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1

Contractor: Contract Number: Contract Type: Total Estimated  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Number: Number: Contract Type: Total Estimated Contract Cost: Performance Period Total Fee Earned FY2008 $2,550,203 FY2009 $39,646,446 FY2010 $64,874,187 FY2011 $66,253,207 FY2012 $41,492,503 FY2013 $0 FY2014 FY2015 FY2016 FY2017 FY2018 Cumulative Fee Earned $214,816,546 Fee Available $2,550,203 Minimum Fee $77,931,569 $69,660,249 Savannah River Nuclear Solutions LLC $458,687,779 $0 Maximum Fee Fee Information $88,851,963 EM Contractor Fee Site: Savannah River Site Office, Aiken, SC Contract Name: Management & Operating Contract September 2013 DE-AC09-08SR22470

2

Notices Total Estimated Number of Annual  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

72 Federal Register 72 Federal Register / Vol. 78, No. 181 / Wednesday, September 18, 2013 / Notices Total Estimated Number of Annual Burden Hours: 10,128. Abstract: Enrollment in the Federal Student Aid (FSA) Student Aid Internet Gateway (SAIG) allows eligible entities to securely exchange Title IV, Higher Education Act (HEA) assistance programs data electronically with the Department of Education processors. Organizations establish Destination Point Administrators (DPAs) to transmit, receive, view and update student financial aid records using telecommunication software. Eligible respondents include the following, but are not limited to, institutions of higher education that participate in Title IV, HEA assistance programs, third-party servicers of eligible institutions,

3

Estimating Radiation Risk from Total Effective Dose Equivalent...  

National Nuclear Security Administration (NNSA)

and UNSCEAR 1988 in Radiation Risk Assessment - Lifetime Total Cancer Mortality Risk Estimates at Low Doses and Low Dose Rates for Low-LET Radiation, Committee on Interagency...

4

Derived Annual Estimates of Manufacturing Energy Consumption, 1974-1988  

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

Manufacturing > Derived Annual Estimates - Executive Summary Manufacturing > Derived Annual Estimates - Executive Summary Derived Annual Estimates of Manufacturing Energy Consumption, 1974-1988 Figure showing Derived Estimates Executive Summary This report presents a complete series of annual estimates of purchased energy used by the manufacturing sector of the U.S. economy, for the years 1974 to 1988. These estimates interpolate over gaps in the actual data collections, by deriving estimates for the missing years 1982-84 and 1986-87. For the purposes of this report, "purchased" energy is energy brought from offsite for use at manufacturing establishments, whether the energy is purchased from an energy vendor or procured from some other source. The actual data on purchased energy comes from two sources, the U.S. Department of Commerce Bureau of the Census's Annual Survey of Manufactures (ASM) and EIA's Manufacturing Energy Consumption Survey (MECS). The ASM provides annual estimates for the years 1974 to 1981. However, in 1982 (and subsequent years) the scope of the ASM energy data was reduced to collect only electricity consumption and expenditures and total expenditures for other purchased energy. In 1985, EIA initiated the triennial MECS collecting complete energy data. The series equivalent to the ASM is referred to in the MECS as "offsite-produced fuels." The completed annual series for 1974 to 1988 developed in this report links the ASM and MECS "offsite" series, estimating for the missing years. Estimates are provided for the manufacturing sector as a whole and at the two-digit Standard Industrial Classification (SIC) level for total energy consumption and for the consumption of individual fuels. There are no direct sources of data for the missing years (1982-1984 and 1986-1987). To derive consumption estimates, a comparison was made between the ASM, MECS, and other economic series to see whether there were any good predictors for the missing data. Various estimation schemes were analyzed to fill in the gaps in data after 1981 by trying to match known data for the 1974 to 1981 period.

5

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

E-Print Network (OSTI)

Estimating Total Energy Consumption and Emissions of China’sof China’s total energy consumption mix. However, accuratelyof China’s total energy consumption, while others estimate

Fridley, David G.

2008-01-01T23:59:59.000Z

6

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

E-Print Network (OSTI)

ABORATORY Estimating Total Energy Consumption and Emissionscomponent of China’s total energy consumption mix. However,about 19% of China’s total energy consumption, while others

Fridley, David G.

2008-01-01T23:59:59.000Z

7

b) Economic i) Total damage estimates: From Pimentel et al. (2000)  

E-Print Network (OSTI)

4) Impacts b) Economic i) Total damage estimates: From Pimentel et al. (2000) · United States #12;4) Impacts b) Economic i) Total damage estimates: From Pimentel et al. (2000) · United States Economic impacts from losses/damage #12;4) Impacts b) Economic i) Total damage estimates: From Pimentel et al

Nowak, Robert S.

8

Eccentricity Error Correction for Automated Estimation of Polyethylene Wear after Total Hip Arthroplasty  

E-Print Network (OSTI)

Eccentricity Error Correction for Automated Estimation of Polyethylene Wear after Total Hip. Wire markers are typically attached to the polyethylene acetabular component of the prosthesis so

St Andrews, University of

9

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

SciTech Connect

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

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

2008-03-01T23:59:59.000Z

10

An evaluation of total body electrical conductivity to estimate body composition of largemouth bass  

E-Print Network (OSTI)

Information about body composition of fish is important for the assessment and management of fish stocks. Measurement of total body electrical conductivity (TOBEC) recently has been used to estimate the body composition of several fish species in a...

Barziza, Daniel Eugene

2012-06-07T23:59:59.000Z

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

ESTIMATION OF TOTAL RADIATIVE POWER FROM THE 6-GEV RING LS-24  

NLE Websites -- All DOE Office Websites (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

15

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

16

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

17

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

18

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

19

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

20

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

Note: This page contains sample records for the topic "derived estimates total" 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

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

22

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

23

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

24

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

25

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

26

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

27

Deriving Atmospheric Density Estimates Using Satellite Precision Orbit Ephemerides  

E-Print Network (OSTI)

Model regardless of solar and geomagnetic activity levels. The POE density estimates were obtained with the desired accuracy for a ±10% variation in the ballistic coefficient used to initialize the process. Fit span length showed little influence...

Hiatt, Andrew Timothy

2009-01-01T23:59:59.000Z

28

Total Ozone Mapping Spectrometer (TOMS) Derived Data, Global Earth Coverage (GEC) from NASA's Earth Probe Satellite  

DOE Data Explorer (OSTI)

This is data from an external datastream processed through the ARM External Data Center (XDC) at Brookhaven National Laboratory. The XDC identifies sources and acquires data, called "external data", to augment the data being generated within the ARM program. The external data acquired are usually converted from native format to either netCDF or HDF formats. The GEC collection contains global data derived from the Total Ozone Mapping Spectrometer (TOMS) instrument on the Earth Probe satellite, consisting of daily values of aerosol index, ozone and reflectivity remapped into a regular 1x1.25 deg grid. Data are available from July 25, 1996 - December 31, 2005, but have been updated or replaced as of September 2007. See the explanation on the ARM web site at http://www.arm.gov/xds/static/toms.stm and the information at the NASA/TOMS web site: http://toms.gsfc.nasa.gov/ (Registration required)

29

Error estimation of bathymetric grid models derived from historic and contemporary datasets  

E-Print Network (OSTI)

1 Error estimation of bathymetric grid models derived from historic and contemporary datasets and rapidly collecting dense bathymetric datasets. Sextants were replaced by radio navigation, then transit, to digitized contours; the test dataset shows examples of all of these types. From this database, we assign

New Hampshire, University of

30

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

E-Print Network (OSTI)

were used to calculate the energy mix in manufacturing,of China’s total energy consumption mix. However, accuratelyof China’s total energy consumption mix. However, accurately

Fridley, David G.

2008-01-01T23:59:59.000Z

31

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

E-Print Network (OSTI)

18 Figure 6 Primary Energy Consumption by End-Use in24 Figure 7 Primary Energy Consumption by Fuel in Commercialbased on total primary energy consumption (source energy),

Fridley, David G.

2008-01-01T23:59:59.000Z

32

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

E-Print Network (OSTI)

of Central Government Buildings. ” Available at: http://Energy Commission, PIER Building End-Use Energy Efficiencythe total lifecycle of a building such as petroleum and

Fridley, David G.

2008-01-01T23:59:59.000Z

33

A Comparison of Load Estimates Using Total Suspended Solids and Suspended-Sediment Concentration Data  

E-Print Network (OSTI)

-sediment concentration (SSC) data and the ramifications of using each type of data to estimate sediment loads from paired TSS and SSC data, to annual loads computed by the U.S. Geological Survey (USGS) using traditional techniques and SSC data. Load estimates were compared for 10 stations where sufficient TSS and SSC

Torgersen, Christian

34

Accumulated CFC-11 in polyurethane foam insulation: an estimate of the total amount in district heating installations in Sweden  

Science Journals Connector (OSTI)

In rigid polyurethane foam used for thermal insulation, CFC-11 has been the main blowing agent for many years, but is now subject to phase-out regulations. During ageing of this foam, air diffuses into it and blowing agents leak into the atmosphere, resulting in a decreased insulating capacity. Determinations of the cell gas composition and the total content of CFC-11 in foam from district heating installations of different ages are reported in this paper. The total amount of CFC-11 in old district heating schemes in Sweden is estimated at 2000 tonnes. The amount in refrigeration equipment in Sweden is about twice as large.

M. Svanstrom

1996-01-01T23:59:59.000Z

35

Estimate the fraction of the total transported energy (in the form of gasoline) in the Trans-Alaska Pipeline that is consumed in pumping.  

E-Print Network (OSTI)

Estimate the fraction of the total transported energy (in the form of gasoline) in the Trans m). So we can toss this out. Now estimate the energy content of gasoline: Many of you tried figuring

Nimmo, Francis

36

Assessment of the validity of conductivity as an estimate of total dissolved solids in heavy-duty coolants  

SciTech Connect

Conductivity is widely used in the analysis of heavy-duty coolants to estimate total dissolved solids. TDS is of concern in heavy-duty coolants because the practice of adding supplemental coolant additives (SCAs) to the coolant can lead to overloading and to subsequent water pump seal weepage and failure. Conductivity has the advantage of being quick and easy to measure and the equipment is inexpensive. However, questions are continually raised as to whether conductivity truly is a valid method of estimating TDS and, if so, over what concentration range. The introduction of new chemistries in heavy-duty coolants and new extended service interval (ESI) technologies prompts a critical assessment. Conductivity and TDS measurements for all of the coolants and SCAs used in heavy-duty engines in North America will be presented. The effects of glycol concentration on conductivity will also be examined.

Carr, R.P. [Penray Companies, Inc., Wheeling, IL (United States)

1999-08-01T23:59:59.000Z

37

Table ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States  

Gasoline and Diesel Fuel Update (EIA)

ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States Year Primary Energy Electric Power Sector h,j Retail Electricity Total Energy g,h,i Coal Coal Coke Natural Gas a Petroleum Nuclear Fuel Biomass Total g,h,i,j Coking Coal Steam Coal Total Exports Imports Distillate Fuel Oil Jet Fuel b LPG c Motor Gasoline d Residual Fuel Oil Other e Total Wood and Waste f,g Prices in Dollars per Million Btu 1970 0.45 0.36 0.38 1.27 0.93 0.59 1.16 0.73 1.43 2.85 0.42 1.38 1.71 0.18 1.29 1.08 0.32 4.98 1.65 1975 1.65 0.90 1.03 2.37 3.47 1.18 2.60 2.05 2.96 4.65 1.93 2.94 3.35 0.24 1.50 2.19 0.97 8.61 3.33 1980 2.10 1.38 1.46 2.54 3.19 2.86 6.70 6.36 5.64 9.84 3.88 7.04 7.40 0.43 2.26 4.57 1.77 13.95 6.89 1985 2.03 1.67 1.69 2.76 2.99 4.61 7.22 5.91 6.63 9.01 4.30 R 7.62 R 7.64 0.71 2.47 4.93 1.91 19.05

38

Collapsing Estimates and the Rigorous Derivation of the 2d Cubic Nonlinear Schrödinger Equation with Anisotropic Switchable Quadratic Traps  

E-Print Network (OSTI)

We consider the 2d and 3d many body Schr\\"odinger equations in the presence of anisotropic switchable quadratic traps. We extend and improve the collapsing estimates in Klainerman-Machedon [24] and Kirkpatrick-Schlein-Staffilani [23]. Together with an anisotropic version of the generalized lens transform in Carles [3], we derive rigorously the cubic NLS with anisotropic switchable quadratic traps in 2d through a modified Elgart-Erd\\"os-Schlein-Yau procedure. For the 3d case, we establish the uniqueness of the corresponding Gross-Pitaevskii hierarchy without the assumption of factorized initial data.

Xuwen Chen

2011-02-03T23:59:59.000Z

39

The Effect of Inaccuracies in Weather-Ship Data on Bulk-Derived Estimates of Flux, Stability and Sea-Surface Roughness  

Science Journals Connector (OSTI)

An analytical error analysis (or sensitivity study) is performed for the momentum, heat, and humidity flux estimates made from weather-ship observations by using the bulk flux method. Bulk-derived stability and roughness errors are also examined. ...

Theodore V. Blanc

1986-03-01T23:59:59.000Z

40

ESTIMATE OF THE TOTAL MECHANICAL FEEDBACK ENERGY FROM GALAXY CLUSTER-CENTERED BLACK HOLES: IMPLICATIONS FOR BLACK HOLE EVOLUTION, CLUSTER GAS FRACTION, AND ENTROPY  

SciTech Connect

The total feedback energy injected into hot gas in galaxy clusters by central black holes can be estimated by comparing the potential energy of observed cluster gas profiles with the potential energy of non-radiating, feedback-free hot gas atmospheres resulting from gravitational collapse in clusters of the same total mass. Feedback energy from cluster-centered black holes expands the cluster gas, lowering the gas-to-dark-matter mass ratio below the cosmic value. Feedback energy is unnecessarily delivered by radio-emitting jets to distant gas far beyond the cooling radius where the cooling time equals the cluster lifetime. For clusters of mass (4-11) x 10{sup 14} M{sub sun}, estimates of the total feedback energy, (1-3) x 10{sup 63} erg, far exceed feedback energies estimated from observations of X-ray cavities and shocks in the cluster gas, energies gained from supernovae, and energies lost from cluster gas by radiation. The time-averaged mean feedback luminosity is comparable to those of powerful quasars, implying that some significant fraction of this energy may arise from the spin of the black hole. The universal entropy profile in feedback-free gaseous atmospheres in Navarro-Frenk-White cluster halos can be recovered by multiplying the observed gas entropy profile of any relaxed cluster by a factor involving the gas fraction profile. While the feedback energy and associated mass outflow in the clusters we consider far exceed that necessary to stop cooling inflow, the time-averaged mass outflow at the cooling radius almost exactly balances the mass that cools within this radius, an essential condition to shut down cluster cooling flows.

Mathews, William G.; Guo Fulai, E-mail: mathews@ucolick.org [University of California Observatories/Lick Observatory, Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States)

2011-09-10T23:59:59.000Z

Note: This page contains sample records for the topic "derived estimates total" 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

1. [M] Estimate the fraction of the total transported energy (in the form of gasoline) in the Trans-Alaska Pipeline that is consumed in pumping. As always, try not to look anything up.  

E-Print Network (OSTI)

1. [M] Estimate the fraction of the total transported energy (in the form of gasoline) in the Trans to this (which is 1 bend per 10 m). So we can toss this out. Now estimate the energy content of gasoline: Many

Nimmo, Francis

42

‘Bioinspired’ Total Synthesis of Agelastatin A and Derivatives for Cellular Target Identification; Syntheses of ^(15)N-labeled Oroidin and Keramadine Analog for ‘Metabiosynthetic’ Studies  

E-Print Network (OSTI)

agelastatin A derivatives leading to a bioactive biotin probe that is proving to be useful for cellular target identification. In an effort toward understanding the biosynthesis of P-2-AIs, a synthesis of^( 15)N-oroidin labeled oroidin was developed and pulse...

Reyes, Jeremy Chris Punzalan

2013-11-08T23:59:59.000Z

43

Estimating the Sea Ice Compressive Strength from Satellite-Derived Sea Ice Drift and NCEP Reanalysis Data  

Science Journals Connector (OSTI)

Satellite-derived sea ice drift maps and sea level pressure from reanalysis data are used to infer upper and lower bounds on the large-scale compressive strength of Arctic sea ice. To this end, the two datasets are searched for special situations ...

L-B. Tremblay; M. Hakakian

2006-11-01T23:59:59.000Z

44

Estimation of the total effective dose from low-dose CT scans and radiopharmaceutical administrations delivered to patients undergoing SPECT/CT explorations  

Science Journals Connector (OSTI)

The effective dose calculation is useful to compare the doses from, and the radiation risks associated with, different diagnostic examinations. ... account the uncertainties associated with the estimated effectiv...

Carlos Montes; Pilar Tamayo; Jorge Hernandez…

2013-08-01T23:59:59.000Z

45

Estimate of the total kinetic power and age of an extragalactic jet by its cocoon dynamics: the case of Cygnus A  

Science Journals Connector (OSTI)

......the quantities of total plasma. Also, for radio bubbles...specific heat ratio of the plasma inside the cocoon, respectively...the ICM with declining atmosphere and the relativistic...visible in the 610-MHz image and the aspect...D., 1998, Phys. Plasmas, 5, 1981. Celotti......

M. Kino; N. Kawakatu

2005-12-01T23:59:59.000Z

46

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

47

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.

48

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

$ 3,422,994.00 $ 3,422,994.00 FY2011 4,445,142.00 $ FY2012 $ 5,021,951.68 FY2013 $ 3,501,670.00 FY2014 $0 FY2015 $0 FY2016 $0 FY2017 $0 FY2018 $0 FY2019 $0 Cumulative Fee Paid $16,391,758 Wackenhut Services, Inc. DE-AC30-10CC60025 Contractor: Cost Plus Award Fee $989,000,000 Contract Period: Contract Type: January 2010 - December 2019 Contract Number: EM Contractor Fee Site: Savannah River Site Office - Aiken, SC Contract Name: Comprehensive Security Services September 2013 Fee Information Maximum Fee $55,541,496 $5,204,095 $3,667,493 $5,041,415 Minimum Fee 0 Fee Available $5,428,947 $6,326,114

49

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Energy Savers (EERE)

Wastren-EnergX Mission Support LLC Contract Number: DE-CI0000004 Contract Type: Cost Plus Award Fee 128,879,762 Contract Period: December 2009 - July 2015 Fee Information...

50

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

Period: Fee Information Maximum Fee Contract Type: Minimum Fee 91,085,394 74,386,573 Target Fee September 2002 - March 2017 Cost Plus Fixed FeeIncentive Fee 1,192,114,896...

51

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

Fee Paid 127,390,991 Contract Number: Fee Available Contract Period: Contract Type: Cost Plus Award Fee 4,104,318,749 28,500,000 31,597,837 0 39,171,018 32,871,600 EM...

52

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

- Oak Ridge, TN Contract Name: Transuranic Waste Processing Contract June, 2014 2,433,940 Cost Plus Award Fee 150,664,017 Fee Information Minimum Fee 2,039,246 Maximum Fee...

53

Total Estimated Contract Cost:) Performance Period Total Fee...  

Office of Environmental Management (EM)

Washington Closure LLC DE-AC06-05RL14655 Contractor: Contract Number: Contract Type: Cost Plus Incentive Fee 2,251,328,348 Fee Information 0 Maximum Fee 337,699,252...

54

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

Analytical Services & Testing Contract June 2014 Contractor: Contract Number: Contract Type: Advanced Technologies & Labs International Inc. DE-AC27-10RV15051 Cost Plus Award Fee...

55

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Energy Savers (EERE)

Cumulative Fee Paid 22,200,285 Wackenhut Services, Inc. DE-AC30-10CC60025 Contractor: Cost Plus Award Fee 989,000,000 Contract Period: Contract Type: January 2010 - December...

56

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Energy Savers (EERE)

& Wilcox Conversion Services, LLC Contract Number: DE-AC30-11CC40015 Contract Type: Cost Plus Award Fee EM Contractor Fee June, 2014 Site: Portsmouth Paducah Project Office...

57

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

Number: Contract Type: Contract Period: 0 Minimum Fee Maximum Fee Washington River Protection Solutions LLC DE-AC27-08RV14800 Cost Plus Award Fee 5,553,789,617 Fee Information...

58

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

2011 - September 2015 June 2014 Contractor: Contract Number: Contract Type: Idaho Treatment Group LLC DE-EM0001467 Cost Plus Award Fee Fee Information 419,202,975 Contract Period:...

59

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

FY2010 FY2011 FY2012 Fee Information Minimum Fee Maximum Fee June 2014 Contract Number: Cost Plus Incentive Fee Contractor: 3,245,814,927 Contract Period: EM Contractor Fee Site:...

60

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

0 Contractor: Bechtel National Inc. Contract Number: DE-AC27-01RV14136 Contract Type: Cost Plus Award Fee Maximum Fee* 595,123,540 Fee Available 102,622,325 10,714,819,974...

Note: This page contains sample records for the topic "derived estimates total" 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.
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61

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

DE-AM09-05SR22405DE-AT30-07CC60011SL14 Contractor: Contract Number: Contract Type: Cost Plus Award Fee 357,223 597,797 894,699 EM Contractor Fee Site: Stanford Linear...

62

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

LLC (UCOR) DE-SC-0004645 April 29, 2011 - July 13, 2016 Contract Number: Maximum Fee Cost Plus Award Fee 16,098,142 EM Contractor Fee Site: Oak Ridge Office - Oak Ridge, TN...

