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  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. Average Neutron Total Cross Sections in the Unresolved Energy Range From ORELA High Resolutio Transmission Measurements

    SciTech Connect (OSTI)

    Derrien, H

    2004-05-27

    Average values of the neutron total cross sections of {sup 233}U, {sup 235}U, {sup 238}U, and {sup 239}Pu have been obtained in the unresolved resonance energy range from high-resolution transmission measurements performed at ORELA in the past two decades. The cross sections were generated by correcting the effective total cross sections for the self-shielding effects due to the resonance structure of the data. The self-shielding factors were found by calculating the effective and true cross sections with the computer code SAMMY for the same Doppler and resolution conditions as for the transmission measurements, using an appropriate set of resonance parameters. Our results are compared to results of previous measurements and to the current ENDF/B-VI data.

  3. 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.

  4. 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 ...

  5. 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 ...

  6. 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 ...

  7. 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 ...

  8. 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 ...

  9. 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 ...

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. Neutron resonance averaging

    SciTech Connect (OSTI)

    Chrien, R.E.

    1986-10-01

    The principles of resonance averaging as applied to neutron capture reactions are described. Several illustrations of resonance averaging to problems of nuclear structure and the distribution of radiative strength in nuclei are provided. 30 refs., 12 figs.

  1. Variable Average Absolute Percent Differences

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

    Variable Average Absolute Percent Differences Percent of Projections Over- Estimated Gross Domestic Product Real Gross Domestic Product (Average Cumulative Growth)* (Table 2) 0.9 45.8 Petroleum Imported Refiner Acquisition Cost of Crude Oil (Constant $) (Table 3a) 37.7 17.3 Imported Refiner Acquisition Cost of Crude Oil (Nominal $) (Table 3b) 36.6 18.7 Total Petroleum Consumption (Table 4) 7.9 70.7 Crude Oil Production (Table 5) 8.1 51.1 Petroleum Net Imports (Table 6) 24.7 73.8 Natural Gas

  2. Average Residential Price

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

    Data Series: Average Residential Price Residential Price - Local Distribution Companies Residential Price - Marketers Residential % Sold by Local Distribution Companies Average Commercial Price Commercial Price - Local Distribution Companies Commerical Price - Marketers Commercial % Sold by Local Distribution Companies Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011

  3. Concentration Averaging | Department of Energy

    Office of Environmental Management (EM)

    Concentration Averaging Concentration Averaging Summary Notes from 3 October 2007 Generic Technical Issue Discussion on Concentration Averaging PDF icon Summary Notes from 3...

  4. NIAMEY DAILY RAINFALL

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

    2006 -2 -1 0 1 +2 +3 Average Normalized Departure () Time series (1941-2006) of normalized April-October rainfall departures () for Niamey (2.1666 o E, 13.4833 o N) in Niger...

  5. 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

  6. 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.

  7. 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...

  8. Spacetime averaged null energy condition

    SciTech Connect (OSTI)

    Urban, Douglas; Olum, Ken D.

    2010-06-15

    The averaged null energy condition has known violations for quantum fields in curved space, even when one considers only achronal geodesics. Many such examples involve rapid variation in the stress-energy tensor in the vicinity of the geodesic under consideration, giving rise to the possibility that averaging in additional dimensions would yield a principle universally obeyed by quantum fields. However, after discussing various procedures for additional averaging, including integrating over all dimensions of the manifold, we give here a class of examples that violate any such averaged condition.

  9. 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 -

  10. High average power pockels cell

    DOE Patents [OSTI]

    Daly, Thomas P.

    1991-01-01

    A high average power pockels cell is disclosed which reduces the effect of thermally induced strains in high average power laser technology. The pockels cell includes an elongated, substantially rectangular crystalline structure formed from a KDP-type material to eliminate shear strains. The X- and Y-axes are oriented substantially perpendicular to the edges of the crystal cross-section and to the C-axis direction of propagation to eliminate shear strains.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. Modeling an Application's Theoretical Minimum and Average Transactional Response Times

    SciTech Connect (OSTI)

    Paiz, Mary Rose

    2015-04-01

    The theoretical minimum transactional response time of an application serves as a ba- sis for the expected response time. The lower threshold for the minimum response time represents the minimum amount of time that the application should take to complete a transaction. Knowing the lower threshold is beneficial in detecting anomalies that are re- sults of unsuccessful transactions. On the converse, when an application's response time falls above an upper threshold, there is likely an anomaly in the application that is causing unusual performance issues in the transaction. This report explains how the non-stationary Generalized Extreme Value distribution is used to estimate the lower threshold of an ap- plication's daily minimum transactional response time. It also explains how the seasonal Autoregressive Integrated Moving Average time series model is used to estimate the upper threshold for an application's average transactional response time.

  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. Study of global daily solar radiation and its relation to sunshine duration in Bahrain

    SciTech Connect (OSTI)

    Al-Sadah, F.H.; Ragab, F.M. )

    1991-01-01

    The regression coefficients a and b of Angstrom type correlation for the monthly daily average global solar radiation have been determined. The two constants a and b have been derived for different months during the period 1983-1987. The clearness index (H/H{sub 0}) based on predicted and measured values of global daily solar radiation is presented for different seasons of the year. The study depicts the various astronomical and meteorological parameters affecting the global radiation in Bahrain.

  3. Average and effective Q-values for fission product average (n...

    Office of Scientific and Technical Information (OSTI)

    Average and effective Q-values for fission product average (n,2n) and (n,3n) reaction cross sections Citation Details In-Document Search Title: Average and effective Q-values for ...

  4. Average and effective Q-values for fission product average (n...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Average and effective Q-values for fission product average (n,2n) and (n,3n) reaction cross sections Citation Details In-Document Search Title: Average and ...

  5. 2014 Total Electric Industry- Average Retail Price (cents/kWh...

    Gasoline and Diesel Fuel Update (EIA)

    17.05 Maine 15.27 12.70 8.95 0.00 12.65 Massachusetts 17.39 14.68 12.74 8.76 15.35 New Hampshire 17.53 14.34 11.93 0.00 15.22 Rhode Island 17.17 14.56 12.86 14.89 15.41 Vermont ...

  6. "2014 Total Electric Industry- Average Retail Price (cents/kWh...

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

    "Massachusetts",17.390969,14.676411,12.740483,8.7639584,15.354558 "New Hampshire",17.52928,14.339091,11.929516,0,15.220362 "Rhode Island",17.167946,14.560559,12.86...

  7. ,"Selected National Average Natural Gas Prices"

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

    Selected National Average Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data ...

