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Sample records for total maximum daily

  1. 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...

  2. TRENDS IN ESTIMATED MIXING DEPTH DAILY MAXIMUMS

    SciTech Connect (OSTI)

    Buckley, R; Amy DuPont, A; Robert Kurzeja, R; Matt Parker, M

    2007-11-12

    Mixing depth is an important quantity in the determination of air pollution concentrations. Fireweather forecasts depend strongly on estimates of the mixing depth as a means of determining the altitude and dilution (ventilation rates) of smoke plumes. The Savannah River United States Forest Service (USFS) routinely conducts prescribed fires at the Savannah River Site (SRS), a heavily wooded Department of Energy (DOE) facility located in southwest South Carolina. For many years, the Savannah River National Laboratory (SRNL) has provided forecasts of weather conditions in support of the fire program, including an estimated mixing depth using potential temperature and turbulence change with height at a given location. This paper examines trends in the average estimated mixing depth daily maximum at the SRS over an extended period of time (4.75 years) derived from numerical atmospheric simulations using two versions of the Regional Atmospheric Modeling System (RAMS). This allows for differences to be seen between the model versions, as well as trends on a multi-year time frame. In addition, comparisons of predicted mixing depth for individual days in which special balloon soundings were released are also discussed.

  3. Application of Markov chain model to daily maximum temperature for thermal comfort in Malaysia

    SciTech Connect (OSTI)

    Nordin, Muhamad Asyraf bin Che; Hassan, Husna

    2015-10-22

    The Markov chain’s first order principle has been widely used to model various meteorological fields, for prediction purposes. In this study, a 14-year (2000-2013) data of daily maximum temperatures in Bayan Lepas were used. Earlier studies showed that the outdoor thermal comfort range based on physiologically equivalent temperature (PET) index in Malaysia is less than 34°C, thus the data obtained were classified into two state: normal state (within thermal comfort range) and hot state (above thermal comfort range). The long-run results show the probability of daily temperature exceed TCR will be only 2.2%. On the other hand, the probability daily temperature within TCR will be 97.8%.

  4. Relative Accuracy of 1-Minute and Daily Total Solar Radiation Data for 12 Global and 4 Direct Beam Solar Radiometers

    SciTech Connect (OSTI)

    Myers, D.; Wilcox, S. M.

    2009-01-01

    We evaluated the relative performance of 12 global and four direct beam solar radiometers deployed at a single site over a 12-month period. Test radiometer irradiances were compared with a reference irradiance consisting of either an absolute cavity radiometer (during calibrations) or a low uncertainty thermopile pyrheliometer (during the evaluation period) for pyrheliometers; and for pyranometers a reference global irradiance computed from the reference pyrheliometer and diffuse irradiance from a shaded pyranometer. One minute averages of 3-second data for 12 months from the test instrument measurements were compared with the computed reference data set. Combined uncertainty in the computed reference irradiance is 1.8% {+-} 0.5%. Total uncertainty in the pyranometer comparisons is {+-}2.5%. We show mean percent difference between reference global irradiance and test pyranometer 1 minute data as a function of zenith angle, and percent differences between daily totals for the reference and test irradiances as a function of day number. We offer no explicit conclusion about the performance of instrument models, as a general array of applications with a wide range of instrumentation and accuracy requirements could be addressed with any of the radiometers.

  5. 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 ...

  6. 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 ...

  7. 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 ...

  8. 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 ...

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. Maximum-likelihood

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

    Jurisdiction waters of the Gulf of Mexico. Alaska is all onshore. Total crews includes crews with unknown survey dimension. Data are reported on the first and fifteenth of each month, except January when they are reported only on the fifteenth. When semi-monthly values differ for the month, the larger of the two values is shown here. Consequently, this table reflects the maximum number of crews at work at any time during the month. See Definitions, Sources, and Notes link above for more

  20. 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

  1. 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...

  2. 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

  3. WAPA Daily Energy Accounting Activities

    Energy Science and Technology Software Center (OSTI)

    1990-10-01

    ISA (Interchange, Scheduling, & Accounting) is the interchange scheduling system used by the DOE Western Area Power Administration to perform energy accounting functions associated with the daily activities of the Watertown Operations Office (WOO). The system's primary role is to provide accounting functions for scheduled energy which is exchanged with other power companies and power operating organizations. The system has a secondary role of providing a historical record of all scheduled interchange transactions. The followingmore » major functions are performed by ISA: scheduled energy accounting for received and delivered energy; generation scheduling accounting for both fossil and hydro-electric power plants; metered energy accounting for received and delivered totals; energy accounting for Direct Current (D.C.) Ties; regulation accounting; automatic generation control set calculations; accounting summaries for Basin, Heartland Consumers Power District, and the Missouri Basin Municipal Power Agency; calculation of estimated generation for the Laramie River Station plant; daily and monthly reports; and dual control areas.« less

  4. Backstage at the Daily Show

    Broader source: Energy.gov [DOE]

    Backstage footage from Secretary Chu's appearance on the Daily Show where he discuses the green room candy dish and possible lighting considerations.

  5. BPA Daily Notice (pbl/products)

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

    Products > Products Daily Notice (surplus power) Transmission Losses Power Products Catalog Wind Smoothing and Intertie Service (Pilot) Firstgov BPA'S DAILY NOTICE Daily Notice...

  6. Removal to Maximum Extent Practical

    Broader source: Energy.gov [DOE]

    Summary Notes from 1 November 2007 Generic Technical Issue Discussion on Removal of Highly Radioactive Radionuclides/Key Radionuclides to the Maximum Extent Practical

  7. 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 -

  8. 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

  9. 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

  10. A new look at maximum and minimum temperature trends for the globe

    SciTech Connect (OSTI)

    Easterling, D.R.; Peterson, T.C.; Karl, T.R.

    1997-11-01

    A number of recent studies have established that differential changes in daily maximum and minimum temperatures are occurring, resulting in changes in the diurnal temperature range (DTR) for many parts of the globe. Large-scale trends in the USA indicate that minimum temperatures are increasing at a faster rate than maximum temperatures, resulting in a narrowing in the DTR. This paper updates and extends the analysis of changes in the DTR in three ways: (1) by increasing the areal coverage to more than half the global landmass, (2) by addressing the issue of homogeneity of the data, and (3) by examining the potential effects of urban stations on the calculated trends. The update includes data for an additional 15% of the global land area and an extension of the analysis period used in a previous study. Homogeneity techniques were used on the data to adjust individual station data for undocumented discontinuities. Annual maximum and minimum temperature and DTR time series for the 1950-1993 period averaged over 54% of the total global land area are presented. The trend for the maximum temperature is 0.88 C/100 years, which is consistent with earlier findings. However, the trend for the minimum temperature is 1.86 C/100 years; this is less than found in previous analyses and leads to a smaller trend in the DTR. This finding is not surprising since much of the data added in this study are for tropical and sub-tropical regions where temperature trends are not expected to be as large as in higher latitude regions. The effect of urbanization on the global trends is found to be on the order of 0.1 C/100 years or less, which is consistent with previous investigations. 14 refs., 2 figs.

  11. Energy Assurance Daily | Department of Energy

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

    Energy Assurance Daily Energy Assurance Daily Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems, flows, and markets, it provides highlights of energy issues rather than a comprehensive coverage. Energy Assurance Daily covers: Major energy developments Electricity, petroleum, and natural gas industries Other relevant news Energy prices The Infrastructure

  12. Table 10.1 Nonswitchable Minimum and Maximum Consumption, 2002

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

    Nonswitchable Minimum and Maximum Consumption, 2002; " " Level: National and Regional Data;" " Row: Energy Sources;" " Column: Consumption Potential;" " Unit: Physical Units." ,,,,"RSE" ,"Actual","Minimum","Maximum","Row" "Energy Sources","Consumption","Consumption(a)","Consumption(b)","Factors" ,"Total United States" "RSE Column

  13. Maximum Performance Group MPG | Open Energy Information

    Open Energy Info (EERE)

    Maximum Performance Group MPG Jump to: navigation, search Name: Maximum Performance Group (MPG) Place: College Point, New York Zip: 11356 Product: Technology based energy and asset...

  14. Boiler Maximum Achievable Control Technology (MACT) Technical...

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

    Boiler Maximum Achievable Control Technology (MACT) Technical Assistance - Fact Sheet, April 2015 Boiler Maximum Achievable Control Technology (MACT) Technical Assistance - Fact ...

  15. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted...

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

    PRIME Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME Docket No. EO-05-01: Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by ...

  16. TWP-ICE Daily Synoptic Overview

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

    Daily Synoptic Overview 16 January - 14 February 2006 Lori Chappel Bureau of Meteorology Weather Overview * 13 January - 2 February 2006 Monsoon across north Australia; - 13-25...