63

Total Estimated Contract Cost: Performance Period Total Fee Paid  

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

Type: Cost Plus Award Fee 4,104,318,749 28,500,000 31,597,837 0 39,171,018 32,871,600 EM Contractor Fee Site: Savannah River Site Office - Aiken, SC Contract Name:...

64

Cell Total Activity Final Estimate.xls  

Office of Legacy Management (LM)

5.26E-02 3.99E-02 9.89E-02 1.02E-01 4.44E-02 3.63E-02 4.44E-02 2.29E+00 Sediments - Train 1 155 1.99E+08 Site soils 2.07E-02 2.05E-02 1.16E-03 8.78E-04 2.17E-03 2.23E-03...

65

Contractor: Contract Number: Contract Type: Total Estimated  

Energy Savers (EERE)

Services Support Contract Fee Information Contract Period: Cost Plus Award Fee 3,311,479,516 September 2014 May 2009 - May 2019 Mission Support Alliance, LLC DE-AC06-09RL14728...

66

Total isomerization gains flexibility  

SciTech Connect

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

67

Deriving a Framework for Estimating Individual Tree Measurements with Lidar for Use in the TAMBEETLE Southern Pine Beetle Infestation Growth Model  

E-Print Network (OSTI)

. TAMBEETLE was used to compare spot growth between a lidar-derived forest map and a forest map generated by TAMBEETLE, based on sample plot characteristics. The lidar-derived forest performed comparably to the TAMBEETLE generated forest. Using lidar to map...

Stukey, Jared D.

2011-02-22T23:59:59.000Z

68

Summary Max Total Units  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

69

Adsorption of Volatile Organic Compounds in Pillared Clays:? Estimation of the Separation Factor by a Method Derived from the Dubinin?Radushkevich Equation  

Science Journals Connector (OSTI)

Figure 1 Adsorption isotherms (nitrogen at 77 K and other vapors at 298 K) in the aluminum oxide pillared clay (Al-PILC). ... Figure 2 Adsorption isotherms (nitrogen at 77 K and other vapors at 298 K) in the zirconium oxide pillared clay (Zr-PILC). ... Figure 3 Separation factors versus coverage for the aluminum oxide pillared clay (Al-PILC) with the values of ? estimated from the parachors (closed symbols) or the molar polarizations (open symbols) using benzene (squares) or carbon tetrachloride (triangles) as standard vapor. ...

Joăo Pires; Moisés L. Pinto; Ana Carvalho; M. B. de Carvalho

2003-08-16T23:59:59.000Z

70

Barge Truck Total  

Annual Energy Outlook 2012 (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...

71

Weekly Coal Production Estimation Methodology  

NLE Websites -- All DOE Office Websites (Extended Search)

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

72

Estimating Derivatives of Noisy Simulations1  

E-Print Network (OSTI)

1Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439. ... partment of Energy, under Contract DE-AC02-06CH11357. .... Of course, tighter bounds are available if we have additional information on the.

2010-11-02T23:59:59.000Z

73

Variations of Total Domination  

Science Journals Connector (OSTI)

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

Michael A. Henning; Anders Yeo

2013-01-01T23:59:59.000Z

74

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

75

Estimating Methods  

Directives, Delegations, and Requirements

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

1997-03-28T23:59:59.000Z

76

Performance Period Total Fee Paid  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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:

77

Total Space Heat-  

Annual Energy Outlook 2012 (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...

78

Project Functions and Activities Definitions for Total Project Cost  

Directives, Delegations, and Requirements

This chapter provides guidelines developed to define the obvious disparity of opinions and practices with regard to what exactly is included in total estimated cost (TEC) and total project cost (TPC).

1997-03-28T23:59:59.000Z

79

"Table A2. Total Consumption of LPG, Distillate Fuel Oil,...  

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

. Total Consumption of LPG, Distillate Fuel Oil, and Residual Fuel" " Oil for Selected Purposes by Census Region, Industry Group, and Selected" " Industries, 1991" " (Estimates in...

80

21 briefing pages total  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

Note: This page contains sample records for the topic "derived estimates total" 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

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

82

Total Precipitable Water  

SciTech Connect

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

83

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

84

Estimating Radiation Risk from Total Effective Dose Equivalent...  

National Nuclear Security Administration (NNSA)

0CTc itt 0 Tw (an) Tj 10.3 0 Tw (an) Tj 10.3 0 Tw (an) Tj 10.3 a ( )75 Tw5ndj 5.25 0 TD F1 10.5 Tf -0.3 33twithsj 24 0 .75059 0 TD(FactorsTw ( 32 ) Tj 5.25 0 TD F1 10.5 Tf...

85

State Emissions Estimates  

Gasoline and Diesel Fuel Update (EIA)

Estimates of state energy-related carbon dioxide emissions Estimates of state energy-related carbon dioxide emissions Because energy-related carbon dioxide (CO 2 ) constitutes over 80 percent of total emissions, the state energy-related CO 2 emission levels provide a good indicator of the relative contribution of individual states to total greenhouse gas emissions. The U.S. Energy Information Administration (EIA) emissions estimates at the state level for energy-related CO 2 are based on data contained in the State Energy Data System (SEDS). 1 The state-level emissions estimates are based on energy consumption data for the following fuel categories: three categories of coal (residential/commercial, industrial, and electric power sector); natural gas; and ten petroleum products including-- asphalt and road oil, aviation gasoline, distillate fuel, jet fuel, kerosene, liquefied petroleum gases

86

Total to Selective Extinction Ratios and Visual Extinctions from Ultraviolet Data  

E-Print Network (OSTI)

We present determinations of the total to selective extinction ratio R_V and visual extinction A_V values for Milky Way stars using ultraviolet color excesses. We extend the analysis of Gnacinski and Sikorski (1999) by using non-equal weights derived from observational errors. We present a detailed discussion of various statistical errors. In addition, we estimate the level of systematic errors by considering different normalization of the extinction curve adopted by Wegner (2002). Our catalog of 782 R_V and A_V values and their errors is available in the electronic form on the World Wide Web.

Anna Geminale; Piotr Popowski

2004-09-21T23:59:59.000Z

87

Complex higher order derivative theories  

SciTech Connect

In this work is considered a complex scalar field theory with higher order derivative terms and interactions. A procedure is developed to quantize consistently this system avoiding the presence of negative norm states. In order to achieve this goal the original real scalar high order field theory is extended to a complex space attaching a complex total derivative to the theory. Next, by imposing reality conditions the complex theory is mapped to a pair of interacting real scalar field theories without the presence of higher derivative terms.

Margalli, Carlos A.; Vergara, J. David [Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, Apartado Postal 70-543, Mexico 04510 DF (Mexico)

2012-08-24T23:59:59.000Z

88

ONLINE TRAFFIC LIGHT CONTROL THROUGH GRADIENT ESTIMATION USING  

E-Print Network (OSTI)

Infinitesimal Perturbation and Analysis (IPA) but the model we use to derive the #12;IPA estimates developed which is based on IPA (Cassandras et al., 2002). In this approach, we derive estimators

Panayiotou, Christos

89

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

90

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

NLE Websites -- All DOE Office Websites (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,...

91

Estimating SCR installation costs  

SciTech Connect

The EUCG surveyed 72 separate US installations of selective catalytic reduction (SCR) systems at coal-fired units totalling 41 GW of capacity to identify the systems' major cost drivers. The results, summarized in this article, provide excellent first-order estimates and guidance for utilities considering installing the downstream emissions-control technology. 4 figs., 1 tab.

Marano, M.; Sharp, G. [American Electric Power (United States)

2006-01-15T23:59:59.000Z

92

Cost Estimator  

Energy.gov (U.S. Department of Energy (DOE))

A successful candidate in this position will serve as a senior cost and schedule estimator who is responsible for preparing life-cycle cost and schedule estimates and analyses associated with the...

93

Total Cross Sections for Neutron Scattering  

E-Print Network (OSTI)

Measurements of neutron total cross-sections are both extensive and extremely accurate. Although they place a strong constraint on theoretically constructed models, there are relatively few comparisons of predictions with experiment. The total cross-sections for neutron scattering from $^{16}$O and $^{40}$Ca are calculated as a function of energy from $50-700$~MeV laboratory energy with a microscopic first order optical potential derived within the framework of the Watson expansion. Although these results are already in qualitative agreement with the data, the inclusion of medium corrections to the propagator is essential to correctly predict the energy dependence given by the experiment.

C. R. Chinn; Ch. Elster; R. M. Thaler; S. P. Weppner

1994-10-19T23:59:59.000Z

94

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

95

Manufacturing Consumption of Energy 1994 - Derived measures of end-use  

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

eialogo eialogo Calculation of MECS Energy Measures Reported energy values were used to construct several derived values, which, in turn, were used to prepare the estimates appearing in MECS consumption tables--First Use, Total Inputs, Offsite-Produced. These derived values are displayed in Table 1 and defined as follows: Energy produced offsite and consumed as a fuel. This derived value represents onsite consumption of fuels that were originally produced offsite. That is, they arrived at the establishment as the result of a purchase or were transferred to the establishment from outside sources. As such, this derived value is equivalent to consumption of "purchased" fuels as reported by the Census Bureau for the years 1974-1981. The Census Bureau defines "purchased" fuels to include those actually purchased plus those

96

Table E6. Transportation Sector Energy Price Estimates, 2012  

Annual Energy Outlook 2012 (EIA)

E6. Transportation Sector Energy Price Estimates, 2012 (Dollars per Million Btu) State Primary Energy Retail Electricity Total Energy Coal Natural Gas Petroleum Total Aviation...

97

Enantioselective total Synthesis of the agelastatin and trigonoliimine alkaloids  

E-Print Network (OSTI)

I. Total Synthesis of the (-)-Agelastatin Alkaloids The pyrrole-imidazole family of marine alkaloids, derived from linear clathrodin-like precursors, constitutes a diverse array of structurally complex natural products. ...

Han, Sunkyu, 1982-

2012-01-01T23:59:59.000Z

98

Estimating UV Index Climatology over Canada  

Science Journals Connector (OSTI)

Hourly UV index values at 45 sites in Canada were estimated using a statistical relationship between UV irradiance and global solar radiation, total ozone, and dewpoint temperature. The estimation method also takes into account the enhancement of ...

V. E. Fioletov; J. B. Kerr; L. J. B. McArthur; D. I. Wardle; T. W. Mathews

2003-03-01T23:59:59.000Z

99

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

100

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

SciTech Connect

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

Note: This page contains sample records for the topic "derived estimates total" 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

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

102

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

103

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

104

Total solar irradiance during the Holocene F. Steinhilber,1  

E-Print Network (OSTI)

Total solar irradiance during the Holocene F. Steinhilber,1 J. Beer,1 and C. Fro¨hlich2 Received 20 solar irradiance covering 9300 years is presented, which covers almost the entire Holocene. This reconstruction is based on a recently observationally derived relationship between total solar irradiance

Wehrli, Bernhard

105

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

106

Table A39. Total Expenditures for Purchased Electricity and Steam  

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

9. Total Expenditures for Purchased Electricity and Steam" 9. Total Expenditures for Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" ," Electricity",," Steam" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,"Total United States" "RSE Column Factors:",0.3,2,1.6,1.2

107

Mujeres Hombres Total Hombres Total 16 5 21 0 10  

E-Print Network (OSTI)

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

Autonoma de Madrid, Universidad

108

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

109

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

110

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

111

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

112

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

113

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

114

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

115

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

116

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

117

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

118

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

119

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

120

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

Note: This page contains sample records for the topic "derived estimates total" 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

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

122

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

123

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

124

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

125

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

126

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

127

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

128

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

129

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

130

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

131

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

132

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

133

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

134

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)

135

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

136

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

137

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)...........................

138

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

139

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

140

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

Note: This page contains sample records for the topic "derived estimates total" 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

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,...

142

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...

143

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

Annual Energy Outlook 2012 (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,...

144

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...

145

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...

146

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...

147

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

Annual Energy Outlook 2012 (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...

148

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

Annual Energy Outlook 2012 (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...

149

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,...

150

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...

151

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...

152

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

Annual Energy Outlook 2012 (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...

153

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...

154

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...

155

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...

156

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...

157

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...

158

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

159

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

160

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

Note: This page contains sample records for the topic "derived estimates total" 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...............................................................  

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

162

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

163

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

164

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

165

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

166

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

167

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

168

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

169

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

170

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

171

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

172

Tropical Africa: Total Forest Biomass (By Country)  

NLE Websites -- All DOE Office Websites (Extended Search)

Tropical Africa: Total Forest Biomass (By Country) Tropical Africa: Total Forest Biomass (By Country) image Brown, S., and G. Gaston. 1996. Tropical Africa: Land Use, Biomass, and Carbon Estimates For 1980. ORNL/CDIAC-92, NDP-055. Carbon Dioxide Information Analysis Center, U.S. Department of Energy, Oak Ridge National Laboratory, Oak Ridge, Tennessee, U.S.A. More Maps Calculated Actual Aboveground Live Biomass in Forests (1980) Maximum Potential Biomass Density Land Use (1980) Area of Closed Forests (By Country) Mean Biomass of Closed Forests (By County) Area of Open Forests (By Country) Mean Biomass of Open Forests (By County) Percent Forest Cover (By Country) Population Density - 1990 (By Administrative Unit) Population Density - 1980 (By Administrative Unit) Population Density - 1970 (By Administrative Unit)

173

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

174

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

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

0. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Fuel Type, Industry Group, Selected Industries, and End Use, 1994:" " Part 2" " (Estimates in Trillion...

175

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Electricity Flow, (Quadrillion Btu) Electricity Flow, (Quadrillion Btu) Electricity Flow diagram image Footnotes: 1 Blast furnace gas, propane gas, and other manufactured and waste gases derived from fossil fuels. 2 Batteries, chemicals, hydrogen, pitch, purchased steam, sulfur, miscellaneous technologies, and non-renewable waste (municipal solid waste from non-biogenic sources, and tire-derived fuels). 3 Data collection frame differences and nonsampling error. Derived for the diagram by subtracting the "T & D Losses" estimate from "T & D Losses and Unaccounted for" derived from Table 8.1. 4 Electric energy used in the operation of power plants. 5 Transmission and distribution losses (electricity losses that occur between the point of generation and delivery to the customer) are estimated

176

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

177

NPP Estimation for Grasslands  

NLE Websites -- All DOE Office Websites (Extended Search)

NPP for Grasslands NPP for Grasslands Introduction The Oak Ridge DAAC Net Primary Production (NPP) Database includes field measurements from grassland study sites worldwide. The following brief review and discussion is intended to explain the complexity of NPP estimates derived from grassland measurements. There is no single answer to the question, "What is the productivity of the ecosystem at study site A?"; rather there may be range of estimates of NPP, depending upon what data were actually collected and how these data are processed. Although some of these methods for determining NPP for grasslands may be applicable to other vegetation types (e.g., semi-deserts, tundra, or some crops), methods for forests, in particular, are significantly different. Nevertheless, it should be possible to answer the question, "Is this modelled value of NPP reasonable for this ecosystem type at this location?"

178

Total Sky Imager (TSI) Handbook  

SciTech Connect

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

179

Estimates of Savings Achievable from Irrigation Controller  

SciTech Connect

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

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

2014-03-28T23:59:59.000Z

180

On the estimation of numerus clausus  

Science Journals Connector (OSTI)

In this paper a method for estimating the necessary number of enrollments is derived, when the future need of graduates and the probabilities of ever graduating and of graduating in a certain time are given. T...

Anita Lukka

1972-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "derived estimates total" 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

Using Surface Remote Sensors to Derive Mixed-Phase Cloud Radiative Forcing:  

NLE Websites -- All DOE Office Websites (Extended Search)

Using Surface Remote Sensors to Derive Mixed-Phase Cloud Radiative Forcing: Using Surface Remote Sensors to Derive Mixed-Phase Cloud Radiative Forcing: An Example from M-PACE Title Using Surface Remote Sensors to Derive Mixed-Phase Cloud Radiative Forcing: An Example from M-PACE Publication Type Journal Article Year of Publication 2011 Authors de Boer, Gijs, William D. Collins, Surabi Menon, and Charles N. Long Journal Atmospheric Chemistry and Physics Volume 11 Start Page 11937 Pagination 11937-11949 Abstract Measurements from ground-based cloud radar, high spectral resolution lidar and microwave radiometer are used in conjunction with a column version of the Rapid Radiative Transfer Model (RRTMG) and radiosonde measurements to derive the surface radiative properties under mixed-phase cloud conditions. These clouds were observed during the United States Department of Energy (US DOE) Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Clouds Experiment (M-PACE) between September and November of 2004. In total, sixteen half hour time periods are reviewed due to their coincidence with radiosonde launches. Cloud liquid (ice) water paths are found to range between 11.0-366.4 (0.5-114.1) gm-2, and cloud physical thicknesses fall between 286-2075 m. Combined with temperature and hydrometeor size estimates, this information is used to calculate surface radiative flux densities using RRTMG, which are demonstrated to generally agree with measured flux densities from surface-based radiometric instrumentation. Errors in longwave flux density estimates are found to be largest for thin clouds, while shortwave flux density errors are generally largest for thicker clouds. A sensitivity study is performed to understand the impact of retrieval assumptions and uncertainties on derived surface radiation estimates. Cloud radiative forcing is calculated for all profiles, illustrating longwave dominance during this time of year, with net cloud forcing generally between 50 and 90 Wm-2.

182

deriving risk estimates that are applicable to ageneralpopulation.  

E-Print Network (OSTI)

. Sources and Effects of Ionizing Radiation. UNSCEAR 2000 Rep. Vols I, II (UNSCEAR, New York, 2000). 3. ICRP Ann. ICRP 21 (1­3) (1991). 4. NRPB Docs NRPB 4 (4), 15­157 (1993). 5. Roesch, W. C. (ed.) US­Japan Joint Reassessment of Atomic Bomb Radiation Dosimetry in Hiroshima and Nagasaki (Radiation Effects Res

Stocker, Thomas

183

Graph Coloring in the Estimation of Sparse Derivative Matrices ...  

E-Print Network (OSTI)

Mar 15, 2004 ... being run for 3 days on a Sun Blade 10 running Solaris. Chaff (a SAT solver) to- .... A sparse matrix library in c++ for high performance ...

2004-03-15T23:59:59.000Z

184

On Global Structure of Hadronic Total Cross-Sections  

E-Print Network (OSTI)

Simple theoretical formula describing the global structure of pp and p\\bar p total cross-secrions in the whole range of energies available up today has been derived. The fit to the experimental data with the formula has been made. It is shown that there is a very good correspondence of the theoretical formula to the existing experimental data.

A. A. Arkhipov

2001-12-14T23:59:59.000Z

185

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Releases Revised Total System Life Cycle Releases Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report for Yucca Mountain Project U.S. Department of Energy Releases Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report for Yucca Mountain Project August 5, 2008 - 2:40pm Addthis WASHINGTON, DC -The U.S. Department of Energy (DOE) today released a revised estimate of the total system life cycle cost for a repository at Yucca Mountain, Nevada. The 2007 total system life cycle cost estimate includes the cost to research, construct and operate Yucca Mountain during a period of 150 years, from the beginning of the program in 1983 through closure and decommissioning in 2133. The new cost estimate of $79.3 billion, when updated to 2007 dollars comes to $96.2 billion, a 38 percent

186

Cost estimate of electricity produced by TPV  

Science Journals Connector (OSTI)

A crucial parameter for the market penetration of TPV is its electricity production cost. In this work a detailed cost estimate is performed for a Si photocell based TPV system, which was developed for electrically self-powered operation of a domestic heating system. The results are compared to a rough estimate of cost of electricity for a projected GaSb based system. For the calculation of the price of electricity, a lifetime of 20 years, an interest rate of 4.25% per year and maintenance costs of 1% of the investment are presumed. To determine the production cost of TPV systems with a power of 12–20 kW, the costs of the TPV components and 100 EUR kW?1el,peak for assembly and miscellaneous were estimated. Alternatively, the system cost for the GaSb system was derived from the cost of the photocells and from the assumption that they account for 35% of the total system cost. The calculation was done for four different TPV scenarios which include a Si based prototype system with existing technology (?sys = 1.0%), leading to 3000 EUR kW?1el,peak, an optimized Si based system using conventional, available technology (?sys = 1.5%), leading to 900 EUR kW?1el,peak, a further improved system with future technology (?sys = 5%), leading to 340 EUR kW?1el,peak and a GaSb based system (?sys = 12.3% with recuperator), leading to 1900 EUR kW?1el,peak. Thus, prices of electricity from 6 to 25 EURcents kWh?1el (including gas of about 3.5 EURcents kWh?1) were calculated and compared with those of fuel cells (31 EURcents kWh?1) and gas engines (23 EURcents kWh?1).

Günther Palfinger; Bernd Bitnar; Wilhelm Durisch; Jean-Claude Mayor; Detlev Grützmacher; Jens Gobrecht

2003-01-01T23:59:59.000Z

187

Estimating Demand Response with Panel Data  

Science Journals Connector (OSTI)

In this paper, we extend to panel data the iterated linear least squares estimator of Blundell and Robin (in J Appl Econometrics 14: 209–232 1999). It is shown to be consistent when total expenditure and regre...

Sébastien Lecocq; Jean-Marc Robin

2006-11-01T23:59:59.000Z

188

Pricing Inflation Derivatives.  

