National Library of Energy BETA

Sample records for type total estimated

  1. Types of Cost Estimates

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

    1997-03-28

    The chapter describes the estimates required on government-managed projects for both general construction and environmental management.

  2. Cell Total Activity Final Estimate.xls

    Office of Legacy Management (LM)

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

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

    Office of Environmental Management (EM)

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

  4. 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 ...

  5. Contractor: Contract Number: Contract Type: Total Estimated

    Office of Environmental Management (EM)

    886,608 Computer Sciences Corporation DE-AC06-04RL14383 895,358 899,230 907,583 Cost Plus Award Fee 134,100,336 8,221,404 Fee Available Contract Period: Fee Information...

  6. Performance Measure Unit Lifecycle Total Estimate Pre-2016 Lifecycle...

    Office of Environmental Management (EM)

    Measure Unit Lifecycle Total Estimate Pre-2016 Lifecycle Values 2016 Target 2017 Target Pu packaged for long-term disposition Number of Containers 5,089 5,089 5,089 5,089 eU ...

  7. ,"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"...

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

    Office of Scientific and Technical Information (OSTI)

    Resource Type: Conference Resource Relation: Conference: Working Party on Evaluation Cooperation ; 2013-05-22 - 2013-05-24 ; Paris, France Research Org: Los Alamos National ...

  9. Total Estimated Contract Cost: Contract Option Period: Maximum...

    Office of Environmental Management (EM)

    LLC Contract Number: DE-AC30-11CC40015 Contract Type: Cost Plus Award Fee EM Contractor Fee December 2015 Site: Portsmouth Paducah Project Office Contract Name: Operation of DUF6

  10. Total Estimated Contract Cost: Contract Option Period: Maximum...

    Office of Environmental Management (EM)

    & Wilcox Conversion Services, LLC Contract Number: DE-AC30-11CC40015 Contract Type: Cost Plus Award Fee EM Contractor Fee September 2015 Site: Portsmouth Paducah Project Office...

  11. Total Estimated Contract Cost: Contract Option Period: Performance

    Office of Environmental Management (EM)

    Contractor: Bechtel National Inc. Contract Number: DE-AC27-01RV14136 Contract Type: Cost Plus Award Fee NA Maximum Fee 599,588,540 Fee Available 102,622,325 10,868,785,789...

  12. Total Estimated Contract Cost: Contract Option Period: Maximum Fee

    Office of Environmental Management (EM)

    Definition and Scope Answer/Comment 1 What significant policy challenges are likely to remain unaddressed if we employ Title XIII's definition? The following points are not referencedd in EISA 1301. ・Power provider should also control the output fluctuation of renewable resources. ・The end user should have the choice of which form of power storage to be used. Certain types of energy conservation and storage could work better in different applications (e.g. not only electricity power but also

  13. Total Estimated Contract Price: Contract Option Periods: Performance

    Office of Environmental Management (EM)

    Price: Contract Option Periods: Performance Period Fee Earned Base Period "A" $0 Base Period "B" Option 1 Option 2 Option 3 Cumulative Fee $0 EM Contractor Fee June 2015 Site: Office of River Protection, Richland, WA Contract Name: Hanford 222-S Laboratory Analysis and Testing Services Contractor: Wastren Advantage, Inc Contract Number: DE-EM0003722 Contract Type: Hybrid Contract with Award Fee Fee Available $44,562,457 Base Contract Period: November 21, 2016 to September 20,

  14. ,"Crude Oil and Petroleum Products Total Stocks Stocks by Type...

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

    Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks ... AM" "Back to Contents","Data 1: Crude Oil and Petroleum Products Total Stocks Stocks ...

  15. Total

    Gasoline and Diesel Fuel Update (EIA)

    Product: Total Crude Oil Liquefied Petroleum Gases PropanePropylene Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other ...

  16. Total

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

    Product: Total Crude Oil Liquefied Petroleum Gases PropanePropylene Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel ...

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

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

    ... Type of Renter-Occupied Housing Unit Housing Units (millions) Single-Family Units ... At Home Behavior Home Used for Business Yes......

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

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

    ... Type of Owner-Occupied Housing Unit U.S. Housing Units (millions) Single-Family Units ... At Home Behavior Home Used for Business Yes......

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

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

    ... Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table ... At Home Behavior Home Used for Business Yes......

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

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

    0.9 Q Q Q Heat Pump......7.7 0.3 Q Q Steam or Hot Water System......Census Division Total West Energy Information Administration ...

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

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

    0.9 Q Q Q Heat Pump......6.2 3.8 2.4 Steam or Hot Water System......Census Division Total Northeast Energy Information ...

  2. 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

  3. 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

  4. 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

  5. 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

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

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

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

  7. 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

  8. 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

  9. 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

  10. 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

  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 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9

  4. Estimating the releasable source term for Type B packages

    SciTech Connect (OSTI)

    Anderson, B.L.; Carlson, R.W.; Osgood, N.

    1995-11-01

    The release rate criteria for Type B packages designed to transport radioactive materials is given in Title 10 of the Code of Federal Regulations (10 CFR 71). Before the maximum allowable volumetric leakage rate that corresponds to the regulatory release rate can be calculated, estimation of the releasable source term activity density (concentration of releasable radioactive material) is required. This work provides methods for estimating the releasable source term for packages holding various contents types. The contents types considered include: (1) radioactive liquids; (2) radioactive gases; (3) radioactive powders and dispersible solids; (4) non-dispersible radioactive solids and (5) irradiated nuclear fuel rods. The numbers given, especially as related to the source term for packages transporting irradiated fuel rods, are preliminary and are subject to change upon development of improved methods and/or upon review of additional experimental data.

  5. Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings

    SciTech Connect (OSTI)

    Fridley, David; Fridley, David G.; Zheng, Nina; Zhou, Nan

    2008-03-01

    Buildings represent an increasingly important component of China's total energy consumption mix. However, accurately assessing the total volume of energy consumed in buildings is difficult owing to deficiencies in China's statistical collection system and a lack of national surveys. Official statistics suggest that buildings account for about 19% of China's total energy consumption, while others estimate the proportion at 23%, rising to 30% over the next few years. In addition to operational energy, buildings embody the energy used in the in the mining, extraction, harvesting, processing, manufacturing and transport of building materials as well as the energy used in the construction and decommissioning of buildings. This embodied energy, along with a building's operational energy, constitutes the building's life-cycle energy and emissions footprint. This report first provides a review of international studies on commercial building life-cycle energy use from which data are derived to develop an assessment of Chinese commercial building life-cycle energy use, then examines in detail two cases for the development of office building operational energy consumption to 2020. Finally, the energy and emissions implications of the two cases are presented.

  6. Cancer risk estimates from radiation therapy for heterotopic ossification prophylaxis after total hip arthroplasty

    SciTech Connect (OSTI)

    Mazonakis, Michalis; Berris, Theoharris; Damilakis, John; Lyraraki, Efrossyni

    2013-10-15

    Purpose: Heterotopic ossification (HO) is a frequent complication following total hip arthroplasty. This study was conducted to calculate the radiation dose to organs-at-risk and estimate the probability of cancer induction from radiotherapy for HO prophylaxis.Methods: Hip irradiation for HO with a 6 MV photon beam was simulated with the aid of a Monte Carlo model. A realistic humanoid phantom representing an average adult patient was implemented in Monte Carlo environment for dosimetric calculations. The average out-of-field radiation dose to stomach, liver, lung, prostate, bladder, thyroid, breast, uterus, and ovary was calculated. The organ-equivalent-dose to colon, that was partly included within the treatment field, was also determined. Organ dose calculations were carried out using three different field sizes. The dependence of organ doses upon the block insertion into primary beam for shielding colon and prosthesis was investigated. The lifetime attributable risk for cancer development was estimated using organ, age, and gender-specific risk coefficients.Results: For a typical target dose of 7 Gy, organ doses varied from 1.0 to 741.1 mGy by the field dimensions and organ location relative to the field edge. Blocked field irradiations resulted in a dose range of 1.4146.3 mGy. The most probable detriment from open field treatment of male patients was colon cancer with a high risk of 564.3 10{sup ?5} to 837.4 10{sup ?5} depending upon the organ dose magnitude and the patient's age. The corresponding colon cancer risk for female patients was (372.2541.0) 10{sup ?5}. The probability of bladder cancer development was more than 113.7 10{sup ?5} and 110.3 10{sup ?5} for males and females, respectively. The cancer risk range to other individual organs was reduced to (0.00368.5) 10{sup ?5}.Conclusions: The risk for cancer induction from radiation therapy for HO prophylaxis after total hip arthroplasty varies considerably by the treatment parameters

  7. Estimation of total cloud cover from solar radiation observations at Lake Rotorua, New Zealand

    SciTech Connect (OSTI)

    Luo, Liancong; Hamilton, David; Han, Boping

    2010-03-15

    The DYRESM-CAEDYM model is a valuable tool for simulating water temperature for biochemical studies in aquatic ecosystem. The model requires inputs of surface short-wave radiation and long-wave radiation or total cloud cover fraction (TC). Long-wave radiation is often not measured directly so a method to determine TC from commonly measured short-wave solar irradiance (E{sub 0}) and theoretical short-wave solar irradiance under a clear sky (E{sub c}) has broad application. A more than 17-year (15 November 1991 to 20 February 2009) hourly solar irradiance data set was used to estimate the peak solar irradiance for each ordinal date over one year, which was assumed to be representative of solar irradiance in the absence of cloud. Comparison between these daily observed values and the modelled clear-sky solar radiation over one year was in close agreement (Pearson correlation coefficient, r = 0.995 and root mean squared error, RMSE = 12.54 W m{sup -2}). The downloaded hourly cloudiness measurements from 15 November 1991 to 20 February 2009 was used to calculate the daily values for this period and then the calculated daily values over the 17 years were used to calculate the average values for each ordinal date over one year. A regression equation between (1 - E{sub 0}/E{sub c}) and TC produced a correlation coefficient value of 0.99 (p > 0.01, n = 71). The validation of this cloud cover estimation model was conducted with observed short-wave solar radiation and TC at two sites. Values of TC derived from the model at the Lake Rotorua site gave a reasonable prediction of the observed values (RMSE = 0.10, r = 0.86, p > 0.01, n = 61). The model was also tested at Queenstown (South Island of New Zealand) and it provided satisfactory results compared to the measurements (RMSE = 0.16, r = 0.67, p > 0.01, n = 61). Therefore the model's good performance and broad applicability will contribute to the DYRESM-CAEDYM accuracy of water temperature simulation when long-wave radiation

  8. Estimating Source Terms for Diverse Spent Nuclear Fuel Types

    SciTech Connect (OSTI)

    Brett Carlsen; Layne Pincock

    2004-11-01

    The U.S. Department of Energy (DOE) National Spent Nuclear Fuel Program is responsible for developing a defensible methodology for determining the radionuclide inventory for the DOE spent nuclear fuel (SNF) to be dispositioned at the proposed Monitored Geologic Repository at the Yucca Mountain Site. SNF owned by DOE includes diverse fuels from various experimental, research, and production reactors. These fuels currently reside at several DOE sites, universities, and foreign research reactor sites. Safe storage, transportation, and ultimate disposal of these fuels will require radiological source terms as inputs to safety analyses that support design and licensing of the necessary equipment and facilities. This paper summarizes the methodology developed for estimating radionuclide inventories associated with DOE-owned SNF. The results will support development of design and administrative controls to manage radiological risks and may later be used to demonstrate conformance with repository acceptance criteria.

  9. An estimation of the total atmospheric pollution in the city of Thessaloniki using solar energy data

    SciTech Connect (OSTI)

    Sahsamanoglou, H.S.; Makrogiannis, T.I.; Meletis, H. )

    1991-01-01

    The atmospheric mass over the city of Thessaloniki is characterized by a generally increased pollution due to solid particles in the lower atmosphere. This conclusion has been reached after a comparison between values of total solar radiation, taken in the city center during clear sky days, and values predicted by the model of D.F. Heermann et al. for corresponding days. Pollution varies between a minimum value which is constant over the year and independent of weather situations (pollution background), and a maximum value. The minimum pollution causes an attenuation of solar radiation about 15%, compared to the values given by the above model. The atmospheric pollution in the city, during a usual day with clear sky, causes an attenuation varying between 10% in the summer and 20% in the winter, when compared to the constant background of the pollution. During the most unfavorable days with clear sky, the percentages are 30% in the summer and 40% in the winter.

  10. Types of Possible Survey Errors in Estimates Published in the Weekly Natural Gas Storage Report

    Reports and Publications (EIA)

    2016-01-01

    This document lists types of potential errors in EIA estimates published in the WNGSR. Survey errors are an unavoidable aspect of data collection. Error is inherent in all collected data, regardless of the source of the data and the care and competence of data collectors. The type and extent of error depends on the type and characteristics of the survey.

  11. Types of Possible Survey Errors in Estimates Published in the Weekly Natural Gas Storage Report

    Weekly Natural Gas Storage Report (EIA)

    U.S. Energy Information Administration | Types of Possible Survey Errors in Estimates Published in the Weekly Natural Gas Storage Report 1 February 2016 Types of Possible Survey Errors in Estimates Published in the Weekly Natural Gas Storage Report The U.S. Energy Information Administration (EIA) collects and publishes natural gas storage information on a monthly and weekly basis. The Form EIA-191, Monthly Underground Natural Gas Storage Report, is a census survey that collects field-level

  12. THE SLOAN LENS ACS SURVEY. X. STELLAR, DYNAMICAL, AND TOTAL MASS CORRELATIONS OF MASSIVE EARLY-TYPE GALAXIES

    SciTech Connect (OSTI)

    Auger, M. W.; Treu, T.; Marshall, P. J.; Bolton, A. S.; Gavazzi, R.; Koopmans, L. V. E.; Moustakas, L. A.

    2010-11-20

    We use stellar masses, surface photometry, strong-lensing masses, and stellar velocity dispersions ({sigma}{sub e/2}) to investigate empirical correlations for the definitive sample of 73 early-type galaxies (ETGs) that are strong gravitational lenses from the SLACS survey. The traditional correlations (fundamental plane (FP) and its projections) are consistent with those found for non-lens galaxies, supporting the thesis that SLACS lens galaxies are representative of massive ETGs (dimensional mass M{sub dim} = 10{sup 11}-10{sup 12} M{sub sun}). The addition of high-precision strong-lensing estimates of the total mass allows us to gain further insights into their internal structure: (1) the average slope of the total mass-density profile ({rho}{sub tot}{proportional_to}r{sup -}{gamma}') is ({gamma}') = 2.078 {+-} 0.027 with an intrinsic scatter of 0.16 {+-} 0.02; (2) {gamma}' correlates with effective radius (r{sub e}) and central mass density, in the sense that denser galaxies have steeper profiles; (3) the dark matter (DM) fraction within r{sub e} /2 is a monotonically increasing function of galaxy mass and size (due to a mass-dependent central cold DM distribution or due to baryonic DM-stellar remnants or low-mass stars-if the initial mass function is non-universal and its normalization increases with mass); (4) the dimensional mass M{sub dim} {identical_to} 5r{sub e} {sigma}{sup 2}{sub e/2}/G is proportional to the total (lensing) mass M{sub r{sub e/2}}, and both increase more rapidly than stellar mass M{sub *} (M{sub *{proportional_to}}M{sub r{sub e/2}{sup 0.8}); (5) the mass plane (MP), obtained by replacing surface brightness with surface mass density in the FP, is found to be tighter and closer to the virial relation than the FP and the M{sub *}P, indicating that the scatter of those relations is dominated by stellar population effects; (6) we construct the fundamental hyper-plane by adding stellar masses to the MP and find the M{sub *} coefficient to be

  13. Final report (Grant No. DOE DE-FG02-97ER62366) [Retrieval of cloud fraction and type using broadband diffuse and total shortwave irradiance measurements

    SciTech Connect (OSTI)

    Clothiaux, Eugene

    2001-05-17

    The primary research effort supported by Grant No. DOE DEFG02-97ER62366 titled ''Retrieval of Cloud Fraction and Type Using Broadband Diffuse and Total Shortwave Irradiance Measurements'' was application of clear-sky identification and cloud fraction estimation algorithms developed by Charles N. Long and Thomas P. Ackerman to the downwelling total, direct and diffuse shortwave irradiance measurements made at all of the central, boundary, and extended facilities of the DOE Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SOP) site. Goals of the research were finalization and publication of the two algorithms in the peer-reviewed literature and operational application of them to all of aforementioned data streams from the ARM SGP site. The clear-sky identification algorithm was published as Long and Ackerman (2000) in the Journal of Geophysical Research, while a description of the cloud fraction estimation algorithm made it to the scientific literature as Long et al. (1999) in the Proceedings of the 10th American Meteorological Association Conference on Atmospheric Radiation held in Madison, Wisconsin. The cloud fraction estimation algorithm relies on empirical relationships between the outputs of the clear-sky identification algorithm and cloud fraction; as such, the cloud fraction estimation algorithm requires significant amounts of data both to properly develop the empirical relationships and to thoroughly test them. With this perspective in mind the major focus of our research efforts in the later half of the project became the operational implementation of the clear-sky identification algorithm on DOE ARM SGP data so that we could develop the data set necessary for final tuning of the cloud fraction estimation algorithm in research extending beyond the lifetime of the project.

  14. Using Geothermal Play Types as an Analogue for Estimating Potential Resource Size

    SciTech Connect (OSTI)

    Terry, Rachel; Young, Katherine

    2015-09-02

    Blind geothermal systems are becoming increasingly common as more geothermal fields are developed. Geothermal development is known to have high risk in the early stages of a project development because reservoir characteristics are relatively unknown until wells are drilled. Play types (or occurrence models) categorize potential geothermal fields into groups based on geologic characteristics. To aid in lowering exploration risk, these groups' reservoir characteristics can be used as analogues in new site exploration. The play type schemes used in this paper were Moeck and Beardsmore play types (Moeck et al. 2014) and Brophy occurrence models (Brophy et al. 2011). Operating geothermal fields throughout the world were classified based on their associated play type, and then reservoir characteristics data were catalogued. The distributions of these characteristics were plotted in histograms to develop probability density functions for each individual characteristic. The probability density functions can be used as input analogues in Monte Carlo estimations of resource potential for similar play types in early exploration phases. A spreadsheet model was created to estimate resource potential in undeveloped fields. The user can choose to input their own values for each reservoir characteristic or choose to use the probability distribution functions provided from the selected play type. This paper also addresses the United States Geological Survey's 1978 and 2008 assessment of geothermal resources by comparing their estimated values to reported values from post-site development. Information from the collected data was used in the comparison for thirty developed sites in the United States. No significant trends or suggestions for methodologies could be made by the comparison.

  15. Types of Possible Survey Errors in Estimates Published in the Weekly

    Weekly Natural Gas Storage Report (EIA)

    Natural Gas Storage Report Types of Possible Survey Errors in Estimates Published in the Weekly Natural Gas Storage Report Release date: March 1, 2016 The U.S. Energy Information Administration (EIA) collects and publishes natural gas storage information on a monthly and weekly basis. The Form EIA-191, Monthly Underground Natural Gas Storage Report, is a census survey that collects field-level information from all underground natural gas storage operators in the United States known to EIA.