  8. Dynamic Multiscale Averaging (DMA) of Turbulent Flow

    SciTech Connect (OSTI)

    Richard W. Johnson

    2012-09-01

    A new approach called dynamic multiscale averaging (DMA) for computing the effects of turbulent flow is described. The new method encompasses multiple applications of temporal and spatial averaging, that is, multiscale operations. Initially, a direct numerical simulation (DNS) is performed for a relatively short time; it is envisioned that this short time should be long enough to capture several fluctuating time periods of the smallest scales. The flow field variables are subject to running time averaging during the DNS. After the relatively short time, the time-averaged variables are volume averaged onto a coarser grid. Both time and volume averaging of the describing equations generate correlations in the averaged equations. These correlations are computed from the flow field and added as source terms to the computation on the next coarser mesh. They represent coupling between the two adjacent scales. Since they are computed directly from first principles, there is no modeling involved. However, there is approximation involved in the coupling correlations as the flow field has been computed for only a relatively short time. After the time and spatial averaging operations are applied at a given stage, new computations are performed on the next coarser mesh using a larger time step. The process continues until the coarsest scale needed is reached. New correlations are created for each averaging procedure. The number of averaging operations needed is expected to be problem dependent. The new DMA approach is applied to a relatively low Reynolds number flow in a square duct segment. Time-averaged stream-wise velocity and vorticity contours from the DMA approach appear to be very similar to a full DNS for a similar flow reported in the literature. Expected symmetry for the final results is produced for the DMA method. The results obtained indicate that DMA holds significant potential in being able to accurately compute turbulent flow without modeling for practical

  9. 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...

  10. Spacetime Average Density (SAD) cosmological measures

    SciTech Connect (OSTI)

    Page, Don N.

    2014-11-01

    The measure problem of cosmology is how to obtain normalized probabilities of observations from the quantum state of the universe. This is particularly a problem when eternal inflation leads to a universe of unbounded size so that there are apparently infinitely many realizations or occurrences of observations of each of many different kinds or types, making the ratios ambiguous. There is also the danger of domination by Boltzmann Brains. Here two new Spacetime Average Density (SAD) measures are proposed, Maximal Average Density (MAD) and Biased Average Density (BAD), for getting a finite number of observation occurrences by using properties of the Spacetime Average Density (SAD) of observation occurrences to restrict to finite regions of spacetimes that have a preferred beginning or bounce hypersurface. These measures avoid Boltzmann brain domination and appear to give results consistent with other observations that are problematic for other widely used measures, such as the observation of a positive cosmological constant.

  11. Table 2. Value and average value of photovoltaic module shipments, 2014

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

    Value and average value of photovoltaic module shipments, 2014" "Module value, total shipments (thousand dollars)" "Total Modules ",5425417 "Module average value (dollars per peak watt)" "Total Modules ",0.87 "Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report' Note: Dollars are not adjusted for inflation.

  12. ,"Total Natural Gas Consumption

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

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

  13. Polarized electron beams at milliampere average current

    SciTech Connect (OSTI)

    Poelker, Matthew

    2013-11-01

    This contribution describes some of the challenges associated with developing a polarized electron source capable of uninterrupted days-long operation at milliAmpere average beam current with polarization greater than 80%. Challenges will be presented in the context of assessing the required level of extrapolation beyond the performance of today's CEBAF polarized source operating at ~ 200 uA average current. Estimates of performance at higher current will be based on hours-long demonstrations at 1 and 4 mA. Particular attention will be paid to beam-related lifetime-limiting mechanisms, and strategies to construct a photogun that operate reliably at bias voltage > 350kV.

  14. Reynolds-Averaged Navier-Stokes

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

    Reynolds-Averaged Navier-Stokes simulation of the heave performance of a two-body floating-point absorber wave energy system Yi-Hsiang Yu, Ye Li ⇑ National Wind Technology Center, National Renewable Energy Laboratory (NREL), Golden, CO 80401, USA a r t i c l e i n f o Article history: Received 7 September 2011 Received in revised form 5 August 2012 Accepted 9 October 2012 Available online 17 October 2012 Keywords: Wave energy conversion Heave Computational Fluid Dynamics Reynolds-averaged

  15. STEO January 2013 - average gasoline prices

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

    drivers to see lower average gasoline prices in 2013 and 2014 U.S. retail gasoline prices are expected to decline over the next two years. The average pump price for regular unleaded gasoline was $3.63 a gallon during 2012. That is expected to fall to $3.44 this year and then drop to $3.34 in 2014, according to the new forecast from the U.S. Energy Information Administration. Expected lower crude oil prices.....which accounted for about two-thirds of the price of gasoline in 2012....will

  16. 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...

  17. 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...

  18. 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:...

  19. HIGH AVERAGE POWER OPTICAL FEL AMPLIFIERS.

    SciTech Connect (OSTI)

    BEN-ZVI, ILAN, DAYRAN, D.; LITVINENKO, V.

    2005-08-21

    Historically, the first demonstration of the optical FEL was in an amplifier configuration at Stanford University [l]. There were other notable instances of amplifying a seed laser, such as the LLNL PALADIN amplifier [2] and the BNL ATF High-Gain Harmonic Generation FEL [3]. However, for the most part FELs are operated as oscillators or self amplified spontaneous emission devices. Yet, in wavelength regimes where a conventional laser seed can be used, the FEL can be used as an amplifier. One promising application is for very high average power generation, for instance FEL's with average power of 100 kW or more. The high electron beam power, high brightness and high efficiency that can be achieved with photoinjectors and superconducting Energy Recovery Linacs (ERL) combine well with the high-gain FEL amplifier to produce unprecedented average power FELs. This combination has a number of advantages. In particular, we show that for a given FEL power, an FEL amplifier can introduce lower energy spread in the beam as compared to a traditional oscillator. This properly gives the ERL based FEL amplifier a great wall-plug to optical power efficiency advantage. The optics for an amplifier is simple and compact. In addition to the general features of the high average power FEL amplifier, we will look at a 100 kW class FEL amplifier is being designed to operate on the 0.5 ampere Energy Recovery Linac which is under construction at Brookhaven National Laboratory's Collider-Accelerator Department.

  20. New applications for high average power beams

    SciTech Connect (OSTI)

    Neau, E.L.; Turman, B.N.; Patterson, E.L.

    1993-08-01

    The technology base formed by the development of high peak power simulators, laser drivers, FEL`s, and ICF drivers from the early 60`s through the late 80`s is being extended to high average power short-pulse machines with the capabilities of supporting new types of manufacturing processes and performing new roles in environmental cleanup applications. This paper discusses a process for identifying and developing possible commercial applications, specifically those requiring very high average power levels of hundreds of kilowatts to perhaps megawatts. The authors discuss specific technology requirements and give examples of application development efforts. The application development work is directed at areas that can possibly benefit from the high specific energies attainable with short pulse machines.

  1. Table 1. Real Average Transportation and Delivered Costs of Coal...

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

    Real Average Transportation and Delivered Costs of Coal, By Year and Primary Transport Mode" "Year","Average Transportation Cost of Coal (Dollars per Ton)","Average Delivered Cost...

