Sample records for derived estimates total

  1. Precise attention filters for Weber contrast derived from centroid estimations

    E-Print Network [OSTI]

    Sperling, George

    Precise attention filters for Weber contrast derived from centroid estimations Department attention filters for Weber contrast derived from centroid estimations. Journal of Vision, 10(10):20, 1

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

    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

  3. Regional Estimation of Total Recharge to Ground Water in Nebraska

    E-Print Network [OSTI]

    Szilagyi, Jozsef

    )over long periods of time when the potential change in ground water storage becomes negligible compared storage other than discharge to streams. One such loss term is evapotranspiration (ET) from ground waterRegional Estimation of Total Recharge to Ground Water in Nebraska by Jozsef Szilagyi1m2,F. Edwin

  4. Estimating Derivatives of Noisy Simulations1

    E-Print Network [OSTI]

    2010-11-02T23:59:59.000Z

    derivative f (x0;p) by examining the errors. E(h) = (f(x0 + hp) ... Following [13], we scale the matrices by their diagonals and randomly select the base point x0 and ...

  5. Uncertainty estimates for derivatives and intercepts

    SciTech Connect (OSTI)

    Clark, E.L.

    1990-01-01T23:59:59.000Z

    Straight line least squares fits of experimental data are widely used in the analysis of test results to provide derivatives and intercepts. A method for evaluating the uncertainty in these parameters is described. The method utilizes conventional least squares results and is applicable to experiments where the independent variable is controlled, but not necessarily free of error. A Monte Carlo verification of the method is given 7 refs., 2 tabs.

  6. Improving total column ozone retrievals by using cloud pressures derived from Raman scattering in the UV

    E-Print Network [OSTI]

    Joiner, Joanna

    Improving total column ozone retrievals by using cloud pressures derived from Raman scattering resolution, coverage, and sampling of the Aura satellite ozone monitoring instrument (OMI), as compared with the total ozone mapping spectrometer (TOMS) should allow for improved ozone retrievals. By default, the TOMS

  7. Estimating and decomposing total uncertainty for survey-based abundance estimates of Norwegian spring-spawning herring

    E-Print Network [OSTI]

    Aldrin, Magne

    the Norwegian coast, feed in the Norwegian Sea and adjacent areas, and overwinter in various partsEstimating and decomposing total uncertainty for survey-based abundance estimates of Norwegian uncertainty for survey-based abundance estimates of Norwegian spring-spawning herring. ­ ICES Journal

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

    SciTech Connect (OSTI)

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

    2008-03-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Barziza, Daniel Eugene

    1998-01-01T23:59:59.000Z

    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...

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

    E-Print Network [OSTI]

    Jaramillo, Francisco

    1993-01-01T23:59:59.000Z

    ESTIMATION OF BODY COMPOSITION IN CHANNEL CATFISH UTILIZING RELATIVE WEIGHT AND TOTAL BODY ELECTRICAL CONDUCTIVITY A Thesis by FRANCISCO JARAMILLO, JR. Submitted to the Office of Graduate Studies of Texas A&M University in partial... fulfillment of the requirements for the degree of MASTER OF SCIENCE August 1993 Major Subject: Wildlife and Fisheries Sciences ESTIMATION OF BODY COMPOSITION IN CHANNEL CATFISH UTILIZING RELATIVE WEIGHT AND TOTAL BODY ELECTRICAL CONDUCTIVITY A Thesis...

  11. A note on wavelet estimation of the derivatives of a regression function in a

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    A note on wavelet estimation of the derivatives of a regression function in a random design setting of the derivatives of a regression function in the nonparametric regression model with random design. New wavelet. Keywords and phrases: Nonparametric regression, Derivatives function estimation, Wavelets, Besov balls

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

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

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

    E-Print Network [OSTI]

    Cohen, Ronald C.

    Summary We estimated total ecosystem respiration from a ponderosa pine (Pinus ponderosa Dougl. ex, 1998. We apportioned ecosystem respi- ration among heterotrophic, root, stem and foliage based on re respiration component at selected sampling points, and scaled the mea- surements up to the ecosystem based

  14. Improved estimates of the total correlation energy in the ground state of the water molecule

    E-Print Network [OSTI]

    Anderson, James B.

    Improved estimates of the total correlation energy in the ground state of the water molecule Arne National Laboratory, Richland, Washington 99352 Received 1 October 1996; accepted 5 February 1997 Two new calculations of the electronic energy of the ground state of the water molecule yield energies lower than those

  15. Deriving Atmospheric Density Estimates Using Satellite Precision Orbit Ephemerides

    E-Print Network [OSTI]

    Hiatt, Andrew Timothy

    2009-01-01T23:59:59.000Z

    due to atmospheric drag m/s2 ap geomagnetic 3-hourly planetary equivalent amplitude index gamma, Telsa, or kg s m-1 A satellite cross-sectional area m2 Ap geomagnetic daily planetary amplitude index gamma, Telsa, or kg s m-1 B B? estimated...

  16. Method used to estimate screening-level Total Failure Probability for human error events

    SciTech Connect (OSTI)

    Burns, R.S.; Turner, J.H. [Oak Ridge National Lab., TN (United States). Engineering Technology Div.

    1994-12-31T23:59:59.000Z

    This document briefly describes the method used to estimate a screening value for the Total Failure Probability (F{sub T}) of human error events that are identified in the fault trees which describe potential liquid UF{sub 6} release accidents at two US Gaseous Diffusion Plants. A discussion is provided of the assumptions, limitations, and overall logic of the F{sub T} assignment method, and a description is presented of how the method is employed. The description herein presents the screening technique used to quantify human errors in the accident analysis portion of the Gaseous Diffusion Plant Safety Analysis Report Upgrade Program. Specifically, the basic events analyzed here are given in the fault trees for one facility at the Paducah Gaseous Diffusion Plant (PGDP) and one at the Portsmouth Gaseous Diffusion Plant (PORTS). These plants are primarily chemical processing facilities that deal with a slightly radioactive process gas, low-enriched uranium hexafluoride (UF{sub 6}). A Human Reliability Analysis (HRA) was not accomplished while drawing the fault trees; the accomplishment of an HRA would be determined by the overall study results. The method described herein provides a framework within which a conservative estimate of human error probability can be made at the screening level for use in the event trees and fault trees.

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

    SciTech Connect (OSTI)

    Mazonakis, Michalis; Berris, Theoharris; Damilakis, John [Department of Medical Physics, Faculty of Medicine, University of Crete, P.O. Box 2208, 71003 Iraklion, Crete (Greece)] [Department of Medical Physics, Faculty of Medicine, University of Crete, P.O. Box 2208, 71003 Iraklion, Crete (Greece); Lyraraki, Efrossyni [Department of Radiotherapy and Oncology, University Hospital of Iraklion, 71110 Iraklion, Crete (Greece)] [Department of Radiotherapy and Oncology, University Hospital of Iraklion, 71110 Iraklion, Crete (Greece)

    2013-10-15T23:59:59.000Z

    Purpose: Heterotopic ossification (HO) is a frequent complication following total hip arthroplasty. This study was conducted to calculate the radiation dose to organs-at-risk and estimate the probability of cancer induction from radiotherapy for HO prophylaxis.Methods: Hip irradiation for HO with a 6 MV photon beam was simulated with the aid of a Monte Carlo model. A realistic humanoid phantom representing an average adult patient was implemented in Monte Carlo environment for dosimetric calculations. The average out-of-field radiation dose to stomach, liver, lung, prostate, bladder, thyroid, breast, uterus, and ovary was calculated. The organ-equivalent-dose to colon, that was partly included within the treatment field, was also determined. Organ dose calculations were carried out using three different field sizes. The dependence of organ doses upon the block insertion into primary beam for shielding colon and prosthesis was investigated. The lifetime attributable risk for cancer development was estimated using organ, age, and gender-specific risk coefficients.Results: For a typical target dose of 7 Gy, organ doses varied from 1.0 to 741.1 mGy by the field dimensions and organ location relative to the field edge. Blocked field irradiations resulted in a dose range of 1.4–146.3 mGy. The most probable detriment from open field treatment of male patients was colon cancer with a high risk of 564.3 × 10{sup ?5} to 837.4 × 10{sup ?5} depending upon the organ dose magnitude and the patient's age. The corresponding colon cancer risk for female patients was (372.2–541.0) × 10{sup ?5}. The probability of bladder cancer development was more than 113.7 × 10{sup ?5} and 110.3 × 10{sup ?5} for males and females, respectively. The cancer risk range to other individual organs was reduced to (0.003–68.5) × 10{sup ?5}.Conclusions: The risk for cancer induction from radiation therapy for HO prophylaxis after total hip arthroplasty varies considerably by the treatment parameters, organ site in respect to treatment volume and patient's gender and age. The presented risk estimates may be useful in the follow-up studies of irradiated patients.

  18. New velocity map and mass-balance estimate of Mertz Glacier, East Antarctica, derived from Landsat

    E-Print Network [OSTI]

    Berthier, Etienne

    streams hasbeen measured recently. Pine Island Glacier accelerated by 18 Æ2% between 1992 and 2000 (Rignot-moving glaciers. Repeat visible or near-infrared images of the same area can be used to track the displace- mentNew velocity map and mass-balance estimate of Mertz Glacier, East Antarctica, derived from Landsat

  19. Derivative-free optimization for parameter estimation in computational nuclear physics

    E-Print Network [OSTI]

    Stefan M. Wild; Jason Sarich; Nicolas Schunck

    2014-09-17T23:59:59.000Z

    We consider optimization problems that arise when estimating a set of unknown parameters from experimental data, particularly in the context of nuclear density functional theory. We examine the cost of not having derivatives of these functionals with respect to the parameters. We show that the POUNDERS code for local derivative-free optimization obtains consistent solutions on a variety of computationally expensive energy density functional calibration problems. We also provide a primer on the operation of the POUNDERS software in the Toolkit for Advanced Optimization.

  20. Estimating crop net primary production using inventory data and MODIS-derived parameters

    SciTech Connect (OSTI)

    Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; Izaurralde, Roberto C.

    2013-06-03T23:59:59.000Z

    National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois in years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

    technology at coal-fired power plants, total SO 2 emissionsemission coefficients for electric power and direct-use coal.Coal Similarly, without improvements in sulfur capture at power plants, SO 2 emissions

  3. Table C4. Total End-Use Energy Consumption Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. Coal Stocks at Manufacturing:: TotalC4. Total

  4. Table E9. Total End-Use Energy Expenditure Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4.E9. Total End-Use

  5. Satellite-derived estimates of forest leaf area index in southwest Western Australia are not tightly coupled to

    E-Print Network [OSTI]

    Montana, University of

    Satellite-derived estimates of forest leaf area index in southwest Western Australia Engineering, University of Western Australia, Nedlands, WA 6009, Australia, Department of Forest Ecosystems and Environment, University of Western Australia, Nedlands, WA 6009, Australia, §Numerical Terradynamics

  6. Table E1. Primary Energy, Electricity, and Total Energy Price Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks DefinitionsWeekly.

  7. Table E2. Total End-Use Energy Price Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4. Electric Power6.E2.

  8. Table E8. Primary Energy, Electricity, and Total Energy Expenditure Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4.

  9. Nonparametric Estimation of Derivative Functions with Data-Driven Optimally Selected Smoothing Parameters

    E-Print Network [OSTI]

    Yao, Shuang

    2014-07-30T23:59:59.000Z

    (x) = h 2B(x) + ? V (x) nh3 Zn + op(h 2 + (nh3)?1/2), (2.4) where B(x) = ( µ4?µ22 2µ2 ) g??(x)f ?(x) f(x) + µ4g???(x) 6µ2 , V (x) = ?2?2(x)/[µ22f(x)], Zn is a mean zero, unit variance random variable (Zn d? N(0, 1) under some standard regularity conditions... of ?ˆLL(x), and choose the smoothing parameter h to minimize a weighted version of the integrated (leading) squared bias and variance of ?ˆLL(x). This approach requires one to obtain initial estimates of g(x) and f(x) and their derivative functions up...

  10. Table 17. Estimated natural gas plant liquids and dry natural gas content of total wet natural gas proved reserves, 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14Total Delivered Residential Energy Consumption,Estimated

  11. Overpressure prediction by mean total stress estimate using well logs for compressional environments with strike-slip or reverse faulting stress state

    E-Print Network [OSTI]

    Ozkale, Aslihan

    2007-04-25T23:59:59.000Z

    OVERPRESSURE PREDICTION BY MEAN TOTAL STRESS ESTIMATE USING WELL LOGS FOR COMPRESSIONAL ENVIRONMENTS WITH STRIKE-SLIP OR REVERSE FAULTING STRESS STATE A Thesis by ASLIHAN OZKALE Submitted to the Office of Graduate Studies... of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE December 2006 Major Subject: Petroleum Engineering OVERPRESSURE PREDICTION BY MEAN TOTAL STRESS ESTIMATE USING WELL LOGS...

  12. A depth-derived Pleistocene age model: Uncertainty estimates, sedimentation variability, and nonlinear climate change

    E-Print Network [OSTI]

    Huybers, Peter

    Geology and Geophysics: Geomagnetism (1550); 3220 Mathematical Geophysics: Nonlinear dynamics; 4267 of ages to measurements and events recorded in marine and ice cores as well as to a variety of isolated. [3] The currently favored method for estimating Pleisto- cene age is orbital tuning [e.g., Imbrie et

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

    E-Print Network [OSTI]

    Fattig, Eric

    2011-04-21T23:59:59.000Z

    NOMENCLATURE Symbol Definition Units draga acceleration vector due to atmospheric drag m/s 2 ap geomagnetic 3-hourly planetary equivalent amplitude index gamma, Telsa, or kg s m-1 A satellite cross-sectional area m2 Ap geomagnetic daily planetary... amplitude index gamma, Telsa, or kg s m-1 BB estimated ballistic coefficient correction ~ BC ballistic coefficient m2/kg Dc satellite drag coefficient ~ d cross correlation delay F10.7 daily solar radio flux measured at 10.7 cm wavelength SFU 10.7F...

  14. Worldwide estimates and bibliography of net primary productivity derived from pre-1982 publications

    SciTech Connect (OSTI)

    Esser, G. [Justus-Liebig-Univ., Giessen (Germany). Inst. for Plant Ecology; Lieth, H.F.H. [Univ. of Osnabrueck (Germany). Systems Research Group; Scurlock, J.M.O.; Olson, R.J. [Oak Ridge National Lab., TN (United States)

    1997-10-01T23:59:59.000Z

    An extensive compilation of more than 700 field estimates of net primary productivity of natural and agricultural ecosystems worldwide was synthesized in Germany in the 1970s and early 1980s. Although the Osnabrueck data set has not been updated since the 1980s, it represents a wealth of information for use in model development and validation. This report documents the development of this data set, its contents, and its recent availability on the Internet from the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics. Caution is advised in using these data, which necessarily include assumptions and conversions that may not be universally applicable to all sites.

  15. 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]

    Stukey, Jared D.

    2011-02-22T23:59:59.000Z

    The overall goal of this study was to develop a framework for using airborne lidar to derive inputs for the SPB infestation growth model TAMBEETLE. The specific objectives were (1) to estimate individual tree characteristics of XY location...

  16. Table ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2012, United States

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4.E9. Total End-UseET1.

  17. Preliminary estimates of the total-system cost for the restructured program: An addendum to the May 1989 analysis of the total-system life cycle cost for the Civilian Radioactive Waste Management Program

    SciTech Connect (OSTI)

    NONE

    1990-12-01T23:59:59.000Z

    The total-system life-cycle cost (TSLCC) analysis for the Department of Energy`s (DOE) Civilian Radioactive Waste Management Program is an ongoing activity that helps determine whether the revenue-producing mechanism established by the Nuclear Waste Policy Act of 1982 - a fee levied on electricity generated and sold by commercial nuclear power plants - is sufficient to cover the cost of the program. This report provides cost estimates for the sixth annual evaluation of the adequacy of the fee. The costs contained in this report represent a preliminary analysis of the cost impacts associated with the Secretary of Energy`s Report to Congress on Reassessment of the Civilian Radioactive Waste Management Program issued in November 1989. The major elements of the restructured program announced in this report which pertain to the program`s life-cycle costs are: a prioritization of the scientific investigations program at the Yucca Mountain candidate site to focus on identification of potentially adverse conditions, a delay in the start of repository operations until 2010, the start of limited waste acceptance at the monitored retrievable storage (MRS) facility in 1998, and the start of waste acceptance at the full-capability MRS facility in 2,000. Based on the restructured program, the total-system cost for the system with a repository at the candidate site at Yucca Mountain in Nevada, a facility for monitored retrievable storage (MRS), and a transportation system is estimated at $26 billion (expressed in constant 1988 dollars). In the event that a second repository is required and is authorized by the Congress, the total-system cost is estimated at $34 to $35 billion, depending on the quantity of spent fuel and high-level waste (HLW) requiring disposal. 17 figs., 17 tabs.

  18. Table 17. Estimated natural gas plant liquids and dry natural gas content of total wet natural gas proved reserves, 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14Total Delivered Residential Energy

  19. Derived Annual Estimates

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469Decade Year-0Cubic Feet)Delaware2 0.2 0.288-1998

  20. Derived Annual Estimates

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469Decade Year-0Cubic Feet)Delaware2 0.2

  1. The picoplankton contribution to the total biomass has not been considered when it is estimated using remote sensors. In this work, In situ chlorophyll-a values were

    E-Print Network [OSTI]

    Gilbes, Fernando

    aportación del picoplancton a la biomasa total del fitoplancton no ha sido considerada cuando esta es (contribuyendo un 60-85% de la biomasa total del fitoplancton y un 61-77% de la absorción de la luz por

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

    Office of Environmental Management (EM)

    Office - Oak Ridge, TN Contract Name: Transuranic Waste Processing Contract Sep-14 2,433,940 Cost Plus Award Fee 150,664,017 Fee Information Minimum Fee 2,039,246 Maximum Fee...

  3. 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 1,640,839,964 Fee Information Minimum Fee 0 EM Contractor Fee Site:...

  4. 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...

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

    Office of Environmental Management (EM)

    FY2011 FY2012 Fee Information Minimum Fee Maximum Fee September 2014 Contract Number: Cost Plus Incentive Fee Contractor: 3,260,603,765 Contract Period: EM Contractor Fee Site:...

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

    Office of Environmental Management (EM)

    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...

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

    Office of Environmental Management (EM)

    - September 2015 September 2014 Contractor: Contract Number: Contract Type: Idaho Treatment Group LLC DE-EM0001467 Cost Plus Award Fee Fee Information 444,161,295 Contract Period:...

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

    Office of Environmental Management (EM)

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

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

    Office of Environmental Management (EM)

    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...

