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Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

Do Diurnal Aerosol Changes Affect Daily Average Radiative Forcing?  

SciTech Connect (OSTI)

Strong diurnal variability of aerosol has been observed frequently for many urban/industrial regions. How this variability may alter the direct aerosol radiative forcing (DARF), however, is largely unknown. To quantify changes in the time-averaged DARF, we perform an assessment of 29 days of high temporal resolution ground-based data collected during the Two-Column Aerosol Project (TCAP) on Cape Cod, which is downwind of metropolitan areas. We demonstrate that strong diurnal changes of aerosol loading (about 20% on average) have a negligible impact on the 24-h average DARF, when daily averaged optical properties are used to find this quantity. However, when there is a sparse temporal sampling of aerosol properties, which may preclude the calculation of daily averaged optical properties, large errors (up to 100%) in the computed DARF may occur. We describe a simple way of reducing these errors, which suggests the minimal temporal sampling needed to accurately find the forcing.

Kassianov, Evgueni I.; Barnard, James C.; Pekour, Mikhail S.; Berg, Larry K.; Michalsky, Joseph J.; Lantz, K.; Hodges, G. B.

2013-06-17T23:59:59.000Z

2

Yearly-averaged daily usefulness efficiency of heliostat surfaces  

SciTech Connect (OSTI)

An analytical expression for estimating the instantaneous usefulness efficiency of a heliostat surface is obtained. A systematic procedure is then introduced to calculate the usefulness efficiency even when overlapping of blocking and shadowing on a heliostat surface exist. For possible estimation of the reflected energy from a given field, the local yearly-averaged daily usefulness efficiency is calculated. This efficiency is found to depend on site latitude angle, radial distance from the tower measured in tower heights, heliostat position azimuth angle and the radial spacing between heliostats. Charts for the local yearly-averaged daily usefulness efficiency are presented for {phi} = 0, 15, 30, and 45 N. These charts can be used in calculating the reflected radiation from a given cell. Utilization of these charts is demonstrated.

Elsayed, M.M.; Habeebuallah, M.B.; Al-Rabghi, O.M. (King Abdulaziz Univ., Jeddah (Saudi Arabia))

1992-08-01T23:59:59.000Z

3

E-Print Network 3.0 - annual average daily traffic Sample Search...  

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

Data Systems 2000. Annual Average Daily Truck Traffic on the California State... Lockout and Non-Lockout Weekdays Average Daily Traffic Volume (vehday) All Cars Trucks ......

4

E-Print Network 3.0 - average daily traffic Sample Search Results  

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

Data Systems 2000. Annual Average Daily Truck Traffic on the California State... Lockout and Non-Lockout Weekdays Average Daily Traffic Volume (vehday) All Cars Trucks...

5

IEP - Water-Energy Interface: Total Maximum Daily Load Page  

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

Total Maximum Daily Loads (TMDLs) Total Maximum Daily Loads (TMDLs) The overall goal of the Clean Water Act is to "restore and maintain the chemical, physical, and biological integrity of the Nation’s waters." In 1999, EPA proposed changes to Section 303(d), to establish Total Maximum Daily Loads (TMDLs) for watersheds that do not meet this goal. The TMDL is the highest amount of a given pollutant that is permissible in that body of water over a given period of time. TMDLs include both waste load allocation (WLA) for point sources and load allocations for non-point sources. In Appalachia, acid mine drainage (AMD) is the single most damaging non-point source. There is also particular concern of the atmospheric deposition of airborne sulfur, nitrogen, and mercury compounds. States are currently in the process of developing comprehensive lists of impaired waters and establishing TMDLs for those waters. EPA has recently proposed a final rule that will require states to develop TMDLs and implement plans for improving water quality within the next 10 years. Under the new rule, TMDL credits could be traded within a watershed.

6

Combined Total Amount of Oil and Gas Recovered Daily from the...  

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

XLS Combined Total Amount of Oil and Gas Recovered Daily from the Top Hat and Choke Line oil recovery systems - XLS Updated through 12:00 AM on July 16, 2010. 52Item84Recovery...

7

Combined Total Amount of Oil and Gas Recovered Daily from the...  

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

ODS format Combined Total Amount of Oil and Gas Recovered Daily from the Top Hat and Choke Line oil recovery systems - ODS format Updated through 12:00 AM on July 16, 2010....

8

"2012 Total Electric Industry- Average Retail Price (cents/kWh)"  

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

Average Retail Price (cents/kWh)" Average Retail Price (cents/kWh)" "(Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",15.713593,13.679941,11.83487,6.6759453,14.017926 "Connecticut",17.343298,14.652335,12.672933,9.6930118,15.54464 "Maine",14.658797,11.52742,7.9819499,".",11.812709 "Massachusetts",14.912724,13.841518,12.566635,4.9056852,13.78825 "New Hampshire",16.070168,13.36121,11.83228,".",14.192854 "Rhode Island",14.404061,11.867247,10.676724,8.2796427,12.740867 "Vermont",17.006075,14.316157,9.9796777,".",14.220244

9

Spatial and Quantitative Approach to Incorporating Stakeholder Values into Total Maximum Daily Loads: Dominguez Channel Case Study  

SciTech Connect (OSTI)

The Federal Clean Water Act (CWA) Section 303(d)(1)(A) requires each state to identify those waters that are not achieving water quality standards. The result of this assessment is called the 303(d) list. The CWA also requires states to develop and implement Total Maximum Daily Loads (TMDLs) for these waters on the 303(d) list. A TMDL specifies the maximum amount of a pollutant that a water body can receive and still meet water quality standards, and allocates the pollutant loadings to point and non-point sources. Nationwide, over 34,900 segments of waterways have been listed as impaired by the Environmental Protection Agency (EPA 2006). The EPA enlists state agencies and local communities to submit TMDL plans to reduce discharges by specified dates or have them developed by the EPA. The Department of Energy requested Lawrence Livermore National Laboratory (LLNL) to develop appropriate tools to assist in improving the TMDL process. An investigation of this process by LLNL found that plans to reduce discharges were being developed based on a wide range of site investigation methods. Our investigation found that given the resources available to the interested and responsible parties, developing a quantitative stakeholder input process and using visualization tools to display quantitative information could improve the acceptability of TMDL plans. We developed a stakeholder allocation model (SAM) which uses multi-attribute utility theory to quantitatively structure the preferences of the major stakeholder groups. We then applied GIS to display allocation options in maps representing economic activity, community groups, and city agencies. This allows allocation options and stakeholder concerns to be represented in both space and time. The primary goal of this tool is to provide a quantitative and visual display of stakeholder concerns over possible TMDL options.

Stewart, J S; Baginski, T A; Greene, K G; Smith, A; Sicherman, A

2006-06-23T23:59:59.000Z

10

5Calculating Total Radiation Dosages at Mars The NASA, Mars Radiation Environment Experiment (MARIE) measured the daily  

E-Print Network [OSTI]

Radiation for astronauts orbiting Mars. The biggest uncertainty is in the SPE dose estimate. We had important than GCRs as a source of radiation? Explain why or why not in terms of estimation uncertainties5Calculating Total Radiation Dosages at Mars The NASA, Mars Radiation Environment Experiment (MARIE

11

Total  

Gasoline and Diesel Fuel Update (EIA)

Total Total .............. 16,164,874 5,967,376 22,132,249 2,972,552 280,370 167,519 18,711,808 1993 Total .............. 16,691,139 6,034,504 22,725,642 3,103,014 413,971 226,743 18,981,915 1994 Total .............. 17,351,060 6,229,645 23,580,706 3,230,667 412,178 228,336 19,709,525 1995 Total .............. 17,282,032 6,461,596 23,743,628 3,565,023 388,392 283,739 19,506,474 1996 Total .............. 17,680,777 6,370,888 24,051,665 3,510,330 518,425 272,117 19,750,793 Alabama Total......... 570,907 11,394 582,301 22,601 27,006 1,853 530,841 Onshore ................ 209,839 11,394 221,233 22,601 16,762 1,593 180,277 State Offshore....... 209,013 0 209,013 0 10,244 260 198,509 Federal Offshore... 152,055 0 152,055 0 0 0 152,055 Alaska Total ............ 183,747 3,189,837 3,373,584 2,885,686 0 7,070 480,828 Onshore ................ 64,751 3,182,782

12

Total............................................................  

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

Total................................................................... Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546

13

Total...................  

Gasoline and Diesel Fuel Update (EIA)

4,690,065 52,331,397 2,802,751 4,409,699 7,526,898 209,616 1993 Total................... 4,956,445 52,535,411 2,861,569 4,464,906 7,981,433 209,666 1994 Total................... 4,847,702 53,392,557 2,895,013 4,533,905 8,167,033 202,940 1995 Total................... 4,850,318 54,322,179 3,031,077 4,636,500 8,579,585 209,398 1996 Total................... 5,241,414 55,263,673 3,158,244 4,720,227 8,870,422 206,049 Alabama ...................... 56,522 766,322 29,000 62,064 201,414 2,512 Alaska.......................... 16,179 81,348 27,315 12,732 75,616 202 Arizona ........................ 27,709 689,597 28,987 49,693 26,979 534 Arkansas ..................... 46,289 539,952 31,006 67,293 141,300 1,488 California ..................... 473,310 8,969,308 235,068 408,294 693,539 36,613 Colorado...................... 110,924 1,147,743

14

Total..........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1 2.8 2.4 2,500 to 2,999..................................................... 10.3 3.7 1.8 2.8 2.1 3,000 to 3,499..................................................... 6.7 2.0 1.4 1.7 1.6 3,500 to 3,999..................................................... 5.2 1.6 0.8 1.5 1.4 4,000 or More.....................................................

15

Total..........................................................................  

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

0.7 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 1.3 2,500 to 2,999..................................................... 10.3 3.0 1.8 0.5 0.7 3,000 to 3,499..................................................... 6.7 2.1 1.2 0.5 0.4 3,500 to 3,999..................................................... 5.2 1.5 0.8 0.3 0.4 4,000 or More.....................................................

16

Total..........................................................................  

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

25.6 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 2.6 2,500 to 2,999..................................................... 10.3 2.2 2.7 3.0 2.4 3,000 to 3,499..................................................... 6.7 1.6 2.1 2.1 0.9 3,500 to 3,999..................................................... 5.2 1.1 1.7 1.5 0.9 4,000 or More.....................................................

17

Total..........................................................................  

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

4.2 4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to 2,999..................................................... 10.3 2.4 0.9 1.4 3,000 to 3,499..................................................... 6.7 0.9 0.3 0.6 3,500 to 3,999..................................................... 5.2 0.9 0.4 0.5 4,000 or More.....................................................

18

Total.........................................................................  

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

Floorspace (Square Feet) 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 2,500 to 2,999.................................................... 10.3 1.5 2.3 2.7 2.1 1.7 3,000 to 3,499.................................................... 6.7 1.0 2.0 1.7 1.0 1.0 3,500 to 3,999.................................................... 5.2 0.8 1.5 1.5 0.7 0.7 4,000 or More.....................................................

19

Total..........................................................................  

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

. . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to 2,999..................................................... 10.3 2.2 1.7 0.6 3,000 to 3,499..................................................... 6.7 1.6 1.0 0.6 3,500 to 3,999..................................................... 5.2 1.1 0.9 0.3 4,000 or More.....................................................

20

Total..........................................................................  

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

7.1 7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4 2,500 to 2,999..................................................... 10.3 0.5 0.5 0.4 1.1 3,000 to 3,499..................................................... 6.7 0.3 Q 0.4 0.3 3,500 to 3,999..................................................... 5.2 Q Q Q Q 4,000 or More.....................................................

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

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 0.4 2,139 1,598 Q Q Q Q 2,500 to 2,999........................................ 10.1 Q Q Q Q Q Q Q 3,000 or More......................................... 29.6 0.3 Q Q Q Q Q Q Heated Floorspace (Square Feet) None...................................................... 3.6 1.8 1,048 0 Q 827 0 407 Fewer than 500......................................

22

Total...................................................................  

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

2,033 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546 3,500 to 3,999................................................. 5.2 3,549 2,509 1,508

23

Total...........................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8 2,500 to 2,999..................................... 10.3 1.2 2.2 2.3 1.7 2.9 0.6 2.0 3,000 to 3,499..................................... 6.7 0.9 1.4 1.5 1.0 1.9 0.4 1.4 3,500 to 3,999..................................... 5.2 0.8 1.2 1.0 0.8 1.5 0.4 1.3 4,000 or More...................................... 13.3 0.9 1.9 2.2 2.0 6.4 0.6 1.9 Heated Floorspace

24

Total...........................................................  

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

14.7 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 1.8 1.4 2.2 2.1 1.6 0.8 2,500 to 2,999..................................... 10.3 1.6 0.9 1.1 1.1 1.5 1.5 1.7 0.8 3,000 to 3,499..................................... 6.7 1.0 0.5 0.8 0.8 1.2 0.8 0.9 0.8 3,500 to 3,999..................................... 5.2 1.1 0.3 0.7 0.7 0.4 0.5 1.0 0.5 4,000 or More...................................... 13.3

25

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 2,499.............................. 12.2 11.9 2,039 1,731 1,055 2,143 1,813 1,152 Q Q Q 2,500 to 2,999.............................. 10.3 10.1 2,519 2,004 1,357 2,492 2,103 1,096 Q Q Q 3,000 or 3,499.............................. 6.7 6.6 3,014 2,175 1,438 3,047 2,079 1,108 N N N 3,500 to 3,999.............................. 5.2 5.1 3,549 2,505 1,518 Q Q Q N N N 4,000 or More...............................

26

Solar: monthly and annual average direct normal (DNI), global horizontal  

Open Energy Info (EERE)

South America from NREL South America from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

27

Solar: monthly and annual average direct normal (DNI), global horizontal  

Open Energy Info (EERE)

Central America and the Carribean from NREL Central America and the Carribean from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

28

Solar: monthly and annual average direct normal (DNI), global horizontal  

Open Energy Info (EERE)

East Asia from NREL East Asia from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

29

Solar: monthly and annual average direct normal (DNI), global horizontal  

Open Energy Info (EERE)

Africa from NREL Africa from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

30

DOE Average Results  

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

DOE DOE Average Results FY 12 DOE Target FY 12 Customer Perspective: Customer Satisfaction: -Timeliness 92 88 -Quality 94 92 Effective Service Partnership: -Extent of Customer Satisfaction with the responsiveness, etc. 90 92 Internal Business Perspective: Acquisition Excellence: -Extent to which internal quality control systems are effective 90 88 Most Effective Use of Contracting Approaches to Maximize Efficiency and Cost Effectiveness: Use of Competition: -% of total $'s obligated on competitive acquisitions >$3000 (Agency Level Only) 94 85 -% of acquisition actions competed for actions > $3000 (Agency Level Only) 65 68 Performance Based Acquisition: - % PBA actions relative to total eligible new acquisition actions (applicable to new actions > $25K) 82

31

Background: Long-Term Daily and Monthly Climate Records from Stations  

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

Background: Long-Term Daily and Monthly Climate Records from Stations Background: Long-Term Daily and Monthly Climate Records from Stations Across the Contiguous United States The United States Historical Climatology Network (USHCN) is a high-quality data set of daily and monthly records of basic meteorological variables from 1218 observing stations across the 48 contiguous United States. Daily data include observations of maximum and minimum temperature, precipitation amount, snowfall amount, and snow depth; monthly data consist of monthly-averaged maximum, minimum, and mean temperature and total monthly precipitation. Most of these stations are U.S. Cooperative Observing Network stations located generally in rural locations, while some are National Weather Service First-Order stations that are often located in more urbanized environments. The USHCN has been developed over the years at

32

Climate Reference Network Daily01 Product | Data.gov  

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

Daily01 Product Daily01 Product Agriculture Community Menu DATA APPS EVENTS DEVELOPER STATISTICS COLLABORATE ABOUT Agriculture You are here Data.gov » Communities » Agriculture » Data Climate Reference Network Daily01 Product Dataset Summary Description The U.S. Climate Reference Network is designed specifically to monitor national climate change with best scientific practice and adherence to the accepted principles of climate observations. USCRN daily temperature mean, maximum, and minimum, daily precipitation, daily global solar radiation, and daily average surface infrared temperature data are available in the Daily01 file set for all stations in the network. Daily mean, maximum, and minimum relative humidity are available for most stations. Tags {"Climate Reference Network",USCRN,CRN,"air temperature",temperature,precipitation,"global solar radiation"," surface temperature","surface infrared temperature","relative humidity","natural resources",water,air,"soil "}

33

Solar: monthly and annual average direct normal (DNI) GIS data at 40km  

Open Energy Info (EERE)

22 22 Varnish cache server Solar: monthly and annual average direct normal (DNI) GIS data at 40km resolution for Mexico, Central America, and the Caribbean Islands from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for 2-axis tracking concentrating collectors for Mexico, Central America, and the Caribbean Islands. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a concentrating collector, such as a dish collector, which tracks the sun continuously. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is

34

Solar: monthly and annual average direct normal (DNI) GIS data at 40km  

Open Energy Info (EERE)

49031 49031 Varnish cache server Solar: monthly and annual average direct normal (DNI) GIS data at 40km resolution for China from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for 2-axis tracking concentrating collectors for China. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a concentrating collector, such as a dish collector, which tracks the sun continuously. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to

35

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...

36

Acceptable Daily Intake (ADI)  

Science Journals Connector (OSTI)

Abstract The acceptable daily intake (ADI) is commonly defined as the maximum amount of a chemical to which a person can be exposed, on a daily basis over an extended period of time, usually without suffering a deleterious effect. It represents a daily intake level of a chemical in humans that is associated with minimal or no risk of adverse effects, and if the ingestion exceeds, this amount may cause toxic effects. It is a numerical estimate of daily oral exposure to the human population, including sensitive subgroups such as children, that is not likely to cause harmful effects during a lifetime. The ADI is expressed in milligrams of the chemical, as it appears in the food, per kilogram of body weight per day (mgkg?1day?1).

J. Chilakapati; H.M. Mehendale

2014-01-01T23:59:59.000Z

37

Solar: monthly and annual average global horizontal (GHI) GIS data at 40km  

Open Energy Info (EERE)

China from NREL China from NREL Dataset Summary Description (Abstract): Monthly average solar resource for horizontal flat-plate collectors for China. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented horizontally. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

38

Solar: monthly and annual average latitude tilt GIS data at 40km resolution  

Open Energy Info (EERE)

China from NREL China from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for flat-plate collectors tilted at latitude for China. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented due south at an angle from horizontal equal to the latitude of the collector location. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations

39

Solar: monthly and annual average global horizontal (GHI) GIS data at 40km  

Open Energy Info (EERE)

Mexico, Central America, and the Caribbean Islands from NREL Mexico, Central America, and the Caribbean Islands from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal flat-plate collectors, for Mexico, Central America, and the Caribbean Islands. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented horizontally. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate

40

Solar: annual average global horizontal (GHI) GIS data at 10km resolution  

Open Energy Info (EERE)

global horizontal (GHI) GIS data at 10km resolution global horizontal (GHI) GIS data at 10km resolution for Cuba from SUNY Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal flat-plate solar collectors for Cuba (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a horizontal flat-plate solar collector, such as a Photovoltaic (PV) solar panel. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 10 km by 10 km in size. The solar resource value is represented as kilowatt-hours per square meter per day for each month. The data were developed from the State University of New York's (SUNY) GOES satellite solar model. This model uses information on hourly satellite observed visible irradiance, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total of the normal or beam insolation falling on a tracking concentrator pointed

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Solar: monthly and annual average global horizontal (GHI) GIS data at 40km  

Open Energy Info (EERE)

Ethiopia from NREL Ethiopia from NREL Dataset Summary Description (Abstract): Monthly average solar resource for horizontal flat-plate collectors for Ethiopia. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented horizontally. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the

42

Solar: monthly and annual average latitude tilt GIS data at 40km resolution  

Open Energy Info (EERE)

Ghana from NREL Ghana from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for flat-plate collectors tilted at latitude for Ghana. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented horizontally. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to

43

Solar: monthly and annual average direct normal (DNI) GIS data at 40km  

Open Energy Info (EERE)

Ethiopia from NREL Ethiopia from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for 2-axis tracking concentrating collectors for Ethiopia. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a concentrating collector, such as a dish collector, which tracks the sun continuously. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

44

Solar: monthly and annual average global horizontal (GHI) GIS data at 40km  

Open Energy Info (EERE)

Nepal from NREL Nepal from NREL Dataset Summary Description (Abstract): Monthly average solar resource for horizontal flat-plate collectors for Nepal. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented horizontally. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

45

Solar: monthly and annual average direct normal (DNI) GIS data at 40km  

Open Energy Info (EERE)

Ghana from NREL Ghana from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for 2-axis tracking concentrating collectors for Ghana. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a concentrating collector, such as a dish collector, which tracks the sun continuously. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

46

Solar: monthly and annual average latitude tilt GIS data at 40km resolution  

Open Energy Info (EERE)

Mexico, Central America, and the Caribbean Islands from NREL Mexico, Central America, and the Caribbean Islands from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for flat-plate collectors tilted at latitude, for Mexico, Central America, and the Caribbean Islands. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented due south at an angle from horizontal equal to the latitude of the collector location. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The

47

Solar: monthly and annual average global horizontal (GHI) GIS data at 40km  

Open Energy Info (EERE)

Ghana from NREL Ghana from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal flat-plate collectors for Ghana. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented horizontally. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

48

Solar: monthly and annual average direct normal (DNI) GIS data at 40km  

Open Energy Info (EERE)

Brazil from NREL Brazil from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for 2-axis tracking concentrating collectors for Brazil. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a concentrating collector, such as a dish collector, which tracks the sun continuously. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

49

Solar: annual average direct normal (DNI) GIS data at 10km resolution for  

Open Energy Info (EERE)

GIS data at 10km resolution for GIS data at 10km resolution for Cuba from SUNY Dataset Summary Description (Abstract): Monthly Average Solar Resource for 2-axis tracking concentrating collectors for Cuba (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a concentrating collector, such as a dish collector, which tracks the sun continuously. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 10 km by 10 km in size. The solar resource value is represented as kilowatt-hours per square meter per day for each month. The data were developed from the State University of New York's (SUNY) GOES satellite solar model. This

50

Solar: monthly and annual average global horizontal (GHI) GIS data at 40km  

Open Energy Info (EERE)

Brazil from NREL Brazil from NREL Dataset Summary Description (Abstract): Monthly average solar resource for horizontal flat-plate collectors for Brazil. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented horizontally. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

51

Solar: monthly and annual average direct normal (DNI) GIS data at 40km for  

Open Energy Info (EERE)

km for km for Sri Lanka from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for 2-axis tracking concentrating collectors for Sri Lanka (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a concentrating collector, such as a dish collector, which tracks the sun continuously. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

52

Solar: monthly and annual average direct normal (DNI) GIS data at 40km  

Open Energy Info (EERE)

Kenya from NREL Kenya from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for 2-axis tracking concentrating collectors for Kenya. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a concentrating collector, such as a dish collector, which tracks the sun continuously. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

53

Solar: monthly and annual average direct normal (DNI) GIS data at 40km  

Open Energy Info (EERE)

Nepal from NREL Nepal from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for 2-axis tracking concentrating collectors for Nepal. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a concentrating collector, such as a dish collector, which tracks the sun continuously. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

54

Solar: monthly and annual average global horizontal (GHI) GIS data at 40km  

Open Energy Info (EERE)

Kenya from NREL Kenya from NREL Dataset Summary Description (Abstract): Monthly average solar resource for horizontal flat-plate collectors for Kenya. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented horizontally. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

55

Solar: monthly and annual average global horizontal (GHI) GIS data at 40km  

Open Energy Info (EERE)

Sri Lanka from NREL Sri Lanka from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal flat-plate collectors, for Sri Lanka (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented horizontally. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

56

Daily Temperature Lag  

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

Daily Temperature Lag Daily Temperature Lag Name: Shyammayi Status: teacher Grade: K-2 Country: Mauritius Date: Summer 2011 Question: At what time of the day is the temperature hottest? At what time of the day is the temperature coldest? Replies: In general, the hottest part of the day is late afternoon. The sun has passed its peak in the sky but still heats the Earth up until very late in the afternoon. The lowest temperatures are around dawn. Earth has had all night to get rid of the day's heat by radiating it into space. After sunrise, temperatures begin to climb. This can be changed by local storms, sea breezes or mountain breezes and even monsoon winds. Hope this helps. R. W. "Bob" Avakian Instructor Arts and Sciences/CRC Oklahoma State Univ. Inst. of Technology Shyammayi

57

Unimodular Gravity and Averaging  

E-Print Network [OSTI]

The question of the averaging of inhomogeneous spacetimes in cosmology is important for the correct interpretation of cosmological data. In this paper we suggest a conceptually simpler approach to averaging in cosmology based on the averaging of scalars within unimodular gravity. As an illustration, we consider the example of an exact spherically symmetric dust model, and show that within this approach averaging introduces correlations (corrections) to the effective dynamical evolution equation in the form of a spatial curvature term.

A. Coley; J. Brannlund; J. Latta

2011-02-16T23:59:59.000Z

58

HFAG Charm Mixing Averages  

E-Print Network [OSTI]

Recently the first evidence for charm mixing has been reported by several experiments. To provide averages of these mixing results and other charm results, a new subgroup of the Heavy Flavor Averaging Group has been formed. We here report on the method and results of averaging the charm mixing results.

B. Aa. Petersen

2007-12-10T23:59:59.000Z

59

Core Measure Average KTR Results  

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

Measure Measure Average KTR Results FY 12 Target FY 12 DOE M&O CONTRACTOR (KTR) BSC RESULTS FY 2012 Customer Perspective and level of communication provided by the procurement office 95 92 Internal Business Perspective: Assessment (%) of the degree to which the purchasing system is in compliance with stakeholder requirements 97 Local Goals % Delivery on-time (includes JIT, excludes Purchase Cards) 88 84 % of total dollars obligated, on actions > $150K , that were awarded using effective competition 73 Local Goals Rapid Purchasing Techniques: -% of transactions placed by users 77 Local Goals -% of transactions placed through electronic commerce 62 Local Goals Average Cycle Time: -Average cycle time for <= $150K 8 6 to 9 days

60

Magnetic Properties of Daily Sampled Total Suspended Particulates in Shanghai  

Science Journals Connector (OSTI)

Acquisition of isothermal remanent magnetization (IRM 10-5 Am2 kg-1) was made in fields of 20 mT, 30 mT, 1 T (SIRM) followed by demagnetiza tion in fields of ?20 mT, ?50 mT, ?100 mT, and ?300 mT using a Molspin pulse magnetizer and spinner magnetometer. ...

Jiong Shu; John A. Dearing; Andrew P. Morse; Lizhong Yu; Chaoyi Li

2000-05-09T23:59:59.000Z

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Bacteria Total Maximum Daily Load Task Force Final Report  

E-Print Network [OSTI]

Research and Development Needs 51 References 64 Appendix 1: Bacteria TMDL Task Force Members and Expert Advisors 71 Appendix 2: Models Used in Bacteria Projects 73 as Described in EPA Publications... Appendix 3: EPA Bacteria TMDL Guidelines 78 Appendix 4: State Approaches to Bacteria TMDL 88 Development Appendix 5: Comments from Expert Advisory Group 100 1 Executive Summary In September 2006, the Texas...

Jones, C. Allan; Wagner, Kevin; Di Giovanni, George; Hauck, Larry; Mott, Joanna; Rifai, Hanadi; Srinivasan, Raghavan; Ward, George; Wythe, Kathy

62

Yesterday's Daily Summary - Hanford Site  

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

Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met Data Met and Climate Data Summary Products Historical Weather Charts Contacts...

63

Daily Normal Precipitation - Hanford Site  

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

Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met Data Met and Climate Data Summary Products Historical Weather Charts Contacts...