  16. Table 8.6a Estimated Consumption of Combustible Fuels for Useful Thermal Output at Combined-Heat-and-Power Plants: Total (All Sectors), 1989-2011 (Sum of Tables 8.6b and 8.6c)

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

    a Estimated Consumption of Combustible Fuels for Useful Thermal Output at Combined-Heat-and-Power Plants: Total (All Sectors), 1989-2011 (Sum of Tables 8.6b and 8.6c) Year Coal 1 Petroleum Natural Gas 6 Other Gases 7 Biomass Other 10 Distillate Fuel Oil 2 Residual Fuel Oil 3 Other Liquids 4 Petroleum Coke 5 Total 5 Wood 8 Waste 9 Short Tons Barrels Short Tons Barrels Thousand Cubic Feet Billion Btu Billion Btu Billion Btu 1989 16,509,639 1,410,151 16,356,550 353,000 247,409 19,356,746

  17. Total Imports

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

    Data Series: Imports - Total Imports - Crude Oil Imports - Crude Oil, Commercial Imports - by SPR Imports - into SPR by Others Imports - Total Products Imports - Total Motor Gasoline Imports - Finished Motor Gasoline Imports - Reformulated Gasoline Imports - Reformulated Gasoline Blended w/ Fuel Ethanol Imports - Other Reformulated Gasoline Imports - Conventional Gasoline Imports - Conv. Gasoline Blended w/ Fuel Ethanol Imports - Conv. Gasoline Blended w/ Fuel Ethanol, Ed55 & < Imports -

  18. Country Total

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

    Country Total Percent of U.S. total Canada 61,078 1% China 3,323,297 57% Germany 154,800 3% Japan 12,593 0% India 47,192 1% South Korea 251,105 4% All Others 2,008,612 34% Total 5,858,677 100% Table 7 . Photovoltaic module import shipments by country, 2014 (peak kilowatts) Note: All Others includes Cambodia, Czech Republic, Hong Kong, Malaysia, Mexico, Netherlands, Philippines, Singapore, Taiwan and Turkey Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic

  19. State Total

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

    State Total Percent of U.S. total Alabama 482 0.0% Alaska 81 0.0% Arizona 194,476 3.3% Arkansas 336 0.0% California 3,163,120 53.0% Colorado 47,240 0.8% Connecticut 50,745 0.9% Delaware 6,600 0.1% District of Columbia 751 0.0% Florida 18,593 0.3% Georgia 47,660 0.8% Hawaii 78,329 1.3% Illinois 5,795 0.1% Indiana 37,016 0.6% Iowa 14,281 0.2% Kansas 1,809 0.0% Kentucky 520 0.0% Louisiana 12,147 0.2% Maine 1,296 0.0% Maryland 63,077 1.1% Massachusetts 157,415 2.6% Michigan 4,210 0.1% Minnesota

  20. Summary Max Total Units

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

    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

  1. Notices Total Estimated Number of Annual

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

    ... 27 Dumont Street, Thursday, September 26, 2013, 5-8 p.m. Requests to speak at one or more public scoping meeting(s) should be received at the address for Brian Mills indicated ...

  2. Total Estimated Contract Cost: Performance Period

    Office of Environmental Management (EM)

    FY2012 Fee Information Minimum Fee Maximum Fee September 2015 Contract Number: Cost Plus Incentive Fee Contractor: 3,264,909,094 Contract Period: EM Contractor Fee s Idaho...

  3. Effects of core type, placement, and width on the estimated interstrand coupling properties of QXF-type Nb3Sn Rutherford cables

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

    Collings, E. W.; Sumption, M. D.; Majoros, M.; Wang, X.; Dietderich, D. R.

    2015-01-12

    The coupling magnetization of a Rutherford cable is inversely proportional to an effective interstrand contact resistance Reff , a function of the crossing-strand resistance Rc, and the adjacent strand resistance Ra. In cored cables, Reff continuously varies with W, the core width expressed as percent interstrand cover. For a series of un-heat-treated stabrite-coated NbTi LHC-inner cables with stainless-steel (SS, insulating) cores, Reff (W) decreased smoothly as W decreased from 100%, whereas for a set of research-wound SS-cored Nb3Sn cables, Reff plummeted abruptly and remained low over most of the range. The difference is due to the controlling influence of Rcmore » - 2.5 μΩ for the stabrite/NbTi and 0.26 μΩ for Nb3Sn. The experimental behavior was replicated in the Reff (W)’s calculated by the program CUDI, which (using the basic parameters of the QXF cable) went on to show in terms of decreasing W that: 1) in QXF-type Nb3Sn cables (Rc = 0.26 μΩ), Reff dropped even more suddenly when the SS core, instead of being centered, was offset to one edge of the cable; 2) Reff decreased more gradually in cables with higher Rc’s; and 3) a suitable Reff for a Nb3Sn cable can be achieved by inserting a suitably resistive core rather than an insulating (SS) one.« less

  4. Estimation of benchmark dose as the threshold levels of urinary cadmium, based on excretion of total protein, {beta} {sub 2}-microglobulin, and N-acetyl-{beta}-D-glucosaminidase in cadmium nonpolluted regions in Japan

    SciTech Connect (OSTI)

    Kobayashi, Etsuko . E-mail: ekoba@faculty.chiba-u.jp; Suwazono, Yasushi; Uetani, Mirei; Inaba, Takeya; Oishi, Mitsuhiro; Kido, Teruhiko; Nishijo, Muneko; Nakagawa, Hideaki; Nogawa, Koji

    2006-07-15

    Previously, we investigated the association between urinary cadmium (Cd) concentration and indicators of renal dysfunction, including total protein, {beta} {sub 2}-microglobulin ({beta} {sub 2}-MG), and N-acetyl-{beta}-D-glucosaminidase (NAG). In 2778 inhabitants {>=}50 years of age (1114 men, 1664 women) in three different Cd nonpolluted areas in Japan, we showed that a dose-response relationship existed between renal effects and Cd exposure in the general environment without any known Cd pollution. However, we could not estimate the threshold levels of urinary Cd at that time. In the present study, we estimated the threshold levels of urinary Cd as the benchmark dose low (BMDL) using the benchmark dose (BMD) approach. Urinary Cd excretion was divided into 10 categories, and an abnormality rate was calculated for each. Cut-off values for urinary substances were defined as corresponding to the 84% and 95% upper limit values of the target population who have not smoked. Then we calculated the BMD and BMDL using a log-logistic model. The values of BMD and BMDL for all urinary substances could be calculated. The BMDL for the 84% cut-off value of {beta} {sub 2}-MG, setting an abnormal value at 5%, was 2.4 {mu}g/g creatinine (cr) in men and 3.3 {mu}g/g cr in women. In conclusion, the present study demonstrated that the threshold level of urinary Cd could be estimated in people living in the general environment without any known Cd-pollution in Japan, and the value was inferred to be almost the same as that in Belgium, Sweden, and China.

  5. Check Estimates and Independent Costs

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

    1997-03-28

    Check estimates and independent cost estimates (ICEs) are tools that can be used to validate a cost estimate. Estimate validation entails an objective review of the estimate to ensure that estimate criteria and requirements have been met and well documented, defensible estimate has been developed. This chapter describes check estimates and their procedures and various types of independent cost estimates.

  6. Derived Annual Estimates

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

    74-1988 For Methodology Concerning the Derived Estimates Total Consumption of Offsite-Produced Energy for Heat and Power by Industry Group, 1974-1988 Total Energy *** Electricity...

  7. THE INFLUENCE OF DARK MATTER HALOS ON DYNAMICAL ESTIMATES OF BLACK HOLE MASS: 10 NEW MEASUREMENTS FOR HIGH-{sigma} EARLY-TYPE GALAXIES

    SciTech Connect (OSTI)

    Rusli, S. P.; Thomas, J.; Saglia, R. P.; Fabricius, M.; Erwin, P.; Bender, R.; Nowak, N.; Lee, C. H.; Riffeser, A.; Sharp, R.

    2013-09-15

    Adaptive optics assisted SINFONI observations of the central regions of 10 early-type galaxies are presented. Based primarily on the SINFONI kinematics, 10 black hole (BH) masses occupying the high-mass regime of the M{sub BH}-{sigma} relation are derived using three-integral Schwarzschild models. The effect of dark matter (DM) inclusion on the BH mass is explored. The omission of a DM halo in the model results in a higher stellar mass-to-light ratio, especially when extensive kinematic data are used in the model. However, when the diameter of the sphere of influence-computed using the BH mass derived without a dark halo-is at least 10 times the point-spread function FWHM during the observations, it is safe to exclude a DM component in the dynamical modeling, i.e., the change in BH mass is negligible. When the spatial resolution is marginal, restricting the mass-to-light ratio to the right value returns the correct M{sub BH} although a dark halo is not present in the model. Compared to the M{sub BH}-{sigma} and M{sub BH}-L relations of McConnell et al., the 10 BHs are all more massive than expected from the luminosities and 7 BH masses are higher than expected from the stellar velocity dispersions of the host bulges. Using new fitted relations, which include the 10 galaxies, we find that the space density of the most massive BHs (M{sub BH} {approx}> 10{sup 9} M{sub Sun }) estimated from the M{sub BH}-L relation is higher than the estimate based on the M{sub BH}-{sigma} relation and the latter is higher than model predictions based on quasar counts, each by about an order of magnitude.

  8. 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...

  9. THE AKARI 2.5-5.0 ?m SPECTRAL ATLAS OF TYPE-1 ACTIVE GALACTIC NUCLEI: BLACK HOLE MASS ESTIMATOR, LINE RATIO, AND HOT DUST TEMPERATURE

    SciTech Connect (OSTI)

    Kim, Dohyeong; Im, Myungshin; Kim, Ji Hoon; Jun, Hyunsung David; Lee, Seong-Kook; Woo, Jong-Hak; Lee, Hyung Mok; Lee, Myung Gyoon; Nakagawa, Takao; Matsuhara, Hideo; Wada, Takehiko; Takagi, Toshinobu; Oyabu, Shinki; Ohyama, Youichi E-mail: mim@astro.snu.ac.kr

    2015-01-01

    We present 2.5-5.0?m spectra of 83 nearby (0.002 < z < 0.48) and bright (K < 14 mag) type-1 active galactic nuclei (AGNs) taken with the Infrared Camera on board AKARI. The 2.5-5.0?m spectral region contains emission lines such as Br? (2.63?m), Br? (4.05?m), and polycyclic aromatic hydrocarbons (3.3?m), which can be used for studying the black hole (BH) masses and star formation activity in the host galaxies of AGNs. The spectral region also suffers less dust extinction than in the ultra violet (UV) or optical wavelengths, which may provide an unobscured view of dusty AGNs. Our sample is selected from bright quasar surveys of Palomar-Green and SNUQSO, and AGNs with reverberation-mapped BH masses from Peterson etal. Using 11 AGNs with reliable detection of Brackett lines, we derive the Brackett-line-based BH mass estimators. We also find that the observed Brackett line ratios can be explained with the commonly adopted physical conditions of the broad line region. Moreover, we fit the hot and warm dust components of the dust torus by adding photometric data of SDSS, 2MASS, WISE, and ISO to the AKARI spectra, finding hot and warm dust temperatures of ?1100 K and ?220 K, respectively, rather than the commonly cited hot dust temperature of 1500 K.

  10. Table A39. Total Expenditures for Purchased Electricity and Steam

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

    9. Total Expenditures for Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" ," Electricity",," Steam" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic

  11. Weekly Coal Production Estimation Methodology

    Gasoline and Diesel Fuel Update (EIA)

    Weekly Coal Production Estimation Methodology Step 1 (Estimate total amount of weekly U.S. coal production) U.S. coal production for the current week is estimated using a ratio ...

  12. ,"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...

  13. Estimating Methods

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

    1997-03-28

    Based on the project's scope, the purpose of the estimate, and the availability of estimating resources, the estimator can choose one or a combination of techniques when estimating an activity or project. Estimating methods, estimating indirect and direct costs, and other estimating considerations are discussed in this chapter.

  14. Types of Radiation Exposure

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

    External Irradiation Contamination Incorporation Biological Effects of Acute, Total Body Irradiation Managing Radiation Emergencies Procedure Demonstration Types of radiation ...

  15. Cost-effectiveness of controlling emissions for various alternative-fuel vehicle types, with vehicle and fuel price subsidies estimated on the basis of monetary values of emission reductions

    SciTech Connect (OSTI)

    Wang, M.Q.

    1993-12-31

    Emission-control cost-effectiveness is estimated for ten alternative-fuel vehicle (AFV) types (i.e., vehicles fueled with reformulated gasoline, M85 flexible-fuel vehicles [FFVs], M100 FFVs, dedicated M85 vehicles, dedicated M100 vehicles, E85 FFVS, dual-fuel liquefied petroleum gas vehicles, dual-fuel compressed natural gas vehicles [CNGVs], dedicated CNGVs, and electric vehicles [EVs]). Given the assumptions made, CNGVs are found to be most cost-effective in controlling emissions and E85 FFVs to be least cost-effective, with the other vehicle types falling between these two. AFV cost-effectiveness is further calculated for various cases representing changes in costs of vehicles and fuels, AFV emission reductions, and baseline gasoline vehicle emissions, among other factors. Changes in these parameters can change cost-effectiveness dramatically. However, the rank of the ten AFV types according to their cost-effectiveness remains essentially unchanged. Based on assumed dollars-per-ton emission values and estimated AFV emission reductions, the per-vehicle monetary value of emission reductions is calculated for each AFV type. Calculated emission reduction values ranged from as little as $500 to as much as $40,000 per vehicle, depending on AFV type, dollar-per-ton emission values, and baseline gasoline vehicle emissions. Among the ten vehicle types, vehicles fueled with reformulated gasoline have the lowest per-vehicle value, while EVs have the highest per-vehicle value, reflecting the magnitude of emission reductions by these vehicle types. To translate the calculated per-vehicle emission reduction values to individual AFV users, AFV fuel or vehicle price subsidies are designed to be equal to AFV emission reduction values. The subsidies designed in this way are substantial. In fact, providing the subsidies to AFVs would change most AFV types from net cost increases to net cost decreases, relative to conventional gasoline vehicles.

  16. 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...

  17. ,"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...

  18. ,"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...

  19. ,"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"...

  20. 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...

  1. ,"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...

  2. ,"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...

  3. 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...

  4. 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*...

  5. 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.

  6. U.S. Total Exports

    Gasoline and Diesel Fuel Update (EIA)

    Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to Egypt ... Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total ...

  7. 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...

  8. Site Performance Measure Unit Lifecycle Total Estimate Pre-2016...

    Office of Environmental Management (EM)

    Number of Release Sites 443 443 443 443 Brookhaven National Laboratory Nuclear Facility Completions Number of Facilities 1 1 2 2 Brookhaven National Laboratory Radioactive Facility ...

  9. Estimating Radiation Risk from Total Effective Dose Equivalent...

    National Nuclear Security Administration (NNSA)

    of Dose to the Public, DOE Report DOEEH-0070, July 1988. DOE, 1988b. Internal Dose Conversion Factors for Calculation of Dose to the Public, DOE Report DOEEH-0071, July 1988. ...

  10. Total Estimated Contract Cost: Contract Option Period: Performance

    Office of Environmental Management (EM)

    Performance Period Fee Earned FY2000 thru 2008 $102,622,325 FY2009 $12,259,719 FY2010 $35,789,418 FY2011 $24,126,240 FY2012 $24,995,209 FY2013 $6,340,762 FY2014 $16,285,867 FY2015 $35,931,000 $8,595,000 FY2016 $20,891,000 $9,310,000 FY2017 $24,849,000 FY2018 $99,100,000 FY2019 $129,700,000 Cumulative Fee $240,324,540 $595,298,540 $12,259,719 $35,789,418 $38,554,240 $41,785,209 $16,698,762 $37,117,867 Maximum Fee $595,298,540 Fee Available $102,622,325 $10,921,302,346 Completion Contract:

  11. Estimating Radiation Risk from Total Effective Dose Equivalent...

    National Nuclear Security Administration (NNSA)

    0 Tc 0.37 No. 1Tj 5.25 0 TD 0.098 Tc 0 Tw (No.) Tj 15.755 -13.5 TD 0.3to Tw ( ) Tj 5.25 0 TD F1 10.5 Tf -0.1925 Tc 0 5 Report 0 1Tj 5.25 0 TD 0.098 Tc 0 Tw 8No. 7 0 TD -0.IRRPC,

  12. 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 Atmospheric Carbon, Aerosols 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

  13. 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).

  14. 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

  15. Independent Cost Estimate (ICE)

    Broader source: Energy.gov [DOE]

    Independent Cost Estimate (ICE). On August 8-12, the Office of Project Management Oversight and Assessments (PM) will conduct an ICE on the NNSA Albuquerque Complex Project (NACP) at Albuquerque, NM. This estimate will support the Critical Decision (CD) for establishing the performance baseline and approval to start construction (CD-2/3). This project is at CD-1, with a total project cost range of $183M to $251M.

  16. Estimation of economic parameters of U.S. hydropower resources

    SciTech Connect (OSTI)

    Hall, Douglas G.; Hunt, Richard T.; Reeves, Kelly S.; Carroll, Greg R.

    2003-06-01

    Tools for estimating the cost of developing and operating and maintaining hydropower resources in the form of regression curves were developed based on historical plant data. Development costs that were addressed included: licensing, construction, and five types of environmental mitigation. It was found that the data for each type of cost correlated well with plant capacity. A tool for estimating the annual and monthly electric generation of hydropower resources was also developed. Additional tools were developed to estimate the cost of upgrading a turbine or a generator. The development and operation and maintenance cost estimating tools, and the generation estimating tool were applied to 2,155 U.S. hydropower sites representing a total potential capacity of 43,036 MW. The sites included totally undeveloped sites, dams without a hydroelectric plant, and hydroelectric plants that could be expanded to achieve greater capacity. Site characteristics and estimated costs and generation for each site were assembled in a database in Excel format that is also included within the EERE Library under the title, “Estimation of Economic Parameters of U.S. Hydropower Resources - INL Hydropower Resource Economics Database.”

  17. Property:Estimated End Date | Open Energy Information

    Open Energy Info (EERE)

    Estimated End Date Jump to: navigation, search Property Name Estimated End Date Property Type String Pages using the property "Estimated End Date" Showing 4 pages using this...

  18. "Table A38. Total Expenditures for Purchased Electricity, Steam, and Natural Gas"

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

    8. Total Expenditures for Purchased Electricity, Steam, and Natural Gas" " by Type of Supplier, Census Region, Census Division, Industry Group," " and Selected Industries, 1994" " (Estimates in Million Dollars)" ,," Electricity",," Steam" ,,,,,,"RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Row" "Code(a)","Industry Group and

  19. "Table A46. Total Expenditures for Purchased Electricity, Steam, and Natural"

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

    6. Total Expenditures for Purchased Electricity, Steam, and Natural" " Gas by Type of Supplier, Census Region, Industry Group, and Selected Industries," 1991 " (Estimates in Million Dollars)" ,," Electricity",," Steam",," Natural Gas" ,,"-","-----------","-","-----------","-","------------","-","RSE"

  20. 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

  1. 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

  2. TOTAL WORKFORCE Males

    National Nuclear Security Administration (NNSA)

    76 Females Male Female Male Female Male Female Male Female Male Female 27 24 86 134 65 24 192 171 1189 423 PAY PLAN SES 96 EX 4 EJ/EK 60 EN 05 39 EN 04 159 EN 03 21 EN 00 8 NN (Engineering) 398 NQ (Prof/Tech/Admin) 1165 NU (Tech/Admin Support) 54 NV (Nuc Mat Courier) 325 GS 15 3 GS 14 1 GS 13 1 GS 10 1 Total includes 2318 permanent and 17 temporary employees. DIVERSITY 2335 1559 66.8% American Indian Alaska Native African American Asian American Pacific Islander Hispanic White 33.2% National

  3. Physisorption and Chemisorption Methods for Evaluating the Total...

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

    Physisorption and Chemisorption Methods for Evaluating the Total Surface Area and Active Surface Area of Two Types of Carbon Materials Physisorption and Chemisorption Methods for ...