  2. Table 19. Average Price of U.S. Coal Imports

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

    9. Average Price of U.S. Coal Imports (dollars per short ton) Year to Date Continent and Country of Origin January - March 2016 October - December 2015 January - March 2015 2016 2015 Percent Change North America Total 71.92 104.33 107.02 71.92 107.02 -32.8 Canada 71.93 104.32 107.01 71.93 107.01 -32.8 Mexico 66.79 360.25 113.43 66.79 113.43 -41.1 South America Total 64.73 64.18 70.82 64.73 70.82 -8.6 Colombia 64.73 63.86 70.58 64.73 70.58 -8.3 Peru 63.31 86.76 86.19 63.31 86.19 -26.5 Venezuela -

  3. Table 22. Average Price of U.S. Coke Imports

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

    2. Average Price of U.S. Coke Imports (dollars per short ton) Year to Date Continent and Country of Origin January - March 2016 October - December 2015 January - March 2015 2016 2015 Percent Change North America Total 181.85 113.11 213.82 181.85 213.82 -15.0 Canada 181.85 113.11 213.82 181.85 213.82 -15.0 Europe Total 270.94 416.80 770.50 270.94 770.50 -64.8 Austria - 1,788.00 - - - - France - 1,110.35 - - - - Germany, Federal Republic of - - 206.27 - 206.27 - Italy 265.37 300.11 - 265.37 - -

  4. Early Clinical Outcomes Demonstrate Preserved Cognitive Function in Children With Average-Risk Medulloblastoma When Treated With Hyperfractionated Radiation Therapy

    SciTech Connect (OSTI)

    Gupta, Tejpal; Jalali, Rakesh; Goswami, Savita; Nair, Vimoj; Moiyadi, Aliasgar; Epari, Sridhar; Sarin, Rajiv

    2012-08-01

    Purpose: To report on acute toxicity, longitudinal cognitive function, and early clinical outcomes in children with average-risk medulloblastoma. Methods and Materials: Twenty children {>=}5 years of age classified as having average-risk medulloblastoma were accrued on a prospective protocol of hyperfractionated radiation therapy (HFRT) alone. Radiotherapy was delivered with two daily fractions (1 Gy/fraction, 6 to 8 hours apart, 5 days/week), initially to the neuraxis (36 Gy/36 fractions), followed by conformal tumor bed boost (32 Gy/32 fractions) for a total tumor bed dose of 68 Gy/68 fractions over 6 to 7 weeks. Cognitive function was prospectively assessed longitudinally (pretreatment and at specified posttreatment follow-up visits) with the Wechsler Intelligence Scale for Children to give verbal quotient, performance quotient, and full-scale intelligence quotient (FSIQ). Results: The median age of the study cohort was 8 years (range, 5-14 years), representing a slightly older cohort. Acute hematologic toxicity was mild and self-limiting. Eight (40%) children had subnormal intelligence (FSIQ <85), including 3 (15%) with mild mental retardation (FSIQ 56-70) even before radiotherapy. Cognitive functioning for all tested domains was preserved in children evaluable at 3 months, 1 year, and 2 years after completion of HFRT, with no significant decline over time. Age at diagnosis or baseline FSIQ did not have a significant impact on longitudinal cognitive function. At a median follow-up time of 33 months (range, 16-58 months), 3 patients had died (2 of relapse and 1 of accidental burns), resulting in 3-year relapse-free survival and overall survival of 83.5% and 83.2%, respectively. Conclusion: HFRT without upfront chemotherapy has an acceptable acute toxicity profile, without an unduly increased risk of relapse, with preserved cognitive functioning in children with average-risk medulloblastoma.

  5. A Green's function quantum average atom model

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

    Starrett, Charles Edward

    2015-05-21

    A quantum average atom model is reformulated using Green's functions. This allows integrals along the real energy axis to be deformed into the complex plane. The advantage being that sharp features such as resonances and bound states are broadened by a Lorentzian with a half-width chosen for numerical convenience. An implementation of this method therefore avoids numerically challenging resonance tracking and the search for weakly bound states, without changing the physical content or results of the model. A straightforward implementation results in up to a factor of 5 speed-up relative to an optimized orbital based code.

  6. 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...

  7. ,"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...

  8. ,"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...

  9. 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...

  10. 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*...

  11. ,"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...

  12. ,"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...

  13. ,"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"...

  14. 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.

  15. Table HC1.1.2 Housing Unit Characteristics by Average Floorspace, 2005

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

    2 Housing Unit Characteristics by Average Floorspace, 2005 " ,,"Average Square Feet per--" ," Housing Units (millions)" ,,"Housing Unit",,,"Household Member" "Housing Unit Characteristics",,"Total1","Heated","Cooled","Total","Heated","Cooled" "Total",111.1,2171,1618,1031,845,630,401 "Census Region and Division" "Northeast",20.6,2334,1664,562,911,649,220

  16. Table HC1.1.4 Housing Unit Characteristics by Average Floorspace--Apartments, 2

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

    4 Housing Unit Characteristics by Average Floorspace--Apartments, 2005" ,,,"Average Square Feet per Apartment in a --" ," Housing Units (millions)" ,,,"2 to 4 Unit Building",,,"5 or More Unit Building" ,,"Apartments (millions)" "Housing Unit Characteristics",,,"Total","Heated","Cooled","Total","Heated","Cooled" "Total",111.1,24.5,1090,902,341,872,780,441

  17. Table HC1.2.4 Living Space Characteristics by Average Floorspace--Apartments, 2

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

    2.4 Living Space Characteristics by Average Floorspace--Apartments, 2005" ,,,"Average Square Feet per Apartment in a --" ," Housing Units (millions)" ,,,"2 to 4 Unit Building",,,"5 or More Unit Building" ,,"Apartments (millions)" "Living Space Characteristics",,,"Total","Heated","Cooled","Total","Heated","Cooled" "Total",111.1,24.5,1090,902,341,872,780,441

  18. 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 ...

  19. Historical Average Priority Firm Power Rates (rates/previous...

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

    (A to Z) - - - - - - - - - - - - - Account Executives Administrator's RODs Aluminum Industry Study (2000-01) Billing Procedures Customer Service Centers Daily Notice Document...

  20. 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

  1. 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

  2. Insolation data manual: long-term monthly averages of solar radiation, temperature, degree-days and global anti K/sub T/ for 248 national weather service stations

    SciTech Connect (OSTI)

    Knapp, C L; Stoffel, T L; Whitaker, S D

    1980-10-01

    Monthly averaged data is presented which describes the availability of solar radiation at 248 National Weather Service stations. Monthly and annual average daily insolation and temperature values have been computed from a base of 24 to 25 years of data. Average daily maximum, minimum, and monthly temperatures are provided for most locations in both Celsius and Fahrenheit. Heating and cooling degree-days were computed relative to a base of 18.3/sup 0/C (65/sup 0/F). For each station, global anti K/sub T/ (cloudiness index) were calculated on a monthly and annual basis. (MHR)

  3. Table 8. Average Price of U.S. Coal Exports

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

    8. Average Price of U.S. Coal Exports (dollars per short ton) Year to Date Continent and Country of Destination January - March 2016 October - December 2015 January - March 2015 2016 2015 Percent Change North America Total 62.62 81.09 76.28 62.62 76.28 -17.9 Canada* 87.37 97.37 80.39 87.37 80.39 8.7 Dominican Republic 213.68 - 461.75 213.68 461.75 -53.7 Guatemala - 66.22 359.27 - 359.27 - Honduras 78.02 78.02 54.43 78.02 54.43 43.3 Jamaica 38.10 39.48 45.51 38.10 45.51 -16.3 Mexico 41.25 37.52

  4. 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...