64

average | OpenEI  

Open Energy Info (EERE)

average average Dataset Summary Description This dataset is part of a larger internal dataset at the National Renewable Energy Laboratory (NREL) that explores various characteristics of large solar electric (both PV and CSP) facilities around the United States. This dataset focuses on the land use characteristics for solar facilities that are either under construction or currently in operation. Source Land-Use Requirements for Solar Power Plants in the United States Date Released June 25th, 2013 (7 months ago) Date Updated Unknown Keywords acres area average concentrating solar power csp Density electric hectares km2 land land requirements land use land-use mean photovoltaic photovoltaics PV solar statistics Data application/vnd.openxmlformats-officedocument.spreadsheetml.sheet icon Master Solar Land Use Spreadsheet (xlsx, 1.5 MiB)

65

Variable Average Absolute Percent Differences  

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

Variable Variable Average Absolute Percent Differences Percent of Projections Over- Estimated Gross Domestic Product Real Gross Domestic Product (Average Cumulative Growth)* (Table 2) 1.0 42.6 Petroleum Imported Refiner Acquisition Cost of Crude Oil (Constant $) (Table 3a) 35.2 18.6 Imported Refiner Acquisition Cost of Crude Oil (Nominal $) (Table 3b) 34.7 19.7 Total Petroleum Consumption (Table 4) 6.2 66.5 Crude Oil Production (Table 5) 6.0 59.6 Petroleum Net Imports (Table 6) 13.3 67.0 Natural Gas Natural Gas Wellhead Prices (Constant $) (Table 7a) 30.7 26.1 Natural Gas Wellhead Prices (Nominal $) (Table 7b) 30.0 27.1 Total Natural Gas Consumption (Table 8) 7.8 70.2 Natural Gas Production (Table 9) 7.1 66.0 Natural Gas Net Imports (Table 10) 29.3 69.7 Coal Coal Prices to Electric Generating Plants (Constant $)** (Table 11a)

66

Seasonal Average Temperature - Hanford Site  

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

Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met Data Met and Climate Data Summary Products Historical Weather Charts Contacts...

67

Unravelling daily human mobility motifs  

E-Print Network [OSTI]

Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for ...

Schneider, Christian M.

68

Americans' Average Radiation Exposure  

SciTech Connect (OSTI)

We live with radiation every day. We receive radiation exposures from cosmic rays, from outer space, from radon gas, and from other naturally radioactive elements in the earth. This is called natural background radiation. It includes the radiation we get from plants, animals, and from our own bodies. We also are exposed to man-made sources of radiation, including medical and dental treatments, television sets and emission from coal-fired power plants. Generally, radiation exposures from man-made sources are only a fraction of those received from natural sources. One exception is high exposures used by doctors to treat cancer patients. Each year in the United States, the average dose to people from natural and man-made radiation sources is about 360 millirem. A millirem is an extremely tiny amount of energy absorbed by tissues in the body.

NA

2000-08-11T23:59:59.000Z

69

Average Commercial Price  

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

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

70

Average Commercial Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

71

Average Residential Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

72

Average Residential Price  

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

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

73

Average Residential Price  

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

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

74

Average Residential Price  

Gasoline and Diesel Fuel Update (EIA)

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

75

Average Commercial Price  

Gasoline and Diesel Fuel Update (EIA)

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

76

Using Utility Bills and Average Daily Energy Consumption to Target Commissioning Efforts and Track Building Performance  

E-Print Network [OSTI]

energy. This sort of analysis can be done using relatively simple techniques such as a hand calculation or a spreadsheet and is the type of thing that any facility engineer or operator could handle and would be interested in. Techniques are also discussed...

Sellers, D.

2001-01-01T23:59:59.000Z

77

E-Print Network 3.0 - average daily global Sample Search Results  

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

Dunlop E.D., Albuisson M., Wald L, 2006. Online data and tools for estimation of solar electricity in Africa: the PVGIS approach. Proceedings from 21st Summary: . Long-term...

78

Energy Assurance Daily | Department of Energy  

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

Energy Assurance Daily 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 Security and Energy Restoration (ISER) Division cannot guarantee the accuracy of the material in the Energy Assurance Daily. Any further use is subject to the copyright restrictions of the source document. The Energy Assurance Daily has workable hypertext links to the

79

Average Interest Rate for Treasury Securities | Data.gov  

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

Average Interest Rate for Treasury Securities Average Interest Rate for Treasury Securities Consumer Data Apps Challenges Resources About Blogs Let's Talk Feedback Consumer You are here Data.gov » Communities » Consumer » Data Average Interest Rate for Treasury Securities Dataset Summary Description This dataset shows the average interest rates for U.S Treasury securities for the most recent month compared with the same month of the previous year. The data is broken down by the various marketable and non-marketable securities. The summary page for the data provides links for monthly reports from 2001 through the current year. Average Interest Rates are calculated on the total unmatured interest-bearing debt. The average interest rates for total marketable, total non-marketable and total interest-bearing debt do not include the U.S. Treasury Inflation-Protected Securities.

80

Viscosity-average molecular weight  

Science Journals Connector (OSTI)

n .... An averaged molecular weight for high polymers that relates most closely to measurements of dilute-solution viscosities ...

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Generating Multiyear Gridded Daily Rainfall over New Zealand  

Science Journals Connector (OSTI)

Daily rainfall totals are a key input for hydrological models that are designed to simulate water and pollutant flow through both soil and waterways. Within New Zealand there are large areas and many river catchments where no long-term rainfall ...

Andrew Tait; Richard Turner

2005-09-01T23:59:59.000Z

82

TOTAL Full-TOTAL Full-  

E-Print Network [OSTI]

Conducting - Orchestral 6 . . 6 5 1 . 6 5 . . 5 Conducting - Wind Ensemble 3 . . 3 2 . . 2 . 1 . 1 Early- X TOTAL Full- Part- X TOTAL Alternative Energy 6 . . 6 11 . . 11 13 2 . 15 Biomedical Engineering 52 English 71 . 4 75 70 . 4 74 72 . 3 75 Geosciences 9 . 1 10 15 . . 15 19 . . 19 History 37 1 2 40 28 3 3 34

Portman, Douglas

83

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 & Ed55 Imports - Other Conventional Gasoline Imports - Motor Gasoline Blend. Components Imports - Motor Gasoline Blend. Components, RBOB Imports - Motor Gasoline Blend. Components, RBOB w/ Ether Imports - Motor Gasoline Blend. Components, RBOB w/ Alcohol Imports - Motor Gasoline Blend. Components, CBOB Imports - Motor Gasoline Blend. Components, GTAB Imports - Motor Gasoline Blend. Components, Other Imports - Fuel Ethanol Imports - Kerosene-Type Jet Fuel Imports - Distillate Fuel Oil Imports - Distillate F.O., 15 ppm Sulfur and Under Imports - Distillate F.O., > 15 ppm to 500 ppm Sulfur Imports - Distillate F.O., > 500 ppm to 2000 ppm Sulfur Imports - Distillate F.O., > 2000 ppm Sulfur Imports - Residual Fuel Oil Imports - Propane/Propylene Imports - Other Other Oils Imports - Kerosene Imports - NGPLs/LRGs (Excluding Propane/Propylene) Exports - Total Crude Oil and Products Exports - Crude Oil Exports - Products Exports - Finished Motor Gasoline Exports - Kerosene-Type Jet Fuel Exports - Distillate Fuel Oil Exports - Residual Fuel Oil Exports - Propane/Propylene Exports - Other Oils Net Imports - Total Crude Oil and Products Net Imports - Crude Oil Net Imports - Petroleum Products Period: Weekly 4-Week Avg.

84

Developing hourly weather data for locations having only daily weather data  

SciTech Connect (OSTI)

A methodology was developed to modify an hourly TMY weather tape to be representative of a location for which only average daily weather parameters were avilable. Typical hourly and daily variations in solar flux, and other parameters, were needed to properly exercise a computer model to predict the transient performance of a solar controlled greenhouse being designed for Riyadh, Saudi Arabia. The starting point was a TMY tape for Yuma, Arizona, since the design temperatures for summer and winter are nearly identical for Yuma and Riyadh. After comparing six of the most important weather variables, the hourly values on the Yuma tape were individually adjusted to give the same overall daily average conditions as existed in the long-term Riyadh data. Finally, a statistical analysis was used to confirm quantitatively that the daily variations between the long term average values for Riyadh and the modified TMY weather tape for Yuma matched satisfactorily.

Talbert, S.G.; Herold, K.E.; Jakob, F.E.; Lundstrom, D.K.

1983-06-01T23:59:59.000Z

85

Solar: annual average direct normal (DNI) map at 40km resolution for  

Open Energy Info (EERE)

map at 40km resolution for map at 40km resolution for Central America from NREL Dataset Summary Description (Abstract): A map depicting model estimates of monthly average daily total radiation using inputs derived from satellite and surface observations of cloud cover, aerosol optical depth, precipitable water vapor, albedo, atmospheric pressure and ozone sampled at a 40km resolution. (Purpose): A visual depiction of solar energy resource for concentrating solar power systems. Source NREL Date Released December 11th, 2003 (11 years ago) Date Updated October 30th, 2007 (7 years ago) Keywords Central America direct normal DNI map NREL solar SWERA UNEP Data application/pdf icon Download Map (pdf, 67.1 KiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency

86

Averaging Hypotheses in Newtonian Cosmology  

E-Print Network [OSTI]

Average properties of general inhomogeneous cosmological models are discussed in the Newtonian framework. It is shown under which circumstances the average flow reduces to a member of the standard Friedmann--Lema\\^\\i tre cosmologies. Possible choices of global boundary conditions of inhomogeneous cosmologies as well as consequences for the interpretation of cosmological parameters are put into perspective.

T. Buchert

1995-12-20T23:59:59.000Z

87

annual average heating degree days | OpenEI  

Open Energy Info (EERE)

average heating degree days average heating degree days Dataset Summary Description (Abstract): Heating Degree Days below 18° C (degree days)The monthly accumulation of degrees when the daily mean temperature is below 18° C.NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly Average & Annual Sum (July 1983 - June 2005)Parameter: Heating Degree Days Below 18 degrees C (degree days)Internet: http://eosweb.larc.nasa.gov/sse/ Source U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE) Date Released March 31st, 2009 (5 years ago) Date Updated April 01st, 2009 (5 years ago) Keywords annual average heating degree days climate GIS NASA SWERA UNEP Data application/zip icon Download Shapefile (zip, 2.7 MiB)

88

State Residential Commercial Industrial Transportation Total  

Gasoline and Diesel Fuel Update (EIA)

schedules 4A-D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total 2012 Total Electric Industry- Average Retail Price (centskWh) (Data from...

89

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,...

90

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,...

91

Energy Assurance Daily (EAD): May 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,...

92

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,...

93

Energy Assurance Daily (EAD): January- March 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,...

94

West Texas Intermediate Spot Average ............................  

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

Crude Oil (dollars per barrel) Crude Oil (dollars per barrel) West Texas Intermediate Spot Average ............................ 102.88 93.42 92.24 87.96 94.34 94.10 105.84 96.30 95.67 95.33 95.67 93.33 94.12 97.64 95.00 Brent Spot Average ........................................................... 118.49 108.42 109.61 110.09 112.49 102.58 110.27 108.29 106.33 105.00 103.00 102.00 111.65 108.41 104.08 Imported Average .............................................................. 108.14 101.18 97.18 97.64 98.71 97.39 103.07 100.03 99.64 99.33 99.69 97.35 101.09 99.85 99.04 Refiner Average Acquisition Cost ...................................... 107.61 101.44 97.38 97.27 101.14 99.45 105.24 100.44 100.15 99.82 100.18 97.83 100.83 101.61 99.50 Liquid Fuels (cents per gallon) Refiner Prices for Resale Gasoline .........................................................................

95

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" 1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Midwest",25.9,2272,1898,1372,912,762,551 "Midwest Divisions and States" "East North Central",17.9,2251,1869,1281,892,741,508 "Illinois",4.8,2186,1911,1451,860,752,571 "Michigan",3.8,1954,1559,962,729,582,359 "Wisconsin",2.3,2605,2091,1258,1105,887,534

96

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

3 Average Square Footage of West Homes, by Housing Characteristics, 2009" 3 Average Square Footage of West Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total West",24.8,1708,1374,800,628,506,294 "West Divisions and States" "Mountain",7.9,1928,1695,1105,723,635,415 "Mountain North",3.9,2107,1858,912,776,684,336 "Colorado",1.9,2082,1832,722,896,788,311 "Idaho, Montana, Utah, Wyoming",2,2130,1883,1093,691,610,354

97

Year Average Transportation Cost of Coal  

Gasoline and Diesel Fuel Update (EIA)

delivered costs of coal, by year and primary transport mode Year Average Transportation Cost of Coal (Dollars per Ton) Average Delivered Cost of Coal (Dollars per Ton)...

98

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 HMS Observations Daily HMS Extremes...

99

Daily HMS Extremes in Met Data - Hanford Site  

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

Meteorological Station > Daily HMS Extremes in Met Data Hanford Meteorological Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met...

100

"Table HC1.2.3 Living Space Characteristics by Average Floorspace--"  

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

3 Living Space Characteristics by Average Floorspace--" 3 Living Space Characteristics by Average Floorspace--" " Single-Family Housing Units and Mobile Homes, 2005" ,,"Single- Family and Mobile Homes (millions)","Average Square Feet per Housing Unit" ," Housing Units (millions)" ,,,"Single-Family Detached",,,"Single-Family Attached",,,"Mobile Homes" "Housing Unit Characteristics",,,"Total1","Heated","Cooled","Total1","Heated","Cooled","Total1","Heated","Cooled" "Total",111.1,86.6,2522,1970,1310,1812,1475,821,1055,944,554 "Total Floorspace (Square Feet)" "Fewer than 500",3.2,0.9,261,336,162,"Q","Q","Q",334,260,"Q"

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

2011 Daily Log Report #: 2011-00168  

E-Print Network [OSTI]

2011 Daily Log March 2011 Report #: 2011-00168 Reported: 03/31/2011 1237 Occurred: 03/31/2011 1235 Incident: Medical Emergency Location: Outside of Student Union Disposition: Report--Closed Comments: Female transported to hospital by ambulance for medical treatment. Report #: 2011-00167 Reported: 03/31/2011 1116

Boyce, Richard L.

102

2009 Daily Log Report #: 2009-00202  

E-Print Network [OSTI]

2009 Daily Log March 2009 Report #: 2009-00202 Reported: 03/31/09 2045 Occurred: 03/29/09 1400 to 03/30/09 2000 Incident: Theft Location: Lot Q Disposition: Report--Open Comments: GPS System stolen from unlocked vehicle. Report #: 2009-00201 Reported: 03/31/09 1833 Occurred: Same Incident: Fire

Boyce, Richard L.

103

2009 Daily Log Report #: 2009-00269  

E-Print Network [OSTI]

2009 Daily Log April 2009 Report #: 2009-00269 Reported: 04/30/09 1508 Occurred: Same Incident: Traffic Crash Location: Johns Hill Road and Kenton Drive Disposition: Report--Closed Comments: Two vehicle accident; no injuries. Report #: 2009-00268 Reported: 04/30/09 1049 Occurred: Same Incident: Traffic Crash

Boyce, Richard L.

104

2011 Daily Log Report #: 2011-00229  

E-Print Network [OSTI]

2011 Daily Log April 2011 Report #: 2011-00229 Reported: 04/29/2011 2327 Occurred: 04/29/2011 2325 Incident: Medical Emergency Location: University Center Disposition: Report--Closed Comments: Female transported by ambulance to hospital for medical treatment. Report #: 2011-00228 Reported: 04/29/2011 1702

Boyce, Richard L.

105

2010 Daily Log Report #: 2010-00262  

E-Print Network [OSTI]

2010 Daily Log June 2010 Report #: 2010-00262 Reported: 06/30/10 0957 Occurred: 06/24/10 1630 to 0957 Incident: Theft Location: Founders Hall Disposition: Report--Open Comments: Several textbooks stolen from office. No Reportable Activity on 06/29/10 Report #: 2010-00261 Reported: 06/28/10 1720

Boyce, Richard L.

106

2009 Daily Log Report #: 2009-00327  

E-Print Network [OSTI]

2009 Daily Log June 2009 Report #: 2009-00327 Reported: 06/30/09 1118 Occurred: Same Incident: Fire/Smoke Alarm Location: Dorm--Kentucky Hall Disposition: Report--Closed Comments: Alarm activation caused by drywall dust from contractors; fire department responded and cleared the scene. No Reportable Activity

Boyce, Richard L.

107

2011 Daily Log Report #: 2011-00261  

E-Print Network [OSTI]

2011 Daily Log May 2011 Report #: 2011-00261 Reported: 05/31/2011 1300 Occurred: Same Incident: Medical Emergency Location: University Center Disposition: Report--Closed Comments: Male transported to hospital by ambulance for evaluation and treatment. No Reportable Activity on 05/30/2011 No Reportable

Boyce, Richard L.

108

2011 Daily Log Report #: 2011-00295  

E-Print Network [OSTI]

2011 Daily Log June 2011 Report #: 2011-00295 Reported: 6/30/2011 0813 Occurred: 6/29/2011 1430 Incident: Traffic Crash Location: Sidewalk on Plaza Level Disposition: Report--Closed Comments: Single vehicle accident; no injuries. Report #: 2011-00294 Reported: 06/29/2011 1909 Occurred: Same Incident

Boyce, Richard L.

109

2010 Daily Log Report #: 2010-00221  

E-Print Network [OSTI]

2010 Daily Log April 2010 Report #: 2010-00221 Reported: 04/30/10 1034 Occurred: Same Incident: Found/Recovered Property Location: Founders Hall Disposition: Report--Closed Comments: Small purse was found in classroom. Report #: 2010-00220 Reported: 04/30/10 1347 Occurred: 04/30/10 0820 to 0900

Boyce, Richard L.

110

2011 Daily Log Report #: 2011-00317  

E-Print Network [OSTI]

2011 Daily Log July 2011 Report #: 2011-00317 Reported: 07/30/2011 1446 Occurred: 07/30/2011 1435 Incident: Odor Related Complaint Location: Power Plant Disposition: Report--Closed Comments: Subject reported a strange odor emanating from somewhere in the vicinity; fire department responded and cleared

Boyce, Richard L.

111

Barge Truck Total  

Annual Energy Outlook 2013 [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...

112

DOE Solar Decathlon: 2009 Daily Journals  

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

Richard King next to a deck and planter boxes. Decathlete Way and the U.S. Capitol are in the background. Richard King next to a deck and planter boxes. Decathlete Way and the U.S. Capitol are in the background. Solar Decathlon Director Richard King takes a break from the competition along Decathlete Way. Solar Decathlon 2009 Daily Journals The daily journals highlighted the events of the U.S. Department of Energy Solar Decathlon 2009. Each day, Richard King, Solar Decathlon director, covered the latest on the teams, their standings, and the events going on in the solar village. October 19, 2009 I personally believe one of the greatest discoveries in the field of energy from the 20th century is our ability to generate electricity from sunlight using photovoltaic solar cells. Read more. October 17, 2009 Solar Decathlon 2009 was intriguing and suspenseful to the very end. None

113

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

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

Average Price of U.S. Coke Exports Average Price of U.S. Coke Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 17. Average Price of U.S. Coke Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Continent and Country of Destination April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change North America Total 240.59 241.38 218.40 240.85 225.80 6.7 Canada* 147.49 330.47 243.04 183.08 286.56 -36.1 Mexico 316.57 211.63 189.12 273.97 171.71 59.6 Other** 612.42 485.63 134.48 525.92 135.04 289.5 South America Total 140.65 156.15 322.70 148.29 250.36 -40.8 Other** 140.65 156.15 322.70 148.29 250.36 -40.8 Europe Total 259.26 255.24 - 257.06 427.83 -39.9 Other**

114

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

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

Average Price of U.S. Coke Imports Average Price of U.S. Coke Imports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 22. Average Price of U.S. Coke Imports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Continent and Country of Origin April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change North America Total 263.21 252.66 353.05 261.29 356.01 -26.6 Canada 263.51 252.66 353.05 258.82 356.01 -27.3 Panama 263.09 - - 263.09 - - South America Total 196.86 194.14 175.88 195.94 181.01 8.2 Brazil - - 157.60 - 157.60 - Colombia 196.86 194.14 322.06 195.94 246.68 -20.6 Europe Total 181.55 232.13 385.65 225.53 384.96 -41.4 Czech Republic - 475.91 - 475.91 - - Spain 360.51

115

Daily HMS Extremes in Met Data - Hanford Site  

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

Daily HMS Extremes in Met Data Hanford Meteorological Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met Data Met and Climate Data...

116

Property:SalinityAverage | Open Energy Information  

Open Energy Info (EERE)

SalinityAverage SalinityAverage Jump to: navigation, search Property Name SalinityAverage Property Type Number Description Mean average of the low and high end measurements of the salinity [ppm] of the fluid. This is a property of type Page. Subproperties This property has the following 1 subproperty: C Coso Geothermal Area Pages using the property "SalinityAverage" Showing 19 pages using this property. A Amedee Geothermal Area + 975 + B Beowawe Hot Springs Geothermal Area + 700 + Blue Mountain Geothermal Area + 4300 + Brady Hot Springs Geothermal Area + 3500 + C Chena Geothermal Area + 325 + D Desert Peak Geothermal Area + 6700 + Dixie Valley Geothermal Area + 2295 + E East Mesa Geothermal Area + 3750 + G Geysers Geothermal Area + 217 + K Kilauea East Rift Geothermal Area + 18750 +

117

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

2 Average Square Footage of South Homes, by Housing Characteristics, 2009" 2 Average Square Footage of South Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total South",42.1,1867,1637,1549,732,642,607 "South Divisions and States" "South Atlantic",22.2,1944,1687,1596,771,668,633 "Virginia",3,2227,1977,1802,855,759,692 "Georgia",3.5,2304,1983,1906,855,736,707 "Florida",7,1668,1432,1509,690,593,625 "DC, DE, MD, WV",3.4,2218,1831,1440,864,713,561

118

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

4 Average Square Footage of Single-Family Homes, by Housing Characteristics, 2009" 4 Average Square Footage of Single-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Single-Family",78.6,2422,2002,1522,880,727,553 "Census Region" "Northeast",12.7,2843,2150,1237,1009,763,439 "Midwest",19.2,2721,2249,1664,1019,842,624 "South",29.7,2232,1945,1843,828,722,684 "West",16.9,2100,1712,1009,725,591,348 "Urban and Rural3"

119

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" 0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Northeast",20.8,2121,1663,921,836,656,363 "Northeast Divisions and States" "New England",5.5,2232,1680,625,903,680,253 "Massachusetts",2.5,2076,1556,676,850,637,277 "CT, ME, NH, RI, VT",3,2360,1781,583,946,714,234 "Mid-Atlantic",15.3,2080,1657,1028,813,647,402

120

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

5 Average Square Footage of Multi-Family Homes, by Housing Characteristics, 2009" 5 Average Square Footage of Multi-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Multi-Family",28.1,930,807,535,453,393,261 "Census Region" "Northeast",7.6,991,897,408,471,426,194 "Midwest",5.6,957,857,518,521,466,282 "South",8.4,924,846,819,462,423,410 "West",6.5,843,606,329,374,269,146 "Urban and Rural3" "Urban",26.9,927,803,531,450,390,258

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

6 Average Square Footage of Mobile Homes, by Housing Characteristics, 2009" 6 Average Square Footage of Mobile Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Mobile Homes",6.9,1087,985,746,413,375,283 "Census Region" "Northeast",0.5,1030,968,711,524,492,362 "Midwest",1.1,1090,1069,595,400,392,218 "South",3.9,1128,1008,894,423,378,335 "West",1.4,995,867,466,369,322,173 "Urban and Rural3" "Urban",3.5,1002,919,684,396,364,271

122

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

9 Average Square Footage of U.S. Homes, by Housing Characteristics, 2009" 9 Average Square Footage of U.S. Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total",113.6,1971,1644,1230,766,639,478 "Census Region" "Northeast",20.8,2121,1663,921,836,656,363 "Midwest",25.9,2272,1898,1372,912,762,551 "South",42.1,1867,1637,1549,732,642,607 "West",24.8,1708,1374,800,628,506,294 "Urban and Rural3" "Urban",88.1,1857,1546,1148,728,607,450

123

Regional averaging and scaling in relativistic cosmology  

E-Print Network [OSTI]

Averaged inhomogeneous cosmologies lie at the forefront of interest, since cosmological parameters like the rate of expansion or the mass density are to be considered as volume-averaged quantities and only these can be compared with observations. For this reason the relevant parameters are intrinsically scale-dependent and one wishes to control this dependence without restricting the cosmological model by unphysical assumptions. In the latter respect we contrast our way to approach the averaging problem in relativistic cosmology with shortcomings of averaged Newtonian models. Explicitly, we investigate the scale-dependence of Eulerian volume averages of scalar functions on Riemannian three-manifolds. We propose a complementary view of a Lagrangian smoothing of (tensorial) variables as opposed to their Eulerian averaging on spatial domains. This program is realized with the help of a global Ricci deformation flow for the metric. We explain rigorously the origin of the Ricci flow which, on heuristic grounds, has already been suggested as a possible candidate for smoothing the initial data set for cosmological spacetimes. The smoothing of geometry implies a renormalization of averaged spatial variables. We discuss the results in terms of effective cosmological parameters that would be assigned to the smoothed cosmological spacetime.

Thomas Buchert; Mauro Carfora

2002-10-11T23:59:59.000Z

124

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

SciTech Connect (OSTI)

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.

Gupta, Tejpal, E-mail: tejpalgupta@rediffmail.com [Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India)] [Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India); Jalali, Rakesh [Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India)] [Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India); Goswami, Savita [Department of Clinical Psychology and Psychiatry Unit, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India)] [Department of Clinical Psychology and Psychiatry Unit, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India); Nair, Vimoj [Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India)] [Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India); Moiyadi, Aliasgar [Division of Neuro-Surgery, Department of Surgical Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India)] [Division of Neuro-Surgery, Department of Surgical Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India); Epari, Sridhar [Department of Pathology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India)] [Department of Pathology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India); Sarin, Rajiv [Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India)] [Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer and Tata Memorial Hospital, Mumbai (India)

2012-08-01T23:59:59.000Z

125

Compare All CBECS Activities: Total Energy Use  

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

Total Energy Use Total Energy Use Compare Activities by ... Total Energy Use Total Major Fuel Consumption by Building Type Commercial buildings in the U.S. used a total of approximately 5.7 quadrillion Btu of all major fuels (electricity, natural gas, fuel oil, and district steam or hot water) in 1999. Office buildings used the most total energy of all the building types, which was not a surprise since they were the most common commercial building type and had an above average energy intensity. Figure showing total major fuel consumption by building type. If you need assistance viewing this page, please call 202-586-8800. Major Fuel Consumption per Building by Building Type Because there were relatively few inpatient health care buildings and they tend to be large, energy intensive buildings, their energy consumption per building was far above that of any other building type.