  4. Crude Oil and Petroleum Products Total Stocks Stocks by Type

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

    Product: Crude Oil and Petroleum Products Crude Oil All Oils (Excluding Crude Oil) Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Butylene Other Hydrocarbons Oxygenates (excluding Fuel Ethanol) MTBE Other Oxygenates Renewables (including Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Unfinished Oils Unfinished Oils, Naphthas & Lighter Unfinished Oils, Kerosene & Light Gas Unfinished Oils, Heavy Gas Oils

  5. 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.

  6. Estimate of federal relighting potential and demand for efficient lighting products

    SciTech Connect (OSTI)

    Shankle, S.A.; Dirks, J.A.; Elliott, D.B.; Richman, E.E.; Grover, S.E.

    1993-11-01

    The increasing level of electric utility rebates for energy-efficient lighting retrofits has recently prompted concern over the adequacy of the market supply of energy-efficient lighting products (Energy User News 1991). In support of the U.S. Department of Energy`s Federal Energy Management Program, Pacific Northwest Laboratory (PNL) has developed an estimate of the total potential for energy-efficient lighting retrofits in federally owned buildings. This estimate can be used to address the issue of the impact of federal relighting projects on the supply of energy-efficient lighting products. The estimate was developed in 1992, using 1991 data. Any investments in energy-efficient lighting products that occurred in 1992 will reduce the potential estimated here. This analysis proceeds by estimating the existing stock of lighting fixtures in federally owned buildings. The lighting technology screening matrix is then used to determine the minimum life-cycle cost retrofit for each type of existing lighting fixture. Estimates of the existing stock are developed for (1) four types of fluorescent lighting fixtures (2-, 3-, and 4-lamp, F40 4-foot fixtures, and 2-lamp, F96 8-foot fixtures, all with standard magnetic ballasts); (2) one type of incandescent fixture (a 75-watt single bulb fixture); and (3) one type of exit sign (containing two 20-watt incandescent bulbs). Estimates of the existing stock of lighting fixtures in federally owned buildings, estimates of the total potential demand for energy-efficient lighting products if all cost-effective retrofits were undertaken immediately, and total potential annual energy savings (in MWh and dollars), the total investment required to obtain the energy savings and the present value of the efficiency investment, are presented.

  7. Supercooled liquid water Estimation Tool

    Energy Science and Technology Software Center (OSTI)

    2012-05-04

    The Cloud Supercooled liquid water Estimation Tool (SEET) is a user driven Graphical User Interface (GUI) that estimates cloud supercooled liquid water (SLW) content in terms of vertical column and total mass from Moderate resolution Imaging Supercooled liquid water Estimation Tool Spectroradiometer (MODIS) spatially derived cloud products and realistic vertical cloud parameterizations that are user defined. It also contains functions for post-processing of the resulting data in tabular and graphical form.

  8. 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.

  9. Estimates of particulate mass in multi-canister overpacks

    SciTech Connect (OSTI)

    SLOUGHTER, J.P.

    1999-02-25

    High, best estimate, and low values are developed for particulate inventories within MCO baskets that have been loaded with freshly cleaned fuel assemblies and scrap. These per-basket estimates are then applied to all anticipated MCO payload configurations to identify which configurations are bounding for each type of particulate. Finally the resulting bounding and nominal values for residual particulates are combined with corresponding values [from other documents] for particulate that may be generated by corrosion of exposed uranium after the fuel has been cleaned. The resulting rounded nominal estimate for a typical MCO after 40 years of storage is 8 kg. The estimate for a bounding total particulate case MCO is that it may contain up to 64 kg of particulate after 40 years of storage.

  10. Estimates of Particulate Mass in Multi Canister Overpacks (MCO)

    SciTech Connect (OSTI)

    SLOUGHTER, J.P.

    2000-02-16

    High, best estimate, and low values are developed for particulate inventories within MCO baskets that have been loaded with freshly cleaned fuel assemblies and scrap. These per-basket estimates are then applied to all anticipated MCO payload configurations to identify which configurations are bounding for each type of particulate. Finally the resulting bounding and nominal values for residual particulates are combined with corresponding values [from other documents] for particulates that may be generated by corrosion of exposed uranium after the fuel has been cleaned. The resulting rounded nominal estimate for a typical MCO after 40 years of storage is 8 kg. The estimate for a bounding total particulate case MCO is that it may contain up to 64 kg of particulate after 40 years of storage.

  11. U.S. Total Exports

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

    Barbados 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 Warroad, MN Babb, MT Havre, MT Port of Morgan, MT Sherwood, ND Pittsburg, NH Buffalo, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to Egypt Freeport, TX Total to India

  12. 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...

  13. Examples of Cost Estimation Packages

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

    1997-03-28

    Estimates can be performed in a variety of ways. Some of these are for projects for an undefined scope, a conventional construction project, or where there is a level of effort required to complete the work. Examples of cost estimation packages for these types of projects are described in this appendix.

  14. Estimates of Savings Achievable from Irrigation Controller

    SciTech Connect (OSTI)

    Williams, Alison; Fuchs, Heidi; Whitehead, Camilla Dunham

    2014-03-28

    This paper performs a literature review and meta-analysis of water savings from several types of advanced irrigation controllers: rain sensors (RS), weather-based irrigation controllers (WBIC), and soil moisture sensors (SMS).The purpose of this work is to derive average water savings per controller type, based to the extent possible on all available data. After a preliminary data scrubbing, we utilized a series of analytical filters to develop our best estimate of average savings. We applied filters to remove data that might bias the sample such as data self-reported by manufacturers, data resulting from studies focusing on high-water users, or data presented in a non-comparable format such as based on total household water use instead of outdoor water use. Because the resulting number of studies was too small to be statistically significant when broken down by controller type, this paper represents a survey and synthesis of available data rather than a definitive statement regarding whether the estimated water savings are representative.

  15. 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

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

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

  17. 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

  18. 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

  19. 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

  20. 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

  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

    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

  3. 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

  4. 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

  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 37.8 3.4 2.2 7.0 3.1 With a Heat Pump....................................... 12.3 9.7 0.6 0.5 1.0 0.6 Window/Wall Units.......................................... 28.9 14.9 2.3 3.5 6.0 2.1 1 Unit........................................................... 14.5 6.6 1.0 1.6 4.2 1.2 2

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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 Cooling Equipment........................................... 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it.......................... 1.9 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat

  15. 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

  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 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

  17. 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

  18. 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

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

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

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

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

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

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

  1. 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

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

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

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

  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 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

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

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

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

    ... Basements Basement in Single-Family Homes and Apartments in 2-4 Unit Buildings ... Attics Attic in Single-Family Homes and Apartments in 2-4 Unit Buildings ...

  6. Total

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

    ... Climate region 3 Very coldCold 31,898 30,469 28,057 28,228 21,019 30,542 25,067 Mixed-humid 27,873 26,716 24,044 26,365 21,026 27,096 22,812 Mixed-dryHot-dry 12,037 10,484 7,628 ...

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

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

    Air-Conditioning Equipment 1, 2 Central System......Central Air-Conditioning...... 65.9 1.1 6.4 6.4 ...

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

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

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

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

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

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

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

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

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

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

    Gasoline and Diesel Fuel Update (EIA)

    ... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ...

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

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

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

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

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

    ... Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005 Below Poverty ... Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005 Below Poverty ...

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

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

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

  15. Total

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

    1,001 to 5,000 2,777 8,041 10,232 2.9 786 56 5,001 to 10,000 1,229 8,900 9,225 7.2 965 62 10,001 to 25,000 884 14,105 14,189 16.0 994 65 25,001 to 50,000 332 11,917 11,327 35.9 1,052 72 50,001 to 100,000 199 13,918 12,345 69.9 1,127 80 100,001 to 200,000 90 12,415 11,310 137.9 1,098 89 200,001 to 500,000 38 10,724 10,356 284.2 1,035 99 Over 500,000 8 7,074 9,196 885.0 769 117 Principal building activity Education 389 12,239 10,885 31.5 1,124 53 Food sales 177 1,252 1,172 7.1 1,067 121 Food

  16. Total

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

    1,001 to 5,000 2,777 8,041 10,232 2.9 786 56 5,001 to 10,000 1,229 8,900 9,225 7.2 965 62 10,001 to 25,000 884 14,105 14,189 16.0 994 65 25,001 to 50,000 332 11,917 11,327 35.9 1,052 72 50,001 to 100,000 199 13,918 12,345 69.9 1,127 80 100,001 to 200,000 90 12,415 11,310 137.9 1,098 89 200,001 to 500,000 38 10,724 10,356 284.2 1,035 99 Over 500,000 8 7,074 9,196 885.0 769 117 Principal building activity Education 389 12,239 10,885 31.5 1,124 53 Food sales 177 1,252 1,172 7.1 1,067 121 Food

  17. Total

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

    1,001 to 5,000 2,777 8,041 10,232 2.9 786 56 5,001 to 10,000 1,229 8,900 9,225 7.2 965 62 10,001 to 25,000 884 14,105 14,189 16.0 994 65 25,001 to 50,000 332 11,917 11,327 35.9 1,052 72 50,001 to 100,000 199 13,918 12,345 69.9 1,127 80 100,001 to 200,000 90 12,415 11,310 137.9 1,098 89 200,001 to 500,000 38 10,724 10,356 284.2 1,035 99 Over 500,000 8 7,074 9,196 885.0 769 117 Principal building activity Education 389 12,239 10,885 31.5 1,124 53 Food sales 177 1,252 1,172 7.1 1,067 121 Food

  18. Total

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

    Median square feet per building (thousand) Median square feet per worker Median operating hours per week Median age of buildings (years) All buildings 5,557 87,093 88,182 5.0 1,029 50 32 Building floorspace (square feet) 1,001 to 5,000 2,777 8,041 10,232 2.8 821 49 37 5,001 to 10,000 1,229 8,900 9,225 7.0 1,167 50 31 10,001 to 25,000 884 14,105 14,189 15.0 1,444 56 32 25,001 to 50,000 332 11,917 11,327 35.0 1,461 60 29 50,001 to 100,000 199 13,918 12,345 67.0 1,442 60 26 100,001 to 200,000 90

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

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

    ... Housing Units (millions) UrbanRural Location (as Self-Reported) Living Space ... Housing Units (millions) UrbanRural Location (as Self-Reported) Living Space ...

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

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

    ... Housing Units (millions) UrbanRural Location (as Self-Reported) City Town Suburbs Rural ... Housing Units (millions) UrbanRural Location (as Self-Reported) City Town Suburbs Rural ...

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

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

    Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 ...

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

    Gasoline and Diesel Fuel Update (EIA)

    Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy ...

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

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

    ... Per Household Member Average Square Feet Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC1.2.2 ...

  4. 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 ...

  5. 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......

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

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

    ... Average Square Feet per Apartment in a -- Apartments (millions) Major Outside Wall Construction Siding (Aluminum, Vinyl, Steel)...... 35.3 3.5 1,286 1,090 325 852 786 461 ...

  7. Physisorption and Chemisorption Methods for Evaluating the Total Surface

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

    Area and Active Surface Area of Two Types of Carbon Materials | Department of Energy Physisorption and Chemisorption Methods for Evaluating the Total Surface Area and Active Surface Area of Two Types of Carbon Materials Physisorption and Chemisorption Methods for Evaluating the Total Surface Area and Active Surface Area of Two Types of Carbon Materials TSA is a gross indicator of soot reactivity and does not always correlate well with the real reactivity. This research shows that a more

  8. Property:Number of Plants included in Capacity Estimate | Open...

    Open Energy Info (EERE)

    Plants included in Capacity Estimate Jump to: navigation, search Property Name Number of Plants included in Capacity Estimate Property Type Number Retrieved from "http:...

  9. Property:Number of Plants Included in Planned Estimate | Open...

    Open Energy Info (EERE)

    Number of Plants Included in Planned Estimate Jump to: navigation, search Property Name Number of Plants Included in Planned Estimate Property Type String Description Number of...

  10. 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

  11. Apparatus and method for quantitatively evaluating total fissile and total fertile nuclide content in samples

    DOE Patents [OSTI]

    Caldwell, John T.; Kunz, Walter E.; Cates, Michael R.; Franks, Larry A.

    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.

  12. Property:EstimatedCostLowUSD | Open Energy Information

    Open Energy Info (EERE)

    Name EstimatedCostLowUSD Property Type Quantity Description the low estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one...

  13. Property:EstimatedCostHighUSD | Open Energy Information

    Open Energy Info (EERE)

    Name EstimatedCostHighUSD Property Type Quantity Description the high estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one...

  14. Property:EstimatedCostMedianUSD | Open Energy Information

    Open Energy Info (EERE)

    Name EstimatedCostMedianUSD Property Type Quantity Description the median estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one...

  15. 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...

  16. ARM - Measurement - Total cloud water

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

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

  17. Property:RenewableFuelStandard/Total | Open Energy Information

    Open Energy Info (EERE)

    Property Edit with form History Facebook icon Twitter icon Property:RenewableFuelStandardTotal Jump to: navigation, search This is a property of type Number. Pages using the...

  18. Award Number: Federal Non-Federal Federal Non-Federal Total

    Office of Environmental Management (EM)

    B - Budget Categories Catalog of Federal Domestic Assistance Number Grant Program Function or Activity Estimated Unobligated Funds e. Supplies i. Total Direct Charges (sum of...

  19. Estimates of Green potentials. Applications

    SciTech Connect (OSTI)

    Danchenko, V I

    2003-02-28

    Optimal Cartan-type covers by hyperbolic discs of carriers of Green {alpha}-potentials are obtained in a simply connected domain in the complex plane and estimates of the potentials outside the carriers are presented. These results are applied to problems on the separation of singularities of analytic and harmonic functions. For instance, uniform and integral estimates in terms of Green capacities of components of meromorphic functions are obtained.

  20. Total aerosol effect: forcing or radiative flux perturbation?

    SciTech Connect (OSTI)

    Lohmann, Ulrike; Storelvmo, Trude; Jones, Andy; Rotstayn, Leon; Menon, Surabi; Quaas, Johannes; Ekman, Annica; Koch, Dorothy; Ruedy, Reto

    2009-09-25

    Uncertainties in aerosol forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of rain formation. Traditionally these feedbacks were not included in estimates of total aerosol forcing. Here we argue that they should be included because these feedbacks act quickly compared with the time scale of global warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Thus we propose replacing the direct and indirect aerosol forcing in the IPCC forcing chart with RFP estimates. This implies that it is better to evaluate the total anthropogenic aerosol effect as a whole.

  1. Cost estimate for muddy water palladium production facility at Mound

    SciTech Connect (OSTI)

    McAdams, R.K.

    1988-11-30

    An economic feasibility study was performed on the ''Muddy Water'' low-chlorine content palladium powder production process developed by Mound. The total capital investment and total operating costs (dollars per gram) were determined for production batch sizes of 1--10 kg in 1-kg increments. The report includes a brief description of the Muddy Water process, the process flow diagram, and material balances for the various production batch sizes. Two types of facilities were evaluated--one for production of new, ''virgin'' palladium powder, and one for recycling existing material. The total capital investment for virgin facilities ranged from $600,000 --$1.3 million for production batch sizes of 1--10 kg, respectively. The range for recycle facilities was $1--$2.3 million. The total operating cost for 100% acceptable powder production in the virgin facilities ranged from $23 per gram for a 1-kg production batch size to $8 per gram for a 10-kg batch size. Similarly for recycle facilities, the total operating cost ranged from $34 per gram to $5 per gram. The total operating cost versus product acceptability (ranging from 50%--100% acceptability) was also evaluated for both virgin and recycle facilities. Because production sizes studied vary widely and because scale-up factors are unknown for batch sizes greater than 1 kg, all costs are ''order-of-magnitude'' estimates. All costs reported are in 1987 dollars.

  2. 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

  3. Airborne aerosol in situ measurements during TCAP: A closure study of total scattering

    SciTech Connect (OSTI)

    Kassianov, Evgueni; Sedlacek, Arthur; Berg, Larry K.; Pekour, Mikhail; Barnard, James; Chand, Duli; Flynn, Connor; Ovchinnikov, Mikhail; Schmid, Beat; Shilling, John; Tomlinson, Jason; Fast, Jerome

    2015-07-31

    We present a framework for calculating the total scattering of both non-absorbing and absorbing aerosol at ambient conditions from aircraft data. Our framework is developed emphasizing the explicit use of chemical composition data for estimating the complex refractive index (RI) of particles, and thus obtaining improved ambient size spectra derived from Optical Particle Counter (OPC) measurements. The feasibility of our framework for improved calculations of total scattering is demonstrated using three types of data collected by the U.S. Department of Energy’s (DOE) aircraft during the Two-Column Aerosol Project (TCAP). Namely, these data types are: (1) size distributions measured by a suite of OPC’s; (2) chemical composition data measured by an Aerosol Mass Spectrometer and a Single Particle Soot Photometer; and (3) the dry total scattering coefficient measured by a integrating nephelometer and scattering enhancement factor measured with a humidification system. We demonstrate that good agreement (~10%) between the observed and calculated scattering can be obtained under ambient conditions (RH < 80%) by applying chemical composition data for the RI-based correction of the OPC-derived size spectra. We also demonstrate that ignoring the RI-based correction or using non-representative RI values can cause a substantial underestimation (~40%) or overestimation (~35%) of the calculated scattering, respectively.

  4. Airborne aerosol in situ measurements during TCAP: A closure study of total scattering

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

    Kassianov, Evgueni; Sedlacek, Arthur; Berg, Larry K.; Pekour, Mikhail; Barnard, James; Chand, Duli; Flynn, Connor; Ovchinnikov, Mikhail; Schmid, Beat; Shilling, John; et al

    2015-07-31

    We present a framework for calculating the total scattering of both non-absorbing and absorbing aerosol at ambient conditions from aircraft data. Our framework is developed emphasizing the explicit use of chemical composition data for estimating the complex refractive index (RI) of particles, and thus obtaining improved ambient size spectra derived from Optical Particle Counter (OPC) measurements. The feasibility of our framework for improved calculations of total scattering is demonstrated using three types of data collected by the U.S. Department of Energy’s (DOE) aircraft during the Two-Column Aerosol Project (TCAP). Namely, these data types are: (1) size distributions measured by amore » suite of OPC’s; (2) chemical composition data measured by an Aerosol Mass Spectrometer and a Single Particle Soot Photometer; and (3) the dry total scattering coefficient measured by a integrating nephelometer and scattering enhancement factor measured with a humidification system. We demonstrate that good agreement (~10%) between the observed and calculated scattering can be obtained under ambient conditions (RH < 80%) by applying chemical composition data for the RI-based correction of the OPC-derived size spectra. We also demonstrate that ignoring the RI-based correction or using non-representative RI values can cause a substantial underestimation (~40%) or overestimation (~35%) of the calculated scattering, respectively.« less

  5. Million Cu. Feet Percent of National Total

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

    0 New Hampshire - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle ...

  6. Total Number of Operable Refineries

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

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

  7. Development of surface mine cost estimating equations

    SciTech Connect (OSTI)

    Not Available

    1980-09-26

    Cost estimating equations were developed to determine capital and operating costs for five surface coal mine models in Central Appalachia, Northern Appalachia, Mid-West, Far-West, and Campbell County, Wyoming. Engineering equations were used to estimate equipment costs for the stripping function and for the coal loading and hauling function for the base case mine and for several mines with different annual production levels and/or different overburden removal requirements. Deferred costs were then determined through application of the base case depreciation schedules, and direct labor costs were easily established once the equipment quantities (and, hence, manpower requirements) were determined. The data points were then fit with appropriate functional forms, and these were then multiplied by appropriate adjustment factors so that the resulting equations yielded the model mine costs for initial and deferred capital and annual operating cost. (The validity of this scaling process is based on the assumption that total initial and deferred capital costs are proportional to the initial and deferred costs for the primary equipment types that were considered and that annual operating cost is proportional to the direct labor costs that were determined based on primary equipment quantities.) Initial capital costs ranged from $3,910,470 in Central Appalachia to $49,296,785; deferred capital costs ranged from $3,220,000 in Central Appalachia to $30,735,000 in Campbell County, Wyoming; and annual operating costs ranged from $2,924,148 in Central Appalachia to $32,708,591 in Campbell County, Wyoming. (DMC)

  8. Design Storm for Total Retention.pdf

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

    Title: Design Storm for "Total Retention" under Individual Permit, Poster, Individual ... International. Environmental Programs Design Storm for "Total Retention" under ...

