National Library of Energy BETA

Sample records for maximum life expectancies

  1. Maximum-likelihood

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

    Maximum-likelihood fitting of data dominated by Poisson statistical uncertainties M. R. Stoneking and D. J. Den Hartog Department of Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706 ͑Presented on 15 May 1996͒ The fitting of data by ␹ 2 minimization is valid only when the uncertainties in the data are normally distributed. When analyzing spectroscopic or particle counting data at very low signal level ͑e.g., a Thomson scattering diagnostic͒, the uncertainties are

  2. Removal to Maximum Extent Practical

    Broader source: Energy.gov [DOE]

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

  3. Structural Genomics: Expectations and Reality

    Office of Scientific and Technical Information (OSTI)

    projects aim to expand our structural knowledge of biological macromolecules, while ... We expect that this analysis will be helpful for informing future strategy in both SG and ...

  4. Liners and Covers: Field Performance & Life Expectancy | Department...

    Office of Environmental Management (EM)

    of Practice Annual Technical Exchange Meeting 11-12 December 2014 Las Vegas, Nevada, USA To view all the P&RA CoP 2014 Technical Exchange Meeting videos click here. Video...

  5. Maximum Performance Group MPG | Open Energy Information

    Open Energy Info (EERE)

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

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

    Office of Environmental Management (EM)

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

  7. Project Management Expectations for Financial Assistance Activities

    Broader source: Energy.gov [DOE]

    Memo on Project Management Expectations for Financial Assistance Activities from David K. Garman, dated June 23, 2006.

  8. Seismic Design Expectations Report | Department of Energy

    Energy Savers [EERE]

    Seismic Design Expectations Report Seismic Design Expectations Report The Seismic Design Expectations Report (SDER) is a tool that assists DOE federal project review teams in evaluating the technical sufficiency of the project seismic design activities prior to Critical Decision (CD) approvals at CD-0, CD-1, CD-2, CD-3 and CD-4. PDF icon Seismic Design Expectations Report More Documents & Publications Natural Phenomena Hazards DOE-STD 1020-2012 & DOE Handbook DOE-STD-1020-2012 DOE

  9. Life Insurance

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

    Life Insurance Life Insurance A comprehensive benefits package with plan options for health care and retirement to take care of our employees today and tomorrow. Contact Benefits Office (505) 667-1806 Email Life Insurance The Lab offers a variety of life insurance options through The Hartford to help you protect your loved ones. Life insurance provides financial assistance to help cover the rising costs of final expenses and any outstanding debts you leave behind. Resources Rates » Provider

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

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

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

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

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

    Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 3, 1, 2 SO2 Case. Compliance based on highest, second-highest, short-term, and highest annual...

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

    Office of Environmental Management (EM)

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

  13. ARM - Guidelines : Expectations of Principal Investigators

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

    Expectations of Principal Investigators Guidelines Overview Annual Facility Call Small Field Campaigns Review Criteria Expectations for Principal Investigators Forms Propose a Campaign Instrument Support Request (ISR) Form (Word, 89KB) Documentation Steps for Submitting Field Campaign Data and Metadata Field Campaign Guidelines (PDF, 574KB) Guidelines : Expectations of Principal Investigators Abstract. An abstract for the field campaign, suitable for posting on the ARM website, is required

  14. Lowell, Massachusetts, Restaurant Exceeds Energy Savings Expectations...

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

    Exceeds Energy Savings Expectations The logo for Better Buildings Lowell. The Athenian Corner, a Greek restaurant owned by the Panagiotopoulos family, has been a familiar sight in...

  15. Lowell, Massachusetts, Restaurant Exceeds Energy Savings Expectations |

    Energy Savers [EERE]

    Department of Energy Restaurant Exceeds Energy Savings Expectations Lowell, Massachusetts, Restaurant Exceeds Energy Savings Expectations The logo for Better Buildings Lowell. The Athenian Corner, a Greek restaurant owned by the Panagiotopoulos family, has been a familiar sight in the historic district of downtown Lowell, Massachusetts, since 1974. Energy efficiency upgrades are helping the Panagiotopoulos family reduce operating costs and make their restaurant more successful. The Athenian

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

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

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

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

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

    Engineer End Uses for Maximum Efficiency Engineer End Uses for Maximum Efficiency This tip sheet outlines steps to ensure the efficiency of compressed air end-use applications....

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

    Office of Scientific and Technical Information (OSTI)

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

  19. Ancient galactic magnetic fields stronger than expected

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

    Ancient galactic magnetic fields Ancient galactic magnetic fields stronger than expected With powerful telescopes and sophisticated measurements, the team probed back in time to see the ancient universe as it existed some 8 to 9 billion years ago. July 23, 2008 Los Alamos National Laboratory sits on top of a once-remote mesa in northern New Mexico with the Jemez mountains as a backdrop to research and innovation covering multi-disciplines from bioscience, sustainable energy sources, to plasma

  20. Setting clear expectations for safety basis development

    SciTech Connect (OSTI)

    MORENO, M.R.

    2003-05-03

    DOE-RL has set clear expectations for a cost-effective approach for achieving compliance with the Nuclear Safety Management requirements (10 CFR 830, Nuclear Safety Rule) which will ensure long-term benefit to Hanford. To facilitate implementation of these expectations, tools were developed to streamline and standardize safety analysis and safety document development resulting in a shorter and more predictable DOE approval cycle. A Hanford Safety Analysis and Risk Assessment Handbook (SARAH) was issued to standardized methodologies for development of safety analyses. A Microsoft Excel spreadsheet (RADIDOSE) was issued for the evaluation of radiological consequences for accident scenarios often postulated for Hanford. A standard Site Documented Safety Analysis (DSA) detailing the safety management programs was issued for use as a means of compliance with a majority of 3009 Standard chapters. An in-process review was developed between DOE and the Contractor to facilitate DOE approval and provide early course correction. As a result of setting expectations and providing safety analysis tools, the four Hanford Site waste management nuclear facilities were able to integrate into one Master Waste Management Documented Safety Analysis (WM-DSA).

  1. Theoretical Estimate of Maximum Possible Nuclear Explosion

    DOE R&D Accomplishments [OSTI]

    Bethe, H. A.

    1950-01-31

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

  2. The expected anisotropy in solid inflation

    SciTech Connect (OSTI)

    Bartolo, Nicola; Ricciardone, Angelo; Peloso, Marco; Unal, Caner E-mail: peloso@physics.umn.edu E-mail: unal@physics.umn.edu

    2014-11-01

    Solid inflation is an effective field theory of inflation in which isotropy and homogeneity are accomplished via a specific combination of anisotropic sources (three scalar fields that individually break isotropy). This results in specific observational signatures that are not found in standard models of inflation: a non-trivial angular dependence for the squeezed bispectrum, and a possibly long period of anisotropic inflation (to drive inflation, the ''solid'' must be very insensitive to any deformation, and thus background anisotropies are very slowly erased). In this paper we compute the expected level of statistical anisotropy in the power spectrum of the curvature perturbations of this model. To do so, we account for the classical background values of the three scalar fields that are generated on large (superhorizon) scales during inflation via a random walk sum, as the perturbation modes leave the horizon. Such an anisotropy is unavoidably generated, even starting from perfectly isotropic classical initial conditions. The expected level of anisotropy is related to the duration of inflation and to the amplitude of the squeezed bispectrum. If this amplitude is close to its current observational limit (so that one of the most interesting predictions of the model can be observed in the near future), we find that a level of statistical anisotropy F{sup 2} gives frozen and scale invariant vector perturbations on superhorizon scales.

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

    SciTech Connect (OSTI)

    Don Augenstein

    2001-02-01

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

  4. ARM - Expectations for Campaign Implementation and Close Out

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

    CampaignsExpectations for Campaign Implementation and Close Out Guidelines Overview Annual Facility Call Small Field Campaigns Review Criteria Expectations for Principal...

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

  8. Why the Earth has not warmed as much as expected?

    SciTech Connect (OSTI)

    Schwartz, S.E.

    2010-05-01

    The observed increase in global mean surface temperature (GMST) over the industrial era is less than 40% of that expected from observed increases in long-lived greenhouse gases together with the best-estimate equilibrium climate sensitivity given by the 2007 Assessment Report of the Intergovernmental Panel on Climate Change. Possible reasons for this warming discrepancy are systematically examined here. The warming discrepancy is found to be due mainly to some combination of two factors: the IPCC best estimate of climate sensitivity being too high and/or the greenhouse gas forcing being partially offset by forcing by increased concentrations of atmospheric aerosols; the increase in global heat content due to thermal disequilibrium accounts for less than 25% of the discrepancy, and cooling by natural temperature variation can account for only about 15%. Current uncertainty in climate sensitivity is shown to preclude determining the amount of future fossil fuel CO2 emissions that would be compatible with any chosen maximum allowable increase in GMST; even the sign of such allowable future emissions is unconstrained. Resolving this situation, by empirical determination of the earth's climate sensitivity from the historical record over the industrial period or through use of climate models whose accuracy is evaluted by their performance over this period, is shown to require substantial reduction in the uncertainty of aerosol forcing over this period.

  9. Why hasn't earth warmed as much as expected?

    SciTech Connect (OSTI)

    Schwartz, S.E.; Charlson, R.; Kahn, R.; Ogren, J.; Rodhe, H.

    2010-03-15

    The observed increase in global mean surface temperature (GMST) over the industrial era is less than 40% of that expected from observed increases in long-lived greenhouse gases together with the best-estimate equilibrium climate sensitivity given by the 2007 Assessment Report of the Intergovernmental Panel on Climate Change. Possible reasons for this warming discrepancy are systematically examined here. The warming discrepancy is found to be due mainly to some combination of two factors: the IPCC best estimate of climate sensitivity being too high and/or the greenhouse gas forcing being partially offset by forcing by increased concentrations of atmospheric aerosols; the increase in global heat content due to thermal disequilibrium accounts for less than 25% of the discrepancy, and cooling by natural temperature variation can account for only about 15%. Current uncertainty in climate sensitivity is shown to preclude determining the amount of future fossil fuel CO2 emissions that would be compatible with any chosen maximum allowable increase in GMST; even the sign of such allowable future emissions is unconstrained. Resolving this situation by empirical determination of Earths climate sensitivity from the historical record over the industrial period or through use of climate models whose accuracy is evaluated by their performance over this period is shown to require substantial reduction in the uncertainty of aerosol forcing over this period.

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

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

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

  11. Photovoltaics: Life-cycle Analyses

    SciTech Connect (OSTI)

    Fthenakis V. M.; Kim, H.C.

    2009-10-02

    Life-cycle analysis is an invaluable tool for investigating the environmental profile of a product or technology from cradle to grave. Such life-cycle analyses of energy technologies are essential, especially as material and energy flows are often interwoven, and divergent emissions into the environment may occur at different life-cycle-stages. This approach is well exemplified by our description of material and energy flows in four commercial PV technologies, i.e., mono-crystalline silicon, multi-crystalline silicon, ribbon-silicon, and cadmium telluride. The same life-cycle approach is applied to the balance of system that supports flat, fixed PV modules during operation. We also discuss the life-cycle environmental metrics for a concentration PV system with a tracker and lenses to capture more sunlight per cell area than the flat, fixed system but requires large auxiliary components. Select life-cycle risk indicators for PV, i.e., fatalities, injures, and maximum consequences are evaluated in a comparative context with other electricity-generation pathways.

  12. Boiler Maximum Achievable Control Technology (MACT) Technical Assistance -

    Office of Environmental Management (EM)

    Fact Sheet, April 2015 | Department of Energy Boiler Maximum Achievable Control Technology (MACT) Technical Assistance - Fact Sheet, April 2015 Boiler Maximum Achievable Control Technology (MACT) Technical Assistance - Fact Sheet, April 2015 This fact sheet about AMO's Boiler Maximum Achievable Control Technology (Boiler MACT) Technical Assistance Program was last updated in April 2015. PDF icon Boiler_MACT_factsheet.pdf More Documents & Publications CHP: A Technical & Economic

  13. Montana Total Maximum Daily Load Development Projects Wiki |...

    Open Energy Info (EERE)

    Wiki Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Montana Total Maximum Daily Load Development Projects Wiki Abstract Provides information on...

  14. Estimating the maximum potential revenue for grid connected electricity storage : arbitrage and regulation.

    SciTech Connect (OSTI)

    Byrne, Raymond Harry; Silva Monroy, Cesar Augusto.

    2012-12-01

    The valuation of an electricity storage device is based on the expected future cash ow generated by the device. Two potential sources of income for an electricity storage system are energy arbitrage and participation in the frequency regulation market. Energy arbitrage refers to purchasing (stor- ing) energy when electricity prices are low, and selling (discharging) energy when electricity prices are high. Frequency regulation is an ancillary service geared towards maintaining system frequency, and is typically procured by the independent system operator in some type of market. This paper outlines the calculations required to estimate the maximum potential revenue from participating in these two activities. First, a mathematical model is presented for the state of charge as a function of the storage device parameters and the quantities of electricity purchased/sold as well as the quantities o ered into the regulation market. Using this mathematical model, we present a linear programming optimization approach to calculating the maximum potential revenue from an elec- tricity storage device. The calculation of the maximum potential revenue is critical in developing an upper bound on the value of storage, as a benchmark for evaluating potential trading strate- gies, and a tool for capital nance risk assessment. Then, we use historical California Independent System Operator (CAISO) data from 2010-2011 to evaluate the maximum potential revenue from the Tehachapi wind energy storage project, an American Recovery and Reinvestment Act of 2009 (ARRA) energy storage demonstration project. We investigate the maximum potential revenue from two di erent scenarios: arbitrage only and arbitrage combined with the regulation market. Our analysis shows that participation in the regulation market produces four times the revenue compared to arbitrage in the CAISO market using 2010 and 2011 data. Then we evaluate several trading strategies to illustrate how they compare to the maximum potential revenue benchmark. We conclude with a sensitivity analysis with respect to key parameters.

  15. Expectations of Mentors and Mentees | Argonne National Laboratory

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

    Expectations of Mentors and Mentees MENTOR EXPECTATIONS MENTEE EXPECTATIONS M Monitors mentee's progress throughout the entire relationship Makes it happen by - developing a plan of action with mentor's advice - accomplishing the plan E Encourages the mentee to engage in the research plan that has a clear set of expectations and high standards Engages actively in the research plan with the support of the mentor N Nurtures relationship with mentee by providing guidance and direction Nurtures

  16. Quality Control, Standardization of Upgrades, and Workforce Expectations

    Broader source: Energy.gov [DOE]

    Better Buildings Residential Network Workforce Peer Exchange Call Series: Quality Control, Standardization of Upgrades, and Workforce Expectations, March 27, 2014.

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

    SciTech Connect (OSTI)

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

    2000-02-26

    Controlled landfilling is an approach to manage solid waste landfills, so as to rapidly complete methane generation, while maximizing gas capture and minimizing the usual emissions of methane to the atmosphere. With controlled landfilling, methane generation is accelerated to more rapid and earlier completion to full potential by improving conditions (principally moisture, but also temperature) to optimize biological processes occurring within the landfill. Gas is contained through use of surface membrane cover. Gas is captured via porous layers, under the cover, operated at slight vacuum. A field demonstration project has been ongoing under NETL sponsorship for the past several years near Davis, CA. Results have been extremely encouraging. Two major benefits of the technology are reduction of landfill methane emissions to minuscule levels, and the recovery of greater amounts of landfill methane energy in much shorter times, more predictably, than with conventional landfill practice. With the large amount of US landfill methane generated, and greenhouse potency of methane, better landfill methane control can play a substantial role both in reduction of US greenhouse gas emissions and in US renewable energy. The work described in this report, to demonstrate and advance this technology, has used two demonstration-scale cells of size (8000 metric tons [tonnes]), sufficient to replicate many heat and compaction characteristics of larger ''full-scale'' landfills. An enhanced demonstration cell has received moisture supplementation to field capacity. This is the maximum moisture waste can hold while still limiting liquid drainage rate to minimal and safely manageable levels. The enhanced landfill module was compared to a parallel control landfill module receiving no moisture additions. Gas recovery has continued for a period of over 4 years. It is quite encouraging that the enhanced cell methane recovery has been close to 10-fold that experienced with conventional landfills. This is the highest methane recovery rate per unit waste, and thus progress toward stabilization, documented anywhere for such a large waste mass. This high recovery rate is attributed to moisture, and elevated temperature attained inexpensively during startup. Economic analyses performed under Phase I of this NETL contract indicate ''greenhouse cost effectiveness'' to be excellent. Other benefits include substantial waste volume loss (over 30%) which translates to extended landfill life. Other environmental benefits include rapidly improved quality and stabilization (lowered pollutant levels) in liquid leachate which drains from the waste.

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

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

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

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

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

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

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

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

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

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

  2. Alaska Maximum Number of Active Crews Engaged in Seismic Surveying...

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

    Seismic Surveying (Number of Elements) Alaska Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec...

  3. NRC Leadership Expectations and Practices for Sustaining a High Performing

    Office of Environmental Management (EM)

    Organization | Department of Energy NRC Leadership Expectations and Practices for Sustaining a High Performing Organization NRC Leadership Expectations and Practices for Sustaining a High Performing Organization May 16, 2012 Presenter: William C. Ostendorff, NRC Commissioner Topics Covered: NRC Mission Safety Culture NRC Oversight NRC Inspection Program Technical Qualification Continuous Learning PDF icon NRC Leadership Expectations and Practices for Sustaining a High Performing Organization

  4. Oxidation State Optimization for Maximum Efficiency of NOx Adsorber

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

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

  5. CABLE TECHNOLOGY LABORATORIES, INC. DETERMINATION OF THRESHOLD AND MAXIMUM

    Office of Scientific and Technical Information (OSTI)

    CABLE TECHNOLOGY LABORATORIES, INC. DETERMINATION OF THRESHOLD AND MAXIMUM OPERATING ELECTRIC STRESSES FOR SELECTED HIGH VOLTAGE INSULATIONS Investigation of Aged Polymeric Dielectric Cable DOE CONTRACT DE-AC 02-80RA 50156 Final Report Prepared by : Approved by: G.S. Eager, Jr. G.W. Seman B. Fryszczyn C. Katz November 1995 690 Jersey Avenue - RO. Box 707 - Fax: (908) 846-5531 New Brunswick, N.J. 08903 Tel: (908) 8463133 DETERMINATION OF THRESHOLD AND MAXIMUM OPERATING ELECTRIC STRESSES FOR

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

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

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

  7. Table 10.1 Nonswitchable Minimum and Maximum Consumption, 2002

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

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

  8. Scientists detect methane levels three times larger than expected...

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

    Methane levels larger over Four Corners region Scientists detect methane levels three times larger than expected over Four Corners region Study is first to show space-based...

  9. Expected annual electricity bill savings for various PPA price...

    Open Energy Info (EERE)

    Expected annual electricity bill savings for various PPA price options Jump to: navigation, search Impact of Utility Rates on PV Economics Bill savings tables (main section): When...

  10. ,"Texas--State Offshore Natural Gas Plant Liquids, Expected Future...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million...

  11. ,"Texas State Offshore Dry Natural Gas Expected Future Production...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas State Offshore Dry Natural Gas Expected Future Production (Billion Cubic...

  12. ,"California State Offshore Dry Natural Gas Expected Future Production...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","California State Offshore Dry Natural Gas Expected Future Production (Billion Cubic...

  13. ,"Louisiana--State Offshore Natural Gas Plant Liquids, Expected...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million...

  14. ,"California--State Offshore Natural Gas Plant Liquids, Expected...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","California--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million...

  15. ,"Louisiana State Offshore Dry Natural Gas Expected Future Production...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana State Offshore Dry Natural Gas Expected Future Production (Billion Cubic...

  16. FY 1996 solid waste integrated life-cycle forecast characteristics summary. Volumes 1 and 2

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters. The range is primarily due to uncertainties associated with the Tank Waste Remediation System (TWRS) program, including uncertainties regarding retrieval of long-length equipment, scheduling, and tank retrieval technologies.

  17. Test report on the Abacus 30 kW bimode{reg_sign} inverter and maximum power tracker (MPT)

    SciTech Connect (OSTI)

    Bonn, R.; Ginn, J.; Zirzow, J.

    1995-06-01

    Sandia National Laboratories conducts the photovoltaic balance of systems (BOS) program, which is sponsored by the US Department of Energy`s Office of Energy Management. Under this program, SNL lets commercialization contracts and conducts a laboratory program designed to advance BOS technology, improve BOS component reliability, and reduce the BOS life-cycle-cost. This report details the testing of the first large US manufactured hybrid inverter and its associated maximum power tracker.

  18. Household heating bills expected to be lower this winter

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

    Household heating bills expected to be lower this winter U.S. consumers are expected to pay less this winter on their home heating bills because of lower oil and natural gas prices and projected milder temperatures than last winter. In its new forecast, the U.S. Energy Information Administration said households that rely on heating oil which are mainly located in the Northeast will pay the lowest heating expenditures in 9 years down 25% from last winter as consumers are expected to save about

  19. Floating Production Systems Market Is Expected To Reach USD 38...

    Open Energy Info (EERE)

    Production Systems Market Is Expected To Reach USD 38,752.7 Million Globally By 2019 Home > Groups > Future of Condition Monitoring for Wind Turbines Wayne31jan's picture...

  20. Average summer electric power bills expected to be lowest in...

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

    of forecasted milder temperatures compared with last summer is expected to more than offset higher electricity prices. The result is lower power bills for most U.S. households...

  1. Program Evaluation: Requirements and Expectations | Department of Energy

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

    Why, What, & When to Evaluate » Program Evaluation: Requirements and Expectations Program Evaluation: Requirements and Expectations Throughout this website, emphasis is placed on evaluation as a good management practice that helps managers make informed decisions. Ideally, offices are motivated to undertake evaluation-related activities to improve program operations and/or to establish evidence to better communicate the value of the program to EERE senior management, Congress, or

  2. The Impact of Structural Genomics: Expectations and Outcomes (Journal

    Office of Scientific and Technical Information (OSTI)

    Article) | SciTech Connect The Impact of Structural Genomics: Expectations and Outcomes Citation Details In-Document Search Title: The Impact of Structural Genomics: Expectations and Outcomes Structural Genomics (SG) projects aim to expand our structural knowledge of biological macromolecules, while lowering the average costs of structure determination. We quantitatively analyzed the novelty, cost, and impact of structures solved by SG centers, and contrast these results with traditional

  3. Indoctrinating Subcontractors into the DOE Safety Culture and Expectations

    Office of Environmental Management (EM)

    | Department of Energy Indoctrinating Subcontractors into the DOE Safety Culture and Expectations Indoctrinating Subcontractors into the DOE Safety Culture and Expectations August 2009 Presenter: Daryl Schilperoort, Washington Closure Hanford Track: 1-1 Topic Covered: Why Indoctrinate Subcontractors? WCH is limited to doing no more than 40% self performance of RCCC value (large business limitation). Many of WCH subcontracts target small businesses with limited experience in the DOE safety

  4. Life Cycle Cost Estimate

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

    1997-03-28

    Life-cycle costs (LCCs) are all the anticipated costs associated with a project or program alternative throughout its life. This includes costs from pre-operations through operations or to the end of the alternative.This chapter discusses life cycle costs and the role they play in planning.

  5. Maximum entanglement in squeezed boson and fermion states

    SciTech Connect (OSTI)

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

    2007-08-15

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

  6. Maximum patch method for directional dark matter detection

    SciTech Connect (OSTI)

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

    2008-07-01

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

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

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

    2001-10-11

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

  8. Extended space expectation values in quantum dynamical system evolutions

    SciTech Connect (OSTI)

    Demiralp, Metin

    2014-10-06

    The time variant power series expansion for the expectation value of a given quantum dynamical operator is well-known and well-investigated issue in quantum dynamics. However, depending on the operator and Hamiltonian singularities this expansion either may not exist or may not converge for all time instances except the beginning of the evolution. This work focuses on this issue and seeks certain cures for the negativities. We work in the extended space obtained by adding all images of the initial wave function under the system Hamiltonians positive integer powers. This requires the introduction of certain appropriately defined weight operators. The resulting better convergence in the temporal power series urges us to call the new defined entities extended space expectation values even though they are constructed over certain weight operators and are somehow pseudo expectation values.