126

Solar Decathlon 2005 Daily Event Schedule  

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

DAILY EVENT SCHEDULE DAILY EVENT SCHEDULE Last updated on September 30, 2005 Note: This schedule is not part of the official Rules and Regulations and is subject to change at any time. Weds, Sept 28 12:00 AM 12:30 AM 1:00 AM 1:30 AM 2:00 AM 2:30 AM 3:00 AM 3:30 AM 4:00 AM 4:30 AM 5:00 AM 5:30 AM 6:00 AM 6:30 AM 7:00 AM 7:30 AM 8:00 AM 8:30 AM 9:00 AM 9:30 AM 10:00 AM 10:30 AM 11:00 AM 11:30 AM 12:00 PM 12:30 PM 1:00 PM 1:30 PM 2:00 PM 2:30 PM 3:00 PM 3:30 PM 4:00 PM 4:30 PM 5:00 PM 5:30 PM 6:00 PM 6:30 PM 7:00 PM 7:30 PM 8:00 PM 8:30 PM 9:00 PM 9:30 PM 10:00 PM 10:30 PM 11:00 PM 11:30 PM Registration Forrestal Bldg (DOE) Cafeteria National Mall Team/Organizer meeting and Safety Orientation Thurs, Sept 29 12:00 AM 12:30 AM 1:00 AM 1:30 AM 2:00 AM 2:30 AM 3:00 AM 3:30 AM 4:00 AM 4:30 AM 5:00 AM 5:30 AM 6:00 AM 6:30 AM 7:00

127

Influence of daily feeding within a limited time on weight, digestive transit and cholesterol turnover in adult rats  

E-Print Network [OSTI]

turnover in adult rats T. MAGOT, F. CHEVALLIER Laboratoire de Physiologie de la Nutrition (*),), Université de Paris-Sud, Bâtiment 447 91405 Orsay Cedex, France. Summary. Rats were trained to a single daily the first hour. This value defined the average volumic capacity of the full stomach of our rats. Body weight

Paris-Sud XI, Université de

128

Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (  

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

Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (after 24-May 2010 06:00):" Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (after 24-May 2010 06:00):" ,,"Choke","Average","Average","Fluid","Methanol","Water","Oil","Gas","Hyd. Eq.","Gas" ,"Choke","Setting","Upstream","Upstream","Recovery","Recovery","Recovery","Recovery","Recovery","Recovery","Recovery" "Date and Time","Setting","Duration","Pressure","Temp.","Rate","Rate","Rate","Rate","Rate","Rate","Portion" "dd-mmm-yy","(64ths)","(hours)","(psia)","(degF)","(bfpd)","(bfpd)","(bwpd)","(bopd)","(mmcfpd)","(boepd)","(%)"

129

Variations of Total Domination  

Science Journals Connector (OSTI)

The study of locatingdominating sets in graphs was pioneered by Slater[186, 187...], and this concept was later extended to total domination in graphs. A locatingtotal dominating set, abbreviated LTD-set, in G

Michael A. Henning; Anders Yeo

2013-01-01T23:59:59.000Z

130

STEO January 2013 - average gasoline prices  

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

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...

131

average air temperature | OpenEI  

Open Energy Info (EERE)

average air temperature average air temperature Dataset Summary Description (Abstract): Air Temperature at 10 m Above The Surface Of The Earth (deg C)NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly & Annual Average (July 1983 - June 2005)Parameter: Air Temperature at 10 m Above The Surface Of The Earth (deg C)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; Source U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE) Date Released March 31st, 2009 (5 years ago) Date Updated April 01st, 2009 (5 years ago) Keywords average air temperature

132

Total Crude by Pipeline  

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

Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 2007 2008 2009 2010 2011 2012 View

133

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

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

Average Price of U.S. Coal Exports Average Price of U.S. Coal Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 8. Average Price of U.S. Coal Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Continent and Country of Destination April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change North America Total 78.29 77.25 102.62 77.88 105.14 -25.9 Canada* 81.61 80.70 110.67 81.30 112.16 -27.5 Dominican Republic 78.54 75.09 73.89 75.77 76.61 -1.1 Honduras - 54.58 54.43 54.58 54.43 0.3 Jamaica 480.00 54.43 - 54.72 55.42 -1.3 Mexico 73.45 75.81 94.36 74.35 100.95 -26.3 Other** 80.33 389.30 70.37 82.45 76.10 8.3 South America Total 107.72 108.02 149.99 107.88

134

Daily Thermal Predictions of the AGR-1 Experiment with Gas Gaps Varying with Time  

SciTech Connect (OSTI)

A new daily as-run thermal analysis was performed at the Idaho National Laboratory on the Advanced Gas Reactor (AGR) test experiment number one at the Advanced Test Reactor (ATR). This thermal analysis incorporates gas gaps changing with time during the irradiation experiment. The purpose of this analysis was to calculate the daily average temperatures of each compact to compare with experimental results. Post irradiation examination (PIE) measurements of the graphite holder and fuel compacts showed the gas gaps varying from the beginning of life. The control temperature gas gap and the fuel compact graphite holder gas gaps were linearly changed from the original fabrication dimensions, to the end of irradiation measurements. A steady-state thermal analysis was performed for each daily calculation. These new thermal predictions more closely match the experimental data taken during the experiment than previous analyses. Results are presented comparing normalized compact average temperatures to normalized log(R/B) Kr-85m. The R/B term is the measured release rate divided by the predicted birth rate for the isotope Kr-85m. Correlations between these two normalized values are presented.

Grant Hawkes; James Sterbentz; John Maki; Binh Pham

2012-06-01T23:59:59.000Z

135

Polarized electron beams at milliampere average current  

SciTech Connect (OSTI)

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.

Poelker, Matthew [JLAB

2013-11-01T23:59:59.000Z

136

Total Space Heat-  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

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...

137

MCBRIDE, GRAHAM B. Simple calculation of daily photosynthesis ...  

Science Journals Connector (OSTI)

Simple calculation of daily photosynthesis by means of five photosynthesis-light equations. Abstract-The performance of five well-known photosynthesis-light...

2000-03-19T23:59:59.000Z

138

Laser Fusion Energy The High Average Power  

E-Print Network [OSTI]

Laser Fusion Energy and The High Average Power Program John Sethian Naval Research Laboratory Dec for Inertial Fusion Energy with lasers, direct drive targets and solid wall chambers Lasers DPPSL (LLNL) Kr posters Snead Payne #12;Laser(s) Goals 1. Develop technologies that can meet the fusion energy

139

Ordered Weighted Average Based Fuzzy Rough Sets  

E-Print Network [OSTI]

Ordered Weighted Average Based Fuzzy Rough Sets Chris Cornelis 1 , Nele Verbiest1 , and Richard rough set model, which is based on a similar rationale, our proposal has the ad- vantage a feature selection application confirm the potential of the OWA-based model. Keywords: fuzzy rough sets

Gent, Universiteit

140

HIGH AVERAGE POWER OPTICAL FEL AMPLIFIERS.  

SciTech Connect (OSTI)

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.

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

2005-08-21T23:59:59.000Z

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Average Price (Cents/kilowatthour) by State by Provider, 1990-2012  

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

Average Price (Cents/kilowatthour) by State by Provider, 1990-2012" Average Price (Cents/kilowatthour) by State by Provider, 1990-2012" "Year","State","Industry Sector Category","Residential","Commercial","Industrial","Transportation","Other","Total" 2012,"AK","Total Electric Industry",17.88,14.93,16.82,0,"NA",16.33 2012,"AL","Total Electric Industry",11.4,10.63,6.22,0,"NA",9.18 2012,"AR","Total Electric Industry",9.3,7.71,5.77,11.23,"NA",7.62 2012,"AZ","Total Electric Industry",11.29,9.53,6.53,0,"NA",9.81 2012,"CA","Total Electric Industry",15.34,13.41,10.49,7.17,"NA",13.53

142

Daily snow depth measurements from 195 stations in the United States  

SciTech Connect (OSTI)

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.

Allison, L.J. [ed.] [Oak Ridge National Lab., TN (United States). Carbon Dioxide Information Analysis Center; Easterling, D.R.; Jamason, P.; Bowman, D.P.; Hughes, P.Y.; Mason, E.H. [National Oceanic and Atmospheric Administration, Asheville, NC (United States). National Climatic Data Center

1997-02-01T23:59:59.000Z

143

Sources Of Average Individual Radiation Exposure  

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

Of Average Individual Radiation Exposure Of Average Individual Radiation Exposure Natural background Medical Consumer products Industrial, security, educational and research Occupational 0.311 rem 0.300 rem 0.013 rem 0.0003 rem 0.0005 rem Savannah River Nuclear Solutions, LLC, provides radiological protection services and oversight at the Savannah River Site (SRS). These services include radiation dose measurements for persons who enter areas where they may be exposed to radiation or radioactive material. The results are periodically reported to monitored individuals. The results listed are based on a radiation dose system developed by the International Commission on Radiation Protection. The system uses the terms "effective dose," "equivalent dose" and units of rem. You may be more familiar with the term "millirem" (mrem), which is 1/1000 of a rem.

144

Fat turnover in obese slower than average  

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

9-04 9-04 For immediate release: 09/23/2011 | NR-11-09-04 Fat turnover in obese slower than average Anne M Stark, LLNL, (925) 422-9799, stark8@llnl.gov Printer-friendly This scanning electron micrograph image shows part of a lobule of adipose tissue (body fat). Adipose tissue is specialized connective tissue that functions as the major storage site for fat. Photo courtesy of David Gregory & Debbie Marshall/Wellcome Images LIVERMORE, Calif. -- It may be more difficult for obese people to lose fat because the "turnover" rate is much slower for those overweight than average weight individuals. New research in the Sept. 25 online edition of the journal Nature shows that the turnover (storage and loss rate) of fat in the human body is about 1 1/2 years compared to fat cells, which turnover about every 10 years,

145

Natural Gas Prices: Well Above Recent Averages  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: The recent surge in spot prices at the Henry Hub are well above a typical range for 1998-1999 (in this context, defined as the average, +/- 2 standard deviations). Past price surges have been of short duration. The possibility of a downward price adjustment before the end of next winter is a source of considerable risk for storage operators who acquire gas at recent elevated prices. Storage levels in the Lower 48 States were 7.5 percent below the 5-year average (1995-1999) by mid-August (August 11), although the differential is only 6.4 percent in the East, which depends most heavily on storage to meet peak demand. Low storage levels are attributable, at least in part, to poor price incentives: high current prices combined with only small price

146

Indirect CP violation results and HFAG averages  

E-Print Network [OSTI]

The current status of the search for indirect CP violation in the neutral D meson system at the B-factories and at LHCb is reported. The indirect CP asymmetry search is performed by the measurement of the proper-time asymmetry ($A_{\\Gamma}$) in decays of $D^0-\\bar{D^0}$ mesons to CP eigenstates, $K^-K^+$ and $\\pi^- \\pi^+$, and by $y_{CP}$, the ratio between the effective lifetime measured in decay to a CP eigenstate and that to the mixed eigenstate $K \\pi$. All results are consistent with the no CP violation hypothesis. The latest world averages for mixing and CP asymmetry in the charm sector evaluated by the Heavy Flavour Averaging Group are presented. The no mixing hypothesis is excluded at more than 12 standard deviations. The search for direct and indirect CP violation in the charm sector is consistent with no CP violation at 2.0% confident level.

Silvia Borghi

2013-12-17T23:59:59.000Z

147

Polarized electron beams at milliampere average current  

SciTech Connect (OSTI)

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 todays 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.

Poelker, M. [Thomas Jefferson National Accelerator Facility, Newport News, Virginia 23606 (United States)

2013-11-07T23:59:59.000Z

148

Predicting Daily Net Radiation Using Minimum Climatological Data1  

E-Print Network [OSTI]

Predicting Daily Net Radiation Using Minimum Climatological Data1 S. Irmak, M.ASCE2 ; A. Irmak3 ; J for predicting daily Rn have been widely used. However, when the paucity of detailed climatological data with National Weather Service climatological datasets that only record Tmax and Tmin on a regular basis. DOI: 10

149

SCIENTIFIC NOTE Variations in daily quality assurance dosimetry from device  

E-Print Network [OSTI]

SCIENTIFIC NOTE Variations in daily quality assurance dosimetry from device levelling, feet procedures are an essential part of radiotherapy medical physics. Devices such as the Sun Nuclear, DQA3 are effective tools for analysis of daily dosimetry including flatness, symmetry, energy, field size and central

Yu, K.N.

150

Table HC1.2.2 Living Space Characteristics by Average Floorspace  

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

2 Living Space Characteristics by Average Floorspace, " 2 Living Space Characteristics by Average Floorspace, " " Per Housing Unit and Per Household Member, 2005" ,,"Average Square Feet" ," Housing Units (millions)" ,,"Per Housing Unit",,,"Per Household Member" "Living Space Characteristics",,"Total1","Heated","Cooled","Total1","Heated","Cooled" "Total",111.1,2033,1618,1031,791,630,401 "Total Floorspace (Square Feet)" "Fewer than 500",3.2,357,336,113,188,177,59 "500 to 999",23.8,733,667,308,343,312,144 "1,000 to 1,499",20.8,1157,1086,625,435,409,235 "1,500 to 1,999",15.4,1592,1441,906,595,539,339 "2,000 to 2,499",12.2,2052,1733,1072,765,646,400

151

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" 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 "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",19.1,5.8,1223,1130,496,1187,1086,696 "1,500 to 1,999",14.4,1,1700,1422,412,1698,1544,1348

152

Average resonance capture study of Te124  

Science Journals Connector (OSTI)

An average resonance capture study of Te124 was carried out by bombarding samples of Te123 with 2- and 24-keV neutron beams. The complete set of 0+, 1+, 2+ states disclosed by the experiment is consistent with the data of Robinson, Hamilton, and Snelling, demonstrating that there are no undetected states of these spins (especially 0+ states) below about 2500 keV. In particular, proposed 0+ levels at 1156 and 1290 keV are ruled out. This impacts various attempted interpretations in terms of intruder states, U(5), and O(6) symmetries.

R. F. Casten; J.-Y. Zhang; B.-C. Liao

1991-07-01T23:59:59.000Z

153

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

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

Price of U.S. Coal Imports Price of U.S. Coal Imports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 19. Average Price of U.S. Coal Imports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Continent and Country of Origin April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change North America Total 147.86 138.39 191.01 144.86 197.96 -26.8 Canada 147.86 138.39 191.00 144.86 197.95 -26.8 Mexico - - 286.23 - 286.23 - South America Total 75.29 80.74 86.52 77.20 87.17 -11.4 Argentina - - 504.70 - 504.70 - Colombia 74.87 80.74 83.03 76.96 85.25 -9.7 Peru 87.09 - - 87.09 - - Venezuela 91.81 - 122.01 91.81 112.61 -18.5 Europe Total - 136.50 137.33 136.50 146.31 -6.7

154

Average Price of Natural Gas Production  

Gasoline and Diesel Fuel Update (EIA)

. . Quantity and Average Price of Natural Gas Production in the United States, 1930-1996 (Volumes in Million Cubic Feet, Prices in Dollars per Thousand Cubic Feet) Table Year Gross Withdrawals Used for Repressuring Nonhydro- carbon Gases Removed Vented and Flared Marketed Production Extraction Loss Dry Production Average Wellhead Price of Marketed Production 1930 ....................... NA NA NA NA 1,978,911 75,140 1,903,771 0.08 1931 ....................... NA NA NA NA 1,721,902 62,288 1,659,614 0.07 1932 ....................... NA NA NA NA 1,593,798 51,816 1,541,982 0.06 1933 ....................... NA NA NA NA 1,596,673 48,280 1,548,393 0.06 1934 ....................... NA NA NA NA 1,815,796 52,190 1,763,606 0.06 1935 ....................... NA NA NA NA 1,968,963 55,488 1,913,475 0.06 1936 ....................... 2,691,512 73,507 NA 392,528 2,225,477

155

Average values and dispersion (in parentheses)  

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

Average values and dispersion (in parentheses) Average values and dispersion (in parentheses) Base-pair Parameters --------------------------------------------------------------------------------------- Shear Stretch Stagger Buckle Propeller Opening 3DNA A 0.01(0.23) -0.18(0.10) 0.02(0.25) -0.13(7.77) -11.79(4.14) 0.57(2.80) B 0.00(0.21) -0.15(0.12) 0.09(0.19) 0.53(6.74) -11.35(5.26) 0.63(3.05) CEHS A 0.01(0.23) -0.18(0.10) 0.02(0.25) -0.13(7.75) -11.82(4.14) 0.56(2.78) B 0.00(0.21) -0.14(0.12) 0.09(0.19) 0.53(6.73) -11.37(5.27) 0.62(3.03) CompDNA A 0.01(0.23) -0.18(0.10) 0.02(0.25) -0.12(7.70) -11.81(4.14) 0.56(2.79) B 0.00(0.21) -0.15(0.12) 0.09(0.19) 0.53(6.70) -11.37(5.26) 0.62(3.03) Curves A 0.01(0.23) -0.18(0.10) 0.02(0.25) -0.13(7.85) -11.76(4.12) 0.57(2.80)

156

21 briefing pages total  

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

briefing pages total p. 1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law effective first day of first pay period on or after March 11, 2009 (March 15 for most executive branch employees) Number of affected employees unclear p. 4 Next Steps

157

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

SciTech Connect (OSTI)

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.

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

2012-01-01T23:59:59.000Z

158

Barge Truck Total  

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

Barge 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 total shipments Year (nominal) (real) (real) (percent) (nominal) (real) (real) (percent) 2008 $6.26 $5.77 $36.50 15.8% 42.3% $6.12 $5.64 $36.36 15.5% 22.2% 2009 $6.23 $5.67 $52.71 10.8% 94.8% $4.90 $4.46 $33.18 13.5% 25.1% 2010 $6.41 $5.77 $50.83 11.4% 96.8% $6.20 $5.59 $36.26 15.4% 38.9% Annual Percent Change First to Last Year 1.2% 0.0% 18.0% - - 0.7% -0.4% -0.1% - - Latest 2 Years 2.9% 1.7% -3.6% - - 26.6% 25.2% 9.3% - - - = No data reported or value not applicable STB Data Source: The Surface Transportation Board's 900-Byte Carload Waybill Sample EIA Data Source: Form EIA-923 Power Plant Operations Report

159

Summary Max Total Units  

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

Max Total Units 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 Refrig Voltage Cond Unit IF-CU Combos 2 4 5 28 References Refrig Voltage C-U type Compressor HP R-404A 208/1/60 Hermetic SA 2.5 R-507 230/1/60 Hermetic MA 2.5 208/3/60 SemiHerm SA 1.5 230/3/60 SemiHerm MA 1.5 SemiHerm HA 1.5 1000lb, remote rack systems, fresh water Refrig/system Voltage Combos 12 2 24 References Refrig/system Voltage IF only

160

Total Precipitable Water  

SciTech Connect (OSTI)

The simulation was performed on 64K cores of Intrepid, running at 0.25 simulated-years-per-day and taking 25 million core-hours. This is the first simulation using both the CAM5 physics and the highly scalable spectral element dynamical core. The animation of Total Precipitable Water clearly shows hurricanes developing in the Atlantic and Pacific.

None

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Total Sustainability Humber College  

E-Print Network [OSTI]

1 Total Sustainability Management Humber College November, 2012 SUSTAINABILITY SYMPOSIUM Green An Impending Global Disaster #12;3 Sustainability is NOT Climate Remediation #12;Our Premises "We cannot, you cannot improve it" (Lord Kelvin) "First rule of sustainability is to align with natural forces

Thompson, Michael

162

Average deployments versus missile and defender parameters  

SciTech Connect (OSTI)

This report evaluates the average number of reentry vehicles (RVs) that could be deployed successfully as a function of missile burn time, RV deployment times, and the number of space-based interceptors (SBIs) in defensive constellations. Leakage estimates of boost-phase kinetic-energy defenses as functions of launch parameters and defensive constellation size agree with integral predictions of near-exact calculations for constellation sizing. The calculations discussed here test more detailed aspects of the interaction. They indicate that SBIs can efficiently remove about 50% of the RVs from a heavy missile attack. The next 30% can removed with two-fold less effectiveness. The next 10% could double constellation sizes. 5 refs., 7 figs.

Canavan, G.H.

1991-03-01T23:59:59.000Z

163

Backstage at the Daily Show | Department of Energy  

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

Backstage at the Daily Show Backstage at the Daily Show Backstage at the Daily Show Addthis Description Backstage footage from Secretary Chu's appearance on the Daily Show where he discuses the green room candy dish and possible lighting considerations. Speakers Secretary Steven Chu Duration 1:32 Topic Energy Efficiency Credit Energy Department Video SECRETARY STEVEN CHU: I'm in the famous green room of the Jon Stewart show. If you look around, I have all these games: Monopoly, a Rubik's Cube, Pictureka! Now if - this is to amuse myself, but in actual fact, the most famous part of this room is this. There's enough chocolate here to put you on a high that - (chuckles) - will really get you going. This is my wife, Jean. JEAN CHU: (Chuckles.) I'm - (chuckles) - edit this out! (Begin recorded segment.)

164

Daily Reporting Rainfall Station HERBERT RIVER Manual Heavy Rainfall Station  

E-Print Network [OSTI]

Daily Reporting Rainfall Station HERBERT RIVER Manual Heavy Rainfall Station Manual River Station Central Mill AL Tung Oil AL Corsis AL Innisfail Clump Point Tide TM Mourilyan Harbour TM 0 10 kilometres

Greenslade, Diana

165

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" 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 "Census Region and Division" "Northeast",20.6,6.7,1247,1032,"Q",811,788,147 "New England",5.5,1.9,1365,1127,"Q",814,748,107 "Middle Atlantic",15.1,4.8,1182,978,"Q",810,800,159 "Midwest",25.6,4.6,1349,1133,506,895,810,346

166

Table 7.5 Average Prices of Selected Purchased Energy Sources, 2002  

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

5 Average Prices of Selected Purchased Energy Sources, 2002;" 5 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate","Natural ","LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

167

Table N8.2. Average Prices of Purchased Energy Sources, 1998  

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

2. Average Prices of Purchased Energy Sources, 1998;" 2. Average Prices of Purchased Energy Sources, 1998;" " 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",," ",," "

168

Table 7.1 Average Prices of Purchased Energy Sources, 2002  

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

Average Prices of Purchased Energy Sources, 2002;" Average Prices of Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Physical Units." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"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",," ",," "

169

Table 7.2 Average Prices of Purchased Energy Sources, 2002  

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

2 Average Prices of Purchased Energy Sources, 2002;" 2 Average Prices of Purchased Energy Sources, 2002;" " 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",," ",," "

170

"Table E8.2. Average Prices of Selected Purchased Energy Sources, 1998;"  

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

2. Average Prices of Selected Purchased Energy Sources, 1998;" 2. Average Prices of Selected Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate",,"LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

171

Total isomerization gains flexibility  

SciTech Connect (OSTI)

Isomerization extends refinery flexibility to meet changing markets. TIP (Total Isomerization Process) allows conversion of paraffin fractions in the gasoline boiling region including straight run naptha, light reformate, aromatic unit raffinate, and hydrocrackate. The hysomer isomerization is compared to catalytic reforming. Isomerization routes are graphed. Cost estimates and suggestions on the use of other feedstocks are given. TIP can maximize gas production, reduce crude runs, and complement cat reforming. In four examples, TIP reduces reformer severity and increases reformer yield.

Symoniak, M.F.; Holcombe, T.C.

1983-05-01T23:59:59.000Z

172

Fuel Economy Standards, New Vehicle Sales, and Average Fuel Efficiency  

Science Journals Connector (OSTI)

The average fuel efficiency of new automobiles sold in the ... trend stagnated in 1981, however, and average fuel efficiency has actually fallen since 1987. Corporate Average Fuel Economy (CAFE) standardsthe maj...

Steven G. Thorpe

1997-05-01T23:59:59.000Z

173

Fact #744: September 10, 2012 Average New Light Vehicle Price...  

Energy Savers [EERE]

4: September 10, 2012 Average New Light Vehicle Price Grows Faster than Average Used Light Vehicle Price Fact 744: September 10, 2012 Average New Light Vehicle Price Grows Faster...

174

STATE OF CALIFORNIA AREA WEIGHTED AVERAGE CALCULATION WORKSHEET: RESIDENTIAL  

E-Print Network [OSTI]

be used to calculate weight-averaged U-factors or averaged SHGC values for prescriptive envelope of window (the SHGC values of skylights cannot be averaged per §151(f)4A). a. "Area" can be replaced

175

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

Energy Savers [EERE]

average is the production-weighted harmonic mean. 2014 data are preliminary. Fact 849 Dataset Supporting Information Average Fuel Economy of New Midsize Cars - Hybrid vs....

176

Total Sales of Kerosene  

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

End Use: Total Residential Commercial Industrial Farm All Other Period: End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

177

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

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

Total Solids in Biomass and Total Dissolved Solids in Liquid Process Samples Laboratory Analytical Procedure (LAP) Issue Date: 3312008 A. Sluiter, B. Hames, D. Hyman, C. Payne,...

178

Total Marketed Production ..............  

Gasoline and Diesel Fuel Update (EIA)

billion cubic feet per day) billion cubic feet per day) Total Marketed Production .............. 68.95 69.77 70.45 71.64 71.91 71.70 71.46 71.57 72.61 72.68 72.41 72.62 70.21 71.66 72.58 Alaska ......................................... 1.04 0.91 0.79 0.96 1.00 0.85 0.77 0.93 0.97 0.83 0.75 0.91 0.93 0.88 0.87 Federal GOM (a) ......................... 3.93 3.64 3.44 3.82 3.83 3.77 3.73 3.50 3.71 3.67 3.63 3.46 3.71 3.70 3.62 Lower 48 States (excl GOM) ...... 63.97 65.21 66.21 66.86 67.08 67.08 66.96 67.14 67.92 68.18 68.02 68.24 65.58 67.07 68.09 Total Dry Gas Production .............. 65.46 66.21 66.69 67.79 68.03 67.83 67.61 67.71 68.69 68.76 68.50 68.70 66.55 67.79 68.66 Gross Imports ................................ 8.48 7.60 7.80 7.95 8.27 7.59 7.96 7.91 7.89 7.17 7.61 7.73 7.96 7.93 7.60 Pipeline ........................................

179

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

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

Invisible Science: Lab Breakthroughs in Our Daily Lives 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. See the Lab Breakthroughs topic page for the most recent videos and Q&As with researchers. 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

180

Daylighter Daily Solar Roof Light | Open Energy Information  

Open Energy Info (EERE)

Daylighter Daily Solar Roof Light 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 Sector Solar Product Installation; Manufacturing Phone number 440-892-3312 Website http://www.SolarLightisFree.co Coordinates 41.4648875°, -81.9506519° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":41.4648875,"lon":-81.9506519,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Warm Weather and the Daily Commute | Department of Energy  

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

Warm Weather and the Daily Commute Warm Weather and the Daily Commute Warm Weather and the Daily Commute May 7, 2013 - 12:02pm Addthis Biking to work helps you get some exercise while reducing your carbon footprint. | Photo courtesy of iStockphoto.com/olaser Biking to work helps you get some exercise while reducing your carbon footprint. | Photo courtesy of iStockphoto.com/olaser Elizabeth Spencer Communicator, National Renewable Energy Laboratory How can I participate? Check out options for busing or carpooling in your area or, if you live close, try walking or biking to work. You know the weather is starting to warm up when you start hearing about those "bike, bus, or walk to work" challenges. And while my local news just started drumming up publicity for theirs, I've seen these events pop up in

182

Bacterial total maximum daily load (TMDL): development and evaluation of a new classification scheme for impaired waterbodies of Texas  

E-Print Network [OSTI]

functions corresponding to NCDC and NEXRAD rainfall datasets ............................... 224 6.4 FOA results corresponding to NCDC ............................................................. 226 6.5 FOA results corresponding to NEXRAD... ................................................... 238 6.12 Means and standard deviations of FOA and MCS..........................................239 1 CHAPTER I INTRODUCTION According to the Code of Federal Regulations (CFR), Title 40, Part 131, all States, Territories, and authorized Tribes...

Paul, Sabu

2005-02-17T23:59:59.000Z

183

Incident Invasive Breast Cancer, Geographic Location of Residence, and Reported Average Time Spent Outside  

Science Journals Connector (OSTI)

...areas of low versus high solar irradiance measured in...residence and geographic solar irradiance are not consistently...total average sunlight energy striking the ground...foods and supplements (energy adjusted IU/d). Some...low compared with high solar irradiance (comparing...