  9. U.S. Department of Energy Releases Revised Total System Life Cycle Cost

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

    Estimate and Fee Adequacy Report for Yucca Mountain Project | Department of Energy Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report for Yucca Mountain Project U.S. Department of Energy Releases Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report for Yucca Mountain Project August 5, 2008 - 2:40pm Addthis WASHINGTON, DC -The U.S. Department of Energy (DOE) today released a revised estimate of the total system life cycle cost for a repository at Yucca

  10. U.S. Total Imports

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

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

  11. Total Imports of Residual Fuel

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

    Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S. Total 9,010 5,030 8,596 6,340 4,707 8,092 1936-2016 PAD District 1 3,127 2,664 2,694 1,250 1,327 2,980 1981-2016 Connecticut 1995-2015 Delaware 280 1995-2016 Florida 858 649 800 200 531 499 1995-2016 Georgia 210 262 149 106 1995-2016 Maine 1995-2015 Maryland 84 1995-2016 Massachusetts 1995-2015 New Hampshire 1995-2015 New Jersey 1,283 843 1,073 734 355 1,984 1995-2016 New York 234 824 210 196 175 1995-2016 North Carolina 1995-2011

  12. Total quality management implementation guidelines

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

    These Guidelines were designed by the Energy Quality Council to help managers and supervisors in the Department of Energy Complex bring Total Quality Management to their organizations. Because the Department is composed of a rich mixture of diverse organizations, each with its own distinctive culture and quality history, these Guidelines are intended to be adapted by users to meet the particular needs of their organizations. For example, for organizations that are well along on their quality journeys and may already have achieved quality results, these Guidelines will provide a consistent methodology and terminology reference to foster their alignment with the overall Energy quality initiative. For organizations that are just beginning their quality journeys, these Guidelines will serve as a startup manual on quality principles applied in the Energy context.

  13. Total Imports of Residual Fuel

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

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

  14. 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

  15. Total quality management program planning

    SciTech Connect (OSTI)

    Thornton, P.T.; Spence, K.

    1994-05-01

    As government funding grows scarce, competition between the national laboratories is increasing dramatically. In this era of tougher competition, there is no for resistance to change. There must instead be a uniform commitment to improving the overall quality of our products (research and technology) and an increased focus on our customers` needs. There has been an ongoing effort to bring the principles of total quality management (TQM) to all Energy Systems employees to help them better prepare for future changes while responding to the pressures on federal budgets. The need exists for instituting a vigorous program of education and training to an understanding of the techniques needed to improve and initiate a change in organizational culture. The TQM facilitator is responsible for educating the work force on the benefits of self-managed work teams, designing a program of instruction for implementation, and thus getting TQM off the ground at the worker and first-line supervisory levels so that the benefits can flow back up. This program plan presents a conceptual model for TQM in the form of a hot air balloon. In this model, there are numerous factors which can individually and collectively impede the progress of TQM within the division and the Laboratory. When these factors are addressed and corrected, the benefits of TQM become more visible. As this occurs, it is hoped that workers and management alike will grasp the ``total quality`` concept as an acceptable agent for change and continual improvement. TQM can then rise to the occasion and take its rightful place as an integral and valid step in the Laboratory`s formula for survival.

  16. Estimating electron drift velocities in magnetron discharges...

    Office of Scientific and Technical Information (OSTI)

    Citation Details In-Document Search Title: Estimating ... OSTI Identifier: 1172974 Report Number(s): LBNL-5865E DOE Contract Number: DE-AC02-05CH11231 Resource Type: Journal ...

  17. State energy data report 1994: Consumption estimates

    SciTech Connect (OSTI)

    1996-10-01

    This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.

  18. Award Types

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

    Awards Team (505) 667-7824 Email Types of Awards The Awards Office, sponsored by the Technology Transfer Division and the Science and Technology Base Program Office, coordinates...

  19. Cost Estimation Package

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

    1997-03-28

    This chapter focuses on the components (or elements) of the cost estimation package and their documentation.

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. ,"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)" ...

  6. ,"Total Crude Oil and Petroleum Products Exports"

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

    Data for" ,"Data 1","Total Crude Oil and Petroleum Products ... "Back to Contents","Data 1: Total Crude Oil and Petroleum Products Exports" ...

  7. ,"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)" ...

  8. ,"North Dakota Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","North Dakota Natural Gas Total Consumption ... 9:10:34 AM" "Back to Contents","Data 1: North Dakota Natural Gas Total Consumption ...

  9. ,"North Carolina Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","North Carolina Natural Gas Total Consumption ... 9:10:33 AM" "Back to Contents","Data 1: North Carolina Natural Gas Total Consumption ...

  10. Using Utility Load Data to Estimate Demand for Space Cooling and Potential for Shiftable Loads

    SciTech Connect (OSTI)

    Denholm, P.; Ong, S.; Booten, C.

    2012-05-01

    This paper describes a simple method to estimate hourly cooling demand from historical utility load data. It compares total hourly demand to demand on cool days and compares these estimates of total cooling demand to previous regional and national estimates. Load profiles generated from this method may be used to estimate the potential for aggregated demand response or load shifting via cold storage.

  11. The Federal Highway Administration Gasohol Consumption Estimation Model

    SciTech Connect (OSTI)

    Hwang, HL

    2003-08-28

    The Federal Highway Administration (FHWA) is responsible for estimating the portion of Federal highway funds attributable to each State. The process involves use of State-reported data (gallons) and a set of estimation models when accurate State data is unavailable. To ensure that the distribution of funds is equitable, FHWA periodically reviews the estimation models. Estimation of the use of gasohol is difficult because of State differences in the definition of gasohol, inability of many States to separate and report gasohol usage from other fuel types, changes in fuel composition in nonattainment areas to address concerns over the use of certain fuel additives, and the lack of a valid State-level surrogate data set for gasohol use. Under the sponsorship of FHWA, Oak Ridge National Laboratory (ORNL) reviewed the regression-based gasohol estimation model that has been in use for several years. Based on an analytical assessment of that model and an extensive review of potential data sets, ORNL developed an improved rule-based model. The new model uses data from Internal Revenue Service, Energy Information Administration, Environmental Protection Agency, Department of Energy, ORNL, and FHWA sources. The model basically consists of three parts: (1) development of a controlled total of national gasohol usage, (2) determination of reliable State gasohol consumption data, and (3) estimation of gasohol usage for all other States. The new model will be employed for the 2004 attribution process. FHWA is currently soliciting comments and inputs from interested parties. Relevant data, as identified, will be pursued and refinements will be made by the research team if warranted.

  12. FY 2007 Total System Life Cycle Cost, Pub 2008 | Department of Energy

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

    FY 2007 Total System Life Cycle Cost, Pub 2008 FY 2007 Total System Life Cycle Cost, Pub 2008 The Analysis of the Total System Life Cycle Cost (TSLCC) of the Civilian Radioactive Waste Management Program presents the Office of Civilian Radioactive Waste Management's (OCRWM) May 2007 total system cost estimate for the disposal of the Nation's spent nuclear fuel (SNF) and high-level radioactive waste (HLW). The TSLCC analysis provides a basis for assessing the adequacy of the Nuclear Waste Fund

  13. " Level: National Data and Regional Totals...

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

    ... by" "petroleum refineries, rather than purchased ... ,,"Total United States" ,"RSE Column ... 324,"Petroleum and Coal ...

  14. Apparatus and method for quantitatively evaluating total fissile and total fertile nuclide content in samples. [Patent application

    DOE Patents [OSTI]

    Caldwell, J.T.; Kunz, W.E.; Cates, M.R.; Franks, L.A.

    1982-07-07

    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 fission 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.

  15. Site: Contract Name: Contractor: Contract Number: Contract Type:

    Office of Environmental Management (EM)

    Contractor: Contract Number: Contract Type: Total Estimated Contract Cost: Contract Base Period: Contract Option Period: Minimum Fee Maximum Fee Performance Period Fee Available Fee Earned FY2011 $6,190,992 $5,779,687 FY2012 $16,380,944 $14,173,044 FY2013 $16,972,816 $12,693,413 FY2014 $15,520,007 $13,207,526 FY2015 $14,269,197 $10,503,998 FY2016 Base Period $24,350,863 March 29, 2016- September 30, 2017 $28,251,114 $6,823,811 October 1, 2017- September 30, 2018 $18,834,076 October 1, 2018-

  16. Process Equipment Cost Estimation, Final Report

    SciTech Connect (OSTI)

    H.P. Loh; Jennifer Lyons; Charles W. White, III

    2002-01-01

    This report presents generic cost curves for several equipment types generated using ICARUS Process Evaluator. The curves give Purchased Equipment Cost as a function of a capacity variable. This work was performed to assist NETL engineers and scientists in performing rapid, order of magnitude level cost estimates or as an aid in evaluating the reasonableness of cost estimates submitted with proposed systems studies or proposals for new processes. The specific equipment types contained in this report were selected to represent a relatively comprehensive set of conventional chemical process equipment types.

  17. State Energy Production Estimates

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

    Energy Production Estimates 1960 Through 2012 2012 Summary Tables Table P1. Energy Production Estimates in Physical Units, 2012 Alabama 19,455 215,710 9,525 0 Alaska 2,052 351,259...

  18. BatPRO: Battery Manufacturing Cost Estimation | Argonne National...

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

    BatPRO: Battery Manufacturing Cost Estimation BatPRO models a stiff prismatic pouch-type cell battery pack with cells linked in series. BatPRO models a stiff prismatic pouch-type ...

  19. U.S. Department of Energy Releases Revised Total System Life...

    Energy Savers [EERE]

    U.S. Department of Energy Releases Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report ... U.S. Department of Energy Awards Contracts for Waste Storage Canisters for ...

  20. 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...

  1. 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.

  2. 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

  3. 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

  4. Million Cu. Feet Percent of National Total

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

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

  5. 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

  6. Million Cu. Feet Percent of National Total

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

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

  7. 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

  8. Total Activity Estimation - Quarry Area. QY-500-501-1.06.

    Office of Legacy Management (LM)

  9. Type: Renewal

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

    1 INCITE Awards Type: Renewal Title: -Ab Initio Dynamical Simulations for the Prediction of Bulk Properties‖ Principal Investigator: Theresa Windus, Iowa State University Co-Investigators: Brett Bode, Iowa State University Graham Fletcher, Argonne National Laboratory Mark Gordon, Iowa State University Monica Lamm, Iowa State University Michael Schmidt, Iowa State University Scientific Discipline: Chemistry: Physical INCITE Allocation: 10,000,000 processor hours Site: Argonne National

  10. Facility Type!

    Office of Legacy Management (LM)

    ITY: --&L~ ----------- srct-r~ -----------~------~------- if yee, date contacted ------------- cl Facility Type! i I 0 Theoretical Studies Cl Sample 84 Analysis ] Production 1 Diepasal/Storage 'YPE OF CONTRACT .--------------- 1 Prime J Subcontract&- 1 Purchase Order rl i '1 ! Other information (i.e., ---------~---~--~-------- :ontrait/Pirchaee Order # , I C -qXlJ- --~-------~~-------~~~~~~ I I ~~~---~~~~~~~T~~~ FONTRACTING PERIODi IWNERSHIP: ,I 1 AECIMED AECMED GOVT GOUT &NTtiAC+OR

  11. Reservoir Temperature Estimator

    Energy Science and Technology Software Center (OSTI)

    2014-12-08

    The Reservoir Temperature Estimator (RTEst) is a program that can be used to estimate deep geothermal reservoir temperature and chemical parameters such as CO2 fugacity based on the water chemistry of shallower, cooler reservoir fluids. This code uses the plugin features provided in The Geochemist’s Workbench (Bethke and Yeakel, 2011) and interfaces with the model-independent parameter estimation code Pest (Doherty, 2005) to provide for optimization of the estimated parameters based on the minimization of themore » weighted sum of squares of a set of saturation indexes from a user-provided mineral assemblage.« less

  12. 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

  13. Million Cu. Feet Percent of National Total

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

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

  14. Million Cu. Feet Percent of National Total

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

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

  15. 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

  16. 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

  17. Million Cu. Feet Percent of National Total

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

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

  18. 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

  19. Million Cu. Feet Percent of National Total

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

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

  20. Million Cu. Feet Percent of National Total

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

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

  1. 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

  2. Million Cu. Feet Percent of National Total

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

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

  3. 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

  4. Million Cu. Feet Percent of National Total

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

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

  5. Million Cu. Feet Percent of National Total

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

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

  6. Million Cu. Feet Percent of National Total

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

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

  7. Million Cu. Feet Percent of National Total

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

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

  8. Million Cu. Feet Percent of National Total

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

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

  9. Million Cu. Feet Percent of National Total

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

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

  10. 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

  11. Million Cu. Feet Percent of National Total

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

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

  12. Million Cu. Feet Percent of National Total

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

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

  13. Million Cu. Feet Percent of National Total

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

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

  14. 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

  15. Million Cu. Feet Percent of National Total

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

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

  16. Million Cu. Feet Percent of National Total

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

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

  17. Million Cu. Feet Percent of National Total

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

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

  18. Million Cu. Feet Percent of National Total

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

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

  19. Million Cu. Feet Percent of National Total

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

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

  20. Million Cu. Feet Percent of National Total

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

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

  1. Type here

    Office of Environmental Management (EM)

    Injury at the Savannah River National Laboratory | Department of Energy January 10, 2006, Flash Fire and Injury at the Savannah River National Laboratory Type B Accident Investigation of the January 10, 2006, Flash Fire and Injury at the Savannah River National Laboratory February 1, 2006 On January 10, 2006, at approximately 7:47 a.m., a first-line manager (FLM) at the Savannah River National Laboratory (SRNL) received first- and second-degree burns to his head, face, neck, and left hand

  2. Estimating Specialty Costs

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

    1997-03-28

    Specialty costs are those nonstandard, unusual costs that are not typically estimated. Costs for research and development (R&D) projects involving new technologies, costs associated with future regulations, and specialty equipment costs are examples of specialty costs. This chapter discusses those factors that are significant contributors to project specialty costs and methods of estimating costs for specialty projects.

  3. Cost Estimating Handbook for Environmental Restoration

    SciTech Connect (OSTI)

    1990-09-01

    Environmental restoration (ER) projects have presented the DOE and cost estimators with a number of properties that are not comparable to the normal estimating climate within DOE. These properties include: An entirely new set of specialized expressions and terminology. A higher than normal exposure to cost and schedule risk, as compared to most other DOE projects, due to changing regulations, public involvement, resource shortages, and scope of work. A higher than normal percentage of indirect costs to the total estimated cost due primarily to record keeping, special training, liability, and indemnification. More than one estimate for a project, particularly in the assessment phase, in order to provide input into the evaluation of alternatives for the cleanup action. While some aspects of existing guidance for cost estimators will be applicable to environmental restoration projects, some components of the present guidelines will have to be modified to reflect the unique elements of these projects. The purpose of this Handbook is to assist cost estimators in the preparation of environmental restoration estimates for Environmental Restoration and Waste Management (EM) projects undertaken by DOE. The DOE has, in recent years, seen a significant increase in the number, size, and frequency of environmental restoration projects that must be costed by the various DOE offices. The coming years will show the EM program to be the largest non-weapons program undertaken by DOE. These projects create new and unique estimating requirements since historical cost and estimating precedents are meager at best. It is anticipated that this Handbook will enhance the quality of cost data within DOE in several ways by providing: The basis for accurate, consistent, and traceable baselines. Sound methodologies, guidelines, and estimating formats. Sources of cost data/databases and estimating tools and techniques available at DOE cost professionals.

  4. 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...

  5. Million Cu. Feet Percent of National Total

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

    Table S22. Summary statistics for natural gas - Maryland, 2010-2014 - continued -- Not applicable. < Percentage is less than 0.05 percent. E Estimated data. R Revised data. W ...

  6. Cost Estimating Guide

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

    2011-05-09

    This Guide provides uniform guidance and best practices that describe the methods and procedures that could be used in all programs and projects at DOE for preparing cost estimates.

  7. Cost Estimating Guide

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

    1997-03-28

    The objective of this Guide is to improve the quality of cost estimates and further strengthen the DOE program/project management system. The original 25 separate chapters and three appendices have been combined to create a single document.

  8. Cost Estimating Guide

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

    2011-05-09

    This Guide provides uniform guidance and best practices that describe the methods and procedures that could be used in all programs and projects at DOE for preparing cost estimates. No cancellations.

  9. Million U.S. Housing Units Total............................................................................

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

    Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Home Electronics Usage Indicators Detached Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of

  10. Total U.S. Housing Units.......................................

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

    ... Energy Information Administration 2005 Residential Energy ... Type of Supplemental Heating Equipment Used Heat Pump......0.6 SteamHot Water System......

  11. Total U.S. Housing Units.......................................

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

    ... 1.3 Q Q Q Energy Information Administration ... Type of Supplemental Heating Equipment Used Heat Pump......Q Q SteamHot Water System......

  12. Total U.S. Housing Units.................................

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

    At Home Behavior Home Used for Business Yes......Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units ...

  13. 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...

  14. Million Cu. Feet Percent of National Total

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

    -3,826 Total Supply 854,673 908,380 892,923 R 900,232 828,785 See footnotes at end of ... Gas Annual 165 Table S43. Summary statistics for natural gas - South Dakota, ...

  15. Total Ore Processing Integration and Management

    SciTech Connect (OSTI)

    Leslie Gertsch; Richard Gertsch

    2004-06-30

    This report outlines the technical progress achieved for project DE-FC26-03NT41785 (Total Ore Processing Integration and Management) during the period 01 April through 30 June of 2004.

  16. 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...

  17. 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...

  18. ARM - Measurement - Net broadband total irradiance

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

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

  19. ARM - Measurement - Shortwave broadband total downwelling irradiance

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

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

  20. Parametric Hazard Function Estimation.

    Energy Science and Technology Software Center (OSTI)

    1999-09-13

    Version 00 Phaze performs statistical inference calculations on a hazard function (also called a failure rate or intensity function) based on reported failure times of components that are repaired and restored to service. Three parametric models are allowed: the exponential, linear, and Weibull hazard models. The inference includes estimation (maximum likelihood estimators and confidence regions) of the parameters and of the hazard function itself, testing of hypotheses such as increasing failure rate, and checking ofmore » the model assumptions.« less

  1. ARM - Measurement - Shortwave spectral total downwelling irradiance

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

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

  2. REQUESTS FOR RETIREMENT ESTIMATE

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

    REQUEST FOR RETIREMENT ANNUITY ESTIMATE Instructions: Please read and answer the following questions thoroughly to include checking all applicable boxes. Unanswered questions may delay processing. Print and Fax back your request form to 202.586.6395 or drop request to GM-169. The request will be assigned to your servicing retirement specialist. They will confirm receipt of your request. SECTION A Request Submitted _____________________ ______________________ ________________________

  3. Population Estimates for Chum Salmon Spawning in the Mainstem Columbia River, 2002 Technical Report.

    SciTech Connect (OSTI)

    Rawding, Dan; Hillson, Todd D.