  17. Energy Assurance Daily (EAD): June 2012

    Broader source: Energy.gov [DOE]

    Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

  18. Energy Assurance Daily (EAD): January- March 2012

    Office of Energy Efficiency and Renewable Energy (EERE)

    Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

  19. Energy Assurance Daily (EAD): April 2012

    Broader source: Energy.gov [DOE]

    Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

  20. Energy Assurance Daily (EAD): May 2012

    Office of Energy Efficiency and Renewable Energy (EERE)

    Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

  1. Energy Assurance Daily (EAD): July 2012

    Broader source: Energy.gov [DOE]

    Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

  2. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted...

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

    Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 5, 1, 2 SO2 Case Docket No. EO-05-01: Mirant Potomac, Alexandria, Virginia: Maximum Impacts ...

  3. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted...

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

    Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 4, 1, 2 SO2 Case Docket No. EO-05-01: Mirant Potomac, Alexandria, Virginia: Maximum Impacts ...

  4. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted...

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

    Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 3, 1, 2 SO2 Case Docket No. EO-05-01: Mirant Potomac, Alexandria, Virginia: Maximum Impacts ...

  5. 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...

  6. Daily temperature and precipitation data for 223 USSR Stations

    SciTech Connect (OSTI)

    Razuvaev, V.N.; Apasova, E.G.; Martuganov, R.A.; Vose, R.S.; Steurer, P.M.

    1993-11-01

    On- May 23, 1972, the United States and the USSR established a bilateral initiative known as the Agreement on Protection of the Environment. Given recent interest in possible greenhouse gas-induced climate change, Working Group VIII (Influence of Environmental Changes on Climate) has become particularly useful to the scientific communities of both nations. Among its many achievements, Working Group VIII has been instrumental in the exchange of climatological information between the principal climate data centers of each country [i.e., the National Climatic Data Center (NCDC) in Asheville, North Carolina, and the Research Institute of Hydrometeorological Information in Obninsk, Russia]. Considering the relative lack of climate records previously available for the USSR, data obtained via this bilateral exchange are particularly valuable to researchers outside the former Soviet Union. To expedite the dissemination of these data, NOAA`s Climate and Global Change Program funded the Carbon Dioxide Information Analysis Center (CDIAC) and NCDC to distribute one of the more useful archives acquired through this exchange: a 223-station daily data set covering the period 1881-1989. This data set contains: (1) daily mean, minimum, and maximum temperature data; (2) daily precipitation data; (3) station inventory information (WMO No., name, coordinates, and elevation); (4) station history information (station relocation and rain gauge replacement dates); and (5) quality assurance information (i.e., flag codes that were assigned as a result of various data checks). The data set is available, free of charge, as a Numeric Data Package (NDP) from CDIAC. The NDP consists of 18 data files and a printed document which describes both the data files and the 223-station network in detail.

  7. ,"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...

  8. Daylighter Daily Solar Roof Light | Open Energy Information

    Open Energy Info (EERE)

    Daylighter Daily Solar Roof Light Jump to: navigation, search Name: Daylighter Daily Solar Roof Light Address: 1991 Crocker Road, Suite 600 Place: Cleveland, Ohio Zip: 44145...

  9. Property:DailyOpWaterUseConsumed | Open Energy Information

    Open Energy Info (EERE)

    Property Name DailyOpWaterUseConsumed Property Type Number Description Daily Operation Water Use (afday) Consumed. Retrieved from "http:en.openei.orgwindex.php?titleProper...

  10. Property:DailyOpWaterUseGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name DailyOpWaterUseGross Property Type Number Description Daily Operation Water Use (afday) Gross. Retrieved from "http:en.openei.orgwindex.php?titleProperty:...

  11. 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...

  12. ,"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...

  13. ,"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...

  14. 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...

  15. 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*...

  16. ,"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...

  17. ,"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...

  18. ,"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"...

  19. 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.

  20. 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 ...

  1. United States Historical Climatology Network Daily Temperature and Precipitation Data (1871-1997)

    SciTech Connect (OSTI)

    Easterling, D.R.

    2002-10-28

    This document describes a database containing daily observations of maximum and minimum temperature, precipitation amount, snowfall amount, and snow depth from 1062 observing stations across the contiguous US. This database is an expansion and update of the original 138-station database previously released by the Carbon Dioxide Information Analysis Center (CDIAC) as CDIAC numeric data package NDP-042. These 1062 stations are a subset of the 1221-station US Historical Climatology Network (HCN), a monthly database compiled by the National Climatic Data Center (Asheville, North Carolina) that has been widely used in analyzing US climate. Data from 1050 of these daily records extend into the 1990s, while 990 of these extend through 1997. Most station records are essentially complete for at least 40 years; the latest beginning year of record is 1948. Records from 158 stations begin prior to 1900, with that of Charleston, South Carolina beginning the earliest (1871). The daily resolution of these data makes them extremely valuable for studies attempting to detect and monitor long-term climatic changes on a regional scale. Studies using daily data may be able to detect changes in regional climate that would not be apparent from analysis of monthly temperature and precipitation data. Such studies may include analyses of trends in maximum and minimum temperatures, temperature extremes, daily temperature range, precipitation ''event size'' frequency, and the magnitude and duration of wet and dry periods. The data are also valuable in areas such as regional climate model validation and climate change impact assessment. This database is available free of charge from CDIAC as a numeric data package (NDP).

  2. Daily HMS Extremes in Met Data - Hanford Site

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

    Hanford Meteorological Station Daily HMS Extremes in Met Data Hanford Meteorological Station Real Time Met Data from Around the Site Current and Past 48 Hours HMS Observations Daily HMS Extremes in Met Data Met and Climate Data Summary Products Contacts / Hours Current NWS Forecast for the Tri-Cities NWS Windchill Chart Daily HMS Extremes in Met Data Email Email Page | Print Print Page | Text Increase Font Size Decrease Font Size This table shows the daily extremes at each of the remote stations

  3. 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

  4. Electron energy spectrum and maximum disruption angle under multi...

    Office of Scientific and Technical Information (OSTI)

    Conference: Electron energy spectrum and maximum disruption angle under multi-photon beamstrahlung Citation Details In-Document Search Title: Electron energy spectrum and maximum ...

  5. Electron energy spectrum and maximum disruption angle under multi...

    Office of Scientific and Technical Information (OSTI)

    Electron energy spectrum and maximum disruption angle under multi-photon beamstrahlung Citation Details In-Document Search Title: Electron energy spectrum and maximum disruption ...

  6. Oxidation State Optimization for Maximum Efficiency of NOx Adsorber...

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

    State Optimization for Maximum Efficiency of NOx Adsorber Catalysts Oxidation State Optimization for Maximum Efficiency of NOx Adsorber Catalysts Presentation given at the 16th ...

  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. 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

  9. Daily air pollution effects on children's respiratory symptoms and peak expiratory flow

    SciTech Connect (OSTI)

    Vedal, S.; Schenker, M.B.; Munoz, A.; Samet, J.M.; Batterman, S.; Speizer, F.E.

    1987-06-01

    To identify acute respiratory health effects associated with air pollution due to coal combustion, a subgroup of elementary school-aged children was selected from a large cross-sectional study and followed daily for eight months. Children were selected to obtain three equal-sized groups: one without respiratory symptoms, one with symptoms of persistent wheeze, and one with cough or phlegm production but without persistent wheeze. Parents completed a daily diary of symptoms from which illness constellations of upper respiratory illness (URI) and lower respiratory illness (LRI) and the symptom of wheeze were derived. Peak expiratory flow rate (PEFR) was measured daily for nine consecutive weeks during the eight-month study period. Maximum hourly concentrations of sulfur dioxide, nitrogen dioxide, ozone, and coefficient of haze for each 24-hour period, as well as minimum hourly temperature, were correlated with daily URI, LRI, wheeze, and PEFR using multiple regression models adjusting for illness occurrence or level of PEFR on the immediately preceding day. Respiratory illness on the preceding day was the most important predictor of current illness. A drop in temperature was associated with increased URI and LRI but not with increased wheeze or with a decrease in level of PEFR. No air pollutant was strongly associated with respiratory illness or with level of PEFR, either in the group of children as a whole, or in either of the symptomatic subgroups; the pollutant concentrations observed, however, were uniformly lower than current ambient air quality standards.

  10. 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

  11. Theoretical Estimate of Maximum Possible Nuclear Explosion

    DOE R&D Accomplishments [OSTI]

    Bethe, H. A.