Amy E. Millen; Mary Pettinger; Jo L. Freudenheim; Robert D. Langer; Carol A. Rosenberg; Yasmin Mossavar-Rahmani; Christine M. Duffy; Dorothy S. Lane; Anne McTiernan; Lewis H. Kuller; Ana Maria Lopez; and Jean Wactawski-Wende

2009-02-01T23:59:59.000Z

184

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings* ........................... 3,037 115 397 384 52 1,143 22 354 64 148 357 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 386 19 43 18 11 93 7 137 8 12 38 5,001 to 10,000 .......................... 262 12 35 17 5 83 4 56 6 9 35 10,001 to 25,000 ........................ 407 20 46 44 8 151 3 53 9 19 54 25,001 to 50,000 ........................ 350 15 55 50 9 121 2 34 7 16 42 50,001 to 100,000 ...................... 405 16 57 65 7 158 2 29 6 18 45 100,001 to 200,000 .................... 483 16 62 80 5 195 1 24 Q 31 56 200,001 to 500,000 .................... 361 8 51 54 5 162 1 9 8 19 43 Over 500,000 ............................. 383 8 47 56 3 181 2 12 8 23 43 Principal Building Activity

185

Table 16. Recoverable Coal Reserves and Average Recovery Percentage at Producing Underground Coal Mines by State and Mining Method,  

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

Recoverable Coal Reserves and Average Recovery Percentage at Producing Underground Coal Mines by State and Mining Method, Recoverable Coal Reserves and Average Recovery Percentage at Producing Underground Coal Mines by State and Mining Method, 2012 (million short tons) U.S. Energy Information Administration | Annual Coal Report 2012 Table 16. Recoverable Coal Reserves and Average Recovery Percentage at Producing Underground Coal Mines by State and Mining Method, 2012 (million short tons) U.S. Energy Information Administration | Annual Coal Report 2012 Continuous 1 Conventional and Other 2 Longwall 3 Total Coal-Producing State Recoverable Coal Reserves at Producing Mines Average Recovery Percentage Recoverable Coal Reserves at Producing Mines Average Recovery Percentage Recoverable Coal Reserves at Producing Mines Average Recovery Percentage Recoverable Coal Reserves at Producing Mines Average Recovery Percentage

186

Daily Cycle of Precipitation over the Northern Coast of Brazil  

Science Journals Connector (OSTI)

The daily cycle of precipitation (DCP) in the austral autumn on the northern coast of Brazil (NCB) is examined in detail. The Tropical Rainfall Measuring Mission 3B42 dataset was used to obtain the DCP, and the intradaily variability was measured ...

Sheila Santana de Barros Brito; Marcos Daisuke Oyama

2014-11-01T23:59:59.000Z

187

Modelling Daily Multivariate Pollutant Data at Multiple Sites  

E-Print Network [OSTI]

. In conducting such time series studies to investigate the relationship between air pollution and a health investigating the health effects of daily changes in air pollution, the exposures are essentially treated effects of air pollution. Alternative objectives include the design problem of the positioning of a new

Washington at Seattle, University of

188

A Feasibility Study: Mining Daily Traces for Home Heating Control  

E-Print Network [OSTI]

savings as well as 14.9%­59.2% reduction in miss time. Keywords Energy, home heating, daily traces, prediction 1. INTRODUCTION Heating, ventilation and cooling (HVAC) contributes most to a home's energy bills, accounting for 48% of residential energy consumption in the U.S. and 61% in the U.K., 64% in Canada where

Whitehouse, Kamin

189

ENVIRONMENTAL LEADER: THE EXECUTIVE'S DAILY GREEN BRIEFING APRIL 25, 2008  

E-Print Network [OSTI]

ENVIRONMENTAL LEADER: THE EXECUTIVE'S DAILY GREEN BRIEFING APRIL 25, 2008 Green Business Experts at MMA Renewable Ventures, a renewable energy firm in San Francisco and formerly the Business Solutions Fellow for the Pew Center on Global Climate Change. http://www.environmentalleader.com/2008/04/25/green-business

Hoffman, Andrew J.

190

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

SciTech Connect (OSTI)

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.

Ekechukwu, A.A.

2002-05-10T23:59:59.000Z

191

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 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 ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

192

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 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 ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

193

Table 7.3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2010;  

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

3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2010; 3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: U.S. Dollars per Physical Units. Electricity Components Natural Gas Components Steam Components Electricity Natural Gas Steam Electricity from Sources Natural Gas from Sources Steam from Sources Electricity from Local Other than Natural Gas from Local Other than Steam from Local Other than NAICS Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Code(a) Subsector and Industry (kWh) (kWh) (kWh) (1000 cu ft) (1000 cu ft) (1000 cu ft) (million Btu)

194

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Babb, MT Havre, MT Port of Morgan, MT Pittsburg, NH 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 India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Kenai, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass, TX El Paso, TX Hidalgo, TX McAllen, TX Penitas, TX Rio Bravo, TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to United Kingdom Sabine Pass, LA Period: Monthly Annual

195

GFD1 23 Jan 2011 Plotting NCEP atmospheric data in Matlab %% The Matlab file ncep-data-2010.mat contains daily average  

E-Print Network [OSTI]

GFD1 23 Jan 2011 Plotting NCEP atmospheric data in Matlab %% The Matlab file ncep-data-2010.mat(:,:,1,1)', 25); %NOTE: transpose ( )' gets lat,lon correct ...note Matlab sometimes requires a squeeze) plot(lat,squeeze(z(121,:,:,1))) % squeeze is needed to tell %Matlab this is just 2 dimensional title

196

From average travel time budgets to daily travel time distributions: an appraisal of two conjectures by Klbl and Helbing and some consequences  

E-Print Network [OSTI]

. The analysis shows the link with energy expenditure to be questionable, but also provides alternative views and human energy expenditure for travel, which is assumed to be constant in time and space. The second one because of the improved comfort of cars, carriages or coaches, or because of devices, such as laptop

Toint, Philippe

197

Dioxin-Like and Transthyretin-Binding Compounds in Indoor Dusts Collected from Japan:? Average Daily Dose and Possible Implications for Children  

Science Journals Connector (OSTI)

Many researchers are increasingly interested in human exposure to house dust containing household compounds such as polybrominated diphenylethers (PBDEs). ... House dust samples were collected from 19 households (n = 19), and office and lab dust samples (hereafter called office samples) were collected from three institutions (n = 14) in Japan during May?December 2005. ...

Go Suzuki; Hidetaka Takigami; Kazutoshi Nose; Shin Takahashi; Misuzu Asari; Shin-ichi Sakai

2007-01-19T23:59:59.000Z

198

Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average  

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

8: July 12, 2004 8: July 12, 2004 Expected Average Annual Miles to someone by E-mail Share Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Facebook Tweet about Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Twitter Bookmark Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Google Bookmark Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Delicious Rank Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Digg Find More places to share Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on AddThis.com... Fact #328: July 12, 2004 Expected Average Annual Miles Twenty-five percent of the respondents to a nationwide survey said that

199

Fact #614: March 15, 2010 Average Age of Household Vehicles  

Broader source: Energy.gov [DOE]

The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first...

200

Fact #615: March 22, 2010 Average Vehicle Trip Length  

Broader source: Energy.gov [DOE]

According to the latest National Household Travel Survey, the average trip length grew to over 10 miles in 2009, just slightly over the 9.9 mile average in 2001. Trips to work in 2009 increased to...

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Fact #835: August 25, Average Historical Annual Gasoline Pump...  

Energy Savers [EERE]

5: August 25, Average Historical Annual Gasoline Pump Price, 1929-2013 Fact 835: August 25, Average Historical Annual Gasoline Pump Price, 1929-2013 When adjusted for inflation,...

202

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... havior of the ratio of total quanta to total energy (Q : W) within the spectral region of photosynthetic ..... For blue-green waters, where hRmax lies.

2000-01-02T23:59:59.000Z

203

FULL TIME CLASS OF 2014 EMPLOYMENT & SALARY STATISTICS Total Offers Received  

E-Print Network [OSTI]

FULL TIME CLASS OF 2014 EMPLOYMENT & SALARY STATISTICS Total Offers Received 1 91% Overall Student Employment 1 88% Accepted Offers Facilitated by Rice University 2 65% Average Base Salary 3 $102,740 Average Students 105 MBA EMPLOYMENT BY FUNCTION Percent Range Average Base Salary Finance/Accounting 40% $70

Alvarez, Pedro J.

204

Spherical averages and applications to spherical splines and interpolation  

Science Journals Connector (OSTI)

This article introduces a method for computing weighted averages on spheres based on least squares minimization that respects spherical distance. We prove existence and uniqueness properties of the weighted averages, and give fast iterative algorithms ... Keywords: Bzier curve, B-spline, barycentric coordinates, least squares minimization, quaternion interpolation, quaternions, spherical average, spherical interpolation, spherical mean, spline curve, spline interpolation

Samuel R. Buss; Jay P. Fillmore

2001-04-01T23:59:59.000Z

205

"Table A25 Average Prices of Selected Purchased Energy Sources by Census"  

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

Average Prices of Selected Purchased Energy Sources by Census" Average Prices of Selected Purchased Energy Sources by Census" " Region, Industry Group, and Selected Industries, 1991: Part 2" " (Estimates in Dollars per Million Btu)" ,,,,,,,,"RSE" "SIC"," "," ","Residual","Distillate"," "," "," ","Row" "Code(a)","Industry Groups and Industry","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","LPG","Coal","Factors" ,,"Total United States" ,"RSE Column Factors:",0.7,0.8,1,2.8,1,0.7 20,"Food and Kindred Products",15.789,2.854,6.064,2.697,7.596,1.433,4.5

206

Mujeres Hombres Total Hombres Total 16 5 21 0 10  

E-Print Network [OSTI]

Julio de 2011 Tipo de Discapacidad Sexo CENTRO 5-Distribución del estudiantado con discapacidad por centro, tipo de discapacidad, sexo y totales. #12;

Autonoma de Madrid, Universidad

207

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... ment of the total energy and vice versa. From a measurement of spectral irradi- ance ... unit energy (for the wavelength region specified).

2000-01-02T23:59:59.000Z

208

Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material  

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

0: March 8, 2004 0: March 8, 2004 Average Material Consumption for a Domestic Automobile to someone by E-mail Share Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Facebook Tweet about Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Twitter Bookmark Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Google Bookmark Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Delicious Rank Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Digg Find More places to share Vehicle Technologies Office: Fact #310:

209

Solar: monthly and annual average global horizontal (GHI) GIS...  

Open Energy Info (EERE)

Facebook icon Twitter icon Home Organizations DLR - Deutsches Zentrum fr ... Solar: monthly and annual ... Dataset Activity Stream Solar: monthly and annual average...

210

,"Selected National Average Natural Gas Prices"  

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

Selected National Average Natural Gas Prices" 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 1","Average Natural Gas Prices",11,"Monthly","11/2013","1/15/1973" ,"Data 2","Annual Average Natural Gas Prices",11,"Annual",2012,"6/30/1922" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","ngm03vmall.xls" ,"Available from Web Page:","http://www.eia.gov/oil_gas/natural_gas/data_publications/natural_gas_monthly/ngm.html"

211

Total.................................................................  

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

49.2 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 Pump................................ 53.5 3.5 12.9 12.7 8.6 5.5 4.2 6.2 With a Heat Pump..................................... 12.3 0.4 2.2 2.9 2.5 1.5 1.0 1.8 Window/Wall Units........................................ 28.9 27.5 0.5 Q 0.3 Q Q Q 1 Unit......................................................... 14.5 13.5 0.3 Q Q Q N Q 2 Units.......................................................

212

Total........................................................................  

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

7.1 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 For One Housing Unit................................... 42.9 1.5 Q 3.1 6.0 For Two Housing Units................................. 1.8 Q N Q Q Steam or Hot Water System............................. 8.2 1.9 Q Q 0.2 For One Housing Unit................................... 5.1 0.8 Q N Q For Two Housing Units.................................

213

Total........................................................................  

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

5.6 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 Unit................................... 42.9 15.5 11.0 4.5 For Two Housing Units................................. 1.8 0.7 0.6 Q Steam or Hot Water System............................. 8.2 1.6 1.2 0.4 For One Housing Unit................................... 5.1 1.1 0.9 Q For Two Housing Units.................................

214

Total...........................................................................  

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

4.2 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 Pump........................................... 53.5 8.7 3.2 5.5 With a Heat Pump............................................... 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit................................................................... 14.5 2.9 0.5 2.4 2 Units.................................................................

215

Total...........................................................  

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

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

216

Total....................................................................................  

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

Personal Computers 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 Hours..................................................... 13.6 5.0 2.6 1.0 1.3 2 to 15 Hours............................................................. 29.1 10.3 5.9 1.6 2.9 16 to 40 Hours........................................................... 13.5 4.1 2.3 0.6 1.2 41 to 167 Hours.........................................................

217

Total..............................................................  

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

,171 ,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 1,269 999 775 510 West North Central................................. 7.9 2,281 1,930 1,566 940 796 646 South.......................................................... 40.7 2,161 1,551 1,295 856 615 513 South Atlantic......................................... 21.7 2,243 1,607 1,359 896 642 543 East South Central.................................

218

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 than 2 Hours......................................................... 13.6 0.7 0.9 0.9 1.4 2 to 15 Hours................................................................. 29.1 1.7 2.1 1.9 3.4 16 to 40 Hours............................................................... 13.5 0.9 0.9 0.9 1.8 41 to 167 Hours.............................................................

219

Total.............................................................................  

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

Cooking Appliances 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 Week....................................... 4.1 0.7 0.3 0.4 No Hot Meals Cooked........................................... 0.9 0.2 Q Q Conventional Oven Use an Oven......................................................... 109.6 23.7 7.5 16.2 More Than Once a Day..................................... 8.9 1.7 0.4 1.3 Once a Day.......................................................

220

Total..............................................................................  

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

0.7 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 Heat Pump.............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................... 12.3 9.0 6.7 1.4 0.9 Window/Wall Units..................................................... 28.9 8.0 3.4 1.7 2.9 1 Unit......................................................................

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Total....................................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5 Persons......................................................... 7.9 0.8 0.4 1.0 1.1 1.2 1.1 1.5 0.9 6 or More Persons........................................... 4.1 0.5 0.3 0.3 0.6 0.5 0.7 0.8 0.4 2005 Annual Household Income Category Less than $9,999............................................. 9.9 1.9 1.1 1.3 0.9 1.7 1.3 1.1 0.5 $10,000 to $14,999..........................................

222

Total....................................................................................  

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

25.6 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 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 Hours..................................................... 13.6 2.4 3.4 5.0 2.9 2 to 15 Hours............................................................. 29.1 5.2 7.0 10.3 6.6 16 to 40 Hours........................................................... 13.5 3.1 2.8 4.1 3.4 41 to 167 Hours.........................................................

223

Total....................................................................................  

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

4.2 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 Hours..................................................... 13.6 2.9 0.9 2.0 2 to 15 Hours............................................................. 29.1 6.6 2.0 4.6 16 to 40 Hours........................................................... 13.5 3.4 0.9 2.5 41 to 167 Hours......................................................... 6.3

224

Total..................................................................  

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

33.0 33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment..................... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment................................. 93.3 26.5 6.5 2.5 4.6 12.0 1.0 Use Cooling Equipment.................................. 91.4 25.7 6.3 2.5 4.4 11.7 0.8 Have Equipment But Do Not Use it................. 1.9 0.8 Q Q 0.2 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 14.1 3.6 1.5 2.1 6.4 0.6 Without a Heat Pump.................................. 53.5 12.4 3.1 1.3 1.8 5.7 0.6 With a Heat Pump....................................... 12.3 1.7 0.6 Q 0.3 0.6 Q Window/Wall Units....................................... 28.9 12.4 2.9 1.0 2.5 5.6 0.4 1 Unit.......................................................... 14.5 7.3 1.2 0.5 1.4 3.9 0.2 2 Units.........................................................

225

Total....................................................................................  

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

Cooking Appliances 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..................................................... 3.9 1.7 0.6 0.9 0.8 Less Than Once a Week.............................................. 4.1 2.2 0.6 0.8 0.5 No Hot Meals Cooked................................................... 0.9 0.4 Q Q Q Conventional Oven Use an Oven................................................................. 109.6 46.2 18.8

226

Total...................................................................  

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

Single-Family Units Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business

227

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... 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 Pump............................................. 53.5 16.2 10.6 5.6 With a Heat Pump................................................. 12.3 1.1 0.8 0.4 Window/Wall Units.................................................. 28.9 6.6 4.9 1.7 1 Unit..................................................................... 14.5 4.1 2.9 1.2 2 Units...................................................................

228

Total..............................................................................  

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

20.6 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 Without a Heat Pump.............................................. 53.5 5.5 16.2 23.2 8.7 With a Heat Pump................................................... 12.3 0.5 1.1 9.0 1.7 Window/Wall Units..................................................... 28.9 10.7 6.6 8.0 3.6 1 Unit......................................................................

229

Total....................................................................................  

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

5.6 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 Hours..................................................... 13.6 3.4 2.5 0.9 2 to 15 Hours............................................................. 29.1 7.0 4.8 2.3 16 to 40 Hours........................................................... 13.5 2.8 2.1 0.7 41 to 167 Hours......................................................... 6.3

230

Total...................................................................  

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

15.2 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 Unit.............................. 3.3 2.9 Q Q Q N For Two Housing Units............................. 1.4 Q Q 0.5 0.8 N Central Warm-Air Furnace........................... 2.8 2.4 Q Q Q 0.2 Other Equipment......................................... 0.3 0.2 Q N Q N Wood..............................................................

231

Total...............................................................  

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

Do Not Have Cooling Equipment................. Do Not Have Cooling Equipment................. 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment.............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment............................... 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Air-Conditioning Equipment 1, 2 Central System............................................ 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units...................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit....................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units.....................................................

232

Total.............................................................................  

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

Cooking Appliances 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 Week....................................... 4.1 1.1 0.7 0.4 No Hot Meals Cooked........................................... 0.9 Q Q N Conventional Oven Use an Oven......................................................... 109.6 25.3 17.6 7.7 More Than Once a Day..................................... 8.9 1.3 0.8 0.5 Once a Day.......................................................

233

Total...............................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer ........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Number of Desktop PCs 1.......................................................... 50.3 8.3 14.2 11.4 7.2 9.2 5.3 14.2 2.......................................................... 16.2 0.9 2.6 3.7 2.9 6.2 0.8 2.6 3 or More............................................. 9.0 0.4 1.2 1.3 1.2 5.0 0.3 1.1 Number of Laptop PCs 1.......................................................... 22.5 2.2 4.6 4.5 2.9 8.3 1.4 4.0 2.......................................................... 4.0 Q 0.4 0.6 0.4 2.4 Q 0.5 3 or More............................................. 0.7 Q Q Q Q 0.4 Q Q Type of Monitor Used on Most-Used PC Desk-top

234

Total...............................................................  

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

20.6 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 1.......................................................... 22.5 4.7 4.6 7.7 5.4 2.......................................................... 4.0 0.6 0.9 1.5 1.1 3 or More............................................. 0.7 Q Q Q 0.3 Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 7.9 11.4 15.4 10.2 Flat-panel LCD.................................

235

Total................................................................  

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

111.1 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Do Not Have Space Heating Equipment....... 1.2 0.5 0.3 0.2 Q 0.2 0.3 0.6 Have Main Space Heating Equipment.......... 109.8 26.2 28.5 20.4 13.0 21.8 16.3 37.9 Use Main Space Heating Equipment............ 109.1 25.9 28.1 20.3 12.9 21.8 16.0 37.3 Have Equipment But Do Not Use It.............. 0.8 0.3 0.3 Q Q N 0.4 0.6 Main Heating Fuel and Equipment Natural Gas.................................................. 58.2 12.2 14.4 11.3 7.1 13.2 7.6 18.3 Central Warm-Air Furnace........................ 44.7 7.5 10.8 9.3 5.6 11.4 4.6 12.0 For One Housing Unit........................... 42.9 6.9 10.3 9.1 5.4 11.3 4.1 11.0 For Two Housing Units......................... 1.8 0.6 0.6 Q Q Q 0.4 0.9 Steam or Hot Water System..................... 8.2 2.4 2.5 1.0 1.0 1.3 1.5 3.6 For One Housing Unit...........................

236

Total...........................................................  

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

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

237

Total........................................................................  

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

25.6 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 16.2 11.0 11.4 For One Housing Unit................................... 42.9 5.6 15.5 10.7 11.1 For Two Housing Units................................. 1.8 0.5 0.7 Q 0.3 Steam or Hot Water System............................. 8.2 4.9 1.6 1.0 0.6 For One Housing Unit................................... 5.1 3.2 1.1 0.4

238

Total...........................................................................  

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

0.6 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 Pump........................................... 53.5 5.5 4.8 0.7 With a Heat Pump............................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................. 28.9 10.7 7.6 3.1 1 Unit................................................................... 14.5 4.3 2.9 1.4 2 Units.................................................................

239

Total.......................................................................  

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

4.2 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 1.................................................................. 22.5 5.4 1.5 3.9 2.................................................................. 4.0 1.1 0.3 0.8 3 or More..................................................... 0.7 0.3 Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)...........................

240

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 Hours..................................................... 13.6 5.7 1.8 2.9 3.2 2 to 15 Hours............................................................. 29.1 11.9 5.1 6.5 5.7 16 to 40 Hours........................................................... 13.5 5.5 2.5 3.3 2.2 41 to 167 Hours.........................................................

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Total........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7 19.8 8.6 12.8 3.6 For One Housing Unit................................... 42.9 18.8 8.3 12.3 3.5 For Two Housing Units................................. 1.8 1.0 0.3 0.4 Q Steam or Hot Water System............................. 8.2 4.4 2.1 1.4 0.3 For One Housing Unit................................... 5.1 2.1 1.6 1.0

242

Total........................................................................  

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

15.1 15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing Unit................................... 42.9 5.6 4.9 0.7 For Two Housing Units................................. 1.8 0.5 0.4 Q Steam or Hot Water System............................. 8.2 4.9 3.6 1.3 For One Housing Unit................................... 5.1 3.2 2.2 1.0 For Two Housing Units.................................

243

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.7 0.5 0.2 Million U.S. Housing Units Home Electronics Usage Indicators Table HC12.12 Home Electronics Usage Indicators by Midwest Census Region,...

244

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 1.8 1.2 0.5 Table HC11.10 Home Appliances Usage Indicators by Northeast Census Region, 2005 Million U.S. Housing Units Home Appliances...

245

Total..........................................................  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

... 2.8 1.1 0.7 Q 0.4 Million U.S. Housing Units Home Electronics Usage Indicators Table HC13.12 Home Electronics Usage Indicators by South Census Region,...

246

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 3.1 1.0 2.2 Table HC14.10 Home Appliances Usage Indicators by West Census Region, 2005 Million U.S. Housing Units Home Appliances...

247

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

States New York Florida Texas California Million U.S. Housing Units Home Electronics Usage Indicators Table HC15.12 Home Electronics Usage Indicators by Four Most Populated...

248

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 2.7 3.5 2.2 1.3 3.5 1.3 3.8 Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line Eligible for Federal...

249

Total..........................................................  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

... 13.2 3.4 2.0 1.4 Table HC12.10 Home Appliances Usage Indicators by Midwest Census Region, 2005 Million U.S. Housing Units Home Appliances...

250

Total..........................................................  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Census Region Northeast Midwest South West Million U.S. Housing Units Home Electronics Usage Indicators Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005...

251

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

(as Self-Reported) City Town Suburbs Rural Million U.S. Housing Units Home Electronics Usage Indicators Table HC8.12 Home Electronics Usage Indicators by UrbanRural Location,...

252

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 4.4 2.5 3.0 3.4 Table HC8.10 Home Appliances Usage Indicators by UrbanRural Location, 2005 Million U.S. Housing Units UrbanRural...

253

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.6 Q 0.5 Million U.S. Housing Units Home Electronics Usage Indicators Table HC14.12 Home Electronics Usage Indicators by West Census Region, 2005...

254

Total..........................................................  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

... 13.2 4.9 2.3 1.1 1.5 Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005 Million U.S. Housing Units South Census Region...

255

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 51.9 7.0 4.8 2.2 Not Asked (Mobile Homes or Apartment in Buildings with 5 or More Units)... 23.7...

256

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

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

257

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

0.7 21.7 6.9 12.1 Do Not Have Space Heating Equipment... 1.2 Q Q N Q Have Main Space Heating Equipment... 109.8 40.3 21.4 6.9 12.0 Use Main Space Heating...

258

Total  

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

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

259

Total  

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

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

260

Total.............................................................................  

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

Cooking Appliances 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 Week....................................... 4.1 0.6 0.4 Q No Hot Meals Cooked........................................... 0.9 0.3 Q Q Conventional Oven Use an Oven......................................................... 109.6 20.3 14.9 5.4 More Than Once a Day..................................... 8.9 1.4 1.2 0.3 Once a Day.......................................................

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Total...............................................................  

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

47.1 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 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 1.......................................................... 22.5 9.1 3.6 6.0 3.8 2.......................................................... 4.0 1.5 0.6 1.3 0.7 3 or More............................................. 0.7 0.3 Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 17.7 7.5 10.2 9.6 Flat-panel LCD.................................

262

Total........................................................  

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

111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351 West North Central........................... 7.9 1.4 913 789 329 751 745 337 South................................................... 40.7 7.8 881 752 572 942 873 797 South Atlantic................................... 21.7 4.9 875 707 522 1,035 934 926 East South Central........................... 6.9 0.7 Q Q Q 852 826 432 West South Central..........................

263

Total...............................................................  

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

0.7 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 1.......................................................... 22.5 7.7 4.3 1.1 2.4 2.......................................................... 4.0 1.5 0.9 Q 0.4 3 or More............................................. 0.7 Q Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 15.4 7.9 2.8 4.8 Flat-panel LCD.................................

264

Total.................................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day.............................. 8.2 2.9 2.5 1.3 0.5 1.0 2.4 4.6 2 Times A Day........................................... 24.6 6.5 7.0 4.3 3.2 3.6 4.8 10.3 Once a Day................................................ 42.3 8.8 9.8 8.7 5.1 10.0 5.0 12.9 A Few Times Each Week........................... 27.2 5.6 7.2 4.7 3.3 6.3 3.2 7.5 About Once a Week................................... 3.9 1.1 1.1 0.6 0.5 0.6 0.4 1.4 Less Than Once a Week............................ 4.1 1.3 1.0 0.9 0.5 0.4 0.7 1.4 No Hot Meals Cooked................................ 0.9 0.5 Q Q Q Q 0.2 0.5 Conventional Oven Use an Oven.............................................. 109.6 26.1 28.5 20.2 12.9 21.8 16.3 37.8 More Than Once a Day..........................

265

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 System.............................................. 65.9 3.7 2.6 6.1 6.8 11.2 13.2 13.9 8.2 Without a Heat Pump.................................. 53.5 3.6 2.3 5.5 5.8 9.5 10.1 10.3 6.4 With a Heat Pump....................................... 12.3 Q 0.3 0.6 1.0 1.7 3.1 3.6 1.7 Window/Wall Units....................................... 28.9 7.3 3.2 4.5 3.7 4.8 3.0 1.9 0.7 1 Unit..........................................................

266

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 Central.................. 17.7 14.5 2,864 2,217 1,490 2,514 1,715 1,408 907 839 553 West North Central................. 7.9 6.4 2,729 2,289 1,924 1,806 1,510 1,085 1,299 1,113 1,059 South.......................................... 40.7 33.0 2,707 1,849 1,563 1,605 1,350 954 1,064 970 685 South Atlantic......................... 21.7 16.8 2,945 1,996 1,695 1,573 1,359 909 1,044 955

267

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 16.5 12.8 3.8 Use Cooling Equipment............................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it............................. 1.9 0.3 Q Q Type of Air-Conditioning Equipment 1, 2 Central System.......................................................... 65.9 6.0 5.2 0.8 Without a Heat Pump.............................................. 53.5 5.5 4.8 0.7 With a Heat Pump................................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................... 28.9 10.7 7.6 3.1 1 Unit.......................................................................