  10. 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 2,366,753,325 Fee Information 0 Maximum Fee 319,511,699...

  11. 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...

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

    Office of Environmental Management (EM)

    & Wilcox Conversion Services, LLC Contract Number: DE-AC30-11CC40015 Contract Type: Cost Plus Award Fee Fee Available 4,324,912 408,822,369 Contract Period: December 2010 -...

  13. 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...

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

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33Frequently AskedEnergyIssuesEnergy SolarRadioactiveI DisposalFive FY2002 $15,829 FY2003

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

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33Frequently AskedEnergyIssuesEnergy SolarRadioactiveI DisposalFive FY2002 $15,829 FY2003 FY2008

  16. TOTAL M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total Spring 2010

    E-Print Network [OSTI]

    Hayes, Jane E.

    202 51 *total new freshmen 684: 636 Lexington campus, 48 Paducah campus MS Total 216 12 5 17 2 0 2 40 248 247 648 45 210 14 *total new freshmen 647: 595 Lexington campus, 52 Paducah campus MS Total 192 14

  17. Total Energy Monitor

    SciTech Connect (OSTI)

    Friedrich, S

    2008-08-11T23:59:59.000Z

    The total energy monitor (TE) is a thermal sensor that determines the total energy of each FEL pulse based on the temperature rise induced in a silicon wafer upon absorption of the FEL. The TE provides a destructive measurement of the FEL pulse energy in real-time on a pulse-by-pulse basis. As a thermal detector, the TE is expected to suffer least from ultra-fast non-linear effects and to be easy to calibrate. It will therefore primarily be used to cross-calibrate other detectors such as the Gas Detector or the Direct Imager during LCLS commissioning. This document describes the design of the TE and summarizes the considerations and calculations that have led to it. This document summarizes the physics behind the operation of the Total Energy Monitor at LCLS and derives associated engineering specifications.

  18. Cell Total Activity Final Estimate.xls

    Office of Legacy Management (LM)

    8.95E+00 4.03E+03 4.78E+01 1.25E+02 9.10E+00 1.47E+02 4.49E+03 68.44% Pit 4 residual sludge 2530 2.36E+09 Raffinate 9.68E-01 9.68E-01 4.48E-02 1.42E-01 6.37E+01 7.55E-01 1.98E+00...

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

    Office of Environmental Management (EM)

    2010 19,332,431 FY2011 23,956,349 FY2012 19,099,251 FY2013 19,352,402 FY2014 0 FY2015 FY2016 FY2017 FY2018 FY2019 Cumulative Fee Paid 81,740,433 208,635,203 21,226,918...

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

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011AT&T, Inc.'sEnergyTexas1.SpaceFluor FederalEnergyContractor: Contract Number:

  1. Notices Total Estimated Number of Annual

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn'tOrigin of Contamination in ManyDepartment of Energy NorthB O N N789266 Federal Register

  2. Notices Total Estimated Number of Annual

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC)Integrated CodesTransparencyDOE Project TapsDOE Directives,83 Federal Register / Vol.

  3. Cell Total Activity Final Estimate.xls

    Office of Legacy Management (LM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilA groupTuba City, Arizona, DisposalFourthNrr-osams ADMIN RCDBaseline t-)WSSRAP Cell

  4. Table 1 -ESTIMATED REDUCTION IN 1985 COTTON YIELDS RESULTING FROM INSECTDAMAGE TOTAL YIELD 13,622 bales INSECTS Loss in AL AZ AR CA FL GA LA MS MO NM NC OK SC TN TX VA No.

    E-Print Network [OSTI]

    Ray, David

    Average cost for all states nTotal yield for all states o Total acres for all states *Does not include BWE cost

  5. Total correlations as fully additive entanglement monotones

    E-Print Network [OSTI]

    Gerardo A. Paz-Silva; John H. Reina

    2007-04-05T23:59:59.000Z

    We generalize the strategy presented in Refs. [1, 2], and propose general conditions for a measure of total correlations to be an entanglement monotone using its pure (and mixed) convex-roof extension. In so doing, we derive crucial theorems and propose a concrete candidate for a total correlations measure which is a fully additive entanglement monotone.

  6. Project Functions and Activities Definitions for Total Project...

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

    exactly is included in total estimated cost (TEC) and total project cost (TPC). g4301-1chp6.pdf -- PDF Document, 46 KB Writer: John Makepeace Subjects: Administration Management...

  7. Project Functions and Activities Definitions for Total Project Cost

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

    1997-03-28T23:59:59.000Z

    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).

  8. Total Light Management

    Broader source: Energy.gov [DOE]

    Presentation covers total light management, and is given at the Spring 2010 Federal Utility Partnership Working Group (FUPWG) meeting in Providence, Rhode Island.

  9. Total Space Heat-

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

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

  10. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

  11. Estimating Methods

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

    1997-03-28T23:59:59.000Z

    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.

  12. Falcon 9 Launch Vehicle NAFCOM Cost Estimates

    E-Print Network [OSTI]

    . ­ The updated estimates provided both Cost Plus Fee and Firm Fixed Price approaches and included two flight Updated Estimate Cost Plus Fee Cost Plus Fee Firm Fixed Price Cost Plus Fee Total Total Total Total in structure Interstage (composite material) was included in structures (aluminum lithium material) Interstage

  13. Total Synthesis of (?)-Himandrine

    E-Print Network [OSTI]

    Movassaghi, Mohammad

    We describe the first total synthesis of (?)-himandrine, a member of the class II galbulimima alkaloids. Noteworthy features of this chemistry include a diastereoselective Diels?Alder reaction in the rapid synthesis of the ...

  14. Complex higher order derivative theories

    SciTech Connect (OSTI)

    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

    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.

  15. Comparison of Direct Normal Irradiance Derived from Silicon and Thermopile Global Hemispherical Radiation Detectors: Preprint

    SciTech Connect (OSTI)

    Myers, D. R.

    2010-01-01T23:59:59.000Z

    Concentrating solar applications utilize direct normal irradiance (DNI) radiation, a measurement rarely available. The solar concentrator industry has begun to deploy numerous measurement stations to prospect for suitable system deployment sites. Rotating shadowband radiometers (RSR) using silicon photodiodes as detectors are typically deployed. This paper compares direct beam estimates from RSR to a total hemispherical measuring radiometer (SPN1) multiple fast thermopiles. These detectors simultaneously measure total and diffuse radiation from which DNI can be computed. Both the SPN1 and RSR-derived DNI are compared to DNI measured with thermopile pyrheliometers. Our comparison shows that the SPN1 radiometer DNI estimated uncertainty is somewhat greater than, and on the same order as, the RSR DNI estimates for DNI magnitudes useful to concentrator technologies.

  16. Total Precipitable Water

    SciTech Connect (OSTI)

    None

    2012-01-01T23:59:59.000Z

    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.

  17. Total to Selective Extinction Ratios and Visual Extinctions from Ultraviolet Data

    E-Print Network [OSTI]

    Anna Geminale; Piotr Popowski

    2004-09-21T23:59:59.000Z

    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.

  18. INTRODUCTION Estimation of RNA concentration or total RNA content

    E-Print Network [OSTI]

    Elser, Jim

    ­60% of the ribosome, the machine of protein synthesis and subsequent cell growth (Becker, 1986), and (ii nucleus corresponds to one cell, RNA levels may be normalized through division with the DNA concen information about cell multiplication and cell enlargement (Bergeron 1997). To date, a number of studies

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

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33Frequently AskedEnergyIssuesEnergy SolarRadioactiveI DisposalFive ThingsWesternDefinition

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

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33Frequently AskedEnergyIssuesEnergy SolarRadioactiveI DisposalFive

  1. TotalView Training

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening a solidSynthesisAppliances » Top InnovativeTopoisomeraseTotalView

  2. Total Cross Sections for Neutron Scattering

    E-Print Network [OSTI]

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

    1994-10-19T23:59:59.000Z

    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.

  3. Theoretical estimates of cross sections for neutron-nucleus collisions

    E-Print Network [OSTI]

    Tapan Mukhopadhyay; Joydev Lahiri; D. N. Basu

    2011-03-14T23:59:59.000Z

    We construct an analytical model derived from nuclear reaction theory and having a simple functional form to demonstrate the quantitative agreement with the measured cross sections for neutron induced reactions. The neutron-nucleus total, reaction and scattering cross sections, for energies ranging from 5 to 700 MeV and for several nuclei spanning a wide mass range are estimated. Systematics of neutron scattering cross sections on various materials for neutron energies upto several hundred MeV are important for ADSS applications. The reaction cross sections of neutrons are useful for determining the neutron induced fission yields in actinides and pre-actinides. The present model based on nuclear reaction theory provides good estimates of the total cross section for neutron induced reaction.

  4. Estimating Temperature Distributions In Geothermal Areas Using...

    Open Energy Info (EERE)

    an analytical model, showing that the errors in neuronet temperature estimates based on well log data derive from: (a) the neuronet "education level" (which depends on the amount...

  5. Enantioselective total Synthesis of the agelastatin and trigonoliimine alkaloids

    E-Print Network [OSTI]

    Han, Sunkyu, 1982-

    2012-01-01T23:59:59.000Z

    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. ...

  6. adjust efficacy estimates: Topics by E-print Network

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

    Entropy Estimation Vincent Q. Vu Mathematics Websites Summary: -likelihood, the Good-Turing coverage estimate and the total probability of unobserved words converge at rate OP...

  7. Reference values for total blood volume and cardiac output in humans

    SciTech Connect (OSTI)

    Williams, L.R. [Indiana Univ., South Bend, IN (United States). Division of Liberal Arts and Sciences] [Indiana Univ., South Bend, IN (United States). Division of Liberal Arts and Sciences

    1994-09-01T23:59:59.000Z

    Much research has been devoted to measurement of total blood volume (TBV) and cardiac output (CO) in humans but not enough effort has been devoted to collection and reduction of results for the purpose of deriving typical or {open_quotes}reference{close_quotes} values. Identification of normal values for TBV and CO is needed not only for clinical evaluations but also for the development of biokinetic models for ultra-short-lived radionuclides used in nuclear medicine (Leggett and Williams 1989). The purpose of this report is to offer reference values for TBV and CO, along with estimates of the associated uncertainties that arise from intra- and inter-subject variation, errors in measurement techniques, and other sources. Reference values are derived for basal supine CO and TBV in reference adult humans, and differences associated with age, sex, body size, body position, exercise, and other circumstances are discussed.

  8. Do Type-Ia Supernovae Constrain the Total Equation of State?

    E-Print Network [OSTI]

    William Komp

    2007-02-01T23:59:59.000Z

    In this paper, we consider a couple of alternative dark energy models using the total equation of state of the cosmological fluid, $\\wt$. These models are fit to the recent type-Ia supernovae data and are compared to previously considered models. The first model is based on the hyperbolic tangent and provides a good estimate of the rate of the transition to dark energy domination. The second model is a cubic spline model. This model demonstrates and quantifies the non-monotonicity in the total equation of state coming from the supernovae observations. At present, the supernovae observations indicate significance to non-monotonically decreasing dark energy. We derive constraints on the spline paramters and compare and constrast the results to the Cosmological Constant dark energy model. Both the hyperbolic and splines models indicate that a precise physical notion of dark enegy is a potentially ever more mysterious quantity?

  9. Estimation of Sm-151 from measured Pm-147

    SciTech Connect (OSTI)

    Dewberry, R.A.

    1988-08-25T23:59:59.000Z

    The attached procedure is a derivation to estimate Sm-151 activity in DWPF glass product and glass melter feed samples. Sm-151 is one of the radioactive fission product species in the glass product which will contribute greater than 0.05% of the total activity, and thus its content must be reported. We will not routinely perform elemental separation of Sm from Pm in the DWPF samples as they are received, but rather will report the Sm-151 activity as a constant fraction of the measured Pm-147 activity. Since Sm-151 decays with a 76 kev ..beta..-endpoint energy and is difficult to chemically separate from Pm, the direct measurement of Sm-151 content is technically very difficult. This document derives the multiplicative constant which will be used to estimate Sm-151 content from measured Pm-147 content, and the error which will be reported for each sample. A rigorous separation of Sm from Pm will be performed on selected samples to assure that the routine DWPF samples do not contain Sm-151/Pm-147 relative activities which deviate from the relationship derived here. Since both Sm-151 and Pm-147 can both be considered to be direct fission products with no other production pathway contributing, their relative production rate can be estimated from the U-235 fission yield curve. Ignoring burnup by neutron capture in a reactor irradiation, the relative activities of the two species is a function only of the decay rates. Sm-151 activity can then be estimated from measured Pm-147 activity, if some knowledge of irradiation time and decay time is available. The attached procedure explains the derivation and discusses the error obtained in the estimation.

  10. Total solar irradiance during the Holocene F. Steinhilber,1

    E-Print Network [OSTI]

    Wehrli, Bernhard

    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

  11. Monotonic Local Decay Estimates

    E-Print Network [OSTI]

    Avy Soffer

    2011-10-29T23:59:59.000Z

    For the Hamiltonian operator H = -{\\Delta}+V(x) of the Schr\\"odinger Equation with a repulsive potential, the problem of local decay is considered. It is analyzed by a direct method, based on a new, L^2 bounded, propagation observable. The resulting decay estimate, is in certain cases monotonic in time, with no "Quantum Corrections". This method is then applied to some examples in one and higher dimensions. In particular the case of the Wave Equation on a Schwarzschild manifold is redone: Local decay, stronger than the known ones are proved (minimal loss of angular derivatives and lower order of radial derivatives of initial data). The method developed here can be an alternative in some cases to the Morawetz type estimates, with L^2-multipliers replacing the first order operators. It provides an alternative to Mourre's method, by including thresholds and high energies.

  12. A Bootstrap Approach to Computing Uncertainty in Inferred Oil and Gas Reserve Estimates

    SciTech Connect (OSTI)

    Attanasi, Emil D. [US Geological Survey MS 956 (United States)], E-mail: attanasi@usgs.gov; Coburn, Timothy C. [Abilene Christian University, Department of Management Science (United States)

    2004-03-15T23:59:59.000Z

    This study develops confidence intervals for estimates of inferred oil and gas reserves based on bootstrap procedures. Inferred reserves are expected additions to proved reserves in previously discovered conventional oil and gas fields. Estimates of inferred reserves accounted for 65% of the total oil and 34% of the total gas assessed in the U.S. Geological Survey's 1995 National Assessment of oil and gas in US onshore and State offshore areas. When the same computational methods used in the 1995 Assessment are applied to more recent data, the 80-year (from 1997 through 2076) inferred reserve estimates for pre-1997 discoveries located in the lower 48 onshore and state offshore areas amounted to a total of 39.7 billion barrels of oil (BBO) and 293 trillion cubic feet (TCF) of gas. The 90% confidence interval about the oil estimate derived from the bootstrap approach is 22.4 BBO to 69.5 BBO. The comparable 90% confidence interval for the inferred gas reserve estimate is 217 TCF to 413 TCF. The 90% confidence interval describes the uncertainty that should be attached to the estimates. It also provides a basis for developing scenarios to explore the implications for energy policy analysis.

  13. MUJERES TOTAL BIOLOGIA 16 27

    E-Print Network [OSTI]

    Autonoma de Madrid, Universidad

    , PLASTICA Y VISUAL 2 2 EDUCACION FISICA, DEPORTE Y MOTRICIDAD HUMANA 1 1 6 11 TOTAL CIENCIAS Nº DE TESIS

  14. MUJERES ( * ) TOTAL BIOLOGA 16 22

    E-Print Network [OSTI]

    Autonoma de Madrid, Universidad

    , DEPORTE Y MOTRICIDAD HUMANA 0 4 TOTAL FORMACIÓN DE PROFESORADO Y EDUCACIÓN 0 6 ANATOMÍA PATOLÓGICA 2 5

  15. The Total RNA Story Introduction

    E-Print Network [OSTI]

    Goldman, Steven A.

    The Total RNA Story Introduction Assessing RNA sample quality as a routine part of the gene about RNA sample quality. Data from a high quality total RNA preparation Although a wide variety RNA data interpretation and identify features from total RNA electropherograms that reveal information

  16. UPRE method for total variation parameter selection

    SciTech Connect (OSTI)

    Wohlberg, Brendt [Los Alamos National Laboratory; Lin, Youzuo [Los Alamos National Laboratory

    2008-01-01T23:59:59.000Z

    Total Variation (TV) Regularization is an important method for solving a wide variety of inverse problems in image processing. In order to optimize the reconstructed image, it is important to choose the optimal regularization parameter. The Unbiased Predictive Risk Estimator (UPRE) has been shown to give a very good estimate of this parameter for Tikhonov Regularization. In this paper we propose an approach to extend UPRE method to the TV problem. However, applying the extended UPRE is impractical in the case of inverse problems such as de blurring, due to the large scale of the associated linear problem. We also propose an approach to reducing the large scale problem to a small problem, significantly reducing computational requirements while providing a good approximation to the original problem.

  17. Quick Estimate of IRR From Capital Estimate Ratios

    E-Print Network [OSTI]

    Larson, R. J.

    specific problem. However, the derivation is simple enough so that a new chart can be derived, using the principles described, which is applicable to a specific situation or class of situations. Using conventional Discounted Cash Flow techniques... of the use of this chart is as follows: The estimate capital to carry out a proj ct is $24,000. The estimated savings to be experienced n the first year of operation is $11,300. 21 ESL-IE-85-05-05 Proceedings from the Seventh National Industrial Energy...

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

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

    Q 0.4 3 or More Units... 5.4 0.3 Q Q Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

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

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

    ... 1.9 1.1 Q Q 0.3 Q Do Not Use Central Air-Conditioning... 45.2 24.6 3.6 5.0 8.8 3.2 Use a Programmable...

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

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

    Q 0.6 3 or More Units... 5.4 3.8 2.9 0.4 Q N 0.2 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

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

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

    1.3 Q 3 or More Units... 5.4 1.6 0.8 Q 0.3 0.3 Q Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

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

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

    3 or More Units... 5.4 2.4 1.4 0.7 0.9 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

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

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

    3 or More Units... 5.4 2.3 1.7 0.6 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  4. Total..........................................................

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

    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......

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

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

    3 or More Units... 5.4 2.1 0.9 0.2 1.0 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

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

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

    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......

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

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

    0.3 3 or More Units... 5.4 0.7 0.5 Q Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

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

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

    3 or More Units... 5.4 2.3 0.7 2.1 0.3 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

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

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

    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......

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

    Gasoline and Diesel Fuel Update (EIA)

    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......

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

    Gasoline and Diesel Fuel Update (EIA)

    Personal Computers Do Not Use a Personal Computer... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer... 75.6...

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

    Gasoline and Diesel Fuel Update (EIA)

    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......

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

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

    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......