E-Print Network (OSTI)

?? This thesis presents an overview of strategies for pricing inflation derivatives. The paper is structured as follows. Firstly, the basic definitions and concepts such… (more)

Tewolde Berhan, Damr

2012-01-01T23:59:59.000Z

189

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

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

Total Expenditures for Purchased Energy Sources by Census Region" Total Expenditures for Purchased Energy Sources by Census Region" " and Economic Characteristics of the Establishment, 1991" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

190

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"

191

ARM - Measurement - Total cloud water  

NLE Websites -- All DOE Office Websites (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

192

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

193

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

194

Derivative Usage and Performance Volatility  

Science Journals Connector (OSTI)

Derivative usage that reduces return volatility is frequently termed hedging, and derivative usage that increases return volatility is called speculation. ... reduce or increase their return volatility with deriv...

Weiying Jia; Yi Kang

2012-01-01T23:59:59.000Z

195

Further Developments in Orbit Ephemeris Derived Neutral Density  

E-Print Network (OSTI)

effect the unmodeled density variations have on orbit propagation. These results are also binned by solar and geomagnetic activity level. The primary input into the orbit determination scheme used to produce the POE derived density estimates is a...

Locke, Travis Cole

2012-12-31T23:59:59.000Z

196

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

197

Solar total energy project Shenandoah  

SciTech Connect

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

198

Grantee Total Number of Homes  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

199

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

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

6. Total Expenditures for Purchased Energy Sources by Census Region," 6. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Group and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors" ,,"Total United States"

200

Notes on Yurok Derivation  

E-Print Network (OSTI)

of root. Different finals distinguish transitive from intransitive verbs. Some are abstract, some concrete. Elements are generally joined by one of two link vowels, e and o. Yurok nouns and particles are simpler in structure, but a few derivational finals...

Proulx, Paul

1985-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "derived estimates total" 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

Estimates of Energy Consumption by Building Type and End Use at U.S. Army Installations  

E-Print Network (OSTI)

4. Figure 5-5. 1993 Electricity Consumption Estimates by EndkWh/ft ) 1993 Electricity Consumption Estimates by End Useof Total) 1993 Electricity Consumption Estimates by End Use

Konopacki, S.J.

2010-01-01T23:59:59.000Z

202

Improved diagnostic model for estimating wind energy  

SciTech Connect

Because wind data are available only at scattered locations, a quantitative method is needed to estimate the wind resource at specific sites where wind energy generation may be economically feasible. This report describes a computer model that makes such estimates. The model uses standard weather reports and terrain heights in deriving wind estimates; the method of computation has been changed from what has been used previously. The performance of the current model is compared with that of the earlier version at three sites; estimates of wind energy at four new sites are also presented.

Endlich, R.M.; Lee, J.D.

1983-03-01T23:59:59.000Z

203

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:

204

Total quality management implementation guidelines  

SciTech Connect

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

205

EPA 402-R-99-003 ESTIMATING RADIOGENIC CANCER RISKS  

E-Print Network (OSTI)

of ionizing radiation. Using this methodology, numerical estimates of the risk per unit dose were derived the Agency's methodology for deriving estimates of excess cancer morbidity and mortality due to low doses-body radiation: the low-LET nominal estimate increased from 5.1Ă?10-2 Gy-1 to 5.75Ă?10-2 Gy-1 . In this document

206

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

207

Efficiency assessment of using satellite data for crop area estimation in Ukraine  

Science Journals Connector (OSTI)

Abstract The knowledge of the crop area is a key element for the estimation of the total crop production of a country and, therefore, the management of agricultural commodities markets. Satellite data and derived products can be effectively used for stratification purposes and a-posteriori correction of area estimates from ground observations. This paper presents the main results and conclusions of the study conducted in 2010 to explore feasibility and efficiency of crop area estimation in Ukraine assisted by optical satellite remote sensing images. The study was carried out on three oblasts in Ukraine with a total area of 78,500 km2. The efficiency of using images acquired by several satellite sensors (MODIS, Landsat-5/TM, AWiFS, LISS-III, and RapidEye) combined with a field survey on a stratified sample of square segments for crop area estimation in Ukraine is assessed. The main criteria used for efficiency analysis are as follows: (i) relative efficiency that shows how much time the error of area estimates can be reduced with satellite images, and (ii) cost-efficiency that shows how much time the costs of ground surveys for crop area estimation can be reduced with satellite images. These criteria are applied to each satellite image type separately, i.e., no integration of images acquired by different sensors is made, to select the optimal dataset. The study found that only MODIS and Landsat-5/TM reached cost-efficiency thresholds while AWiFS, LISS-III, and RapidEye images, due to its high price, were not cost-efficient for crop area estimation in Ukraine at oblast level.

Francisco Javier Gallego; Nataliia Kussul; Sergii Skakun; Oleksii Kravchenko; Andrii Shelestov; Olga Kussul

2014-01-01T23:59:59.000Z

208

7 - Estimation of Radiation Doses  

Science Journals Connector (OSTI)

Abstract Radiation doses to the Japanese population from inhalation of contaminated air, external irradiation, terrestrial and marine food contamination are estimated and compared with other sources of anthropogenic (global fallout, Chernobyl accident), natural (radionuclides in food, cosmic radiation) and medical applications (X-ray tests, CT-tests, etc.) of ionizing radiation. The estimated doses from inhalation, ingestion of terrestrial and marine food, and radiation exposure from radioactive clouds and deposited radionuclides were generally below the levels which could cause health damage of the Japanese population, as well as of the world population. The estimated total radiation doses to fish and shellfish in coastal waters during the largest radionuclide releases were by a factor of 10 lower than the baseline safe level postulated for the marine organisms, therefore no harmful effects are expected for the marine ecosystem as well.

Pavel P. Povinec; Katsumi Hirose; Michio Aoyama

2013-01-01T23:59:59.000Z

209

Estimated Cost Description Determination Date:  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

and posted 2/10/2011 and posted 2/10/2011 *Title, Location Estimated Cost Description Determination Date: uncertain Transmittal to State: uncertain EA Approval: uncertain $50,000 FONSI: uncertain Determination Date: uncertain Transmittal to State: uncertain EA Approval: uncertain FONSI: uncertain Total Estimated Cost $70,000 Attachment: Memo, Moody to Marcinowski, III, SUBJECT: NEPA 2011 APS for DOE-SRS, Dated: Annual NEPA Planning Summary Environmental Assessments (EAs) Expected to be Initiated in the Next 12 Months Department of Energy (DOE) Savannah River Site (SRS) Jan-11 Estimated Schedule (**NEPA Milestones) South Carolina Department of Health and Environmental Control (SCDHEC) issued a National Pollutant Discharge Elimination System (NPDES) Industrial Stormwater General Permit (IGP) # SCR000000 November 12, with an effective date of January

210

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

211

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

212

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

213

Performance Period Total Fee Paid FY2001  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

01 01 $4,547,400 FY2002 $4,871,000 FY2003 $6,177,902 FY2004 $8,743,007 FY2005 $13,134,189 FY2006 $7,489,704 FY2007 $9,090,924 FY2008 $10,045,072 FY2009 $12,504,247 FY2010 $17,590,414 FY2011 $17,558,710 FY2012 $14,528,770 Cumulative Fee Paid $126,281,339 Cost Plus Award Fee DE-AC29-01AL66444 Washington TRU Solutions LLC Contractor: Contract Number: Contract Type: $8,743,007 Contract Period: $1,813,482,000 Fee Information Maximum Fee $131,691,744 Total Estimated Contract Cost: $4,547,400 $4,871,000 $6,177,902 October 2000 - September 2012 Minimum Fee $0 Fee Available EM Contractor Fee Site: Carlsbad Field Office - Carlsbad, NM Contract Name: Waste Isolation Pilot Plant Operations March 2013 $13,196,690 $9,262,042 $10,064,940 $14,828,770 $12,348,558 $12,204,247 $17,590,414 $17,856,774

214

Etude des flux de leucine : total, catabolisme oxydatif, synthse et catabolisme protique,  

E-Print Network (OSTI)

synthesis and protein degradation - were studied in male rats weighing 160 and 300 g and infused h of infusion. The excretion rate of 14C02was estimated during infusion. Total leucine flux

Boyer, Edmond

215

Responses of primary production and total carbon storage to changes in climate and atmospheric CO? concentration  

E-Print Network (OSTI)

The authors used the terrestrial ecosystem model (TEM, version 4.0) to estimate global responses of annual net primary production (NPP) and total carbon storage to changes in climate and atmospheric CO2, driven by the ...

Xiao, Xiangming.; Kicklighter, David W.; Melillo, Jerry M.; McGuire, A. David.; Stone, Peter H.; Sokolov, Andrei P.

216

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

217

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

218

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

219

Nickel-Catalyzed Cross-Coupling of Phenol Derivatives and Total Synthesis of Welwitindolinone Natural Products  

E-Print Network (OSTI)

heterocyclic carbene ligand IPr in toluene at 120 °C (Scheme1.52 Ni(COD) 2 (20 mol%) IPr•HCl (40 mol%) OCH 3 HNR 2 NR 2heterocyclic carbene ligand IPr, allows for the coupling of

Quasdorf, Kyle

2012-01-01T23:59:59.000Z

220

Internal Dose Estimates from  

E-Print Network (OSTI)

Appendix F Internal Dose Estimates from NTS Fallout F-1 #12;Radiation Dose to the Population;TABLE OF CONTENTS Page F- Part I. Estimates of Dose...........................................................................................40 Comparison to dose estimates from global fallout

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221

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

222

Results from Infrared Spectral Observation of 1991 Total Solar Eclipse Hui Li and Jianqi You  

E-Print Network (OSTI)

Results from Infrared Spectral Observation of 1991 Total Solar Eclipse Hui Li and Jianqi You Purple and analytical results of infrared spectra (10712°A­10972°A) observed in the total solar eclipse of 1991 July 11 in Mexico. The surface brightness curve, derived from the continua of extreme limb photosphere of flash

Li, Hui

223

Results from Infrared Spectral Observation of 1991 Total Solar Eclipse Hui Li and Jianqi You  

E-Print Network (OSTI)

Results from Infrared Spectral Observation of 1991 Total Solar Eclipse Hui Li and Jianqi You Purple and analytical results of infrared spectra (10712 š A--10972 š A) observed in the total solar eclipse of 1991 July 11 in Mexico. The surface brightness curve, derived from the continua of extreme limb photosphere

Li, Hui

224

A continuous traffic study - estimation of population parameters and the variance of the estimated parameters  

E-Print Network (OSTI)

. 32 5. 88 6. 36 1. 68 13 TABLE 3. 2 ESTIMATED TOTAL 'fONS BY CARRiER Carrier Sample Size ToGs Standard Error Coefficient Variation (/) Maximum Variation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 '7 l 22.... 37 14. 71 13. 33 12. 48 18. 62 6. 26 7. 07 l. 72 15 3. 4 Traffic Characteristics for a Group of Carri rs The estimation of totals and estimated variances for a group of carriers is merely an extension of formula 3. 1 and 3. 3. In this case...

Dresser, George Brayton

1969-01-01T23:59:59.000Z

225

County-level Estimates for Carbon Distribution in U.S. Croplands, 1990-2005 Method of Estimation  

E-Print Network (OSTI)

to estimate total above-ground biomass. Multiplying aboveground biomass with the root:shoot ratio provides an estimate of below-ground biomass. Finally, summing above- and below-ground biomass provides an estimate-carbon for U.S. crops. Crop Reporting units mass per unit (kg) Conversion to Dry matter Harvest Index Root

226

Estimated United States Transportation Energy Use 2005  

SciTech Connect

A flow chart depicting energy flow in the transportation sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 31,000 trillion British Thermal Units (trBTUs) of energy were used throughout the United States in transportation activities. Vehicles used in these activities include automobiles, motorcycles, trucks, buses, airplanes, rail, and ships. The transportation sector is powered primarily by petroleum-derived fuels (gasoline, diesel and jet fuel). Biomass-derived fuels, electricity and natural gas-derived fuels are also used. The flow patterns represent a comprehensive systems view of energy used within the transportation sector.

Smith, C A; Simon, A J; Belles, R D

2011-11-09T23:59:59.000Z

227

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

SciTech Connect

Accurate and precise population estimates of chum salmon (Oncorhynchus keta) spawning in the mainstem Columbia River are needed to provide a basis for informed water allocation decisions, to determine the status of chum salmon listed under the Endangered Species Act, and to evaluate the contribution of the Duncan Creek re-introduction program to mainstem spawners. Currently, mark-recapture experiments using the Jolly-Seber model provide the only framework for this type of estimation. In 2002, a study was initiated to estimate mainstem Columbia River chum salmon populations using seining data collected while capturing broodstock as part of the Duncan Creek re-introduction. The five assumptions of the Jolly-Seber model were examined using hypothesis testing within a statistical framework, including goodness of fit tests and secondary experiments. We used POPAN 6, an integrated computer system for the analysis of capture-recapture data, to obtain maximum likelihood estimates of standard model parameters, derived estimates, and their precision. A more parsimonious final model was selected using Akaike Information Criteria. Final chum salmon escapement estimates and (standard error) from seining data for the Ives Island, Multnomah, and I-205 sites are 3,179 (150), 1,269 (216), and 3,468 (180), respectively. The Ives Island estimate is likely lower than the total escapement because only the largest two of four spawning sites were sampled. The accuracy and precision of these estimates would improve if seining was conducted twice per week instead of weekly, and by incorporating carcass recoveries into the analysis. Population estimates derived from seining mark-recapture data were compared to those obtained using the current mainstem Columbia River salmon escapement methodologies. The Jolly-Seber population estimate from carcass tagging in the Ives Island area was 4,232 adults with a standard error of 79. This population estimate appears reasonable and precise but batch marks and lack of secondary studies made it difficult to test Jolly-Seber assumptions, necessary for unbiased estimates. We recommend that individual tags be applied to carcasses to provide a statistical basis for goodness of fit tests and ultimately model selection. Secondary or double marks should be applied to assess tag loss and male and female chum salmon carcasses should be enumerated separately. Carcass tagging population estimates at the two other sites were biased low due to limited sampling. The Area-Under-the-Curve escapement estimates at all three sites were 36% to 76% of Jolly-Seber estimates. Area-Under-the Curve estimates are likely biased low because previous assumptions that observer efficiency is 100% and residence time is 10 days proved incorrect. If managers continue to rely on Area-Under-the-Curve to estimate mainstem Columbia River spawners, a methodology is provided to develop annual estimates of observer efficiency and residence time, and to incorporate uncertainty into the Area-Under-the-Curve escapement estimate.

Rawding, Dan; Hillson, Todd D. (Washington Department of Fish and Wildlife, Olympia, WA)

2003-11-15T23:59:59.000Z

228

Derived Concentration Technical Standard  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

196-2011 196-2011 April 2011 DOE STANDARD DERIVED CONCENTRATION TECHNICAL STANDARD U.S. Department of Energy AREA ENVR Washington, D.C. 20585 Not Measurement Sensitive This document is available on the Department of Energy Technical Standards Program Web Site at http://www.hss.doe.gov/nuclearsafety/ns/techstds/standard/standard.html DOE-STD-1196-2011 ACKNOWLEDGEMENTS This Derived Concentration Technical Standard was a collaborative effort sponsored by the DOE Office of Environmental Policy and Assistance, with support from Department subject matter experts (SMEs) in the field of radiation protection. This standard, which complements DOE Order (O) 458.1, Radiation Protection of the Public and the Environment, was developed taking

229

The MIRD method of estimating absorbed dose  

SciTech Connect

The estimate of absorbed radiation dose from internal emitters provides the information required to assess the radiation risk associated with the administration of radiopharmaceuticals for medical applications. The MIRD (Medical Internal Radiation Dose) system of dose calculation provides a systematic approach to combining the biologic distribution data and clearance data of radiopharmaceuticals and the physical properties of radionuclides to obtain dose estimates. This tutorial presents a review of the MIRD schema, the derivation of the equations used to calculate absorbed dose, and shows how the MIRD schema can be applied to estimate dose from radiopharmaceuticals used in nuclear medicine.

Weber, D.A.

1991-01-01T23:59:59.000Z

230

A priori estimates for relativistic liquid bodies  

E-Print Network (OSTI)

We demonstrate that a sufficiently smooth solution of the relativistic Euler equations that represents a dynamical compact liquid body, when expressed in Lagrangian coordinates, determines a solution to a system of non-linear wave equations with acoustic boundary conditions. Using this wave formulation, we prove that these solutions satisfy energy estimates without loss of derivatives. Importantly, our wave formulation does not require the liquid to be irrotational, and the energy estimates do not rely on divergence and curl type estimates employed in previous works.

Oliynyk, Todd A

2015-01-01T23:59:59.000Z

231

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...

232

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

233

Cost Estimation Package  

Directives, Delegations, and Requirements

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

1997-03-28T23:59:59.000Z

234

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

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

7. Total Expenditures for Purchased Energy Sources by Census Region," 7. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

235

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

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

4. Total First Use (formerly Primary Consumption) of Energy for All Purposes" 4. Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row"," "," "," ",," "," "," "," " "Code(a)","Industry Group and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"," "," "," "," "," "," "," "," ",," "

236

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

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Enclosed Floorspace, Percent Conditioned Floorspace, and Presence of Computer" " Controls for Building Environment, 1991" " (Estimates in Trillion Btu)" ,,"Presence of Computer Controls" ,," for Buildings Environment",,"RSE" "Enclosed Floorspace and"," ","--------------","--------------","Row" "Percent Conditioned Floorspace","Total","Present","Not Present","Factors" " "," " "RSE Column Factors:",0.8,1.3,0.9 "ALL SQUARE FEET CATEGORIES" "Approximate Conditioned Floorspace"

237

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

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

0. Total Primary Consumption of Energy for All Purposes by Value of" 0. Total Primary Consumption of Energy for All Purposes by Value of" "Shipment Categories, Industry Group, and Selected Industries, 1991" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," ","(million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," "," ",500,"Row"," "," "," ",," "," "," "," " "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"," "," "," "," "," "," "," "," ",," "

238

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

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

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

239

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

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1991" " (Continued)" " (Estimates in Trillion Btu)",,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"

240

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

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

Components of Total Electricity Demand by Census Region and" Components of Total Electricity Demand by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,1.4,1.3,1.9,0.5 "Value of Shipments and Receipts" "(million dollars)"

Note: This page contains sample records for the topic "derived estimates total" 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

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

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

1. Total Primary Consumption of Combustible Energy for Nonfuel" 1. Total Primary Consumption of Combustible Energy for Nonfuel" " Purposes by Census Region and Economic Characteristics of the Establishment," 1991 " (Estimates in Btu or Physical Units)" " "," "," "," ","Natural"," "," ","Coke"," "," " " ","Total","Residual","Distillate","Gas(c)"," ","Coal","and Breeze","Other(d)","RSE" " ","(trillion","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000","(1000","(trillion","Row"

242

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

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

6. Components of Total Electricity Demand by Census Region, Industry" 6. Components of Total Electricity Demand by Census Region, Industry" " Group, and Selected Industries, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total Onsite","Transfers","Net Demand for","Row" "Code(a)","Industry Groups and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)","Factors"

243

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

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

Components of Total Electricity Demand by Census Region, Census Division, and" Components of Total Electricity Demand by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,2.1,1.2,2,0.4 "Value of Shipments and Receipts"

244

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

245

RESPONSES OF PRIMARY PRODUCTION AND TOTAL CARBON STORAGE TO CHANGES IN CLIMATE AND ATMOSPHERIC CO2 CONCENTRATION  

E-Print Network (OSTI)

Model (TEM, version 4.0) to estimate global responses of annual net primary production (NPP) and total. For contemporary climate with 315 ppmv CO2, TEM estimated that global NPP is 47.9 PgC/yr and global total carbon-q climate and +20.6% (9.9 PgC/yr) for the GISS climate. The responses of global total carbon storage are +17

246

Check Estimates and Independent Costs  

Directives, Delegations, and Requirements

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

1997-03-28T23:59:59.000Z

247

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

248

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

249

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

250

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

251

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

252

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

253

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

254

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

255

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

256

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

257

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

258

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

259

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

260

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

Note: This page contains sample records for the topic "derived estimates total" 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

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

262

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

263

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

264

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

265

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

266

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

267

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

268

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

269

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.

270

TotalView Parallel Debugger at NERSC  

NLE Websites -- All DOE Office Websites (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

271

A Priori Error Estimates for Some Discontinuous Galerkin Immersed ...  

E-Print Network (OSTI)

estimate in a mesh-dependant energy norm is derived, and this error ... 0 (Th), integrate both sides on each element K ? Th, and apply the Green's formula to.

2015-01-12T23:59:59.000Z

272

Annual and Seasonal Global Variation in Total Ozone and Layer-Mean Ozone,  

NLE Websites -- All DOE Office Websites (Extended Search)

Atmospheric Trace Gases » Ozone » Total Ozone and Layer-Mean Ozone Atmospheric Trace Gases » Ozone » Total Ozone and Layer-Mean Ozone Annual and Seasonal Global Variation in Total Ozone and Layer-Mean Ozone, 1958-1987 (1991) DOI: 10.3334/CDIAC/atg.ndp023 data Data Investigators J. K. Angell, J. Korshover, and W. G. Planet Description For 1958 through 1987, this data base presents total ozone variations and layer mean ozone variations expressed as percent deviations from the 1958 to 1977 mean. The total ozone variations were derived from mean monthly ozone values published in Ozone Data for the World by the Atmospheric Environment Service in cooperation with the World Meteorological Organization. The layer mean ozone variations are derived from ozonesonde and Umkehr observations. The data records include year, seasonal and annual

273

Estimation of Density of Biodiesel  

Science Journals Connector (OSTI)

In addition, the numeric value for coefficient e is very small (?0.00001) and the nd(ave) of most biodiesels are not greater than 2. Therefore, the product of e × nd(ave) can be neglected without affecting the accuracy of the calculation and eq 30 is good for estimation of density of biodiesel. ... Interestingly, the %AAD for mixed biodiesel (0.38) is lower than those of pure (0.41%) and total biodiesels. ... (21) The model cannot differentiate a mixed biodiesel from pure biodiesels. ...