268

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... 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 Pump............................................. 53.5 21.2 9.7 13.7 8.9 With a Heat Pump................................................. 12.3 4.6 1.2 2.8 3.6 Window/Wall Units.................................................. 28.9 13.4 5.6 3.9 6.1 1 Unit.....................................................................

269

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... 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 Pump............................................. 53.5 8.7 3.2 5.5 With a Heat Pump................................................. 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit..................................................................... 14.5 2.9 0.5 2.4 2 Units...................................................................

270

Total..................................................................  

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

78.1 78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat Pump.................................. 53.5 41.1 34.8 2.1 0.5 1.2 2.6 With a Heat Pump....................................... 12.3 10.6 9.1 0.4 Q 0.3 0.6 Window/Wall Units....................................... 28.9 16.5 12.0 1.3 1.0 0.4 1.7 1 Unit.......................................................... 14.5 7.2 5.4 0.5 0.2 Q 0.9 2 Units.........................................................

271

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... 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 Pump............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................. 12.3 9.0 6.7 1.4 0.9 Window/Wall Units.................................................. 28.9 8.0 3.4 1.7 2.9 1 Unit.....................................................................

272

Total........................................................................  

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

4.2 4.2 7.6 16.6 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.7 Have Main Space Heating Equipment.................. 109.8 23.4 7.5 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One Housing Unit................................... 42.9 11.1 3.8 7.3 For Two Housing Units................................. 1.8 0.3 Q Q Steam or Hot Water System............................. 8.2 0.6 0.3 0.3 For One Housing Unit................................... 5.1 0.4 0.2 0.1 For Two Housing Units.................................

273

Total..............................................................  

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

Do Not Have Cooling Equipment................ Do Not Have Cooling Equipment................ 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit...................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units....................................................

274

Idle Operating Total Stream Day  

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

3 3 Idle Operating Total Stream Day Barrels per Idle Operating Total Calendar Day Barrels per Atmospheric Crude Oil Distillation Capacity Idle Operating Total Operable Refineries Number of State and PAD District a b b 11 10 1 1,293,200 1,265,200 28,000 1,361,700 1,329,700 32,000 ............................................................................................................................................... PAD District I 1 1 0 182,200 182,200 0 190,200 190,200 0 ................................................................................................................................................................................................................................................................................................ Delaware......................................

275

FALL AND SPRING Per Hour # Hours # Semesters Total  

E-Print Network [OSTI]

$4,060.00 FALL AND SPRING Per Hour # Hours # Semesters Total Tuition $765.00 15 2 $22,950.00 ISS, Engineering, Journalism & Mass Communications, Music and Social Welfare fees. These amounts do NOT include to complete at least 12 hours each fall and spring semester. Calculations are based on 15 hours (an average

276

Daily Dialysis Lessons from a Randomized, Controlled Trial  

Science Journals Connector (OSTI)

...as urea, which rapidly equilibrate among body-fluid compartments. With thrice-weekly hemodialysis, the relatively long interval between dialysis sessions results in a "peak-and-valley" effect characterized by fluctuations in the levels of toxins and body-fluid volume, affecting the ability of patients... The frequency of dialysis was established at three times a week in 1965,1 and this frequency has been used in most centers around the world. Soon after the establishment of this dialysis schedule, an analogue simulation concluded that daily (also known as ...

Twardowski Z.J.; Misra M.

2010-12-09T23:59:59.000Z

277

Higher-order averaging, formal series and numerical integration II  

E-Print Network [OSTI]

systems of ordinary differential equations with d 1 non- resonant constant frequencies. Formal series frequency and four resonant fast frequencies. Keywords and sentences: Averaging, high-order averaging, quasi Schumann, 35170 Bruz, France. Email: Philippe.Chartier@inria.fr Konputazio Zientziak eta A. A. Saila

Murua, Ander

278

Averaged dynamics of ultra-relativisitc charged particles beams  

E-Print Network [OSTI]

In this thesis, we consider the suitability of using the charged cold fluid model in the description of ultra-relativistic beams. The method that we have used is the following. Firstly, the necessary notions of kinetic theory and differential geometry of second order differential equations are explained. Then an averaging procedure is applied to a connection associated with the Lorentz force equation. The result of this averaging is an affine connection on the space-time manifold. The corresponding geodesic equation defines the averaged Lorentz force equation. We prove that for ultra-relativistic beams described by narrow distribution functions, the solutions of both equations are similar. This fact justifies the replacement of the Lorentz force equation by the simpler {\\it averaged Lorentz force equation}. After this, for each of these models we associate the corresponding kinetic model, which are based on the Vlasov equation and {\\it averaged Vlasov equation} respectively. The averaged Vlasov equation is simpler than the original Vlasov equation. This fact allows us to prove that the differential operation defining the averaged charged cold fluid equation is controlled by the {\\it diameter of the distribution function}, by powers of the {\\it energy of the beam} and by the time of evolution $t$. We show that the Vlasov equation and the averaged Vlasov equation have similar solutions, when the initial conditions are the same. Finally, as an application of the {\\it averaged Lorentz force equation} we re-derive the beam dynamics formalism used in accelerator physics from the Jacobi equation of the averaged Lorentz force equation.

Ricardo Gallego Torrom

2012-06-19T23:59:59.000Z

279

total energy | OpenEI  

Open Energy Info (EERE)

total energy total energy Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed

280

Climbing and the daily energy cost of locomotion in wild chimpanzees: implications for hominoid locomotor evolution  

E-Print Network [OSTI]

Climbing and the daily energy cost of locomotion in wild chimpanzees: implications for hominoid in a population of wild chimpanzees and used published equations to calculate the relative daily energy costs, specifically whether arboreal adaptations serve to minimize daily locomotor energy costs by decreasing

Pontzer, Herman

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Measurement of average resistance in underwater breathing apparatus  

SciTech Connect (OSTI)

Underwater Breathing Apparatus (UBA) have long been characterized by the mechanical work done on them during simulated breathing. For 20 years, the work of breathing has been divided by tidal volume to yield what is properly considered a volume-averaged pressure. The authors assert that when volume-averaged pressure is divided by a factor proportional to ventilation, the result is a measure of flow resistance averaged over an entire breath. This point is illustrated with both theoretical and actual pressure-volume and pressure-flow curves for a MK 16 closed-circuit UBA.

Clarke, J.R. [Navy Experimental Diving Unit, Panama City, FL (United States)

1996-09-01T23:59:59.000Z

282

Time average vibration fringe analysis using Hilbert transformation  

SciTech Connect (OSTI)

Quantitative phase information from a single interferogram can be obtained using the Hilbert transform (HT). We have applied the HT method for quantitative evaluation of Bessel fringes obtained in time average TV holography. The method requires only one fringe pattern for the extraction of vibration amplitude and reduces the complexity in quantifying the data experienced in the time average reference bias modulation method, which uses multiple fringe frames. The technique is demonstrated for the measurement of out-of-plane vibration amplitude on a small scale specimen using a time average microscopic TV holography system.

Kumar, Upputuri Paul; Mohan, Nandigana Krishna; Kothiyal, Mahendra Prasad

2010-10-20T23:59:59.000Z

283

Total Sky Imager (TSI) Handbook  

SciTech Connect (OSTI)

The total sky imager (TSI) provides time series of hemispheric sky images during daylight hours and retrievals of fractional sky cover for periods when the solar elevation is greater than 10 degrees.

Morris, VR

2005-06-01T23:59:59.000Z

284

Form EIA-930 HOURLY AND DAILY BALANCING AUTHORITY OPERATIONS REPORT  

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

930 930 HOURLY AND DAILY BALANCING AUTHORITY OPERATIONS REPORT INSTRUCTIONS Due Date: mm/dd/yyyy Approved: OMB No. 1905-0129 Approval Expires: 10/31/2016 Burden: 0.19 hours Page 1 Draft for Discussion only PURPOSE Form EIA-930 requires Internet posting of hourly balancing authority operating data. The posted data are used to monitor the current status and trends of the electric power industry, and to support enhancement of electric system operations. REQUIRED RESPONDENTS For the contiguous United States: all entities that are listed in NERC's Compliance Registry as a balancing authority must post balancing authority operating information required by this survey. Other than the Midwest ISO (MISO), registered balancing authorities that are parties

285

Averaging Spacetime: Where do we go from here?  

E-Print Network [OSTI]

The construction of an averaged theory of gravity based on Einstein's General Relativity is very difficult due to the non-linear nature of the gravitational field equations. This problem is further exacerbated by the difficulty in defining a mathematically precise covariant averaging procedure for tensor fields over differentiable manifolds. Together, these two ideas have been called the averaging problem for General Relativity. In the first part of the talk, an attempt to review some the various approaches to this problem will be given, highlighting strengths, weaknesses, and commonalities between them. In the second part of the talk, an argument will be made, that if one wishes to develop a well-defined averaging procedure, one may choose to parallel transport along geodesics with respect to the Levi-Cevita connection or, use the Weitzenb\\"ock connection and ensure the transportation is independent of path. The talk concludes with some open questions to generate further discussion.

R. J. van den Hoogen

2010-04-15T23:59:59.000Z

286

U.S. average gasoline price up slightly  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

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....

287

Fact #671: April 18, 2011 Average Truck Speeds  

Broader source: Energy.gov [DOE]

The Federal Highway Administration studies traffic volume and flow on major truck routes by tracking more than 500,000 trucks. The average speed of trucks on selected interstate highways is between...

288

Abstract Interpretation for Worst and Average Case Analysis  

E-Print Network [OSTI]

energy usage whilst bounding the average number of requests waiting to be served. PRISM is used phase extracts a control flow graph ­ for some classes of language this may already involve an abstract

Di Pierro, Alessandra

289

Weighted Coherence: A More Effective Measure Than Average Coherence  

Science Journals Connector (OSTI)

In this study, we evaluated the effectiveness of the statistic, Weighted Coherence in relation to the average or mean coherence in a particular frequency band after cross- ... using cross-spectral analysis is r...

Vikram Kumar Yeragani; Arindam Barua

2003-12-01T23:59:59.000Z

290

Table 17. Recoverable Coal Reserves and Average Recovery Percentage...  

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

Recoverable Coal Reserves and Average Recovery Percentage at Producing U.S. Mines by Mine Production Range and Mine Type, 2012 (million short tons) U.S. Energy Information...

291

Table A44. Average Prices of Purchased Electricity and Steam  

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

4. Average Prices of Purchased Electricity and Steam" 4. Average Prices of Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Dollars per Physical Units)" ," Electricity",," Steam" ," (kWh)",," (million Btu)" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors"

292

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.

293

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 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 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History Conventional, Average 3.030 3.137 3.122 3.063 3.042 2.972 1994-2013 Conventional Regular 3.005 3.116 3.102 3.040 3.017 2.948 1994-2013 Conventional Midgrade 3.167 3.256 3.239 3.200 3.193 3.121 1994-2013 Conventional Premium 3.269 3.354 3.327 3.291 3.274 3.203 1994-2013 Oxygenated, Average - - - - - - 1994-2013 Oxygenated Regular - - - - - - 1994-2013 Oxygenated Midgrade - - - - - - 1994-2013

294

Table 10. Average Price of U.S. Steam Coal Exports  

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

Average Price of U.S. Steam Coal Exports Average Price of U.S. Steam Coal Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 10. Average Price of U.S. Steam Coal Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Continent and Country of Destination April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change North America Total 65.10 63.67 73.81 64.48 78.90 -18.3 Canada* 59.34 55.22 63.02 57.57 73.63 -21.8 Dominican Republic 78.47 74.41 73.89 75.40 76.61 -1.6 Honduras - 54.58 54.43 54.58 54.43 0.3 Jamaica 480.00 54.43 - 54.72 55.42 -1.3 Mexico 69.42 73.33 82.64 70.83 86.44 -18.1 Other** 80.33 389.30 70.37 82.45 76.10 8.3 South America Total 79.44 77.85 70.55

295

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

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

Average Price of U.S. Metallurgical Coal Exports Average Price of U.S. Metallurgical Coal Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 12. Average Price of U.S. Metallurgical Coal Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Continent and Country of Destination April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change North America Total 92.50 99.40 146.56 94.82 140.70 -32.6 Canada* 99.83 125.20 142.46 106.43 138.19 -23.0 Dominican Republic 114.60 77.21 - 77.27 - - Mexico 78.93 78.54 180.76 78.77 153.65 -48.7 South America Total 119.26 117.51 167.05 118.30 168.12 -29.6 Argentina 146.70 131.08 182.47 137.36 196.37 -30.1 Brazil 119.21 117.38 165.61 118.20

296

Table 7.1 Average Prices of Purchased Energy Sources, 2010  

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

Average Prices of Purchased Energy Sources, 2010; 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 Physical Units. Coal NAICS TOTAL Acetylene Breeze Total Anthracite Code(a) Subsector and Industry (million Btu) (cu ft) (short tons) (short tons) (short tons) Total United States 311 Food 9.12 0.26 0.00 53.43 90.85 3112 Grain and Oilseed Milling 6.30 0.29 0.00 51.34 50.47 311221 Wet Corn Milling 4.87 0.48 0.00 47.74 50.47 31131 Sugar Manufacturing 5.02 0.31 0.00 53.34 236.66 3114 Fruit and Vegetable Preserving and Specialty Foods 9.78 0.27 0.00 90.59 0.00 3115 Dairy Products 11.21 0.10 0.00 103.12 0.00 3116 Animal Slaughtering and Processing

297

"2012 Average Monthly Bill- Residential"  

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

Residential" Residential" "(Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U)" "State","Number of Customers","Average Monthly Consumption (kWh)","Average Price (cents/kWh)","Average Monthly Bill (Dollar and cents)" "New England",6203726,634.13095,15.713593,99.644755 "Connecticut",1454651,730.85302,17.343298,126.75402 "Maine",703770,530.56349,14.658797,77.774225 "Massachusetts",2699141,627.15845,14.912724,93.52641 "New Hampshire",601697,614.81776,16.070168,98.802249 "Rhode Island",435448,597.34783,14.404061,86.042344 "Vermont",309019,565.03618,17.006075,96.090478 "Middle Atlantic",15727423,700.63673,15.272654,107.00582

298

"2012 Average Monthly Bill- Industrial"  

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

Industrial" Industrial" "(Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U)" "State","Number of Customers","Average Monthly Consumption (kWh)","Average Price (cents/kWh)","Average Monthly Bill (Dollar and cents)" "New England",34164,67854.037,11.83487,8030.4373 "Connecticut",4647,63947.063,12.672933,8103.9685 "Maine",2780,90741.457,7.9819499,7242.9376 "Massachusetts",21145,66710.826,12.566635,8383.3057 "New Hampshire",3444,47247.217,11.83228,5590.423 "Rhode Island",1927,39935.911,10.676724,4263.8471 "Vermont",221,536044.12,9.9796777,53495.475 "Middle Atlantic",45836,126368.14,7.4903534,9465.42 "New Jersey",12729,50817.89,10.516509,5344.2677

299

Time-average TV holography for vibration fringe analysis  

SciTech Connect (OSTI)

Time-average TV holography is widely used method for vibration measurement. The method generates speckle correlation time-averaged J0 fringes that can be used for full-field qualitative visualization of mode shapes at resonant frequencies of an object under harmonic excitation. In order to map the amplitudes of vibration, quantitative evaluation of the time-averaged fringe pattern is desired. A quantitative evaluation procedure based on the phase-shifting technique used in two beam interferometry has also been adopted for this application with some modification. The existing procedure requires a large number of frames to be recorded for implementation. We propose a procedure that will reduce the number of frames required for the analysis. The TV holographic system used and the experimental results obtained with it on an edge-clamped, sinusoidally excited square aluminium plate sample are discussed.

Kumar, Upputuri Paul; Kalyani, Yanam; Mohan, Nandigana Krishna; Kothiyal, Mahendra Prasad

2009-06-01T23:59:59.000Z

300

Globally Averaged Atmospheric CFC-11 Concentrations: Monthly and Annual  

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

Chlorofluorocarbons » Chlorofluorocarbons » Atmospheric CFC-11 Concentrations Globally Averaged Atmospheric CFC-11 Concentrations: Monthly and Annual Data for the Period 1975-1992 DOI: 10.3334/CDIAC/atg.db1010 data Data (DB1010) Investigator M. A. K. Khalil and R. A. Rasmussen Description This data set presents globally averaged atmospheric concentrations of chlorofluorocarbon 11, known also as CFC-11 or F-11 (chemical name: trichlorofluoromethane; formula: CCl3F). The monthly global average data are derived from flask air samples collected at eight sites in six locations over the period August 1980-July 1992. The sites are Barrow (Alaska), Cape Meares (Oregon), Cape Kumukahi and Mauna Loa (Hawaii), Cape Matatula (American Samoa), Cape Grim (Tasmania), Palmer Station, and the

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Comparison of Average Transport and Dispersion Among a Gaussian, a  

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

Comparison of Average Transport and Dispersion Among a Gaussian, a Comparison of Average Transport and Dispersion Among a Gaussian, a Two-Dimensional, and a Three-Dimensional Model Comparison of Average Transport and Dispersion Among a Gaussian, a Two-Dimensional, and a Three-Dimensional Model The Nuclear Regulatory Commission's (NRC's) code for predicting off-site consequences, MACCS2 (Chanin, et al. 1998) (MELCOR Accident Consequence Code System, Version 2), uses a simplified model for atmospheric transport and d ispersion (ATD), that is, a straight-line Gaussian model. The MACCS2 calculations are used by the NRC for planning purposes, for cost-benefit analyses, and in level-3 probabilistic risk analyses (PRAs). The MACCS2 ATD model has been criticized as being overly simplistic, even for its purposes. The justification for its use has been

302

High average power scaleable thin-disk laser  

DOE Patents [OSTI]

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.

Beach, Raymond J. (Livermore, CA); Honea, Eric C. (Sunol, CA); Bibeau, Camille (Dublin, CA); Payne, Stephen A. (Castro Valley, CA); Powell, Howard (Livermore, CA); Krupke, William F. (Pleasanton, CA); Sutton, Steven B. (Manteca, CA)

2002-01-01T23:59:59.000Z

303

Averaged equations for Josephson junction series arrays with LRC load  

E-Print Network [OSTI]

We derive the averaged equations describing a series array of Josephson junctions shunted by a parallel inductor-resistor-capacitor load. We assume that the junctions have negligable capacitance ($\\beta = 0$), and derive averaged equations which turn out to be completely tractable: in particular the stability of both in-phase and splay states depends on a single parameter, $\\del$. We find an explicit expression for $\\delta$ in terms of the load parameters and the bias current. We recover (and refine) a common claim found in the technical literature, that the in-phase state is stable for inductive loads and unstable for capacitive loads.

Kurt Wiesenfeld; James W. Swift

1994-08-26T23:59:59.000Z

304

An investigation of nonlinear xenon oscillation by method of averaging  

Science Journals Connector (OSTI)

A nonlinear analysis of xenon-temperature controlled nuclear reactor dynamics is presented. The set of equations in question belongs to a general class of rate equations with quadratic nonlinearities. Boundedness of the solutions is examined. The mean value of periodic solutions for the flux is shown to be always less than the equilibrium value. The Bogoliubov's method of averaging as extended by Case is applied to obtain approximate solutions. The mechanism of the existence of relaxation oscillations in the linear stability region is analyzed. Computer calculations are performed and found in good agreement with the approximate solutions obtained by means of the method of averaging.

Yoshiro Asahi; A.Ziya Akcasu

1973-01-01T23:59:59.000Z

305

"2012 Retail Power Marketers Sales- Total"  

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

Total" Total" "(Data from form EIA-861 schedule 4B)" "Entity","State","Ownership","Customers (Count)","Sales (Megawatthours)","Revenues (Thousands Dollars)","Average Price (cents/kWh)" "3 Phases Renewables","CA","Power Marketer",354,148820,7268.5,4.8840882 "Calpine Power America LLC","CA","Power Marketer",1,1072508,54458,5.0776311 "City of Corona - (CA)","CA","Municipal",859,65933,5749.5,8.720216 "Commerce Energy, Inc.","CA","Power Marketer",23386,596604,37753,6.3279831 "Constellation NewEnergy, Inc","CA","Power Marketer",362,4777373,250287.4,5.2390173

306

"2012 Utility Bundled Retail Sales- Total"  

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

Total" Total" "(Data from forms EIA-861- schedules 4A & 4D and EIA-861S)" "Entity","State","Ownership","Customers (Count)","Sales (Megawatthours)","Revenues (Thousands Dollars)","Average Price (cents/kWh)" "Alaska Electric Light&Power Co","AK","Investor Owned",16180,399144,41820,10.477422 "Alaska Power and Telephone Co","AK","Investor Owned",6976,64788,18175,28.053035 "Alaska Village Elec Coop, Inc","AK","Cooperative",7923,73956,42708,57.74785 "Anchorage Municipal Light and Power","AK","Municipal",30747,1100665,100959.2,9.1725639 "Barrow Utils & Elec Coop, Inc","AK","Cooperative",1871,49580,5293,10.675676

307

Daily HMS Extremes in Met Data - Hanford Site  

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

Sun Feb 01 00:04:15 PST 2015 For the day: Sat Jan 31 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 15.6 0:15 39.7 15:00 35.4 7:00 0.00 2 EOC 17.1 6:00 36.3...

308

Daily HMS Extremes in Met Data - Hanford Site  

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

Mon Jan 12 00:04:15 PST 2015 For the day: Sun Jan 11 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 11.9 22:30 40.2 15:15 32.2 5:00 0.00 2 EOC 14.6 20:00 37.2...

309

Daily HMS Extremes in Met Data - Hanford Site  

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

Thu Jan 08 00:04:15 PST 2015 For the day: Wed Jan 07 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 11.4 14:15 41.3 14:00 25.0 7:15 0.00 2 EOC 15.0 1:15 42.3...

310

Daily HMS Extremes in Met Data - Hanford Site  

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

Wed Jan 14 00:04:15 PST 2015 For the day: Tue Jan 13 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 10.8 16:45 37.5 14:15 34.1 7:30 0.00 2 EOC 9.3 23:30 38.8...

311

Daily HMS Extremes in Met Data - Hanford Site  

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

Fri Jan 09 00:04:21 PST 2015 For the day: Thu Jan 08 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 16.3 21:00 35.4 0:00 31.7 0:15 0.00 2 EOC 22.0 22:30 34.8...

312

Daily HMS Extremes in Met Data - Hanford Site  

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

Tue Jan 13 00:04:15 PST 2015 For the day: Mon Jan 12 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 10.2 19:15 42.7 13:45 33.0 3:00 0.00 2 EOC 10.0 17:30 39.1...

313

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 from Sources Waste Gases Waste Oils Industrial Wood Byproducts and NAICS Coal Subbituminous Coal Petroleum Electricity from Local Other than Distillate Diesel Distillate Residual Blast Coke Oven (excluding or LPG and Natural Gas from Local

314

Residual Fuel Oil Prices, Average - Sales to End Users  

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

Product/Sales Type: Residual Fuel, Average - Sales to End Users Residual Fuel, Average - Sales for Resale Sulfur Less Than or Equal to 1% - Sales to End Users Sulfur Less Than or Equal to 1% - Sales for Resale Sulfur Greater Than 1% - Sales to End Users Sulfur Greater Than 1% - Sales for Resale Period: Monthly Annual Product/Sales Type: Residual Fuel, Average - Sales to End Users Residual Fuel, Average - Sales for Resale Sulfur Less Than or Equal to 1% - Sales to End Users Sulfur Less Than or Equal to 1% - Sales for Resale Sulfur Greater Than 1% - Sales to End Users Sulfur Greater Than 1% - Sales for Resale Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product/Sales Type Area Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History U.S. - - - - - - 1983-2013 East Coast (PADD 1) - - - - - - 1983-2013 New England (PADD 1A) - - - - - - 1983-2013 Connecticut - - - - - - 1983-2013 Maine - - - - - - 1983-2013 Massachusetts - - - - - - 1983-2013

315

Navy Estimated Average Hourly Load Profile by Month (in MW)  

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

Navy Estimated Average Hourly Load Profile by Month (in MW) MONTH HE1 HE2 HE3 HE4 HE5 HE6 HE7 HE8 HE9 HE10 HE11 HE12 HE13 HE14 HE15 HE16 HE17 HE18 HE19 HE20 HE21 HE22 HE23 HE24...

316

Disk-averaged Spectra & light-curves of Earth  

E-Print Network [OSTI]

We are using computer models to explore the observational sensitivity to changes in atmospheric and surface properties, and the detectability of biosignatures, in the globally averaged spectra and light-curves of the Earth. Using AIRS (Atmospheric Infrared Sounder) data, as input for atmospheric and surface properties, we have generated spatially resolved high-resolution synthetic spectra using the SMART radiative transfer model, for a variety of conditions, from the UV to the far-IR (beyond the range of current Earth-based satellite data). We have then averaged over the visible disk for a number of different viewing geometries to quantify the sensitivity to surface types and atmospheric features as a function of viewing geometry, and spatial and spectral resolution. These results have been processed with an instrument simulator to improve our understanding of the detectable characteristics of Earth-like planets as viewed by the first generation extrasolar terrestrial planet detection and characterization missions (Terrestrial Planet Finder/Darwin and Life finder). The wavelength range of our results are modelled over are applicable to both the proposed visible coronograph and mid-infrared interferometer TPF architectures. We have validated this model against disk-averaged observations by the Mars Global Surveyor Thermal Emission Spectrometer (MGS TES). This model was also used to analyze Earth-shine data for detectability of planetary characteristics and biosignatures in disk-averaged spectra.

G. Tinetti; V. S. Meadows; D. Crisp; W. Fong; N. Kiang; E. Fishbein; T. Velusamy; E. Bosc; M. Turnbull

2005-02-11T23:59:59.000Z

317

Averaging of Temporal Memories by Rats Dale N. Swanton  

E-Print Network [OSTI]

Averaging of Temporal Memories by Rats Dale N. Swanton Villanova University Cynthia M. Gooch University of Pennsylvania School of Medicine Matthew S. Matell Villanova University Rats were trained on a mixed fixed-interval schedule in which stimulus A (tone or light) indicated food availability after 10

Matell, Matthew S.

318

IE 361 Module 15 The Average Run Length Concept  

E-Print Network [OSTI]

IE 361 Module 15 The Average Run Length Concept Reading: Section 3.5 of Statistical Quality Assurance Methods for Engineers Prof. Steve Vardeman and Prof. Max Morris Iowa State University Vardeman Electric set of alarm rules to a control charting scheme? The most e¤ective means known for making

Vardeman, Stephen B.