    1950-01-31

    The maximum nuclear accident which could occur in a Na-cooled, Be moderated, Pu and power producing reactor is estimated theoretically. (T.R.H.) 2O82 Results of nuclear calculations for a variety of compositions of fast, heterogeneous, sodium-cooled, U-235-fueled, plutonium- and power-producing reactors are reported. Core compositions typical of plate-, pin-, or wire-type fuel elements and with uranium as metal, alloy, and oxide were considered. These compositions included atom ratios in the following range: U-23B to U-235 from 2 to 8; sodium to U-235 from 1.5 to 12; iron to U-235 from 5 to 18; and vanadium to U-235 from 11 to 33. Calculations were performed to determine the effect of lead and iron reflectors between the core and blanket. Both natural and depleted uranium were evaluated as the blanket fertile material. Reactors were compared on a basis of conversion ratio, specific power, and the product of both. The calculated results are in general agreement with the experimental results from fast reactor assemblies. An analysis of the effect of new cross-section values as they became available is included. (auth)

  12. New director of Jefferson Lab named (Daily Press) | Jefferson...

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

    https:www.jlab.orgnewsarticlesnew-director-jefferson-lab-named-daily-press New director of Jefferson Lab named Hugh Montgomery Hugh Montgomery has been named president of...

  13. Question of the Week: What Is Your Daily Commute Like?

    Broader source: Energy.gov [DOE]

    In data collected from 2005 through 2007, The U.S. Census Bureau found that 76% of workers drove alone to work. Tell us about your daily commute?

  14. 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

  15. Property:Maximum Velocity(m/s) | Open Energy Information

    Open Energy Info (EERE)

    Velocity(ms) Jump to: navigation, search Property Name Maximum Velocity(ms) Property Type String Pages using the property "Maximum Velocity(ms)" Showing 25 pages using this...

  16. Property:Maximum Wave Length(m) | Open Energy Information

    Open Energy Info (EERE)

    Length(m) Jump to: navigation, search Property Name Maximum Wave Length(m) Property Type String Pages using the property "Maximum Wave Length(m)" Showing 18 pages using this...

  17. Property:Maximum Wave Height(m) | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Property Name Maximum Wave Height(m) Property Type String Pages using the property "Maximum Wave Height(m)" Showing 25 pages using this property....

  18. Pool daily fuel scheduling. Volume 1: technical manual. Final Report, February 1981

    SciTech Connect (OSTI)

    Pang, C.K.; Mikolinnas, T.A.; Reppen, N.D.; Ringlee, R.J.; Wollenberg, B.F.

    1981-02-01

    The results and efforts of research and development of methods for daily fuel scheduling performed under EPRI Project RP 1048-5 by Power Technologies, Inc. (PTI) are reported in three volumes: Technical Manual, Programming Manual, and Program Listings. Daily fuel scheduling involves the scheduling and dispatching of generating facilities to meet all system loads and operating requirements for periods ranging from a day to a week. Daily fuel scheduling and computer requirements are defined. The scheduling problem is formulated as a mixed-integer linear programming (MILP) optimization problem in which the total system operating cost is minimized. A potentially practical scheduling procedure, based on a combination of search and MILP approaches, was proposed; these two approaches were investigated, coded in FORTRAN and tested individually. This volume of the report (Volume 1) is the Technical Manual and contains the main body of the report, which includes descriptions and results for two approaches to the daily fuel scheduling problem: Search Approach and Mixed Integer Linear Programming (MILP) Approach. Prototype computer programs on these approaches have been coded in FORTRAN for testing and evaluation purposes using PTI in-house PRIME time-sharing computer.

  19. Daily snow depth measurements from 195 stations in the United States

    SciTech Connect (OSTI)

    Allison, L.J.; Easterling, D.R.; Jamason, P.; Bowman, D.P.; Hughes, P.Y.; Mason, E.H.

    1997-02-01

    This document describes a database containing daily measurements of snow depth at 195 National Weather Service (NWS) first-order climatological stations in the United States. The data have been assembled and made available by the National Climatic Data Center (NCDC) in Asheville, North Carolina. The 195 stations encompass 388 unique sampling locations in 48 of the 50 states; no observations from Delaware or Hawaii are included in the database. Station selection criteria emphasized the quality and length of station records while seeking to provide a network with good geographic coverage. Snow depth at the 388 locations was measured once per day on ground open to the sky. The daily snow depth is the total depth of the snow on the ground at measurement time. The time period covered by the database is 1893--1992; however, not all station records encompass the complete period. While a station record ideally should contain daily data for at least the seven winter months (January through April and October through December), not all stations have complete records. Each logical record in the snow depth database contains one station`s daily data values for a period of one month, including data source, measurement, and quality flags.

  20. "Table A52. Nonswitchable Minimum Requirements and Maximum Consumption"

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

    2. Nonswitchable Minimum Requirements and Maximum Consumption" " Potential by Census Region, 1991" " (Estimates in Physical Units)" ,,,,"RSE" ,"Actual","Minimum","Maximum","Row" "Type of Energy","Consumption","Consumption(a)","Consumption(b)","Factors" "RSE Column Factors:",1,1.2,0.8 ," Total United States" ,"-","-","-"

  1. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by

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

    AERMOD-PRIME | Department of Energy PRIME Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME Docket No. EO-05-01: Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Compliance based on highest, second-highest, short-term, and highest annual concentrations. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME (24.52

  2. Their best defense is good fiscal sense (Daily Press) | Jefferson...

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

    https:www.jlab.orgnewsarticlestheir-best-defense-good-fiscal-sense-daily-press Their best defense is good fiscal sense Top Guard Security finds it can be a good idea to say,...

  3. Jefferson Lab: Laser gun to eventually shoot down missiles (Daily...

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

    Jefferson Lab: Laser gun to eventually shoot down missiles (Daily Press) External Link: http:articles.dailypress.com2011-02-21newsdp-nws-jefferson-lab-201102211j... By ...

  4. JLab's economic footprint expands (Daily Press) | Jefferson Lab

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

    JLab's economic footprint expands (Daily Press) External Link: http://articles.dailypress.com/2011-01-20/news/dp-nws-jlab-economy-20110120_1_je... By jlab_admin on Thu, 2011-01-2

  5. Italian Physicist Named Deputy Associate Director at JLab (Daily Press) |

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

    Jefferson Lab Italian Physicist Named Deputy Associate Director at JLab (Daily Press) External Link: http://www.dailypress.com/news/science/dead-rise-blog/dp-italian-physicist-named... By jlab_admin on Tue, 2012-02-1

  6. 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.

  7. Laser selection based on maximum permissible exposure limits...

    Office of Scientific and Technical Information (OSTI)

    Laser selection based on maximum permissible exposure limits for visible and middle-near infrared repetitively pulsed lasers. Citation Details In-Document Search Title: Laser ...

  8. Engineer End Uses for Maximum Efficiency | Department of Energy

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

    for Maximum Efficiency (August 2004) More Documents & Publications Maintaining System Air Quality Compressed Air Storage Strategies Alternative Strategies for Low Pressure End Uses

  9. Invisible Science: Lab Breakthroughs in Our Daily Lives | Department of

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

    Energy Invisible Science: Lab Breakthroughs in Our Daily Lives Invisible Science: Lab Breakthroughs in Our Daily Lives April 24, 2012 - 2:30pm Addthis The Lab Breakthroughs video series focuses on the array of technological advancements and discoveries that stem from research performed in the National Labs, including improvements in industrial processes, discoveries in fundamental scientific research, and innovative medicines. <a href="http://energy.gov/lab-breakthroughs">See

  10. 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

  11. Maximum Diameter Measurements of Aortic Aneurysms on Axial CT Images After Endovascular Aneurysm Repair: Sufficient for Follow-up?

    SciTech Connect (OSTI)

    Baumueller, Stephan Nguyen, Thi Dan Linh Goetti, Robert Paul; Lachat, Mario; Seifert, Burkhardt; Pfammatter, Thomas Frauenfelder, Thomas

    2011-12-15

    Purpose: To assess the accuracy of maximum diameter measurements of aortic aneurysms after endovascular aneurysm repair (EVAR) on axial computed tomographic (CT) images in comparison to maximum diameter measurements perpendicular to the intravascular centerline for follow-up by using three-dimensional (3D) volume measurements as the reference standard. Materials and Methods: Forty-nine consecutive patients (73 {+-} 7.5 years, range 51-88 years), who underwent EVAR of an infrarenal aortic aneurysm were retrospectively included. Two blinded readers twice independently measured the maximum aneurysm diameter on axial CT images performed at discharge, and at 1 and 2 years after intervention. The maximum diameter perpendicular to the centerline was automatically measured. Volumes of the aortic aneurysms were calculated by dedicated semiautomated 3D segmentation software (3surgery, 3mensio, the Netherlands). Changes in diameter of 0.5 cm and in volume of 10% were considered clinically significant. Intra- and interobserver agreements were calculated by intraclass correlations (ICC) in a random effects analysis of variance. The two unidimensional measurement methods were correlated to the reference standard. Results: Intra- and interobserver agreements for maximum aneurysm diameter measurements were excellent (ICC = 0.98 and ICC = 0.96, respectively). There was an excellent correlation between maximum aneurysm diameters measured on axial CT images and 3D volume measurements (r = 0.93, P < 0.001) as well as between maximum diameter measurements perpendicular to the centerline and 3D volume measurements (r = 0.93, P < 0.001). Conclusion: Measurements of maximum aneurysm diameters on axial CT images are an accurate, reliable, and robust method for follow-up after EVAR and can be used in daily routine.