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

    Gasoline and Diesel Fuel Update (EIA)

    ..... 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......

  15. Total..........................................................

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

    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......

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

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

    1.3 0.8 0.5 Once a Day... 19.2 4.6 3.0 1.6 Between Once a Day and Once a Week... 32.0 8.9 6.3 2.6 Once a...

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

    Gasoline and Diesel Fuel Update (EIA)

    AppliancesTools.... 56.2 11.6 3.3 8.2 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 0.2 Q 0.1 Hot Tub or Spa......

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

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

    Tools... 56.2 20.5 10.8 3.6 6.1 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 N N N N Hot Tub or Spa......

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

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

    Tools... 56.2 27.2 10.6 9.3 9.2 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 Q Q Q 0.4 Hot Tub or Spa......

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

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

    AppliancesTools.... 56.2 12.2 9.4 2.8 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 Q Q Q Hot Tub or Spa......

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

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

    1.3 3.8 Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line Eligible for Federal Assistance 1 40,000 to 59,999 60,000 to 79,999 80,000...

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6 2,720

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6 2,720..

  4. Total........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6 2,720..

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q Table

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q TableQ

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q26.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7 28.8 20.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7 28.8

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7 28.8,171

  15. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.7 21.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.747.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.747.1Do

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.747.1Do

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4 12.5 12.5

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4 12.5

  4. Total..................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4 12.578.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4. 111.1 14.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4. 111.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4. 111.115.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,033 1,618

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,033 1,61814.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,033

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.6 17.7

  15. Total.......................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.6 17.74.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.615.1 5.5

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.615.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.615.10.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not Have

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not Have7.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not

  4. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not25.6 40.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not25.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not25.65.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.6 16.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.67.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.67.10.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.24.2 7.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.24.2

  15. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.24.2Cooking

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not Have

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not HaveDo

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not HaveDoDo

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo Not

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo Not

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo Not20.6

  4. Total..............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1 19.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1...

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking25.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking25.65.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6 Personal

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6 Personal

  15. Total.........................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6

  16. Total

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)July 23,

  17. Total

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)July 23,Product:

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720 1,970

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720 111.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q Table

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q

  4. Total...........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q14.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8 20.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8 20.6,171

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.6 25.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.626.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7

  15. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.0 22.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.0 22.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.014.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.178.1 64.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.178.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.178.1.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770

  4. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2 3.3 1.9

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2 3.3

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2 3.3Type

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.214.7 7.4

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.214.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.214.75.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.6 40.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.65.6 17.7

  15. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.65.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.65.64.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.0 22.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.025.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.025.6.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.025.6.5.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1

  4. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.6 16.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.67.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.67.10.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2 7.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2 7.6Do

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2Cooking

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not Have Cooling

  15. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not Have

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo Not

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo NotDo

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo0.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo0.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo0.77.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1 7.0 8.0

  4. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1 7.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1 7.05.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1Personal

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1Personal4.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do 111.1 47.1 19.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do 111.1 47.1

  12. Second order accurate variance estimation in poststratified two-stage sampling

    E-Print Network [OSTI]

    Kim, Kyong Ryun

    2007-09-17T23:59:59.000Z

    We proposed new variance estimators for the poststratified estimator of the population total in two-stage sampling. The linearization or Taylor series variance estimator and the jackknife linearization variance estimator are popular...

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

    SciTech Connect (OSTI)

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

    2009-09-25T23:59:59.000Z

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

  14. Estimating radiogenic cancer risks

    SciTech Connect (OSTI)

    NONE

    1994-06-01T23:59:59.000Z

    This document presents a revised methodology for EPA`s estimation of cancer risks due to low-LET radiation exposures in light of information that has become available since the publication of BIER III, especially new information on the Japanese atomic bomb survivors. For most cancer sites, the risk model is one in which the age-specific relative risk coefficients are obtained by taking the geometric mean of coefficients derived from the atomic bomb survivor data employing two different methods for transporting risks from Japan to the U.S. (multiplicative and NIH projection methods). Using 1980 U.S. vital statistics, the risk models are applied to estimate organ-specific risks, per unit dose, for a stationary population.

  15. Estimates of Savings Achievable from Irrigation Controller

    SciTech Connect (OSTI)

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

    2014-03-28T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    2004-03-15T23:59:59.000Z

    Mar 15, 2004 ... taining nonzero entries in the column positions mapped by the column segments. A(w˜i,q) and A(w˜p,j) for all ˜p = ˜i. This is done for every pair ...

  17. Derived Annual Estimates of Manufacturing Energy Consumption, 1974-1988

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at CommercialDecadeReservesYear21CompanySFoot)Year

  18. Advances in total scattering analysis

    SciTech Connect (OSTI)

    Proffen, Thomas E [Los Alamos National Laboratory; Kim, Hyunjeong [Los Alamos National Laboratory

    2008-01-01T23:59:59.000Z

    In recent years the analysis of the total scattering pattern has become an invaluable tool to study disordered crystalline and nanocrystalline materials. Traditional crystallographic structure determination is based on Bragg intensities and yields the long range average atomic structure. By including diffuse scattering into the analysis, the local and medium range atomic structure can be unravelled. Here we give an overview of recent experimental advances, using X-rays as well as neutron scattering as well as current trends in modelling of total scattering data.

  19. Total Imports of Residual Fuel

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013,Iowa"Dakota"YearProductionShaleInput Product: TotalCountry:

  20. Page (Total 3) Philadelphia University

    E-Print Network [OSTI]

    Page (Total 3) Philadelphia University Faculty of Science Department of Biotechnology and Genetic be used in animals or plants. It can be also used in environmental monitoring, food processing ...etc are developed and marketed in kit format by biotechnology companies. The main source of information is web sites

  1. Quality Estimation and Segmentation of Pig Backs

    E-Print Network [OSTI]

    Quality Estimation and Segmentation of Pig Backs Mads Fogtmann Hansen Kongens Lyngby 2005 Master the quality of the pig product "18cm back". It presents the necessary tools for deriving the measures, which are needed to perform a quality estimation. This includes finding the ribs, extracting the 18cm back from

  2. Derivative actions in China 

    E-Print Network [OSTI]

    Lin, Shaowei

    2014-07-02T23:59:59.000Z

    The enactment of derivative action was expected to be actively used by shareholders to protect their interests. In fact, it turned out that this reform effort seemed futile as the right to engage in such actions was ...

  3. Dynamic Derivative Strategies

    E-Print Network [OSTI]

    Liu, Jun

    2003-09-25T23:59:59.000Z

    This paper studies the optimal investment strategy of an investor who can access not only the bond and the stock markets, but also the derivatives market. We consider the investment situation where, in addition to the usual ...

  4. Credit derivatives in Brazil

    E-Print Network [OSTI]

    Rüther, Henrique

    2007-01-01T23:59:59.000Z

    The amounts outstanding of credit derivatives have grown exponentially over the past years, and these financial intruments that allow market participants to trade credit risk have become very popular in Europe and in the ...

  5. Estimating the kinetic luminosity function of jets from Galactic X-ray binaries

    E-Print Network [OSTI]

    S. Heinz; H. -J. Grimm

    2005-08-11T23:59:59.000Z

    By combining the recently derived X-ray luminosity function for Galactic X-ray binaries (XRBs) by Grimm et al. (2002) and the radio-X-ray-mass relation of accreting black holes found by Merloni et al. (2003), we derive predictions for the radio luminosity function and radio flux distribution (logN/logS) for XRBs. Based on the interpretation that the radio-X-ray-mass relation is an expression of an underlying relation between jet power and nuclear radio luminosity, we derive the kinetic luminosity function for Galactic black hole jets, up to a normalization constant in jet power. We present estimates for this constant on the basis of known ratios of jet power to core flux for AGN jets and available limits for individual XRBs. We find that, if XRB jets do indeed fall on the same radio flux--kinetic power relation as AGN jets, the estimated mean kinetic luminosity of typical low/hard state jets is of the order of ~ 2x10^37 ergs/s, with a total integrated power output of W \\~ 5.5x10^38 ergs/s. We find that the power carried in transient jets should be of comparable magnitude to that carried in low/hard state jets. Including neutron star systems increases this estimate to W ~ 9x10^38 ergs/s. We estimate the total kinetic energy output from low/hard state jets over the history of the Galaxy to be E_{XRB} ~ 7x10^56 ergs.

  6. Total Adjusted Sales of Kerosene

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)JulyEnd Use: Total

  7. U.S. Total Exports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009 2010(Billion

  8. U.S. Total Exports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009 2010(Billion120,814 136,932

  9. U.S. Total Imports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009 2010(Billion120,814

  10. U.S. Total Imports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009 2010(Billion120,814Pipeline

  11. U.S. Total Stocks

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009Feet)

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

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01T23:59:59.000Z

    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

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

    SciTech Connect (OSTI)

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

    2012-05-01T23:59:59.000Z

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

  14. Connected Operators for the Totally Asymmetric Exclusion Process

    E-Print Network [OSTI]

    Golinelli, O; 10.1088/1751-8113/40/44/004

    2009-01-01T23:59:59.000Z

    We fully elucidate the structure of the hierarchy of the connected operators that commute with the Markov matrix of the Totally Asymmetric Exclusion Process (TASEP). We prove for the connected operators a combinatorial formula that was conjectured in a previous work. Our derivation is purely algebraic and relies on the algebra generated by the local jump operators involved in the TASEP. Keywords: Non-Equilibrium Statistical Mechanics, ASEP, Exact Results, Algebraic Bethe Ansatz.

  15. Connected Operators for the Totally Asymmetric Exclusion Process

    E-Print Network [OSTI]

    O. Golinelli; K. Mallick

    2007-04-06T23:59:59.000Z

    We fully elucidate the structure of the hierarchy of the connected operators that commute with the Markov matrix of the Totally Asymmetric Exclusion Process (TASEP). We prove for the connected operators a combinatorial formula that was conjectured in a previous work. Our derivation is purely algebraic and relies on the algebra generated by the local jump operators involved in the TASEP. Keywords: Non-Equilibrium Statistical Mechanics, ASEP, Exact Results, Algebraic Bethe Ansatz.

  16. A Flexible Method of Estimating Luminosity Functions

    E-Print Network [OSTI]

    Brandon C. Kelly; Xiaohui Fan; Marianne Vestergaard

    2008-05-19T23:59:59.000Z

    We describe a Bayesian approach to estimating luminosity functions. We derive the likelihood function and posterior probability distribution for the luminosity function, given the observed data, and we compare the Bayesian approach with maximum-likelihood by simulating sources from a Schechter function. For our simulations confidence intervals derived from bootstrapping the maximum-likelihood estimate can be too narrow, while confidence intervals derived from the Bayesian approach are valid. We develop our statistical approach for a flexible model where the luminosity function is modeled as a mixture of Gaussian functions. Statistical inference is performed using Markov chain Monte Carlo (MCMC) methods, and we describe a Metropolis-Hastings algorithm to perform the MCMC. The MCMC simulates random draws from the probability distribution of the luminosity function parameters, given the data, and we use a simulated data set to show how these random draws may be used to estimate the probability distribution for the luminosity function. In addition, we show how the MCMC output may be used to estimate the probability distribution of any quantities derived from the luminosity function, such as the peak in the space density of quasars. The Bayesian method we develop has the advantage that it is able to place accurate constraints on the luminosity function even beyond the survey detection limits, and that it provides a natural way of estimating the probability distribution of any quantities derived from the luminosity function, including those that rely on information beyond the survey detection limits.

  17. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

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

  18. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All...

  19. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,870 1,276...

  20. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings ... 2,037...

  1. Improved diagnostic model for estimating wind energy

    SciTech Connect (OSTI)

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

    1983-03-01T23:59:59.000Z

    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.

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

    DOE Patents [OSTI]

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

    1982-07-07T23:59:59.000Z

    Simultaneous photon and neutron interrogation of samples for the quantitative determination of total fissile nuclide and total fertile nuclide material present is made possible by the use of an electron accelerator. Prompt and delayed neutrons produced from resulting induced fission are counted using a single detection system and allow the resolution of the contributions from each interrogating flux leading in turn to the quantitative determination sought. Detection limits for /sup 239/Pu are estimated to be about 3 mg using prompt fission neutrons and about 6 mg using delayed neutrons.

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

    E-Print Network [OSTI]

    Boyer, Edmond

    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

  4. Derived Azumaya algebras and generators for twisted derived categories

    E-Print Network [OSTI]

    Toen, Bertrand

    implies the existence of a global compact generator. We present explicit examples of derived Azumaya

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

    E-Print Network [OSTI]

    Quasdorf, Kyle

    2012-01-01T23:59:59.000Z

    LiEt 3 BD (“super deuteride”) was obtained from Aldrich.5.9 with super deuteride, followed by carbamoylation (FigureMe H Me Me H O H O Super Deuteride H THF, –78 °C to –10 °C (

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

    E-Print Network [OSTI]

    Quasdorf, Kyle

    2012-01-01T23:59:59.000Z

    Organic Synthesis, 2010. Nickel-Catalyzed Cross-CouplingsMeeting. 2011, FUEL-99. Nickel-catalyzed cross-couplings ofSymposium. 2011 (poster). Nickel-catalyzed cross-couplings

  7. Pushing schedule derivation method

    SciTech Connect (OSTI)

    Henriquez, B. [Compania Siderurgica Huachipato S.A., Talcahuano (Chile)

    1996-12-31T23:59:59.000Z

    The development of a Pushing Schedule Derivation Method has allowed the company to sustain the maximum production rate at CSH`s Coke Oven Battery, in spite of having single set oven machinery with a high failure index as well as a heat top tendency. The stated method provides for scheduled downtime of up to two hours for machinery maintenance purposes, periods of empty ovens for decarbonization and production loss recovery capability, while observing lower limits and uniformity of coking time.

  8. Total termination of term rewriting is undecidable

    E-Print Network [OSTI]

    Utrecht, Universiteit

    Total termination of term rewriting is undecidable Hans Zantema Utrecht University, Department Usually termination of term rewriting systems (TRS's) is proved by means of a monotonic well­founded order. If this order is total on ground terms, the TRS is called totally terminating. In this paper we prove that total

  9. Total Petroleum Systems and Assessment Units (AU)

    E-Print Network [OSTI]

    Torgersen, Christian

    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

  10. Energy and materials flows in the production of olefins and their derivatives

    SciTech Connect (OSTI)

    Gaines, L.L.; Shen, S.Y.

    1980-08-01T23:59:59.000Z

    Production of olefins and their derivatives uses almost 3.5% of the oil and gas consumed annually in the United States. It is estimated that their production requires an input energy of 2 Q, which is 50% of the energy used in the production of all petrochemicals. Substantial amounts of this energy could be recovered through recycling. For example, recycling of a single plastic product, polyester soft drink bottles, could have recovered about 0.014 Q in 1979. (About 1.4 Q is used to produce plastic derivatives of olefins). Petrochemical processes use fuels as feedstocks, as well as for process energy, and a portion of this energy is not foregone and can be recovered through combustion of the products. The energy foregone in the production of ethylene is estimated to be 7800 Btu/lb. The energy foregone in plastics production ranges from 12,100 Btu/lb for the new linear low-density polyethylene to 77,200 Btu/lb for nylon 66, which is about 60% of the total energy input for that product. Further investigation of the following areas could yield both material and energy savings in the olefins industry: (1) recycling of petrochemical products to recover energy in addition to that recoverable through combustion, (2) impact of feedstock substitution on utilization of available national resources, and (3) effective use of the heat embodied in process steam. This steam accounts for a major fraction of the industry's energy input.

  11. Total energy cycle energy use and emissions of electric vehicles.

    SciTech Connect (OSTI)

    Singh, M. K.

    1999-04-29T23:59:59.000Z

    A total energy cycle analysis (TECA) of electric vehicles (EV) was recently completed. The EV energy cycle includes production and transport of fuels used in power plants to generate electricity, electricity generation, EV operation, and vehicle and battery manufacture. This paper summarizes the key assumptions and results of the EVTECA. The total energy requirements of EVS me estimated to be 24-35% lower than those of the conventional, gasoline-fueled vehicles they replace, while the reductions in total oil use are even greater: 55-85%. Greenhouse gases (GHG) are 24-37% lower with EVs. EVs reduce total emissions of several criteria air pollutants (VOC, CO, and NO{sub x}) but increase total emissions of others (SO{sub x}, TSP, and lead) over the total energy cycle. Regional emissions are generally reduced with EVs, except possibly SO{sub x}. The limitations of the EVTECA are discussed, and its results are compared with those of other evaluations of EVs. In general, many of the results (particularly the oil use, GHG, VOC, CO, SO{sub x}, and lead results) of the analysis are consistent with those of other evaluations.

  12. Unconventional fuel: Tire derived fuel

    SciTech Connect (OSTI)

    Hope, M.W. [Waste Recovery, Inc., Portland, OR (United States)

    1995-09-01T23:59:59.000Z

    Material recovery of scrap tires for their fuel value has moved from a pioneering concept in the early 1980`s to a proven and continuous use in the United States` pulp and paper, utility, industrial, and cement industry. Pulp and paper`s use of tire derived fuel (TDF) is currently consuming tires at the rate of 35 million passenger tire equivalents (PTEs) per year. Twenty mills are known to be burning TDF on a continuous basis. The utility industry is currently consuming tires at the rate of 48 million PTEs per year. Thirteen utilities are known to be burning TDF on a continuous basis. The cement industry is currently consuming tires at the rate of 28 million PTEs per year. Twenty two cement plants are known to be burning TDF on a continuous basis. Other industrial boilers are currently consuming tires at the rate of 6.5 million PTEs per year. Four industrial boilers are known to be burning TDF on a continuous basis. In total, 59 facilities are currently burning over 117 million PTEs per year. Although 93% of these facilities were not engineered to burn TDF, it has become clear that TDF has found acceptance as a supplemental fuel when blending with conventional fuels in existing combustion devices designed for normal operating conditions. The issues of TDF as a supplemental fuel and its proper specifications are critical to the successful development of this fuel alternative. This paper will focus primarily on TDF`s use in a boiler type unit.

  13. Hydrotreating the bitumen-derived hydrocarbon liquid produced in a fluidized-bed pyrolysis reactor

    SciTech Connect (OSTI)

    Longstaff, D.C.; Deo, M.D.; Hanson, F.V.; Oblad, A.G.; Tsai, C.H.