    2003-11-15

    Accurate and precise population estimates of chum salmon (Oncorhynchus keta) spawning in the mainstem Columbia River are needed to provide a basis for informed water allocation decisions, to determine the status of chum salmon listed under the Endangered Species Act, and to evaluate the contribution of the Duncan Creek re-introduction program to mainstem spawners. Currently, mark-recapture experiments using the Jolly-Seber model provide the only framework for this type of estimation. In 2002, a study was initiated to estimate mainstem Columbia River chum salmon populations using seining data collected while capturing broodstock as part of the Duncan Creek re-introduction. The five assumptions of the Jolly-Seber model were examined using hypothesis testing within a statistical framework, including goodness of fit tests and secondary experiments. We used POPAN 6, an integrated computer system for the analysis of capture-recapture data, to obtain maximum likelihood estimates of standard model parameters, derived estimates, and their precision. A more parsimonious final model was selected using Akaike Information Criteria. Final chum salmon escapement estimates and (standard error) from seining data for the Ives Island, Multnomah, and I-205 sites are 3,179 (150), 1,269 (216), and 3,468 (180), respectively. The Ives Island estimate is likely lower than the total escapement because only the largest two of four spawning sites were sampled. The accuracy and precision of these estimates would improve if seining was conducted twice per week instead of weekly, and by incorporating carcass recoveries into the analysis. Population estimates derived from seining mark-recapture data were compared to those obtained using the current mainstem Columbia River salmon escapement methodologies. The Jolly-Seber population estimate from carcass tagging in the Ives Island area was 4,232 adults with a standard error of 79. This population estimate appears reasonable and precise but batch

  4. Sorting through the many total-energy-cycle pathways possible with early plug-in hybrids.

    SciTech Connect (OSTI)

    Gaines, L.; Burnham, A.; Rousseau, A.; Santini, D.; Energy Systems

    2008-01-01

    Using the 'total energy cycle' methodology, we compare U.S. near term (to {approx}2015) alternative pathways for converting energy to light-duty vehicle kilometers of travel (VKT) in plug-in hybrids (PHEVs), hybrids (HEVs), and conventional vehicles (CVs). For PHEVs, we present total energy-per-unit-of-VKT information two ways (1) energy from the grid during charge depletion (CD); (2) energy from stored on-board fossil fuel when charge sustaining (CS). We examine 'incremental sources of supply of liquid fuel such as (a) oil sands from Canada, (b) Fischer-Tropsch diesel via natural gas imported by LNG tanker, and (c) ethanol from cellulosic biomass. We compare such fuel pathways to various possible power converters producing electricity, including (i) new coal boilers, (ii) new integrated, gasified coal combined cycle (IGCC), (iii) existing natural gas fueled combined cycle (NGCC), (iv) existing natural gas combustion turbines, (v) wood-to-electricity, and (vi) wind/solar. We simulate a fuel cell HEV and also consider the possibility of a plug-in hybrid fuel cell vehicle (FCV). For the simulated FCV our results address the merits of converting some fuels to hydrogen to power the fuel cell vs. conversion of those same fuels to electricity to charge the PHEV battery. The investigation is confined to a U.S. compact sized car (i.e. a world passenger car). Where most other studies have focused on emissions (greenhouse gases and conventional air pollutants), this study focuses on identification of the pathway providing the most vehicle kilometers from each of five feedstocks examined. The GREET 1.7 fuel cycle model and the new GREET 2.7 vehicle cycle model were used as the foundation for this study. Total energy, energy by fuel type, total greenhouse gases (GHGs), volatile organic compounds (VOC), carbon monoxide (CO), nitrogen oxides (NO{sub x}), fine particulate (PM2.5) and sulfur oxides (SO{sub x}) values are presented. We also isolate the PHEV emissions contribution

  5. U.S. Total No. 2 Distillate Prices by Sales Type

    Gasoline and Diesel Fuel Update (EIA)

    2010 2011 2012 2013 2014 2015 View History No. 2 Distillate Sales to End Users, Average 2.449 - - - - - 1983-2015 Residential 2.798 - - - - - 1978-2015 CommercialInstitutional ...

  6. U.S. Total Propane (Consumer Grade) Prices by Sales Type

    Gasoline and Diesel Fuel Update (EIA)

    Area: U.S. East Coast (PADD 1) New England (PADD 1A) Central Atlantic (PADD 1B) Lower Atlantic (PADD 1C) Midwest (PADD 2) Gulf Coast (PADD 3) Rocky Mountain (PADD 4) West Coast ...

  7. U.S. Total No. 2 Distillate Prices by Sales Type

    Gasoline and Diesel Fuel Update (EIA)

    Area: U.S. East Coast (PADD 1) New England (PADD 1A) Connecticut Maine Massachusetts New Hampshire Rhode Island Vermont Central Atlantic (PADD 1B) Delaware District of Columbia ...

  8. Residential Lighting End-Use Consumption Study: Estimation Framework and Initial Estimates

    SciTech Connect (OSTI)

    Gifford, Will R.; Goldberg, Miriam L.; Tanimoto, Paulo M.; Celnicker, Dane R.; Poplawski, Michael E.

    2012-12-01

    The U.S. DOE Residential Lighting End-Use Consumption Study is an initiative of the U.S. Department of Energy’s (DOE’s) Solid-State Lighting Program that aims to improve the understanding of lighting energy usage in residential dwellings. The study has developed a regional estimation framework within a national sample design that allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications (e.g., by dwelling type AND lamp type or fixture type AND control type).

  9. 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.

  10. Million Cu. Feet Percent of National Total

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

    R 196 184 Total Supply 2,627 2,619 2,689 R 2,855 2,928 See footnotes at end of table. 0 ... Gas Annual 105 Table S13. Summary statistics for natural gas - Hawaii, 2010-2014 - ...

  11. The Leica TCRA1105 Reflectorless Total Station

    SciTech Connect (OSTI)

    Gaudreault, F.

    2005-09-06

    This poster provides an overview of SLAC's TCRA1105 reflectorless total station for the Alignment Engineering Group. This instrument has shown itself to be very useful for planning new construction and providing quick measurements to difficult to reach or inaccessible surfaces.

  12. 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.

  13. "Table A22. Total Quantity of Purchased Energy Sources by Census Region,"

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

    2. Total Quantity of Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,"Natural",,,"Coke" " "," ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC","

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

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

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

  15. Patient dose estimation from CT scans at the Mexican National Neurology and Neurosurgery Institute

    SciTech Connect (OSTI)

    Alva-Sánchez, Héctor

    2014-11-07

    In the radiology department of the Mexican National Institute of Neurology and Neurosurgery, a dedicated institute in Mexico City, on average 19.3 computed tomography (CT) examinations are performed daily on hospitalized patients for neurological disease diagnosis, control scans and follow-up imaging. The purpose of this work was to estimate the effective dose received by hospitalized patients who underwent a diagnostic CT scan using typical effective dose values for all CT types and to obtain the estimated effective dose distributions received by surgical and non-surgical patients. Effective patient doses were estimated from values per study type reported in the applications guide provided by the scanner manufacturer. This retrospective study included all hospitalized patients who underwent a diagnostic CT scan between 1 January 2011 and 31 December 2012. A total of 8777 CT scans were performed in this two-year period. Simple brain scan was the CT type performed the most (74.3%) followed by contrasted brain scan (6.1%) and head angiotomography (5.7%). The average number of CT scans per patient was 2.83; the average effective dose per patient was 7.9 mSv; the mean estimated radiation dose was significantly higher for surgical (9.1 mSv) than non-surgical patients (6.0 mSv). Three percent of the patients had 10 or more brain CT scans and exceeded the organ radiation dose threshold set by the International Commission on Radiological Protection for deterministic effects of the eye-lens. Although radiation patient doses from CT scans were in general relatively low, 187 patients received a high effective dose (>20 mSv) and 3% might develop cataract from cumulative doses to the eye lens.

  16. Country/Continent Total Percent of U.S. Total Africa/Europe

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

    peak kilowatts Country/Continent Total Percent of U.S. Total Africa/Europe 53,898 29% Asia/Australia 107,460 59% South/Central America 11,692 6% Canada 4,378 2% Mexico 5,556 3% Total 182,984 100% Table 8. Destination of photovoltaic module export shipments, 2014 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.'

  17. Total Natural Gas Gross Withdrawals (Summary)

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

    Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From

  18. Magnetic nanoparticle temperature estimation

    SciTech Connect (OSTI)

    Weaver, John B.; Rauwerdink, Adam M.; Hansen, Eric W.

    2009-05-15

    The authors present a method of measuring the temperature of magnetic nanoparticles that can be adapted to provide in vivo temperature maps. Many of the minimally invasive therapies that promise to reduce health care costs and improve patient outcomes heat tissue to very specific temperatures to be effective. Measurements are required because physiological cooling, primarily blood flow, makes the temperature difficult to predict a priori. The ratio of the fifth and third harmonics of the magnetization generated by magnetic nanoparticles in a sinusoidal field is used to generate a calibration curve and to subsequently estimate the temperature. The calibration curve is obtained by varying the amplitude of the sinusoidal field. The temperature can then be estimated from any subsequent measurement of the ratio. The accuracy was 0.3 deg. K between 20 and 50 deg. C using the current apparatus and half-second measurements. The method is independent of nanoparticle concentration and nanoparticle size distribution.

  19. State Energy Production Estimates

    Gasoline and Diesel Fuel Update (EIA)

    Production Estimates 1960 Through 2014 2014 Summary Tables U.S. Energy Information Administration | State Energy Data 2014: Production 1 Table P1. Energy Production Estimates in Physical Units, 2014 Alabama 16,377 181,054 9,828 0 Alaska 1,502 345,331 181,175 0 Arizona 8,051 106 56 1,044 Arkansas 94 1,123,678 6,845 0 California 0 252,718 204,269 4,462 Colorado 24,007 1,631,391 95,192 3,133 Connecticut 0 0 0 0 Delaware 0 0 0 0 District of Columbia 0 0 0 0 Florida 0 369 2,227 0 Georgia 0 0 0 2,517

  20. Guidelines for Estimating Unmetered Landscaping Water Use | Department of

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

    Energy Landscaping Water Use Guidelines for Estimating Unmetered Landscaping Water Use Document describes the step-by-step instructions to estimate landscaping water using two alternative approaches: the evapotranspiration method and the irrigation audit method. This report presents annual irrigation factors for 36 cities across the United States that represent the gallons of irrigation required per square foot for distinct landscape types. Download the Guidelines for Estimating Unmetered

  1. 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.

  2. 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.

  3. Total Crude Oil and Petroleum Products Exports

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

    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 Kerosene and

  4. ARM - Measurement - Shortwave broadband total net irradiance

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

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

  5. ARM - Measurement - Shortwave narrowband total downwelling irradiance

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

    downwelling irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Shortwave narrowband total downwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 {mu}m, passes through a horizontal unit area in a downward direction. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following

  6. ARM - Measurement - Shortwave narrowband total upwelling irradiance

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

    upwelling irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Shortwave narrowband total upwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 {mu}m, passes through a horizontal unit area in an upward direction. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following instruments.

  7. Use of Cost Estimating Relationships

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

    1997-03-28

    Cost Estimating Relationships (CERs) are an important tool in an estimator's kit, and in many cases, they are the only tool. Thus, it is important to understand their limitations and characteristics. This chapter discusses considerations of which the estimator must be aware so the Cost Estimating Relationships can be properly used.

  8. A bottom-up engineering estimate of the aggregate heating andcooling loads of the entire U.S. building stock

    SciTech Connect (OSTI)

    Huang, Yu Joe; Brodrick, Jim

    2000-08-01

    A recently completed project for the U.S. Department of Energy's (DOE) Office of Building Equipment combined DOE-2 results for a large set of prototypical commercial and residential buildings with data from the Energy Information Administration (EIA) residential and commercial energy consumption surveys (RECS, CBECS) to estimate the total heating and cooling loads in U.S. buildings attributable to different shell components such as windows, roofs, walls, etc., internal processes, and space-conditioning systems. This information is useful for estimating the national conservation potentials for DOE's research and market transformation activities in building energy efficiency. The prototypical building descriptions and DOE-2 input files were developed from 1986 to 1992 to provide benchmark hourly building loads for the Gas Research Institute (GRI) and include 112 single-family, 66 multi-family, and 481 commercial building prototypes. The DOE study consisted of two distinct tasks : (1) perform DOE-2 simulations for the prototypical buildings and develop methods to extract the heating and cooling loads attributable to the different building components; and (2) estimate the number of buildings or floor area represented by each prototypical building based on EIA survey information. These building stock data were then multiplied by the simulated component loads to derive aggregated totals by region, vintage, and building type. The heating and cooling energy consumption of the national building stock estimated by this bottom-up engineering approach was found to agree reasonably well with estimates from other sources, although significant differences were found for certain end-uses. The main added value from this study, however, is the insight it provides about the contributing factors behind this energy consumption, and what energy savings can be expected from efficiency improvements for different building components by region, vintage, and building type.

  9. Site: Contract Name: Contractor: Contract Number: Contract Type:

    Office of Environmental Management (EM)

    Number: Contract Type: Total Estimated Contract Cost: Contract Base Period: Contract Option Periods: Minimum Fee Maximum Fee Performance Period Fee Available Fee Earned FY2009/2010 $22,386,342 $19,332,431 FY2011 $26,164,766 $23,956,349 FY2012 $21,226,918 $19,099,251 FY2013 $21,030,647 $19,352,402 FY2014 $18,986,489 $16,518,626 FY2015 $21,043,816 $18,776,345 FY2016 $21,027,870 FY2017 Cumulative Fee $151,866,848 $117,035,404 $151,866,848 EM Contractor Fee Richland Operations Office - Richland, WA

  10. Site: Contract Name: Contractor: Contract Number: Contract Type:

    Office of Environmental Management (EM)

    Number: Contract Type: Total Estimated Contract Cost: Contract Base Period: Contract Option Period: Minimum Fee Target Fee Maximum Fee Performance Period Fee Available (N/A) Fee Earned (Equals 10% of Target) FY2005 $223,991 FY2006 $1,548,986 FY2007 $1,170,889 FY2008 $1,270,755 FY2009 $1,567,325 FY2010 $2,374,992 FY2011 $2,498,835 FY2012 $1,440,273 FY2013 $1,595,460 FY2014 $33,113,257 FY2015 $1,546,386 FY2016 $6,553,927 Cumulative Fee $54,905,075 N/A EM Contractor Fee Richland Operations Office -

  11. Robust Optical Richness Estimation with Reduced Scatter

    SciTech Connect (OSTI)

    Rykoff, E.S.; Koester, B.P.; Rozo, E.; Annis, J.; Evrard, A.E.; Hansen, S.M.; Hao, J.; Johnston, D.E.; McKay, T.A.; Wechsler, R.H.; /KIPAC, Menlo Park /SLAC

    2012-06-07

    Reducing the scatter between cluster mass and optical richness is a key goal for cluster cosmology from photometric catalogs. We consider various modifications to the red-sequence matched filter richness estimator of Rozo et al. (2009b), and evaluate their impact on the scatter in X-ray luminosity at fixed richness. Most significantly, we find that deeper luminosity cuts can reduce the recovered scatter, finding that {sigma}{sub ln L{sub X}|{lambda}} = 0.63 {+-} 0.02 for clusters with M{sub 500c} {approx}> 1.6 x 10{sup 14} h{sub 70}{sup -1} M{sub {circle_dot}}. The corresponding scatter in mass at fixed richness is {sigma}{sub ln M|{lambda}} {approx} 0.2-0.3 depending on the richness, comparable to that for total X-ray luminosity. We find that including blue galaxies in the richness estimate increases the scatter, as does weighting galaxies by their optical luminosity. We further demonstrate that our richness estimator is very robust. Specifically, the filter employed when estimating richness can be calibrated directly from the data, without requiring a-priori calibrations of the red-sequence. We also demonstrate that the recovered richness is robust to up to 50% uncertainties in the galaxy background, as well as to the choice of photometric filter employed, so long as the filters span the 4000 {angstrom} break of red-sequence galaxies. Consequently, our richness estimator can be used to compare richness estimates of different clusters, even if they do not share the same photometric data. Appendix A includes 'easy-bake' instructions for implementing our optimal richness estimator, and we are releasing an implementation of the code that works with SDSS data, as well as an augmented maxBCG catalog with the {lambda} richness measured for each cluster.

  12. Low-Temperature Hydrothermal Resource Potential Estimate

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

    Katherine Young

    2016-06-30

    Compilation of data (spreadsheet and shapefiles) for several low-temperature resource types, including isolated springs and wells, delineated area convection systems, sedimentary basins and coastal plains sedimentary systems. For each system, we include estimates of the accessible resource base, mean extractable resource and beneficial heat. Data compiled from USGS and other sources. The paper (submitted to GRC 2016) describing the methodology and analysis is also included.

  13. 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...

  14. Guidelines for Estimating Unmetered Landscaping Water Use

    SciTech Connect (OSTI)

    McMordie Stoughton, Kate

    2010-07-28

    The document lays-out step by step instructions to estimate landscaping water using two alternative approaches: evapotranspiration method and irrigation audit method. The evapotranspiration method option calculates the amount of water needed to maintain a healthy turf or landscaped area for a given location based on the amount of water transpired and evaporated from the plants. The evapotranspiration method offers a relatively easy one-stop-shop for Federal agencies to develop an initial estimate of annual landscape water use. The document presents annual irrigation factors for 36 cities across the U.S. that represents the gallons of irrigation required per square foot for distinct landscape types. By following the steps outlined in the document, the reader can choose a location that is a close match their location and landscape type to provide a rough estimate of annual irrigation needs without the need to research specific data on their site. The second option presented in the document is the irrigation audit method, which is the physical measurement of water applied to landscaped areas through irrigation equipment. Steps to perform an irrigation audit are outlined in the document, which follow the Recommended Audit Guidelines produced by the Irrigation Association.[5] An irrigation audit requires some knowledge on the specific procedures to accurately estimate how much water is being consumed by the irrigation equipment.

  15. Table 10. Total natural gas proved reserves, reserves changes, and production, w

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

    Total natural gas proved reserves, reserves changes, and production, wet after lease separation, 2014" "billion cubic feet" ,,"Changes in reserves during 2014" ,"Published",,,,,,,,"New Reservoir" ,"Proved",,"Revision","Revision",,,,"New Field","Discoveries","Estimated","Proved"

  16. Estimated recharge rates at the Hanford Site

    SciTech Connect (OSTI)

    Fayer, M.J.; Walters, T.B.