Suriya Phankosol; Kaokanya Sudaprasert; Supathra Lilitchan; Kornkanok Aryusuk; Kanit Krisnangkura

2014-06-16T23:59:59.000Z

274

Is newer better? Penn World Table Revisions and their impact on growth estimates  

E-Print Network (OSTI)

This paper sheds light on two problems in the Penn World Table (PWT) GDP estimates. First, we show that these estimates vary substantially across different versions of the PWT despite being derived from very similar ...

Johnson, Simon

275

Program Potential: Estimates of Federal Energy Cost Savings from Energy Efficient Procurement  

E-Print Network (OSTI)

24   Energy and Costsavings in Table 7: Annual energy and cost savings of waterwere used to derive energy and cost savings estimates:

Taylor, Margaret

2014-01-01T23:59:59.000Z

276

Cost Analysis of Bio-Derived Liquids Reforming (Presentation)  

NLE Websites -- All DOE Office Websites (Extended Search)

Analysis of Analysis of Bio-Derived Liquids Reforming Brian James Directed Technologies, Inc. 6 November 2007 This presentation does not contain any proprietary, confidential, or otherwise restricted information Objective * Assess cost of H 2 from bio-derived liquids * Looking at forecourt scale systems: 100-1500kg/day * Emphasis on Ethanol * Looking at both "conventional" and "advanced" systems * Interaction with the Researchers is bi-directional * Researchers help me with catalysts, performance, configurations * I can assist Researchers with system studies, configurations, and system performance estimates * Output of my work will be: * System/Configuration Definition * Performance specification & optimization * Capital cost estimation

277

The energy spectrum of cosmic rays above 10^15 eV as derived from air Cherenkov light measurements in Yakutsk  

E-Print Network (OSTI)

The Yakutsk array observes the Cherenkov light emitted by UHECR in atmosphere. Recently, an autonomous subarray is added consisting of photomultipliers to measure the showers in the knee region. Our aim is to analyze the combined data set in order to derive the cosmic ray spectrum in the energy range as wide as possible using the same technique. The advantage of the air Cherenkov light measurement is the model independent estimation of the EAS primary energy using the total light flux emitted in the atmosphere. A set of the light lateral distributions observed in the extended energy range is presented also.

A. A. Ivanov; S. P. Knurenko; I. Ye. Sleptsov

2003-05-05T23:59:59.000Z

278

ARM - Measurement - Shortwave broadband total net irradiance  

NLE Websites -- All DOE Office Websites (Extended Search)

Range Weather Forecasts Diagnostic Analyses ECMWF : European Centre for Medium Range Weather Forecasts Model Data Value-Added Products ARMBE : ARM Best Estimate Data Products...

279

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

FY 2007 Total System Life Cycle Cost, Pub 2008 FY 2007 Total System Life Cycle Cost, Pub 2008 FY 2007 Total System Life Cycle Cost, Pub 2008 The Analysis of the Total System Life Cycle Cost (TSLCC) of the Civilian Radioactive Waste Management Program presents the Office of Civilian Radioactive Waste Management's (OCRWM) May 2007 total system cost estimate for the disposal of the Nation's spent nuclear fuel (SNF) and high-level radioactive waste (HLW). The TSLCC analysis provides a basis for assessing the adequacy of the Nuclear Waste Fund (NWF) Fee as required by Section 302 of the Nuclear Waste Policy Act of 1982 (NWPA), as amended. In addition, the TSLCC analysis provides a basis for the calculation of the Government's share of disposal costs for government-owned and managed SNF and HLW. The TSLCC estimate includes both historical costs and

280

Estimating the Burden of Neurocysticercosis in Mexico  

E-Print Network (OSTI)

region (p< 0.05). The mean total number of DALYs lost due to NCC in Mexico was estimated to be 99,866 (95 percent CR: 43,187 –189,182), with a mean of 0.95 (95 percent CR: 0.4–1.8) DALYs lost per thousand persons per year....

Bhattarai, Rachana

2012-10-19T23:59:59.000Z

Note: This page contains sample records for the topic "derived estimates total" 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

Radiation Dose Estimates from  

E-Print Network (OSTI)

Summary: Radiation Dose Estimates from Hanford Radioactive Material Releases to the Air- tantly, what radiation dose people may have received. An independent Technical Steering Panel (TSP, additionalProjectworkcouldresultin revisions of these dose estimates. April 21, 1994 Companion

282

State Energy Production Estimates  

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

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

283

VIMOS total transmission profiles for broad-band filters  

E-Print Network (OSTI)

VIMOS is a wide-field imager and spectrograph mounted on UT3 at the VLT, whose FOV consists of four 7'x8' quadrants. Here we present the measurements of total transmission profiles -- i.e. the throughput of telescope + instrument -- for the broad band filters U, B, V, R, I, and z for each of its four quadrants. Those measurements can also be downloaded from the public VIMOS web-page. The transmission profiles are compared with previous estimates from the VIMOS consortium.

S. Mieske; M. Rejkuba; S. Bagnulo; C. Izzo; G. Marconi

2007-04-13T23:59:59.000Z

284

Types of Cost Estimates  

Directives, Delegations, and Requirements

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

1997-03-28T23:59:59.000Z

285

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

286

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

287

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

288

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

289

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

290

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

291

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

292

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

293

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

294

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

295

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

296

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

297

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

298

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

299

ARM - Measurement - Shortwave spectral total downwelling irradiance  

NLE Websites -- All DOE Office Websites (Extended Search)

Shadowband Spectroradiometer SPEC-TOTDN : Shortwave Total Downwelling Spectrometer UAV-EGRETT : UAV-Egrett Value-Added Products VISST : Minnis Cloud Products Using Visst...

300

,"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"...

Note: This page contains sample records for the topic "derived estimates total" 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

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 &...

302

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...

303

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

304

External Dose Estimates from  

E-Print Network (OSTI)

Appendix G External Dose Estimates from Global Fallout G-1 #12;External Radiation Exposure-MQ-003539 March 15, 2000 G-2 #12;Abstract This report provides estimates of the external radiation-62. Estimates are given on a county by county basis for each month from 1953-1972. The average population dose

305

External Dose Estimates from  

E-Print Network (OSTI)

Appendix E External Dose Estimates from NTS Fallout E-1 #12;External Radiation Exposure. 1, 1999) E-2 #12;Abstract This report provides estimates of the external radiation exposure of this report to: "Prepare crude estimates of the doses from external irradiation received by the American

306

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

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

4. Total Expenditures for Purchased Energy Sources by Census Region," 4. Total Expenditures for Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Groupsc and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors" ,,"Total United States" ,"RSE Column Factors:","0.6 ",0.6,1.3,1.3,0.7,1.2,1.2,1.5,1.1

307

Derivation Tree Based Genetic Programming  

E-Print Network (OSTI)

Derivation Tree Based Genetic Programming Summary of the Ph.D. Thesis by R´obert V´anyi supervisor presented in the Ph.D. thesis enti- tled Derivation Tree Based Genetic Programming. The thesis describes of the generated candidates. [6] 1.2 Proposed method The method presented in the thesis uses derivation trees

Fernandez, Thomas

308

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

309

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

310

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

E-Print Network (OSTI)

water heating Technologies Electric heater Gas boilerCoal Boiler Small cogen Stove District heating Heat pumpElectric water heater Gas boiler Coal Boiler Small cogen Oil

Fridley, David G.

2008-01-01T23:59:59.000Z

311

Estimation of body composition in channel catfish utilizing relative weight and total body electrical conductivity  

E-Print Network (OSTI)

, Fish, and Parks; South Dakota State University; Tennessee Valley Authority; Texas Parks and Wildlife Department; and Department of Recreation, Fish and Game of Quebec. Last and most importantly, I would like to thank Jesus Christ for always being..., Fish, and Parks; South Dakota State University; Tennessee Valley Authority; Texas Parks and Wildlife Department; and Department of Recreation, Fish and Game of Quebec. Last and most importantly, I would like to thank Jesus Christ for always being...

Jaramillo, Francisco

2012-06-07T23:59:59.000Z

312

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

E-Print Network (OSTI)

Small cogen Stove District heating Heat pump Central AC Roomin heat delivery (district heating), heat management (poorInstalled Capacity) District Heating Boiler Gas Boiler Small

Fridley, David G.

2008-01-01T23:59:59.000Z

313

Summary We estimated total ecosystem respiration from a ponderosa pine (Pinus ponderosa Dougl. ex Laws.) plantation  

E-Print Network (OSTI)

Forest ecosystems are important in global carbon cycling be- cause 80% of the carbon stored in terrestrial vegetation is for- est biomass and forest soil contains more than 70% of the world's soil carbon- aged not only for timber and non-timber products, but also for CO2 sequestration. Therefore, ecosystem

Cohen, Ronald C.

314

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

E-Print Network (OSTI)

rate of technology penetration and rate of intensity change,energy. In addition, the penetration rate of each end-use isinstalled base (i.e. penetration rate) for each end-use set

Fridley, David G.

2008-01-01T23:59:59.000Z

315

Oklahoma's Native Languages with Total Population c. 1993 and Estimated Numbers of Speakers c. 2004  

E-Print Network (OSTI)

,927) 0 0 5 1(?) 24 0 Tonkawan Tonkawa (186) 0 Iroquoian Cherokee (122,000) Keetoowah Band Cherokee (7,450) Wyandotte (3,617) Seneca-Cayuga# (2,460) 9,000 (w/Cherokee) 0 0 Uto-Aztecan Comanche (8,500) Uchean Euchee

Oklahoma, University of

316

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

E-Print Network (OSTI)

material intensity, energy intensity of materials, buildingtype’s manufacturing energy intensity (how much energy itthe manufacturing energy intensity of each type of building

Fridley, David G.

2008-01-01T23:59:59.000Z

317

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

E-Print Network (OSTI)

of energy consumed from coal, coke, liquid fuels, naturalwas expressed in terms of coal equivalency. 2.1.8.1 Tnational fuel inputs of coal, natural gas and petroleum were

Fridley, David G.

2008-01-01T23:59:59.000Z

318

Cost Estimating Handbook for Environmental Restoration  

SciTech Connect

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

NONE

1990-09-01T23:59:59.000Z

319

PSERC 98-21 "Analytic and Experimentally-Derived  

E-Print Network (OSTI)

-regulated retail energy pricing until a single supplier does not dominate initial market shares, it is morePSERC 98-21 "Analytic and Experimentally-Derived Estimates of Market Power in Deregulated and Permissions/IEEE Service Center/445 Hoes Lane/P.O. Box 1331/Piscataway, NJ 08855-1331, USA. Telephone: + Intl

320

Part cost estimation at early design phase  

Science Journals Connector (OSTI)

Abstract Although 70% of part cost is determined during the early design stage, designers rarely accurately estimate the costs of their designs. Based on extensive literature review, in-depth industrial survey and close collaboration with multiple manufacturers, forty factors were identified as governing part cost and ranked according to cost impact. Based on parameter ranking and availability at the early stages of design, a cost estimator for designers is proposed. As the design progresses and more parameters become available, a more accurate cost model is derived and proposed to manufacturers. Results are analyzed and compared to actual manufacturing costing demonstrating good fit.

Gila Molcho; Asher Cristal; Moshe Shpitalni

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "derived estimates total" 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

Estimates of US biofuels consumption, 1990  

SciTech Connect

This report is the sixth in the series of publications developed by the Energy Information Administration to quantify the amount of biofuel-derived primary energy used by the US economy. It provides preliminary estimates of 1990 US biofuels energy consumption by sector and by biofuels energy resource type. The objective of this report is to provide updated annual estimates of biofuels energy consumption for use by congress, federal and state agencies, and other groups involved in activities related to the use of biofuels. 5 figs., 10 tabs.

Not Available

1991-10-01T23:59:59.000Z

322

Total integrals of global solutions to Painleve II  

E-Print Network (OSTI)

We evaluate the total integral from negative infinity to positive infinity of all global solutions to the Painleve II equation on the real line. The method is based on the interplay between one of the equations of the associated Lax pair and the corresponding Riemann-Hilbert problem. In addition, we evaluate the total integral of a function related to a special solution to the Painleve V equation. As a corollary, we obtain short proofs of the computation of the constant terms of the limiting gap probabilities in the edge and the bulk of the Gaussian Orthogonal and Gaussian Symplectic Ensembles that were obtained recently in [4] and [18]. We also evaluate the total integrals of certain polynomials of the Painleve functions and their derivatives. These polynomials are the densities of the first integrals of the modified Korteweg-de Vries equation. We discuss the relations of the formulae we have obtained to the classical trace formulae for the Dirac operator on the line.

Jinho Baik; Robert Buckingham; Jeffery DiFranco; Alexander Its

2008-10-15T23:59:59.000Z

323

Prediction of the Proton-to-Total Turbulent Heating in the Solar Wind  

E-Print Network (OSTI)

This paper employs a recent turbulent heating prescription to predict the ratio of proton-to-total heating due to the kinetic dissipation of Alfvenic turbulence as a function of heliocentric distance. Comparing to a recent empirical estimate for this turbulent heating ratio in the high-speed solar wind, the prediction shows good agreement with the empirical estimate for R >~ 0.8 AU, but predicts less ion heating than the empirical estimate at smaller heliocentric radii. At these smaller radii, the turbulent heating prescription, calculated in the gyrokinetic limit, fails because the turbulent cascade is predicted to reach the proton cyclotron frequency before Landau damping terminates the cascade. These findings suggest that the turbulent cascade can reach the proton cyclotron frequency at R ~ 0.8 AU, this turbulent heating prescription contains all of the necessary physical mechanisms needed to reproduce the empirically estimated proton-to-total heating ratio.

Howes, G G

2011-01-01T23:59:59.000Z

324

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

325

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

326

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

327

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

328

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

329

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

330

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

331

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

332

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

333

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

334

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

335

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

336

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

337

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

338

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

339

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

340

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

Note: This page contains sample records for the topic "derived estimates total" 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

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

342

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

343

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

344

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

345

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

346

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

347

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

348

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

349

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

350

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

351

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

352

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

353

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

354

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

355

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

356

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Pennsylvania - 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 S40. Summary statistics for natural gas - Pennsylvania, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 52,700 55,631 57,356 44,500 54,347 Production (million cubic feet) Gross Withdrawals From Gas Wells 182,277 R 188,538 R 184,795 R 173,450 242,305 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0

357

Total synthesis and study of myrmicarin alkaloids  

E-Print Network (OSTI)

I. Enantioselective Total Synthesis of Tricyclic Myrmicarin Alkaloids An enantioselective gram-scale synthesis of a key dihydroindolizine intermediate for the preparation of myrmicarin alkaloids is described. Key transformations ...

Ondrus, Alison Evelynn, 1981-

2009-01-01T23:59:59.000Z

358

Total synthesis of cyclotryptamine and diketopiperazine alkaloids  

E-Print Network (OSTI)

I. Total Synthesis of the (+)-12,12'-Dideoxyverticillin A The fungal metabolite (+)-12,12'-dideoxyverticillin A, a cytotoxic alkaloid isolated from a marine Penicillium sp., belongs to a fascinating family of densely ...

Kim, Justin, Ph. D. Massachusetts Institute of Technology

2013-01-01T23:59:59.000Z

359

Provides Total Tuition Charge to Source Contribution  

E-Print Network (OSTI)

,262 1,938 TGR 4-20 0-3 2,871 2,871 - % of time appointed Hours of Work/Week Units TAL Provides Total

Kay, Mark A.

360

Enantioselective Total Synthesis of (?)-Acylfulvene and (?)- Irofulven  

E-Print Network (OSTI)

We report our full account of the enantioselective total synthesis of (?)-acylfulvene (1) and (?)-irofulven (2), which features metathesis reactions for the rapid assembly of the molecular framework of these antitumor ...

Movassaghi, Mohammad

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361

A GENUINELY HIGH ORDER TOTAL VARIATION DIMINISHING ...  

E-Print Network (OSTI)

(TVD) schemes solving one-dimensional scalar conservation laws degenerate to first order .... where the total variation is measured by the standard bounded variation ..... interval Ij and into the jump discontinuities at cell interfaces, see [12].

362

Million Cu. Feet Percent of National Total  

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

8 8 Texas - 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 S45. Summary statistics for natural gas - Texas, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 87,556 93,507 95,014 100,966 96,617 Production (million cubic feet) Gross Withdrawals From Gas Wells 5,285,458 4,860,377 4,441,188 3,794,952 3,619,901 From Oil Wells 745,587 774,821 849,560 1,073,301 860,675

363

Million Cu. Feet Percent of National Total  

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

0 0 Alabama - 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 S1. Summary statistics for natural gas - Alabama, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,860 6,913 7,026 7,063 6,327 Production (million cubic feet) Gross Withdrawals From Gas Wells 158,964 142,509 131,448 116,872 114,407 From Oil Wells 6,368 5,758 6,195 5,975 10,978

364

Million Cu. Feet Percent of National Total  

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

8 8 Louisiana - 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 S20. Summary statistics for natural gas - Louisiana, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 19,213 18,860 19,137 21,235 19,792 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,288,559 1,100,007 911,967 883,712 775,506 From Oil Wells 61,663 58,037 63,638 68,505 49,380

365

Million Cu. Feet Percent of National Total  

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

4 4 South 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 S43. Summary statistics for natural gas - South Dakota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 71 89 102 100 95 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,098 1,561 1,300 933 14,396 From Oil Wells 10,909 11,366 11,240 11,516 689 From Coalbed Wells 0 0 0 0 0

366

Million Cu. Feet Percent of National Total  

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

4 4 Kansas - 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 S18. Summary statistics for natural gas - Kansas, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 17,862 21,243 22,145 25,758 24,697 Production (million cubic feet) Gross Withdrawals From Gas Wells 286,210 269,086 247,651 236,834 264,610 From Oil Wells 45,038 42,647 39,071 37,194 0 From Coalbed Wells 44,066

367

Million Cu. Feet Percent of National Total  

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

6 6 Arkansas - 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 S4. Summary statistics for natural gas - Arkansas, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 5,592 6,314 7,397 8,388 8,538 Production (million cubic feet) Gross Withdrawals From Gas Wells 173,975 164,316 152,108 132,230 121,684 From Oil Wells 7,378 5,743 5,691 9,291 3,000

368

Million Cu. Feet Percent of National Total  

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

8 8 California - 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 S5. Summary statistics for natural gas - California, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 1,645 1,643 1,580 1,308 1,423 Production (million cubic feet) Gross Withdrawals From Gas Wells 91,460 82,288 73,017 63,902 120,579 From Oil Wells 122,345 121,949 151,369 120,880 70,900

369

Million Cu. Feet Percent of National Total  

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

4 4 Oklahoma - 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 S38. Summary statistics for natural gas - Oklahoma, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 41,921 43,600 44,000 41,238 40,000 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,452,148 1,413,759 1,140,111 1,281,794 1,394,859 From Oil Wells 153,227 92,467 210,492 104,703 53,720

370

Million Cu. Feet Percent of National Total  

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

2 2 Alaska - 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 S2. Summary statistics for natural gas - Alaska, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 261 261 269 277 185 Production (million cubic feet) Gross Withdrawals From Gas Wells 150,483 137,639 127,417 112,268 107,873 From Oil Wells 3,265,401 3,174,747 3,069,683 3,050,654 3,056,918

371

A METHOD FOR ESTIMATING GAS PRESSURE IN 3013 CONTAINERS USING AN ISP DATABASE QUERY  

SciTech Connect

The U.S. Department of Energy's Integrated Surveillance Program (ISP) is responsible for the storage and surveillance of plutonium-bearing material. During storage, plutonium-bearing material has the potential to generate hydrogen gas from the radiolysis of adsorbed water. The generation of hydrogen gas is a safety concern, especially when a container is breached within a glove box during destructive evaluation. To address this issue, the DOE established a standard (DOE, 2004) that sets the criteria for the stabilization and packaging of material for up to 50 years. The DOE has now packaged most of its excess plutonium for long-term storage in compliance with this standard. As part of this process, it is desirable to know within reasonable certainty the total maximum pressure of hydrogen and other gases within the 3013 container if safety issues and compliance with the DOE standards are to be attained. The principal goal of this investigation is to document the method and query used to estimate total (i.e. hydrogen and other gases) gas pressure within a 3013 container based on the material properties and estimated moisture content contained in the ISP database. Initial attempts to estimate hydrogen gas pressure in 3013 containers was based on G-values (hydrogen gas generation per energy input) derived from small scale samples. These maximum G-values were used to calculate worst case pressures based on container material weight, assay, wattage, moisture content, container age, and container volume. This paper documents a revised hydrogen pressure calculation that incorporates new surveillance results and includes a component for gases other than hydrogen. The calculation is produced by executing a query of the ISP database. An example of manual mathematical computations from the pressure equation is compared and evaluated with results from the query. Based on the destructive evaluation of 17 containers, the estimated mean absolute pressure was significantly higher (P<.01) than the mean GEST pressure. There was no significant difference (P>.10) between the mean pressures from DR and the calculation. The mean predicted absolute pressure was consistently higher than GEST by an average difference of 57 kPa (8 psi). The mean difference between the estimated pressure and digital radiography was 11 kPa (2 psi). Based on the initial results of destructive evaluation, the pressure query was found to provide a reasonably conservative estimate of the total pressure in 3013 containers whose material contained minimal moisture content.