    1991-12-31T23:59:59.000Z

    The pyrolysis of bitumen-impregnated sandstone produces three primary product streams: C{sub 1}-C{sub 4} hydrocarbons gases, a C{sub 5}{sup +} total liquid product, and a carbonaceous residue on the spent sand. The bitumen-derived hydrocarbon liquid was significantly upgraded relative to the native bitumen: it had a higher API gravity, lower Conradson carbon residue, asphaltene content, pour point and viscosity and a reduced distillation endpoint relative to the native bitumen. The elemental composition was little different from that of the native bitumen except for the hydrogen content which was lower. The bitumen-derived liquid produced in a 4-inch diameter fluidized-bed reactor from the Whiterocks tar sand deposit has been hydrotreated in a fixed-bed reactor to determine the extent of upgrading as a function of process operating variables. The extent of denitrogenation and desulfurization of the bitumen-derived liquid was used to monitor catalyst activity as a function of process operating variables and to estimate the extent of catalyst deactivation as a function of time on-stream. The apparent kinetics for the nitrogen and sulfur removal reactions were determined. Product distribution and yield data were also obtained.

  14. Hydrotreating the bitumen-derived hydrocarbon liquid produced in a fluidized-bed pyrolysis reactor

    SciTech Connect (OSTI)

    Longstaff, D.C.; Deo, M.D.; Hanson, F.V.; Oblad, A.G.; Tsai, C.H.

    1991-01-01T23:59:59.000Z

    The pyrolysis of bitumen-impregnated sandstone produces three primary product streams: C{sub 1}-C{sub 4} hydrocarbons gases, a C{sub 5}{sup +} total liquid product, and a carbonaceous residue on the spent sand. The bitumen-derived hydrocarbon liquid was significantly upgraded relative to the native bitumen: it had a higher API gravity, lower Conradson carbon residue, asphaltene content, pour point and viscosity and a reduced distillation endpoint relative to the native bitumen. The elemental composition was little different from that of the native bitumen except for the hydrogen content which was lower. The bitumen-derived liquid produced in a 4-inch diameter fluidized-bed reactor from the Whiterocks tar sand deposit has been hydrotreated in a fixed-bed reactor to determine the extent of upgrading as a function of process operating variables. The extent of denitrogenation and desulfurization of the bitumen-derived liquid was used to monitor catalyst activity as a function of process operating variables and to estimate the extent of catalyst deactivation as a function of time on-stream. The apparent kinetics for the nitrogen and sulfur removal reactions were determined. Product distribution and yield data were also obtained.

  15. Recursive Total Least Squares: An Alternative to the Discrete Kalman Filter

    E-Print Network [OSTI]

    Boley, Daniel

    Recursive Total Least Squares: An Alternative to the Discrete Kalman Filter Daniel L. Boley The discrete Kalman lter, which is becoming a common tool for reducing uncertainty in robot navigation, su ers total least squares estimator (RTLS) as an alternative to the Kalman lter, and compare

  16. Recursive Total Least Squares: An Alternative to Using the Discrete Kalman

    E-Print Network [OSTI]

    Boley, Daniel

    Recursive Total Least Squares: An Alternative to Using the Discrete Kalman Filter in Robot to ob- tain the best estimate of the robot position. The discrete Kalman filter, com- monly used the Kalman filter. To this end, we propose the use of a Recursive Total Least Squares Filter. This filter

  17. Using Surface Remote Sensors to Derive Radiative Characteristics of Mixed-Phase Clouds: An Example from M-PACE

    SciTech Connect (OSTI)

    de Boer, Gijs; Collins, William D.; Menon, Surabi; Long, Charles N.

    2011-12-02T23:59:59.000Z

    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.

  18. Estimates of US biomass energy consumption 1992

    SciTech Connect (OSTI)

    Not Available

    1994-05-06T23:59:59.000Z

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  19. Estimated United States Transportation Energy Use 2005

    SciTech Connect (OSTI)

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

    2011-11-09T23:59:59.000Z

    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.

  20. Seismic Pulses Derivation from the Study of Source Signature Characteristics

    SciTech Connect (OSTI)

    Rahman, Syed Mustafizur; Nawawi, M. N. Mohd.; Saad, Rosli [School of Physics, Univeristi Sains Malaysia, 11800 USM, Pulau Pinang (Malaysia)

    2010-07-07T23:59:59.000Z

    This paper deals with a deterministic technique for the derivation of seismic pulses by the study of source characteristics. The spectral characteristics of the directly or the nearest detected seismic signal is analyzed and considered as the principle source signature. Using this signature seismic pulses are derived with accurate time position in the seismic traces. The technique is applied on both synthetic and field refraction seismic traces. In both cases it has estimated that the accurate time shifts along with amplitude coefficients.

  1. Total System Performance Assessment Peer Review Panel

    Broader source: Energy.gov [DOE]

    Total System Performance Assessment (TSPA) Peer Review Panel for predicting the performance of a repository at Yucca Mountain.

  2. 8, 31433162, 2008 Total ozone over

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    ACPD 8, 3143­3162, 2008 Total ozone over oceanic regions M. C. R. Kalapureddy et al. Title Page Chemistry and Physics Discussions Total column ozone variations over oceanic region around Indian sub­3162, 2008 Total ozone over oceanic regions M. C. R. Kalapureddy et al. Title Page Abstract Introduction

  3. 5, 1133111375, 2005 NH total ozone

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    ACPD 5, 11331­11375, 2005 NH total ozone increase S. Dhomse et al. Title Page Abstract Introduction On the possible causes of recent increases in NH total ozone from a statistical analysis of satellite data from License. 11331 #12;ACPD 5, 11331­11375, 2005 NH total ozone increase S. Dhomse et al. Title Page Abstract

  4. 6, 39133943, 2006 Svalbard total ozone

    E-Print Network [OSTI]

    Boyer, Edmond

    ACPD 6, 3913­3943, 2006 Svalbard total ozone C. Vogler et al. Title Page Abstract Introduction Discussions Re-evaluation of the 1950­1962 total ozone record from Longyearbyen, Svalbard C. Vogler 1 , S. Br total ozone C. Vogler et al. Title Page Abstract Introduction Conclusions References Tables Figures Back

  5. About Total Lubricants USA, Inc. Headquartered in Linden, New Jersey, Total Lubricants USA provides

    E-Print Network [OSTI]

    Fisher, Kathleen

    New Jersey, Total Lubricants USA provides advanced quality industrial lubrication productsAbout Total Lubricants USA, Inc. Headquartered in Linden, New Jersey, Total Lubricants USA provides. A subsidiary of Total, S.A., the world's fourth largest oil company, Total Lubricants USA still fosters its

  6. Estimate of the Geothermal Energy Resource in the Major Sedimentary Basins in the United States (Presentation)

    SciTech Connect (OSTI)

    Esposito, A.; Porro, C.; Augustine, C.; Roberts, B.

    2012-09-01T23:59:59.000Z

    Because most sedimentary basins have been explored for oil and gas, well logs, temperatures at depth, and reservoir properties such as depth to basement and formation thickness are well known. The availability of this data reduces exploration risk and allows development of geologic exploration models for each basin. This study estimates the magnitude of recoverable geothermal energy from 15 major known U.S. sedimentary basins and ranks these basins relative to their potential. The total available thermal resource for each basin was estimated using the volumetric heat-in-place method originally proposed by (Muffler, 1979). A qualitative recovery factor was determined for each basin based on data on flow volume, hydrothermal recharge, and vertical and horizontal permeability. Total sedimentary thickness maps, stratigraphic columns, cross sections, and temperature gradient information was gathered for each basin from published articles, USGS reports, and state geological survey reports. When published data were insufficient, thermal gradients and reservoir properties were derived from oil and gas well logs obtained on oil and gas commission databases. Basin stratigraphy, structural history, and groundwater circulation patterns were studied in order to develop a model that estimates resource size, temperature distribution, and a probable quantitative recovery factor.

  7. Estimate of Geothermal Energy Resource in Major U.S. Sedimentary Basins (Presentation)

    SciTech Connect (OSTI)

    Porro, C.; Augustine, C.

    2012-04-01T23:59:59.000Z

    This study estimates the magnitude of geothermal energy from fifteen major known US sedimentary basins and ranks these basins relative to their potential. Because most sedimentary basins have been explored for oil and gas, well logs, temperatures at depth, and reservoir properties are known. This reduces exploration risk and allows development of geologic exploration models for each basin as well as a relative assessment of geologic risk elements for each play. The total available thermal resource for each basin was estimated using the volumetric heat-in-place method originally proposed by Muffler (USGS). Total sedimentary thickness maps, stratigraphic columns, cross sections, and temperature gradient Information were gathered for each basin from published articles, USGS reports, and state geological survey reports. When published data was insufficient, thermal gradients and reservoir properties were derived from oil and gas well logs obtained on oil and gas commission websites. Basin stratigraphy, structural history, and groundwater circulation patterns were studied in order to develop a model that estimates resource size and temperature distribution, and to qualitatively assess reservoir productivity.

  8. Jitter compensation in sampling via polynomial least squares estimation

    E-Print Network [OSTI]

    Weller, Daniel Stuart

    Sampling error due to jitter, or noise in the sample times, affects the precision of analog-to-digital converters in a significant, nonlinear fashion. In this paper, a polynomial least squares (PLS) estimator is derived ...

  9. Estimation of clock parameters and performance benchmarks for synchronization in wireless sensor networks

    E-Print Network [OSTI]

    Chaudhari, Qasim Mahmood

    2009-05-15T23:59:59.000Z

    . This dissertation focuses on deriving e±cient estimators for the clock parameters of the network nodes for synchronization with the reference node and the estimators variance thresholds are obtained to lower bound the maximum achievable performance. For any general...

  10. Cost Estimation Package

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

    1997-03-28T23:59:59.000Z

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

  11. Check Estimates and Independent Costs

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

    1997-03-28T23:59:59.000Z

    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.

  12. Fourier Analytic Approach to Phase Estimation

    E-Print Network [OSTI]

    Hiroshi Imai; Masahito Hayashi

    2008-10-31T23:59:59.000Z

    For a unified analysis on the phase estimation, we focus on the limiting distribution. It is shown that the limiting distribution can be given by the absolute square of the Fourier transform of $L^2$ function whose support belongs to $[-1,1]$. Using this relation, we study the relation between the variance of the limiting distribution and its tail probability. As our result, we prove that the protocol minimizing the asymptotic variance does not minimize the tail probability. Depending on the width of interval, we derive the estimation protocol minimizing the tail probability out of a given interval. Such an optimal protocol is given by a prolate spheroidal wave function which often appears in wavelet or time-limited Fourier analysis. Also, the minimum confidence interval is derived with the framework of interval estimation that assures a given confidence coefficient.

  13. Efficient Semiparametric Estimators for Nonlinear Regressions and Models under Sample Selection Bias

    E-Print Network [OSTI]

    Kim, Mi Jeong

    2012-10-19T23:59:59.000Z

    . Overview of Semiparametric Theory . . . . . . . . . . . . . 2 B. The Second-order Least Squares Estimator . . . . . . . . . 3 C. Sample Selection Bias . . . . . . . . . . . . . . . . . . . . . 4 II THE EFFICIENCY OF THE SECOND-ORDER NONLIN- EAR LEAST... . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1. Semiparametric Derivation . . . . . . . . . . . . . . . 24 2. Robust Estimation Family . . . . . . . . . . . . . . . 25 3. E cient Estimation . . . . . . . . . . . . . . . . . . . 29 4. Population Density Estimation...

  14. VIMOS total transmission profiles for broad-band filters

    E-Print Network [OSTI]

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

    2007-04-13T23:59:59.000Z

    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.

  15. Optimization Online - Total variation superiorization schemes in ...

    E-Print Network [OSTI]

    S.N. Penfold

    2010-10-08T23:59:59.000Z

    Oct 8, 2010 ... Total variation superiorization schemes in proton computed tomography ... check improved the image quality, in particular image noise, in the ...

  16. ,"New Mexico Natural Gas Total Consumption (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Total Consumption (MMcf)",1,"Annual",2013 ,"Release Date:","331...

  17. ,"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:","2272015"...

  18. SPEECH ENHANCEMENT USING A STATISTICALLY DERIVED FILTER MAPPING

    E-Print Network [OSTI]

    Kabal, Peter

    SPEECH ENHANCEMENT USING A STATISTICALLY DERIVED FILTER MAPPING Yan Ming Cheng, Douglas, Quebec H3E 1H6 Canada Abstract We view the speech enhancement task in two aspects: reduc- tion Mapping (NISSM) to estimate a speech enhancement Wiener filter. NISSM consists of a noise

  19. Bounds on Quantum Multiple-Parameter Estimation with Gaussian State

    E-Print Network [OSTI]

    Yang Gao; Hwang Lee

    2014-07-28T23:59:59.000Z

    We investigate the quantum Cramer-Rao bounds on the joint multiple-parameter estimation with the Gaussian state as a probe. We derive the explicit right logarithmic derivative and symmetric logarithmic derivative operators in such a situation. We compute the corresponding quantum Fisher information matrices, and find that they can be fully expressed in terms of the mean displacement and covariance matrix of the Gaussian state. Finally, we give some examples to show the utility of our analytical results.

  20. TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION

    E-Print Network [OSTI]

    Skogestad, Sigurd

    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

  1. Optimal Training Signals for MIMO OFDM Channel Estimation

    E-Print Network [OSTI]

    Minn, Hlaing

    Optimal Training Signals for MIMO OFDM Channel Estimation Hlaing Minn*, Member, IEEE and Naofal Al.minn@utdallas.edu, aldhahir@utdallas.edu Abstract--This paper presents general classes of optimal train- ing signals transform are used to derive the optimal training signals which minimize the channel estimation mean square

  2. The Effect of Signal Quality on Six Cardiac Output Estimators

    E-Print Network [OSTI]

    Mark, Roger Greenwood

    The effect of signal quality on the accuracy of cardiac output (CO) estimation from arterial blood pressure (ABP) was evaluated using data from the MIMIC II database. Thermodilution CO (TCO) was the gold standard. A total ...

  3. April 9, 2002 STATISTICAL ESTIMATES FOR THE NAVIER-STOKES

    E-Print Network [OSTI]

    Jolly, Michael S.

    rigorous support for Kraichnan's eddy breakup mechanism. A rigorous estimate for the total energy is found by NSF grant number DMS-0074460, CNPq, Bras#19;#16;lia, Brazil, and FAPERJ, Rio de Janeiro, Brazil. Much

  4. Some methods of estimating uncertainty in accident reconstruction

    E-Print Network [OSTI]

    Milan Batista

    2011-07-20T23:59:59.000Z

    In the paper four methods for estimating uncertainty in accident reconstruction are discussed: total differential method, extreme values method, Gauss statistical method, and Monte Carlo simulation method. The methods are described and the program solutions are given.

  5. AN OVERVIEW OF TOOL FOR RESPONSE ACTION COST ESTIMATING (TRACE)

    SciTech Connect (OSTI)

    FERRIES SR; KLINK KL; OSTAPKOWICZ B

    2012-01-30T23:59:59.000Z

    Tools and techniques that provide improved performance and reduced costs are important to government programs, particularly in current times. An opportunity for improvement was identified for preparation of cost estimates used to support the evaluation of response action alternatives. As a result, CH2M HILL Plateau Remediation Company has developed Tool for Response Action Cost Estimating (TRACE). TRACE is a multi-page Microsoft Excel{reg_sign} workbook developed to introduce efficiencies into the timely and consistent production of cost estimates for response action alternatives. This tool combines costs derived from extensive site-specific runs of commercially available remediation cost models with site-specific and estimator-researched and derived costs, providing the best estimating sources available. TRACE also provides for common quantity and key parameter links across multiple alternatives, maximizing ease of updating estimates and performing sensitivity analyses, and ensuring consistency.

  6. Regionalization of subsurface stormflow parameters of hydrologic models: Derivation from regional analysis of streamflow recession curves

    SciTech Connect (OSTI)

    Ye, Sheng; Li, Hongyi; Huang, Maoyi; Ali, Melkamu; Leng, Guoyong; Leung, Lai-Yung R.; Wang, Shaowen; Sivapalan, Murugesu

    2014-07-21T23:59:59.000Z

    Subsurface stormflow is an important component of the rainfall–runoff response, especially in steep terrain. Its contribution to total runoff is, however, poorly represented in the current generation of land surface models. The lack of physical basis of these common parameterizations precludes a priori estimation of the stormflow (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global land surface models. This paper is aimed at deriving regionalized parameterizations of the storage–discharge relationship relating to subsurface stormflow from a top–down empirical data analysis of streamflow recession curves extracted from 50 eastern United States catchments. Detailed regression analyses were performed between parameters of the empirical storage–discharge relationships and the controlling climate, soil and topographic characteristics. The regression analyses performed on empirical recession curves at catchment scale indicated that the coefficient of the power-law form storage–discharge relationship is closely related to the catchment hydrologic characteristics, which is consistent with the hydraulic theory derived mainly at the hillslope scale. As for the exponent, besides the role of field scale soil hydraulic properties as suggested by hydraulic theory, it is found to be more strongly affected by climate (aridity) at the catchment scale. At a fundamental level these results point to the need for more detailed exploration of the co-dependence of soil, vegetation and topography with climate.

  7. Total synthesis of all (?)-agelastatin alkaloids

    E-Print Network [OSTI]

    Movassaghi, Mohammad

    The pyrrole-imidazole family of marine alkaloids, derived from linear clathrodin-like precursors, constitutes a diverse array of structurally complex natural products. The bioactive agelastatins are members of this family ...

  8. Types of Cost Estimates

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

    1997-03-28T23:59:59.000Z

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

  9. Systems Engineering Cost Estimation

    E-Print Network [OSTI]

    Bryson, Joanna J.

    on project, human capital impact. 7 How to estimate Cost? Difficult to know what we are building early on1 Systems Engineering Lecture 3 Cost Estimation Dr. Joanna Bryson Dr. Leon Watts University of Bath: Contrast approaches for estimating software project cost, and identify the main sources of cost

  10. Total to withdraw from Qatar methanol - MTBE?

    SciTech Connect (OSTI)

    NONE

    1996-05-01T23:59:59.000Z

    Total is rumored to be withdrawing from the $700-million methanol and methyl tert-butyl ether (MTBE) Qatar Fuel Additives Co., (Qafac) project. The French company has a 12.5% stake in the project. Similar equity is held by three other foreign investors: Canada`s International Octane, Taiwan`s Chinese Petroleum Corp., and Lee Change Yung Chemical Industrial Corp. Total is said to want Qafac to concentrate on methanol only. The project involves plant unit sizes of 610,000 m.t./year of MTBE and 825,000 m.t./year of methanol. Total declines to comment.