319

Performance Period Total Fee Paid  

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

Period Period Total Fee Paid 4/29/2012 - 9/30/2012 $418,348 10/1/2012 - 9/30/2013 $0 10/1/2013 - 9/30/2014 $0 10/1/2014 - 9/30/2015 $0 10/1/2015 - 9/30/2016 $0 Cumulative Fee Paid $418,348 Contract Type: Cost Plus Award Fee Contract Period: $116,769,139 November 2011 - September 2016 $475,395 $0 Fee Information Total Estimated Contract Cost $1,141,623 $1,140,948 $1,140,948 $5,039,862 $1,140,948 Maximum Fee $5,039,862 Minimum Fee Fee Available Portage, Inc. DE-DT0002936 EM Contractor Fee Site: MOAB Uranium Mill Tailings - MOAB, UT Contract Name: MOAB Uranium Mill Tailings Remedial Action Contract September 2013 Contractor: Contract Number:

320

Buildings","Total  

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

L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings*",54068,51570,45773,6746,34910,1161,3725,779 "Building Floorspace" "(Square Feet)" "1,001 to 5,000",6272,5718,4824,986,3767,50,22,54 "5,001 to 10,000",7299,6667,5728,1240,4341,61,169,45 "10,001 to 25,000",10829,10350,8544,1495,6442,154,553,"Q"

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

ARM - Measurement - Total cloud water  

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

cloud water 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 list of all available measurements, including those recorded for diagnostic or quality assurance purposes. External Instruments NCEPGFS : National Centers for Environment Prediction Global Forecast System Field Campaign Instruments CSI : Cloud Spectrometer and Impactor PDI : Phase Doppler Interferometer

322

Buildings","Total  

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

L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",61707,58693,49779,6496,37150,3058,5343,1913 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6750,5836,4878,757,3838,231,109,162 "5,001 to 10,000 ..............",7940,7166,5369,1044,4073,288,160,109 "10,001 to 25,000 .............",10534,9773,7783,1312,5712,358,633,232

323

Buildings","Total  

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

L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",64783,62060,51342,5556,37918,4004,4950,2403 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6789,6038,4826,678,3932,206,76,124 "5,001 to 10,000 ..............",6585,6090,4974,739,3829,192,238,248 "10,001 to 25,000 .............",11535,11229,8618,1197,6525,454,506,289

324

McGinness Hills Well 27A-10 Daily Drilling Report Data  

SciTech Connect (OSTI)

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

Knudsen, Steven

2014-03-25T23:59:59.000Z

325

McGinness Hills Well 27A-10 Daily Drilling Report Data  

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

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

Knudsen, Steven

326

E-Print Network 3.0 - amplitude daily geomagnetic Sample Search...  

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

level of geomagnetic disturbances. The anomalies were registered daily... -speed solar wind, mag- netic field disturbances in the interplanetary space and in the geomagnetic...

327

Future projections of daily precipitation and its extremes in simulations of 21st century climate change.  

E-Print Network [OSTI]

??The current generation of climate models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) is used to assess the future changes in daily precipitation (more)

Yin, Lei

2013-01-01T23:59:59.000Z

328

Arctic daily temperature and precipitation extremes: Observed and simulated physical behavior.  

E-Print Network [OSTI]

??ARCTIC DAILY TEMPERATURE AND PRECIPITATION EXTREMES: OBSERVED AND SIMULATED PHYSICAL BEHAVIOR Justin M. Glisan Department of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa (more)

Glisan, Justin Michael

2012-01-01T23:59:59.000Z

329

Climate: monthly and annual average cooling degree days above 10° C GIS  

Open Energy Info (EERE)

cooling degree days above 10° C GIS cooling degree days above 10° C GIS data at one-degree resolution of the World from NASA/SSE Dataset Summary Description (Abstract): Cooling Degree Days above 10° C (degree days)The monthly accumulation of degrees when the daily mean temperature is above 10° C.NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly Average & Annual Sum (July 1983 - June 2005)Parameter: Cooling Degree Days Above 10 degrees C (degree days)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180,

330

Climate: monthly and annual average heating degree days below 18° C GIS  

Open Energy Info (EERE)

heating degree days below 18° C GIS heating degree days below 18° C GIS data at one-degree resolution of the World from NASA/SSE Dataset Summary Description (Abstract): Heating Degree Days below 18° C (degree days)The monthly accumulation of degrees when the daily mean temperature is below 18° C.NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly Average & Annual Sum (July 1983 - June 2005)Parameter: Heating Degree Days Below 18 degrees C (degree days)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180,

331

Gas/particle partitioning of total alkyl nitrates observed with TD-LIF in Bakersfield  

E-Print Network [OSTI]

total AN (gas + aerosol) and ANaer show that on average 21% of ANs are in the condensed phaseGas/particle partitioning of total alkyl nitrates observed with TD-LIF in Bakersfield A. W. Rollins samples. These measurements show that ANs are a ubiquitous component of the OA with the ­ONO2 subunit

Cohen, Ronald C.

332

Receptor modeling assessment of particle total exposure assessment methodology data  

SciTech Connect (OSTI)

Data from the 1991 Particle Total Exposure Assessment Methodology (PTEAM) study in Riverside, CA, were analyzed using a new receptor modeling method. In this study, ambient (outdoor), indoor, and personal particulate matter (PM) concentrations and elemental concentrations of PM{sub 2.5} and PM{sub 10} were measured for a number of participants. These measurements made is possible to relate the pollution to which people were exposed throughout their daily activities with the outdoor air conditions. Personal daytime concentrations of the PM{sub 10} and majority of elements were significantly higher than outdoor or indoor concentrations, suggesting that a significant part of personal aerosol exposure is the result of personal daily activities. Possible sources of additional particulate mass include resuspension of particles that penetrate from the outdoors and formation of new particles during cooking, smoking, etc. Positive matrix factorization analysis was performed to describe the sources of personal exposure. To identify relative contribution of different sources, regression of the particulate matter mass against the factor contributions was performed. Major sources of PM{sub 2.5} were oil combustion, nonferrous metal operations, and motor vehicles. The mass contributions of particles from these sources were similar for outdoor air and personal exposure. Personal exposure to particles from these sources can be controlled by changing outdoor sources. The primary source of PM{sub 10} was soil.

Yakovleva, E.; Hopke, P.K.; Wallace, L.

1999-10-15T23:59:59.000Z

333

Table 7.4 Average Prices of Selected Purchased Energy Sources, 2010;  

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

4 Average Prices of Selected Purchased Energy Sources, 2010; 4 Average Prices of Selected Purchased Energy Sources, 2010; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: U.S. Dollars per Physical Units. Residual Distillate LPG and Economic Electricity Fuel Oil Fuel Oil(b) Natural Gas(c) NGL(d) Coal Characteristic(a) (kWh) (gallons) (gallons) (1000 cu ft) (gallons) (short tons) Total United States Value of Shipments and Receipts (million dollars) Under 20 0.093 1.55 2.58 6.64 1.80 78.29 20-49 0.075 1.66 2.45 6.44 1.80 80.13 50-99 0.070 1.64 1.79 6.04 2.19 68.10 100-249 0.061 1.62 2.38 5.51 1.69 100.69 250-499 0.056 1.69 2.41 5.54 1.59 92.51 500 and Over 0.054 1.54 2.35 5.08 1.15 96.25 Total

334

A Multivariate Moving Average Control Chart for Photovoltaic Processes  

E-Print Network [OSTI]

AbstractFor the electrical metrics that describe photovoltaic cell performance are inherently multivariate in nature, use of a univariate, or one variable, statistical process control chart can have important limitations. Development of a comprehensive process control strategy is known to be significantly beneficial to reducing process variability that ultimately drives up the manufacturing cost photovoltaic cells. The multivariate moving average or MMA chart, is applied to the electrical metrics of photovoltaic cells to illustrate the improved sensitivity on process variability this method of control charting offers. The result show the ability of the MMA chart to expand to as any variables as needed, suggests an application with multiple photovoltaic electrical metrics being used in concert to determine the processes state of control. KeywordsThe multivariate moving average control chart, Photovoltaic processes control, Multivariate system. I.

Chunchom Pongchavalit

335

A holographic proof of the averaged null energy condition  

E-Print Network [OSTI]

The averaged null energy conditions (ANEC) states that, along a complete null curve, the negative energy fluctuations of a quantum field must be balanced by positive energy fluctuations. We use the AdS/CFT correspondence to prove the ANEC for a class of strongly coupled conformal field theories in flat spacetime. A violation of the ANEC in the field theory would lead to acausal propagation of signals in the bulk.

William R. Kelly; Aron C. Wall

2014-11-03T23:59:59.000Z

336

Average dynamics of a finite set of coupled phase oscillators  

SciTech Connect (OSTI)

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.

Dima, Germn C., E-mail: gdima@df.uba.ar; Mindlin, Gabriel B. [Laboratorio de Sistemas Dinmicos, IFIBA y Departamento de Fsica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabelln 1, Ciudad Universitaria, Buenos Aires (Argentina)] [Laboratorio de Sistemas Dinmicos, IFIBA y Departamento de Fsica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabelln 1, Ciudad Universitaria, Buenos Aires (Argentina)

2014-06-15T23:59:59.000Z

337

Better than Average? - Green Building Certification in International Projects  

E-Print Network [OSTI]

8th International Conference for Enhanced Building Operations - ICEBO?08 Conference Center of the Federal Ministry of Economics and Technology Berlin, October 20 - 22, 2008 Dipl.-Ing. Oliver Baumann Ebert & Baumann Consulting Engineers, Inc.... An Enterprise of the Ebert-Consulting Group 1004 Pennsylvania Avenue, SE Washington, D.C. 20003, USA 00 12 02/ 6 08 - 13 34 o.baumann@eb-engineers.com Better than Average? - Green Building Certification in International Projects Green Building...

Baumann, O.

2008-01-01T23:59:59.000Z

338

RENORMALIZATION TECHNIQUES AND MEAN SQUARE AVERAGING, I. DETERMINISTIC EQUATIONS  

Science Journals Connector (OSTI)

...U2 - 1)u' by a linear expression clu + c2u' and using a time average, we find that...equation to (4.1) is given by U" + C2U' + U = 0, rT where C2 = lim f (a2 cos2...0, (4.5) we write g(u) = clu + c2u', where C, = lim g(u)udt/ f u...

Richard Bellman; John M. Richardson

1961-01-01T23:59:59.000Z

339

High Average Power, High Energy Short Pulse Fiber Laser System  

SciTech Connect (OSTI)

Recently continuous wave fiber laser systems with output powers in excess of 500W with good beam quality have been demonstrated [1]. High energy, ultrafast, chirped pulsed fiber laser systems have achieved record output energies of 1mJ [2]. However, these high-energy systems have not been scaled beyond a few watts of average output power. Fiber laser systems are attractive for many applications because they offer the promise of high efficiency, compact, robust systems that are turn key. Applications such as cutting, drilling and materials processing, front end systems for high energy pulsed lasers (such as petawatts) and laser based sources of high spatial coherence, high flux x-rays all require high energy short pulses and two of the three of these applications also require high average power. The challenge in creating a high energy chirped pulse fiber laser system is to find a way to scale the output energy while avoiding nonlinear effects and maintaining good beam quality in the amplifier fiber. To this end, our 3-year LDRD program sought to demonstrate a high energy, high average power fiber laser system. This work included exploring designs of large mode area optical fiber amplifiers for high energy systems as well as understanding the issues associated chirped pulse amplification in optical fiber amplifier systems.

Messerly, M J

2007-11-13T23:59:59.000Z

340

Total Adjusted Sales of Kerosene  

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

End Use: Total Residential Commercial Industrial Farm All Other Period: End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Solar total energy project Shenandoah  

SciTech Connect (OSTI)

This document presents the description of the final design for the Solar Total Energy System (STES) to be installed at the Shenandoah, Georgia, site for utilization by the Bleyle knitwear plant. The system is a fully cascaded total energy system design featuring high temperature paraboloidal dish solar collectors with a 235 concentration ratio, a steam Rankine cycle power conversion system capable of supplying 100 to 400 kW(e) output with an intermediate process steam take-off point, and a back pressure condenser for heating and cooling. The design also includes an integrated control system employing the supervisory control concept to allow maximum experimental flexibility. The system design criteria and requirements are presented including the performance criteria and operating requirements, environmental conditions of operation; interface requirements with the Bleyle plant and the Georgia Power Company lines; maintenance, reliability, and testing requirements; health and safety requirements; and other applicable ordinances and codes. The major subsystems of the STES are described including the Solar Collection Subysystem (SCS), the Power Conversion Subsystem (PCS), the Thermal Utilization Subsystem (TUS), the Control and Instrumentation Subsystem (CAIS), and the Electrical Subsystem (ES). Each of these sections include design criteria and operational requirements specific to the subsystem, including interface requirements with the other subsystems, maintenance and reliability requirements, and testing and acceptance criteria. (WHK)

None

1980-01-10T23:59:59.000Z

342

Grantee Total Number of Homes  

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

Grantee Grantee Total Number of Homes Weatherized through November 2011 [Recovery Act] Total Number of Homes Weatherized through November 2011 (Calendar Year 2009 - November 2011) [Recovery Act + Annual Program Funding] Alabama 6,704 7,867 1 Alaska 443 2,363 American Samoa 304 410 Arizona 6,354 7,518 Arkansas 5,231 6,949 California 41,649 50,002 Colorado 12,782 19,210 Connecticut 8,940 10,009 2 Delaware** 54 54 District of Columbia 962 1,399 Florida 18,953 20,075 Georgia 13,449 14,739 Guam 574 589 Hawaii 604 1,083 Idaho** 4,470 6,614 Illinois 35,530 44,493 Indiana** 18,768 21,689 Iowa 8,794 10,202 Kansas 6,339 7,638 Kentucky 7,639 10,902 Louisiana 4,698 6,946 Maine 5,130 6,664 Maryland 8,108 9,015 Massachusetts 17,687 21,645 Michigan 29,293 37,137 Minnesota 18,224 22,711 Mississippi 5,937 6,888 Missouri 17,334 20,319 Montana 3,310 6,860 Navajo Nation

343

Daily torpor in mice: high foraging costs trigger energy-saving hypothermia  

Science Journals Connector (OSTI)

...high foraging costs trigger energy-saving hypothermia Kristin A. Schubert...the use of daily torpor as an energy-saving strategy. The finding that daily...metabolic rate over time represented energy savings which ranged from 1-8 kJ d1...

2010-01-01T23:59:59.000Z

344

Daily routines of body mass gain in birds: 2. An experiment with reduced food availability  

E-Print Network [OSTI]

; published online 31 July 2006; MS. number: 8608R) Theoretical models predict that small birds should adjust daily patterns of body mass gain in response to environmental and internal factors. In a companion paper, we described a model on daily fattening that allows the analysis of precise changes in the shape

Carrascal, Luis M.

345

Intra-daily variations in volatility and transaction costs in the Credit Default Swap market  

E-Print Network [OSTI]

Intra-daily variations in volatility and transaction costs in the Credit Default Swap market Andras : Credit Default Swap, Intra-daily patterns, Stochastic transaction costs, Volatility, Interdealer market on the Microstructure of Financial Markets in Hong Kong, the 2008 Credit conference in Venice, the Third Annual Risk

Del Moral , Pierre

346

Statistical Characteristics of Daily Precipitation: Comparisons of Gridded and Point Datasets  

E-Print Network [OSTI]

Statistical Characteristics of Daily Precipitation: Comparisons of Gridded and Point Datasets Gauge Dataset (URD) and those of its nearest (rain gauge) station. To further examine differences between the two datasets, return periods of daily precipitation were calculated over a region encompassing

Roy Chowdhury, Rinku

347

ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan  

Science Journals Connector (OSTI)

...the advanced research WRF version 3Boulder, CONational...Semenov1991A serial approach to local stochastic weather modelsEcol...ELPIS-JP: a dataset of local-scale daily climate...developed a dataset of local-scale daily climate...relative humidity; and wind speed) at 938 sites in...

2012-01-01T23:59:59.000Z

348

Changes in daily temperature and precipitation extremes in central and south Asia  

E-Print Network [OSTI]

Changes in daily temperature and precipitation extremes in central and south Asia A. M. G. Klein in indices of climate extremes are studied on the basis of daily series of temperature and precipitation, the indices of temperature extremes indicate warming of both the cold tail and the warm tail

Klein Tank, Albert

349

The environmental protection agency's research program on total human exposure  

Science Journals Connector (OSTI)

The U.S. Environmental Protection Agency's (U.S. EPA) research program on total human exposure to environmental pollution seeks to develop a newly emerging concept in the environmental sciences. Instead of focusing purely on the sources of pollution or their transport and movement through the environment, this research focuses on human beings as the receptors of these pollutants. People and daily activities become the center of attention. The methodology measures and models the pollutant concentrations found at the physical boundaries of people, regardless of whether the pollutants arrive through the air, water, food, or skin. It seeks to characterize quantitatively the impact of pollution on people by determining if an environmental problem exists at the human interface and, if so, by determining the sources, nature, extent, and severity of this environmental problem. By exploiting an emerging new arsenal of miniaturized instruments and by developing statistically representative survey designs for sampling the population of cities, significant progress has been made in recent years in providing previously unavailable human exposure field data needed for making valid risk assessments. The U.S. EPA total human exposure research program includes: development of measurement methods and instruments, development of exposure models and statistical protocols, microenvironmental field studies, total human exposure studies, validation of human exposure models with empirical data, and dosage research investigations.

Wayne Ott; Lance Wallace; David Mage; Gerald Akland; Robert Lewis; Harold Sauls; Charles Rodes; David Kleffman; Donna Kuroda; Karen Morehouse

1986-01-01T23:59:59.000Z

350

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 Capacity (B/SD) Thermal Cracking Downstream Charge Capacity (B/SD) Thermal Cracking Total Coking Downstream Charge Capacity (B/SD) Thermal Cracking Delayed Coking Downstream Charge Capacity (B/SD Thermal Cracking Fluid Coking Downstream Charge Capacity (B/SD) Thermal Cracking Visbreaking Downstream Charge Capacity (B/SD) Thermal Cracking Other/Gas Oil Charge Capacity (B/SD) Catalytic Cracking Fresh Feed Charge Capacity (B/SD) Catalytic Cracking Recycle Charge Capacity (B/SD) Catalytic Hydro-Cracking Charge Capacity (B/SD) Catalytic Hydro-Cracking Distillate Charge Capacity (B/SD) Catalytic Hydro-Cracking Gas Oil Charge Capacity (B/SD) Catalytic Hydro-Cracking Residual Charge Capacity (B/SD) Catalytic Reforming Charge Capacity (B/SD) Catalytic Reforming Low Pressure Charge Capacity (B/SD) Catalytic Reforming High Pressure Charge Capacity (B/SD) Catalytic Hydrotreating/Desulfurization Charge Capacity (B/SD) Catalytic Hydrotreating Naphtha/Reformer Feed Charge Cap (B/SD) Catalytic Hydrotreating Gasoline Charge Capacity (B/SD) Catalytic Hydrotreating Heavy Gas Oil Charge Capacity (B/SD) Catalytic Hydrotreating Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Kerosene/Jet Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Diesel Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Other Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Residual/Other Charge Capacity (B/SD) Catalytic Hydrotreating Residual Charge Capacity (B/SD) Catalytic Hydrotreating Other Oils Charge Capacity (B/SD) Fuels Solvent Deasphalting Charge Capacity (B/SD) Catalytic Reforming Downstream Charge Capacity (B/CD) Total Coking Downstream Charge Capacity (B/CD) Catalytic Cracking Fresh Feed Downstream Charge Capacity (B/CD) Catalytic Hydro-Cracking Downstream Charge Capacity (B/CD) Period:

351

Principal Investigators: Long-Term Daily and Monthly Climate Records from  

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

Principal Investigators: Long-Term Daily and Monthly Climate Records from Principal Investigators: Long-Term Daily and Monthly Climate Records from Stations Across the Contiguous United States M.J. Menne, C.N. Williams, Jr., and R.S. Vose National Climatic Data Center National Oceanic and Atmospheric Administration CDIAC and the USHCN PIs encourage users to make this site their main source for obtaining USHCN data, where you can take advantage of data plotting, and, for daily data, user-friendly station-specific downloading. This site will update both daily and monthly data near the beginning of each year, so as to include data through December of the previous year. However, if you need real-time data updates, you should visit the NCDC website. For NCDC-updated daily data please use the Global Historical Climatology Network (GHCN) website where you will find a directory of USHCN stations.

352

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

Gasoline and Diesel Fuel Update (EIA)

December 20, 2013Daily Prices December 20, 2013Daily Prices Daily wholesale and retail prices for various energy products are shown below, including spot prices and select futures prices at national or regional levels. Prices are updated each weekday (excluding federal holidays), typically between 7:30 and 8:30 a.m. This page is meant to provide a snapshot of selected daily prices only. Prices are republished by EIA with permission as follows: Wholesale Spot Petroleum Prices from Thomson Reuters, Retail Petroleum Prices from AAA Fuel Gauge Report, Prompt-Month Energy Futures from CME Group, and Select Spot Prices from SNL Energy. Daily Prices Wholesale Spot Petroleum Prices, 12/19/13 Close Product Area Price Percent Change* Crude Oil ($/barrel) WTI 98.40 +0.8 Brent 110.78 +1.1 Louisiana Light 108.27 +4.9

353

Estimation of Rectal Dose Using Daily Megavoltage Cone-Beam Computed Tomography and Deformable Image Registration  

SciTech Connect (OSTI)

Purpose: The actual dose delivered to critical organs will differ from the simulated dose because of interfractional organ motion and deformation. Here, we developed a method to estimate the rectal dose in prostate intensity modulated radiation therapy with consideration to interfractional organ motion using daily megavoltage cone-beam computed tomography (MVCBCT). Methods and Materials: Under exemption status from our institutional review board, we retrospectively reviewed 231 series of MVCBCT of 8 patients with prostate cancer. On both planning CT (pCT) and MVCBCT images, the rectal contours were delineated and the CT value within the contours was replaced by the mean CT value within the pelvis, with the addition of 100 Hounsfield units. MVCBCT images were rigidly registered to pCT and then nonrigidly registered using B-Spline deformable image registration (DIR) with Velocity AI software. The concordance between the rectal contours on MVCBCT and pCT was evaluated using the Dice similarity coefficient (DSC). The dose distributions normalized for 1 fraction were also deformed and summed to estimate the actual total dose. Results: The DSC of all treatment fractions of 8 patients was improved from 0.750.04 (mean SD) to 0.90 0.02 by DIR. Six patients showed a decrease of the generalized equivalent uniform dose (gEUD) from total dose compared with treatment plans. Although the rectal volume of each treatment fraction did not show any correlation with the change in gEUD (R{sup 2}=0.180.13), the displacement of the center of gravity of rectal contours in the anterior-posterior (AP) direction showed an intermediate relationship (R{sup 2}=0.610.16). Conclusion: We developed a method for evaluation of rectal dose using DIR and MVCBCT images and showed the necessity of DIR for the evaluation of total dose. Displacement of the rectum in the AP direction showed a greater effect on the change in rectal dose compared with the rectal volume.

Akino, Yuichi, E-mail: akino@radonc.med.osaka-u.ac.jp [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Department of Radiology, Osaka University Hospital, Suita, Osaka (Japan); Yoshioka, Yasuo [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Fukuda, Shoichi [Department of Radiation Oncology, Osaka General Medical Center, Osaka (Japan); Maruoka, Shintaroh [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Takahashi, Yutaka [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Department of Radiation Oncology, University of Minnesota, Minneapolis, Minnesota (United States); Yagi, Masashi [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Mizuno, Hirokazu [Department of Radiology, Osaka University Hospital, Suita, Osaka (Japan); Isohashi, Fumiaki [Oncology Center, Osaka University Hospital, Suita, Osaka (Japan); Ogawa, Kazuhiko [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan)

2013-11-01T23:59:59.000Z

354

Total quality management implementation guidelines  

SciTech Connect (OSTI)

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

Not Available

1993-12-01T23:59:59.000Z

355

2010-2011 2 3 Year Average 0.7  

E-Print Network [OSTI]

FTS/number of students enrolled for the last three fall semesters. 4 Employment Profile (In field External Review Date of last formal external review, updated when changed 13 Faculty Teaching Load Total number of semester credit hours in organized teaching courses taught per academic year by core faculty

356

Hilbert Space Average Method and adiabatic quantum search  

E-Print Network [OSTI]

We discuss some aspects related to the so-called Hilbert space Average Method, as an alternative to describe the dynamics of open quantum systems. First we present a derivation of the method which does not make use of the algebra satisfied by the operators involved in the dynamics, and extend the method to systems subject to a Hamiltonian that changes with time. Next we examine the performance of the adiabatic quantum search algorithm with a particular model for the environment. We relate our results to the criteria discussed in the literature for the validity of the above-mentioned method for similar environments.

A. Perez

2009-01-19T23:59:59.000Z

357

W. R. Johnson An Average-Atom Model  

E-Print Network [OSTI]

W. R. Johnson An Average-Atom Model h0 - Z r + V (r) a(r) = aa(r) potential: V (r) = (r )/R d - (3) d 1 + exp[( - µ)/kT ] P 2 (r) norm: Z = R 0 4r 2 (r) dr ­ ND ­ 04/02 1 #12;W. R. Johnson Electron-Fermi contributions to continuum ­ ND ­ 04/02 2 #12;W. R. Johnson Phase shifts: Al - T=10eV 0 1 2 3 4 5 6 7 8 electron

Johnson, Walter R.

358

Total Heart Transplant: A Modern Overview  

E-Print Network [OSTI]

use of the total artificial heart. New England Journal ofJ. (1997). Artificial heart transplants. British medicala total artificial heart as a bridge to transplantation. New

Lingampalli, Nithya

2014-01-01T23:59:59.000Z

359

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

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

a. Average Electricity Prices, Projected vs. Actual 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 Dollar Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 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 AEO 1996 1994 7.09 6.99 6.94 6.93 6.96 6.96 6.96 6.97 6.98 6.97 6.98 6.95 6.95 6.94 6.96 6.95 6.91 AEO 1997 1995 6.94 6.89 6.90 6.91 6.86 6.84 6.78 6.73 6.66 6.60 6.58 6.54 6.49 6.48 6.45 6.36

360

Retrieval of Areal-averaged Spectral Surface Albedo from Transmission Data Alone: Computationally Simple and Fast Approach  

SciTech Connect (OSTI)

We introduce and evaluate a simple retrieval of areal-averaged surface albedo using ground-based measurements of atmospheric transmission alone at five wavelengths (415, 500, 615, 673 and 870nm), under fully overcast conditions. Our retrieval is based on a one-line semi-analytical equation and widely accepted assumptions regarding the weak spectral dependence of cloud optical properties, such as cloud optical depth and asymmetry parameter, in the visible and near-infrared spectral range. To illustrate the performance of our retrieval, we use as input measurements of spectral atmospheric transmission from Multi-Filter Rotating Shadowband Radiometer (MFRSR). These MFRSR data are collected at two well-established continental sites in the United States supported by the U.S. Department of Energys (DOEs) Atmospheric Radiation Measurement (ARM) Program and National Oceanic and Atmospheric Administration (NOAA). The areal-averaged albedos obtained from the MFRSR are compared with collocated and coincident Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky albedo. In particular, these comparisons are made at four MFRSR wavelengths (500, 615, 673 and 870nm) and for four seasons (winter, spring, summer and fall) at the ARM site using multi-year (2008-2013) MFRSR and MODIS data. Good agreement, on average, for these wavelengths results in small values (?0.01) of the corresponding root mean square errors (RMSEs) for these two sites. The obtained RMSEs are comparable with those obtained previously for the shortwave albedos (MODIS-derived versus tower-measured) for these sites during growing seasons. We also demonstrate good agreement between tower-based daily-averaged surface albedos measured for nearby overcast and non-overcast days. Thus, our retrieval originally developed for overcast conditions likely can be extended for non-overcast days by interpolating between overcast retrievals.

Kassianov, Evgueni I.; Barnard, James C.; Flynn, Connor J.; Riihimaki, Laura D.; Michalsky, Joseph; Hodges, G. B.