  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. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2.

    SciTech Connect (OSTI)

    Thornton, Peter E; Thornton, Michele M; Mayer, Benjamin W; Wilhelmi, Nate; Wei, Yaxing; Devarakonda, Ranjeet; Cook, Robert B

    2014-01-01

    More information: http://daymet.ornl.gov Presenter: Ranjeet Devarakonda Environmental Sciences Division Oak Ridge National Laboratory (ORNL) Daymet: Daily Surface Weather Data and Climatological Summaries provides gridded estimates of daily weather parameters for North America, including daily continuous surfaces of minimum and maximum temperature, precipitation occurrence and amount, humidity, shortwave radiation, snow water equivalent, and day length. The current data product (Version 2) covers the period January 1, 1980 to December 31, 2013 [1]. The prior product (Version 1) only covered from 1980-2008. Data are available on a daily time step at a 1-km x 1-km spatial resolution in Lambert Conformal Conic projection with a spatial extent that covers the conterminous United States, Mexico, and Southern Canada as meteorological station density allows. Daymet data can be downloaded from 1) the ORNL Distributed Active Archive Center (DAAC) search and order tools (http://daac.ornl.gov/cgi-bin/cart/add2cart.pl?add=1219) or directly from the DAAC FTP site (http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1219) and 2) the Single Pixel Tool [2] and THREDDS (Thematic Real-time Environmental Data Services) Data Server [3]. The Single Pixel Data Extraction Tool allows users to enter a single geographic point by latitude and longitude in decimal degrees. A routine is executed that translates the (lon, lat) coordinates into projected Daymet (x,y) coordinates. These coordinates are used to access the Daymet database of daily-interpolated surface weather variables. Daily data from the nearest 1 km x 1 km Daymet grid cell are extracted from the database and formatted as a table with one column for each Daymet variable and one row for each day. All daily data for selected years are returned as a single (long) table, formatted for display in the browser window. At the top of this table is a link to the same data in a simple comma-separated text format, suitable for import into a

  14. Pool daily fuel scheduling. Volume 2: programming manual. Final report, February 1981

    SciTech Connect (OSTI)

    Pang, C.K.; Mikolinnas, T.A.

    1981-02-01

    The results and efforts of research and development of methods for daily fuel scheduling performed under EPRI Project RP 1048-5 by Power Technologies, Inc. (PTI) are reported in three volumes: Technical Manual; Programming Manual and Program Listings. Daily fuel scheduling involves the scheduling and dispatching of generating facilities to meet all system loads and operating requirements for periods ranging from a day to a week. Daily fuel scheduling and computer requirements are defined. The scheduling problem is formulated as a mixed-integer linear programming (MILP) optimization problem in which the total system operating cost is minimized. A potentially practical scheduling procedure, based on a combination of search and MILP approaches, was proposed; these two approaches were investigated, coded in FORTRAN and tested individually. Tests using the New York Power Pool system show that the search approach may produce potential savings for fuel scheduling approaches. Additional efforts are needed to make the MILP approach practical. Finally, a number of special scheduling problems have been identified and recommended for future work. This volume of the report (Volume 2) is the Programming Manual which describes the organization and structure of the programs. Layout and function of data files, sample outputs and test data are also presented. Program organization and data for the search and MILP approaches are given. Preliminary test results, system data descriptions and sample outputs for the search approach are included in the appendices.

  15. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by

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

    AERMOD-PRIME, Units 3, 1, 2 SO2 Case | Department of Energy PRIME, Units 3, 1, 2 SO2 Case Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 3, 1, 2 SO2 Case Docket No. EO-05-01: Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 3, 1, 2 SO2 Case. Compliance based on highest, second-highest, short-term, and highest annual concentrations. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME,

  16. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by

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

    AERMOD-PRIME, Units 4, 1, 2 SO2 Case | Department of Energy 4, 1, 2 SO2 Case Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 4, 1, 2 SO2 Case Docket No. EO-05-01: Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 4, 1, 2 SO2 Case. Compliance based on highest, second-highest, short-term, and highest annual concentrations. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 4, 1, 2

  17. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by

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

    AERMOD-PRIME, Units 5, 1, 2 SO2 Case | Department of Energy 5, 1, 2 SO2 Case Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 5, 1, 2 SO2 Case Docket No. EO-05-01: Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 5, 1, 2 SO2 Case. Compliance based on highest, second-highest, short-term, and highest annual concentrations. Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 5, 1, 2

  18. 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

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

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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

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

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

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

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

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

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

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

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

    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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

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

  18. 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

  19. 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

  20. 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 ...

  1. 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 ...

  2. 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 ...

  3. 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 ...

  4. 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 ...

  5. 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 ...

  6. 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 ...

  7. 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 ...

  8. 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 ...

  9. 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 ...

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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......

  15. 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......

  16. 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......

  17. 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 ...

  18. 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 ...

  19. 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......

  20. 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 ...

  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. STOCHASTIC DESCRIPTION OF THE HIGH-FREQUENCY CONTENT OF DAILY SUNSPOTS AND EVIDENCE FOR REGIME CHANGES

    SciTech Connect (OSTI)

    Shapoval, A.; Le Mouël, J.-L.; Courtillot, V.; Shnirman, M.

    2015-01-20

    The irregularity index λ is applied to the high-frequency content of daily sunspot numbers ISSN. This λ is a modification of the standard maximal Lyapunov exponent. It is computed here as a function of embedding dimension m, within four-year time windows centered at the maxima of Schwabe cycles. The λ(m) curves form separate clusters (pre-1923 and post-1933). This supports a regime transition and narrows its occurrence to cycle 16, preceding the growth of activity leading to the Modern Maximum. The two regimes are reproduced by a simple autoregressive process AR(1), with the mean of Poisson noise undergoing 11 yr modulation. The autocorrelation a of the process (linked to sunspot lifetime) is a ≈ 0.8 for 1850-1923 and ≈0.95 for 1933-2013. The AR(1) model suggests that groups of spots appear with a Poisson rate and disappear at a constant rate. We further applied the irregularity index to the daily sunspot group number series for the northern and southern hemispheres, provided by the Greenwich Royal Observatory (RGO), in order to study a possible desynchronization. Correlations between the north and south λ(m) curves vary quite strongly with time and indeed show desynchronization. This may reflect a slow change in the dimension of an underlying dynamical system. The ISSN and RGO series of group numbers do not imply an identical mechanism, but both uncover a regime change at a similar time. Computation of the irregularity index near the maximum of cycle 24 will help in checking whether yet another regime change is under way.

  6. Maximum Photovoltaic Penetration Levels on Typical Distribution Feeders: Preprint

    SciTech Connect (OSTI)

    Hoke, A.; Butler, R.; Hambrick, J.; Kroposki, B.

    2012-07-01

    This paper presents simulation results for a taxonomy of typical distribution feeders with various levels of photovoltaic (PV) penetration. For each of the 16 feeders simulated, the maximum PV penetration that did not result in steady-state voltage or current violation is presented for several PV location scenarios: clustered near the feeder source, clustered near the midpoint of the feeder, clustered near the end of the feeder, randomly located, and evenly distributed. In addition, the maximum level of PV is presented for single, large PV systems at each location. Maximum PV penetration was determined by requiring that feeder voltages stay within ANSI Range A and that feeder currents stay within the ranges determined by overcurrent protection devices. Simulations were run in GridLAB-D using hourly time steps over a year with randomized load profiles based on utility data and typical meteorological year weather data. For 86% of the cases simulated, maximum PV penetration was at least 30% of peak load.