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

    construction,” Energy and Buildings 20: 205–217. Chau 2007.management in China,” Energy and Buildings (forthcoming).addition to operational energy, buildings embody the energy

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

    such as increasing boiler efficiency from 68% averageBuildings: Water Heating Efficiency Boiler Gas Boiler SmallSpace Heating Efficiency District Heating Boiler Gas Boiler

  13. Estimating Total Length of Headless White Hake, Urophycis tenuis, Landed in Maine

    E-Print Network [OSTI]

    , Urophycis tenuis, oc- curs in continental waters between the Gulf of the St. Lawrence and the Mid- dle

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

    Primary Electricity Coal Final energy use in buildings is9 million tonnes of coal equivalent energy could be saved byproportion of energy consumed from coal, coke, liquid fuels,

  15. estimate total CO2 emission from European estuaries (Fig. 4), which appears to be a signif-

    E-Print Network [OSTI]

    Gilli, Adrian

    . Wanninkhof, J. Geophys. Res. 97, 7373 (1992). 25. J. P. Bennet and R. E. Rathbun, U.S. Geol. Surv. Prof. Pap

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

    electricity, oil and coal consumption, offset by increasedsaved in electricity, oil and gas consumption, offset by 2.4energy consumption by fuel type. Natural gas, oil and some

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

    forecasts of operational energy till 2020 based on differing assumptions of technology penetration and efficiency. China

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

    Geothermal Heat Pump Central AC by NG Electric water heaterwater heating Technologies Electric heater Gas boiler Coal Boiler Small cogen Stove District heating Heat pumpHeat Pump* *COP Reference Case Alternative Case Table 10 Office Buildings: Water Heating Efficiency Boiler Gas Boiler Small Cogen Electric Water Heater

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

    Case 25 Figure 9 CO2 Emissions from Commercial Buildings (27 Figure 12 CO2 Emissions by Sector (Primary Energy,16 Office Building CO2 Emissions (Reference Case, Primary

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

    Office of Legacy Management (LM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilA group currentBradleyTableSelling7 AugustAFRICAN3uj: ;;IDEC. i' , iiU i.1 '7,

  2. Estimating Radiation Risk from Total Effective Dose Equivalent (TEDE) ISCORS Technical Report No. 1

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilA Approved:AdministrationAnalysisDarby/%2AO 474.2 ChgQuestionsReporting

  3. Estimating Radiation Risk from Total Effective Dose Equivalent (TEDE) ISCORS Technical Report No. 1

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilA Approved:AdministrationAnalysisDarby/%2AO 474.2 ChgQuestionsReportingan 0 Tw

  4. Techniques and Methods Used to Determine the Best Estimate of Total Downwelling Shortwave Radiation

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGESafety Tag:8,, 20153 To.T. J. DetermineDetermine

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

    SciTech Connect (OSTI)

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

    2008-07-31T23:59:59.000Z

    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.

  6. Cost Estimating Handbook for Environmental Restoration

    SciTech Connect (OSTI)

    NONE

    1990-09-01T23:59:59.000Z

    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.

  7. TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION

    E-Print Network [OSTI]

    Skogestad, Sigurd

    TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION BERND WITTGENS, RAJAB LITTO, EVA SØRENSEN 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

  8. Total Energy Management in General Motors

    E-Print Network [OSTI]

    DeKoker, N.

    1979-01-01T23:59:59.000Z

    This paper presents an overview of General Motors' energy management program with special emphasis on energy conservation. Included is a description of the total program organization, plant guidelines, communication and motivation techniques...

  9. Total synthesis and study of myrmicarin alkaloids

    E-Print Network [OSTI]

    Ondrus, Alison Evelynn, 1981-

    2009-01-01T23:59:59.000Z

    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 ...

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

    E-Print Network [OSTI]

    Movassaghi, Mohammad

    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 ...

  11. Total synthesis of cyclotryptamine and diketopiperazine alkaloids

    E-Print Network [OSTI]

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

    2013-01-01T23:59:59.000Z

    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 ...

  12. Total Ore Processing Integration and Management

    SciTech Connect (OSTI)

    Leslie Gertsch; Richard Gertsch

    2003-12-31T23:59:59.000Z

    This report outlines the technical progress achieved for project DE-FC26-03NT41785 (Total Ore Processing Integration and Management) during the period 01 October through 31 December of 2003.

  13. Total Building Air Management: When Dehumidification Counts

    E-Print Network [OSTI]

    Chilton, R. L.; White, C. L.

    1996-01-01T23:59:59.000Z

    , total air management of sensible and latent heat, filtration and zone pressure was brought about through the implementation of non-integrated, composite systems. Composite systems typically are built up of multi-vendor equipment each of which perform...

  14. Gravitational Potential Variations of the Sun and Moon for Estimation

    E-Print Network [OSTI]

    Firoozabadi, Abbas

    compressibility in a fractured reservoir is estimated using the pressure response due to gravitational potentialGravitational Potential Variations of the Sun and Moon for Estimation of Reservoir Compressibility Eric Chang,* SPE, and Abbas Firoozabadi, SPE, Reservoir Engineering Research Inst. Summary Total

  15. SCIENCE: JAMES WEBB SPACE TELESCOPE (JWST) Budget Authority Actual Estimate

    E-Print Network [OSTI]

    ) Prior FY 2011 FY 2012 FY 2013 FY 2014 FY 2015 FY 2016 FY 2017 BTC Total FY 2013 President's Budget TELESCOPE (JWST) Formulation Development Operations JWST-2 FY 2013 BUDGET Budget Authority Actual Estimate (in $ millions) Prior FY 2011 FY 2012 2013 FY 2014 FY 2015 FY 2016 FY 2017 BTC Total FY 2013 President

  16. Estimates of US biofuels consumption, 1990

    SciTech Connect (OSTI)

    Not Available

    1991-10-01T23:59:59.000Z

    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.

  17. Building unbiased estimators from non-gaussian likelihoods with application to shear estimation

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

    Madhavacheril, Mathew S. [Stony Brook Univ., NY (United States); Slosar, Anze [Brookhaven National Lab. (BNL), Upton, NY (United States); McDonald, Patrick [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sehgal, Neelima [Stony Brook Univ., NY (United States)

    2015-01-01T23:59:59.000Z

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the work of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong’s estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.

  18. Building unbiased estimators from non-gaussian likelihoods with application to shear estimation

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

    Madhavacheril, Mathew S.; Slosar, Anze; McDonald, Patrick; Sehgal, Neelima

    2015-01-01T23:59:59.000Z

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the workmore »of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong’s estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.« less

  19. Total football in innovation policy Discussion paper on the evaluation of innovation policy

    E-Print Network [OSTI]

    innovation policy can be derived. Effective innovation policy addresses the issues within the technology1 Total football in innovation policy Discussion paper on the evaluation of innovation policy Koen Schoots, Bert Daniëls, Rodrigo Rivera ECN Policy Studies The innovation climate in the Netherlands

  20. Evaluation of "all weather" microwave-derived land surface temperatures with in situ CEOP measurements

    E-Print Network [OSTI]

    Evaluation of "all weather" microwave-derived land surface temperatures with in situ CEOP conditions. Ts estimates from infrared satellite observations can only be derived under clear sky. Passive from Special Sensor Microwave/Imager measurements, with a spatial resolution of 0.25° × 0.25°, at least

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

    SciTech Connect (OSTI)

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

    2013-01-01T23:59:59.000Z

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

  2. Inflationary universe from higher-derivative quantum gravity

    E-Print Network [OSTI]

    Ratbay Myrzakulov; Sergei Odintsov; Lorenzo Sebastiani

    2015-04-08T23:59:59.000Z

    We consider higher-derivative quantum gravity where renormalization group improved effective action beyond one-loop approximation is derived. Using this effective action, the quantum-corrected FRW equations are analyzed. De Sitter universe solution is found. It is demonstrated that such de Sitter inflationary universe is instable. The slow-roll inflationary parameters are calculated. The contribution of renormalization group improved Gauss-Bonnet term to quantum-corrected FRW equations as well as to instability of de Sitter universe is estimated. It is demonstrated that in this case the spectral index and tensor-to-scalar ratio are consistent with Planck data.

  3. Inflationary universe from higher-derivative quantum gravity

    E-Print Network [OSTI]

    Myrzakulov, Ratbay; Sebastiani, Lorenzo

    2014-01-01T23:59:59.000Z

    We consider higher-derivative quantum gravity where renormalization group improved effective action beyond one-loop approximation is derived. Using this effective action, the quantum-corrected FRW equations are analyzed. De Sitter universe solution is found. It is demonstrated that such de Sitter inflationary universe is instable. The slow-roll inflationary parameters are calculated. The contribution of renormalization group improved Gauss-Bonnet term to quantum-corrected FRW equations as well as to instability of de Sitter universe is estimated. It is demonstrated that in this case the spectral index and tensor-to-scalar ratio are consistent with Planck data.

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

    Office of Environmental Management (EM)

    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...

  5. Asymptomatic Chronic Dislocation of a Cemented Total Hip Prosthesis

    E-Print Network [OSTI]

    Salvi, Andrea Emilio; Florschutz, Anthony Vatroslav; Grappiolo, Guido

    2014-01-01T23:59:59.000Z

    Dislocation of Hip Prosthesis dislocation after total hipa Cemented Total Hip Prosthesis * Mellino Mellini HospitalDislocation of a total hip prosthesis is a painful and

  6. Total Blender Net Input of Petroleum Products

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013,Iowa"Dakota"YearProductionShaleInput Product: Total Input Natural

  7. Derivative

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilA Approved:AdministrationAnalysisDarby/%2AO 474.2 Chg U.S.09 | Nationaldocument

  8. Total System Performance Assessment, 1993: An evaluation of the potential Yucca Mountain repository

    SciTech Connect (OSTI)

    Andrews, R.W.; Dale, T.F.; McNeish, J.A.

    1994-03-01T23:59:59.000Z

    Total System Performance Assessments are an important component in the evaluation of the suitability of Yucca Mountain, Nevada as a potential site for a mined geologic repository for the permanent disposal of high-level radioactive wastes in the United States. The Total System Performance Assessments are conducted iteratively during site characterization to identify issues which should be addressed by the characterization and design activities as well as providing input to regulatory/licensing and programmatic decisions. During fiscal years 1991 and 1992, the first iteration of Total System Performance Assessment (hereafter referred to as TSPA 1991) was completed by Sandia National Laboratories and Pacific Northwest Laboratory. Beginning in fiscal year 1993, the Civilian Radioactive Waste Management System Management and Operating Contractor was assigned the responsibility to plan, coordinate, and contribute to the second iteration of Total System Performance Assessment (hereafter referred to as TSPA 1993). This document presents the objectives, approach, assumptions, input, results, conclusions, and recommendations associated with the Management and Operating Contractor contribution to TSPA 1993. The new information incorporated in TSPA 1993 includes (1) revised estimates of radionuclide solubilities (and their thermal and geochemical dependency), (2) thermal and geochemical dependency of spent fuel waste alteration and glass dissolution rates, (3) new distribution coefficient (k{sub d}) estimates, (4) revised estimates of gas-phase velocities and travel times, and (5) revised hydrologic modeling of the saturated zone which provides updated estimates of the advective flux through the saturated zone.

  9. Cyclical adjustment, capital-labor substitution and total factor productivity convergence East Germany after unification

    E-Print Network [OSTI]

    Pfeifer, Holger

    Cyclical adjustment, capital-labor substitution and total factor productivity convergence ­ East integration and massive help from the Federal Government East German productivity catching up faded out in the nineties. This paper presents panel-data estimates of the productivity adjustment based on a production

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

    SciTech Connect (OSTI)

    Huang, Yu Joe; Brodrick, Jim

    2000-08-01T23:59:59.000Z

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

  11. Budget estimates. Fiscal year 1998

    SciTech Connect (OSTI)

    NONE

    1997-02-01T23:59:59.000Z

    The U.S. Congress has determined that the safe use of nuclear materials for peaceful purposes is a legitimate and important national goal. It has entrusted the Nuclear Regulatory Commission (NRC) with the primary Federal responsibility for achieving that goal. The NRC`s mission, therefore, is to regulate the Nation`s civilian use of byproduct, source, and special nuclear materials to ensure adequate protection of public health and safety, to promote the common defense and security, and to protect the environment. The NRC`s FY 1998 budget requests new budget authority of $481,300,000 to be funded by two appropriations - one is the NRC`s Salaraies and Expenses appropriation for $476,500,000, and the other is NRC`s Office of Inspector General appropriation for $4,800,000. Of the funds appropriated to the NRC`s Salaries and Expenses, $17,000,000, shall be derived from the Nuclear Waste Fund and $2,000,000 shall be derived from general funds. The proposed FY 1998 appropriation legislation would also exempt the $2,000,000 for regulatory reviews and other assistance provided to the Department of Energy from the requirement that the NRC collect 100 percent of its budget from fees. The sums appropriated to the NRC`s Salaries and Expenses and NRC`s Office of Inspector General shall be reduced by the amount of revenues received during FY 1998 from licensing fees, inspection services, and other services and collections, so as to result in a final FY 1998 appropriation for the NRC of an estimated $19,000,000 - the amount appropriated from the Nuclear Waste Fund and from general funds. Revenues derived from enforcement actions shall be deposited to miscellaneous receipts of the Treasury.

  12. Fully corrected estimates of common minke whale abundance in West Greenland in 2007

    E-Print Network [OSTI]

    Laidre, Kristin L.

    Fully corrected estimates of common minke whale abundance in West Greenland in 2007 M.P. HEIDE West Greenland in August and September 2007. A total of 8,670km of survey effort covered 11 strata SURVEY; SATELLITE TAGGING; WEST GREENLAND minke whales to fully corrected total estimates of abundance

  13. Estimating Specialty Costs

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

    1997-03-28T23:59:59.000Z

    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.

  14. Cooling load estimation methods

    SciTech Connect (OSTI)

    McFarland, R.D.

    1984-01-01T23:59:59.000Z

    Ongoing research on quantifying the cooling loads in residential buildings, particularly buildings with passive solar heating systems, is described. Correlations are described that permit auxiliary cooling estimates from monthly average insolation and weather data. The objective of the research is to develop a simple analysis method, useful early in design, to estimate the annual cooling energy required of a given building.

  15. ON DEVELOPMENT OF TOTALLY IMPLANTABLE VESTIBULAR PROSTHESIS

    E-Print Network [OSTI]

    Tang, William C

    ON DEVELOPMENT OF TOTALLY IMPLANTABLE VESTIBULAR PROSTHESIS Andrei M. Shkel 1 Department vestibular prosthesis. The sensing element of the prosthesis is a custom designed one-axis MEMS gyroscope of the prosthesis on a rate table indicate that the device's output matches the average firing rate of vestibular

  16. Total Building Air Management: When Dehumidification Counts 

    E-Print Network [OSTI]

    Chilton, R. L.; White, C. L.

    1996-01-01T23:59:59.000Z

    to heat rejection to contain the size of the ground loop. In areas where seasonal heating is required, but cooling remains the dominant load, a hybrid heat rejection system can be specified. A hybrid system consists of a ground loop sized for total...

  17. Nondestructive estimates of above-ground biomass using terrestrial laser scanning

    E-Print Network [OSTI]

    Jones, Peter JS

    , The Netherlands; 2 CSIRO Land and Water, Private Bag 10, Clayton South, Vic. 3169, Australia; 3 Department these estimates against destructively harvested AGB estimates and AGB derived from allometric equations. We also. Single trees are extracted from the TLS data and quantitative structure models are used to estimate

  18. Estimating a Nucleotide Substitution Rate for Maize from Polymorphism at a Major Domestication Locus

    E-Print Network [OSTI]

    Doebley, John

    Estimating a Nucleotide Substitution Rate for Maize from Polymorphism at a Major Domestication To estimate a rate for single nucleotide substitutions for maize (Zea mays ssp. mays), we have taken advantage ge- nealogy, we have derived estimates for the nucleotide substitution rate for the tb1 intergenic

  19. Sol-gel derived sorbents

    DOE Patents [OSTI]

    Sigman, Michael E.; Dindal, Amy B.

    2003-11-11T23:59:59.000Z

    Described is a method for producing copolymerized sol-gel derived sorbent particles for the production of copolymerized sol-gel derived sorbent material. The method for producing copolymerized sol-gel derived sorbent particles comprises adding a basic solution to an aqueous metal alkoxide mixture for a pH.ltoreq.8 to hydrolyze the metal alkoxides. Then, allowing the mixture to react at room temperature for a precalculated period of time for the mixture to undergo an increased in viscosity to obtain a desired pore size and surface area. The copolymerized mixture is then added to an immiscible, nonpolar solvent that has been heated to a sufficient temperature wherein the copolymerized mixture forms a solid upon the addition. The solid is recovered from the mixture, and is ready for use in an active sampling trap or activated for use in a passive sampling trap.

  20. Magnetic cellulose-derivative structures

    DOE Patents [OSTI]

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

    1986-09-16T23:59:59.000Z

    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.

  1. Robust quantum parameter estimation: Coherent magnetometry with feedback

    SciTech Connect (OSTI)

    Stockton, John K.; Geremia, J.M.; Doherty, Andrew C.; Mabuchi, Hideo [Norman Bridge Laboratory of Physics, Mail Code 12-33, California Institute of Technology, Pasadena, California 91125 (United States)

    2004-03-01T23:59:59.000Z

    We describe the formalism for optimally estimating and controlling both the state of a spin ensemble and a scalar magnetic field with information obtained from a continuous quantum limited measurement of the spin precession due to the field. The full quantum parameter estimation model is reduced to a simplified equivalent representation to which classical estimation and control theory is applied. We consider both the tracking of static and fluctuating fields in the transient and steady-state regimes. By using feedback control, the field estimation can be made robust to uncertainty about the total spin number.

  2. Quaternion Derivatives: The GHR Calculus

    E-Print Network [OSTI]

    Dongpo Xu; Cyrus Jahanchahi; Clive C. Took; Danilo P. Mandic

    2014-09-25T23:59:59.000Z

    Quaternion derivatives in the mathematical literature are typically defined only for analytic (regular) functions. However, in engineering problems, functions of interest are often real-valued and thus not analytic, such as the standard cost function. The HR calculus is a convenient way to calculate formal derivatives of both analytic and non-analytic functions of quaternion variables, however, both the HR and other functional calculus in quaternion analysis have encountered an essential technical obstacle, that is, the traditional product rule is invalid due to the non- commutativity of the quaternion algebra. To address this issue, a generalized form of the HR derivative is proposed based on a general orthogonal system. The so introduced generalization, called the generalized HR (GHR) calculus, encompasses not just the left- and right-hand versions of quaternion derivative, but also enables solutions to some long standing problems, such as the novel product rule, the chain rule, the mean-valued theorem and Taylor's theorem. At the core of the proposed approach is the quaternion rotation, which can naturally be applied to other functional calculi in non-commutative settings. Examples on using the GHR calculus in adaptive signal processing support the analysis.

