National Library of Energy BETA

Sample records for a9 total inputs

  1. Total Blender Net Input of Petroleum Products

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

    Input Product: Total Input Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquid Petroleum Gases Normal Butane Isobutane Other Liquids OxygenatesRenewables ...

  2. U.S. Total Weekly Inputs & Utilization

    Gasoline and Diesel Fuel Update (EIA)

    739 15,653 15,665 15,724 15,824 15,861 1982-2016 Gross Inputs 15,900 15,805 15,811 15,895 16,032 16,064 1990-2016 Operable Capacity (Calendar Day) 18,137 18,149 18,160 18,172 18,172 18,172 1990-2016 Percent Operable Utilization 87.7 87.1 87.1 87.5 88.2 88.4 1990-2016 Refiner and Blender Net Inputs Motor Gasoline Blending Components 104 200 257 502 612 696 2008-2016 RBOB 362 316 291 395 435 470 2010-2016 CBOB -355 -283 -247 -99 -16 46 2010-2016 GTAB 60 75 81 77 46 54 2010-2016 All Other 38 92 132

  3. Table A9. Total Primary Consumption of Energy for All Purposes by Census

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

    A9. Total Primary Consumption of Energy for All Purposes by Census" " Region and Economic Characteristics of the Establishment, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke" " "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" " ","Total","Electricity(b)","Fuel

  4. Table A52. Total Inputs of Energy for Heat, Power, and Electricity Generatio

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

    2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" " Categories and Presence of General Technologies and Cogeneration Technologies, 1994" " (Estimates in Trillion Btu)" ,,,,"Employment Size(a)" ,,,,,,,,"RSE" ,,,,,,,"1000 and","Row" "General/Cogeneration Technologies","Total","Under

  5. Table A31. Total Inputs of Energy for Heat, Power, and Electricity Generation

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

    Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1991" " (Continued)" " (Estimates in Trillion Btu)",,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," ","

  6. Table A45. Total Inputs of Energy for Heat, Power, and Electricity Generation

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

    Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Enclosed Floorspace, Percent Conditioned Floorspace, and Presence of Computer" " Controls for Building Environment, 1991" " (Estimates in Trillion Btu)" ,,"Presence of Computer Controls" ,," for Buildings Environment",,"RSE" "Enclosed Floorspace and"," ","--------------","--------------","Row" "Percent

  7. Table A41. Total Inputs of Energy for Heat, Power, and Electricity

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

    A41. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Census Region, Industry Group, Selected Industries, and Type of" " Energy Management Program, 1991" " (Estimates in Trillion Btu)" ,,," Census Region",,,,"RSE" "SIC","Industry Groups",," -------------------------------------------",,,,"Row" "Code(a)","and

  8. Table A50. Total Inputs of Energy for Heat, Power, and Electricity Generatio

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

    A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Industry Group, Selected Industries, and Type of" " Energy-Management Program, 1994" " (Estimates in Trillion Btu)" ,,,," Census Region",,,"RSE" "SIC",,,,,,,"Row" "Code(a)","Industry Group and

  9. Table A55. Number of Establishments by Total Inputs of Energy for Heat, Powe

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

    Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of Cogeneration Technologies, 1994: Part 2" ,,,"Steam Turbines",,,,"Steam Turbines" ,," ","Supplied by Either","Conventional",,,"Supplied by","One or More",," " " "," ",,"Conventional","Combustion

  10. Table A15. Total Inputs of Energy for Heat, Power, and Electricity Generation

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

    Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry

  11. Table A34. Total Inputs of Energy for Heat, Power, and Electricity Generation

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

    Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Employment Size Categories, Industry Group, and Selected Industries, 1991" " (Continued)" " (Estimates in Trillion Btu)" ,,,,,"Employment Size" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," ",,"1,000","Row"

  12. Table A10. Total Inputs of Energy for Heat, Power, and Electricity Generatio

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

    0. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Fuel Type, Industry Group, Selected Industries, and End Use, 1994:" " Part 2" " (Estimates in Trillion Btu)" ,,,,,"Distillate",,,"Coal" ,,,,,"Fuel Oil",,,"(excluding",,"RSE" "SIC",,,"Net","Residual","and Diesel",,,"Coal Coke",,"Row" "Code(a)","End-Use

  13. Table A54. Number of Establishments by Total Inputs of Energy for Heat, Powe

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

    Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of General Technologies, 1994: Part 2" ,," "," ",," "," ",," "," "," "," " ,,,,"Computer Control" ,," "," ","of Processes"," "," ",," "," ",," "

  14. Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio

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

    2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural

  15. Table A37. Total Inputs of Energy for Heat, Power, and Electricity

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

    2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural

  16. Table A10. Total Inputs of Energy for Heat, Power, and Electricity Generatio

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

    1" " (Estimates in Btu or Physical Units)" ,,,,,"Distillate",,,"Coal" ,,,,,"Fuel Oil",,,"(excluding" ,,,"Net","Residual","and Diesel",,,"Coal Coke",,"RSE" "SIC",,"Total","Electricity(b)","Fuel Oil","Fuel(c)","Natural Gas(d)","LPG","and Breeze)","Other(e)","Row" "Code(a)","End-Use

  17. Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio

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

    1" " (Estimates in Btu or Physical Units)" ,,,,"Distillate",,,"Coal" ,,,,"Fuel Oil",,,"(excluding" ,,"Net","Residual","and Diesel",,,"Coal Coke",,"RSE" ,"Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","and Breeze)","Other(d)","Row" "End-Use Categories","(trillion

  18. Table A36. Total Inputs of Energy for Heat, Power, and Electricity

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

    ,,,,,,,,"Coal" " Part 1",,,,,,,,"(excluding" " (Estimates in Btu or Physical Units)",,,,,"Distillate",,,"Coal Coke" ,,,,,"Fuel Oil",,,"and" ,,,"Net","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" "SIC",,"Total","Electricity(b)","Fuel Oil","Fuel","(billion","LPG","(1000

  19. Table A36. Total Inputs of Energy for Heat, Power, and Electricity

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

    " Part 2" " (Estimates in Trillion Btu)",,,,,,,,"Coal" ,,,,,"Distillate",,,"(excluding" ,,,,,"Fuel Oil",,,"Coal Coke",,"RSE" "SIC",,,"Net","Residual","and Diesel",,,"and",,"Row" "Code(a)","End-Use Categories","Total","Electricity(b)","Fuel Oil","Fuel(c)","Natural

  20. Table A37. Total Inputs of Energy for Heat, Power, and Electricity

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

    1",,,,,,,"Coal" " (Estimates in Btu or Physical Units)",,,,,,,"(excluding" ,,,,"Distillate",,,"Coal Coke" ,,"Net",,"Fuel Oil",,,"and" ,,"Electricity(a)","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" ,"Total","(million","Fuel Oil","Fuel","(billion","LPG","(1000

  1. Total..........................................................

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

    Floorspace (Square Feet) Total Floorspace 2 Fewer than 500... 3.2 Q 0.8 0.9 0.8 0.5 500 to 999......

  2. Total..........................................................

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

    2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500... 3.2 357 336 113 188 177 59 500 to 999......

  3. Total..........................................................

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

    . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500... 3.2 0.9 0.5 0.4 500 to 999......

  4. Total..........................................................

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

    25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500... 3.2 0.9 0.5 0.9 1.0 500 to 999......

  5. Total..........................................................

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

    5.6 17.7 7.9 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500... 3.2 0.5 0.3 Q 500 to 999......

  6. Total............................................................

    Gasoline and Diesel Fuel Update (EIA)

    Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592

  7. Total

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

    Product: Total Crude Oil Liquefied Petroleum Gases Propane/Propylene Normal Butane/Butylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending Components Petroleum Products Finished Motor Gasoline Reformulated Gasoline Conventional Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm Sulfur and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Sulfur

  8. Total

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

    Product: Total Crude Oil Liquefied Petroleum Gases Propane/Propylene Normal Butane/Butylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending Components Petroleum Products Finished Motor Gasoline Reformulated Gasoline Conventional Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm Sulfur and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Sulfur

  9. Total..........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7

  10. Total..........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1

  11. Total................................................

    Gasoline and Diesel Fuel Update (EIA)

    .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to

  12. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7

  13. Total..........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4

  14. Total...........................................................

    Gasoline and Diesel Fuel Update (EIA)

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9

  15. A=9 Nuclides

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

    9 Publications: revised manuscripts of: Evaluations PDF HTML TUNL evaluation (2004) A = 9 9He, 9Li, 9Be, 9B, 9C, 9N FAS evaluation (1988) A = 9 9n, 9He, 9Li, 9Be, 9B, 9C, 9N FAS evaluation (1984) A = 9 9n, 9He, 9Li, 9Be, 9B, 9C, 9N FAS evaluation (1979) A = 9 9n, 9He, 9Li, 9Be, 9B, 9C, 9N FAS evaluation (1974) A = 9 9He, 9Li, 9Be, 9B, 9C FAS evaluation (1966) A = 9 9Li, 9Be, 9B, 9C FAS evaluation (1959) A = 9 9Li, 9Be, 9B, 9C Tables of Adopted Levels: 9Li, 9Be, 9B, 9C Energy Level Diagrams: 9Li,

  16. Refiner Crude Oil Inputs

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

    Percent Operable Utilization Net Inputs (Refiner and Blender) of Motor Gasoline Blending Comp Net Inputs (Refiner and Blender) of RBOB Blending Components Net Inputs (Refiner and ...

  17. ,"U.S. Blender Net Input"

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

    PM" "Back to Contents","Data 1: U.S. Blender Net Input" "Sourcekey","MTXRBNUS1","ME..."MO7RBNUS1","MO9RBNUS1" "Date","U.S. Blender Net Input of Total Petroleum Products ...

  18. Energy Level Diagrams A=9

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

    9 Available in the following years: (2004), (1988), (1984), (1979), (1974), (1966), (1959) A=9 Energy Level Diagrams from (2004TI06) GIF (Graphic Interchange Format): 9Li (24 KB) 9Be (44 KB) 9B (36 KB) 9C (20 KB) Isobar diagram (36 KB) PDF (Portable Document Format): 9Li (36 KB) 9Be (60 KB) 9B (48 KB) 9C (28 KB) Isobar diagram (56 KB) EPS (Encapsulated Postscript): 9Li (1.7 MB) 9Be (1.7 MB) 9B (1.6 MB) 9C (1.7 MB) Isobar diagram (1.8 MB) A=9 Energy Level Diagrams from (1988AJ01) GIF (Graphic

  19. ,"U.S. Blender Net Input"

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

    7:11:07 PM" "Back to Contents","Data 1: U.S. Blender Net Input" "Sourcekey","MTXRBNUS1...US1","MO7RBNUS1","MO9RBNUS1" "Date","U.S. Blender Net Input of Total Petroleum ...

  20. Total Refinery Net Input of Crude Oil and Petroleum Products

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

    346,773 340,480 321,878 318,765 321,561 328,213 2005-2015 PADD 1 22,886 23,148 20,094 22,062 22,083 20,464 2005-2015 East Coast 19,812 20,114 17,024 19,313 19,160 17,357 2005-2015 Appalachian No. 1 3,074 3,034 3,070 2,749 2,923 3,107 2005-2015 PADD 2 70,767 68,865 61,444 54,690 59,836 63,570 2005-2015 Ind., Ill. and Ky. 44,601 42,709 39,206 34,355 39,460 40,006 2005-2015 Minn., Wis., N. Dak., S. Dak. 10,306 9,772 7,576 7,633 8,646 9,446 2005-2015 Okla., Kans., Mo. 15,860 16,384 14,662 12,702

  1. U.S. Blender Net Input

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

    2010 2011 2012 2013 2014 2015 View History Total Input 2,166,784 2,331,109 2,399,318 2,539,812 2,824,480 2,987,634 2005-2015 Natural Gas Plant Liquids and Liquefied Refinery Gases ...

  2. U.S. Blender Net Input

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

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Total Input 262,502 262,483 248,620 258,292 242,060 252,467 2005-2015 Natural Gas Plant Liquids and Liquefied Refinery Gases ...

  3. A=9Li (1979AJ01)

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

    2.3 2.9 keV for the second T 32 state in A 9 (1975KA18). 1. 9Li(-)9Be Qm 13.607 The half-life of 9Li is 178.3 0.4 msec (1976AL02). Other recent values are 175 1...

  4. SNOiioaroad A9U3N3

    Gasoline and Diesel Fuel Update (EIA)

    SNOiioaroad A9U3N3 (DW96) 2020-VI3/3OQ HOW TO OBTAIN EIA PRODUCTS AND SERVICES For further information on any of the following services, or for answers to energy information questions, please contact EIA's National Energy Information Center: National Energy Information Center (NEIC) (202) 586-8800 Energy Information Administration (202) 586-0727 (fax) Forrestal Building, Room 1F-048 TTY: (202) 586-1181 Washington, DC 20585 E-mail: infoctr@eia.doe.gov Electronic Products and Services EIA's

  5. A=9He (1974AJ01)

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

    4AJ01) (Not illustrated) 9He is predicted to be particle unstable: its calculated mass excess > 40.17 MeV (1970WA1G, 1972WA07), = 43.54 MeV (1972TH13). Particle instability with respect to 8He + n, 7He + 2n and 6He + 3n implies atomic mass excesses greater than 39.7, 42.25 and 41.812 MeV, respectively. See also (1968CE1A). 9He has not been observed in a pion experiment [9Be(π-, π+)9He] (1965GI10) nor in the spontaneous fission of 252Cf (1967CO1K

  6. Generation Inputs Workshop June 25, 2014

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

    Inputs Workshop 25 June 2014 BPA's Centralized Wind Power Forecasting Initiative Scott Winner June 25, 2014 Generation Inputs Workshop Predecisional. For Discussion Purposes Only....

  7. Categorical Exclusion Determinations: A9 | Department of Energy

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

    A9 Categorical Exclusion Determinations: A9 Existing Regulations A9: Information gathering, analysis, and dissemination Information gathering (including, but not limited to, literature surveys, inventories, site visits, and audits), data analysis (including, but not limited to, computer modeling), document preparation (including, but not limited to, conceptual design, feasibility studies, and analytical energy supply and demand studies), and information dissemination (including, but not limited

  8. Recommendation 177: Facilitating Early Public Input

    Broader source: Energy.gov [DOE]

    DOE should initiate consultation meetings with stake holders immediately to allow early public input into the planning for IFDP

  9. Louisiana Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Louisiana Natural Gas Input Supplemental Fuels (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 249 435 553 560 517 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Total Supplemental Supply of Natural Gas Louisiana Supplemental Supplies of

  10. Input apparatus for dynamic signature verification systems

    DOE Patents [OSTI]

    EerNisse, Errol P.; Land, Cecil E.; Snelling, Jay B.

    1978-01-01

    The disclosure relates to signature verification input apparatus comprising a writing instrument and platen containing piezoelectric transducers which generate signals in response to writing pressures.

  11. ,"Maine Natural Gas Input Supplemental Fuels (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Maine Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","0930...

  12. ,"Hawaii Natural Gas Input Supplemental Fuels (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Hawaii Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","0930...

  13. ,"Washington Natural Gas Input Supplemental Fuels (MMcf)"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Washington Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","09...

  14. ,"Texas Natural Gas Input Supplemental Fuels (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","0930...

  15. Refinery & Blenders Net Input of Crude Oil

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

    Input Product: Total Crude Oil & Petroleum Products Crude Oil Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquefied Petroleum Gases Ethane Normal Butane Isobutane Other Liquids Hydrogen/Oxygenates/Renewables/Other Hydrocarbons Hydrogen Oxygenates (excl. Fuel Ethanol) Methyl Tertiary Butyl Ether (MTBE) All Other Oxygenates Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Other Hydrocarbons Unfinished Oils (net) Unfinished

  16. US Nuclear Regulatory Commission Input to DOE Request for Information...

    Energy Savers [EERE]

    Input US Nuclear Regulatory Commission Input to DOE Request for Information Smart Grid Implementation Input. Comments relevant to the following two sections of the...

  17. Barge Truck Total

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

    Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over...

  18. Wireless, relative-motion computer input device

    DOE Patents [OSTI]

    Holzrichter, John F.; Rosenbury, Erwin T.

    2004-05-18

    The present invention provides a system for controlling a computer display in a workspace using an input unit/output unit. A train of EM waves are sent out to flood the workspace. EM waves are reflected from the input unit/output unit. A relative distance moved information signal is created using the EM waves that are reflected from the input unit/output unit. Algorithms are used to convert the relative distance moved information signal to a display signal. The computer display is controlled in response to the display signal.

  19. Opportunities for Public Input Into DOE Projects

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

    Opportunities for Public Input Into DOE Projects There are currently several DOE-proposed activities that citizens can comment on in the near future. Here is a summary of each, as well as a description of how to provide your input into the project: Hanford Draft Closure and Waste Management Environmental Impact Statement Idahoans might be interested in this document because one of the proposed actions involves sending a small amount of radioactive waste (approximately 5 cubic meters of special

  20. U-139: IBM Tivoli Directory Server Input Validation Flaw

    Broader source: Energy.gov [DOE]

    The Web Admin Tool does not properly filter HTML code from user-supplied input before displaying the input.

  1. U-147:Red Hat Enterprise MRG Grid Input Validation Flaw

    Broader source: Energy.gov [DOE]

    The MRG Management Console (Cumin) does not properly filter HTML code from user-supplied input before displaying the input.

  2. Agricultural and Environmental Input Parameters for the Biosphere Model

    SciTech Connect (OSTI)

    K. Rasmuson; K. Rautenstrauch

    2004-09-14

    This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.

  3. Table A4. Total Inputs of Energy for Heat, Power, and Electricity Generation

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

    1 " " (Estimates in Btu or Physical Units)" " "," "," "," "," "," "," "," "," ","Coke"," "," " " "," "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" "SIC","

  4. Table A4. Total Inputs of Energy for Heat, Power, and Electricity Generation

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

    2" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," "," "," "," "," " " "," "," "," "," "," "," "," "," "," "," ","RSE" "SIC"," "," ","Net","Residual","Distillate","

  5. Table A4. Total Inputs of Energy for Heat, Power, and Electricity Generation

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

    by Census Region, Census Division, Industry Group, and Selected Industries, 1994: Part 2" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," "," "," "," "," " " "," "," "," "," "," "," "," "," "," "," ","RSE" "SIC","

  6. Table A56. Number of Establishments by Total Inputs of Energy...

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

    ... Heating and Cooling Operations and Minimal Energy Use",157,13 ," Forehearth Designed ... Heating and Cooling Operations and Minimal Energy Use",8,13 ," Forehearth Designed ...

  7. V-229: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site Scripting

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

    Attacks | Department of EnergyA> 9: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site Scripting Attacks V-229: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site Scripting Attacks August 28, 2013 - 6:00am Addthis PROBLEM: Several vulnerabilities were reported in IBM Lotus iNotes PLATFORM: IBM Lotus iNotes 8.5.x ABSTRACT: IBM Lotus iNotes 8.5.x contains four cross-site scripting vulnerabilities REFERENCE LINKS: Security Tracker Alert ID 1028954 IBM Security Bulletin 1647740

  8. Alaska Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Natural Gas Input Supplemental Fuels (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 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: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Total Supplemental Supply of Natural Gas Alaska Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual

  9. Total Crude by Pipeline

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

    Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign

  10. ,"Total Natural Gas Consumption

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

    Gas Consumption (billion cubic feet)",,,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  11. XBox Input -Version 1.0

    Energy Science and Technology Software Center (OSTI)

    2012-10-03

    Contains class for connecting to the Xbox 360 controller, displaying the user inputs {buttons, triggers, analog sticks), and controlling the rumble motors. Also contains classes for converting the raw Xbox 360 controller inputs into meaningful commands for the following objects: • Robot arms - Provides joint control and several tool control schemes • UGV's - Provides translational and rotational commands for "skid-steer" vehicles • Pan-tilt units - Provides several modes of control including velocity, position,more » and point-tracking • Head-mounted displays (HMO)- Controls the viewpoint of a HMO • Umbra frames - Controls the position andorientation of an Umbra posrot object • Umbra graphics window - Provides several modes of control for the Umbra OSG window viewpoint including free-fly, cursor-focused, and object following.« less

  12. Tribal Leaders Provide White House with Input on Bolstering Climate...

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

    Leaders Provide White House with Input on Bolstering Climate Resilience Tribal Leaders Provide White House with Input on Bolstering Climate Resilience January 7, 2015 - 10:29am ...

  13. T-693: Symantec Endpoint Protection Manager Input Validation...

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

    Input Validation Hole Permits Cross-Site Scripting and Cross-Site Request Forgery Attacks T-693: Symantec Endpoint Protection Manager Input Validation Hole Permits Cross-Site...

  14. T-701: Citrix Access Gateway Enterprise Edition Input Validation...

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

    1: Citrix Access Gateway Enterprise Edition Input Validation Flaw in Logon Portal Permits Cross-Site Scripting Attacks T-701: Citrix Access Gateway Enterprise Edition Input...

  15. V-150: Apache VCL Input Validation Flaw Lets Remote Authenticated...

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

    Apache VCL Input Validation Flaw Lets Remote Authenticated Users Gain Elevated Privileges V-150: Apache VCL Input Validation Flaw Lets Remote Authenticated Users Gain Elevated...

  16. V-153: Symantec Brightmail Gateway Input Validation Flaw Permits...

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

    3: Symantec Brightmail Gateway Input Validation Flaw Permits Cross-Site Scripting Attacks V-153: Symantec Brightmail Gateway Input Validation Flaw Permits Cross-Site Scripting...

  17. U-252: Barracuda Web Filter Input Validation Flaws Permit Cross...

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

    2: Barracuda Web Filter Input Validation Flaws Permit Cross-Site Scripting Attacks U-252: Barracuda Web Filter Input Validation Flaws Permit Cross-Site Scripting Attacks September...

  18. Addressing Uncertainties in Design Inputs: A Case Study of Probabilist...

    Office of Environmental Management (EM)

    Addressing Uncertainties in Design Inputs: A Case Study of Probabilistic Settlement Evaluations for Soft Zone Collapse at SWPF Addressing Uncertainties in Design Inputs: A Case...

  19. DOE Seeks Input On Addressing Contractor Pension and Medical...

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

    Input On Addressing Contractor Pension and Medical Benefits Liabilities DOE Seeks Input On Addressing Contractor Pension and Medical Benefits Liabilities March 27, 2007 - 12:10pm...

  20. decreasing water input and waste generation

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

    decreasing water input and waste generation - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense Waste

  1. Prioritization Tool Measurement Input Form | Department of Energy

    Energy Savers [EERE]

    Prioritization Tool Measurement Input Form Prioritization Tool Measurement Input Form BTO encourages stakeholders to recommend updates and improvements to the Prioritization Tool by using the below Measure Input Form. Download File Prioritization Tool Measurement Input Form More Documents & Publications Energy Savings Potential and RD&D Opportunities for Commercial Refrigration Austin Energy Data Dashboard Massachusetts -- SEP Data Dashboard

  2. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

  3. ,"Total Fuel Oil Expenditures

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

    . Fuel Oil Expenditures by Census Region for Non-Mall Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per...

  4. ,"Total Fuel Oil Consumption

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

    0. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for Non-Mall Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  5. ,"Total Fuel Oil Expenditures

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

    4. Fuel Oil Expenditures by Census Region, 1999" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per Square Foot"...

  6. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

  7. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings*...

  8. ,"Total Fuel Oil Expenditures

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

    A. Fuel Oil Expenditures by Census Region for All Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per...

  9. ,"Total Fuel Oil Consumption

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

    A. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  10. PADD 3 Weekly Inputs & Utilization

    Gasoline and Diesel Fuel Update (EIA)

    8,010 8,256 8,111 8,266 8,214 8,498 1992-2016 Gross Inputs 7,992 8,287 8,142 8,332 8,356 8,547 1990-2016 Operable Capacity (Calendar Day) 9,437 9,437 9,437 9,437 9,437 9,437 2010-2016 Percent Operable Utilization 84.7 87.8 86.3 88.3 88.6 90.6 2010-2016 Refiner and Blender Net Inputs Motor Gasoline Blending Components -1,974 -2,183 -2,099 -2,078 -1,837 -2,068 2004-2016 RBOB -73 -333 -278 -178 -192 -218 2010-2016 CBOB -1,786 -1,821 -1,763 -1,824 -1,574 -1,711 2004-2016 GTAB 0 0 0 0 0 0 2004-2016

  11. Parallel Total Energy

    Energy Science and Technology Software Center (OSTI)

    2004-10-21

    This is a total energy electronic structure code using Local Density Approximation (LDA) of the density funtional theory. It uses the plane wave as the wave function basis set. It can sue both the norm conserving pseudopotentials and the ultra soft pseudopotentials. It can relax the atomic positions according to the total energy. It is a parallel code using MP1.

  12. Multiple-Input Multiple-Output (MIMO) Linear Systems Extreme Inputs/Outputs

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

    Smallwood, David O.

    2007-01-01

    A linear structure is excited at multiple points with a stationary normal random process. The response of the structure is measured at multiple outputs. If the autospectral densities of the inputs are specified, the phase relationships between the inputs are derived that will minimize or maximize the trace of the autospectral density matrix of the outputs. If the autospectral densities of the outputs are specified, the phase relationships between the outputs that will minimize or maximize the trace of the input autospectral density matrix are derived. It is shown that other phase relationships and ordinary coherence less than one willmore » result in a trace intermediate between these extremes. Least favorable response and some classes of critical response are special cases of the development. It is shown that the derivation for stationary random waveforms can also be applied to nonstationary random, transients, and deterministic waveforms.« less

  13. Summary Max Total Units

    Energy Savers [EERE]

    Summary Max Total Units *If All Splits, No Rack Units **If Only FW, AC Splits 1000 52 28 28 2000 87 59 35 3000 61 33 15 4000 61 33 15 Totals 261 153 93 ***Costs $1,957,500.00 $1,147,500.00 $697,500.00 Notes: added several refrigerants removed bins from analysis removed R-22 from list 1000lb, no Glycol, CO2 or ammonia Seawater R-404A only * includes seawater units ** no seawater units included *** Costs = (total units) X (estimate of $7500 per unit) 1000lb, air cooled split systems, fresh water

  14. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other...

  15. ARM - Measurement - Total carbon

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

    carbon ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total carbon The total concentration of carbon in all its organic and non-organic forms. Categories Aerosols, Atmospheric Carbon Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including

  16. U.S. Refinery & Blender Net Input

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

    2010 2011 2012 2013 2014 2015 View History Total 6,345,372 6,422,710 6,406,693 6,577,077 6,779,342 6,882,105 1981-2015 Crude Oil 5,374,094 5,404,347 5,489,516 5,589,006 5,784,637 ...

  17. U.S. Refinery & Blender Net Input

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

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Total 609,275 602,963 570,498 577,057 563,621 580,680 1981-2015 Crude Oil 523,409 516,507 485,221 479,416 494,682 519,726 ...

  18. U-144:Juniper Secure Access Input Validation Flaw Permits Cross...

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

    4:Juniper Secure Access Input Validation Flaw Permits Cross-Site Scripting Attacks U-144:Juniper Secure Access Input Validation Flaw Permits Cross-Site Scripting Attacks April 10,...

  19. V-193: Barracuda SSL VPN Input Validation Hole Permits Cross...

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

    3: Barracuda SSL VPN Input Validation Hole Permits Cross-Site Scripting Attacks V-193: Barracuda SSL VPN Input Validation Hole Permits Cross-Site Scripting Attacks July 5, 2013 -...

  20. Texas Natural Gas Input Supplemental Fuels (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

    Input Supplemental Fuels (Million Cubic Feet) Texas Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  1. Connecticut Natural Gas Input Supplemental Fuels (Million Cubic...

    Gasoline and Diesel Fuel Update (EIA)

    Input Supplemental Fuels (Million Cubic Feet) Connecticut Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

  2. North Carolina Natural Gas Input Supplemental Fuels (Million...

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

    Input Supplemental Fuels (Million Cubic Feet) North Carolina Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

  3. New York Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) New York Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

  4. Refinery Input by PADD - Petroleum Supply Annual (2004)

    SciTech Connect (OSTI)

    2009-01-18

    Table showing refinery input of crude oil and petroleum products by Petroleum Administration for Defense Districts (PADD).

  5. Input File Creation for the Molecular Dynamics Program LAMMPS.

    Energy Science and Technology Software Center (OSTI)

    2001-05-30

    The program creates an input data file for the molecular dynamics program LAMMPS. The input file created is a liquid mixture between two walls explicitly composed of particles. The liquid molecules are modeled as a bead-spring molecule. The input data file specifies the position and topology of the starting state. The data structure of input allows for dynamic bond creation (cross-linking) within the LAMMPS code.

  6. U-001:Symantec IM Manager Input Validation Flaws

    Broader source: Energy.gov [DOE]

    Symantec IM Manager Input Validation Flaws Permit Cross-Site Scripting, SQL Injection, and Code Execution Attacks.

  7. Analysis of Stochastic Response of Neural Networks with Stochastic Input

    Energy Science and Technology Software Center (OSTI)

    1996-10-10

    Software permits the user to extend capability of his/her neural network to include probablistic characteristics of input parameter. User inputs topology and weights associated with neural network along with distributional characteristics of input parameters. Network response is provided via a cumulative density function of network response variable.

  8. Input visualization for the Cyclus nuclear fuel cycle simulator: CYClus Input Control

    SciTech Connect (OSTI)

    Flanagan, R.; Schneider, E.

    2013-07-01

    This paper discusses and demonstrates the methods used for the graphical user interface for the Cyclus fuel cycle simulator being developed at the University of Wisconsin-Madison. Cyclus Input Control (CYCIC) is currently being designed with nuclear engineers in mind, but future updates to the program will be made to allow even non-technical users to quickly and efficiently simulate fuel cycles to answer the questions important to them. (authors)

  9. High-frequency matrix converter with square wave input

    DOE Patents [OSTI]

    Carr, Joseph Alexander; Balda, Juan Carlos

    2015-03-31

    A device for producing an alternating current output voltage from a high-frequency, square-wave input voltage comprising, high-frequency, square-wave input a matrix converter and a control system. The matrix converter comprises a plurality of electrical switches. The high-frequency input and the matrix converter are electrically connected to each other. The control system is connected to each switch of the matrix converter. The control system is electrically connected to the input of the matrix converter. The control system is configured to operate each electrical switch of the matrix converter converting a high-frequency, square-wave input voltage across the first input port of the matrix converter and the second input port of the matrix converter to an alternating current output voltage at the output of the matrix converter.

  10. 21 briefing pages total

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

    1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law

  11. U.S. Refinery Net Input

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

    2010 2011 2012 2013 2014 2015 View History Total 4,178,588 4,091,601 4,007,375 4,037,265 3,954,862 3,894,471 2005-2015 Crude Oil 5,374,094 5,404,347 5,489,516 5,589,006 5,784,637 5,915,532 2005-2015 Natural Gas Plant Liquids 154,941 171,074 175,607 168,808 172,563 171,936 2005-2015 Pentanes Plus 54,697 61,059 59,432 56,153 52,853 50,850 2005-2015 Liquefied Petroleum Gases 100,244 110,015 116,175 112,655 119,710 121,086 2005-2015 Normal Butane 39,253 42,087 45,747 42,461 45,916 47,870 2005-2015

  12. NIDR (New Input Deck Reader) V2.0 2

    Energy Science and Technology Software Center (OSTI)

    2010-03-31

    NIDR (New Input Deck Reader) is a facility for processing block-structured input to large programs. NIDR was written to simplify maintenance of DAKOTA (a program for uncertainty quantification and optimization), to provide better error checking of input and to allow use of aliases in the input. While written to support DAKOTA input conventions, NIDR itself is independent of DAKOTA and can be used in many kinds of programs. The initial version of NIDR was copyrightedmore » in 2008. We have since extended NIDR to support a graphical user interface called Jaguar for DAKOTA. In the Review and Approval process for an updated paper on NIDR, the Classification Approver states that a new copyright assertion should be performed.processing input to programs. NIDR is not primarily for military applications.« less

  13. Generates 2D Input for DYNA NIKE & TOPAZ

    Energy Science and Technology Software Center (OSTI)

    1996-07-15

    MAZE is an interactive program that serves as an input and two-dimensional mesh generator for DYNA2D, NIKE2D, TOPAZ2D, and CHEMICAL TOPAZ2D. MAZE also generates a basic template for ISLAND input. MAZE has been applied to the generation of input data to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.

  14. DOE Seeks Industry Input on Nickel Disposition Strategy | Department of

    Office of Environmental Management (EM)

    Energy Industry Input on Nickel Disposition Strategy DOE Seeks Industry Input on Nickel Disposition Strategy March 23, 2012 - 12:00pm Addthis WASHINGTON, D.C. - The Energy Department's prime contractor, Fluor-B&W Portsmouth (FBP), managing the Portsmouth Gaseous Diffusion Plant (GDP), issued a request for Expressions of Interest (EOI) seeking industry input to support the development of an acquisition strategy for potential disposition of DOE nickel. The EOI requests technical,

  15. U.S. Refinery Net Input

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Total 346,773 340,480 321,878 318,765 321,561 328,213 2005-2015 Crude Oil 523,409 516,507 485,221 479,416 494,682 519,726 2005-2015 Natural Gas Plant Liquids 13,079 13,240 14,690 15,903 17,686 18,057 2005-2015 Pentanes Plus 4,606 4,453 4,693 4,431 3,897 3,932 2005-2015 Liquefied Petroleum Gases 8,473 8,787 9,997 11,472 13,789 14,125 2005-2015 Normal Butane 2,137 1,869 3,144 5,323 7,093 7,560 2005-2015 Isobutane 6,336 6,918 6,853 6,149 6,696

  16. V-192: Symantec Security Information Manager Input Validation...

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

    Flaws Permit Cross-Site Scripting, SQL Injection, and Information Disclosure Attacks V-192: Symantec Security Information Manager Input Validation Flaws Permit Cross-Site...

  17. ,"New Mexico Natural Gas Input Supplemental Fuels (MMcf)"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","0930...

  18. Abandoned Uranium Mines Report to Congress: LM Wants Your Input

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy (DOE) Office of Legacy Management (LM) is seeking stakeholder input on an abandoned uranium mines report to Congress.

  19. Total Sales of Kerosene

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

    End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 269,010 305,508 187,656 81,102 79,674 137,928 1984-2014 East Coast (PADD 1) 198,762 237,397 142,189 63,075 61,327 106,995 1984-2014 New England (PADD 1A) 56,661 53,363 38,448 15,983 15,991 27,500 1984-2014 Connecticut 8,800 7,437

  20. Control Board Digital Interface Input Devices Touchscreen, Trackpad, or Mouse?

    SciTech Connect (OSTI)

    Thomas A. Ulrich; Ronald L. Boring; Roger Lew

    2015-08-01

    The authors collaborated with a power utility to evaluate input devices for use in the human system interface (HSI) for a new digital Turbine Control System (TCS) at a nuclear power plant (NPP) undergoing a TCS upgrade. A standalone dynamic software simulation of the new digital TCS and a mobile kiosk were developed to conduct an input device study to evaluate operator preference and input device effectiveness. The TCS software presented the anticipated HSI for the TCS and mimicked (i.e., simulated) the turbine systems responses to operator commands. Twenty-four licensed operators from the two nuclear power units participated in the study. Three input devices were tested: a trackpad, mouse, and touchscreen. The subjective feedback from the survey indicates the operators preferred the touchscreen interface. The operators subjectively rated the touchscreen as the fastest and most comfortable input device given the range of tasks they performed during the study, but also noted a lack of accuracy for selecting small targets. The empirical data suggest the mouse input device provides the most consistent performance for screen navigation and manipulating on screen controls. The trackpad input device was both empirically and subjectively found to be the least effective and least desired input device.

  1. Developing a low input and sustainable switchgrass feedstock production

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

    system utilizing beneficial bacterial endophytes | Department of Energy Developing a low input and sustainable switchgrass feedstock production system utilizing beneficial bacterial endophytes Developing a low input and sustainable switchgrass feedstock production system utilizing beneficial bacterial endophytes Dr. Chuansheng Mei gave this presentation at the Symbiosis Conference. PDF icon symbiosis_conference_mei.pdf More Documents & Publications Symbiosis Biofeedstock Conference:

  2. TotalView Training 2015

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

    TotalView Training 2015 TotalView Training 2015 NERSC will host an in-depth training course on TotalView, a graphical parallel debugger developed by Rogue Wave Software, on...

  3. Determination of Total Petroleum Hydrocarbons (TPH) Using Total Carbon Analysis

    SciTech Connect (OSTI)

    Ekechukwu, A.A.

    2002-05-10

    Several methods have been proposed to replace the Freon(TM)-extraction method to determine total petroleum hydrocarbon (TPH) content. For reasons of cost, sensitivity, precision, or simplicity, none of the replacement methods are feasible for analysis of radioactive samples at our facility. We have developed a method to measure total petroleum hydrocarbon content in aqueous sample matrixes using total organic carbon (total carbon) determination. The total carbon content (TC1) of the sample is measured using a total organic carbon analyzer. The sample is then contacted with a small volume of non-pokar solvent to extract the total petroleum hydrocarbons. The total carbon content of the resultant aqueous phase of the extracted sample (TC2) is measured. Total petroleum hydrocarbon content is calculated (TPH = TC1-TC2). The resultant data are consistent with results obtained using Freon(TM) extraction followed by infrared absorbance.

  4. Wavelength meter having single mode fiber optics multiplexed inputs

    DOE Patents [OSTI]

    Hackel, Richard P. (Livermore, CA); Paris, Robert D. (San Ramon, CA); Feldman, Mark (Pleasanton, CA)

    1993-01-01

    A wavelength meter having a single mode fiber optics input is disclosed. The single mode fiber enables a plurality of laser beams to be multiplexed to form a multiplexed input to the wavelength meter. The wavelength meter can provide a determination of the wavelength of any one or all of the plurality of laser beams by suitable processing. Another aspect of the present invention is that one of the laser beams could be a known reference laser having a predetermined wavelength. Hence, the improved wavelength meter can provide an on-line calibration capability with the reference laser input as one of the plurality of laser beams.

  5. Wavelength meter having single mode fiber optics multiplexed inputs

    DOE Patents [OSTI]

    Hackel, R.P.; Paris, R.D.; Feldman, M.

    1993-02-23

    A wavelength meter having a single mode fiber optics input is disclosed. The single mode fiber enables a plurality of laser beams to be multiplexed to form a multiplexed input to the wavelength meter. The wavelength meter can provide a determination of the wavelength of any one or all of the plurality of laser beams by suitable processing. Another aspect of the present invention is that one of the laser beams could be a known reference laser having a predetermined wavelength. Hence, the improved wavelength meter can provide an on-line calibration capability with the reference laser input as one of the plurality of laser beams.

  6. V-139: Cisco Network Admission Control Input Validation Flaw...

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

    PROBLEM: Cisco Network Admission Control Input Validation Flaw Lets Remote Users Inject SQL Commands PLATFORM: Cisco NAC Manager versions prior to 4.8.3.1 and 4.9.2 ABSTRACT: A...

  7. Proposed Process: NNMCAB Input on Campaigns | Department of Energy

    Office of Environmental Management (EM)

    Proposed Process: NNMCAB Input on Campaigns Proposed Process: NNMCAB Input on Campaigns Topic: Jeff Mousseau LANL, Provided Information on the New Proposed Campaign Process for Field Work. Field work at LANL to be Divided into 17 Campaigns in 5 Categories. PDF icon Campaign Process - April 9, 2014 More Documents & Publications Associate Directorate for Environmental Programs Update March 26, 2014 Chromium Groundwater Remediation Campaign Associate Directorate for Environmental Programs

  8. DOE Seeks Input On Addressing Contractor Pension and Medical Benefits

    Energy Savers [EERE]

    Liabilities | Department of Energy Input On Addressing Contractor Pension and Medical Benefits Liabilities DOE Seeks Input On Addressing Contractor Pension and Medical Benefits Liabilities March 27, 2007 - 12:10pm Addthis WASHINGTON, DC - The U.S. Department of Energy (DOE) today announced in the Federal Register that it is seeking public comment on how to address the increasing costs and liabilities of contractor employee pension and medical benefits. Under the Department of Energy's unique

  9. Tribal Leaders Provide White House with Input on Bolstering Climate

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

    Resilience | Department of Energy Leaders Provide White House with Input on Bolstering Climate Resilience Tribal Leaders Provide White House with Input on Bolstering Climate Resilience January 7, 2015 - 10:29am Addthis As members of the President's State, Local, and Tribal Leaders Task Force on Climate Preparedness, Mayor Reggie Joule, Northwest Arctic Borough (AK) and Chairwoman Karen Diver, Fond du Lac Band of Lake Superior Chippewa (MN), were tasked by the President with providing

  10. Jimmy Bell's Experience Brings Valuable Input to Federal Advisory Board |

    Office of Environmental Management (EM)

    Department of Energy Jimmy Bell's Experience Brings Valuable Input to Federal Advisory Board Jimmy Bell's Experience Brings Valuable Input to Federal Advisory Board October 9, 2013 - 12:00pm Addthis As a youngster growing up in Hazlehurst, Ga., Jimmy Bell never imagined his future would take him across the globe to places he had only read about. However, through dedication and hard work, he was involved in important projects throughout the United States and around the world. Today, Jimmy is

  11. Summary of Stakeholder Input From May 2015 Request for Information |

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

    Department of Energy Summary of Stakeholder Input From May 2015 Request for Information Summary of Stakeholder Input From May 2015 Request for Information The U.S. Department of Energy (DOE) sought FY15 feedback through issuance of a Request for Information from public and private sector stakeholders. This RFI received commentary across five areas of interest, including: Technology Commercialization Fund, Cross-Research and Development Linkages and Innovation Cycle Transitions, Central

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    Broader source: Energy.gov [DOE]

    The software does not properly filter HTML code from user-supplied input before displaying the input.

  13. V-193: Barracuda SSL VPN Input Validation Hole Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Several scripts do not properly filter HTML code from user-supplied input before displaying the input via several parameters

  14. U.S. Total Exports

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

    Warroad, MN Babb, MT Havre, MT Port of Morgan, MT Sherwood, ND Pittsburg, NH Buffalo, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to Egypt Freeport, TX Total to India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Freeport, TX Kenai, AK Port Nikiski, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Sasabe, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA San

  15. U.S. Total Exports

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

    Babb, MT Havre, MT Port of Morgan, MT Sherwood, ND Pittsburg, NH Buffalo, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to Egypt Freeport, TX Total to India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Kenai, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Sasabe, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass,

  16. Total Eolica | Open Energy Information

    Open Energy Info (EERE)

    Eolica Jump to: navigation, search Name: Total Eolica Place: Spain Product: Project developer References: Total Eolica1 This article is a stub. You can help OpenEI by expanding...

  17. Total........................................................

    Gasoline and Diesel Fuel Update (EIA)

    111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351

  18. Total...........................................................

    Gasoline and Diesel Fuel Update (EIA)

    Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space

  19. Total...........................................................

    Gasoline and Diesel Fuel Update (EIA)

    Q Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing

  20. Total............................................................

    Gasoline and Diesel Fuel Update (EIA)

  1. Total.............................................................

    Gasoline and Diesel Fuel Update (EIA)

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer....................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Most-Used Personal Computer Type of PC Desk-top Model.................................. 58.6 7.6 14.2 13.1 9.2 14.6 5.0 14.5 Laptop Model...................................... 16.9 2.0 3.8 3.3 2.1 5.7 1.3 3.5 Hours Turned on Per Week Less than 2 Hours..............................

  2. Total..............................................................

    Gasoline and Diesel Fuel Update (EIA)

    ,171 1,618 1,031 845 630 401 Census Region and Division Northeast................................................... 20.6 2,334 1,664 562 911 649 220 New England.......................................... 5.5 2,472 1,680 265 1,057 719 113 Middle Atlantic........................................ 15.1 2,284 1,658 670 864 627 254 Midwest...................................................... 25.6 2,421 1,927 1,360 981 781 551 East North Central.................................. 17.7 2,483 1,926 1,269

  3. Total..............................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment................ 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat

  4. Total...............................................................

    Gasoline and Diesel Fuel Update (EIA)

    20.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer ........... 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer......................... 75.6 13.7 17.5 26.6 17.8 Number of Desktop PCs 1.......................................................... 50.3 9.3 11.9 18.2 11.0 2.......................................................... 16.2 2.9 3.5 5.5 4.4 3 or More............................................. 9.0 1.5 2.1 2.9 2.5 Number of Laptop PCs

  5. Total...............................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.7 21.7 6.9 12.1 Personal Computers Do Not Use a Personal Computer ........... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer......................... 75.6 26.6 14.5 4.1 7.9 Number of Desktop PCs 1.......................................................... 50.3 18.2 10.0 2.9 5.3 2.......................................................... 16.2 5.5 3.0 0.7 1.8 3 or More............................................. 9.0 2.9 1.5 0.5 0.8 Number of Laptop PCs

  6. Total...............................................................

    Gasoline and Diesel Fuel Update (EIA)

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer ........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Number of Desktop PCs 1.......................................................... 50.3 8.3 14.2 11.4 7.2 9.2 5.3 14.2 2.......................................................... 16.2 0.9 2.6 3.7 2.9 6.2 0.8 2.6 3 or More............................................. 9.0 0.4 1.2

  7. Total...............................................................

    Gasoline and Diesel Fuel Update (EIA)

    47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer ........... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......................... 75.6 30.3 12.5 18.1 14.7 Number of Desktop PCs 1.......................................................... 50.3 21.1 8.3 10.7 10.1 2.......................................................... 16.2 6.2 2.8 4.1 3.0 3 or More............................................. 9.0 2.9 1.4 3.2 1.6 Number of Laptop PCs

  8. Total.................................................................

    Gasoline and Diesel Fuel Update (EIA)

    49.2 15.1 15.6 11.1 7.0 5.2 8.0 Have Cooling Equipment............................... 93.3 31.3 15.1 15.6 11.1 7.0 5.2 8.0 Use Cooling Equipment................................ 91.4 30.4 14.6 15.4 11.1 6.9 5.2 7.9 Have Equipment But Do Not Use it............... 1.9 1.0 0.5 Q Q Q Q Q Do Not Have Cooling Equipment................... 17.8 17.8 N N N N N N Air-Conditioning Equipment 1, 2 Central System............................................. 65.9 3.9 15.1 15.6 11.1 7.0 5.2 8.0 Without a Heat

  9. Total.................................................................

    Gasoline and Diesel Fuel Update (EIA)

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Space Heating Equipment........ 1.2 N Q Q 0.2 0.4 0.2 0.2 Q Have Main Space Heating Equipment........... 109.8 14.7 7.4 12.4 12.2 18.5 18.3 17.1 9.2 Use Main Space Heating Equipment............. 109.1 14.6 7.3 12.4 12.2 18.2 18.2 17.1 9.1 Have Equipment But Do Not Use It............... 0.8 Q Q Q Q 0.3 Q N Q Main Heating Fuel and Equipment Natural Gas................................................... 58.2 9.2 4.9 7.8 7.1 8.8 8.4 7.8 4.2 Central

  10. Total..................................................................

    Gasoline and Diesel Fuel Update (EIA)

    78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat

  11. Total..................................................................

    Gasoline and Diesel Fuel Update (EIA)

    33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment..................... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment................................. 93.3 26.5 6.5 2.5 4.6 12.0 1.0 Use Cooling Equipment.................................. 91.4 25.7 6.3 2.5 4.4 11.7 0.8 Have Equipment But Do Not Use it................. 1.9 0.8 Q Q 0.2 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 14.1 3.6 1.5 2.1 6.4 0.6 Without a Heat

  12. Total..................................................................

    Gasoline and Diesel Fuel Update (EIA)

    . 111.1 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Cooling Equipment..................... 17.8 3.9 1.8 2.2 2.1 3.1 2.6 1.7 0.4 Have Cooling Equipment................................. 93.3 10.8 5.6 10.3 10.4 15.8 16.0 15.6 8.8 Use Cooling Equipment.................................. 91.4 10.6 5.5 10.3 10.3 15.3 15.7 15.3 8.6 Have Equipment But Do Not Use it................. 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central

  13. Total...................................................................

    Gasoline and Diesel Fuel Update (EIA)

    15.2 7.8 1.0 1.2 3.3 1.9 For Two Housing Units............................. 0.9 Q N Q 0.6 N Heat Pump.................................................. 9.2 7.4 0.3 Q 0.7 0.5 Portable Electric Heater............................... 1.6 0.8 Q Q Q 0.3 Other Equipment......................................... 1.9 0.7 Q Q 0.7 Q Fuel Oil........................................................... 7.7 5.5 0.4 0.8 0.9 0.2 Steam or Hot Water System........................ 4.7 2.9 Q 0.7 0.8 N For One Housing

  14. Total...................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Air-Conditioning Equipment 1, 2 Central System............................................... 65.9 47.5 4.0 2.8 7.9 3.7 Without a Heat Pump.................................. 53.5 37.8 3.4 2.2 7.0 3.1 With a Heat Pump....................................... 12.3 9.7 0.6 0.5 1.0 0.6 Window/Wall Units.......................................... 28.9 14.9 2.3 3.5 6.0 2.1 1 Unit........................................................... 14.5 6.6 1.0 1.6 4.2 1.2 2

  15. Total...................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 47.5 4.0 2.8 7.9 3.7 Without a Heat Pump.................................. 53.5 37.8 3.4 2.2 7.0 3.1 With a Heat Pump....................................... 12.3 9.7 0.6 0.5 1.0 0.6 Window/Wall Units........................................ 28.9 14.9 2.3 3.5 6.0 2.1 1 Unit........................................................... 14.5 6.6 1.0 1.6 4.2 1.2 2

  16. Total.......................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.6 15.1 5.5 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.9 5.3 1.6 Use a Personal Computer................................ 75.6 13.7 9.8 3.9 Number of Desktop PCs 1.................................................................. 50.3 9.3 6.8 2.5 2.................................................................. 16.2 2.9 1.9 1.0 3 or More..................................................... 9.0 1.5 1.1 0.4 Number of Laptop PCs

  17. Total.......................................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer ................... 35.5 8.1 5.6 2.5 Use a Personal Computer................................ 75.6 17.5 12.1 5.4 Number of Desktop PCs 1.................................................................. 50.3 11.9 8.4 3.4 2.................................................................. 16.2 3.5 2.2 1.3 3 or More..................................................... 9.0 2.1 1.5 0.6 Number of Laptop PCs

  18. Total.......................................................................

    Gasoline and Diesel Fuel Update (EIA)

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.4 2.2 4.2 Use a Personal Computer................................ 75.6 17.8 5.3 12.5 Number of Desktop PCs 1.................................................................. 50.3 11.0 3.4 7.6 2.................................................................. 16.2 4.4 1.3 3.1 3 or More..................................................... 9.0 2.5 0.7 1.8 Number of Laptop PCs

  19. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    25.6 40.7 24.2 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.7 Have Main Space Heating Equipment.................. 109.8 20.5 25.6 40.3 23.4 Use Main Space Heating Equipment.................... 109.1 20.5 25.6 40.1 22.9 Have Equipment But Do Not Use It...................... 0.8 N N Q 0.6 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 18.4 13.6 14.7 Central Warm-Air Furnace................................ 44.7 6.1

  20. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing

  1. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Do Not Have Space Heating Equipment............... 1.2 Q Q N Have Main Space Heating Equipment.................. 109.8 25.6 17.7 7.9 Use Main Space Heating Equipment.................... 109.1 25.6 17.7 7.9 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 18.4 13.1 5.3 Central Warm-Air Furnace................................ 44.7 16.2 11.6 4.7 For One Housing

  2. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.7 21.7 6.9 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q N Q Have Main Space Heating Equipment.................. 109.8 40.3 21.4 6.9 12.0 Use Main Space Heating Equipment.................... 109.1 40.1 21.2 6.9 12.0 Have Equipment But Do Not Use It...................... 0.8 Q Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 13.6 5.6 2.3 5.7 Central Warm-Air Furnace................................ 44.7 11.0 4.4

  3. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    4.2 7.6 16.6 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.7 Have Main Space Heating Equipment.................. 109.8 23.4 7.5 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One

  4. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 7.0 8.0 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.2 Have Main Space Heating Equipment.................. 109.8 7.1 6.8 7.9 11.9 Use Main Space Heating Equipment.................... 109.1 7.1 6.6 7.9 11.4 Have Equipment But Do Not Use It...................... 0.8 N Q N 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 3.8 0.4 3.8 8.4 Central Warm-Air Furnace................................ 44.7 1.8 Q 3.1 6.0

  5. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7

  6. Total...........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.6 15.1 5.5 Do Not Have Cooling Equipment............................. 17.8 4.0 2.4 1.7 Have Cooling Equipment.......................................... 93.3 16.5 12.8 3.8 Use Cooling Equipment........................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it.......................... 1.9 0.3 Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 5.2 0.8 Without a Heat

  7. Total...........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Do Not Have Cooling Equipment............................. 17.8 2.1 1.8 0.3 Have Cooling Equipment.......................................... 93.3 23.5 16.0 7.5 Use Cooling Equipment........................................... 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it.......................... 1.9 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat

  8. Total...........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    4.2 7.6 16.6 Do Not Have Cooling Equipment............................. 17.8 10.3 3.1 7.3 Have Cooling Equipment.......................................... 93.3 13.9 4.5 9.4 Use Cooling Equipment........................................... 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it.......................... 1.9 1.0 Q 0.8 Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat

  9. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................ 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................ 1.9 0.3 Q 0.5 1.0 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 17.3 32.1 10.5 Without a Heat

  10. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.2 1.0 0.2 2 Times A Day...................................................... 24.6 4.0 2.7 1.2 Once a Day........................................................... 42.3 7.9 5.4 2.5 A Few Times Each Week...................................... 27.2 6.0 4.8 1.2 About Once a Week.............................................. 3.9 0.6 0.5 Q Less Than Once a

  11. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.4 1.0 0.4 2 Times A Day...................................................... 24.6 5.8 3.5 2.3 Once a Day........................................................... 42.3 10.7 7.8 2.9 A Few Times Each Week...................................... 27.2 5.6 4.0 1.6 About Once a Week.............................................. 3.9 0.9 0.6 0.3 Less Than Once a

  12. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 2.1 1.8 0.3 Have Cooling Equipment............................................ 93.3 23.5 16.0 7.5 Use Cooling Equipment............................................. 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it............................ 1.9 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat

  13. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................ 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................ 1.9 0.5 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 32.1 17.6 5.2 9.3 Without a Heat

  14. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 2.6 0.7 1.9 2 Times A Day...................................................... 24.6 6.6 2.0 4.6 Once a Day........................................................... 42.3 8.8 2.9 5.8 A Few Times Each Week...................................... 27.2 4.7 1.5 3.1 About Once a Week.............................................. 3.9 0.7 Q 0.6 Less Than Once a

  15. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 10.3 3.1 7.3 Have Cooling Equipment............................................ 93.3 13.9 4.5 9.4 Use Cooling Equipment............................................. 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it............................ 1.9 1.0 Q 0.8 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat

  16. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................ 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................ 1.9 0.9 0.3 0.3 0.4 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 25.8 10.9 16.6 12.5 Without a Heat

  17. Total..............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    20.6 25.6 40.7 24.2 Do Not Have Cooling Equipment................................ 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................. 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment.............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................. 1.9 0.3 Q 0.5 1.0 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 6.0 17.3 32.1 10.5

  18. Total..............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.7 21.7 6.9 12.1 Do Not Have Cooling Equipment................................ 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................. 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment.............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................. 1.9 0.5 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 32.1 17.6 5.2 9.3 Without a

  19. Total..............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer .......................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer....................................... 75.6 4.2 5.0 5.3 9.0 Number of Desktop PCs 1......................................................................... 50.3 3.1 3.4 3.4 5.4 2......................................................................... 16.2 0.7 1.1 1.2 2.2 3 or More............................................................ 9.0 0.3

  20. Total..............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 19.0 22.7 22.3 Do Not Have Cooling Equipment................................ 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................. 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment.............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................. 1.9 0.9 0.3 0.3 0.4 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 25.8 10.9 16.6 12.5

  1. Total.................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    ... 111.1 20.6 15.1 5.5 Do Not Have Cooling Equipment................................. 17.8 4.0 2.4 1.7 Have Cooling Equipment............................................. 93.3 16.5 12.8 3.8 Use Cooling Equipment............................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it............................. 1.9 0.3 Q Q Type of Air-Conditioning Equipment 1, 2 Central System.......................................................... 65.9 6.0 5.2 0.8 Without a Heat

  2. Total.................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 7.0 8.0 12.1 Do Not Have Cooling Equipment................................... 17.8 1.8 Q Q 4.9 Have Cooling Equipment................................................ 93.3 5.3 7.0 7.8 7.2 Use Cooling Equipment................................................. 91.4 5.3 7.0 7.7 6.6 Have Equipment But Do Not Use it............................... 1.9 Q N Q 0.6 Air-Conditioning Equipment 1, 2 Central System.............................................................. 65.9 1.1 6.4 6.4 5.4 Without a

  3. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer.............................................. 75.6 13.7 17.5 26.6 17.8 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 10.4 14.1 20.5 13.7 Laptop Model............................................................. 16.9 3.3 3.4 6.1 4.1 Hours Turned on Per Week Less than 2

  4. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer.................................. 35.5 8.1 5.6 2.5 Use a Personal Computer.............................................. 75.6 17.5 12.1 5.4 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 14.1 10.0 4.0 Laptop Model............................................................. 16.9 3.4 2.1 1.3 Hours Turned on Per Week Less than 2

  5. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Personal Computers Do Not Use a Personal Computer.................................. 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer.............................................. 75.6 26.6 14.5 4.1 7.9 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 20.5 11.0 3.4 6.1 Laptop Model............................................................. 16.9 6.1 3.5 0.7 1.9 Hours Turned on Per Week Less than 2

  6. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.4 2.2 4.2 Use a Personal Computer.............................................. 75.6 17.8 5.3 12.5 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 13.7 4.2 9.5 Laptop Model............................................................. 16.9 4.1 1.1 3.0 Hours Turned on Per Week Less than 2

  7. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer.................................. 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer.............................................. 75.6 30.3 12.5 18.1 14.7 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 22.9 9.8 14.1 11.9 Laptop Model............................................................. 16.9 7.4 2.7 4.0 2.9 Hours Turned on Per Week Less than 2

  8. Total.........................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer...................................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer.................................................. 75.6 4.2 5.0 5.3 9.0 Most-Used Personal Computer Type of PC Desk-top Model............................................................. 58.6 3.2 3.9 4.0 6.7 Laptop Model................................................................. 16.9 1.0 1.1 1.3 2.4 Hours Turned on Per Week Less

  9. Total..........................................................

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

    ... 2.0 0.4 Q 0.3 Basements Basement in Single-Family Homes and Apartments in 2-4 Unit Buildings Yes......

  10. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    Housing Units Living Space Characteristics Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Single-Family Units Detached...

  11. Total..........................................................

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

    ... Living Space Characteristics Below Poverty Line Eligible for Federal Assistance 1 Million ... Living Space Characteristics Below Poverty Line Eligible for Federal Assistance 1 Million ...

  12. Total..........................................................

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

    ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More 60,000 to 79,999 ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More 60,000 to 79,999 ...

  13. Total..........................................................

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

    ... Table HC7.4 Space Heating Characteristics by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More Space Heating ...

  14. Total..........................................................

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

    ... Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 40,000 to 59,999 60,000 to 79,999 ...

  15. Total..........................................................

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

    Income Relative to Poverty Line Below 100 Percent......1.3 1.2 0.8 0.4 1. Below 150 percent of poverty line or 60 percent of median State ...

  16. Total..........................................................

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

    ... Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005 Million U.S. Housing Units South Census Region Home Appliances Usage Indicators South Atlantic East ...

  17. Total..........................................................

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

    ... Table HC8.10 Home Appliances Usage Indicators by UrbanRural Location, 2005 Million U.S. Housing Units UrbanRural Location (as Self-Reported) Housing Units (millions) Home ...

  18. Total..............................................

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

    ... 14.8 10.5 2,263 1,669 1,079 1,312 1,019 507 N N N ConcreteConcrete Block... 5.3 3.4 2,393 1,660 1,614 Q Q Q Q Q Q Composition...

  19. Input-output model for MACCS nuclear accident impacts estimation

    SciTech Connect (OSTI)

    Outkin, Alexander V.; Bixler, Nathan E.; Vargas, Vanessa N

    2015-01-27

    Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.

  20. Optical device with conical input and output prism faces

    DOE Patents [OSTI]

    Brunsden, Barry S.

    1981-01-01

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

  1. TH-A-9A-06: Inverse Planning of Gamma Knife Radiosurgery Using Natural

    Office of Scientific and Technical Information (OSTI)

    Physical Models (Journal Article) | SciTech Connect TH-A-9A-06: Inverse Planning of Gamma Knife Radiosurgery Using Natural Physical Models Citation Details In-Document Search Title: TH-A-9A-06: Inverse Planning of Gamma Knife Radiosurgery Using Natural Physical Models Purpose: Treatment-planning systems rely on computer intensive optimization algorithms in order to provide radiation dose localization. We are investigating a new optimization paradigm based on natural physical modeling and

  2. US Nuclear Regulatory Commission Input to DOE Request for Information Smart

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

    Grid Implementation Input | Department of Energy US Nuclear Regulatory Commission Input to DOE Request for Information Smart Grid Implementation Input US Nuclear Regulatory Commission Input to DOE Request for Information Smart Grid Implementation Input US Nuclear Regulatory Commission Input to DOE Request for Information Smart Grid Implementation Input. Comments relevant to the following two sections of the RFI: "Long Term Issues: Managing a Grid with High Penetration of New

  3. Table 3. U.S. Inputs to biodiesel production

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

    U.S. Inputs to biodiesel production" "million pounds" ,"Feedstock inputs" ,"Vegetable oils",,,,,,,,,,,,"Animal fats" "Period","Canola oil",,"Corn oil",,"Cottonseed oil",,"Palm oil",,"Soybean oil",,"Other",,"Poultry",,"Tallow" 2013 "January",16,,60,,0,,"W",,313,,"W",,7,,15

  4. Minnesota Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Minnesota Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 48 106 337 1 3 11 2 1 385 315 1990's 56 49 52 78 289 194 709 172 50 64 2000's 101 118 13 42 71 154 13 54 46 47 2010's 12 20 9 22 66 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  5. New Hampshire Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) New Hampshire Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 774 720 582 328 681 509 362 464 492 592 1990's 205 128 96 154 160 90 147 102 103 111 2000's 180 86 66 58 91 84 92 9 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

  6. South Carolina Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) South Carolina Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 74 184 63 73 62 87 31 22 191 201 1990's 17 47 26 34 154 62 178 10 0 18 2000's 63 6 3 15 2 86 75 0 2010's 0 0 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  7. Virginia Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Virginia Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 127 443 454 375 209 414 75 141 643 428 1990's 59 240 245 538 1,195 445 716 350 148 179 2000's 493 239 124 368 145 192 39 89 89 247 2010's 159 89 48 130 301 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  8. Georgia Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Georgia Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 24 57 151 84 28 121 124 248 241 292 1990's 209 185 166 199 123 130 94 14 16 12 2000's 73 51 7 14 5 0 3 2 52 2010's 732 701 660 642 635 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  9. Maryland Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Maryland Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 484 498 984 352 332 373 155 136 743 899 1990's 24 72 126 418 987 609 882 178 80 498 2000's 319 186 48 160 124 382 41 245 181 170 2010's 115 89 116 107 809 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  10. STCH Annual Merit Review Input - EERE Hydrogen Program. (Conference) |

    Office of Scientific and Technical Information (OSTI)

    SciTech Connect STCH Annual Merit Review Input - EERE Hydrogen Program. Citation Details In-Document Search Title: STCH Annual Merit Review Input - EERE Hydrogen Program. Abstract not provided. Authors: Siegel, Nathan Phillip Publication Date: 2008-05-01 OSTI Identifier: 1145867 Report Number(s): SAND2008-3332C 518638 DOE Contract Number: DE-AC04-94AL85000 Resource Type: Conference Resource Relation: Conference: Annual merit review held June 10-12, 2008 in DC, DC.; Related Information:

  11. Characteristics RSE Column Factor: Total

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

    and 1994 Vehicle Characteristics RSE Column Factor: Total 1993 Family Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factor: Less than 5,000 5,000...

  12. ARM - Measurement - Total cloud water

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

    cloud water ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total cloud water The total concentration (mass/vol) of ice and liquid water particles in a cloud; this includes condensed water content (CWC). Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a

  13. Microchannel cross load array with dense parallel input

    DOE Patents [OSTI]

    Swierkowski, Stefan P.

    2004-04-06

    An architecture or layout for microchannel arrays using T or Cross (+) loading for electrophoresis or other injection and separation chemistry that are performed in microfluidic configurations. This architecture enables a very dense layout of arrays of functionally identical shaped channels and it also solves the problem of simultaneously enabling efficient parallel shapes and biasing of the input wells, waste wells, and bias wells at the input end of the separation columns. One T load architecture uses circular holes with common rows, but not columns, which allows the flow paths for each channel to be identical in shape, using multiple mirror image pieces. Another T load architecture enables the access hole array to be formed on a biaxial, collinear grid suitable for EDM micromachining (square holes), with common rows and columns.

  14. Alabama Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Alabama Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 50 23 91 9 54 14 3 2 17 16 1990's 320 332 171 410 69 0 18 21 2 4 2000's 0 0 0 22 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: 2/29/2016 Next

  15. Arizona Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Arizona Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 7 0 0 0 91 101 0 0 1990's 0 0 0 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 data. Release Date: 2/29/2016 Next Release Date:

  16. Arkansas Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Arkansas Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 7 8 6 0 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 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: 2/29/2016 Next Release Date:

  17. Massachusetts Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Massachusetts Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 15,366 21,828 17,586 10,732 6,545 3,668 2,379 1,404 876 692 1990's 317 120 105 61 154 420 426 147 68 134 2000's 26 16 137 324 80 46 51 15 13 10 2010's 0 3 8 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  18. Michigan Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Michigan Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 3 3,038 2,473 2,956 2,773 2,789 2,754 2,483 2,402 2,402 1990's 19,106 15,016 14,694 12,795 13,688 21,378 21,848 22,238 21,967 20,896 2000's 12,423 4,054 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

  19. Missouri Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Missouri Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 65 60 2,129 1,278 326 351 1 1 2 1,875 1990's 0 0 0 0 371 4 785 719 40 207 2000's 972 31 62 1,056 917 15 78 66 6 10 2010's 18 172 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  20. Nebraska Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Nebraska Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 9 1,838 63 2,006 2,470 2,689 2,142 2,199 1,948 2,088 1990's 2,361 2,032 1,437 791 890 15 315 134 11 4 2000's 339 6 1 13 39 16 19 33 28 18 2010's 12 9 4 2 376 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  1. Nevada Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Nevada Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 4 0 2 2 2 4 11 11 32 37 1990's 125 0 30 38 9 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 data. Release Date: 2/29/2016 Next Release Date:

  2. New Jersey Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) New Jersey Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 9,574 11,504 9,786 9,896 8,616 13,421 12,099 13,774 14,846 14,539 1990's 9,962 14,789 14,362 14,950 7,737 7,291 6,778 6,464 9,082 5,761 2000's 8,296 12,330 3,526 473 530 435 175 379 489 454 2010's 457 392 139 255 530 - = No Data Reported; -- = Not Applicable;

  3. New Mexico Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) New Mexico Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 1 3 0 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 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: 2/29/2016 Next Release Date:

  4. North Dakota Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) North Dakota Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 196 417 102 0 8,335 40,370 49,847 51,543 49,014 54,408 1990's 53,144 52,557 58,496 57,680 57,127 57,393 55,867 53,179 54,672 53,185 2000's 49,190 51,004 53,184 53,192 47,362 51,329 54,361 51,103 50,536 53,495 2010's 54,813 51,303 52,541 45,736 48,394 - = No

  5. Ohio Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Ohio Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 69,169 69,850 64,812 62,032 43,866 24,444 5,182 18 44 348 1990's 849 891 1,051 992 1,432 904 1,828 1,423 1,194 1,200 2000's 1,442 1,149 79 1,002 492 579 423 608 460 522 2010's 353 296 366 416 641 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  6. Oregon Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Oregon Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 24 3 6 6 10 10 6 3 1990's 3 4 2 3 2 2 2 2 2 3 2000's 2 2 5 5 2 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: 2/29/2016 Next Release Date:

  7. Pennsylvania Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Pennsylvania Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 3,127 10,532 5,621 3,844 82 221 196 247 254 305 1990's 220 222 132 110 252 75 266 135 80 119 2000's 261 107 103 126 131 132 124 145 123 205 2010's 4 2 2 3 20 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  8. Rhode Island Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Rhode Island Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 257 951 718 594 102 130 182 109 391 219 1990's 51 92 155 126 0 27 42 18 1 1 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:

  9. South Dakota Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) South Dakota Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 9 24 50 1 0 0 0 0 10 16 1990's 10 3 10 9 61 37 87 30 4 5 2000's 13 5 3 57 5 4 0 1 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: 2/29/2016 Next

  10. Tennessee Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Tennessee Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 12 42 90 39 25 36 13 26 36 78 1990's 3 8 12 13 84 33 73 19 4 11 2000's 13 0 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: 2/29/2016 Next

  11. Vermont Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Vermont Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 0 0 0 0 0 0 0 1990's 0 6 3 4 9 4 5 6 0 1 2000's 7 104 2 10 12 9 2 2 1 2 2010's 1 2 3 3 5 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date:

  12. Washington Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Washington Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 15 13 15 11 11 9 10 21 79 154 1990's 181 154 180 4 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 data. Release Date: 2/29/2016 Next

  13. Delaware Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Delaware Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 55 135 56 20 13 12 9 0 2 18 1990's 4,410 4,262 3,665 3,597 3,032 1 1 2 0 0 2000's 6 0 0 7 17 0 W 5 2 2 2010's 1 0 6 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016

  14. District of Columbia Natural Gas Input Supplemental Fuels (Million Cubic

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

    Feet) Input Supplemental Fuels (Million Cubic Feet) District of Columbia Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 2 1 46 0 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 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: 2/29/2016

  15. Florida Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Florida Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 1 3 1 0 3 0 0 0 0 1990's 0 0 0 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 data. Release Date: 2/29/2016 Next Release Date:

  16. Hawaii Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Hawaii Natural Gas Input Supplemental Fuels (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 3,190 2,993 2,899 2,775 2,449 2,655 2,630 2,461 2,801 2,844 1990's 2,817 2,725 2,711 2,705 2,831 2,793 2,761 2,617 2,715 2,752 2000's 2,769 2,689 2,602 2,602 2,626 2,606 2,613 2,683 2,559 2,447 2010's 2,472 2,467 2,510 2,658 2,743 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  17. Illinois Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Illinois Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 36,713 29,509 19,005 19,734 17,308 19,805 22,980 12,514 9,803 9,477 1990's 8,140 6,869 8,042 9,760 7,871 6,256 3,912 4,165 2,736 2,527 2000's 1,955 763 456 52 14 15 13 11 15 20 2010's 17 1 1 63 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  18. Indiana Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Indiana Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 1,602 5,056 3,496 4,142 4,027 2,711 2,351 3,890 4,243 3,512 1990's 3,015 3,077 3,507 3,232 2,457 3,199 3,194 3,580 3,149 5,442 2000's 5,583 5,219 1,748 2,376 2,164 1,988 1,642 635 30 1 2010's 1 5 1 6 69 - = No Data Reported; -- = Not Applicable; NA = Not

  19. Iowa Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Iowa Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 57 64 68 23 53 45 44 40 34 82 1990's 81 46 45 84 123 96 301 137 17 12 2000's 44 39 23 143 30 31 46 40 27 3 2010's 2 1 0 0 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  20. Kentucky Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Kentucky Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 42 2 131 259 94 4 1 0 6 44 1990's 2 2 5 16 50 6 45 24 2 3 2000's 10 2 1 98 0 15 3 124 15 18 2010's 5 8 1 29 52 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next

  1. Maine Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Maine Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 157 94 71 12 0 0 0 0 0 0 1990's 0 0 0 0 0 96 61 31 24 43 2000's 6 0 5 6 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: 2/29/2016 Next Release

  2. Wisconsin Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Wisconsin Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 2 4 13 2 6 14 1 1 2 5 1990's 1 1 1 3 5 2 21 5 21 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: 2/29/2016 Next Release Date:

  3. Wyoming Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Wyoming Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 124 222 518 373 271 316 339 303 291 167 1990's 0 0 0 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 data. Release Date: 2/29/2016 Next

  4. U-050: Adobe Flex SDK Input Validation Flaw Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Flex applications created using the Flex SDK may not properly filter HTML code from user-supplied input before displaying the input.

  5. PERSPECTIVES ON A DOE CONSEQUENCE INPUTS FOR ACCIDENT ANALYSIS APPLICATIONS

    SciTech Connect (OSTI)

    , K; Jonathan Lowrie, J; David Thoman , D; Austin Keller , A

    2008-07-30

    Department of Energy (DOE) accident analysis for establishing the required control sets for nuclear facility safety applies a series of simplifying, reasonably conservative assumptions regarding inputs and methodologies for quantifying dose consequences. Most of the analytical practices are conservative, have a technical basis, and are based on regulatory precedent. However, others are judgmental and based on older understanding of phenomenology. The latter type of practices can be found in modeling hypothetical releases into the atmosphere and the subsequent exposure. Often the judgments applied are not based on current technical understanding but on work that has been superseded. The objective of this paper is to review the technical basis for the major inputs and assumptions in the quantification of consequence estimates supporting DOE accident analysis, and to identify those that could be reassessed in light of current understanding of atmospheric dispersion and radiological exposure. Inputs and assumptions of interest include: Meteorological data basis; Breathing rate; and Inhalation dose conversion factor. A simple dose calculation is provided to show the relative difference achieved by improving the technical bases.

  6. Characterization of industrial process waste heat and input heat streams

    SciTech Connect (OSTI)

    Wilfert, G.L.; Huber, H.B.; Dodge, R.E.; Garrett-Price, B.A.; Fassbender, L.L.; Griffin, E.A.; Brown, D.R.; Moore, N.L.

    1984-05-01

    The nature and extent of industrial waste heat associated with the manufacturing sector of the US economy are identified. Industry energy information is reviewed and the energy content in waste heat streams emanating from 108 energy-intensive industrial processes is estimated. Generic types of process equipment are identified and the energy content in gaseous, liquid, and steam waste streams emanating from this equipment is evaluated. Matchups between the energy content of waste heat streams and candidate uses are identified. The resultant matrix identifies 256 source/sink (waste heat/candidate input heat) temperature combinations. (MHR)

  7. Gross Input to Atmospheric Crude Oil Distillation Units

    Gasoline and Diesel Fuel Update (EIA)

    Day) Process: Gross Input to Atmospheric Crude Oil Dist. Units Operable Capacity (Calendar Day) Operating Capacity Idle Operable Capacity Operable Utilization Rate Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Process Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S. 17,178 16,963 16,394 15,690 16,673 16,848 1985-2015 PADD 1 1,192 1,196 1,063 1,133 1,190 1,136 1985-2015 East

  8. Summary of Input Request for Information DE-FOA-0001346 | Department of

    Energy Savers [EERE]

    Energy Summary of Input Request for Information DE-FOA-0001346 Summary of Input Request for Information DE-FOA-0001346 PDF icon September 2015 More Documents & Publications Summary of Stakeholder Input From May 2015 Request for Information Summary of Input Request for Information DE-FOA-0001346 DE-FOA-0001346 -- Request for Information (RFI) Summary of Input Request for Information DE-FOA-0001346 FY 2017 President's Budget Request for the Office of Technology Transitions

  9. Heat transfer analysis in Stirling engine heat input system

    SciTech Connect (OSTI)

    Chung, W.; Kim, S.

    1995-12-31

    One of the major factor in commercialization of Stirling engine is mass productivity, and the heat input system including tubular heater is one of the obstacles to mass production because of its complexity in shape and difficulty in manufacturing, which resulted from using oxidation-resistant, low-creep alloys which are not easy to machine and weld. Therefore a heater heat exchanger which is very simple in shape and easy to make has been devised, and a burner system appropriate to this heater also has been developed. In this paper specially devised heat input system which includes a heater shell shaped like U-cup and a flame tube located in the heater shell is analyzed in point of heat transfer processes to find optimum heat transfer. To enhance the heat transfer from the flame tube to the heater shell wall, it is required that the flame tube diameter be enlarged as close to the heater shell diameter as possible, and the flame tube temperature be raised as high as possible. But the enlargement of the flame tube diameter should be restricted by the state of combustion affected by hydraulic resistance of combustion gas, and the boost of the flame tube temperature should be considered carefully in the aspects of the flame tube`s service life.

  10. RF Input Power Couplers for High Current SRF Applications

    SciTech Connect (OSTI)

    Khan, V. F.; Anders, W.; Burrill, Andrew; Knobloch, Jens; Kugeler, Oliver; Neumann, Axel; Wang, Haipeng

    2014-12-01

    High current SRF technology is being explored in present day accelerator science. The bERLinPro project is presently being built at HZB to address the challenges involved in high current SRF machines with the goal of generating and accelerating a 100 mA electron beam to 50 MeV in continuous wave (cw) mode at 1.3 GHz. One of the main challenges in this project is that of handling the high input RF power required for the photo-injector as well as booster cavities where there is no energy recovery process. A high power co-axial input power coupler is being developed to be used for the photo-injector and booster cavities at the nominal beam current. The coupler is based on the KEK–cERL design and has been modified to minimise the penetration of the coupler tip in the beam pipe without compromising on beam-power coupling (Qext ~105). Herein we report on the RF design of the high power (115 kW per coupler, dual couplers per cavity) bERLinPro (BP) coupler along with initial results on thermal calculations. We summarise the RF conditioning of the TTF-III couplers (modified for cw operation) performed in the past at BESSY/HZB. A similar conditioning is envisaged in the near future for the low current SRF photo-injector and the bERLinPro main linac cryomodule.

  11. Colorado Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Colorado Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 9,868 9,133 8,877 7,927 9,137 8,934 8,095 8,612 10,322 9,190 1990's 15,379 6,778 7,158 8,456 8,168 7,170 6,787 6,314 5,292 4,526 2000's 4,772 5,625 5,771 5,409 5,308 5,285 6,149 6,869 6,258 7,527 2010's 5,148 4,268 4,412 4,077 4,120 - = No Data Reported; -- = Not

  12. Residential oil burners with low input and two stages firing

    SciTech Connect (OSTI)

    Butcher, T.; Krajewski, R.; Leigh, R.

    1997-12-31

    The residential oil burner market is currently dominated by the pressure-atomized, retention head burner. At low firing rates pressure atomizing nozzles suffer rapid fouling of the small internal passages, leading to bad spray patterns and poor combustion performance. To overcome the low input limitations of conventional burners, a low pressure air-atomized burner has been developed watch can operate at fining rates as low as 0.25 gallons of oil per hour (10 kW). In addition, the burner can be operated in a high/low fining rate mode. Field tests with this burner have been conducted at a fixed input rate of 0.35 gph (14 kW) with a side-wall vented boiler/water storage tank combination. At the test home, instrumentation was installed to measure fuel and energy flows and record trends in system temperatures. Laboratory efficiency testing with water heaters and boilers has been completed using standard single purpose and combined appliance test procedures. The tests quantify benefits due to low firing rates and other burner features. A two stage oil burner gains a strong advantage in rated efficiency while maintaining capacity for high domestic hot water and space heating loads.

  13. Total Number of Operable Refineries

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

    Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge

  14. Total Energy Outcome City Pilot

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

    Total Energy Outcome City Pilot 2014 Building Technologies Office Peer Review Targeted Energy Outcomes A New City Energy Policy for Buildings Ken Baker - kbaker@neea.org Northwest Energy Efficiency Alliance Project Summary Timeline: Key Partners: Start date: 09/01/2012 Planned end date: 08/31/2015 Key Milestones 1. Produce outcome based marketing collateral; 04/03/14 New Buildings Institute Two to three NW cities 2. Quantify and define participating city actions; 04/03/14 3. Quantify ongoing

  15. Total Estimated Contract Cost: Performance Period Total Fee Paid

    Office of Environmental Management (EM)

    Total Fee Paid FY2008 $134,832 FY2009 $142,578 FY2010 $299,878 FY2011 $169,878 Cumulative Fee Paid $747,166 Contract Period: September 2007 - October 2012 $31,885,815 C/P/E Environmental Services, LLC DE-AM09-05SR22405/DE-AT30-07CC60011/SL14 Contractor: Contract Number: Contract Type: Cost Plus Award Fee $357,223 $597,797 $894,699 EM Contractor Fee Site: Stanford Linear Accelerator Center (SLAC) Contract Name: SLAC Environmental Remediation December 2012 $1,516,646 Fee Available $208,620 Fee

  16. U.S. Total Stocks

    Gasoline and Diesel Fuel Update (EIA)

    Stock Type: Total Stocks Strategic Petroleum Reserve Non-SPR Refinery Tank Farms and Pipelines Leases Alaskan in Transit Bulk Terminal Pipeline Natural Gas Processing Plant Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Stock Type Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Crude Oil and Petroleum Products 1,968,618 1,991,182 2,001,135 2,009,097 2,021,553 2,014,788 1956-2015 Crude Oil

  17. U.S. Total Exports

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

    International Falls, MN Noyes, MN Warroad, MN Babb, MT Havre, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate Springs, VT North Troy, VT U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Alamo, TX El Paso, TX Galvan Ranch, TX Hidalgo, TX McAllen, TX Penitas, TX LNG Imports from Algeria Cove Point, MD Everett, MA Lake Charles, LA LNG

  18. Total Imports of Residual Fuel

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S. Total 4,471 6,479 7,281 4,217 5,941 6,842 1936-2015 PAD District 1 1,854 1,956 4,571 2,206 2,952 3,174 1981-2015 Connecticut 1995-2015 Delaware 204 678 85 1995-2015 Florida 677 351 299 932 836 1995-2015 Georgia 232 138 120 295 1995-2015 Maine 50 1995-2015 Maryland 1995-2015 Massachusetts 1995-2015 New Hampshire 1995-2015 New Jersey 1,328 780 1,575 400 1,131 1,712 1995-2015 New York 7 6 1,475 998 350 322 1995-2015 North Carolina

  19. 2014 Total Electric Industry- Customers

    Gasoline and Diesel Fuel Update (EIA)

    Customers (Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 6,243,013 862,269 28,017 8 7,133,307 Connecticut 1,459,239 155,372 4,648 4 1,619,263 Maine 706,952 91,541 3,023 0 801,516 Massachusetts 2,720,128 398,717 14,896 3 3,133,744 New Hampshire 606,883 105,840 3,342 0 716,065 Rhode Island 438,879 58,346 1,884 1 499,110 Vermont 310,932 52,453 224 0 363,609 Middle Atlantic 15,806,914 2,247,455 44,397 17

  20. Total Adjusted Sales of Kerosene

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

    End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 269,010 305,508 187,656 81,102 79,674 137,928 1984-2014 East Coast (PADD 1) 198,762 237,397 142,189 63,075 61,327 106,995 1984-2014 New England (PADD 1A) 56,661 53,363 38,448 15,983 15,991 27,500 1984-2014 Connecticut 8,800 7,437

  1. Total Imports of Residual Fuel

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

    2010 2011 2012 2013 2014 2015 View History U.S. Total 133,646 119,888 93,672 82,173 63,294 68,265 1936-2015 PAD District 1 88,999 79,188 59,594 33,566 30,944 33,789 1981-2015 Connecticut 220 129 1995-2015 Delaware 748 1,704 510 1,604 2,479 1995-2015 Florida 15,713 11,654 10,589 8,331 5,055 7,013 1995-2015 Georgia 5,648 7,668 6,370 4,038 2,037 1,629 1995-2015 Maine 1,304 651 419 75 317 135 1995-2015 Maryland 3,638 1,779 1,238 433 938 539 1995-2015 Massachusetts 123 50 78 542 88 1995-2015 New

  2. V-112: Microsoft SharePoint Input Validation Flaws Permit Cross...

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

    Input Validation Flaws Permit Cross-Site Scripting and Denial of Service Attacks V-112: Microsoft SharePoint Input Validation Flaws Permit Cross-Site Scripting and Denial...

  3. V-168: Splunk Web Input Validation Flaw Permits Cross-Site Scripting...

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

    8: Splunk Web Input Validation Flaw Permits Cross-Site Scripting Attacks V-168: Splunk Web Input Validation Flaw Permits Cross-Site Scripting Attacks May 31, 2013 - 6:00am Addthis...

  4. T-602: BlackBerry Enterprise Server Input Validation Flaw in...

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

    02: BlackBerry Enterprise Server Input Validation Flaw in BlackBerry Web Desktop Manager Permits Cross-Site Scripting Attacks T-602: BlackBerry Enterprise Server Input Validation...

  5. V-124: Splunk Web Input Validation Flaw Permits Cross-Site Scripting...

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

    4: Splunk Web Input Validation Flaw Permits Cross-Site Scripting Attacks V-124: Splunk Web Input Validation Flaw Permits Cross-Site Scripting Attacks April 2, 2013 - 1:13am Addthis...

  6. U-144:Juniper Secure Access Input Validation Flaw Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    The VPN management interface does not properly filter HTML code from user-supplied input before displaying the input. A remote user can cause arbitrary scripting code to be executed by the target user's browser.

  7. Interface module for transverse energy input to dye laser modules

    DOE Patents [OSTI]

    English, R.E. Jr.; Johnson, S.A.

    1994-10-11

    An interface module for transverse energy input to dye laser modules is provided particularly for the purpose of delivering enhancing transverse energy beams in the form of illumination bar to the lasing zone of a dye laser device, in particular to a dye laser amplifier. The preferred interface module includes an optical fiber array having a plurality of optical fibers arrayed in a co-planar fashion with their distal ends receiving coherent laser energy from an enhancing laser source, and their proximal ends delivered into a relay structure. The proximal ends of the optical fibers are arrayed so as to be coplanar and to be aimed generally at a common point. The transverse energy beam array delivered from the optical fiber array is acted upon by an optical element array to produce an illumination bar which has a cross section in the form of a elongated rectangle at the position of the lasing window. The illumination bar is selected to have substantially uniform intensity throughout. 5 figs.

  8. Interface module for transverse energy input to dye laser modules

    DOE Patents [OSTI]

    English, Jr., Ronald E.; Johnson, Steve A.

    1994-01-01

    An interface module (10) for transverse energy input to dye laser modules is provided particularly for the purpose of delivering enhancing transverse energy beams (36) in the form of illumination bar (54) to the lasing zone (18) of a dye laser device, in particular to a dye laser amplifier (12). The preferred interface module (10) includes an optical fiber array (30) having a plurality of optical fibers (38) arrayed in a co-planar fashion with their distal ends (44) receiving coherent laser energy from an enhancing laser source (46), and their proximal ends (4) delivered into a relay structure (3). The proximal ends (42) of the optical fibers (38) are arrayed so as to be coplanar and to be aimed generally at a common point. The transverse energy beam array (36) delivered from the optical fiber array (30) is acted upon by an optical element array (34) to produce an illumination bar (54) which has a cross section in the form of a elongated rectangle at the position of the lasing window (18). The illumination bar (54) is selected to have substantially uniform intensity throughout.

  9. Geological input to reservoir simulation, Champion Field, offshore Brunei

    SciTech Connect (OSTI)

    Carter, R.; Salahudin, S.; Ho, T.C.

    1994-07-01

    Brunei Shell Petroleum's giant Champion field is in a mature stage of development with about 23 yr of production history to date. The field comprises a complex sequence of Miocene shallow marine and deltaic layered clastic reservoirs cut by numerous growth faults. This study was aimed at providing a quantified estimate of the effect of lateral and vertical discontinuities within the I and J reservoirs on the recovery for both depletion drive and in a waterflood, with a view to identifying the optimal method of completing the development of the oil reserves in this area. Geological input to the ECLIPSE simulator was aimed at quantifying two key parameters: (1) STOIIP connected to the well bore and (2) permeability contrast. Connected STOIIP is a function of the domain size of interconnected sand bodies, and this parameter was quantified by the use of detailed sedimentology resulting in sand-body facies maps for each reservoir sublayer. Permeability contrast was quantified by using a wireline-log based algorithm, calibrated against core data, which improved the existing accuracy of permeability estimates in this part of the field. Results of simulation runs illustrate the importance of quantifying geologic heterogeneity and provide valuable information for future field development planning.

  10. Total-derivative supersymmetry breaking

    SciTech Connect (OSTI)

    Haba, Naoyuki; Uekusa, Nobuhiro

    2010-05-15

    On an interval compactification in supersymmetric theory, boundary conditions for bulk fields must be treated carefully. If they are taken arbitrarily following the requirement that a theory is supersymmetric, the conditions could give redundant constraints on the theory. We construct a supersymmetric action integral on an interval by introducing brane interactions with which total-derivative terms under the supersymmetry transformation become zero due to a cancellation. The variational principle leads equations of motion and also boundary conditions for bulk fields, which determine boundary values of bulk fields. By estimating mass spectrum, spontaneous supersymmetry breaking in this simple setup can be realized in a new framework. This supersymmetry breaking does not induce a massless R axion, which is favorable for phenomenology. It is worth noting that fermions in hyper-multiplet, gauge bosons, and the fifth-dimensional component of gauge bosons can have zero-modes (while the other components are all massive as Kaluza-Klein modes), which fits the gauge-Higgs unification scenarios.

  11. Total Space Heating Water Heating Cook-

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

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing...

  12. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,870 1,276...

  13. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All...

  14. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,602 1,397...

  15. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings ... 2,037...

  16. U.S. Refinery Crude Oil Input Qualities

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Sulfur Content, Weighted Average (Percent) 1.39 1.36 1.36 1.37 1.44 1.44 1985-2015 API Gravity, Weighted Average (Degrees) 31.73 31.69 31.44 31.53 31.67 31.31 1985-2015 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Totals may not equal sum of components due to independent rounding. See Definitions, Sources, and Notes link above for more information on this

  17. U.S. Refinery Crude Oil Input Qualities

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

    2010 2011 2012 2013 2014 2015 View History Sulfur Content, Weighted Average (Percent) 1.39 1.40 1.42 1.44 1.45 1.40 1985-2015 API Gravity, Weighted Average (Degrees) 30.71 30.69 31.0 30.79 31.77 31.68 1985-2015 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Totals may not equal sum of components due to independent rounding. See Definitions, Sources, and Notes link above for more information on this table. Release

  18. The SCALE Verified, Archived Library of Inputs and Data - VALID

    SciTech Connect (OSTI)

    Marshall, William BJ J; Rearden, Bradley T

    2013-01-01

    The Verified, Archived Library of Inputs and Data (VALID) at ORNL contains high quality, independently reviewed models and results that improve confidence in analysis. VALID is developed and maintained according to a procedure of the SCALE quality assurance (QA) plan. This paper reviews the origins of the procedure and its intended purpose, the philosophy of the procedure, some highlights of its implementation, and the future of the procedure and associated VALID library. The original focus of the procedure was the generation of high-quality models that could be archived at ORNL and applied to many studies. The review process associated with model generation minimized the chances of errors in these archived models. Subsequently, the scope of the library and procedure was expanded to provide high quality, reviewed sensitivity data files for deployment through the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE). Sensitivity data files for approximately 400 such models are currently available. The VALID procedure and library continue fulfilling these multiple roles. The VALID procedure is based on the quality assurance principles of ISO 9001 and nuclear safety analysis. Some of these key concepts include: independent generation and review of information, generation and review by qualified individuals, use of appropriate references for design data and documentation, and retrievability of the models, results, and documentation associated with entries in the library. Some highlights of the detailed procedure are discussed to provide background on its implementation and to indicate limitations of data extracted from VALID for use by the broader community. Specifically, external users of data generated within VALID must take responsibility for ensuring that the files are used within the QA framework of their organization and that use is appropriate. The future plans for the VALID library include expansion to include additional experiments from the IHECSBE, to include experiments from areas beyond criticality safety, such as reactor physics and shielding, and to include application models. In the future, external SCALE users may also obtain qualification under the VALID procedure and be involved in expanding the library. The VALID library provides a pathway for the criticality safety community to leverage modeling and analysis expertise at ORNL.

  19. U.S. Downstream Processing of Fresh Feed Input

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Catalytic Reforming 2,854 2,929 2,837 2,690 2,748 2,812 2010-2015 Catalytic Cracking 5,140 5,177 5,000 4,572 4,831 4,892 1987-2015 Catalytic Hydrocracking 1,772 1,772 1,723 1,721 1,806 1,864 1987-2015 Delayed and Fluid Coking 2,403 2,450 2,333 2,293 2,509 2,537 1987-2015 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Totals may not equal sum of components due

  20. U.S. Downstream Processing of Fresh Feed Input

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

    2010 2011 2012 2013 2014 2015 View History Catalytic Reforming 2,632 2,571 2,606 2,601 2,592 2,731 2010-2015 Catalytic Cracking 4,873 4,952 4,901 4,811 4,885 4,834 1987-2015 Catalytic Hydrocracking 1,422 1,467 1,529 1,670 1,663 1,700 1987-2015 Delayed and Fluid Coking 1,996 2,094 2,177 2,303 2,337 2,367 1987-2015 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Totals may not equal sum of components due to

  1. Documentation of Calculation Methodology, Input data, and Infrastructure for the Home Energy Saver Web Site

    SciTech Connect (OSTI)

    Pinckard, Margaret J.; Brown, Richard E.; Mills, Evan; Lutz, James D.; Moezzi, Mithra M.; Atkinson, Celina; Bolduc, Chris; Homan, Gregory K.; Coughlin, Katie

    2005-07-13

    The Home Energy Saver (HES, http://HomeEnergySaver.lbl.gov) is an interactive web site designed to help residential consumers make decisions about energy use in their homes. This report describes the underlying methods and data for estimating energy consumption. Using engineering models, the site estimates energy consumption for six major categories (end uses); heating, cooling, water heating, major appliances, lighting, and miscellaneous equipment. The approach taken by the Home Energy Saver is to provide users with initial results based on a minimum of user input, allowing progressively greater control in specifying the characteristics of the house and energy consuming appliances. Outputs include energy consumption (by fuel and end use), energy-related emissions (carbon dioxide), energy bills (total and by fuel and end use), and energy saving recommendations. Real-world electricity tariffs are used for many locations, making the bill estimates even more accurate. Where information about the house is not available from the user, default values are used based on end-use surveys and engineering studies. An extensive body of qualitative decision-support information augments the analytical results.

  2. Input of 129I into the western Pacific Ocean resulting from the Fukushima nuclear event

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

    Tumey, S. J.; Guilderson, T. P.; Brown, T. A.; Broek, T.; Buesseler, K. O.

    2013-04-02

    We present an initial characterization of the input of 129I into the Pacific Ocean resulting from the 2011 Fukushima nuclear accident. This characterization is based primarily on 129I measurements on samples collected from a research cruise conducted in waters off the eastern coast of Japan in June 2011. The resulting measurements were compared with samples intended to reflect pre-Fukushima background that were collected during a May 2011 transect of the Pacific by a commercial container vessel. In surface waters, we observed peak 129I concentrations of ~300 μBq/m3 which represents an elevation of nearly three orders of magnitude compared to pre-Fukushimamore » backgrounds. The 129I results were coupled with 137Cs measurements from the same cruise and derived an average 129I/137Cs activity ratio of 0.442 × 10-6 for the effluent from Fukushima. Finally, we present 129I depth profiles from five stations from this cruise which form the basis for future studies of ocean transport and mixing process as well as estimations of the total budget of 129I released into the Pacific.« less

  3. DOE Seeks Additional Input on Next Generation Nuclear Plant | Department of

    Energy Savers [EERE]

    Energy Additional Input on Next Generation Nuclear Plant DOE Seeks Additional Input on Next Generation Nuclear Plant April 17, 2008 - 10:49am Addthis WASHINGTON, DC -The U.S. Department of Energy (DOE) today announced it is seeking public and industry input on how to best achieve the goals and meet the requirements for the Next Generation Nuclear Plant (NGNP) demonstration project work at DOE's Idaho National Laboratory. DOE today issued a Request for Information and Expressions of Interest

  4. Rail-to-rail differential input amplification stage with main and surrogate differential pairs

    DOE Patents [OSTI]

    Britton, Jr., Charles Lanier; Smith, Stephen Fulton

    2007-03-06

    An operational amplifier input stage provides a symmetrical rail-to-rail input common-mode voltage without turning off either pair of complementary differential input transistors. Secondary, or surrogate, transistor pairs assume the function of the complementary differential transistors. The circuit also maintains essentially constant transconductance, constant slew rate, and constant signal-path supply current as it provides rail-to-rail operation.

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

    SciTech Connect (OSTI)

    Mark D. McKay

    2011-02-01

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

  6. DOE Seeks Public Input on an Integrated, Interagency Pre-Application

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

    Process for Transmission Authorizations | Department of Energy Seeks Public Input on an Integrated, Interagency Pre-Application Process for Transmission Authorizations DOE Seeks Public Input on an Integrated, Interagency Pre-Application Process for Transmission Authorizations August 29, 2013 - 9:09am Addthis A Request for Information (RFI) seeking public input for a draft Integrated, Interagency Pre-application (IIP) Process was published in the Federal Register on August 29, 2013. The

  7. Stanford's input to the Commission to Review the Effectiveness of the

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

    National Energy Laboratories | Department of Energy Stanford's input to the Commission to Review the Effectiveness of the National Energy Laboratories Stanford's input to the Commission to Review the Effectiveness of the National Energy Laboratories Stanford's input was presented to the Commission to Review the Effectiveness of the National Energy Laboratories by Bill Madia, Vice President of SLAC National Acceleratory Laboratory and Chair, Board of Overseers, Stanford University. PDF icon

  8. A Requirement for Significant Reduction in the Maximum BTU Input Rate of

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

    Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers | Department of Energy A Requirement for Significant Reduction in the Maximum BTU Input Rate of Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers A Requirement for Significant Reduction in the Maximum BTU Input Rate of Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers Comment that a requirement to reduce the BTU input rate of existing decorative

  9. Total Space Heating Water Heating Cook-

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

    Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 634 578 46 1 Q 116.4 106.3...

  10. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    2 Alaska - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S2. Summary statistics for natural gas - Alaska, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 269 277 185 R 159 170 Production (million cubic feet) Gross Withdrawals From Gas Wells 127,417 112,268

  11. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    2 Connecticut - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. Summary statistics for natural gas - Connecticut, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil

  12. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    6 District of Columbia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells

  13. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    0 Indiana - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S16. Summary statistics for natural gas - Indiana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 620 914 819 R 921 895 Production (million cubic feet) Gross Withdrawals From Gas Wells 6,802 9,075

  14. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    2 Maryland - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S22. Summary statistics for natural gas - Maryland, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7 8 9 7 7 Production (million cubic feet) Gross Withdrawals From Gas Wells 43 34 44 32 20 From Oil

  15. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    4 Massachusetts - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0

  16. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 Minnesota - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S25. Summary statistics for natural gas - Minnesota, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil

  17. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    6 Nebraska - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S29. Summary statistics for natural gas - Nebraska, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 276 322 270 R 357 310 Production (million cubic feet) Gross Withdrawals From Gas Wells 2,092 1,854

  18. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    0 New Hampshire - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S31. Summary statistics for natural gas - New Hampshire, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0

  19. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 North Carolina - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. Summary statistics for natural gas - North Carolina, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0

  20. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    50 North Dakota - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S36. Summary statistics for natural gas - North Dakota, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 188 239 211 200 200 Production (million cubic feet) Gross Withdrawals From Gas Wells

  1. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    2 South Carolina - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S42. Summary statistics for natural gas - South Carolina, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0

  2. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    6 Washington - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S49. Summary statistics for natural gas - Washington, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil

  3. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    80 Wisconsin - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S51. Summary statistics for natural gas - Wisconsin, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil

  4. Total System Performance Assessment Peer Review Panel

    Office of Energy Efficiency and Renewable Energy (EERE)

    Total System Performance Assessment (TSPA) Peer Review Panel for predicting the performance of a repository at Yucca Mountain.

  5. T-670: Skype Input Validation Flaw in 'mobile phone' Profile Entry Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    The software does not properly filter HTML code from user-supplied input in the The "mobile phone" profile entry before displaying the input.

  6. SRTC input to DOE-HQ R and D database for FY99

    SciTech Connect (OSTI)

    Chandler, L.R. Jr.

    2000-01-05

    This is a database of the Savannah River Site input to the DOE Research and Development database. The report contains approximately 50 project abstracts.

  7. [Composite analysis E-area vaults and saltstone disposal facilities]. PORFLOW and FACT input files

    SciTech Connect (OSTI)

    Cook, J.R.

    1997-09-01

    This diskette contains the PORFLOW and FACT input files described in Appendix B of the accompanying report `Composite Analysis E-Area Vaults and Saltstone Disposal Facilities`.

  8. ARM - Measurement - Shortwave broadband total downwelling irradiance

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

    total downwelling irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Shortwave broadband total downwelling irradiance The total diffuse and direct radiant energy that comes from some continuous range of directions, at wavelengths between 0.4 and 4 {mu}m, that is being emitted downwards. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the

  9. Design Storm for Total Retention.pdf

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

    Storm Events for Select Western U.S. Cities (adapted from Energy Independence and Security Act Technical Guidance, USEPA, 2009) City 95th Percentile Event Rainfall Total...

  10. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    0 Alabama - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S1. Summary statistics for natural gas - Alabama, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,026 7,063 6,327 R 6,165 6,118 Production (million cubic feet) Gross Withdrawals From Gas Wells

  11. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    6 Arkansas - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S4. Summary statistics for natural gas - Arkansas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,397 8,388 8,538 R 9,843 10,150 Production (million cubic feet) Gross Withdrawals From Gas Wells

  12. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 California - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S5. Summary statistics for natural gas - California, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 1,580 1,308 1,423 R 1,335 1,118 Production (million cubic feet) Gross Withdrawals From Gas

  13. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    0 Colorado - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 28,813 30,101 32,000 R 32,468 38,346 Production (million cubic feet) Gross Withdrawals From Gas

  14. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 Florida - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S10. Summary statistics for natural gas - Florida, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 17,182 16,459 19,742

  15. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    0 Georgia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. Summary statistics for natural gas - Georgia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells

  16. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 Illinois - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S15. Summary statistics for natural gas - Illinois, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 50 40 40 R 34 36 Production (million cubic feet) Gross Withdrawals From Gas Wells E 1,697 2,114

  17. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    2 Iowa - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S17. Summary statistics for natural gas - Iowa, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0

  18. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    4 Kansas - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S18. Summary statistics for natural gas - Kansas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 22,145 25,758 24,697 R 23,792 24,354 Production (million cubic feet) Gross Withdrawals From Gas Wells

  19. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    6 Kentucky - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S19. Summary statistics for natural gas - Kentucky, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 17,670 14,632 17,936 R 19,494 19,256 Production (million cubic feet) Gross Withdrawals From Gas

  20. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 Louisiana - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S20. Summary statistics for natural gas - Louisiana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 19,137 21,235 19,792 R 19,528 19,251 Production (million cubic feet) Gross Withdrawals From Gas

  1. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    0 Maine - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S21. Summary statistics for natural gas - Maine, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0

  2. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    6 Michigan - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S24. Summary statistics for natural gas - Michigan, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 10,100 11,100 10,900 R 10,550 10,500 Production (million cubic feet) Gross Withdrawals From Gas

  3. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    0 Mississippi - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S26. Summary statistics for natural gas - Mississippi, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 1,979 5,732 1,669 R 1,967 1,645 Production (million cubic feet) Gross Withdrawals From Gas

  4. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    2 Missouri - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S27. Summary statistics for natural gas - Missouri, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 53 100 R 26 28 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 R 8 8 From

  5. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    4 Montana - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S28. Summary statistics for natural gas - Montana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 6,059 6,477 6,240 5,754 5,754 Production (million cubic feet) Gross Withdrawals From Gas Wells

  6. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 Nevada - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S30. Summary statistics for natural gas - Nevada, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 R 4 4 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 3 From Oil Wells

  7. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    2 New Jersey - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. Summary statistics for natural gas - New Jersey, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil

  8. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    4 New Mexico - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S33. Summary statistics for natural gas - New Mexico, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,748 32,302 28,206 R 27,073 27,957 Production (million cubic feet) Gross Withdrawals From

  9. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    6 New York - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S34. Summary statistics for natural gas - New York, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 6,736 6,157 7,176 R 6,902 7,119 Production (million cubic feet) Gross Withdrawals From Gas Wells

  10. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    2 Ohio - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S37. Summary statistics for natural gas - Ohio, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 34,931 46,717 35,104 R 32,664 32,967 Production (million cubic feet) Gross Withdrawals From Gas Wells

  11. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    4 Oklahoma - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S38. Summary statistics for natural gas - Oklahoma, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,000 41,238 40,000 39,776 40,070 Production (million cubic feet) Gross Withdrawals From Gas

  12. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    6 Oregon - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 26 24 27 R 26 28 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,407 1,344 770 770

  13. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 Pennsylvania - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S40. Summary statistics for natural gas - Pennsylvania, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,500 54,347 55,136 R 53,762 70,400 Production (million cubic feet) Gross Withdrawals

  14. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    0 Rhode Island - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S41. Summary statistics for natural gas - Rhode Island, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From

  15. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    6 Tennessee - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S44. Summary statistics for natural gas - Tennessee, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 230 210 212 R 1,089 1,024 Production (million cubic feet) Gross Withdrawals From Gas Wells 5,144

  16. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 Texas - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S45. Summary statistics for natural gas - Texas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 95,014 100,966 96,617 97,618 98,279 Production (million cubic feet) Gross Withdrawals From Gas Wells

  17. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    0 Utah - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S46. Summary statistics for natural gas - Utah, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 6,075 6,469 6,900 R 7,030 7,275 Production (million cubic feet) Gross Withdrawals From Gas Wells 328,135

  18. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    2 Vermont - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S47. Summary statistics for natural gas - Vermont, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells

  19. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    4 Virginia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S48. Summary statistics for natural gas - Virginia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,470 7,903 7,843 R 7,956 7,961 Production (million cubic feet) Gross Withdrawals From Gas Wells

  20. Million Cu. Feet Percent of National Total

    Gasoline and Diesel Fuel Update (EIA)

    8 West Virginia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S50. Summary statistics for natural gas - West Virginia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 52,498 56,813 50,700 R 54,920 60,000 Production (million cubic feet) Gross Withdrawals

  1. 2014 Total Electric Industry- Sales (Megawatthours

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

    and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",47211525,53107038,19107433,557463,119983459 "Connecticut",12777579,12893531,3...

  2. ,"Total Natural Gas Underground Storage Capacity "

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

    ...orcapaepg0sacmmcfm.htm" ,"Source:","Energy Information Administration" ,"For Help, ... 1: Total Natural Gas Underground Storage Capacity " "Sourcekey","N5290US2","NGMEP...

  3. Role of the nonperturbative input in QCD resummed Drell-Yan Q{sub T}

    Office of Scientific and Technical Information (OSTI)

    distributions (Journal Article) | SciTech Connect SciTech Connect Search Results Journal Article: Role of the nonperturbative input in QCD resummed Drell-Yan Q{sub T} distributions Citation Details In-Document Search Title: Role of the nonperturbative input in QCD resummed Drell-Yan Q{sub T} distributions We analyze the role of the nonperturbative input in the Collins-Soper-Sterman (CSS) b-space QCD resummation formalism for Drell-Yan transverse momentum (Q{sub T}) distributions, and

  4. T-546: Microsoft MHTML Input Validation Hole May Permit Cross-Site

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

    Scripting Attacks Arbitrary Code | Department of Energy 6: Microsoft MHTML Input Validation Hole May Permit Cross-Site Scripting Attacks Arbitrary Code T-546: Microsoft MHTML Input Validation Hole May Permit Cross-Site Scripting Attacks Arbitrary Code January 31, 2011 - 7:00am Addthis PROBLEM: Microsoft MHTML Input Validation Hole May Permit Cross-Site Scripting Attacks Arbitrary Code. PLATFORM: Microsoft 2003 SP2, Vista SP2, 2008 SP2, XP SP3, 7; and prior service packs ABSTRACT: A

  5. T-722: IBM WebSphere Commerce Edition Input Validation Holes Permit

    Energy Savers [EERE]

    Cross-Site Scripting Attacks | Department of Energy 2: IBM WebSphere Commerce Edition Input Validation Holes Permit Cross-Site Scripting Attacks T-722: IBM WebSphere Commerce Edition Input Validation Holes Permit Cross-Site Scripting Attacks September 21, 2011 - 8:15am Addthis PROBLEM: IBM WebSphere Commerce Edition Input Validation Holes Permit Cross-Site Scripting Attacks. PLATFORM: WebSphere Commerce Edition V7.0 ABSTRACT: A remote user can access the target user's cookies (including

  6. Summary of Input to DOE Request for Information DE-FOA-0000225 | Department

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

    of Energy FOA-0000225 Summary of Input to DOE Request for Information DE-FOA-0000225 Presentation on Sumary of Input to DOE Request for Information DE-FOA-0000225 - U.S. DOE Fuel Cells Technology Program PDF icon fuelcell_pre-solicitation_wkshop_mar10_kleen.pdf More Documents & Publications Long Term Innovative Technologies Summary of Input to DOE Request for Information DE-PS36-08GO38002 (Presentation) Balance of Plant (BoP) Components Validation for Fuel Cells

  7. 2009 Total Energy Production by State | Department of Energy

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

    Total Energy Production by State 2009 Total Energy Production by State 2009 Total Energy Production by State...

  8. Cell Total Activity Final Estimate.xls

    Office of Legacy Management (LM)

    WSSRAP Cell Total Activity Final Estimate (calculated September 2002, Fleming) (Waste streams & occupied cell volumes from spreadsheet titled "cell waste volumes-8.23.02 with macros.xls") Waste Stream a Volume (cy) Mass (g) 2 Radiological Profile 3 Nuclide Activity (Ci) 4 Total % of Total U-238 U-234 U-235 Th-228 Th-230 Th-232 Ra-226 Ra-228 Rn-222 5 Activity if > 1% Raffinate Pits Work Zone (Ci) Raffinate processed through CSS Plant 1 159990 1.49E+11 Raffinate 6.12E+01 6.12E+01

  9. DOE Seeks Further Public Input on How Best To Streamline Existing...

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

    DOE Seeks Further Public Input on How Best To Streamline Existing Regulations December 7, 2011 - 12:34pm Addthis The Department of Energy (DOE) has announced a further step to...

  10. U-255: Apache Wicket Input Validation Flaw Permits Cross-Site...

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

    in ajax links before displaying the input. A remote user can create a specially crafted URL that, when loaded by a target user, will cause arbitrary scripting code to be executed...

  11. V-229: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site...

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

    V-229: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site Scripting Attacks August ... Addthis Related Articles V-211: IBM iNotes Multiple Vulnerabilities U-198: IBM Lotus ...

  12. Lessons Learned in Optimizing Workers' and Worker Representatives' Input to Work Planning and Control

    Broader source: Energy.gov [DOE]

    Slide Presentation by Tom McQuiston, Dr. P.H., United Steelworkers - Tony Mazzocchi Center for Health, Safety and Environmental Education. Lessons Learned in Optimizing Workers’ and Worker Representatives’ Input in Work Planning and Control.

  13. Tribes Provide Input on 10-Year Plan for Renewable Energy in the Arctic Region

    Broader source: Energy.gov [DOE]

    The DOE Office of Indian Energy hosted a second round of tribal consultations and outreach meetings throughout Alaska in February and March to gather input on the National Strategy for the Arctic Region (NSAR).

  14. BETO Seeks Stakeholder Input on the Use of Advanced Biofuel Blends...

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

    the Use of Advanced Biofuel Blends in Small Engines BETO Seeks Stakeholder Input on the Use of Advanced Biofuel Blends in Small Engines June 22, 2015 - 4:39pm Addthis The U.S. ...

  15. Approaches used for Clearance of Lands from Nuclear Facilities among Several Countries: Evaluation for Regulatory Input

    Broader source: Energy.gov [DOE]

    The study entitled, “Approaches used for Clearance of Lands from Nuclear Facilities among Several Countries: Evaluation for Regulatory Input,” focuses on the issue of showing compliance with given...

  16. HEAT INPUT AND POST WELD HEAT TREATMENT EFFECTS ON REDUCED-ACTIVATION

    Office of Scientific and Technical Information (OSTI)

    FERRITIC/MARTENSITIC STEEL FRICTION STIR WELDS (Conference) | SciTech Connect HEAT INPUT AND POST WELD HEAT TREATMENT EFFECTS ON REDUCED-ACTIVATION FERRITIC/MARTENSITIC STEEL FRICTION STIR WELDS Citation Details In-Document Search Title: HEAT INPUT AND POST WELD HEAT TREATMENT EFFECTS ON REDUCED-ACTIVATION FERRITIC/MARTENSITIC STEEL FRICTION STIR WELDS Reduced-activation ferritic/martensitic (RAFM) steels are an important class of structural materials for fusion reactor internals developed

  17. First QER Report Incorporates Tribal Input on U.S. Transmission System

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

    Updates | Department of Energy First QER Report Incorporates Tribal Input on U.S. Transmission System Updates First QER Report Incorporates Tribal Input on U.S. Transmission System Updates April 23, 2015 - 1:16pm Addthis Affordable, clean, and secure energy and energy services are essential for improving U.S. economic productivity, enhancing quality of life, protecting the environment, and ensuring national security. To help the federal government meet these energy goals, President Obama

  18. USDA, Departments of Energy and Navy Seek Input from Industry to Advance

    Energy Savers [EERE]

    Biofuels for Military and Commercial Transportation | Department of Energy USDA, Departments of Energy and Navy Seek Input from Industry to Advance Biofuels for Military and Commercial Transportation USDA, Departments of Energy and Navy Seek Input from Industry to Advance Biofuels for Military and Commercial Transportation August 30, 2011 - 12:23pm Addthis WASHINGTON, Aug. 30, 2011 -Secretary of Agriculture Tom Vilsack, Secretary of Energy Steven Chu, and Secretary of the Navy Ray Mabus

  19. Microsoft Word - SmartGrid - NRC Input to DOE Requestrvjcomments.docx

    Office of Environmental Management (EM)

    Nuclear Regulatory Commission Input to DOE Request for Information/RFI (Federal Register / Vol. 75, No. 180 / Friday, September 17, 2010/Pages 57006-57011 / Notices) / Smart Grid Implementation Input - NRC Contact: Kenn A. Miller, Office of Nuclear Reactor Regulation, 301-415-3152 Comments relevant to the following two sections of the RFI: "Long Term Issues: Managing a Grid with High Penetration of New Technologies" and "Reliability and Cyber-Security," Page 57010. Nuclear

  20. Microsoft PowerPoint - OTT RFI Summary of Input_Public_Oct 2015

    Office of Environmental Management (EM)

    Input Request for Information DE-FOA-0001346 September 2015 Prepared for the Office of Technology Transitions and Technology Transfer Policy Board 1 Note: the views expressed in this document solely reflect the input received from the RFI respondents and do not necessarily represent DOE's perspective. 13 10 8 7 6 5 4 2 24% 18% 15% 13% 11% 9% 7% 4% 0 5 10 15 Industry National Labs Funding Contractors Academic Tech commercialization consultants Independent Research Organizations Other Number of

  1. TotalView Parallel Debugger at NERSC

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

    The performance of the GUI can be greatly improved if used in conjunction with free NX software. The TotalView documentation web page is a good resource for learning more...

  2. Million Cu. Feet Percent of National Total

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

    as known volumes of natural gas that were the result of leaks, damage, accidents, migration, andor blow down. Notes: Totals may not add due to independent rounding. Prices are...

  3. EQUUS Total Return Inc | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Name: EQUUS Total Return Inc Place: Houston, Texas Product: A business development company and VC investor that trades as a closed-end fund. EQUUS is...

  4. "2014 Total Electric Industry- Revenue (Thousands Dollars)"

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

    and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",8414175.4,7806276.7,2262752.4,57837.4,18541041.8 "Connecticut",2523348.7,2004...

  5. Total Natural Gas Underground Storage Capacity

    Gasoline and Diesel Fuel Update (EIA)

    Salt Caverns Storage Capacity Aquifers Storage Capacity Depleted Fields Storage Capacity Total Working Gas Capacity Working Gas Capacity of Salt Caverns Working Gas Capacity of Aquifers Working Gas Capacity of Depleted Fields Total Number of Existing Fields Number of Existing Salt Caverns Number of Existing Aquifers Number of Depleted Fields Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data

  6. Total Natural Gas Underground Storage Capacity

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

    Salt Caverns Storage Capacity Aquifers Storage Capacity Depleted Fields Storage Capacity Total Working Gas Capacity Working Gas Capacity of Salt Caverns Working Gas Capacity of Aquifers Working Gas Capacity of Depleted Fields Total Number of Existing Fields Number of Existing Salt Caverns Number of Existing Aquifers Number of Depleted Fields Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data

  7. ARM - Measurement - Net broadband total irradiance

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

    govMeasurementsNet broadband total irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Net broadband total irradiance The difference between upwelling and downwelling, covering longwave and shortwave radiation. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each

  8. T-701: Citrix Access Gateway Enterprise Edition Input Validation Flaw in Logon Portal Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Citrix Access Gateway Enterprise Edition Input Validation Flaw in Logon Portal Permits Cross-Site Scripting Attacks.

  9. ARM - Measurement - Shortwave spectral total downwelling irradiance

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

    total downwelling irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Shortwave spectral total downwelling irradiance The rate at which radiant energy, at specrally-resolved wavelengths between 0.4 and 4 {mu}m, is being emitted upwards and downwards into a radiation field and transferred across a surface area (real or imaginary) in a hemisphere of directions. Categories Radiometric Instruments

  10. A9_ISO

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

  11. A = 9 General Tables

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

    The General Table for 9Li is subdivided into the following categories: Shell Model Cluster Model Theoretical Ground State Properties Special States Other Model Calculations...

  12. 2014 Total Electric Industry- Revenue (Thousands Dollars)

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

    4A-D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 8,414,175 7,806,277 2,262,752 57,837 18,541,042 Connecticut 2,523,349...

  13. Input for solar annual merit review. (Conference) | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    Input for solar annual merit review. Citation Details In-Document Search Title: Input for solar annual merit review. Abstract not provided. Authors: Siegel, Nathan Phillip Publication Date: 2008-05-01 OSTI Identifier: 1145749 Report Number(s): SAND2008-3333C 518639 DOE Contract Number: DE-AC04-94AL85000 Resource Type: Conference Resource Relation: Conference: Solar annual merit review held April 21-24, 2008 in austin, TX.; Related Information: Proposed for presentation at the solar annual merit

  14. Probabilistic Density Function Method for Stochastic ODEs of Power Systems with Uncertain Power Input

    SciTech Connect (OSTI)

    Wang, Peng; Barajas-Solano, David A.; Constantinescu, Emil; Abhyankar, S.; Ghosh, Donetta L.; Smith, Barry; Huang, Zhenyu; Tartakovsky, Alexandre M.

    2015-09-22

    Wind and solar power generators are commonly described by a system of stochastic ordinary differential equations (SODEs) where random input parameters represent uncertainty in wind and solar energy. The existing methods for SODEs are mostly limited to delta-correlated random parameters (white noise). Here we use the Probability Density Function (PDF) method for deriving a closed-form deterministic partial differential equation (PDE) for the joint probability density function of the SODEs describing a power generator with time-correlated power input. The resulting PDE is solved numerically. A good agreement with Monte Carlo Simulations shows accuracy of the PDF method.

  15. ,"Sulfur Content, Weighted Average Refinery Crude Oil Input Qualities"

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

    Sulfur Content, Weighted Average Refinery Crude Oil Input Qualities" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Sulfur Content, Weighted Average Refinery Crude Oil Input Qualities",16,"Monthly","12/2015","1/15/1985" ,"Release Date:","2/29/2016" ,"Next Release

  16. CASL-U-2015-0043-000 MPACT VERA Common Input User's Manual Benjamin Collins

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

    43-000 MPACT VERA Common Input User's Manual Benjamin Collins Oak Ridge National Laboratory Brendan Kochunas University of Michigan February 20, 2015 CASL-U-2015-0043-000 VERA Common Input User's Manual Version 2.0.0 February 20, 2015 CASL-U-2015-0043-000 2 Contributors (in alphabetical order) * Dr. Benjamin Collins (ORNL) * Prof. Thomas J. Downar (UM) * Dr. Jess Gehin (ORNL) * Andrew Godfrey (ORNL) * Aaron Graham (UM) * Daniel Jabaay (UM) * Blake Kelley (UM) * Dr. Kang Seog Kim (ORNL) * Dr.

  17. ,"Catalytic Reforming Downstream Processing of Fresh Feed Input"

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

    Catalytic Reforming Downstream Processing of Fresh Feed Input" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Catalytic Reforming Downstream Processing of Fresh Feed Input",16,"Monthly","12/2015","1/15/2010" ,"Release Date:","2/29/2016" ,"Next Release

  18. DEPARTMENT OF ENERGY SOLICITS PUBLIC INPUT TO INFORM DEVELOPMENT OF A

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

    PREFERRED ALTERNATIVE FOR DISPOSAL OF GREATER-THAN-CLASS C WASTE | Department of Energy DEPARTMENT OF ENERGY SOLICITS PUBLIC INPUT TO INFORM DEVELOPMENT OF A PREFERRED ALTERNATIVE FOR DISPOSAL OF GREATER-THAN-CLASS C WASTE DEPARTMENT OF ENERGY SOLICITS PUBLIC INPUT TO INFORM DEVELOPMENT OF A PREFERRED ALTERNATIVE FOR DISPOSAL OF GREATER-THAN-CLASS C WASTE March 1, 2011 - 12:00pm Addthis During the months of April and May, 2011 the Department of Energy's Office of Environmental Management

  19. BETO Seeks Stakeholder Input on the Co-Optimization of Fuels and Engines |

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

    Department of Energy BETO Seeks Stakeholder Input on the Co-Optimization of Fuels and Engines BETO Seeks Stakeholder Input on the Co-Optimization of Fuels and Engines December 17, 2015 - 9:48am Addthis The U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy's (EERE) Bioenergy Technologies Office (BETO) and Vehicle Technologies Office (VTO) have released a request for information (RFI) titled "Co-Optimization of Fuels and Engines" (Optima). BETO and VTO are

  20. Graph of Total Number of Oligos Within Windows of a Sequence

    Energy Science and Technology Software Center (OSTI)

    1995-11-28

    SEQWIN is user-friendly software which graphs the total number of oligos present in a sequence. The sequence is scanned one window at a time; windows can be overlapping. Each bar on the graph represents a single window down the sequence. The user specifies the sequence of interest and a list of oligos as program input. If the sequence is known, locations of specific structure or sequences can be specified and compared with the bars onmorea graph. The window size, amount of overlap of the windows, number of windows to be considered, and the starting position of the first window used can be adjusted at the user's discretion.less

  1. Frustrated total internal reflection acoustic field sensor

    DOE Patents [OSTI]

    Kallman, Jeffrey S. (Pleasanton, CA)

    2000-01-01

    A frustrated total internal reflection acoustic field sensor which allows the acquisition of the acoustic field over an entire plane, all at once. The sensor finds use in acoustic holography and acoustic diffraction tomography. For example, the sensor may be produced by a transparent plate with transparent support members tall enough to support one or more flexible membranes at an appropriate height for frustrated total internal reflection to occur. An acoustic wave causes the membrane to deflect away from its quiescent position and thus changes the amount of light that tunnels through the gap formed by the support members and into the membrane, and so changes the amount of light reflected by the membrane. The sensor(s) is illuminated by a uniform tight field, and the reflection from the sensor yields acoustic wave amplitude and phase information which can be picked up electronically or otherwise.

  2. Fractionated total body irradiation for metastatic neuroblastoma

    SciTech Connect (OSTI)

    Kun, L.E.; Casper, J.T.; Kline, R.W.; Piaskowski, V.D.

    1981-11-01

    Twelve patients over one year old with neuroblastoma (NBL) metastatic to bone and bone marrow entered a study of adjuvant low-dose, fractionated total body irradiation (TBI). Six children who achieved a ''complete clinical response'' following chemotherapy (cyclophosphamide and adriamycin) and surgical resection of the abdominal primary received TBI (10 rad/fraction to totals of 100-120 rad/10-12 fx/12-25 days). Two children received concurrent local irradiation for residual abdominal tumor. The intervals from cessation of chemotherapy to documented progression ranged from 2-16 months, not substatially different from patients receiving similar chemotherapy and surgery without TBI. Three additional children with progressive NBL received similar TBI (80-120 rad/8-12 fx) without objective response.

  3. Total Natural Gas Underground Storage Capacity

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

    Total Working Gas Capacity Total Number of Existing Fields Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S. 9,228,173 9,219,173 9,224,005 9,225,079 9,225,911 9,228,240 1989-2015 Alaska 83,592 83,592 83,592 83,592 83,592 83,592 2013-2015 Lower 48 States 9,144,581 9,135,581 9,140,412 9,141,486 9,142,319 9,144,648

  4. Contractor: Contract Number: Contract Type: Total Estimated

    Office of Environmental Management (EM)

    Contract Number: Contract Type: Total Estimated Contract Cost: Performance Period Total Fee Paid FY2004 $294,316 FY2005 $820,074 FY2006 $799,449 FY2007 $877,898 FY2008 $866,608 FY2009 $886,404 FY2010 $800,314 FY2011 $871,280 FY2012 $824,517 FY2013 Cumulative Fee Paid $7,040,860 $820,074 $799,449 $877,898 $916,130 $886,608 Computer Sciences Corporation DE-AC06-04RL14383 $895,358 $899,230 $907,583 Cost Plus Award Fee $134,100,336 $8,221,404 Fee Available Contract Period: Fee Information Minimum

  5. Total Crude Oil and Petroleum Products Exports

    Gasoline and Diesel Fuel Update (EIA)

    Exports Product: Total Crude Oil and Petroleum Products Crude Oil Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Isobutylene Other Liquids Hydrogen/Oxygenates/Renewables/Other Hydrocarbons Oxygenates (excl. Fuel Ethanol) Methyl Tertiary Butyl Ether (MTBE) Other Oxygenates Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Biomass-Based Diesel Unfinished Oils Naphthas and Lighter

  6. ARM - Measurement - Shortwave broadband total net irradiance

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

    net irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Shortwave broadband total net irradiance The difference between upwelling and downwelling broadband shortwave radiation. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available

  7. ARM - Measurement - Shortwave narrowband total downwelling irradiance

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

    downwelling irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Shortwave narrowband total downwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 {mu}m, passes through a horizontal unit area in a downward direction. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following

  8. ARM - Measurement - Shortwave narrowband total upwelling irradiance

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

    upwelling irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Shortwave narrowband total upwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 {mu}m, passes through a horizontal unit area in an upward direction. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following instruments.

  9. Notices Total Estimated Number of Annual

    Energy Savers [EERE]

    372 Federal Register / Vol. 78, No. 181 / Wednesday, September 18, 2013 / Notices Total Estimated Number of Annual Burden Hours: 10,128. Abstract: Enrollment in the Federal Student Aid (FSA) Student Aid Internet Gateway (SAIG) allows eligible entities to securely exchange Title IV, Higher Education Act (HEA) assistance programs data electronically with the Department of Education processors. Organizations establish Destination Point Administrators (DPAs) to transmit, receive, view and update

  10. U-195: PHPlist Input Validation Flaws Permit Cross-Site Scripting and SQL Injection Attacks

    Broader source: Energy.gov [DOE]

    The 'public_html/lists/admin' pages do not properly validate user-supplied input in the 'sortby' parameter [CVE-2012-2740]. A remote authenticated administrative user can supply a specially crafted parameter value to execute SQL commands on the underlying database.

  11. BETO Seeks Stakeholder Input on the Use of Advanced Biofuel Blends in Small Engines

    Office of Energy Efficiency and Renewable Energy (EERE)

    The U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy’s Bioenergy Technologies Office has released a Request for Information (RFI) seeking stakeholder input on the following topics related to the use of advanced biofuel blends in small engines

  12. Summary, Attendee Input, and Day 1 Wrap Up | Department of Energy

    Energy Savers [EERE]

    Day 1 Wrap Up Summary, Attendee Input, and Day 1 Wrap Up Addthis Description Summary and wrap up of day 1 presentations and preview of day 2 by DOE Integrated Safety Management Co-champions Patricia R. Worthington, HSS Director, Office of Health and Safety; and and Ray J. Corey, Assistant Manager for Safety and Environment, DOE Richland Operations Office

  13. Summary, Attendee Input, and Final Day 2 Wrap up | Department of Energy

    Energy Savers [EERE]

    Final Day 2 Wrap up Summary, Attendee Input, and Final Day 2 Wrap up Addthis Description Summary and wrap up by DOE Integrated Safety Management Co-champions Patricia R. Worthington, HSS Director, Office of Health and Safety; and and Ray J. Corey, Assistant Manager for Safety and Environment, DOE Richland Operations Office of day 2 presentations and discussions

  14. Table 6a. Total Electricity Consumption per Effective Occupied...

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

    a. Total Electricity Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Electricity (thousand) Total Electricity Consumption...

  15. Using Economic Input/Output Tables to Predict a Countrys Nuclear Status

    SciTech Connect (OSTI)

    Weimar, Mark R.; Daly, Don S.; Wood, Thomas W.

    2010-07-15

    Both nuclear power and nuclear weapons programs should have (related) economic signatures which are detectible at some scale. We evaluated this premise in a series of studies using national economic input/output (IO) data. Statistical discrimination models using economic IO tables predict with a high probability whether a country with an unknown predilection for nuclear weapons proliferation is in fact engaged in nuclear power development or nuclear weapons proliferation. We analyzed 93 IO tables, spanning the years 1993 to 2005 for 37 countries that are either members or associates of the Organization for Economic Cooperation and Development (OECD). The 2009 OECD input/output tables featured 48 industrial sectors based on International Standard Industrial Classification (ISIC) Revision 3, and described the respective economies in current country-of-origin valued currency. We converted and transformed these reported values to US 2005 dollars using appropriate exchange rates and implicit price deflators, and addressed discrepancies in reported industrial sectors across tables. We then classified countries with Random Forest using either the adjusted or industry-normalized values. Random Forest, a classification tree technique, separates and categorizes countries using a very small, select subset of the 2304 individual cells in the IO table. A nations efforts in nuclear power, be it for electricity or nuclear weapons, are an enterprise with a large economic footprint -- an effort so large that it should discernibly perturb coarse country-level economics data such as that found in yearly input-output economic tables. The neoclassical economic input-output model describes a countrys or regions economy in terms of the requirements of industries to produce the current level of economic output. An IO table row shows the distribution of an industrys output to the industrial sectors while a table column shows the input required of each industrial sector by a given industry.

  16. "Table A10. Total Consumption of LPG, Distillate Fuel Oil, and Residual Fuel"

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

    0. Total Consumption of LPG, Distillate Fuel Oil, and Residual Fuel" " Oil for Selected Purposes by Census Region and Economic Characteristics of the" " Establishment, 1991" " (Estimates in Barrels per Day)" ,,,," Inputs for Heat",,," Primary Consumption" " "," Primary Consumption for all Purposes",,," Power, and Generation of Electricity",,," for Nonfuel Purposes",,,"RSE" ,"

  17. "Table A2. Total Consumption of LPG, Distillate Fuel Oil, and Residual Fuel"

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

    . Total Consumption of LPG, Distillate Fuel Oil, and Residual Fuel" " Oil for Selected Purposes by Census Region, Industry Group, and Selected" " Industries, 1991" " (Estimates in Barrels per Day) " ,,,,," Input for Heat,",,," Primary" " ",," Consumption for All Purposes",,,"Power, and Generation of Electricity",,," Consumption for Nonfuel Purposes ",,,"RSE" "SIC",,"

  18. Total Adjusted Sales of Distillate Fuel Oil

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

    End Use: Total Residential Commercial Industrial Oil Company Farm Electric Power Railroad Vessel Bunkering On-Highway Military Off-Highway All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 55,664,448 58,258,830 59,769,444 57,512,994 58,675,008 61,890,990 1984-2014 East Coast (PADD 1) 18,219,180 17,965,794 17,864,868 16,754,388

  19. Total Adjusted Sales of Residual Fuel Oil

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

    End Use: Total Commercial Industrial Oil Company Electric Power Vessel Bunkering Military All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 7,835,436 8,203,062 7,068,306 5,668,530 4,883,466 3,942,750 1984-2014 East Coast (PADD 1) 3,339,162 3,359,265 2,667,576 1,906,700 1,699,418 1,393,068 1984-2014 New England (PADD 1A) 318,184

  20. Total Sales of Residual Fuel Oil

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

    End Use: Total Commercial Industrial Oil Company Electric Power Vessel Bunkering Military All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 6,908,028 7,233,765 6,358,120 6,022,115 5,283,350 4,919,255 1984-2014 East Coast (PADD 1) 2,972,575 2,994,245 2,397,932 2,019,294 1,839,237 1,724,167 1984-2014 New England (PADD 1A) 281,895

  1. Total Sales of Distillate Fuel Oil

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

    End Use: Total Residential Commercial Industrial Oil Company Farm Electric Power Railroad Vessel Bunkering On-Highway Military Off-Highway All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 54,100,092 56,093,645 57,082,558 57,020,840 58,107,155 60,827,930 1984-2014 East Coast (PADD 1) 17,821,973 18,136,965 17,757,005 17,382,566

  2. ARM - Measurement - Shortwave broadband total upwelling irradiance

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

    upwelling irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Shortwave broadband total upwelling irradiance The rate at which radiant energy, at a wavelength between 0.4 and 4 {mu}m, is being emitted upwards into a radiation field and transferred across a surface area (real or imaginary) in a hemisphere of directions. Categories Radiometric Instruments The above measurement is considered

  3. Input of 129I into the western Pacific Ocean resulting from the Fukushima nuclear event

    SciTech Connect (OSTI)

    Tumey, S. J.; Guilderson, T. P.; Brown, T. A.; Broek, T.; Buesseler, K. O.

    2013-04-02

    We present an initial characterization of the input of 129I into the Pacific Ocean resulting from the 2011 Fukushima nuclear accident. This characterization is based primarily on 129I measurements on samples collected from a research cruise conducted in waters off the eastern coast of Japan in June 2011. The resulting measurements were compared with samples intended to reflect pre-Fukushima background that were collected during a May 2011 transect of the Pacific by a commercial container vessel. In surface waters, we observed peak 129I concentrations of ~300 μBq/m3 which represents an elevation of nearly three orders of magnitude compared to pre-Fukushima backgrounds. The 129I results were coupled with 137Cs measurements from the same cruise and derived an average 129I/137Cs activity ratio of 0.442 × 10-6 for the effluent from Fukushima. Finally, we present 129I depth profiles from five stations from this cruise which form the basis for future studies of ocean transport and mixing process as well as estimations of the total budget of 129I released into the Pacific.

  4. A non-linear dimension reduction methodology for generating data-driven stochastic input models

    SciTech Connect (OSTI)

    Ganapathysubramanian, Baskar; Zabaras, Nicholas

    2008-06-20

    Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R{sup n}. An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R{sup d}(d<input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low-dimensional input stochastic models to represent thermal diffusivity in two-phase microstructures. This model is used in analyzing the effect of topological variations of two-phase microstructures on the evolution of temperature in heat conduction processes.

  5. Total Ore Processing Integration and Management

    SciTech Connect (OSTI)

    Leslie Gertsch; Richard Gertsch

    2006-01-30

    This report outlines the technical progress achieved for project DE-FC26-03NT41785 (Total Ore Processing Integration and Management) during the period 01 July through 30 September of 2005. This ninth quarterly report discusses the activities of the project team during the period 1 July through 30 September 2005. Richard Gertsch's unexpected death due to natural causes while in Minnesota to work on this project has temporarily slowed progress. Statistical analysis of the Minntac Mine data set for late 2004 is continuing. Preliminary results raised several questions that could be amenable to further study. Detailed geotechnical characterization is being applied to improve the predictability of mill and agglomerator performance at Hibtac Mine.

  6. 2014 Utility Bundled Retail Sales- Total

    Gasoline and Diesel Fuel Update (EIA)

    Total (Data from forms EIA-861- schedules 4A & 4D and EIA-861S) Entity State Ownership Customers (Count) Sales (Megawatthours) Revenues (Thousands Dollars) Average Price (cents/kWh) Alaska Electric Light&Power Co AK Investor Owned 16,464 399,492 41,691.0 10.44 Alaska Power and Telephone Co AK Investor Owned 7,630 63,068 17,642.0 27.97 Alaska Village Elec Coop, Inc AK Cooperative 10,829 97,874 53,522.0 54.68 Anchorage Municipal Light and Power AK Municipal 30,791 1,012,784 134,950.6 13.32

  7. Total Estimated Contract Cost: Performance Period

    Office of Environmental Management (EM)

    Fee Available (N/A) Total Fee Paid $23,179,000 $18,632,000 $16,680,000 $18,705,000 $25,495,000 $34,370,000 $32,329,000 $33,913,000 $66,794,000 $10,557,000 $3,135,000 $283,789,000 FY2015 FY2014 FY2013 FY2009 FY2010 FY2011 FY2012 Fee Information Minimum Fee Maximum Fee Dec 2015 Contract Number: Cost Plus Incentive Fee Contractor: $3,264,909,094 Contract Period: EM Contractor Fee s Idaho Operations Office - Idaho Falls, ID Contract Name: Idaho Cleanup Project $0 Contract Type: CH2M Washington Group

  8. Performance Period Total Fee Paid FY2001

    Office of Environmental Management (EM)

    FY2001 $4,547,400 FY2002 $4,871,000 FY2003 $6,177,902 FY2004 $8,743,007 FY2005 $13,134,189 FY2006 $7,489,704 FY2007 $9,090,924 FY2008 $10,045,072 FY2009 $12,504,247 FY2010 $17,590,414 FY2011 $17,558,710 FY2012 $14,528,770 Cumulative Fee Paid $126,281,339 Cost Plus Award Fee DE-AC29-01AL66444 Washington TRU Solutions LLC Contractor: Contract Number: Contract Type: $8,743,007 Contract Period: $1,813,482,000 Fee Information Maximum Fee $131,691,744 Total Estimated Contract Cost: $4,547,400

  9. Performance Period Total Fee Paid FY2008

    Office of Environmental Management (EM)

    FY2008 $87,580 FY2009 $87,580 FY2010 $171,763 FY2011 $1,339,286 FY 2012 $38,126 FY 2013 $42,265 Cumulative Fee Paid $1,766,600 $42,265 Cost Plus Incentive Fee/Cost Plus Fixed Fee $36,602,425 Contract Period: September 2007 - November 30, 2012 Target Fee $521,595 Total Estimated Contract Cost Contract Type: Maximum Fee $3,129,570 $175,160 $377,516 $1,439,287 Fee Available $175,160 $80,871 Accelerated Remediation Company (aRc) DE-AT30-07CC60013 Contractor: Contract Number: Minimum Fee $2,086,380

  10. Total Supplemental Supply of Natural Gas

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

    Product: Total Supplemental Supply Synthetic Propane-Air Refinery Gas Biomass Other Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 2010 2011 2012 2013 2014 2015 View History U.S. 64,575 60,088 61,366 54,650 59,528 59,693 1980-2015 Alabama 0 0 0 0 0 1967-2014 Alaska 0 0 0 0 0 2004-2014 Arizona 0 0 0 0 0 1967-2014 Arkansas 0 0 0 0 0 1967-2014 Colorado 5,148 4,268 4,412 4,077 4,120

  11. State Residential Commercial Industrial Transportation Total

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

    Sales (Megawatthours) (Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 47,211,525 53,107,038 19,107,433 557,463 119,983,459 Connecticut 12,777,579 12,893,531 3,514,798 168,552 29,354,460 Maine 4,660,605 3,984,570 3,357,486 0 12,002,661 Massachusetts 20,071,160 26,076,208 7,960,941 360,983 54,469,292 New Hampshire 4,510,487 4,464,530 1,969,064 0 10,944,081 Rhode Island 3,070,347 3,657,679 887,150 27,928

  12. Development of a Low Input and sustainable Switchgrass Feedstock Production System Utilizing Beneficial Bacterial Endophytes

    SciTech Connect (OSTI)

    Mei, Chuansheng; Nowak, Jerzy; Seiler, John

    2014-10-24

    Switchgrass represents a promising feedstock crop for US energy sustainability. However, its broad utilization for bioenergy requires improvements of biomass yields and stress tolerance. In this DOE funded project, we have been working on harnessing beneficial bacterial endophytes to enhance switchgrass performance and to develop a low input feedstock production system for marginal lands that do not compete with the production of food crops. We have demonstrated that one of most promising plant growth-promoting bacterial endophytes, Burkholderia phytofirmans strain PsJN, is able to colonize roots and significantly promote growth of switchgrass cv. Alamo under in vitro, growth chamber, greenhouse, as well as field conditions. Furthermore, PsJN bacterization improved growth and development of switchgrass seedlings, significantly stimulated plant root and shoot growth, and tiller number in the field, and enhanced biomass accumulation on both poor (p<0.001) and rich (p<0.05) soils, with more effective stimulation of plant growth in low fertility soil. Plant physiology measurements showed that PsJN inoculated Alamo had consistently lower transpiration, lower stomatal conductance, and higher water use efficiency in greenhouse conditions. These physiological changes may significantly contribute to the recorded growth enhancement. PsJN inoculation rapidly results in an increase in photosynthetic rates which contributes to the advanced growth and development. Some evidence suggests that this initial growth advantage decreases with time when resources are not limited such as in greenhouse studies. Additionally, better drought resistance and drought hardening were observed in PsJN inoculated switchgrass. Using the DOE-funded switchgrass EST microarray, in a collaboration with the Genomics Core Facility at the Noble Foundation, we have determined gene expression profile changes in both responsive switchgrass cv. Alamo and non-responsive cv. Cave-in-Rock (CR) following PsJN bacterization. With the MapMan software to analyze microarray data, the number of up- and down-regulated probes was calculated. The number of up-regulated probes in Alamo was 26, 14, 14, and 12% at 0.5, 2, 4 and 8 days after inoculation (DAI) with PsJN, respectively while the corresponding number in CR was 24, 22, 21, and 19%, respectively. In both cultivars, the largest number of up-regulated probes occurred at 0.5 DAI. Noticeable differences throughout the timeframe between Alamo and CR were that the number was dramatically decreased to half (12%) in Alamo but remained high in CR (approximately 20%). The number of down regulated genes demonstrated different trends in Alamo and CR. Alamo had an increasing trend from 9% at 0.5 DAI to 11, 17, and 28% at 2, 4, and 8 DAI, respectively. However, CR had 13% at 0.5 and 2 DAI, and declined to 10% at 4 and 8 DAI. With the aid of MapMan and PageMan, we mapped the response of the ID probes to the observed major gene regulatory network and major biosynthetic pathway changes associated with the beneficial bacterial endophyte infection, colonization, and early growth promotion process. We found significant differences in gene expression patterns between responsive and non-responsive cultivars in many pathways, including redox state regulation, signaling, proteolysis, transcription factors, as well as hormone (SA and JA in particular)-associated pathways. Form microarray data, a total of 50 key genes have been verified using qPCR. Ten of these genes were chosen for further functional study via either overexpression and/or RNAi knockout technologies. These genes were calmodulin-related calcium sensor protein (CAM), glutathione S-transferase (GST), histidine-containing phosphotransfer protein (H-221), 3 different zinc finger proteins (ZF-371, ZF131 and ZF242), EF hand transcription factor (EF-622), peroxidase, cellulose synthase catalytic submit A2 (CESA2), and Aux/IAA family. A total of 8 overexpression and 5 RNAi transgenic plants have been regenerated, and their gene expression levels determined using qPCR. Consequently

  13. Method for guessing the response of a physical system to an arbitrary input

    DOE Patents [OSTI]

    Wolpert, David H.

    1996-01-01

    Stacked generalization is used to minimize the generalization errors of one or more generalizers acting on a known set of input values and output values representing a physical manifestation and a transformation of that manifestation, e.g., hand-written characters to ASCII characters, spoken speech to computer command, etc. Stacked generalization acts to deduce the biases of the generalizer(s) with respect to a known learning set and then correct for those biases. This deduction proceeds by generalizing in a second space whose inputs are the guesses of the original generalizers when taught with part of the learning set and trying to guess the rest of it, and whose output is the correct guess. Stacked generalization can be used to combine multiple generalizers or to provide a correction to a guess from a single generalizer.

  14. U.S. Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) U.S. Natural Gas Input Supplemental Fuels (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 154,590 175,702 144,811 131,894 109,977 126,363 113,189 101,382 101,134 106,745 1990's 122,806 112,606 117,919 118,999 110,826 110,290 109,455 103,153 102,189 98,249 2000's 90,000 86,312 67,980 67,706 60,365 63,691 66,058 63,132 60,889 65,259 2010's 64,575 60,088 61,366 54,650 59,528 59,693 - = No Data

  15. Steering and focusing effects in TESLA cavity due to high order mode and input couplers

    SciTech Connect (OSTI)

    Piot, P.; /Fermilab; Dohlus, M.; Flottmann, K.; Marx, M.; Wipf, S.G.; /DESY

    2005-05-01

    Many state-of-art electron accelerator proposals incorporate TESLA-type superconducting radio-frequency (rf) cavities [1]. These standing wave rf cavities include rf input couplers and a pair of high order mode (HOM) couplers to absorb the energy associated to HOM field excited as the bunch passes through the cavity. In the present paper we investigate, using numerical simulations, the impact of the input and HOM couplers on the beam dynamics to zeroth and first order in initial position, and present parametric studies of the strength of these effects for various incoming beam energies. We finally study the impact of this asymmetric field on the beam dynamics, taking as an example the low energy section of the X-ray FEL injector.

  16. Method and apparatus for smart battery charging including a plurality of controllers each monitoring input variables

    DOE Patents [OSTI]

    Hammerstrom, Donald J.

    2013-10-15

    A method for managing the charging and discharging of batteries wherein at least one battery is connected to a battery charger, the battery charger is connected to a power supply. A plurality of controllers in communication with one and another are provided, each of the controllers monitoring a subset of input variables. A set of charging constraints may then generated for each controller as a function of the subset of input variables. A set of objectives for each controller may also be generated. A preferred charge rate for each controller is generated as a function of either the set of objectives, the charging constraints, or both, using an algorithm that accounts for each of the preferred charge rates for each of the controllers and/or that does not violate any of the charging constraints. A current flow between the battery and the battery charger is then provided at the actual charge rate.

  17. BETO Seeks Stakeholder Input on Achieving High Yields from Algal Feedstocks

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

    | Department of Energy Bioenergy Technologies Office (BETO) has released a Request for Information (RFI) titled "High Yields through Productivity and Integration Research." BETO is seeking input from industry, academia, and other stakeholders regarding supply systems and services for the cultivation, logistics, and preprocessing of algal feedstocks. This RFI provides algae stakeholders with an opportunity to contribute their views on the requirements necessary to develop reliable

  18. High-Frequency Matrix Converter with Square Wave Input - Energy Innovation

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

    Portal Solar Photovoltaic Solar Photovoltaic Geothermal Geothermal Energy Storage Energy Storage Electricity Transmission Electricity Transmission Find More Like This Return to Search High-Frequency Matrix Converter with Square Wave Input DOE Grant Recipients Contact GRANT About This Technology Publications: PDF Document Publication 8995159.pdf (1,648 KB) Technology Marketing Summary As the use of renewable energy sources increase, there is an increasing need for power converters capable of

  19. 2012 Congestion Study Webinars to Present Preliminary Findings and Receive Input from Stakeholders

    Broader source: Energy.gov [DOE]

    The Department of Energy will host three webinars in August 2012 to present the preliminary findings of the 2012 National Electric Transmission Congestion Study and to receive input and suggestions from state officials, industry representatives, and other stakeholders. Two of the webinars will be designed to discuss with state officials the initial findings of the DOE 2012 congestion analysis. The third webinar will be for industry representatives and other interested parties, although stakeholders may dial into any of the three meetings.

  20. A New Ensemble of Perturbed-Input-Parameter Simulations by the Community Atmosphere Model

    SciTech Connect (OSTI)

    Covey, C; Brandon, S; Bremer, P T; Domyancis, D; Garaizar, X; Johannesson, G; Klein, R; Klein, S A; Lucas, D D; Tannahill, J; Zhang, Y

    2011-10-27

    Uncertainty quantification (UQ) is a fundamental challenge in the numerical simulation of Earth's weather and climate, and other complex systems. It entails much more than attaching defensible error bars to predictions: in particular it includes assessing low-probability but high-consequence events. To achieve these goals with models containing a large number of uncertain input parameters, structural uncertainties, etc., raw computational power is needed. An automated, self-adapting search of the possible model configurations is also useful. Our UQ initiative at the Lawrence Livermore National Laboratory has produced the most extensive set to date of simulations from the US Community Atmosphere Model. We are examining output from about 3,000 twelve-year climate simulations generated with a specialized UQ software framework, and assessing the model's accuracy as a function of 21 to 28 uncertain input parameter values. Most of the input parameters we vary are related to the boundary layer, clouds, and other sub-grid scale processes. Our simulations prescribe surface boundary conditions (sea surface temperatures and sea ice amounts) to match recent observations. Fully searching this 21+ dimensional space is impossible, but sensitivity and ranking algorithms can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination. Bayesian statistical constraints, employing a variety of climate observations as metrics, also seem promising. Observational constraints will be important in the next step of our project, which will compute sea surface temperatures and sea ice interactively, and will study climate change due to increasing atmospheric carbon dioxide.

  1. SPP Staff appreciates the opportunity to provide input regarding the Draft Conge

    Energy Savers [EERE]

    SPP Staff appreciates the opportunity to provide input regarding the Draft Congestion Study. The following remarks have not been vetted with SPP members, and do not represent any approved official remarks on behalf of SPP's members. Given the long lead times to get EHV transmission approved and constructed, DOE Congestion Studies need to look beyond 3-5 year horizons. DOE assessments regarding congestion need to go beyond reporting historical data and summarizing regional studies to reflect

  2. Apparatus and method for quantitatively evaluating total fissile and total fertile nuclide content in samples

    DOE Patents [OSTI]

    Caldwell, John T. (Los Alamos, NM); Kunz, Walter E. (Santa Fe, NM); Cates, Michael R. (Oak Ridge, TN); Franks, Larry A. (Santa Barbara, CA)

    1985-01-01

    Simultaneous photon and neutron interrogation of samples for the quantitative determination of total fissile nuclide and total fertile nuclide material present is made possible by the use of an electron accelerator. Prompt and delayed neutrons produced from resulting induced fissions are counted using a single detection system and allow the resolution of the contributions from each interrogating flux leading in turn to the quantitative determination sought. Detection limits for .sup.239 Pu are estimated to be about 3 mg using prompt fission neutrons and about 6 mg using delayed neutrons.

  3. Data:B0c510db-7e64-4d8c-a9ae-f8521cbb8489 | Open Energy Information

    Open Energy Info (EERE)

    d8c-a9ae-f8521cbb8489 No revision has been approved for this page. It is currently under review by our subject matter experts. Jump to: navigation, search Loading... 1. Basic...

  4. OSU-A9 inhibits angiogenesis in human umbilical vein endothelial cells via disrupting AktNF-?B and MAPK signaling pathways

    SciTech Connect (OSTI)

    Omar, Hany A.; Arafa, El-Shaimaa A.; Salama, Samir A.; Arab, Hany H.; Wu, Chieh-Hsi; Weng, Jing-Ru

    2013-11-01

    Since the introduction of angiogenesis as a useful target for cancer therapy, few agents have been approved for clinical use due to the rapid development of resistance. This problem can be minimized by simultaneous targeting of multiple angiogenesis signaling pathways, a potential strategy in cancer management known as polypharmacology. The current study aimed at exploring the anti-angiogenic activity of OSU-A9, an indole-3-carbinol-derived pleotropic agent that targets mainly Aktnuclear factor-kappa B (NF-?B) signaling which regulates many key players of angiogenesis such as vascular endothelial growth factor (VEGF) and matrix metalloproteinases (MMPs). Human umbilical vein endothelial cells (HUVECs) were used to study the in vitro anti-angiogenic effect of OSU-A9 on several key steps of angiogenesis. Results showed that OSU-A9 effectively inhibited cell proliferation and induced apoptosis and cell cycle arrest in HUVECs. Besides, OSU-A9 inhibited angiogenesis as evidenced by abrogation of migration/invasion and Matrigel tube formation in HUVECs and attenuation of the in vivo neovascularization in the chicken chorioallantoic membrane assay. Mechanistically, Western blot, RT-PCR and ELISA analyses showed the ability of OSU-A9 to inhibit MMP-2 production and VEGF expression induced by hypoxia or phorbol-12-myristyl-13-acetate. Furthermore, dual inhibition of AktNF-?B and mitogen-activated protein kinase (MAPK) signaling, the key regulators of angiogenesis, was observed. Together, the current study highlights evidences for the promising anti-angiogenic activity of OSU-A9, at least in part through the inhibition of AktNF-?B and MAPK signaling and their consequent inhibition of VEGF and MMP-2. These findings support OSU-A9's clinical promise as a component of anticancer therapy. - Highlights: The antiangiogenic activity of OSU-A9 in HUVECs was explored. OSU-A9 inhibited HUVECs proliferation, migration, invasion and tube formation. OSU-A9 targeted signaling pathways mediated by Akt-NF-kB, VEGF, and MMP-2. The anti-angiogenic activity of OSU-A9 supports its clinical promise.

  5. Total Energy Facilities Biomass Facility | Open Energy Information

    Open Energy Info (EERE)

    Energy Facilities Biomass Facility Jump to: navigation, search Name Total Energy Facilities Biomass Facility Facility Total Energy Facilities Sector Biomass Facility Type...

  6. ,"Total District Heat Consumption (trillion Btu)",,,,,"District...

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

    Heat Consumption (trillion Btu)",,,,,"District Heat Energy Intensity (thousand Btusquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  7. ,"Total Natural Gas Consumption (trillion Btu)",,,,,"Natural...

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

    Gas Consumption (trillion Btu)",,,,,"Natural Gas Energy Intensity (thousand Btusquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  8. National Fuel Cell and Hydrogen Energy Overview: Total Energy...

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

    National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 Presentation by Sunita Satyapal at the ...

  9. Table 5a. Total District Heat Consumption per Effective Occupied...

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

    a. Total District Heat Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using District Heat (thousand) Total District Heat Consumption...

  10. NREL: Building America Total Quality Management - 2015 Peer Review...

    Energy Savers [EERE]

    NREL: Building America Total Quality Management - 2015 Peer Review NREL: Building America Total Quality Management - 2015 Peer Review Presenter: Stacey Rothgeb, NREL View the...

  11. Federal Offshore -- Gulf of Mexico Natural Gas Total Consumption...

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

    -- Gulf of Mexico Natural Gas Total Consumption (Million Cubic Feet) Federal Offshore -- Gulf of Mexico Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1...

  12. ,"Crude Oil and Petroleum Products Total Stocks Stocks by Type...

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

    Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks ... PM" "Back to Contents","Data 1: Crude Oil and Petroleum Products Total Stocks Stocks ...

  13. Table 6b. Relative Standard Errors for Total Electricity Consumption...

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

    b. Relative Standard Errors for Total Electricity Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Electricity (thousand) Total...

  14. Methods to Register Models and Input/Output Parameters for Integrated Modeling

    SciTech Connect (OSTI)

    Droppo, James G.; Whelan, Gene; Tryby, Michael E.; Pelton, Mitchell A.; Taira, Randal Y.; Dorow, Kevin E.

    2010-07-10

    Significant resources can be required when constructing integrated modeling systems. In a typical application, components (e.g., models and databases) created by different developers are assimilated, requiring the frameworks functionality to bridge the gap between the users knowledge of the components being linked. The framework, therefore, needs the capability to assimilate a wide range of model-specific input/output requirements as well as their associated assumptions and constraints. The process of assimilating such disparate components into an integrated modeling framework varies in complexity and difficulty. Several factors influence the relative ease of assimilating components, including, but not limited to, familiarity with the components being assimilated, familiarity with the framework and its tools that support the assimilation process, level of documentation associated with the components and the framework, and design structure of the components and framework. This initial effort reviews different approaches for assimilating models and their model-specific input/output requirements: 1) modifying component models to directly communicate with the framework (i.e., through an Application Programming Interface), 2) developing model-specific external wrappers such that no component model modifications are required, 3) using parsing tools to visually map pre-existing input/output files, and 4) describing and linking models as dynamic link libraries. Most of these approaches are illustrated using the widely distributed modeling system called Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES). The review concludes that each has its strengths and weakness, the factors that determine which approaches work best in a given application.

  15. Procedure for developing biological input for the design, location, or modification of water-intake structures

    SciTech Connect (OSTI)

    Neitzel, D.A.; McKenzie, D.H.

    1981-12-01

    To minimize adverse impact on aquatic ecosystems resulting from the operation of water intake structures, design engineers must have relevant information on the behavior, physiology and ecology of local fish and shellfish. Identification of stimulus/response relationships and the environmental factors that influence them is the first step in incorporating biological information in the design, location or modification of water intake structures. A procedure is presented in this document for providing biological input to engineers who are designing, locating or modifying a water intake structure. The authors discuss sources of stimuli at water intakes, historical approaches in assessing potential/actual impact and review biological information needed for intake design.

  16. Multi-input and binary reproducible, high bandwidth floating point adder in a collective network

    DOE Patents [OSTI]

    Chen, Dong; Eisley, Noel A; Heidelberger, Philip; Steinmacher-Burow, Burkhard

    2015-03-10

    To add floating point numbers in a parallel computing system, a collective logic device receives the floating point numbers from computing nodes. The collective logic devices converts the floating point numbers to integer numbers. The collective logic device adds the integer numbers and generating a summation of the integer numbers. The collective logic device converts the summation to a floating point number. The collective logic device performs the receiving, the converting the floating point numbers, the adding, the generating and the converting the summation in one pass. One pass indicates that the computing nodes send inputs only once to the collective logic device and receive outputs only once from the collective logic device.

  17. Approaches used for Clearance of Lands from Nuclear Facilities among Several Countries: Evaluation for Regulatory Input

    Office of Environmental Management (EM)

    :14 Report number: 2013:14 ISSN: 2000-0456 Available at www.stralsakerhetsmyndigheten.se Approaches used for Clearance of Lands from Nuclear Facilities among Several Countries Evaluation for Regulatory Input Robert A. Meck Author: SSM perspektiv SSM har nyligen beslutat om föreskrifter om friklassning av material, loka- ler, byggnader och mark vid verksamhet med joniserande strålning (SSMFS 201 1:2). Föreskrifterna innehåller bland annat krav på att tillståndshavare, vid avveckling av

  18. Table A13. Selected Combustible Inputs of Energy for Heat, Power, and

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

    3. Selected Combustible Inputs of Energy for Heat, Power, and" " Electricity Generation and Net Demand for Electricity by Fuel Type," " Census Region, Census Division, and End Use, 1994: Part 1" " (Estimates in Btu or Physical Units)" ,,,,,,"Coal" ,,,"Distillate",,,"(excluding" ,"Net Demand",,"Fuel Oil",,,"Coal Coke" ,"for","Residual","and","Natural

  19. Table A39. Selected Combustible Inputs of Energy for Heat, Power, and

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

    9. Selected Combustible Inputs of Energy for Heat, Power, and" " Electricity Generation and Net Demand for Electricity by Fuel Type, Census" " Region, and End Use, 1991: Part 2" " (Estimates in Trillion Btu)" ,,,"Distillate",,,"Coal" ,"Net Demand",,"Fuel Oil",,,"(excluding","RSE" ,"for","Residual","and",,,"Coal Coke","Row" "End-Use

  20. RELAP5/MOD3 code manual: User`s guide and input requirements. Volume 2

    SciTech Connect (OSTI)

    1995-08-01

    The RELAP5 code has been developed for best estimate transient simulation of light water reactor coolant systems during postulated accidents. The code models the coupled behavior of the reactor coolant system and the core for loss-of-coolant accidents, and operational transients, such as anticipated transient without scram, loss of offsite power, loss of feedwater, and loss of flow. A generic modeling approach is used that permits simulating a variety of thermal hydraulic systems. Control system and secondary system components are included to permit modeling of plant controls, turbines, condensers, and secondary feedwater systems. Volume II contains detailed instructions for code application and input data preparation.

  1. Summary of Input to DOE Request for Information DE-PS36-08GO38002

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

    (Presentation) | Department of Energy PS36-08GO38002 (Presentation) Summary of Input to DOE Request for Information DE-PS36-08GO38002 (Presentation) Presented at the DOE Fuel Cell Pre-Solicitation Workshop held January 23-24, 2008 in Golden, Colorado. PDF icon fuelcell_pre-solicitation_wkshop_jan08_peterson.pdf More Documents & Publications Greenpower Trap Mufflerl System BILIWG: Consistent "Figures of Merit" (Presentation) Heating Ventilation and Air Conditioning Effic

  2. Input-independent, Scalable and Fast String Matching on the Cray XMT

    SciTech Connect (OSTI)

    Villa, Oreste; Chavarra-Miranda, Daniel; Maschhoff, Kristyn J.

    2009-05-25

    String searching is at the core of many security and network applications like search engines, intrusion detection systems, virus scanners and spam ?lters. The growing size of on-line content and the increasing wire speeds push the need for fast, and often real- time, string searching solutions. For these conditions, many software implementations (if not all) targeting conventional cache-based microprocessors do not perform well. They either exhibit overall low performance or exhibit highly variable performance depending on the types of inputs. For this reason, real-time state of the art solutions rely on the use of either custom hardware or Field-Programmable Gate Arrays (FPGAs) at the expense of overall system ?exibility and programmability. This paper presents a software based implementation of the Aho-Corasick string searching algorithm on the Cray XMT multithreaded shared memory machine. Our so- lution relies on the particular features of the XMT architecture and on several algorith- mic strategies: it is fast, scalable and its performance is virtually content-independent. On a 128-processor Cray XMT, it reaches a scanning speed of ? 28 Gbps with a performance variability below 10 %. In the 10 Gbps performance range, variability is below 2.5%. By comparison, an Intel dual-socket, 8-core system running at 2.66 GHz achieves a peak performance which varies from 500 Mbps to 10 Gbps depending on the type of input and dictionary size.

  3. EO 13690 (2015): Establishing a Federal Flood Risk Management Standard and a Process for Further Soliciting and Considering Stakeholder Input

    Broader source: Energy.gov [DOE]

    Executive Order (E.O.) 13690, Establishing a Federal Flood Risk Management Standard [FFRMS] and a Process for Further Soliciting and Considering Stakeholder Input (2015) amends E.O. 11988,...

  4. Computer code input for thermal hydraulic analysis of Multi-Function Waste Tank Facility Title II design

    SciTech Connect (OSTI)

    Cramer, E.R.

    1994-10-01

    The input files to the P/Thermal computer code are documented for the thermal hydraulic analysis of the Multi-Function Waste Tank Facility Title II design analysis.

  5. HEAT INPUT AND POST WELD HEAT TREATMENT EFFECTS ON REDUCED-ACTIVATION FERRITIC/MARTENSITIC STEEL FRICTION STIR WELDS

    SciTech Connect (OSTI)

    Tang, Wei; Chen, Gaoqiang; Chen, Jian; Yu, Xinghua; Frederick, David Alan; Feng, Zhili

    2015-01-01

    Reduced-activation ferritic/martensitic (RAFM) steels are an important class of structural materials for fusion reactor internals developed in recent years because of their improved irradiation resistance. However, they can suffer from welding induced property degradations. In this paper, a solid phase joining technology friction stir welding (FSW) was adopted to join a RAFM steel Eurofer 97 and different FSW parameters/heat input were chosen to produce welds. FSW response parameters, joint microstructures and microhardness were investigated to reveal relationships among welding heat input, weld structure characterization and mechanical properties. In general, FSW heat input results in high hardness inside the stir zone mostly due to a martensitic transformation. It is possible to produce friction stir welds similar to but not with exactly the same base metal hardness when using low power input because of other hardening mechanisms. Further, post weld heat treatment (PWHT) is a very effective way to reduce FSW stir zone hardness values.

  6. Visualizations, Screen Shots, and Data Input Files from VisIT

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

    VisIt is a free interactive parallel visualization and graphical analysis tool for viewing scientific data on Unix and PC platforms. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images for presentations. VisIt contains a rich set of visualization features so that you can view your data in a variety of ways. It can be used to visualize scalar and vector fields defined on two- and three-dimensional (2D and 3D) structured and unstructured meshes. VisIt was designed to handle very large data set sizes in the terascale range and yet can also handle small data sets in the kilobyte range. The VisIT website provides a gallery of vizualizations, another set of screen shots, and allows downloads of data files for input and source codes and executables for the VisIT software suite.

  7. User manual for IOSYM: an input-oriented simulation language for continuous systems

    SciTech Connect (OSTI)

    Polito, J.

    1981-03-01

    IOSYM is an extension of the GASP IV simulation language. It permits systems which are sequences of continuous processes to be modeled graphically. Normally the system can be described by data input only. The language permits stochastic sequencing and termination criteria for processes and allows crossing conditions for ending operations that are more general than GASP IV. Extensive capability exists for conditional branching and logical modification of the network. IOSYM has been used to model the cost of geothermal drilling where the various costly processes of drilling are represented by IOSYM operations. The language is much more general, however, since it retains most of GASP IV's discrete event capabilities and permits easy modeling of continuous processes.

  8. Device for modular input high-speed multi-channel digitizing of electrical data

    DOE Patents [OSTI]

    VanDeusen, Alan L. (Lee's Summit, MO); Crist, Charles E. (Waxahachie, TX)

    1995-09-26

    A multi-channel high-speed digitizer module converts a plurality of analog signals to digital signals (digitizing) and stores the signals in a memory device. The analog input channels are digitized simultaneously at high speed with a relatively large number of on-board memory data points per channel. The module provides an automated calibration based upon a single voltage reference source. Low signal noise at such a high density and sample rate is accomplished by ensuring the A/D converters are clocked at the same point in the noise cycle each time so that synchronous noise sampling occurs. This sampling process, in conjunction with an automated calibration, yields signal noise levels well below the noise level present on the analog reference voltages.

  9. Device for modular input high-speed multi-channel digitizing of electrical data

    DOE Patents [OSTI]

    VanDeusen, A.L.; Crist, C.E.

    1995-09-26

    A multi-channel high-speed digitizer module converts a plurality of analog signals to digital signals (digitizing) and stores the signals in a memory device. The analog input channels are digitized simultaneously at high speed with a relatively large number of on-board memory data points per channel. The module provides an automated calibration based upon a single voltage reference source. Low signal noise at such a high density and sample rate is accomplished by ensuring the A/D converters are clocked at the same point in the noise cycle each time so that synchronous noise sampling occurs. This sampling process, in conjunction with an automated calibration, yields signal noise levels well below the noise level present on the analog reference voltages. 1 fig.

  10. Contaminant transport in unconfined aquifer, input to low-level tank waste interim performance assessment

    SciTech Connect (OSTI)

    Lu, A.H., Westinghouse Hanford

    1996-08-14

    This report describes briefly the Hanford sitewide groundwater model and its application to the Low-Level Tank Waste Disposal (LLTWD) interim Performance Assessment (PA). The Well Intercept Factor (WIF) or dilution factor from a given areal flux entering the aquifer released from the LLTWD site are calculated for base case and various sensitivity cases. In conjunction with the calculation for released fluxes through vadose zone transport,the dose at the compliance point can be obtained by a simple multiplication. The relative dose contribution from the upstream sources was also calculated and presented in the appendix for an equal areal flux at the LLTWD site. The results provide input for management decisions on remediation action needed for reduction of the released fluxes from the upstream facilities to the allowed level to meet the required dose criteria.

  11. Using Whole-House Field Tests to Empirically Derive Moisture Buffering Model Inputs

    SciTech Connect (OSTI)

    Woods, J.; Winkler, J.; Christensen, D.; Hancock, E.

    2014-08-01

    Building energy simulations can be used to predict a building's interior conditions, along with the energy use associated with keeping these conditions comfortable. These models simulate the loads on the building (e.g., internal gains, envelope heat transfer), determine the operation of the space conditioning equipment, and then calculate the building's temperature and humidity throughout the year. The indoor temperature and humidity are affected not only by the loads and the space conditioning equipment, but also by the capacitance of the building materials, which buffer changes in temperature and humidity. This research developed an empirical method to extract whole-house model inputs for use with a more accurate moisture capacitance model (the effective moisture penetration depth model). The experimental approach was to subject the materials in the house to a square-wave relative humidity profile, measure all of the moisture transfer terms (e.g., infiltration, air conditioner condensate) and calculate the only unmeasured term: the moisture absorption into the materials. After validating the method with laboratory measurements, we performed the tests in a field house. A least-squares fit of an analytical solution to the measured moisture absorption curves was used to determine the three independent model parameters representing the moisture buffering potential of this house and its furnishings. Follow on tests with realistic latent and sensible loads showed good agreement with the derived parameters, especially compared to the commonly-used effective capacitance approach. These results show that the EMPD model, once the inputs are known, is an accurate moisture buffering model.

  12. FY 2007 Total System Life Cycle Cost, Pub 2008

    Broader source: Energy.gov [DOE]

    The Analysis of the Total System Life Cycle Cost (TSLCC) of the Civilian Radioactive Waste Management Program presents the Office of Civilian Radioactive Waste Management’s (OCRWM) May 2007 total...

  13. Total China Investment Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    China Investment Co Ltd Jump to: navigation, search Name: Total (China) Investment Co. Ltd. Place: Beijing, China Zip: 100004 Product: Total has been present in China for about 30...

  14. Texas Natural Gas Total Consumption (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Total Consumption (Million Cubic Feet) Texas Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's...

  15. Texas Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Texas Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  16. West Virginia Natural Gas % of Total Residential Deliveries ...

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

    % of Total Residential Deliveries (Percent) West Virginia Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

  17. Connecticut Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Connecticut Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

  18. Connecticut Natural Gas Total Consumption (Million Cubic Feet...

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

    Total Consumption (Million Cubic Feet) Connecticut Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  19. North Carolina Natural Gas Total Consumption (Million Cubic Feet...

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

    Total Consumption (Million Cubic Feet) North Carolina Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  20. North Carolina Natural Gas % of Total Residential Deliveries...

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

    % of Total Residential Deliveries (Percent) North Carolina Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

  1. New York Natural Gas Total Consumption (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Total Consumption (Million Cubic Feet) New York Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  2. New York Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) New York Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  3. Project Functions and Activities Definitions for Total Project Cost

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

    1997-03-28

    This chapter provides guidelines developed to define the obvious disparity of opinions and practices with regard to what exactly is included in total estimated cost (TEC) and total project cost (TPC).

  4. Total dissolved gas prediction and optimization in RiverWare

    SciTech Connect (OSTI)

    Stewart, Kevin M.; Witt, Adam M.; Hadjerioua, Boualem

    2015-09-01

    Management and operation of dams within the Columbia River Basin (CRB) provides the region with irrigation, hydropower production, flood control, navigation, and fish passage. These various system-wide demands can require unique dam operations that may result in both voluntary and involuntary spill, thereby increasing tailrace levels of total dissolved gas (TDG) which can be fatal to fish. Appropriately managing TDG levels within the context of the systematic demands requires a predictive framework robust enough to capture the operationally related effects on TDG levels. Development of the TDG predictive methodology herein attempts to capture the different modes of hydro operation, thereby making it a viable tool to be used in conjunction with a real-time scheduling model such as RiverWare. The end result of the effort will allow hydro operators to minimize system-wide TDG while meeting hydropower operational targets and constraints. The physical parameters such as spill and hydropower flow proportions, accompanied by the characteristics of the dam such as plant head levels and tailrace depths, are used to develop the empirically-based prediction model. In the broader study, two different models are developed a simplified and comprehensive model. The latter model incorporates more specific bubble physics parameters for the prediction of tailrace TDG levels. The former model is presented herein and utilizes an empirically based approach to predict downstream TDG levels based on local saturation depth, spillway and powerhouse flow proportions, and entrainment effects. Representative data collected from each of the hydro projects is used to calibrate and validate model performance and the accuracy of predicted TDG uptake. ORNL, in conjunction with IIHR - Hydroscience & Engineering, The University of Iowa, carried out model adjustments to adequately capture TDG levels with respect to each plant while maintaining a generalized model configuration. Validation results indicate excellent model performance with coefficient of determination values exceeding 92% for all sites. This approach enables model extension to an increasingly wider array of hydropower plants, i.e., with the proper data input, TDG uptake can be calculated independent of actual physical component design. The TDG model is used as a module in the systematic optimization framework of RiverWare, a river and reservoir modeling tool used by federal agencies, public utility districts, and other dam owners and operators to forecast, schedule, and manage hydropower assets. The integration and testing of the TDG module within RiverWare, led by University of Colorado s Center for Advanced Decision Support for Water and Environmental Systems (CADSWES), will allow users to generate optimum system schedules based on the minimization of TDG. Optimization analysis and added value will be quantified as system wide reductions in TDG achieved while meeting existing hydropower constraints. Future work includes the development of a method to predict downstream reservoir forebay TDG levels as a function of upstream reservoir tailrace TDG values based on river hydrodynamics, hydro operations, and reservoir characteristics. Once implemented, a holistic model that predicts both TDG uptake and transport will give hydropower operators valuable insight into how system-wide environmental effects can be mitigated while simultaneously balancing stakeholder interests.

  5. Energy and crude oil input requirements for the production of reformulated gasolines

    SciTech Connect (OSTI)

    Singh, M.; McNutt, B.

    1993-11-01

    The energy and crude oil requirements for the production of reformulated gasolines (RFG) are estimated. Both the energy and crude oil embodied in the final product and the process energy required to manufacture the RFG and its components are included. The effects on energy and crude oil use of using various oxygenates to meet the minimum oxygen content level required by the Clean Air Act Amendments are evaluated. The analysis illustrates that production of RFG requires more total energy than that of conventional gasoline but uses less crude oil. The energy and crude oil use requirements of the different RFGs vary considerably. For the same emissions performance level, RFG with ethanol requires substantially more total energy and crude oil than RFG with MTBE or ETBE. A specific proposal by the EPA designed to allow the use of ethanol in RFG would increase the total energy required to produce RFG by 2% and the total crude oil required by 2.0 to 2.5% over that for the base RFG with MTBE.

  6. Energy and crude oil input requirements for the production of reformulated gasolines

    SciTech Connect (OSTI)

    Singh, M.; McNutt, B.

    1993-10-01

    The energy and crude oil requirements for the production of reformulated gasoline (RFG) are estimated. The scope of the study includes both the energy and crude oil embodied in the final product and the process energy required to manufacture the RFG and its components. The effects on energy and crude oil use of employing various oxygenates to meet the minimum oxygen-content level required by the Clean Air Act Amendments are evaluated. The analysis shows that production of RFG requires more total energy, but uses less crude oil, than that of conventional gasoline. The energy and crude oil use requirements of the different RFGs vary considerably. For the same emissions performance level, RFG with ethanol requires substantially more total energy and crude oil than does RFG with methyl tertiary butyl ether (MTBE) or ethyl tertiary butyl ether. A specific proposal by the US Environmental Protection Agency, designed to allow the use of ethanol in RFG, would increase the total energy required to produce RFG by 2% and the total crude oil required by 2.0 to 2.5% over the corresponding values for the base RFG with MTBE.

  7. T-693: Symantec Endpoint Protection Manager Input Validation Hole Permits Cross-Site Scripting and Cross-Site Request Forgery Attacks

    Broader source: Energy.gov [DOE]

    Symantec Endpoint Protection Manager Input Validation Hole Permits Cross-Site Scripting and Cross-Site Request Forgery Attacks .

  8. Effect of heat input on the microstructure, residual stresses and corrosion resistance of 304L austenitic stainless steel weldments

    SciTech Connect (OSTI)

    Unnikrishnan, Rahul, E-mail: rahulunnikrishnannair@gmail.com [Department of Metallurgical and Materials Engineering, Visvesvaraya National Institute of Technology (VNIT), South Ambazari Road, Nagpur 440010, Maharashtra (India); Idury, K.S.N. Satish, E-mail: satishidury@gmail.com [Department of Metallurgical and Materials Engineering, Visvesvaraya National Institute of Technology (VNIT), South Ambazari Road, Nagpur 440010, Maharashtra (India); Ismail, T.P., E-mail: tpisma@gmail.com [Department of Metallurgical and Materials Engineering, Visvesvaraya National Institute of Technology (VNIT), South Ambazari Road, Nagpur 440010, Maharashtra (India); Bhadauria, Alok, E-mail: alokbhadauria1@gmail.com [Department of Metallurgical and Materials Engineering, Visvesvaraya National Institute of Technology (VNIT), South Ambazari Road, Nagpur 440010, Maharashtra (India); Shekhawat, S.K., E-mail: satishshekhawat@gmail.com [Department of Metallurgical Engineering and Materials Science, Indian Institute of Technology Bombay (IITB), Powai, Mumbai 400076, Maharashtra (India); Khatirkar, Rajesh K., E-mail: rajesh.khatirkar@gmail.com [Department of Metallurgical and Materials Engineering, Visvesvaraya National Institute of Technology (VNIT), South Ambazari Road, Nagpur 440010, Maharashtra (India); Sapate, Sanjay G., E-mail: sgsapate@yahoo.com [Department of Metallurgical and Materials Engineering, Visvesvaraya National Institute of Technology (VNIT), South Ambazari Road, Nagpur 440010, Maharashtra (India)

    2014-07-01

    Austenitic stainless steels are widely used in high performance pressure vessels, nuclear, chemical, process and medical industry due to their very good corrosion resistance and superior mechanical properties. However, austenitic stainless steels are prone to sensitization when subjected to higher temperatures (673 K to 1173 K) during the manufacturing process (e.g. welding) and/or certain applications (e.g. pressure vessels). During sensitization, chromium in the matrix precipitates out as carbides and intermetallic compounds (sigma, chi and Laves phases) decreasing the corrosion resistance and mechanical properties. In the present investigation, 304L austenitic stainless steel was subjected to different heat inputs by shielded metal arc welding process using a standard 308L electrode. The microstructural developments were characterized by using optical microscopy and electron backscattered diffraction, while the residual stresses were measured by X-ray diffraction using the sin{sup 2}? method. It was observed that even at the highest heat input, shielded metal arc welding process does not result in significant precipitation of carbides or intermetallic phases. The ferrite content and grain size increased with increase in heat input. The grain size variation in the fusion zone/heat affected zone was not effectively captured by optical microscopy. This study shows that electron backscattered diffraction is necessary to bring out changes in the grain size quantitatively in the fusion zone/heat affected zone as it can consider twin boundaries as a part of grain in the calculation of grain size. The residual stresses were compressive in nature for the lowest heat input, while they were tensile at the highest heat input near the weld bead. The significant feature of the welded region and the base metal was the presence of a very strong texture. The texture in the heat affected zone was almost random. - Highlights: Effect of heat input on microstructure, residual stresses and corrosion is studied. HAZ and width of dendrite in the welded region increase with heat input. Residual stresses are tensile near the welded region after the highest heat input. Welded region has the highest pit density after highest heat input. Dendrites and ?-ferrite were highly oriented in the welded region.

  9. LLNL Input to SNL L2 MS: Report on the Basis for Selection of Disposal Options

    SciTech Connect (OSTI)

    Sutton, M; Blink, J A; Halsey, W G

    2011-03-02

    This mid-year deliverable has two parts. The first part is a synopsis of J. Blink's interview of the former Nevada Attorney General, Frankie Sue Del Papa, which was done in preparation for the May 18-19, 2010 Legal and Regulatory Framework Workshop held in Albuquerque. The second part is a series of sections written as input for the SNL L2 Milestone M21UF033701, due March 31, 2011. Disposal of high-level radioactive waste is categorized in this review into several categories. Section II discusses alternatives to geologic disposal: space, ice-sheets, and an engineered mountain or mausoleum. Section III discusses alternative locations for mined geologic disposal: islands, coastlines, mid-continent, and saturated versus unsaturated zone. Section IV discusses geologic disposal alternatives other than emplacement in a mine: well injection, rock melt, sub-seabed, and deep boreholes in igneous or metamorphic basement rock. Finally, Secton V discusses alternative media for mined geologic disposal: basalt, tuff, granite and other igneous/metamorphic rock, alluvium, sandstone, carbonates and chalk, shale and clay, and salt.

  10. Development of a Novel Bi-Directional Isolated Multiple-Input DC-DC Converter

    SciTech Connect (OSTI)

    Li, H.

    2005-10-24

    There is vital need for a compact, lightweight, and efficient energy-storage system that is both affordable and has an acceptable cycle life for the large-scale production of electric vehicles (EVs) and hybrid electric vehicles (HEVs). Most of the current research employs a battery-storage unit (BU) combined with a fuel cell (FC) stack in order to achieve the operating voltage-current point of maximum efficiency for the FC system. A system block diagram is shown in Fig.1.1. In such a conventional arrangement, the battery is sized to deliver the difference between the energy required by the traction drive and the energy supplied by the FC system. Energy requirements can increase depending on the drive cycle over which the vehicle is expected to operate. Peak-power transients result in an increase of losses and elevated temperatures which result in a decrease in the lifetime of the battery. This research will propose a novel two-input direct current (dc) dc to dc converter to interface an additional energy-storage element, an ultracapacitor (UC), which is shown in Fig.1.2. It will assist the battery during transients to reduce the peak-power requirements of the battery.

  11. Sensitivity of injection costs to input petrophysical parameters in numerical geologic carbon sequestration models

    SciTech Connect (OSTI)

    Cheng, C. L.; Gragg, M. J.; Perfect, E.; White, Mark D.; Lemiszki, P. J.; McKay, L. D.

    2013-08-24

    Numerical simulations are widely used in feasibility studies for geologic carbon sequestration. Accurate estimates of petrophysical parameters are needed as inputs for these simulations. However, relatively few experimental values are available for CO2-brine systems. Hence, a sensitivity analysis was performed using the STOMP numerical code for supercritical CO2 injected into a model confined deep saline aquifer. The intrinsic permeability, porosity, pore compressibility, and capillary pressure-saturation/relative permeability parameters (residual liquid saturation, residual gas saturation, and van Genuchten alpha and m values) were varied independently. Their influence on CO2 injection rates and costs were determined and the parameters were ranked based on normalized coefficients of variation. The simulations resulted in differences of up to tens of millions of dollars over the life of the project (i.e., the time taken to inject 10.8 million metric tons of CO2). The two most influential parameters were the intrinsic permeability and the van Genuchten m value. Two other parameters, the residual gas saturation and the residual liquid saturation, ranked above the porosity. These results highlight the need for accurate estimates of capillary pressure-saturation/relative permeability parameters for geologic carbon sequestration simulations in addition to measurements of porosity and intrinsic permeability.

  12. Percentage of Total Natural Gas Commercial Deliveries included in Prices

    Gasoline and Diesel Fuel Update (EIA)

    City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S.

  13. Percentage of Total Natural Gas Industrial Deliveries included in Prices

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

    Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010

  14. Percentage of Total Natural Gas Industrial Deliveries included in Prices

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

    City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S.

  15. Percentage of Total Natural Gas Residential Deliveries included in Prices

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

    City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S.

  16. NREL: Building America Total Quality Management - 2015 Peer Review |

    Energy Savers [EERE]

    Department of Energy NREL: Building America Total Quality Management - 2015 Peer Review NREL: Building America Total Quality Management - 2015 Peer Review Presenter: Stacey Rothgeb, NREL View the Presentation PDF icon NREL: Building America Total Quality Management - 2015 Peer Review More Documents & Publications Home Performance with ENERGY STAR - 2014 BTO Peer Review Residential Buildings Integration Program Overview - 2015 BTO Peer Review LBNL's FLEXLAB test facility, which includes

  17. Trends in Commercial Buildings--Total Primary Energy Detail

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

    Energy Consumption and Graph Total Primary Energy Consumption Graph Detail and Data Table 1979 to 1992 primary consumption trend with 95% confidence ranges 1979 to 1992 primary...

  18. Trends in Commercial Buildings--Total Site Energy Detail

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

    Energy Consumption and Graph Total Site Energy Consumption Graph Detail and Data Table 1979 to 1992 site consumption trend with 95% confidence ranges 1979 to 1992 site...

  19. Table 3a. Total Natural Gas Consumption per Effective Occupied...

    Gasoline and Diesel Fuel Update (EIA)

    3a. Natural Gas Consumption per Sq Ft Table 3a. Total Natural Gas Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Natural Gas...

  20. Montana Total Maximum Daily Load Development Projects Wiki |...

    Open Energy Info (EERE)

    Wiki Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Montana Total Maximum Daily Load Development Projects Wiki Abstract Provides information on...

  1. ,"U.S. Total Refiner Petroleum Product Prices"

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

    NUSDPG","EMAEPPRPTGNUSDPG","EMAEPPRLPTGNUSDPG","EMAEPPRHPTGNUSDPG" "Date","U.S. Total Gasoline Retail Sales by Refiners (Dollars per Gallon)","U.S. Aviation Gasoline...

  2. ,"U.S. Total Refiner Acquisition Cost of Crude Oil"

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

    for" ,"Data 1","U.S. Total Refiner Acquisition Cost of Crude Oil",3,"Annual",2014,"6301968" ,"Release Date:","212016" ,"Next Release Date:","312016" ,"Excel File...

  3. TENESOL formerly known as TOTAL ENERGIE | Open Energy Information

    Open Energy Info (EERE)

    search Name: TENESOL (formerly known as TOTAL ENERGIE) Place: la Tour de Salvagny, France Zip: 69890 Sector: Solar Product: Makes polycrystalline silicon modules, and PV-based...

  4. Total Agroindustria Canavieira S A | Open Energy Information

    Open Energy Info (EERE)

    Agroindustria Canavieira S A Jump to: navigation, search Name: Total Agroindustria Canavieira SA Place: Bambui, Minas Gerais, Brazil Product: Ethanol producer in Minas Gerais,...

  5. ,"Crude Oil and Petroleum Products Total Stocks Stocks by Type...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks by Type",6,"Monthly","82015","1151956"...

  6. $787 Million Total in Small Business Contract Funding Awarded...

    National Nuclear Security Administration (NNSA)

    787 Million Total in Small Business Contract Funding Awarded in FY2009 by DOE Programs in Oak Ridge | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS...

  7. ,"Texas Natural Gas Gross Withdrawals Total Offshore (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release...

  8. Refinery & Blender Net Production of Total Finished Petroleum...

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

    & Blender Net Production Product: Total Finished Petroleum Products Liquefied Refinery Gases EthaneEthylene Ethane Ethylene PropanePropylene Propane Propylene Normal Butane...

  9. ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy...

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

    A. Fuel Oil Consumption (Btu) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy Intensity (thousand Btu...

  10. US-CERT Control System Center Input/Output (I/O) Conceputal Design

    SciTech Connect (OSTI)

    Not Available

    2005-02-01

    This document was prepared for the US-CERT Control Systems Center of the National Cyber Security Division (NCSD) of the Department of Homeland Security (DHS). DHS has been tasked under the Homeland Security Act of 2002 to coordinate the overall national effort to enhance the protection of the national critical infrastructure. Homeland Security Presidential Directive HSPD-7 directs the federal departments to identify and prioritize critical infrastructure and protect it from terrorist attack. The US-CERT National Strategy for Control Systems Security was prepared by the NCSD to address the control system security component addressed in the National Strategy to Secure Cyberspace and the National Strategy for the Physical Protection of Critical Infrastructures and Key Assets. The US-CERT National Strategy for Control Systems Security identified five high-level strategic goals for improving cyber security of control systems; the I/O upgrade described in this document supports these goals. The vulnerability assessment Test Bed, located in the Information Operations Research Center (IORC) facility at Idaho National Laboratory (INL), consists of a cyber test facility integrated with multiple test beds that simulate the nation's critical infrastructure. The fundamental mission of the Test Bed is to provide industry owner/operators, system vendors, and multi-agency partners of the INL National Security Division a platform for vulnerability assessments of control systems. The Input/Output (I/O) upgrade to the Test Bed (see Work Package 3.1 of the FY-05 Annual Work Plan) will provide for the expansion of assessment capabilities within the IORC facility. It will also provide capabilities to connect test beds within the Test Range and other Laboratory resources. This will allow real time I/O data input and communication channels for full replications of control systems (Process Control Systems [PCS], Supervisory Control and Data Acquisition Systems [SCADA], and components). This will be accomplished through the design and implementation of a modular infrastructure of control system, communications, networking, computing and associated equipment, and measurement/control devices. The architecture upgrade will provide a flexible patching system providing a quick ''plug and play''configuration through various communication paths to gain access to live I/O running over specific protocols. This will allow for in-depth assessments of control systems in a true-to-life environment. The full I/O upgrade will be completed through a two-phased approach. Phase I, funded by DHS, expands the capabilities of the Test Bed by developing an operational control system in two functional areas, the Science & Technology Applications Research (STAR) Facility and the expansion of various portions of the Test Bed. Phase II (see Appendix A), funded by other programs, will complete the full I/O upgrade to the facility.

  11. Input-output relations at dispersing and absorbing planar multilayers for the quantized electromagnetic field containing evanescent components

    SciTech Connect (OSTI)

    Khanbekyan, Mikayel; Knoell, Ludwig; Welsch, Dirk-Gunnar

    2003-06-01

    By using the Green-function concept of quantization of the electromagnetic field in dispersing and absorbing media, the quantized field in the presence of a dispersing and absorbing dielectric multilayer plate is studied. Three-dimensional input-output relations are derived for both amplitude operators in the k space and the field operators in the coordinate space. The conditions are discussed, under which the input-output relations can be expressed in terms of bosonic operators. The theory applies to both (effectively) free fields and fields, created by active atomic sources inside and/or outside the plate, including also evanescent-field components.

  12. Addressing Uncertainty in Desigh Inputs: A Case Study of Probabilistic Settlement Evaluations for Soft Zone Collapse at SWPF

    Office of Environmental Management (EM)

    Addressing Uncertainties in Design Inputs: A Case Study of Probabilistic Settlement Evaluations for Soft Zone Collapse at SWPF Tom Houston, Greg Mertz, Carl Costantino, Michael Costantino, Andrew Maham Carl J. Costantino & Associates DOE NPH Conference Germantown, Maryland October 25-26 2011 1 CJCAssociates Introduction * Description of the SWPF Settlement Problem * Deterministic v. Probabilistic Approach to Settlement Profile Development * Analysis Approach * Parameters considered *

  13. Addressing Uncertainties in Design Inputs: A Case Study of Probabilistic Settlement Evaluations for Soft Zone Collapse at SWPF

    Broader source: Energy.gov [DOE]

    Addressing Uncertainties in Design Inputs: A Case Study of Probabilistic Settlement Evaluations for Soft Zone Collapse at SWPF Tom Houston, Greg Mertz, Carl Costantino, Michael Costantino, Andrew Maham Carl J. Costantino & Associates DOE NPH Conference Germantown, Maryland October 25-26 2011

  14. Evaluating the efficiency of municipalities in collecting and processing municipal solid waste: A shared input DEA-model

    SciTech Connect (OSTI)

    Rogge, Nicky; De Jaeger, Simon

    2012-10-15

    Highlights: Black-Right-Pointing-Pointer Complexity in local waste management calls for more in depth efficiency analysis. Black-Right-Pointing-Pointer Shared-input Data Envelopment Analysis can provide solution. Black-Right-Pointing-Pointer Considerable room for the Flemish municipalities to improve their cost efficiency. - Abstract: This paper proposed an adjusted 'shared-input' version of the popular efficiency measurement technique Data Envelopment Analysis (DEA) that enables evaluating municipality waste collection and processing performances in settings in which one input (waste costs) is shared among treatment efforts of multiple municipal solid waste fractions. The main advantage of this version of DEA is that it not only provides an estimate of the municipalities overall cost efficiency but also estimates of the municipalities' cost efficiency in the treatment of the different fractions of municipal solid waste (MSW). To illustrate the practical usefulness of the shared input DEA-model, we apply the model to data on 293 municipalities in Flanders, Belgium, for the year 2008.

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

    SciTech Connect (OSTI)

    Blaise Collin

    2014-09-01

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

  16. Efficient Screening of Climate Model Sensitivity to a Large Number of Perturbed Input Parameters [plus supporting information

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

    Covey, Curt; Lucas, Donald D.; Tannahill, John; Garaizar, Xabier; Klein, Richard

    2013-07-01

    Modern climate models contain numerous input parameters, each with a range of possible values. Since the volume of parameter space increases exponentially with the number of parameters N, it is generally impossible to directly evaluate a model throughout this space even if just 2-3 values are chosen for each parameter. Sensitivity screening algorithms, however, can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination.This can aid both model development and the uncertainty quantification (UQ) process. Here we report results from a parameter sensitivity screening algorithm hitherto untested in climate modeling,more » the Morris one-at-a-time (MOAT) method. This algorithm drastically reduces the computational cost of estimating sensitivities in a high dimensional parameter space because the sample size grows linearly rather than exponentially with N. It nevertheless samples over much of the N-dimensional volume and allows assessment of parameter interactions, unlike traditional elementary one-at-a-time (EOAT) parameter variation. We applied both EOAT and MOAT to the Community Atmosphere Model (CAM), assessing CAM’s behavior as a function of 27 uncertain input parameters related to the boundary layer, clouds, and other subgrid scale processes. For radiation balance at the top of the atmosphere, EOAT and MOAT rank most input parameters similarly, but MOAT identifies a sensitivity that EOAT underplays for two convection parameters that operate nonlinearly in the model. MOAT’s ranking of input parameters is robust to modest algorithmic variations, and it is qualitatively consistent with model development experience. Supporting information is also provided at the end of the full text of the article.« less

  17. A9R7296.tmp

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

  18. A9R7298.tmp

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

  19. A9_ISO.PDF

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

  20. A9_iso.PDF

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