  7. Are There Practical Approaches for Achieving the Theoretical Maximum Engine

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

    Efficiency? | Department of Energy Are There Practical Approaches for Achieving the Theoretical Maximum Engine Efficiency? Are There Practical Approaches for Achieving the Theoretical Maximum Engine Efficiency? 2004 Diesel Engine Emissions Reduction (DEER) Conference Presentation: University of Wisconsin, Madison 2004_deer_foster.pdf (273.98 KB) More Documents & Publications Fuel Modification t Facilitate Future Combustion Regimes? The Next ICE Age The Next ICE Age

  8. Oxidation State Optimization for Maximum Efficiency of NOx Adsorber

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

    Catalysts | Department of Energy State Optimization for Maximum Efficiency of NOx Adsorber Catalysts Oxidation State Optimization for Maximum Efficiency of NOx Adsorber Catalysts Presentation given at the 16th Directions in Engine-Efficiency and Emissions Research (DEER) Conference in Detroit, MI, September 27-30, 2010. deer10_li.pdf (1.68 MB) More Documents & Publications Lean NOx Trap Regeneration Selectivity Towards N2O -- Similarities and Differences Between H2, CO and C3H6

  9. Once-Daily Radiation Therapy for Inflammatory Breast Cancer

    SciTech Connect (OSTI)

    Brown, Lindsay; Harmsen, William; Blanchard, Miran; Goetz, Matthew; Jakub, James; Mutter, Robert; Petersen, Ivy; Rooney, Jessica; Stauder, Michael; Yan, Elizabeth; Laack, Nadia

    2014-08-01

    Purpose: Inflammatory breast cancer (IBC) is a rare and aggressive breast cancer variant treated with multimodality therapy. A variety of approaches intended to escalate the intensity and efficacy of radiation therapy have been reported, including twice-daily radiation therapy, dose escalation, and aggressive use of bolus. Herein, we examine our outcomes for patients treated with once-daily radiation therapy with aggressive bolus utilization, focusing on treatment technique. Methods and Materials: A retrospective review of patients with nonmetastatic IBC treated from January 1, 2000, through December 31, 2010, was performed. Locoregional control (LRC), disease-free survival (DFS), overall survival (OS) and predictors thereof were assessed. Results: Fifty-two women with IBC were identified, 49 (94%) of whom were treated with neoadjuvant chemotherapy. All underwent mastectomy followed by adjuvant radiation therapy. Radiation was delivered in once-daily fractions of 1.8 to 2.25 Gy (median, 2 Gy). Patients were typically treated with daily 1-cm bolus throughout treatment, and 33 (63%) received a subsequent boost to the mastectomy scar. Five-year Kaplan Meier survival estimates for LRC, DFS, and OS were 81%, 56%, and 64%, respectively. Locoregional recurrence was associated with poorer OS (P<.001; hazard ratio [HR], 4.1). Extracapsular extension was associated with worse LRC (P=.02), DFS (P=.007), and OS (P=.002). Age greater than 50 years was associated with better DFS (P=.03). Pathologic complete response was associated with a trend toward improved LRC (P=.06). Conclusions: Once-daily radiation therapy with aggressive use of bolus for IBC results in outcomes consistent with previous reports using various intensified radiation therapy regimens. LRC remains a challenge despite modern systemic therapy. Extracapsular extension, age ≤50 years, and lack of complete response to chemotherapy appear to be associated with worse outcomes. Novel strategies are needed in IBC

  10. Enhancement of maximum attainable ion energy in the radiation pressure acceleration regime using a guiding structure

    SciTech Connect (OSTI)

    Bulanov, S. S.; Esarey, E.; Schroeder, C. B.; Bulanov, S. V.; Esirkepov, T. Zh.; Kando, M.; Pegoraro, F.; Leemans, W. P.

    2015-03-13

    Radiation Pressure Acceleration is a highly efficient mechanism of laser driven ion acceleration, with the laser energy almost totally transferrable to the ions in the relativistic regime. There is a fundamental limit on the maximum attainable ion energy, which is determined by the group velocity of the laser. In the case of a tightly focused laser pulses, which are utilized to get the highest intensity, another factor limiting the maximum ion energy comes into play, the transverse expansion of the target. Transverse expansion makes the target transparent for radiation, thus reducing the effectiveness of acceleration. Utilization of an external guiding structure for the accelerating laser pulse may provide a way of compensating for the group velocity and transverse expansion effects.

  11. Enhancement of maximum attainable ion energy in the radiation pressure acceleration regime using a guiding structure

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

    Bulanov, S. S.; Esarey, E.; Schroeder, C. B.; Bulanov, S. V.; Esirkepov, T. Zh.; Kando, M.; Pegoraro, F.; Leemans, W. P.

    2015-03-13

    Radiation Pressure Acceleration is a highly efficient mechanism of laser driven ion acceleration, with the laser energy almost totally transferrable to the ions in the relativistic regime. There is a fundamental limit on the maximum attainable ion energy, which is determined by the group velocity of the laser. In the case of a tightly focused laser pulses, which are utilized to get the highest intensity, another factor limiting the maximum ion energy comes into play, the transverse expansion of the target. Transverse expansion makes the target transparent for radiation, thus reducing the effectiveness of acceleration. Utilization of an external guidingmore » structure for the accelerating laser pulse may provide a way of compensating for the group velocity and transverse expansion effects.« less

  12. Quality, precision and accuracy of the maximum No. 40 anemometer

    SciTech Connect (OSTI)

    Obermeir, J.; Blittersdorf, D.

    1996-12-31

    This paper synthesizes available calibration data for the Maximum No. 40 anemometer. Despite its long history in the wind industry, controversy surrounds the choice of transfer function for this anemometer. Many users are unaware that recent changes in default transfer functions in data loggers are producing output wind speed differences as large as 7.6%. Comparison of two calibration methods used for large samples of Maximum No. 40 anemometers shows a consistent difference of 4.6% in output speeds. This difference is significantly larger than estimated uncertainty levels. Testing, initially performed to investigate related issues, reveals that Gill and Maximum cup anemometers change their calibration transfer functions significantly when calibrated in the open atmosphere compared with calibration in a laminar wind tunnel. This indicates that atmospheric turbulence changes the calibration transfer function of cup anemometers. These results call into question the suitability of standard wind tunnel calibration testing for cup anemometers. 6 refs., 10 figs., 4 tabs.

  13. 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...

  14. 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

  15. Markov chain decomposition of monthly rainfall into daily rainfall: Evaluation of climate change impact

    SciTech Connect (OSTI)

    Yoo, Chulsang; Lee, Jinwook; Ro, Yonghun

    2016-01-01

    This paper evaluates the effect of climate change on daily rainfall, especially on the mean number of wet days and the mean rainfall intensity. Assuming that the mechanism of daily rainfall occurrences follows the first-order Markov chain model, the possible changes in the transition probabilities are estimated by considering the climate change scenarios. Also, the change of the stationary probabilities of wet and dry day occurrences and finally the change in the number of wet days are derived for the comparison of current (1x CO2) and 2x CO2conditions. As a result of this study, the increase or decrease in the mean number of wet days was found to be not enough to explain all of the change in monthly rainfall amounts, so rainfall intensity should also be modified. The application to the Seoul weather station in Korea shows that about 30% of the total change in monthly rainfall amount can be explained by the change in the number of wet days and the remaining 70% by the change in the rainfall intensity. That is, as an effect of climate change, the increase in the rainfall intensity could be more significant than the increase in the wet days and, thus, the risk of flood will be much highly increased.

  16. Markov chain decomposition of monthly rainfall into daily rainfall: Evaluation of climate change impact

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

    Yoo, Chulsang; Lee, Jinwook; Ro, Yonghun

    2016-01-01

    This paper evaluates the effect of climate change on daily rainfall, especially on the mean number of wet days and the mean rainfall intensity. Assuming that the mechanism of daily rainfall occurrences follows the first-order Markov chain model, the possible changes in the transition probabilities are estimated by considering the climate change scenarios. Also, the change of the stationary probabilities of wet and dry day occurrences and finally the change in the number of wet days are derived for the comparison of current (1x CO2) and 2x CO2conditions. As a result of this study, the increase or decrease in themore » mean number of wet days was found to be not enough to explain all of the change in monthly rainfall amounts, so rainfall intensity should also be modified. The application to the Seoul weather station in Korea shows that about 30% of the total change in monthly rainfall amount can be explained by the change in the number of wet days and the remaining 70% by the change in the rainfall intensity. That is, as an effect of climate change, the increase in the rainfall intensity could be more significant than the increase in the wet days and, thus, the risk of flood will be much highly increased.« less

  17. LITERATURE REVIEW ON MAXIMUM LOADING OF RADIONUCLIDES ON CRYSTALLINE SILICOTITANATE

    SciTech Connect (OSTI)

    Adu-Wusu, K.; Pennebaker, F.

    2010-10-13

    Plans are underway to use small column ion exchange (SCIX) units installed in high-level waste tanks to remove Cs-137 from highly alkaline salt solutions at Savannah River Site. The ion exchange material slated for the SCIX project is engineered or granular crystalline silicotitanate (CST). Information on the maximum loading of radionuclides on CST is needed by Savannah River Remediation for safety evaluations. A literature review has been conducted that culminated in the estimation of the maximum loading of all but one of the radionuclides of interest (Cs-137, Sr-90, Ba-137m, Pu-238, Pu-239, Pu-240, Pu-241, Am-241, and Cm-244). No data was found for Cm-244.