  9. Miscellaneous States Dry Natural Gas Expected Future Production (Billion

    Gasoline and Diesel Fuel Update (EIA)

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Miscellaneous States Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 102 109 153 1980's 176 191 69 78 75 76 133 65 83 83 1990's 70 75 92 94 65 69 67 43 38 66 2000's 42 82 99 134 110 131 138 239 270 349 2010's 350 379 222 179 176 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  10. Miscellaneous States Natural Gas Plant Liquids, Expected Future Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Miscellaneous States Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 2 1980's 3 21 2 1 2 2 3 3 1990's 2 3 6 6 7 7 7 9 8 8 2000's 7 6 8 8 8 9 11 14 14 0 2010's 9 10 12 32 350 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015

  11. Mississippi (with State Offshore) Natural Gas Plant Liquids, Expected

    Gasoline and Diesel Fuel Update (EIA)

    Future Production (Million Barrels) Expected Future Production (Million Barrels) Mississippi (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 5 1980's 5 5 6 6 5 4 3 3 3 3 1990's 3 3 3 3 3 3 2 2 3 3 2000's 2 2 2 2 1 2 2 3 3 4 2010's 4 6 4 3 4 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  12. Montana Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Montana Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 887 926 825 1980's 1,287 1,321 847 896 802 857 803 780 819 867 1990's 899 831 859 673 717 782 796 762 782 841 2000's 885 898 906 1,059 995 986 1,057 1,052 1,000 976 2010's 944 778 602 575 667 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  13. Montana Natural Gas Plant Liquids, Expected Future Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Expected Future Production (Million Barrels) Montana Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 10 1980's 16 11 18 19 18 21 16 16 11 16 1990's 15 14 12 8 8 8 7 5 5 8 2000's 3 5 6 7 6 9 10 11 11 12 2010's 11 10 10 11 14 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next

  14. Colorado Natural Gas Plant Liquids, Expected Future Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Expected Future Production (Million Barrels) Colorado Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 170 1980's 183 195 174 173 142 155 127 142 162 191 1990's 152 181 193 190 210 243 254 244 235 277 2000's 288 298 329 325 362 386 382 452 612 722 2010's 879 925 705 762 813 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  15. Federal Offshore--California Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Federal Offshore--California Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0 1980's 0 0 0 0 10 12 16 19 1990's 13 11 15 20 17 21 19 10 8 0 2000's 1 1 0 0 0 0 0 0 1 1 2010's 1 1 1 2 2 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  16. Federal Offshore--Texas Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Federal Offshore--Texas Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 2 1980's 6 5 12 17 36 34 36 29 26 21 1990's 21 26 34 34 25 27 27 27 21 24 2000's 27 25 28 17 13 9 9 4 7 0 2010's 0 0 35 41 30 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  17. Florida Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Florida Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 151 119 77 1980's 84 69 64 49 65 55 49 49 51 46 1990's 45 38 47 50 98 92 96 96 88 84 2000's 82 84 91 79 78 77 45 108 1 7 2010's 56 6 16 15 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next

  18. Florida Natural Gas Plant Liquids, Expected Future Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Expected Future Production (Million Barrels) Florida Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 21 1980's 27 17 11 17 17 14 9 16 10 1990's 8 7 8 9 18 17 22 17 18 16 2000's 11 12 14 17 12 7 3 2 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next

  19. Kansas Natural Gas Plant Liquids, Expected Future Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Expected Future Production (Million Barrels) Kansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 400 1980's 387 407 300 441 422 370 437 459 342 327 1990's 311 426 442 378 396 367 336 263 331 355 2000's 303 300 261 245 267 218 204 194 175 162 2010's 195 192 174 138 186 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  20. Kentucky Natural Gas Plant Liquids, Expected Future Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Expected Future Production (Million Barrels) Kentucky Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 26 1980's 25 25 35 31 24 27 29 23 24 15 1990's 24 24 32 25 39 42 45 47 53 69 2000's 56 72 65 65 71 69 104 88 96 101 2010's 124 88 81 95 108 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  1. Louisiana (with State Offshore) Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Louisiana (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400 287 301 294 294 1990's 324 321 317 260 281 430 381 261 234 281 2000's 241 204 186 183 167 191 176 191 201 231 2010's 216 192 189 212 243 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  2. Louisiana State Offshore Dry Natural Gas Expected Future Production

    Gasoline and Diesel Fuel Update (EIA)

    (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Louisiana State Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,202 1,312 1,431 1,172 1,219 1990's 969 1,024 776 917 960 838 734 725 551 628 2000's 696 745 491 506 382 418 424 378 898 701 2010's 371 502 502 402 327 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  3. Louisiana--North Natural Gas Plant Liquids, Expected Future Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Louisiana--North Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 54 1980's 59 63 59 50 38 47 39 33 39 40 1990's 38 38 41 38 48 55 61 50 34 36 2000's 35 35 30 48 53 57 60 69 68 98 2010's 79 54 35 52 83 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  4. Louisiana--South Onshore Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Louisiana--South Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 413 1980's 273 291 258 289 225 222 220 235 228 215 1990's 249 242 229 201 214 359 284 199 187 222 2000's 178 128 119 100 87 103 94 97 78 90 2010's 113 94 134 144 145 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  5. Louisiana--State Offshore Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Louisiana--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 46 28 33 27 39 1990's 37 41 47 21 19 16 36 12 13 23 2000's 28 41 37 35 27 31 22 25 55 43 2010's 24 44 20 16 15 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  6. Lower 48 Federal Offshore Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Lower 48 Federal Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 363 382 350 331 337 1990's 295 329 295 309 309 239 245 389 370 427 2000's 515 486 511 364 423 416 399 369 321 302 2010's 341 355 405 335 399 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  7. Michigan Natural Gas Plant Liquids, Expected Future Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Expected Future Production (Million Barrels) Michigan Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 102 1980's 102 93 91 99 77 62 77 90 82 79 1990's 66 54 52 44 43 38 48 45 43 42 2000's 32 41 42 44 44 36 36 50 58 43 2010's 48 38 26 27 24 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  8. Alabama (with State Offshore) Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Alabama (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 31 1980's 33 25 35 50 48 39 38 34 36 38 1990's 48 35 53 55 51 48 52 34 31 57 2000's 104 32 28 33 29 31 41 32 92 55 2010's 68 68 55 51 59 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  9. Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 13 1980's 11 10 9 8 0 382 381 418 401 380 1990's 340 360 347 321 301 306 337 631 320 299 2000's 277 405 405 387 369 352 338 325 312 299 2010's 288 288 288 288 241 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  10. Arkansas Natural Gas Plant Liquids, Expected Future Production (Million

    Gasoline and Diesel Fuel Update (EIA)

    Barrels) Expected Future Production (Million Barrels) Arkansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 16 1980's 15 15 12 9 10 9 15 15 11 8 1990's 7 3 2 2 3 3 2 3 3 3 2000's 3 3 3 2 2 2 2 2 1 2 2010's 2 3 3 4 5 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date:

  11. California (with State Offshore) Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Expected Future Production (Million Barrels) California (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 107 1980's 109 73 146 139 128 124 118 109 1990's 101 87 94 98 86 88 89 92 71 97 2000's 100 75 95 101 121 135 130 126 113 129 2010's 114 94 99 102 112 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  12. California - Coastal Region Onshore Dry Natural Gas Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) California - Coastal Region Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 334 350 365 1980's 299 306 362 381 265 256 255 238 215 222 1990's 217 216 203 189 194 153 156 164 106 192 2000's 234 177 190 167 189 268 206 205 146 163 2010's 173 165 290 266 261 - = No Data Reported; -- = Not

  13. California - Los Angeles Basin Onshore Dry Natural Gas Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) California - Los Angeles Basin Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 255 178 163 1980's 193 154 96 107 156 181 142 148 151 137 1990's 106 115 97 102 103 111 109 141 149 168 2000's 193 187 207 187 174 176 153 144 75 84 2010's 87 97 93 86 80 - = No Data Reported; -- = Not Applicable;

  14. California State Offshore Dry Natural Gas Expected Future Production

    Gasoline and Diesel Fuel Update (EIA)

    (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) California State Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 114 213 231 1980's 164 254 252 241 231 1990's 192 59 63 64 61 59 49 56 44 76 2000's 91 85 92 83 86 90 90 82 57 57 2010's 66 82 66 75 76 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  15. California--Coastal Region Onshore Natural Gas Plant Liquids, Expected

    Gasoline and Diesel Fuel Update (EIA)

    Future Production (Million Barrels) Coastal Region Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) California--Coastal Region Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 22 1980's 23 14 16 17 14 15 15 13 13 11 1990's 12 11 9 10 9 7 9 9 9 31 2000's 27 16 17 15 19 16 22 14 10 10 2010's 11 12 18 13 12

  16. California--State Offshore Natural Gas Plant Liquids, Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) California--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 2 1980's 1 2 6 5 2 2 2 3 1990's 2 1 1 1 1 0 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  17. Texas State Offshore Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas State Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,111 1,065 732 627 561 605 1990's 458 475 348 335 230 313 292 289 348 418 2000's 398 467 437 456 321 265 305 261 219 164 2010's 131 118 94 59 42 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  18. New Mexico Natural Gas Plant Liquids, Expected Future Production (Million

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

    Barrels) Liquids, Expected Future Production (Million Barrels) New Mexico Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 465 1980's 478 496 475 495 462 395 514 708 926 863 1990's 915 840 994 925 946 881 998 814 876 896 2000's 804 794 779 824 805 781 804 788 726 715 2010's 764 776 662 679 789 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  19. North Dakota Dry Natural Gas Expected Future Production (Billion Cubic

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

    Feet) Expected Future Production (Billion Cubic Feet) North Dakota Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 361 374 439 1980's 537 581 629 600 566 569 541 508 541 561 1990's 586 472 496 525 507 463 462 479 447 416 2000's 433 443 471 448 417 453 479 511 541 1,079 2010's 1,667 2,381 3,569 5,420 6,034 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  20. North Dakota Natural Gas Plant Liquids, Expected Future Production (Million

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

    Barrels) Liquids, Expected Future Production (Million Barrels) North Dakota Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 33 1980's 42 52 53 54 57 59 53 53 40 48 1990's 50 47 54 46 46 44 40 40 41 46 2000's 47 50 41 40 39 45 51 54 51 104 2010's 157 193 297 466 540 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  1. Oklahoma Natural Gas Plant Liquids, Expected Future Production (Million

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

    Barrels) Liquids, Expected Future Production (Million Barrels) Oklahoma Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 511 1980's 537 565 667 740 683 731 768 702 686 586 1990's 592 567 566 575 592 605 615 610 613 667 2000's 639 605 601 582 666 697 732 797 870 985 2010's 1,270 1,445 1,452 1,408 1,752 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  2. Wyoming Natural Gas Plant Liquids, Expected Future Production (Million

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

    Barrels) Liquids, Expected Future Production (Million Barrels) Wyoming Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 822 887 1,010 2010's 1,001 1,122 1,064 894 881 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Natural Gas Plant Liquids

  3. Utah Natural Gas Plant Liquids, Expected Future Production (Million

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

    Barrels) Liquids, Expected Future Production (Million Barrels) Utah Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 56 54 116 2010's 132 196 181 169 206 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Natural Gas Plant Liquids Proved

  4. Utah and Wyoming Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) and Wyoming Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Utah and Wyoming Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 280 1980's 294 363 381 483 577 681 700 701 932 704 1990's 641 580 497 458 440 503 639 680 600 531 2000's 858 782 806 756 765 710 686 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  5. West Virginia Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) Liquids, Expected Future Production (Million Barrels) West Virginia Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 74 1980's 97 84 78 90 79 86 87 86 92 99 1990's 85 102 96 107 93 61 60 70 71 72 2000's 104 105 98 67 84 84 109 114 97 108 2010's 122 140 199 320 1,229 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  6. LIFE Target Fabrication Research Plan Sept 2008

    SciTech Connect (OSTI)

    Miles, R; Biener, J; Kucheyev, S; Montesanti, R; Satcher, J; Spadaccini, C; Rose, K; Wang, M; Hamza, A; Alexander, N; Brown, L; Hund, J; Petzoldt, R; Sweet, W; Goodin, D

    2008-11-10

    The target-system for the baseline LIFE fast-ignition target was analyzed to establish a preliminary estimate for the costs and complexities involved in demonstrating the technologies needed to build a prototype LIFE plant. The baseline fast-ignition target upon which this analysis was developed is shown in Figure 1.0-1 below. The LIFE target-system incorporates requirements for low-cost, high throughput manufacture, high-speed, high accuracy injection of the target into the chamber, production of sufficient energy from implosion and recovery and recycle of the imploded target material residue. None of these functions has been demonstrated to date. Existing target fabrication techniques which lead to current 'hot spot' target costs of {approx}$100,000 per target and at a production rate of 2/day are unacceptable for the LIFE program. Fabrication techniques normally used for low-cost, low accuracy consumer products such as toys must be adapted to the high-accuracy LIFE target. This will be challenge. A research program resulting is the demonstration of the target-cycle technologies needed for a prototype LIFE reactor is expected to cost {approx}$51M over the course of 5 years. The effort will result in targets which will cost an estimated $0.23/target at a rep-rate of 20 Hz or about 1.73M targets/day.

  7. Maximum U.S. Active Seismic Crew Counts

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

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

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

    SciTech Connect (OSTI)

    Virgo, Nathaniel Ikegami, Takashi

    2014-12-05

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

  9. OPEC's maximum oil revenue will be $80 billion per year

    SciTech Connect (OSTI)

    Steffes, D.W.

    1986-01-01

    OPEC's income from oil is less than $80 billion this year, only one fourth its 1981 revenue. The optimum revenue OPEC can expect is 15 MBB/D at $15/barrel. Energy conservation will continue despite falling prices because consumers no longer feel secure that OPEC can deliver needed supplies. Eleven concepts which affect the future world economic outlook include dependence upon petroleum and petroleum products, the condition of capital markets, low energy and commodity prices, the growth in money supply without a corresponding growth in investment, and the high debt level of the US and the developing countries.

  10. Life Extension Program

    National Nuclear Security Administration (NNSA)

    en NNSA, Air Force Complete Successful B61-12 Life Extension Program Development Flight Test at Tonopah Test Range http:nnsa.energy.govmediaroompressreleases...

  11. Life Extension Programs

    National Nuclear Security Administration (NNSA)

    B61-12 Life Extension Program Milestone: First Full-System Mechanical Environment Test Completed Successfully http:nnsa.energy.govmediaroompressreleasesb61lep

  12. Mississippi Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Mississippi Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,437 1,635 1,504 1980's 1,769 2,035 1,796 1,596 1,491 1,360 1,300 1,220 1,143 1,104 1990's 1,126 1,057 869 797 650 663 631 582 658 677 2000's 618 661 744 746 691 755 813 954 1,030 917 2010's 853 860 607 595 558 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  13. Kentucky Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Kentucky Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 451 545 468 1980's 508 530 551 554 613 766 841 909 923 992 1990's 1,016 1,155 1,084 1,003 969 1,044 983 1,364 1,222 1,435 2000's 1,760 1,860 1,907 1,889 1,880 2,151 2,227 2,469 2,714 2,782 2010's 2,613 2,006 1,408 1,663 1,611 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  14. Louisiana - South Onshore Dry Natural Gas Expected Future Production

    Gasoline and Diesel Fuel Update (EIA)

    (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Louisiana - South Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 18,580 17,755 13,994 1980's 13,026 12,645 11,801 11,142 10,331 9,808 9,103 8,693 8,654 8,645 1990's 8,171 7,504 6,693 5,932 6,251 5,648 5,704 5,855 5,698 5,535 2000's 5,245 5,185 4,224 3,745 3,436 3,334 3,335 3,323 2,799 2,844 2010's

  15. Louisiana Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Louisiana Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 19,117 12,930 12,430 12,224 12,516 1990's 11,728 10,912 9,780 9,174 9,748 9,274 9,543 9,673 9,147 9,242 2000's 9,239 9,811 8,960 9,325 9,588 10,447 10,474 10,045 11,573 20,688 2010's 29,277 30,358 21,949 20,164 22,975 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  16. Lower 48 States Natural Gas Plant Liquids, Expected Future Production

    Gasoline and Diesel Fuel Update (EIA)

    (Million Barrels) Expected Future Production (Million Barrels) Lower 48 States Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 5,191 1980's 5,187 5,478 5,611 6,280 6,121 6,109 6,348 6,327 6,448 6,000 1990's 5,944 5,860 5,878 5,709 5,722 5,896 6,179 6,001 5,868 6,112 2000's 6,596 6,190 6,243 5,857 6,338 6,551 6,795 7,323 7,530 8,258 2010's 9,521 10,537 10,489 11,655 14,788 - = No Data

  17. Michigan Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Michigan Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,386 1,422 1,204 1980's 1,406 1,118 1,084 1,219 1,112 985 1,139 1,451 1,323 1,342 1990's 1,243 1,334 1,223 1,160 1,323 1,294 2,061 2,195 2,328 2,255 2000's 2,729 2,976 3,254 3,428 3,091 2,910 3,065 3,630 3,174 2,763 2010's 2,919 2,505 1,750 1,807 1,845 - = No Data Reported; -- = Not

  18. Alabama Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Alabama Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 530 514 652 1980's 636 648 1990's 4,125 5,414 5,802 5,140 4,830 4,868 5,033 4,968 4,604 4,287 2000's 4,149 3,915 3,884 4,301 4,120 3,965 3,911 3,994 3,290 2,871 2010's 2,629 2,475 2,228 1,597 2,036 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  19. California - San Joaquin Basin Onshore Dry Natural Gas Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) California - San Joaquin Basin Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3,784 3,960 3,941 1980's 4,344 4,163 3,901 3,819 3,685 3,574 3,277 3,102 2,912 2,784 1990's 2,670 2,614 2,415 2,327 2,044 1,920 1,768 1,912 1,945 1,951 2000's 2,331 2,232 2,102 2,013 2,185 2,694 2,345 2,309 2,128

  20. California Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) California Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 4,487 4,701 4,700 1980's 5,000 3,928 3,740 3,519 3,374 1990's 3,185 3,004 2,778 2,682 2,402 2,243 2,082 2,273 2,244 2,387 2000's 2,849 2,681 2,591 2,450 2,634 3,228 2,794 2,740 2,406 2,773 2010's 2,647 2,934 1,999 1,887 2,107 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  1. California Federal Offshore Dry Natural Gas Expected Future Production

    Gasoline and Diesel Fuel Update (EIA)

    (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) California Federal Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 250 246 322 1980's 414 1,325 1,452 1,552 1,496 1990's 1,454 1,162 1,118 1,099 1,170 1,265 1,244 544 480 536 2000's 576 540 515 511 459 824 811 805 704 739 2010's 724 710 651 261 240 - = No Data Reported; -- = Not Applicable; NA = Not

  2. Texas (with State Offshore) Natural Gas Plant Liquids, Expected Future

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

    Production (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 2,125 1980's 2,081 2,285 2,393 2,650 2,660 2,610 2,671 2,509 2,339 2,270 1990's 2,305 2,237 2,162 2,211 2,151 2,269 2,337 2,376 2,262 2,257 2000's 2,479 2,318 2,368 2,192 2,466 2,723 2,913 3,158 3,148 3,432 2010's 3,983

  3. Texas Dry Natural Gas Expected Future Production (Billion Cubic Feet)

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

    Expected Future Production (Billion Cubic Feet) Texas Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 43,591 43,264 40,574 38,711 38,167 38,381 1990's 38,192 36,174 35,093 34,718 35,974 36,542 38,270 37,761 37,584 40,157 2000's 42,082 43,527 44,297 45,730 49,955 56,507 61,836 72,091 77,546 80,424 2010's 88,997 98,165 86,924 90,349 97,154 - = No Data Reported; -- = Not Applicable; NA = Not

  4. Ohio Dry Natural Gas Expected Future Production (Billion Cubic Feet)

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

    Expected Future Production (Billion Cubic Feet) Ohio Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 495 684 1,479 1980's 1,699 965 1,141 2,030 1,541 1,331 1,420 1,069 1,229 1,275 1990's 1,214 1,181 1,161 1,104 1,094 1,054 1,113 985 890 1,179 2000's 1,185 970 1,117 1,126 974 898 975 1,027 985 896 2010's 832 758 1,233 3,161 6,723 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  5. Oklahoma Dry Natural Gas Expected Future Production (Billion Cubic Feet)

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

    Expected Future Production (Billion Cubic Feet) Oklahoma Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 13,889 14,417 13,816 1980's 13,138 14,699 16,207 16,211 16,126 16,040 16,685 16,711 16,495 15,916 1990's 16,151 14,725 13,926 13,289 13,487 13,438 13,074 13,439 13,645 12,543 2000's 13,699 13,558 14,886 15,401 16,238 17,123 17,464 19,031 20,845 22,769 2010's 26,345 27,830 26,599 26,873 31,778 -

  6. Pennsylvania Dry Natural Gas Expected Future Production (Billion Cubic

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

    Feet) Expected Future Production (Billion Cubic Feet) Pennsylvania Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 769 899 1,515 1980's 951 1,264 1,429 1,882 1,575 1,617 1,560 1,647 2,072 1,642 1990's 1,720 1,629 1,528 1,717 1,800 1,482 1,696 1,852 1,840 1,772 2000's 1,741 1,775 2,216 2,487 2,361 2,782 3,050 3,361 3,577 6,985 2010's 13,960 26,529 36,348 49,674 59,873 - = No Data Reported; -- =

  7. Wyoming Dry Natural Gas Expected Future Production (Billion Cubic Feet)

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

    Expected Future Production (Billion Cubic Feet) Wyoming Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 6,305 7,211 7,526 1980's 9,100 9,307 9,758 10,227 10,482 10,617 9,756 10,023 10,308 10,744 1990's 9,944 9,941 10,826 10,933 10,879 12,166 12,320 13,562 13,650 14,226 2000's 16,158 18,398 20,527 21,744 22,632 23,774 23,549 29,710 31,143 35,283 2010's 35,074 35,290 30,094 33,618 27,553 - = No Data

  8. Utah Dry Natural Gas Expected Future Production (Billion Cubic Feet)

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

    Expected Future Production (Billion Cubic Feet) Utah Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 877 925 948 1980's 1,201 1,912 2,161 2,333 2,080 1,999 1,895 1,947 1,298 1,507 1990's 1,510 1,702 1,830 2,040 1,789 1,580 1,633 1,839 2,388 3,213 2000's 4,235 4,579 4,135 3,516 3,866 4,295 5,146 6,391 6,643 7,257 2010's 6,981 7,857 7,548 6,829 6,685 - = No Data Reported; -- = Not Applicable; NA =

  9. Virginia Dry Natural Gas Expected Future Production (Billion Cubic Feet)

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

    Expected Future Production (Billion Cubic Feet) Virginia Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 122 175 216 235 253 248 230 217 1990's 138 225 904 1,322 1,833 1,836 1,930 2,446 1,973 2,017 2000's 1,704 1,752 1,673 1,717 1,742 2,018 2,302 2,529 2,378 3,091 2010's 3,215 2,832 2,579 2,373 2,800 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  10. Speech processing using conditional observable maximum likelihood continuity mapping

    DOE Patents [OSTI]

    Hogden, John; Nix, David

    2004-01-13

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

  11. Reduction in maximum time uncertainty of paired time signals

    DOE Patents [OSTI]

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

    1981-02-11

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

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

    Office of Environmental Management (EM)

    Maximum Fee Performance Period Fee Earned FY2011/2012 $4,059,840 FY2013 $2,928,000 FY2014 $3,022,789 FY2015 FY2016 Cumulative Fee $10,010,629 $19,878,019 $3,214,544 $5,254,840 $5,662,028 $1,421,695 Fee Available $4,324,912 $417,833,183 Contract Base Period: January 3, 2011 - September 2, 2016 (Extended) Fee Information Minimum Fee $0 N/A $19,878,019 Contractor: Babcock & Wilcox Conversion Services, LLC Contract Number: DE-AC30-11CC40015 Contract Type: Cost Plus Award Fee EM Contractor Fee

  13. Reduction in maximum time uncertainty of paired time signals

    DOE Patents [OSTI]

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

    1983-10-04

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

  14. Reduction in maximum time uncertainty of paired time signals

    DOE Patents [OSTI]

    Theodosiou, George E. (West Chicago, IL); Dawson, John W. (Clarendon Hills, IL)

    1983-01-01

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

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

    Open Energy Info (EERE)

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

  16. FY 1996 solid waste integrated life-cycle forecast container summary volume 1 and 2

    SciTech Connect (OSTI)

    Valero, O.J.

    1996-04-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the containers expected to be used for these waste shipments from 1996 through the remaining life cycle of the Hanford Site. In previous years, forecast data have been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to the more detailed report on waste volumes: WHC-EP0900, FY 1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary. Both of these documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on the types of containers that will be used for packaging low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major waste generators for each waste category and container type are also discussed. Containers used for low-level waste (LLW) are described in Appendix A, since LLW requires minimal treatment and storage prior to onsite disposal in the LLW burial grounds. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste are expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters.

  17. Battery Life Data Analysis

    Energy Science and Technology Software Center (OSTI)

    2008-07-01

    The FreedomCar Partnership has established life goals for batteries. Among them is a 15 year calendar life. The software and the underlying methodology attempt to predict cell and battery life using, at most, two years of test data. The software uses statistical models based on data from accelerated aging experiments to estimate cell life. The life model reflects the average cell performance under a given set of stress conditions with time. No specific form ofmore » the life model is assumed. The software will fit the model to experimental data. An error model, reflecting the cell-to-cell variability and measurement errors, is included in the software. Monte Carlo simulations, based on the developed models, are used to assess Lack-of-fit and develop uncertainty limis for the average cell life. The software has three operating modes: fit only, fit and simulation and simulation only. The user is given these options by means of means and alert boxes.« less

  18. EFFECTIVE DOSIMETRIC HALF LIFE OF CESIUM 137 SOIL CONTAMINATION

    SciTech Connect (OSTI)

    Jannik, T; P Fledderman, P; Michael Paller, M

    2008-01-09

    In the early 1960s, an area of privately-owned swamp adjacent to the US Department of Energy's Savannah River Site (SRS), known as Creek Plantation, was contaminated by site operations. Studies conducted in 1974 estimated that approximately 925 GBq of {sup 137}Cs was deposited in the swamp. Subsequently, a series of surveys--composed of 52 monitoring locations--was initiated to characterize and trend the contaminated environment. The annual, potential, maximum doses to a hypothetical hunter were estimated by conservatively using the maximum {sup 137}Cs concentrations measured in the soil. The purpose of this report is to calculate an 'effective dosimetric' half-life for {sup 137}Cs in soil (based on the maximum concentrations) and compare it to the effective environmental half-life (based on the geometric mean concentrations).

  19. Thermal and Mechanical Design Aspects of the LIFE Engine

    SciTech Connect (OSTI)

    Abbott, R P; Gerhard, M A; Latkowski, J F; Kramer, K J; Morris, K R; Peterson, P F; Seifried, J E

    2008-10-25

    The Laser Inertial confinement fusion - Fission Energy (LIFE) engine encompasses the components of a LIFE power plant responsible for converting the thermal energy of fusion and fission reactions into electricity. The design and integration of these components must satisfy a challenging set of requirements driven by nuclear, thermal, geometric, structural, and materials considerations. This paper details a self-consistent configuration for the LIFE engine along with the methods and technologies selected to meet these stringent requirements. Included is discussion of plant layout, coolant flow dynamics, fuel temperatures, expected structural stresses, power cycle efficiencies, and first wall survival threats. Further research and to understand and resolve outstanding issues is also outlined.

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

    Reports and Publications (EIA)

    2006-01-01

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

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

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

    Agnese, R.

    2015-03-30

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

  2. Kansas Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Kansas Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 11,457 10,992 10,243 1980's 9,508 9,860 9,724 9,553 9,387 9,337 10,509 10,494 10,104 10,091 1990's 9,614 9,358 9,681 9,348 9,156 8,571 7,694 6,989 6,402 5,753 2000's 5,299 5,101 4,983 4,819 4,652 4,314 3,931 3,982 3,557 3,279 2010's 3,673 3,486 3,308 3,592 4,359 - = No Data Reported; -- = Not

  3. Louisiana - North Dry Natural Gas Expected Future Production (Billion Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Louisiana - North Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3,135 3,203 2,798 1980's 3,076 3,270 2,912 2,939 2,494 2,587 2,515 2,306 2,398 2,652 1990's 2,588 2,384 2,311 2,325 2,537 2,788 3,105 3,093 2,898 3,079 2000's 3,298 3,881 4,245 5,074 5,770 6,695 6,715 6,344 7,876 17,143 2010's 26,030 27,337 18,418 17,044

  4. Alaska Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Alaska Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 32,243 32,045 32,259 1980's 33,382 33,037 34,990 34,283 34,476 33,847 32,664 33,225 9,078 8,939 1990's 9,300 9,553 9,638 9,907 9,733 9,497 9,294 10,562 9,927 9,734 2000's 9,237 8,800 8,468 8,285 8,407 8,171 10,245 11,917 7,699 9,101 2010's 8,838 9,424 9,579 7,316 6,745 - = No Data Reported; -- =

  5. Arkansas Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Arkansas Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,660 1,681 1,703 1980's 1,774 1,801 1,958 2,069 2,227 2,019 1,992 1,997 1,986 1,772 1990's 1,731 1,669 1,750 1,552 1,607 1,563 1,470 1,475 1,328 1,542 2000's 1,581 1,616 1,650 1,663 1,835 1,964 2,269 3,305 5,626 10,869 2010's 14,178 16,370 11,035 13,518 12,789 - = No Data Reported; -- = Not

  6. Colorado Dry Natural Gas Expected Future Production (Billion Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Expected Future Production (Billion Cubic Feet) Colorado Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 2,512 2,765 2,608 1980's 2,922 2,961 3,314 3,148 2,943 2,881 3,027 2,942 3,535 4,274 1990's 4,555 5,767 6,198 6,722 6,753 7,256 7,710 6,828 7,881 8,987 2000's 10,428 12,527 13,888 15,436 14,743 16,596 17,149 21,851 23,302 23,058 2010's 24,119 24,821 20,666 22,381 20,851 - = No Data Reported; --

  7. West Virginia Dry Natural Gas Expected Future Production (Billion Cubic

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

    Feet) Expected Future Production (Billion Cubic Feet) West Virginia Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,567 1,634 1,558 1980's 2,422 1,834 2,148 2,194 2,136 2,058 2,148 2,242 2,306 2,201 1990's 2,207 2,528 2,356 2,439 2,565 2,499 2,703 2,846 2,868 2,936 2000's 2,900 2,678 3,360 3,306 3,397 4,459 4,509 4,729 5,136 5,946 2010's 7,000 10,345 14,611 22,765 29,432 - = No Data

  8. Life Extension Programs

    National Nuclear Security Administration (NNSA)

    in the U.S. and abroad.