  3. Estimate of the scatter component in SPECT

    SciTech Connect (OSTI)

    Ivanovic, M.; Weber, D.A. [Univ. of California, Sacramento, CA (United States); Loncaric, S. [Univ. of Zagreb (Croatia)

    1996-12-31T23:59:59.000Z

    Analytical expressions that describe the dependence of slopes and amplitudes of the scatter distribution functions (SDF) on source depth and media density are used to estimate a scatter component in SPECT projection data. Since the ratio of detected scattered to total photons (S/T), SDF amplitude and slope depend strongly on line source length (SL) used to obtain SDFs, we compared estimated scattered components using SDFs, obtained for lengths of 2-21 cm. At 10 cm source depth, S/T changes from 0.19 to 0.36 when SL changes from 2 to 21 cm. Scatter amplitude`s dependence on source depth (d) in water was described by 6.38e{sup -0.186d} for a 2 cm and 16.15e{sup -0.129d} for a 21 cm SL. Slope was described by 0.292d{sup -0.601} for a cm SL and by 0.396d{sup -0.82} for a 21 cm SL. The estimated scatter components are compared with simulated SPECT projection data obtained with Monte Carlo modeling of six hot spheres placed in a cylindrical water filled phantom. The comparison of estimated with simulated total counts/projection shows very good agreement when approaching SDF for a point source (the % difference varied from 2 to 13% for 2 cm SL). Significant overestimate is seen when source length increases.

  4. OGJ300; Smaller list, bigger financial totals

    SciTech Connect (OSTI)

    Beck, R.J.; Biggs, J.B.

    1991-09-30T23:59:59.000Z

    This paper reports on Oil and Gas Journal's list of the largest, publicly traded oil and gas producing companies in the U.S. which is both smaller and larger this year than it was in 1990. It's smaller because it covers fewer companies. Industry consolidation has slashed the number of public companies. As a result, the former OGJ400 has become the OGJ300, which includes the 30 largest limited partnerships. But the assets-ranked list is larger because important financial totals - representing 1990 results - are significantly higher than those of a year ago, despite the lower number of companies. Consolidation of the U.S. producing industry gained momentum throughout the 1980s. Unable to sustain profitability in a period of sluggish energy prices and, for many, rising costs, companies sought relief through mergers or liquidation of producing properties. As this year's list shows, however, surviving companies have managed to grow. Assets for the OGJ300 group totaled $499.3 billion in 1990 - up 6.3% from the 1989 total of last year's OGJ400. Stockholders' equity moved up 5.3% to $170.7 billion. Stockholders' equity was as high as $233.8 billion in 1983.

  5. Cost Estimating Guide

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

    2011-05-09T23:59:59.000Z

    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.

  6. Estimation of food consumption

    SciTech Connect (OSTI)

    Callaway, J.M. Jr.

    1992-04-01T23:59:59.000Z

    The research reported in this document was conducted as a part of the Hanford Environmental Dose Reconstruction (HEDR) Project. The objective of the HEDR Project is to estimate the radiation doses that people could have received from operations at the Hanford Site. Information required to estimate these doses includes estimates of the amounts of potentially contaminated foods that individuals in the region consumed during the study period. In that general framework, the objective of the Food Consumption Task was to develop a capability to provide information about the parameters of the distribution(s) of daily food consumption for representative groups in the population for selected years during the study period. This report describes the methods and data used to estimate food consumption and presents the results developed for Phase I of the HEDR Project.

  7. Operated device estimation framework

    E-Print Network [OSTI]

    Rengarajan, Janarthanan

    2009-05-15T23:59:59.000Z

    Protective device estimation is a challenging task because there are numerous protective devices present in a typical distribution system. Among various protective devices, auto-reclosers and fuses are the main overcurrent protection on distribution...

  8. EXPLORATION Actual Estimate

    E-Print Network [OSTI]

    FY 2015 FY 2016 FY 2017 FY 2013 President's Budget Request 3,821.2 3,712.8 3,932.8 4,076.5 4,076.5 4 Estimate Budget Authority (in $ millions) FY 2011 FY 2012 FY 2013 FY 2014 FY 2015 FY 2016 FY 2017 FY 2013EXPLORATION EXP-1 Actual Estimate Budget Authority (in $ millions) FY 2011 FY 2012 FY 2013 FY 2014

  9. Bounded limit for the Monte Carlo point-flux-estimator

    SciTech Connect (OSTI)

    Grimesey, R.A.

    1981-01-01T23:59:59.000Z

    In a Monte Carlo random walk the kernel K(R,E) is used as an expected value estimator at every collision for the collided flux phi/sub c/ r vector,E) at the detector point. A limiting value for the kernel is derived from a diffusion approximation for the probability current at a radius R/sub 1/ from the detector point. The variance of the collided flux at the detector point is thus bounded using this asymptotic form for K(R,E). The bounded point flux estimator is derived. (WHK)

  10. Transport-constrained extensions of collision and track length estimators for solutions of radiative transport problems

    SciTech Connect (OSTI)

    Kong, Rong, E-mail: kongr413@yahoo.com [Veros Software Inc., 2333 N. Broadway, Santa Ana, CA 92706 (United States)] [Veros Software Inc., 2333 N. Broadway, Santa Ana, CA 92706 (United States); Spanier, Jerome, E-mail: jspanier@uci.edu [Beckman Laser Institute and Medical Clinic, 1002 Health Science Road E., University of California, Irvine, CA 92612 (United States)] [Beckman Laser Institute and Medical Clinic, 1002 Health Science Road E., University of California, Irvine, CA 92612 (United States)

    2013-06-01T23:59:59.000Z

    In this paper we develop novel extensions of collision and track length estimators for the complete space-angle solutions of radiative transport problems. We derive the relevant equations, prove that our new estimators are unbiased, and compare their performance with that of more conventional estimators. Such comparisons based on numerical solutions of simple one dimensional slab problems indicate the the potential superiority of the new estimators for a wide variety of more general transport problems.

  11. TotalView | Argonne Leadership Computing Facility

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6TotalView

  12. 2013 Retail Power Marketers Sales- Total

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at Commercial andSeptember 25,9,1996 N Y M E2003CommercialTotal (Data

  13. 2013 Utility Bundled Retail Sales- Total

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4 Oil demand8)Commercial (DataTotal (Data

  14. EQUUS Total Return Inc | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE FacilityDimondale,South, NewDyerTier2 Submit SoftwareEPB JumpEQUUS Total

  15. 2013 Total Electric Industry- Sales (Megawatthours

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi" ,"Plant","Primary1. TotalRevenue for

  16. Positron interactions with water–total elastic, total inelastic, and elastic differential cross section measurements

    SciTech Connect (OSTI)

    Tattersall, Wade [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia) [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia); Centre for Antimatter-Matter Studies, School of Engineering and Physical Sciences, James Cook University, Townsville, 4810 Queensland (Australia); Chiari, Luca [Centre for Antimatter-Matter Studies, School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide 5001, South Australia (Australia)] [Centre for Antimatter-Matter Studies, School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide 5001, South Australia (Australia); Machacek, J. R.; Anderson, Emma; Sullivan, James P. [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia)] [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia); White, Ron D. [Centre for Antimatter-Matter Studies, School of Engineering and Physical Sciences, James Cook University, Townsville, 4810 Queensland (Australia)] [Centre for Antimatter-Matter Studies, School of Engineering and Physical Sciences, James Cook University, Townsville, 4810 Queensland (Australia); Brunger, M. J. [Centre for Antimatter-Matter Studies, School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide 5001, South Australia (Australia) [Centre for Antimatter-Matter Studies, School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide 5001, South Australia (Australia); Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur (Malaysia); Buckman, Stephen J. [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia) [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia); Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur (Malaysia); Garcia, Gustavo [Instituto de F?sica Fundamental, Consejo Superior de Investigationes Cient?ficas (CSIC), Serrano 113-bis, E-28006 Madrid (Spain)] [Instituto de F?sica Fundamental, Consejo Superior de Investigationes Cient?ficas (CSIC), Serrano 113-bis, E-28006 Madrid (Spain); Blanco, Francisco [Departamento de F?sica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid, E-28040 Madrid (Spain)] [Departamento de F?sica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid, E-28040 Madrid (Spain)

    2014-01-28T23:59:59.000Z

    Utilising a high-resolution, trap-based positron beam, we have measured both elastic and inelastic scattering of positrons from water vapour. The measurements comprise differential elastic, total elastic, and total inelastic (not including positronium formation) absolute cross sections. The energy range investigated is from 1 eV to 60 eV. Comparison with theory is made with both R-Matrix and distorted wave calculations, and with our own application of the Independent Atom Model for positron interactions.

  17. Solar Total Energy Project final test report

    SciTech Connect (OSTI)

    Nelson, R.F.; Abney, L.O.; Towner, M.L. (Georgia Power Co., Shenandoah, GA (USA))

    1990-09-01T23:59:59.000Z

    The Solar Total Energy Project (STEP), a cooperative effort between the United States Department of Energy (DOE) and Georgia Power Company (GPC) located at Shenandoah, Georgia, has undergone several design modifications based on experience from previous operations and test programs. The experiences encountered were discussed in detail in the Solar Total Energy Project Summary Report'' completed in 1987 for DOE. Most of the proposed changes discussed in this report were installed and tested in 1987 as part of two 15-day test programs (SNL Contract No. 06-3049). However, several of the suggested changes were not completed before 1988. These plant modifications include a new distributed control system for the balance of plant (BOP), a fiber a optical communications ring for the field control system, and new control configuration reflecting the new operational procedures caused by the plant modifications. These modifications were tested during a non-consecutive day test, and a 60-day field test conducted during the autumn of 1989. These test were partially funded by SNL under Contract No. 42-4859, dated June 22, 1989. Results of these tests and preliminary analysis are presented in this test summary report. 9 refs., 19 figs., 7 tabs.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal"1" " (Estimates5.6. Total

  19. "Table A47. Selected Energy Operating Ratios for Total Energy Consumption for"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal"1" " (Estimates5.6. Total7.7.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal"1" " (Estimates5.6.8. Total

  1. MELE: Maximum Entropy Leuven Estimators

    E-Print Network [OSTI]

    Paris, Quirino

    2001-01-01T23:59:59.000Z

    of the Generalized Maximum Entropy Estimator of the Generaland Douglas Miller, Maximum Entropy Econometrics, Wiley andCalifornia Davis MELE: Maximum Entropy Leuven Estimators by

  2. Thermodynamic estimation: Ionic materials

    SciTech Connect (OSTI)

    Glasser, Leslie, E-mail: l.glasser@curtin.edu.au

    2013-10-15T23:59:59.000Z

    Thermodynamics establishes equilibrium relations among thermodynamic parameters (“properties”) and delineates the effects of variation of the thermodynamic functions (typically temperature and pressure) on those parameters. However, classical thermodynamics does not provide values for the necessary thermodynamic properties, which must be established by extra-thermodynamic means such as experiment, theoretical calculation, or empirical estimation. While many values may be found in the numerous collected tables in the literature, these are necessarily incomplete because either the experimental measurements have not been made or the materials may be hypothetical. The current paper presents a number of simple and relible estimation methods for thermodynamic properties, principally for ionic materials. The results may also be used as a check for obvious errors in published values. The estimation methods described are typically based on addition of properties of individual ions, or sums of properties of neutral ion groups (such as “double” salts, in the Simple Salt Approximation), or based upon correlations such as with formula unit volumes (Volume-Based Thermodynamics). - Graphical abstract: Thermodynamic properties of ionic materials may be readily estimated by summation of the properties of individual ions, by summation of the properties of ‘double salts’, and by correlation with formula volume. Such estimates may fill gaps in the literature, and may also be used as checks of published values. This simplicity arises from exploitation of the fact that repulsive energy terms are of short range and very similar across materials, while coulombic interactions provide a very large component of the attractive energy in ionic systems. Display Omitted - Highlights: • Estimation methods for thermodynamic properties of ionic materials are introduced. • Methods are based on summation of single ions, multiple salts, and correlations. • Heat capacity, entropy, lattice energy, enthalpy, Gibbs energy values are available.

  3. Elastic scattering and total reaction cross section of {sup 6}He+{sup 120}Sn

    SciTech Connect (OSTI)

    Faria, P. N. de; Lichtenthaeler, R.; Pires, K. C. C.; Lepine-Szily, A.; Guimaraes, V.; Mendes, D. R. Jr.; Barioni, A.; Morcelle, V.; Morais, M. C.; Camargo, O. Jr.; Alcantara Nunez, J. [Instituto de Fisica-Universidade de Sao Paulo, C. P. 66318, 05389-970 Sao Paulo, SP (Brazil); Moro, A. M. [Departamento de FAMN, Universidad de Sevilla, Apartado 1065, E-41080 Sevilla (Spain); Arazi, A. [Laboratorio Tandar, Comision Nacional de Energia Atomica, Av. del Libertador 8250, 1429 Buenos Aires (Argentina); Rodriguez-Gallardo, M. [Departamento de FAMN, Universidad de Sevilla, Apartado 1065, E-41080 Sevilla (Spain); Instituto de Estructura de la Materia, CSIC, Serrano 123, E-28006 Madrid (Spain); Assuncao, M. [Universidade Federal de Sao Paulo, Campus Diadema, 09941-510 Sao Paulo, SP (Brazil)

    2010-04-15T23:59:59.000Z

    The elastic scattering of {sup 6}He on {sup 120}Sn has been measured at four energies above the Coulomb barrier using the {sup 6}He beam produced at the RIBRAS (Radioactive Ion Beams in Brasil) facility. The elastic angular distributions have been analyzed with the optical model and three- and four-body continuum-discretized coupled-channels calculations. The total reaction cross sections have been derived and compared with other systems of similar masses.

  4. Maximum total organic carbon limit for DWPF melter feed

    SciTech Connect (OSTI)

    Choi, A.S.

    1995-03-13T23:59:59.000Z

    DWPF recently decided to control the potential flammability of melter off-gas by limiting the total carbon content in the melter feed and maintaining adequate conditions for combustion in the melter plenum. With this new strategy, all the LFL analyzers and associated interlocks and alarms were removed from both the primary and backup melter off-gas systems. Subsequently, D. Iverson of DWPF- T{ampersand}E requested that SRTC determine the maximum allowable total organic carbon (TOC) content in the melter feed which can be implemented as part of the Process Requirements for melter feed preparation (PR-S04). The maximum TOC limit thus determined in this study was about 24,000 ppm on an aqueous slurry basis. At the TOC levels below this, the peak concentration of combustible components in the quenched off-gas will not exceed 60 percent of the LFL during off-gas surges of magnitudes up to three times nominal, provided that the melter plenum temperature and the air purge rate to the BUFC are monitored and controlled above 650 degrees C and 220 lb/hr, respectively. Appropriate interlocks should discontinue the feeding when one or both of these conditions are not met. Both the magnitude and duration of an off-gas surge have a major impact on the maximum TOC limit, since they directly affect the melter plenum temperature and combustion. Although the data obtained during recent DWPF melter startup tests showed that the peak magnitude of a surge can be greater than three times nominal, the observed duration was considerably shorter, on the order of several seconds. The long surge duration assumed in this study has a greater impact on the plenum temperature than the peak magnitude, thus making the maximum TOC estimate conservative. Two models were used to make the necessary calculations to determine the TOC limit.

  5. Project Profile: Transformational Approach to Reducing the Total...

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

    Transformational Approach to Reducing the Total System Costs of Building-Integrated Photovoltaics Project Profile: Transformational Approach to Reducing the Total System Costs of...

  6. Enantioselective total syntheses of acylfulvene, irofulven, and the agelastatins

    E-Print Network [OSTI]

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

    2010-01-01T23:59:59.000Z

    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 ...

  7. Total synthesis of Class II and Class III Galbulimima Alkaloids

    E-Print Network [OSTI]

    Tjandra, Meiliana

    2010-01-01T23:59:59.000Z

    I. Total Synthesis of All Class III Galbulimima Alkaloids We describe the total synthesis of (+)- and (-)-galbulimima alkaloid 13, (-)-himgaline anad (-)-himbadine. The absolute stereochemistry of natural (-)-galbulimima ...

  8. In vivo tibial force measurement after total knee arthroplasty

    E-Print Network [OSTI]

    D'Lima, Darryl David

    2007-01-01T23:59:59.000Z

    and Colwell, C. W. , Jr. : The press-fit condylar total kneeColwell, C. W. , Jr. : Press-fit condylar design total knee

  9. NREL: Building America Total Quality Management - 2015 Peer Review...

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

    Building America Total Quality Management - 2015 Peer Review NREL: Building America Total Quality Management - 2015 Peer Review Presenter: Stacey Rothgeb, NREL View the...

  10. Binder enhanced refuse derived fuel

    DOE Patents [OSTI]

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

    1996-01-01T23:59:59.000Z

    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.

  11. Organic derivatives of zirconium phosphate

    E-Print Network [OSTI]

    Fine, Steven Beryl

    1980-01-01T23:59:59.000Z

    -zirconium phosphate derivatives. 9 Thermogravimetric analysis of y-zirconium 2-hydroxy- 1-ethyl phosphate. 25 10 Thermogravimetric analysis of y-zirconium 2-carboxy- 2-hydroxy-1-ethyl phosphate. 28 11 Thermo gravimetric 1-ethyl phosphate. analysis of n...-ZrP Figure 3. A comparison of the layered structures of c and y zirconium phosphate. according to Yamanaka [9], ethylene oxide is 18. 4 A [ 10] . When this phase is dehydrated at 150 for one hour, the d-spacing decreases to 17. 2 A, but when left in air...

  12. Deriving Ontologies from XML Schema

    E-Print Network [OSTI]

    Bedini, Ivan; Nguyen, Benjamin

    2010-01-01T23:59:59.000Z

    In this paper, we present a method and a tool for deriving a skeleton of an ontology from XML schema files. We first recall what an is ontology and its relationships with XML schemas. Next, we focus on ontology building methodology and associated tool requirements. Then, we introduce Janus, a tool for building an ontology from various XML schemas in a given domain. We summarize the main features of Janus and illustrate its functionalities through a simple example. Finally, we compare our approach to other existing ontology building tools.

  13. Analytical models for total dose ionization effects in MOS devices.

    SciTech Connect (OSTI)

    Campbell, Phillip Montgomery; Bogdan, Carolyn W.

    2008-08-01T23:59:59.000Z

    MOS devices are susceptible to damage by ionizing radiation due to charge buildup in gate, field and SOI buried oxides. Under positive bias holes created in the gate oxide will transport to the Si / SiO{sub 2} interface creating oxide-trapped charge. As a result of hole transport and trapping, hydrogen is liberated in the oxide which can create interface-trapped charge. The trapped charge will affect the threshold voltage and degrade the channel mobility. Neutralization of oxidetrapped charge by electron tunneling from the silicon and by thermal emission can take place over long periods of time. Neutralization of interface-trapped charge is not observed at room temperature. Analytical models are developed that account for the principal effects of total dose in MOS devices under different gate bias. The intent is to obtain closed-form solutions that can be used in circuit simulation. Expressions are derived for the aging effects of very low dose rate radiation over long time periods.