2014-10-25T23:59:59.000Z

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Total Imports of Residual Fuel  

Gasoline and Diesel Fuel Update (EIA)

May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View History U.S. Total 5,752 5,180 7,707 9,056 6,880 6,008 1936-2013 PAD District 1 1,677 1,689 2,008 3,074 2,135 2,814 1981-2013 Connecticut 1995-2009 Delaware 1995-2012 Florida 359 410 439 392 704 824 1995-2013 Georgia 324 354 434 364 298 391 1995-2013 Maine 65 1995-2013 Maryland 1995-2013 Massachusetts 1995-2012 New Hampshire 1995-2010 New Jersey 903 756 948 1,148 1,008 1,206 1995-2013 New York 21 15 14 771 8 180 1995-2013 North Carolina 1995-2011 Pennsylvania 1995-2013 Rhode Island 1995-2013 South Carolina 150 137 194 209 1995-2013 Vermont 5 4 4 5 4 4 1995-2013 Virginia 32 200 113 1995-2013 PAD District 2 217 183 235 207 247 179 1981-2013 Illinois 1995-2013

362

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Noyes, MN Warroad, MN Babb, 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 U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Galvan Ranch, TX LNG Imports from Algeria LNG Imports from Australia LNG Imports from Brunei LNG Imports from Canada Highgate Springs, VT LNG Imports from Egypt Cameron, LA Elba Island, GA Freeport, TX Gulf LNG, MS LNG Imports from Equatorial Guinea LNG Imports from Indonesia LNG Imports from Malaysia LNG Imports from Nigeria Cove Point, MD LNG Imports from Norway Cove Point, MD Freeport, TX Sabine Pass, LA LNG Imports from Oman LNG Imports from Peru Cameron, LA Freeport, TX LNG Imports from Qatar Elba Island, GA Golden Pass, TX Sabine Pass, LA LNG Imports from Trinidad/Tobago Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf LNG, MS Lake Charles, LA Sabine Pass, LA LNG Imports from United Arab Emirates LNG Imports from Yemen Everett, MA Freeport, TX Sabine Pass, LA LNG Imports from Other Countries Period: Monthly Annual

363

Natural Gas Total Liquids Extracted  

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

Thousand Barrels) Thousand Barrels) Data Series: Natural Gas Processed Total Liquids Extracted NGPL Production, Gaseous Equivalent Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 658,291 673,677 720,612 749,095 792,481 873,563 1983-2012 Alabama 13,381 11,753 11,667 13,065 1983-2010 Alaska 22,419 20,779 19,542 17,798 18,314 18,339 1983-2012 Arkansas 126 103 125 160 212 336 1983-2012 California 11,388 11,179 11,042 10,400 9,831 9,923 1983-2012 Colorado 27,447 37,804 47,705 57,924 1983-2010 Florida 103 16 1983-2008 Illinois 38 33 24 231 705 0 1983-2012

364

Total Petroleum Systems and Assessment Units (AU)  

E-Print Network [OSTI]

Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Surface water Groundwater X X X X X X X X AU 00000003 Oil/ Gas X X X X X X X X Total X X X X X X X Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Total undiscovered petroleum (MMBO or BCFG) Water per oil

Torgersen, Christian

365

Locating and total dominating sets in trees  

Science Journals Connector (OSTI)

A set S of vertices in a graph G = ( V , E ) is a total dominating set of G if every vertex of V is adjacent to a vertex in S. We consider total dominating sets of minimum cardinality which have the additional property that distinct vertices of V are totally dominated by distinct subsets of the total dominating set.

Teresa W. Haynes; Michael A. Henning; Jamie Howard

2006-01-01T23:59:59.000Z

366

Locating-total domination in graphs  

Science Journals Connector (OSTI)

In this paper, we continue the study of locating-total domination in graphs. A set S of vertices in a graph G is a total dominating set in G if every vertex of G is adjacent to a vertex in S . We consider total dominating sets S which have the additional property that distinct vertices in V ( G ) ? S are totally dominated by distinct subsets of the total dominating set. Such a set S is called a locating-total dominating set in G , and the locating-total domination number of G is the minimum cardinality of a locating-total dominating set in G . We obtain new lower and upper bounds on the locating-total domination number of a graph. Interpolation results are established, and the locating-total domination number in special families of graphs, including cubic graphs and grid graphs, is investigated.

Michael A. Henning; Nader Jafari Rad

2012-01-01T23:59:59.000Z

367

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

SciTech Connect (OSTI)

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)

United States. Bonneville Power Administration.

1984-06-01T23:59:59.000Z

368

Climate: monthly and annual average relative humidity GIS data at  

Open Energy Info (EERE)

relative humidity GIS data at relative humidity GIS data at one-degree resolution of the World from NASA/SSE Dataset Summary Description (Abstract): Relative Humidity at 10 m Above The Surface Of The Earth (%)NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly & Annual Average (July 1983 - June 2005)Parameter: Relative Humidity at 10 m Above The Surface Of The Earth (%)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of

369

FY 2009 CONTRACTOR PURCHASING BALANCED SCORECARD RESULTS DEPARTMENTAL AVERAGES BY FISCAL YEAR  

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

9 CONTRACTOR PURCHASING BALANCED SCORECARD RESULTS 9 CONTRACTOR PURCHASING BALANCED SCORECARD RESULTS DEPARTMENTAL AVERAGES BY FISCAL YEAR FY 2009 FY2005 FY2006 FY 2007 FY 2008 FY 2009 National Tarpets Customer Perspective Objective: Customer Satisfaction Core Measure: Customer Satisfaction Rating Internal Business Perspective Objective: Effective Internal Controls 93 94 Core Measure: assessment of degree to which purchasing systems are in compliance Objective: Effective Supplier Management 8 1 83 Core Measure: % Delivery on-time, including Just-in-Time Objective: Use of Effective Competition 74 69 Core Measure: % of total dollars obligated on actions over $100,000 that were competed 97 97 N/A - locally set 84 8 6 84 67 74 N/A - locally set 2 FY 2009 FY 2005 FY 2006 FY 2007 FY 2008 FY2009 National Targets

370

FY 2008 CONTRACTOR PURCHASING BALANCED SCORECARD RESULTS DEPARTMENTAL AVERAGES BY FISCAL YEAR  

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

8 CONTRACTOR PURCHASING BALANCED SCORECARD RESULTS 8 CONTRACTOR PURCHASING BALANCED SCORECARD RESULTS DEPARTMENTAL AVERAGES BY FISCAL YEAR FY 2008 FY 2004 FY 2005 FY2006 FY2007 FY2008 National Taraets Customer Perspective Objective: Customer Satisfaction 93 9 3 Core Measure: Customer Satisfaction Rating Internal Business Perspective Objective: Effective Internal Controls 95 93 Core Measure: assessment of degree to which purchasing systems are in compliance Objective: Effective Supplier Management 8 3 8 1 Core Measure: % Delivery on-time, including Just-in-Time Objective: Use of Effective Competition 7 1 74 Core Measure: % of total dollars obligated on actions over $100,000 that were competed N/A - locally set 84 N/A - locally set 2 FY 2008 FY 2004 FY 2005 FY2006 FY 2007 FY2008 National Tarpets

371

U.S. Total Exports  

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

International Falls, MN Noyes, MN Warroad, MN Babb, MT Havre, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate Springs, VT North Troy, VT LNG Imports into Cameron, LA LNG Imports into Cove Point, MD LNG Imports into Elba Island, GA LNG Imports into Everett, MA LNG Imports into Freeport, TX LNG Imports into Golden Pass, TX LNG Imports into Gulf Gateway, LA LNG Imports into Gulf LNG, MS LNG Imports into Lake Charles, LA LNG Imports into Neptune Deepwater Port LNG Imports into Northeast Gateway LNG Imports into Sabine Pass, LA U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Alamo, TX El Paso, TX Galvan Ranch, TX Hidalgo, TX McAllen, TX Penitas, TX LNG Imports from Algeria Cove Point, MD Everett, MA Lake Charles, LA LNG Imports from Australia Everett, MA Lake Charles, LA LNG Imports from Brunei Lake Charles, LA LNG Imports from Canada Highgate Springs, VT LNG Imports from Egypt Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf LNG, MS Lake Charles, LA Northeast Gateway Sabine Pass, LA LNG Imports from Equatorial Guinea Elba Island, GA Lake Charles, LA LNG Imports from Indonesia Lake Charles, LA LNG Imports from Malaysia Gulf Gateway, LA Lake Charles, LA LNG Imports from Nigeria Cove Point, MD Elba Island, GA Freeport, TX Gulf Gateway, LA Lake Charles, LA Sabine Pass, LA LNG Imports from Norway Cove Point, MD Sabine Pass, LA LNG Imports from Oman Lake Charles, LA LNG Imports from Peru Cameron, LA Freeport, TX Sabine Pass, LA LNG Imports from Qatar Cameron, LA Elba Island, GA Golden Pass, TX Gulf Gateway, LA Lake Charles, LA Northeast Gateway Sabine Pass, LA LNG Imports from Trinidad/Tobago Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf Gateway, LA Gulf LNG, MS Lake Charles, LA Neptune Deepwater Port Northeast Gateway Sabine Pass, LA LNG Imports from United Arab Emirates Lake Charles, LA LNG Imports from Yemen Everett, MA Freeport, TX Neptune Deepwater Port Sabine Pass, LA LNG Imports from Other Countries Lake Charles, LA Period: Monthly Annual

372

Get Daily Energy Analysis Delivered to Your Website | Department of Energy  

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

Get Daily Energy Analysis Delivered to Your Website Get Daily Energy Analysis Delivered to Your Website Get Daily Energy Analysis Delivered to Your Website August 8, 2011 - 3:39pm Addthis Get Daily Energy Analysis Delivered to Your Website Matthew Loveless Matthew Loveless Data Integration Specialist, Office of Public Affairs How can I participate? Go to EIA's outreach page for Today in Energy widgets, badges and banners. Now everyone can feature the U.S. Energy Information Administration's (EIA) Today in Energy content on their website and favorite social networking sites. Today in Energy, the agency's education product published every weekday, highlights current energy issues, topics, and data trends in short articles written in plain language. EIA has banners and widgets in different colors and sizes to fit many different websites.

373

A stochastic model for the daily coordination of pumped storage hydro plants and wind power plants  

Science Journals Connector (OSTI)

We propose a stochastic model for the daily operation scheduling of a generation system including pumped storage hydro plants and wind power plants, where the uncertainty is represented by the hourly wind power p...

Maria Teresa Vespucci; Francesca Maggioni

2012-03-01T23:59:59.000Z

374

U.S. Daily Temperatures: The Meaning of Extremes in the Context of Nonnormality  

Science Journals Connector (OSTI)

Variations in extreme daily temperatures are explored in relation to changes in seasonal mean temperature using 1218 high-quality U.S. temperature stations spanning 19002012. Extreme temperatures are amplified (or damped) by as much as 50% ...

P. Huybers; K. A. McKinnon; A. Rhines; M. Tingley

2014-10-01T23:59:59.000Z

375

Daily Reporting Rainfall Station TULLY & JOHNSTONE RIVERS Manual Heavy Rainfall Station  

E-Print Network [OSTI]

Daily Reporting Rainfall Station TULLY & JOHNSTONE RIVERS Manual Heavy Rainfall Station Manual Tide TM Bulgun Ck AL Bingil Bay The Boulders TM Nerada AL Tung Oil AL Fishers Ck TM Corsis AL Russell

Greenslade, Diana

376

Daily Reporting Rainfall Station TULLY & JOHNSTONE RIVERS Manual Heavy Rainfall Station  

E-Print Network [OSTI]

Daily Reporting Rainfall Station TULLY & JOHNSTONE RIVERS Manual Heavy Rainfall Station Manual The Boulders TM Nerada AL Tung Oil AL Fishers Ck TM Corsis AL RussellR Babinda Clyde Rd AL Central Mill AL

Greenslade, Diana

377

LCA comparison of windrow composting of yard wastes with use as alternative daily cover (ADC)  

E-Print Network [OSTI]

LCA comparison of windrow composting of yard wastes with use as alternative daily cover (ADC) Rob Assessment was made using the SimaPro LCA software and showed that the ADC scenario is more beneficial

Columbia University

378

Nanotechnology in our Daily Life Iridescent car paint: Based on interference colors  

E-Print Network [OSTI]

Nanotechnology in our Daily Life Iridescent car paint: Based on interference colors (like a butterly, no bleaching after 5 years Miami) #12;Nanotechnology on our Desktops Hard Disk Sensor Medium

Himpsel, Franz J.

379

Daily torpor in mice: high foraging costs trigger energy-saving hypothermia  

Science Journals Connector (OSTI)

...strategies to save energy. Facultative daily...between environmental quality, foraging behaviour...environmental quality|foraging costs|energy balance| 1. Introduction...foraging costs in poor quality habitat. As an...strategy to maintain energy balance, natural...

2010-01-01T23:59:59.000Z

380

Cakewalking into representation : Gabriele Mnter's America travels (1898-1900) and art of dailiness  

E-Print Network [OSTI]

This study explores the fashioning of Gabriele Mnter as a German modernist with a focus on the eclipse of her struggles in coming to representation, the rich complexity of her processes, and the importance of dailiness ...

Bible, Ann Vollmann

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Dynamic Shape Modeling of Consumers Daily Load Based on Data Mining  

Science Journals Connector (OSTI)

The shape characteristic of daily power consumption of consumers can be applied to guide their power consumption behaviors and improve load structures of power system. It is also the basis to obtain the shape cha...

Lianmei Zhang; Shihong Chen; Qiping Hu

2005-01-01T23:59:59.000Z

382

Micro-simulation of daily activity-travel patterns for travel demand forecasting  

Science Journals Connector (OSTI)

The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day ...

Ryuichi Kitamura; Cynthia Chen; Ram M. Pendyala; Ravi Narayanan

383

African Press International (API) This is your "Daily Online News Channel".  

E-Print Network [OSTI]

African Press International (API) This is your "Daily Online News Channel". Home A:Contact us powerful as before ­ Is this good for new Kenya? (api) The travelling man: Pope Benedict XVI is due

384

Review of Methods to Map Peoples Daily Activity Application for Smart Homes  

Science Journals Connector (OSTI)

Peoples daily activity in their home has widespread implications, including health and energy ... the winter of 2012. Within a smart home, these methods could potentially be used to...

Stephanie Gauthier; David Shipworth

2013-01-01T23:59:59.000Z

385

Automation: A Step toward Improving the Quality of Daily Temperature Data Produced by Climate Observing Networks  

Science Journals Connector (OSTI)

The research documented in this manuscript demonstrates that undeniable differences exist between values of daily temperature recorded by the National Weather Service Cooperative Observer Program network and data recorded by the Oklahoma Mesonet. ...

Christopher A. Fiebrich; Kenneth C. Crawford

2009-07-01T23:59:59.000Z

386

Grid History: A Geostationary Satellite Technique for Estimating Daily Rainfall in the Tropics  

Science Journals Connector (OSTI)

A new technique is described for estimating daily rainfall by means of visible and infrared geostationary satellite imagery. It is designed for the tropics and warm-season midlatitudes. Because it operates on a grid of points and measures time ...

David W. Martin; Michael R. Howland

1986-02-01T23:59:59.000Z

387

An Exact Thickness-Weighted Average Formulation of the Boussinesq Equations WILLIAM R. YOUNG  

E-Print Network [OSTI]

An Exact Thickness-Weighted Average Formulation of the Boussinesq Equations WILLIAM R. YOUNG application of thickness-weighted averaging to the Boussinesq equa- tions of motion results in averaged

Young, William R.

388

Two photo permits are available: Daily Photographer Permit and Annual Photographer Permit. Daily Photographer Permit is $75 and includes gate admission for up to 15 adults and photographer. To reserve  

E-Print Network [OSTI]

Two photo permits are available: Daily Photographer Permit and Annual Photographer Permit. Daily of the photo session will be $75 plus a $25 processing fee. Your Daily Photo Badge can be picked up the business day before. Any permits purchased on the day of the photo session will be $225 and subject

Netoff, Theoden

389

Table 15. Average Electricity Prices, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Average Electricity Prices, Projected vs. Actual Average Electricity Prices, Projected vs. Actual (nominal cents per kilowatt-hour) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 6.38 6.96 7.63 8.23 8.83 9.49 AEO 1983 6.85 7.28 7.74 8.22 8.68 9.18 13.12 AEO 1984 6.67 7.05 7.48 7.89 8.25 8.65 11.53 AEO 1985 6.62 6.94 7.32 7.63 7.89 8.15 8.46 8.85 9.20 9.61 10.04 AEO 1986 6.67 6.88 7.05 7.18 7.35 7.52 7.65 7.87 8.31 8.83 9.41 10.01 10.61 11.33 12.02 AEO 1987 6.63 6.65 6.92 7.12 7.38 7.62 7.94 8.36 8.86 11.99 AEO 1989* 6.50 6.75 7.14 7.48 7.82 8.11 8.50 8.91 9.39 9.91 10.49 11.05 11.61 AEO 1990 6.49 6.72 8.40 10.99 14.5 AEO 1991 6.94 7.31 7.59 7.82 8.18 8.38 8.54 8.73 8.99 9.38 9.83 10.29 10.83 11.36 11.94 12.58 13.21 13.88 14.58 15.21 AEO 1992 6.97 7.16 7.32 7.56 7.78 8.04 8.29 8.57 8.93 9.38 9.82 10.26 10.73 11.25 11.83 12.37 12.96 13.58 14.23 AEO 1993

390

The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data  

SciTech Connect (OSTI)

The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32 16'N, 48 25'E), are used in this study. In order to consider the effect of each meteorological variable on daily GSR prediction, six following combinations of input variables are considered: (I)Day of the year, daily mean air temperature and relative humidity as inputs and daily GSR as output. (II)Day of the year, daily mean air temperature and sunshine hours as inputs and daily GSR as output. (III)Day of the year, daily mean air temperature, relative humidity and sunshine hours as inputs and daily GSR as output. (IV)Day of the year, daily mean air temperature, relative humidity, sunshine hours and evaporation as inputs and daily GSR as output. (V)Day of the year, daily mean air temperature, relative humidity, sunshine hours and wind speed as inputs and daily GSR as output. (VI)Day of the year, daily mean air temperature, relative humidity, sunshine hours, evaporation and wind speed as inputs and daily GSR as output. Multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are applied for daily GSR modeling based on six proposed combinations. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. The comparison of obtained results from ANNs and different conventional GSR prediction (CGSRP) models shows very good improvements (i.e. the predicted values of best ANN model (MLP-V) has a mean absolute percentage error (MAPE) about 5.21% versus 10.02% for best CGSRP model (CGSRP 5)). (author)

Behrang, M.A.; Assareh, E. [Department of Mechanical Engineering, Young Researchers Club, Islamic Azad University, Dezful Branch (Iran); Ghanbarzadeh, A.; Noghrehabadi, A.R. [Department of Mechanical Engineering, Engineering Faculty, Shahid Chamran University, Ahvaz (Iran)

2010-08-15T23:59:59.000Z

391

E-Print Network 3.0 - averaged pulsar profiles Sample Search...  

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

for: averaged pulsar profiles Page: << < 1 2 3 4 5 > >> 1 astroph9911319 Pulsar Astronomy ---2000 and Beyond Summary: with higher than average surface dipole magnetic fields....

392

E-Print Network 3.0 - average power ratio Sample Search Results  

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

a wind turbine Summary: of pairs of poles over the average power is also studied. Index Terms-- average wind power, battery... charging, permanent magnet synchronous machine. I....

393

Climate: monthly and annual average atmospheric pressure GIS data at  

Open Energy Info (EERE)

atmospheric pressure GIS data at atmospheric pressure GIS data at one-degree resolution of the World from NASA/SSE Dataset Summary Description (Abstract):Atmospheric Pressure (kPa)NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly & Annual Average (July 1983 - June 2005)Parameter: Atmospheric Pressure (kPa)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of the region is +0.5 added to the the Lat/Lon value. These data are

394

Ensemble bayesian model averaging using markov chain Monte Carlo sampling  

SciTech Connect (OSTI)

Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In their seminal paper (Raftery etal. Mon Weather Rev 133: 1155-1174, 2(05)) has recommended the Expectation-Maximization (EM) algorithm for BMA model training, even though global convergence of this algorithm cannot be guaranteed. In this paper, we compare the performance of the EM algorithm and the recently developed Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm for estimating the BMA weights and variances. Simulation experiments using 48-hour ensemble data of surface temperature and multi-model stream-flow forecasts show that both methods produce similar results, and that their performance is unaffected by the length of the training data set. However, MCMC simulation with DREAM is capable of efficiently handling a wide variety of BMA predictive distributions, and provides useful information about the uncertainty associated with the estimated BMA weights and variances.

Vrugt, Jasper A [Los Alamos National Laboratory; Diks, Cees G H [NON LANL; Clark, Martyn P [NON LANL

2008-01-01T23:59:59.000Z

395

Total cost model for making sourcing decisions  

E-Print Network [OSTI]

This thesis develops a total cost model based on the work done during a six month internship with ABB. In order to help ABB better focus on low cost country sourcing, a total cost model was developed for sourcing decisions. ...

Morita, Mark, M.B.A. Massachusetts Institute of Technology

2007-01-01T23:59:59.000Z

396

Team Total Points Beta Theta Pi 2271  

E-Print Network [OSTI]

Bubbles 40 Upset City 30 Team Success 30 #12;Team Total Points Sly Tye 16 Barringer 15 Fire Stinespring 15

Buehrer, R. Michael

397

Million Cu. Feet Percent of National Total  

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

38 38 Nevada - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S30. Summary statistics for natural gas - Nevada, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 4 4 4 3 4 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 4 4 4 3 4

398

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Idaho - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S14. Summary statistics for natural gas - Idaho, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

399

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Washington - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S49. Summary statistics for natural gas - Washington, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

400

Million Cu. Feet Percent of National Total  

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

0 0 Maine - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S21. Summary statistics for natural gas - Maine, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Million Cu. Feet Percent of National Total  

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

8 8 Minnesota - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S25. Summary statistics for natural gas - Minnesota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

402

Million Cu. Feet Percent of National Total  

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

2 2 South Carolina - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S42. Summary statistics for natural gas - South Carolina, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

403

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 North Carolina - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. Summary statistics for natural gas - North Carolina, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

404

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Iowa - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S17. Summary statistics for natural gas - Iowa, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

405

Million Cu. Feet Percent of National Total  

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

4 4 Massachusetts - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

406

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Minnesota - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S25. Summary statistics for natural gas - Minnesota, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

407

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 New Jersey - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. Summary statistics for natural gas - New Jersey, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

408

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Vermont - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S47. Summary statistics for natural gas - Vermont, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

409

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Wisconsin - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S51. Summary statistics for natural gas - Wisconsin, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

410

Million Cu. Feet Percent of National Total  

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

8 8 North Carolina - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. Summary statistics for natural gas - North Carolina, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

411

Million Cu. Feet Percent of National Total  

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

2 2 New Jersey - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. Summary statistics for natural gas - New Jersey, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

412

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Maryland - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S22. Summary statistics for natural gas - Maryland, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 7 7 7 7 8 Production (million cubic feet) Gross Withdrawals From Gas Wells 35 28 43 43 34 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 35

413

Million Cu. Feet Percent of National Total  

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

0 0 New Hampshire - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S31. Summary statistics for natural gas - New Hampshire, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

414

Million Cu. Feet Percent of National Total  

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

2 2 Maryland - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S22. Summary statistics for natural gas - Maryland, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 7 7 7 8 9 Production (million cubic feet) Gross Withdrawals From Gas Wells 28 43 43 34 44 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 28

415

Million Cu. Feet Percent of National Total  

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

2 2 Missouri - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S27. Summary statistics for natural gas - Missouri, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 53 100 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

416

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Massachusetts - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

417

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 South Carolina - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S42. Summary statistics for natural gas - South Carolina, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

418

Million Cu. Feet Percent of National Total  

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

0 0 Rhode Island - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S41. Summary statistics for natural gas - Rhode Island, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

419

TotalView Parallel Debugger at NERSC  

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

Totalview Totalview Totalview Description TotalView from Rogue Wave Software is a parallel debugging tool that can be run with up to 512 processors. It provides both X Windows-based Graphical User Interface (GUI) and command line interface (CLI) environments for debugging. The performance of the GUI can be greatly improved if used in conjunction with free NX software. The TotalView documentation web page is a good resource for learning more about some of the advanced TotalView features. Accessing Totalview at NERSC To use TotalView at NERSC, first load the TotalView modulefile to set the correct environment settings with the following command: % module load totalview Compiling Code to Run with TotalView In order to use TotalView, code must be compiled with the -g option. We

420

RTOG 0913: A Phase 1 Study of Daily Everolimus (RAD001) in Combination With Radiation Therapy and Temozolomide in Patients With Newly Diagnosed Glioblastoma  

SciTech Connect (OSTI)

Purpose: To determine the safety of the mammalian target of rapamycin inhibitor everolimus (RAD001) administered daily with concurrent radiation and temozolomide in newly diagnosed glioblastoma patients. Methods and Materials: Everolimus was administered daily with concurrent radiation (60 Gy in 30 fractions) and temozolomide (75 mg/m{sup 2} per day). Everolimus was escalated from 2.5 mg/d (dose level 1) to 5 mg/d (dose level 2) to 10 mg/d (dose level 3). Adjuvant temozolomide was delivered at 150 to 200 mg/m{sup 2} on days 1 to 5, every 28 days, for up to 12 cycles, with concurrent everolimus at the previously established daily dose of 10 mg/d. Dose escalation continued if a dose level produced dose-limiting toxicities (DLTs) in fewer than 3 of the first 6 evaluable patients. Results: Between October 28, 2010, and July 2, 2012, the Radiation Therapy Oncology Group 0913 protocol initially registered a total of 35 patients, with 25 patients successfully meeting enrollment criteria receiving the drug and evaluable for toxicity. Everolimus was successfully escalated to the predetermined maximum tolerated dose of 10 mg/d. Two of the first 6 eligible patients had a DLT at each dose level. DLTs included gait disturbance, febrile neutropenia, rash, fatigue, thrombocytopenia, hypoxia, ear pain, headache, and mucositis. Other common toxicities were grade 1 or 2 hypercholesterolemia and hypertriglyceridemia. At the time of analysis, there was 1 death reported, which was attributed to tumor progression. Conclusions: Daily oral everolimus (10 mg) combined with both concurrent radiation and temozolomide followed by adjuvant temozolomide is well tolerated, with an acceptable toxicity profile. A randomized phase 2 clinical trial with mandatory correlative biomarker analysis is currently under way, designed to both determine the efficacy of this regimen and identify molecular determinants of response.