    B61-12 Life Extension Program Undergoes First Full-Scale Wind Tunnel Test http:www.nnsa.energy.govmediaroompressreleaseswindtunnel

  9. Battery Life Predictive Model

    Energy Science and Technology Software Center (OSTI)

    2009-12-31

    The Software consists of a model used to predict battery capacity fade and resistance growth for arbitrary cycling and temperature profiles. It allows the user to extrapolate from experimental data to predict actual life cycle.

  10. Expected brine movement at potential nuclear waste repository salt sites

    SciTech Connect (OSTI)

    McCauley, V.S.; Raines, G.E.

    1987-08-01

    The BRINEMIG brine migration code predicts rates and quantities of brine migration to a waste package emplaced in a high-level nuclear waste repository in salt. The BRINEMIG code is an explicit time-marching finite-difference code that solves a mass balance equation and uses the Jenks equation to predict velocities of brine migration. Predictions were made for the seven potentially acceptable salt sites under consideration as locations for the first US high-level nuclear waste repository. Predicted total quantities of accumulated brine were on the order of 1 m/sup 3/ brine per waste package or less. Less brine accumulation is expected at domal salt sites because of the lower initial moisture contents relative to bedded salt sites. Less total accumulation of brine is predicted for spent fuel than for commercial high-level waste because of the lower temperatures generated by spent fuel. 11 refs., 36 figs., 29 tabs.

  11. Siting Samplers to Minimize Expected Time to Detection

    SciTech Connect (OSTI)

    Walter, Travis; Lorenzetti, David M.; Sohn, Michael D.

    2012-05-02

    We present a probabilistic approach to designing an indoor sampler network for detecting an accidental or intentional chemical or biological release, and demonstrate it for a real building. In an earlier paper, Sohn and Lorenzetti(1) developed a proof of concept algorithm that assumed samplers could return measurements only slowly (on the order of hours). This led to optimal detect to treat architectures, which maximize the probability of detecting a release. This paper develops a more general approach, and applies it to samplers that can return measurements relatively quickly (in minutes). This leads to optimal detect to warn architectures, which minimize the expected time to detection. Using a model of a real, large, commercial building, we demonstrate the approach by optimizing networks against uncertain release locations, source terms, and sampler characteristics. Finally, we speculate on rules of thumb for general sampler placement.

  12. Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

    SciTech Connect (OSTI)

    Aad, G.; Abat, E.; Abbott, B.; Abdallah, J.; Abdelalim, A.A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abramowicz, H.; Acharya, Bobby Samir; Adams, D.L.; Addy, T.N.; Adorisio, C.; Adragna, P.; Adye, T.; Aguilar-Saavedra, J.A.; Aharrouche, M.; Ahlen, S.P.; Ahles, F.; Ahmad, A.; /SUNY, Albany /Alberta U. /Ankara U. /Annecy, LAPP /Argonne /Arizona U. /Texas U., Arlington /Athens U. /Natl. Tech. U., Athens /Baku, Inst. Phys. /Barcelona, IFAE /Belgrade U. /VINCA Inst. Nucl. Sci., Belgrade /Bergen U. /LBL, Berkeley /Humboldt U., Berlin /Bern U., LHEP /Birmingham U. /Bogazici U. /INFN, Bologna /Bologna U.

    2011-11-28

    The Large Hadron Collider (LHC) at CERN promises a major step forward in the understanding of the fundamental nature of matter. The ATLAS experiment is a general-purpose detector for the LHC, whose design was guided by the need to accommodate the wide spectrum of possible physics signatures. The major remit of the ATLAS experiment is the exploration of the TeV mass scale where groundbreaking discoveries are expected. In the focus are the investigation of the electroweak symmetry breaking and linked to this the search for the Higgs boson as well as the search for Physics beyond the Standard Model. In this report a detailed examination of the expected performance of the ATLAS detector is provided, with a major aim being to investigate the experimental sensitivity to a wide range of measurements and potential observations of new physical processes. An earlier summary of the expected capabilities of ATLAS was compiled in 1999 [1]. A survey of physics capabilities of the CMS detector was published in [2]. The design of the ATLAS detector has now been finalised, and its construction and installation have been completed [3]. An extensive test-beam programme was undertaken. Furthermore, the simulation and reconstruction software code and frameworks have been completely rewritten. Revisions incorporated reflect improved detector modelling as well as major technical changes to the software technology. Greatly improved understanding of calibration and alignment techniques, and their practical impact on performance, is now in place. The studies reported here are based on full simulations of the ATLAS detector response. A variety of event generators were employed. The simulation and reconstruction of these large event samples thus provided an important operational test of the new ATLAS software system. In addition, the processing was distributed world-wide over the ATLAS Grid facilities and hence provided an important test of the ATLAS computing system - this is the origin of the expression 'CSC studies' ('computing system commissioning'), which is occasionally referred to in these volumes. The work reported does generally assume that the detector is fully operational, and in this sense represents an idealised detector: establishing the best performance of the ATLAS detector with LHC proton-proton collisions is a challenging task for the future. The results summarised here therefore represent the best estimate of ATLAS capabilities before real operational experience of the full detector with beam. Unless otherwise stated, simulations also do not include the effect of additional interactions in the same or other bunch-crossings, and the effect of neutron background is neglected. Thus simulations correspond to the low-luminosity performance of the ATLAS detector. This report is broadly divided into two parts: firstly the performance for identification of physics objects is examined in detail, followed by a detailed assessment of the performance of the trigger system. This part is subdivided into chapters surveying the capabilities for charged particle tracking, each of electron/photon, muon and tau identification, jet and missing transverse energy reconstruction, b-tagging algorithms and performance, and finally the trigger system performance. In each chapter of the report, there is a further subdivision into shorter notes describing different aspects studied. The second major subdivision of the report addresses physics measurement capabilities, and new physics search sensitivities. Individual chapters in this part discuss ATLAS physics capabilities in Standard Model QCD and electroweak processes, in the top quark sector, in b-physics, in searches for Higgs bosons, supersymmetry searches, and finally searches for other new particles predicted in more exotic models.

  13. Work/Life Balance

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

    Workplace » Work/Life Balance /careers/_assets/images/careers-icon.jpg Work/Life Balance Explore the multiple dimensions of a career at Los Alamos Lab: work with the best minds on the planet in an inclusive environment that is rich in intellectual vitality and opportunities for growth. What our employees say: Health & Wellness "The Lab pays 80 percent of my family's medical premiums with Blue Cross Blue Shield of New Mexico." Retirement & Savings "With the Lab matching my

  14. Numerical estimation of adsorption energy distributions from adsorption isotherm data with the expectation-maximization method

    SciTech Connect (OSTI)

    Stanley, B.J.; Guiochon, G. |

    1993-08-01

    The expectation-maximization (EM) method of parameter estimation is used to calculate adsorption energy distributions of molecular probes from their adsorption isotherms. EM does not require prior knowledge of the distribution function or the isotherm, requires no smoothing of the isotherm data, and converges with high stability towards the maximum-likelihood estimate. The method is therefore robust and accurate at high iteration numbers. The EM algorithm is tested with simulated energy distributions corresponding to unimodal Gaussian, bimodal Gaussian, Poisson distributions, and the distributions resulting from Misra isotherms. Theoretical isotherms are generated from these distributions using the Langmuir model, and then chromatographic band profiles are computed using the ideal model of chromatography. Noise is then introduced in the theoretical band profiles comparable to those observed experimentally. The isotherm is then calculated using the elution-by-characteristic points method. The energy distribution given by the EM method is compared to the original one. Results are contrasted to those obtained with the House and Jaycock algorithm HILDA, and shown to be superior in terms of robustness, accuracy, and information theory. The effect of undersampling of the high-pressure/low-energy region of the adsorption is reported and discussed for the EM algorithm, as well as the effect of signal-to-noise ratio on the degree of heterogeneity that may be estimated experimentally.

  15. Expected result of firing an ICE load on Z without vacuum.

    SciTech Connect (OSTI)

    Savage, Mark Edward; Struve, Kenneth William; Lemke, Raymond William

    2010-07-01

    In addressing the issue of the determining the hazard categorization of the Z Accelerator of doing Special Nuclear Material (SNM) experiments the question arose as to whether the machine could be fired with its central vacuum chamber open, thus providing a path for airborne release of SNM materials. In this report we summarize calculations that show that we could only expect a maximum current of 460 kA into such a load in a long-pulse mode, which will be used for the SNM experiments, and 750 kA in a short-pulse mode, which is not useful for these experiments. We also investigated the effect of the current for both cases and found that for neither case is the current high enough to either melt or vaporize these loads, with a melt threshold of 1.6 MA. Therefore, a necessary condition to melt, vaporize, or otherwise disperse SNM material is that a vacuum must exist in the Z vacuum chamber. Thus the vacuum chamber serves as a passive feature that prevents any airborne release during the shot, regardless of whatever containment may be in place.

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

    Open Energy Info (EERE)

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

  17. U.S. Lower 48 States Onshore Maximum Number of Active Crews Engaged...

    Gasoline and Diesel Fuel Update (EIA)

    Onshore Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) U.S. Lower 48 States Onshore Maximum Number of Active Crews Engaged in Seismic Surveying...

  18. U.S. Maximum Number of Active Crews Engaged in Seismic Surveying...

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

    Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) U.S. Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) Year Jan Feb...

  19. U.S. Lower 48 States Offshore Maximum Number of Active Crews...

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

    Offshore Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) U.S. Lower 48 States Offshore Maximum Number of Active Crews Engaged in Seismic Surveying...

  20. Life With Energy

    K-12 Energy Lesson Plans and Activities Web site (EERE)

    Students will describe ways in which technology affects the environment, both negatively and positively, and identify different forms of energy and their advantages/disadvantages. They will also determine the benefits as well as the environmental harms of using energy to improve our quality of life.

  1. Energy Efficiency Services Sector: Workforce Size and Expectations for Growth

    SciTech Connect (OSTI)

    Goldman, Charles; Fuller, Merrian C.; Stuart, Elizabeth; Peters, Jane S.; McRae, Marjorie; Albers, Nathaniel; Lutzenhiser, Susan; Spahic, Mersiha

    2010-03-22

    The energy efficiency services sector (EESS) is poised to become an increasingly important part of the U.S. economy. Climate change and energy supply concerns, volatile and increasing energy prices, and a desire for greater energy independence have led many state and national leaders to support an increasingly prominent role for energy efficiency in U.S. energy policy. The national economic recession has also helped to boost the visibility of energy efficiency, as part of a strategy to support economic recovery. We expect investment in energy efficiency to increase dramatically both in the near-term and through 2020 and beyond. This increase will come both from public support, such as the American Recovery and Reinvestment Act (ARRA) and significant increases in utility ratepayer funds directed toward efficiency, and also from increased private spending due to codes and standards, increasing energy prices, and voluntary standards for industry. Given the growing attention on energy efficiency, there is a concern among policy makers, program administrators, and others that there is an insufficiently trained workforce in place to meet the energy efficiency goals being put in place by local, state, and federal policy. To understand the likelihood of a potential workforce gap and appropriate response strategies, one needs to understand the size, composition, and potential for growth of the EESS. We use a bottom-up approach based upon almost 300 interviews with program administrators, education and training providers, and a variety of EESS employers and trade associations; communications with over 50 sector experts; as well as an extensive literature review. We attempt to provide insight into key aspects of the EESS by describing the current job composition, the current workforce size, our projections for sector growth through 2020, and key issues that may limit this growth.

  2. LIFE IC | Open Energy Information

    Open Energy Info (EERE)

    Zip: S60 5WG Product: LIFE-IC is a UK national resource centre for the development of all new energy technology innovations. References: LIFE-IC1 This article is a stub. You can...

  3. Geothermal Life Cycle Calculator

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

    Sullivan, John

    This calculator is a handy tool for interested parties to estimate two key life cycle metrics, fossil energy consumption (Etot) and greenhouse gas emission (ghgtot) ratios, for geothermal electric power production. It is based solely on data developed by Argonne National Laboratory for DOEs Geothermal Technologies office. The calculator permits the user to explore the impact of a range of key geothermal power production parameters, including plant capacity, lifetime, capacity factor, geothermal technology, well numbers and depths, field exploration, and others on the two metrics just mentioned. Estimates of variations in the results are also available to the user.

  4. Geothermal Life Cycle Calculator

    SciTech Connect (OSTI)

    Sullivan, John

    2014-03-11

    This calculator is a handy tool for interested parties to estimate two key life cycle metrics, fossil energy consumption (Etot) and greenhouse gas emission (ghgtot) ratios, for geothermal electric power production. It is based solely on data developed by Argonne National Laboratory for DOEs Geothermal Technologies office. The calculator permits the user to explore the impact of a range of key geothermal power production parameters, including plant capacity, lifetime, capacity factor, geothermal technology, well numbers and depths, field exploration, and others on the two metrics just mentioned. Estimates of variations in the results are also available to the user.

  5. What to Expect When Readying to Move Spent Nuclear Fuel from...

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

    What to Expect When Readying to Move Spent Nuclear Fuel from Commercial Nuclear Power Plants What to Expect When Readying to Move Spent Nuclear Fuel from Commercial Nuclear Power ...

  6. Electron energy spectrum and maximum disruption angle under multi-photon

    Office of Scientific and Technical Information (OSTI)

    beamstrahlung (Conference) | SciTech Connect Electron energy spectrum and maximum disruption angle under multi-photon beamstrahlung Citation Details In-Document Search Title: Electron energy spectrum and maximum disruption angle under multi-photon beamstrahlung The final electron energy spectrum under multi-photon beamstrahlung process is derived analytically in the classical and the intermediate regimes. The maximum disruption angle from the low energy tail of the spectrum is also

  7. EERE Takes Important Steps to Ensure Maximum Impact of Technology Program

    Office of Environmental Management (EM)

    Investments | Department of Energy Takes Important Steps to Ensure Maximum Impact of Technology Program Investments EERE Takes Important Steps to Ensure Maximum Impact of Technology Program Investments November 20, 2014 - 6:06pm Addthis Tracking impact of EERE’s investments in wind, solar and other programs is essential to achieve maximum return for taxpayer investment. | Photos courtesy of the National Renewable Energy Laboratory Tracking impact of EERE's investments in wind, solar and

  8. Maximum allowable hydraulic ram force for heel jet removal Tank 241-C-106

    SciTech Connect (OSTI)

    PAULSEN, S.S.

    2003-01-10

    This document contains an evaluation of the maximum force that can be used to actuate the hydraulic ram assembly without causing permanent damage to the riser or pit.

  9. Beyond pollution prevention: Managing life-cycle costs

    SciTech Connect (OSTI)

    Cohan, D.; Gess, D. )

    1993-01-01

    Companies that purchases and use chemicals and materials in their everyday operation are finding that disposing of these products is becoming increasingly expensive. These disposal and liability costs have been the motivating factor behind recent efforts at pollution prevention. This paper suggests an alternative approach: considering the full life-cycle costs of chemicals and materials at the time purchase decisions are made. Life-cycle cost is the sum of all the costs that a product is expected to incur from the time of its purchase, during its use, until the disposal of any wastes or by-products and beyond as long as liabilities may remain. It represents the product's real cost to the company, and as such is a better basis for making cost-effective decisions. By using life-cycle costs to make decisions, companies can prevent uneconomical decisions on potentially hazardous materials and more effectively minimize overall costs. Life-cycle cost management can also help in the formulation of pollution prevention plans by identifying cost-effective waste-reduction alternatives. Although the concepts of life-cycle cost management are straightforward and intuitive, applying these concepts to real decisions may be challenging. This paper presents an overview of life-cycle cost management, discusses some of the challenges companies face applying this approach to real decisions, and provides solutions that meet these challenges.

  10. Coiled tubing working life prediction

    SciTech Connect (OSTI)

    Wu, J.

    1995-12-31

    Failure of coiled tubing, due to the repeated bending and plastic deformation of coiled tubing on and off the reel and gooseneck, is of great concern in coiled tubing operations. This paper discusses the coiled tubing working life based on one of the coiled tubing life models published in the literature, and compares the results with other models. Certain agreements are found among these models. A group of curves is presented to illustrate the coiled tubing working life affected by coiled tubing size and wall thickness, internal pressure, yield strength, reel diameter, gooseneck radius, operation condition (corrosion) and butt-welded connection (stress concentration). The results show that coiled tubing life can be greatly increased by increasing CT wall thickness and CT strength, while the coiled tubing working life decreases under high internal pressure, corrosion, and butt-weld conditions. These curves can be easily used in estimating coiled tubing life for the field use.

  11. Life Events | Department of Energy

    Energy Savers [EERE]

    Life Events Life Events Life Events is a listing of common events that may occur during or after your Federal career. It's divided into three sections: me/my family, job, and retirement. When you click on a question, you will see what actions you may need to take for each of the following programs: Federal Employees Health Benefits (FEHB) Program, Federal Employees Dental and Vision Insurance Program (FEDVIP), Federal Flexible Spending Account Program (FSAFEDS), Federal Long Term Care Insurance

  12. Life Cycle Asset Management

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

    1998-10-14

    (The following directives are deleted or consolidated into this Order and shall be phased out as noted in Paragraph 2: DOE 1332.1A; DOE 4010.1A; DOE 4300.1C; DOE 4320.1B; DOE 4320.2A; DOE 4330.4B; DOE 4330.5; DOE 4540.1C; DOE 4700.1). This Order supersedes specific project management provisions within DOE O 430.1A, LIFE CYCLE ASSET MANAGEMENT. The specific paragraphs canceled by this Order are 6e(7); 7a(3); 7b(11) and (14); 7c(4),(6),(7),(11), and (16); 7d(4) and (8); 7e(3),(10), and (17); Attachment 1, Definitions (item 30 - Line Item Project, item 42 - Project, item 48 - Strategic System); and Attachment 2, Contractor Requirements Document (paragraph 1d regarding a project management system). The remainder of DOE O 430.1A remains in effect. Cancels DOE O 430.1. Canceled by DOE O 413.3.

  13. Microsoft PowerPoint - Snippet 4.9 High Level EVM Expectations 20140711 [Compatibility Mode]

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

    focuses on the DOE Federal Project Director's expectations of the contractor's earned value management system and the resultant EVM data. The high-level EVM expectations presented in this Snippet will cover these areas: EVM concepts and objectives, the scheduling and budgeting process, work authorization, level of effort concerns, variance analysis and reporting, evaluation of the contractor's estimate at completion, baseline control and revisions, and a synopsis of expectations. The requirement

  14. Title 43 CFR 3206.12 What are the Minimum and Maximum Lease Sizes...

    Open Energy Info (EERE)

    .12 What are the Minimum and Maximum Lease Sizes? Jump to: navigation, search OpenEI Reference LibraryAdd to library Legal Document- Federal RegulationFederal Regulation: Title 43...

  15. U.S. Lower 48 States Offshore Maximum Number of Active Crews...

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

    Offshore Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 167...

  16. U.S. Lower 48 States Onshore Maximum Number of Active Crews Engaged...

    Gasoline and Diesel Fuel Update (EIA)

    Onshore Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 435 512...

  17. U.S. Maximum Number of Active Crews Engaged in Seismic Surveying...

    Gasoline and Diesel Fuel Update (EIA)

    Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 615 717 624 481...

  18. A Requirement for Significant Reduction in the Maximum BTU Input Rate of

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

    Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers | Department of Energy A Requirement for Significant Reduction in the Maximum BTU Input Rate of Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers A Requirement for Significant Reduction in the Maximum BTU Input Rate of Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers Comment that a requirement to reduce the BTU input rate of existing decorative

  19. Heterogeneity-corrected vs -uncorrected critical structure maximum point doses in breast balloon brachytherapy

    SciTech Connect (OSTI)

    Kim, Leonard; Narra, Venkat; Yue, Ning

    2013-07-01

    Recent studies have reported potentially clinically meaningful dose differences when heterogeneity correction is used in breast balloon brachytherapy. In this study, we report on the relationship between heterogeneity-corrected and -uncorrected doses for 2 commonly used plan evaluation metrics: maximum point dose to skin surface and maximum point dose to ribs. Maximum point doses to skin surface and ribs were calculated using TG-43 and Varian Acuros for 20 patients treated with breast balloon brachytherapy. The results were plotted against each other and fit with a zero-intercept line. Max skin dose (Acuros) = max skin dose (TG-43) ? 0.930 (R{sup 2} = 0.995). The average magnitude of difference from this relationship was 1.1% (max 2.8%). Max rib dose (Acuros) = max rib dose (TG-43) ? 0.955 (R{sup 2} = 0.9995). The average magnitude of difference from this relationship was 0.7% (max 1.6%). Heterogeneity-corrected maximum point doses to the skin surface and ribs were proportional to TG-43-calculated doses. The average deviation from proportionality was 1%. The proportional relationship suggests that a different metric other than maximum point dose may be needed to obtain a clinical advantage from heterogeneity correction. Alternatively, if maximum point dose continues to be used in recommended limits while incorporating heterogeneity correction, institutions without this capability may be able to accurately estimate these doses by use of a scaling factor.

  20. Program Evaluation: Program Life Cycle

    Broader source: Energy.gov [DOE]

    In general, different types of evaluation are carried out over different parts of a program's life cycle (e.g., Creating a program, Program is underway, or Closing out or end of program)....

  1. Life Sciences | Argonne National Laboratory

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

    Life Sciences Having a healthy impact on energy, medicine and the environment Argonne National Laboratory's life sciences research has yielded a portfolio of advanced technologies that are having a profound impact on medical technologies and therapies, energy production and sustainability, and bioremediation. Argonne's roster of world-class biology and environmental scientists develop viable technologies - from cancer therapies and antibody engineering to biological methane production and

  2. Households to pay more than expected to stay warm this winter

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

    Households to pay more than expected to stay warm this winter Following a colder-than-expected November, U.S. households are forecast to consume more heating fuels than previously expected....resulting in higher heating bills. Homeowners that rely on natural gas will see their total winter expenses rise nearly 13 percent from last winter....while users of electric heat will see a 2.6 percent increase in costs. That's the latest forecast from the U.S. Energy Information Administration. Propane

  3. Loan Guarantees for Three California PV Solar Plants Expected to Create

    Office of Environmental Management (EM)

    1,400 Jobs | Department of Energy Loan Guarantees for Three California PV Solar Plants Expected to Create 1,400 Jobs Loan Guarantees for Three California PV Solar Plants Expected to Create 1,400 Jobs June 30, 2011 - 2:29pm Addthis Ginny Simmons Ginny Simmons Former Managing Editor for Energy.gov, Office of Public Affairs What will these projects produce? These projects are expected to create 1,400 jobs in California and hundreds along the PV module supply chain across the country. Combined,

  4. EVMS Training Snippet: 4.9 High-level EVM Expectations | Department of

    Office of Environmental Management (EM)

    Energy 9 High-level EVM Expectations EVMS Training Snippet: 4.9 High-level EVM Expectations This EVMS Training Snippet, sponsored by the Office of Project Management (PM) focuses on the DOE Federal Project Director's expectations of the contractor's earned value management system and the resultant EVM data. Link to Video Presentation | Prior Snippet (4.8) | Next Snippet (5.1) | Return to Index PDF icon Slides Only PDF icon Slides with Notes More Documents & Publications EVMS Training

  5. U.S. oil production expected to decline over next year, rebounding...

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

    decline over next year, rebounding in late 2016 U.S. monthly crude oil production is ... of this year is expected to decline through August 2016 to 8.6 million barrels per day. ...

  6. Artificial Lift Systems Market is expected to reach USD 19,806...

    Open Energy Info (EERE)

    Artificial Lift Systems Market is expected to reach USD 19,806.8 Million by 2020 Home > Groups > Renewable Energy RFPs Wayne31jan's picture Submitted by Wayne31jan(150) Contributor...

  7. Active hurricane season expected to shut-in higher amount of...

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

    oil and natural gas production An above-normal 2013 hurricane season is expected to ... of natural gas production in the Gulf of Mexico, according to the new forecast from the ...

  8. Work & Life at Munich | GE Global Research

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

    Work & Life at Munich Work & Life at Munich Living at Germany's Cosmopolitan Crossroads offers easy access to outdoor pursuits in the Alps and travel throughout Europe. Click to...

  9. Scientists detect methane levels three times larger than expected over Four

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

    Corners region Methane levels larger over Four Corners region Scientists detect methane levels three times larger than expected over Four Corners region Study is first to show space-based techniques can successfully verify international regulations on fossil energy emissions. December 22, 2014 Scientists detect methane levels three times larger than expected over Four Corners region Study is first to show space-based techniques can successfully verify international regulations on fossil

  10. WHAT CAN I EXPECT FROM THE HEADQUARTERS MEDIATION PROCESS? | Department of

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

    Energy WHAT CAN I EXPECT FROM THE HEADQUARTERS MEDIATION PROCESS? WHAT CAN I EXPECT FROM THE HEADQUARTERS MEDIATION PROCESS? October 18, 2012 - 9:42am Addthis Convening Process After mediation has been requested by one party to a conflict, the Headquarters (HQ) Mediation Program Manager will contact the other side to determine whether they agree to mediate. If they agree to mediate, she will meet separately with each party to discuss and prepare them for the mediation. This private

  11. On the Stochastic Maximum Principle in Optimal Control of Degenerate Diffusions with Lipschitz Coefficients

    SciTech Connect (OSTI)

    Bahlali, Khaled Djehiche, Boualem Mezerdi, Brahim

    2007-12-15

    We establish a stochastic maximum principle in optimal control of a general class of degenerate diffusion processes with global Lipschitz coefficients, generalizing the existing results on stochastic control of diffusion processes. We use distributional derivatives of the coefficients and the Bouleau Hirsh flow property, in order to define the adjoint process on an extension of the initial probability space.

  12. Powering the Future with LIFE

    SciTech Connect (OSTI)

    Moses, E I; Diaz de la Rubia, T

    2009-04-28

    This month's issue has the following articles: (1) Leveraging the National Ignition Facility to meet the climate-energy challenge; (2) The journal into a new era of scientific discoveries; and (3) Safe and sustainable energy with LIFE (Laser Inertial Fusion Energy).

  13. Evaluation of Maximum Radionuclide Groundwater Concentrations for Basement Fill Model. Zion Station Restoration Project

    SciTech Connect (OSTI)

    Sullivan, Terry

    2014-12-02

    ZionSolutions is in the process of decommissioning the Zion Nuclear Power Plant in order to establish a new water treatment plant. There is some residual radioactive particles from the plant which need to be brought down to levels so an individual who receives water from the new treatment plant does not receive a radioactive dose in excess of 25 mrem/y?. The objectives of this report are: (a) To present a simplified conceptual model for release from the buildings with residual subsurface structures that can be used to provide an upper bound on contaminant concentrations in the fill material; (b) Provide maximum water concentrations and the corresponding amount of mass sorbed to the solid fill material that could occur in each building for use in dose assessment calculations; (c) Estimate the maximum concentration in a well located outside of the fill material; and (d) Perform a sensitivity analysis of key parameters.