    1995-02-01

    The Ground-Water Surveillance Project monitors the distribution of contaminants in ground water at the Hanford Site for the U.S. Department of Energy. A subtask called {open_quotes}Water Budget at Hanford{close_quotes} was initiated in FY 1994. The objective of this subtask was to produce a defensible map of estimated recharge rates across the Hanford Site. Methods that have been used to estimate recharge rates at the Hanford Site include measurements (of drainage, water contents, and tracers) and computer modeling. For the simulations of 12 soil-vegetation combinations, the annual rates varied from 0.05 mm/yr for the Ephrata sandy loam with bunchgrass to 85.2 mm/yr for the same soil without vegetation. Water content data from the Grass Site in the 300 Area indicated that annual rates varied from 3.0 to 143.5 mm/yr during an 8-year period. The annual volume of estimated recharge was calculated to be 8.47 {times} 10{sup 9} L for the potential future Hanford Site (i.e., the portion of the current Site bounded by Highway 240 and the Columbia River). This total volume is similar to earlier estimates of natural recharge and is 2 to 10x higher than estimates of runoff and ground-water flow from higher elevations. Not only is the volume of natural recharge significant in comparison to other ground-water inputs, the distribution of estimated recharge is highly skewed to the disturbed sandy soils (i.e., the 200 Areas, where most contaminants originate). The lack of good estimates of the means and variances of the supporting data (i.e., the soil map, the vegetation/land use map, the model parameters) translates into large uncertainties in the recharge estimates. When combined, the significant quantity of estimated recharge, its high sensitivity to disturbance, and the unquantified uncertainty of the data and model parameters suggest that the defensibility of the recharge estimates should be improved.

  17. ARM - Measurement - Shortwave broadband total upwelling irradiance

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

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

  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. Automated Estimating System

    Energy Science and Technology Software Center (OSTI)

    1996-04-15

    AES6.1 is a PC software package developed to aid in the preparation and reporting of cost estimates. AES6.1 provides an easy means for entering and updating the detailed cost, schedule information, project work breakdown structure, and escalation information contained in a typical project cost estimate through the use of menus and formatted input screens. AES6.1 combines this information to calculate both unescalated and escalated cost for a project which can be reported at varying levelsmore » of detail. Following are the major modifications to AES6.0f: Contingency update was modified to provide greater flexibility for user updates, Schedule Update was modified to provide user ability to schedule Bills of Material at the WBS/Participant/Cost Code level, Schedule Plot was modified to graphically show schedule by WBS/Participant/Cost Code, All Fiscal Year reporting has been modified to use the new schedule format, The Schedule 1-B-7, Cost Schedule, and the WBS/Participant reprorts were modified to determine Phase of Work from the B/M Cost Code, Utility program was modified to allow selection by cost code and update cost code in the Global Schedule update, Generic summary and line item download were added to the utility program, and an option was added to all reports which allows the user to indicate where overhead is to be reported (bottom line or in body of report)« less

  2. Total Ore Processing Integration and Management

    SciTech Connect (OSTI)

    Leslie 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 October through 31 December of 2005. Graphical analysis of blast patterns according to drill monitor data is continuing. Multiple linear regression analysis of 16 mine and mill variables (powder factor, two modeled size fractions, liberation index, predicted grind, total crude Fe, Satmagan Fe, sat ratio, DSC, geologic blend, ambient temperature, cobbing hours, feeder plugs, and percent feeder run time-of-mill time) indicates that December variations in plant performance are generally predictable (Figure 1). The outlier on December 28th coincides with low cobbing availability and equipment downtime. Mill productivity appeared to be most influenced, as usual, by ore quality as indicated by the liberation index--the higher the liberation index, the lower the throughput. The upcoming quarter will be concerned with wrapping up the work in progress, such as the detailed statistical analyses, and writing a final report. Hibtac Mine engineers are evaluating neural network software to determine its utility for modeling, and eventually predicting, mill throughput.

  3. Estimate of the Potential Amount of Low-Level Waste from the Fukushima Prefecture - 12370

    SciTech Connect (OSTI)

    Hill, Carolyn; Olson, Eric A.J.; Elmer, John

    2012-07-01

    The amount of waste generated by the cleanup of the Fukushima Prefecture (Fukushima-ken) following the releases from the Fukushima Daiichi nuclear power plant accident (March 2011) is dependent on many factors, including: - Contamination amounts; - Cleanup levels determined for the radioisotopes contaminating the area; - Future land use expectations and human exposure scenarios; - Groundwater contamination considerations; - Costs and availability of storage areas, and eventually disposal areas for the waste; and - Decontamination and volume reduction techniques and technologies used. For the purposes of estimating these waste volumes, Fukushima-ken is segregated into zones of similar contamination level and expected future use. Techniques for selecting the appropriate cleanup methods for each area are shown in a decision tree format. This approach is broadly applied to the 20 km evacuation zone and the total amounts and types of waste are estimated; waste resulting from cleanup efforts outside of the evacuation zone is not considered. Some of the limits of future use and potential zones where residents must be excluded within the prefecture are also described. The size and design of the proposed intermediate storage facility is also discussed and the current situation, cleanup, waste handling, and waste storage issues in Japan are described. The method for estimating waste amounts outlined above illustrates the large amount of waste that could potentially be generated by remediation of the 20 km evacuation zone (619 km{sup 2} total) if the currently proposed cleanup goals are uniformly applied. The Japanese environment ministry estimated in early October that the 1 mSv/year exposure goal would make the government responsible for decontaminating about 8,000 km{sup 2} within Fukushima-ken and roughly 4,900 km{sup 2} in areas outside the prefecture. The described waste volume estimation method also does not give any consideration to areas with localized hot spots

  4. Million U.S. Housing Units Total............................................................................

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

    Personal Computers Do Not Use a Personal Computer......................... 35.5 3.2 8.3 8.9 7.7 7.5 Use a Personal Computer...................................... 75.6 7.8 17.8 18.4 16.3 15.3 Most-Used Personal Computer Type of PC Desk-top Model................................................. 58.6 6.2 14.3 14.2 12.1 11.9 Laptop Model.................................................... 16.9 1.6 3.5 4.3 4.2 3.4 Hours Turned on Per Week Less than 2 Hours.............................................

  5. Total Supplemental Supply of Natural Gas

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

    Product: Total Supplemental Supply Synthetic Propane-Air Refinery Gas Biomass Other Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 2010 2011 2012 2013 2014 2015 View History U.S. 64,575 60,088 61,366 54,650 59,528 58,555 1980-2015 Alabama 0 0 0 0 0 1967-2014 Alaska 0 0 0 0 0 2004-2014 Arizona 0 0 0 0 0 1967-2014 Arkansas 0 0 0 0 0 1967-2014 Colorado 5,148 4,268 4,412 4,077 4,120

  6. 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.

  7. 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

  8. Million U.S. Housing Units Total.........................................................................

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

    .... 111.1 10.9 26.1 27.3 24.0 22.8 Do Not Have Cooling Equipment........................... 17.8 3.2 4.7 3.6 5.5 0.9 Have Cooling Equipment........................................ 93.3 7.7 21.4 23.7 18.5 21.9 Use Cooling Equipment......................................... 91.4 7.6 21.0 23.4 17.9 21.7 Have Equipment But Do Not Use it........................ 1.9 Q 0.4 0.4 0.6 0.3 Type of Air-Conditioning Equipment 2, 3 Central System..................................................... 65.9 4.8

  9. Million U.S. Housing Units Total............................................................................

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

    8.1 64.1 4.2 1.8 2.3 5.7 Personal Computers Do Not Use a Personal Computer......................... 35.5 20.3 14.8 1.2 0.6 0.9 2.8 Use a Personal Computer...................................... 75.6 57.8 49.2 2.9 1.2 1.4 3.0 Most-Used Personal Computer Type of PC Desk-top Model................................................. 58.6 45.8 38.9 2.2 1.0 1.1 2.6 Laptop Model.................................................... 16.9 12.0 10.3 0.8 0.2 Q 0.4 Hours Turned on Per Week Less than 2

  10. Million U.S. Housing Units Total............................................................................

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

    33.0 8.0 3.4 5.9 14.4 1.2 Personal Computers Do Not Use a Personal Computer......................... 35.5 15.3 3.0 1.9 3.1 6.4 0.8 Use a Personal Computer...................................... 75.6 17.7 5.0 1.6 2.8 8.0 0.4 Most-Used Personal Computer Type of PC Desk-top Model................................................. 58.6 12.8 4.0 1.1 2.0 5.4 0.3 Laptop Model.................................................... 16.9 4.9 1.0 0.4 0.8 2.6 Q Hours Turned on Per Week Less than 2

  11. Cost Estimating, Analysis, and Standardization

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

    1984-11-02

    To establish policy and responsibilities for: (a) developing and reviewing project cost estimates; (b) preparing independent cost estimates and analysis; (c) standardizing cost estimating procedures; and (d) improving overall cost estimating and analytical techniques, cost data bases, cost and economic escalation models, and cost estimating systems. Cancels DOE O 5700.2B, dated 8-5-1983; DOE O 5700.8, dated 5-27-1981; and HQ 1130.1A, dated 12-30-1981. Canceled by DOE O 5700.2D, dated 6-12-1992

  12. 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.

  13. A Planning Tool for Estimating Waste Generated by a Radiological Incident and Subsequent Decontamination Efforts - 13569

    SciTech Connect (OSTI)

    Boe, Timothy; Lemieux, Paul; Schultheisz, Daniel; Peake, Tom; Hayes, Colin

    2013-07-01

    Management of debris and waste from a wide-area radiological incident would probably constitute a significant percentage of the total remediation cost and effort. The U.S. Environmental Protection Agency's (EPA's) Waste Estimation Support Tool (WEST) is a unique planning tool for estimating the potential volume and radioactivity levels of waste generated by a radiological incident and subsequent decontamination efforts. The WEST was developed to support planners and decision makers by generating a first-order estimate of the quantity and characteristics of waste resulting from a radiological incident. The tool then allows the user to evaluate the impact of various decontamination/demolition strategies on the waste types and volumes generated. WEST consists of a suite of standalone applications and Esri{sup R} ArcGIS{sup R} scripts for rapidly estimating waste inventories and levels of radioactivity generated from a radiological contamination incident as a function of user-defined decontamination and demolition approaches. WEST accepts Geographic Information System (GIS) shape-files defining contaminated areas and extent of contamination. Building stock information, including square footage, building counts, and building composition estimates are then generated using the Federal Emergency Management Agency's (FEMA's) Hazus{sup R}-MH software. WEST then identifies outdoor surfaces based on the application of pattern recognition to overhead aerial imagery. The results from the GIS calculations are then fed into a Microsoft Excel{sup R} 2007 spreadsheet with a custom graphical user interface where the user can examine the impact of various decontamination/demolition scenarios on the quantity, characteristics, and residual radioactivity of the resulting waste streams. (authors)

  14. Monitored Geologic Repository Life Cycle Cost Estimate Assumptions Document

    SciTech Connect (OSTI)

    R. Sweeney

    2000-03-08

    The purpose of this assumptions document is to provide general scope, strategy, technical basis, schedule and cost assumptions for the Monitored Geologic Repository (MGR) life cycle cost estimate and schedule update incorporating information from the Viability Assessment (VA), License Application Design Selection (LADS), 1999 Update to the Total System Life Cycle Cost (TSLCC) estimate and from other related and updated information. This document is intended to generally follow the assumptions outlined in the previous MGR cost estimates and as further prescribed by DOE guidance.

  15. MONITORED GEOLOGIC REPOSITORY LIFE CYCLE COST ESTIMATE ASSUMPTIONS DOCUMENT

    SciTech Connect (OSTI)

    R.E. Sweeney

    2001-02-08

    The purpose of this assumptions document is to provide general scope, strategy, technical basis, schedule and cost assumptions for the Monitored Geologic Repository (MGR) life cycle cost (LCC) estimate and schedule update incorporating information from the Viability Assessment (VA) , License Application Design Selection (LADS), 1999 Update to the Total System Life Cycle Cost (TSLCC) estimate and from other related and updated information. This document is intended to generally follow the assumptions outlined in the previous MGR cost estimates and as further prescribed by DOE guidance.

  16. New York Natural Gas % of Total Residential Deliveries (Percent...

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

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

  18. New Jersey Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

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

  19. 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. ...

  20. ARM - Measurement - Cloud type

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

    Measurement : Cloud type Cloud type such as cirrus, stratus, cumulus etc Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  1. 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...

  2. ARM: GRAMS: data from the total solar broadband radiometer (TBBR...

    Office of Scientific and Technical Information (OSTI)

    solar broadband radiometer (TBBR) Title: ARM: GRAMS: data from the total solar broadband radiometer (TBBR) GRAMS: data from the total solar broadband radiometer (TBBR) Authors: ...

  3. ARM: GRAMS: calibration information for the total solar broadband...

    Office of Scientific and Technical Information (OSTI)

    solar broadband radiometer (TBBR) Title: ARM: GRAMS: calibration information for the total solar broadband radiometer (TBBR) GRAMS: calibration information for the total solar ...

  4. 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...

  5. Webtrends Archives by Fiscal Year — EERE Totals

    Office of Energy Efficiency and Renewable Energy (EERE)

    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.

  6. New Jersey Natural Gas Total Consumption (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

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

  7. New York Natural Gas Total Consumption (Million Cubic Feet)

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

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

  8. New Mexico Natural Gas Total Consumption (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

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

  9. West Virginia Natural Gas Total Consumption (Million Cubic Feet...

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

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

  10. Virginia Natural Gas Total Consumption (Million Cubic Feet)

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

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

  11. 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 ...

  12. ,"Alaska (with Total Offshore) Natural Gas Liquids Lease Condensate...

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

    Data for" ,"Data 1","Alaska (with Total Offshore) Natural Gas Liquids Lease Condensate, ... to Contents","Data 1: Alaska (with Total Offshore) Natural Gas Liquids Lease Condensate, ...

  13. ,"Alaska (with Total Offshore) Coalbed Methane Proved Reserves...

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

    Data for" ,"Data 1","Alaska (with Total Offshore) Coalbed Methane Proved Reserves ... to Contents","Data 1: Alaska (with Total Offshore) Coalbed Methane Proved Reserves ...

  14. ,"Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected...

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

    Data for" ,"Data 1","Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected ... to Contents","Data 1: Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected ...

  15. ,"Alaska (with Total Offshore) Shale Proved Reserves (Billion...

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

    Data for" ,"Data 1","Alaska (with Total Offshore) Shale Proved Reserves (Billion Cubic ... to Contents","Data 1: Alaska (with Total Offshore) Shale Proved Reserves (Billion Cubic ...

  16. Federal Offshore -- Gulf of Mexico Natural Gas Total Consumption...

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

    -- Gulf of Mexico Natural Gas Total Consumption (Million Cubic Feet) Federal Offshore -- Gulf of Mexico Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 ...

  17. ,"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...

  18. ,"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...

  19. North Carolina Natural Gas Total Consumption (Million Cubic Feet...

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

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

  20. North Dakota Natural Gas Total Consumption (Million Cubic Feet...

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

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

  1. 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 ...

  2. ARM: GRAMS: data from the total direct diffuse radiometer (TDDR...

    Office of Scientific and Technical Information (OSTI)

    direct diffuse radiometer (TDDR) Title: ARM: GRAMS: data from the total direct diffuse radiometer (TDDR) GRAMS: data from the total direct diffuse radiometer (TDDR) Authors: ...

  3. ,"Texas Natural Gas Gross Withdrawals Total Offshore (MMcf)"

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

    Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals Total ... 7:03:02 AM" "Back to Contents","Data 1: Texas Natural Gas Gross Withdrawals Total ...

  4. 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.

  5. Million U.S. Housing Units 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 Personal Computers Do Not Use a Personal Computer.................... 35.5 5.7 3.3 4.6 4.7 5.8 5.7 4.0 1.7 Use a Personal Computer................................ 75.6 9.0 4.1 7.9 7.8 13.1 12.9 13.3 7.5 Most-Used Personal Computer Type of PC Desk-top Model........................................... 58.6 6.7 3.5 6.3 6.2 10.3 9.9 10.2 5.6 Laptop Model............................................... 16.9 2.3 0.7 1.7 1.5 2.8 2.9 3.1 1.9 Hours Turned on

  6. "Table A11. Total Primary Consumption of Combustible Energy for Nonfuel"

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

    1. Total Primary Consumption of Combustible Energy for Nonfuel" " Purposes by Census Region and Economic Characteristics of the Establishment," 1991 " (Estimates in Btu or Physical Units)" " "," "," "," ","Natural"," "," ","Coke"," "," " " ","Total","Residual","Distillate","Gas(c)"," ","Coal","and

  7. "Table A16. Components of Total Electricity Demand by Census Region, Industry"

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

    6. Components of Total Electricity Demand by Census Region, Industry" " Group, and Selected Industries, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total

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

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

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

  9. Robust and intelligent bearing estimation

    DOE Patents [OSTI]

    Claassen, John P.

    2000-01-01

    A method of bearing estimation comprising quadrature digital filtering of event observations, constructing a plurality of observation matrices each centered on a time-frequency interval, determining for each observation matrix a parameter such as degree of polarization, linearity of particle motion, degree of dyadicy, or signal-to-noise ratio, choosing observation matrices most likely to produce a set of best available bearing estimates, and estimating a bearing for each observation matrix of the chosen set.

  10. Reference air kerma and kerma-area product as estimators of peak skin dose for fluoroscopically guided interventions

    SciTech Connect (OSTI)

    Kwon, Deukwoo; Little, Mark P.; Miller, Donald L.

    2011-07-15

    Purpose: To determine more accurate regression formulas for estimating peak skin dose (PSD) from reference air kerma (RAK) or kerma-area product (KAP). Methods: After grouping of the data from 21 procedures into 13 clinically similar groups, assessments were made of optimal clustering using the Bayesian information criterion to obtain the optimal linear regressions of (log-transformed) PSD vs RAK, PSD vs KAP, and PSD vs RAK and KAP. Results: Three clusters of clinical groups were optimal in regression of PSD vs RAK, seven clusters of clinical groups were optimal in regression of PSD vs KAP, and six clusters of clinical groups were optimal in regression of PSD vs RAK and KAP. Prediction of PSD using both RAK and KAP is significantly better than prediction of PSD with either RAK or KAP alone. The regression of PSD vs RAK provided better predictions of PSD than the regression of PSD vs KAP. The partial-pooling (clustered) method yields smaller mean squared errors compared with the complete-pooling method.Conclusion: PSD distributions for interventional radiology procedures are log-normal. Estimates of PSD derived from RAK and KAP jointly are most accurate, followed closely by estimates derived from RAK alone. Estimates of PSD derived from KAP alone are the least accurate. Using a stochastic search approach, it is possible to cluster together certain dissimilar types of procedures to minimize the total error sum of squares.

  11. "Table A24. Total Expenditures for Purchased Energy Sources by Census Region,"

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

    4. Total Expenditures for Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Groupsc and

  12. "Table A32. Total Quantity of Purchased Energy Sources by Census Region,"

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

    Quantity of Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Btu or Physical Units)" ,,,,,,"Natural",,,"Coke" " "," ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC","

  13. "Table A36. Total Expenditures for Purchased Energy Sources by Census Region,"

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

    6. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Group and

  14. "Table A37. Total Expenditures for Purchased Energy Sources by Census Region,"

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

    7. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," ","

  15. Table A17. Total First Use (formerly Primary Consumption) of Energy for All P

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

    Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Employment Size Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," "," Employment Size(b)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",1000,"Row" "Code(a)","Industry Group and

  16. Table A19. Components of Total Electricity Demand by Census Region and

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

    Components of Total Electricity Demand by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic

  17. Table A20. Total First Use (formerly Primary Consumption) of Energy for All P

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

    Total First Use (formerly Primary Consumption) of Energy for All Purposes by Census" " Region, Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke",,"Shipments" " "," ","Net","Residual","Distillate","Natural Gas(e)"," ","Coal","and Breeze"," ","of Energy

  18. Table A22. Total First Use (formerly Primary Consumption) of Combustible Ener

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

    First Use (formerly Primary Consumption) of Combustible Energy for Nonfuel" " Purposes by Census Region, Census Division, and Economic Characteristics of the Establishment," 1994 " (Estimates in Btu or Physical Units)" " "," "," "," ","Natural"," "," ","Coke"," "," " " ","Total","Residual","Distillate","Gas(c)","

  19. Table A26. Components of Total Electricity Demand by Census Region, Census Di

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

    Components of Total Electricity Demand by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic

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

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

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

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

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

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

  2. 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

  3. 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

  4. Derived Annual Estimates of Manufacturing Energy Consumption...

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

    > Derived Annual Estimates - Executive Summary Derived Annual Estimates of Manufacturing Energy Consumption, 1974-1988 Figure showing Derived Estimates Executive Summary This...

