ,"Louisiana--South Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--South Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  6. ,"Louisiana--State Offshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--State Offshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  7. DOE - Office of Legacy Management -- Queen City Barrel Co - OH...

    Office of Legacy Management (LM)

    Year: 1987 OH.41-1 Site Operations: Cleaned and reconditioned 30- and 55-gallon drums. OH.41-2 OH.41-3 Site Disposition: Eliminated - Based upon limited scope of...

  8. U.S. Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Million Barrels) U.S. Natural Gas Plant Liquids, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 6,615 1980's 6,728 7,068 7,221 7,901 7,643 7,944 8,165 8,147 8,238 7,769 1990's 7,586 7,464 7,451 7,222 7,170 7,399 7,823 7,973 7,524 7,906 2000's 8,345 7,993 7,994 7,459 7,928 8,165 8,472 9,143 9,275 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  9. U.S. Total Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) U.S. Total Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 3,474 3,755 4,147 4,206 2000's 4,019 5,195 5,271 5,580 5,143 5,691 5,174 5,455 5,400 6,015 2010's 6,980 9,049 11,884 13,200 14,816 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  10. Fact #676: May 23, 2011 U.S. Refiners Produce about 19 Gallons of Gasoline from a Barrel of Oil

    Broader source: Energy.gov [DOE]

    A standard U.S. barrel contains 42 gallons of crude oil which yields about 44 gallons of petroleum products. The additional 2 gallons of petroleum products come from refiner gains which result in...

  11. FY 2013 Real Property Deferred, Actual, and Required Maintenance...

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

    Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY 2013 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement PDF icon FY ...

  12. FY 2012 Real Property Deferred, Actual, and Required Maintenance...

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

    Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY 2012 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement PDF icon FY ...

  13. Table 13. Coal Production, Projected vs. Actual

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

    Coal Production, Projected vs. Actual" "Projected" " (million short tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",999,1021,1041,1051,1056,1066,1073,1081,1087,1098,1107,1122,1121,1128,1143,1173,1201,1223 "AEO 1995",,1006,1010,1011,1016,1017,1021,1027,1033,1040,1051,1066,1076,1083,1090,1108,1122,1137 "AEO

  14. Table 22. Energy Intensity, Projected vs. Actual

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

    Energy Intensity, Projected vs. Actual" "Projected" " (quadrillion Btu / $Billion 2005 Chained GDP)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",10.89145253,10.73335719,10.63428655,10.48440125,10.33479508,10.20669515,10.06546105,9.94541493,9.822393757,9.707148466,9.595465524,9.499032573,9.390723436,9.29474735,9.185496812,9.096176848,9.007677565,8.928276581 "AEO

  15. ,"California--Coastal Region Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Coastal Region Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--Coastal Region Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release

  16. ,"California--Los Angeles Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Los Angeles Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--Los Angeles Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release

  17. ,"California--San Joaquin Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    San Joaquin Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--San Joaquin Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release

  18. Precise mapping of the magnetic field in the CMS barrel yoke using cosmic rays

    SciTech Connect (OSTI)

    Chatrchyan, S.; et al.,

    2010-03-01

    The CMS detector is designed around a large 4 T superconducting solenoid, enclosed in a 12000-tonne steel return yoke. A detailed map of the magnetic field is required for the accurate simulation and reconstruction of physics events in the CMS detector, not only in the inner tracking region inside the solenoid but also in the large and complex structure of the steel yoke, which is instrumented with muon chambers. Using a large sample of cosmic muon events collected by CMS in 2008, the field in the steel of the barrel yoke has been determined with a precision of 3 to 8% depending on the location.

  19. Stereotactic, Single-Dose Irradiation of Lung Tumors: A Comparison of Absolute Dose and Dose Distribution Between Pencil Beam and Monte Carlo Algorithms Based on Actual Patient CT Scans

    SciTech Connect (OSTI)

    Chen Huixiao; Lohr, Frank; Fritz, Peter; Wenz, Frederik; Dobler, Barbara; Lorenz, Friedlieb; Muehlnickel, Werner

    2010-11-01

    Purpose: Dose calculation based on pencil beam (PB) algorithms has its shortcomings predicting dose in tissue heterogeneities. The aim of this study was to compare dose distributions of clinically applied non-intensity-modulated radiotherapy 15-MV plans for stereotactic body radiotherapy between voxel Monte Carlo (XVMC) calculation and PB calculation for lung lesions. Methods and Materials: To validate XVMC, one treatment plan was verified in an inhomogeneous thorax phantom with EDR2 film (Eastman Kodak, Rochester, NY). Both measured and calculated (PB and XVMC) dose distributions were compared regarding profiles and isodoses. Then, 35 lung plans originally created for clinical treatment by PB calculation with the Eclipse planning system (Varian Medical Systems, Palo Alto, CA) were recalculated by XVMC (investigational implementation in PrecisePLAN [Elekta AB, Stockholm, Sweden]). Clinically relevant dose-volume parameters for target and lung tissue were compared and analyzed statistically. Results: The XVMC calculation agreed well with film measurements (<1% difference in lateral profile), whereas the deviation between PB calculation and film measurements was up to +15%. On analysis of 35 clinical cases, the mean dose, minimal dose and coverage dose value for 95% volume of gross tumor volume were 1.14 {+-} 1.72 Gy, 1.68 {+-} 1.47 Gy, and 1.24 {+-} 1.04 Gy lower by XVMC compared with PB, respectively (prescription dose, 30 Gy). The volume covered by the 9 Gy isodose of lung was 2.73% {+-} 3.12% higher when calculated by XVMC compared with PB. The largest differences were observed for small lesions circumferentially encompassed by lung tissue. Conclusions: Pencil beam dose calculation overestimates dose to the tumor and underestimates lung volumes exposed to a given dose consistently for 15-MV photons. The degree of difference between XVMC and PB is tumor size and location dependent. Therefore XVMC calculation is helpful to further optimize treatment planning.

  20. Microsecond acquisition of heterogeneous structure in the folding of a TIM barrel protein

    SciTech Connect (OSTI)

    Wu, Ying; Kondrashkina, Elena; Kayatekin, Can; Matthews, C. Robert; Bilsel, Osman (NWU); (UMASS, Amherst)

    2008-09-29

    The earliest kinetic folding events for ({beta}{alpha}){sub 8} barrels reflect the appearance of off-pathway intermediates. Continuous-flow microchannel mixing methods interfaced to small-angle x-ray scattering (SAXS), circular dichroism (CD), time-resolved Foerster resonant energy transfer (trFRET), and time-resolved fluorescence anisotropy (trFLAN) have been used to directly monitor global and specific dimensional properties of the partially folded state in the microsecond time range for a representative ({beta}{alpha}){sub 8} barrel protein. Within 150 {micro}s, the {alpha}-subunit of Trp synthase ({alpha}TS) experiences a global collapse and the partial formation of secondary structure. The time resolution of the folding reaction was enhanced with trFRET and trFLAN to show that, within 30 {micro}s, a distinct and autonomous partially collapsed structure has already formed in the N-terminal and central regions but not in the C-terminal region. A distance distribution analysis of the trFRET data confirmed the presence of a heterogeneous ensemble that persists for several hundreds of microseconds. Ready access to locally folded, stable substructures may be a hallmark of repeat-module proteins and the source of early kinetic traps in these very common motifs. Their folding free-energy landscapes should be elaborated to capture this source of frustration.

  1. FY 2012 Real Property Deferred, Actual, and Required Maintenance Reporting

    Energy Savers [EERE]

    Requirement | Department of Energy Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY 2012 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement PDF icon FY 2012 DARM Transmittal Letter and Attachment Final.pdf More Documents & Publications FY 2013 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement Real Property Maintenance Reporting Requirement Memorandum (July 13, 2010)

  2. ,"Lower 48 Federal Offshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Lower 48 Federal Offshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  3. ,"Mississippi (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  4. ,"New Mexico--East Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico--East Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  5. ,"New Mexico--East Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico--East Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  6. ,"New Mexico--West Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico--West Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  7. ,"New Mexico--West Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico--West Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  8. ,"Texas (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  9. ,"Texas (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  10. ,"Texas--RRC District 1 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 1 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  11. ,"Texas--RRC District 1 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 1 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  12. ,"Texas--RRC District 10 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 10 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  13. ,"Texas--RRC District 10 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 10 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  14. ,"Texas--RRC District 2 Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 2 Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  15. ,"Texas--RRC District 2 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 2 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  16. ,"Texas--RRC District 3 Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 3 Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  17. ,"Texas--RRC District 3 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 3 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  18. ,"Texas--RRC District 4 Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 4 Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  19. ,"Texas--RRC District 4 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 4 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  20. ,"Texas--RRC District 5 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 5 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  1. ,"Texas--RRC District 5 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 5 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  2. ,"Texas--RRC District 6 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 6 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  3. ,"Texas--RRC District 6 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 6 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  4. ,"Texas--RRC District 7B Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 7B Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  5. ,"Texas--RRC District 7B Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 7B Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  6. ,"Texas--RRC District 7C Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 7C Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  7. ,"Texas--RRC District 7C Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 7C Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  8. ,"Texas--RRC District 8 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 8 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  9. ,"Texas--RRC District 8 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 8 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  10. ,"Texas--RRC District 8A Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 8A Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  11. ,"Texas--RRC District 8A Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 8A Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  12. ,"Texas--RRC District 9 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 9 Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  13. ,"Texas--RRC District 9 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 9 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  14. ,"Alabama (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  15. ,"Alabama (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  16. ,"Alaska (with Total Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska (with Total Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  17. ,"Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  18. ,"Calif--Coastal Region Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Calif--Coastal Region Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  19. ,"Calif--Los Angeles Basin Onshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Calif--Los Angeles Basin Onshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  20. ,"Calif--Los Angeles Basin Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Calif--Los Angeles Basin Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  1. ,"Calif--San Joaquin Basin Onshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)"

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

    Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Calif--San Joaquin Basin Onshore Crude Oil Reserves in Nonproducing Reservoirs (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  2. ,"Calif--San Joaquin Basin Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Calif--San Joaquin Basin Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  3. ,"California (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  4. ,"California (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  5. ,"California - Los Angeles Basin Onshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California - Los Angeles Basin Onshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  6. ,"California - San Joaquin Basin Onshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)"

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

    Crude Oil + Lease Condensate Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California - San Joaquin Basin Onshore Crude Oil + Lease Condensate Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  7. ,"Federal Offshore--California Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--California Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  8. ,"Federal Offshore--California Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--California Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  9. ,"Federal Offshore--Louisiana and Alabama Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Louisiana and Alabama Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  10. ,"Federal Offshore--Louisiana and Alabama Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Louisiana and Alabama Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  11. ,"Federal Offshore--Texas Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Texas Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  12. ,"Federal Offshore--Texas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Texas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  13. ,"Louisiana (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)"

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

    Liquids Lease Condensate, Proved Reserves (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  14. ,"Louisiana (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  15. Table 5.10 Natural Gas Plant Liquids Production, 1949-2011 (Thousand Barrels)

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

    0 Natural Gas Plant Liquids Production, 1949-2011 (Thousand Barrels) Year Finished Petroleum Products 1 Liquefied Petroleum Gases Pentanes Plus 4 Total Ethane 2 Isobutane Normal Butane 3 Propane 2,3 Total 1949 19,210 3,056 4,182 22,283 27,114 56,634 81,241 157,086 1950 23,931 4,253 4,667 25,323 37,018 71,261 86,769 181,961 1951 26,505 5,545 5,509 27,960 45,798 84,812 93,437 204,754 1952 25,488 7,089 6,568 31,349 54,732 99,738 98,289 223,515 1953 25,739 6,151 7,006 35,308 61,544 110,009 102,831

  16. Table 5.17 Strategic Petroleum Reserve, 1977-2011 (Thousand Barrels, Except as Noted)

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

    7 Strategic Petroleum Reserve, 1977-2011 (Thousand Barrels, Except as Noted) Year Foreign Crude Oil Receipts Domestic Crude Oil Receipts Withdrawals End-of-Year Stocks Days of Petroleum Net Imports 4 Imported by SPR Imported by Others 1,2 Purchases Exchanges 2 Sales Exchanges Quantity Percent of Crude Oil 3 Stocks Percent of Total Petroleum Stocks 1977 7,540 0 370 [5] 0 0 0 7,455 2.1 0.6 1 1978 58,798 0 0 0 0 0 66,860 17.8 5.2 8 1979 24,434 0 4 0 0 0 91,191 21.2 6.8 11 1980 16,067 0 1,296 0 0 0

  17. Table 5.18 Crude Oil Domestic First Purchase Prices, 1949-2011 (Dollars per Barrel)

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

    8 Crude Oil Domestic First Purchase Prices, 1949-2011 (Dollars per Barrel) Year Alaska North Slope California Texas U.S. Average Nominal 1 Real 2 Nominal 1 Real 2 Nominal 1 Real 2 Nominal 1 Real 2 1949 – – – – NA NA NA NA 2.54 17.52 [R] 1950 – – – – NA NA NA NA 2.51 17.13 [R] 1951 – – – – NA NA NA NA 2.53 16.10 [R] 1952 – – – – NA NA NA NA 2.53 15.83 [R] 1953 – – – – NA NA NA NA 2.68 16.57 [R] 1954 – – – – NA NA NA NA 2.78 17.03 [R] 1955 – – – – NA NA NA NA 2.77 16.69

  18. Table 5.6 Petroleum Exports by Country of Destination, 1960-2011 (Thousand Barrels)

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

    Petroleum Exports by Country of Destination, 1960-2011 (Thousand Barrels) Year Belgium 1 Brazil Canada France Italy Japan Mexico Nether- lands South Korea Spain United Kingdom U.S. Virgin Islands and Puerto Rico Other Total 1960 1,128 1,547 12,622 1,591 2,184 22,681 6,428 2,057 NA NA 4,273 487 18,908 73,906 1961 1,418 1,337 8,401 1,442 1,706 21,473 4,548 1,496 NA NA 3,705 400 17,637 63,563 1962 1,182 1,649 7,714 969 1,994 19,687 4,981 1,671 NA NA 3,044 344 18,155 61,390 1963 3,191 1,335 7,987

  19. Light yield of Kuraray SCSF-78MJ scintillating fibers for the Gluex barrel calorimeter

    SciTech Connect (OSTI)

    Beattie, T.D.; Fischer, A.P.; Krueger, S.T.; Lolos, G.J.; Papandreou, Z.; Plummer, E.L.; Semenov, A.Yu.; Semenova, I.A.; Sichello, L.M.; Teigro, L.A.; Smith, E S

    2014-09-01

    Over three quarters of a million 1-mm-diameter 4-m-long Kuraray double-clad SCSF-78MJ (blue-green) scintillating fibers have been used in the construction of the GlueX electromagnetic barrel calorimeter for the Hall D experimental program at Jefferson Lab. The quality of a random sample of 4,750 of these fibers was evaluated by exciting the fibers at their mid point using a 90Sr source in order to determine the light yield using a calibrated vacuum photomultiplier as the photosensor. A novel methodology was developed to extract the number of photoelectrons detected for measurements where individual photoelectron peaks are not discernible. The average number of photoelectrons from this sample of fibers was 9.17±0.6 at a source distance of 200 cm from the PMT.

  20. OPTIMIZING CENTRIFUGAL BARREL POLISHING FOR MIRROR FINISH SRF CAVITY AND RF TESTS AT JEFFERSON LAB

    SciTech Connect (OSTI)

    Ari Palczewski, Rongli Geng, Hui Tian

    2012-07-01

    We performed Centrifugal Barrel Polishing (CBP) on a 1.3 GHz fine grain TESLA single cell cavity and 1.5 GHz fine grain CEBAF high gradient superconducting radio frequency (SRF) single cell cavity following a modified recipe originally developed at Fermi National Accelerator Lab (FNAL). We were able to obtain a mirror like surface similar to that obtained at FNAL, while reducing the number of CBP steps and total processing time. This paper will discuss the change in surface and subsequent cavity performance post CBP, after a 800 C bake (no pre-bake chemistry) and minimal controlled electro-polishing (10 micron). In addition to Q vs. E{sub ACC} thermometry mapping with preheating characteristics and optical inspection of the cavity after CBP will also be shown.

  1. Detailed Surface Analysis Of Incremental Centrifugal Barrel Polishing (CBP) Of Single-Crystal Niobium Samples

    SciTech Connect (OSTI)

    Palczewski, Ari D.; Hui Tian; Trofimova, Olga; Reece, Charles E.

    2011-07-01

    We performed Centrifugal Barrel Polishing (CBP) on single crystal niobium samples/coupons housed in a stainless steel sample holder following the polishing recipe developed at Fermi Lab (FNAL) in 2011 \\cite{C. A. Cooper 2011}. Post CBP, the sample coupons were analyzed for surface roughness, crystal composition and structure, and particle contamination. Following the initial analysis each coupon was high pressure rinsed (HRP) and analyzed for the effectiveness of contamination removal. We were able to obtain the mirror like surface finish after the final stage of tumbling, although some defects and embedded particles remained. In addition, standard HPR appears to have little effect on removing embedded particles which remain after each tumbling step, although final polishing media removal was partially affected by standard/extended HPR.

  2. FY 2013 Real Property Deferred, Actual, and Required Maintenance Reporting

    Energy Savers [EERE]

    Requirement | Department of Energy Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY 2013 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement PDF icon FY 2013 DARM Transmittal Letter and Attachment Final.pdf More Documents & Publications FY 2012 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY_09_DM_RM_AM_Reporting_Memo_and_attachment_072009.pdf Real Property Maintenance Reporting Requirement

  3. Table 14a. Average Electricity Prices, Projected vs. Actual

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

    a. Average Electricity Prices, Projected vs. Actual" "Projected Price in Constant Dollars" " (constant dollars, cents per kilowatt-hour in ""dollar year"" specific to each AEO)" ...

  4. Table 5.21 Crude Oil Refiner Acquisition Costs, 1968-2011 (Dollars per Barrel)

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

    1 Crude Oil Refiner Acquisition Costs, 1968-2011 (Dollars per Barrel) Year Domestic Imported Composite Nominal 1 Real 2 Nominal 1 Real 2 Nominal 1 Real 2 1968E 3.21 14.57 [R] 2.90 13.16 [R] 3.17 14.39 [R] 1969E 3.37 14.58 [R] 2.80 12.11 [R] 3.29 14.23 [R] 1970E 3.46 14.22 [R] 2.96 12.16 [R] 3.40 13.97 [R] 1971E 3.68 14.40 [R] 3.17 12.41 [R] 3.60 14.09 [R] 1972E 3.67 13.77 [R] 3.22 12.08 [R] 3.58 13.43 [R] 1973E 4.17 14.82 [R] 4.08 14.50 [R] 4.15 14.75 [R] 1974 7.18 23.40 [R] 12.52 40.80 [R] 9.07

  5. Colorado Natural Gas Plant Liquids, Reserves Based Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Reserves Based Production (Million Barrels) Colorado Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 10 1980's 10 11 10 9 8 9 8 8 9 10 1990's 10 12 13 14 15 18 17 21 18 19 2000's 21 22 23 24 26 26 26 27 38 48 2010's 58 63 57 52 61 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015

  6. Lower 48 States Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Reserves Based Production (Million Barrels) Lower 48 States Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 579 1980's 572 580 564 568 597 580 566 569 572 549 1990's 556 577 599 608 608 616 655 655 631 649 2000's 688 655 657 593 627 597 615 637 654 701 2010's 734 773 854 920 1,107 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  7. Michigan Natural Gas Plant Liquids, Reserves Based Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Reserves Based Production (Million Barrels) Michigan Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 11 1980's 12 12 11 10 10 8 9 8 8 8 1990's 6 6 6 5 5 5 5 4 4 4 2000's 4 4 3 3 3 3 2 3 3 2 2010's 3 2 2 2 2 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date:

  8. Miscellaneous States Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Reserves Based Production (Million Barrels) Miscellaneous States Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0 1980's 0 8 0 0 0 0 0 0 1990's 0 0 0 0 0 0 0 0 0 0 2000's 0 0 0 0 0 1 1 1 1 0 2010's 0 0 0 1 24 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release

  9. North Dakota Natural Gas Plant Liquids, Reserves Based Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Reserves Based Production (Million Barrels) North Dakota Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 2 1980's 3 4 4 5 6 6 5 6 5 5 1990's 5 5 5 5 4 4 4 4 4 4 2000's 5 5 5 4 5 5 6 6 6 8 2010's 9 11 19 26 36 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date:

  10. Oklahoma Natural Gas Plant Liquids, Reserves Based Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Reserves Based Production (Million Barrels) Oklahoma Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 59 1980's 62 65 67 70 75 77 76 76 79 73 1990's 75 76 77 77 76 70 74 71 69 70 2000's 69 66 61 59 64 65 67 69 74 77 2010's 82 88 96 99 117 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  11. Utah and Wyoming Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Liquids Lease Condensate, Reserves Based Production (Million Barrels) Utah and Wyoming Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 4 1980's 5 11 8 20 26 31 31 28 25 23 1990's 16 17 15 14 14 9 8 8 8 14 2000's 7 11 11 10 10 12 13 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  12. West Virginia Natural Gas Plant Liquids, Reserves Based Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Reserves Based Production (Million Barrels) West Virginia Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 6 1980's 6 6 5 5 6 7 6 6 7 7 1990's 7 7 7 7 6 4 4 4 4 4 2000's 6 6 6 4 4 4 5 5 5 5 2010's 5 5 8 10 41 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date:

  13. Table 16. Total Energy Consumption, Projected vs. Actual Projected

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

    6. Total Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 ...

  14. Table 8. Total Natural Gas Consumption, Projected vs. Actual

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

    Actual Projected (trillion cubic feet) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 19.87 20.21 20.64 20.99 ...

  15. Table 14b. Average Electricity Prices, Projected vs. Actual

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

    b. Average Electricity Prices, Projected vs. Actual" "Projected Price in Nominal Dollars" " (nominal dollars, cents per kilowatt-hour)" ,1993,1994,1995,1996,1997,1998,1999,2000,200...

  16. Table 14b. Average Electricity Prices, Projected vs. Actual

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

    b. Average Electricity Prices, Projected vs. Actual Projected Price in Nominal Dollars (nominal dollars, cents per kilowatt-hour) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 ...

  17. Table 9. Natural Gas Production, Projected vs. Actual

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

    Natural Gas Production, Projected vs. Actual" "Projected" " (trillion cubic feet)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2...

  18. Table 10. Natural Gas Net Imports, Projected vs. Actual

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

    Natural Gas Net Imports, Projected vs. Actual" "Projected" " (trillion cubic feet)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,...

  19. "Table 7b. Natural Gas Price, Electric Power Sector, Actual...

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

    b. Natural Gas Price, Electric Power Sector, Actual vs. Projected" "Projected Price in Nominal Dollars" " (nominal dollars per million Btu)" ,1993,1994,1995,1996,1997,1998,1999,200...

  20. Table 10. Natural Gas Net Imports, Projected vs. Actual Projected

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

    Natural Gas Net Imports, Projected vs. Actual Projected (trillion cubic feet) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012...

  1. U.S. Natural Gas Liquids Lease Condensate, Reserves Based Production

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

    (Million Barrels) Based Production (Million Barrels) U.S. Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 147 1980's 159 161 157 157 179 168 169 162 162 165 1990's 158 153 147 153 157 145 162 174 178 199 2000's 208 215 207 191 182 174 182 181 173 178 2010's 224 231 274 311 326 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  2. Calif--Los Angeles Basin Onshore Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Plant Liquids, Reserves Based Production (Million Barrels) Calif--Los Angeles Basin Onshore Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1 1980's 1 1 1 1 1 1 1 1 1 0 1990's 0 0 1 0 0 0 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  3. Calif--San Joaquin Basin Onshore Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Plant Liquids, Reserves Based Production (Million Barrels) Calif--San Joaquin Basin Onshore Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 6 1980's 4 4 9 9 9 10 10 10 9 8 1990's 8 7 8 8 7 8 8 7 6 7 2000's 7 7 9 9 9 10 10 10 10 10 2010's 9 9 9 10 9 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  4. Dose Rate Analysis Capability for Actual Spent Fuel Transportation Cask Contents

    SciTech Connect (OSTI)

    Radulescu, Georgeta; Lefebvre, Robert A; Peplow, Douglas E.; Williams, Mark L; Scaglione, John M

    2014-01-01

    The approved contents for a U.S. Nuclear Regulatory Commission (NRC) licensed spent nuclear fuel casks are typically based on bounding used nuclear fuel (UNF) characteristics. However, the contents of the UNF canisters currently in storage at independent spent fuel storage installations are considerably heterogeneous in terms of fuel assembly burnup, initial enrichment, decay time, cladding integrity, etc. Used Nuclear Fuel Storage, Transportation & Disposal Analysis Resource and Data System (UNF ST&DARDS) is an integrated data and analysis system that facilitates automated cask-specific safety analyses based on actual characteristics of the as-loaded UNF. The UNF-ST&DARDS analysis capabilities have been recently expanded to include dose rate analysis of as-loaded transportation packages. Realistic dose rate values based on actual canister contents may be used in place of bounding dose rate values to support development of repackaging operations procedures, evaluation of radiation-related transportation risks, and communication with stakeholders. This paper describes the UNF-ST&DARDS dose rate analysis methodology based on actual UNF canister contents and presents sample dose rate calculation results.