  5. 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

  6. Annual average efficiency of a solar thermochemical reactor....

    Office of Scientific and Technical Information (OSTI)

    Annual average efficiency of a solar thermochemical reactor. Citation Details In-Document Search Title: Annual average efficiency of a solar thermochemical reactor. Abstract not ...

  7. ARM: Temperature Profiles from Raman Lidar at 60-min averaging...

    Office of Scientific and Technical Information (OSTI)

    Citation Details In-Document Search Title: ARM: Temperature Profiles from Raman Lidar at 60-min averaging interval Temperature Profiles from Raman Lidar at 60-min averaging ...

  8. ARM: Temperature Profiles from Raman Lidar at 10-min averaging...

    Office of Scientific and Technical Information (OSTI)

    Temperature Profiles from Raman Lidar at 10-min averaging interval Title: ARM: Temperature Profiles from Raman Lidar at 10-min averaging interval Temperature Profiles from Raman ...

  9. ARM: AOS Wet Nephelometer 1 Minute Averages (Dataset) | Data...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: AOS Wet Nephelometer 1 Minute Averages AOS Wet Nephelometer 1 Minute Averages Authors: Scott Smith ; Cynthia Salwen ; Janek Uin ; Gunnar Senum ; Stephen Springston ; ...

  10. ARM: AOS Dry Nephelometer 1 Minute Averages (Dataset) | Data...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: AOS Dry Nephelometer 1 Minute Averages AOS Dry Nephelometer 1 Minute Averages Authors: Scott Smith ; Cynthia Salwen ; Janek Uin ; Gunnar Senum ; Stephen Springston ; ...

  11. High Average Brightness Photocathode Development for FEL Applications...

    Office of Scientific and Technical Information (OSTI)

    Conference: High Average Brightness Photocathode Development for FEL Applications Citation Details In-Document Search Title: High Average Brightness Photocathode Development for...

  12. 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

  13. Influence of wind speed averaging on estimates of dimethylsulfide emission fluxes

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

    Chapman, E. G.; Shaw, W. J.; Easter, R. C.; Bian, X.; Ghan, S. J.

    2002-12-03

    The effect of various wind-speed-averaging periods on calculated DMS emission fluxes is quantitatively assessed. Here, a global climate model and an emission flux module were run in stand-alone mode for a full year. Twenty-minute instantaneous surface wind speeds and related variables generated by the climate model were archived, and corresponding 1-hour-, 6-hour-, daily-, and monthly-averaged quantities calculated. These various time-averaged, model-derived quantities were used as inputs in the emission flux module, and DMS emissions were calculated using two expressions for the mass transfer velocity commonly used in atmospheric models. Results indicate that the time period selected for averaging wind speedsmore » can affect the magnitude of calculated DMS emission fluxes. A number of individual marine cells within the global grid show DMS emissions fluxes that are 10-60% higher when emissions are calculated using 20-minute instantaneous model time step winds rather than monthly-averaged wind speeds, and at some locations the differences exceed 200%. Many of these cells are located in the southern hemisphere where anthropogenic sulfur emissions are low and changes in oceanic DMS emissions may significantly affect calculated aerosol concentrations and aerosol radiative forcing.« less

  14. 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...

  15. 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?

  16. 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

  17. Fact #889: September 7, 2015 Average Diesel Price Lower than...

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

    9: September 7, 2015 Average Diesel Price Lower than Gasoline for the First Time in Six Years Fact 889: September 7, 2015 Average Diesel Price Lower than Gasoline for the First ...

  18. Fact #849: December 1, 2014 Midsize Hybrid Cars Averaged 51%...

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

    9: December 1, 2014 Midsize Hybrid Cars Averaged 51% Better Fuel Economy than Midsize Non-Hybrid Cars in 2014 Fact 849: December 1, 2014 Midsize Hybrid Cars Averaged 51% Better ...

  19. Fact #835: August 25, 2014 Average Annual Gasoline Pump Price...

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

    35: Average Annual Gasoline Pump Price, 1929-2013 fotw835web.xlsx (21.31 KB) More Documents & Publications Fact 915: March 7, 2016 Average Historical Annual Gasoline Pump Price, ...

  20. Fact #693: September 19, 2011 Average Vehicle Footprint for Cars...

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

    It is calculated as the product of the wheelbase and the average track width of the vehicle. The upcoming Corporate Average Fuel Economy (CAFE) Standards have fuel economy targets ...

  1. Fact #870: April 27, 2015 Corporate Average Fuel Economy Progress...

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

    0: April 27, 2015 Corporate Average Fuel Economy Progress, 1978-2014 - Dataset Fact 870: April 27, 2015 Corporate Average Fuel Economy Progress, 1978-2014 - Dataset Excel file and ...

  2. Average Price (Cents/kilowatthour) by State by Provider, 1990-2014

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

    Average Price (Cents/kilowatthour) by State by Provider, 1990-2014" "Year","State","Industry Sector Category","Residential","Commercial","Industrial","Transportation","Other","Total" 2014,"AK","Total Electric Industry",19.14,17.09,15.66,0,"NA",17.46 2014,"AL","Total Electric Industry",11.48,10.79,6.15,0,"NA",9.27

  3. 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.

  4. 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.

  5. High Average Brightness Photocathode Development for FEL Applications...

    Office of Scientific and Technical Information (OSTI)

    Title: High Average Brightness Photocathode Development for FEL Applications Authors: Rao T. ; Ben-Zvi I. ; Skarita, J. ; Wang, E. Publication Date: 2013-08-26 OSTI Identifier: ...

  6. Turning Bayesian model averaging into Bayesian model combination...

    Office of Scientific and Technical Information (OSTI)

    Title: Turning Bayesian model averaging into Bayesian model combination Authors: Carroll, James 1 ; Monteith, Kristine 2 ; Seppi, Kevin 2 ; Martinez, Tony 2 + Show Author ...

  7. "Table 2. Real Average Annual Coal Transportation Costs, By Primary...

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

    Real Average Annual Coal Transportation Costs, By Primary Transport Mode and Supply Region" "(2013 dollars per ton)" "Coal Supply Region",2008,2009,2010,2011,2012,2013 "Railroad"...

  8. "Variable","Average Absolute Percent Differences","Percent of...

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

    Annual Energy Outlook Retrospective Review, 2014" "Variable","Average Absolute Percent Differences","Percent of Projections Over- Estimated" "Gross Domestic Product" "Real Gross ...

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

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

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

  10. 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,...

  11. 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 ...