Friday, G; L. G. Peppers, L; D. K. Veirs, D

2008-07-31T23:59:59.000Z

372

Stationary IPA Estimates for Non-Smooth G/G/1/ Functionals via Palm Inversion and  

E-Print Network (OSTI)

Stationary IPA Estimates for Non-Smooth G/G/1/ Functionals via Palm Inversion and Level, the derivative of J with respect to . To this end, we use Infinitesimal Perturbation Analysis (IPA), a method on IPA. Alternative methods have been used to estimate derivatives, namely Smooth Perturbation Analysis

Paris-Sud XI, Université de

373

A steady-state measurement system for total hemispherical emissivity  

Science Journals Connector (OSTI)

A steady-state calorimetric technique was developed for measuring the total hemispherical emissivity of a conductive material. The system uses a thin strip of the conductive sample electrically heated by alternating current to high temperatures in a vacuum chamber. The emissivity was measured in a central region of the sample with an approximately uniform temperature distribution. Considering the influences of the gray body assumption, wire heat losses, effects of residual gas and conductive heat loss from the region to the rest of the strip, the emissivity was accurately determined by solving the inverse one-dimension steady-state heat transfer problem. The emissivities of various metal samples (nickel and 45# steel) were measured to verify the system accuracy. And the results were then analyzed to estimate the relative errors of emissivity arising from the gray body assumption, wire heat losses, effects of residual gas, non-uniform temperature distribution and the measurement uncertainty of emissivity. In the temperature range from 700 to 1300 K, the accuracy is acceptable for practical applications within the total measurement uncertainties of 1.1%. To increase the system applicability, some issues related to sample specifications, heating power control and temperature uniformity of sample test section were discussed. Thus, this system can provide accurate measurements of the total hemispherical emissivity of conductive samples at high temperatures.

Tairan Fu; Peng Tan; Chuanhe Pang

2012-01-01T23:59:59.000Z

374

Wind derivatives: hedging wind risk:.  

E-Print Network (OSTI)

??Wind derivatives are financial contracts that can be used to hedge or mitigate wind risk. In this thesis, the focus was on pricing these wind… (more)

Hoyer, S.A.

2013-01-01T23:59:59.000Z

375

| Los Alamos National Laboratory | Total Scattering Developments forTotal Scattering Developments for  

E-Print Network (OSTI)

Laboratory | Total Scattering at the Lujan Center Neutron Powder Diffractometer (NPDF) High-Intensity Powder. Shoemaker, et al., Reverse Monte Carlo neutron scattering study of disordered crystalline materials neutron| Los Alamos National Laboratory | Total Scattering Developments forTotal Scattering Developments

Magee, Joseph W.

376

Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

1" 1" " (Estimates in Btu or Physical Units)" ,,,,"Distillate",,,"Coal" ,,,,"Fuel Oil",,,"(excluding" ,,"Net","Residual","and Diesel",,,"Coal Coke",,"RSE" ,"Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","and Breeze)","Other(d)","Row" "End-Use Categories","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","(billion cu ft)","(1000 bbls)","(1000 short tons)","(trillion Btu)","Factors" ,,,,,,,,,,, ,"Total United States"

377

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

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

: Total natural gas proved reserves, reserves changes, and production, wet after lease separation, 2011" : Total natural gas proved reserves, reserves changes, and production, wet after lease separation, 2011" "billion cubic feet" ,,"Changes in reserves during 2011" ,"Published",,,,,,,,"New Reservoir" ,"Proved",,"Revision","Revision",,,,"New Field","Discoveries","Estimated","Proved" ,"Reserves","Adjustments","Increases","Decreases","Sales","Acquisitions","Extensions","Discoveries","in Old Fields","Production","Reserves" "State and subdivision",40543,"(+,-)","(+)","(-)","(-)","(+)","(+)","(+)","(+)","(-)",40908

378

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

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

6. Total Expenditures for Purchased Electricity, Steam, and Natural" 6. Total Expenditures for Purchased Electricity, Steam, and Natural" " Gas by Type of Supplier, Census Region, Industry Group, and Selected Industries," 1991 " (Estimates in Million Dollars)" ,," Electricity",," Steam",," Natural Gas" ,,"-","-----------","-","-----------","-","------------","-","RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Utility","Transmission","Other","Row" "Code(a)","Industry Groups and Industry","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors"

379

"Table A48. Total Expenditures for Purchased Electricity, Steam, and Natural"  

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

8. Total Expenditures for Purchased Electricity, Steam, and Natural" 8. Total Expenditures for Purchased Electricity, Steam, and Natural" " Gas by Type of Supplier, Census Region, and Economic Characteristics of the" " Establishment, 1991" " (Estimates in Million Dollars)" ," Electricity",," Steam",," Natural Gas" ,"-","-----------","-","-----------","-","------------","-----------","RSE" " ","Utility","Nonutility","Utility","Nonutility","Utility","Transmission","Other","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors"," "

380

Introduction Estimation paramtrique (exemples)  

E-Print Network (OSTI)

Introduction Estimation paramétrique (exemples) FARMAN : Laboratoire SATIE Jean-Pierre Barbot J.P. Barbot Séminaires FARMAN (Traitement du Signal) - 1/36 #12;Introduction Estimation paramétrique (exemples de paramètres de synchronisation (VDSL 2) J.P. Barbot Séminaires FARMAN (Traitement du Signal) - 2

Note: This page contains sample records for the topic "derived estimates total" 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

Internal Dose Estimates from  

E-Print Network (OSTI)

Appendix H Internal Dose Estimates from Global Fallout H-1 #12;Radiation Dose to the Population. 263-MQ-008090 September 30, 2000 H-2 #12;Radiation Dose to the Population of the Continental United Site Part I. Estimates of Dose Lynn R. Anspaugh Lynn R. Anspaugh, Consulting Salt Lake City, UT Report

382

Estimating Specialty Costs  

Directives, Delegations, and Requirements

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

1997-03-28T23:59:59.000Z

383

ON THE RELIABILITY OF POLARIZATION ESTIMATION USING ROTATION MEASURE SYNTHESIS  

SciTech Connect

We benchmark the reliability of the rotation measure (RM) synthesis algorithm using the 1005 Centaurus A field sources of Feain et al. The RM synthesis solutions are compared with estimates of the polarization parameters using traditional methods. This analysis provides verification of the reliability of RM synthesis estimates. We show that estimates of the polarization parameters can be made at lower signal-to-noise ratio (S/N) if the range of RMs is bounded, but reliable estimates of individual sources with unusual RMs require unconstrained solutions and higher S/N. We derive from first principles the statistical properties of the polarization amplitude associated with RM synthesis in the presence of noise. The amplitude distribution depends explicitly on the amplitude of the underlying (intrinsic) polarization signal. Hence, it is necessary to model the underlying polarization signal distribution in order to estimate the reliability and errors in polarization parameter estimates. We introduce a Bayesian method to derive the distribution of intrinsic amplitudes based on the distribution of measured amplitudes. The theoretically derived distribution is compared with the empirical data to provide quantitative estimates of the probability that an RM synthesis solution is correct as a function of S/N. We provide quantitative estimates of the probability that any given RM synthesis solution is correct as a function of measured polarized amplitude and the intrinsic polarization amplitude compared to the noise.

Macquart, J.-P.; Ekers, R. D. [ICRAR/Curtin University of Technology, Bentley, WA 6845 (Australia); Feain, I. [CSIRO Astronomy and Space Science, P.O. Box 76, Epping, NSW 1710 (Australia); Johnston-Hollitt, M., E-mail: J.Macquart@curtin.edu.au [School of Chemical and Physical Sciences, Victoria University of Wellington, P.O. Box 600, Wellington 6140 (New Zealand)

2012-05-10T23:59:59.000Z

384

Total elastic-scattering cross sections for metastable Ar on Kr  

Science Journals Connector (OSTI)

Velocity-dependent total elastic-scattering cross sections are measured for metastable argon scattered from krypton in the velocity range 500 to 5000 m/sec. An interaction potential for the reaction is derived from the data by both a semiclassical analysis and a full quantum calculation. The results are compared with previous measurements.

H. Li; E. S. Gillman; J. W. Sheldon; K. A. Hardy

1992-01-01T23:59:59.000Z

385

Total electron and proton energy input during auroral substorms: Remote sensing with IMAGE-FUV  

E-Print Network (OSTI)

, it is found that the most critical factor is the assumption made on the energy of the auroral protonsTotal electron and proton energy input during auroral substorms: Remote sensing with IMAGE-FUV B and proton energy fluxes. The proton energy flux is derived from the Lyman a measurements on the basis

California at Berkeley, University of

386

Energy Perspectives, Total Energy - Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Total Energy Glossary › FAQS › Overview Data Monthly Annual Analysis & Projections this will be filled with a highchart PREVIOUSNEXT Energy Perspectives 1949-2011 September 2012 PDF | previous editions Release Date: September 27, 2012 Introduction Energy Perspectives is a graphical overview of energy history in the United States. The 42 graphs shown here reveal sweeping trends related to the Nation's production, consumption, and trade of energy from 1949 through 2011. Energy Flow, 2011 (Quadrillion Btu) Total Energy Flow diagram image For footnotes see here. Energy can be grouped into three broad categories. First, and by far the largest, is the fossil fuels-coal, petroleum, and natural gas. Fossil fuels have stored the sun's energy over millennia past, and it is primarily

387

Property:TotalValue | Open Energy Information  

Open Energy Info (EERE)

TotalValue TotalValue Jump to: navigation, search This is a property of type Number. Pages using the property "TotalValue" Showing 25 pages using this property. (previous 25) (next 25) 4 44 Tech Inc. Smart Grid Demonstration Project + 10,000,000 + A ALLETE Inc., d/b/a Minnesota Power Smart Grid Project + 3,088,007 + Amber Kinetics, Inc. Smart Grid Demonstration Project + 10,000,000 + American Transmission Company LLC II Smart Grid Project + 22,888,360 + American Transmission Company LLC Smart Grid Project + 2,661,650 + Atlantic City Electric Company Smart Grid Project + 37,400,000 + Avista Utilities Smart Grid Project + 40,000,000 + B Baltimore Gas and Electric Company Smart Grid Project + 451,814,234 + Battelle Memorial Institute, Pacific Northwest Division Smart Grid Demonstration Project + 177,642,503 +

388

ARM - Measurement - Net broadband total irradiance  

NLE Websites -- All DOE Office Websites (Extended Search)

govMeasurementsNet broadband total irradiance govMeasurementsNet broadband total irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Net broadband total irradiance The difference between upwelling and downwelling, covering longwave and shortwave radiation. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those recorded for diagnostic or quality assurance purposes. ARM Instruments EBBR : Energy Balance Bowen Ratio Station SEBS : Surface Energy Balance System External Instruments ECMWF : European Centre for Medium Range Weather Forecasts Model

389

SolarTotal | Open Energy Information  

Open Energy Info (EERE)

SolarTotal SolarTotal Jump to: navigation, search Name SolarTotal Place Bemmel, Netherlands Zip 6681 LN Sector Solar Product The company sells and installs PV solar instalations Coordinates 51.894112°, 5.89881° 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":51.894112,"lon":5.89881,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

390

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

391

Table A50. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Industry Group, Selected Industries, and Type of" " Energy-Management Program, 1994" " (Estimates in Trillion Btu)" ,,,," Census Region",,,"RSE" "SIC",,,,,,,"Row" "Code(a)","Industry Group and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.2,1.1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",12605,1209,3303,6386,1706,2.9

392

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

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

2. Total Quantity of Purchased Energy Sources by Census Region," 2. Total Quantity of Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,"Natural",,,"Coke" " "," ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","(trillion","(million","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000","(1000","Other(d)","Row" "Code(a)","Industry Groups and Industry","Btu)","kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","short tons)","short tons)","(trillion Btu)","Factors"

393

Award Number: Federal Non-Federal Federal Non-Federal Total  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Prescribed by OMB Circular A-102 Prescribed by OMB Circular A-102 Previous Edition Usable Total (5) f. Contractual g. Construction Section B - Budget Categories Catalog of Federal Domestic Assistance Number Grant Program Function or Activity Estimated Unobligated Funds e. Supplies i. Total Direct Charges (sum of 6a-6h) Grant Program, Function or Activity Object Class Categories Authorized for Local Reproduction h. Other a. Personnel b. Fringe Benefits c. Travel d. Equipment 6. j. Indirect Charges k. Totals (sum of 6i-6j) Program Income Applicant Name: Budget Information - Non Construction Programs OMB Approval No. 0348-0044 New or Revised Budget Section A - Budget Summary

394

Award Number: Federal Non-Federal Federal Non-Federal Total  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

j. Indirect Charges j. Indirect Charges k. Totals (sum of 6i-6j) Program Income Applicant Name: Budget Information - Non Construction Programs OMB Approval No. 0348-0044 New or Revised Budget Section A - Budget Summary i. Total Direct Charges (sum of 6a-6h) Grant Program, Function or Activity Object Class Categories Authorized for Local Reproduction h. Other a. Personnel b. Fringe Benefits c. Travel d. Equipment 6. Total (5) f. Contractual g. Construction Section B - Budget Categories Catalog of Federal Domestic Assistance Number Grant Program Function or Activity Estimated Unobligated Funds e. Supplies Prescribed by OMB Circular A-102 Previous Edition Usable

395

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

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

A9. Total Primary Consumption of Energy for All Purposes by Census" A9. Total Primary Consumption of Energy for All Purposes by Census" " Region and Economic Characteristics of the Establishment, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke" " "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" " ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","LPG","(1000","(1000","Other(e)","Row" "Economic Characteristics(a)","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","(cu ft)","(1000 bbls)","short tons)","short tons)","(trillion Btu)","Factors"

396

Table A37. Total Inputs of Energy for Heat, Power, and Electricity  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" "Total United States" "RSE Column Factors:","NF",0.4,1.6,1.5,0.7,1,1.6,"NF" "TOTAL INPUTS",15027,2370,414,139,5506,105,1184,5309,3 "Boiler Fuel","--","W",296,40,2098,18,859,"--",3.6

397

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

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

Total First Use (formerly Primary Consumption) of Energy for All Purposes by Census" Total First Use (formerly Primary Consumption) of Energy for All Purposes by Census" " Region, Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke",,"Shipments" " "," ","Net","Residual","Distillate","Natural Gas(e)"," ","Coal","and Breeze"," ","of Energy Sources","RSE" " ","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","(billion","LPG","(1000","(1000","Other(f)","Produced Onsite(g)","Row"

398

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

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

Total First Use (formerly Primary Consumption) of Energy for All Purposes" Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Employment Size Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," "," Employment Size(b)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",1000,"Row" "Code(a)","Industry Group and Industry","Total","Under 50","50-99","100-249","250-499","500-999","and Over","Factors" ,"RSE Column Factors:",0.6,1.5,1.5,1,0.9,0.9,0.9 , 20,"Food and Kindred Products",1193,119,207,265,285,195,122,6

399

Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:"," NF",0.5,1.3,1.4,0.8,1.2,1.2," NF" "TOTAL INPUTS",16515,2656,441,152,6141,99,1198,5828,2.7 "Indirect Uses-Boiler Fuel"," --",28,313,42,2396,15,875," --",4

400

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

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry Group and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors" ,"RSE Column Factors:",0.6,1.3,1,1,0.9,1.2,1.2

Note: This page contains sample records for the topic "derived estimates total" 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

Table A41. Total Inputs of Energy for Heat, Power, and Electricity  

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

A41. Total Inputs of Energy for Heat, Power, and Electricity" A41. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Census Region, Industry Group, Selected Industries, and Type of" " Energy Management Program, 1991" " (Estimates in Trillion Btu)" ,,," Census Region",,,,"RSE" "SIC","Industry Groups",," -------------------------------------------",,,,"Row" "Code(a)","and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.3,1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",10743,1150,2819,5309,1464,2.6,,,"/WIR{D}~"

402

Comparison of blood flow models and acquisitions for quantitative myocardial perfusion estimation from dynamic CT  

Science Journals Connector (OSTI)

Myocardial blood flow (MBF) can be estimated from dynamic contrast enhanced (DCE) cardiac CT acquisitions, leading to quantitative assessment of regional perfusion. The need for low radiation dose and the lack of consensus on MBF estimation methods motivates this study to refine the selection of acquisition protocols and models for CT-derived MBF. DCE cardiac CT acquisitions were simulated for a range of flow states (MBF = 0.5, 1, 2, 3 ml (min g)?1, cardiac output = 3, 5, 8 L min?1). Patient kinetics were generated by a mathematical model of iodine exchange incorporating numerous physiological features including heterogenenous microvascular flow, permeability and capillary contrast gradients. CT acquisitions were simulated for multiple realizations of realistic x-ray flux levels. CT acquisitions that reduce radiation exposure were implemented by varying both temporal sampling (1, 2, and 3 s sampling intervals) and tube currents (140, 70, and 25 mAs). For all acquisitions, we compared three quantitative MBF estimation methods (two-compartment model, an axially-distributed model, and the adiabatic approximation to the tissue homogeneous model) and a qualitative slope-based method. In total, over 11 000 time attenuation curves were used to evaluate MBF estimation in multiple patient and imaging scenarios. After iodine-based beam hardening correction, the slope method consistently underestimated flow by on average 47.5% and the quantitative models provided estimates with less than 6.5% average bias and increasing variance with increasing dose reductions. The three quantitative models performed equally well, offering estimates with essentially identical root mean squared error (RMSE) for matched acquisitions. MBF estimates using the qualitative slope method were inferior in terms of bias and RMSE compared to the quantitative methods. MBF estimate error was equal at matched dose reductions for all quantitative methods and range of techniques evaluated. This suggests that there is no particular advantage between quantitative estimation methods nor to performing dose reduction via tube current reduction compared to temporal sampling reduction. These data are important for optimizing implementation of cardiac dynamic CT in clinical practice and in prospective CT MBF trials.

Michael Bindschadler; Dimple Modgil; Kelley R Branch; Patrick J La Riviere; Adam M Alessio

2014-01-01T23:59:59.000Z

403

Augmenting Satellite Precipitation Estimation with Lightning Information  

SciTech Connect

We have used lightning information to augment the Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Network - Cloud Classification System (PERSIANN-CCS). Co-located lightning data are used to segregate cloud patches, segmented from GOES-12 infrared data, into either electrified (EL) or non-electrified (NEL) patches. A set of features is extracted separately for the EL and NEL cloud patches. The features for the EL cloud patches include new features based on the lightning information. The cloud patches are classified and clustered using self-organizing maps (SOM). Then brightness temperature and rain rate (T-R) relationships are derived for the different clusters. Rain rates are estimated for the cloud patches based on their representative T-R relationship. The Equitable Threat Score (ETS) for daily precipitation estimates is improved by almost 12% for the winter season. In the summer, no significant improvements in ETS are noted.

Mahrooghy, Majid [Mississippi State University (MSU); Anantharaj, Valentine G [ORNL; Younan, Nicolas H. [Mississippi State University (MSU); Petersen, Walter A. [NASA Marshall Space Flight Center, Huntsville, AL; Hsu, Kuo-Lin [University of California, Irvine; Behrangi, Ali [Jet Propulsion Laboratory, Pasadena, CA; Aanstoos, James [Mississippi State University (MSU)

2013-01-01T23:59:59.000Z

404

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

and Hydrogen Energy Overview: Total Energy USA 2012 National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 Presentation by Sunita Satyapal at the Total Energy USA...

405

Estimation theoretical image restoration  

E-Print Network (OSTI)

In this thesis, we have developed an extensive study to evaluate image restoration from a single image, colored or monochromatic. Using a mixture of Gaussian and Poisson noise process, we derived an objective function to ...

Dolne, Jean J

2008-01-01T23:59:59.000Z

406

THE HEIGHT EVOLUTION OF THE ''TRUE'' CORONAL MASS EJECTION MASS DERIVED FROM STEREO COR1 AND COR2 OBSERVATIONS  

SciTech Connect

Using combined STEREO-A and STEREO-B EUVI, COR1, and COR2 data, we derive deprojected coronal mass ejection (CME) kinematics and CME ''true'' mass evolutions for a sample of 25 events that occurred during 2007 December to 2011 April. We develop a fitting function to describe the CME mass evolution with height. The function considers both the effect of the coronagraph occulter, at the beginning of the CME evolution, and an actual mass increase. The latter becomes important at about 10-15 R{sub Sun} and is assumed to mostly contribute up to 20 R{sub Sun }. The mass increase ranges from 2% to 6% per R{sub Sun} and is positively correlated to the total CME mass. Due to the combination of COR1 and COR2 mass measurements, we are able to estimate the ''true'' mass value for very low coronal heights (<3 R{sub Sun }). Based on the deprojected CME kinematics and initial ejected masses, we derive the kinetic energies and propelling forces acting on the CME in the low corona (<3 R{sub Sun }). The derived CME kinetic energies range between 1.0-66 Multiplication-Sign 10{sup 23} J, and the forces range between 2.2-510 Multiplication-Sign 10{sup 14} N.