  14. 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

  15. External Dose Estimates from

    E-Print Network [OSTI]

    ; - calculated separately for the most important radionuclides produced in nuclear weapons tests. Those would averages for all tests. 2. Provide a list of references regarding: (1) the history of nuclear weapons to the Population of the Continental U.S. from Nevada Weapons Tests and Estimates of Deposition Density

  16. UNSCENTED KALMAN FILTERING FOR SPACECRAFT ATTITUDE STATE AND PARAMETER ESTIMATION

    E-Print Network [OSTI]

    Hall, Christopher D.

    AAS-04-115 UNSCENTED KALMAN FILTERING FOR SPACECRAFT ATTITUDE STATE AND PARAMETER ESTIMATION Matthew C. VanDyke , Jana L. Schwartz , Christopher D. Hall An Unscented Kalman Filter (UKF) is derived with an Extended Kalman Filter (EKF). The EKF is an extension of the linear Kalman Filter for nonlinear systems

  17. Greenland snow accumulation estimates from satellite radar scatterometer data

    E-Print Network [OSTI]

    Long, David G.

    Greenland snow accumulation estimates from satellite radar scatterometer data Mark R. Drinkwater accumulation on the Greenland ice sheet. Microwave radar backscatter images of Greenland are derived using (or decrease) in net snow accumulation on the polar ice caps. The net mass balance of the Greenland

  18. Survival Estimates for the Passage of Spring-Migrating Juvenile Salmonids through Snake and Columbia River Dams and Reservoirs, 2008.

    SciTech Connect (OSTI)

    Faulkner, James R.; Smith, Steven G.; Muir, William D. [Northwest Fisheries Science Center

    2009-06-23T23:59:59.000Z

    In 2008, the National Marine Fisheries Service completed the sixteenth year of a study to estimate survival and travel time of juvenile salmonids Oncorhynchus spp. passing through dams and reservoirs on the Snake and Columbia Rivers. All estimates were derived from detections of fish tagged with passive integrated transponder (PIT) tags. We PIT tagged and released a total of 18,565 hatchery steelhead O. mykiss, 15,991 wild steelhead, and 9,714 wild yearling Chinook salmon O. tshawytscha at Lower Granite Dam in the Snake River. In addition, we utilized fish PIT tagged by other agencies at traps and hatcheries upstream from the hydropower system and at sites within the hydropower system in both the Snake and Columbia Rivers. These included 122,061 yearling Chinook salmon tagged at Lower Granite Dam for evaluation of latent mortality related to passage through Snake River dams. PIT-tagged smolts were detected at interrogation facilities at Lower Granite, Little Goose, Lower Monumental, Ice Harbor, McNary, John Day, and Bonneville Dams and in the PIT-tag detector trawl operated in the Columbia River estuary. Survival estimates were calculated using a statistical model for tag-recapture data from single release groups (the single-release model). Primary research objectives in 2008 were to: (1) estimate reach survival and travel time in the Snake and Columbia Rivers throughout the migration period of yearling Chinook salmon and steelhead, (2) evaluate relationships between survival estimates and migration conditions, and (3) evaluate the survival estimation models under prevailing conditions. This report provides reach survival and travel time estimates for 2008 for PIT-tagged yearling Chinook salmon (hatchery and wild), hatchery sockeye salmon O. nerka, hatchery coho salmon O. kisutch, and steelhead (hatchery and wild) in the Snake and Columbia Rivers. Additional details on the methodology and statistical models used are provided in previous reports cited here. Survival and detection probabilities were estimated precisely for most of the 2008 yearling Chinook salmon and steelhead migrations. Hatchery and wild fish were combined in some of the analyses. For yearling Chinook salmon, overall percentages for combined release groups used in survival analyses in the Snake River were 80% hatchery-reared and 20% wild. For steelhead, the overall percentages were 65% hatchery-reared and 35% wild. Estimated survival from the tailrace of Lower Granite Dam to the tailrace of Little Goose Dam averaged 0.939 for yearling Chinook salmon and 0.935 for steelhead.

  19. Use of Cost Estimating Relationships

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

    1997-03-28T23:59:59.000Z

    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.

  20. Rise of Kp Total Cross Section and Universality

    E-Print Network [OSTI]

    Muneyuki Ishida; Vernon Barger

    2011-06-24T23:59:59.000Z

    The increase of the measured hadronic total cross sections at the highest energies is empirically described by squared log of center-of-mass energy sqrt s as sigma(tot)= B (log s)2, consistent with the energy dependence of the Froissart unitarity bound. The coefficient B is argued to have a universal value, but this is not proved directly from QCD. In the previous tests of this universality, the p(pbar)p, pi p, and K p forward scatterings were analyzed independently and found to be consistent with B(pp) = B(pip) = B(Kp), although the determined value of B(Kp) had large uncertainty. In the present work, we have further analyzed forward Kp scattering to obtain a more exact value of B(Kp). Making use of continuous moment sum rules(CMSR) we have fully exploited the information of low-energy scattering data to predict the high-energy behavior of the amplitude hrough duality. The estimation of B(Kp) is improved remarkably, and our result strongly supports the universality of B.

  1. Analogue of the quantum total probability rule from Paraconsistent bayesian probability theory

    E-Print Network [OSTI]

    R. Salazar; C. Jara-Figueroa; A. Delgado

    2014-08-22T23:59:59.000Z

    We derive an analogue of the quantum total probability rule by constructing a probability theory based on paraconsistent logic. Bayesian probability theory is constructed upon classical logic and a desiderata, that is, a set of desired properties that the theory must obey. We construct a new probability theory following the desiderata of Bayesian probability theory but replacing the classical logic by paraconsistent logic. This class of logic has been conceived to handle eventual inconsistencies or contradictions among logical propositions without leading to the trivialisation of the theory. Within this Paraconsistent bayesian probability theory it is possible to deduce a new total probability rule which depends on the probabilities assigned to the inconsistencies. Certain assignments of values for these probabilities lead to expressions identical to those of Quantum mechanics, in particular to the quantum total probability rule obtained via symmetric informationally complete positive- operator valued measure.

  2. MONITORED GEOLOGIC REPOSITORY LIFE CYCLE COST ESTIMATE ASSUMPTIONS DOCUMENT

    SciTech Connect (OSTI)

    R.E. Sweeney

    2001-02-08T23:59:59.000Z

    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.

  3. Analysis of the total system life cycle cost for the Civilian Radioactive Waste Management Program

    SciTech Connect (OSTI)

    NONE

    1989-05-01T23:59:59.000Z

    The total-system life-cycle cost (TSLCC) analysis for the Department of Energy`s (DOE) Civilian Radioactive Waste Management Program is an ongoing activity that helps determine whether the revenue-producing mechanism established by the Nuclear Waste Policy Act of 1982 -- a fee levied on electricity generated in commercial nuclear power plants -- is sufficient to cover the cost of the program. This report provides cost estimates for the sixth annual evaluation of the adequacy of the fee and is consistent with the program strategy and plans contained in the DOE`s Draft 1988 Mission Plan Amendment. The total-system cost for the system with a repository at Yucca Mountain, Nevada, a facility for monitored retrievable storage (MRS), and a transportation system is estimated at $24 billion (expressed in constant 1988 dollars). In the event that a second repository is required and is authorized by the Congress, the total-system cost is estimated at $31 to $33 billion, depending on the quantity of spent fuel to be disposed of. The $7 billion cost savings for the single-repository system in comparison with the two-repository system is due to the elimination of $3 billion for second-repository development and $7 billion for the second-repository facility. These savings are offset by $2 billion in additional costs at the first repository and $1 billion in combined higher costs for the MRS facility and transportation. 55 refs., 2 figs., 24 tabs.

  4. 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

  5. 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 (OSTI)

    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

    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.

  6. Soil Test P vs. Total P in Wisconsin Soils

    E-Print Network [OSTI]

    Balser, Teri C.

    Soil Test P vs. Total P in Wisconsin Soils Larry G. Bundy & Laura W. Good Department of Soil Science University of Wisconsin-Madison #12;Introduction · Soil test P is often measured · Little information is available on total P content of soils · Why do we care about total P now? ­ Soil total P

  7. Total Operators and Inhomogeneous Proper Values Equations

    E-Print Network [OSTI]

    Jose G. Vargas

    2015-03-27T23:59:59.000Z

    Kaehler's two-sided angular momentum operator, K + 1, is neither vector-valued nor bivector-valued. It is total in the sense that it involves terms for all three dimensions. Constant idempotents that are "proper functions" of K+1's components are not proper functions of K+1. They rather satisfy "inhomogeneous proper-value equations", i.e. of the form (K + 1)U = {\\mu}U + {\\pi}, where {\\pi} is a scalar. We consider an equation of that type with K+1 replaced with operators T that comprise K + 1 as a factor, but also containing factors for both space and spacetime translations. We study the action of those T's on linear combinations of constant idempotents, so that only the algebraic (spin) part of K +1 has to be considered. {\\pi} is now, in general, a non-scalar member of a Kaehler algebra. We develop the system of equations to be satisfied by the combinations of those idempotents for which {\\pi} becomes a scalar. We solve for its solutions with {\\mu} = 0, which actually also makes {\\pi} = 0: The solutions with {\\mu} = {\\pi} = 0 all have three constituent parts, 36 of them being different in the ensemble of all such solutions. That set of different constituents is structured in such a way that we might as well be speaking of an algebraic representation of quarks. In this paper, however, we refrain from pursuing this identification in order to emphasize the purely mathematical nature of the argument.

  8. Totally Corrective Boosting with Cardinality Penalization

    E-Print Network [OSTI]

    Vasil S. Denchev; Nan Ding; Shin Matsushima; S. V. N. Vishwanathan; Hartmut Neven

    2015-04-07T23:59:59.000Z

    We propose a totally corrective boosting algorithm with explicit cardinality regularization. The resulting combinatorial optimization problems are not known to be efficiently solvable with existing classical methods, but emerging quantum optimization technology gives hope for achieving sparser models in practice. In order to demonstrate the utility of our algorithm, we use a distributed classical heuristic optimizer as a stand-in for quantum hardware. Even though this evaluation methodology incurs large time and resource costs on classical computing machinery, it allows us to gauge the potential gains in generalization performance and sparsity of the resulting boosted ensembles. Our experimental results on public data sets commonly used for benchmarking of boosting algorithms decidedly demonstrate the existence of such advantages. If actual quantum optimization were to be used with this algorithm in the future, we would expect equivalent or superior results at much smaller time and energy costs during training. Moreover, studying cardinality-penalized boosting also sheds light on why unregularized boosting algorithms with early stopping often yield better results than their counterparts with explicit convex regularization: Early stopping performs suboptimal cardinality regularization. The results that we present here indicate it is beneficial to explicitly solve the combinatorial problem still left open at early termination.

  9. Survival Estimates for the Passage of Spring-Migrating Juvenile Salmonids through Snake and Columbia River Dams and Reservoirs, 2001-2002 Annual Report.

    SciTech Connect (OSTI)

    Zabel, Richard; Williams, John G.; Smith, Steven G. (Northwest and Alaska Fisheries Science Center, Fish Ecology Division, Seattle, WA)

    2002-06-01T23:59:59.000Z

    In 2001, the National Marine Fisheries Service and the University of Washington completed the ninth year of a study to estimate survival and travel time of juvenile salmonids (Oncorhynchus spp.) passing through dams and reservoirs on the Snake and Columbia Rivers. All estimates were derived from passive integrated transponder (PIT)-tagged fish. We PIT tagged and released at Lower Granite Dam a total of 17,028 hatchery and 3,550 wild steelhead. In addition, we utilized fish PIT tagged by other agencies at traps and hatcheries upstream of the hydropower system and sites within the hydropower system. PIT-tagged smolts were detected at interrogation facilities at Lower Granite, Little Goose, Lower Monumental, McNary, John Day, and Bonneville Dams and in the PIT-tag detector trawl operated in the Columbia River estuary. Survival estimates were calculated using the Single-Release Model. Primary research objectives in 2001 were to: (1) estimate reach and project survival and travel time in the Snake and Columbia Rivers throughout the yearling chinook salmon and steelhead migrations; (2) evaluate relationships between survival estimates and migration conditions; and (3) evaluate the survival-estimation models under prevailing conditions. This report provides reach survival and travel time estimates for 2001 for PIT-tagged yearling chinook salmon and steelhead (hatchery and wild) in the Snake and Columbia Rivers. Results are reported primarily in the form of tables and figures with a minimum of text. More details on methodology and statistical models used are provided in previous reports cited in the text. Results for summer-migrating chinook salmon will be reported separately.

  10. Survival Estimates for the Passage of Spring-Migrating Juvenile Salmonids through Snake and Columbia River Dams and Reservoirs, 2005-2006 Annual Report.

    SciTech Connect (OSTI)

    Smith, Steven G.; Muir, William D.; Marsh, Douglas M. (National Marine Fisheries Service, Northwest Fisheries Science Center, Fish Ecology Division, Seattle, WA)

    2006-05-01T23:59:59.000Z

    In 2005, the National Marine Fisheries Service and the University of Washington completed the thirteenth year of a study to estimate survival and travel time of juvenile salmonids Oncorhynchus spp. passing through dams and reservoirs on the Snake and Columbia Rivers. All estimates were derived from detections of fish tagged with passive integrated transponder tags (PIT tags). We PIT tagged and released a total of 18,439 hatchery steelhead, 5,315 wild steelhead, and 6,964 wild yearling Chinook salmon at Lower Granite Dam in the Snake River. In addition, we utilized fish PIT tagged by other agencies at traps and hatcheries upstream from the hydropower system and at sites within the hydropower system in both the Snake and Columbia Rivers. PIT-tagged smolts were detected at interrogation facilities at Lower Granite, Little Goose, Lower Monumental, Ice Harbor, McNary, John Day, and Bonneville Dams and in the PIT-tag detector trawl operated in the Columbia River estuary. Survival estimates were calculated using a statistical model for tag-recapture data from single release groups (the ''single-release model''). Primary research objectives in 2005 were: (1) Estimate reach survival and travel time in the Snake and Columbia Rivers throughout the migration period of yearling Chinook salmon O. tshawytscha and steelhead O. mykiss. (2) Evaluate relationships between survival estimates and migration conditions. (3) Evaluate the survival estimation models under prevailing conditions. This report provides reach survival and travel time estimates for 2005 for PIT-tagged yearling Chinook salmon (hatchery and wild), hatchery sockeye salmon O. nerka, hatchery coho salmon O. kisutch, and steelhead (hatchery and wild) in the Snake and Columbia Rivers. Additional details on the methodology and statistical models used are provided in previous reports cited here.

  11. Introduction Aliphatic polyesters derived from renewable

    E-Print Network [OSTI]

    Introduction Aliphatic polyesters derived from renewable resources are of increasing interest, there are also opportunities to derive lactones from biomass, which can then be converted to a wide range

  12. A study on real estate derivatives

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    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 ...

  13. Extremal index estimation 

    E-Print Network [OSTI]

    Kampa, Aleksander Edward

    1988-01-01T23:59:59.000Z

    ) December 1988 Extremal Index Estimation (December 1988) Aleksander Edward Kampa, Ecole Centrale de Paris, France Chairman of Advisory Comittee: Dr. Tailen Hsing If (X ) is a strictly stationary sequence satisfying certain n dependence restrictions (e.... g. D or A), then the relationship between the extremal properties of (X ) and its associated independent sequence (X ) n n can. under certain conditions, be summed up by a single constant Be[0. 1]. called the extremal index. Results of extreme...

  14. Estimating Corn Grain Yields

    E-Print Network [OSTI]

    Blumenthal, Jurg M.; Thompson, Wayne

    2009-06-12T23:59:59.000Z

    can collect samples from a corn field and use this data to calculate the yield estimate. An interactive grain yield calculator is provided in the Appendix of the pdf version of this publication. The calculator is also located in the publication.... Plan and prepare for sample and data collection. 2. Collect field samples and record data. 3. Analyze the data using the interactive grain yield calculator in the Appendix. Plan and prepare for sample and data collection Predetermine sample locations...

  15. Production of jet fuels from coal-derived liquids

    SciTech Connect (OSTI)

    Johnson, R.W.; Zackro, W.C.; Czajkowski, G. (Allied-Signal, Inc., Des Plaines, IL (USA). Engineered Materials Research Center); Shah, P.P.; Kelly, A.P. (UOP, Inc., Des Plaines, IL (USA))

    1989-03-01T23:59:59.000Z

    The US Air Force is evaluating various feedstock sources of endothermic fuels. The technical feasibility of producing endothermic fuel from the naphtha by-product from Great Plains Gasification Plant in Beulah, North Dakota was evaluated. The capital and operating costs of deriving the fuel from coal naphtha were also estimated. The coal naphtha from Great Plains was successfully processed to remove sulfur, nitrogen and oxygen contaminants (UOP HD Unibon{reg sign} Hydrotreating) and then to saturate aromatic molecules (UOP AH Unibon{reg sign}). The AH Unibon product was fractionated to yield endothermic fuel candidates with less than 5% aromatics. The major cycloparaffins in the AH Unibon product were cyclohexane and methylcyclohexane. The production of endothermic fuel from the naphtha by-product stream was estimated to be cost competitive with existing technology. 17 figs., 23 tabs.

  16. The Fourth Partial Derivative In Transport Dynamics

    E-Print Network [OSTI]

    Trinh Khanh Tuoc

    2010-01-11T23:59:59.000Z

    A new fourth partial derivative is introduced for the study of transport dynamics. It is a Lagrangian partial derivative following the path of diffusion, not the path of convection. Use of this derivative decouples the effect of diffusion and convection and simplifies the analysis of transport processes.

  17. Postgraduate Scholarship Pricing temperature derivatives and modelling

    E-Print Network [OSTI]

    Banaji,. Murad

    the volumetric risk of the energy units sold, rather than the price risk of each unit. Weather derivativesPostgraduate Scholarship Pricing temperature derivatives and modelling the market price of risk: Pricing temperature derivatives and modelling the market price of risk. Main Supervisor: A. Alexandridis

  18. Estimation of steady-state basic parameters of stars

    B. V. Vasiliev

    2000-03-30T23:59:59.000Z

    From a minimum of total energy of celestial bodies, their basic parameters are obtained. The steady-state values of the mass, radius, and temperature of stars and white dwarfs, as well as masses of pulsars are calculated. The luminosity and giromagnetic ratio of celestial bodies are estimated. All the obtained values are in a satisfactory agreement with observation data.