  12. 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

  13. 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

  14. SU-E-J-153: MRI Based, Daily Adaptive Radiotherapy for Rectal Cancer: Contour Adaptation

    SciTech Connect (OSTI)

    Kleijnen, J; Burbach, M; Verbraeken, T; Weggers, R; Zoetelief, A; Reerink, O; Lagendijk, J; Raaymakers, B; Asselen, B

    2014-06-01

    Purpose: A major hurdle in adaptive radiotherapy is the adaptation of the planning MRI's delineations to the daily anatomy. We therefore investigate the accuracy and time needed for online clinical target volume (CTV) adaptation by radiation therapists (RTT), to be used in MRI-guided adaptive treatments on a MRI-Linac (MRL). Methods: Sixteen patients, diagnosed with early stage rectal cancer, underwent a T2-weighted MRI prior to each fraction of short-course radiotherapy, resulting in 4–5 scans per patient. On these scans, the CTV was delineated according to guidelines by an experienced radiation oncologist (RO) and considered to be the gold standard. For each patient, the first MRI was considered as the planning MRI and matched on bony anatomy to the 3–4 daily MRIs. The planning MRI's CTV delineation was rigidly propagated to the daily MRI scans as a proposal for adaptation. Three RTTs in training started the adaptation of the CTV conform guidelines, after a two hour training lecture and a two patient (n=7) training set. To assess the inter-therapist variation, all three RTTs altered delineations of 3 patients (n=12). One RTT altered the CTV delineations (n=53) of the remaining 11 patients. Time needed for adaptation of the CTV to guidelines was registered.As a measure of agreement, the conformity index (CI) was determined between the RTTs' delineations as a group. Dice similarity coefficients were determined between delineations of the RTT and the RO. Results: We found good agreement between RTTs' and RO's delineations (average Dice=0.91, SD=0.03). Furthermore, the inter-observer agreement between the RTTs was high (average CI=0.94, SD=0.02). Adaptation time reduced from 10:33 min (SD= 3:46) to 2:56 min (SD=1:06) between the first and last ten delineations, respectively. Conclusion: Daily CTV adaptation by RTTs, seems a feasible and safe way to introduce daily, online MRI-based plan adaptation for a MRL.

  15. 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.

  16. 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

  17. Experimental analysis of thermal performance of flat plate and evacuated tube solar collectors in stationary standard and daily conditions

    SciTech Connect (OSTI)

    Zambolin, E.; Del Col, D.

    2010-08-15

    New comparative tests on two different types of solar collectors are presented in this paper. A standard glazed flat plate collector and an evacuated tube collector are installed in parallel and tested at the same working conditions; the evacuated collector is a direct flow through type with external compound parabolic concentrator (CPC) reflectors. Efficiency in steady-state and quasi-dynamic conditions is measured following the standard and it is compared with the input/output curves measured for the whole day. The first purpose of the present work is the comparison of results in steady-state and quasi-dynamic test methods both for flat plate and evacuated tube collectors. Besides this, the objective is to characterize and to compare the daily energy performance of these two types of collectors. An effective mean for describing and analyzing the daily performance is the so called input/output diagram, in which the collected solar energy is plotted against the daily incident solar radiation. Test runs have been performed in several conditions to reproduce different conventional uses (hot water, space heating, solar cooling). Results are also presented in terms of daily efficiency versus daily average reduced temperature difference: this allows to represent the comparative characteristics of the two collectors when operating under variable conditions, especially with wide range of incidence angles. (author)

  18. Assessing Energy Impact of Plug-In Hybrid Electric Vehicles: Significance of Daily Distance Variation over Time and Among Drivers

    SciTech Connect (OSTI)

    Lin, Zhenhong [ORNL; Greene, David L [ORNL

    2012-01-01

    Accurate assessment of the impact of plug-in hybrid electric vehicles (PHEVs) on petroleum and electricity consumption is a necessary step toward effective policies. Variations in daily vehicle miles traveled (VMT) over time and among drivers affect PHEV energy impact, but the significance is not well understood. This paper uses a graphical illustration, a mathematical derivation, and an empirical study to examine the cause and significance of such an effect. The first two methods reveal that ignoring daily variation in VMT always causes underestimation of petroleum consumption and overestimation of electricity consumption by PHEVs; both biases increase as the assumed PHEV charge-depleting (CD) range moves closer to the average daily VMT. The empirical analysis based on national travel survey data shows that the assumption of uniform daily VMT over time and among drivers causes nearly 68% underestimation of expected petroleum use and nearly 48% overestimation of expected electricity use by PHEVs with a 40-mi CD range (PHEV40s). Also for PHEV40s, consideration of daily variation in VMT over time but not among drivers similar to the way the utility factor curve is derived in SAE Standard SAE J2841 causes underestimation of expected petroleum use by more than 24% and overestimation of expected electricity use by about 17%. Underestimation of petroleum use and overestimation of electricity use increase with larger-battery PHEVs.

  19. Fact #803: November 11, 2013 Average Number of Transmission Gears...

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

    Average Number of Gears for New Light Vehicles, Model Years 1979-2012 Model Year Average Number of Gears 1979 3.3 1980 3.5 1981 3.5 1982 3.6 1983 3.7 1984 3.7 1985 3.8 1986 3.8 ...

  20. 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

  1. 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...

  2. Fact #870: April 27, 2015 Corporate Average Fuel Economy Progress,

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

    1978-2014 - Dataset | Department of Energy 0: April 27, 2015 Corporate Average Fuel Economy Progress, 1978-2014 - Dataset Fact #870: April 27, 2015 Corporate Average Fuel Economy Progress, 1978-2014 - Dataset Excel file and dataset for Corporate Average Fuel Economy Progress, 1978-2014 fotw#870_web.xlsx (17.92 KB) More Documents & Publications Reactor Pressure Vessel Task of Light Water Reactor Sustainability Program: Milestone Report on Materials and Machining of Specimens for the ATR-2

  3. U.S. Refiner Sales to End Users (Average) Prices

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

    Sales Type: Sales to End Users, Average Through Retail Outlets Sales for Resale, Average DTW Rack Bulk Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Formulation/ Grade Sales Type Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History Conventional, Average 1.346 1.209 1.450 1.617 1.790 1.894 1994-2016 Conventional Regular 1.305 1.167 1.412 1.576 1.749 1.854 1994-2016 Conventional Midgrade 1.524 1.376 1.601 1.781

  4. Table 7.2 Average Prices of Purchased Energy Sources, 2010;

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

    Table 7.2 Average Prices of Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Million Btu. Selected Wood and Other Biomass Components Coal Components Coke Electricity Components Natural Gas Components Steam Components Total Wood Residues Bituminous Electricity Diesel Fuel Motor Natural Gas Steam and Wood-Related and Electricity from Sources and Gasoline Pulping Liquor Natural Gas from Sources Steam

  5. 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.

  6. Does anyone have access to 2012 average residential rates by...

    Open Energy Info (EERE)

    Does anyone have access to 2012 average residential rates by utility company? I'm seeing an inconsistency between the OpenEI website and EIA 861 data set. Home > Groups > Utility...