  5. Improved characterization of reservoir behavior by integration of reservoir performances data and rock type distributions

    SciTech Connect (OSTI)

    Davies, D.K.; Vessell, R.K.; Doublet, L.E.

    1997-08-01

    An integrated geological/petrophysical and reservoir engineering study was performed for a large, mature waterflood project (>250 wells, {approximately}80% water cut) at the North Robertson (Clear Fork) Unit, Gaines County, Texas. The primary goal of the study was to develop an integrated reservoir description for {open_quotes}targeted{close_quotes} (economic) 10-acre (4-hectare) infill drilling and future recovery operations in a low permeability, carbonate (dolomite) reservoir. Integration of the results from geological/petrophysical studies and reservoir performance analyses provide a rapid and effective method for developing a comprehensive reservoir description. This reservoir description can be used for reservoir flow simulation, performance prediction, infill targeting, waterflood management, and for optimizing well developments (patterns, completions, and stimulations). The following analyses were performed as part of this study: (1) Geological/petrophysical analyses: (core and well log data) - {open_quotes}Rock typing{close_quotes} based on qualitative and quantitative visualization of pore-scale features. Reservoir layering based on {open_quotes}rock typing {close_quotes} and hydraulic flow units. Development of a {open_quotes}core-log{close_quotes} model to estimate permeability using porosity and other properties derived from well logs. The core-log model is based on {open_quotes}rock types.{close_quotes} (2) Engineering analyses: (production and injection history, well tests) Material balance decline type curve analyses to estimate total reservoir volume, formation flow characteristics (flow capacity, skin factor, and fracture half-length), and indications of well/boundary interference. Estimated ultimate recovery analyses to yield movable oil (or injectable water) volumes, as well as indications of well and boundary interference.

  6. Types of Reuse

    Broader source: Energy.gov [DOE]

    The following provides greater detail regarding the types of reuse pursued for LM sites. It should be noted that many actual reuses combine several types of the uses listed below.

  7. Postdoc Appointment Types

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

    Appointment Types Postdoc Appointment Types Most postdocs will be offered a postdoctoral research associate appointment. Each year, approximately 30 Postdoctoral Fellow appointments, including the Distinguished Fellows, are awarded. Postdoc appointment types offer world of possibilities Meet the current LANL Distinguished Postdocs Research Associates Research Associates pursue research as part of ongoing LANL science and engineering programs. Sponsored postdoctoral candidate packages are

  8. Module: Estimating Historical Emissions from Deforestation |...

    Open Energy Info (EERE)

    Website: www.leafasia.orgtoolstechnical-guidance-series-estimating-historical Cost: Free Language: English Module: Estimating Historical Emissions from Deforestation Screenshot...

  9. 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.

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. North Carolina Natural Gas % of Total Residential Deliveries...

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

    % of Total Residential Deliveries (Percent) North Carolina Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

  15. Washington Natural Gas Total Consumption (Million Cubic Feet...

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

    Total Consumption (Million Cubic Feet) Washington 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...

  16. ,"U.S. Total Shell Storage Capacity at Operable Refineries"

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

    Data for" ,"Data 1","U.S. Total Shell Storage Capacity at Operable ... 9:47:20 AM" "Back to Contents","Data 1: U.S. Total Shell Storage Capacity at Operable ...

  17. 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...

  18. 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...

  19. 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...

  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. New Hampshire Natural Gas Total Consumption (Million Cubic Feet...

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

    Total Consumption (Million Cubic Feet) New Hampshire Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 ...

  2. New Hampshire Natural Gas % of Total Residential Deliveries ...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) New Hampshire Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  3. ,"U.S. Total Imports Natural Gas Plant Processing"

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

    Data for" ,"Data 1","U.S. Total Imports Natural Gas Plant Processing",1,"Monthly"... "Back to Contents","Data 1: U.S. Total Imports Natural Gas Plant Processing" ...

  4. 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 NREL: Building America Total Quality Management - 2015 Peer Review (2.43 MB) 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

  5. Numerical Estimation of the Spent Fuel Ratio

    SciTech Connect (OSTI)

    Lindgren, Eric R.; Durbin, Samuel; Wilke, Jason; Margraf, J.; Dunn, T. A.

    2016-01-01

    Sabotage of spent nuclear fuel casks remains a concern nearly forty years after attacks against shipment casks were first analyzed and has a renewed relevance in the post-9/11 environment. A limited number of full-scale tests and supporting efforts using surrogate materials, typically depleted uranium dioxide (DUO 2 ), have been conducted in the interim to more definitively determine the source term from these postulated events. However, the validity of these large- scale results remain in question due to the lack of a defensible spent fuel ratio (SFR), defined as the amount of respirable aerosol generated by an attack on a mass of spent fuel compared to that of an otherwise identical surrogate. Previous attempts to define the SFR in the 1980's have resulted in estimates ranging from 0.42 to 12 and include suboptimal experimental techniques and data comparisons. Because of the large uncertainty surrounding the SFR, estimates of releases from security-related events may be unnecessarily conservative. Credible arguments exist that the SFR does not exceed a value of unity. A defensible determination of the SFR in this lower range would greatly reduce the calculated risk associated with the transport and storage of spent nuclear fuel in dry cask systems. In the present work, the shock physics codes CTH and ALE3D were used to simulate spent nuclear fuel (SNF) and DUO 2 targets impacted by a high-velocity jet at an ambient temperature condition. These preliminary results are used to illustrate an approach to estimate the respirable release fraction for each type of material and ultimately, an estimate of the SFR. This page intentionally blank

  6. Estimate Radiological Dose for Animals

    Energy Science and Technology Software Center (OSTI)

    1997-12-18

    Estimate Radiological dose for animals in ecological environment using open literature values for parameters such as body weight, plant and soil ingestion rate, rad. halflife, absorbed energy, biological halflife, gamma energy per decay, soil-to-plant transfer factor, ...etc

  7. New Methodology for Estimating Fuel Economy by Vehicle Class

    SciTech Connect (OSTI)

    Chin, Shih-Miao; Dabbs, Kathryn; Hwang, Ho-Ling

    2011-01-01

    Office of Highway Policy Information to develop a new methodology to generate annual estimates of average fuel efficiency and number of motor vehicles registered by vehicle class for Table VM-1 of the Highway Statistics annual publication. This paper describes the new methodology developed under this effort and compares the results of the existing manual method and the new systematic approach. The methodology developed under this study takes a two-step approach. First, the preliminary fuel efficiency rates are estimated based on vehicle stock models for different classes of vehicles. Then, a reconciliation model is used to adjust the initial fuel consumption rates from the vehicle stock models and match the VMT information for each vehicle class and the reported total fuel consumption. This reconciliation model utilizes a systematic approach that produces documentable and reproducible results. The basic framework utilizes a mathematical programming formulation to minimize the deviations between the fuel economy estimates published in the previous year s Highway Statistics and the results from the vehicle stock models, subject to the constraint that fuel consumptions for different vehicle classes must sum to the total fuel consumption estimate published in Table MF-21 of the current year Highway Statistics. The results generated from this new approach provide a smoother time series for the fuel economies by vehicle class. It also utilizes the most up-to-date and best available data with sound econometric models to generate MPG estimates by vehicle class.

  8. 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.

  9. Category:NEPA Environmental Analysis Types | Open Energy Information

    Open Energy Info (EERE)

    Analysis Types" The following 5 pages are in this category, out of 5 total. C CU CX D DNA E EA EIS Retrieved from "http:en.openei.orgwindex.php?titleCategory:NEPAEnvironme...

  10. Letters of Interest PRICE/COST Estimate Sheet for [Insert LOI #]

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

    Form (10-19-2000) Estimated Budget Form Offeror's Name And Address: Principal Investigator Name: Telephone Number: Project Title: Proposed Lower-Tier Subcontractor(s) Organization's Name and Address: Telephone Number: Type of Business: Approval Signatures: _____________________________ ___________ (Signature) Date _________________________________________ (Typed Name) _____________________________ ___________ (Signature) Date _________________________________________ (Typed Name) NREL Form

  11. Synchrophasor Measurement-Based Wind Plant Inertia Estimation: Preprint

    SciTech Connect (OSTI)

    Zhang, Y.; Bank, J.; Wan, Y. H.; Muljadi, E.; Corbus, D.

    2013-05-01

    The total inertia stored in all rotating masses that are connected to power systems, such as synchronous generations and induction motors, is an essential force that keeps the system stable after disturbances. To ensure bulk power system stability, there is a need to estimate the equivalent inertia available from a renewable generation plant. An equivalent inertia constant analogous to that of conventional rotating machines can be used to provide a readily understandable metric. This paper explores a method that utilizes synchrophasor measurements to estimate the equivalent inertia that a wind plant provides to the system.

  12. Alaska (with Total Offshore) Shale Production (Billion Cubic...

    Gasoline and Diesel Fuel Update (EIA)

    company data. Release Date: 11192015 Next Release Date: 12312016 Referring Pages: Shale Natural Gas Estimated Production Alaska Shale Gas Proved Reserves, Reserves Changes,...

  13. Weldon Spring historical dose estimate

    SciTech Connect (OSTI)

    Meshkov, N.; Benioff, P.; Wang, J.; Yuan, Y.

    1986-07-01

    This study was conducted to determine the estimated radiation doses that individuals in five nearby population groups and the general population in the surrounding area may have received as a consequence of activities at a uranium processing plant in Weldon Spring, Missouri. The study is retrospective and encompasses plant operations (1957-1966), cleanup (1967-1969), and maintenance (1969-1982). The dose estimates for members of the nearby population groups are as follows. Of the three periods considered, the largest doses to the general population in the surrounding area would have occurred during the plant operations period (1957-1966). Dose estimates for the cleanup (1967-1969) and maintenance (1969-1982) periods are negligible in comparison. Based on the monitoring data, if there was a person residing continually in a dwelling 1.2 km (0.75 mi) north of the plant, this person is estimated to have received an average of about 96 mrem/yr (ranging from 50 to 160 mrem/yr) above background during plant operations, whereas the dose to a nearby resident during later years is estimated to have been about 0.4 mrem/yr during cleanup and about 0.2 mrem/yr during the maintenance period. These values may be compared with the background dose in Missouri of 120 mrem/yr.

  14. Preliminary assessment of the Velocity Pump Reaction Turbine as a geothermal total-flow expander

    SciTech Connect (OSTI)

    Demuth, O.J.

    1985-01-01

    A preliminary evaluation was made of the Velocity Pump Reaction Turbine (VPRT) as a total flow expander in a geothermal-electric conversion cycle. Values of geofluid effectiveness of VPRT systems were estimated for conditions consisting of: a 360/sup 0/F geothermal resource, 60/sup 0/F wet-bulb ambient temperature, zero and 0.003 mass concentrations of dissolved noncondensible gas in the geofluid, 100 and 120/sup 0/F condensing temperature, and engine efficiencies ranging from 0.4 to 1.0. Achievable engine efficiencies were estimated to range from 0.47 to 0.77, with plant geofluid effectivenss values ranging as high as 9.5 Watt hr/lbm geofluid. This value is competitive with magnitudes of geofluid effectiveness projected for advanced binary plants, and is on the order of 40% higher than estimates for dual-flash steam systems and other total flow systems reviewed. Because of its potentially high performance and relative simplicity, the VPRT system appears to warrant further investigation toward its use in a well-head geothermal plant. 13 refs., 5 figs.

  15. Preliminary assessment of the velocity pump reaction turbine as a geothermal total-flow expander

    SciTech Connect (OSTI)

    Demuth, O.J.

    1984-06-01

    A preliminary evaluation was made of the Velocity Pump Reaction Turbine (VPRT) as a total flow expander in a geothermal-electric conversion cycle. Values of geofluid effectiveness of VPRT systems were estimated for conditions consisting of: a 360/sup 0/ geothermal resource, 60/sup 0/F wet-bulb ambient temperature, zero and 0.003 mass concentrations of dissolved noncondensible gas in the geofluid, 100 and 120/sup 0/F condensing temperatures, and engine efficiencies ranging from 0.4 to 1.0. Achievable engine efficiencies were estimated to range from 0.47 to 0.77, with plant geofluid effectiveness values ranging as high as 9.5 Watt hr/lbm geofluid for the 360/sup 0/F resource temperature. This value is competitive with magnitudes of geofluid effectiveness projected for advanced binary plants, and is on the order of 40% higher than estimates for dual-flash steam and other total flow systems reviewed. Because of its potentially high performance and relative simplicity, the VPRT system appears to warrant further investigation toward its use in a well-head geothermal plant.

  16. Quick estimating for thermal conductivity

    SciTech Connect (OSTI)

    Sastri, S.R.S.; Rao, K.K. )

    1993-08-01

    Accurate values for thermal conductivity--an important engineering property used in heat transfer calculations of liquids--are not as readily available as those for other physical properties. Therefore, it often becomes necessary to use estimated data. A new estimating method combines ease of use with an accuracy that is generally better than existing procedures. The paper discusses how to select terms and testing correlations, then gives two examples of the use of the method for calculation of the thermal conductivity of propionic acid and chlorobenzene.

  17. New developments in capital cost estimating

    SciTech Connect (OSTI)

    Stutz, R.A.; Zocher, M.A.

    1988-01-01

    The new developments in cost engineering revolve around the ability to capture information that in the past could not be automated. The purpose of automation is not to eliminate the expert cost engineer. The goal is to use available technology to have more information available to the professionals in the cost engineering field. In that sense, the demand for expertise increases in order to produce the highest quality estimate and project possible from all levels of cost engineers. We cannot overemphasize the importance of using a good source of expert information in building these types of programs. ''Garbage in, garbage out'' still applies in this form of programming. Expert systems technology will become commonplace in many vertical markets; it is important to undersand what can and cannot be accomplished in our field, and where this technology will lead us in the future.

  18. 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 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S.

  19. 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

  20. 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 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S.

  1. 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 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S.

  2. FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION

    SciTech Connect (OSTI)

    Rodney, Steven A.; Tonry, John L. E-mail: jt@ifa.hawaii.ed

    2010-05-20

    Wide-field surveys will soon be discovering Type Ia supernovae (SNe) at rates of several thousand per year. Spectroscopic follow-up can only scratch the surface for such enormous samples, so these extensive data sets will only be useful to the extent that they can be characterized by the survey photometry alone. In a companion paper we introduced the Supernova Ontology with Fuzzy Templates (SOFT) method for analyzing SNe using direct comparison to template light curves, and demonstrated its application for photometric SN classification. In this work we extend the SOFT method to derive estimates of redshift and luminosity distance for Type Ia SNe, using light curves from the Sloan Digital Sky Survey (SDSS) and Supernova Legacy Survey (SNLS) as a validation set. Redshifts determined by SOFT using light curves alone are consistent with spectroscopic redshifts, showing an rms scatter in the residuals of rms{sub z} = 0.051. SOFT can also derive simultaneous redshift and distance estimates, yielding results that are consistent with the currently favored {Lambda}CDM cosmological model. When SOFT is given spectroscopic information for SN classification and redshift priors, the rms scatter in Hubble diagram residuals is 0.18 mag for the SDSS data and 0.28 mag for the SNLS objects. Without access to any spectroscopic information, and even without any redshift priors from host galaxy photometry, SOFT can still measure reliable redshifts and distances, with an increase in the Hubble residuals to 0.37 mag for the combined SDSS and SNLS data set. Using Monte Carlo simulations, we predict that SOFT will be able to improve constraints on time-variable dark energy models by a factor of 2-3 with each new generation of large-scale SN surveys.

  3. 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 ...

  4. 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...

  5. 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...

  6. Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected...

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

    Expected Future Production (Million Barrels) Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3...

  7. United States Total Electric Power Industry Net Summer Capacity...

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

    Total Electric Power Industry Net Summer Capacity, by Energy Source, 2006 - 2010" "(Megawatts)" "United ... Gases",2256,2313,1995,1932,2700 "Nuclear",100334,100266,100755,101004,10116...

  8. 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,...

  9. 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...

  10. ,"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...

  11. 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...

  12. ,"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...

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

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

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

  15. "Table 17. Total Delivered Residential Energy Consumption, Projected...

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

    Total Delivered Residential Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2...

  16. $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...

  17. Achieving Total Employee Engagement in Energy Efficiency | Department...

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

    Ratheon and GM share their experiences with employee engagement to achieve energy efficiency and sustainability goals in this presentation. Achieving Total Employee Engagement in ...

  18. 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...

  19. U.S. Total Imports of Residual Fuel

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

    Area: U.S. Total PAD District 1 Connecticut Delaware Florida Georgia Maine Maryland Massachusetts New Hampshire New Jersey New York North Carolina Pennsylvania Rhode Island South ...

  20. "Table 18. Total Delivered Commercial Energy Consumption, Projected...

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

    Total Delivered Commercial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,20...

  1. United States Total Electric Power Industry Net Generation, by...

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

    Total Electric Power Industry Net Generation, by Energy Source, 2006 - 2010" "(Thousand Megawatthours)" "United States" "Energy Source",2006,2007,2008,2009,2010 ...

  2. ARM: GRAMS: calibration information for the total direct diffuse...

    Office of Scientific and Technical Information (OSTI)

    OSTI Identifier: 1025194 DOE Contract Number: DE-AC05-00OR22725 Resource Type: Dataset Data Type: Numeric Data Research Org: Atmospheric Radiation Measurement (ARM) Archive, Oak ...

  3. Mandatory Photovoltaic System Cost Estimate

    Broader source: Energy.gov [DOE]

    If the customer has a ratio of estimated monthly kilowatt-hour (kWh) usage to line extension mileage that is less than or equal to 1,000, the utility must provide the comparison at no cost. If the...

  4. BLE: Battery Life Estimator | Argonne National Laboratory

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

    BLE: Battery Life Estimator BLE: Battery Life Estimator Argonne's Battery Life Estimator (BLE) software is a state-of-the-art tool kit for fitting battery aging data and for ...

  5. Incorporating Experimental Information in the Total Monte Carlo Methodology Using File Weights

    SciTech Connect (OSTI)

    Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rochman, D.; Alhassan, E.; Pomp, S.

    2015-01-15

    Some criticism has been directed towards the Total Monte Carlo method because experimental information has not been taken into account in a statistically well-founded manner. In this work, a Bayesian calibration method is implemented by assigning weights to the random nuclear data files and the method is illustratively applied to a few applications. In some considered cases, the estimated nuclear data uncertainties are significantly reduced and the central values are significantly shifted. The study suggests that the method can be applied both to estimate uncertainties in a more justified way and in the search for better central values. Some improvements are however necessary; for example, the treatment of outliers and cross-experimental correlations should be more rigorous and random files that are intended to be prior files should be generated.