  14. Three dimensional winds: A maximum cross-correlation application to elastic lidar data

    SciTech Connect (OSTI)

    Buttler, W.T.

    1996-05-01

    Maximum cross-correlation techniques have been used with satellite data to estimate winds and sea surface velocities for several years. Los Alamos National Laboratory (LANL) is currently using a variation of the basic maximum cross-correlation technique, coupled with a deterministic application of a vector median filter, to measure transverse winds as a function of range and altitude from incoherent elastic backscatter lidar (light detection and ranging) data taken throughout large volumes within the atmospheric boundary layer. Hourly representations of three-dimensional wind fields, derived from elastic lidar data taken during an air-quality study performed in a region of complex terrain near Sunland Park, New Mexico, are presented and compared with results from an Environmental Protection Agency (EPA) approved laser doppler velocimeter. The wind fields showed persistent large scale eddies as well as general terrain-following winds in the Rio Grande valley.

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

    SciTech Connect (OSTI)

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

    2015-03-13

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

  16. Direct tests of micro channel plates as the active element of a new shower maximum detector

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

    Ronzhin, A.; Los, S.; Ramberg, E.; Apresyan, A.; Xie, S.; Spiropulu, M.; Kim, H.

    2015-05-22

    We continue the study of micro channel plates (MCP) as the active element of a shower maximum (SM) detector. We present below test beam results obtained with MCPs detecting directly secondary particles of an electromagnetic shower. The MCP efficiency to shower particles is close to 100%. In conclusion, the time resolution obtained for this new type of the SM detector is at the level of 40 ps.

  17. Hydrodynamic equations for electrons in graphene obtained from the maximum entropy principle

    SciTech Connect (OSTI)

    Barletti, Luigi

    2014-08-15

    The maximum entropy principle is applied to the formal derivation of isothermal, Euler-like equations for semiclassical fermions (electrons and holes) in graphene. After proving general mathematical properties of the equations so obtained, their asymptotic form corresponding to significant physical regimes is investigated. In particular, the diffusive regime, the Maxwell-Boltzmann regime (high temperature), the collimation regime and the degenerate gas limit (vanishing temperature) are considered.

  18. Direct tests of micro channel plates as the active element of a new shower maximum detector

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

    Ronzhin, A.; Los, S.; Ramberg, E.; Apresyan, A.; Xie, S.; Spiropulu, M.; Kim, H.

    2015-05-22

    We continue the study of micro channel plates (MCP) as the active element of a shower maximum (SM) detector. We present below test beam results obtained with MCPs detecting directly secondary particles of an electromagnetic shower. The MCP efficiency to shower particles is close to 100%. Furthermore, the time resolution obtained for this new type of the SM detector is at the level of 40 ps.

  19. Federal Offshore--Louisiana and Alabama Natural Gas Plant Liquids, Expected

    Gasoline and Diesel Fuel Update (EIA)

    Future Production (Million Barrels) Expected Future Production (Million Barrels) Federal Offshore--Louisiana and Alabama Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 358 336 309 289 297 1990's 261 292 246 255 267 191 199 352 341 403 2000's 487 460 483 347 410 407 390 365 313 301 2010's 340 354 369 292 367 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  20. California--Los Angeles Basin Onshore Natural Gas Plant Liquids, Expected

    Gasoline and Diesel Fuel Update (EIA)

    Future Production (Million Barrels) Los Angeles Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) California--Los Angeles Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 9 1980's 11 6 6 6 5 6 7 7 7 4 1990's 5 4 5 6 5 4 3 4 5 7 2000's 10 8 10 8 8 9 8 9 6 6 2010's 5 4 4 4 4

  1. California--San Joaquin Basin Onshore Natural Gas Plant Liquids, Expected

    Gasoline and Diesel Fuel Update (EIA)

    Future Production (Million Barrels) San Joaquin Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) California--San Joaquin Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 74 1980's 74 51 118 111 100 115 104 102 96 91 1990's 82 71 79 81 71 77 77 79 57 59 2000's 63 51 68 78 94 110 100 103 97 113 2010's 98 78 77 85 96

  2. Expectations for the hard x-ray continuum and gamma-ray line fluxes from

    Office of Scientific and Technical Information (OSTI)

    the typE IA supernova SN 2014J in M82 (Journal Article) | SciTech Connect Expectations for the hard x-ray continuum and gamma-ray line fluxes from the typE IA supernova SN 2014J in M82 Citation Details In-Document Search Title: Expectations for the hard x-ray continuum and gamma-ray line fluxes from the typE IA supernova SN 2014J in M82 The hard X-ray continuum and gamma-ray lines from a Type Ia supernova dominate its integrated photon emissions and can provide unique diagnostics of the mass

  3. U.S. crude oil production expected to top 9 million barrels per day in December

    Gasoline and Diesel Fuel Update (EIA)

    3 2015 Falling crude prices to slow U.S. oil production growth in 2015 U.S. crude oil production is expected to increase again this year, but lower crude prices will slow the growth in output. In its new forecast, the U.S. Energy Information Administration said domestic crude oil production should average 9.3 million barrels per day in 2015. On-shore production in the Lower 48-states is expected to grow in the early part of the year, before declining in the second half. Production for the

  4. U.S. crude oil production expected to top 9 million barrels per day in December

    Gasoline and Diesel Fuel Update (EIA)

    crude oil production expected to top 9 million barrels per day in December U.S. crude oil production is expected to continue to increase through next year, despite the outlook for lower crude oil prices. In its new short-term forecast, the U.S. Energy Information Administration said monthly average oil production is on track to surpass 9 million barrels per day in December for the first time since 1986 and then rise to an average 9.4 million barrels a day next year. Even though that's down about

  5. U.S. gasoline price expected to drop further below $3 per gallon

    Gasoline and Diesel Fuel Update (EIA)

    gasoline price expected to drop further below $3 per gallon The national average pump price of gasoline dropped below $3 per gallon last week for the first time in nearly four years. U.S. gasoline prices are expected to sink further below the $3 per gallon mark through the end of this year and average under $3 for the year in 2015. In its new short-term forecast, the U.S. Energy Information Administration said the average price for gasoline will continue to decline, reaching an average $2.80 per

  6. U.S. gasoline price expected to drop further below $3 per gallon

    Gasoline and Diesel Fuel Update (EIA)

    U.S. households to pay an average $750 less for gasoline in 2015 In its new forecast, the U.S. Energy Information Administration expects the average U.S. household to spend $750 less for gasoline this year compared to 2014. The price for regular gasoline this year is forecast to average $2.33 per gallon. The average pump price is expected to rise to $2.72 per gallon in 2016. Gasoline prices have already fallen for 15 weeks in a row, matching the record streak in price declines set at the end of

  7. U.S. gasoline prices expected to be cheaper in the second half of 2013

    Gasoline and Diesel Fuel Update (EIA)

    gasoline prices expected to be cheaper in the second half of 2013 U.S. retail gasoline prices should be slightly lower during the second half of 2013. In its new monthly energy forecast, the U.S. Energy Information Administration projects regular- grade gasoline will average $3.59 per gallon in the current third quarter and $3.33 in the fourth quarter. Pump prices are expected to fall as crude oil prices begin to decline and the summer driving season winds down. Crude oil accounts for about

  8. ,"Montana Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  9. ,"New Mexico - East Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico - East Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  10. ,"New Mexico - West Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico - West Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  11. ,"New Mexico Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  12. ,"New Mexico Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  13. ,"New York Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New York Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  14. ,"North Dakota Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  15. ,"North Dakota Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  16. ,"Ohio Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  17. ,"Oklahoma Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  18. ,"Oklahoma Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  19. ,"Pennsylvania Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  20. ,"Texas Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  1. ,"U.S. Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  2. ,"U.S. Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel

  3. ,"Utah Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  4. ,"Utah Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  5. ,"Utah and Wyoming Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    and Wyoming Natural Gas Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah and Wyoming Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2006 ,"Release Date:","11/19/2015" ,"Next Release

  6. ,"Virginia Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  7. ,"West Virginia Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  8. ,"West Virginia Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  9. ,"Wyoming Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  10. ,"Wyoming Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  11. Texas--RRC District 1 Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 1 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 16 1980's 18 20 24 35 33 33 30 22 23 15 1990's 20 23 24 23 23 23 44 46 32 161 2000's 49 35 34 24 31 31 32 43 44 87 2010's 163 158 197 233 343 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  12. Texas--RRC District 10 Natural Gas Plant Liquids, Expected Future

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

    Production (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 10 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 356 1980's 350 349 376 397 425 416 411 402 351 331 1990's 318 346 327 316 305 343 323 372 342 191 2000's 191 311 326 315 373 367 396 458 473 494 2010's 566 578 522 481 598 - = No Data Reported; -- = Not Applicable; NA = Not

  13. Texas--RRC District 2 Onshore Natural Gas Plant Liquids, Expected Future

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

    Production (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 2 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 45 1980's 48 68 52 73 81 76 69 70 67 56 1990's 63 61 66 72 74 82 85 75 75 64 2000's 59 53 60 56 64 72 74 94 88 77 2010's 113 203 374 698 1,037 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  14. Texas--RRC District 3 Onshore Natural Gas Plant Liquids, Expected Future

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

    Production (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 3 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 177 1980's 164 179 212 228 217 211 184 166 150 140 1990's 132 160 172 196 200 204 210 170 169 152 2000's 140 144 170 135 149 148 159 143 131 127 2010's 129 158 184 196 199 - = No Data Reported; -- = Not Applicable; NA =

  15. Texas--RRC District 4 Onshore Natural Gas Plant Liquids, Expected Future

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

    Production (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 4 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 172 1980's 177 183 204 212 208 183 197 197 186 188 1990's 208 204 207 213 220 217 241 261 267 300 2000's 316 281 279 202 253 238 246 250 231 231 2010's 258 402 562 1,069 987 - = No Data Reported; -- = Not Applicable; NA =

  16. Texas--RRC District 5 Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 5 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 24 1980's 32 42 44 61 61 62 73 76 72 65 1990's 61 53 55 50 50 47 48 31 31 24 2000's 24 43 39 40 44 40 42 50 126 192 2010's 225 237 214 183 193 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure

  17. Texas--RRC District 6 Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 6 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 228 1980's 268 259 232 280 253 247 224 213 210 212 1990's 195 195 205 202 218 223 242 221 235 182 2000's 182 215 213 195 233 264 279 324 318 330 2010's 369 360 269 376 387 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  18. Texas--RRC District 7B Natural Gas Plant Liquids, Expected Future

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

    Production (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 7B Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 62 1980's 82 99 99 129 103 101 106 90 95 71 1990's 74 81 67 73 61 69 64 57 48 34 2000's 34 28 24 31 42 89 131 200 269 326 2010's 359 416 295 332 312 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  19. Texas--RRC District 7C Natural Gas Plant Liquids, Expected Future

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

    Production (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 7C Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 168 1980's 120 172 184 204 219 242 232 231 226 225 1990's 234 218 266 250 241 255 285 309 266 291 2000's 291 271 326 319 365 391 404 464 402 412 2010's 465 549 524 438 473 - = No Data Reported; -- = Not Applicable; NA = Not

  20. Texas--RRC District 8 Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 8 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 452 1980's 452 498 554 650 662 646 697 623 530 542 1990's 545 466 426 430 398 432 417 447 479 479 2000's 479 504 488 484 487 559 547 525 524 536 2010's 618 689 802 830 1,240 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  1. Texas--RRC District 8A Natural Gas Plant Liquids, Expected Future

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

    Production (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 8A Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 350 1980's 289 335 296 262 282 282 331 307 325 332 1990's 353 333 257 297 267 284 262 290 226 222 2000's 222 250 180 163 197 248 231 260 194 201 2010's 230 239 242 239 245 - = No Data Reported; -- = Not Applicable; NA = Not

  2. Texas--RRC District 9 Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--RRC District 9 Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 75 1980's 81 81 111 115 113 106 112 107 102 90 1990's 100 96 89 88 94 90 116 96 91 156 2000's 156 182 229 228 228 276 372 347 348 419 2010's 488 552 542 578 662 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  3. Texas--State Offshore Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) Texas--State Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0 1980's 0 0 5 4 3 5 5 5 2 3 1990's 2 1 1 1 0 0 0 1 1 1 2000's 1 1 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  4. New Mexico--East Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) New Mexico--East Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 192 1980's 192 197 193 216 206 192 200 176 193 179 1990's 200 187 204 215 222 236 287 253 243 230 2000's 302 259 266 251 245 237 264 274 261 289 2010's 342 350 310 329 443 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  5. New Mexico--West Natural Gas Plant Liquids, Expected Future Production

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

    (Million Barrels) Plant Liquids, Expected Future Production (Million Barrels) New Mexico--West Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 273 1980's 286 299 282 279 256 203 314 532 733 684 1990's 715 653 790 710 724 645 711 561 633 666 2000's 502 535 513 573 560 544 540 514 465 426 2010's 422 426 352 350 346 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  6. New York Dry Natural Gas Expected Future Production (Billion Cubic Feet)

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

    Expected Future Production (Billion Cubic Feet) New York Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 165 193 211 1980's 208 264 229 295 389 369 457 410 351 368 1990's 354 331 329 264 242 197 232 224 218 221 2000's 322 318 315 365 324 349 363 376 389 196 2010's 281 253 184 144 143 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  7. ,"Alabama Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  8. ,"Alaska Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  9. ,"Arkansas Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  10. ,"Arkansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  11. ,"California Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  12. ,"California Federal Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Federal Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  13. ,"Colorado Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  14. ,"Colorado Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  15. ,"Florida Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  16. ,"Florida Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  17. ,"Kansas Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  18. ,"Kansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  19. ,"Kentucky Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  20. ,"Kentucky Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  1. ,"Louisiana - North Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana - North Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  2. ,"Louisiana - South Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana - South Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  3. ,"Louisiana Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  4. ,"Louisiana--North Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--North Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  5. ,"Louisiana--South Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--South Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  6. ,"Lower 48 States Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Lower 48 States Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  7. ,"Lower 48 States Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Lower 48 States Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  8. ,"Michigan Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  9. ,"Michigan Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016"

  10. ,"Miscellaneous States Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Miscellaneous States Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  11. ,"Miscellaneous States Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Miscellaneous States Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  12. ,"Mississippi Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  13. ,"Montana Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release Date:","12/31/2016" ,"Excel File

  14. Average household expected to save $675 at the pump in 2015

    Gasoline and Diesel Fuel Update (EIA)

    Average household expected to save $675 at the pump in 2015 Although retail gasoline prices have risen in recent weeks U.S. consumers are still expected to save about $675 per household in motor fuel costs this year. In its new monthly forecast, the U.S. Energy Information Administration says the average pump price for regular grade gasoline in 2015 will be $2.43 per gallon. That's about 93 cents lower than last year's average. The savings for consumers will be even bigger during the

  15. Extended space expectation values of position related operators for hydrogen-like quantum system evolutions

    SciTech Connect (OSTI)

    Kalay, Berfin; Demiralp, Metin

    2014-10-06

    The expectation value definitions over an extended space from the considered Hilbert space of the system under consideration is given in another paper of the second author in this symposium. There, in that paper, the conceptuality rather than specification is emphasized on. This work uses that conceptuality to investigate the time evolutions of the position related operators' expectation values not in its standard meaning but rather in a new version of the definition over not the original Hilbert space but in the space obtained by extensions via introducing the images of the given initial wave packet under the positive integer powers of the system Hamiltonian. These images may not be residing in the same space of the initial wave packet when certain singularities appear in the structure of the system Hamiltonian. This may break down the existence of the integrals in the definitions of the expectation values. The cure is the use of basis functions in the abovementioned extended space and the sandwiching of the target operator whose expectation value is under questioning by an appropriately chosen operator guaranteeing the existence of the relevant integrals. Work specifically focuses on the hydrogen-like quantum systems whose Hamiltonians contain a polar singularity at the origin.

  16. What to Expect When Readying to Move Spent Nuclear Fuel from Commercial

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

    Nuclear Power Plants | Department of Energy PDF icon What to Expect When Readying to Move Spent Nuclear Fuel from Commercial Nuclear Power Plants More Documents & Publications Nuclear Fuel Storage and Transportation Planning Project Overview Indiana Department of Homeland Security - NNPP Exercise Better Security Through Discussion

  17. Chemistry, Life, and Earth Sciences

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

    ADCLES Chemistry, Life, and Earth Sciences The CLES Directorate is home to world class capabilities in chemistry, bioscience, and earth and environmental sciences. Structural protein research Structural protein research A wide range of protein folding research Field Instrument Deployments and Operations (FIDO) Field Instrument Deployments and Operations (FIDO) Atmospheric science research Quantum Dots Quantum Dots Quantum dot research for energy and light Contact Us Associate Director Nan Sauer

  18. Free kick instead of cross-validation in maximum-likelihood refinement of macromolecular crystal structures

    SciTech Connect (OSTI)

    Pranikar, Jure [Institute Joef Stefan, Jamova 39, 1000 Ljubljana (Slovenia); University of Primorska, (Slovenia); Turk, Duan, E-mail: dusan.turk@ijs.si [Institute Joef Stefan, Jamova 39, 1000 Ljubljana (Slovenia); Center of Excellence for Integrated Approaches in Chemistry and Biology of Proteins, (Slovenia)

    2014-12-01

    The maximum-likelihood free-kick target, which calculates model error estimates from the work set and a randomly displaced model, proved superior in the accuracy and consistency of refinement of crystal structures compared with the maximum-likelihood cross-validation target, which calculates error estimates from the test set and the unperturbed model. The refinement of a molecular model is a computational procedure by which the atomic model is fitted to the diffraction data. The commonly used target in the refinement of macromolecular structures is the maximum-likelihood (ML) function, which relies on the assessment of model errors. The current ML functions rely on cross-validation. They utilize phase-error estimates that are calculated from a small fraction of diffraction data, called the test set, that are not used to fit the model. An approach has been developed that uses the work set to calculate the phase-error estimates in the ML refinement from simulating the model errors via the random displacement of atomic coordinates. It is called ML free-kick refinement as it uses the ML formulation of the target function and is based on the idea of freeing the model from the model bias imposed by the chemical energy restraints used in refinement. This approach for the calculation of error estimates is superior to the cross-validation approach: it reduces the phase error and increases the accuracy of molecular models, is more robust, provides clearer maps and may use a smaller portion of data for the test set for the calculation of R{sub free} or may leave it out completely.

  19. Alaska Maximum Number of Active Crews Engaged in Three-Dimensional Seismic

    Gasoline and Diesel Fuel Update (EIA)

    Surveying (Number of Elements) Three-Dimensional Seismic Surveying (Number of Elements) Alaska Maximum Number of Active Crews Engaged in Three-Dimensional Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 1 2 2 2 1 1 0 0 0 0 2001 0 0 0 0 1 1 0 0 0 0 0 0 2002 1 1 1 1 1 1 1 1 1 1 1 0 2003 0 0 1 1 1 1 1 1

  20. A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.

    SciTech Connect (OSTI)

    Wahl, Daniel E.; Yocky, David A.; Jakowatz, Charles V,

    2014-09-01

    In this paper, we derive a new optimal change metric to be used in synthetic aperture RADAR (SAR) coherent change detection (CCD). Previous CCD methods tend to produce false alarm states (showing change when there is none) in areas of the image that have a low clutter-to-noise power ratio (CNR). The new estimator does not suffer from this shortcoming. It is a surprisingly simple expression, easy to implement, and is optimal in the maximum-likelihood (ML) sense. The estimator produces very impressive results on the CCD collects that we have tested.

  1. Federal Employees' Group Life Insurance (FEGLI) | Department...

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

    The Types of Coverage Available Basic Life Basic life is based on your annual basic rate ... FEGLI insurance is a term insurance policy and has no cash value. Optional Insurance There ...

  2. Analysis to determine the maximum dimensions of flexible apertures in sensored security netting products.

    SciTech Connect (OSTI)

    Murton, Mark; Bouchier, Francis A.; vanDongen, Dale T.; Mack, Thomas Kimball; Cutler, Robert Paul; Ross, Michael P.

    2013-08-01

    Although technological advances provide new capabilities to increase the robustness of security systems, they also potentially introduce new vulnerabilities. New capability sometimes requires new performance requirements. This paper outlines an approach to establishing a key performance requirement for an emerging intrusion detection sensor: the sensored net. Throughout the security industry, the commonly adopted standard for maximum opening size through barriers is a requirement based on square inches-typically 96 square inches. Unlike standard rigid opening, the dimensions of a flexible aperture are not fixed, but variable and conformable. It is demonstrably simple for a human intruder to move through a 96-square-inch opening that is conformable to the human body. The longstanding 96-square-inch requirement itself, though firmly embedded in policy and best practice, lacks a documented empirical basis. This analysis concluded that the traditional 96-square-inch standard for openings is insufficient for flexible openings that are conformable to the human body. Instead, a circumference standard is recommended for these newer types of sensored barriers. The recommended maximum circumference for a flexible opening should be no more than 26 inches, as measured on the inside of the netting material.

  3. Estimates of maximum strains induced in buried pipelines by dynamic loading

    SciTech Connect (OSTI)

    Fernandez, G.; Al-Chaar, G.; Brady, P.

    1995-12-31

    An evaluation of pipe strains measured during full scale blast in-situ tests was carried out to assess the effects produced by a nearby quarry blast in a buried, steel pipeline carrying pressurized gas. The result of the blast tests indicated that the magnitude of the maximum circumferential strain is equal or larger than the magnitude of the maximum axial strain measured in the pipe. It was also observed that circumferential strains can develop simultaneously with the dynamic-induced axial strains, resulting in a more critical loading condition than the one contemplated by the ASCE (1983) design guidelines for seismic loading. This behavior can become critical in pressurized pipes where significant circumferential stresses are already present under normal operating conditions. Based on the results of these tests, recommendations for including circumferential strains are suggested to the ASCE (1983) Design Guidelines. Consideration should be given to a compressive wave traveling at a high angle which respect to the longitudinal axis of the pipe which can induce squeezing or ovaling of the pipe section, resulting in significant circumferential strains in the pipe.

  4. Tropical Cloud Life Cycle and Overlap Structure

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

    Life Cycle and Overlap Structure Vogelmann, Andrew Brookhaven National Laboratory Jensen, Michael Brookhaven National Laboratory Kollias, Pavlos Brookhaven National Laboratory...

  5. Licensable Life Science Technologies | Argonne National Laboratory

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

    Licensable Life Science Technologies A selection of biology-based technologies available for licensing PDF icon licensable_biological_technologies

  6. Gulf of Mexico Federal Offshore - Texas Dry Natural Gas Expected Future

    Gasoline and Diesel Fuel Update (EIA)

    Production (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Gulf of Mexico Federal Offshore - Texas Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6,878 6,493 7,444 7,219 7,241 6,968 1990's 7,300 6,675 6,996 6,661 6,383 6,525 5,996 5,988 5,648 5,853 2000's 6,384 6,775 6,189 5,331 4,127 3,342 2,725 2,544 2,392 2,451 2010's 2,145 1,554 1,450 1,450 1,397 - =

  7. Gulf of Mexico Federal Offshore Dry Natural Gas Expected Future Production

    Gasoline and Diesel Fuel Update (EIA)

    (Billion Cubic Feet) Expected Future Production (Billion Cubic Feet) Gulf of Mexico Federal Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 26,649 26,044 27,218 27,917 27,852 27,922 26,422 25,451 2000's 26,172 26,456 24,689 22,059 18,812 17,007 14,549 13,634 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  8. Lower 48 States Dry Natural Gas Expected Future Production (Billion Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Lower 48 States Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 175,170 175,988 168,738 1980's 165,639 168,693 166,522 165,964 162,987 159,522 158,922 153,986 158,946 158,177 1990's 160,046 157,509 155,377 152,508 154,104 155,649 157,180 156,661 154,114 157,672 2000's 168,190 174,660 178,478 180,759 184,106 196,214 200,840

  9. Texas - RRC District 1 Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 1 Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,319 986 919 1980's 829 1,022 892 1,087 838 967 913 812 1,173 1,267 1990's 1,048 1,030 933 698 703 712 906 953 1,104 1,008 2000's 1,032 1,018 1,045 1,062 1,184 1,161 1,063 1,040 985 1,398 2010's 2,399 5,910 8,868 7,784 11,945 - = No Data Reported;

  10. Texas - RRC District 2 Onshore Dry Natural Gas Expected Future Production

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

    (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 2 Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3,162 2,976 2,974 1980's 2,502 2,629 2,493 2,534 2,512 2,358 2,180 2,273 2,037 1,770 1990's 1,737 1,393 1,389 1,321 1,360 1,251 1,322 1,634 1,614 1,881 2000's 1,980 1,801 1,782 1,770 1,844 2,073 2,060 2,255 2,238 1,800 2010's 2,090

  11. Texas - RRC District 3 Onshore Dry Natural Gas Expected Future Production

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

    (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 3 Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 7,518 7,186 6,315 1980's 5,531 5,292 4,756 4,680 4,708 4,180 3,753 3,632 3,422 3,233 1990's 2,894 2,885 2,684 2,972 3,366 3,866 4,349 4,172 3,961 3,913 2000's 3,873 3,770 3,584 3,349 3,185 3,192 3,050 2,904 2,752 2,616 2010's 2,588

  12. Texas - RRC District 4 Onshore Dry Natural Gas Expected Future Production

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

    (Billion Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 4 Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 9,621 9,031 8,326 1980's 8,130 8,004 8,410 8,316 8,525 8,250 8,274 7,490 7,029 7,111 1990's 7,475 7,048 6,739 7,038 7,547 7,709 7,769 8,099 8,429 8,915 2000's 9,645 9,956 9,469 8,763 8,699 8,761 8,116 7,963 7,604 6,728 2010's 7,014

  13. Texas - RRC District 5 Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 5 Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 931 1,298 1,155 1980's 1,147 1,250 1,308 1,448 1,874 2,058 2,141 2,119 1,996 1,845 1990's 1,875 1,863 1,747 1,867 2,011 1,862 2,079 1,710 1,953 2,319 2000's 3,168 4,231 4,602 5,407 6,523 9,557 12,593 17,205 20,281 22,343 2010's 24,363 27,843 17,331

  14. Texas - RRC District 7B Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 7B Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 699 743 751 1980's 745 804 805 1,027 794 708 684 697 704 459 1990's 522 423 455 477 425 440 520 478 442 416 2000's 312 252 260 340 310 802 1,471 2,117 2,382 2,077 2010's 2,242 3,305 2,943 2,787 2,290 - = No Data Reported; -- = Not Applicable; NA =

  15. Texas - RRC District 8A Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 8A Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,630 1,473 1,055 1980's 1,057 1,071 1,041 966 907 958 845 876 832 1,074 1990's 1,036 1,073 1,239 1,043 1,219 941 931 847 807 1,257 2000's 1,101 1,085 1,084 1,056 1,188 1,366 1,290 1,431 1,172 1,218 2010's 1,164 1,226 1,214 1,269 1,257 - = No Data

  16. Texas - RRC District 9 Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 9 Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 724 908 700 1980's 649 953 1,103 932 900 892 868 834 783 703 1990's 776 738 670 688 728 738 705 794 734 1,137 2000's 1,626 2,289 2,877 3,309 4,221 4,328 6,218 7,476 9,037 10,904 2010's 12,464 10,115 8,894 9,195 8,791 - = No Data Reported; -- = Not

  17. U.S. Dry Natural Gas Expected Future Production (Billion Cubic Feet)

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

    Expected Future Production (Billion Cubic Feet) U.S. Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1920's 23,000 1930's 46,000 62,000 66,000 70,000 1940's 85,000 113,800 110,000 110,000 133,500 146,987 159,704 165,026 172,925 179,402 1950's 184,585 192,759 198,632 210,299 210,561 222,483 236,483 245,230 252,762 261,170 1960's 262,326 266,274 272,279 276,151 281,251 286,469 289,333 292,908 287,350

  18. U.S. Federal Offshore Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) U.S. Federal Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 31,433 29,448 27,767 27,143 28,388 29,182 29,096 28,466 26,902 25,987 2000's 26,748 27,036 25,204 22,570 19,271 17,831 15,360 14,439 13,546 12,552 2010's 11,765 10,420 9,392 8,193 8,527 - = No Data Reported; -- = Not Applicable; NA = Not Available; W

  19. New Mexico - West Dry Natural Gas Expected Future Production (Billion Cubic

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

    Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) New Mexico - West Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 8,152 8,799 9,693 1980's 9,757 10,272 8,986 8,446 8,167 7,866 9,114 8,739 14,221 12,359 1990's 14,004 15,333 15,868 15,585 14,207 14,624 13,695 12,872 12,294 12,412 2000's 13,785 13,896 13,688 13,719 14,891 14,410 14,020 13,251 12,254 11,457 2010's 11,186

  20. New Mexico Dry Natural Gas Expected Future Production (Billion Cubic Feet)

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

    Expected Future Production (Billion Cubic Feet) New Mexico Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 12,000 12,688 13,724 1980's 13,287 13,870 12,418 11,676 11,364 10,900 11,808 11,620 17,166 15,434 1990's 17,260 18,539 18,998 18,619 17,228 17,491 16,485 15,514 14,987 15,449 2000's 17,322 17,414 17,320 17,020 18,512 18,201 17,934 17,245 16,285 15,598 2010's 15,412 15,005 13,586 13,576 15,283

  1. U.S. Natural Gas Plant Liquids, Expected Future Production (Million

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

    Barrels) Liquids, Expected Future Production (Million Barrels) U.S. Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 5,204 1980's 5,198 5,488 5,620 6,288 6,121 6,491 6,729 6,745 6,849 6,380 1990's 6,284 6,220 6,225 6,030 6,023 6,202 6,516 6,632 6,188 6,503 2000's 6,873 6,595 6,648 6,244 6,707 6,903 7,133 7,648 7,842 8,557 2010's 9,809 10,825 10,777 11,943 15,029 - = No Data Reported; --

  2. What to Expect when being Processed for a Department of Energy Security Clearance or Access Authorization

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

    WHAT TO EXPECT WHEN BEING PROCESSED FOR A DEPARTMENT OF ENERGY SECURITY CLEARANCE OR ACCESS AUTHORIZATION INTRODUCTION This overview will help individuals new to the process understand what it means to obtain and maintain a Department of Energy (DOE) security clearance or access authorization. You are a part of a select group of individuals who are being considered for access to classified information maintained by DOE. WHAT IS CLASSIFIED INFORMATION? As you know, the protection of classified

  3. Assumptions and Expectations for Annual Energy Outlook 2015: Oil and Gas Working Group

    Gasoline and Diesel Fuel Update (EIA)

    Assumptions and Expectations for Annual Energy Outlook 2016: Oil and Gas Working Group AEO2016 Oil and Gas Supply Working Group Meeting Office of Petroleum, Gas, and Biofuels Analysis December 1, 2015| Washington, DC http://www.eia.gov/forecasts/aeo/workinggroup/ WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE We welcome feedback on our assumptions and documentation * The AEO Assumptions report http://www.eia.gov/forecasts/aeo/assumptions/

  4. Programmable AC power supply for simulating power transient expected in fusion reactor

    SciTech Connect (OSTI)

    Halimi, B.; Suh, K. Y.