  7. Fact #915: March 7, 2016 Average Historical Annual Gasoline Pump...

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

    Average Historical Annual Gasoline Pump Price, 1929-2015 fotw915web.xlsx (24.76 KB) More Documents & Publications Fact 888: August 31, 2015 Historical Gas Prices - Dataset Fact ...

  8. Fact #624: May 24, 2010 Corporate Average Fuel Economy Standards...

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

    The final rule for the Corporate Average Fuel Economy (CAFE) Standards was published in ... The CAFE levels that must be met by the fleet of each manufacturer will be determined by ...

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

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

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

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

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

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

  11. 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

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

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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  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 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

  15. 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

  16. 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

  17. 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

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

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

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

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

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

    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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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.....................................................

  11. 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

  12. 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

  13. 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 ...

  14. 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 ...

  15. 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 ...

  16. 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 ...

  17. 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 ...

  18. 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 ...

  19. 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 ...

  20. 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 ...

  1. 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 ...

  2. 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 ...

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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......

  8. 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......

  9. 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......

  10. 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 ...

  11. 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 ...

  12. 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......

  13. 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 ...

  14. 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 ...

  15. 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 ...

  16. Flavor Physics Data from the Heavy Flavor Averaging Group (HFAG)

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

    The Heavy Flavor Averaging Group (HFAG) was established at the May 2002 Flavor Physics and CP Violation Conference in Philadelphia, and continues the LEP Heavy Flavor Steering Group's tradition of providing regular updates to the world averages of heavy flavor quantities. Data are provided by six subgroups that each focus on a different set of heavy flavor measurements: B lifetimes and oscillation parameters, Semi-leptonic B decays, Rare B decays, Unitarity triangle parameters, B decays to charm final states, and Charm Physics.

  17. Averaged null energy condition violation in a conformally flat spacetime

    SciTech Connect (OSTI)

    Urban, Douglas; Olum, Ken D.

    2010-01-15

    We show that the averaged null energy condition can be violated by a conformally coupled scalar field in a conformally flat spacetime in 3+1 dimensions. The violation is dependent on the quantum state and can be made as large as desired. It does not arise from the presence of anomalies, although anomalous violations are also possible. Since all geodesics in conformally flat spacetimes are achronal, the achronal averaged null energy condition is likewise violated.

  18. ,"Housing Units1","Average Square Footage Per Housing Unit",...

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

    ... Vacant housing units, seasonal units, second homes, military housing, and group quarters are excluded. 2Total square footage includes all basements, finished or conditioned (heated ...

  19. "Table A49. Average Prices of Purchased Electricity, Steam...

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

    ...teristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors" " "," "," "," "," "," "," " ,"Total United States" "RSE ...

  20. 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

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

    SciTech Connect (OSTI)

    Luo, Liancong; Hamilton, David; Han, Boping

    2010-03-15

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

  2. Table 17. Average Price of U.S. Coke Exports

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

    2015 2016 2015 Percent Change North America Total 294.80 204.63 276.27 294.80 276.27 ... 355.59 611.72 791.78 611.72 29.4 South America Total 501.14 - 702.17 501.14 702.17 -28.6 ...

  3. High average power scaleable thin-disk laser

    DOE Patents [OSTI]

    Beach, Raymond J.; Honea, Eric C.; Bibeau, Camille; Payne, Stephen A.; Powell, Howard; Krupke, William F.; Sutton, Steven B.

    2002-01-01

    Using a thin disk laser gain element with an undoped cap layer enables the scaling of lasers to extremely high average output power values. Ordinarily, the power scaling of such thin disk lasers is limited by the deleterious effects of amplified spontaneous emission. By using an undoped cap layer diffusion bonded to the thin disk, the onset of amplified spontaneous emission does not occur as readily as if no cap layer is used, and much larger transverse thin disks can be effectively used as laser gain elements. This invention can be used as a high average power laser for material processing applications as well as for weapon and air defense applications.

  4. Turning Bayesian model averaging into Bayesian model combination

    Office of Scientific and Technical Information (OSTI)

    (Conference) | SciTech Connect Turning Bayesian model averaging into Bayesian model combination Citation Details In-Document Search Title: Turning Bayesian model averaging into Bayesian model combination Authors: Carroll, James [1] ; Monteith, Kristine [2] ; Seppi, Kevin [2] ; Martinez, Tony [2] + Show Author Affiliations Los Alamos National Laboratory BYU Publication Date: 2011-07-28 OSTI Identifier: 1084524 Report Number(s): LA-UR-11-04419; LA-UR-11-4419 DOE Contract Number: AC52-06NA25396

  5. U.S. average gasoline price up slightly

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

    U.S. average gasoline price up slightly The U.S. average retail price for regular gasoline rose slightly to $3.65 a gallon on Monday. That's up a tenth of a penny from a week ago, based on the weekly price survey by the U.S. Energy Information Administration. Pump prices were highest in the West Coast region at 3.89 a gallon, down 4.4 cents from a week ago. Prices were lowest in the Gulf Coast States at 3.34 a gallon, down 2.6 cents. Jonathan Cogan for EIA,

  6. Virginia Average Price of Natural Gas Delivered to Residential and

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

    Commercial Consumers by Local Distribution and Market 9.45 8.76 10.20 10.63 12.69 15.51 1989-2016 Commercial Average Price 6.88 6.67 7.18 6.65 7.24 7.22

  7. Speckle averaging system for laser raster-scan image projection

    DOE Patents [OSTI]

    Tiszauer, Detlev H.; Hackel, Lloyd A.

    1998-03-17

    The viewers' perception of laser speckle in a laser-scanned image projection system is modified or eliminated by the addition of an optical deflection system that effectively presents a new speckle realization at each point on the viewing screen to each viewer for every scan across the field. The speckle averaging is accomplished without introduction of spurious imaging artifacts.

  8. Maryland Average Price of Natural Gas Delivered to Residential...

    Gasoline and Diesel Fuel Update (EIA)

    8.35 18.44 19.08 19.39 13.51 12.72 1989-2015 Commercial Average Price 11.74 10.98 11.61 11.11 9.98 9.56...

  9. Michigan Average Price of Natural Gas Delivered to Residential...

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

    2.50 13.65 13.52 13.21 8.93 7.84 1989-2015 Commercial Average Price 8.91 9.31 9.17 9.05 7.46 6.75...

  10. Parity-violating anomalies and the stationarity of stochastic averages

    SciTech Connect (OSTI)

    Reuter, M.

    1988-01-15

    Within the framework of stochastic quantization the parity-violating anomalies in odd space-time dimensions are derived from the asymptotic stationarity of the stochastic average of a certain fermion bilinear. Contrary to earlier attempts, this method yields the correct anomalies for both massive and massless fermions.

  11. Pennsylvania Average Price of Natural Gas Delivered to Residential and

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

    Commercial Consumers by Local Distribution and Ma 8.75 8.64 9.51 9.91 11.30 15.62 1989-2016 Commercial Average Price 7.19 7.44 8.21 8.12 8.74 10.69

  12. Speckle averaging system for laser raster-scan image projection

    DOE Patents [OSTI]

    Tiszauer, D.H.; Hackel, L.A.