  5. FRACTIONAL CRYSTALLIZATION FLOWSHEET TESTS WITH ACTUAL TANK WASTE

    SciTech Connect (OSTI)

    HERTING, D.L.

    2007-04-13

    Laboratory-scale flowsheet tests of the fractional crystallization process were conducted with actual tank waste samples in a hot cell at the 2224 Laboratory. The process is designed to separate medium-curie liquid waste into a low-curie stream for feeding to supplemental treatment and a high-curie stream for double-shell tank storage. Separations criteria (for Cesium-137 sulfate and sodium) were exceeded in all three of the flowsheet tests that were performed.

  6. FRACTIONAL CRYSTALLIZATION FLOWSHEET TESTS WITH ACTUAL TANK WASTE

    SciTech Connect (OSTI)

    HERTING, D.L.

    2006-10-18

    Laboratory-scale flowsheet tests of the fractional crystallization process were conducted with actual tank waste samples in a hot cell at the 222-S Laboratory. The process is designed to separate medium-curie liquid waste into a low-curie stream for feeding to supplemental treatment and a high-curie stream for double-shell tank storage. Separations criteria (for Cs-137 sulfate, and sodium) were exceeded in all three of the flowsheet tests that were performed.

  7. Table 12. Total Coal Consumption, Projected vs. Actual

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

    Total Coal Consumption, Projected vs. Actual" "Projected" " (million short tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",920,928,933,938,943,948,953,958,962,967,978,990,987,992,1006,1035,1061,1079 "AEO 1995",,935,940,941,947,948,951,954,958,963,971,984,992,996,1002,1013,1025,1039 "AEO

  8. Table 12. Total Coal Consumption, Projected vs. Actual Projected

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

    Total Coal Consumption, Projected vs. Actual Projected (million short tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 920 928 933 938 943 948 953 958 962 967 978 990 987 992 1006 1035 1061 1079 AEO 1995 935 940 941 947 948 951 954 958 963 971 984 992 996 1002 1013 1025 1039 AEO 1996 937 942 954 962 983 990 1004 1017 1027 1033 1046 1067 1070 1071 1074 1082 1087 1094 1103 AEO 1997 948 970 987 1003 1017 1020 1025 1034 1041

  9. Table 13. Coal Production, Projected vs. Actual Projected

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

    Coal Production, Projected vs. Actual Projected (million short tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 999 1021 1041 1051 1056 1066 1073 1081 1087 1098 1107 1122 1121 1128 1143 1173 1201 1223 AEO 1995 1006 1010 1011 1016 1017 1021 1027 1033 1040 1051 1066 1076 1083 1090 1108 1122 1137 AEO 1996 1037 1044 1041 1045 1061 1070 1086 1100 1112 1121 1135 1156 1161 1167 1173 1184 1190 1203 1215 AEO 1997 1028 1052 1072 1088

  10. Table 15. Total Electricity Sales, Projected vs. Actual

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

    Total Electricity Sales, Projected vs. Actual" "Projected" " (billion kilowatt-hours)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",2843,2891,2928,2962,3004,3039,3071,3112,3148,3185,3228,3263,3298,3332,3371,3406,3433,3469 "AEO 1995",,2951,2967,2983,3026,3058,3085,3108,3134,3166,3204,3248,3285,3321,3357,3396,3433,3475 "AEO

  11. Table 15. Total Electricity Sales, Projected vs. Actual Projected

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

    Total Electricity Sales, Projected vs. Actual Projected (billion kilowatt-hours) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 2843 2891 2928 2962 3004 3039 3071 3112 3148 3185 3228 3263 3298 3332 3371 3406 3433 3469 AEO 1995 2951 2967 2983 3026 3058 3085 3108 3134 3166 3204 3248 3285 3321 3357 3396 3433 3475 AEO 1996 2973 2998 3039 3074 3106 3137 3173 3215 3262 3317 3363 3409 3454 3505 3553 3604 3660 3722 3775 AEO 1997 3075

  12. Actual and Estimated Energy Savings Comparison for Deep Energy Retrofits in the Pacific Northwest

    SciTech Connect (OSTI)

    Blanchard, Jeremy; Widder, Sarah H.; Giever, Elisabeth L.; Baechler, Michael C.

    2012-10-01

    Seven homes from the Pacific Northwest were selected to evaluate the differences between estimated and actual energy savings achieved from deep energy retrofits. The energy savings resulting from these retrofits were estimated, using energy modeling software, to save at least 30% on a whole-house basis. The modeled pre-retrofit energy use was trued against monthly utility bills. After the retrofits were completed, each of the homes was extensively monitored, with the exception of one home which was monitored pre-retrofit. This work is being conducted by Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy Building Technologies Program as part of the Building America Program. This work found many discrepancies between actual and estimated energy savings and identified the potential causes for the discrepancies. The differences between actual energy use and modeled energy use also suggest improvements to improve model accuracy. The difference between monthly whole-house actual and estimated energy savings ranged from 75% more energy saved than predicted by the model to 16% less energy saved for all the monitored homes. Similarly, the annual energy savings difference was between 36% and -14%, which was estimated based on existing monitored savings because an entire year of data is not available. Thus, on average, for all six monitored homes the actual energy use is consistently less than estimates, indicating home owners are saving more energy than estimated. The average estimated savings for the eight month monitoring period is 43%, compared to an estimated savings average of 31%. Though this average difference is only 12%, the range of inaccuracies found for specific end-uses is far greater and are the values used to directly estimate energy savings from specific retrofits. Specifically, the monthly post-retrofit energy use differences for specific end-uses (i.e., heating, cooling, hot water, appliances, etc.) ranged from 131% under-predicted to 77% over-predicted by the model with respect to monitored energy use. Many of the discrepancies were associated with occupant behavior which influences energy use, dramatically in some cases, actual versus modeled weather differences, modeling input limitations, and complex homes that are difficult to model. The discrepancy between actual and estimated energy use indicates a need for better modeling tools and assumptions. Despite the best efforts of researchers, the estimated energy savings are too inaccurate to determine reliable paybacks for retrofit projects. While the monitored data allows researchers to understand why these differences exist, it is not cost effective to monitor each home with the level of detail presented here. Therefore an appropriate balance between modeling and monitoring must be determined for more widespread application in retrofit programs and the home performance industry. Recommendations to address these deficiencies include: (1) improved tuning process for pre-retrofit energy use, which currently utilized broad-based monthly utility bills; (2) developing simple occupant-based energy models that better address the many different occupant types and their impact on energy use; (3) incorporating actual weather inputs to increase accuracy of the tuning process, which uses utility bills from specific time period; and (4) developing simple, cost-effective monitoring solutions for improved model tuning.

  13. Table 16. Total Energy Consumption, Projected vs. Actual

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

    Total Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",88.02,89.53,90.72,91.73,92.71,93.61,94.56,95.73,96.69,97.69,98.89,100,100.79,101.7,102.7,103.6,104.3,105.23 "AEO 1995",,89.21,89.98,90.57,91.91,92.98,93.84,94.61,95.3,96.19,97.18,98.38,99.37,100.3,101.2,102.1,102.9,103.88 "AEO

  14. Table 8. Total Natural Gas Consumption, Projected vs. Actual

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

    Total Natural Gas Consumption, Projected vs. Actual" "Projected" " (trillion cubic feet)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",19.87,20.21,20.64,20.99,21.2,21.42,21.6,21.99,22.37,22.63,22.95,23.22,23.58,23.82,24.09,24.13,24.02,24.14 "AEO 1995",,20.82,20.66,20.85,21.21,21.65,21.95,22.12,22.25,22.43,22.62,22.87,23.08,23.36,23.61,24.08,24.23,24.59 "AEO

  15. Method and apparatus for distinguishing actual sparse events from sparse event false alarms

    DOE Patents [OSTI]

    Spalding, Richard E. (Albuquerque, NM); Grotbeck, Carter L. (Albuquerque, NM)

    2000-01-01

    Remote sensing method and apparatus wherein sparse optical events are distinguished from false events. "Ghost" images of actual optical phenomena are generated using an optical beam splitter and optics configured to direct split beams to a single sensor or segmented sensor. True optical signals are distinguished from false signals or noise based on whether the ghost image is presence or absent. The invention obviates the need for dual sensor systems to effect a false target detection capability, thus significantly reducing system complexity and cost.

  16. Table 14a. Average Electricity Prices, Projected vs. Actual

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

    a. Average Electricity Prices, Projected vs. Actual Projected Price in Constant Dollars (constant dollars, cents per kilowatt-hour in "dollar year" specific to each AEO) AEO $ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1992 6.80 6.80 6.90 6.90 6.90 6.90 7.00 7.00 7.10 7.10 7.20 7.20 7.20 7.30 7.30 7.40 7.50 7.60 AEO 1995 1993 6.80 6.80 6.70 6.70 6.70 6.70 6.70 6.80 6.80 6.90 6.90 6.90 7.00 7.00 7.10 7.10 7.20

  17. Table 17. Total Delivered Residential Energy Consumption, Projected vs. Actual

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

    Total Delivered Residential Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 10.3 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.5 10.5 10.5 10.5 10.5 10.6 10.6 AEO 1995 11.0 10.8 10.8 10.8 10.8 10.8 10.8 10.7 10.7 10.7 10.7 10.7 10.7 10.7 10.8 10.8 10.9 AEO 1996 10.4 10.7 10.7 10.7 10.8 10.8 10.9 10.9 11.0 11.2 11.2 11.3 11.4 11.5 11.6 11.7 11.8 12.0 12.1

  18. Table 18. Total Delivered Commercial Energy Consumption, Projected vs. Actual

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

    Total Delivered Commercial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 6.8 6.9 6.9 7.0 7.1 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.4 7.5 7.5 7.5 7.5 7.6 AEO 1995 6.9 6.9 7.0 7.0 7.0 7.1 7.1 7.1 7.1 7.1 7.2 7.2 7.2 7.2 7.3 7.3 7.3 AEO 1996 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.5 7.6 7.6 7.7 7.7 7.8 7.9 8.0 8.0 8.1 8.2 8.2 AEO 1997 7.4 7.4 7.4 7.5 7.5 7.6 7.7 7.7 7.8 7.8 7.9 7.9

  19. Table 19. Total Delivered Industrial Energy Consumption, Projected vs. Actual

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

    Total Delivered Industrial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 25.4 25.9 26.3 26.7 27.0 27.1 26.8 26.6 26.9 27.2 27.7 28.1 28.3 28.7 29.1 29.4 29.7 30.0 AEO 1995 26.2 26.3 26.5 27.0 27.3 26.9 26.6 26.8 27.1 27.5 27.9 28.2 28.4 28.7 29.0 29.3 29.6 AEO 1996 26.5 26.6 27.3 27.5 26.9 26.5 26.7 26.9 27.2 27.6 27.9 28.2 28.3 28.5 28.7 28.9 29.2 29.4 29.6

  20. Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual

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

    Total Delivered Transportation Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 23.6 24.1 24.5 24.7 25.1 25.4 25.7 26.2 26.5 26.9 27.2 27.6 27.9 28.3 28.6 28.9 29.2 29.5 AEO 1995 23.3 24.0 24.2 24.7 25.1 25.5 25.9 26.2 26.5 26.9 27.3 27.7 28.0 28.3 28.5 28.7 28.9 AEO 1996 23.9 24.1 24.5 24.8 25.3 25.7 26.0 26.4 26.7 27.1 27.5 27.8 28.1 28.4 28.6 28.9 29.1 29.3

  1. Table 22. Energy Intensity, Projected vs. Actual Projected

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

    Energy Intensity, Projected vs. Actual Projected (quadrillion Btu / $Billion 2005 Chained GDP) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 10.9 10.7 10.6 10.5 10.3 10.2 10.1 9.9 9.8 9.7 9.6 9.5 9.4 9.3 9.2 9.1 9.0 8.9 AEO 1995 10.5 10.4 10.3 10.1 10.0 9.8 9.7 9.6 9.4 9.3 9.2 9.1 9.0 8.9 8.9 8.8 8.7 AEO 1996 10.4 10.3 10.1 10.0 9.8 9.7 9.5 9.4 9.3 9.2 9.1 9.0 8.9 8.9 8.8 8.7 8.7 8.6 8.5 AEO 1997 10.0 9.9 9.8 9.7 9.6 9.5 9.4

  2. Table 9. Natural Gas Production, Projected vs. Actual Projected

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

    Natural Gas Production, Projected vs. Actual Projected (trillion cubic feet) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 17.71 17.68 17.84 18.12 18.25 18.43 18.58 18.93 19.28 19.51 19.80 19.92 20.13 20.18 20.38 20.35 20.16 20.19 AEO 1995 18.28 17.98 17.92 18.21 18.63 18.92 19.08 19.20 19.36 19.52 19.75 19.94 20.17 20.28 20.60 20.59 20.88 AEO 1996 18.90 19.15 19.52 19.59 19.59 19.65 19.73 19.97 20.36 20.82 21.25 21.37 21.68

  3. R&D progress in SRF surface preparation with centrifugal barrel polishing (cbp) for both Nb and Cu

    SciTech Connect (OSTI)

    Palczewski, Ari

    2013-09-01

    Centrifugal Barrel polishing (CBP) is becoming a common R&D tool for SRF cavity preparation around the world. During the CBP process a cylindrically symmetric SRF cavity is filled with relatively cheap and environmentally friendly abrasive and sealed. The cavity is then spun around a cylindrically symmetric axis at high speeds uniformly conditioning the inner surface. This uniformity is especially relevant for SRF application because many times a single manufacturing defects limits cavity?s performance well below it?s theoretical limit. In addition CBP has created surfaces with roughness?s on the order of 10?s of nm which create a unique surface for wet chemistry or thin film deposition. CBP is now being utilized at Jefferson Laboratory, Fermi Laboratory and Cornell University in the US, Deutsches Elektronen-Synchrotron in Germany, Laboratori Nazionali di Legnaro in Italy, and Raja Ramanna Centre for Advanced Technology in India. In this talk we will present current CBP research from each lab including equipment, baseline recipes, cavity removal rates and subsequent cryogenic cavity tests on niobium as well as copper cavities where available.

  4. Structure of Rhodococcus equi virulence-associated protein B (VapB) reveals an eight-stranded antiparallel ?-barrel consisting of two Greek-key motifs

    SciTech Connect (OSTI)

    Geerds, Christina; Wohlmann, Jens; Haas, Albert; Niemann, Hartmut H.

    2014-06-18

    The structure of VapB, a member of the Vap protein family that is involved in virulence of the bacterial pathogen R. equi, was determined by SAD phasing and reveals an eight-stranded antiparallel ?-barrel similar to avidin, suggestive of a binding function. Made up of two Greek-key motifs, the topology of VapB is unusual or even unique. Members of the virulence-associated protein (Vap) family from the pathogen Rhodococcus equi regulate virulence in an unknown manner. They do not share recognizable sequence homology with any protein of known structure. VapB and VapA are normally associated with isolates from pigs and horses, respectively. To contribute to a molecular understanding of Vap function, the crystal structure of a protease-resistant VapB fragment was determined at 1.4 resolution. The structure was solved by SAD phasing employing the anomalous signal of one endogenous S atom and two bound Co ions with low occupancy. VapB is an eight-stranded antiparallel ?-barrel with a single helix. Structural similarity to avidins suggests a potential binding function. Unlike other eight- or ten-stranded ?-barrels found in avidins, bacterial outer membrane proteins, fatty-acid-binding proteins and lysozyme inhibitors, Vaps do not have a next-neighbour arrangement but consist of two Greek-key motifs with strand order 41238567, suggesting an unusual or even unique topology.

  5. Arkansas Natural Gas Plant Liquids, Reserves Based Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Reserves Based Production (Million Barrels) Arkansas Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1 1980's 1 1 1 1 1 1 1 1 1 1 1990's 1 0 0 0 0 0 0 0 0 0 2000's 0 1 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016

  6. Florida Natural Gas Plant Liquids, Reserves Based Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Reserves Based Production (Million Barrels) Florida Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 10 1980's 10 5 4 3 2 2 1 1 1 1990's 1 1 1 1 1 1 1 1 1 1 2000's 1 1 1 1 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016

  7. Kentucky Natural Gas Plant Liquids, Reserves Based Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Reserves Based Production (Million Barrels) Kentucky Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3 1980's 3 2 3 2 2 2 2 1 2 1 1990's 1 2 2 2 3 3 3 3 3 3 2000's 2 3 3 3 3 3 3 3 3 4 2010's 5 4 5 5 5 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016

  8. Montana Natural Gas Plant Liquids, Reserves Based Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Reserves Based Production (Million Barrels) Montana Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1 1980's 1 1 1 1 1 1 1 1 1 1 1990's 1 1 1 1 1 0 0 0 0 0 2000's 0 0 1 1 1 1 1 1 1 1 2010's 1 1 1 1 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016

  9. ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2007 through 2011 " ,"(Thousands of Megawatthours and 2006 Base Year)" ,"Net Energy For Load (Annual)",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC","MRO (U.S.) ","NPCC (U.S.)

  10. ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2008 through 2012 " ,"(Thousands of Megawatthours and 2007 Base Year)",,,,,,,,,,,," " ,"Net Energy For Load (Annual)",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC","MRO (U.S.)

  11. ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    . Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2009 and Projected 2010 through 2014" ,"(Thousands of Megawatthours and 2009 Base Year)",,,,,,,,,,,," " ,"Net Energy For Load (Annual)",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC","MRO (U.S.)

  12. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2007 through 2011 " ,"(Megawatts and 2006 Base Year)" ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC","MRO (U.S.) ","NPCC (U.S.)

  13. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2007 and Projected 2008 through 2012 " ,"(Megawatts and 2007 Base Year)" ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid",,,," " ,"Projected Year Base","Year",,"FRCC","MRO (U.S.)

  14. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2007 through 2011 " ,"(Megawatts and 2006 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC"," MRO (U.S.) ","NPCC (U.S.)

  15. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2007 and Projected 2008 through 2012 " ,"(Megawatts and 2007 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC"," MRO (U.S.) ","NPCC (U.S.)

  16. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2008 and Projected 2009 through 2013 " ,"(Megawatts and 2008 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC"," MRO (U.S.) ","NPCC (U.S.)

  17. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2009 and Projected 2010 through 2014 " ,"(Megawatts and 2009 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC"," MRO (U.S.) ","NPCC (U.S.)

  18. Actual Versus Estimated Utility Factor of a Large Set of Privately Owned Chevrolet Volts

    SciTech Connect (OSTI)

    John Smart; Thomas Bradley; Stephen Schey

    2014-04-01

    In order to determine the overall fuel economy of a plug-in hybrid electric vehicle (PHEV), the amount of operation in charge depleting (CD) versus charge sustaining modes must be determined. Mode of operation is predominantly dependent on customer usage of the vehicle and is therefore highly variable. The utility factor (UF) concept was developed to quantify the distance a group of vehicles has traveled or may travel in CD mode. SAE J2841 presents a UF calculation method based on data collected from travel surveys of conventional vehicles. UF estimates have been used in a variety of areas, including the calculation of window sticker fuel economy, policy decisions, and vehicle design determination. The EV Project, a plug-in electric vehicle charging infrastructure demonstration being conducted across the United States, provides the opportunity to determine the real-world UF of a large group of privately owned Chevrolet Volt extended range electric vehicles. Using data collected from Volts enrolled in The EV Project, this paper compares the real-world UF of two groups of Chevrolet Volts to estimated UF's based on J2841. The actual observed fleet utility factors (FUF) for the MY2011/2012 and MY2013 Volt groups studied were observed to be 72% and 74%, respectively. Using the EPA CD ranges, the method prescribed by J2841 estimates a FUF of 65% and 68% for the MY2011/2012 and MY2013 Volt groups, respectively. Volt drivers achieved higher percentages of distance traveled in EV mode for two reasons. First, they had fewer long-distance travel days than drivers in the national travel survey referenced by J2841. Second, they charged more frequently than the J2841 assumption of once per day - drivers of Volts in this study averaged over 1.4 charging events per day. Although actual CD range varied widely as driving conditions varied, the average CD ranges for the two Volt groups studied matched the EPA CD range estimates, so CD range variation did not affect FUF results.

  19. BENCH-SCALE STEAM REFORMING OF ACTUAL TANK 48H WASTE

    SciTech Connect (OSTI)

    Burket, P; Gene Daniel, G; Charles Nash, C; Carol Jantzen, C; Michael Williams, M

    2008-09-25

    Fluidized Bed Steam Reforming (FBSR) has been demonstrated to be a viable technology to remove >99% of the organics from Tank 48H simulant, to remove >99% of the nitrate/nitrite from Tank 48H simulant, and to form a solid product that is primarily carbonate based. The technology was demonstrated in October of 2006 in the Engineering Scale Test Demonstration Fluidized Bed Steam Reformer1 (ESTD FBSR) at the Hazen Research Inc. (HRI) facility in Golden, CO. The purpose of the Bench-scale Steam Reformer (BSR) testing was to demonstrate that the same reactions occur and the same product is formed when steam reforming actual radioactive Tank 48H waste. The approach used in the current study was to test the BSR with the same Tank 48H simulant and same Erwin coal as was used at the ESTD FBSR under the same operating conditions. This comparison would allow verification that the same chemical reactions occur in both the BSR and ESTD FBSR. Then, actual radioactive Tank 48H material would be steam reformed in the BSR to verify that the actual tank 48H sample reacts the same way chemically as the simulant Tank 48H material. The conclusions from the BSR study and comparison to the ESTD FBSR are the following: (1) A Bench-scale Steam Reforming (BSR) unit was successfully designed and built that: (a) Emulated the chemistry of the ESTD FBSR Denitration Mineralization Reformer (DMR) and Carbon Reduction Reformer (CRR) known collectively as the dual reformer flowsheet. (b) Measured and controlled the off-gas stream. (c) Processed real (radioactive) Tank 48H waste. (d) Met the standards and specifications for radiological testing in the Savannah River National Laboratory (SRNL) Shielded Cells Facility (SCF). (2) Three runs with radioactive Tank 48H material were performed. (3) The Tetraphenylborate (TPB) was destroyed to > 99% for all radioactive Bench-scale tests. (4) The feed nitrate/nitrite was destroyed to >99% for all radioactive BSR tests the same as the ESTD FBSR. (5) The radioactive Tank 48H DMR product was primarily made up of soluble carbonates. The three most abundant species were thermonatrite, [Na{sub 2}CO{sub 3} {center_dot} H{sub 2}O], sodium carbonate, [Na{sub 2}CO{sub 3}], and trona, [Na{sub 3}H(CO{sub 3}){sub 2} {center_dot} 2H{sub 2}O] the same as the ESTD FBSR. (6) Insoluble solids analyzed by X-Ray Diffraction (XRD) did not detect insoluble carbonate species. However, they still may be present at levels below 2 wt%, the sensitivity of the XRD methodology. Insoluble solids XRD characterization indicated that various Fe/Ni/Cr/Mn phases are present. These crystalline phases are associated with the insoluble sludge components of Tank 48H slurry and impurities in the Erwin coal ash. The percent insoluble solids, which mainly consist of un-burnt coal and coal ash, in the products were 4 to 11 wt% for the radioactive runs. (7) The Fe{sup +2}/Fe{sub total} REDOX measurements ranged from 0.58 to 1 for the three radioactive Bench-scale tests. REDOX measurements > 0.5 showed a reducing atmosphere was maintained in the DMR indicating that pyrolysis was occurring. (8) Greater than 90% of the radioactivity was captured in the product for all three runs. (9) The collective results from the FBSR simulant tests and the BSR simulant tests indicate that the same chemistry occurs in the two reactors. (10) The collective results from the BSR simulant runs and the BSR radioactive waste runs indicates that the same chemistry occurs in the simulant as in the real waste. The FBSR technology has been proven to destroy the organics and nitrates in the Tank 48H waste and form the anticipated solid carbonate phases as expected.