    2012-07-01

    This paper focus on control engineering of the programmable AC power source which has capability to simulate power transient expected in fusion reactor. To generate the programmable power source, AC-AC power electronics converter is adopted to control the power of a set of heaters to represent the transient phenomena of heat exchangers or heat sources of a fusion reactor. The International Thermonuclear Experimental Reactor (ITER) plasma operation scenario is used as the basic reference for producing this transient power source. (authors)

  5. Title: The Life-cycle

    Office of Scientific and Technical Information (OSTI)

    The Life-cycle of Operons Authors: Morgan N. Price, Adam P. Arkin, and Eric J. Alm Author affiliation: Lawrence Berkeley Lab, Berkeley CA, USA and the Virtual Institute for Microbial Stress and Survival. A.P.A. is also affiliated with the Howard Hughes Medical Institute and the UC Berkeley Dept. of Bioengineering. Corresponding author: Eric Alm, ejalm@lbl.gov, phone 510-486-6899, fax 510-486-6219, address Lawrence Berkeley National Lab, 1 Cyclotron Road, Mailstop 977-152, Berkeley, CA 94720

  6. Life extension system for fossil power plants

    SciTech Connect (OSTI)

    Isreb, M.

    1996-11-01

    A general, multi-disciplinary life extension system for new and existing power plants has been absent in the literature. The present paper presents a general, multi-disciplinary life extension system for new and existing fossil power plants. The paper formulates the optimization problem framework for plants` components. The paper discusses the framework of the iterative process, objective functions, plant components, life extension constraints, new life or remnant life parameters and optimization techniques. Other system attributes discussed in the paper include: design invariant parameters, relationships between plant components and objective functions and a strategy for system sizing and simulation.

  7. Technology development life cycle processes.

    SciTech Connect (OSTI)

    Beck, David Franklin

    2013-05-01

    This report and set of appendices are a collection of memoranda originally drafted in 2009 for the purpose of providing motivation and the necessary background material to support the definition and integration of engineering and management processes related to technology development. At the time there was interest and support to move from Capability Maturity Model Integration (CMMI) Level One (ad hoc processes) to Level Three. As presented herein, the material begins with a survey of open literature perspectives on technology development life cycles, including published data on %E2%80%9Cwhat went wrong.%E2%80%9D The main thrust of the material presents a rational expose%CC%81 of a structured technology development life cycle that uses the scientific method as a framework, with further rigor added from adapting relevant portions of the systems engineering process. The material concludes with a discussion on the use of multiple measures to assess technology maturity, including consideration of the viewpoint of potential users.

  8. A 3D approximate maximum likelihood solver for localization of fish implanted with acoustic transmitters

    SciTech Connect (OSTI)

    Li, Xinya; Deng, Z. Daniel; USA, Richland Washington; Sun, Yannan; USA, Richland Washington; Martinez, Jayson J.; USA, Richland Washington; Fu, Tao; USA, Richland Washington; McMichael, Geoffrey A.; USA, Richland Washington; Carlson, Thomas J.; USA, Richland Washington

    2014-11-27

    Better understanding of fish behavior is vital for recovery of many endangered species including salmon. The Juvenile Salmon Acoustic Telemetry System (JSATS) was developed to observe the out-migratory behavior of juvenile salmonids tagged by surgical implantation of acoustic micro-transmitters and to estimate the survival when passing through dams on the Snake and Columbia Rivers. A robust three-dimensional solver was needed to accurately and efficiently estimate the time sequence of locations of fish tagged with JSATS acoustic transmitters, to describe in sufficient detail the information needed to assess the function of dam-passage design alternatives. An approximate maximum likelihood solver was developed using measurements of time difference of arrival from all hydrophones in receiving arrays on which a transmission was detected. Field experiments demonstrated that the developed solver performed significantly better in tracking efficiency and accuracy than other solvers described in the literature.

  9. A 3D approximate maximum likelihood solver for localization of fish implanted with acoustic transmitters

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

    Li, Xinya; Deng, Z. Daniel; USA, Richland Washington; Sun, Yannan; USA, Richland Washington; Martinez, Jayson J.; USA, Richland Washington; Fu, Tao; USA, Richland Washington; McMichael, Geoffrey A.; et al

    2014-11-27

    Better understanding of fish behavior is vital for recovery of many endangered species including salmon. The Juvenile Salmon Acoustic Telemetry System (JSATS) was developed to observe the out-migratory behavior of juvenile salmonids tagged by surgical implantation of acoustic micro-transmitters and to estimate the survival when passing through dams on the Snake and Columbia Rivers. A robust three-dimensional solver was needed to accurately and efficiently estimate the time sequence of locations of fish tagged with JSATS acoustic transmitters, to describe in sufficient detail the information needed to assess the function of dam-passage design alternatives. An approximate maximum likelihood solver was developedmore » using measurements of time difference of arrival from all hydrophones in receiving arrays on which a transmission was detected. Field experiments demonstrated that the developed solver performed significantly better in tracking efficiency and accuracy than other solvers described in the literature.« less

  10. Alaska Maximum Number of Active Crews Engaged in Two-Dimensional Seismic

    Gasoline and Diesel Fuel Update (EIA)

    Surveying (Number of Elements) Two-Dimensional Seismic Surveying (Number of Elements) Alaska Maximum Number of Active Crews Engaged in Two-Dimensional Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 1 1 1 1 0 0 0 0 0 0 2001 0 0 0 0 1 1 0 0 0 0 0 0 2002 1 1 1 1 1 1 1 1 1 1 1 1 2003 0 0 1 1 1 1 1 1 0 0 0 0 2004 0 0 0 0 0 0 0 0 0 0 0 0 2005 0 0 0 0 0 0 0 0 0 0 0 0 2006 0 0 0 0 0 0 0 0 0 0 0 0 2007 0 0 0 0 0 0 0 0 0 0 0 0 2008 0 0 0 0 0 0 0 0

  11. Maximum Achievable Control Technology for New Industrial Boilers (released in AEO2005)

    Reports and Publications (EIA)

    2005-01-01

    As part of Clean Air Act 90 (CAAA90, the EPA on February 26, 2004, issued a final rulethe National Emission Standards for Hazardous Air Pollutants (NESHAP) to reduce emissions of hazardous air pollutants (HAPs) from industrial, commercial, and institutional boilers and process heaters. The rule requires industrial boilers and process heaters to meet limits on HAP emissions to comply with a Maximum Achievable Control Technology (MACT) floor level of control that is the minimum level such sources must meet to comply with the rule. The major HAPs to be reduced are hydrochloric acid, hydrofluoric acid, arsenic, beryllium, cadmium, and nickel. The EPA predicts that the boiler MACT rule will reduce those HAP emissions from existing sources by about 59,000 tons per year in 2005.

  12. U.S.Lower 48 States Offshore Maximum Number of Active Crews Engaged in

    Gasoline and Diesel Fuel Update (EIA)

    Four-Dimensional Seismic Surveying (Number of Elements) Four-Dimensional Seismic Surveying (Number of Elements) U.S.Lower 48 States Offshore Maximum Number of Active Crews Engaged in Four-Dimensional Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 NA NA 0 0 0 0 0 0 0 0 0 0 2001 0 0 0 0 0 0 0 0 0 0 0 0 2002 0 0 0 0 0 0 0 0 0 0 0 0 2003 0 0 0 0 0 0 0 0 0 0 0 0 2004 0 0 0 0 0 0 0 0 0 0 0 0 2005 0 0 0 0 0 0 0 0 0 0 0 0 2006 0 0 0 0 0 0 0 0 0 0 0 0

  13. U.S.Lower 48 States Offshore Maximum Number of Active Crews Engaged in

    Gasoline and Diesel Fuel Update (EIA)

    Three-Dimensional Seismic Surveying (Number of Elements) Three-Dimensional Seismic Surveying (Number of Elements) U.S.Lower 48 States Offshore Maximum Number of Active Crews Engaged in Three-Dimensional Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 11 11 11 9 6 7 8 9 8 8 2001 7 7 9 9 8 7 8 8 9 10 10 9 2002 6 6 7 7 8 7 8 7 7 7 5 4 2003 4 4 4 4 4 4 4 4 2 3 3 5 2004 5 5 5 4 4 4 4 4 2 2 4 4 2005 4 4 6 6 6 5 5 5 5 5 5 5 2006 5 6 6 6 6 5 5 5 5

  14. U.S.Lower 48 States Offshore Maximum Number of Active Crews Engaged in

    Gasoline and Diesel Fuel Update (EIA)

    Two-Dimensional Seismic Surveying (Number of Elements) Two-Dimensional Seismic Surveying (Number of Elements) U.S.Lower 48 States Offshore Maximum Number of Active Crews Engaged in Two-Dimensional Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 7 7 6 7 6 7 7 7 7 8 2001 9 8 9 9 9 9 8 7 6 9 7 8 2002 8 9 10 9 9 9 8 8 10 10 8 7 2003 8 8 7 7 8 8 7 7 7 5 4 5 2004 5 5 5 5 5 4 4 4 4 2 1 3 2005 5 5 6 6 7 7 6 6 6 6 6 6 2006 6 6 6 5 5 7 4 3 2 2 3 3

  15. U.S.Lower 48 States Onshore Maximum Number of Active Crews Engaged in

    Gasoline and Diesel Fuel Update (EIA)

    Four-Dimensional Seismic Surveying (Number of Elements) Four-Dimensional Seismic Surveying (Number of Elements) U.S.Lower 48 States Onshore Maximum Number of Active Crews Engaged in Four-Dimensional Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 1 1 1 1 1 1 1 1 1 1 2001 1 1 1 1 1 1 1 1 1 1 1 1 2002 0 0 0 0 0 0 0 0 0 0 0 0 2003 1 0 0 0 0 0 0 0 0 0 0 0 2004 0 0 0 0 0 0 0 0 0 0 0 0 2005 0 0 0 0 0 0 0 0 0 0 0 0 2006 0 0 0 0 0 0 0 0 0 0 0 0

  16. U.S.Lower 48 States Onshore Maximum Number of Active Crews Engaged in

    Gasoline and Diesel Fuel Update (EIA)

    Three-Dimensional Seismic Surveying (Number of Elements) Three-Dimensional Seismic Surveying (Number of Elements) U.S.Lower 48 States Onshore Maximum Number of Active Crews Engaged in Three-Dimensional Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 36 36 34 37 39 40 39 41 40 41 2001 38 38 38 39 37 35 35 32 30 33 34 33 2002 32 31 26 25 24 23 26 26 28 30 27 22 2003 19 20 20 20 17 18 21 22 22 24 24 25 2004 25 27 27 27 26 30 30 31 32 34 33 32

  17. U.S.Lower 48 States Onshore Maximum Number of Active Crews Engaged in

    Gasoline and Diesel Fuel Update (EIA)

    Two-Dimensional Seismic Surveying (Number of Elements) Two-Dimensional Seismic Surveying (Number of Elements) U.S.Lower 48 States Onshore Maximum Number of Active Crews Engaged in Two-Dimensional Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 4 4 3 5 4 4 3 4 4 5 2001 5 6 6 7 7 6 6 8 8 5 7 7 2002 6 9 9 7 8 9 8 7 9 8 8 8 2003 8 9 8 7 7 7 7 8 8 7 7 7 2004 8 8 8 9 9 9 8 8 8 8 9 9 2005 8 8 6 8 8 9 8 8 7 6 5 6 2006 5 5 4 4 4 9 5 4 4 5 5 5 2007

  18. A new maximum-likelihood change estimator for two-pass SAR coherent change detection

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

    Wahl, Daniel E.; Yocky, David A.; Jakowatz, Jr., Charles V.; Simonson, Katherine Mary

    2016-01-11

    In past research, two-pass repeat-geometry synthetic aperture radar (SAR) coherent change detection (CCD) predominantly utilized the sample degree of coherence as a measure of the temporal change occurring between two complex-valued image collects. Previous coherence-based CCD approaches tend to show temporal change when there is none in areas of the image that have a low clutter-to-noise power ratio. Instead of employing the sample coherence magnitude as a change metric, in this paper, we derive a new maximum-likelihood (ML) temporal change estimate—the complex reflectance change detection (CRCD) metric to be used for SAR coherent temporal change detection. The new CRCD estimatormore » is a surprisingly simple expression, easy to implement, and optimal in the ML sense. As a result, this new estimate produces improved results in the coherent pair collects that we have tested.« less

  19. Federal Employee Group Life Insurance (FEGLI) | Department of Energy

    Energy Savers [EERE]

    Group Life Insurance (FEGLI) Federal Employee Group Life Insurance (FEGLI) The Federal Employees' Group Life Insurance (FEGLI) Program is a group term life insurance program for Federal and Postal employees and retirees. The Office of Personnel Management administers the Program and sets the premiums. OPM has a contract with the Metropolitan Life Insurance Company (MetLife) to provide this life insurance. The MetLife has an office called Office of Federal Employees' Group Life Insurance

  20. Weakest solar wind of the space age and the current 'MINI' solar maximum

    SciTech Connect (OSTI)

    McComas, D. J.; Angold, N.; Elliott, H. A.; Livadiotis, G.; Schwadron, N. A.; Smith, C. W.; Skoug, R. M.

    2013-12-10

    The last solar minimum, which extended into 2009, was especially deep and prolonged. Since then, sunspot activity has gone through a very small peak while the heliospheric current sheet achieved large tilt angles similar to prior solar maxima. The solar wind fluid properties and interplanetary magnetic field (IMF) have declined through the prolonged solar minimum and continued to be low through the current mini solar maximum. Compared to values typically observed from the mid-1970s through the mid-1990s, the following proton parameters are lower on average from 2009 through day 79 of 2013: solar wind speed and beta (?11%), temperature (?40%), thermal pressure (?55%), mass flux (?34%), momentum flux or dynamic pressure (?41%), energy flux (?48%), IMF magnitude (?31%), and radial component of the IMF (?38%). These results have important implications for the solar wind's interaction with planetary magnetospheres and the heliosphere's interaction with the local interstellar medium, with the proton dynamic pressure remaining near the lowest values observed in the space age: ?1.4 nPa, compared to ?2.4 nPa typically observed from the mid-1970s through the mid-1990s. The combination of lower magnetic flux emergence from the Sun (carried out in the solar wind as the IMF) and associated low power in the solar wind points to the causal relationship between them. Our results indicate that the low solar wind output is driven by an internal trend in the Sun that is longer than the ?11 yr solar cycle, and they suggest that this current weak solar maximum is driven by the same trend.

  1. Thirty-Year Solid Waste Generation Maximum and Minimum Forecast for SRS

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01

    This report is the third phase (Phase III) of the Thirty-Year Solid Waste Generation Forecast for Facilities at the Savannah River Site (SRS). Phase I of the forecast, Thirty-Year Solid Waste Generation Forecast for Facilities at SRS, forecasts the yearly quantities of low-level waste (LLW), hazardous waste, mixed waste, and transuranic (TRU) wastes generated over the next 30 years by operations, decontamination and decommissioning and environmental restoration (ER) activities at the Savannah River Site. The Phase II report, Thirty-Year Solid Waste Generation Forecast by Treatability Group (U), provides a 30-year forecast by waste treatability group for operations, decontamination and decommissioning, and ER activities. In addition, a 30-year forecast by waste stream has been provided for operations in Appendix A of the Phase II report. The solid wastes stored or generated at SRS must be treated and disposed of in accordance with federal, state, and local laws and regulations. To evaluate, select, and justify the use of promising treatment technologies and to evaluate the potential impact to the environment, the generic waste categories described in the Phase I report were divided into smaller classifications with similar physical, chemical, and radiological characteristics. These smaller classifications, defined within the Phase II report as treatability groups, can then be used in the Waste Management Environmental Impact Statement process to evaluate treatment options. The waste generation forecasts in the Phase II report includes existing waste inventories. Existing waste inventories, which include waste streams from continuing operations and stored wastes from discontinued operations, were not included in the Phase I report. Maximum and minimum forecasts serve as upper and lower boundaries for waste generation. This report provides the maximum and minimum forecast by waste treatability group for operation, decontamination and decommissioning, and ER activities.

  2. Life Cycle Modeling of Propulsion Materials | Department of Energy

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

    More Documents & Publications Life Cycle Modeling of Propulsion Materials Technical Cost Modeling - Life Cycle Analysis Basis for Program Focus Technical Cost Modeling - Life Cycle ...

  3. End-of-life flows of multiple cycle consumer products

    SciTech Connect (OSTI)

    Tsiliyannis, C.A.

    2011-11-15

    Explicit expressions for the end-of-life flows (EOL) of single and multiple cycle products (MCPs) are presented, including deterministic and stochastic EOL exit. The expressions are given in terms of the physical parameters (maximum lifetime, T, annual cycling frequency, f, number of cycles, N, and early discard or usage loss). EOL flows are also obtained for hi-tech products, which are rapidly renewed and thus may not attain steady state (e.g. electronic products, passenger cars). A ten-step recursive procedure for obtaining the dynamic EOL flow evolution is proposed. Applications of the EOL expressions and the ten-step procedure are given for electric household appliances, industrial machinery, tyres, vehicles and buildings, both for deterministic and stochastic EOL exit, (normal, Weibull and uniform exit distributions). The effect of the physical parameters and the stochastic characteristics on the EOL flow is investigated in the examples: it is shown that the EOL flow profile is determined primarily by the early discard dynamics; it also depends strongly on longevity and cycling frequency: higher lifetime or early discard/loss imply lower dynamic and steady state EOL flows. The stochastic exit shapes the overall EOL dynamic profile: Under symmetric EOL exit distribution, as the variance of the distribution increases (uniform to normal to deterministic) the initial EOL flow rise becomes steeper but the steady state or maximum EOL flow level is lower. The steepest EOL flow profile, featuring the highest steady state or maximum level, as well, corresponds to skew, earlier shifted EOL exit (e.g. Weibull). Since the EOL flow of returned products consists the sink of the reuse/remanufacturing cycle (sink to recycle) the results may be used in closed loop product lifecycle management operations for scheduling and sizing reverse manufacturing and for planning recycle logistics. Decoupling and quantification of both the full age EOL and of the early discard flows is useful, the latter being the target of enacted legislation aiming at increasing reuse.

  4. Limited-life cartridge primers

    DOE Patents [OSTI]

    Makowiecki, Daniel M. (Livermore, CA); Rosen, Robert S. (San Ramon, CA)

    1998-01-01

    A cartridge primer which utilizes an explosive that can be designed to become inactive in a predetermined period of time: a limited-life primer. The explosive or combustible material of the primer is an inorganic reactive multilayer (RML). The reaction products of the RML are sub-micron grains of non-corrosive inorganic compounds that would have no harmful effects on firearms or cartridge cases. Unlike use of primers containing lead components, primers utilizing RML's would not present a hazard to the environment. The sensitivity of an RML is determined by the physical structure and the stored interfacial energy. The sensitivity lowers with time due to a decrease in interfacial energy resulting from interdiffusion of the elemental layers. Time-dependent interdiffusion is predictable, thereby enabling the functional lifetime of an RML primer to be predetermined by the initial thickness and materials selection of the reacting layers.

  5. Limited-life cartridge primers

    DOE Patents [OSTI]

    Makowiecki, Daniel M.; Rosen, Robert S.

    2005-04-19

    A cartridge primer which utilizes an explosive that can be designed to become inactive in a predetermined period of time: a limited-life primer. The explosive or combustible material of the primer is an inorganic reactive multilayer (RML). The reaction products of the RML are sub-micron grains of non-corrosive inorganic compounds that would have no harmful effects on firearms or cartridge cases. Unlike use of primers containing lead components, primers utilizing RML's would not present a hazard to the environment. The sensitivity of an RML is determined by the physical structure and the stored interfacial energy. The sensitivity lowers with time due to a decrease in interfacial energy resulting from interdiffusion of the elemental layers. Time-dependent interdiffusion is predictable, thereby enabling the functional lifetime of an RML primer to be predetermined by the initial thickness and materials selection of the reacting layers.

  6. Life sciences and environmental sciences

    SciTech Connect (OSTI)

    Not Available

    1992-02-01

    The DOE laboratories play a unique role in bringing multidisciplinary talents -- in biology, physics, chemistry, computer sciences, and engineering -- to bear on major problems in the life and environmental sciences. Specifically, the laboratories utilize these talents to fulfill OHER's mission of exploring and mitigating the health and environmental effects of energy use, and of developing health and medical applications of nuclear energy-related phenomena. At Lawrence Berkeley Laboratory (LBL) support of this mission is evident across the spectrum of OHER-sponsored research, especially in the broad areas of genomics, structural biology, basic cell and molecular biology, carcinogenesis, energy and environment, applications to biotechnology, and molecular, nuclear and radiation medicine. These research areas are briefly described.

  7. Life sciences and environmental sciences

    SciTech Connect (OSTI)

    Not Available

    1992-02-01

    The DOE laboratories play a unique role in bringing multidisciplinary talents -- in biology, physics, chemistry, computer sciences, and engineering -- to bear on major problems in the life and environmental sciences. Specifically, the laboratories utilize these talents to fulfill OHER`s mission of exploring and mitigating the health and environmental effects of energy use, and of developing health and medical applications of nuclear energy-related phenomena. At Lawrence Berkeley Laboratory (LBL) support of this mission is evident across the spectrum of OHER-sponsored research, especially in the broad areas of genomics, structural biology, basic cell and molecular biology, carcinogenesis, energy and environment, applications to biotechnology, and molecular, nuclear and radiation medicine. These research areas are briefly described.

  8. Limited-life cartridge primers

    DOE Patents [OSTI]

    Makowiecki, D.M.; Rosen, R.S.

    1998-06-30

    A cartridge primer is described which utilizes an explosive that can be designed to become inactive in a predetermined period of time: a limited-life primer. The explosive or combustible material of the primer is an inorganic reactive multilayer (RML). The reaction products of the RML are sub-micron grains of non-corrosive inorganic compounds that would have no harmful effects on firearms or cartridge cases. Unlike use of primers containing lead components, primers utilizing RML`s would not present a hazard to the environment. The sensitivity of an RML is determined by the physical structure and the stored interfacial energy. The sensitivity lowers with time due to a decrease in interfacial energy resulting from interdiffusion of the elemental layers. Time-dependent interdiffusion is predictable, thereby enabling the functional lifetime of an RML primer to be predetermined by the initial thickness and materials selection of the reacting layers. 10 figs.

  9. Confronting Regulatory Cost and Quality Expectations. An Exploration of Technical Change in Minimum Efficiency Performance Standards

    SciTech Connect (OSTI)

    Taylor, Margaret; Spurlock, C. Anna; Yang, Hung-Chia

    2015-09-21

    The dual purpose of this project was to contribute to basic knowledge about the interaction between regulation and innovation and to inform the cost and benefit expectations related to technical change which are embedded in the rulemaking process of an important area of national regulation. The area of regulation focused on here is minimum efficiency performance standards (MEPS) for appliances and other energy-using products. Relevant both to U.S. climate policy and energy policy for buildings, MEPS remove certain product models from the market that do not meet specified efficiency thresholds.

  10. Maximizing the life cycle of plastics. Final report

    SciTech Connect (OSTI)

    Hawkins, W. L.