  18. Maximum patch method for directional dark matter detection

    SciTech Connect (OSTI)

    Henderson, Shawn; Monroe, Jocelyn; Fisher, Peter [Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Laboratory for Nuclear Science, MIT Kavli Institute for Astrophysics and Space Research, Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States)

    2008-07-01

    Present and planned dark matter detection experiments search for WIMP-induced nuclear recoils in poorly known background conditions. In this environment, the maximum gap statistical method provides a way of setting more sensitive cross section upper limits by incorporating known signal information. We give a recipe for the numerical calculation of upper limits for planned directional dark matter detection experiments, that will measure both recoil energy and angle, based on the gaps between events in two-dimensional phase space.

  19. Industry guidelines for the calibration of maximum anemometers

    SciTech Connect (OSTI)

    Bailey, B.H.

    1996-12-31

    The purpose of this paper is to report on a framework of guidelines for the calibration of the Maximum Type 40 anemometer. This anemometer model is the wind speed sensor of choice in the majority of wind resource assessment programs in the U.S. These guidelines were established by the Utility Wind Resource Assessment Program. In addition to providing guidelines for anemometers, the appropriate use of non-calibrated anemometers is also discussed. 14 refs., 1 tab.

  20. Maximum entanglement in squeezed boson and fermion states

    SciTech Connect (OSTI)

    Khanna, F. C.; Malbouisson, J. M. C.; Santana, A. E.; Santos, E. S.

    2007-08-15

    A class of squeezed boson and fermion states is studied with particular emphasis on the nature of entanglement. We first investigate the case of bosons, considering two-mode squeezed states. Then we construct the fermion version to show that such states are maximum entangled, for both bosons and fermions. To achieve these results, we demonstrate some relations involving squeezed boson states. The generalization to the case of fermions is made by using Grassmann variables.

  1. Maximum Entry and Mandatory Separation Ages for Certain Security Employees

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

    2001-10-11

    The policy establishes the DOE policy on maximum entry and mandatory separation ages for primary or secondary positions covered under special statutory retirement provisions and for those employees whose primary duties are the protection of officials of the United States against threats to personal safety or the investigation, apprehension, and detention of individuals suspected or convicted of offenses against the criminal laws of the United States. Admin Chg 1, dated 12-1-11, supersedes DOE P 310.1.

  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. 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 ...

  4. Maximum Reasonable Radioxenon Releases from Medical Isotope Production Facilities and Their Effect on Monitoring Nuclear Explosions

    SciTech Connect (OSTI)

    Bowyer, Ted W.; Kephart, Rosara F.; Eslinger, Paul W.; Friese, Judah I.; Miley, Harry S.; Saey, Paul R.

    2013-01-01

    Fission gases such as 133Xe are used extensively for monitoring the world for signs of nuclear testing in systems such as the International Monitoring System (IMS). These gases are also produced by nuclear reactors and by fission production of 99Mo for medical use. Recently, medical isotope production facilities have been identified as the major contributor to the background of radioactive xenon isotopes (radioxenon) in the atmosphere (Saey, et al., 2009). These releases pose a potential future problem for monitoring nuclear explosions if not addressed. As a starting point, a maximum acceptable daily xenon emission rate was calculated, that is both scientifically defendable as not adversely affecting the IMS, but also consistent with what is possible to achieve in an operational environment. This study concludes that an emission of 5×109 Bq/day from a medical isotope production facility would be both an acceptable upper limit from the perspective of minimal impact to monitoring stations, but also appears to be an achievable limit for large isotope producers.

  5. 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

  6. 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

  7. 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 ...

  8. Possible dynamical explanations for Paltridge's principle of maximum entropy production

    SciTech Connect (OSTI)

    Virgo, Nathaniel Ikegami, Takashi

    2014-12-05

    Throughout the history of non-equilibrium thermodynamics a number of theories have been proposed in which complex, far from equilibrium flow systems are hypothesised to reach a steady state that maximises some quantity. Perhaps the most celebrated is Paltridge's principle of maximum entropy production for the horizontal heat flux in Earth's atmosphere, for which there is some empirical support. There have been a number of attempts to derive such a principle from maximum entropy considerations. However, we currently lack a more mechanistic explanation of how any particular system might self-organise into a state that maximises some quantity. This is in contrast to equilibrium thermodynamics, in which models such as the Ising model have been a great help in understanding the relationship between the predictions of MaxEnt and the dynamics of physical systems. In this paper we show that, unlike in the equilibrium case, Paltridge-type maximisation in non-equilibrium systems cannot be achieved by a simple dynamical feedback mechanism. Nevertheless, we propose several possible mechanisms by which maximisation could occur. Showing that these occur in any real system is a task for future work. The possibilities presented here may not be the only ones. We hope that by presenting them we can provoke further discussion about the possible dynamical mechanisms behind extremum principles for non-equilibrium systems, and their relationship to predictions obtained through MaxEnt.

  9. 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

  10. Changes in maximum and minimal temperatures at high elevation stations in the central Andes of South America

    SciTech Connect (OSTI)

    Quintana-Gomez, R.A.

    1997-11-01

    Temperature trends and deviations were evaluated for the central Andes portion of Bolivia. Data were collected primarily from stations located at very high altitude (3,000 m above sea level and higher) for a 73-year period from 1918 to 1990. The analysis determined maximum and minimum temperature trends and the daily temperature range (DTR) at each station. The minimum temperature series showed a rather sustained increase starting in the 1960s and continuing to the present, and a reduction of the differential rate of warming for the same interval. The high elevation, rural area data appears to reinforce evidence of a global and generalized rise of minimum temperature and decrease of the DTR. 3 refs., 2 figs., 1 tab.

  11. Maximum Likelihood Analysis of Low Energy CDMS II Germanium Data

    SciTech Connect (OSTI)

    Agnese, R.

    2015-03-30

    We report on the results of a search for a Weakly Interacting Massive Particle (WIMP) signal in low-energy data of the Cryogenic Dark Matter Search experiment using a maximum likelihood analysis. A background model is constructed using GEANT4 to simulate the surface-event background from Pb210decay-chain events, while using independent calibration data to model the gamma background. Fitting this background model to the data results in no statistically significant WIMP component. In addition, we also perform fits using an analytic ad hoc background model proposed by Collar and Fields, who claimed to find a large excess of signal-like events in our data. Finally, we confirm the strong preference for a signal hypothesis in their analysis under these assumptions, but excesses are observed in both single- and multiple-scatter events, which implies the signal is not caused by WIMPs, but rather reflects the inadequacy of their background model.

  12. Reduction in maximum time uncertainty of paired time signals

    DOE Patents [OSTI]

    Theodosiou, G.E.; Dawson, J.W.

    1983-10-04

    Reduction in the maximum time uncertainty (t[sub max]--t[sub min]) of a series of paired time signals t[sub 1] and t[sub 2] varying between two input terminals and representative of a series of single events where t[sub 1][<=]t[sub 2] and t[sub 1]+t[sub 2] equals a constant, is carried out with a circuit utilizing a combination of OR and AND gates as signal selecting means and one or more time delays to increase the minimum value (t[sub min]) of the first signal t[sub 1] closer to t[sub max] and thereby reduce the difference. The circuit may utilize a plurality of stages to reduce the uncertainty by factors of 20--800. 6 figs.

  13. Reduction in maximum time uncertainty of paired time signals

    DOE Patents [OSTI]

    Theodosiou, George E.; Dawson, John W.

    1983-01-01

    Reduction in the maximum time uncertainty (t.sub.max -t.sub.min) of a series of paired time signals t.sub.1 and t.sub.2 varying between two input terminals and representative of a series of single events where t.sub.1 .ltoreq.t.sub.2 and t.sub.1 +t.sub.2 equals a constant, is carried out with a circuit utilizing a combination of OR and AND gates as signal selecting means and one or more time delays to increase the minimum value (t.sub.min) of the first signal t.sub.1 closer to t.sub.max and thereby reduce the difference. The circuit may utilize a plurality of stages to reduce the uncertainty by factors of 20-800.

  14. Reduction in maximum time uncertainty of paired time signals

    DOE Patents [OSTI]

    Theodosiou, G.E.; Dawson, J.W.

    1981-02-11

    Reduction in the maximum time uncertainty (t/sub max/ - t/sub min/) of a series of paired time signals t/sub 1/ and t/sub 2/ varying between two input terminals and representative of a series of single events where t/sub 1/ less than or equal to t/sub 2/ and t/sub 1/ + t/sub 2/ equals a constant, is carried out with a circuit utilizing a combination of OR and AND gates as signal selecting means and one or more time delays to increase the minimum value (t/sub min/) of the first signal t/sub 1/ closer to t/sub max/ and thereby reduce the difference. The circuit may utilize a plurality of stages to reduce the uncertainty by factors of 20 to 800.