  6. Estimate of B(B{yields}X{sub s}{gamma}) at O({alpha}{sub s}{sup 2})

    SciTech Connect (OSTI)

    Misiak, M.; Asatrian, H. M.; Hovhannisyan, A.; Poghosyan, V.; Bieri, K.; Ewerth, T.; Greub, C.; Czakon, M.; Czarnecki, A.; Slusarczyk, M.; Ferroglia, A.; Gambino, P.; Gorbahn, M.; Steinhauser, M.; Haisch, U.; Hurth, T.; Mitov, A.

    2007-01-12

    Combining our results for various O({alpha}{sub s}{sup 2}) corrections to the weak radiative B-meson decay, we are able to present the first estimate of the branching ratio at the next-to-next-to-leading order in QCD. We find B(B{yields}X{sub s}{gamma})=(3.15{+-}0.23)x10{sup -4} for E{sub {gamma}}>1.6 GeV in the B-meson rest frame. The four types of uncertainties: nonperturbative (5%), parametric (3%), higher-order (3%), and m{sub c}-interpolation ambiguity (3%) have been added in quadrature to obtain the total error.

  7. "Table A28. Total Expenditures for Purchased Energy Sources by Census Region"

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

    Total Expenditures for Purchased Energy Sources by Census Region" " and Economic Characteristics of the Establishment, 1991" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke","

  8. Table A14. Total First Use (formerly Primary Consumption) of Energy for All P

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

    4. Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row"," ","

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

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

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

  10. Table A30. Total Primary Consumption of Energy for All Purposes by Value of

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

    0. Total Primary Consumption of Energy for All Purposes by Value of" "Shipment Categories, Industry Group, and Selected Industries, 1991" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," ","(million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," ","

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

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

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

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

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

    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

  13. 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

  14. 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

  15. 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

  16. 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

  17. Estimates and Recommendations for Coincidence Geometry (Technical...

    Office of Scientific and Technical Information (OSTI)

    Estimates and Recommendations for Coincidence Geometry Citation Details In-Document Search Title: Estimates and Recommendations for Coincidence Geometry You are accessing a...

  18. Estimating Waste Inventory and Waste Tank Characterization |...

    Office of Environmental Management (EM)

    Estimating Waste Inventory and Waste Tank Characterization Estimating Waste Inventory and Waste Tank Characterization Summary Notes from 28 May 2008 Generic Technical Issue ...

  19. Total Acid Value Titration of Hydrotreated Biomass Fast Pyrolysis Oil: Determination of Carboxylic Acids and Phenolics with Multiple End-Point Detection

    SciTech Connect (OSTI)

    Christensen, E.; Alleman, T. L.; McCormick, R. L.

    2013-01-01

    Total acid value titration has long been used to estimate corrosive potential of petroleum crude oil and fuel oil products. The method commonly used for this measurement, ASTM D664, utilizes KOH in isopropanol as the titrant with potentiometric end point determination by pH sensing electrode and Ag/AgCl reference electrode with LiCl electrolyte. A natural application of the D664 method is titration of pyrolysis-derived bio-oil, which is a candidate for refinery upgrading to produce drop in fuels. Determining the total acid value of pyrolysis derived bio-oil has proven challenging and not necessarily amenable to the methodology employed for petroleum products due to the different nature of acids present. We presented an acid value titration for bio-oil products in our previous publication which also utilizes potentiometry using tetrabutylammonium hydroxide in place of KOH as the titrant and tetraethylammonium bromide in place of LiCl as the reference electrolyte to improve the detection of these types of acids. This method was shown to detect numerous end points in samples of bio-oil that were not detected by D664. These end points were attributed to carboxylic acids and phenolics based on the results of HPLC and GC-MS studies. Additional work has led to refinement of the method and it has been established that both carboxylic acids and phenolics can be determined accurately. Use of pH buffer calibration to determine half-neutralization potentials of acids in conjunction with the analysis of model compounds has allowed us to conclude that this titration method is suitable for the determination of total acid value of pyrolysis oil and can be used to differentiate and quantify weak acid species. The measurement of phenolics in bio-oil is subject to a relatively high limit of detection, which may limit the utility of titrimetric methodology for characterizing the acidic potential of pyrolysis oil and products.

  20. Greater-than-Class C low-level radioactive waste characterization: Estimated volumes, radionuclide activities, and other characteristics. Revision 1

    SciTech Connect (OSTI)

    Not Available

    1994-09-01

    The Department of Energy`s (DOE`s) planning for the disposal of greater-than-Class C low-level radioactive waste (GTCC LLW) requires characterization of the waste. This report estimates volumes, radionuclide activities, and waste forms of GTCC LLW to the year 2035. It groups the waste into four categories, representative of the type of generator or holder of the waste: Nuclear Utilities, Sealed Sources, DOE-Held, and Other Generator. GTCC LLW includes activated metals (activation hardware from reactor operation and decommissioning), process wastes (i.e., resins, filters, etc.), sealed sources, and other wastes routinely generated by users of radioactive material. Estimates reflect the possible effect that packaging and concentration averaging may have on the total volume of GTCC LLW. Possible GTCC mixed LLW is also addressed. Nuclear utilities will probably generate the largest future volume of GTCC LLW with 65--83% of the total volume. The other generators will generate 17--23% of the waste volume, while GTCC sealed sources are expected to contribute 1--12%. A legal review of DOE`s obligations indicates that the current DOE-Held wastes described in this report will not require management as GTCC LLW because of the contractual circumstances under which they were accepted for storage. This report concludes that the volume of GTCC LLW should not pose a significant management problem from a scientific or technical standpoint. The projected volume is small enough to indicate that a dedicated GTCC LLW disposal facility may not be justified. Instead, co-disposal with other waste types is being considered as an option.

  1. Effects of spent fuel types on offsite consequences of hypothetical accidents

    SciTech Connect (OSTI)

    Courtney, J. C.; Dwight, C. C.; Lehto, M. A.

    2000-02-18

    Argonne National Laboratory (ANL) conducts experimental work on the development of waste forms suitable for several types of spent fuel at its facility on the Idaho National Engineering and Environmental Laboratory (INEEL) located 48 km West of Idaho Falls, ID. The objective of this paper is to compare the offsite radiological consequences of hypothetical accidents involving the various types of spent nuclear fuel handled in nonreactor nuclear facilities. The highest offsite total effective dose equivalents (TEDEs) are estimated at a receptor located about 5 km SSE of ANL facilities. Criticality safety considerations limit the amount of enriched uranium and plutonium that could be at risk in any given scenario. Heat generated by decay of fission products and actinides does not limit the masses of spent fuel within any given operation because the minimum time elapsed since fissions occurred in any form is at least five years. At cooling times of this magnitude, fewer than ten radionuclides account for 99% of the projected TEDE at offsite receptors for any credible accident. Elimination of all but the most important nuclides allows rapid assessments of offsite doses with little loss of accuracy. Since the ARF (airborne release fraction), RF (respirable fraction), LPF (leak path fraction) and atmospheric dilution factor ({chi}/Q) can vary by orders of magnitude, it is not productive to consider nuclides that contribute less than a few percent of the total dose. Therefore, only {sup 134}Cs, {sup 137}Cs-{sup 137m}Ba, and the actinides significantly influence the offsite radiological consequences of severe accidents. Even using highly conservative assumptions in estimating radiological consequences, they remain well below current Department of Energy guidelines for highly unlikely accidents.

  2. Background estimation in experimental spectra

    SciTech Connect (OSTI)

    Fischer, R.; Hanson, K. M.; Los Alamos National Laboratory, MS P940, Los Alamos, New Mexico 87545 ; Dose, V.; Linden, W. von der

    2000-02-01

    A general probabilistic technique for estimating background contributions to measured spectra is presented. A Bayesian model is used to capture the defining characteristics of the problem, namely, that the background is smoother than the signal. The signal is allowed to have positive and/or negative components. The background is represented in terms of a cubic spline basis. A variable degree of smoothness of the background is attained by allowing the number of knots and the knot positions to be adaptively chosen on the basis of the data. The fully Bayesian approach taken provides a natural way to handle knot adaptivity and allows uncertainties in the background to be estimated. Our technique is demonstrated on a particle induced x-ray emission spectrum from a geological sample and an Auger spectrum from iron, which contains signals with both positive and negative components. (c) 2000 The American Physical Society.

  3. Cell Shipments Total Inventory, Start-of-Year

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

    Cell Shipments Total Inventory, Start-of-Year 628,668 Manufactured and Purchased During Reporting Year 652,696 Imported During Reporting Year 233,377 Total Available for Shipment 1,514,740 Cells Assembled into Modules and Sold for Resale 1,129,525 Export Shipments 106,472 Total Shipments 1,235,997 Inventory, End-of-Year 278,744 Table 5. Source and disposition of photovoltaic cell shipments, 2014 (peak kilowatts) Source Disposition Source: U.S. Energy Information Administration, Form EIA-63B,

  4. Module Shipments Total Inventory, Start-of-Year

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

    Module Shipments Total Inventory, Start-of-Year 906,914 Manufactured During Reporting Year 726,915 Imported During Reporting Year 5,858,676 Purchased from U.S. OEM 33,951 Total Available for Shipment 7,526,456 U.S. Shipments and Sales for Resale 6,054,538 Export Shipments 182,985 Total Shipments 6,237,524 Inventory, End-of-Year 1,288,933 Table 6. Source and disposition of photovoltaic module shipments, 2014 (peak kilowatts) Source Disposition Source: U.S. Energy Information Administration, Form

  5. Guidelines for Estimating Unmetered Landscapting Water Use

    SciTech Connect (OSTI)

    None

    2010-07-30

    Guidance to help Federal agencies estimate unmetered landscaping water use as required by Executive Order 13514

  6. SECPOP90: Sector population, land fraction, and economic estimation program

    SciTech Connect (OSTI)

    Humphreys, S.L.; Rollstin, J.A.; Ridgely, J.N.

    1997-09-01

    In 1973 Mr. W. Athey of the Environmental Protection Agency wrote a computer program called SECPOP which calculated population estimates. Since that time, two things have changed which suggested the need for updating the original program - more recent population censuses and the widespread use of personal computers (PCs). The revised computer program uses the 1990 and 1992 Population Census information and runs on current PCs as {open_quotes}SECPOP90.{close_quotes} SECPOP90 consists of two parts: site and regional. The site provides population and economic data estimates for any location within the continental United States. Siting analysis is relatively fast running. The regional portion assesses site availability for different siting policy decisions; i.e., the impact of available sites given specific population density criteria within the continental United States. Regional analysis is slow. This report compares the SECPOP90 population estimates and the nuclear power reactor licensee-provided information. Although the source, and therefore the accuracy, of the licensee information is unknown, this comparison suggests SECPOP90 makes reasonable estimates. Given the total uncertainty in any current calculation of severe accidents, including the potential offsite consequences, the uncertainty within SECPOP90 population estimates is expected to be insignificant. 12 refs., 55 figs., 7 tabs.

  7. ,"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...

  8. ,"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" ...

  9. ,"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" ...

  10. ,"U.S. Total Crude Oil and Products Imports"

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

    to Contents","Data 1: U.S. Total Crude Oil and Products Imports" "Sourcekey","MTTIMUS1... "Date","U.S. Imports of Crude Oil and Petroleum Products (Thousand ...

  11. ,"U.S. Total Crude Oil and Products Imports"

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

    to Contents","Data 1: U.S. Total Crude Oil and Products Imports" "Sourcekey","MTTIMUS2... "Date","U.S. Imports of Crude Oil and Petroleum Products (Thousand Barrels ...

  12. "Table A48. Total Expenditures for Purchased Electricity,...

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

    ...teristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors"," " ,"Total United States" "RSE Column Factors:",0.4,2.7,1.5...

  13. Lower 48 States Total Natural Gas Underground Storage Capacity...

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

    Lower 48 States Total Natural Gas Underground Storage Capacity (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2012 8,842,950 8,854,720 8,854,720 ...

  14. AEO2011:Total Energy Supply, Disposition, and Price Summary ...

    Open Energy Info (EERE)

    case. The dataset uses quadrillion Btu and the U.S. Dollar. The data is broken down into production, imports, exports, consumption and price. Data and Resources AEO2011:Total...

  15. Gathering total items count for pagination | OpenEI Community

    Open Energy Info (EERE)

    Gathering total items count for pagination Home > Groups > Utility Rate Hi I'm using the following base link plus some restrictions to sector, utility, and locations to poll for...

  16. Table A1. Total First Use (formerly Primary Consumption) of...

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

    ... Manufacturing Industries"," W ",613,0," W ",2," W ",0,0," W ",0,28.1 ,"Total",1947,98827,2220,2397,500,6887,13448,1627,728,48,8.2 ,,"West South Central Census Division" ...

  17. Table A1. Total First Use (formerly Primary Consumption) of...

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

    ... Manufacturing Industries"," W ",2,0," W ",2," W ",0,0," W ",0,28.1 ,"Total",1947,337,14,14,515,26,320,40,728,48,8.3 ,,"West South Central Census Division" ,"RSE Column ...

  18. 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...

  19. Table 21. Total Energy Related Carbon Dioxide Emissions, Projected...

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

    Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual Projected (million metric tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 ...

  20. "Table 21. Total Energy Related Carbon Dioxide Emissions, Projected...

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

    Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual" "Projected" " (million metric tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,200...

  1. 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.

  2. 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 ...

  3. 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. National Fuel Cell and Hydrogen Energy Overview (4.73 MB) More ...

  4. 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.

  5. 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.

  6. Property:Building/SPElectrtyUsePercTotal | Open Energy Information

    Open Energy Info (EERE)

    PElectrtyUsePercTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 100.0 + Sweden Building 05K0002 + 100.0 + Sweden Building 05K0003 +...

  7. Alabama Natural Gas Percentage Total Industrial Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    Industrial Deliveries (Percent) Alabama Natural Gas Percentage Total Industrial Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  8. 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.

  9. Measurements and modeling of total solar irradiance in X-class solar flares

    SciTech Connect (OSTI)

    Moore, Christopher Samuel; Chamberlin, Phillip Clyde; Hock, Rachel

    2014-05-20

    The Total Irradiance Monitor (TIM) from NASA's SOlar Radiation and Climate Experiment can detect changes in the total solar irradiance (TSI) to a precision of 2 ppm, allowing observations of variations due to the largest X-class solar flares for the first time. Presented here is a robust algorithm for determining the radiative output in the TIM TSI measurements, in both the impulsive and gradual phases, for the four solar flares presented in Woods et al., as well as an additional flare measured on 2006 December 6. The radiative outputs for both phases of these five flares are then compared to the vacuum ultraviolet (VUV) irradiance output from the Flare Irradiance Spectral Model (FISM) in order to derive an empirical relationship between the FISM VUV model and the TIM TSI data output to estimate the TSI radiative output for eight other X-class flares. This model provides the basis for the bolometric energy estimates for the solar flares analyzed in the Emslie et al. study.

  10. " Level: National Data and Regional Totals;"

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

    0 Capability to Switch Coal to Alternative Energy Sources, 2002; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Short Tons." ,,"Coal",,,"Alternative Energy Sources(b)" ,,,,,,,,,,,"RSE" "NAICS"," ","Total","

  11. " Level: National Data and Regional Totals;"

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

    2 Capability to Switch Natural Gas to Alternative Energy Sources, 2002;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Billion Cubic Feet." ,,"Natural Gas",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total","

  12. " Level: National Data and Regional Totals;"

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

    4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Residual Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total","

  13. " Level: National Data and Regional Totals;"

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

    6 Capability to Switch Electricity to Alternative Energy Sources, 2002; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Million Kilowatthours." ,,"Electricity Receipts",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total","

  14. " Level: National Data and Regional Totals;"

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

    8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Distillate Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total","

  15. " Level: National Data and Regional Totals;"

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

    0 Capability to Switch Coal to Alternative Energy Sources, 2006; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Short Tons." ,,"Coal",,,"Alternative Energy Sources(b)" "NAICS"," ","Total","

  16. " Level: National Data and Regional Totals;"

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

    2 Capability to Switch Natural Gas to Alternative Energy Sources, 2006;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Billion Cubic Feet." ,,"Natural Gas",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total","

  17. " Level: National Data and Regional Totals;"

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

    4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2006;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Residual Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total","

  18. " Level: National Data and Regional Totals;"

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

    8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2006; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Distillate Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total","

  19. Estimating Terrorist Risk with Possibility Theory

    SciTech Connect (OSTI)

    J.L. Darby

    2004-11-30

    This report summarizes techniques that use possibility theory to estimate the risk of terrorist acts. These techniques were developed under the sponsorship of the Department of Homeland Security (DHS) as part of the National Infrastructure Simulation Analysis Center (NISAC) project. The techniques have been used to estimate the risk of various terrorist scenarios to support NISAC analyses during 2004. The techniques are based on the Logic Evolved Decision (LED) methodology developed over the past few years by Terry Bott and Steve Eisenhawer at LANL. [LED] The LED methodology involves the use of fuzzy sets, possibility theory, and approximate reasoning. LED captures the uncertainty due to vagueness and imprecision that is inherent in the fidelity of the information available for terrorist acts; probability theory cannot capture these uncertainties. This report does not address the philosophy supporting the development of nonprobabilistic approaches, and it does not discuss possibility theory in detail. The references provide a detailed discussion of these subjects. [Shafer] [Klir and Yuan] [Dubois and Prade] Suffice to say that these approaches were developed to address types of uncertainty that cannot be addressed by a probability measure. An earlier report discussed in detail the problems with using a probability measure to evaluate terrorist risk. [Darby Methodology]. Two related techniques are discussed in this report: (1) a numerical technique, and (2) a linguistic technique. The numerical technique uses traditional possibility theory applied to crisp sets, while the linguistic technique applies possibility theory to fuzzy sets. Both of these techniques as applied to terrorist risk for NISAC applications are implemented in software called PossibleRisk. The techniques implemented in PossibleRisk were developed specifically for use in estimating terrorist risk for the NISAC program. The LEDTools code can be used to perform the same linguistic evaluation as

  20. A statistical study of the macroepidemiology of air pollution and total mortality

    SciTech Connect (OSTI)

    Lipfert, F.W.; Malone, R.G.; Daum, M.L.; Mendell, N.R.; Yang, Chin-Chun

    1988-04-01

    A statistical analysis of spatial patterns of 1980 US urban total mortality (all causes) was performed, evaluating demographic, socioeconomic and air pollution factors as predictors. Specific mortality predictors included cigarette smoking, drinking water hardness, heating fuel use, and 1978-1982 annual concentrations of the following air pollutants: ozone, carbon monoxide, sulfate aerosol, particulate concentrations of lead, iron, cadmium, manganese, vanadium, as well as total and fine particle mass concentrations from the inhalable particulate network (dichotomous samplers). In addition, estimates of sulfur dioxide, oxides of nitrogen, and sulfate aerosol were made for each city using the ASTRAP long-range transport diffusion model, and entered into the analysis as independent variables. Because the number of cities with valid air quality and water hardness data varied considerably by pollutant, it was necessary to consider several different data sets, ranging from 48 to 952 cities. The relatively strong associations (ca. 5--10%) shown for 1980 pollution with 1980 total mortality are generally not confirmed by independent studies, for example, in Europe. In addition, the US studies did not find those pollutants with known adverse health effects at the concentrations in question (such as ozone or CO) to be associated with mortality. The question of causality vs. circumstantial association must therefore be regarded as still unresolved. 59 refs., 20 figs., 40 tabs.