Chinnaiyan, Prakash, E-mail: prakash.chinnaiyan@moffitt.org [Department of Radiation Oncology, Experimental Therapeutics and Cancer Imaging and Metabolism, H. Lee Moffitt Cancer Center, Tampa, Florida (United States); Won, Minhee [Radiation Therapy Oncology Group, Philadelphia, Pennsylvania (United States); Wen, Patrick Y. [Center for Neuro-Oncology, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts (United States); Rojiani, Amyn M. [Department of Pathology, Medical College of Georgia, Augusta, Georgia (United States); Wendland, Merideth [Radiation Oncology, US Oncology-Willamette Valley Cancer Institute, Eugene, Oregon (United States); Dipetrillo, Thomas A. [Department of Radiation Oncology, Rhode Island Hospital, Providence, Rhode Island (United States); Corn, Benjamin W. [Department of Radiation Oncology, Tel Aviv Medical Center, Tel Aviv (Israel); Mehta, Minesh P. [Department of Radiation Oncology, University of Maryland, Baltimore, Maryland (United States)

2013-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Million Cu. Feet Percent of National Total  

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

6 6 Tennessee - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S44. Summary statistics for natural gas - Tennessee, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 285 310 230 210 212 Production (million cubic feet) Gross Withdrawals From Gas Wells 4,700 5,478 5,144 4,851 5,825 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

422

Million Cu. Feet Percent of National Total  

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

2 2 Connecticut - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. Summary statistics for natural gas - Connecticut, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

423

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Oregon - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 18 21 24 26 24 Production (million cubic feet) Gross Withdrawals From Gas Wells 409 778 821 1,407 1,344 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

424

Million Cu. Feet Percent of National Total  

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

6 6 District of Columbia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

425

Million Cu. Feet Percent of National Total  

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

6 6 Oregon - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 21 24 26 24 27 Production (million cubic feet) Gross Withdrawals From Gas Wells 778 821 1,407 1,344 770 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

426

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Georgia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. Summary statistics for natural gas - Georgia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

427

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Delaware - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. Summary statistics for natural gas - Delaware, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

428

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 District of Columbia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

429

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Tennessee - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S44. Summary statistics for natural gas - Tennessee, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 305 285 310 230 210 Production (million cubic feet) Gross Withdrawals From Gas Wells NA 4,700 5,478 5,144 4,851 From Oil Wells 3,942 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

430

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Nebraska - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S29. Summary statistics for natural gas - Nebraska, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 186 322 285 276 322 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,331 2,862 2,734 2,092 1,854 From Oil Wells 228 221 182 163 126 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

431

Million Cu. Feet Percent of National Total  

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

0 0 Georgia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. Summary statistics for natural gas - Georgia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

432

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Connecticut - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. Summary statistics for natural gas - Connecticut, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

433

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Florida - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S10. Summary statistics for natural gas - Florida, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 2,000 2,742 290 13,938 17,129 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

434

Million Cu. Feet Percent of National Total  

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

4 4 Delaware - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. Summary statistics for natural gas - Delaware, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

435

ARM - Measurement - Shortwave spectral total downwelling irradiance  

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

Shadowband Spectroradiometer SPEC-TOTDN : Shortwave Total Downwelling Spectrometer UAV-EGRETT : UAV-Egrett Value-Added Products VISST : Minnis Cloud Products Using Visst...

436

,"New York Natural Gas Total Consumption (MMcf)"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Total Consumption (MMcf)",1,"Annual",2013 ,"Release Date:","12312014"...

437

Total Supplemental Supply of Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

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

438

Total Natural Gas Gross Withdrawals (Summary)  

Gasoline and Diesel Fuel Update (EIA)

Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to...

439

Million Cu. Feet Percent of National Total  

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

0 0 Indiana - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S16. Summary statistics for natural gas - Indiana, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 525 563 620 914 819 Production (million cubic feet) Gross Withdrawals From Gas Wells 4,701 4,927 6,802 9,075 8,814 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

440

Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip  

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

5: March 22, 5: March 22, 2010 Average Vehicle Trip Length to someone by E-mail Share Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Facebook Tweet about Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Twitter Bookmark Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Google Bookmark Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Delicious Rank Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Digg Find More places to share Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on AddThis.com... Fact #615: March 22, 2010 Average Vehicle Trip Length According to the latest National Household Travel Survey, the average trip

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Total Particulate Matter Air Sampling Data (TEOM) from Los Alamos National Laboratory  

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

LANL measures the total particulate mass concentration in the air on a routine basis as well as during incidents that may affect ambient air. The collected data is added to the Air Quality Index (AQI). AQI is an index for reporting daily air quality. It tells you how clean or polluted your air is, and what associated health effects might be a concern for you. The AQI focuses on health effects you may experience within a few hours or days after breathing polluted air. EPA calculates the AQI for five major air pollutants regulated by the Clean Air Act.

442

Total Synthesis of Irciniastatin A (Psymberin)  

E-Print Network [OSTI]

Total Synthesis of Irciniastatin A (Psymberin) Michael T. Crimmins,* Jason M. Stevens, and Gregory, North Carolina 27599 crimmins@email.unc.edu Received July 21, 2009 ABSTRACT The total synthesis of a hemiaminal and acid chloride to complete the synthesis. In 2004, Pettit and Crews independently reported

443

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION  

E-Print Network [OSTI]

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION BERND WITTGENS, RAJAB LITTO, EVA S RENSEN a generalization of previously proposed batch distillation schemes. A simple feedback control strategy for total re verify the simulations. INTRODUCTION Although batch distillation generally is less energy e cient than

Skogestad, Sigurd

444

Detecting Eating Using a Wrist Mounted Device During Normal Daily Activities  

E-Print Network [OSTI]

Detecting Eating Using a Wrist Mounted Device During Normal Daily Activities Yujie Dong1, Adam method for automated monitoring of eating. Our method uses a single sensor that is worn on the wrist, similar in form to a watch. Wrist orientation was captured at a rate of 60 Hz for an entire day while four

Hoover, Adam

445

The Daily Princetonian -International fusion project will use Princeton physics lab Summer Program  

E-Print Network [OSTI]

to determine the viability of exploiting cold fusion as an energy source around the world. Much of the researchThe Daily Princetonian - International fusion project will use Princeton physics lab Summer Program | Previous | Next | Calendar International fusion project will use Princeton physics lab By ABBY WILLIAMS

446

Home Science One fish, two fish, dumb fish, dead fish DAILY SECTIONS  

E-Print Network [OSTI]

Home Science One fish, two fish, dumb fish, dead fish Home DAILY SECTIONS News Sports Opinion Arts America! Study Spanish & Volunteer ONE FISH, TWO FISH, DUMB FISH, DEAD FISH | Print | E- mail Written scientists say fish are capable of deducing how they stack up against the competition by simply watching

Fernald, Russell

447

A Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water Quality: Evidence  

E-Print Network [OSTI]

A Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water carrying capacity. Keywords Visitation model Á Recreation management Á Water quality Á River visitation Á Clark, Fort Collins, Colorado 80523, USA 123 Environmental Management DOI 10.1007/s00267-008-9079-5 #12

448

Using daily satellite observations to estimate emissions of short-lived  

E-Print Network [OSTI]

Chapter 4 Using daily satellite observations to estimate emissions of short-lived air pollutants on a mesoscopic scale Abstract Emission inventories of air pollutants are crucial information for pol- icy makers and form important input data for air quality models. Using satellite observations for emission estimates

Haak, Hein

449

Biomass burning emission inventory with daily resolution: Application to aircraft observations of Asian outflow  

E-Print Network [OSTI]

Biomass burning emission inventory with daily resolution: Application to aircraft observations for biomass burning using AVHRR satellite observations of fire activity corrected for data gaps and scan angle biomass burning in SE Asia was a major contributor to the outflow of Asian pollution observed in TRACE

Palmer, Paul

450

Water Research 37 (2003) 37563766 Seasonal and daily variations in concentrations of methyl-  

E-Print Network [OSTI]

by volume to gasoline from November to February, and blending 11% MTBE by volume during the rest of the year; accepted 24 March 2003 Abstract Methyl-tertiary-butyl ether (MTBE), an additive used to oxygenate gasoline of gasoline-powered watercraft. This paper documents and explains both seasonal and daily variations in MTBE

Toran, Laura

451

Northwestern Researchers Develop Bistable Nanoswitch Science Daily --Carbon nanotubes (CNT) have been under intense study by  

E-Print Network [OSTI]

Northwestern Researchers Develop Bistable Nanoswitch Science Daily -- Carbon nanotubes (CNT) have been under intense study by scientists all over the world for more than a decade and are being thought with high-aspect ratio, carbon nanotubes have emerged as a promising material because of their many

Espinosa, Horacio D.

452

Daily foraging patterns in free-living birds: exploring the predationstarvation trade-off  

Science Journals Connector (OSTI)

...day, possibly in response to a low but non-trivial...predictable, high-energy food, we failed...feeders with greater frequency on colder days is...between gaining energy and avoiding predation...Daily patterns of energy storage in food-caching...

2013-01-01T23:59:59.000Z

453

Modeling and Generating Daily Changes in Market Variables Using A Multivariate Mixture of Normal Distributions  

E-Print Network [OSTI]

Modeling and Generating Daily Changes in Market Variables Using A Multivariate Mixture of Normal Distributions Jin Wang Department of Mathematics and Computer Science Valdosta State University Valdosta, GA 31698-0040 January 28, 2000 Abstract The mixture of normal distributions provides a useful extension

Wang, Jin

454

Image Source: http://activefiremaps.fs.fed.us Daily Wildfire Update  

E-Print Network [OSTI]

Page 1 Image Source: http://activefiremaps.fs.fed.us Daily Wildfire Update June 14, 2011 Current Large Fires in Colorado TRACK FIRE (Updated 12:00 p.m., June 14, 2011) Fire Jurisdiction: CSFS of approximately 500 people. Closures: In Colorado, Interstate 25 is currently closed south of Exit 11. Injuries

455

Geophysical Fluid Dynamics Laboratory Daily to decadal variability in sources of  

E-Print Network [OSTI]

over the western U.S.: Stratospheric intrusions, Asian pollution, and wildfires Meiyun Lin WESTAR.g. stratospheric [Langford et al., 2009]; wildfires [Pfister et al. 2008] 2. Rising Asian emissions [e.g., Jacob et.66) (Range ~100km) Daily max 8-hr surface O3 at Boulder (~2 km a.s.l.), Colorado Insights from satellite

Jacob, Daniel J.

456

Supervised Classification of Activities of Daily Living in Health Smart Homes using SVM  

E-Print Network [OSTI]

Supervised Classification of Activities of Daily Living in Health Smart Homes using SVM Anthony studies of our laboratory focus on the monitoring of elderly people at home. This aims at detect, as early Home is used to achieve this goal. This flat includes different sensors. The data from the various

Paris-Sud XI, Université de

457

Resting and daily energy expenditures of free-living field voles are positively correlated but reflect  

E-Print Network [OSTI]

, University of Oslo, P.O. Box 1050 Blindern, 0316 Oslo, Norway; Aberdeen Centre for Energy RegulationResting and daily energy expenditures of free-living field voles are positively correlated and Obesity, Division of Energy Balance and Obesity, Rowett Research Institute, Bucksburn, Aberdeen AB24 9SB

Lambin, Xavier

458

Time of birth and daily activity mediated by feeding rhythms in the pregnant rat  

E-Print Network [OSTI]

Time of birth and daily activity mediated by feeding rhythms in the pregnant rat M. J. BOSC, Agnès studied in rats submitted to different feeding rhythms. Animals, put under 14 h of light and 10 h to one of five groups. Group C was fed ad libitum, and groups 2PF, 9PF, 14PF and 21 PF had food available

Boyer, Edmond

459

Vehicle Technologies Office: Fact #265: April 28, 2003 State Average Fuel  

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

5: April 28, 5: April 28, 2003 State Average Fuel Prices to someone by E-mail Share Vehicle Technologies Office: Fact #265: April 28, 2003 State Average Fuel Prices on Facebook Tweet about Vehicle Technologies Office: Fact #265: April 28, 2003 State Average Fuel Prices on Twitter Bookmark Vehicle Technologies Office: Fact #265: April 28, 2003 State Average Fuel Prices on Google Bookmark Vehicle Technologies Office: Fact #265: April 28, 2003 State Average Fuel Prices on Delicious Rank Vehicle Technologies Office: Fact #265: April 28, 2003 State Average Fuel Prices on Digg Find More places to share Vehicle Technologies Office: Fact #265: April 28, 2003 State Average Fuel Prices on AddThis.com... Fact #265: April 28, 2003 State Average Fuel Prices The American Automobile Association tracks gasoline and diesel prices

460

Fact #715: February 20, 2012 The Average Age of Light Vehicles Continues to Rise  

Broader source: Energy.gov [DOE]

The average age for cars and light trucks continues to rise as consumers hold onto their vehicles longer. Between 1995 and 2011, the average age for cars increased by 32% from 8.4 years to 11.1...

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

The U.S. average retail price for on-highway diesel fuel rose...  

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

The U.S. average retail price for on-highway diesel fuel rose this week The U.S. average retail price for on-highway diesel fuel rose slightly to 3.90 a gallon on Monday. That's...

462

Vehicle Technologies Office: Fact #671: April 18, 2011 Average Truck Speeds  

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

1: April 18, 1: April 18, 2011 Average Truck Speeds to someone by E-mail Share Vehicle Technologies Office: Fact #671: April 18, 2011 Average Truck Speeds on Facebook Tweet about Vehicle Technologies Office: Fact #671: April 18, 2011 Average Truck Speeds on Twitter Bookmark Vehicle Technologies Office: Fact #671: April 18, 2011 Average Truck Speeds on Google Bookmark Vehicle Technologies Office: Fact #671: April 18, 2011 Average Truck Speeds on Delicious Rank Vehicle Technologies Office: Fact #671: April 18, 2011 Average Truck Speeds on Digg Find More places to share Vehicle Technologies Office: Fact #671: April 18, 2011 Average Truck Speeds on AddThis.com... Fact #671: April 18, 2011 Average Truck Speeds The Federal Highway Administration studies traffic volume and flow on major

463

ESTIMATION OF TOTAL RADIATIVE POWER FROM THE 6-GEV RING LS-24  

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

TOTAL RADIATIVE POWER TOTAL RADIATIVE POWER FROM THE 6-GEV RING LS-24 G. K. Shenoy APRIL 18,1985 Here we make an estimation of the total power radiated from a positron trajectory through the bending magnets, undulators and wigglers. Bending Magnets The power P B per each bending magnet in the ring is given by (1) where E = 6 GeV B = field average over the magnet length = 0.67 T I = stored current = 0.1 A L = trajectory in each dipole magnet = 2.95 m (Ref. LS-12) This gives P B = 6021 watts. Since there are 64 such dipoles in the ring, the total power radiated from dipoles is T P B (watts) = P B (watts) x 64 = 385 kwatts 2 Undulators The total power radiated from a sinosoidal undulator is either given by P u (watts) (2) or by (3) where N = number of undulator periods of length AO (em), K is the deflection

464

Effect of Alfaprostol, Lasalocid and Once Daily Suckling on postpartum interval in Brahman and Brahman crossbred cattle  

E-Print Network [OSTI]

by age, breed and date of calving to one of 8 treatments (Table 1): 1) Control; 2) Lasalocid (Hoffmann-LaRoche, Inc. , Nutley, N. J. ); 3) Once daily suckling; 4) Alfaprostol (Hoffmann-LaRoche, Inc. , Nutley, N. J. ); 5) Lasalocid and once daily... by age, breed and date of calving to one of 8 treatments (Table 1): 1) Control; 2) Lasalocid (Hoffmann-LaRoche, Inc. , Nutley, N. J. ); 3) Once daily suckling; 4) Alfaprostol (Hoffmann-LaRoche, Inc. , Nutley, N. J. ); 5) Lasalocid and once daily...

Del Vecchio, Ronald Paul

2012-06-07T23:59:59.000Z

465

Optical Properties of Plasmas Based on an Average-Atom Walter Johnson, Notre Dame University  

E-Print Network [OSTI]

Optical Properties of Plasmas Based on an Average-Atom Model Walter Johnson, Notre Dame University of Plasmas Based on an Average-Atom Model Walter Johnson, Notre Dame University Claude Guet, CEA/DAM Ile de of Plasmas Based on an Average-Atom Model Walter Johnson, Notre Dame University Claude Guet, CEA/DAM Ile de

Johnson, Walter R.

466

A Structural Analysis of Vehicle Design Responses to Corporate Average Fuel Economy Policy  

E-Print Network [OSTI]

sensitive to fuel prices than to CAFE standards, with the 2007 average fuel price implying that current CAFE09-0588 A Structural Analysis of Vehicle Design Responses to Corporate Average Fuel Economy Policy, Michalek, and Hendrickson 1 ABSTRACT The U.S. Corporate Average Fuel Economy (CAFE) regulations, which aim

Michalek, Jeremy J.

467

Interactive multiobjective daily volt/var control of distribution networks considering wind power and fuel-cell power plants  

Science Journals Connector (OSTI)

This paper deals with a multiobjective daily volt/var control (MDVVC) for radial distribution feeders integrated renewable energy sources (RES) by means of the tap position of the under load tap changer (ULTC) transformers shunt capacitors and active and reactive power of RES. The multiple objective functions to be minimized are the electrical energy losses the voltage deviations and the total emissions of RES and substations. Discrete behavior of equipments in the distribution systems and nonlinear power flow equations change the VVC problem into a mixed integer non-linear programming (MINLP). Hence a new optimization method based upon the shuffled frog leaping algorithm (SFLA) is presented to solve the optimization problem. The SFLA is modified for resolving the disadvantages of the original algorithm. Besides of accurately passing local optima the MSFLA takes less time to achieve the optimal response. Furthermore the tribe-MSFLA is proposed through using the concept of the tribe. Dealing with the multiobjective optimization problem an interactive fuzzy satisfying method is used while the objective functions are formulated by a fuzzy set theory. An 85-bus radial distribution system is used to test and assess the performance of the proposed algorithm.

Taher Niknam; Mohsen Zare; Jamshid Aghaei; Rasoul Azizipanah-Abarghooee

2012-01-01T23:59:59.000Z

468

The level crossing analysis of German stock market index (DAX) and daily oil price time series  

E-Print Network [OSTI]

The level crossing analysis of DAX and oil price time series are given. We determine the average frequency of positive-slope crossings, $\

Shayeganfar, F; Peinke, J; Tabar, M Reza Rahimi

2010-01-01T23:59:59.000Z

469

Million Cu. Feet Percent of National Total  

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

8 8 Illinois - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S15. Summary statistics for natural gas - Illinois, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 45 51 50 40 40 Production (million cubic feet) Gross Withdrawals From Gas Wells E 1,188 E 1,438 E 1,697 2,114 2,125 From Oil Wells E 5 E 5 E 5 7 0 From Coalbed Wells E 0 E 0 0 0 0 From Shale Gas Wells 0

470

Million Cu. Feet Percent of National Total  

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

50 50 North Dakota - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S36. Summary statistics for natural gas - North Dakota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 194 196 188 239 211 Production (million cubic feet) Gross Withdrawals From Gas Wells 13,738 11,263 10,501 14,287 22,261 From Oil Wells 54,896 45,776 38,306 27,739 17,434 From Coalbed Wells 0

471

Million Cu. Feet Percent of National Total  

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

0 0 Mississippi - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S26. Summary statistics for natural gas - Mississippi, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 2,343 2,320 1,979 5,732 1,669 Production (million cubic feet) Gross Withdrawals From Gas Wells 331,673 337,168 387,026 429,829 404,457 From Oil Wells 7,542 8,934 8,714 8,159 43,421 From Coalbed Wells 7,250

472

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Virginia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S48. Summary statistics for natural gas - Virginia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 5,735 6,426 7,303 7,470 7,903 Production (million cubic feet) Gross Withdrawals From Gas Wells R 6,681 R 7,419 R 16,046 R 23,086 20,375 From Oil Wells 0 0 0 0 0 From Coalbed Wells R 86,275 R 101,567

473

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Michigan - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S24. Summary statistics for natural gas - Michigan, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 9,712 9,995 10,600 10,100 11,100 Production (million cubic feet) Gross Withdrawals From Gas Wells R 80,090 R 16,959 R 20,867 R 7,345 18,470 From Oil Wells 54,114 10,716 12,919 9,453 11,620 From Coalbed Wells 0

474

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Montana - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S28. Summary statistics for natural gas - Montana, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 6,925 7,095 7,031 6,059 6,477 Production (million cubic feet) Gross Withdrawals From Gas Wells R 69,741 R 67,399 R 57,396 R 51,117 37,937 From Oil Wells 23,092 22,995 21,522 19,292 21,777 From Coalbed Wells

475

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Mississippi - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S26. Summary statistics for natural gas - Mississippi, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 2,315 2,343 2,320 1,979 5,732 Production (million cubic feet) Gross Withdrawals From Gas Wells R 259,001 R 331,673 R 337,168 R 387,026 429,829 From Oil Wells 6,203 7,542 8,934 8,714 8,159 From Coalbed Wells

476

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Indiana - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S16. Summary statistics for natural gas - Indiana, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 2,350 525 563 620 914 Production (million cubic feet) Gross Withdrawals From Gas Wells 3,606 4,701 4,927 6,802 9,075 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

477

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 New York - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S34. Summary statistics for natural gas - New York, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 6,680 6,675 6,628 6,736 6,157 Production (million cubic feet) Gross Withdrawals From Gas Wells 54,232 49,607 44,273 35,163 30,495 From Oil Wells 710 714 576 650 629 From Coalbed Wells 0

478

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Texas - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S45. Summary statistics for natural gas - Texas, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 76,436 87,556 93,507 95,014 100,966 Production (million cubic feet) Gross Withdrawals From Gas Wells R 4,992,042 R 5,285,458 R 4,860,377 R 4,441,188 3,794,952 From Oil Wells 704,092 745,587 774,821 849,560 1,073,301

479

Million Cu. Feet Percent of National Total  

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

2 2 Ohio - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S37. Summary statistics for natural gas - Ohio, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 34,416 34,963 34,931 46,717 35,104 Production (million cubic feet) Gross Withdrawals From Gas Wells 79,769 83,511 73,459 30,655 65,025 From Oil Wells 5,072 5,301 4,651 45,663 6,684 From Coalbed Wells 0

480

Million Cu. Feet Percent of National Total  

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

0 0 Colorado - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 25,716 27,021 28,813 30,101 32,000 Production (million cubic feet) Gross Withdrawals From Gas Wells 496,374 459,509 526,077 563,750 1,036,572 From Oil Wells 199,725 327,619 338,565

Note: This page contains sample records for the topic "total daily average" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 South Dakota - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S43. Summary statistics for natural gas - South Dakota, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 71 71 89 102 100 Production (million cubic feet) Gross Withdrawals From Gas Wells 422 R 1,098 R 1,561 1,300 933 From Oil Wells 11,458 10,909 11,366 11,240 11,516 From Coalbed Wells 0 0

482

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Illinois - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S15. Summary statistics for natural gas - Illinois, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 43 45 51 50 40 Production (million cubic feet) Gross Withdrawals From Gas Wells RE 1,389 RE 1,188 RE 1,438 RE 1,697 2,114 From Oil Wells E 5 E 5 E 5 E 5 7 From Coalbed Wells RE 0 RE

483

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Colorado - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 22,949 25,716 27,021 28,813 30,101 Production (million cubic feet) Gross Withdrawals From Gas Wells R 436,330 R 496,374 R 459,509 R 526,077 563,750 From Oil Wells 160,833 199,725 327,619

484

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Alaska - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S2. Summary statistics for natural gas - Alaska, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 239 261 261 269 277 Production (million cubic feet) Gross Withdrawals From Gas Wells 165,624 150,483 137,639 127,417 112,268 From Oil Wells 3,313,666 3,265,401 3,174,747 3,069,683 3,050,654

485

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Ohio - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S37. Summary statistics for natural gas - Ohio, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 34,416 34,416 34,963 34,931 46,717 Production (million cubic feet) Gross Withdrawals From Gas Wells R 82,812 R 79,769 R 83,511 R 73,459 30,655 From Oil Wells 5,268 5,072 5,301 4,651 45,663 From Coalbed Wells

486

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Kentucky - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S19. Summary statistics for natural gas - Kentucky, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 16,563 16,290 17,152 17,670 14,632 Production (million cubic feet) Gross Withdrawals From Gas Wells 95,437 R 112,587 R 111,782 133,521 122,578 From Oil Wells 0 1,529 1,518 1,809 1,665 From Coalbed Wells 0

487

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Utah - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S46. Summary statistics for natural gas - Utah, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 5,197 5,578 5,774 6,075 6,469 Production (million cubic feet) Gross Withdrawals From Gas Wells R 271,890 R 331,143 R 340,224 R 328,135 351,168 From Oil Wells 35,104 36,056 36,795 42,526 49,947 From Coalbed Wells

488

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 California - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S5. Summary statistics for natural gas - California, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 1,540 1,645 1,643 1,580 1,308 Production (million cubic feet) Gross Withdrawals From Gas Wells 93,249 91,460 82,288 73,017 63,902 From Oil Wells R 116,652 R 122,345 R 121,949 R 151,369 120,880

489

Million Cu. Feet Percent of National Total  

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

0 0 Utah - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S46. Summary statistics for natural gas - Utah, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 5,578 5,774 6,075 6,469 6,900 Production (million cubic feet) Gross Withdrawals From Gas Wells 331,143 340,224 328,135 351,168 402,899 From Oil Wells 36,056 36,795 42,526 49,947 31,440 From Coalbed Wells 74,399

490

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Louisiana - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S20. Summary statistics for natural gas - Louisiana, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 18,145 19,213 18,860 19,137 21,235 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,261,539 R 1,288,559 R 1,100,007 R 911,967 883,712 From Oil Wells 106,303 61,663 58,037 63,638 68,505

491

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Oklahoma - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S38. Summary statistics for natural gas - Oklahoma, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 38,364 41,921 43,600 44,000 41,238 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,583,356 R 1,452,148 R 1,413,759 R 1,140,111 1,281,794 From Oil Wells 35,186 153,227 92,467 210,492 104,703

492

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 New Mexico - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S33. Summary statistics for natural gas - New Mexico, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 42,644 44,241 44,784 44,748 32,302 Production (million cubic feet) Gross Withdrawals From Gas Wells R 657,593 R 732,483 R 682,334 R 616,134 556,024 From Oil Wells 227,352 211,496 223,493 238,580 252,326

493

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 West Virginia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S50. Summary statistics for natural gas - West Virginia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 48,215 49,364 50,602 52,498 56,813 Production (million cubic feet) Gross Withdrawals From Gas Wells R 189,968 R 191,444 R 192,896 R 151,401 167,113 From Oil Wells 701 0 0 0 0 From Coalbed Wells

494

Million Cu. Feet Percent of National Total  

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

6 6 Michigan - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S24. Summary statistics for natural gas - Michigan, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 9,995 10,600 10,100 11,100 10,900 Production (million cubic feet) Gross Withdrawals From Gas Wells 16,959 20,867 7,345 18,470 17,041 From Oil Wells 10,716 12,919 9,453 11,620 4,470 From Coalbed Wells 0

495

Million Cu. Feet Percent of National Total  

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

8 8 West Virginia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S50. Summary statistics for natural gas - West Virginia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 49,364 50,602 52,498 56,813 50,700 Production (million cubic feet) Gross Withdrawals From Gas Wells 191,444 192,896 151,401 167,113 397,313 From Oil Wells 0 0 0 0 1,477 From Coalbed Wells 0

496

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

80 80 Wyoming - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S52. Summary statistics for natural gas - Wyoming, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 27,350 28,969 25,710 26,124 26,180 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,649,284 R 1,764,084 R 1,806,807 R 1,787,599 1,709,218 From Oil Wells 159,039 156,133 135,269 151,871 152,589

497

Million Cu. Feet Percent of National Total  

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

6 6 New York - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S34. Summary statistics for natural gas - New York, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,675 6,628 6,736 6,157 7,176 Production (million cubic feet) Gross Withdrawals From Gas Wells 49,607 44,273 35,163 30,495 25,985 From Oil Wells 714 576 650 629 439 From Coalbed Wells 0

498

Million Cu. Feet Percent of National Total  

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

2 2 Wyoming - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S52. Summary statistics for natural gas - Wyoming, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 28,969 25,710 26,124 26,180 22,171 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,764,084 1,806,807 1,787,599 1,709,218 1,762,095 From Oil Wells 156,133 135,269 151,871 152,589 24,544

499

Million Cu. Feet Percent of National Total  

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

4 4 Virginia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S48. Summary statistics for natural gas - Virginia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,426 7,303 7,470 7,903 7,843 Production (million cubic feet) Gross Withdrawals From Gas Wells 7,419 16,046 23,086 20,375 21,802 From Oil Wells 0 0 0 0 9 From Coalbed Wells 101,567 106,408

500

Million Cu. Feet Percent of National Total  

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

6 6 Kentucky - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S19. Summary statistics for natural gas - Kentucky, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 16,290 17,152 17,670 14,632 17,936 Production (million cubic feet) Gross Withdrawals From Gas Wells 112,587 111,782 133,521 122,578 106,122 From Oil Wells 1,529 1,518 1,809 1,665 0 From Coalbed Wells 0