  15. Speech processing using conditional observable maximum likelihood continuity mapping

    DOE Patents [OSTI]

    Hogden, John; Nix, David

    2004-01-13

    A computer implemented method enables the recognition of speech and speech characteristics. Parameters are initialized of first probability density functions that map between the symbols in the vocabulary of one or more sequences of speech codes that represent speech sounds and a continuity map. Parameters are also initialized of second probability density functions that map between the elements in the vocabulary of one or more desired sequences of speech transcription symbols and the continuity map. The parameters of the probability density functions are then trained to maximize the probabilities of the desired sequences of speech-transcription symbols. A new sequence of speech codes is then input to the continuity map having the trained first and second probability function parameters. A smooth path is identified on the continuity map that has the maximum probability for the new sequence of speech codes. The probability of each speech transcription symbol for each input speech code can then be output.

  16. Property:Maximum Velocity with Constriction(m/s) | Open Energy...

    Open Energy Info (EERE)

    Velocity with Constriction(ms) Jump to: navigation, search Property Name Maximum Velocity with Constriction(ms) Property Type String Pages using the property "Maximum Velocity...

  17. 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.

  18. 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

  19. 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

  20. Total Adjusted Sales of Kerosene

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

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

  1. Total 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.

  2. Pool daily fuel scheduling. Volume 3: Program listings. Final report, February 1981. [START; MASTER; THCC; HYDR; PSTO; NFLA; LMTF

    SciTech Connect (OSTI)

    Pang, C.K.; Mikolinnas, T.A.

    1981-02-01

    The results and efforts of research and development of methods for daily fuel scheduling performed under EPRI Project RP 1048-5 by Power Technologies, Inc. (PTI) are reported in three volumes: Technical Manual; Programming Manual and Program Listing. Daily fuel scheduling involves the scheduling and dispatching of generating facilities to meet all system loads and operating requirements for periods ranging from a day to a week. Daily fuel scheduling and computer requirements are defined. The scheduling problem is formulated as a mixed-integer linear programming (MILP) optimization problem in which the total system operating cost is minimized. A potentially practical scheduling procedure, based on a combination of search and MILP approaches, was proposed; these two approaches were investigated, coded in FORTRAN and tested individually. Tests using the New York Power Pool system show that the search approach may produce potential savings for fuel scheduling approaches. Additional efforts are needed to make the MILP approach practical. Finally, a number of special scheduling problems have been identified and recommended for future work. This volume of the report (Volume 3) gives the FORTRAN listings of the programs, which had been developed during the course of this project. In the programs, there may be certain statements and functions which could be specific to the PRIME computer system. Comments on them are provided.

  3. Maximum-likelihood fitting of data dominated by Poisson statistical uncertainties

    SciTech Connect (OSTI)

    Stoneking, M.R.; Den Hartog, D.J.

    1996-06-01

    The fitting of data by {chi}{sup 2}-minimization is valid only when the uncertainties in the data are normally distributed. When analyzing spectroscopic or particle counting data at very low signal level (e.g., a Thomson scattering diagnostic), the uncertainties are distributed with a Poisson distribution. The authors have developed a maximum-likelihood method for fitting data that correctly treats the Poisson statistical character of the uncertainties. This method maximizes the total probability that the observed data are drawn from the assumed fit function using the Poisson probability function to determine the probability for each data point. The algorithm also returns uncertainty estimates for the fit parameters. They compare this method with a {chi}{sup 2}-minimization routine applied to both simulated and real data. Differences in the returned fits are greater at low signal level (less than {approximately}20 counts per measurement). the maximum-likelihood method is found to be more accurate and robust, returning a narrower distribution of values for the fit parameters with fewer outliers.

  4. 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.

  5. Estimate of Maximum Underground Working Gas Storage Capacity in the United States

    Reports and Publications (EIA)

    2006-01-01

    This report examines the aggregate maximum capacity for U.S. natural gas storage. Although the concept of maximum capacity seems quite straightforward, there are numerous issues that preclude the determination of a definitive maximum volume. The report presents three alternative estimates for maximum capacity, indicating appropriate caveats for each.

  6. Boiler Maximum Achievable Control Technology (MACT) Technical Assistance- Fact Sheet, April 2015

    Broader source: Energy.gov [DOE]

    Fact sheet about the Boiler Maximum Achievable Control Technology (MACT) Technical Assistance Program

  7. Maximum Likelihood Analysis of Low Energy CDMS II Germanium Data

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

    Agnese, R.

    2015-03-30

    We report on the results of a search for a Weakly Interacting Massive Particle (WIMP) signal in low-energy data of the Cryogenic Dark Matter Search experiment using a maximum likelihood analysis. A background model is constructed using GEANT4 to simulate the surface-event background from Pb210decay-chain events, while using independent calibration data to model the gamma background. Fitting this background model to the data results in no statistically significant WIMP component. In addition, we also perform fits using an analytic ad hoc background model proposed by Collar and Fields, who claimed to find a large excess of signal-like events in ourmore » data. Finally, we confirm the strong preference for a signal hypothesis in their analysis under these assumptions, but excesses are observed in both single- and multiple-scatter events, which implies the signal is not caused by WIMPs, but rather reflects the inadequacy of their background model.« less

  8. LANDFILL OPERATION FOR CARBON SEQUESTRATION AND MAXIMUM METHANE EMISSION CONTROL

    SciTech Connect (OSTI)

    Don Augenstein

    2001-02-01

    The work described in this report, to demonstrate and advance this technology, has used two demonstration-scale cells of size (8000 metric tons [tonnes]), sufficient to replicate many heat and compaction characteristics of larger ''full-scale'' landfills. An enhanced demonstration cell has received moisture supplementation to field capacity. This is the maximum moisture waste can hold while still limiting liquid drainage rate to minimal and safely manageable levels. The enhanced landfill module was compared to a parallel control landfill module receiving no moisture additions. Gas recovery has continued for a period of over 4 years. It is quite encouraging that the enhanced cell methane recovery has been close to 10-fold that experienced with conventional landfills. This is the highest methane recovery rate per unit waste, and thus progress toward stabilization, documented anywhere for such a large waste mass. This high recovery rate is attributed to moisture, and elevated temperature attained inexpensively during startup. Economic analyses performed under Phase I of this NETL contract indicate ''greenhouse cost effectiveness'' to be excellent. Other benefits include substantial waste volume loss (over 30%) which translates to extended landfill life. Other environmental benefits include rapidly improved quality and stabilization (lowered pollutant levels) in liquid leachate which drains from the waste.

  9. 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...

  10. 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...

  11. 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...

  12. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

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

  13. 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...

  14. ,"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)" ...

  15. ,"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" ...

  16. ,"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)" ...

  17. ,"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 ...

  18. ,"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 ...

  19. " 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 ...

  20. Today in Energy - Daily Prices - Prices - U.S. Energy Information

    Gasoline and Diesel Fuel Update (EIA)

    Administration (EIA) September 2, 2016Daily Prices Daily wholesale and retail prices for various energy products are shown below, including spot prices and select futures prices at national or regional levels. Prices are updated each weekday (excluding federal holidays), typically between 7:30 and 8:30 a.m. This page is meant to provide a snapshot of selected daily prices only. Prices are republished by EIA with permission as follows: Wholesale Spot Petroleum Prices from Thomson Reuters,

  1. Characterizing Sub-Daily Flow Regimes: Implications of Hydrologic Resolution on Ecohydrology Studies

    SciTech Connect (OSTI)

    Bevelhimer, Mark S.; McManamay, Ryan A.; O'Connor, B.

    2014-05-26

    Natural variability in flow is a primary factor controlling geomorphic and ecological processes in riverine ecosystems. Within the hydropower industry, there is growing pressure from environmental groups and natural resource managers to change reservoir releases from daily peaking to run-of-river operations on the basis of the assumption that downstream biological communities will improve under a more natural flow regime. In this paper, we discuss the importance of assessing sub-daily flows for understanding the physical and ecological dynamics within river systems. We present a variety of metrics for characterizing sub-daily flow variation and use these metrics to evaluate general trends among streams affected by peaking hydroelectric projects, run-of-river projects and streams that are largely unaffected by flow altering activities. Univariate and multivariate techniques were used to assess similarity among different stream types on the basis of these sub-daily metrics. For comparison, similar analyses were performed using analogous metrics calculated with mean daily flow values. Our results confirm that sub-daily flow metrics reveal variation among and within streams that are not captured by daily flow statistics. Using sub-daily flow statistics, we were able to quantify the degree of difference between unaltered and peaking streams and the amount of similarity between unaltered and run-of-river streams. The sub-daily statistics were largely uncorrelated with daily statistics of similar scope. Furthermore, on short temporal scales, sub-daily statistics reveal the relatively constant nature of unaltered streamreaches and the highly variable nature of hydropower-affected streams, whereas daily statistics show just the opposite over longer temporal scales.

  2. Characterizing Sub-Daily Flow Regimes: Implications of Hydrologic Resolution on Ecohydrology Studies

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

    Bevelhimer, Mark S.; McManamay, Ryan A.; O'Connor, B.