Bein, B. M.; Temmer, M.; Veronig, A. M.; Utz, D. [Kanzelhoehe Observatory-IGAM, Institute of Physics, University of Graz, Universitaetsplatz 5, A-8010 Graz (Austria); Vourlidas, A. [Space Science Division, Naval Research Laboratory, Washington, DC (United States)

2013-05-01T23:59:59.000Z

407

The Leica TCRA1105 Reflectorless Total Station  

SciTech Connect

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

Gaudreault, F.

2005-09-06T23:59:59.000Z

408

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION  

E-Print Network (OSTI)

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION BERND WITTGENS, RAJAB LITTO, EVA SĂ?RENSEN in this paper provides a generalization of previously proposed batch distillation schemes. A simple feedback been built and the experiments verify the simulations. INTRODUCTION Although batch distillation

Skogestad, Sigurd

409

Total Solar Irradiance Satellite Composites and their  

E-Print Network (OSTI)

Chapter 12 Total Solar Irradiance Satellite Composites and their Phenomenological Effect on Climate. Phenomenological solar signature on climate 310 9. Conclusion 312 1. INTRODUCTION A contiguoustotal solar from each other, in particular about whether the TSI minimum during solar Cycles 22e23 (1995

Scafetta, Nicola

410

Table A1. Total Primary Consumption of Energy for All Purposes by Census  

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

1 " 1 " " (Estimates in Btu or Physical Units)" " "," "," "," "," "," "," "," "," "," "," "," " " "," "," ",," "," ",," "," ","Coke and"," "," " " "," ",,"Net","Residual","Distillate","Natural Gas(d)"," ","Coal","Breeze"," ","RSE" "SIC"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","LPG","(1000","(1000","Other(e)","Row"

411

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

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

2" 2" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," "," "," "," "," " " "," "," "," "," "," "," "," "," "," "," ","RSE" "SIC"," "," ","Net","Residual","Distillate"," "," "," ","Coke"," ","Row" "Code(a)","Industry Groups and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","LPG","Coal","and Breeze","Other(e)","Factors"

412

Table A1. Total First Use (formerly Primary Consumption) of Energy for All Pu  

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

2" 2" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," "," "," "," ",," " " "," "," ",," "," ",," "," ",," ","Shipments","RSE" "SIC"," ",,"Net","Residual","Distillate",," ",,"Coke and"," ","of Energy Sources","Row" "Code(a)","Industry Group and Industry","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","LPG","Coal","Breeze","Other(f)","Produced Onsite(g)","Factors"

413

Table A3. Total First Use (formerly Primary Consumption) of Combustible Energ  

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

Nonfuel Purposes by" Nonfuel Purposes by" " Census Region, Industry Group, and Selected Industries, 1994: Part 1 " " (Estimates in Btu or Physical Units)" " "," "," "," "," "," "," "," ","Coke"," "," " " "," "," ","Residual","Distillate","Natural Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","Total","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000","(1000 ","Other(d)","Row"

414

Table A3. Total First Use (formerly Primary Consumption) of Combustible Energ  

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

Nonfuel" Nonfuel" " Purposes by Census Region, Industry Group, and Selected Industries, 1994: Part 2" " (Estimates in Trillion Btu) " " "," "," "," "," "," "," "," "," "," "," " " "," "," "," "," "," "," "," "," "," ","RSE" "SIC"," "," ","Residual","Distillate "," "," "," ","Coke "," ","Row" "Code(a)","Industry Group and Industry","Total","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

415

Table A1. Total First Use (formerly Primary Consumption) of Energy for All Pu  

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

1 " 1 " " (Estimates in Btu or Physical Units)" " "," "," "," "," "," "," "," "," "," "," ",," " " "," "," ",," "," ",," "," ","Coke and"," ","Shipments"," " " "," ",,"Net","Residual","Distillate","Natural Gas(e)"," ","Coal","Breeze"," ","of Energy Sources","RSE" "SIC"," ","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","(billion","LPG","(1000","(1000","Other(f)","Produced Onsite(g)","Row"

416

Table A1. Total Primary Consumption of Energy for All Purposes by Census  

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

2" 2" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," "," "," "," "," " " "," ",," "," "," "," "," "," "," "," ","RSE" "SIC"," ",,"Net","Residual","Distillate "," "," "," ","Coke"," ","Row" "Code(a)","Industry Groups and Industry"," Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","LPG","Coal","and Breeze","Other(e)","Factors"

417

Table A33. Total Primary Consumption of Energy for All Purposes by Employment  

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

Primary Consumption of Energy for All Purposes by Employment" Primary Consumption of Energy for All Purposes by Employment" " Size Categories, Industry Group, and Selected Industries, 1991 (Continued)" " (Estimates in Trillion Btu)" ,,,,,"Employment Size" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," ",,500,"Row" "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"," "," "," "," "," "," "," "

418

"Table A25. Components of Total Electricity Demand by Census Region, Census Division, Industry"  

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

Components of Total Electricity Demand by Census Region, Census Division, Industry" Components of Total Electricity Demand by Census Region, Census Division, Industry" " Group, and Selected Industries, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total Onsite","Transfers","Net Demand for","Row" "Code(a)","Industry Group and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)","Factors"

419

Cost Estimating Guide  

Directives, Delegations, and Requirements

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

2011-05-09T23:59:59.000Z

420

: Helmholtz machine estimation .  

E-Print Network (OSTI)

: Helmholtz machine density estimation . . : . . . (supervised learning) , (active learning) (query learning) [1, 3]. . (unsupervised learning), . , [5]. . Helmholtz machine , . Helmholtz machine : Helmholtz machine [2] . Helmholtz machine (generative network) (recognition network) . , , . Helmholtz machine (self

Note: This page contains sample records for the topic "derived estimates total" 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

Estimates of heat flow from Cenozoic seafloor using global depth and age data  

E-Print Network (OSTI)

-independent estimate of the total heat output of Cenozoic seafloor is 18.6 to 20.5 TW, which leads to a global output: Oceanic heat flow; Global heat budget; Subsidence rate 1. Introduction The total heat output of the EarthEstimates of heat flow from Cenozoic seafloor using global depth and age data Meng Wei , David

Sandwell, David T.

422

On the Derivatives of Propane  

Science Journals Connector (OSTI)

1 January 1869 research-article On the Derivatives of Propane C. Schorlemmer The Royal Society is collaborating with JSTOR to digitize, preserve, and extend access to Proceedings of the Royal Society of London. www.jstor.org

1869-01-01T23:59:59.000Z

423

The assimilation of satellite-derived data into a one-dimensional lower trophic level marine ecosystem model  

E-Print Network (OSTI)

The assimilation of satellite-derived data into a one-dimensional lower trophic level marine, Virginia 23062-1346. Email: marjy@vims.edu #12; 2 The assimilation of satellite-derived data of experiments assimilating synthetic and actual satellite-derived data, including total chlorophyll, size

Latour, Robert J.

424

Biodegradation of total petroleum hydrocarbon (TPH) in Jordanian petroleum sludge  

Science Journals Connector (OSTI)

Bioremediation, or the use of micro-organisms to decontaminate soil or groundwater, is being increasingly seen as an effective, environment-friendly treatment for oil-contaminated sites. In this study, the results are presented concerning a laboratory screening of several natural bacterial consortia and laboratory tests to establish the performance in degradation of hydrocarbons contained in oily sludge from the Jordan Oil Refinery Plant. As a result of the laboratory screening, 18 isolates were selected and grouped into two main clusters; cluster 1 containing 12 isolates grown at 43°C, and cluster 2 containing six isolates grown at 37°C. Three natural bacterial consortia with ability to degrade total petroleum hydrocarbons (TPH) were prepared from these isolates. Experiments were conducted in Erlenmeyer flasks under aerobic conditions, with TPH removal percentage varying from 5.9% to 25.1%, depending upon consortia type and concentration. Consortia 7B and 13B exhibited the highest TPH removal percentages of 25% and 23%, respectively before nutrient addition. TPH removal rate was enhanced after addition of nutrients to incubated flasks. The highest TPH reduction (37%) was estimated after addition of a combination of nitrogen, phosphorus and sulphur to consortia 7B. This is the first report concerning biological treatment of total petroleum hydrocarbon by bacteria isolated from the oil refinery plant, where it lay the ground for full integrated studies recommended for hydrocarbon degradation that assist in solving sludge problems.

Bassam Mrayyan; Mohammad Battikhi

2004-01-01T23:59:59.000Z

425

ARM - Measurement - Shortwave broadband total downwelling irradiance  

NLE Websites -- All DOE Office Websites (Extended Search)

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

426

Total Neutron Scattering in Vitreous Silica  

Science Journals Connector (OSTI)

The structure of Corning superpure vitreous silica glass has been investigated with neutrons. A new method of analysis using variable neutron wavelengths and the measurement of total scattering cross sections from transmission experiments is developed and the results are compared with those from differential x-ray scattering. The total neutron scattering method permits a simple and direct structure analysis with resolution apparently superior to x-rays. The preliminary results compare well in a first approximation analysis with the basic structure model of Warren and others and in addition the neutron-determined atomic radial distribution curve exhibits some finer details than the x-ray results. Thermal inelastic scattering of neutrons was corrected for in an approximate way.

R. J. Breen; R. M. Delaney; P. J. Persiani; A. H. Weber

1957-01-15T23:59:59.000Z

427

Frustrated total internal reflection acoustic field sensor  

DOE Patents (OSTI)

A frustrated total internal reflection acoustic field sensor which allows the acquisition of the acoustic field over an entire plane, all at once. The sensor finds use in acoustic holography and acoustic diffraction tomography. For example, the sensor may be produced by a transparent plate with transparent support members tall enough to support one or more flexible membranes at an appropriate height for frustrated total internal reflection to occur. An acoustic wave causes the membrane to deflect away from its quiescent position and thus changes the amount of light that tunnels through the gap formed by the support members and into the membrane, and so changes the amount of light reflected by the membrane. The sensor(s) is illuminated by a uniform tight field, and the reflection from the sensor yields acoustic wave amplitude and phase information which can be picked up electronically or otherwise.

Kallman, Jeffrey S. (Pleasanton, CA)

2000-01-01T23:59:59.000Z

428

Improved selection in totally monotone arrays  

SciTech Connect

This paper's main result is an O(({radical}{bar m}lgm)(n lg n) + mlg n)-time algorithm for computing the kth smallest entry in each row of an m {times} n totally monotone array. (A two-dimensional A = a(i,j) is totally monotone if for all i{sub 1} < i{sub 2} and j{sub 1} < j{sup 2}, < a(i{sub 1},j{sub 2}) implies a(i{sub 2},j{sub 1})). For large values of k (in particular, for k=(n/2)), this algorithm is significantly faster than the O(k(m+n))-time algorithm for the same problem due to Kravets and Park. An immediate consequence of this result is an O(n{sup 3/2} lg{sup 2}n)-time algorithm for computing the kth nearest neighbor of each vertex of a convex n-gon. In addition to the main result, we also give an O(n lg m)-time algorithm for computing an approximate median in each row of an m {times} n totally monotone array; this approximate median is an entry whose rank in its row lies between (n/4) and (3n/4) {minus} 1. 20 refs., 3 figs.

Mansour, Y. (Harvard Univ., Cambridge, MA (United States). Aiken Computation Lab.); Park, J.K. (Sandia National Labs., Albuquerque, NM (United States)); Schieber, B. (International Business Machines Corp., Yorktown Heights, NY (United States). Thomas J. Watson Research Center); Sen, S. (AT and T Bell Labs., Murray Hill, NJ (United States))

1991-01-01T23:59:59.000Z

429

EQUUS Total Return Inc | Open Energy Information  

Open Energy Info (EERE)

EQUUS Total Return Inc EQUUS Total Return Inc Jump to: navigation, search Name EQUUS Total Return Inc Place Houston, Texas Product A business development company and VC investor that trades as a closed-end fund. EQUUS is managed by MCC Global NV, a Frankfurt stock exchange listed management and merchant banking group. Coordinates 29.76045°, -95.369784° 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":29.76045,"lon":-95.369784,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

430

Position Estimation of a Parametrically Driven Optomechanical System  

E-Print Network (OSTI)

We study the position estimation of a mechanical oscillator undergoing both detuned parametric amplification and continuous quantum measurement. This model, which can be utilised to produce squeezed states, is applied to a general optoelectromechanical system. Using a stochastic master equation formalism, we derive general formulae for the reduction in position uncertainty of one quadrature of motion. The filter for extracting the optimal position estimate from the measurement record is derived. We also find that since this scheme does not work far into the back-action dominated regime, implementing resolved-sideband cooling improves the squeezing only marginally.

Alex Szorkovszky; Andrew C. Doherty; Glen I. Harris; Warwick P. Bowen

2012-08-03T23:59:59.000Z

431

Derivative-Free Optimization Proximal Point Methods Derivative-Free Proximal Point Conclusion Derivative-Free Optimization via Proximal  

E-Print Network (OSTI)

Derivative-Free Optimization Proximal Point Methods Derivative-Free Proximal Point Conclusion Derivative-Free Optimization via Proximal Point Methods Yves Lucet & Warren Hare July 24, 2013 1 / 26 #12;Derivative-Free Optimization Proximal Point Methods Derivative-Free Proximal Point Conclusion Outline 1

432

REQUESTS FOR RETIREMENT ESTIMATE  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

REQUEST FOR RETIREMENT ANNUITY ESTIMATE REQUEST FOR RETIREMENT ANNUITY ESTIMATE Instructions: Please read and answer the following questions thoroughly to include checking all applicable boxes. Unanswered questions may delay processing. Print and Fax back your request form to 202.586.6395 or drop request to GM-169. The request will be assigned to your servicing retirement specialist. They will confirm receipt of your request. SECTION A Request Submitted _____________________ ______________________ ________________________ _____________________ Name (last, first, middle) Last four SSN Date of Birth ___________________________ _________________________ __________________________ Organization Office Telephone Number Fax Number

433

Total solar house description and performance  

SciTech Connect

The initial attempt to apply the Total Solar concept to a residence in the Philadelphia, Pennsylvania, area is described. A very large storage capacity has made it possible to use only solar energy for meeting the heating, cooling and hot water needs for the entire year, with a parasitic power penalty of about 3500 kWh. Winter temperatures were maintained at 68/sup 0/F with 60/sup 0/F night setback, summer at 76/sup 0/F. Occupant intervention was negligible and passive overheat was minimized. The extra cost for the system, approximately $30,000 is readily amortized by the savings in purchased energy.

Starobin, L. (Univ. of Pennsylvania, Philadelphia); Starobin, J.

1981-01-01T23:59:59.000Z

434

Neutron Total Cross Sections at 20 Mev  

Science Journals Connector (OSTI)

With the T(d, n)He4 reaction as a monoenergetic source of neutrons of about 20 Mev, the total cross sections of 13 elements have been measured by a transmission experiment. These cross sections vary approximately as A23 as is to be expected from the continuum theory of nuclear reactions. The cross section for hydrogen at 19.93 Mev is 0.504±0.01 barn. This result, together with other results at lower energies, seems to require a Yukawa potential in both the singlet and triplet n-p states and a singlet effective range that is lower than that obtained from p-p scattering data.

Robert B. Day and Richard L. Henkel

1953-10-15T23:59:59.000Z

435

Magnetic cellulose-derivative structures  

DOE Patents (OSTI)

Structures to serve as selective magnetic sorbents are formed by dissolving a cellulose derivative such as cellulose triacetate in a solvent containing magnetic particles. The resulting solution is sprayed as a fine mist into a chamber containing a liquid coagulant such as n-hexane in which the cellulose derivative is insoluble but in which the coagulant is soluble or miscible. On contact with the coagulant, the mist forms free-flowing porous magnetic microspheric structures. These structures act as containers for the ion-selective or organic-selective sorption agent of choice. Some sorption agents can be incorporated during the manufacture of the structure. 3 figs.

Walsh, M.A.; Morris, R.S.

1986-09-16T23:59:59.000Z

436

Magnetic cellulose-derivative structures  

DOE Patents (OSTI)

Structures to serve as selective magnetic sorbents are formed by dissolving a cellulose derivative such as cellulose triacetate in a solvent containing magnetic particles. The resulting solution is sprayed as a fine mist into a chamber containing a liquid coagulant such as n-hexane in which the cellulose derivative is insoluble but in which the coagulant is soluble or miscible. On contact with the coagulant, the mist forms free-flowing porous magnetic microspheric structures. These structures act as containers for the ion-selective or organic-selective sorption agent of choice. Some sorbtion agents can be incorporated during the manufacture of the structure.

Walsh, Myles A. (Falmouth, MA); Morris, Robert S. (Fairhaven, MA)

1986-09-16T23:59:59.000Z

437

SPACE TECHNOLOGY Actual Estimate  

E-Print Network (OSTI)

SPACE TECHNOLOGY TECH-1 Actual Estimate Budget Authority (in $ millions) FY 2011 FY 2012 FY 2013 FY.7 247.0 Exploration Technology Development 144.6 189.9 202.0 215.5 215.7 214.5 216.5 Notional SPACE TECHNOLOGY OVERVIEW .............................. TECH- 2 SBIR AND STTR

438

Total Pollution Effect and Total Energy Cost per Output of Different Products for Polish Industrial System  

Science Journals Connector (OSTI)

For many years a broad use has been made of the indices of total energy requirements in the whole large production system corresponding to unit output of particular goods (Boustead I., Hancock G.F., 1979). The...

Henryk W. Balandynowicz

1988-01-01T23:59:59.000Z

439

Total Sales of Residual Fuel Oil  

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

End Use: Total Commercial Industrial Oil Company Electric Power Vessel Bunkering Military All Other Period: End Use: Total Commercial Industrial Oil Company Electric Power Vessel Bunkering Military All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 10,706,479 8,341,552 6,908,028 7,233,765 6,358,120 6,022,115 1984-2012 East Coast (PADD 1) 5,527,235 4,043,975 2,972,575 2,994,245 2,397,932 2,019,294 1984-2012 New England (PADD 1A) 614,965 435,262 281,895 218,926 150,462 101,957 1984-2012 Connecticut 88,053 33,494 31,508 41,686 6,534 5,540 1984-2012 Maine 152,082 110,648 129,181 92,567 83,603 49,235 1984-2012 Massachusetts 300,530 230,057 59,627 52,228 34,862 30,474 1984-2012

440

Total Space Heating Water Heating Cook-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ........................... 1,870 1,276 322 138 133 43.0 29.4 7.4 3.2 3.1 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 243 151 34 40 18 78.7 48.9 11.1 13.0 5.7 5,001 to 10,000 .......................... 202 139 31 29 Q 54.8 37.6 8.5 7.9 Q 10,001 to 25,000 ........................ 300 240 31 21 7 42.5 34.1 4.4 3.0 1.1 25,001 to 50,000 ........................ 250 182 40 11 Q 41.5 30.2 6.6 1.9 Q 50,001 to 100,000 ...................... 236 169 41 8 19 35.4 25.2 6.2 1.2 2.8 100,001 to 200,000 .................... 241 165 54 7 16 36.3 24.8 8.1 1.0 2.4 200,001 to 500,000 .................... 199 130 42 11 16 35.0 22.8 7.5 1.9 2.8 Over 500,000 ............................. 198

Note: This page contains sample records for the topic "derived estimates total" 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 Space Heating Water Heating Cook-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings ............................. 2,037 1,378 338 159 163 42.0 28.4 7.0 3.3 3.4 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 249 156 35 41 18 78.6 49.1 11.0 12.9 5.6 5,001 to 10,000 .......................... 218 147 32 31 7 54.8 37.1 8.1 7.9 1.7 10,001 to 25,000 ........................ 343 265 34 25 18 43.8 33.9 4.4 3.2 2.3 25,001 to 50,000 ........................ 270 196 41 13 Q 40.9 29.7 6.3 2.0 2.9 50,001 to 100,000 ...................... 269 186 45 13 24 35.8 24.8 6.0 1.8 3.2 100,001 to 200,000 .................... 267 182 56 10 19 35.4 24.1 7.4 1.3 2.6 200,001 to 500,000 .................... 204 134 43 11 17 34.7 22.7 7.3 1.8 2.9 Over 500,000 .............................

442

Total assessment audits (TAA) in Iowa  

SciTech Connect

Traditionally, energy, waste reduction and productivity audits are performed for a manufacturing facility independent of one another. Auditors generally deliver recommendations for improvement based on their specialized expertise (energy, waste reduction, productivity, etc.) without regard to how those recommendations may impact other, sometimes less obvious, subsystems or processes within the facility. The audits are typically performed in isolation from the plant upper management and commonly without adequate knowledge of how inherent interrelated operational constraints may directly or indirectly influence the success of audit recommendations. The Total Assessment Audit (TAA) concept originated from the belief that a manufacturing facility is better served using a holistic approach to problem solving rather than the more conventional isolated approach. The total assessment audit methodology partners the upper management team of a company with a multi-disciplined team of industry-specific specialists to collectively ascertain the core opportunities for improvement in the company and then to formulate a company oriented continuous improvement plan. Productivity, waste reduction, and energy efficiency objectives are seamlessly integrated into a single service delivery with the TAA approach. Nontraditional audit objectives that influence profitability and competitiveness such as business management practices, employee training, human resource issues, etc. are also subject to evaluation in a TAA. The underlying premise of this approach is that the objectives are interrelated and that simultaneous evaluation will province synergistic results. Ultimately, it is believed that the TAA approach can motivate a manufacturer to implement improvements it might not otherwise pursue if it were focused only on singular objectives.

Haman, W.G.