  20. ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    Jaunary 2010" ,"Next Update: October 2010" ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2008 and Projected 2009 through 2013 " ,"(Thousands of Megawatthours and 2008 Base Year)",,,,,,,,,,,," " ,"Net Energy For Load (Annual)",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid"

  1. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    8" ,"Released: February 2010" ,"Next Update: October 2010" ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2008 and Projected 2009 through 2013 " ,"(Megawatts and 2008 Base Year)" ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid",,,,"

  2. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    9" ,"Released: December 2010" ,"Next Update: December 2011" ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2009 and Projected 2010 through 2014 " ,"(Megawatts and 2009 Base Year)" ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid",,,,"

  3. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, "

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

    5" ,"Released: January 23, 2008" ,"Next Update: October 2007" ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, " ,"2005 and Projected 2006 through 2010 " ,"(Megawatts and 2005 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected

  4. Exploration of material removal rate of srf elliptical cavities as a function of media type and cavity shape on niobium and copper using centrifugal barrel polishing (cbp)

    SciTech Connect (OSTI)

    Palczewski, Ari; Ciovati, Gianluigi; Li, Yongming; Geng, Rongli

    2013-09-01

    Centrifugal barrel polishing (cbp) for SRF application is becoming more wide spread as the technique for cavity surface preparation. CBP is now being used in some form at SRF laboratories around the world including in the US, Europe and Asia. Before the process can become as mature as wet chemistry like eletro-polishing (EP) and buffered chemical polishing (BCP) there are many questions which remain unanswered. One of these topics includes the uniformity of removal as a function of cavity shape and material type. In this presentation we show CBP removal rates for various media types on 1.3 GHz TESLA and 1.5 GHz CEBAF large/fine grain niobium cavities, and 1.3GHz low surface field copper cavity. The data will also include calculated RF frequency shift modeling non-uniform removal as a function of cavity position and comparing them with CBP results.

  5. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    January 2010" ,"Next Update: October 2010" ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2008 and Projected 2009 through 2010 " ,"(Megawatts and 2008 Base Year)" ,"Projected Monthly Base","Year","Contiguous U.S.","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid"

  6. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Council Region, "

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

    ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Council Region, " ,"1996 through 2003 and Projected 2004 through 2005 " ,"(Megawatts and 2003 Base Year)" ,"Projected Monthly Base","Year","Contiguous U.S.","Eastern Power Grid",,,,,,,,"Texas Power Grid","Western Power Grid"

  7. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Council Region, "

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

    3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Council Region, " ,"2005 and Projected 2006 through 2010 " ,"(Megawatts and 2005 Base Year)" ,"Projected Monthly Base","Year","Contiguous U.S.","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid"

  8. Technique of estimation of actual strength of a gas pipeline section at its deformation in landslide action zone

    SciTech Connect (OSTI)

    Tcherni, V.P.

    1996-12-31

    The technique is given which permits determination of stress and strain state (SSS) and estimation of actual strength of a section of a buried main gas pipeline (GP) in the case of its deformation in a landslide action zone. The technique is based on the use of three-dimensional coordinates of axial points of the deformed GP section. These coordinates are received by a full-scale survey. The deformed axis of the surveyed GP section is described by the polynomial. The unknown coefficients of the polynomial can be determined from the boundary conditions at points of connection with contiguous undeformed sections as well as by use of minimization methods in mathematical processing of full-scale survey results. The resulting form of GP section`s axis allows one to determine curvatures and, accordingly, bending moments along all the length of the considered section. The influence of soil resistance to longitudinal displacements of a pipeline is used to determine longitudinal forces. Resulting values of bending moments and axial forces as well as the known value of internal pressure are used to analyze all necessary components of an actual SSS of pipeline section and to estimate its strength by elastic analysis.

  9. Table 11b. Coal Prices to Electric Generating Plants, Projected vs. Actual

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

    b. Coal Prices to Electric Generating Plants, Projected vs. Actual" "Projected Price in Nominal Dollars" " (nominal dollars per million Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO

  10. "Table 2. Real Gross Domestic Product Growth Trends, Projected vs. Actual"

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

    Real Gross Domestic Product Growth Trends, Projected vs. Actual" "Projected Real GDP Growth Trend" " (cumulative average percent growth in projected real GDP from first year shown for each AEO)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO

  11. NEW GUN CAPABILITY WITH INTERCHANGABLE BARRELS TO INVESTIGATE LOW VELOCITY IMPACT REGIMES AT THE LAWRENCE LIVERMORE NATIONAL LABORATORY HIGH EXPLOSIVES APPLICATIONS FACILITY

    SciTech Connect (OSTI)

    Vandersall, K S; Behn, A; Gresshoff, M; Jr., L F; Chiao, P I

    2009-09-16

    A new gas gun capability is being activated at Lawrence Livermore National Laboratories located in the High Explosives Applications Facility (HEAF). The single stage light gas (dry air, nitrogen, or helium) gun has interchangeable barrels ranging from 25.4 mm to 76.2 mm in diameter with 1.8 meters in length and is being fabricated by Physics Applications, Inc. Because it is being used for safety studies involving explosives, the gun is planned for operation inside a large enclosed firing tank, with typical velocities planned in the range of 10-300 m/s. Three applications planned for this gun include: low velocity impact of detonator or detonator/booster assemblies with various projectile shapes, the Steven Impact test that involves impact initiation of a cased explosive target, and the Taylor impact test using a cylindrical explosive sample impacted onto a rigid anvil for fracture studies of energetic materials. A highlight of the gun features, outline on work in progress for implementing this capability, and discussion of the planned areas of research will be included.

  12. Investigation of EMIC wave scattering as the cause for the BARREL 17 January 2013 relativistic electron precipitation event: A quantitative comparison of simulation with observations

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

    Li, Zan; Millan, Robyn M.; Hudson, Mary K.; Woodger, Leslie A.; Smith, David M.; Chen, Yue; Friedel, Reiner; Rodriguez, Juan V.; Engebretson, Mark J.; Goldstein, Jerry; et al

    2014-12-23

    Electromagnetic ion cyclotron (EMIC) waves were observed at multiple observatory locations for several hours on 17 January 2013. During the wave activity period, a duskside relativistic electron precipitation (REP) event was observed by one of the Balloon Array for Radiation belt Relativistic Electron Losses (BARREL) balloons and was magnetically mapped close to Geostationary Operational Environmental Satellite (GOES) 13. We simulate the relativistic electron pitch angle diffusion caused by gyroresonant interactions with EMIC waves using wave and particle data measured by multiple instruments on board GOES 13 and the Van Allen Probes. We show that the count rate, the energy distribution,more » and the time variation of the simulated precipitation all agree very well with the balloon observations, suggesting that EMIC wave scattering was likely the cause for the precipitation event. The event reported here is the first balloon REP event with closely conjugate EMIC wave observations, and our study employs the most detailed quantitative analysis on the link of EMIC waves with observed REP to date.« less

  13. Investigation of EMIC wave scattering as the cause for the BARREL 17 January 2013 relativistic electron precipitation event: A quantitative comparison of simulation with observations

    SciTech Connect (OSTI)

    Li, Zan; Millan, Robyn M.; Hudson, Mary K.; Woodger, Leslie A.; Smith, David M.; Chen, Yue; Friedel, Reiner; Rodriguez, Juan V.; Engebretson, Mark J.; Goldstein, Jerry; Fennell, Joseph F.; Spence, Harlan E.

    2014-12-23

    Electromagnetic ion cyclotron (EMIC) waves were observed at multiple observatory locations for several hours on 17 January 2013. During the wave activity period, a duskside relativistic electron precipitation (REP) event was observed by one of the Balloon Array for Radiation belt Relativistic Electron Losses (BARREL) balloons and was magnetically mapped close to Geostationary Operational Environmental Satellite (GOES) 13. We simulate the relativistic electron pitch angle diffusion caused by gyroresonant interactions with EMIC waves using wave and particle data measured by multiple instruments on board GOES 13 and the Van Allen Probes. We show that the count rate, the energy distribution, and the time variation of the simulated precipitation all agree very well with the balloon observations, suggesting that EMIC wave scattering was likely the cause for the precipitation event. The event reported here is the first balloon REP event with closely conjugate EMIC wave observations, and our study employs the most detailed quantitative analysis on the link of EMIC waves with observed REP to date.

  14. Reaction chemistry of nitrogen species in hydrothermal systems: Simple reactions, waste simulants, and actual wastes

    SciTech Connect (OSTI)

    Dell`Orco, P.; Luan, L.; Proesmans, P.; Wilmanns, E.

    1995-02-01

    Results are presented from hydrothermal reaction systems containing organic components, nitrogen components, and an oxidant. Reaction chemistry observed in simple systems and in simple waste simulants is used to develop a model which presents global nitrogen chemistry in these reactive systems. The global reaction path suggested is then compared with results obtained for the treatment of an actual waste stream containing only C-N-0-H species.

  15. "Table 21. Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual"

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

    Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual" "Projected" " (million metric tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",5060,5129.666667,5184.666667,5239.666667,5287.333333,5335,5379,5437.666667,5481.666667,5529.333333,5599,5657.666667,5694.333333,5738.333333,5797,5874,5925.333333,5984 "AEO

  16. Treatability studies of actual listed waste sludges from the Oak Ridge Reservation (ORR)

    SciTech Connect (OSTI)

    Jantzen, C.M.; Peeler, D.K.; Gilliam, T.M.; Bleier, A.; Spence, R.D.

    1996-05-06

    Oak Ridge National Laboratory (ORNL) and Savannah River Technology Center (SRTC) are investigating vitrification for various low-level and mixed wastes on the Oak Ridge Reservation (ORR). Treatability studies have included surrogate waste formulations at the laboratory-, pilot-, and field-scales and actual waste testing at the laboratory- and pilot-scales. The initial waste to be processing through SRTC`s Transportable Vitrification System (TVS) is the K-1407-B and K-1407-C (B/C) Pond sludge waste which is a RCRA F-listed waste. The B/C ponds at the ORR K-25 site were used as holding and settling ponds for various waste water treatment streams. Laboratory-, pilot-, and field- scale ``proof-of-principle`` demonstrations are providing needed operating parameters for the planned field-scale demonstration with actual B/C Pond sludge waste at ORR. This report discusses the applied systems approach to optimize glass compositions for this particular waste stream through laboratory-, pilot-, and field-scale studies with surrogate and actual B/C waste. These glass compositions will maximize glass durability and waste loading while optimizing melt properties which affect melter operation, such as melt viscosity and melter refractory corrosion. Maximum waste loadings minimize storage volume of the final waste form translating into considerable cost savings.

  17. Making appropriate comparisons of estimated and actual costs of reducing SO{sub 2} emissions under Title IV

    SciTech Connect (OSTI)

    Smith, A.E.

    1998-12-31

    A current sentiment within some parts of the environmental policy community is that market-based regulatory approaches such as emissions trading have proven so effective that actual costs will be only a small fraction of what ex ante cost estimation procedures would project. With this line of reasoning, some have dismissed available cost estimates for major proposed new regulations, such as the new PM and ozone NAAQS, as not meaningful for policy decisions. The most commonly used evidence in support of this position is the experience with SO{sub 2} reductions under Title IV of the 1990 Clean Air Act Amendments. In Title IV, a market for emissions allowances has been used to achieve reductions in sulfur dioxides (SO{sub 2}) to ameliorate acid rain. It is commonly asserted today that the cost of achieving the SO{sub 2} emissions reductions has been only one-tenth or less of what Title IV was originally expected to cost. This paper demonstrates that, to the contrary, actual costs for SO{sub 2} reductions remain roughly in line with original estimates associated with Title IV. Erroneous conclusions about Title IV`s costs are due to inappropriate comparisons of a variety of different measures that appear to be comparable only because they are all stated in dollars per ton. Program cost estimates include the total costs of a fully-implemented regulatory program. The very low costs of Title IV that are commonly cited today are neither directly reflective of a fully implemented Title IV, (which is still many years away) nor reflective of all the costs already incurred. Further, a careful review of history finds that the initial cost estimates that many cite were never associated with Title IV. Technically speaking, people are comparing the estimated control costs for the most-costly power plant associated with earlier acid rain regulatory proposals with prices from a market that do not directly reflect total costs.

  18. Actual versus predicted impacts of three ethanol plants on aquatic and terrestrial resources

    SciTech Connect (OSTI)

    Eddlemon, G.K.; Webb, J.W.; Hunsaker, D.B. Jr.; Miller, R.L.

    1993-03-15

    To help reduce US dependence on imported petroleum, Congress passed the Energy Security Act of 1980 (public Law 96-294). This legislation authorized the US Department of Energy (DOE) to promote expansion of the fuel alcohol industry through, among other measures, its Alcohol Fuels Loan Guarantee Program. Under this program, selected proposals for the conversion of plant biomass into fuel-grade ethanol would be granted loan guarantees. of 57 applications submitted for loan guarantees to build and operate ethanol fuel projects under this program, 11 were considered by DOE to have the greatest potential for satisfying DOE`s requirements and goals. In accordance with the National Environmental Policy Act (NEPA), DOE evaluated the potential impacts of proceeding with the Loan Guarantee Program in a programmatic environmental assessment (DOE 1981) that resulted in a finding of no significant impact (FANCY) (47 Federal Register 34, p. 7483). The following year, DOE conducted site-specific environmental assessments (EAs) for 10 of the proposed projects. These F-As predicted no significant environmental impacts from these projects. Eventually, three ethanol fuel projects received loan guarantees and were actually built: the Tennol Energy Company (Tennol; DOE 1982a) facility near Jasper in southeastern Tennessee; the Agrifuels Refining Corporation (Agrifuels; DOE 1985) facility near New Liberia in southern Louisiana; and the New Energy Company of Indiana (NECI; DOE 1982b) facility in South Bend, Indiana. As part of a larger retrospective examination of a wide range of environmental effects of ethanol fuel plants, we compared the actual effects of the three completed plants on aquatic and terrestrial resources with the effects predicted in the NEPA EAs several years earlier. A secondary purpose was to determine: Why were there differences, if any, between actual effects and predictions? How can assessments be improved and impacts reduced?

  19. TESTING OF THE SPINTEK ROTARY MICROFILTER USING ACTUAL HANFORD WASTE SAMPLES

    SciTech Connect (OSTI)

    HUBER HJ

    2010-04-13

    The SpinTek rotary microfilter was tested on actual Hanford tank waste. The samples were a composite of archived Tank 241-AN-105 material and a sample representing single-shell tanks (SST). Simulants of the two samples have been used in non-rad test runs at the 222-S laboratory and at Savannah River National Laboratory (SRNL). The results of these studies are compared in this report. Two different nominal pore sizes for the sintered steel rotating disk filter were chosen: 0.5 and 0.1 {micro}m. The results suggest that the 0.5-{micro}m disk is preferable for Hanford tank waste for the following reasons: (1) The filtrate clarity is within the same range (<<4 ntu for both disks); (2) The filtrate flux is in general higher for the 0.5-{micro}m disk; and (3) The 0.1-{micro}m disk showed a higher likelihood of fouling. The filtrate flux of the actual tank samples is generally in the range of 20-30% compared to the equivalent non-rad tests. The AN-105 slurries performed at about twice the filtrate flux of the SST slurries. The reason for this difference has not been identified. Particle size distributions in both cases are very similar; comparison of the chemical composition is not conclusive. The sole hint towards what material was stuck in the filter pore holes came from the analysis of the dried flakes from the surface of the fouled 0.1-{micro}m disk. A cleaning approach developed by SRNL personnel to deal with fouled disks has been found adaptable when using actual Hanford samples. The use of 1 M nitric acid improved the filtrate flux by approximately two times; using the same simulants as in the non-rad test runs showed that the filtrate flux was restored to 1/2 of its original amount.

  20. Table 21. Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual

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

    Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual Projected (million metric tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 5060 5130 5185 5240 5287 5335 5379 5438 5482 5529 5599 5658 5694 5738 5797 5874 5925 5984 AEO 1995 5137 5174 5188 5262 5309 5361 5394 5441 5489 5551 5621 5680 5727 5775 5841 5889 5944 AEO 1996 5182 5224 5295 5355 5417 5464 5525 5589 5660 5735 5812 5879 5925 5981 6030 6087 6142 6203

  1. "Table 19. Total Delivered Industrial Energy Consumption, Projected vs. Actual"

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

    Total Delivered Industrial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",25.43,25.904,26.303,26.659,26.974,27.062,26.755,26.598,26.908,27.228,27.668,28.068,28.348,28.668,29.068,29.398,29.688,30.008 "AEO

  2. ACTUAL WASTE TESTING OF GYCOLATE IMPACTS ON THE SRS TANK FARM

    SciTech Connect (OSTI)

    Martino, C.

    2014-05-28

    Glycolic acid is being studied as a replacement for formic acid in the Defense Waste Processing Facility (DWPF) feed preparation process. After implementation, the recycle stream from DWPF back to the high-level waste Tank Farm will contain soluble sodium glycolate. Most of the potential impacts of glycolate in the Tank Farm were addressed via a literature review and simulant testing, but several outstanding issues remained. This report documents the actual-waste tests to determine the impacts of glycolate on storage and evaporation of Savannah River Site high-level waste. The objectives of this study are to address the following: ? Determine the extent to which sludge constituents (Pu, U, Fe, etc.) dissolve (the solubility of sludge constituents) in the glycolate-containing 2H-evaporator feed. ? Determine the impact of glycolate on the sorption of fissile (Pu, U, etc.) components onto sodium aluminosilicate solids. The first objective was accomplished through actual-waste testing using Tank 43H and 38H supernatant and Tank 51H sludge at Tank Farm storage conditions. The second objective was accomplished by contacting actual 2H-evaporator scale with the products from the testing for the first objective. There is no anticipated impact of up to 10 g/L of glycolate in DWPF recycle to the Tank Farm on tank waste component solubilities as investigated in this test. Most components were not influenced by glycolate during solubility tests, including major components such as aluminum, sodium, and most salt anions. There was potentially a slight increase in soluble iron with added glycolate, but the soluble iron concentration remained so low (on the order of 10 mg/L) as to not impact the iron to fissile ratio in sludge. Uranium and plutonium appear to have been supersaturated in 2H-evaporator feed solution mixture used for this testing. As a result, there was a reduction of soluble uranium and plutonium as a function of time. The change in soluble uranium concentration was independent of added glycolate concentration. The change in soluble plutonium content was dependent on the added glycolate concentration, with higher levels of glycolate (5 g/L and 10 g/L) appearing to suppress the plutonium solubility. The inclusion of glycolate did not change the dissolution of or sorption onto actual-waste 2H-evaporator pot scale to an extent that will impact Tank Farm storage and concentration. The effects that were noted involved dissolution of components from evaporator scale and precipitation of components onto evaporator scale that were independent of the level of added glycolate.

  3. Green Future Double Barrel House

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

    of Science in Construction Science, May 2017 Shelly Pottorf Faculty Advisor - AIA; LEED AP, CPHC Adjunct Assistant Professor, Prairie View A&M University School of ...

  4. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    6" ,"Released: February 7, 2008" ,"Next Update: October 2008" ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2007 through 2011 " ,"(Megawatts and 2006 Base Year)" ,"Projected Monthly Base","Year","Contiguous U.S.","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid"

  5. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    7" ,"Released: February 2009" ,"Next Update: October 2009" ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2007 and Projected 2008 through 2009 " ,"(Megawatts and 2007 Base Year)" ,"Projected Monthly Base","Year","Contiguous U.S.","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid"

  6. PERFORMANCE TESTING OF THE NEXT-GENERATION CSSX SOLVENT WITH ACTUAL SRS TANK WASTE

    SciTech Connect (OSTI)

    Pierce, R.; Peters, T.; Crowder, M.; Fink, S.

    2011-11-01

    Efforts are underway to qualify the Next-Generation Solvent for the Caustic Side Solvent Extraction (CSSX) process. Researchers at multiple national laboratories have been involved in this effort. As part of the effort to qualify the solvent extraction system at the Savannah River Site (SRS), SRNL performed a number of tests at various scales. First, SRNL completed a series of batch equilibrium, or Extraction-Scrub-Strip (ESS), tests. These tests used {approx}30 mL of Next-Generation Solvent and either actual SRS tank waste, or waste simulant solutions. The results from these cesium mass transfer tests were used to predict solvent behavior under a number of conditions. At a larger scale, SRNL assembled 12 stages of 2-cm (diameter) centrifugal contactors. This rack of contactors is structurally similar to one tested in 2001 during the demonstration of the baseline CSSX process. Assembly and mechanical testing found no issues. SRNL performed a nonradiological test using 35 L of cesium-spiked caustic waste simulant and 39 L of actual tank waste. Test results are discussed; particularly those related to the effectiveness of extraction.

  7. Filtration and Leach Testing for REDOX Sludge and S-Saltcake Actual Waste Sample Composites

    SciTech Connect (OSTI)

    Shimskey, Rick W.; Billing, Justin M.; Buck, Edgar C.; Daniel, Richard C.; Draper, Kathryn E.; Edwards, Matthew K.; Geeting, John GH; Hallen, Richard T.; Jenson, Evan D.; Kozelisky, Anne E.; MacFarlan, Paul J.; Peterson, Reid A.; Snow, Lanee A.; Swoboda, Robert G.

    2009-02-20

    A testing program evaluating actual tank waste was developed in response to Task 4 from the M-12 External Flowsheet Review Team (EFRT) issue response plan.( ) The test program was subdivided into logical increments. The bulk water-insoluble solid wastes that are anticipated to be delivered to the Waste Treatment and Immobilization Plant (WTP) were identified according to type such that the actual waste testing could be targeted to the relevant categories. Under test plan TP-RPP-WTP-467, eight broad waste groupings were defined. Samples available from the 222S archive were identified and obtained for testing. Under this test plan, a waste-testing program was implemented that included: • Homogenizing the archive samples by group as defined in the test plan • Characterizing the homogenized sample groups • Performing parametric leaching testing on each group for compounds of interest • Performing bench-top filtration/leaching tests in the hot cell for each group to simulate filtration and leaching activities if they occurred in the UFP2 vessel of the WTP Pretreatment Facility. This report focuses on filtration/leaching tests performed on two of the eight waste composite samples and follow-on parametric tests to support aluminum leaching results from those tests.

  8. Table 11a. Coal Prices to Electric Generating Plants, Projected vs. Actual

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

    a. Coal Prices to Electric Generating Plants, Projected vs. Actual" "Projected Price in Constant Dollars" " (constant dollars per million Btu in ""dollar year"" specific to each AEO)" ,"AEO $ Year",1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",1992,1.4699,1.4799,1.53,1.57,1.58,1.57,1.61,1.63,1.68,1.69,1.7,1.72,1.7,1.76,1.79,1.81,1.88,1.92 "AEO

  9. Table 11a. Coal Prices to Electric Generating Plants, Projected vs. Actual

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

    a. Coal Prices to Electric Generating Plants, Projected vs. Actual Projected Price in Constant Dollars (constant dollars per million Btu in "dollar year" specific to each AEO) AEO $ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1992 1.47 1.48 1.53 1.57 1.58 1.57 1.61 1.63 1.68 1.69 1.70 1.72 1.70 1.76 1.79 1.81 1.88 1.92 AEO 1995 1993 1.39 1.39 1.38 1.40 1.40 1.39 1.39 1.42 1.41 1.43 1.44 1.45 1.46 1.46 1.46 1.47

  10. Table 7a. Natural Gas Price, Electric Power Sector, Actual vs. Projected

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

    a. Natural Gas Price, Electric Power Sector, Actual vs. Projected Projected Price in Constant Dollars (constant dollars per million Btu in "dollar year" specific to each AEO) AEO $ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1992 2.44 2.48 2.57 2.66 2.70 2.79 2.84 2.92 3.04 3.16 3.25 3.36 3.51 3.60 3.77 3.91 3.97 4.08 AEO 1995 1993 2.39 2.48 2.42 2.45 2.45 2.53 2.59 2.78 2.91 3.10 3.24 3.38 3.47 3.53 3.61 3.68

  11. Characterization, Leaching, and Filtrations Testing of Ferrocyanide Tank sludge (Group 8) Actual Waste Composite

    SciTech Connect (OSTI)

    Fiskum, Sandra K.; Billing, Justin M.; Crum, J. V.; Daniel, Richard C.; Edwards, Matthew K.; Shimskey, Rick W.; Peterson, Reid A.; MacFarlan, Paul J.; Buck, Edgar C.; Draper, Kathryn E.; Kozelisky, Anne E.

    2009-02-28

    This is the final report in a series of eight reports defining characterization, leach, and filtration testing of a wide variety of Hanford tank waste sludges. The information generated from this series is intended to supplement the Waste Treatment and Immobilization Plant (WTP) project understanding of actual waste behaviors associated with tank waste sludge processing through the pretreatment portion of the WTP. The work described in this report presents information on a high-iron waste form, specifically the ferrocyanide tank waste sludge. Iron hydroxide has been shown to pose technical challenges during filtration processing; the ferrocyanide tank waste sludge represented a good source of the high-iron matrix to test the filtration processing.