    2014-05-26

    Natural variability in flow is a primary factor controlling geomorphic and ecological processes in riverine ecosystems. Within the hydropower industry, there is growing pressure from environmental groups and natural resource managers to change reservoir releases from daily peaking to run-of-river operations on the basis of the assumption that downstream biological communities will improve under a more natural flow regime. In this paper, we discuss the importance of assessing sub-daily flows for understanding the physical and ecological dynamics within river systems. We present a variety of metrics for characterizing sub-daily flow variation and use these metrics to evaluate general trends amongmore » streams affected by peaking hydroelectric projects, run-of-river projects and streams that are largely unaffected by flow altering activities. Univariate and multivariate techniques were used to assess similarity among different stream types on the basis of these sub-daily metrics. For comparison, similar analyses were performed using analogous metrics calculated with mean daily flow values. Our results confirm that sub-daily flow metrics reveal variation among and within streams that are not captured by daily flow statistics. Using sub-daily flow statistics, we were able to quantify the degree of difference between unaltered and peaking streams and the amount of similarity between unaltered and run-of-river streams. The sub-daily statistics were largely uncorrelated with daily statistics of similar scope. Furthermore, on short temporal scales, sub-daily statistics reveal the relatively constant nature of unaltered streamreaches and the highly variable nature of hydropower-affected streams, whereas daily statistics show just the opposite over longer temporal scales.« less

  3. MO-G-BRE-04: Automatic Verification of Daily Treatment Deliveries and Generation of Daily Treatment Reports for a MR Image-Guided Treatment Machine

    SciTech Connect (OSTI)

    Yang, D; Li, X; Li, H; Wooten, H; Green, O; Rodriguez, V; Mutic, S

    2014-06-15

    Purpose: Two aims of this work were to develop a method to automatically verify treatment delivery accuracy immediately after patient treatment and to develop a comprehensive daily treatment report to provide all required information for daily MR-IGRT review. Methods: After systematically analyzing the requirements for treatment delivery verification and understanding the available information from a novel MR-IGRT treatment machine, we designed a method to use 1) treatment plan files, 2) delivery log files, and 3) dosimetric calibration information to verify the accuracy and completeness of daily treatment deliveries. The method verifies the correctness of delivered treatment plans and beams, beam segments, and for each segment, the beam-on time and MLC leaf positions. Composite primary fluence maps are calculated from the MLC leaf positions and the beam-on time. Error statistics are calculated on the fluence difference maps between the plan and the delivery. We also designed the daily treatment delivery report by including all required information for MR-IGRT and physics weekly review - the plan and treatment fraction information, dose verification information, daily patient setup screen captures, and the treatment delivery verification results. Results: The parameters in the log files (e.g. MLC positions) were independently verified and deemed accurate and trustable. A computer program was developed to implement the automatic delivery verification and daily report generation. The program was tested and clinically commissioned with sufficient IMRT and 3D treatment delivery data. The final version has been integrated into a commercial MR-IGRT treatment delivery system. Conclusion: A method was developed to automatically verify MR-IGRT treatment deliveries and generate daily treatment reports. Already in clinical use since December 2013, the system is able to facilitate delivery error detection, and expedite physician daily IGRT review and physicist weekly chart

  4. LANDFILL OPERATION FOR CARBON SEQUESTRATION AND MAXIMUM METHANE EMISSION CONTROL

    SciTech Connect (OSTI)

    Don Augenstein; Ramin Yazdani; Rick Moore; Michelle Byars; Jeff Kieffer; Professor Morton Barlaz; Rinav Mehta

    2000-02-26

    Controlled landfilling is an approach to manage solid waste landfills, so as to rapidly complete methane generation, while maximizing gas capture and minimizing the usual emissions of methane to the atmosphere. With controlled landfilling, methane generation is accelerated to more rapid and earlier completion to full potential by improving conditions (principally moisture, but also temperature) to optimize biological processes occurring within the landfill. Gas is contained through use of surface membrane cover. Gas is captured via porous layers, under the cover, operated at slight vacuum. A field demonstration project has been ongoing under NETL sponsorship for the past several years near Davis, CA. Results have been extremely encouraging. Two major benefits of the technology are reduction of landfill methane emissions to minuscule levels, and the recovery of greater amounts of landfill methane energy in much shorter times, more predictably, than with conventional landfill practice. With the large amount of US landfill methane generated, and greenhouse potency of methane, better landfill methane control can play a substantial role both in reduction of US greenhouse gas emissions and in US renewable energy. The work described in this report, to demonstrate and advance this technology, has used two demonstration-scale cells of size (8000 metric tons [tonnes]), sufficient to replicate many heat and compaction characteristics of larger ''full-scale'' landfills. An enhanced demonstration cell has received moisture supplementation to field capacity. This is the maximum moisture waste can hold while still limiting liquid drainage rate to minimal and safely manageable levels. The enhanced landfill module was compared to a parallel control landfill module receiving no moisture additions. Gas recovery has continued for a period of over 4 years. It is quite encouraging that the enhanced cell methane recovery has been close to 10-fold that experienced with conventional

  5. Fact #917: March 21, 2016 Work Truck Daily Idle Time by Industry |

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

    Department of Energy 7: March 21, 2016 Work Truck Daily Idle Time by Industry Fact #917: March 21, 2016 Work Truck Daily Idle Time by Industry SUBSCRIBE to the Fact of the Week Results of the 2015 Work Truck Electrification and Idle Management Study showed the daily idle time for work truck fleets. Daily idle times by industry show that the truck fleets in the utility/telecommunications industry had the longest idle times. Thirty-nine percent of respondents indicated that their fleets idled

  6. McGinness Hills Well 27A-10 Daily Drilling Report Data

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

    Knudsen, Steven

    This data should be used with the daily drilling record and other data which can be obtained from the contact listed below

  7. McGinness Hills Well 27A-10 Daily Drilling Report Data

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

    Knudsen, Steven

    2014-03-25

    This data should be used with the daily drilling record and other data which can be obtained from the contact listed below

  8. 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...

  9. Property:Maximum Wave Height(m) at Wave Period(s) | Open Energy...

    Open Energy Info (EERE)

    at Wave Period(s) Jump to: navigation, search Property Name Maximum Wave Height(m) at Wave Period(s) Property Type String Pages using the property "Maximum Wave Height(m) at Wave...

  10. 2011-07 "Maximum Utilization of WIPP by Increasing MDA G TRU...

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

    7 "Maximum Utilization of WIPP by Increasing MDA G TRU Shipments" 2011-07 "Maximum Utilization of WIPP by Increasing MDA G TRU Shipments" The intent of this recommendation is to ...

  11. 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...

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. Maximum mass of stable magnetized highly super-Chandrasekhar white dwarfs: stable solutions with varying magnetic fields

    SciTech Connect (OSTI)

    Das, Upasana; Mukhopadhyay, Banibrata E-mail: bm@physics.iisc.ernet.in

    2014-06-01

    We address the issue of stability of recently proposed significantly super-Chandrasekhar white dwarfs. We present stable solutions of magnetostatic equilibrium models for super-Chandrasekhar white dwarfs pertaining to various magnetic field profiles. This has been obtained by self-consistently including the effects of the magnetic pressure gradient and total magnetic density in a general relativistic framework. We estimate that the maximum stable mass of magnetized white dwarfs could be more than 3 solar mass. This is very useful to explain peculiar, overluminous type Ia supernovae which do not conform to the traditional Chandrasekhar mass-limit.

  20. Relative Accuracy of 1-Minute and Daily Total Solar Radiation Data for 12 Global and 4 Direct Beam Solar Radiometers: Preprint

    SciTech Connect (OSTI)

    Myers, D. R.; Wilcox, S. M.

    2009-03-01

    This report evaluates the relative performance of 12 global and four direct beam solar radiometers deployed at a single site over a 12-month period. Test radiometer irradiances were compared with a reference irradiance consisting of either an absolute cavity radiometer (during calibrations) or a low uncertainty thermopile pyrheliometer (during the evaluation period) for pyrheliometers; and for pyranometers a reference global irradiance computed from the reference pyrheliometer and diffuse irradiance from a shaded pyranometer.

  1. Fact #917: March 21, 2016 Work Truck Daily Idle Time by Industry - Dataset

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

    | Department of Energy 7: March 21, 2016 Work Truck Daily Idle Time by Industry - Dataset Fact #917: March 21, 2016 Work Truck Daily Idle Time by Industry - Dataset Excel file and dataset for Work Truck Daily Idle Time by Industry fotw#917_web.xlsx (15.85 KB) More Documents & Publications Fact #916: March 14, 2016 Fuel Savings/Emissions Reduction was the Top Reason Cited by Truck Fleet Management for Adopting Idle Reduction Technologies - Dataset Fact #833: August 11, 2014 Fuel Economy

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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