    1998-03-17

    The viewers` perception of laser speckle in a laser-scanned image projection system is modified or eliminated by the addition of an optical deflection system that effectively presents a new speckle realization at each point on the viewing screen to each viewer for every scan across the field. The speckle averaging is accomplished without introduction of spurious imaging artifacts. 5 figs.

  13. Florida Average Price of Natural Gas Delivered to Residential and

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

    Commercial Consumers by Local Distribution and Markete 6.78 16.00 17.06 17.83 20.52 22.40 1989-2016 Commercial Average Price 10.70 10.62 10.50 10.29 10.16 10.38

  14. Georgia Average Price of Natural Gas Delivered to Residential and

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

    Commercial Consumers by Local Distribution and Markete 0.79 10.94 13.01 16.48 20.53 24.74 1989-2016 Commercial Average Price 6.57 7.05 7.42 7.98 8.22 8.53

  15. Maryland Average Price of Natural Gas Delivered to Residential...

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

    Local Distribution Companies 12.20 2006-2010 Marketers 13.51 2006-2010 Percent Sold by Local Distribution Companies 81.7 2006-2010 Commercial Average Price 9.87 10.29 10.00 10.06 ...

  16. Florida Average Price of Natural Gas Delivered to Residential...

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

    Local Distribution Companies 17.85 2006-2010 Marketers 19.44 2006-2010 Percent Sold by Local Distribution Companies 97.9 2006-2010 Commercial Average Price 10.60 11.14 10.41 10.87 ...

  17. New Jersey Average Price of Natural Gas Delivered to Residential...

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

    Local Distribution Companies 12.77 2006-2010 Marketers 14.87 2006-2010 Percent Sold by Local Distribution Companies 96.6 2006-2010 Commercial Average Price 10.11 9.51 8.50 9.55 ...

  18. Michigan Average Price of Natural Gas Delivered to Residential...

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

    Commercial Average Price 8.95 9.14 8.35 7.82 8.28 7.49 1967-2015 Local Distribution Companies 10.00 2006-2010 Marketers 7.61 2006-2010 Percent Sold by Local Distribution Companies ...

  19. Virginia Average Price of Natural Gas Delivered to Residential...

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

    Local Distribution Companies 12.64 2006-2010 Marketers 13.64 2006-2010 Percent Sold by Local Distribution Companies 90.9 2006-2010 Commercial Average Price 9.55 9.69 8.77 8.83 9.17 ...

  20. Pennsylvania Average Price of Natural Gas Delivered to Residential...

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

    Local Distribution Companies 12.82 2006-2010 Marketers 13.78 2006-2010 Percent Sold by Local Distribution Companies 91.2 2006-2010 Commercial Average Price 10.47 10.42 10.24 10.11 ...

  1. District of Columbia Average Price of Natural Gas Delivered to...

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

    Average Price 12.26 12.24 11.19 11.64 12.18 11.55 1980-2015 Local Distribution Companies 12.99 2006-2010 Marketers 12.12 2006-2010 Percent Sold by Local Distribution Companies 16.4 ...

  2. "Table A29. Average Prices of Selected Purchased Energy Sources...

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

    ...,"(gallon)","(gallon)","(1000 cu ft)","(gallon)","(short ton)","Factors" ,"Total United States" "RSE Column Factors:",0.7,1.2,1.1,0.8,1.2,1 "Value of Shipments and Receipts " ...

  3. "Table A41. Average Prices of Selected Purchased Energy Sources...

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

    ...allons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors" ,"Total United States" "RSE Column Factors:",0.6,0.8,1.2,0.7,2.5,0.9 "Value of Shipments and Receipts" ...

  4. "Table A29. Average Prices of Selected Purchased Energy Sources...

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

    ...","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","Factors" ,"Total United States" "RSE Column Factors:",0.8,1.2,1.2,0.9,1.3,0.8 "Value of Shipments and Receipts" ...

  5. Table A44. Average Prices of Purchased Electricity and Steam

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

    ...cs(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,"Total United States" "RSE Column Factors:",0.3,1.6,1.5,1.3 "Value of Shipments and Receipts" "(million ...

  6. "Table A41. Average Prices of Selected Purchased Energy Sources...

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

    ...","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","Factors" ,"Total United States" "RSE Column Factors:",0.6,0.8,1.2,0.7,2.5,0.9 "Value of Shipments and Receipts" ...

  7. 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...

  8. 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

  9. Averaging cross section data so we can fit it

    SciTech Connect (OSTI)

    Brown, D.

    2014-10-23

    The 56Fe cross section we are interested in have a lot of fluctuations. We would like to fit the average of the cross section with cross sections calculated within EMPIRE. EMPIRE is a Hauser-Feshbach theory based nuclear reaction code, requires cross sections to be smoothed using a Lorentzian profile. The plan is to fit EMPIRE to these cross sections in the fast region (say above 500 keV).

  10. Electric Sales, Revenue, and Average Price 2011 - Energy Information

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

    Administration Electricity Glossary › FAQS › Overview Data Electricity Data Browser (interactive query tool with charting & mapping) Summary Sales (consumption), revenue, prices & customers Generation and thermal output Capacity of electric power plants Consumption of fuels used to generate electricity Receipts of fossil-fuels for electricity generation Average cost of fossil-fuels for electricity generation Fossil-fuel stocks for electricity generation Cost, revenue and expense

  11. Average dynamics of a finite set of coupled phase oscillators

    SciTech Connect (OSTI)

    Dima, Germn C. Mindlin, Gabriel B.

    2014-06-15

    We study the solutions of a dynamical system describing the average activity of an infinitely large set of driven coupled excitable units. We compared their topological organization with that reconstructed from the numerical integration of finite sets. In this way, we present a strategy to establish the pertinence of approximating the dynamics of finite sets of coupled nonlinear units by the dynamics of its infinitely large surrogate.

  12. Table 12. Average Price of U.S. Metallurgical Coal Exports

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

    2. Average Price of U.S. Metallurgical Coal Exports (dollars per short ton) Year to Date Continent and Country of Destination January - March 2016 October - December 2015 January - March 2015 2016 2015 Percent Change North America Total 91.86 102.82 92.36 91.86 92.36 -0.5 Canada* 88.10 104.16 87.30 88.10 87.30 0.9 Guatemala - 66.22 - - - - Honduras 78.02 78.02 - 78.02 - - Mexico 111.56 110.99 108.37 111.56 108.37 2.9 South America Total 64.83 75.44 96.14 64.83 96.14 -32.6 Argentina - - 100.77 -

  13. 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.

  14. 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

  15. 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.

  16. Table 4. Average value of photovoltaic modules, 2004-2014

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

    Average value of photovoltaic modules, 2004-2014" "(dollars per peak watt)" "Year","Modules" 2004,2.99 2005,3.19 2006,3.5 2007,3.37 2008,3.49 2009,2.79 2010,1.96 2011,1.59 2012,1.15 2013,0.75 2014,0.87 "Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.' Note: Dollars are not adjusted for inflation.