    1980-02-01

    The Plastics Research Institute has conducted a coordinated research program designed to extend the useful life of plastics. Since feedstock for practically all synthetic plastics is derived from fossil fuel, every effort should be made to obtain the maximum useful life from these materials. Eventually, plastic scrap may be used as a fuel supplement, but this disposal route should be followed only after the scrap is no longer reusable in its polymeric form. The extent to which plastic scrap will be recovered and reused will be affected by the economic situation as well as the available supply of fossil fuel. The Institute's program was conducted at five major universities. Dedicated faculty members were assembled into a research team and met frequently with members of the Institute's Board of Trustees to review progress of the program. The research was conducted by graduate students in partial fulfillment of degree requirements. Summaries are presented of the following research projects: Improved Stabilization; Separation of Mixed Plastic Scrap; Compatibilizing Agents for Mixed Plastic Scrap; Controlled Degradation of Plastic Scrap; and Determination of Compatibility.

  11. Technology development: HEPA filter service life test plan

    SciTech Connect (OSTI)

    Kirchner, K.N.; Cummings, K.G.; Leck, W.C.; Fretthold, J.K.

    1995-05-31

    Rocky Flats Environmental Technology Site (the Site) has approximately 10,000 High Efficiency Particulate Air (HEPA) Filters installed in a variety of filter plenums. These ventilation/filtration plenum systems are used to control the release of airborne particulate contaminates to the environment during normal operations and also during potential design-based accidents. The operational integrity of the HEPA filter plenums is essential to maintaining the margins of safety as required by building specific Final Safety Analysis Reports (FSARS) for protection of the public and environment. An Unreviewed Safety Question Determination (USQD), USDQ-RFP94.0615-ARS, was conducted in 1994 addressing the potential inadequacy of the safety envelope for Protected Area building HEPA plenums. While conducting this USQD, questions were raised concerning the maximum service life criteria for HEPA filters. Accident scenarios in existing FSARs identify conditions that could potentially cause plugging or damage of down stream HEPA filters as a result of impaction from failed filters. Additionally, available data indicates that HEPA filters experience structural degradation due to the effects of age. The Unresolved Safety Question (USQ) compensatory measures thus require testing and analysis of used HEPA filters in order to determine and implement service life criteria.

  12. Comparison of Battery Life Across Real-World Automotive Drive-Cycles (Presentation)

    SciTech Connect (OSTI)

    Smith, K.; Earleywine, M.; Wood, E.; Pesaran, A.

    2011-11-01

    Laboratories run around-the-clock aging tests to try to understand as quickly as possible how long new Li-ion battery designs will last under certain duty cycles. These tests may include factors such as duty cycles, climate, battery power profiles, and battery stress statistics. Such tests are generally accelerated and do not consider possible dwell time at high temperatures and states-of-charge. Battery life-predictive models provide guidance as to how long Li-ion batteries may last under real-world electric-drive vehicle applications. Worst-case aging scenarios are extracted from hundreds of real-world duty cycles developed from vehicle travel surveys. Vehicles examined included PHEV10 and PHEV40 EDVs under fixed (28 degrees C), limited cooling (forced ambient temperature), and aggressive cooling (20 degrees C chilled liquid) scenarios using either nightly charging or opportunity charging. The results show that battery life expectancy is 7.8 - 13.2 years for the PHEV10 using a nightly charge in Phoenix, AZ (hot climate), and that the 'aggressive' cooling scenario can extend battery life by 1-3 years, while the 'limited' cooling scenario shortens battery life by 1-2 years. Frequent (opportunity) charging can reduce battery life by 1 year for the PHEV10, while frequent charging can extend battery life by one-half year.

  13. Texas - RRC District 10 Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 10 Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 7,744 7,406 6,784 1980's 6,435 6,229 6,210 5,919 5,461 5,469 5,276 4,962 4,830 4,767 1990's 4,490 4,589 4,409 4,040 4,246 4,436 4,391 4,094 4,273 4,424 2000's 4,079 3,955 3,838 4,064 4,873 4,910 5,387 6,281 6,922 6,882 2010's 7,663 7,513 7,253

  14. Texas - RRC District 6 Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 6 Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3,214 3,240 3,258 1980's 4,230 4,177 4,326 4,857 4,703 4,822 4,854 4,682 4,961 5,614 1990's 5,753 5,233 5,317 5,508 5,381 5,726 5,899 5,887 5,949 5,857 2000's 5,976 6,128 6,256 6,685 7,638 8,976 9,087 11,257 12,184 12,795 2010's 14,886 15,480 11,340

  15. Texas - RRC District 7C Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 7C Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 2,831 2,821 2,842 1980's 2,378 2,503 2,659 2,568 2,866 2,914 2,721 2,708 2,781 3,180 1990's 3,514 3,291 3,239 3,215 3,316 3,107 3,655 3,407 3,113 3,178 2000's 3,504 3,320 3,702 4,327 4,668 5,123 5,126 5,341 4,946 4,827 2010's 4,787 4,475 4,890

  16. Texas - RRC District 8 Dry Natural Gas Expected Future Production (Billion

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

    Cubic Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) Texas - RRC District 8 Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 11,728 11,093 10,077 1980's 9,144 8,546 8,196 8,156 7,343 7,330 7,333 6,999 7,058 6,753 1990's 6,614 6,133 5,924 5,516 5,442 5,441 5,452 5,397 4,857 5,434 2000's 5,388 5,255 5,361 5,142 5,301 5,993 6,070 6,560 6,824 6,672 2010's 7,206 7,039 7,738

  17. New Mexico - East Dry Natural Gas Expected Future Production (Billion Cubic

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

    Feet) Dry Natural Gas Expected Future Production (Billion Cubic Feet) New Mexico - East Dry Natural Gas Expected Future Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3,848 3,889 4,031 1980's 3,530 3,598 3,432 3,230 3,197 3,034 2,694 2,881 2,945 3,075 1990's 3,256 3,206 3,130 3,034 3,021 2,867 2,790 2,642 2,693 3,037 2000's 3,537 3,518 3,632 3,301 3,621 3,791 3,914 3,994 4,031 4,141 2010's 4,226 4,379 4,386 4,633 5,799 - =

  18. ESTIMATE OF SOLAR MAXIMUM USING THE 1-8 GEOSTATIONARY OPERATIONAL ENVIRONMENTAL SATELLITES X-RAY MEASUREMENTS

    SciTech Connect (OSTI)

    Winter, L. M.; Balasubramaniam, K. S.

    2014-10-01

    We present an alternate method of determining the progression of the solar cycle through an analysis of the solar X-ray background. Our results are based on the NOAA Geostationary Operational Environmental Satellites (GOES) X-ray data in the 1-8 band from 1986 to the present, covering solar cycles 22, 23, and 24. The X-ray background level tracks the progression of the solar cycle through its maximum and minimum. Using the X-ray data, we can therefore make estimates of the solar cycle progression and the date of solar maximum. Based upon our analysis, we conclude that the Sun reached its hemisphere-averaged maximum in solar cycle 24 in late 2013. This is within six months of the NOAA prediction of a maximum in spring 2013.

  19. Extended maximum likelihood halo-independent analysis of dark matter direct detection data

    SciTech Connect (OSTI)

    Gelmini, Graciela B.; Georgescu, Andreea; Gondolo, Paolo; Huh, Ji-Haeng

    2015-11-24

    We extend and correct a recently proposed maximum-likelihood halo-independent method to analyze unbinned direct dark matter detection data. Instead of the recoil energy as independent variable we use the minimum speed a dark matter particle must have to impart a given recoil energy to a nucleus. This has the advantage of allowing us to apply the method to any type of target composition and interaction, e.g. with general momentum and velocity dependence, and with elastic or inelastic scattering. We prove the method and provide a rigorous statistical interpretation of the results. As first applications, we find that for dark matter particles with elastic spin-independent interactions and neutron to proton coupling ratio f{sub n}/f{sub p}=−0.7, the WIMP interpretation of the signal observed by CDMS-II-Si is compatible with the constraints imposed by all other experiments with null results. We also find a similar compatibility for exothermic inelastic spin-independent interactions with f{sub n}/f{sub p}=−0.8.

  20. Robust Maximum Lifetime Routing and Energy Allocation in Wireless Sensor Networks

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

    Paschalidis, Ioannis Ch.; Wu, Ruomin

    2012-01-01

    We consider the maximum lifetime routing problem in wireless sensor networks in two settings: (a) when nodes’ initial energy is given and (b) when it is subject to optimization. The optimal solution and objective value provide optimal flows and the corresponding predicted lifetime, respectively. We stipulate that there is uncertainty in various network parameters (available energy and energy depletion rates). In setting (a) we show that for specific, yet typical, network topologies, the actual network lifetime will reach the predicted value with a probability that converges to zero as the number of nodes grows large. In setting (b) the samemore » result holds for all topologies. We develop a series of robust problem formulations, ranging from pessimistic to optimistic. A set of parameters enable the tuning of the conservatism of the formulation to obtain network flows with a desirably high probability that the corresponding lifetime prediction is achieved. We establish a number of properties for the robust network flows and energy allocations and provide numerical results to highlight the tradeoff between predicted lifetime and the probability achieved. Further, we analyze an interesting limiting regime of massively deployed sensor networks and essentially solve a continuous version of the problem.« less

  1. Fire and Life Safety Information - Hanford Site

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

    Fire Department Fire and Life Safety Information Hanford Fire Department Hanford Fire Department Home About Hanford Fire Department Fire and Life Safety Information Hot Links to Cool Spots Contact Hanford Fire Department Fire and Life Safety Information Email Email Page | Print Print Page |Text Increase Font Size Decrease Font Size Fire Extinguishers Fire Extinguisher PDF, 182 Kb Fire Extinguishers - Fast Facts (PDF) PDF, 182 Kb Fire Extinguishers - U.S Fire Administration Website PDF, 182 Kb

  2. Life Cycle Inventory Database | Department of Energy

    Energy Savers [EERE]

    Past Projects » Life Cycle Inventory Database Life Cycle Inventory Database The U.S. Life Cycle Inventory (LCI) Database serves as a central repository for information about the total energy and resource impacts of developing and using various commercial building materials, components, and assemblies. The database helps manufacturers, building designers, and developers select energy-efficient and environmentally friendly materials, products, and processes for their projects based on the

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

    SciTech Connect (OSTI)

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

    2011-12-15

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

  4. Patent: Long life lithium batteries with stabilized electrodes | DOEpatents

    Office of Scientific and Technical Information (OSTI)

    Long life lithium batteries with stabilized electrodes Citation Details Title: Long life lithium batteries with stabilized electrodes

  5. Extend the Operating Life of Your Motor

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

    In such cases, motor life can be extended by purchasing special motors, such as those conforming to the Institute of Electrical and Electronics Engineers (IEEE) 841 specifcations, ...

  6. Life Extension Programs | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    Life Extension Programs Life Extension Programs NNSA, Air Force Complete Successful B61-12 Life Extension Program Development Flight Test at Tonopah Test Range WASHINGTON - The National Nuclear Security Administration (NNSA) and United States Air Force completed the third development flight test of a non-nuclear B61-12 nuclear gravity bomb at Tonopah Test Sandia California works on nuclear weapon W80-4 Life Extension Program The W80-4 mechanical team at Sandia National Laboratories reviews the

  7. Life Extension Programs | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    The term "life extension program (LEP)" means a program to repairreplace components of nuclear weapons to ensure the ability to meet military requirements. By extending the ...

  8. Development and Performance of Detectors for the Cryogenic Dark Matter Search Experiment with an Increased Sensitivity Based on a Maximum Likelihood Analysis of Beta Contamination

    SciTech Connect (OSTI)

    Driscoll, Donald D.; /Case Western Reserve U.

    2004-01-01

    The Cryogenic Dark Matter Search (CDMS) uses cryogenically-cooled detectors made of germanium and silicon in an attempt to detect dark matter in the form of Weakly-Interacting Massive Particles (WIMPs). The expected interaction rate of these particles is on the order of 1/kg/day, far below the 200/kg/day expected rate of background interactions after passive shielding and an active cosmic ray muon veto. Our detectors are instrumented to make a simultaneous measurement of both the ionization energy and thermal energy deposited by the interaction of a particle with the crystal substrate. A comparison of these two quantities allows for the rejection of a background of electromagnetically-interacting particles at a level of better than 99.9%. The dominant remaining background at a depth of {approx} 11 m below the surface comes from fast neutrons produced by cosmic ray muons interacting in the rock surrounding the experiment. Contamination of our detectors by a beta emitter can add an unknown source of unrejected background. In the energy range of interest for a WIMP study, electrons will have a short penetration depth and preferentially interact near the surface. Some of the ionization signal can be lost to the charge contacts there and a decreased ionization signal relative to the thermal signal will cause a background event which interacts at the surface to be misidentified as a signal event. We can use information about the shape of the thermal signal pulse to discriminate against these surface events. Using a subset of our calibration set which contains a large fraction of electron events, we can characterize the expected behavior of surface events and construct a cut to remove them from our candidate signal events. This thesis describes the development of the 6 detectors (4 x 250 g Ge and 2 x 100 g Si) used in the 2001-2002 CDMS data run at the Stanford Underground Facility with a total of 119 livedays of data. The preliminary results presented are based on the first use of a beta-eliminating cut based on a maximum-likelihood characterization described above.

  9. Microbial Gas Generation Under Expected Waste Isolation Pilot Plant Repository Conditions: Final Report

    SciTech Connect (OSTI)

    Gillow, J.B.; Francis, A.

    2011-07-01

    Gas generation from the microbial degradation of the organic constituents of transuranic (TRU) waste under conditions expected in the Waste Isolation Pilot Plant (WIPP) was investigated. The biodegradation of mixed cellulosic materials and electron-beam irradiated plastic and rubber materials (polyethylene, polyvinylchloride, hypalon, leaded hypalon, and neoprene) was examined. We evaluated the effects of environmental variables such as initial atmosphere (air or nitrogen), water content (humid ({approx}70% relative humidity, RH) and brine inundated), and nutrient amendments (nitogen phosphate, yeast extract, and excess nitrate) on microbial gas generation. Total gas production was determined by pressure measurement and carbon dioxide (CO{sub 2}) and methane (CH{sub 4}) were analyzed by gas chromatography; cellulose degradation products in solution were analyzed by high-performance liquid chromatography. Microbial populations in the samples were determined by direct microscopy and molecular analysis. The results of this work are summarized.

  10. Expected Power-Utility Maximization Under Incomplete Information and with Cox-Process Observations

    SciTech Connect (OSTI)

    Fujimoto, Kazufumi; Nagai, Hideo; Runggaldier, Wolfgang J.

    2013-02-15

    We consider the problem of maximization of expected terminal power utility (risk sensitive criterion). The underlying market model is a regime-switching diffusion model where the regime is determined by an unobservable factor process forming a finite state Markov process. The main novelty is due to the fact that prices are observed and the portfolio is rebalanced only at random times corresponding to a Cox process where the intensity is driven by the unobserved Markovian factor process as well. This leads to a more realistic modeling for many practical situations, like in markets with liquidity restrictions; on the other hand it considerably complicates the problem to the point that traditional methodologies cannot be directly applied. The approach presented here is specific to the power-utility. For log-utilities a different approach is presented in Fujimoto et al. (Preprint, 2012).

  11. Setting the Renormalization Scale in QCD: The Principle of Maximum Conformality

    SciTech Connect (OSTI)

    Brodsky, Stanley J.; Di Giustino, Leonardo; /SLAC

    2011-08-19

    A key problem in making precise perturbative QCD predictions is the uncertainty in determining the renormalization scale {mu} of the running coupling {alpha}{sub s}({mu}{sup 2}): The purpose of the running coupling in any gauge theory is to sum all terms involving the {beta} function; in fact, when the renormalization scale is set properly, all non-conformal {beta} {ne} 0 terms in a perturbative expansion arising from renormalization are summed into the running coupling. The remaining terms in the perturbative series are then identical to that of a conformal theory; i.e., the corresponding theory with {beta} = 0. The resulting scale-fixed predictions using the 'principle of maximum conformality' (PMC) are independent of the choice of renormalization scheme - a key requirement of renormalization group invariance. The results avoid renormalon resummation and agree with QED scale-setting in the Abelian limit. The PMC is also the theoretical principle underlying the BLM procedure, commensurate scale relations between observables, and the scale-setting method used in lattice gauge theory. The number of active flavors nf in the QCD {beta} function is also correctly determined. We discuss several methods for determining the PMC/BLM scale for QCD processes. We show that a single global PMC scale, valid at leading order, can be derived from basic properties of the perturbative QCD cross section. The elimination of the renormalization scheme ambiguity using the PMC will not only increase the precision of QCD tests, but it will also increase the sensitivity of collider experiments to new physics beyond the Standard Model.

  12. Design and life-cycle considerations for unconventional-reservoir wells

    SciTech Connect (OSTI)

    Miskimins, J.L.

    2009-05-15

    This paper provides an overview of design and life-cycle considerations for certain unconventional-reservoir wells. An overview of unconventional-reservoir definitions is provided. Well design and life-cycle considerations are addressed from three aspects: upfront reservoir development, initial well completion, and well-life and long-term considerations. Upfront-reservoir-development issues discussed include well spacing, well orientation, reservoir stress orientations, and tubular metallurgy. Initial-well-completion issues include maximum treatment pressures and rates, treatment diversion, treatment staging, flowback and cleanup, and dewatering needs. Well-life and long-term discussions include liquid loading, corrosion, refracturing and associated fracture reorientation, and the cost of abandonment. These design considerations are evaluated with case studies for five unconventional-reservoir types: shale gas (Barnett shale), tight gas (Jonah feld), tight oil (Bakken play), coalbed methane (CBM) (San Juan basin), and tight heavy oil (Lost Hills field). In evaluating the life cycle and design of unconventional-reservoir wells, 'one size' does not fit all and valuable knowledge and a shortening of the learning curve can be achieved for new developments by studying similar, more-mature fields.

  13. Draft Final Phase II Report: Review of Life Cycle and Technology Applications of the Office of Environmental Managements Tank

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

    A1-1 APPENDIX 1 Charge Summary Issue Suggested Activities Expected Output/ Work Product Notes Charge 1 Modeling for Life-Cycle Analysis This task entails reviewing the modeling approaches for determining tank waste remediation life-cycle costs at both SRS and Hanford. This includes evaluating assumptions in system plans for completing tank waste missions at Hanford and SRS, as well as the rigor of the models for identifying activities and costs through the end of each site's program.

  14. HEV America End of Life Test Sequence

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

    END OF LIFE TEST SEQUENCE Revision 0 September 1, 2006 Prepared by Electric Transportation Applications Prepared by: _______________________________ Date: __________ Roberta Brayer Approved by: _________ _________________________________ Date: _______________ _____ Donald B. Karner ©2005 Electric Transportation Applications All Rights Reserved HEV America End of Life Test Sequence Page 1 HEV PERFORMANCE TEST PROCEDURE SEQUENCE The following test sequence shall be used for conduct of HEV America

  15. U.S. average gasoline and diesel fuel prices expected to be slightly lower in 2013 than in 2012

    Gasoline and Diesel Fuel Update (EIA)

    average gasoline and diesel fuel prices expected to be slightly lower in 2013 than in 2012 Despite the recent run-up in gasoline prices, the U.S. Energy Information Administration expects falling crude oil prices will lead to a small decline in average motor fuel costs this year compared with last year. The price for regular gasoline is expected to average $3.55 a gallon in 2013 and $3.39 next year, according to EIA's new Short-Term Energy Outlook. That's down from $3.63 a gallon in 2012. For

  16. Evaluation of a photovoltaic energy mechatronics system with a built-in quadratic maximum power point tracking algorithm

    SciTech Connect (OSTI)

    Chao, R.M.; Ko, S.H.; Lin, I.H.; Pai, F.S.; Chang, C.C.

    2009-12-15

    The historically high cost of crude oil price is stimulating research into solar (green) energy as an alternative energy source. In general, applications with large solar energy output require a maximum power point tracking (MPPT) algorithm to optimize the power generated by the photovoltaic effect. This work aims to provide a stand-alone solution for solar energy applications by integrating a DC/DC buck converter to a newly developed quadratic MPPT algorithm along with its appropriate software and hardware. The quadratic MPPT method utilizes three previously used duty cycles with their corresponding power outputs. It approaches the maximum value by using a second order polynomial formula, which converges faster than the existing MPPT algorithm. The hardware implementation takes advantage of the real-time controller system from National Instruments, USA. Experimental results have shown that the proposed solar mechatronics system can correctly and effectively track the maximum power point without any difficulties. (author)

  17. Controlling RPV embrittlement through wet annealing in support of life attainment and life extension decisions

    SciTech Connect (OSTI)

    Krasikov, E. A.

    2012-07-01

    As a main barrier against radioactivity outlet reactor pressure vessel (RPV) is a key component in terms of Nuclear Power Plant (NPP) safety. Therefore present-day demands in RPV reliability enhance have to be met by all possible actions for RPV in-service embrittlement mitigation. Annealing treatment is known to be the effective measure to restore the RPV metal properties deteriorated by neutron irradiation. Low temperature 'wet' annealing at a maximum coolant temperature which can be obtained using the reactor core or primary circuit pumps, although it cannot be expected to produce complete recovery, is more attractive from the practical point of view especially in cases when the removal of the internals is impossible. As a rule there is no recovery effect up to annealing and irradiation temperature difference of 70 deg. C. It is known, however, that along with radiation embrittlement neutron irradiation may mitigate the radiation damage in metals. Therefore we have tried to test the possibility to use the effect of radiation-induced ductilization in 'wet' annealing technology by means of nuclear heat utilization as heat and neutron irradiation sources at once. In support of the above-mentioned conception the 3-year duration reactor experiment on 15Cr3NiMoV type steel with preliminary irradiation at operating Pressurized Water Reactor (PWR) at 270 deg. C and following extra irradiation (87 h at 330 deg. C) at IR-8 test reactor was fulfilled. In fact, embrittlement was partly suppressed up to value equivalent to 1,5 fold neutron fluence decrease. The degree of recovery in case of radiation enhanced annealing is equal to 27% whereas furnace annealing results in zero effect under existing conditions. Mechanism of the radiation-induced damage mitigation is proposed. It is hoped that 'wet' annealing technology will help provide a better management of the RPV degradation as a factor affecting the lifetime of nuclear power plants which, together with associated management methods, will help facilitate safe and economic long-term operation of PWRs. (authors)

  18. Application of the Principle of Maximum Conformality to Top-Pair Production

    SciTech Connect (OSTI)

    Brodsky, Stanley J.; Wu, Xing-Gang; /SLAC /Chongqing U.

    2013-05-13

    A major contribution to the uncertainty of finite-order perturbative QCD predictions is the perceived ambiguity in setting the renormalization scale {mu}{sub r}. For example, by using the conventional way of setting {mu}{sub r} {element_of} [m{sub t}/2, 2m{sub t}], one obtains the total t{bar t} production cross-section {sigma}{sub t{bar t}} with the uncertainty {Delta}{sigma}{sub t{bar t}}/{sigma}{sub t{bar t}} {approx} (+3%/-4%) at the Tevatron and LHC even for the present NNLO level. The Principle of Maximum Conformality (PMC) eliminates the renormalization scale ambiguity in precision tests of Abelian QED and non-Abelian QCD theories. By using the PMC, all nonconformal {l_brace}{beta}{sub i}{r_brace}-terms in the perturbative expansion series are summed into the running coupling constant, and the resulting scale-fixed predictions are independent of the renormalization scheme. The correct scale-displacement between the arguments of different renormalization schemes is automatically set, and the number of active flavors n{sub f} in the {l_brace}{beta}{sub i}{r_brace}-function is correctly determined. The PMC is consistent with the renormalization group property that a physical result is independent of the renormalization scheme and the choice of the initial renormalization scale {mu}{sub r}{sup init}. The PMC scale {mu}{sub r}{sup PMC} is unambiguous at finite order. Any residual dependence on {mu}{sub r}{sup init} for a finite-order calculation will be highly suppressed since the unknown higher-order {l_brace}{beta}{sub i}{r_brace}-terms will be absorbed into the PMC scales higher-order perturbative terms. We find that such renormalization group invariance can be satisfied to high accuracy for {sigma}{sub t{bar t}} at the NNLO level. In this paper we apply PMC scale-setting to predict the t{bar t} cross-section {sigma}{sub t{bar t}} at the Tevatron and LHC colliders. It is found that {sigma}{sub t{bar t}} remains almost unchanged by varying {mu}{sub r}{sup init} within the region of [m{sub t}/4, 4m{sub t}]. The convergence of the expansion series is greatly improved. For the (q{bar q})-channel, which is dominant at the Tevatron, its NLO PMC scale is much smaller than the top-quark mass in the small x-region, and thus its NLO cross-section is increased by about a factor of two. In the case of the (gg)-channel, which is dominant at the LHC, its NLO PMC scale slightly increases with the subprocess collision energy {radical}s, but it is still smaller than m{sub t} for {radical} {approx}< 1 TeV, and the resulting NLO cross-section is increased by {approx}20%. As a result, a larger {sigma}{sub t{bar t}} is obtained in comparison to the conventional scale-setting method, which agrees well with the present Tevatron and LHC data. More explicitly, by setting m{sub t} = 172.9 {+-} 1.1 GeV, we predict {sigma}{sub Tevatron, 1.96 TeV} = 7.626{sub -0.257}{sup +0.265} pb, {sigma}{sub LHC, 7 TeV} = 171.8{sub -5.6}{sup +5.8} pb and {sigma}{sub LHC, 14 TeV} = 941.3{sub -26.5}{sup +28.4} pb.

  19. Work and Life Balance | GE Global Research

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

    Balancing Work with Life Click to email this to a friend (Opens in new window) Share on Facebook (Opens in new window) Click to share (Opens in new window) Click to share on LinkedIn (Opens in new window) Click to share on Tumblr (Opens in new window) Flex Ability: Balancing Work with Life Achieving work/life balance is a much-talked-about topic. According to GE Healthcare's Kelly Piacsek, "GE hires people for what's inside their head-what they know-and the specific hours you spend at work

  20. ,"California--Coastal Region Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Coastal Region Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--Coastal Region Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release

  1. ,"California--Los Angeles Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Los Angeles Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--Los Angeles Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release

  2. ,"California--San Joaquin Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    San Joaquin Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--San Joaquin Basin Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release

  3. Local Solar: What Do Leading Solar Communities Have in Common? It May Not be the Characteristics You Expect

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

    8 Planning December 2015 Local SO What do leading solar communities have in common? It may not be what you expect. By Megan Day, aicp American Planning Association 29 OLAR The recently completed six-acre one- megawatt cooperative solar farm next to Walton Energy Membership Corporation headquarters in Walton County, Georgia, consists of 4,280 solar panels and is expected to produce approximately two million kilowatt-hours of solar electricity per year. COURTESY WALTON ELECTRIC MEMBERSHIP

  4. Expected environments in high-level nuclear waste and spent fuel repositories in salt

    SciTech Connect (OSTI)

    Claiborne, H.C.; Rickertsen, L.D., Graham, R.F.

    1980-08-01

    The purpose of this report is to describe the expected environments associated with high-level waste (HLW) and spent fuel (SF) repositories in salt formations. These environments include the thermal, fluid, pressure, brine chemistry, and radiation fields predicted for the repository conceptual designs. In this study, it is assumed that the repository will be a room and pillar mine in a rock-salt formation, with the disposal horizon located approx. 2000 ft (610 m) below the surface of the earth. Canistered waste packages containing HLW in a solid matrix or SF elements are emplaced in vertical holes in the floor of the rooms. The emplacement holes are backfilled with crushed salt or other material and sealed at some later time. Sensitivity studies are presented to show the effect of changing the areal heat load, the canister heat load, the barrier material and thickness, ventilation of the storage room, and adding a second row to the emplacement configuration. The calculated thermal environment is used as input for brine migration calculations. The vapor and gas pressure will gradually attain the lithostatic pressure in a sealed repository. In the unlikely event that an emplacement hole will become sealed in relatively early years, the vapor space pressure was calculated for three scenarios (i.e., no hole closure - no backfill, no hole closure - backfill, and hole closure - no backfill). It was assumed that the gas in the system consisted of air and water vapor in equilibrium with brine. A computer code (REPRESS) was developed assuming that these changes occur slowly (equilibrium conditions). The brine chemical environment is outlined in terms of brine chemistry, corrosion, and compositions. The nuclear radiation environment emphasized in this report is the stored energy that can be released as a result of radiation damage or crystal dislocations within crystal lattices.

  5. Updating the LED Life Cycle Assessment

    Energy Savers [EERE]

    Part 2: LED Manufacturing and Performance 7 Goal of the New Study Review new literature on the life- cycle assessment of LED products. Determine if newer A-19 products...

  6. Work & Life at Niskayuna | GE Global Research

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

    Work & Life at Niskayuna Living in New York's Tech Valley provides easy access to arts, culture and the great outdoors. Click to email this to a friend (Opens in new window)...

  7. Life at Argonne | Argonne National Laboratory

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

    Apply for a Job Connect with Argonne LinkedIn Facebook Twitter YouTube Google+ More Social Media Life at Argonne What's it like to work at Argonne? You've come to a place...

  8. Techno-Economics & Life Cycle Assessment (Presentation)

    SciTech Connect (OSTI)

    Dutta, A.; Davis, R.

    2011-12-01

    This presentation provides an overview of the techno-economic analysis (TEA) and life cycle assessment (LCA) capabilities at the National Renewable Energy Laboratory (NREL) and describes the value of working with NREL on TEA and LCA.

  9. Life-Cycle Analysis of Geothermal Technologies

    Broader source: Energy.gov [DOE]

    The results and tools from this project will help GTP and stakeholders determine and communicate GT energy and GHG benefits and water impacts. The life-cycle analysis (LCA) approach is taken to address these effects.

  10. Work-Life Balance | Argonne National Laboratory

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

    to my work, and when I go home, I'm able to have a life outside work. I used to play soccer, so I'm looking to join a women's soccer team in the Chicago suburbs." - Emily...

  11. Life Extension Programs | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    Alvin Leung and Matt H. B61-12 Life Extension Program Undergoes First Full-Scale Wind Tunnel Test WASHINGTON, D.C. - The National Nuclear Security Administration (NNSA)...

  12. Prospective Life Cycle and Technology Analysis

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

    Prospective Life Cycle and Technology Analysis Advanced Manufacturing Office Peer Review May 28, 2015 Diane J. Graziano E. Masanet R. Huang M.E. Riddle This presentation does not contain any proprietary, confidential, or otherwise restricted information. DOE-AMO Analysis Summary - ANL/NU * Quantifying, from a life-cycle perspective, the enabling effects of advanced manufacturing in achieving AMO's mission for energy savings across the economy * Assessing net energy, emissions, and economic

  13. NREL: Energy Analysis: Life Cycle Assessment Harmonization

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

    Life Cycle Assessment Harmonization Life cycle assessment (LCA) harmonization helps lenders, utility executives, and lawmakers get the best, most precise information on greenhouse gas emissions from various sources of energy. LCA has been used to estimate and compare GHG emissions from utility-scale power systems for three decades, often with considerable variability in results. Harmonization provides more exact estimates of greenhouse-gas emissions for renewable and conventional electricity

  14. Parameter Study of the LIFE Engine Nuclear Design

    SciTech Connect (OSTI)

    Kramer, K J; Meier, W R; Latkowski, J F; Abbott, R P

    2009-07-10

    LLNL is developing the nuclear fusion based Laser Inertial Fusion Energy (LIFE) power plant concept. The baseline design uses a depleted uranium (DU) fission fuel blanket with a flowing molten salt coolant (flibe) that also breeds the tritium needed to sustain the fusion energy source. Indirect drive targets, similar to those that will be demonstrated on the National Ignition Facility (NIF), are ignited at {approx}13 Hz providing a 500 MW fusion source. The DU is in the form of a uranium oxycarbide kernel in modified TRISO-like fuel particles distributed in a carbon matrix forming 2-cm-diameter pebbles. The thermal power is held at 2000 MW by continuously varying the 6Li enrichment in the coolants. There are many options to be considered in the engine design including target yield, U-to-C ratio in the fuel, fission blanket thickness, etc. Here we report results of design variations and compare them in terms of various figures of merit such as time to reach a desired burnup, full-power years of operation, time and maximum burnup at power ramp down and the overall balance of plant utilization.

  15. How the Weatherization Assistance Program Changed Jasmine's Life...

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

    How the Weatherization Assistance Program Changed Jasmine's Life How the Weatherization Assistance Program Changed Jasmine's Life February 19, 2015 - 4:45pm Addthis The Rocky...

  16. Life Cycle Assessment of Renewable Hydrogen Production viaWind...

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

    Renewable Hydrogen Production via WindElectrolysis: Milestone Completion Report Life Cycle ... Analysis Activities at National Renewable Energy Laboratory Life Cycle Assessment of ...

  17. Technical Cost Modeling - Life Cycle Analysis Basis for Program...

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

    Technical Cost Modeling - Life Cycle Analysis Basis for Program Focus Technical Cost Modeling - Life Cycle Analysis Basis for Program Focus Polymer Composites Research in the LM ...

  18. Life-Cycle Assessment of Energy and Environmental Impacts of...

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

    Life-Cycle Assessment of Energy and Environmental Impacts of LED Lighting Products Life-Cycle Assessment of Energy and Environmental Impacts of LED Lighting Products PDF icon ...

  19. Page 5, Federal Employees' Group Life Insurance (FEGLI)

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

    5 of 11 Previous Page Federal Employees' Group Life Insurance (FEGLI) Initial Enrollment Period All Employees in eligible positions are automatically enrolled in Basic Life...

  20. Bioproduct Life Cycle Analysis with the GREET Model | Department...

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

    Bioeconomy Bioproduct Life Cycle Analysis with the GREETTM Model Jennifer B. Dunn, Biofuel Life Cycle Analysis Team Lead, Argonne National Laboratory PDF icon ...

  1. LEP: Extending stockpile life | Y-12 National Security Complex

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

    The Life Extension Program allows safe, effective weapons to remain in the stockpile well beyond their original service life. Nuclear weapons are intricate and, in a sense, ...

  2. Nuclear Weapons Life Cycle | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    Apply for Our Jobs Our Jobs Working at NNSA Blog Home Our Mission Maintaining the Stockpile Nuclear Weapons Life Cycle Nuclear Weapons Life Cycle Nuclear weapons are ...

  3. Recommendations for Maximizing Battery Life in Photovoltaic Systems...

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

    for Maximizing Battery Life in Photovoltaic Systems: A Review of Lessons Learned Recommendations for Maximizing Battery Life in Photovoltaic Systems: A Review of Lessons ...

  4. Closing the Lithium-ion Battery Life Cycle: Poster handout |...

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

    Closing the Lithium-ion Battery Life Cycle: Poster handout Title Closing the Lithium-ion Battery Life Cycle: Poster handout Publication Type Miscellaneous Year of Publication 2014...

  5. Impact of the 3Cs of Batteries on PHEV Value Proposition: Cost, Calendar Life, and Cycle Life (Presentation)

    SciTech Connect (OSTI)

    Pesaran, A.; Smith, K.; Markel, T.

    2009-06-01

    Battery cost, calendar life, and cycle life are three important challenges for those commercializing plug-in hybrid electric vehicles; battery life is sensitive to temperature and solar loading.

  6. LIFE Materails: Molten-Salt Fuels Volume 8

    SciTech Connect (OSTI)

    Moir, R; Brown, N; Caro, A; Farmer, J; Halsey, W; Kaufman, L; Kramer, K; Latkowski, J; Powers, J; Shaw, H; Turchi, P

    2008-12-11

    The goals of the Laser Inertial Fusion Fission Energy (LIFE) is to use fusion neutrons to fission materials with no enrichment and minimum processing and have greatly reduced wastes that are not of interest to making weapons. Fusion yields expected to be achieved in NIF a few times per day are called for with a high reliable shot rate of about 15 per second. We have found that the version of LIFE using TRISO fuel discussed in other volumes of this series can be modified by replacing the molten-flibe-cooled TRISO fuel zone with a molten salt in which the same actinides present in the TRISO particles are dissolved in the molten salt. Molten salts have the advantage that they are not subject to radiation damage, and hence overcome the radiation damage effects that may limit the lifetime of solid fuels such as TRISO-containing pebbles. This molten salt is pumped through the LIFE blanket, out to a heat exchanger and back into the blanket. To mitigate corrosion, steel structures in contact with the molten salt would be plated with tungsten or nickel. The salt will be processed during operation to remove certain fission products (volatile and noble and semi-noble fission products), impurities and corrosion products. In this way neutron absorbers (fission products) are removed and neutronics performance of the molten salt is somewhat better than that of the TRISO fuel case owing to the reduced parasitic absorption. In addition, the production of Pu and rare-earth elements (REE) causes these elements to build up in the salt, and leads to a requirement for a process to remove the REE during operation to insure that the solubility of a mixed (Pu,REE)F3 solid solution is not exceeded anywhere in the molten salt system. Removal of the REE will further enhance the neutronics performance. With molten salt fuels, the plant would need to be safeguarded because materials of interest for weapons are produced and could potentially be removed.

  7. Determining Remaining Useful Life of Aging Cables in Nuclear Power Plants Interim Study FY13

    SciTech Connect (OSTI)

    Simmons, Kevin L.; Fifield, Leonard S.; Westman, Matthew P.; Ramuhalli, Pradeep; Pardini, Allan F.; Tedeschi, Jonathan R.; Jones, Anthony M.

    2013-09-27

    The most important criterion for cable performance is its ability to withstand a design-basis accident. With nearly 1000 km of power, control, instrumentation, and other cables typically found in an NPP, it would be a significant undertaking to inspect all of the cables. Degradation of the cable jacket, electrical insulation, and other cable components is a key issue that is likely to affect the ability of the currently installed cables to operate safely and reliably for another 20 to 40 years beyond the initial operating life. The development of one or more nondestructive evaluation (NDE) techniques and supporting models that could assist in determining the remaining life expectancy of cables or their current degradation state would be of significant interest. The ability to nondestructively determine material and electrical properties of cable jackets and insulation without disturbing the cables or connections has been deemed essential. Currently, the only technique accepted by industry to measure cable elasticity (the gold standard for determining cable insulation degradation) is the indentation measurement. All other NDE techniques are used to find flaws in the cable and do not provide information to determine the current health or life expectancy. There is no single NDE technique that can satisfy all of the requirements needed for making a life-expectancy determination, but a wide range of methods have been evaluated for use in NPPs as part of a continuous evaluation program. The commonly used methods are indentation and visual inspection, but these are only suitable for easily accessible cables. Several NDE methodologies using electrical techniques are in use today for flaw detection but there are none that can predict the life of a cable. There are, however, several physical and chemical ptoperty changes in cable insulation as a result of thermal and radiation damage. In principle, these properties may be targets for advanced NDE methods to provide early warning of aging and degradation. Examples of such key indicators include changes in chemical structure, mechanical modulus, and dielectric permittivity. While some of these indicators are the basis of currently used technologies, there is a need to increase the volume of cable that may be inspected with a single measurement, and if possible, to develop techniques for in-situ inspection (i.e., while the cable is in operation). This is the focus of the present report.

  8. Room at the Mountain: Estimated Maximum Amounts of Commercial Spent Nuclear Fuel Capable of Disposal in a Yucca Mountain Repository

    SciTech Connect (OSTI)

    Kessler, John H. [Electric Power Research Institute - EPRI, 3420 Hillview Avenue, Palo Alto, California 94304 (United States); Kemeny, John [University of Arizona, Tucson AZ 85721 (United States); King, Fraser [Integrity Corrosion Consulting, Ltd., 6732 Silverview Drive NW, Calgary, Alberta (Canada); Ross, Alan M. [Alan M. Ross and Associates, 1061 Gray Fox Circle Pleasanton, CA 94566 (Canada); Ross, Benjamen [Disposal Safety, Inc., Bethesda, MD 20814 (United States)

    2006-07-01

    The purpose of this paper is to present an initial analysis of the maximum amount of commercial spent nuclear fuel (CSNF) that could be emplaced into a geological repository at Yucca Mountain. This analysis identifies and uses programmatic, material, and geological constraints and factors that affect this estimation of maximum amount of CSNF for disposal. The conclusion of this initial analysis is that the current legislative limit on Yucca Mountain disposal capacity, 63,000 MTHM of CSNF, is a small fraction of the available physical capacity of the Yucca Mountain system assuming the current high-temperature operating mode (HTOM) design. EPRI is confident that at least four times the legislative limit for CSNF ({approx}260,000 MTHM) can be emplaced in the Yucca Mountain system. It is possible that with additional site characterization, upwards of nine times the legislative limit ({approx}570,000 MTHM) could be emplaced. (authors)

  9. Measurement of the Depth of Maximum of Extensive Air Showers above 10^18 eV

    SciTech Connect (OSTI)

    Abraham, J.; Abreu, P.; Aglietta, M.; Ahn, E.J.; Allard, D.; Allekotte, I.; Allen, J.; Alvarez-Muniz, J.; Ambrosio, M.; Anchordoqui, L.; Andringa, S.; /Lisbon, IST /Boskovic Inst., Zagreb

    2010-02-01

    We describe the measurement of the depth of maximum, X{sub max}, of the longitudinal development of air showers induced by cosmic rays. Almost 4000 events above 10{sup 18} eV observed by the fluorescence detector of the Pierre Auger Observatory in coincidence with at least one surface detector station are selected for the analysis. The average shower maximum was found to evolve with energy at a rate of (106{sub -21}{sup +35}) g/cm{sup 2}/decade below 10{sup 18.24 {+-} 0.05}eV, and (24 {+-} 3) g/cm{sup 2}/decade above this energy. The measured shower-to-shower fluctuations decrease from about 55 to 26 g/cm{sup 2}. The interpretation of these results in terms of the cosmic ray mass composition is briefly discussed.

  10. U.S. crude oil production expected to top 8 million barrels per day, highest output since 1988

    Gasoline and Diesel Fuel Update (EIA)

    U.S. crude oil production expected to top 8 million barrels per day, highest output since 1988 U.S. crude oil production in 2014 is now expected to top 8 million barrels per day for the first time in over a quarter century. The U.S. Energy Information Administration boosted its forecast for daily crude oil production this year by 120,000 barrels to 7.4 million barrels per day. For 2014, EIA's forecast for daily production was revised upward by 310,000 barrels to nearly 8.2 million barrels per

  11. U.S. gasoline price expected to average less than $2 a gallon both this year and next

    Gasoline and Diesel Fuel Update (EIA)

    U.S. gasoline price expected to average less than $2 a gallon both this year and next U.S. drivers are now expected to see back-to-back years of annual average gasoline prices below $2 per gallon for the first time in more than a decade. In its latest monthly forecast, the U.S. Energy Information Administration said low oil prices will keep the average annual price for a gallon of regular-grade gasoline at $1.89 this year and at $1.97 in 2017. The last time gasoline averaged less than $2 for two

  12. U.S. net oil and petroleum product imports expected to fall to just 29 percent of demand in 2014

    Gasoline and Diesel Fuel Update (EIA)

    net oil and petroleum product imports expected to fall to just 29 percent of demand in 2014 With rising domestic crude oil production, the United States will rely less on imports of crude oil and petroleum products to meet domestic demand next year. In its new monthly forecast, the U.S. Energy Information Administration expects total net imports to average 5.4 million barrels per day in 2014. That's down 2 million barrels per day from last year. As a result, the share of U.S. consumption met by

  13. ,"New Mexico--East Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico--East Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  14. ,"New Mexico--West Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico--West Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  15. ,"Texas (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  16. ,"Texas - RRC District 1 Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 1 Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  17. ,"Texas - RRC District 10 Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 10 Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  18. ,"Texas - RRC District 2 Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 2 Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  19. ,"Texas - RRC District 3 Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 3 Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  20. ,"Texas - RRC District 4 Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 4 Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  1. ,"Texas - RRC District 5 Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 5 Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  2. ,"Texas - RRC District 6 Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 6 Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  3. ,"Texas - RRC District 7B Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 7B Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  4. ,"Texas - RRC District 7C Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 7C Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  5. ,"Texas - RRC District 8 Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 8 Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  6. ,"Texas - RRC District 8A Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 8A Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  7. ,"Texas - RRC District 9 Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas - RRC District 9 Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  8. ,"Texas--RRC District 1 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 1 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  9. ,"Texas--RRC District 10 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 10 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  10. ,"Texas--RRC District 2 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 2 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  11. ,"Texas--RRC District 3 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 3 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  12. ,"Texas--RRC District 4 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 4 Onshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  13. ,"Texas--RRC District 5 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 5 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  14. ,"Texas--RRC District 6 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 6 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  15. ,"Texas--RRC District 7B Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 7B Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  16. ,"Texas--RRC District 7C Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 7C Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  17. ,"Texas--RRC District 8 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 8 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  18. ,"Texas--RRC District 8A Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 8A Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  19. ,"Texas--RRC District 9 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--RRC District 9 Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  20. ,"U.S. Federal Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Federal Offshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  1. ,"Alabama (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  2. ,"Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  3. ,"California (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  4. ,"California - Coastal Region Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California - Coastal Region Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  5. ,"California - Los Angeles Basin Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California - Los Angeles Basin Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  6. ,"California - San Joaquin Basin Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California - San Joaquin Basin Onshore Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  7. ,"Federal Offshore--California Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--California Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  8. ,"Federal Offshore--Louisiana and Alabama Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Louisiana and Alabama Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  9. ,"Federal Offshore--Texas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Texas Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  10. ,"Gulf of Mexico Federal Offshore - Texas Dry Natural Gas Expected Future Production (Billion Cubic Feet)"

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

    Dry Natural Gas Expected Future Production (Billion Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Gulf of Mexico Federal Offshore - Texas Dry Natural Gas Expected Future Production (Billion Cubic Feet)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  11. ,"Louisiana (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  12. ,"Lower 48 Federal Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Lower 48 Federal Offshore Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  13. ,"Mississippi (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)"

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

    Plant Liquids, Expected Future Production (Million Barrels)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi (with State Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels)",1,"Annual",2014 ,"Release Date:","11/19/2015" ,"Next Release

  14. Quality of Work Life brochure | Argonne National Laboratory

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

    Quality of Work Life brochure PDF icon 2013_08_29 hr_worklifepolicies brochure

  15. Developing High Capacity, Long Life Anodes | Department of Energy

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

    Life Anodes Developing High Capacity, Long Life Anodes 2011 DOE Hydrogen and Fuel Cells Program, and Vehicle Technologies Program Annual Merit Review and Peer Evaluation PDF icon es020_amine_2011_p.pdf More Documents & Publications Developing A New High Capacity Anode With Long Cycle Life Developing High Capacity, Long Life Anodes Development of High Capacity Anode for Li-ion Batteries

  16. Battery Technology Life Verification Testing and Analysis

    SciTech Connect (OSTI)

    Jon P. Christophersen; Gary L. Hunt; Ira Bloom; Ed Thomas; Vince Battaglia

    2007-12-01

    A critical component to the successful commercialization of batteries for automotive applications is accurate life prediction. The Technology Life Verification Test (TLVT) Manual was developed to project battery life with a high level of statistical confidence within only one or two years of accelerated aging. The validation effort that is presently underway has led to several improvements to the original methodology. For example, a newly developed reference performance test revealed a voltage path dependence effect on resistance for lithium-ion cells. The resistance growth seems to depend on how a target condition is reached (i.e., by a charge or a discharge). Second, the methodology for assessing the level of measurement uncertainty was improved using a propagation of errors in the fundamental measurements to the derived response (e.g., resistance). This new approach provides a more realistic assessment of measurement uncertainty. Third, the methodology for allocating batteries to the test matrix has been improved. The new methodology was developed to assign batteries to the matrix such that the average of each test group would be representative of the overall population. These changes to the TLVT methodology will help to more accurately predict a battery technologys life capability with a high degree of confidence.

  17. Workplace Charging Success: MetLife | Department of Energy

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

    MetLife Workplace Charging Success: MetLife October 2, 2014 - 6:26pm Addthis Workplace Charging Success: MetLife MetLife is talking the "green" talk and walking the walk. The insurance company has long encouraged its policyholders to live environmentally-conscious lifestyles, and continues to embrace emerging technologies, work with green products, and utilize environmentally-friendly services. As part of their commitment to environmental sustainability, MetLife provides alternative

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

    SciTech Connect (OSTI)

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

    2014-06-01

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

  19. Application of asymptotic expansions for maximum likelihood estimators errors to gravitational waves from binary mergers: The single interferometer case

    SciTech Connect (OSTI)

    Zanolin, M.; Vitale, S.; Makris, N.

    2010-06-15

    In this paper we apply to gravitational waves (GW) from the inspiral phase of binary systems a recently derived frequentist methodology to calculate analytically the error for a maximum likelihood estimate of physical parameters. We use expansions of the covariance and the bias of a maximum likelihood estimate in terms of inverse powers of the signal-to-noise ration (SNR)s where the square root of the first order in the covariance expansion is the Cramer Rao lower bound (CRLB). We evaluate the expansions, for the first time, for GW signals in noises of GW interferometers. The examples are limited to a single, optimally oriented, interferometer. We also compare the error estimates using the first two orders of the expansions with existing numerical Monte Carlo simulations. The first two orders of the covariance allow us to get error predictions closer to what is observed in numerical simulations than the CRLB. The methodology also predicts a necessary SNR to approximate the error with the CRLB and provides new insight on the relationship between waveform properties, SNR, dimension of the parameter space and estimation errors. For example the timing match filtering can achieve the CRLB only if the SNR is larger than the Kurtosis of the gravitational wave spectrum and the necessary SNR is much larger if other physical parameters are also unknown.

  20. Better Buildings Residential Network Workforce Peer Exchange Call Series: Quality Control, Standardization of Upgrades, and Workforce Expectations, March 27, 2014

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

    Workforce Peer Exchange Call Series: Quality Control, Standardization of Upgrades, and Workforce Expectations March 27, 2014 Agenda 2  Call Logistics and Introductions  BBRN and Peer Exchange Call Overview  Featured Speakers - QA/QC Approaches & Lessons Learned  Dan Wildenhaus -Technical and QC Lead for Seattle's Community Power Works Program and Senior Building Scientist at CLEAResult  Brian Atchinson - Associate Project Manager, Quality, Standards and Compliance, New York

  1. Impact of Fast Charging on Life of EV Batteries; NREL (National Renewable Energy Laboratory)

    SciTech Connect (OSTI)

    Neubauer, Jeremy; Wood, Eric; Burton, Evan; Smith, Kandler; Pesaran, Ahmad

    2015-05-03

    Installation of fast charging infrastructure is considered by many as one of potential solutions to increase the utility and range of electric vehicles (EVs). This is expected to reduce the range anxiety of drivers of EVs and thus increase their market penetration. Level 1 and 2 charging in homes and workplaces is expected to contribute to the majority of miles driven by EVs. However, a small percentage of urban driving and most of inter-city driving could be only achieved by a fast-charging network. DC fast charging at 50 kW, 100 kW, 120 kW compared to level 1 (3.3 kW) and level 2 (6.6 kW) results in high-current charging that can adversely impact the life of the battery. In the last couple of years, we have investigated the impact of higher current rates in batteries and potential of higher temperatures and thus lower service life. Using mathematical models, we investigated the temperature increase of batteries due to higher heat generation during fast charge and have found that this could lead to higher temperatures. We compared our models with data from other national laboratories both for fine-tuning and calibration. We found that the incremental temperature rise of batteries during 1C to 3C fast charging may reduce the practical life of the batteries by less than 10% over 10 to 15 years of vehicle ownership. We also found that thermal management of batteries is needed for fast charging to prevent high temperature excursions leading to unsafe conditions.

  2. Life Redefined: Microbes Built with Arsenic

    SciTech Connect (OSTI)

    Webb, Sam

    2011-03-22

    Life can survive in many harsh environments, from extreme heat to the presence of deadly chemicals. However, life as we know it has always been based on the same six elements -- carbon, oxygen, nitrogen, hydrogen, sulfur and phosphorus. Now it appears that even this rule has an exception. In the saline and poisonous environment of Mono Lake, researchers have found a bacterium that can grow by incorporating arsenic into its structure in place of phosphorus. X-ray images taken at SLAC's synchrotron light source reveal that this microbe may even use arsenic as a building block for DNA. Please join us as we describe this discovery, which rewrites the textbook description of how living cells work.

  3. Sandia National Laboratories: Careers: Life at Sandia

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

    Life at Sandia Karla Software Developer and Mechanical Engineer "There is always something new and exciting to learn. Sandia gives me the opportunity to collaborate with the best scientists and engineers in bioscience, climate, microsystems, and combustion." Karla - Software Developer and Mechanical Engineer Kelsey Aerospace Engineer "Sandia provides amazing educational opportunities and career path flexibility. All of my teammates are motivated and passionate about our work. I

  4. GREET Life-Cycle Analysis of Biofuels

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

    BETO Project Peer Review GREET Life-Cycle Analysis of Biofuels March 24, 2015 Analysis and Sustainability Michael Wang, Jennifer B. Dunn Argonne National Laboratory Key acronyms list AD Anaerobic digestion FR Forest residue AEO Annual Energy Outlook FTD Fischer Tropsch Diesel AEZ Agricultural Ecological Zone FN Fuel gas/natural gas AGE Air emissions, greenhouse gas emissions, energy consumption FY Fiscal year ALU Algal lipid upgrading GHG Greenhouse gas AHTL Algal hydrothermal liquefaction GREET

  5. Emissions Modeling: GREET Life Cycle Analysis

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

    Emissions Modeling: GREET Life Cycle Analysis Michael Wang, Amgad Elgowainy, Jeongwoo Han Argonne National Laboratory The 2014 DOE Vehicle Technologies Office Annual Merit Review and Peer Evaluation Meeting Washington, DC June 18, 2014 This presentation does not contain any proprietary, confidential, or otherwise restricted information Project ID: van002 Project Overview  Start: Oct. 1993  End: not applicable (ongoing annual allocation  % complete: 70% (for FY14)  Indicators and

  6. Extend the Operating Life of Your Motor

    Broader source: Energy.gov [DOE]

    Certain components of motors degrade with time and operating stress. Electrical insulation weakens over time with exposure to voltage unbalance, over and undervoltage, voltage disturbances, and temperature. Contact between moving surfaces causes wear. Wear is affected by dirt, moisture, and corrosive fumes and is greatly accelerated when lubricant is misapplied, becomes overheated or contaminated, or is not replaced at regular intervals. When any components are degraded beyond the point of economical repair or replacement, the motor’s economic life ends.

  7. Life state response to environmental crisis: the case of the Love Canal, Niagara Falls, New York

    SciTech Connect (OSTI)

    Masters, S.K.

    1986-01-01

    This thesis explored the differences between two life stages - young and old - in perceiving and responding to man-made environmental disaster, as well as the support resources utilized to cope with disaster - personal, familial/friendship, and organizational. Because of the characteristics of man-made environmental disaster, and because of the different conditions of life and constructions of reality of older and younger families, it was expected that definitions of the situation would vary by life stage and locus of control - authoritative and personal. The research took place in the Love Canal neighborhood of Niagara Falls, New York. Fifty-eight families were interviewed in the fall of 1978, and thirty-nine of these families were reinterviewed in the spring of 1979. Interviews were tape recorded, transcribed, and coded. The data were presented in contingency tables and interview excerpts. The interview schedules elicited information of perception of impact, responses to impact, and the utilization of support resources. In an authoritative locus of control situation, the major findings were that both older and younger families perceived impact, that older families were slightly less disrupted, that younger families relied on organizational and familial/friendship support resources, and that older families relied on familial/friendship support resources.

  8. Application of Distribution Transformer Thermal Life Models to Electrified Vehicle Charging Loads Using Monte-Carlo Method: Preprint

    SciTech Connect (OSTI)

    Kuss, M.; Markel, T.; Kramer, W.

    2011-01-01

    Concentrated purchasing patterns of plug-in vehicles may result in localized distribution transformer overload scenarios. Prolonged periods of transformer overloading causes service life decrements, and in worst-case scenarios, results in tripped thermal relays and residential service outages. This analysis will review distribution transformer load models developed in the IEC 60076 standard, and apply the model to a neighborhood with plug-in hybrids. Residential distribution transformers are sized such that night-time cooling provides thermal recovery from heavy load conditions during the daytime utility peak. It is expected that PHEVs will primarily be charged at night in a residential setting. If not managed properly, some distribution transformers could become overloaded, leading to a reduction in transformer life expectancy, thus increasing costs to utilities and consumers. A Monte-Carlo scheme simulated each day of the year, evaluating 100 load scenarios as it swept through the following variables: number of vehicle per transformer, transformer size, and charging rate. A general method for determining expected transformer aging rate will be developed, based on the energy needs of plug-in vehicles loading a residential transformer.

  9. Basement Fill Model Evaluation of Maximum Radionuclide Concentrations for Initial Suite of Radionuclides. Zion Station Restoration Project

    SciTech Connect (OSTI)

    Sullivan, Terry

    2014-12-10

    ZionSolutions is in the process of decommissioning the Zion Nuclear Power Plant in order to establish a new water treatment plant. There is some residual radioactive particles from the plant which need to be brought down to levels so an individual who receives water from the new treatment plant does not receive a radioactive dose in excess of 25 mrem/y? as specified in 10 CFR 20 Subpart E. The objectives of this report are: (a) To present a simplified conceptual model for release from the buildings with residual subsurface structures that can be used to provide an upper bound on radionuclide concentrations in the fill material and the water in the interstitial spaces of the fill. (b) Provide maximum water concentrations and the corresponding amount of mass sorbed to the solid fill material that could occur in each building for use by ZSRP in selecting ROCs for detailed dose assessment calculations.

  10. Potential Impact of Adopting Maximum Technologies as Minimum Efficiency Performance Standards in the U.S. Residential Sector

    SciTech Connect (OSTI)

    Letschert, Virginie; Desroches, Louis-Benoit; McNeil, Michael; Saheb, Yamina

    2010-05-03

    The US Department of Energy (US DOE) has placed lighting and appliance standards at a very high priority of the U.S. energy policy. However, the maximum energy savings and CO2 emissions reduction achievable via minimum efficiency performance standards (MEPS) has not yet been fully characterized. The Bottom Up Energy Analysis System (BUENAS), first developed in 2007, is a global, generic, and modular tool designed to provide policy makers with estimates of potential impacts resulting from MEPS for a variety of products, at the international and/or regional level. Using the BUENAS framework, we estimated potential national energy savings and CO2 emissions mitigation in the US residential sector that would result from the most aggressive policy foreseeable: standards effective in 2014 set at the current maximum technology (Max Tech) available on the market. This represents the most likely characterization of what can be maximally achieved through MEPS in the US. The authors rely on the latest Technical Support Documents and Analytical Tools published by the U.S. Department of Energy as a source to determine appliance stock turnover and projected efficiency scenarios of what would occur in the absence of policy. In our analysis, national impacts are determined for the following end uses: lighting, television, refrigerator-freezers, central air conditioning, room air conditioning, residential furnaces, and water heating. The analyzed end uses cover approximately 65percent of site energy consumption in the residential sector (50percent of the electricity consumption and 80percent of the natural gas and LPG consumption). This paper uses this BUENAS methodology to calculate that energy savings from Max Tech for the U.S. residential sector products covered in this paper will reach an 18percent reduction in electricity demand compared to the base case and 11percent in Natural Gas and LPG consumption by 2030 The methodology results in reductions in CO2 emissions of a similar magnitude.

  11. Life-Cycle Assessment of Energy and Environmental Impacts of...

    Energy Savers [EERE]

    Life-Cycle Assessment of Energy and Environmental Impacts of LED Lighting Products Part I: Review of the Life-Cycle Energy Consumption of Incandescent, Compact Fluorescent, and LED ...

  12. Life-Cycle Assessment of Energy and Environmental Impacts of...

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

    Life-Cycle Assessment of Energy and Environmental Impacts of LED Lighting Products Life-Cycle Assessment of Energy and Environmental Impacts of LED Lighting Products This March 28, ...

  13. Life-Cycle Assessment of Energy and Environmental Impacts of...

    Office of Scientific and Technical Information (OSTI)

    Life-Cycle Assessment of Energy and Environmental Impacts of LED Lighting Products Part 2: LED Manufacturing and Performance Citation Details In-Document Search Title: Life-Cycle ...

  14. Bioproduct Life Cycle Analysis with the GREET Model

    Broader source: Energy.gov [DOE]

    Breakout Session 2B—Integration of Supply Chains II: Bioproducts—Enabling Biofuels and Growing the Bioeconomy Bioproduct Life Cycle Analysis with the GREET Model Jennifer B. Dunn, Biofuel Life Cycle Analysis Team Lead, Argonne National Laboratory

  15. GREET Bioenergy Life Cycle Analysis and Key Issues for Woody...

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

    GREET Bioenergy Life Cycle Analysis and Key Issues for Woody Feedstocks GREET Bioenergy Life Cycle Analysis and Key Issues for Woody Feedstocks Breakout Session 2D-Building Market ...

  16. U.S. Life Cycle Inventory Database Roadmap (Brochure)

    SciTech Connect (OSTI)

    Deru, M.

    2009-08-01

    Life cycle inventory data are the primary inputs for conducting life cycle assessment studies. Studies based on high-quality data that are consistent, accurate, and relevant allow for robust, defensible, and meaningful results.

  17. U.S. Life Cycle Inventory Database Roadmap

    SciTech Connect (OSTI)

    none,

    2009-08-01

    Life cycle inventory data are the primary inputs for conducting life cycle assessment studies. Studies based on high-quality data that are consistent, accurate, and relevant allow for robust, defensible, and meaningful results.

  18. Day4 Energy Certus Life Cycle JV | Open Energy Information

    Open Energy Info (EERE)

    Day4 Energy Certus Life Cycle JV Jump to: navigation, search Name: Day4 Energy & Certus Life Cycle JV Place: Italy Product: JV company will develop photovoltaic power projects in...

  19. Seismic Design Expectations Report

    Office of Environmental Management (EM)

    ldg. 3019 60% rned from this r ule. ) Post Ope design review review have be eration w as part een Standard Review Plan, 2 nd Edition, March 2010 i FOREWORD The Standard Review...

  20. Planetary formation theory developed, tested: predicts timeline for life

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

    Planetary formation theory developed, tested: predicts timeline for life After the Big Bang: Theory suggests first planets formed after first generations of stars The researchers' calculations predict properties of first planet and timeline for life. May 3, 2012 image description The researchers state that the formation of Earth-like planets is not itself a sufficient prerequisite for life. Early galaxies contained strong sources of life-threatening radiation, such as supernovae and black holes.

  1. 90 Seconds of Discovery: Biofuel Catalyst Life and Plugs

    SciTech Connect (OSTI)

    Zacher, Alan; Olarte, Mariefel

    2014-06-11

    Scientist at PNNL are working to extend the life of the catalysts used in the production of biomass fuels.

  2. 90 Seconds of Discovery: Biofuel Catalyst Life and Plugs

    ScienceCinema (OSTI)

    Zacher, Alan; Olarte, Mariefel

    2014-06-12

    Scientist at PNNL are working to extend the life of the catalysts used in the production of biomass fuels.

  3. Life Cycle Greenhouse Gas Emissions from Solar Photovoltaics (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2012-11-01

    The National Renewable Energy Laboratory (NREL) recently led the Life Cycle Assessment (LCA) Harmonization Project, a study that helps to clarify inconsistent and conflicting life cycle GHG emission estimates in the published literature and provide more precise estimates of life cycle GHG emissions from PV systems.

  4. Long life lithium batteries with stabilized electrodes

    DOE Patents [OSTI]

    Amine, Khalil (Downers Grove, IL); Liu, Jun (Naperville, IL); Vissers, Donald R. (Naperville, IL); Lu, Wenquan (Darien, IL)

    2009-03-24

    The present invention relates to non-aqueous electrolytes having electrode stabilizing additives, stabilized electrodes, and electrochemical devices containing the same. Thus the present invention provides electrolytes containing an alkali metal salt, a polar aprotic solvent, and an electrode stabilizing additive. In some embodiments the additives include a substituted or unsubstituted cyclic or spirocyclic hydrocarbon containing at least one oxygen atom and at least one alkenyl or alkynyl group. When used in electrochemical devices with, e.g., lithium manganese oxide spinel electrodes or olivine or carbon-coated olivine electrodes, the new electrolytes provide batteries with improved calendar and cycle life.

  5. Curiosity rover zaps Mars for life signs

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

    Curiosity rover zaps Mars for life signs Mars rover depends on three LANL technologies Curiosity zaps Mars for vital signs: Designed by Lab team, ChemCam looks for crucial elements such as carbon, nitrogen and oxygen. July 30, 2012 Curiosity rover zapping rocks on Mars Power up! The third part of the "LANL Visits Mars" trio is an essential component of the heat-producing Multi-Mission Radioisotope Thermoelectric Generator unit. It powers the rover and keeps the instruments from

  6. Metal fueled long life fast reactor cores with inherent safety features

    SciTech Connect (OSTI)

    Yokoyama, Tsugio; Ninokata, Hisashi; Endo, Hiroshi

    2007-07-01

    A large fast reactor core concept is proposed that has inherent safety characteristics against both the Unprotected Loss of Flow (ULOF) event and the Unprotected Transient of Over-Power (UTOP) event, where commonly used zirconium alloy metal fuel (U-Pu- Zr) is adopted to achieve a long life cycle length up to 5 years. The burn-up reactivity of the core which is equivalent to the maximum insertion reactivity in the UTOP due to the control rod run-out event at the rated power, is reduced to less than 1 $ by introducing minor actinides to the fuel, while the sodium void reactivity is suppressed to be negative by applying a step core concept, where the inner core height is lower than the outer core height, and by deleting the upper axial blanket. (authors)

  7. Deviations from tribimaximal mixing due to the vacuum expectation value misalignment in A{sub 4} models

    SciTech Connect (OSTI)

    Barry, James; Rodejohann, Werner

    2010-05-01

    The addition of an A{sub 4} family symmetry and extended Higgs sector to the standard model can generate the tribimaximal mixing pattern for leptons, assuming the correct vacuum expectation value alignment of the Higgs scalars. Deviating this alignment affects the predictions for the neutrino oscillation and neutrino mass observables. An attempt is made to classify the plethora of models in the literature, with respect to the chosen A{sub 4} particle assignments. Of these models, two particularly popular examples have been analyzed for deviations from tribimaximal mixing by perturbing the vacuum expectation value alignments. The effect of perturbations on the mixing angle observables is studied. However, it is only investigation of the mass-related observables (the effective mass for neutrinoless double beta decay and the sum of masses from cosmology) that can lead to the exclusion of particular models by constraints from future data, which indicates the importance of neutrino mass in disentangling models. The models have also been tested for fine-tuning of the parameters. Furthermore, a well-known seesaw model is generalized to include additional scalars, which transform as representations of A{sub 4} not included in the original model.

  8. Load controller and method to enhance effective capacity of a photovotaic power supply using a dynamically determined expected peak loading

    DOE Patents [OSTI]

    Perez, Richard (Delmar, NY)

    2003-04-01

    A load controller and method are provided for maximizing effective capacity of a non-controllable, renewable power supply coupled to a variable electrical load also coupled to a conventional power grid. Effective capacity is enhanced by monitoring power output of the renewable supply and loading, and comparing the loading against the power output and a load adjustment threshold determined from an expected peak loading. A value for a load adjustment parameter is calculated by subtracting the renewable supply output and the load adjustment parameter from the current load. This value is then employed to control the variable load in an amount proportional to the value of the load control parameter when the parameter is within a predefined range. By so controlling the load, the effective capacity of the non-controllable, renewable power supply is increased without any attempt at operational feedback control of the renewable supply. The expected peak loading of the variable load can be dynamically determined within a defined time interval with reference to variations in the variable load.

  9. Validation of a 4D-PET Maximum Intensity Projection for Delineation of an Internal Target Volume

    SciTech Connect (OSTI)

    Callahan, Jason; Kron, Tomas; Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne ; Schneider-Kolsky, Michal; Dunn, Leon; Thompson, Mick; Siva, Shankar; Aarons, Yolanda; Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne ; Binns, David; Hicks, Rodney J.; Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne

    2013-07-15

    Purpose: The delineation of internal target volumes (ITVs) in radiation therapy of lung tumors is currently performed by use of either free-breathing (FB) {sup 18}F-fluorodeoxyglucose-positron emission tomography-computed tomography (FDG-PET/CT) or 4-dimensional (4D)-CT maximum intensity projection (MIP). In this report we validate the use of 4D-PET-MIP for the delineation of target volumes in both a phantom and in patients. Methods and Materials: A phantom with 3 hollow spheres was prepared surrounded by air then water. The spheres and water background were filled with a mixture of {sup 18}F and radiographic contrast medium. A 4D-PET/CT scan was performed of the phantom while moving in 4 different breathing patterns using a programmable motion device. Nine patients with an FDG-avid lung tumor who underwent FB and 4D-PET/CT and >5 mm of tumor motion were included for analysis. The 3 spheres and patient lesions were contoured by 2 contouring methods (40% of maximum and PET edge) on the FB-PET, FB-CT, 4D-PET, 4D-PET-MIP, and 4D-CT-MIP. The concordance between the different contoured volumes was calculated using a Dice coefficient (DC). The difference in lung tumor volumes between FB-PET and 4D-PET volumes was also measured. Results: The average DC in the phantom using 40% and PET edge, respectively, was lowest for FB-PET/CT (DCAir = 0.72/0.67, DCBackground 0.63/0.62) and highest for 4D-PET/CT-MIP (DCAir = 0.84/0.83, DCBackground = 0.78/0.73). The average DC in the 9 patients using 40% and PET edge, respectively, was also lowest for FB-PET/CT (DC = 0.45/0.44) and highest for 4D-PET/CT-MIP (DC = 0.72/0.73). In the 9 lesions, the target volumes of the FB-PET using 40% and PET edge, respectively, were on average 40% and 45% smaller than the 4D-PET-MIP. Conclusion: A 4D-PET-MIP produces volumes with the highest concordance with 4D-CT-MIP across multiple breathing patterns and lesion sizes in both a phantom and among patients. Freebreathing PET/CT consistently underestimates ITV when compared with 4D PET/CT for a lesion affected by respiration.

  10. Life Cycle Nitrogen Trifluoride Emissions from Photovoltaics

    SciTech Connect (OSTI)

    Fthenakis, V.

    2010-10-25

    Amorphous- and nanocrystalline-silicon thin-film photovoltaic modules are made in high-throughput manufacturing lines that necessitate quickly cleaning the reactor. Using NF{sub 3}, a potent greenhouse gas, as the cleaning agent triggered concerns as recent reports reveal that the atmospheric concentrations of this gas have increased significantly. We quantified the life-cycle emissions of NF{sub 3} in photovoltaic (PV) manufacturing, on the basis of actual measurements at the facilities of a major producer of NF{sub 3} and of a manufacturer of PV end-use equipment. From these, we defined the best practices and technologies that are the most likely to keep worldwide atmospheric concentrations of NF{sub 3} at very low radiative forcing levels. For the average U.S. insolation and electricity-grid conditions, the greenhouse gas (GHG) emissions from manufacturing and using NF{sub 3} in current PV a-Si and tandem a-Si/nc-Si facilities add 2 and 7 g CO{sub 2eq}/kWh, which can be displaced within the first 1-4 months of the PV system life.

  11. Application of Maximum Likelihood Bayesian Model Averaging to Groundwater Flow and Transport at the Hanford Site 300 Area

    SciTech Connect (OSTI)

    Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.; Rockhold, Mark L.

    2008-06-01

    A methodology to systematically and quantitatively assess model predictive uncertainty was applied to saturated zone uranium transport at the 300 Area of the U.S. Department of Energy Hanford Site in Washington State, USA. The methodology extends Maximum Likelihood Bayesian Model Averaging (MLBMA) to account jointly for uncertainties due to the conceptual-mathematical basis of models, model parameters, and the scenarios to which the models are applied. Conceptual uncertainty was represented by postulating four alternative models of hydrogeology and uranium adsorption. Parameter uncertainties were represented by estimation covariances resulting from the joint calibration of each model to observed heads and uranium concentration. Posterior model probability was dominated by one model. Results demonstrated the role of model complexity and fidelity to observed system behavior in determining model probabilities, as well as the impact of prior information. Two scenarios representing alternative future behavior of the Columbia River adjacent to the site were considered. Predictive simulations carried out with the calibrated models illustrated the computation of model- and scenario-averaged predictions and how results can be displayed to clearly indicate the individual contributions to predictive uncertainty of the model, parameter, and scenario uncertainties. The application demonstrated the practicability of applying a comprehensive uncertainty assessment to large-scale, detailed groundwater flow and transport modelling.

  12. Power flattening on modified CANDLE small long life gas-cooled fast reactor

    SciTech Connect (OSTI)

    Monado, Fiber; Su'ud, Zaki; Waris, Abdul; Basar, Khairul; Ariani, Menik; Sekimoto, Hiroshi

    2014-09-30

    Gas-cooled Fast Reactor (GFR) is one of the candidates of next generation Nuclear Power Plants (NPPs) that expected to be operated commercially after 2030. In this research conceptual design study of long life 350 MWt GFR with natural uranium metallic fuel as fuel cycle input has been performed. Modified CANDLE burn-up strategy with first and second regions located near the last region (type B) has been applied. This reactor can be operated for 10 years without refuelling and fuel shuffling. Power peaking reduction is conducted by arranging the core radial direction into three regions with respectively uses fuel volume fraction 62.5%, 64% and 67.5%. The average power density in the modified core is about 82 Watt/cc and the power peaking factor decreased from 4.03 to 3.43.

  13. Bayesian Models for Life Prediction and Fault-Mode Classification in Solid State Lamps

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2015-04-19

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classifY failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identifY luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L 70 life for the manifestation of failure.

  14. Load controller and method to enhance effective capacity of a photovoltaic power supply using a dynamically determined expected peak loading

    DOE Patents [OSTI]

    Perez, Richard

    2005-05-03

    A load controller and method are provided for maximizing effective capacity of a non-controllable, renewable power supply coupled to a variable electrical load also coupled to a conventional power grid. Effective capacity is enhanced by monitoring power output of the renewable supply and loading, and comparing the loading against the power output and a load adjustment threshold determined from an expected peak loading. A value for a load adjustment parameter is calculated by subtracting the renewable supply output and the load adjustment parameter from the current load. This value is then employed to control the variable load in an amount proportional to the value of the load control parameter when the parameter is within a predefined range. By so controlling the load, the effective capacity of the non-controllable, renewable power supply is increased without any attempt at operational feedback control of the renewable supply.

  15. Improving thermocouple service life in slagging gasifiers

    SciTech Connect (OSTI)

    Bennett, James P.; Kwong, Kyei-Sing; Powell, Cynthia A.; Thomas, Hugh; Krabbe, Rick

    2005-01-01

    The measurement of temperature within slagging gasifiers for long periods of time is difficult/impossible because of sensor failure or blockage of inputs used to monitor gasifier temperature. One of the most common means of temperature measurement in a gasifier is physically, through the use of thermocouples in a gasifier sidewall. These units can fail during startup, standby, or during the first 40-90 days of gasifier service. Failure can be caused by a number of issues; including thermocouple design, construction, placement in the gasifier, gasifier operation, and molten slag attack of the materials used in a thermocouple assembly. Lack of temperature control in a gasifier can lead to improper preheating, slag buildup on gasifier sidewalls, slag attack of gasifier refractories used to line a gasifier, or changes in desired gas output from a gasifier. A general outline of thermocouple failure issues and attempts by the Albany Research Center to improve the service life of thermocouples will be discussed.

  16. Evaluation of HEPA filter service life

    SciTech Connect (OSTI)

    Fretthold, J.K.; Stithem, A.R.

    1997-07-14

    Rocky Flats Environmental Technology Site (RFETS), has approximately 10,000 High Efficiency Particulate Air (HEPA) Filters installed in a variety of filter plenums. These ventilation/filtration plenum systems are used to control the release of airborne particulate contaminates to the environment during normal operations and potential accidents. This report summarizes the results of destructive and non-destructive tests on HEPA filters obtained from a wide variety of ages and service conditions. These tests were performed to determine an acceptable service life criteria for HEPA filters used at Rocky Flats Environmental Technology Site (RFETS). A total of 140 filters of various ages (1972 to 1996) and service history (new, aged unused, used) were tested. For the purpose of this report, filter age from manufacture date/initial test date to the current sample date was used, as opposed to the actual time a filter was installed in an operating system.

  17. Life assessments of a boiler economizer unit

    SciTech Connect (OSTI)

    Lichti, K.A.; Thomas, C.W.; Wilson, P.T.; Julian, W.

    1997-09-01

    An economizer which experienced pitting corrosion during a cleaning accident was subject to recurring corrosion fatigue failures. A condition assessment was undertaken to assess the risk of further failures through metallurgical assessment, extreme value pitting assessments, and on-site NDT condition assessment with on-site extreme value pitting analysis. This was followed by a fatigue life assessment in accordance with PD6493. Condition assessment work and lifetime prediction progressed from initial failure investigation through to final recommendations in a stepwise process. Each stage of the work was followed by a review of the findings and an economic assessment of the alternative options i.e. continue with assessment, full economizer replacement or partial replacement. Selective replacement of a portion of the economizer was recommended.

  18. Life-cycle environmental analysis--A three dimensional view

    SciTech Connect (OSTI)

    Sutherlin, K.L.; Black, R.E. )

    1993-01-01

    Both the US Air Force and the US Army have recently increased their emphasis on life-cycles of weapons systems. Along with that emphasis, there has also been an increase in emphasis in life-cycle National Environmental Policy Act (NEPA) documentation. Conflicts and inefficiencies arise when a weapon system is fielded and prompts the need for a site-specific environmental analysis. In their research and experience, the authors found no real link between life-cycle environmental analysis and site-specific environmental analyses required at various points within the life-cycle of a weapon. This other look at the relation between life-cycle and site-specific environmental analyses has the potential to increase efficiency in NEPA compliance actions and save tax dollars in the process. The authors present a three-dimensional model that relates life-cycle analyses to site-specific analyses.

  19. Battery Calendar Life Estimator Manual Modeling and Simulation

    SciTech Connect (OSTI)

    Jon P. Christophersen; Ira Bloom; Ed Thomas; Vince Battaglia

    2012-10-01

    The Battery Life Estimator (BLE) Manual has been prepared to assist developers in their efforts to estimate the calendar life of advanced batteries for automotive applications. Testing requirements and procedures are defined by the various manuals previously published under the United States Advanced Battery Consortium (USABC). The purpose of this manual is to describe and standardize a method for estimating calendar life based on statistical models and degradation data acquired from typical USABC battery testing.

  20. Life Cycle Assessment of Hydrogen Production via Natural Gas Steam

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

    Reforming | Department of Energy Hydrogen Production via Natural Gas Steam Reforming Life Cycle Assessment of Hydrogen Production via Natural Gas Steam Reforming A life cycle assessment of hydrogen production via natural gas steam reforming was performed to examine the net emissions of greenhouse gases as well as other major environmental consequences. PDF icon 27637.pdf More Documents & Publications Life Cycle Assessment of Renewable Hydrogen Production via Wind/Electrolysis: Milestone

  1. Computing, Environment and Life Sciences | Argonne National Laboratory

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

    Intranet About Us Intranet Argonne National Laboratory Computing, Environment and Life Sciences Organizations Facilities and Institutes News Events Advancing the Frontiers of Knowledge More The mission of Argonne's Computing, Environment, and Life Sciences (CELS) directorate is to enable groundbreaking scientific and technical accomplishments in areas of critical importance to the 21st century. The CELS directorate integrates Argonne's research in the life sciences with the environmental

  2. Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas

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

    from the United States | Department of Energy Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas from the United States Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas from the United States On May 29, 2014, the Department of Energy's (DOE) Office of Fossil Energy announced the availability for public review and comment the report Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas from the United States (LCA GHG Report).

  3. DOE ESPC Life of Contract Plan Template | Department of Energy

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

    ESPC Life of Contract Plan Template DOE ESPC Life of Contract Plan Template Document describes the energy savings performance contract (ESPC) Life of Contract (LOC) Plan template. It provides guidance to agency personnel during the post installation performance period of a Department of Energy's (DOEs) Energy Savings Performance Contract (ESPC) project. This document will assist the agency in effective ESPC project administration and management. It is intended to be a guide and may be modified

  4. Recommendations for Maximizing Battery Life in Photovoltaic Systems: A

    Energy Savers [EERE]

    Review of Lessons Learned | Department of Energy Information Resources » Recommendations for Maximizing Battery Life in Photovoltaic Systems: A Review of Lessons Learned Recommendations for Maximizing Battery Life in Photovoltaic Systems: A Review of Lessons Learned Notes, observations and recommendations about the use of batteries in small stand-alone photovoltaic system drawn from over a decade of research at FSEC. The most critical findings were battery life and the importance of an

  5. Briefing: DOE and the Life and Medical Sciences

    Broader source: Energy.gov [DOE]

    Aristides Patrinos, Deputy Director for Research, NYU Center for Urban Science and Progress, discussed DOE and the Life and Medical Sciences in his presentation entitled, The Promise and Challenges of the Human Genome Program. Sharlene Weatherwax, Associate Director, Biological and Environmental Research, Office of Science, DOE, discussed DOE and the Life and Medical Sciences in her presentation entitled, The Department of Energy's Activities Supporting the Life and Medical Sciences.

  6. EV Everywhere: Electric Car Safety, