National Library of Energy BETA

Sample records for a9 total inputs

  1. Table A55. Number of Establishments by Total Inputs of Energy...

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

    Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity ... Industry","Total(b)","Bed Boilers","Heat Recovery","Turbines","Heat Recovery","Processes",...

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

    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 ...

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

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

    ... produced" "onsite from input materials not classified as energy. Examples of the latter" "are hydrogen produced from the electrolysis of brine; the output of captive" "(onsite) ...

  4. 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

  5. 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

  6. Table A56. 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 Industry-Specific Technologies for Selected Industries, 1994: Part 2" ,,,"RSE" "SIC",,,"Row" "Code(a)","Industry Group and Industry","Total(b)","Factors" ,"RSE Column Factors:",1 20,"FOOD and KINDRED PRODUCTS"

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. Total

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

    Cell shipments Total Inventory, start-of-year 328,658 Manufactured during reporting year ... Table 5. Source and disposition of photovoltaic cell shipments, 2013 (peak kilowatts) ...

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

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

    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

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

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

    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 ...

  18. 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

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

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

    . 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........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to

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

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

    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........................................................... 23.8 3.9 2.4 1.5 1,000 to 1,499..................................................... 20.8 4.4 3.2 1.2 1,500 to 1,999..................................................... 15.4 3.5 2.4 1.1 2,000 to 2,499..................................................... 12.2 3.2 2.1 1.1 2,500 to

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

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

    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

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

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

    4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to

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

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

    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

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

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

    .. 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

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

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

    .. 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

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

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

    Floorspace (Square Feet) Total Floorspace 1 Fewer than 500............................................ 3.2 0.4 Q 0.6 1.7 0.4 500 to 999................................................... 23.8 4.8 1.4 4.2 10.2 3.2 1,000 to 1,499............................................. 20.8 10.6 1.8 1.8 4.0 2.6 1,500 to 1,999............................................. 15.4 12.4 1.5 0.5 0.5 0.4 2,000 to 2,499............................................. 12.2 10.7 1.0 0.2 Q Q 2,500 to

  7. 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.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3

  8. 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........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1

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

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

    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

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

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

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8

  11. Total Blender Net Input of Petroleum Products

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

    - Reformulated, RBOB for Blending w Alcohol MGBC - Reformulated, RBOB for Blending w ... Notes: RBOB with Ether, RBOB with Alcohol, and Reformulated GTAB Motor Gasoline Blending ...

  12. Minnesota Natural Gas Input Supplemental Fuels (Million Cubic...

    Gasoline and Diesel Fuel Update (EIA)

    Input Supplemental Fuels (Million Cubic Feet) Minnesota Natural Gas Input Supplemental ... Total Supplemental Supply of Natural Gas Minnesota Supplemental Supplies of Natural Gas ...

  13. Refiner Crude Oil Inputs

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

    Data Series: Refiner Crude Oil Inputs Refiner Gross Inputs Refiner Operable Capacity ... Download Series History Download Series History Definitions, Sources & Notes Definitions, ...

  14. 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

  15. U.S. Total Weekly Inputs & Utilization

    Gasoline and Diesel Fuel Update (EIA)

    Crude Oil and Petroleum Products 1,794,099 1,750,087 1,807,777 1,761,373 1,859,514 2,014,788 1956-2015 Crude Oil 1,059,975 1,026,630 1,060,764 1,053,032 1,084,300 1,176,487 1913-2015 All Oils (Excluding Crude Oil) 734,124 723,457 747,013 708,341 775,214 838,301 1993-2015 Pentanes Plus 12,510 17,596 12,739 14,471 20,608 20,543 1981-2015 Liquefied Petroleum Gases 108,272 111,778 140,529 113,954 154,756 176,730 1967-2015 Ethane/Ethylene 24,323 22,892 35,396 30,818 34,863 33,928 1967-2015

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

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

    3,070 2,749 2,923 2005-2015 PADD 2 65,167 70,767 68,865 61,444 54,690 59,836 2005-2015 Ind., Ill. and Ky. 39,434 44,601 42,709 39,206 34,355 39,460 2005-2015 Minn., Wis., N....

  17. 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 ...

  18. Influential input classification in probabilistic multimedia models

    SciTech Connect (OSTI)

    Maddalena, Randy L.; McKone, Thomas E.; Hsieh, Dennis P.H.; Geng, Shu

    1999-05-01

    Monte Carlo analysis is a statistical simulation method that is often used to assess and quantify the outcome variance in complex environmental fate and effects models. Total outcome variance of these models is a function of (1) the uncertainty and/or variability associated with each model input and (2) the sensitivity of the model outcome to changes in the inputs. To propagate variance through a model using Monte Carlo techniques, each variable must be assigned a probability distribution. The validity of these distributions directly influences the accuracy and reliability of the model outcome. To efficiently allocate resources for constructing distributions one should first identify the most influential set of variables in the model. Although existing sensitivity and uncertainty analysis methods can provide a relative ranking of the importance of model inputs, they fail to identify the minimum set of stochastic inputs necessary to sufficiently characterize the outcome variance. In this paper, we describe and demonstrate a novel sensitivity/uncertainty analysis method for assessing the importance of each variable in a multimedia environmental fate model. Our analyses show that for a given scenario, a relatively small number of input variables influence the central tendency of the model and an even smaller set determines the shape of the outcome distribution. For each input, the level of influence depends on the scenario under consideration. This information is useful for developing site specific models and improving our understanding of the processes that have the greatest influence on the variance in outcomes from multimedia models.

  19. Prioritization Tool Measurement Input Form

    Broader source: Energy.gov [DOE]

    BTO encourages stakeholders to recommend updates and improvements to the Prioritization Tool by using the below Measure Input Form.

  20. 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...

  1. Country Total

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

    Country Total Percent of U.S. total China 1,461,074 34 Republic of Korea 172,379 4 Taiwan 688,311 16 All others 1,966,263 46 Total 4,288,027 100 Note: All Others includes Canada, Czech Republic, Federal Republic of Germany, Malaysia, Mexico, Philippines and Singapore Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.' Table 7 . Photovoltaic module import shipments by country, 2013 (peak kilowatts)

  2. Appendix A Scoping Input Appendix ...

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

    Species Act Correspondence with the U.S. Fish & Wildlife Service Appendix F Section 106 ... December 13, 2013. The following input was received during the Scoping period: * U.S. Fish ...

  3. State Total

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

    State Total Percent of U.S. total Alabama 1,652 0.0 Alaska 152 0.0 Arizona 912,975 19.9 Arkansas 2,724 0.1 California 2,239,983 48.8 Colorado 49,903 1.1 Connecticut 33,627 0.7 Delaware 3,080 0.1 District of Columbia 1,746 0.0 Florida 22,061 0.5 Georgia 99,713 2.2 Guam 39 0.0 Hawaii 126,595 2.8 Idaho 1,423 0.0 Illinois 8,176 0.2 Indiana 12,912 0.3 Iowa 4,480 0.1 Kansas 523 0.0 Kentucky 2,356 0.1 Louisiana 27,704 0.6 Maine 993 0.0 Maryland 30,528 0.7 Massachusetts 143,539 3.1 Michigan 3,416 0.1

  4. 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

  5. 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....

  6. U.S. Blender Net Input

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

    Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History Total Input 248,620 258,292 242,060 252,467 242,396 238,655 2005-2016 Natural Gas Plant Liquids and Liquefied Refinery Gases 1,681 2,789 2,599 2,073 2,044 1,531 2008-2016 Pentanes Plus 111 413 479 223 489 347 2005-2016 Liquid Petroleum Gases 1,570 2,376 2,120 1,850 1,555 1,184 2008-2016 Normal Butane 1,563 2,376 2,120 1,850 1,555 1,184 2005-2016 Isobutane 7 2005-2015 Other Liquids 246,939 255,503 239,461 250,394 240,352 237,124 2008-2016

  7. U.S. Weekly Inputs & Utilization

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

    Data Series Area 031116 031816 032516 040116 040816 041516 View History Refiner Inputs and Utilization Crude Oil Inputs 15,996 15,820 16,234 16,433 15,941 16,104 ...