  19. A Hierarchical Model for Estimating the Reliability of Complex Systems

    E-Print Network [OSTI]

    Reese, Shane

    an approximation to the joint posterior distribution on the total system reliability was obtained. Many reliability or bounding moments of the system reliability posterior distribution (Cole (1975), Mastran (1976), DostalA Hierarchical Model for Estimating the Reliability of Complex Systems Valen E. Johnson, Todd L

  20. T.Q.M.: Total Quality Management or total quackery and mismanagement

    SciTech Connect (OSTI)

    Stallard, T.F.

    1996-12-31T23:59:59.000Z

    The concept of total quality management (TQM) is outlined. The basic idea of TQM is that quality products and services will lead a company to greater financial success than will mass quantities of inferior products. The following topics are outlined: standard labs and TQM;TQM benefits to be gained by standard labs; TQM at standard labs is quality improvement system (QIS), TQM, reduces of attitude. QIS team leader training agenda; and the safety connection.

  1. Managerial information behaviour: Relationships among Total Quality Management orientation, information use environments, and managerial roles

    E-Print Network [OSTI]

    Simard, C; Rice, Ronald E

    2006-01-01T23:59:59.000Z

    TQM orientations: total quality control (TQC) and totalIts Implications for Total Quality Control and Total QualityWilenski, 1967). Total Quality Control, organizational

  2. Training Signal Design for Estimation of Correlated MIMO Channels with Colored

    E-Print Network [OSTI]

    Hager, William

    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

  3. A NON-PARAMETRIC ESTIMATOR FOR RESERVE PRICES IN PROCUREMENT AUCTIONS

    E-Print Network [OSTI]

    Cengarle, María Victoria

    in implementing the optimal reserve price is the use of unobservables such as the distribution of supplier's costsA NON-PARAMETRIC ESTIMATOR FOR RESERVE PRICES IN PROCUREMENT AUCTIONS MARTIN BICHLER and JAYANT estimation of the bid distributions and the possibility to derive optimal reserve prices. In this paper we

  4. A posteriori error estimates, stopping criteria, and adaptivity for multiphase compositional Darcy flows in porous media

    E-Print Network [OSTI]

    A posteriori error estimates, stopping criteria, and adaptivity for multiphase compositional Darcy derive a posteriori error estimates for the compositional model of multiphase Darcy flow in porous media, consisting of a system of strongly coupled nonlinear unsteady partial differential and algebraic equations

  5. Seismic Velocity Estimation from Time Migration Velocities M. K. Cameron, S. B. Fomel, J. A. Sethian

    E-Print Network [OSTI]

    Sethian, James A.

    Seismic Velocity Estimation from Time Migration Velocities M. K. Cameron, S. B. Fomel, J. A the problem of estimating seismic velocities inside the earth which is necessary for obtaining seismic images in regular Cartesian coordinates. We derive a relation between the true seismic velocities and the routinely

  6. Strichartz estimates for the Schr\\"odinger equation on polygonal domains

    E-Print Network [OSTI]

    Blair, Matthew D; Herr, Sebastian; Marzuola, Jeremy L

    2010-01-01T23:59:59.000Z

    We prove Strichartz estimates with a loss of derivatives for the Schr\\"odinger equation on polygonal domains with either Dirichlet or Neumann homogeneous boundary conditions. Using a standard doubling procedure, estimates the on polygon follow from those on Euclidean surfaces with conical singularities. We develop a Littlewood-Paley squarefunction estimate with respect to the spectrum of the Laplacian on these spaces. This allows us to reduce matters to proving estimates at each frequency scale. The problem can be localized in space provided the time intervals are sufficiently small. Strichartz estimates then follow from a result of the second author regarding the Schr\\"odinger equation on the Euclidean cone.

  7. Contribution of nano-scale effects to the total efficiency of converters of thermal neutrons on the basis of gadolinium foils

    E-Print Network [OSTI]

    D. A. Abdushukurov; D. V. Bondarenko; Kh. Kh. Muminov; D. Yu. Chistyakov

    2008-02-04T23:59:59.000Z

    We study the influence of nano-scale layers of converters made from natural gadolinium and its 157 isotope into the total efficiency of registration of thermal neutrons. Our estimations show that contribution of low-energy Auger electrons with the runs about nanometers in gadolinium, to the total efficiency of neutron converters in this case is essential and results in growth of the total efficiency of converters. The received results are in good consent to the experimental data.

  8. Decomposition of the total momentum in a linear dielectric into field and matter components

    SciTech Connect (OSTI)

    Crenshaw, Michael E., E-mail: michael.crenshaw@us.army.mil

    2013-11-15T23:59:59.000Z

    The long-standing resolution of the Abraham–Minkowski electromagnetic momentum controversy is predicated on a decomposition of the total momentum of a closed continuum electrodynamic system into separate field and matter components. Using a microscopic model of a simple linear dielectric, we derive Lagrangian equations of motion for the electric dipoles and show that the dielectric can be treated as a collection of stationary simple harmonic oscillators that are driven by the electric field and produce a polarization field in response. The macroscopic energy and momentum are defined in terms of the electric, magnetic, and polarization fields that travel through the dielectric together as a pulse of electromagnetic radiation. We conclude that both the macroscopic total energy and the macroscopic total momentum are entirely electromagnetic in nature for a simple linear dielectric in the absence of significant reflections. -- Highlights: •The total momentum in a dielectric is identified by conservation principles. •The total momentum in a dielectric cannot be decomposed into field and matter parts. •A component of momentum in a dielectric is due to motion of the polarization field.

  9. Image-based meteorologic visibility estimation

    E-Print Network [OSTI]

    Graves, Nathan

    2011-01-01T23:59:59.000Z

    the estimated luminance. . . . . . . . . . . . . . . . . .Nephelometer . . . . . . 3.4.3 Luminance Meter . . . . 4intensity and the estimated luminance. . . . . . . . . .

  10. Density derived estimates of standing crop and net primary production in the giant kelp Macrocystis pyrifera

    E-Print Network [OSTI]

    Reed, Daniel; Rassweiler, Andrew; Arkema, Katie

    2009-01-01T23:59:59.000Z

    1991) Production and standing stocks of the kelp Macrocystisproduction in the giant kelp Macrocystis pyrifera Danielproduction (NPP) in the giant kelp Macrocystis pyrifera off

  11. Considerations for the use of radar-derived precipitation estimates in determining return intervals for extreme

    E-Print Network [OSTI]

    Allen, Robert J.

    to those based on traditional rain gauge networks. For both the radar and gauge data, increasing, considerable differences between radar ARF and gauge ARF exist. Radar ARF decays at a faster rate (with increasing area) than gauge ARF. For a basin size of 20,000 km2 , the percent difference between radar ARF

  12. Total thermoelectric-power withdrawals Freshwater thermoelectric-power withdrawals Saline-water thermoelectric-power withdrawals

    E-Print Network [OSTI]

    Total thermoelectric-power withdrawals Freshwater thermoelectric-power withdrawals Saline-water thermoelectric-power withdrawals Louisiana New Hampshire Florida Idaho Washington Oregon Nevada California New,000 9,000 to 13,000 Thermoelectric-power withdrawals by water quality and State, 2005. Estimated Use

  13. average neutron total: Topics by E-print Network

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

    16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 1 Total Cross Sections for Neutron Scattering Nuclear Theory (arXiv) Summary: Measurements of neutron total...

  14. Multiple phase estimation for arbitrary pure states under white noise

    E-Print Network [OSTI]

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

    2014-09-08T23:59:59.000Z

    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.

  15. Energy Expenditure Estimation DEMO Application

    E-Print Network [OSTI]

    Lu?trek, Mitja

    and against the SenseWear, a dedicated commercial product for energy expenditure estimation. Keywords: humanEnergy Expenditure Estimation DEMO Application Bozidara Cvetkovi´c1,2 , Simon Kozina1,2 , Bostjan://www.mps.si Abstract. The paper presents two prototypes for the estimation of hu- man energy expenditure during normal

  16. anorrectal total reporte: Topics by E-print Network

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

    markets including finance, energy, healthcare, telecommunications, unknown authors 5 Computer Integrated Revision Total Hip Replacement Surgery: Preliminary Report Computer...

  17. MUJERES ( * ) TOTAL ANATOMA, HISTOLOGA Y NEUROCIENCIA 4 10

    E-Print Network [OSTI]

    Autonoma de Madrid, Universidad

    , DEPORTE Y MOTRICIDAD HUMANA 1 1 TOTAL FORMACIÓN DE PROFESORADO Y EDUCACIÓN 4 6 Nº de tesis leídas y

  18. Quantitative analysis of SCIAMACHY carbon monoxide total column measurements

    E-Print Network [OSTI]

    Laat, Jos de

    , SCIAMACHY CO total column retrievals are of sufficient quality to provide useful new information]. Ground-based FTIR measurements provide high quality total column measurements but have very limitedQuantitative analysis of SCIAMACHY carbon monoxide total column measurements A. T. J. de Laat,1,2 A

  19. Summertime total ozone variations over middle and polar latitudes

    E-Print Network [OSTI]

    Wirosoetisno, Djoko

    Summertime total ozone variations over middle and polar latitudes 1234567 89A64BC7DEF72B4 467342 $7D425BE27B725CE9393BE647 #12;Summertime total ozone variations over middle and polar latitudes and summertime ozone over middle and polar latitudes is analyzed using zonally averaged total ozone data. Short

  20. Cost Estimating, Analysis, and Standardization

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

    1984-11-02T23:59:59.000Z

    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

  1. Calibration by Optimization Without Using Derivatives

    E-Print Network [OSTI]

    Markus Lazar

    2015-03-06T23:59:59.000Z

    Mar 6, 2015 ... Abstract: Applications in engineering frequently require the ... to upper and lower bounds without relying on the knowledge of the derivative of f .

  2. Anisotropic higher derivative gravity and inflationary universe

    E-Print Network [OSTI]

    W. F. Kao

    2006-05-21T23:59:59.000Z

    Stability analysis of the Kantowski-Sachs type universe in pure higher derivative gravity theory is studied in details. The non-redundant generalized Friedmann equation of the system is derived by introducing a reduced one dimensional generalized KS type action. This method greatly reduces the labor in deriving field equations of any complicate models. Existence and stability of inflationary solution in the presence of higher derivative terms are also studied in details. Implications to the choice of physical theories are discussed in details in this paper.

  3. GLOBAL CONVERGENCE OF GENERAL DERIVATIVE-FREE ...

    E-Print Network [OSTI]

    2006-10-26T23:59:59.000Z

    a relatively recent topic [1, 3, 7, 10]. In this paper we address trust-region methods for unconstrained derivative-free optimization. These methods ... Page 2

  4. Reassessing Wind Potential Estimates for India: Economic and Policy Implications

    SciTech Connect (OSTI)

    Phadke, Amol; Bharvirkar, Ranjit; Khangura, Jagmeet

    2011-09-15T23:59:59.000Z

    We assess developable on-shore wind potential in India at three different hub-heights and under two sensitivity scenarios – one with no farmland included, the other with all farmland included. Under the “no farmland included” case, the total wind potential in India ranges from 748 GW at 80m hub-height to 976 GW at 120m hub-height. Under the “all farmland included” case, the potential with a minimum capacity factor of 20 percent ranges from 984 GW to 1,549 GW. High quality wind energy sites, at 80m hub-height with a minimum capacity factor of 25 percent, have a potential between 253 GW (no farmland included) and 306 GW (all farmland included). Our estimates are more than 15 times the current official estimate of wind energy potential in India (estimated at 50m hub height) and are about one tenth of the official estimate of the wind energy potential in the US.

  5. Ocean Sciences 2006 An Estimate of Carbon Sequestration via Antarctic Intermediate Water Formation in the

    E-Print Network [OSTI]

    Talley, Lynne D.

    Ocean Sciences 2006 An Estimate of Carbon Sequestration via Antarctic Intermediate Water Formation traditional deep water formation via entrainment of carbon dioxide and other greenhouse-active species collected for oxygen, total carbon, alkalinity, nutrients, and CFCs. The alkalinity and total carbon data

  6. Nearest Neighbor Conditional Estimation for Harris Recurrent Markov Chains

    E-Print Network [OSTI]

    Sancetta, Alessio

    and to estimate Ei?1f (Xi) (Ei?1 is expectation conditional on the sigma algebra generated by (Xs)sEi?1f (Xi) over some class of functions from which we can derive conditional extremum estimators. Most common examples include... . To formalize this we need the following additional condition, which is minimal. Condition 19 For any x ? C ? E, let G = Gx be any arbitrary open set that contains f0 (x) and let Gc be its complement. Then, inf f?Gc Pf (x) > Pf0 (x) . Corollary 20 Suppose (F, ?...

  7. A Total Cost of Ownership Model for Low Temperature PEM Fuel Cells in Combined Heat and Power and Backup Power Applications

    SciTech Connect (OSTI)

    University of California, Berkeley; Wei, Max; Lipman, Timothy; Mayyas, Ahmad; Chien, Joshua; Chan, Shuk Han; Gosselin, David; Breunig, Hanna; Stadler, Michael; McKone, Thomas; Beattie, Paul; Chong, Patricia; Colella, Whitney; James, Brian

    2014-06-23T23:59:59.000Z

    A total cost of ownership model is described for low temperature proton exchange membrane stationary fuel cell systems for combined heat and power (CHP) applications from 1-250kW and backup power applications from 1-50kW. System designs and functional specifications for these two applications were developed across the range of system power levels. Bottom-up cost estimates were made for balance of plant costs, and detailed direct cost estimates for key fuel cell stack components were derived using design-for-manufacturing-and-assembly techniques. The development of high throughput, automated processes achieving high yield are projected to reduce the cost for fuel cell stacks to the $300/kW level at an annual production volume of 100 MW. Several promising combinations of building types and geographical location in the U.S. were identified for installation of fuel cell CHP systems based on the LBNL modelling tool DER CAM. Life-cycle modelling and externality assessment were done for hotels and hospitals. Reduced electricity demand charges, heating credits and carbon credits can reduce the effective cost of electricity ($/kWhe) by 26-44percent in locations such as Minneapolis, where high carbon intensity electricity from the grid is displaces by a fuel cell system operating on reformate fuel. This project extends the scope of existing cost studies to include externalities and ancillary financial benefits and thus provides a more comprehensive picture of fuel cell system benefits, consistent with a policy and incentive environment that increasingly values these ancillary benefits. The project provides a critical, new modelling capacity and should aid a broad range of policy makers in assessing the integrated costs and benefits of fuel cell systems versus other distributed generation technologies.

  8. Cosmic Four-Fermion Neutrino Secret Interactions, Enhancement and Total Cross Section

    E-Print Network [OSTI]

    Dante Carcamo; Ashok K. Das; Jorge Gamboa; Fernando Mendez; Alexios P. Polychronakos

    2015-03-18T23:59:59.000Z

    The scattering of neutrinos assuming a "secret" interaction at low energy is considered. To leading order in energy, the two-body potential is a $\\delta$-potential, and it is used as a motivation to study generic short-range elastic interactions between neutrinos. The scattering cross section and Sommerfeld enhancement depend on two phenomenological parameters deriving from the exact form of the potential, akin to "renormalized" coupling constants. Repulsive potentials lead to a decrease in the total cross section, resulting in an enhancement of the neutrino density. For attractive potentials of the right form, substantial Sommerfeld enhancement can appear.

  9. A Multi-period Equilibrium Pricing Model of Weather Derivatives

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2008-01-01T23:59:59.000Z

    2002). On modelling and pricing weather derivatives. Applied2003). Arbitrage-fee pricing of weather derivatives based onfects and valuation of weather derivatives. The Financial

  10. A multi-period equilibrium pricing model of weather derivatives

    E-Print Network [OSTI]

    Lee, Yongheon; Oren, Shmuel S.

    2010-01-01T23:59:59.000Z

    Y. : Valuation and hedging of weather derivatives on monthlyJ. Risk 31. Yoo, S. : Weather derivatives and seasonaleffects and valuation of weather derivatives. Financ. Rev.

  11. Quantitative Total and Diffuse Reflectance Laboratory Measurements for Remote, Standoff, and Point Sensing

    SciTech Connect (OSTI)

    Blake, Thomas A.; Johnson, Timothy J.; Tonkyn, Russell G.; Forland, Brenda M.; Myers, Tanya L.; Brauer, Carolyn S.; Su, Yin-Fong

    2014-06-10T23:59:59.000Z

    Methods for making total and diffuse directional/hemispherical reflectance measurements in the shortwave to longwave infrared using an integrating sphere are described. The sphere is a commercial, off-the-shelf optical device with its sample port at the bottom, which is essential for examining powdered samples without using a cover glass. The reflectance spectra of recently-developed National Institute of Standards and Technology (NIST, USA) infrared reflectance standards have been measured using the sphere. Reflectance spectra of other materials such as Spectralon and Infragold were also measured. The relative systematic error for the total reflectance measurements is estimated to be on the order of 3%, and random measurement error for multiple samples of each material is on the order of 0.5%.

  12. Determination of lithium ion--rare gas potentials from total cross section measurements

    SciTech Connect (OSTI)

    Polak-Dingels, P.; Rajan, M.S.; Gislason, E.A.

    1982-10-15T23:59:59.000Z

    Total cross sections have been measured for Li/sup +/ ions scattered by He, Ne, Ar, Kr, and Xe in the range Etheta/sub R/ = 5--1000 eV deg. Here E is the laboratory energy of the Li/sup +/ beam, and theta/sub R/ is the resolution angle of the apparatus. The cross sections have been inverted to obtain accurate estimates of the potential V(R) over a wide range of R including the attractive well region. The results are compared with other theoretical and experimental work on these systems.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013,Iowa"Dakota" ,"FullWestQuantity of2" " (Estimates

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013,Iowa"Dakota" ,"FullWestQuantity of2" " (Estimates

  15. "Table A45. Selected Energy Operating Ratios for Total Energy Consumption"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal"1" " (Estimates5. Selected

  16. "Table A46. Selected Energy Operating Ratios for Total Energy Consumption"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal"1" " (Estimates5.

  17. "Table A48. Selected Energy Operating Ratios for Total Energy Consumption for"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal"1" " (Estimates5.6.

  18. "Table A50. Selected Energy Operating Ratios for Total Energy Consumption for"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal"1" " (Estimates5.6.8.

  19. "Table A51. Selected Energy Operating Ratios for Total Energy Consumption for"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal"1" " (Estimates5.6.8.1.

  20. FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION

    SciTech Connect (OSTI)

    Rodney, Steven A. [Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States); Tonry, John L., E-mail: rodney@jhu.ed, E-mail: jt@ifa.hawaii.ed [Institute for Astronomy, University of Hawaii, Honolulu, HI 96822 (United States)

    2010-05-20T23:59:59.000Z

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