  12. "Table 17. Total Delivered Residential Energy Consumption, Projected vs. Actual"

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

    Total Delivered Residential Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",10.31,10.36,10.36,10.37,10.38,10.4,10.4,10.41,10.43,10.43,10.44,10.45,10.46,10.49,10.51,10.53,10.56,10.6 "AEO 1995",,10.96,10.8,10.81,10.81,10.79,10.77,10.75,10.73,10.72,10.7,10.7,10.69,10.7,10.72,10.75,10.8,10.85 "AEO

  13. "Table 18. Total Delivered Commercial Energy Consumption, Projected vs. Actual"

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

    Total Delivered Commercial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",6.82,6.87,6.94,7,7.06,7.13,7.16,7.22,7.27,7.32,7.36,7.38,7.41,7.45,7.47,7.5,7.51,7.55 "AEO 1995",,6.94,6.9,6.95,6.99,7.02,7.05,7.08,7.09,7.11,7.13,7.15,7.17,7.19,7.22,7.26,7.3,7.34 "AEO

  14. "Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual"

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

    Total Delivered Transportation Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",23.62,24.08,24.45,24.72,25.06,25.38,25.74,26.16,26.49,26.85,27.23,27.55,27.91,28.26,28.61,28.92,29.18,29.5 "AEO 1995",,23.26,24.01,24.18,24.69,25.11,25.5,25.86,26.15,26.5,26.88,27.28,27.66,27.99,28.25,28.51,28.72,28.94 "AEO

  15. "Table 7a. Natural Gas Price, Electric Power Sector, Actual vs. Projected"

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

    a. Natural Gas Price, Electric Power Sector, Actual vs. Projected" "Projected Price in Constant Dollars" " (constant dollars per million Btu in ""dollar year"" specific to each AEO)" ,"AEO $ Year",1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",1992,2.44,2.48,2.57,2.66,2.7,2.79,2.84,2.92,3.04,3.16,3.25,3.36,3.51,3.6,3.77,3.91,3.97,4.08 "AEO

  16. An insight into actual energy use and its drivers in high-performance buildings

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

    Li, Cheng; Hong, Tianzhen; Yan, Da

    2014-07-12

    Using portfolio analysis and individual detailed case studies, we studied the energy performance and drivers of energy use in 51 high-performance office buildings in the U.S., Europe, China, and other parts of Asia. Portfolio analyses revealed that actual site energy use intensity (EUI) of the study buildings varied by a factor of as much as 11, indicating significant variation in real energy use in HPBs worldwide. Nearly half of the buildings did not meet the American Society of Heating, Refrigerating, and Air Conditioning Engineers (ASHRAE) Standard 90.1-2004 energy target, raising questions about whether a building’s certification as high performing accuratelymore » indicates that a building is energy efficient and suggesting that improvement in the design and operation of HPBs is needed to realize their energy-saving potential. We studied the influence of climate, building size, and building technologies on building energy performance and found that although all are important, none are decisive factors in building energy use. EUIs were widely scattered in all climate zones. There was a trend toward low energy use in small buildings, but the correlation was not absolute; some small HPBs exhibited high energy use, and some large HPBs exhibited low energy use. We were unable to identify a set of efficient technologies that correlated directly to low EUIs. In two case studies, we investigated the influence of occupant behavior as well as operation and maintenance on energy performance and found that both play significant roles in realizing energy savings. We conclude that no single factor determines the actual energy performance of HPBs, and adding multiple efficient technologies does not necessarily improve building energy performance; therefore, an integrated design approach that takes account of climate, technology, occupant behavior, and operations and maintenance practices should be implemented to maximize energy savings in HPBs. As a result, these findings are intended to help architects, engineers, operators, and policy makers improve the design and operation of HPBs.« less

  17. An insight into actual energy use and its drivers in high-performance buildings

    SciTech Connect (OSTI)

    Li, Cheng; Hong, Tianzhen; Yan, Da

    2014-07-12

    Using portfolio analysis and individual detailed case studies, we studied the energy performance and drivers of energy use in 51 high-performance office buildings in the U.S., Europe, China, and other parts of Asia. Portfolio analyses revealed that actual site energy use intensity (EUI) of the study buildings varied by a factor of as much as 11, indicating significant variation in real energy use in HPBs worldwide. Nearly half of the buildings did not meet the American Society of Heating, Refrigerating, and Air Conditioning Engineers (ASHRAE) Standard 90.1-2004 energy target, raising questions about whether a building’s certification as high performing accurately indicates that a building is energy efficient and suggesting that improvement in the design and operation of HPBs is needed to realize their energy-saving potential. We studied the influence of climate, building size, and building technologies on building energy performance and found that although all are important, none are decisive factors in building energy use. EUIs were widely scattered in all climate zones. There was a trend toward low energy use in small buildings, but the correlation was not absolute; some small HPBs exhibited high energy use, and some large HPBs exhibited low energy use. We were unable to identify a set of efficient technologies that correlated directly to low EUIs. In two case studies, we investigated the influence of occupant behavior as well as operation and maintenance on energy performance and found that both play significant roles in realizing energy savings. We conclude that no single factor determines the actual energy performance of HPBs, and adding multiple efficient technologies does not necessarily improve building energy performance; therefore, an integrated design approach that takes account of climate, technology, occupant behavior, and operations and maintenance practices should be implemented to maximize energy savings in HPBs. As a result, these findings are intended to help architects, engineers, operators, and policy makers improve the design and operation of HPBs.

  18. Table 11b. Coal Prices to Electric Generating Plants, Projected vs. Actual

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

    b. Coal Prices to Electric Generating Plants, Projected vs. Actual Projected Price in Nominal Dollars (nominal dollars per million Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1.50 1.55 1.64 1.73 1.78 1.82 1.92 2.01 2.13 2.22 2.30 2.41 2.46 2.64 2.78 2.90 3.12 3.30 AEO 1995 1.42 1.46 1.49 1.55 1.59 1.62 1.67 1.76 1.80 1.89 1.97 2.05 2.13 2.21 2.28 2.38 2.50 AEO 1996 1.35 1.35 1.37 1.39 1.42 1.46 1.50 1.56 1.62 1.67 1.75

  19. Table 2. Real Gross Domestic Product Growth Trends, Projected vs. Actual

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

    Real Gross Domestic Product Growth Trends, Projected vs. Actual Projected Real GDP Growth Trend (cumulative average percent growth in projected real GDP from first year shown for each AEO) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 3.09 3.15 2.86 2.78 2.73 2.65 2.62 2.60 2.56 2.53 2.52 2.49 2.45 2.41 2.40 2.36 2.32 2.29 AEO 1995 3.66 2.77 2.53 2.71 2.67 2.61 2.55 2.48 2.46 2.45 2.45 2.43 2.39 2.35 2.31 2.27 2.24 AEO 1996 2.61

  20. Table 7b. Natural Gas Price, Electric Power Sector, Actual vs. Projected

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

    b. Natural Gas Price, Electric Power Sector, Actual vs. Projected Projected Price in Nominal Dollars (nominal dollars per million Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 2.49 2.60 2.76 2.93 3.05 3.24 3.39 3.60 3.86 4.15 4.40 4.70 5.08 5.39 5.85 6.27 6.59 7.01 AEO 1995 2.44 2.61 2.61 2.70 2.78 2.95 3.11 3.44 3.72 4.10 4.43 4.78 5.07 5.33 5.64 5.95 6.23 AEO 1996 2.08 2.19 2.20 2.39 2.47 2.54 2.64 2.74 2.84 2.95 3.09

  1. FRACTIONAL CRYSTALLIZATION LABORATORY TESTING FOR INCLUSION & COPRECIPITATION WITH ACTUAL TANK WASTE

    SciTech Connect (OSTI)

    WARRANT, R.W.

    2006-12-11

    Fractional crystallization is being considered as a pretreatment method to support supplemental treatment of retrieved single-shell tank (SST) saltcake waste at the Hanford Site. The goal of the fractional crystallization process is to optimize the separation of the radioactivity (radionuclides) from the saltcake waste and send it to the Waste Treatment and Immobilization Plant and send the bulk of the saltcake to the supplemental treatment plant (bulk vitrification). The primary factors that influence the separation efficiency are (1) solid/liquid separation efficiency, (2) contaminant inclusions, and (3) co-precipitation. This is a report of testing for factors (2) and (3) with actual tank waste samples. For the purposes of this report, contaminant inclusions are defined as the inclusion of supernatant, containing contaminating radionuclides, in a pocket within the precipitating saltcake crystals. Co-precipitation is defined as the simultaneous precipitation of a saltcake crystal with a contaminating radionuclide. These two factors were tested for various potential fractional crystallization product salts by spiking the composite tank waste samples (SST Early or SST Late, external letter CH2M-0600248, ''Preparation of Composite Tank Waste Samples for ME-21 Project'') with the desired target salt and then evaporating to precipitate that salt. SST Early represents the typical composition of dissolved saltcake early in the retrieval process, and SST Late represents the typical composition during the later stages of retrieval.

  2. Relationship between self-reported activity levels and actual heart rates in teenagers

    SciTech Connect (OSTI)

    Terblanche, A.P.S.; Ozkaynak, H.; Spengler, J.D.; Butler, D.A. )

    1991-08-01

    A study was designed to explore the relationship between self-reported activity levels and actual heart rate (HR) as measured by a portable heart rate monitor. Twenty-two teenagers (8 boys, 14 girls, median age of 16) from Watertown High School, Massachusetts participated in this pilot study which involved continuous monitoring of HR during normal daily activities and simultaneous completion of a time-activity diary. There were 31 successful monitoring sessions ranging from 1.9 to 17 hours with a median monitoring time of 12.6 hours. Four unsuccessful monitoring sessions were experienced due to equipment failure. Apart from participant cooperation, the single most important factor affecting the feasibility of continuous heart rate monitoring was found to be equipment design. Th overall average heart rate observed was 88.4 bpm (SD = 24.3). An individual's correlation coefficient for perceived activity level (documented in half-hour intervals) and heart rate (averaged over the half-hour intervals) varied from 0.24 to 0.89. More than half of the correlation coefficients were below 0.40. There was a significant difference between average heart rate for time spent indoors (90 bpm) versus outdoors (103 bpm) even after correcting for sleeping time. It is concluded that continuous HR monitoring with simultaneous completion of a time/activity dairy is feasible and is a promising source of information for studies on exposure to air pollutants.

  3. Predicted Versus Actual Savings for a Low-Rise Multifamily Retrofit in Boulder, Colorado

    SciTech Connect (OSTI)

    Arena, L.; Williamson, J.

    2013-11-01

    To determine the most cost-effective methods of improving buildings, accurate analysis and prediction of the energy use of existing buildings is essential. However, multiple studies confirm that analysis methods tend to over-predict energy use in poorly insulated, leaky homes and thus, the savings associated with improving those homes. In this project, the Building America CARB team evaluated the retrofit of a multifamily building in Boulder, CO. The updated property is a 37 unit, 2 story apartment complex built in 1950, which underwent renovations in early 2009 to bring it into compliance with Boulder, CO's SmartRegs ordinance. Goals of the study were to: 1) evaluate predicted versus actual savings due to the improvements, 2) identify areas where the modeling assumptions may need to be changed, and 3) determine common changes made by renters that would negatively impact energy savings. Other issues that were investigated include the effects of improving building efficiency on tenant comfort, the impact on tenant turnover rates, and the potential market barriers for this type of community scale project.

  4. Predicted Versus Actual Savings for a Low-Rise Multifamily Retrofit in Boulder, Colorado

    SciTech Connect (OSTI)

    Arena, L.; Williamson, J.

    2013-11-01

    To determine the most cost-effective methods of improving buildings, accurate analysis and prediction of the energy use of existing buildings is essential. However, multiple studies confirm that analysis methods tend to over-predict energy use in poorly insulated, leaky homes and thus, the savings associated with improving those homes. In NREL's report titled 'Assessing and Improving the Accuracy of Energy Analysis of Residential Buildings,' researchers propose a method for improving the accuracy of residential energy analysis methods. A key step in this process involves the comparisons of predicted versus metered energy use and savings. In support of this research need, CARB evaluated the retrofit of a multifamily building in Boulder, CO. The updated property is a 37 unit, 2 story apartment complex built in 1950, which underwent renovations in early 2009 to bring it into compliance with Boulder, CO's SmartRegs ordinance. Goals of the study were to: 1) evaluate predicted versus actual savings due to the improvements, 2) identify areas where the modeling assumptions may need to be changed, and 3) determine common changes made by renters that would negatively impact energy savings. In this study, CARB seeks to improve the accuracy of modeling software while assessing retrofit measures to specifically determine which are most effective for large multifamily complexes in the cold climate region. Other issues that were investigated include the effects of improving building efficiency on tenant comfort, the impact on tenant turnover rates, and the potential market barriers for this type of community scale project.

  5. ACTUAL-WASTE TESTING OF ULTRAVIOLET LIGHT TO AUGMENT THE ENHANCED CHEMICAL CLEANING OF SRS SLUDGE

    SciTech Connect (OSTI)

    Martino, C.; King, W.; Ketusky, E.

    2012-07-10

    In support of Savannah River Site (SRS) tank closure efforts, the Savannah River National Laboratory (SRNL) conducted Real Waste Testing (RWT) to evaluate Enhanced Chemical Cleaning (ECC), an alternative to the baseline 8 wt% oxalic acid (OA) chemical cleaning technology for tank sludge heel removal. ECC utilizes a more dilute OA solution (2 wt%) and an oxalate destruction technology using ozonolysis with or without the application of ultraviolet (UV) light. SRNL conducted tests of the ECC process using actual SRS waste material from Tanks 5F and 12H. The previous phase of testing involved testing of all phases of the ECC process (sludge dissolution, OA decomposition, product evaporation, and deposition tank storage) but did not involve the use of UV light in OA decomposition. The new phase of testing documented in this report focused on the use of UV light to assist OA decomposition, but involved only the OA decomposition and deposition tank portions of the process. Compared with the previous testing at analogous conditions without UV light, OA decomposition with the use of UV light generally reduced time required to reach the target of <100 mg/L oxalate. This effect was the most pronounced during the initial part of the decomposition batches, when pH was <4. For the later stages of each OA decomposition batch, the increase in OA decomposition rate with use of the UV light appeared to be minimal. Testing of the deposition tank storage of the ECC product resulted in analogous soluble concentrations regardless of the use or non-use of UV light in the ECC reactor.

  6. STEAM REFORMING TECHNOLOGY DEMONSTRATION FOR THE DESTRUCTION OF ORGANICS ON ACTUAL DOE SAVANNAH RIVER SITE TANK 48H WASTE 9138

    SciTech Connect (OSTI)

    Burket, P

    2009-02-24

    This paper describes the design of the Bench-scale Steam Reformer (BSR); a processing unit for demonstrating steam reforming technology on actual radioactive waste [1]. It describes the operating conditions of the unit used for processing a sample of Savannah River Site (SRS) Tank 48H waste. Finally, it compares the results from processing the actual waste in the BSR to processing simulant waste in the BSR to processing simulant waste in a large pilot scale unit, the Fluidized Bed Steam Reformer (FBSR), operated at Hazen Research Inc. in Golden, CO. The purpose of this work was to prove that the actual waste reacted in the same manner as the simulant waste in order to validate the work performed in the pilot scale unit which could only use simulant waste.

  7. Final Report. LAW Glass Formulation to Support AP-101 Actual Waste Testing, VSL-03R3470-2, Rev. 0

    SciTech Connect (OSTI)

    Muller, I. S.; Pegg, I. L.; Rielley, Elizabeth; Carranza, Isidro; Hight, Kenneth; Lai, Shan-Tao T.; Mooers, Cavin; Bazemore, Gina; Cecil, Richard; Kruger, Albert A.

    2015-06-22

    The main objective of the work was to develop and select a glass formulation for vitrification testing of the actual waste sample of LAW AP-101 at Battelle - Pacific Northwest Division (PNWD). Other objectives of the work included preparation and characterization of glasses to demonstrate compliance with contract and processing requirements, evaluation of the ability to achieve waste loading requirements, testing to demonstrate compatibility of the glass melts with melter materials of construction, comparison of the properties of simulant and actual waste glasses, and identification of glass formulation issues with respect to contract specifications and processing requirements.

  8. Next Update: December 2011 Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region,

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

    Released: December 2010 Next Update: December 2011 Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, 2009 and Projected 2010 through 2014 (Megawatts and 2009 Base Year) 2009 725,958 46,550 37,963 55,944 161,241 191,032 41,465 63,518 128,245 Contiguou s U.S. FRCC MRO (U.S.) NPCC (U.S.) RFC SERC SPP TRE WECC (U.S.) 772,089 46,006 42,240 60,215 177,688 201,350 43,395 63,810 137,385 785,069 46,124 42,733 60,820 181,867 205,351

  9. Next Update: December 2011 Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region,

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

    b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, 2009 and Projected 2010 through 2014 (Megawatts and 2009 Base Year) 2009/2010 668,818 53,022 35,351 44,864 143,827 193,135 32,863 56,191 109,565 Contiguous U.S. FRCC MRO (U.S.) NPCC (U.S.) RFC SERC SPP TRE WECC (U.S.) 639,073 46,235 35,722 46,374 143,040 183,614 31,415 43,823 108,850 646,845 46,821 36,816 46,529 146,591 186,364 33,047 43,823 106,854 657,839 47,558 37,359 46,753

  10. Ion exchange removal of cesium from simulated and actual supernate from Hanford tanks 241-SY-101 and 241-SY-103

    SciTech Connect (OSTI)

    Brown, G.N.; Bontha, J.R.; Carlson, C.D.

    1995-09-01

    Pacific Northwest Laboratory (PNL), in conjunction with the Process Chemistry and Statistics Section of Westinghouse Hanford Company (WHC), conducted this study as part of the Supernatant Treatment Development Task for the Initial Pretreatment Module (IPM) Applied Engineering Project. The study assesses the performance of the CS-100 ion exchange material for removing cesium from simulated and actual alkaline supernate from Hanford tanks 241-SY-101 and 241-SY-103. The objective of these experiments is to compare the cesium ion exchange loading and elution profiles of actual and simulated wastes. Specific experimental objectives include (1) demonstration of decontamination factors (DF) for cesium removal, 92) verification of simulant performance, (3) investigation of waste/exchanger chemistry, and (4) determination of the radionuclide content of the regenerated CS-100 resin prior to disposal.

  11. Sugars Can Actually Be Good For Your Health (LBNL Science at the Theater)

    ScienceCinema (OSTI)

    Bertozzi, Carolyn

    2011-10-04

    Like peanut M&Ms, all cells are coated with sugars but the functions of these sugar coatings were a mystery until very recently. This presentation will highlight recent fascinating discoveries regarding why cells are coated with sugars, as well as new tools for cancer detection that take advantage of the cells sugar coating. Professor Bertozzis lab focuses on profiling changes in cell surface glycosylation associated with cancer, inflammation and bacterial infection, and exploiting this information for development of diagnostic and therapeutic approaches. In addition, her group develops nanoscience-based technologies for probing cell function and for medical diagnostics.

  12. DESTRUCTION OF TETRAPHENYLBORATE IN TANK 48H USING WET AIR OXIDATION BATCH BENCH SCALE AUTOCLAVE TESTING WITH ACTUAL RADIOACTIVE TANK 48H WASTE

    SciTech Connect (OSTI)

    Adu-Wusu, K; Paul Burket, P

    2009-03-31

    Wet Air Oxidation (WAO) is one of the two technologies being considered for the destruction of Tetraphenylborate (TPB) in Tank 48H. Batch bench-scale autoclave testing with radioactive (actual) Tank 48H waste is among the tests required in the WAO Technology Maturation Plan. The goal of the autoclave testing is to validate that the simulant being used for extensive WAO vendor testing adequately represents the Tank 48H waste. The test objective was to demonstrate comparable test results when running simulated waste and real waste under similar test conditions. Specifically: (1) Confirm the TPB destruction efficiency and rate (same reaction times) obtained from comparable simulant tests, (2) Determine the destruction efficiency of other organics including biphenyl, (3) Identify and quantify the reaction byproducts, and (4) Determine off-gas composition. Batch bench-scale stirred autoclave tests were conducted with simulated and actual Tank 48H wastes at SRNL. Experimental conditions were chosen based on continuous-flow pilot-scale simulant testing performed at Siemens Water Technologies Corporation (SWT) in Rothschild, Wisconsin. The following items were demonstrated as a result of this testing. (1) Tetraphenylborate was destroyed to below detection limits during the 1-hour reaction time at 280 C. Destruction efficiency of TPB was > 99.997%. (2) Other organics (TPB associated compounds), except biphenyl, were destroyed to below their respective detection limits. Biphenyl was partially destroyed in the process, mainly due to its propensity to reside in the vapor phase during the WAO reaction. Biphenyl is expected to be removed in the gas phase during the actual process, which is a continuous-flow system. (3) Reaction byproducts, remnants of MST, and the PUREX sludge, were characterized in this work. Radioactive species, such as Pu, Sr-90 and Cs-137 were quantified in the filtrate and slurry samples. Notably, Cs-137, boron and potassium were shown as soluble as a result of the WAO reaction. (4) Off-gas composition was measured in the resulting gas phase from the reaction. Benzene and hydrogen were formed during the reaction, but they were reasonably low in the off-gas at 0.096 and 0.0063 vol% respectively. Considering the consistency in replicating similar test results with simulated waste and Tank 48H waste under similar test conditions, the results confirm the validity of the simulant for other WAO test conditions.

  13. Analysis of Actual Operating Conditions of an Off-grid Solid Oxide Fuel Cell

    SciTech Connect (OSTI)

    Dennis Witmer; Thomas Johnson; Jack Schmid

    2008-12-31

    Fuel cells have been proposed as ideal replacements for other technologies in remote locations such as Rural Alaska. A number of suppliers have developed systems that might be applicable in these locations, but there are several requirements that must be met before they can be deployed: they must be able to operate on portable fuels, and be able to operate with little operator assistance for long periods of time. This project was intended to demonstrate the operation of a 5 kW fuel cell on propane at a remote site (defined as one without access to grid power, internet, or cell phone, but on the road system). A fuel cell was purchased by the National Park Service for installation in their newly constructed visitor center at Exit Glacier in the Kenai Fjords National Park. The DOE participation in this project as initially scoped was for independent verification of the operation of this demonstration. This project met with mixed success. The fuel cell has operated over 6 seasons at the facility with varying degrees of success, with one very good run of about 1049 hours late in the summer of 2006, but in general the operation has been below expectations. There have been numerous stack failures, the efficiency of electrical generation has been lower than expected, and the field support effort required has been far higher than expected. Based on the results to date, it appears that this technology has not developed to the point where demonstrations in off road sites are justified.

  14. Next Update: December 2011 Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region,

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

    . Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, 2009 and Projected 2010 through 2014 2009 3,832,180 225,966 213,797 285,625 880,377 997,142 202,301 308,278 718,694 Contiguous U.S. FRCC MRO (U.S.) NPCC (U.S.) RFC SERC SPP TRE WECC (U.S.) 3,969,750 223,174 225,167 291,540 961,436 1,027,470 211,438 310,444 719,081 4,084,175 225,498 229,258 292,816 1,024,183 1,051,645 215,333 316,194 729,248 4,203,875 229,393 240,817 295,623 1,081,320 1,072,124

  15. Next Update: October 2009 Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region,

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

    1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, 2006 and Projected 2008 through 2012 2007 4,012,728 232,405 217,602 301,766 954,700 1,049,298 210,875 307,064 739,018 Contiguous U.S. FRCC MRO (U.S.) NPCC (U.S.) RFC SERC SPP TRE (ERCOT) WECC (U.S.) 4,085,683 242,923 225,058 301,767 973,800 1,073,081 208,532 313,946 746,575 4,149,201 248,996 230,745 305,223 984,000 1,086,304 212,884 319,355 761,694 4,226,516 255,216 239,483 308,534 999,200

  16. Next Update: October 2010 Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region,

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

    Jaunary 2010 Next Update: October 2010 Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, 2008 and Projected 2009 through 2013 2008 3,989,058 226,874 227,536 297,362 936,201 1,035,390 207,603 312,401 745,691 Contiguous U.S. FRCC MRO (U.S.) NPCC (U.S.) RFC SERC SPP TRE WECC (U.S.) 4,025,705 227,690 233,519 295,883 958,792 1,051,350 207,850 312,205 738,416 4,076,698 228,579 239,702 295,753 967,962 1,067,893 211,343 315,065 750,401

  17. Baseballs and Barrels: World Statistics Day

    Broader source: Energy.gov [DOE]

    Statistics don’t just help us answer trivia questions – they also help us make intelligent decisions. For example, if I heat my home with natural gas, I’m probably interested in what natural gas prices are likely to be this winter.

  18. New Mexico--West Natural Gas Liquids Lease Condensate, Reserves...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Reserves Based Production (Million Barrels) New Mexico--West Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3...

  19. New Mexico--East Natural Gas Liquids Lease Condensate, Reserves...

    Gasoline and Diesel Fuel Update (EIA)

    Reserves Based Production (Million Barrels) New Mexico--East Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3...

  20. California (with State Offshore) Natural Gas Plant Liquids, Reserves...

    Gasoline and Diesel Fuel Update (EIA)

    Reserves Based Production (Million Barrels) California (with State Offshore) Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 ...

  1. ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Assessment Area,"

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

    1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Assessment Area," ,"1990-2010 Actual, 2011-2015 Projected" ,"(Thousands of Megawatthours)" ,"Interconnection","NERC Regional Assesment Area" ,,,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,"2011E","2012E","2013E","2014E","2015E" ,"Eastern

  2. ACTUAL-WASTE TESTS OF ENHANCED CHEMICAL CLEANING FOR RETRIEVAL OF SRS HLW SLUDGE TANK HEELS AND DECOMPOSITION OF OXALIC ACID

    SciTech Connect (OSTI)

    Martino, C.; King, W.; Ketusky, E.

    2012-01-12

    Savannah River National Laboratory conducted a series of tests on the Enhanced Chemical Cleaning (ECC) process using actual Savannah River Site waste material from Tanks 5F and 12H. Testing involved sludge dissolution with 2 wt% oxalic acid, the decomposition of the oxalates by ozonolysis (with and without the aid of ultraviolet light), the evaporation of water from the product, and tracking the concentrations of key components throughout the process. During ECC actual waste testing, the process was successful in decomposing oxalate to below the target levels without causing substantial physical or chemical changes in the product sludge.

  3. ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Council Region, "

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

    3 and Projected 2004 through 2008 " ,"(Thousands of Megawatthours and 2003 Base Year)" ,"Net Energy For Load (Annual)",,"Contiguous U.S. ","Eastern Power Grid",,,,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"ECAR","FRCC","MAAC","MAIN","MAPP (U.S.) ","NPCC (U.S.)

  4. ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Council Region, "

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

    4 and Projected 2005 through 2009 " ,"(Thousands of Megawatthours and 2004 Base Year)" ,"Net Energy For Load (Annual)",,"Contiguous U.S. ","Eastern Power Grid",,,,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"ECAR","FRCC","MAAC","MAIN","MAPP/MRO (U.S.) ","NPCC (U.S.)

  5. ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Council Region, "

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

    2005 and Projected 2006 through 2010 " ,"(Thousands of Megawatthours and 2005 Base Year)" ,"Net Energy For Load (Annual)",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC","MRO (U.S.) ","NPCC (U.S.) ","RFC","SERC","SPP","ERCOT","WECC (U.S.) "

  6. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Council Region, "

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

    3 and Projected 2004 through 2008 " ,"(Megawatts and 2003 Base Year)",,,," " ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"ECAR","FRCC","MAAC","MAIN","MAPP (U.S.) ","NPCC (U.S.)

  7. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Council Region, "

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

    4 and Projected 2005 through 2009 " ,"(Megawatts and 2004 Base Year)",,,," " ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"ECAR","FRCC","MAAC","MAIN","MAPP/MRO (U.S.) ","NPCC (U.S.)

  8. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Council Region, "

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

    2005 and Projected 2006 through 2010 " ,"(Megawatts and 2005 Base Year)" ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC","MRO (U.S.) ","NPCC (U.S.) ","RFC","SERC","SPP","ERCOT","WECC (U.S.) "

  9. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, "

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

    3 and Projected 2004 through 2008 " ,"(Megawatts and 2003 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"ECAR","FRCC","MAAC","MAIN","MAPP (U.S.) ","NPCC (U.S.) ","SERC","SPP","ERCOT","WECC (U.S.)

  10. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, "

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

    4 and Projected 2005 through 2009 " ,"(Megawatts and 2004 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"ECAR","FRCC","MAAC","MAIN","MAPP/MRO (U.S.) ","NPCC (U.S.) ","SERC","SPP","ERCOT","WECC (U.S.)

  11. Characterization, Leaching, and Filtration Testing for Bismuth Phosphate Sludge (Group 1) and Bismuth Phosphate Saltcake (Group 2) Actual Waste Sample Composites

    SciTech Connect (OSTI)

    Lumetta, Gregg J.; Buck, Edgar C.; Daniel, Richard C.; Draper, Kathryn; Edwards, Matthew K.; Fiskum, Sandra K.; Hallen, Richard T.; Jagoda, Lynette K.; Jenson, Evan D.; Kozelisky, Anne E.; MacFarlan, Paul J.; Peterson, Reid A.; Shimskey, Rick W.; Sinkov, Sergey I.; Snow, Lanee A.

    2009-02-19

    A testing program evaluating actual tank waste was developed in response to Task 4 from the M-12 External Flowsheet Review Team (EFRT) issue response plan.() The test program was subdivided into logical increments. The bulk water-insoluble solid wastes that are anticipated to be delivered to the Waste Treatment and Immobilization Plant (WTP) were identified according to type such that the actual waste testing could be targeted to the relevant categories. Eight broad waste groupings were defined. Samples available from the 222S archive were identified and obtained for testing. The actual waste-testing program included homogenizing the samples by group, characterizing the solids and aqueous phases, and performing parametric leaching tests. Two of the eight defined groups—bismuth phosphate sludge (Group 1) and bismuth phosphate saltcake (Group 2)—are the subjects of this report. The Group 1 waste was anticipated to be high in phosphorus and was implicitly assumed to be present as BiPO4 (however, results presented here indicate that the phosphate in Group 1 is actually present as amorphous iron(III) phosphate). The Group 2 waste was also anticipated to be high in phosphorus, but because of the relatively low bismuth content and higher aluminum content, it was anticipated that the Group 2 waste would contain a mixture of gibbsite, sodium phosphate, and aluminum phosphate. Thus, the focus of the Group 1 testing was on determining the behavior of P removal during caustic leaching, and the focus of the Group 2 testing was on the removal of both P and Al. The waste-type definition, archived sample conditions, homogenization activities, characterization (physical, chemical, radioisotope, and crystal habit), and caustic leaching behavior as functions of time, temperature, and hydroxide concentration are discussed in this report. Testing was conducted according to TP-RPP-WTP-467.

  12. Lipopolysaccharide density and structure govern the extent and distance of nanoparticle interaction with actual and model bacterial outer membranes

    SciTech Connect (OSTI)

    Jacobson, Kurt H.; Gunsolus, Ian L.; Kuech, Thomas R.; Troiano, Julianne M.; Melby, Eric S.; Lohse, Samuel E.; Hu, Dehong; Chrisler, William B.; Murphy, Catherine; Orr, Galya; Geiger, Franz M.; Haynes, Christy L.; Pedersen, Joel A.

    2015-07-24

    Design of nanomedicines and nanoparticle-based antimicrobial and antifouling formulations, and assessment of the potential implications of nanoparticle release into the environment require understanding nanoparticle interaction with bacterial surfaces. Here we demonstrate electrostatically driven association of functionalized nanoparticles with lipopolysaccharides of Gram-negative bacterial outer membranes and find that lipopolysaccharide structure influences the extent and location of binding relative to the lipid-solution interface. By manipulating the lipopolysaccharide content in Shewanella oneidensis outer membranes, we observed electrostatically driven interaction of cationic gold nanoparticles with the lipopolysaccharide-containing leaflet. We probed this interaction by quartz crystal microbalance with dissipation monitoring (QCM-D) and second harmonic generation (SHG) using solid-supported lipopolysaccharide-containing bilayers. Association of cationic nanoparticles increased with lipopolysaccharide content, while no association of anionic nanoparticles was observed. The harmonic-dependence of QCM-D measurements suggested that a population of the cationic nanoparticles was held at a distance from the outer leaflet-solution interface of bilayers containing smooth lipopolysaccharides (those bearing a long O-polysaccharide). Additionally, smooth lipopolysaccharides held the bulk of the associated cationic particles outside of the interfacial zone probed by SHG. Our results demonstrate that positively charged nanoparticles are more likely to interact with Gram-negative bacteria than are negatively charged particles, and this interaction occurs primarily through lipopolysaccharides.

  13. Tracking target objects orbiting earth using satellite-based telescopes

    DOE Patents [OSTI]

    De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

    2014-10-14

    A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

  14. SU-E-T-417: A Method for Predicting and Correcting the Dosimetric Effect of a Radiotherapy Treatment Couch in Actual Treatment Position

    SciTech Connect (OSTI)

    Duan, J; Shen, S; Wu, X; Huang, M; Benhabib, S; Cardan, R; Popple, R; Brezovich, I

    2014-06-01

    Purpose: Although radiation attenuation by the treatment couch can be included in the calculation of radiotherapy dose, difference between planned and actual treatment couch positions can generate significant dose discrepancies. We propose a method to predict and correct the dosimetric effect of the couch in actual treatment position. Methods: The couch transmission factor, T, varies with beam angle, G, couch lateral position, x, and vertical position, y, i.e., T=T(x,y,G). If T(x,y,G) is known for a fixed couch vertical position y=h, the transmission of central-axis beam (CAX) T(x,y,G) can be obtained by T(x,y,G)=T(x{sup +},h,G), where x{sup +}=x-(y-h)tan(G) and G is the angle between the beam and the vertical axis. Similarly, the transmission of any off-CAX point can be obtained using a similar formula. We measured CAX couch transmission at a fixed couch vertical position over the couch lateral motion range for all gantry angles by continuously scanning rotating arc beams. A 2D couch transmission correction matrix can thus be generated from T(x,h,G) for each treatment field for the actual couch position. By applying the transmission correction matrix to the planned field dose, the couch effect can be predicted and corrected. To verify this method, we measured couch transmission T(x, y=10cm, G=225)(225=IEC 135) and compared to that obtained from equivalent T(x{sup +}, y=3cm, G=225) over the range of lateral motion with a step size of 2 cm . Results: The measured couch transmission factors T(x, y=10cm, G=225) are in excellent agreement with those obtained from the equivalent T(x{sup +}, y=3cm, G=225). The mean difference is 0.004060.00135. Conclusion: The couch transmission correction matrix for any couch position and beam angle can be obtained from one set of scanning measurements at a fixed couch vertical position. The dosimetric effect of the treatment couch can be predicted and corrected by applying the couch transmission correction to the planned dose.

  15. Alabama (with State Offshore) Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Reserves (Million Barrels) Proved Reserves (Million Barrels) Alabama (with State Offshore) Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 182 1980's 193 167 158 166 152 143 139 132 130 130 1990's 122 110 118 103 91 72 67 59 50 50 2000's 46 32 29 27 21 30 15 21 14 16 2010's 18 19 18 14 13 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  16. Alaska (with Total Offshore) Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 13 1980's 11 10 9 8 0 382 381 418 401 380 1990's 340 360 347 321 301 306 337 631 320 299 2000's 277 405 405 387 369 352 338 325 312 299 2010's 288 288 288 288 241 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  17. Federal Offshore--California Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Federal Offshore--California Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0 1980's 0 0 0 0 10 12 16 19 1990's 13 11 15 20 17 21 19 10 8 0 2000's 1 1 0 0 0 0 0 0 1 1 2010's 1 1 1 2 2 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  18. Louisiana (with State Offshore) Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Louisiana (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400 287 301 294 294 1990's 324 321 317 260 281 430 381 261 234 281 2000's 241 204 186 183 167 191 176 191 201 231 2010's 216 192 189 212 243 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  19. Louisiana--North Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Louisiana--North Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 54 1980's 59 63 59 50 38 47 39 33 39 40 1990's 38 38 41 38 48 55 61 50 34 36 2000's 35 35 30 48 53 57 60 69 68 98 2010's 79 54 35 52 83 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  20. Louisiana--South Onshore Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Louisiana--South Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 413 1980's 273 291 258 289 225 222 220 235 228 215 1990's 249 242 229 201 214 359 284 199 187 222 2000's 178 128 119 100 87 103 94 97 78 90 2010's 113 94 134 144 145 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  1. Lower 48 Federal Offshore Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Lower 48 Federal Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 363 382 350 331 337 1990's 295 329 295 309 309 239 245 389 370 427 2000's 515 486 511 364 423 416 399 369 321 302 2010's 341 355 405 335 399 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  2. Mississippi (with State Offshore) Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Future Production (Million Barrels) Expected Future Production (Million Barrels) Mississippi (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 5 1980's 5 5 6 6 5 4 3 3 3 3 1990's 3 3 3 3 3 3 2 2 3 3 2000's 2 2 2 2 1 2 2 3 3 4 2010's 4 6 4 3 4 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  3. Utah and Wyoming Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Utah and Wyoming Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 280 1980's 294 363 381 483 577 681 700 701 932 704 1990's 641 580 497 458 440 503 639 680 600 531 2000's 858 782 806 756 765 710 686 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

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

    SciTech Connect (OSTI)

    Hong, Tianzhen; Chang, Wen-Kuei; Lin, Hung-Wen

    2013-05-01

    Buildings consume more than one third of the world?s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980 to 2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: 1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; 2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; 3) the weather impact is greater for buildings in colder climates than warmer climates; 4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small office; and 5) simulated energy savings and peak demand reduction by energy conservation measures using the TMY3 weather data can be significantly underestimated or overestimated. It is crucial to run multi-decade simulations with AMY weather data to fully assess the impact of weather on the long-term performance of buildings, and to evaluate the energy savings potential of energy conservation measures for new and existing buildings from a life cycle perspective.

  5. Replacing the whole barrel of oil with plants and microbes

    ScienceCinema (OSTI)

    Simmons, Blake

    2014-06-24

    In this May 13, 2013 talk, Blake Simmons discusses how scientists are exploring how plants and microbes can be used to replace many of the everyday goods we use that are derived from petroleum. To watch the entire entire Science at the Theater event, in which seven of our scientists present BIG ideas in eight minutes each.

  6. Extrusion of electrode material by liquid injection into extruder barrel

    DOE Patents [OSTI]

    Keller, D.G.; Giovannoni, R.T.; MacFadden, K.O.

    1998-03-10

    An electrode sheet product is formed using an extruder having a feed throat and a downstream section by separately mixing an active electrode material and a solid polymer electrolyte composition that contains lithium salt. The active electrode material is fed into the feed throat of the extruder, while a portion of at least one fluid component of the solid polymer electrolyte composition is introduced to the downstream section. The active electrode material and the solid polymer electrolyte composition are compounded in a downstream end of the extruder. The extruded sheets, adhered to current collectors, can be formed into battery cells. 1 fig.

  7. Alabama Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 3,691 1,856 3,634 3,342 4,651 6,493 8,348 8,892 7,157 7,473 7,007 6,324 2002 9,105 8,006 7,301 7,217 7,316 12,396 15,228 15,892 11,855 7,064 5,415 5,608 2003 9,428 5,069 4,057 5,528 4,274 8,673 12,971 17,126 6,906 2,735 3,573 5,791 2004 9,038 8,270 8,672 8,552 10,409 11,388 17,481 14,662 9,689 7,254 4,995 6,647 2005 6,019 4,524 6,532 3,991 6,678 11,921 15,974 17,573 9,582 5,720 6,523 9,749 2006 4,041 5,197 7,726 9,059 11,642

  8. Alaska Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 3,189 2,833 2,962 2,255 2,427 2,439 2,574 2,392 2,865 2,986 3,235 2002 2,769 2,342 2,663 2,562 2,398 2,518 2,786 2,482 2,601 2,861 2,605 3,118 2003 3,346 2,960 2,855 2,590 2,515 2,769 2,869 2,668 2,628 2,848 2,990 3,365 2004 3,694 3,316 2,860 2,640 3,027 3,275 3,317 2,960 2,999 2,788 3,003 3,762 2005 3,422 2,993 3,098 2,769 2,815 2,968 3,527 3,809 3,157 3,507 3,443 3,776 2006 3,831 3,390 3,554 3,174 3,327 3,641 3,800 3,741 3,237

  9. Arkansas Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 116,522 156,627 169,257 1970's 181,351 172,154 166,522 157,529 123,975 116,237 109,533 104,096 106,792 109,452 1980's 111,808 92,986 124,611 127,561 135,161 155,099 131,075 141,151 166,573 174,158 1990's 174,956 164,702 202,479 196,370 187,673 187,242 221,822 208,514 188,372 170,006 2000's 171,642 166,804 161,871 169,599 187,069 190,533 270,293 269,886 446,457 679,952 2010's 926,639 1,072,212 1,146,168 1,139,654

  10. Colorado Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 116,857 121,424 118,754 1970's 105,804 108,537 116,949 137,725 144,629 171,629 183,972 188,792 183,693 191,239 1980's 188,001 195,706 209,892 163,545 173,257 178,233 163,684 164,557 191,544 216,737 1990's 242,997 285,961 323,041 400,985 453,207 523,084 572,071 637,375 696,321 722,738 2000's 752,985 817,206 937,245 1,011,285 1,079,235 1,133,086 1,202,821 1,242,571 1,389,399 1,499,070 2010's 1,578,379 1,637,576

  11. Florida Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 123 108 50 1970's 903 15,521 33,857 38,137 44,383 43,165 48,171 51,595 50,190 1980's 40,638 32,470 22,515 21,056 12,585 10,545 8,833 8,281 7,484 7,534 1990's 6,483 4,884 6,657 7,085 7,486 6,463 6,006 6,114 5,796 5,933 2000's 6,491 5,710 3,353 3,087 3,123 2,616 2,540 1,778 2,436 257 2010's 12,409 15,125 773 292 369

    Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 639 550 577 597 660 571 638 645 665 708

  12. Kentucky Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 89,168 89,024 81,304 1970's 77,892 72,723 63,648 62,396 71,876 60,511 66,137 60,902 70,044 59,520 1980's 57,180 61,312 51,924 46,720 61,518 73,126 80,195 70,125 73,629 72,417 1990's 75,333 78,904 79,690 86,966 73,081 74,754 81,435 79,547 81,869 76,770 2000's 81,545 81,723 88,259 87,608 94,259 92,795 95,320 95,437 114,116 113,300 2010's 135,330 124,243 106,122 94,665 78,737

    Year Jan Feb Mar Apr May Jun Jul Aug

  13. Louisiana Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 14,443 11,997 14,142 21,746 20,692 21,707 32,832 38,346 25,901 19,391 10,270 11,549 2002 20,006 19,396 24,864 27,662 28,456 34,039 40,542 41,790 32,420 23,674 16,204 14,750 2003 19,955 15,360 14,860 18,716 20,153 22,791 26,663 28,685 20,590 18,689 15,461 14,484 2004 17,038 17,344 19,280 15,608 19,393 22,176 24,790 27,960 23,911 22,987 16,905 17,970 2005 19,636 15,729 19,997 22,435 28,666 30,717 32,870 31,768 29,702 18,668 13,130

  14. Michigan Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 33,589 40,480 36,163 1970's 38,851 25,662 34,221 44,579 69,133 102,113 119,262 129,954 148,047 159,731 1980's 158,302 152,593 153,051 138,910 144,537 131,855 127,287 146,996 146,145 155,988 1990's 172,151 195,749 194,815 204,635 222,657 238,203 245,740 305,950 278,076 277,364 2000's 296,556 275,036 274,476 236,987 259,681 261,112 263,009 264,907 153,130 153,736 2010's 131,118 138,162 129,333 123,622 114,946

  15. Mississippi Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Feet) (No intransit Receipts) (Million Cubic Feet) Mississippi Natural Gas Imports (No intransit Receipts) (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 2010's 0 5,774 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Natural Gas Imports (Summary) Mississippi U.S. Natural Gas

  16. Montana Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 25,866 19,313 41,229 1970's 42,705 32,720 33,474 56,175 54,873 40,734 42,563 46,819 46,522 53,888 1980's 51,867 56,565 56,517 51,967 51,474 52,494 46,592 46,456 51,654 51,307 1990's 50,429 51,999 53,867 54,528 50,416 50,264 50,996 52,437 57,645 61,163 2000's 69,936 81,397 86,075 86,027 96,762 107,918 112,845 116,848 112,529 98,245 2010's 87,539 74,624 66,954 63,242 59,930 57,218

    Year Jan Feb Mar Apr May Jun

  17. New York Natural Gas Liquids Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    (No intransit Receipts) (Million Cubic Feet) New York Natural Gas Imports (No intransit Receipts) (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 24,139 22,348 29,326 47,677 35,720 52,013 70,993 67,956 1990's 98,217 188,233 435,470 502,701 562,267 630,321 652,578 656,332 666,256 754,484 2000's 832,761 718,982 787,619 761,859 785,055 856,107 865,952 892,283 780,862 640,119 2010's 434,526 324,474 278,422 233,453 200,394 - = No Data Reported;

  18. North Dakota Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 40,462 41,023 33,587 1970's 34,889 33,864 32,472 27,703 31,206 24,786 31,470 29,173 30,499 18,468 1980's 42,346 42,573 53,818 69,319 70,496 72,633 55,098 62,258 57,747 51,174 1990's 52,169 53,479 54,883 59,851 57,805 49,468 49,674 52,401 53,185 52,862 2000's 52,426 54,732 57,048 55,693 55,009 52,557 55,273 60,255 52,444 59,369 2010's 81,837 97,102 172,242 235,711 326,537 460,406

    Year Jan Feb Mar Apr May Jun

  19. Ohio Natural Gas Liquids Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 281 271 571 602 1,060 923 2,372 2,889 627 354 404 191 2002 184 740 645 1,261 655 2,444 6,411 5,335 3,175 1,034 410 428 2003 928 730 1,377 1,393 887 1,052 2,489 6,891 954 608 751 713 2004 822 888 881 809 4,107 2,668 2,843 2,634 1,400 68 862 276 2005 1,665 606 1,524 1,614 743 4,721 6,150 6,032 2,104 952 677 1,151 2006 563 500 564 503 1,213 1,904 6,113 5,191 1,347 2,246 1,958 1,081 2007 1,513 1,977 904 1,690 3,052 3,115 3,799

  20. Oklahoma Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 1,412,952 1,390,884 1,523,715 1970's 1,594,943 1,684,260 1,806,887 1,770,980 1,638,942 1,605,410 1,726,513 1,769,519 1,773,582 1,835,366 1980's 1,891,824 2,019,199 1,985,384 1,779,541 2,046,339 1,993,405 1,971,988 2,073,461 2,167,050 2,237,037 1990's 2,258,471 2,153,852 2,017,356 2,049,942 1,934,864 1,811,734 1,734,887 1,703,888 1,669,367 1,594,002 2000's 1,612,890 1,615,384 1,581,606 1,558,155 1,655,769

  1. Pennsylvania Natural Gas Liquids Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 486 712 1,140 773 1,109 1,771 2,262 3,427 2,964 2,732 2,582 2,675 2002 1,487 3,362 3,212 1,733 2,051 5,822 8,680 10,396 5,545 3,617 2,284 2,064 2003 1,872 1,635 2,717 2,468 2,210 3,279 6,446 8,721 3,401 3,391 2,248 2,849 2004 4,087 6,499 3,712 3,302 11,504 7,421 12,436 10,361 8,535 1,074 3,120 4,135 2005 3,681 2,103 5,459 2,436 2,771 10,076 14,795 14,914 10,640 5,409 4,766 3,590 2006 2,157 4,828 8,760 5,619 6,787 11,967

  2. Texas Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 101,920 87,176 100,334 115,391 131,842 151,710 190,037 191,478 135,134 118,063 91,505 91,523 2002 105,480 90,578 104,754 116,473 125,291 156,428 182,218 190,565 148,525 124,397 103,613 101,970 2003 106,379 100,241 103,485 101,849 141,494 143,084 172,747 183,393 119,762 103,052 89,312 89,060 2004 92,080 90,099 98,499 103,954 118,578 137,272 160,095 157,525 131,609 120,125 89,952 94,619 2005 93,970 83,671 93,732 104,415 116,656

  3. Replacing the whole barrel of oil with plants and microbes

    SciTech Connect (OSTI)

    Simmons, Blake

    2013-05-29

    In this May 13, 2013 talk, Blake Simmons discusses how scientists are exploring how plants and microbes can be used to replace many of the everyday goods we use that are derived from petroleum. To watch the entire entire Science at the Theater event, in which seven of our scientists present BIG ideas in eight minutes each.

  4. West Virginia Natural Gas Plant Liquids, Proved Reserves (Million Barrels)

    Gasoline and Diesel Fuel Update (EIA)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 211,460 236,971 231,759 1970's 242,452 234,027 214,951 208,676 202,306 154,484 153,322 152,767 148,564 150,505 1980's 156,551 161,251 150,850 130,078 143,730 144,883 135,431 160,000 174,942 177,192 1990's 178,000 198,605 182,000 171,024 183,773 186,231 169,839 172,268 180,000 1,760,150 2000's 264,139 191,889 190,249 187,723 197,217 221,108 225,530 231,184 244,880 264,436 2010's 265,174 394,125 539,860 741,853

  5. Replacing a Barrel of Oil with Plants and Microbes (Conference...

    Office of Scientific and Technical Information (OSTI)

    APA Chicago Bibtex Export Metadata Endnote Excel CSV XML Save to My Library Send to Email Send to Email Email address: Content: Close Send Cite: MLA Format Close Cite: APA ...

  6. Extrusion of electrode material by liquid injection into extruder barrel

    DOE Patents [OSTI]

    Keller, David Gerard; Giovannoni, Richard Thomas; MacFadden, Kenneth Orville

    1998-01-01

    An electrode sheet product is formed using an extruder having a feed throat and a downstream section by separately mixing an active electrode material and a solid polymer electrolyte composition that contains lithium salt. The active electrode material is fed into the feed throat of the extruder, while a portion of at least one fluid component of the solid polymer electrolyte composition is introduced to the downstream section. The active electrode material and the solid polymer electrolyte composition are compounded in a downstream end of the extruder. The extruded sheets, adhered to current collectors, can be formed into battery cells.

  7. Calif--Coastal Region Onshore Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Reserves (Million Barrels) Liquids Lease Condensate, Proved Reserves (Million Barrels) Calif--Coastal Region Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0 1980's 0 0 0 0 1 1 0 0 0 0 1990's 0 1 1 2 2 1 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 3 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  8. Texas--RRC District 1 Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Texas--RRC District 1 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 16 1980's 18 20 24 35 33 33 30 22 23 15 1990's 20 23 24 23 23 23 44 46 32 161 2000's 49 35 34 24 31 31 32 43 44 87 2010's 163 158 197 233 343 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  9. Texas--RRC District 10 Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Texas--RRC District 10 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 356 1980's 350 349 376 397 425 416 411 402 351 331 1990's 318 346 327 316 305 343 323 372 342 191 2000's 191 311 326 315 373 367 396 458 473 494 2010's 566 578 522 481 598 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  10. Texas--RRC District 2 Onshore Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Reserves (Million Barrels) Proved Reserves (Million Barrels) Texas--RRC District 2 Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 19 1980's 16 20 23 26 22 24 20 32 25 16 1990's 17 14 14 14 12 11 8 12 10 12 2000's 13 14 11 13 15 19 16 17 17 15 2010's 47 229 506 594 706 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  11. Texas--RRC District 3 Onshore Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Reserves (Million Barrels) Proved Reserves (Million Barrels) Texas--RRC District 3 Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 54 1980's 52 51 53 57 53 49 53 75 58 73 1990's 49 48 39 57 54 68 79 116 77 74 2000's 69 82 71 72 72 78 75 128 65 74 2010's 75 76 81 63 67 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  12. Texas--RRC District 4 Onshore Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Reserves (Million Barrels) Proved Reserves (Million Barrels) Texas--RRC District 4 Onshore Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 76 1980's 75 77 85 80 87 86 84 80 74 72 1990's 71 69 65 65 70 70 82 86 96 122 2000's 90 97 91 85 73 71 87 77 79 74 2010's 96 202 181 228 223 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  13. Texas--RRC District 5 Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Texas--RRC District 5 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 24 1980's 32 42 44 61 61 62 73 76 72 65 1990's 61 53 55 50 50 47 48 31 31 24 2000's 24 43 39 40 44 40 42 50 126 192 2010's 225 237 214 183 193 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  14. Texas--RRC District 6 Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Texas--RRC District 6 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 228 1980's 268 259 232 280 253 247 224 213 210 212 1990's 195 195 205 202 218 223 242 221 235 182 2000's 182 215 213 195 233 264 279 324 318 330 2010's 369 360 269 376 387 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  15. Texas--RRC District 7B Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Texas--RRC District 7B Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 62 1980's 82 99 99 129 103 101 106 90 95 71 1990's 74 81 67 73 61 69 64 57 48 34 2000's 34 28 24 31 42 89 131 200 269 326 2010's 359 416 295 332 312 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  16. Texas--RRC District 7C Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Texas--RRC District 7C Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 168 1980's 120 172 184 204 219 242 232 231 226 225 1990's 234 218 266 250 241 255 285 309 266 291 2000's 291 271 326 319 365 391 404 464 402 412 2010's 465 549 524 438 473 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  17. Texas--RRC District 8 Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Texas--RRC District 8 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 452 1980's 452 498 554 650 662 646 697 623 530 542 1990's 545 466 426 430 398 432 417 447 479 479 2000's 479 504 488 484 487 559 547 525 524 536 2010's 618 689 802 830 1,240 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  18. Texas--RRC District 8A Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Texas--RRC District 8A Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 350 1980's 289 335 296 262 282 282 331 307 325 332 1990's 353 333 257 297 267 284 262 290 226 222 2000's 222 250 180 163 197 248 231 260 194 201 2010's 230 239 242 239 245 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  19. Texas--RRC District 9 Natural Gas Plant Liquids, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Texas--RRC District 9 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 75 1980's 81 81 111 115 113 106 112 107 102 90 1990's 100 96 89 88 94 90 116 96 91 156 2000's 156 182 229 228 228 276 372 347 348 419 2010's 488 552 542 578 662 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  20. CENTIMETER CONTINUUM OBSERVATIONS OF THE NORTHERN HEAD OF THE HH 80/81/80N JET: REVISING THE ACTUAL DIMENSIONS OF A PARSEC-SCALE JET

    SciTech Connect (OSTI)

    Masque, Josep M.; Estalella, Robert; Girart, Josep M.; Rodriguez, Luis F.; Beltran, Maria T.

    2012-10-10

    We present 6 and 20 cm Jansky Very Large Array/Very Large Array observations of the northern head of the HH 80/81/80N jet, one of the largest collimated jet systems known so far, aimed to look for knots farther than HH 80N, the northern head of the jet. Aligned with the jet and 10' northeast of HH 80N, we found a radio source not reported before, with a negative spectral index similar to that of HH 80, HH 81, and HH 80N. The fit of a precessing jet model to the knots of the HH 80/81/80N jet, including the new source, shows that the position of this source is close to the jet path resulting from the modeling. If the new source belongs to the HH 80/81/80N jet, its derived size and dynamical age are 18.4 pc and >9 Multiplication-Sign 10{sup 3} yr, respectively. If the jet is symmetric, its southern lobe would expand beyond the cloud edge resulting in an asymmetric appearance of the jet. Based on the updated dynamical age, we speculate on the possibility that the HH 80/81/80N jet triggered the star formation observed in a dense core found ahead of HH 80N, which shows signposts of interaction with the jet. These results indicate that parsec-scale radio jets can play a role in the stability of dense clumps and the regulation of star formation in the molecular cloud.

  1. Texas (with State Offshore) Natural Gas Plant Liquids, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Texas (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 2,125 1980's 2,081 2,285 2,393 2,650 2,660 2,610 2,671 2,509 2,339 2,270 1990's 2,305 2,237 2,162 2,211 2,151 2,269 2,337 2,376 2,262 2,257 2000's 2,479 2,318 2,368 2,192 2,466 2,723 2,913 3,158 3,148 3,432 2010's 3,983 4,541 4,727 5,653

  2. Discomfort Glare: What Do We Actually Know?

    SciTech Connect (OSTI)

    Clear, Robert

    2012-02-29

    Glare models were reviewed with an eye for missing conditions or inconsistencies. We found ambiguities as to when to use small source versus large source models, and as to what constitutes a glare source in a complex scene. We also found surprisingly little information validating the assumed independence of the factors driving glare. A barrier to progress in glare research is the lack of a standardized dependent measure of glare. We inverted the glare models to predict luminance, and compared model predictions against the 1949 Luckiesh & Guth data that form the basis of many of them. The models perform surprisingly poorly, particularly with regards to the luminance-size relationship and additivity. Evaluating glare in complex scenes may require fundamental changes to form of the glare models.

  3. EPICS BASE

    Energy Science and Technology Software Center (OSTI)

    002230MLTPL00 Experimental Physics and Industrial Control System BASE http://www.aps.anl.gov/epics

  4. Crystal structure of phototoxic orange fluorescent proteins with α tryptophan-based chromophore

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

    Pletneva, Nadya V.; Pletnev, Vladimir Z.; Sarkisyan, Karen S.; Gorbachev, Dmitry A.; Egorov, Evgeny S.; Mishin, Alexander S.; Lukyanov, Konstantin A.; Dauter, Zbigniew; Pletnev, Sergei

    2015-12-23

    Phototoxic fluorescent proteins represent a sparse group of genetically encoded photosensitizers that could be used for precise light-induced inactivation of target proteins, DNA damage, and cell killing. Only two such GFP-based fluorescent proteins (FPs), KillerRed and its monomeric variant SuperNova, were described up to date. We present a crystallographic study of their two orange successors, dimeric KillerOrange and monomeric mKiller-Orange, at 1.81 and 1.57 Å resolution, respectively. They are the first orange-emitting protein photosensitizers with a tryptophan-based chromophore (Gln65-Trp66-Gly67). Same as their red progenitors, both orange photosensitizers have a water-filled channel connecting the chromophore to the β-barrel exterior and enablingmore » transport of ROS. In both proteins, Trp66 of the chromophore adopts an unusual trans-cis conformation stabilized by H-bond with the nearby Gln159. This trans-cis conformation along with the water channel was shown to be a key structural feature providing bright orange emission and phototoxicity of both examined orange photosensitizers.« less

  5. Crystal structure of phototoxic orange fluorescent proteins with α tryptophan-based chromophore

    SciTech Connect (OSTI)

    Pletneva, Nadya V.; Pletnev, Vladimir Z.; Sarkisyan, Karen S.; Gorbachev, Dmitry A.; Egorov, Evgeny S.; Mishin, Alexander S.; Lukyanov, Konstantin A.; Dauter, Zbigniew; Pletnev, Sergei

    2015-12-23

    Phototoxic fluorescent proteins represent a sparse group of genetically encoded photosensitizers that could be used for precise light-induced inactivation of target proteins, DNA damage, and cell killing. Only two such GFP-based fluorescent proteins (FPs), KillerRed and its monomeric variant SuperNova, were described up to date. We present a crystallographic study of their two orange successors, dimeric KillerOrange and monomeric mKiller-Orange, at 1.81 and 1.57 Å resolution, respectively. They are the first orange-emitting protein photosensitizers with a tryptophan-based chromophore (Gln65-Trp66-Gly67). Same as their red progenitors, both orange photosensitizers have a water-filled channel connecting the chromophore to the β-barrel exterior and enabling transport of ROS. In both proteins, Trp66 of the chromophore adopts an unusual trans-cis conformation stabilized by H-bond with the nearby Gln159. This trans-cis conformation along with the water channel was shown to be a key structural feature providing bright orange emission and phototoxicity of both examined orange photosensitizers.

  6. The Pathway to Energy Security

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

    Even More Vehicles 0 2 4 6 8 10 12 14 16 18 20 22 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 Millions of Barrels per Day Domestic Production Actual Projected Light ...

  7. Geophysics-based method of locating a stationary earth object

    DOE Patents [OSTI]

    Daily, Michael R.; Rohde, Steven B.; Novak, James L.

    2008-05-20

    A geophysics-based method for determining the position of a stationary earth object uses the periodic changes in the gravity vector of the earth caused by the sun- and moon-orbits. Because the local gravity field is highly irregular over a global scale, a model of local tidal accelerations can be compared to actual accelerometer measurements to determine the latitude and longitude of the stationary object.

  8. Ultrasound based monitoring of the injection moulding process - Methods, applications and limitations

    SciTech Connect (OSTI)

    Praher, B., E-mail: bernhard.praher@jku.at, E-mail: klaus.straka@jku.at, E-mail: jesenka.usanovic@jku.at, E-mail: georg.steinbichler@jku.at; Straka, K., E-mail: bernhard.praher@jku.at, E-mail: klaus.straka@jku.at, E-mail: jesenka.usanovic@jku.at, E-mail: georg.steinbichler@jku.at; Usanovic, J., E-mail: bernhard.praher@jku.at, E-mail: klaus.straka@jku.at, E-mail: jesenka.usanovic@jku.at, E-mail: georg.steinbichler@jku.at; Steinbichler, G., E-mail: bernhard.praher@jku.at, E-mail: klaus.straka@jku.at, E-mail: jesenka.usanovic@jku.at, E-mail: georg.steinbichler@jku.at [Institute of Polymer Injection Moulding and Process Automation, Johannes Kepler University Linz (Austria)

    2014-05-15

    We developed novel non-invasive ultrasound based systems for the measurement of temperature distributions in the screw-ante chamber, the detection of unmelted granules and for the monitoring of the plasticizing process along the screw channel. The temperature of the polymer melt stored in the screw ante-chamber after the plasticization should be homogeneous. However, in reality the polymer melt in the screw ante-chamber is not homogeneous. Due to the fact the sound velocity in a polymer melt is temperature depending, we developed a tomography system using the measured transit times of ultrasonic pulses along different sound paths for calculating the temperature distribution in radial direction of a polymer melt in the screw ante-chamber of an injection moulding machine. For the detection of unmelted granules in the polymer melt we implemented an ultrasound transmission measurement. By analyzing the attenuation of the received pulses it is possible to detect unwanted inclusions. For the monitoring of the plasticizing process in the channels of the screw an ultrasonic pulse is transmitted into the barrel. By analyzing the reflected pulses it is possible to estimate solid bed and melt regions in the screw channel. The proposed systems were tested for accuracy and validity by simulations and test measurements.

  9. Savannah River Site generic data base development

    SciTech Connect (OSTI)

    Blanchard , A.

    2000-01-04

    This report describes the results of a project to improve the generic component failure database for the Savannah River Site (SRS). Additionally, guidelines were developed further for more advanced applications of database values. A representative list of components and failure modes for SRS risk models was generated by reviewing existing safety analyses and component failure data bases and from suggestions from SRS safety analysts. Then sources of data or failure rate estimates were identified and reviewed for applicability. A major source of information was the Nuclear Computerized Library for Assessing Reactor Reliability, or NUCLARR. This source includes an extensive collection of failure data and failure rate estimates for commercial nuclear power plants. A recent Idaho National Engineering Laboratory report on failure data from the Idaho Chemical Processing Plant was also reviewed. From these and other recent sources, failure data and failure rate estimates were collected for the components and failure modes of interest. For each component failure mode, this information was aggregated to obtain a recommended generic failure rate distribution (mean and error factor based on a lognormal distribution). Results are presented in a table in this report. A major difference between generic database and previous efforts is that this effort estimates failure rates based on actual data (failure events) rather than on existing failure rate estimates. This effort was successful in that over 75% of the results are now based on actual data. Also included is a section on guidelines for more advanced applications of failure rate data. This report describes the results of a project to improve the generic component failure database for the Savannah River site (SRS). Additionally, guidelines were developed further for more advanced applications of database values.

  10. Petroleum resources of South America: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, and Peru. Foreign Energy Supply Assessment Program series

    SciTech Connect (OSTI)

    Dietzman, W.D.; Rafidi, N.R.

    1983-01-01

    This report is an analysis of discovered crude oil reserves, undiscovered recoverable crude oil resources, and estimated annual oil field production. The countries analyzed are Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, and Peru. All of the countries in this report have a history of petroleum exploration and development. Also, they maintain policies which support the search for, and exploitation of, petroleum resources. This systematic assessment provides estimates of the quantities of remaining known petroleum reserves and undiscovered recoverable resources. The future feasible production rates from the respective countries are also discussed. The FESAP assessments are limited to petroleum resources recoverable by conventional primary and secondary extraction technology. It is estimated that over 29.4 billion barrels of recoverable oil (both discovered and undiscovered) originally existed within the sedimentary basins of these countries, as follows: Argentina (9.4 billion barrels); Brazil (6.5 billion barrels); Colombia (5.0 billion barrels); Peru (3.6 billion barrels); Ecuador (over 3.0 billion barrels); Chile (1.1 billion barrels); and Bolivia (over 0.8 billion barrels). Through 1982, about 10.2 billion barrels of the oil had been produced. Thus, some 19.2 billion barrels constitute the remaining recoverable petroleum resource base. It is estimated that the most likely volume of crude oil remaining to be found in the seven countries is 12 billion barrels. 91 refs., 59 figs., 82 tabs.

  11. FIPA agent based network distributed control system

    SciTech Connect (OSTI)

    D. Abbott; V. Gyurjyan; G. Heyes; E. Jastrzembski; C. Timmer; E. Wolin

    2003-03-01

    A control system with the capabilities to combine heterogeneous control systems or processes into a uniform homogeneous environment is discussed. This dynamically extensible system is an example of the software system at the agent level of abstraction. This level of abstraction considers agents as atomic entities that communicate to implement the functionality of the control system. Agents' engineering aspects are addressed by adopting the domain independent software standard, formulated by FIPA. Jade core Java classes are used as a FIPA specification implementation. A special, lightweight, XML RDFS based, control oriented, ontology markup language is developed to standardize the description of the arbitrary control system data processor. Control processes, described in this language, are integrated into the global system at runtime, without actual programming. Fault tolerance and recovery issues are also addressed.

  12. California (with State Offshore) Natural Gas Liquids Lease Condensate...

    Gasoline and Diesel Fuel Update (EIA)

    Reserves Based Production (Million Barrels) California (with State Offshore) Natural Gas ... Referring Pages: Lease Condensate Estimated Production California Lease Condensate Proved ...

  13. Weekly Preliminary Crude Imports by Top 10 Countries of Origin...

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

    Preliminary Crude Imports by Top 10 Countries of Origin (ranking based on 2013 Petroleum Supply Monthly data) (Thousand Barrels per Day) Period: Weekly 4-Week Average Download ...

  14. TABLE14.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    ... barrels): Alaska: State - 6,171; California: State - 1,870; Louisiana: State - ... Division estimates based on Form EIA-182, "Domestic Crude Oil First Purchase Report" data. ...

  15. Development of simplified design aids based on the results of simulation analysis

    SciTech Connect (OSTI)

    Balcomb, J.D.

    1980-01-01

    The Solar Load Ratio method for estimating the performance of passive solar heating systems is described. It is a simplified technique which is based on correlating the monthly solar savings fraction in terms of the ratio of monthly solar radiation absorbed by the building to total monthly building thermal load. The effect of differences between actual design parameters and those used to develop the correlations is estimated afterwards using sensitivity curves. The technique is fast and simple and sufficiently accurate for design purposes.

  16. MMCR Spectra-based Hydrometeor Phase Classifier: Evaluation & New Insights

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

    MMCR Spectra-based Hydrometeor Phase Classifier: Evaluation & New Insights Edward Luke 1 , Pavlos Kollias 1 , Matthew Shupe 2 1. Brookhaven National Laboratory 2. CIRES/NOAA/ETL Predicting HSRL depolarization with MMCR classifier Actual Depolarization Predicted Depolarization How accurately can combined HSRL, MMCR, MWR, and radiosonde generate the "golden" phase retrievals needed to train an MMCR-only classifier? For further discussion see Shupe, 2007. How well can the MMCR-only

  17. Level: National and Regional Data; Row: Energy Sources; Column: Consumption Potential;

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

    Nonswitchable Minimum and Maximum Consumption, 2010; Level: National and Regional Data; Row: Energy Sources; Column: Consumption Potential; Unit: Physical Units. Actual Minimum Maximum Energy Sources Consumption Consumption(a) Consumption(b) Total United States Electricity Receipts(c) (million kilowatthour 745,247 727,194 770,790 Natural Gas (billion cubic feet) 5,064 4,331 5,298 Distillate Fuel Oil (thousand barrels) 22 20 82 Residual Fuel Oil (thousand barrels) 13 9 46 Coal (thousand short

  18. Cloud-Based Model Calibration Using OpenStudio: Preprint

    SciTech Connect (OSTI)

    Hale, E.; Lisell, L.; Goldwasser, D.; Macumber, D.; Dean, J.; Metzger, I.; Parker, A.; Long, N.; Ball, B.; Schott, M.; Weaver, E.; Brackney, L.

    2014-03-01

    OpenStudio is a free, open source Software Development Kit (SDK) and application suite for performing building energy modeling and analysis. The OpenStudio Parametric Analysis Tool has been extended to allow cloud-based simulation of multiple OpenStudio models parametrically related to a baseline model. This paper describes the new cloud-based simulation functionality and presents a model cali-bration case study. Calibration is initiated by entering actual monthly utility bill data into the baseline model. Multiple parameters are then varied over multiple iterations to reduce the difference between actual energy consumption and model simulation results, as calculated and visualized by billing period and by fuel type. Simulations are per-formed in parallel using the Amazon Elastic Cloud service. This paper highlights model parameterizations (measures) used for calibration, but the same multi-nodal computing architecture is available for other purposes, for example, recommending combinations of retrofit energy saving measures using the calibrated model as the new baseline.

  19. Replacing the Whole Barrel To Reduce U.S. Dependence on Oil

    SciTech Connect (OSTI)

    2013-05-13

    This overview provides highlights of the DOE Bioenergy Technologies Office's major research, development, demonstration, and deployment activities to advance biomass conversion, technology integration in biorefineries, and supply logistics to provide a secure, sustainable supply of advanced biofuels.

  20. U.S. monthly oil production tops 8 million barrels per day for...

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

    More coal and less natural gas will be used to generate electricity this summer compared to last year, while combined power generated by wind, sun, and other renewables will also ...

  1. U.S. Crude Oil + Lease Condensate Proved Reserves (Million Barrels...

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

    Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 22,315 2010's 25,181 28,950 33,403 36,520 39,933 - No Data Reported; -- Not Applicable; NA Not Available; W ...

  2. U.S. monthly oil production tops 8 million barrels per day for...

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

    Oil production in the Gulf of Mexico is also expected to rise this year and again in 2015, marking the first increase in offshore oil output in five years, according to EIA. The ...

  3. U.S. monthly oil production tops 8 million barrels per day for...

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

    Robust production is also supporting increased natural gas exports to Mexico and reductions in natural gas imports from Canada. Several companies plan to build U.S. terminals to ...

  4. U.S. monthly oil production tops 8 million barrels per day for...

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

    shut-ins The government's weather experts are predicting a relatively mild hurricane season, but U.S. oil and natural gas production in the Gulf of Mexico could still be disrupted. ...

  5. U.S. monthly oil production tops 8 million barrels per day for...

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

    Midwest households expected to see a 33% drop in propane heating bills this winter Midwest households that paid record-high prices for propane last winter to stay warm are expected ...

  6. U.S. monthly oil production tops 8 million barrels per day for...

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

    U.S. gasoline prices expected to fall over next few months U.S. drivers should see lower gasoline prices over the next few months. In its new forecast, the U.S. Energy Information ...

  7. U.S. monthly oil production tops 8 million barrels per day for...

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

    residential summer power bills to be higher than last year The average household power bill this summer is expected to be 4.9 percent higher than last year. In its new monthly ...

  8. U.S. monthly oil production tops 8 million barrels per day for...

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

    U.S. natural gas stocks at the end of the heating season expected to be lowest since 2003 In its new monthly forecast....the U.S. Energy Information Administration expects the ...

  9. U.S. monthly oil production tops 8 million barrels per day for...

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

    U.S. natural gas inventories strong heading into winter heating season U.S. natural gas inventories have recovered from their big drawdown last winter and are expected to be at ...

  10. U.S. monthly oil production tops 8 million barrels per day for...

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

    U.S. drivers expected to pay slightly lower average gasoline price this summer U.S. drivers pulling up to the pump this summer are expected to pay an average of 3.57 for a gallon ...

  11. U.S. monthly oil production tops 8 million barrels per day for...

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

    More than 1 trillion cubic feet of natural gas has been injected into underground storage since mid-April...the shortest time for that much natural gas to be added to inventories ...

  12. U.S. monthly oil production tops 8 million barrels per day for...

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

    summer gasoline price higher due to rising crude oil costs The price U.S. drivers pay for gasoline this summer is expected to average 3.61 per gallon....that's 3 cents more than ...

  13. U.S. monthly oil production tops 8 million barrels per day for...

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

    EIA forecasts record 2.6 trillion cubic feet build in U.S. natural gas inventories With the winter heating season over, U.S. natural gas producers now turn to ramping up output to ...

  14. U.S. monthly oil production tops 8 million barrels per day for...

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

    gasoline prices in december expected to be lowest in nearly 4 years Falling crude oil prices are expected to push U.S. retail gasoline prices in December to their lowest level in ...

  15. U.S. monthly oil production tops 8 million barrels per day for...

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

    Households heating bills expected to be lower this winter U.S. households in all regions of the country can expect to see lower heating bills this winter....mainly because ...

  16. U.S. monthly oil production tops 8 million barrels per day for...

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

    The amount of natural gas in underground storage was just under 1 trillion cubic feet in late April, about half the level typically seen for that time of year. The U.S. Energy ...

  17. U.S. monthly oil production tops 8 million barrels per day for...

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

    Snow and cold cut into U.S. crude oil production this winter This winter's harsh weather conditions temporarily slowed U.S. crude oil production. In its new forecast....the U.S. ...

  18. U.S. monthly oil production tops 8 million barrels per day for...

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

    World oil supply more than adequate to meet demand over next 2 years Rising U.S. crude oil production will help non-OPEC supply growth exceed global demand growth for the next two ...

  19. U.S. monthly oil production tops 8 million barrels per day for...

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

    1.3 trillion cubic feet by the end of March, the lowest level of inventories for that time of year since 2008. Extreme cold during January caused a record monthly withdrawal of ...

  20. U.S. monthly oil production tops 8 million barrels per day for...

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

    4 Oil demand expected to rise in non-industrialized countries, led by strong growth in China Nonindustrialized countries are expected to account for all of the growth in global ...

  1. Data base of chemical explosions in Kazakhstan

    SciTech Connect (OSTI)

    Demin, V.N.; Malahova, M.N.; Martysevich, P.N.; Mihaylova, N.N.; Nurmagambetov, A.; Kopnichev, Yu.F. D.; Edomin, V.I.

    1996-12-01

    Within the bounds of this report, the following works were done: (1) Information about explosion quarries, located in Southern, Eastern and Northern Kasakstan was summarized. (2) The general information about seismicity of areas of location of explosion quarries was adduced. (3) The system of observation and seismic apparatus, recording the local earthquakes and quarry explosions at the territory of Kazakstan were described. (4) Data base of quarry explosions, that were carried out in Southern, Eastern and Northern Kazakstan during 1995 and first half of 1996 year was adduced. (5) Upon the data of registration of explosions in Southern Kazakstan the correlative dependences between power class of explosions and summary weight of charge were constructed. (6) Seismic records of quarry explosions were adduced. It is necessary to note, that the collection of data about quarry explosions in Kazakstan in present time is very difficult task. Organizations, that makes these explosions, are always suffering reorganizations and sometimes it is actually impossible to receive all the necessary information. Some quarries are situated in remote, almost inaccessible regions, and within the bounds of supplier financing not the every quarry was in success to visit. So the present data base upon the chemical explosions for 1995 is not full and in further it`s expansion is possible.

  2. Grid-based Production

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

    Grid-based Production Grid-based Production PDSF is a Tier 2 site for ALICE and as such has the infrastructure in place to run automated grid-based ALICE production jobs. The main...

  3. CCP_FinalActual_2011_11_06.xlsx

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

    15 TROJAN DECOMMISSIONING (26,485) 1,500 (27,985) 16 WNP-1&3 DECOMMISSIONING 607 448 159 17 Sub-Total (25,878) 1,948 (27,826) 18 Gross Contracted Power...

  4. Meteorological field measurements at potential and actual wind turbine sites

    SciTech Connect (OSTI)

    Renne, D.S.; Sandusky, W.F.; Hadley, D.L.

    1982-09-01

    An overview of experiences gained in a meteorological measurement program conducted at a number of locations around the United States for the purpose of site evaluation for wind energy utilization is provided. The evolution of the measurement program from its inception in 1976 to the present day is discussed. Some of the major accomplishments and areas for improvement are outlined. Some conclusions on research using data from this program are presented.

  5. Dissolution Studies With Pilot Plant and Actual INTEC Calcines

    SciTech Connect (OSTI)

    Herbst, Ronald Scott; Garn, Troy Gerry

    1999-04-01

    The dissolution of Idaho Nuclear Technology and Engineering Center (INTEC) pilot plant calcines was examined to determine solubility of calcine matrix components in acidic media. Two representatives pilot plant calcine types were studied: Zirconia calcine and Zirconia/ Sodium calcine. Dissolution of these calcines was evaluated using lower initial concentrations of nitric acid than used in previous tests to decrease the [H+] concentration in the final solutions. Lower [H+] concentrations contribute to more favorable TRUEX/SREX solvent extraction flowsheet performance. Dissolution and analytical results were also obtained for radioactive calcines produced using high sodium feeds blended with non-radioactive A1(NO3)3 solutions to dilute the sodium concentration and prevent bed agglomeration during the calcination process. Dissolution tests indicated >95 wt. % of the initial calcine mass can be dissolved using the baseline dissolution procedure, with the exception that higher initial nitric acid concentrations are required. The higher initial acid concentration is required for stoichiometric dissolution of the oxides, primarily aluminum oxide. Statistically designed experiments using pilot plant calcine were performed to determine the effect of mixing rate on dissolution efficiency. Mixing rate was determined to provide minimal effects on wt. % dissolution. The acid/calcine ratio and temperature were the predominate variables affecting the wt. % dissolution, a result consistent with previous studies using other similar types of pilot plant calcines.

  6. Carbon Nanotube Based Sensors

    SciTech Connect (OSTI)

    Jiang, Mian; Lin, Yuehe

    2006-11-01

    This review article provides a comprehensive review on sensors and biosensors based on functionalized carbon nanotubes.

  7. Template based parallel checkpointing in a massively parallel computer system

    DOE Patents [OSTI]

    Archer, Charles Jens; Inglett, Todd Alan

    2009-01-13

    A method and apparatus for a template based parallel checkpoint save for a massively parallel super computer system using a parallel variation of the rsync protocol, and network broadcast. In preferred embodiments, the checkpoint data for each node is compared to a template checkpoint file that resides in the storage and that was previously produced. Embodiments herein greatly decrease the amount of data that must be transmitted and stored for faster checkpointing and increased efficiency of the computer system. Embodiments are directed to a parallel computer system with nodes arranged in a cluster with a high speed interconnect that can perform broadcast communication. The checkpoint contains a set of actual small data blocks with their corresponding checksums from all nodes in the system. The data blocks may be compressed using conventional non-lossy data compression algorithms to further reduce the overall checkpoint size.

  8. Process for fabricating ZnO-based varistors

    DOE Patents [OSTI]

    Lauf, Robert J.

    1985-01-01

    The invention is a process for producing ZnO-based varistors incorporating a metal oxide dopant. In one form, the invention comprises providing a varistor powder mix of colloidal particles of ZnO and metal-oxide dopants including Bi.sub.2 O.sub.3. The mix is hot-pressed to form a compact at temperatures below 850.degree. C. and under conditions effecting reduction of the ZnO to sub-stoichiometric oxide. This promotes densification while restricting liquid formation and grain growth. The compact then is heated under conditions restoring the zinc oxide to stoichiometric composition, thus improving the varistor properties of the compact. The process produces fine-grain varistors characterized by a high actual breakdown voltage and a high average breakdown voltage per individual grain boundary.

  9. Process for fabricating ZnO-based varistors

    DOE Patents [OSTI]

    Lauf, R.J.

    The invention is a process for producing ZnO-based varistors incorporating a metal oxide dopant. In one form, the invention comprises providing a varistor powder mix of colloidal particles of ZnO and metal-oxide dopants including Bi/sub 2/O/sub 3/. The mix is hot-pressed to form a compact at temperatures below 850/sup 0/C and under conditions effecting reduction of the ZnO to sub-stoichiometric oxide. This promotes densification while restricting liquid formation and grain growth. The compact then is heated under conditions restoring the zinc oxide to stoichiometric composition, thus improving the varistor properties of the compact. The process produces fine-grain varistors characterized by a high actual breakdown voltage and a high average breakdown voltage per individual grain boundary.

  10. Tariff-based analysis of commercial building electricityprices

    SciTech Connect (OSTI)

    Coughlin, Katie M.; Bolduc, Chris A.; Rosenquist, Greg J.; VanBuskirk, Robert D.; McMahon, James E.

    2008-03-28

    This paper presents the results of a survey and analysis ofelectricity tariffs and marginal electricity prices for commercialbuildings. The tariff data come from a survey of 90 utilities and 250tariffs for non-residential customers collected in 2004 as part of theTariff Analysis Project at LBNL. The goals of this analysis are toprovide useful summary data on the marginal electricity prices commercialcustomers actually see, and insight into the factors that are mostimportant in determining prices under different circumstances. We providea new, empirically-based definition of several marginal prices: theeffective marginal price and energy-only anddemand-only prices, andderive a simple formula that expresses the dependence of the effectivemarginal price on the marginal load factor. The latter is a variable thatcan be used to characterize the load impacts of a particular end-use orefficiency measure. We calculate all these prices for eleven regionswithin the continental U.S.

  11. Large-scale Manufacturing of Nanoparticulate-based Lubrication Additives for Improved Energy Efficiency and Reduced Emissions

    SciTech Connect (OSTI)

    Erdemir, Ali

    2013-09-26

    This project was funded under the Department of Energy (DOE) Lab Call on Nanomanufacturing for Energy Efficiency and was directed toward the development of novel boron-based nanocolloidal lubrication additives for improving the friction and wear performance of machine components in a wide range of industrial and transportation applications. Argonne's research team concentrated on the scientific and technical aspects of the project, using a range of state-of-the art analytical and tribological test facilities. Argonne has extensive past experience and expertise in working with boron-based solid and liquid lubrication additives, and has intellectual property ownership of several. There were two industrial collaborators in this project: Ashland Oil (represented by its Valvoline subsidiary) and Primet Precision Materials, Inc. (a leading nanomaterials company). There was also a sub-contract with the University of Arkansas. The major objectives of the project were to develop novel boron-based nanocolloidal lubrication additives and to optimize and verify their performance under boundary-lubricated sliding conditions. The project also tackled problems related to colloidal dispersion, larger-scale manufacturing and blending of nano-additives with base carrier oils. Other important issues dealt with in the project were determination of the optimum size and concentration of the particles and compatibility with various base fluids and/or additives. Boron-based particulate additives considered in this project included boric acid (H{sub 3}BO{sub 3}), hexagonal boron nitride (h-BN), boron oxide, and borax. As part of this project, we also explored a hybrid MoS{sub 2} + boric acid formulation approach for more effective lubrication and reported the results. The major motivation behind this work was to reduce energy losses related to friction and wear in a wide spectrum of mechanical systems and thereby reduce our dependence on imported oil. Growing concern over greenhouse gas emissions was also a major reason. The transportation sector alone consumes about 13 million barrels of crude oil per day (nearly 60% of which is imported) and is responsible for about 30% of the CO{sub 2} emission. When we consider manufacturing and other energy-intensive industrial processes, the amount of petroleum being consumed due to friction and wear reaches more than 20 million barrels per day (from official energy statistics, U.S. Energy Information Administration). Frequent remanufacturing and/or replacement of worn parts due to friction-, wear-, and scuffing-related degradations also consume significant amounts of energy and give rise to additional CO{sub 2} emission. Overall, the total annual cost of friction- and wear-related energy and material losses is estimated to be rather significant (i.e., as much as 5% of the gross national products of highly industrialized nations). It is projected that more than half of the total friction- and wear-related energy losses can be recovered by developing and implementing advanced friction and wear control technologies. In transportation vehicles alone, 10% to 15% of the fuel energy is spent to overcome friction. If we can cut down the friction- and wear-related energy losses by half, then we can potentially save up to 1.5 million barrels of petroleum per day. Also, less friction and wear would mean less energy consumption as well as less carbon emissions and hazardous byproducts being generated and released to the environment. New and more robust anti-friction and -wear control technologies may thus have a significant positive impact on improving the efficiency and environmental cleanliness of the current legacy fleet and future transportation systems. Effective control of friction in other industrial sectors such as manufacturing, power generation, mining and oil exploration, and agricultural and earthmoving machinery may bring more energy savings. Therefore, this project was timely and responsive to the energy and environmental objectives of DOE and our nation. In this project, most of the boron-based materials with known and potential anti-friction and -wear properties have been manufactured as colloidal additives and tested for their effectiveness in controlling friction and wear. Unlike other anti-friction and -wear additives, which consist of zinc, molybdenum, sulfur, phosphorus, and even chlorine, lubricious boron compounds considered in this project are made of boron, oxygen, nitrogen, and hydrogen, which are more environmentally benign. Among others, boric acid is a natural mineral (known in mineralogy as "sassolite"). Based on our earlier exploratory research, it was found to offer the best overall prospect in terms of performance improvements, environmental friendliness, and ease of manufacturing and, hence, cost effectiveness. Hexagonal boron nitride and borax also offered good prospects for improving the tribological properties of lubricated sliding surfaces. Boron oxide particles were found to be rather hard and somewhat abrasive and, hence, were not considered beyond the initial screening studies. In our bench-top tribological evaluation, we also demonstrated that those additives which worked well with engine oils could work equally well with very common gear oils. When added at appropriate concentrations, such gear oils were found to provide significant resistance to micropitting and scuffing failures in bench-top tribological test systems. Their traction coefficients were also reduced substantially and their scuffing limits were improved considerably. Such impressive tribological behavior of boron-based additives may have been due to their high chemical affinities to interact with sliding contact surfaces and to form slick and protective boundary films. Indeed, our surface studies have confirmed that most of the boron-based nanoparticulate additives prepared in our project possess a strong tendency to form a boron-rich boundary film on sliding contact surfaces. It is believed that the formation of such slick and highly durable boundary films is perhaps one of the fundamental reasons for their superior anti-friction, -wear, and -scuffing performance. Boron-based additives developed under this project have shown potential to reduce or replace the uses of environmentally unsafe sulfur- and phosphorus-bearing anti-wear and friction additives, such as zinc dialkyl dithiophosphate (ZDDP) and molybdenum dialkyl dithiocarbamate (MoDTC), in current lubricating oils. Because ZDDP and MoDTC were suspected of adversely impacting the performance of after-treatment catalysts in current engines, the Environmental Protection Agency (EPA) and other regulatory agencies are demanding that the concentrations of these catalysts in current oils be curtailed drastically. The boron-based nano-additives developed in this project may help reduce the use of ZDDP and MoDTC additives and, hence, help ease the poisoning effects on after-treatment catalysts. When used as lubricity additives, these boron additives can chemically interact with sliding or contacting surfaces and form a protective and slick boundary film, which can, in turn, help reduce friction and wear and increase resistance to scuffing. In the cases of traditional anti-friction and -wear additives mentioned, such protective boundary films result from phosphorus, sulfur, and other elements in the additive package, and again they have been under increased scrutiny in recent years, mainly because of their adverse effects on after-treatment devices. Overall, the boron-based nano-additive technology of this project was shown to hold promise for a broad range of industrial and transportation applications where lower friction and higher resistance to wear and scuffing are needed. Due to more stringent operating conditions of modern machinery, rolling, rotating, and sliding components have been failing to meet the projected lifetimes, mainly because of failures related to mechanical wear, corrosion, and scuffing. The novel boron-based additive technology developed under this project may help such machine components to function reliably by cutting down the friction and wear losses and by increasing resistance to scuffing.

  12. U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis

    Broader source: Energy.gov [DOE]

    The National Renewable Energy Laboratory (NREL) routinely estimates the technical potential of specific renewable electricity generation technologies. These are technology-specific estimates of energy generation potential based on renewable resource availability and quality, technical system performance, topographic limitations, environmental, and land-use constraints only. The estimates do not consider (in most cases) economic or market constraints, and therefore do not represent a level of renewable generation that might actually be deployed. Technical potential estimates for six different renewable energy technologies were calculated by NREL, and methods and results for several other renewable technologies from previously published reports are also presented.

  13. Provably Secure Password-based Authentication in TLS

    SciTech Connect (OSTI)

    Abdalla, Michel; Emmanuel, Bresson; Chevassut, Olivier; Moeller,Bodo; Pointcheval, David

    2005-12-20

    In this paper, we show how to design an efficient, provably secure password-based authenticated key exchange mechanism specifically for the TLS (Transport Layer Security) protocol. The goal is to provide a technique that allows users to employ (short) passwords to securely identify themselves to servers. As our main contribution, we describe a new password-based technique for user authentication in TLS, called Simple Open Key Exchange (SOKE). Loosely speaking, the SOKE ciphersuites are unauthenticated Diffie-Hellman ciphersuites in which the client's Diffie-Hellman ephemeral public value is encrypted using a simple mask generation function. The mask is simply a constant value raised to the power of (a hash of) the password.The SOKE ciphersuites, in advantage over previous pass-word-based authentication ciphersuites for TLS, combine the following features. First, SOKE has formal security arguments; the proof of security based on the computational Diffie-Hellman assumption is in the random oracle model, and holds for concurrent executions and for arbitrarily large password dictionaries. Second, SOKE is computationally efficient; in particular, it only needs operations in a sufficiently large prime-order subgroup for its Diffie-Hellman computations (no safe primes). Third, SOKE provides good protocol flexibility because the user identity and password are only required once a SOKE ciphersuite has actually been negotiated, and after the server has sent a server identity.

  14. Hickam Air Force Base

    Broader source: Energy.gov [DOE]

    Hickam Air Force Base spans 2,850 acres in Honolulu, Hawaii. The military base is home to the 15th Airlift Wing, the Hawaii Air National Guard, and the Pacific Air Forces headquarters.

  15. Based Accelerators Gennady Shvets

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

    Finally, I will discuss a new structure-based laser-driven surface wave accelerator based on silicon carbide (SiC) that employs a polaritonic material with a negative dielectric ...

  16. Activity Based Costing

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

    1997-03-28

    Activity Based Costing (ABC) is method for developing cost estimates in which the project is subdivided into discrete, quantifiable activities or a work unit. This chapter outlines the Activity Based Costing method and discusses applicable uses of ABC.

  17. ,"Projected Monthly Base","Year","Contiguous U.S.","Eastern Power Grid",,,,,,,,"Texas Power Grid","Western Power Grid"

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

    ","Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Council Region, " ,"1996 through 2004 and Projected 2005 through 2006 " ,"(Megawatts and 2004 Base Year)" ,"Projected Monthly Base","Year","Contiguous U.S.","Eastern Power Grid",,,,,,,,"Texas Power Grid","Western Power Grid"

  18. Development of an In Situ Biosurfactant Production Technology for Enhanced Oil Recovery

    SciTech Connect (OSTI)

    M.J. McInerney; R.M. Knapp; Kathleen Duncan; D.R. Simpson; N. Youssef; N. Ravi; M.J. Folmsbee; T.Fincher; S. Maudgalya; Jim Davis; Sandra Weiland

    2007-09-30

    The long-term economic potential for enhanced oil recovery (EOR) is large with more than 300 billion barrels of oil remaining in domestic reservoirs after conventional technologies reach their economic limit. Actual EOR production in the United States has never been very large, less than 10% of the total U. S. production even though a number of economic incentives have been used to stimulate the development and application of EOR processes. The U.S. DOE Reservoir Data Base contains more than 600 reservoirs with over 12 billion barrels of unrecoverable oil that are potential targets for microbially enhanced oil recovery (MEOR). If MEOR could be successfully applied to reduce the residual oil saturation by 10% in a quarter of these reservoirs, more than 300 million barrels of oil could be added to the U.S. oil reserve. This would stimulate oil production from domestic reservoirs and reduce our nation's dependence on foreign imports. Laboratory studies have shown that detergent-like molecules called biosurfactants, which are produced by microorganisms, are very effective in mobilizing entrapped oil from model test systems. The biosurfactants are effective at very low concentrations. Given the promising laboratory results, it is important to determine the efficacy of using biosurfactants in actual field applications. The goal of this project is to move biosurfactant-mediated oil recovery from laboratory investigations to actual field applications. In order to meet this goal, several important questions must be answered. First, it is critical to know whether biosurfactant-producing microbes are present in oil formations. If they are present, then it will be important to know whether a nutrient regime can be devised to stimulate their growth and activity in the reservoir. If biosurfactant producers are not present, then a suitable strain must be obtained that can be injected into oil reservoirs. We were successful in answering all three questions. The specific objectives of the project were (1) to determine the prevalence of biosurfactant producers in oil reservoirs, and (2) to develop a nutrient regime that would stimulate biosurfactant production in the oil reservoir.

  19. Simulation-Based Engineering

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

    Simulation-Based Engineering Simulation-Based Engineering is focused on predicting the behavior of complex multiphase flow reactors used in fossil-energy technologies. This effort combines theory, computational modeling, experiments, and industrial input. Physics- and science-based computational models and tools are needed to support the development and deployment of advanced fossil-fuel energy devices such as gasifiers and carbon capture reactors. It is critical to develop a practical framework

  20. Roadmap Toward a Predictive Performance-based Commercial Energy Code

    SciTech Connect (OSTI)

    Rosenberg, Michael I.; Hart, Philip R.

    2014-10-01

    Energy codes have provided significant increases in building efficiency over the last 38 years, since the first national energy model code was published in late 1975. The most commonly used path in energy codes, the prescriptive path, appears to be reaching a point of diminishing returns. The current focus on prescriptive codes has limitations including significant variation in actual energy performance depending on which prescriptive options are chosen, a lack of flexibility for designers and developers, and the inability to handle control optimization that is specific to building type and use. This paper provides a high level review of different options for energy codes, including prescriptive, prescriptive packages, EUI Target, outcome-based, and predictive performance approaches. This paper also explores a next generation commercial energy code approach that places a greater emphasis on performance-based criteria. A vision is outlined to serve as a roadmap for future commercial code development. That vision is based on code development being led by a specific approach to predictive energy performance combined with building specific prescriptive packages that are designed to be both cost-effective and to achieve a desired level of performance. Compliance with this new approach can be achieved by either meeting the performance target as demonstrated by whole building energy modeling, or by choosing one of the prescriptive packages.

  1. Experimental Design for Evaluation of Co-extruded Refractory Metal/Nickel Base Superalloy Joints

    SciTech Connect (OSTI)

    ME Petrichek

    2005-12-16

    Prior to the restructuring of the Prometheus Program, the NRPCT was tasked with delivering a nuclear space reactor. Potential NRPCT nuclear space reactor designs for the Prometheus Project required dissimilar materials to be in contact with each other while operating at extreme temperatures under irradiation. As a result of the high reactor core temperatures, refractory metals were the primary candidates for many of the reactor structural and cladding components. They included the tantalum-base alloys ASTAR-811C and Ta-10W, the niobium-base alloy FS-85, and the molybdenum base alloys Moly 41-47.5 Rhenium. The refractory metals were to be joined to candidate nickel base alloys such as Haynes 230, Alloy 617, or Nimonic PE 16 either within the core if the nickel-base alloys were ultimately selected to form the outer core barrel, or at a location exterior to the core if the nickel-base alloys were limited to components exterior to the core. To support the need for dissimilar metal joints in the Prometheus Project, a co-extrusion experiment was proposed. There are several potential methods for the formation of dissimilar metal joints, including explosive bonding, friction stir welding, plasma spray, inertia welding, HIP, and co-extrusion. Most of these joining methods are not viable options because they result in the immediate formation of brittle intermetallics. Upon cooling, intermetallics form in the weld fusion zone between the joined metals. Because brittle intermetallics do not form during the initial bonding process associated with HIP, co-extrusion, and explosive bonding, these three joining procedures are preferred for forming dissimilar metal joints. In reference to a Westinghouse Astronuclear Laboratory report done under a NASA sponsored program, joints that were fabricated between similar materials via explosive bonding had strengths that were directly affected by the width of the diffusion barrier. It was determined that the diffusion zone should not exceed a critical thickness (0.0005 in.). A diffusion barrier that exceeded this thickness would likely fail. The joint fabrication method must therefore mechanically bond the two materials causing little or no interdiffusion upon formation. Co-extrusion fits this description since it forms a mechanical joint between two materials by using heat and pressure. The two materials to be extruded are first assembled and sealed within a co-extrusion billet which is subsequently heated and then extruded through a die. For a production application, once the joint is formed, it is dejacketed to remove the outer canister. The remaining piece consists of two materials bonded together with a thin diffusion barrier. Therefore, the long-term stability of the joint is determined primarily by the kinetics of interdiffusion reaction between the two materials. An experimental design for co-extrusion of refractory metals and nickel-based superalloys was developed to evaluate this joining process and determine the long-term stability of the joints.

  2. Gasification-based biomass

    SciTech Connect (OSTI)

    None, None

    2009-01-18

    The gasification-based biomass section of the Renewable Energy Technology Characterizations describes the technical and economic status of this emerging renewable energy option for electricity supply.

  3. TF Web Based Training

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

    TF-Web-Based-Training Sign In About | Careers | Contact | Investors | bpa.gov Search News & Us Expand News & Us Projects & Initiatives Expand Projects & Initiatives Finance...

  4. Soy-based polyols

    SciTech Connect (OSTI)

    Suppes, Galen; Lozada, Zueica; Lubguban, Arnold

    2013-06-25

    The invention provides processes for preparing soy-based oligomeric polyols or substituted oligomeric polyols, as well as urethane bioelasteromers comprising the oligomeric polyols or substituted oligomeric polyols.

  5. Risk assessment based on point source deposition

    SciTech Connect (OSTI)

    Chadwick, G.F.

    1997-12-31

    The International Joint Commission (IJC) in a recently published report states that various clean-up techniques have resulted in significantly cleaner lakes than 20 years ago. Both the US EPA and Environment Canada have passed laws that require emissions controls on significant sources of contaminants. Improved emission controls have played a large part in the reduced pollution levels to the Great Lakes. Improved controls have significantly reduced the pollutants deposited to both land and water. This paper will discuss a Risk Analysis for the emissions from a Hospital in Rochester, New York. Current New York Department of Environmental Conservation (DEC) regulations require emission controls on such incinerators. This hospital has added both a scrubber and a bag house to control emissions. Twenty years ago, such incinerators, like many other emission sources would not have had control devices. New York`s Department of Environmental Conservation requires, as part of the Permitting process, that an Impact Analysis and if required, a multipathway Health Risk Assessment (HRA) be performed for all Medical Waste Incinerators before a Permit can be issued. This insures that the emissions will not create a health hazard to humans. Such an analysis was performed for a new 1,000 lb/hr Medical Waste Incinerator (MWI) installed in the North-East part of Rochester, New York. An Air Quality Impact Assessment (AQIA) based on an actual stack test indicated that this facility`s dioxin emissions would exceed the NY DEC Guideline levels. The Carcinogenic Risk (of death) for our most exposed individual (MEI) was calculated to be 8.75 E{sup {minus}06} (<1:100,000). The Hazard Index calculated for this MEI was 0.43. Hazard Index`s less then 1 are considered a reasonable risk. Health risk assessments are by design, very conservative. EPA sources have concluded that calculated death risks between one (1) and one hundred (100) per million are not excessive.

  6. Performance-based Contracting

    Energy Savers [EERE]

    Performance-based Contracting [Reference: FAR 37.6; DEAR 970.1001] Overview This section provides guidance and instruction for the development and administration of Performance-Based Contracting concepts for the Department's management and operating contracts, and other major operating contracts, as appropriate. Background In 1997, the Department published a final rule (62 FR 34842) which implemented a number of recommendations principally in areas relating to the acquisition processes of its

  7. Radioisotope power system based on derivative of existing Stirling engine

    SciTech Connect (OSTI)

    Schock, A.; Or, C.T.; Kumar, V.

    1995-12-31

    In a recent paper, the authors presented the results of a system design study of a 75-watt(c) RSG (Radioisotope Stirling Generator) for possible application to the Pluto Fast Flyby mission. That study was based on a Stirling engine design generated by MTI (Mechanical Technology, Inc.). The MTI design was a derivative of a much larger (13 kwe) engine that they had developed and tested for NASA`s LERC. Clearly, such a derivative would be a major extrapolation (downsizing) from what has actually been built and tested. To avoid that, the present paper describes a design for a 75-watt RSG system based on derivatives of a small (11-watt) engine and linear alternator system that has been under development by STC (Stirling Technology Company) for over three years and that has operated successfully for over 15,000 hours as of March 1995. Thus, the STC engines would require much less extrapolation from proven designs. The design employs a heat source consisting of two standard General Purpose Heat Source (GPHS) modules, coupled to four Stirling engines with linear alternators, any three of which could deliver the desired 75-watt(e) output if the fourth should fail. The four engines are coupled to four common radiators with redundant heatpipes for rejecting the engines` waste heat to space. The above engine and radiator redundancies promote system reliability. The paper describes detailed analyses to determine the effect of radiator geometry on system mass and performance, before and after an engine or heatpipe failure.

  8. Enhancing VHTR Passive Safety and Economy with Thermal Radiation Based Direct Reactor Auxiliary Cooling System

    SciTech Connect (OSTI)

    Haihua Zhao; Hongbin Zhang; Ling Zou; Xiaodong Sun

    2012-06-01

    One of the most important requirements for Gen. IV Very High Temperature Reactor (VHTR) is passive safety. Currently all the gas cooled version of VHTR designs use Reactor Vessel Auxiliary Cooling System (RVACS) for passive decay heat removal. The decay heat first is transferred to the core barrel by conduction and radiation, and then to the reactor vessel by thermal radiation and convection; finally the decay heat is transferred to natural circulated air or water systems. RVACS can be characterized as a surface based decay heat removal system. The RVACS is especially suitable for smaller power reactors since small systems have relatively larger surface area to volume ratio. However, RVACS limits the maximum achievable power level for modular VHTRs due to the mismatch between the reactor power (proportional to volume) and decay heat removal capability (proportional to surface area). When the relative decay heat removal capability decreases, the peak fuel temperature increases, even close to the design limit. Annular core designs with inner graphite reflector can mitigate this effect; therefore can further increase the reactor power. Another way to increase the reactor power is to increase power density. However, the reactor power is also limited by the decay heat removal capability. Besides the safety considerations, VHTRs also need to be economical in order to compete with other reactor concepts and other types of energy sources. The limit of decay heat removal capability set by using RVACS has affected the economy of VHTRs. A potential alternative solution is to use a volume-based passive decay heat removal system, called Direct Reactor Auxiliary Cooling Systems (DRACS), to remove or mitigate the limitation on decay heat removal capability. DRACS composes of natural circulation loops with two sets of heat exchangers, one on the reactor side and another on the environment side. For the reactor side, cooling pipes will be inserted into holes made in the outer or inner graphite reflector blocks. There will be gaps between these cooling pipes and their corresponding surrounding graphite surfaces. Graphite has an excellent heat conduction property. By taking advantage of this feature, we can have a volume-based method to remove decay heat. The scalability can be achieved, if needed, by employing more rows of cooling pipes to accommodate higher decay heat rates. Since heat can easily conduct through the graphite regions between the holes made for the cooling pipes, those cooling pipes located further away from the active core region can still be very effective in removing decay heat. By removing the limit on the decay heat removal capability due to the limited available surface area as in a RVACS, the reactor power and power density can be significantly increased, without losing the passive heat removal feature. This paper will introduce the concept of using DRACS to enhance VHTR passive safety and economics. Three design options will be discussed, depending on the cooling pipe locations. Analysis results from a lumped volume based model and CFD simulations will be presented.

  9. Table Definitions, Sources, and Explanatory Notes

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    ton. Barrel A unit of volume equal to 42 U.S. gallons. Biomass-Based Diesel Fuel Biodiesel and other renewable diesel fuel or diesel fuel blending components derived from...

  10. This Week In Petroleum Printer-Friendly Version

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    per day from a base production level of 27.5 million barrels per day (excluding Angola and Iraq), have firmed oil markets. Although OPEC did not achieve total compliance,...

  11. U.S. Movements of Crude Oil by Rail

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

    A zero may indicate volume of less than 0.5 thousand barrels per day. Source: U.S. Energy Information Administration estimates based on analysis of data from the Surface ...

  12. BASE Operator's Manual - 88-Inch Cyclotron

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

    BASE Operator's Manual BASE_Facility_-_SEE_Software_Operation.doc

  13. operation_tbl2_October_2011M.xlsx

    Gasoline and Diesel Fuel Update (EIA)

    Mean of Recovering 10.3 Billion Barrels 4. Production Schedules at Two Development Rates for the Statistical Mean of Recovering 10.3 Billion Barrels of Technically Recoverable Oil from the ANWR Coastal Plain of Alaska fig4.jpg (4109

    Next Update: October 2007 Table 3a . January Monthly Peak Hour Demand, Actual by North American Electric Reliability Council Region, 1996 through 2004 (Megawatts) Month Year Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid ECAR FRCC MAAC

  14. Level: National and Regional Data; Row: Energy Sources; Column: Consumption Potential;

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

    Table 10.1 Nonswitchable Minimum and Maximum Consumption, 2006; Level: National and Regional Data; Row: Energy Sources; Column: Consumption Potential; Unit: Physical Units. Actual Minimum Maximum Energy Sources Consumption Consumption(a) Consumption(b) Total United States Electricity Receipts(c) (million kilowatthour 854,102 826,077 889,281 Natural Gas (billion cubic feet) 5,357 4,442 5,649 Distillate Fuel Oil (thousand barrels) 22,139 19,251 101,340 Residual Fuel Oil (thousand barrels) 39,925

  15. Helicity Beam Asymmetry I{center_dot} in Two Neutral Pseudoscalar Photoproduction Reactions at the Crystal Barrel Experiment

    SciTech Connect (OSTI)

    Wilson, Andrew

    2010-08-05

    A method for measuring the helicity beam asymmetry (I{sub {center_dot}}is shown and demonstrated using the reaction {gamma}p{yields}p{pi}{sup 0{eta}}. The very preliminary results for this channel are presented and suggest that the helicity beam asymmetry is small. The statistics for this channel in this analysis are limited making an analysis of angular dependencies difficult.

  16. LL/ILW: Post-Qualification of Old Waste through Non-Destructive Extraction of Barrels from Cement Shields - 13535

    SciTech Connect (OSTI)

    Oehmigen, Steffen; Ambos, Frank

    2013-07-01

    Currently there is a large number of radioactive waste drums entombed in cement shields at German nuclear power plants. These concrete containers used in the past for the waste are not approved for the final repository. Compliance with current acceptance criteria of the final repository has to be proven by qualification measures on the waste. To meet these criteria, a new declaration and new packing is necessary. A simple non-destructive extraction of about 2000 drums from their concrete shields is not possible. So different methods were tested to find a way of non-destructive extraction of old waste drums from cement shields and therefore reduce the final repository volume and final repository costs by using a container accepted and approved for Konrad. The main objective was to build a mobile system to offer this service to nuclear plant stations. (authors)

  17. Use a DCS-based simulator to proactively manage your fossil DCS retrofit and eliminate unit trips

    SciTech Connect (OSTI)

    Krueger, S.; Greenlee, T.; Wilburs, D.

    1996-10-01

    Several fossil power plants are upgrading their current analog control with a modern distributed control system (DCS). A unit-specific DCS-based simulator for a fossil plant can offer several advantages if acquired early in the upgrade process. Three basic types of DCS-based simulators are discussed below. The experience of the Illinois Power`s (IP) Hennepin Unit 2 is summarized. The Hennepin simulator was developed in parallel with the new DCS-based control system and ready for use three months prior to the actual unit startup. The advantages gained by IP include an opportunity to test/tune the control systems and time to properly train the operations staff. These activities minimized the number of unit trips following the controls retrofit.

  18. physics-based-html

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

    physical security Physical Security Systems After the 9/11 terrorist attacks, NNSA took steps to protect its critical facilities from vehicle bombs and strengthened its facilities against attacks. NNSA has begun consolidating its nuclear weapons material which reduces the number of targets to be protected. It has hardened its

    Physics-based High-Resolution Numerical Modeling of Bridge Foundation Scour

  19. Plant-based Materials

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

    Plant-based Materials Catalysis Center for Energy Innovation teams with consumer goods and car companies in renewable plastics research [Newark, Delaware] The University of Delaware's Catalysis Center for Energy Innovation (CCEI) recently announced a research program with the Plant PET Technology Collaborative (PTC) to explore methods of producing renewable beverage bottles, packaging, automotive components and fabric from biomass. Together, CCEI and PTC are working to accelerate the development

  20. Texas--RRC District 1 Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Coalbed Methane Proved Reserves as of Dec. 31 TX, RRC District 1 Coalbed Methane Proved Reserves, Reserves Changes, and (Million Barrels)

    Crude Oil

  1. Texas--RRC District 5 Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Coalbed Methane Proved Reserves as of Dec. 31 TX, RRC District 5 Coalbed Methane Proved Reserves, Reserves Changes, and (Million Barrels)

    Crude Oil

  2. Texas--RRC District 6 Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Coalbed Methane Proved Reserves as of Dec. 31 TX, RRC District 6 Coalbed Methane Proved Reserves, Reserves Changes, and (Million Barrels)

    Crude Oil

  3. Texas--RRC District 7B Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Coalbed Methane Proved Reserves as of Dec. 31 TX, RRC District 7B Coalbed Methane Proved Reserves, Reserves Changes, and (Million Barrels)

    Crude Oil

  4. Texas--RRC District 7C Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Coalbed Methane Proved Reserves as of Dec. 31 TX, RRC District 7C Coalbed Methane Proved Reserves, Reserves Changes, and (Million Barrels)

    Crude Oil

  5. Texas--RRC District 8 Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Coalbed Methane Proved Reserves as of Dec. 31 TX, RRC District 8 Coalbed Methane Proved Reserves, Reserves Changes, and (Million Barrels)

    Crude Oil

  6. Texas--RRC District 8A Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Coalbed Methane Proved Reserves as of Dec. 31 TX, RRC District 8A Coalbed Methane Proved Reserves, Reserves Changes, and (Million Barrels)

    Crude Oil

  7. Texas--RRC District 9 Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Coalbed Methane Proved Reserves as of Dec. 31 TX, RRC District 9 Coalbed Methane Proved Reserves, Reserves Changes, and (Million Barrels)

    Crude Oil

  8. Texas--State Offshore Natural Gas Liquids Lease Condensate, Reserves Based

    Gasoline and Diesel Fuel Update (EIA)

    Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Coalbed Methane Proved Reserves as of Dec. 31 TX, State Offshore Coalbed Methane Proved Reserves, Reserves Changes, and (Million Barrels)

    Crude Oil

  9. Review and comparison of web- and disk-based tools for residentialenergy analysis

    SciTech Connect (OSTI)

    Mills, Evan

    2002-08-25

    There exist hundreds of building energy software tools, both web- and disk-based. These tools exhibit considerable range in approach and creativity, with some being highly specialized and others able to consider the building as a whole. However, users are faced with a dizzying array of choices and, often, conflicting results. The fragmentation of development and deployment efforts has hampered tool quality and market penetration. The purpose of this review is to provide information for defining the desired characteristics of residential energy tools, and to encourage future tool development that improves on current practice. This project entails (1) creating a framework for describing possible technical and functional characteristics of such tools, (2) mapping existing tools onto this framework, (3) exploring issues of tool accuracy, and (4) identifying ''best practice'' and strategic opportunities for tool design. evaluated 50 web-based residential calculators, 21 of which we regard as ''whole-house'' tools(i.e., covering a range of end uses). Of the whole-house tools, 13 provide open-ended energy calculations, 5 normalize the results to actual costs (a.k.a ''bill-disaggregation tools''), and 3 provide both options. Across the whole-house tools, we found a range of 5 to 58 house-descriptive features (out of 68 identified in our framework) and 2 to 41 analytical and decision-support features (55 possible). We also evaluated 15 disk-based residential calculators, six of which are whole-house tools. Of these tools, 11 provide open-ended calculations, 1 normalizes the results to actual costs, and 3 provide both options. These tools offered ranges of 18 to 58 technical features (70 possible) and 10 to 40 user- and decision-support features (56 possible). The comparison shows that such tools can employ many approaches and levels of detail. Some tools require a relatively small number of well-considered inputs while others ask a myriad of questions and still miss key issues. The value of detail has a lot to do with the type of question(s) being asked by the user (e.g., the availability of dozens of miscellaneous appliances is immaterial for a user attempting to evaluate the potential for space-heating savings by installing a new furnace). More detail does not, according to our evaluation, automatically translate into a ''better'' or ''more accurate'' tool. Efforts to quantify and compare the ''accuracy'' of these tools are difficult at best, and prior tool-comparison studies have not undertaken this in a meaningful way. The ability to evaluate accuracy is inherently limited by the availability of measured data. Furthermore, certain tool outputs can only be measured against ''actual'' values that are themselves calculated (e.g., HVAC sizing), while others are rarely if ever available (e.g., measured energy use or savings for specific measures). Similarly challenging is to understand the sources of inaccuracies. There are many ways in which quantitative errors can occur in tools, ranging from programming errors to problems inherent in a tool's design. Due to hidden assumptions and non-variable ''defaults'', most tools cannot be fully tested across the desirable range of building configurations, operating conditions, weather locations, etc. Many factors conspire to confound performance comparisons among tools. Differences in inputs can range from weather city, to types of HVAC systems, to appliance characteristics, to occupant-driven effects such as thermostat management. Differences in results would thus no doubt emerge from an extensive comparative exercise, but the sources or implications of these differences for the purposes of accuracy evaluation or tool development would remain largely unidentifiable (especially given the paucity of technical documentation available for most tools). For the tools that we tested, the predicted energy bills for a single test building ranged widely (by nearly a factor of three), and far more so at the end-use level. Most tools over-predicted energy bills and all over-predicted consumption. Variability was lower among disk-based tools,but they more significantly over-predicted actual use. The deviations (over-predictions) we observed from actual bills corresponded to up to $1400 per year (approx. 250 percent of the actual bills). For bill-disaggregation tools, wherein the results are forced to equal actual bills, the accuracy issue shifts to whether or not the total is properly attributed to the various end uses and to whether savings calculations are done accurately (a challenge that demands relatively rare end-use data). Here, too, we observed a number of dubious results. Energy savings estimates automatically generated by the web-based tools varied from $46/year (5 percent of predicted use) to $625/year (52 percent of predicted use).

  10. Data bases for rapid response to power reactor problems

    SciTech Connect (OSTI)

    Maskewitz, B.F.

    1980-01-01

    The urgency of the TMI-2 incident demanded prompt answers to an imperious situation. In responding to these challenging circumstances, both government and industry recognized deficiencies in both availability of essential retrievable data and calculational capabilities designed to respond immediately to actual abnormal events. Each responded by initiating new programs to provide a remedy for the deficiencies and to generally improve all safety measures in the nuclear power industry. Many data bases and information centers offer generic data and other technology resources which are generally useful in support of nuclear safety programs. A few centers can offer rapid access to calculational methods and associated data and more will make an effort to do so. As a beneficial spin-off from the lessons learned from TMI-2, more technical effort and financial resources will be devoted to the prevention of accidents, and to improvement of safety measures in the immediate future and for long term R and D programs by both government and the nuclear power industry.

  11. H. R. 1086: A Bill to amend the Internal Revenue code of 1986 to reduce emissions of carbon dioxide by imposing a tax on certain fuels based on their carbon content, introduced in the House of Representatives, One Hundred Second Congress, First Session, February 21, 1991

    SciTech Connect (OSTI)

    Not Available

    1991-01-01

    A new subchapter would be added to the Internal Revenue Code entitled Carbon Tax on Primary Fossil Fuels. The tax is imposed on coal, petroleum, and natural gas, and is phased in over five years beginning in 1992. The tax on coal is $3.60 per ton in 1992 and climbs to $18.00 per ton in 1996. The tax on petroleum begins at $0.78 per barrel and climbs to $3.90 per barrel in 1996. Natural gas is taxed at $0.096 per MCF in 1992 and $0.48 per MCF in 1996. The bill also describes inflation adjustments.

  12. NICKEL-BASE ALLOY

    DOE Patents [OSTI]

    Inouye, H.; Manly, W.D.; Roche, T.K.

    1960-01-19

    A nickel-base alloy was developed which is particularly useful for the containment of molten fluoride salts in reactors. The alloy is resistant to both salt corrosion and oxidation and may be used at temperatures as high as 1800 deg F. Basically, the alloy consists of 15 to 22 wt.% molybdenum, a small amount of carbon, and 6 to 8 wt.% chromium, the balance being nickel. Up to 4 wt.% of tungsten, tantalum, vanadium, or niobium may be added to strengthen the alloy.

  13. Base drive circuit

    DOE Patents [OSTI]

    Lange, A.C.

    1995-04-04

    An improved base drive circuit having a level shifter for providing bistable input signals to a pair of non-linear delays. The non-linear delays provide gate control to a corresponding pair of field effect transistors through a corresponding pair of buffer components. The non-linear delays provide delayed turn-on for each of the field effect transistors while an associated pair of transistors shunt the non-linear delays during turn-off of the associated field effect transistor. 2 figures.

  14. Base drive circuit

    DOE Patents [OSTI]

    Lange, Arnold C.

    1995-01-01

    An improved base drive circuit (10) having a level shifter (24) for providing bistable input signals to a pair of non-linear delays (30, 32). The non-linear delays (30, 32) provide gate control to a corresponding pair of field effect transistors (100, 106) through a corresponding pair of buffer components (88, 94). The non-linear delays (30, 32) provide delayed turn-on for each of the field effect transistors (100, 106) while an associated pair of transistors (72, 80) shunt the non-linear delays (30, 32) during turn-off of the associated field effect transistor (100, 106).

  15. Consent-Based Siting

    Energy Savers [EERE]

    University of Chicago, Gleacher Center 450 North Cityfront Plaza Drive Chicago, IL 60611 March 29, 2016 12:00-1:00 PM Informal Open House and Poster Session (Before Meeting Begins) 1:00-1:15 PM Welcoming Remarks Robert Rosner, Distinguished Service Professor, Department of Astronomy & Astrophysics & Physics, University of Chicago 1:15-1:30 PM Moving Forward with Consent-Based Siting John Kotek, Acting Assistant Secretary for Nuclear Energy, Department of Energy 1:30-2:00 PM Perspectives

  16. Comparison of strength and load-based methods for testing wind turbine blades

    SciTech Connect (OSTI)

    Musial, W.D.; Clark, M.E.; Egging, N.

    1996-11-01

    The purpose of this paper is to compare two methods of blade test loading and show how they are applied in an actual blade test. Strength and load-based methods were examined to determine the test load for an Atlantic Orient Corporation (AOC) 15/50 wind turbine blade for fatigue and static testing. Fatigue load-based analysis was performed using measured field test loads extrapolated for extreme rare events and scaled to thirty-year spectra. An accelerated constant amplitude fatigue test that gives equivalent damage at critical locations was developed using Miner`s Rule and the material S-N curves. Test load factors were applied to adjust the test loads for uncertainties, and differences between the test and operating environment. Similar analyses were carried, out for the strength-based fatigue test using the strength of the blade and the material properties to determine the load level and number of constant amplitude cycles to failure. Static tests were also developed using load and strength criteria. The resulting test loads were compared and contrasted. The analysis shows that, for the AOC 15/50 blade, the strength-based test loads are higher than any of the static load-based cases considered but were exceeded in the fatigue analysis for a severe hot/wet environment.

  17. Biosensors Based on Carbon Nanotubes

    SciTech Connect (OSTI)

    Lin, Yuehe; Yantasee, Wassana; Lu, Fang; Wang, Joseph; Musameh, Mustafa; Tu, Yi; Ren, Zhifeng

    2009-03-24

    This chapter summarizes the recent development of carbon nanotube based electrochemical biosensors work at PNNL.

  18. Biosensors Based on Carbon Nanotubes

    SciTech Connect (OSTI)

    Lin, Yuehe; Yantasee, Wassana; Lu, Fang; Wang, Joseph; Musameh, Mustafa; Tu, Yi; Ren, Zhifeng; J. A. Schwarz, C. Contescu, K. Putyera

    2004-04-01

    This invited review article summarizes recent work on biosensor development based on carbon nanotubes

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

    SciTech Connect (OSTI)

    Kohler, Christian

    2012-08-01

    Complex glazing systems such as venetian blinds, fritted glass and woven shades require more detailed optical and thermal input data for their components than specular non light-redirecting glazing systems. Various methods for measuring these data sets are described in this paper. These data sets are used in multiple simulation tools to model the thermal and optical properties of complex glazing systems. The output from these tools can be used to generate simplified rating values or as an input to other simulation tools such as whole building annual energy programs, or lighting analysis tools. I also describe some of the challenges of creating a rating system for these products and which factors affect this rating. A potential future direction of simulation and building operations is model based predictive controls, where detailed computer models are run in real-time, receiving data for an actual building and providing control input to building elements such as shades.

  20. MS Based Metabonomics

    SciTech Connect (OSTI)

    Want, Elizabeth J.; Metz, Thomas O.

    2010-03-01

    Metabonomics is the latest and least mature of the systems biology triad, which also includes genomics and proteomics, and has its origins in the early orthomolecular medicine work pioneered by Linus Pauling and Arthur Robinson. It was defined by Nicholson and colleagues in 1999 as the quantitative measurement of perturbations in the metabolite complement of an integrated biological system in response to internal or external stimuli, and is often used today to describe many non-global types of metabolite analyses. Applications of metabonomics are extensive and include toxicology, nutrition, pharmaceutical research and development, physiological monitoring and disease diagnosis. For example, blood samples from millions of neonates are tested routinely by mass spectrometry (MS) as a diagnostic tool for inborn errors of metabolism. The metabonome encompasses a wide range of structurally diverse metabolites; therefore, no single analytical platform will be sufficient. Specialized sample preparation and detection techniques are required, and advances in NMR and MS technologies have led to enhanced metabonome coverage, which in turn demands improved data analysis approaches. The role of MS in metabonomics is still evolving as instrumentation and software becomes more sophisticated and as researchers realize the strengths and limitations of current technology. MS offers a wide dynamic range, high sensitivity, and reproducible, quantitative analysis. These attributes are essential for addressing the challenges of metabonomics, as the range of metabolite concentrations easily exceeds nine orders of magnitude in biofluids, and the diversity of molecular species ranges from simple amino and organic acids to lipids and complex carbohydrates. Additional challenges arise in generating a comprehensive metabolite profile, downstream data processing and analysis, and structural characterization of important metabolites. A typical workflow of MS-based metabonomics is shown in Figure 1. Gas chromatography-(GC)-MS was the most commonly used MS-based method for small molecule analysis in the 1970s and 1980s. It is still used today for the detection of many metabolic disorders and plays a strong role in plant metabonomics. Liquid chromatography (LC)-MS approaches have grown in popularity for metabolite studies, due to simpler sample preparation, reduced analysis times through the introduction of ultra-high performance liquid chromatography (UPLC)-MS and the ability to observe a wider range of metabolites. This chapter will discuss the role of MS in metabonomics, the techniques involved in this exciting area, and the current and future applications of the field. The various bioinformatics tools and multivariate analysis techniques used to maximize information recovery and to aid in the interpretation of the very large data sets typically obtained in metabonomics studies will also be discussed. While there are many different MS-based approaches utilized in metabonomics studies, emphasis will be placed on more established methods.