1999-07-01T23:59:59.000Z

443

A new method for estimating carbon dioxide emissions from transportation at fine spatial  

Science Journals Connector (OSTI)

Detailed estimates of carbon dioxide (CO2) emissions at fine spatial scales are useful to both modelers and decision makers who are faced with the problem of global warming and climate change. Globally, transport related emissions of carbon dioxide are growing. This letter presents a new method based on the volume-preserving principle in the areal interpolation literature to disaggregate transportation-related CO2 emission estimates from the county-level scale to a 1?km2 grid scale. The proposed volume-preserving interpolation (VPI) method, together with the distance-decay principle, were used to derive emission weights for each grid based on its proximity to highways, roads, railroads, waterways, and airports. The total CO2 emission value summed from the grids within a county is made to be equal to the original county-level estimate, thus enforcing the volume-preserving property. The method was applied to downscale the transportation-related CO2 emission values by county (i.e.?parish) for the state of Louisiana into 1?km2 grids. The results reveal a more realistic spatial pattern of CO2 emission from transportation, which can be used to identify the emission 'hot spots'. Of the four highest transportation-related CO2 emission hotspots in Louisiana, high-emission grids literally covered the entire East Baton Rouge Parish and Orleans Parish, whereas CO2 emission in Jefferson Parish (New Orleans suburb) and Caddo Parish (city of Shreveport) were more unevenly distributed. We argue that the new method is sound in principle, flexible in practice, and the resultant estimates are more accurate than previous gridding approaches.

Yuqin Shu; Nina S N Lam; Margaret Reams

2010-01-01T23:59:59.000Z

444

Informational derivation of quantum theory  

SciTech Connect

We derive quantum theory from purely informational principles. Five elementary axioms - causality, perfect distinguishability, ideal compression, local distinguishability, and pure conditioning - define a broad class of theories of information processing that can be regarded as standard. One postulate - purification - singles out quantum theory within this class.

Chiribella, Giulio; D'Ariano, Giacomo Mauro; Perinotti, Paolo [Perimeter Institute for Theoretical Physics, 31 Caroline Street North, Ontario, N2L 2Y5 (Canada); QUIT Group, Dipartimento di Fisica ''A. Volta'' and INFN Sezione di Pavia, via Bassi 6, I-27100 Pavia (Italy)

2011-07-15T23:59:59.000Z

445

A comparison of cloudiness measures derived from longwave measurements and  

NLE Websites -- All DOE Office Websites (Extended Search)

A comparison of cloudiness measures derived from longwave measurements and A comparison of cloudiness measures derived from longwave measurements and shortwave sky imagers Takara, Ezra Florida State University Ellingson, Robert Florida State University Ma, Yingtao University of Maryland Category: Cloud Properties In the longwave, two measures of cloudiness for single layer clouds are the probability of clear line of sight (PCLoS) and the effective cloud fraction. As the name states, the PCLoS is the probability of a clear line of sight through a broken cloud field. The effectivecloud fraction is the fraction of the sky that is taken up by the clouds; this includes the portion blocked by the cloud sides as well as the fraction taken up by the cloud bases. The effective cloud fraction can be derived from measurements or from the PCLoS. Here the PCLoS obtained from the shortwave-based Total

446

Estimating climatological variability of solar energy production  

Science Journals Connector (OSTI)

Abstract A method is presented for estimating the climatological variability of yearly and monthly photovoltaic power production per 1 kWp of installed power. This quantity is computed for a specified portfolio of sources on the basis of historical data. Its climatological variability is derived from a simulation of 33 years of power production with hourly time step. Underlying meteorological variables are taken from the MERRA reanalysis for the years 1979–2011. Since the MERRA reanalysis is not a traditional data source for photovoltaic power modelling, various comparisons to available and more frequently used data sources are included. The method of estimation has the advantage of wide applicability due to the global coverage of the meteorological data.

Pavel Juruš; Kryštof Eben; Jaroslav Resler; Pavel Kr?; Ivan Kasanický; Emil Pelikán; Marek Brabec; Ji?í Hošek

2013-01-01T23:59:59.000Z

447

Use of Cost Estimating Relationships  

Directives, Delegations, and Requirements

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

1997-03-28T23:59:59.000Z

448

Reinforcing flood–risk estimation  

Science Journals Connector (OSTI)

...publication of the Flood estimation handbook, studies of ood risk are now...especially for its neglect of the physics of catchment pro- cesses of...recommended in the Flood estimation handbook (Institute of Hydrology 1999...estimates. The Flood estimation handbook (Institute of Hydrology 1999...

2002-01-01T23:59:59.000Z

449

ARM - Measurement - Shortwave narrowband total upwelling irradiance  

NLE Websites -- All DOE Office Websites (Extended Search)

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

450

ARM - Measurement - Shortwave narrowband total downwelling irradiance  

NLE Websites -- All DOE Office Websites (Extended Search)

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

451

Total Blender Net Input of Petroleum Products  

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

Input Input Product: Total Input Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquid Petroleum Gases Normal Butane Isobutane Other Liquids Oxygenates/Renewables Methyl Tertiary Butyl Ether (MTBE) Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Unfinished Oils (net) Unfinished Oils, Naphthas and Lighter Unfinished Oils, Kerosene and Light Gas Oils Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Components (MGBC) (net) MGBC - Reformulated MGBC - Reformulated - RBOB MGBC - Reformulated, RBOB for Blending w/ Alcohol MGBC - Reformulated, RBOB for Blending w/ Ether MGBC - Reformulated, GTAB MGBC - Conventional MGBC - Conventional, CBOB MGBC - Conventional, GTAB MGBC - Other Conventional Period-Unit: Monthly-Thousand Barrels Monthly-Thousand Barrels per Day Annual-Thousand Barrels Annual-Thousand Barrels per Day

452

Provides Total Tuition Charge to Source Contribution  

E-Print Network (OSTI)

Contribution 10 4 * 1,914 1,550 364 15 6 3 2,871 2,326 545 20 8 4 3,828 3,101 727 25 10 5 4,785 3,876 909 30 12,752 1,818 TGR 4-20 0-3 2,871 2,871 - % of time appointed Hours of Work/Week Units TAL Provides Total,742 4,651 1,091 75 30 5 4,785 3,876 909 80 32 4 3,828 3,101 727 85 34 3 2,871 2,326 545 90 36 3 2,871 2

Kay, Mark A.

453

Serck standard packages for total energy  

Science Journals Connector (OSTI)

Although the principle of combined heat and power generation is attractive, practical problems have hindered its application. In the U.K. the scope for ‘small scale’ combined heat and power (total energy) systems has been improved markedly by the introduction of new Electricity Board regulations which allow the operation of small a.c. generators in parallel with the mains low voltage supply. Following this change, Serck have developed a standard total energy unit, the CG100, based on the 2.25 1 Land Rover gas engine with full engine (coolant and exhaust gas) heat recovery. The unit incorporates an asynchronous generator, which utilising mains power for its magnetising current and speed control, offers a very simple means of generating electricity in parallel with the mains supply, without the need for expensive synchronising controls. Nominal output is 15 kW 47 kW heat; heat is available as hot water at temperatures up to 85°C, allowing the heat output to be utilised directly in low pressure hot water systems. The CG100 unit can be used in any application where an appropriate demand exists for heat and electricity, and the annual utilisation will give an acceptable return on capital cost; it produces base load heat and electricity, with LPHW boilers and the mains supply providing top-up/stand-by requirements. Applications include ‘residential’ use (hospitals, hotels, boarding schools, etc.), swimming pools and industrial process systems. The unit also operates on digester gas produced by anaerobic digestion of organic waste. A larger unit based on a six cylinder Ford engine (45 kWe output) is now available.

R. Kelcher

1984-01-01T23:59:59.000Z

454

Los Alamos PC estimating system  

SciTech Connect

The Los Alamos Cost Estimating System (QUEST) is being converted to run on IBM personal computers. This very extensive estimating system is capable of supporting cost estimators from many different and varied fields. QUEST does not dictate any fixed method for estimating. QUEST supports many styles and levels of detail estimating. QUEST can be used with or without data bases. This system allows the estimator to provide reports based on levels of detail defined by combining work breakdown structures. QUEST provides a set of tools for doing any type of estimate without forcing the estimator to use any given method. The level of detail in the estimate can be mixed based on the amount of information known about different parts of the project. The system can support many different data bases simultaneously. Estimators can modify any cost in any data base.

Stutz, R.A.; Lemon, G.D.

1987-01-01T23:59:59.000Z

455

Methodology for reconstruction of historical food consumption estimates  

SciTech Connect

This report was written to provide the food consumption methodology to be used in the Hanford Environmental Dose Reconstruction (HDER) Project beyond Phase I (which ended in July 1990). In Phase I (Callaway 1992), baseline food consumption estimates (grams per day) for 10 primary food types in the original 10-county study region were derived from the 1977--1978 National Food Consumption Survey (USDA 1983). The baseline estimates were multiplied by the 1945:1977 ratios to produce consumption estimates for 1945. This ratio backcasting method used in Phase I to project consumption estimates from 1977 back to 1945 will be refined using additional USDA data to improve and document the acceptability of the ratios for deriving backcast consumption estimates. The number of food types and population groups will be expanded to provide more disaggregated estimates of food consumption. Food consumption estimates will be developed for 1945, 1951, and 1957. A database of individual diets will be created from which daily diets will be randomly selected for use in the dose model to calculate doses for reference individuals.

Anderson, D.M.

1992-05-01T23:59:59.000Z

456

Methodology for EIA Weekly Underground Natural Gas Storage Estimates  

Weekly Natural Gas Storage Report (EIA)

Methodology for EIA Weekly Underground Natural Gas Storage Estimates Methodology for EIA Weekly Underground Natural Gas Storage Estimates Latest Update: November 25, 2008 This report consists of the following sections: Survey and Survey Processing - a description of the survey and an overview of the program Sampling - a description of the selection process used to identify companies in the survey Estimation - how the regional estimates are prepared from the collected data Computing the 5-year Averages, Maxima, Minima, and Year-Ago Values for the Weekly Natural Gas Storage Report - the method used to prepare weekly data to compute the 5-year averages, maxima, minima, and year-ago values for the weekly report Derivation of the Weekly Historical Estimates Database - a description of the process used to generate the historical database for the

457

Enantioselective total syntheses of acylfulvene, irofulven, and the agelastatins  

E-Print Network (OSTI)

I. Enantioselective Total Synthesis of (-)-Acylfulvene, and (-)-Irofulven We report the enantioselective total synthesis of (-)-acylfulvene and (-)-irofulven, which features metathesis reactions for the rapid assembly of ...

Siegel, Dustin S. (Dustin Scott), 1980-

2010-01-01T23:59:59.000Z

458

Price of Lake Charles, LA Liquefied Natural Gas Total Imports...  

Gasoline and Diesel Fuel Update (EIA)

Liquefied Natural Gas Total Imports (Dollars per Thousand Cubic Feet) Price of Lake Charles, LA Liquefied Natural Gas Total Imports (Dollars per Thousand Cubic Feet) Decade Year-0...

459

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

Annual Energy Outlook 2012 (EIA)

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

460

California Onshore Natural Gas Total Liquids Extracted in California...  

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

Total Liquids Extracted in California (Thousand Barrels) California Onshore Natural Gas Total Liquids Extracted in California (Thousand Barrels) Decade Year-0 Year-1 Year-2 Year-3...

Note: This page contains sample records for the topic "derived estimates total" 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

Analysis of Serum Total and Free PSA Using Immunoaffinity Depletion...  

NLE Websites -- All DOE Office Websites (Extended Search)

Serum Total and Free PSA Using Immunoaffinity Depletion Coupled to SRM: Correlation with Clinical Immunoassay Tests. Analysis of Serum Total and Free PSA Using Immunoaffinity...

462

Exploring Total Power Saving from High Temperature of Server Operations  

E-Print Network (OSTI)

Air Temperature Total system power (%) Cooling power (%)Total system power (%) Cooling power (%) JunctionTo simulate the cooling power consumption at different

Lai, Liangzhen; Chang, Chia-Hao; Gupta, Puneet

2014-01-01T23:59:59.000Z

463

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

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

National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 Presentation by Sunita Satyapal at the...

464

Deriving confinement via RG decimations  

E-Print Network (OSTI)

We present the general framework and building blocks of a recent derivation of the fact that the SU(2) LGT is in a confining phase for all values of the coupling $0 < \\beta < \\infty$, for space-time dimension $d \\leq 4$. The method employs approximate but explicitly computable RG decimations that are shown to constrain the exact partition function and order parameters from above and below, and flow from the weak to the strong coupling regime without encountering a fixed point.

E. T. Tomboulis

2007-10-10T23:59:59.000Z

465

Title, Location, Document Number Estimated Cost Description  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Moody to Lev, SUBJECT: NEPA 2012 APS for DOE-SRS, Dated: JAN 25 2012 Moody to Lev, SUBJECT: NEPA 2012 APS for DOE-SRS, Dated: JAN 25 2012 Title, Location, Document Number Estimated Cost Description EA Determination Date: uncertain Transmittal to State: uncertain EA Approval: uncertain FONSI: uncertain EA Determination Date: uncertain Transmittal to State: uncertain EA Approval: uncertain FONSI: uncertain Total Estimated Cost $65,000 Annual NEPA Planning Summary NEPA Reviews of Proposals to Implement Enterprise SRS Initiatives unknown The Savannah River Site Strategic Plan for 2011 - 2015 describes 12 initiatives that Enterprise SRS will pursue by applying SRS's management core competencies in nuclear materials. Implementation of new missions resulting from this effort will likely require NEPA review. However, until firm proposals are developed

466

MONITORED GEOLOGIC REPOSITORY LIFE CYCLE COST ESTIMATE ASSUMPTIONS DOCUMENT  

SciTech Connect

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

R.E. Sweeney

2001-02-08T23:59:59.000Z

467

Derivation of Hamiltonians for accelerators  

SciTech Connect

In this report various forms of the Hamiltonian for particle motion in an accelerator will be derived. Except where noted, the treatment will apply generally to linear and circular accelerators, storage rings, and beamlines. The generic term accelerator will be used to refer to any of these devices. The author will use the usual accelerator coordinate system, which will be introduced first, along with a list of handy formulas. He then starts from the general Hamiltonian for a particle in an electromagnetic field, using the accelerator coordinate system, with time t as independent variable. He switches to a form more convenient for most purposes using the distance s along the reference orbit as independent variable. In section 2, formulas will be derived for the vector potentials that describe the various lattice components. In sections 3, 4, and 5, special forms of the Hamiltonian will be derived for transverse horizontal and vertical motion, for longitudinal motion, and for synchrobetatron coupling of horizontal and longitudinal motions. Hamiltonians will be expanded to fourth order in the variables.

Symon, K.R.

1997-09-12T23:59:59.000Z

468

Total Crude Oil and Petroleum Products Exports  

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

Exports Exports Product: Total Crude Oil and Petroleum Products Crude Oil Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Isobutylene Other Liquids Hydrogen/Oxygenates/Renewables/Other Hydrocarbons Oxygenates (excl. Fuel Ethanol) Methyl Tertiary Butyl Ether (MTBE) Other Oxygenates Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Biomass-Based Diesel Motor Gasoline Blend. Comp. (MGBC) MGBC - Reformulated MGBC - Conventional Aviation Gasoline Blend. Comp. Finished Petroleum Products Finished Motor Gasoline Reformulated Gasoline Conventional Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm and under Distillate F.O., Greater than 15 to 500 ppm Distillate F.O., Greater than 500 ppm Residual Fuel Oil Naphtha for Petro. Feed. Use Other Oils Petro. Feed. Use Special Naphthas Lubricants Waxes Petroleum Coke Asphalt and Road Oil Miscellaneous Products Period-Unit: Monthly-Thousand Barrels Monthly-Thousand Barrels per Day Annual-Thousand Barrels Annual-Thousand Barrels per Day

469

Brush Busters: How to Estimate Costs for Controlling Small Mesquite  

E-Print Network (OSTI)

rapidly as plant size increases. ? Costs can escalate rapidly if you apply leaf or stem sprays using excessive pressure or nozzles with large orifices. ? Labor is usually a major component of total cost with Brush Busters methods. Costs escalate rapidly... and Figure 2 estimates costs for the stem spray method). Each figure consists of three graphs. The upper graph shows the cost for the spray only. The center graph shows total cost for spray plus labor at $6 per hour. The bottom graph shows total cost...

Ueckert, Darrell; McGinty, Allan

1999-04-15T23:59:59.000Z

470

THE DENSITY PROFILES OF MASSIVE, RELAXED GALAXY CLUSTERS. I. THE TOTAL DENSITY OVER THREE DECADES IN RADIUS  

SciTech Connect

Clusters of galaxies are excellent locations to probe the distribution of baryons and dark matter (DM) over a wide range of scales. We study a sample of seven massive (M {sub 200} = 0.4-2 Multiplication-Sign 10{sup 15} M {sub Sun }), relaxed galaxy clusters with centrally located brightest cluster galaxies (BCGs) at z = 0.2-0.3. Using the observational tools of strong and weak gravitational lensing, combined with resolved stellar kinematics within the BCG, we measure the total radial density profile, comprising both dark and baryonic matter, over scales of {approx_equal} 3-3000 kpc. We present Keck spectroscopy yielding seven new spectroscopic redshifts of multiply imaged sources and extended stellar velocity dispersion profiles of the BCGs. Lensing-derived mass profiles typically agree with independent X-ray estimates within {approx_equal} 15%, suggesting that departures from hydrostatic equilibrium are small and that the clusters in our sample (except A383) are not strongly elongated or compressed along the line of sight. The inner logarithmic slope {gamma}{sub tot} of the total density profile measured over r/r {sub 200} = 0.003-0.03, where {rho}{sub tot}{proportional_to}r{sup -{gamma}{sub t}{sub o}{sub t}}, is found to be nearly universal, with a mean ({gamma}{sub tot}) = 1.16 {+-} 0.05(random){sup +0.05} {sub -0.07} (systematic) and an intrinsic scatter {sigma}{sub {gamma}} < 0.13 (68% confidence). This is further supported by the very homogeneous shape of the observed velocity dispersion profiles, which are mutually consistent after a simple scaling. Remarkably, this slope agrees closely with high-resolution numerical simulations that contain only DM, despite the significant contribution of stellar mass on the scales we probe. The Navarro-Frenk-White profile characteristic of collisionless cold DM is a better description of the total mass density at radii {approx}> 5-10 kpc than that of DM alone. Hydrodynamical simulations that include baryons, cooling, and feedback currently provide a poorer match. We discuss the significance of our findings for understanding the physical processes governing the assembly of BCGs and cluster cores, particularly the influence of baryons on the inner DM halo.

Newman, Andrew B.; Ellis, Richard S. [Cahill Center for Astronomy and Astrophysics, California Institute of Technology, MS 249-17, Pasadena, CA 91125 (United States)] [Cahill Center for Astronomy and Astrophysics, California Institute of Technology, MS 249-17, Pasadena, CA 91125 (United States); Treu, Tommaso; Sand, David J. [Department of Physics, University of California, Santa Barbara, CA 93106 (United States)] [Department of Physics, University of California, Santa Barbara, CA 93106 (United States); Nipoti, Carlo [Astronomy Department, University of Bologna, via Ranzani 1, I-40127 Bologna (Italy)] [Astronomy Department, University of Bologna, via Ranzani 1, I-40127 Bologna (Italy); Richard, Johan [CRAL, Observatorie de Lyon, Universite Lyon 1, 9 Avenue Ch. Andre, F-69561 Saint Genis Laval Cedex (France)] [CRAL, Observatorie de Lyon, Universite Lyon 1, 9 Avenue Ch. Andre, F-69561 Saint Genis Laval Cedex (France); Jullo, Eric, E-mail: anewman@astro.caltech.edu [Laboratoire d'Astrophysique de Marseille, Universite d'Aix-Marseille and CNRS, UMR7326, 38 rue F. Joliot-Curie, F-13388 Marseille Cedex 13 (France)] [Laboratoire d'Astrophysique de Marseille, Universite d'Aix-Marseille and CNRS, UMR7326, 38 rue F. Joliot-Curie, F-13388 Marseille Cedex 13 (France)

2013-03-01T23:59:59.000Z

471

Isotopic Tracking of Hanford 300 Area Derived Uranium in the Columbia River  

SciTech Connect

Our objectives in this study are to quantify the discharge rate of uranium (U) to the Columbia River from the Hanford Site's 300 Area, and to follow that U down river to constrain its fate. Uranium from the Hanford Site has variable isotopic composition due to nuclear industrial processes carried out at the site. This characteristic makes it possible to use high-precision isotopic measurements of U in environmental samples to identify even trace levels of contaminant U, determine its sources, and estimate discharge rates. Our data on river water samples indicate that as much as 3.2 kg/day can enter the Columbia River from the 300 Area, which is only a small fraction of the total load of dissolved natural background U carried by the Columbia River. This very low-level of Hanford derived U can be discerned, despite dilution to < 1 percent of natural background U, 350 km downstream from the Hanford Site. These results indicate that isotopic methods can allow the amounts of U from the 300 Area of the Hanford Site entering the Columbia River to be measured accurately to ascertain whether they are an environmental concern, or are insignificant relative to natural uranium background in the Columbia River.

Christensen, John N.; Dresel, P. Evan; Conrad, Mark E.; Patton, Gregory W.; DePaolo, Donald J.

2010-10-31T23:59:59.000Z

472

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

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

1 " 1 " " (Estimates in Btu or Physical Units)" " "," "," "," "," "," "," "," "," ","Coke"," "," " " "," "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","LPG","(1000","(1000","Other(e)","Row" "Code(a)","Industry Groups and Industry","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","short tons)","short tons)","(trillion Btu)","Factors"

473

Table A37. Total Inputs of Energy for Heat, Power, and Electricity  

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

1",,,,,,,"Coal" 1",,,,,,,"Coal" " (Estimates in Btu or Physical Units)",,,,,,,"(excluding" ,,,,"Distillate",,,"Coal Coke" ,,"Net",,"Fuel Oil",,,"and" ,,"Electricity(a)","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" ,"Total","(million","Fuel Oil","Fuel","(billion","LPG","(1000 short","Other","Row" "End-Use Categories","(trillion Btu)","kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","tons)","(trillion Btu)","Factors"

474

Table A32. Total Consumption of Offsite-Produced Energy for Heat, Power, and  

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

Consumption of Offsite-Produced Energy for Heat, Power, and" Consumption of Offsite-Produced Energy for Heat, Power, and" " Electricity Generation by Value of Shipment Categories, Industry Group, and" " Selected Industries, 1991" " (Estimates in Trillion Btu)" ,,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,," ","-","-","-","-","-","-","RSE" ," "," "," ",,,,,500,"Row" "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"," "," "," "," "," "

475

Table A36. Total Inputs of Energy for Heat, Power, and Electricity  

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

,,,,,,,,"Coal" ,,,,,,,,"Coal" " Part 1",,,,,,,,"(excluding" " (Estimates in Btu or Physical Units)",,,,,"Distillate",,,"Coal Coke" ,,,,,"Fuel Oil",,,"and" ,,,"Net","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" "SIC",,"Total","Electricity(b)","Fuel Oil","Fuel","(billion","LPG","(1000 Short","Other","Row" "Code(a)","End-Use Categories","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","tons)","(trillion Btu)","Factors",

476

Cost Savings of Nuclear Power with Total Fuel Reprocessing  

SciTech Connect

The cost of fast reactor (FR) generated electricity with pyro-processing is estimated in this article. It compares favorably with other forms of energy and is shown to be less than that produced by light water reactors (LWR's). FR's use all the energy in natural uranium whereas LWR's utilize only 0.7% of it. Because of high radioactivity, pyro-processing is not open to weapon material diversion. This technology is ready now. Nuclear power has the same advantage as coal power in that it is not dependent upon a scarce foreign fuel and has the significant additional advantage of not contributing to global warming or air pollution. A jump start on new nuclear plants could rapidly allow electric furnaces to replace home heating oil furnaces and utilize high capacity batteries for hybrid automobiles: both would reduce US reliance on oil. If these were fast reactors fueled by reprocessed fuel, the spent fuel storage problem could also be solved. Costs are derived from assumptions on the LWR's and FR's five cost components: 1) Capital costs: LWR plants cost $106/MWe. FR's cost 25% more. Forty year amortization is used. 2) The annual O and M costs for both plants are 9% of the Capital Costs. 3) LWR fuel costs about 0.0035 $/kWh. Producing FR fuel from spent fuel by pyro-processing must be done in highly shielded hot cells which is costly. However, the five foot thick concrete walls have the advantage of prohibiting diversion. LWR spent fuel must be used as feedstock for the FR initial core load and first two reloads so this FR fuel costs more than LWR fuel. FR fuel costs much less for subsequent core reloads (< LWR fuel) if all spent fuel feedstock is from the fast reactor (i.e., Breeding Ratio =1). 4) Yucca Mountain storage of unprocessed LWR spent fuel is estimated as $360,000/MTHM. But this fuel can be processed to remove TRU for use as fast reactor fuel. The remaining fission products repository costs are only one fifth that of the original fuel. Storage of short half life fission products alone requires less storage time and long term integrity than LWR spent fuel (300 years storage versus 100,000 years.) 5) LWR decommissioning costs are estimated to be $0.3 x 10{sup 6}/MWe. The annual cost for a 40 year licensed plant would be 2.5 % of this or less if interest is taken into account. All plants will eventually have to replace those components which become radiation damaged. FR's should be designed to replace parts rather than decommission. The LWR costs are estimated to be 2.65 cents/kWh. FR costs are 2.99 cents/kWh for the first 7.5 years and 2.39 cents/kWh for the next 32.5 years. The average cost over forty years is 2.50 cents/kWh which is less than the LWR costs. These power costs are similar to coal power, are lower than gas, oil, and much lower than renewable power.(authors)

Solbrig, Charles W.; Benedict, Robert W. [Fuel Cycle Programs Division, Idaho National Laboratory, Idaho Falls, Idaho (United States)

2006-07-01T23:59:59.000Z

477

Estimating Cardiac Exposure From Breast Cancer Radiotherapy in Clinical Practice  

SciTech Connect

Purpose: To assess the value of maximum heart distance (MHD) in predicting the dose and biologically effective dose (BED) to the heart and the left anterior descending (LAD) coronary artery for left-tangential breast or chest wall irradiation. Methods and Materials: A total of 50 consecutive breast cancer patients given adjuvant left-tangential irradiation at a large U.K. radiotherapy center during 2006 were selected. For each patient, the following were derived using three-dimensional computed tomography (CT) planning: (1) mean dose and BED to the heart, (2) mean dose and BED to the LAD coronary artery, (3) MHD, (4) position of the CT slice showing the maximum area of the irradiated heart relative to the mid-plane slice, and (5) sternal and contralateral breast thickness (measures of body fat). Results: A strong linear correlation was found between the MHD and the mean heart dose. For every 1-cm increase in MHD, the mean heart dose increased by 2.9% on average (95% confidence interval 2.5-3.3). A strong linear-quadratic relationship was seen between the MHD and the mean heart BED. The mean LAD coronary artery dose and BED were also correlated with the MHD but the associations were weaker. These relationships were not affected by body fat. The mid-plane CT slice did not give a reliable assessment of cardiac irradiation. Conclusion: The MHD is a reliable predictor of the mean heart dose and BED and gives an approximate estimate of the mean LAD coronary artery dose and BED. Doses predicted by the MHD could help assess the risk of radiation-induced cardiac toxicity where individual CT-based cardiac dosimetry is not possible.

Taylor, C.W. [Clinical Trial Service Unit, Oxford (United Kingdom)], E-mail: carolyn.taylor@ctsu.ox.ac.uk; McGale, P. [Clinical Trial Service Unit, Oxford (United Kingdom); Povall, J.M.; Thomas, E.; Kumar, S.; Dodwell, D. [Yorkshire Centre for Clinical Oncology, St. James's Institute of Oncology, St. James's Hospital, Leeds (United Kingdom); Darby, S.C. [Clinical Trial Service Unit, Oxford (United Kingdom)

2009-03-15T23:59:59.000Z

478

"Table A10. Total Consumption of LPG, Distillate Fuel Oil, and Residual Fuel"  

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

0. Total Consumption of LPG, Distillate Fuel Oil, and Residual Fuel" 0. Total Consumption of LPG, Distillate Fuel Oil, and Residual Fuel" " Oil for Selected Purposes by Census Region and Economic Characteristics of the" " Establishment, 1991" " (Estimates in Barrels per Day)" ,,,," Inputs for Heat",,," Primary Consumption" " "," Primary Consumption for all Purposes",,," Power, and Generation of Electricity",,," for Nonfuel Purposes",,,"RSE" ," ------------------------------------",,," ------------------------------------",,," -------------------------------",,,"Row" "Economic Characteristics(a)","LPG","Distillate(b)","Residual","LPG","Distillate(b)","Residual","LPG","Distillate(b)","Residual","Factors"

479

Parameter Estimation Through Ignorance  

E-Print Network (OSTI)

Dynamical modelling lies at the heart of our understanding of physical systems. Its role in science is deeper than mere operational forecasting, in that it allows us to evaluate the adequacy of the mathematical structure of our models. Despite the importance of model parameters, there is no general method of parameter estimation outside linear systems. A new relatively simple method of parameter estimation for nonlinear systems is presented, based on variations in the accuracy of probability forecasts. It is illustrated on the Logistic Map, the Henon Map and the 12-D Lorenz96 flow, and its ability to outperform linear least squares in these systems is explored at various noise levels and sampling rates. As expected, it is more effective when the forecast error distributions are non-Gaussian. The new method selects parameter values by minimizing a proper, local skill score for continuous probability forecasts as a function of the parameter values. This new approach is easier to implement in practice than alternative nonlinear methods based on the geometry of attractors or the ability of the model to shadow the observations. New direct measures of inadequacy in the model, the "Implied Ignorance" and the information deficit are introduced.

Hailiang Du; Leonard A. Smith

2012-06-06T23:59:59.000Z

480

County-level Estimates for Carbon Distribution in U.S. Croplands, 1990-2005  

NLE Websites -- All DOE Office Websites (Extended Search)

Metadata Metadata Method of Estimation The United Sates Department of Agriculture (USDA), National Agricultural Statistics Survey (NASS) produces estimates of crop yields per county per year. These yield estimates can be converted to carbon by converting units reported by NASS to one standard unit (kg), converting to dry matter, and multiplying by a carbon content factor of 0.45 (Brady and Weil, 1996). Yield estimates are divided by the harvest index to estimate total above-ground biomass. Multiplying aboveground biomass with the root:shoot ratio provides an estimate of below-ground biomass. Finally, summing above- and below-ground biomass provides an estimate for total net primary productivity (NPP). This method follows approaches used by Prince et al. (2001), Hicke and Lobell (2004), and Hicke et al. (2004). A mean harvest

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481

PREDICTION OF THE PROTON-TO-TOTAL TURBULENT HEATING IN THE SOLAR WIND  

SciTech Connect

This paper employs a recent turbulent heating prescription to predict the ratio of proton-to-total heating due to the kinetic dissipation of Alfvenic turbulence as a function of heliocentric distance. Comparing to a recent empirical estimate for this turbulent heating ratio in the high-speed solar wind, the prediction shows good agreement with the empirical estimate for R {approx}> 0.8 AU, but predicts less ion heating than the empirical estimate at smaller heliocentric radii. At these smaller radii, the turbulent heating prescription, calculated in the gyrokinetic limit, fails because the turbulent cascade is predicted to reach the proton cyclotron frequency before Landau damping terminates the cascade. These findings suggest that the turbulent cascade can reach the proton cyclotron frequency at R {approx}< 0.8 AU, leading to a higher level of proton heating than predicted by the turbulent heating prescription in the gyrokinetic limit. At larger heliocentric radii, R {approx}> 0.8 AU, this turbulent heating prescription contains all of the necessary physical mechanisms needed to reproduce the empirically estimated proton-to-total heating ratio.

Howes, G. G. [Department of Physics and Astronomy, University of Iowa, Iowa City, IA 52242 (United States)

2011-09-01T23:59:59.000Z

482

Binder enhanced refuse derived fuel  

DOE Patents (OSTI)

A refuse derived fuel (RDF) pellet having about 11% or more particulate calcium hydroxide which is utilized in a combustionable mixture. The pellets are used in a particulate fuel bring a mixture of 10% or more, on a heat equivalent basis, of the RDF pellet which contains calcium hydroxide as a binder, with 50% or more, on a heat equivalent basis, of a sulphur containing coal. Combustion of the mixture is effective to produce an effluent gas from the combustion zone having a reduced SO.sub.2 and polycyclic aromatic hydrocarbon content of effluent gas from similar combustion materials not containing the calcium hydroxide.

Daugherty, Kenneth E. (Lewisville, TX); Venables, Barney J. (Denton, TX); Ohlsson, Oscar O. (Naperville, IL)

1996-01-01T23:59:59.000Z

483

Assessment of terrigenous organic carbon input to the total organic carbon in sediments from Scottish transitional waters Hydrology and Earth System Sciences, 6(6), 959970 (2002) EGS  

E-Print Network (OSTI)

Assessment of terrigenous organic carbon input to the total organic carbon in sediments from of terrigenous organic carbon input to the total organic carbon in sediments from Scottish transitional waters This paper addresses the assessment of terrestrially derived organic carbon in sediments from two Scottish

Paris-Sud XI, Université de

484

Determination of Total Biodiesel Fatty Acid Methyl, Ethyl Esters, and Hydrocarbon Types in Diesel Fuels by Supercritical Fluid Chromatography-Flame Ionization Detection  

Science Journals Connector (OSTI)

......Research and Engineering, Paulsboro...determining total biodiesel methyl and...in diesel fuels by supercritical...mixture. Introduction The proposed use of biodiesel esters derived...as diesel fuel blending...of Total Biodiesel Fatty Acid...in Diesel Fuels by Supercritical...Research and Engineering, Paulsboro......

John W. Diehl; Frank P. DiSanzo

485

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

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

2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" 2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" " Categories and Presence of General Technologies and Cogeneration Technologies, 1994" " (Estimates in Trillion Btu)" ,,,,"Employment Size(a)" ,,,,,,,,"RSE" ,,,,,,,"1000 and","Row" "General/Cogeneration Technologies","Total","Under 50","50-99","100-249","250-499","500-999","Over","Factors" "RSE Column Factors:",0.5,2,2.1,1,0.7,0.7,0.9 "One or More General Technologies Present",14601,387,781,2054,2728,3189,5462,3.1 " Computer Control of Building Environment (b)",5079,64,116,510,802,1227,2361,5

486

Locating-total domination in claw-free cubic graphs  

Science Journals Connector (OSTI)

In this paper, we continue the study of locating-total domination in graphs. A set S of vertices of a graph G is a total dominating set of 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 . A claw-free graph is a graph that does not contain K 1 , 3 as an induced subgraph. We show that the locating-total domination number of a claw-free cubic graph is at most one-half its order and we characterize the graphs achieving this bound.

Michael A. Henning; Christian Löwenstein

2012-01-01T23:59:59.000Z

487

Statistical error in a chord estimator of correlation dimension: The ``rule of five``  

SciTech Connect

The statistical precision of a chord method for estimating dimension from a correlation integral is derived. The optimal chord length is determined, and a comparison is made to other estimators. The simple chord estimator is only 25% less precise than the optimal estimator which uses the full resolution and full range of the correlation integral. The analytic calculations are based on the hypothesis that all pairwise distances between the points in the embedding space are statistically independent. The adequacy of this approximation is assessed numerically, and a surprising result is observed in which dimension estimators can be anomalously precise for sets with reasonably uniform (nonfractal) distributions.

Theiler, J. [Los Alamos National Lab., NM (United States); Lookman, T. [University of Western Ontario, London, ON (Canada). Dept. of Applied Mathematics

1992-09-01T23:59:59.000Z

488

Statistical error in a chord estimator of correlation dimension: The rule of five''  

SciTech Connect

The statistical precision of a chord method for estimating dimension from a correlation integral is derived. The optimal chord length is determined, and a comparison is made to other estimators. The simple chord estimator is only 25% less precise than the optimal estimator which uses the full resolution and full range of the correlation integral. The analytic calculations are based on the hypothesis that all pairwise distances between the points in the embedding space are statistically independent. The adequacy of this approximation is assessed numerically, and a surprising result is observed in which dimension estimators can be anomalously precise for sets with reasonably uniform (nonfractal) distributions.

Theiler, J. (Los Alamos National Lab., NM (United States)); Lookman, T. (University of Western Ontario, London, ON (Canada). Dept. of Applied Mathematics)

1992-09-01T23:59:59.000Z

489

Training Signal Design for Estimation of Correlated MIMO Channels with Colored  

E-Print Network (OSTI)

Training Signal Design for Estimation of Correlated MIMO Channels with Colored Interference Yong error (MMSE) channel estimator is derived and the optimal training sequences are designed based in the construction of the optimal training sequences. We also design an efficient scheme to feed back the required

Hager, William

490

OnLine IPA Gradient Estimators in Stochastic Continuous Fluid Models  

E-Print Network (OSTI)

On­Line IPA Gradient Estimators in Stochastic Continuous Fluid Models Yorai Wardi # School Perturbation Analysis (IPA) to loss­related and workload­ related metrics in a class of Stochastic Flow Models parameters of interest, such as bu#er size, service rate and inflow rate. The IPA estimators derived

491

Cost Estimating, Analysis, and Standardization  

Directives, Delegations, and Requirements

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

1984-11-02T23:59:59.000Z

492

Short communication Satellite-derived surface water pCO2 and airsea CO2 fluxes  

E-Print Network (OSTI)

Short communication Satellite-derived surface water pCO2 and air­sea CO2 fluxes in the northern for the estimation of the partial pressure of carbon dioxide (pCO2) and air­sea CO2 fluxes in the northern South), respectively, the monthly pCO2 fields were computed. The derived pCO2 was compared with the shipboard pCO2

493

Multiple phase estimation for arbitrary pure states under white noise  

E-Print Network (OSTI)

In any realistic quantum metrology scenarios, the ultimate precision in the estimation of parameters is limited not only by the so-called Heisenberg scaling, but also the environmental noise encountered by the underlying system. In the context of quantum estimation theory, it is of great significance to carefully evaluate the impact of a specific type of noise on the corresponding quantum Fisher information (QFI) or quantum Fisher information matrix (QFIM). Here we investigate the multiple phase estimation problem for a natural parametrization of arbitrary pure states under white noise. We obtain the explicit expression of the symmetric logarithmic derivative (SLD) and hence the analytical formula of QFIM. Moreover, the attainability of the quantum Cram\\'{e}r-Rao bound (QCRB) is confirmed by the commutability of SLDs and the optimal estimators are elucidated for the experimental purpose. These findings generalize previously known partial results and highlight the role of white noise in quantum metrology.

Yao Yao; Li Ge; Xing Xiao; Xiaoguang Wang; C. P. Sun

2014-09-08T23:59:59.000Z

494

THE IMPORTANCE OF PHYSICAL MODELS FOR DERIVING DUST MASSES AND GRAIN SIZE DISTRIBUTIONS IN SUPERNOVA EJECTA. I. RADIATIVELY HEATED DUST IN THE CRAB NEBULA  

SciTech Connect

Recent far-infrared (IR) observations of supernova remnants (SNRs) have revealed significantly large amounts of newly condensed dust in their ejecta, comparable to the total mass of available refractory elements. The dust masses derived from these observations assume that all the grains of a given species radiate at the same temperature, regardless of the dust heating mechanism or grain radius. In this paper, we derive the dust mass in the ejecta of the Crab Nebula, using a physical model for the heating and radiation from the dust. We adopt a power-law distribution of grain sizes and two different dust compositions (silicates and amorphous carbon), and calculate the heating rate of each dust grain by the radiation from the pulsar wind nebula. We find that the grains attain a continuous range of temperatures, depending on their size and composition. The total mass derived from the best-fit models to the observed IR spectrum is 0.019-0.13 M{sub Sun }, depending on the assumed grain composition. We find that the power-law size distribution of dust grains is characterized by a power-law index of 3.5-4.0 and a maximum grain size larger than 0.1 {mu}m. The grain sizes and composition are consistent with what is expected for dust grains formed in a Type IIP supernova (SN). Our derived dust mass is at least a factor of two less than the mass reported in previous studies of the Crab Nebula that assumed more simplified two-temperature models. These models also require a larger mass of refractory elements to be locked up in dust than was likely available in the ejecta. The results of this study show that a physical model resulting in a realistic distribution of dust temperatures can constrain the dust properties and affect the derived dust masses. Our study may also have important implications for deriving grain properties and mass estimates in other SNRs and for the ultimate question of whether SNe are major sources of dust in the Galactic interstellar medium and in external galaxies.

Temim, Tea; Dwek, Eli, E-mail: tea.temim@nasa.gov [Observational Cosmology Lab, Code 665, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)

2013-09-01T23:59:59.000Z

495

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E-Print Network (OSTI)

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Collett Jr., Jeffrey L.

496

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E-Print Network (OSTI)

surface elevation [Holland et al., 2011] and can substantially influence mass balance calculations based

Howat, Ian M.

497

Using sensitivity derivatives for design and parameter estimation in an atmospheric plasma discharge simulation  

Science Journals Connector (OSTI)

The problem of applying sensitivity analysis to a one-dimensional atmospheric radio frequency plasma discharge simulation is considered. A fluid simulation is used to model an atmospheric pressure radio frequency helium discharge with a small nitrogen ... Keywords: Adjoint, Direct differentiation, Optimization, Plasma discharge, Sensitivity analysis, Uncertainty analysis

Kyle J. Lange; W. Kyle Anderson

2010-08-01T23:59:59.000Z

498

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E-Print Network (OSTI)

in the solar wind, the magnetosheath, and the plasmashere by the use of CIS ion density and WHISPER electron, in operation from early 2001 in a high inclination orbit, have provided data over nearly half of the 11-year are in the magnetotail from approximately beginning of July to end of October, and the high inclination orbit makes

California at Berkeley, University of

499

Comparison of Precision Orbit Derived Density Estimates for CHAMP and GRACE Satellites  

E-Print Network (OSTI)

. These density variations are the result of many factors; however, the Sun is the main driver in upper atmospheric density changes. The Sun influences the densities in Earth's atmosphere through solar heating of the atmosphere, as well as through geomagnetic...

Fattig, Eric

2011-04-21T23:59:59.000Z

500

A study on real estate derivatives  

E-Print Network (OSTI)

All major asset classes including stocks and bonds have a well developed derivative market. Derivatives enable counterparties to reflect a view on a particular market, without having to trade the underlying asset. This ...

Lim, Jong Yoon, S.M. Massachusetts Institute of Technology

2006-01-01T23:59:59.000Z