  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: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Total Supplemental Supply of Natural Gas Louisiana Supplemental Supplies of

  10. Categorical Exclusion Determinations: A9 | Department of Energy

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

    publication and distribution, and classroom training and informational programs), ... CX(s) Applied: A9 Federal Energy Management Program Date: 04132016 Location(s): ...

  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. ,"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...

  13. 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.

  14. ,"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...

  15. ,"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...

  16. 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...

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

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

    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 ...

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

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

    ... W ",518," W ",39,654,466,9.2 3312," Blast Furnaces and Steel Mills",1824,148,42," W ",476," W ",35,654,464,7.6 3313," Electrometallurgical Products",23,16,0," * ...

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

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

    ... Products",1907," W "," W ",50,176,114,1514,10.2 3312," Blast Furnaces and Steel Mills",1824," W "," W ",40,159,110,1503,9.3 3313," Electrometallurgical Products",23,2,14," Q "," Q ...

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

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

    ... 3321," Gray and Ductile Iron Foundries",74,3,3,"W","W",13,27,10.3 3331," Primary Copper",22,"*",0,"W","W",16,0,1.1 3334," Primary Aluminum",252,"*","*","*","W",148,"W",4 ...

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

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

    ...,4,144,28,105,5,859,1,11.4 3331," Primary Copper",22,1246,"W","W",15,3,"W",0,1,1.1 3334," ...50,0,13,2,18,1,67,"*",16.5 3331," Primary Copper","*","W",0,"W","*","*",0,0,"*",1.1 3334," ...

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

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

    ... 3321," Gray and Ductile Iron Foundries","74 ","W",15,17,13,"W",0,8.5 3331," Primary Copper","22 ","W",0,"*","W",12,"W",1 3334," Primary Aluminum","252 ","*","*",0,112,"W","W",3....

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

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

    ",0.6,1.3,1.3,0.7,1.2,1.2,1.6,1.2 , 20,"Food and Kindred Products",953,169,27,17,512,5,... ",0.7,1,1.2,0.8,1.2,1.3,1.3,1.1 , 20,"Food and Kindred Products",79,18,7,5,42,1,2,0,3...

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

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

    "One or More General Technologies Present",14601,387,781,2054,2728,3189,5462,3.1 " Computer Control of Building Environment (b)",5079,64,116,510,802,1227,2361,5 " Computer Control ...

  6. Table A54. Number of Establishments by Total Inputs of Energy...

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

    ,," "," ",," "," ",," "," "," "," " ,,,,"Computer Control" ,," "," ","of Processes"," "," ",," "," ",," " ,," ","Computer Control","or Major",,,"One or More"," ","RSE" "SIC"," ...

  7. 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.

  8. 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.

  9. ,"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...

  10. 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.

  11. 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

  12. 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: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Total Supplemental Supply of Natural Gas Alaska Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual

  13. Midwest (PADD 2) Weekly Inputs & Utilization

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

    3,290 3,276 3,258 3,350 3,411 3,475 1992-2016 Gross Inputs 3,294 3,279 3,262 3,353 3,414 3,478 1990-2016 Operable Capacity (Calendar Day) 3,882 3,893 3,904 3,915 3,922 3,922 2010-2016 Percent Operable Utilization 84.9 84.3 83.6 85.7 87.0 88.7 2010-2016 Refiner and Blender Net Inputs Motor Gasoline Blending Components 416 444 485 464 486 472 2010-2016 RBOB 51 57 69 56 60 67 2010-2016 CBOB 290 327 361 373 396 348 2010-2016 GTAB 0 0 0 0 0 0 2010-2016 All Other 75 60 55 35 30 56 2010-2016 Fuel

  14. 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

  15. ,"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...

  16. ,"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...

  17. ,"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"...

  18. 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...

  19. ,"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...

  20. ,"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...

  1. 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...

  2. 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*...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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 ...

  10. 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

  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. 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

  13. Country/Continent Total

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

    peak kilowatts) Country/Continent Total Percent of U.S. total Africa 14,279 3.7 Asia/Australia 330,200 86.2 Europe 19,771 5.1 South/Central America 7,748 2.0 Canada 5,507 1.4 Mexico 5,747 1.5 Total 383,252 100.0 Table 8. Destination of photovoltaic module export shipments, 2013 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.'

  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. PADD 3 Weekly Inputs & Utilization

    Gasoline and Diesel Fuel Update (EIA)

    8,932 8,698 8,654 8,467 8,531 8,502 1992-2016 Gross Inputs 8,973 8,796 8,658 8,607 8,811 8,490 1990-2016 Operable Capacity (Calendar Day) 9,437 9,437 9,437 9,512 9,512 9,512 2010-2016 Percent Operable Utilization 95.1 93.2 91.7 90.5 92.6 89.3 2010-2016 Refiner and Blender Net Inputs Motor Gasoline Blending Components -2,198 -2,086 -2,262 -2,381 -2,286 -2,129 2004-2016 RBOB -454 -429 -442 -405 -342 -355 2010-2016 CBOB -1,777 -1,684 -1,862 -1,882 -1,896 -1,869 2004-2016 GTAB 0 0 0 0 0 0 2004-2016

  17. 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

  18. Total DOE/NNSA

    National Nuclear Security Administration (NNSA)

    8 Actuals 2009 Actuals 2010 Actuals 2011 Actuals 2012 Actuals 2013 Actuals 2014 Actuals 2015 Actuals Total DOE/NNSA 4,385 4,151 4,240 4,862 5,154 5,476 7,170 7,593 Total non-NNSA 3,925 4,017 4,005 3,821 3,875 3,974 3,826 3765 Total Facility 8,310 8,168 8,245 8,683 9,029 9,450 10,996 11,358 non-NNSA includes DOE offices and Strategic Parternship Projects (SPP) employees NNSA M&O Employee Reporting

  19. 21 briefing pages total

    Energy Savers [EERE]

    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

  20. 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...

  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...

  2. 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 -...

  3. Clean Energy Investment Center Seeks Input to Enhance Its Services...

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

    Clean Energy Investment Center Seeks Input to Enhance Its Services Clean Energy Investment Center Seeks Input to Enhance Its Services March 2, 2016 - 9:21am Addthis On March 1, the ...

  4. 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,...

  5. Arizona Natural Gas Input Supplemental Fuels (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

    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...

  6. Developing a low input and sustainable switchgrass feedstock...

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

    switchgrass feedstock production system utilizing beneficial bacterial endophytes Developing a low input and sustainable switchgrass feedstock production system utilizing ...

  7. 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).

  8. 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.

  9. 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.

  10. 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.

  11. 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)

  12. 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.

  13. 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

  14. 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

  15. 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

  16. U.S. Refinery Net Input

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

    Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History Total 321,878 318,765 321,561 328,213 302,955 290,718 2005-2016 Crude Oil 485,221 479,416 494,682 519,726 495,806 460,629 2005-2016 Natural Gas Plant Liquids 14,690 15,903 17,686 18,057 18,673 14,924 2005-2016 Pentanes Plus 4,693 4,431 3,897 3,932 4,389 3,616 2005-2016 Liquefied Petroleum Gases 9,997 11,472 13,789 14,125 14,284 11,308 2005-2016 Normal Butane 3,144 5,323 7,093 7,560 7,947 5,592 2005-2016 Isobutane 6,853 6,149 6,696 6,565

  17. 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.

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

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

    Weighted Average Refinery Crude Oil Input Qualities",16,"Monthly","22016","1151985" ,"Release Date:","4292016" ,"Next Release Date:","5312016" ,"Excel File ...

  20. ,"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...

  1. 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...

  2. 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.

  3. 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.

  4. 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:

  5. 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...

  6. Wavelength meter having single mode fiber optics multiplexed inputs

    DOE Patents [OSTI]

    Hackel, Richard P.; Paris, Robert D.; Feldman, Mark

    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.

  7. 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.

  8. Total

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

    Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm Sulfur and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Sulfur Distillate Fuel Oil, Greater than 500 ppm ...

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

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

    5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units ...

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

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

    111.1 86.6 2,720 1,970 1,310 1,941 1,475 821 1,059 944 554 Census Region and Division Northeast.................................... 20.6 13.9 3,224 2,173 836 2,219 1,619 583 903 830 Q New England.......................... 5.5 3.6 3,365 2,154 313 2,634 1,826 Q 951 940 Q Middle Atlantic........................ 15.1 10.3 3,167 2,181 1,049 2,188 1,603 582 Q Q Q Midwest...................................... 25.6 21.0 2,823 2,239 1,624 2,356 1,669 1,336 1,081 961 778 East North

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

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

    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

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

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

    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

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

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

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

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

    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..............................

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

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

    ,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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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 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

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

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

    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

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

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

    111.1 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Do Not Have Space Heating Equipment....... 1.2 0.5 0.3 0.2 Q 0.2 0.3 0.6 Have Main Space Heating Equipment.......... 109.8 26.2 28.5 20.4 13.0 21.8 16.3 37.9 Use Main Space Heating Equipment............ 109.1 25.9 28.1 20.3 12.9 21.8 16.0 37.3 Have Equipment But Do Not Use It.............. 0.8 0.3 0.3 Q Q N 0.4 0.6 Main Heating Fuel and Equipment Natural Gas.................................................. 58.2 12.2 14.4 11.3 7.1 13.2 7.6 18.3 Central

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

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

    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

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

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

    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

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

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

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day.............................. 8.2 2.9 2.5 1.3 0.5 1.0 2.4 4.6 2 Times A Day........................................... 24.6 6.5 7.0 4.3 3.2 3.6 4.8 10.3 Once a Day................................................ 42.3 8.8 9.8 8.7 5.1 10.0 5.0 12.9 A Few Times Each Week........................... 27.2 5.6 7.2 4.7 3.3 6.3 3.2 7.5 About Once a Week................................... 3.9 1.1 1.1

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

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

    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

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

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

    . 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

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

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

    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

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

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

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    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

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

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.0 1.6 0.3 1.1 2 Times A Day.............................................................. 24.6 8.3 4.2 1.3 2.7 Once a Day................................................................... 42.3 15.0 8.1 2.7 4.2 A Few Times Each Week............................................. 27.2 10.9 6.0 1.8 3.1 About Once a Week..................................................... 3.9

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

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

    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

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

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

    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

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

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.7 1.6 1.4 1.5 2 Times A Day.............................................................. 24.6 10.8 4.1 4.3 5.5 Once a Day................................................................... 42.3 17.0 7.2 8.7 9.3 A Few Times Each Week............................................. 27.2 11.4 4.7 6.4 4.8 About Once a Week.....................................................

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

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

    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

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

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

    ..... 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

  19. Total

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

    Administration, Form EIA-63B, 'Annual Photovoltaic CellModule Shipments Report.'rounding. ... Form EIA-63B, 'Annual Photovoltaic CellModule Shipments Report.' CellModule ...

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

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

    ... 41.8 2,603 2,199 1,654 941 795 598 1-Car Garage...... 9.5 2,064 1,664 1,039 775 624 390 2-Car Garage......

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

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

    ... Type of Glass in Windows Single-pane Glass...... 27.4 ... Q Q N Q N N Proportion of Windows Replaced All......

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

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

    ... Type of Glass in Windows Single-pane Glass......Q Q Q Q Proportion of Windows Replaced All......

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

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 25.8 10.9 16.6 12.5 Without a Heat Pump......

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

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 6.0 17.3 32.1 10.5 Without a Heat Pump......

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

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

    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 ...

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

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump......

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

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

    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 ...

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

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

    ... 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 ...

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

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

    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 ...

  10. 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...

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

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

    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 ...

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

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

    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

  13. T-623: HP Business Availability Center Input Validation Hole Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

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

  14. 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

  15. Determination of Total Solids in Biomass and Total Dissolved...

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

    ... The published moisture loss on drying for sodium tartrate is 15.62% (84.38% total solids). 14.6 Sample size: Determined by sample matrix. 14.7 Sample storage: Samples should be ...

  16. 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.

  17. 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 Thursday, March 26, 2015. This will be provided by Rogue Wave Software staff members. The training will include a lecture and demo sessions in the morning, followed by a hands-on parallel debugging session in the afternoon. Location This event will be presented online using WebEx technology and in person at NERSC Oakland

  18. 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

  19. 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:

  20. 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

  1. 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" 2014 "January",35.75,,72.72,,"W",,"W",,273,,"W",,2,,15

  2. 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.

  3. 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

  4. 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

  5. Significance of microbial asynchronous anabolism to soil carbon dynamics driven by litter inputs

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

    Fan, Zhaosheng; Liang, Chao

    2015-04-02

    Soil organic carbon (SOC) plays an important role in the global carbon cycle. However, it remains largely unknown how plant litter inputs impact magnitude, composition and source configuration of the SOC stocks over long term through microbial catabolism and anabolism, mostly due to uncoupled research on litter decomposition and SOC formation. This limits our ability to predict soil system responses to changes in land-use and climate. Here, we examine how microbes act as a valve controlling carbon sequestrated from plant litters versus released to the atmosphere in natural ecosystems amended with plant litters varying in quantity and quality. We findmore » that litter quality – not quantity – regulates long-term SOC dynamics under different plausible scenarios. Long-term changes in bulk SOC stock occur only when the quality of carbon inputs causes asynchronous change in a microbial physiological trait, defined as ‘‘microbial biosynthesis acceleration’’ (MBA). This is the first theoretical demonstration that the response of the SOC stocks to litter inputs is critically determined by the microbial physiology. Our work suggests that total SOC at an equilibrium state may be an intrinsic property of a given ecosystem, which ultimately is controlled by the asynchronous MBA between microbial functional groups.« less

  6. Significance of microbial asynchronous anabolism to soil carbon dynamics driven by litter inputs

    SciTech Connect (OSTI)

    Fan, Zhaosheng; Liang, Chao

    2015-04-02

    Soil organic carbon (SOC) plays an important role in the global carbon cycle. However, it remains largely unknown how plant litter inputs impact magnitude, composition and source configuration of the SOC stocks over long term through microbial catabolism and anabolism, mostly due to uncoupled research on litter decomposition and SOC formation. This limits our ability to predict soil system responses to changes in land-use and climate. Here, we examine how microbes act as a valve controlling carbon sequestrated from plant litters versus released to the atmosphere in natural ecosystems amended with plant litters varying in quantity and quality. We find that litter quality – not quantity – regulates long-term SOC dynamics under different plausible scenarios. Long-term changes in bulk SOC stock occur only when the quality of carbon inputs causes asynchronous change in a microbial physiological trait, defined as ‘‘microbial biosynthesis acceleration’’ (MBA). This is the first theoretical demonstration that the response of the SOC stocks to litter inputs is critically determined by the microbial physiology. Our work suggests that total SOC at an equilibrium state may be an intrinsic property of a given ecosystem, which ultimately is controlled by the asynchronous MBA between microbial functional groups.

  7. 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...

  8. U.S. Total Exports

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

    CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass, TX El Paso, TX Freeport, TX Hidalgo, TX Laredo, TX McAllen, TX Penitas, TX Rio Bravo, TX Rio Grande, TX Roma, TX Total ...

  9. 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...

  10. 2014 Total Electric Industry- Customers

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

    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 ...

  11. "2014 Total Electric Industry- Customers"

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

    Customers" "(Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",6243013,8...

  12. DOE Seeks Industry Input on Nickel Disposition Strategy

    Broader source: Energy.gov [DOE]

    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.

  13. Fee Determinations: Requirement to Obtain Acquisition Executive's Input

    Broader source: Energy.gov [DOE]

    On January 28, 2013, the Deputy Secretary issued the attached memorandum to the Department's senior officials requiring any Fee Determining Official whose contract falls under the cognizance of an Acquisition Executive to brief and obtain the input of that Acquisition Executive before determining earned fee under the contract.

  14. CATEGORY Total Procurement Total Small Business Small Disadvantaged

    National Nuclear Security Administration (NNSA)

    CATEGORY Total Procurement Total Small Business Small Disadvantaged Business Woman Owned Small Business HubZone Small Business Veteran-Owned Small Business Service Disabled Veteran Owned Small Business FY 2013 Dollars Accomplished $1,049,087,940 $562,676,028 $136,485,766 $106,515,229 $12,080,258 $63,473,852 $28,080,960 FY 2013 % Accomplishment 54.40% 13.00% 10.20% 1.20% 6.60% 2.70% FY 2014 Dollars Accomplished $868,961,755 $443,711,175 $92,478,522 $88,633,031 $29,867,820 $43,719,452 $26,826,374

  15. 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:

  16. 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: 4/29/2016 Next

  17. 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: 4/29/2016 Next

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

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

    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 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 0 1 14 2 9 19 4 4 9 1990's 1,240 1,076 1 3 1 1 0 0 0 17 2000's 0 1,505 2 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: 4/29/2016 Next Release

  19. 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: 4/29/2016 Next Release Date:

  20. 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: 4/29/2016 Next

  1. 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: 4/29/2016 Next Release Date:

  2. 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: 4/29/2016 Next Release Date:

  3. 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: 4/29/2016

  4. 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: 4/29/2016

  5. 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: 4/29/2016 Next Release Date:

  6. 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 =

  7. 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 =

  8. 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

  9. 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:

  10. 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;

  11. 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: 4/29/2016 Next Release Date:

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

    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 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 3,226 4,722 2,350 1,646 1,792 1,797 707 416 728 1,239 1990's 385 678 1,190 1,638 1,460 1,490 1,259 881 699 459 2000's 858 970 1 18 8 14 4 13 7 6 2010's 2 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

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

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

    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 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 42 58 59 60 43 43 0 0 0 1990's 0 0 2 4 3 0 0 0 0 21 2000's 2 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: 4/29/2016 Next

  14. 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

  15. 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 =

  16. 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: 4/29/2016 Next Release Date:

  17. 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

  18. 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: 4/29/2016 Next

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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: 4/29/2016 Next Release Date:

  4. 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.

  5. 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: 4/29/2016 Next

  6. 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: 4/29/2016 Next

  7. 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.

  8. HEAT INPUT AND POST WELD HEAT TREATMENT EFFECTS ON

    Office of Scientific and Technical Information (OSTI)

    INPUT AND POST WELD HEAT TREATMENT EFFECTS ON REDUCED-ACTIVATION FERRITIC/MARTENSITIC STEEL FRICTION STIR WELDS Wei Tang, Jian Chen, Xinghua Yu, David A. Frederick, Zhili Feng Oak Ridge National Laboratory, Oak Ridge, TN Keywords: Eurofer'97, friction stir welding, microstructure, microhardness Abstract 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

  9. 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.

  10. Method of validating measurement data of a process parameter from a plurality of individual sensor inputs

    DOE Patents [OSTI]

    Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

    1998-01-01

    A method for generating a validated measurement of a process parameter at a point in time by using a plurality of individual sensor inputs from a scan of said sensors at said point in time. The sensor inputs from said scan are stored and a first validation pass is initiated by computing an initial average of all stored sensor inputs. Each sensor input is deviation checked by comparing each input including a preset tolerance against the initial average input. If the first deviation check is unsatisfactory, the sensor which produced the unsatisfactory input is flagged as suspect. It is then determined whether at least two of the inputs have not been flagged as suspect and are therefore considered good inputs. If two or more inputs are good, a second validation pass is initiated by computing a second average of all the good sensor inputs, and deviation checking the good inputs by comparing each good input including a present tolerance against the second average. If the second deviation check is satisfactory, the second average is displayed as the validated measurement and the suspect sensor as flagged as bad. A validation fault occurs if at least two inputs are not considered good, or if the second deviation check is not satisfactory. In the latter situation the inputs from each of all the sensors are compared against the last validated measurement and the value from the sensor input that deviates the least from the last valid measurement is displayed.

  11. 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)

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

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

    Energy 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. Total Imports of Residual Fuel

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

    Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S. Total 7,281 4,217 5,941 6,842 9,010 5,030 1936-2016 PAD District 1 4,571 2,206 2,952 3,174 3,127 2,664 1981-2016 Connecticut 1995-2015 Delaware 678 85 1995-2015 Florida 351 299 932 836 858 649 1995-2016 Georgia 120 295 210 262 1995-2016 Maine 1995-2015 Maryland 1995-2015 Massachusetts 1995-2015 New Hampshire 1995-2015 New Jersey 1,575 400 1,131 1,712 1,283 843 1995-2016 New York 1,475 998 350 322 234 824 1995-2016 North Carolina

  19. 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.

  20. MULTIPLE INPUT BINARY ADDER EMPLOYING MAGNETIC DRUM DIGITAL COMPUTING APPARATUS

    DOE Patents [OSTI]

    Cooke-Yarborough, E.H.

    1960-12-01

    A digital computing apparatus is described for adding a plurality of multi-digit binary numbers. The apparatus comprises a rotating magnetic drum, a recording head, first and second reading heads disposed adjacent to the first and second recording tracks, and a series of timing signals recorded on the first track. A series of N groups of digit-representing signals is delivered to the recording head at time intervals corresponding to the timing signals, each group consisting of digits of the same significance in the numbers, and the signal series is recorded on the second track of the drum in synchronism with the timing signals on the first track. The multistage registers are stepped cyclically through all positions, and each of the multistage registers is coupled to the control lead of a separate gate circuit to open the corresponding gate at only one selected position in each cycle. One of the gates has its input coupled to the bistable element to receive the sum digit, and the output lead of this gate is coupled to the recording device. The inputs of the other gates receive the digits to be added from the second reading head, and the outputs of these gates are coupled to the adding register. A phase-setting pulse source is connected to each of the multistage registers individually to step the multistage registers to different initial positions in the cycle, and the phase-setting pulse source is actuated each N time interval to shift a sum digit to the bistable element, where the multistage register coupled to bistable element is operated by the phase- setting pulse source to that position in its cycle N steps before opening the first gate, so that this gate opens in synchronism with each of the shifts to pass the sum digits to the recording head.

  1. ,"West Virginia Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","West Virginia Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: West Virginia Natural Gas Total Consumption (MMcf)" ...

  2. ,"New Mexico Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","New Mexico Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: New Mexico Natural Gas Total Consumption (MMcf)" ...

  3. ARM - Measurement - Shortwave broadband total downwelling irradiance

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

    Measurement : Shortwave broadband total downwelling irradiance The total diffuse and direct radiant energy that comes from some continuous range of directions, at wavelengths ...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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.

  13. 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...

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

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

    Seeks Stakeholder Input on 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 - ...

  15. 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.

  16. 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.

  17. 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.

  18. 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...

  19. Million Cu. Feet Percent of National Total

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

    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

  20. Million Cu. Feet Percent of National Total

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

    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

  1. Million Cu. Feet Percent of National Total

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

    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

  2. Million Cu. Feet Percent of National Total

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

    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

  3. Million Cu. Feet Percent of National Total

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

    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

  4. Total System Performance Assessment Peer Review Panel

    Broader source: Energy.gov [DOE]

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

  5. 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.

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

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

    Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History Catalytic Reforming 2,837 2,690 2,748 2,812 2,668 2,629 2010-2016 Catalytic Cracking 5,000 4,572 4,831 4,892 4,989 4,767 1987-2016 Catalytic Hydrocracking 1,723 1,721 1,806 1,864 1,639 1,697 1987-2016 Delayed and Fluid Coking 2,333 2,293 2,509 2,537 2,393 2,378 1987-2016 - = 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

  7. U.S. Refinery & Blender Net Input

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

    Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History Total 570,498 577,057 563,621 580,680 545,351 529,373 1981-2016 Crude Oil 485,221 479,416 494,682 519,726 495,806 460,629 1981-2016 Natural Gas Plant Liquids and Liquefied Refinery Gases 16,371 18,692 20,285 20,130 20,717 16,455 1981-2016 Pentanes Plus 4,804 4,844 4,376 4,155 4,878 3,963 1981-2016 Liquefied Petroleum Gases 11,567 13,848 15,909 15,975 15,839 12,492 1981-2016 Ethane 1981-1992 Normal Butane 4,707 7,699 9,213 9,410 9,502 6,776

  8. 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 5,915,532 1981-2015 Natural Gas Plant Liquids and Liquefied Refinery Gases 161,479 178,884 186,270 181,112 186,601 188,270 1981-2015 Pentanes Plus 56,686 63,385 63,596 60,394 56,037 53,404 1981-2015 Liquefied Petroleum Gases 104,793 115,499 122,674 120,718 130,564 134,866 1981-2015 Ethane 1981-1992 Normal Butane 43,802

  9. 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.

  10. 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

  11. BETO Seeks Stakeholder Input on the Use of Advanced Biofuel Blends in Small

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

    Engines | Department of Energy Seeks Stakeholder Input on 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. 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. DOE Seeking Input on Alternative Uses of Nickel Inventory | Department of

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

    Energy Seeking Input on Alternative Uses of Nickel Inventory DOE Seeking Input on Alternative Uses of Nickel Inventory March 9, 2007 - 10:28am Addthis WASHINGTON, DC - The U.S. Department of Energy (DOE) is seeking input from industry representatives on the safe disposition of approximately 15,300 tons of nickel scrap recovered from uranium enrichment process equipment at the Department's Oak Ridge, TN, and Paducah, KY, facilities. The Expression of Interest (EOI), released today, will

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

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

    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

  14. 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

  15. 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

  16. 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.

  17. BETO Seeks Stakeholder Input on Achieving High Yields from Algal Feedstocks

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

    | Department of Energy Seeks Stakeholder Input on Achieving High Yields from Algal Feedstocks BETO Seeks Stakeholder Input on Achieving High Yields from Algal Feedstocks September 3, 2015 - 4:09pm Addthis The U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy's 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,

  18. 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.

  19. Summary of Input to DOE Request for Information DE-FOA-0000225

    Broader source: Energy.gov [DOE]

    Presentation on Sumary of Input to DOE Request for Information DE-FOA-0000225 - U.S. DOE Fuel Cells Technology Program

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

    Office of Scientific and Technical Information (OSTI)

    are an important class of structural materials for fusion reactor internals developed ... among welding heat input, weld structure characterization and mechanical properties. ...

  1. [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`.

  2. Role of the nonperturbative input in QCD resummed Drell-Yan Q...

    Office of Scientific and Technical Information (OSTI)

    SciTech Connect Search Results Journal Article: Role of the nonperturbative input in QCD ... Sponsoring Org: (US) Country of Publication: United States Language: English Subject: 71 ...

  3. 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.

  4. 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 ...

  5. Million Cu. Feet Percent of National Total

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

    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

  6. Million Cu. Feet Percent of National Total

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

    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

  7. Million Cu. Feet Percent of National Total

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

    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

  8. Million Cu. Feet Percent of National Total

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

    4 Hawaii - 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 S13. Summary statistics for natural gas - Hawaii, 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

  9. Million Cu. Feet Percent of National Total

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

    6 Idaho - 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 S14. Summary statistics for natural gas - Idaho, 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

  10. Million Cu. Feet Percent of National Total

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

    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

  11. Million Cu. Feet Percent of National Total

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

    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

  12. Million Cu. Feet Percent of National Total

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

    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

  13. Million Cu. Feet Percent of National Total

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

    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

  14. Million Cu. Feet Percent of National Total

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

    Total Net Movements: - Industrial: Dry Production: Vehicle ... due to independent rounding. Prices are in nominal dollars. ... Annual Consumption per Consumer (thousand cubic feet) ...

  15. Million Cu. Feet Percent of National Total

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

    from Electric Power to Industrial for years 2002 through ... Totals may not add due to independent rounding. Prices are ... Annual Consumption per Consumer (thousand cubic feet) ...

  16. Total Natural Gas Underground Storage Capacity

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

    Storage Capacity Salt Caverns Storage Capacity Aquifers Storage Capacity Depleted Fields Storage Capacity Total Working Gas Capacity Working Gas Capacity of Salt Caverns Working...

  17. ARM - Measurement - Shortwave narrowband total downwelling irradiance

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

    Send Measurement : Shortwave narrowband total downwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 mum, passes ...

  18. ARM - Measurement - Shortwave narrowband total upwelling irradiance

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

    Send Measurement : Shortwave narrowband total upwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 mum, passes ...

  19. ARM - Measurement - Shortwave spectral total downwelling irradiance

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

    Send Measurement : Shortwave spectral total downwelling irradiance The rate at which radiant energy, at specrally-resolved wavelengths between 0.4 and 4 mum, is being emitted ...

  20. 2014 Total Electric Industry- Sales (Megawatthours

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

    EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",47211525,53107038,19107433,557463,119983459 "Connecticut",12777579,12893531,351479...

  1. Total Supplemental Supply of Natural Gas

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

    Product: Total Supplemental Supply Synthetic Propane-Air Refinery Gas Biomass Other Period: Monthly Annual Download Series History Download Series History Definitions, Sources & ...

  2. 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...

  3. Million Cu. Feet Percent of National Total

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

    8 Minnesota - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet ... Summary statistics for natural gas - Minnesota, 2010-2014 2010 2011 2012 2013 2014 ...

  4. 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...

  5. Million Cu. Feet Percent of National Total

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

    Totals may not add due to independent rounding. Prices are ... 250,994 253,127 Industrial 9,332 9,088 8,833 8,497 8,156 Average Annual Consumption per Consumer (thousand cubic ...

  6. Million Cu. Feet Percent of National Total

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

    Notes: Totals may not add due to independent rounding. Prices ... 34,078 34,283 34,339 Industrial 102 94 97 95 92 Average Annual Consumption per Consumer (thousand cubic feet) ...

  7. 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...

  8. 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...

  9. ARM - Measurement - Shortwave broadband total upwelling irradiance

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

    Send Measurement : Shortwave broadband total upwelling irradiance The rate at which radiant energy, at a wavelength between 0.4 and 4 mum, is being emitted upwards into a ...

  10. "2014 Total Electric Industry- Revenue (Thousands Dollars)"

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

    EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",8414175.4,7806276.7,2262752.4,57837.4,18541041.8 "Connecticut",2523348.7,2004629.1...

  11. 2014 Total Electric Industry- Revenue (Thousands Dollars)

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

    Revenue (Thousands Dollars) (Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 8,414,175 ...

  12. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. ... 2,314 764 719 180 4,046 Supplemental Gas Supplies 732 701 660 642 635 Balancing Item ...

  13. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. ... 3,762 7,315 10,303 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item 65,897 -19,970 ...

  14. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. ... 473 526 484 626 1,359 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -6,645 3,976 ...

  15. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S31. ... 35 108 71 124 185 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -1,393 -3,726 ...

  16. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S51. ... 92 87 100 89 138 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -2,885 -12,890 ...

  17. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. ... 76 96 66 131 128 Supplemental Gas Supplies 1 0 * * 6 Balancing Item 3,249 7,362 ...

  18. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S17. ... 1,844 980 2,403 2,701 Supplemental Gas Supplies 2 1 0 0 1 Balancing Item -1,989 -7,914 ...

  19. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. ... 4,404 3,278 5,208 6,218 Supplemental Gas Supplies 457 392 139 255 530 Balancing Item ...

  20. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S41. ... 698 436 457 645 879 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -1,269 1,045 ...

  1. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S47. ... 0 LNG Storage 0 0 0 0 0 Supplemental Gas Supplies 1 2 3 3 5 Balancing Item -453 -1,711 ...

  2. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S30. ... 195 154 146 210 211 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item 17,590 4,622 ...

  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. 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...

  5. 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...

  6. 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 ...

  7. 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.

  8. 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).

  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. Microsoft PowerPoint - OTT RFI Summary of Input_Public_Oct 2015

    Energy Savers [EERE]

    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

  11. 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

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

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

    Biofuels for Military and Commercial Transportation | Department of Energy 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 today

  13. 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

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

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

    Regulations | Department of Energy Further Public Input on How Best To Streamline Existing Regulations 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 implementing the President's Executive Order on Improving Regulatory Review. The Executive Order directs federal agencies to review existing regulations and determine whether they are still necessary and crafted

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

    Energy Savers [EERE]

    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

  16. Table A14. Total First Use (formerly Primary Consumption)...

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

    ... produced" "onsite from input materials not classified as energy. Examples of the latter" "are hydrogen produced from the electrolysis of brine; the output of captive" "(onsite) ...

  17. Table A22. Total First Use (formerly Primary Consumption)...

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

    ... produced onsite from input materials not" "classified as an energy. Examples of the latter are hydrogen produced from the" "electrolysis of brine; the output of captive (onsite) ...

  18. "Table A3. Total Primary Consumption of Combustible Energy...

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

    ... produced onsite from input" "materials not classified as energy. Examples of the latter are hydrogen" "produced from the electrolysis of brine; the output of captive (onsite) ...

  19. "Table A11. Total Primary Consumption of Combustible Energy...

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

    ... produced onsite from input materials not" "classified as an energy. Examples of the latter are hydrogen produced from the" "electrolysis of brine; the output of captive (onsite) ...

  20. Table A17. Total First Use (formerly Primary Consumption)...

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

    ... produced" "onsite from input materials not classified as energy. Examples of the latter" "are hydrogen produced from the electrolysis of brine; the output of captive" "(onsite) ...

  1. Table A20. Total First Use (formerly Primary Consumption)...

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

    ... produced" "onsite from input materials not classified as energy. Examples of the latter" "are hydrogen produced from the electrolysis of brine; the output of captive" "(onsite) ...

  2. "Table A3. Total Primary Consumption of Combustible Energy...

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

    ... produced onsite" "from input materials not classified as energy. Examples of the latter are hydrogen produced from the electrolysis" "of brine; the output of captive (onsite) ...

  3. Total internal reflection laser tools and methods

    DOE Patents [OSTI]

    Zediker, Mark S.; Faircloth, Brian O.; Kolachalam, Sharath K.; Grubb, Daryl L.

    2016-02-02

    There is provided high power laser tools and laser heads that utilize total internal reflection ("TIR") structures to direct the laser beam along a laser beam path within the TIR structure. The TIR structures may be a TIR prism having its hypotenuse as a TIR surface.

  4. Total pressing Indonesian gas development, exports

    SciTech Connect (OSTI)

    Not Available

    1994-01-24

    Total is on track to become Indonesia's leading gas exporter by the turn of the century. Total's aggressive development of its Mahakam Delta acreage in East Kalimantan is intended to keep pace with growing liquefied natural gas demand, mainly from Japan but also increasingly from South Korea and Taiwan. A frantic scramble is under way among natural gas suppliers in the Pacific Rim region, particularly those with current LNG export facilities, to accommodate projections of soaring natural gas demand in the region. Accordingly, Total's Indonesian gas production goal is the centerpiece of a larger strategy to become a major player in the Far East Asia gas scene. Its goals also fall in line with Indonesia's. Facing flat or declining oil production while domestic oil demand continues to soar along with a rapidly growing economy, Indonesia is heeding some studies that project the country could become a net oil importer by the turn of the century. The paper describes Total's Far East strategy, the Mahakam acreage which it operates, the shift to gas development, added discoveries, future development, project spending levels, and LNG export capacity.

  5. Frustrated total internal reflection acoustic field sensor

    DOE Patents [OSTI]

    Kallman, Jeffrey S.

    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.

  6. 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.

  7. Total Crude Oil and Petroleum Products Exports

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

    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

  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. A9_ISO

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

    November 2014 1 November 2014 Short-Term Energy Outlook (STEO) Highlights  North Sea Brent crude oil spot prices fell from $95/barrel (bbl) on October 1 to $84/bbl at the end of the month. The causes included weakening outlooks for global economic and oil demand growth, the return to the market of previously disrupted Libyan crude oil production, and continued growth in U.S. tight oil production. Brent crude oil spot prices averaged $87/bbl in October, the first month Brent prices have

  10. A=9 Nuclides

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

    A short list of corrections to mistakes found after the evaluation was published Elsevier Electronic Online: Elsevier (Nuclear Physics A) has made available PDF versions of A...

  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. Field measurement of moisture-buffering model inputs for residential buildings

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

    Woods, Jason; Winkler, Jon

    2016-02-05

    Moisture adsorption and desorption in building materials impact indoor humidity. This effect should be included in building-energy simulations, particularly when humidity is being investigated or controlled. Several models can calculate this moisture-buffering effect, but accurate ones require model inputs that are not always known to the user of the building-energy simulation. This research developed an empirical method to extract whole-house model inputs for the effective moisture penetration depth (EMPD) 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 onlymore » unmeasured term—the moisture sorption into the materials. We validated this method with laboratory measurements, which we used to measure the EMPD model inputs of two houses. After deriving these inputs, we measured the humidity of the same houses during tests with realistic latent and sensible loads and demonstrated the accuracy of this approach. Furthermore, these results show that the EMPD model, when given reasonable inputs, is an accurate moisture-buffering model.« less

  13. Hydromechanical transmission with two planetary assemblies that are clutchable to both the input and output shafts

    DOE Patents [OSTI]

    Orshansky, Jr., deceased, Elias; Weseloh, William E.

    1979-01-01

    A power transmission having two planetary assemblies, each having its own carrier and its own planet, sun, and ring gears. A speed-varying module is connected in driving relation to the input shaft and in driving relationship to the two sun gears, which are connected together. The speed-varying means may comprise a pair of hydraulic units hydraulically interconnected so that one serves as a pump while the other serves as a motor and vice versa, one of the units having a variable stroke and being connected in driving relation to the input shaft, the other unit, which may have a fixed stroke, being connected in driving relation to the sun gears. A brake grounds the first carrier in the first range and in reverse and causes drive to be delivered to the output shaft through the first ring gear in a hydrostatic mode, the first ring gear being rigidly connected to the output shaft. The input shaft also is clutchable to either the carrier or the ring gear of the second planetary assembly. The output shaft is also clutchable to the carrier of the second planetary assembly when the input is clutched to the ring gear of the second planetary assembly, and is clutchable to the ring gear of the second planetary assembly when the input is clutched to the carrier thereof.

  14. 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 high, medium and low expression lines were propagated in vitro for gene function study. When adequate numbers of individual transgenic lines were obtained, they were challenged with PsJN to see if PsJN promotes or inhibits growth of transgenic plants. Our results demonstrated that EF-622 overexpression, ZF-371, GST, H-221 and CAM RNAi transgenic lines lost responses to PsJN, i.e. PsJN had no growth promotive effects on these transgenic plants. Further study needs to be done to characterize this loss of responsiveness to PsJN. During this funding period, we have done more work related to this funded project and established collaborations with other institutions and obtained some interesting results, building a foundation for further research projects. For example, we isolated a naturally-occurring bacterium from surface-sterilized switchgrass seeds, identified as a unique Panteoa agglomerans species, and named strain PaKM. PaKM has been proved to be an efficient growth promoter of switchgrass over a broad spectrum of genotypes and has potential in applications with low input and sustainable production systems on marginal lands. In collaboration with Dr. Shuijin Hu (North Carolina State University), we conducted experiments on how endophyte-inoculated switchgrass affects soil N and P availability and the number of AMF in roots. Our preliminary results showed that PsJN increased AMF infection of switchgrass roots, and enhanced soil N availability and soil N mineralization on a low nutrient field. Further study of this phenomenon on different soils, over longer time periods, is needed to assess its potential impact on the productivity and longevity of switchgrass stands.

  15. "Table A28. Total Expenditures for Purchased Energy Sources...

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

    Total Expenditures for Purchased Energy Sources by Census Region" " and Economic ... "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity...

  16. 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...

  17. Input-output model for MACCS nuclear accident impacts estimation¹

    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.

  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 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

  1. 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

  2. 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

  3. 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 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

  4. EERE Seeks Stakeholder Input on the Co-Optimization of Fuels and Engines |

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

    Department of Energy EERE Seeks Stakeholder Input on the Co-Optimization of Fuels and Engines EERE Seeks Stakeholder Input on the Co-Optimization of Fuels and Engines December 18, 2015 - 1:00pm 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

  5. 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.

  6. ,"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","2/2016","1/15/2010" ,"Release Date:","4/29/2016" ,"Next Release

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

    Gasoline and Diesel Fuel Update (EIA)

    Miami, FL Total To Brazil Freeport, TX Sabine Pass, LA Total to Canada Eastport, ID Calais, ME Detroit, MI Marysville, MI Port Huron, MI Crosby, ND Portal, ND Sault St. Marie, MI St. Clair, MI Noyes, 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

  8. 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

  9. 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.

  10. 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

  11. 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

  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. DOE Seeks Public Input on an Integrated, Interagency Pre-Application Process for Transmission Authorizations

    Broader source: Energy.gov [DOE]

    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 Federal Register Notice is available now for downloading. Comments must be received on or before September 29, 2013. As comments are received, they will be posted online.

  15. 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.

  16. 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.

  17. 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.

  18. Total least squares for anomalous change detection

    SciTech Connect (OSTI)

    Theiler, James P; Matsekh, Anna M

    2010-01-01

    A family of difference-based anomalous change detection algorithms is derived from a total least squares (TLSQ) framework. This provides an alternative to the well-known chronochrome algorithm, which is derived from ordinary least squares. In both cases, the most anomalous changes are identified with the pixels that exhibit the largest residuals with respect to the regression of the two images against each other. The family of TLSQ-based anomalous change detectors is shown to be equivalent to the subspace RX formulation for straight anomaly detection, but applied to the stacked space. However, this family is not invariant to linear coordinate transforms. On the other hand, whitened TLSQ is coordinate invariant, and furthermore it is shown to be equivalent to the optimized covariance equalization algorithm. What whitened TLSQ offers, in addition to connecting with a common language the derivations of two of the most popular anomalous change detection algorithms - chronochrome and covariance equalization - is a generalization of these algorithms with the potential for better performance.

  19. 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.

  20. Minnesota Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    Minnesota Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 ... Share of Total U.S. Natural Gas Residential Deliveries Minnesota Share of Total U.S. ...

  1. California Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    California Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 ... Share of Total U.S. Natural Gas Residential Deliveries California Share of Total U.S. ...

  2. 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.

  3. Minnesota Natural Gas Total Consumption (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Total Consumption (Million Cubic Feet) Minnesota Natural Gas Total Consumption (Million ... Referring Pages: Natural Gas Consumption Minnesota Natural Gas Consumption by End Use ...

  4. California Natural Gas Total Consumption (Million Cubic Feet...

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

    Total Consumption (Million Cubic Feet) California Natural Gas Total Consumption (Million ... Referring Pages: Natural Gas Consumption California Natural Gas Consumption by End Use ...

  5. Total Crude Oil and Petroleum Products Imports by Processing...

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

    Product: Total Crude Oil and Petroleum Products Crude Oil Total Products Other Liquids Unfinished Oils Naphthas and Lighter Kerosene and Light Gas Oils Heavy Gas Oils Residuum ...

  6. NREL: Building America Total Quality Management - 2015 Peer Review...

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

    NREL: Building America Total Quality Management - 2015 Peer Review NREL: Building America Total Quality Management - 2015 Peer Review Presenter: Stacey Rothgeb, NREL View the ...

  7. 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...

  8. ,"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...

  9. ,"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...

  10. 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...

  11. 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...

  12. Webtrends Archives by Fiscal Year — EERE Totals

    Broader source: Energy.gov [DOE]

    Historical EERE office total reports include only Webtrends archives by fiscal year. EERE total reports dating after FY11 can be accessed in EERE's Google Analytics account.

  13. Estimation of Anisotoropy from Total Cross Section and Optical...

    Office of Scientific and Technical Information (OSTI)

    Conference: Estimation of Anisotoropy from Total Cross Section and Optical Model Citation Details In-Document Search Title: Estimation of Anisotoropy from Total Cross Section and ...

  14. Total lymphoid irradiation for multiple sclerosis

    SciTech Connect (OSTI)

    Devereux, C.K.; Vidaver, R.; Hafstein, M.P.; Zito, G.; Troiano, R.; Dowling, P.C.; Cook, S.D.

    1988-01-01

    Although chemical immunosuppression has been shown to benefit patients with chronic progressive multiple sclerosis (MS), it appears that chemotherapy has an appreciable oncogenic potential in patients with multiple sclerosis. Accordingly, we developed a modified total lymphoid irradiation (TLI) regimen designed to reduce toxicity and applied it to a randomized double blind trial of TLI or sham irradiation in MS. Standard TLI regimens were modified to reduce dose to 1,980 rad, lowering the superior mantle margin to midway between the thyroid cartilage and angle of the mandible (to avert xerostomia) and the lower margin of the mantle field to the inferior margin of L1 (to reduce gastrointestinal toxicity by dividing abdominal radiation between mantle and inverted Y), limiting spinal cord dose to 1,000 rad by custom-made spine blocks in the mantle and upper 2 cm of inverted Y fields, and also protecting the left kidney even if part of the spleen were shielded. Clinical efficacy was documented by the less frequent functional scale deterioration of 20 TLI treated patients with chronic progressive MS compared to to 20 sham-irradiated progressive MS patients after 12 months (16% versus 55%, p less than 0.03), 18 months (28% versus 63%, p less than 0.03), and 24 months (44% versus 74%, N.S.). Therapeutic benefit during 3 years follow-up was related to the reduction in lymphocyte count 3 months post-irradiation (p less than 0.02). Toxicity was generally mild and transient, with no instance of xerostomia, pericarditis, herpes zoster, or need to terminate treatment in TLI patients. However, menopause was induced in 2 patients and staphylococcal pneumonia in one.

  15. 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 59,689 - = No Data

  16. Method and apparatus for smart battery charging including a plurality of controllers each monitoring input variables

    SciTech Connect (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. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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...

  3. 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.

  4. 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 framework’s functionality to bridge the gap between the user’s 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.

  5. 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

  6. 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

  7. 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

  8. Level density inputs in nuclear reaction codes and the role of the spin cutoff parameter

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

    Voinov, A. V.; Grimes, S. M.; Brune, C. R.; Burger, A.; Gorgen, A.; Guttormsen, M.; Larsen, A. C.; Massey, T. N.; Siem, S.

    2014-09-03

    Here, the proton spectrum from the 57Fe(α,p) reaction has been measured and analyzed with the Hauser-Feshbach model of nuclear reactions. Different input level density models have been tested. It was found that the best description is achieved with either Fermi-gas or constant temperature model functions obtained by fitting them to neutron resonance spacing and to discrete levels and using the spin cutoff parameter with much weaker excitation energy dependence than it is predicted by the Fermi-gas model.

  9. 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.

  10. 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.

  11. 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.

  12. 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 onmore » a 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

  13. 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.

  14. New Mexico Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) New Mexico 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...

  15. 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...

  16. 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...

  17. Maine Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Maine 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...

  18. Maine Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Maine 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...

  19. 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).

  20. 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...

  1. Virginia Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) 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 Year-8...

  2. Washington Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) Washington 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. Delaware Total Electric Power Industry Net Generation, by Energy...

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

    ...e","-","-","-","-","-" "Other","-","-",11,6,"-" "Total",7182,8534,7524,4842,5628 " " "s Value is less than 0.5 of the table metric, but value is included in any associated total.

  4. Kansas Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Kansas 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...

  5. Arizona Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Arizona 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...

  6. Arizona Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) Arizona 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...

  7. ,"Total Crude Oil and Petroleum Products Net Receipts by Pipeline...

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

    Data for" ,"Data 1","Total Crude Oil and Petroleum Products Net Receipts by ... PM" "Back to Contents","Data 1: Total Crude Oil and Petroleum Products Net Receipts by ...

  8. NREL: Building America Total Quality Management - 2015 Peer Review |

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

    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 NREL: Building America Total Quality Management - 2015 Peer Review R25 Polyisocyanurate Composite Insulation Material

  9. 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.

  10. Scaling properties of proton-nucleus total reaction cross sections

    SciTech Connect (OSTI)

    Abu-Ibrahim, Badawy; Kohama, Akihisa

    2010-05-15

    We study the scaling properties of proton-nucleus total reaction cross sections for stable nuclei and propose an approximate expression in proportion to Z{sup 2/3}sigma{sub pp}{sup total}+N{sup 2/3}sigma{sub pn}{sup total}. Based on this expression, we can derive a relation that enables us to predict a total reaction cross section for any stable nucleus within 10% uncertainty at most, using the empirical value of the total reaction cross section of a given nucleus.

  11. 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.

  12. 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.

  13. 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,...

  14. 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.

  15. 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.

  16. 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.

  17. Time dependence in atmospheric carbon inputs from drainage of organic soils

    SciTech Connect (OSTI)

    Rojstaczer, S.; Deverel, S.J. )

    1993-07-09

    The authors report the results of a study in the San Joaquin-Sacramento Delta of CO[sub 2] emission from drained soils relative to the rate of subsidence of the land. Their interest is in quantifying the rate carbon is freed from soils which are being drained, primarily for agricultural purposes, relative to the observed subsidence rates. This information is one of the inputs in the global carbon cycle. It is argued that most subsidence is the result of carbon oxidation. The fact that subsidence rates correlate with carbon dioxide emission rates supports this argument. In this Delta, subsidence rates have been decreasing in recent years, and measurements indicate that present carbon dioxide emission rates are lower than previous estimates by a factor or 3 or 4.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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 Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S.

  3. 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 Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S.

  4. Percentage of Total Natural Gas Commercial 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 Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S.

  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. 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...

  8. Real-space formulation of the electrostatic potential and total...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Real-space formulation of the electrostatic potential and total energy of solids Citation Details In-Document Search Title: Real-space formulation of the ...

  9. Table A19. Components of Total Electricity Demand by Census...

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

    Components of Total Electricity Demand by Census Region and" " Economic Characteristics of ...ansfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)",...

  10. 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...

  11. 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...

  12. ,"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"...

  13. ,"Other States Total Natural Gas Gross Withdrawals and Production...

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

    Total Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ...

  14. 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...

  15. Texas Natural Gas Gross Withdrawals Total Offshore (Million Cubic...

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

    Gross Withdrawals Total Offshore (Million Cubic Feet) Texas Natural Gas Gross Withdrawals ... Offshore Gross Withdrawals of Natural Gas Natural Gas Gross Withdrawals Texas Offshore ...

  16. National Fuel Cell and Hydrogen Energy Overview: Total Energy...

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

    Presentation by Sunita Satyapal at the Total Energy USA 2012 meeting in Houston, Texas, on November 27, 2012. PDF icon National Fuel Cell and Hydrogen Energy Overview More ...

  17. 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...

  18. ,"Motor Gasoline Sales to End Users, Total Refiner Sales Volumes...

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

    Sales to End Users, Total Refiner Sales Volumes",60,"Monthly","22016","1151983" ,"Release Date:","522016" ,"Next Release Date:","612016" ,"Excel File Name:","petconsrefmg...

  19. 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,...

  20. ,"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...

  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. $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...

  3. ,"Conventional Gasoline Sales to End Users, Total Refiner Sales...

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

    Sales to End Users, Total Refiner Sales Volumes",60,"Monthly","22016","1151994" ,"Release Date:","522016" ,"Next Release Date:","612016" ,"Excel File Name:","petconsrefmg...

  4. 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 .

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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

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

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

  12. Prisms with total internal reflection as solar reflectors

    DOE Patents [OSTI]

    Rabl, Arnulf; Rabl, Veronika

    1978-01-01

    An improved reflective wall for radiant energy collection and concentration devices is provided. The wall is comprised of a plurality of prisms whose frontal faces are adjacent and which reflect the desired radiation by total internal reflection.

  13. ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy...

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

    in this table do not include enclosed malls and strip malls. In the 1999 CBECS, total fuel oil consumption in malls was not statistically significant. (*)Value rounds to zero...

  14. CIGNA Study Uncovers Relationship of Disabilities to Total Benefits Costs

    Broader source: Energy.gov [DOE]

    The findings of a new study reveal an interesting trend. Integrating disability programs with health care programs can potentially lower employers' total benefits costs and help disabled employees get back to work sooner and stay at work.

  15. ,"U.S. Total Natural Gas Underground Storage Capacity (MMcf)...

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

    ...dnavnghistn5290us2m.htm" ,"Source:","Energy Information Administration" ,"For Help, ... 1: U.S. Total Natural Gas Underground Storage Capacity (MMcf)" "Sourcekey","N5290US2" ...

  16. ,"U.S. Total Natural Gas Underground Storage Capacity (MMcf)...

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

    ...dnavnghistn5290us2a.htm" ,"Source:","Energy Information Administration" ,"For Help, ... 1: U.S. Total Natural Gas Underground Storage Capacity (MMcf)" "Sourcekey","N5290US2" ...

  17. AGA Producing Region Natural Gas Total Underground Storage Capacity...

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

    Storage Capacity (Million Cubic Feet) AGA Producing Region Natural Gas Total Underground Storage Capacity (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec...

  18. U.S. Total Shell Storage Capacity at Operable Refineries

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

    Product Area 2010 2011 2012 2013 2014 2015 View History Total 710,413 -- -- -- -- -- 1982-2015 Crude Oil 180,846 -- -- -- -- -- 1985-2015 Liquefied Petroleum Gases 33,842 -- -- -- ...

  19. Summary and recommendations: Total fuel cycle assessment workshop

    SciTech Connect (OSTI)

    1995-08-01

    This report summarizes the activities of the Total Fuel Cycle Assessment Workshop held in Austin, Texas, during October 6--7, 1994. It also contains the proceedings from that workshop.

  20. Ultrasound image guided acetabular implant orientation during total hip replacement

    DOE Patents [OSTI]

    Chang, John; Haddad, Waleed; Kluiwstra, Jan-Ulco; Matthews, Dennis; Trauner, Kenneth

    2003-08-19

    A system for assisting in precise location of the acetabular implant during total hip replacement. The system uses ultrasound imaging for guiding the placement and orientation of the implant.