  17. 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

  18. Predictive RANS simulations via Bayesian Model-Scenario Averaging

    SciTech Connect (OSTI)

    Edeling, W.N.; Cinnella, P.; Dwight, R.P.

    2014-10-15

    The turbulence closure model is the dominant source of error in most Reynolds-Averaged Navier–Stokes simulations, yet no reliable estimators for this error component currently exist. Here we develop a stochastic, a posteriori error estimate, calibrated to specific classes of flow. It is based on variability in model closure coefficients across multiple flow scenarios, for multiple closure models. The variability is estimated using Bayesian calibration against experimental data for each scenario, and Bayesian Model-Scenario Averaging (BMSA) is used to collate the resulting posteriors, to obtain a stochastic estimate of a Quantity of Interest (QoI) in an unmeasured (prediction) scenario. The scenario probabilities in BMSA are chosen using a sensor which automatically weights those scenarios in the calibration set which are similar to the prediction scenario. The methodology is applied to the class of turbulent boundary-layers subject to various pressure gradients. For all considered prediction scenarios the standard-deviation of the stochastic estimate is consistent with the measurement ground truth. Furthermore, the mean of the estimate is more consistently accurate than the individual model predictions.

  19. 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 ...

  20. 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

  1. 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

  2. U.S. Conventional, Average Refiner Gasoline Prices

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

    346 1.209 1.450 1.617 1.790 1.894 1994-2016 Through Retail Outlets 1.345 1.209 1.451 1.617 1.791 1.895 1994-2016 Sales for Resale, Average 1.117 0.998 1.276 1.416 1.573 1.597 1994-2016 DTW 1.337 1.143 1.369 1.498 1.641 1.696 1994-2016 Rack 1.109 0.995 1.283 1.421 1.583 1.602 1994-2016 Bulk 1.137 0.991 1.194 1.339 1.451 1.522

  3. U.S. Reformulated, Average Refiner Gasoline Prices

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

    790 1.553 1.736 1.921 2.011 2.078 1994-2016 Through Retail Outlets 1.792 1.554 1.737 1.921 2.012 2.079 1994-2016 Sales for Resale, Average 1.331 1.143 1.463 1.601 1.694 1.740 1994-2016 DTW 1.796 1.471 1.783 1.895 1.917 1.983 1994-2016 Rack 1.221 1.066 1.388 1.533 1.645 1.690 1994-2016 Bulk 1.307 1.074 1.377 1.514 1.602 1.619

  4. Average System Cost Methodology : Administrator's Record of Decision.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1984-06-01

    Significant features of average system cost (ASC) methodology adopted are: retention of the jurisdictional approach where retail rate orders of regulartory agencies provide primary data for computing the ASC for utilities participating in the residential exchange; inclusion of transmission costs; exclusion of construction work in progress; use of a utility's weighted cost of debt securities; exclusion of income taxes; simplification of separation procedures for subsidized generation and transmission accounts from other accounts; clarification of ASC methodology rules; more generous review timetable for individual filings; phase-in of reformed methodology; and each exchanging utility must file under the new methodology within 20 days of implementation by the Federal Energy Regulatory Commission of the ten major participating utilities, the revised ASC will substantially only affect three. (PSB)

  5. Gauge and averaging in gravitational self-force

    SciTech Connect (OSTI)

    Gralla, Samuel E.

    2011-10-15

    A difficulty with previous treatments of the gravitational self-force is that an explicit formula for the force is available only in a particular gauge (Lorenz gauge), where the force in other gauges must be found through a transformation law once the Lorenz-gauge force is known. For a class of gauges satisfying a 'parity condition' ensuring that the Hamiltonian center of mass of the particle is well-defined, I show that the gravitational self-force is always given by the angle average of the bare gravitational force. To derive this result I replace the computational strategy of previous work with a new approach, wherein the form of the force is first fixed up to a gauge-invariant piece by simple manipulations, and then that piece is determined by working in a gauge designed specifically to simplify the computation. This offers significant computational savings over the Lorenz gauge, since the Hadamard expansion is avoided entirely and the metric perturbation takes a very simple form. I also show that the rest mass of the particle does not evolve due to first-order self-force effects. Finally, I consider the 'mode sum regularization' scheme for computing the self-force in black hole background spacetimes, and use the angle-average form of the force to show that the same mode-by-mode subtraction may be performed in all parity-regular gauges. It appears plausible that suitably modified versions of the Regge-Wheeler and radiation gauges (convenient to Schwarzschild and Kerr, respectively) are in this class.

  6. 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 ...

  7. 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

  8. Long-term average performance benefits of parabolic trough improvements

    SciTech Connect (OSTI)

    Gee, R.; Gaul, H.W.; Kearney, D.; Rabl, A.

    1980-03-01

    Improved parabolic trough concentrating collectors will result from better design, improved fabrication techniques, and the development and utilization of improved materials. The difficulty of achieving these improvements varies as does their potential for increasing parabolic trough performance. The purpose of this analysis is to quantify the relative merit of various technology advancements in improving the long-term average performance of parabolic trough concentrating collectors. The performance benefits of improvements are determined as a function of operating temperature for north-south, east-west, and polar mounted parabolic troughs. The results are presented graphically to allow a quick determination of the performance merits of particular improvements. Substantial annual energy gains are shown to be attainable. Of the improvements evaluated, the development of stable back-silvered glass reflective surfaces offers the largest performance gain for operating temperatures below 150/sup 0/C. Above 150/sup 0/C, the development of trough receivers that can maintain a vacuum is the most significant potential improvement. The reduction of concentrator slope errors also has a substantial performance benefit at high operating temperatures.

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

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

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

  10. High average power magnetic modulator for copper lasers

    SciTech Connect (OSTI)

    Cook, E.G.; Ball, D.G.; Birx, D.L.; Branum, J.D.; Peluso, S.E.; Langford, M.D.; Speer, R.D.; Sullivan, J.R.; Woods, P.G.

    1991-06-14

    Magnetic compression circuits show the promise of long life for operation at high average powers and high repetition rates. When the Atomic Vapor Laser Isotope Separation (AVLIS) Program at Lawrence Livermore National Laboratory needed new modulators to drive their higher power copper lasers in the Laser Demonstration Facility (LDF), existing technology using thyratron switched capacitor inversion circuits did not meet the goal for long lifetimes at the required power levels. We have demonstrated that magnetic compression circuits can achieve this goal. Improving thyratron lifetime is achieved by increasing the thyratron conduction time, thereby reducing the effect of cathode depletion. This paper describes a three stage magnetic modulator designed to provide a 60 kV pulse to a copper laser at a 4. 5 kHz repetition rate. This modulator operates at 34 kW input power and has exhibited MTBF of {approx}1000 hours when using thyratrons and even longer MTBFs with a series of stack of SCRs for the main switch. Within this paper, the electrical and mechanical designs for the magnetic compression circuits are discussed as are the important performance parameters of lifetime and jitter. Ancillary circuits such as the charge circuit and reset circuit are shown. 8 refs., 5 figs., 1 tab.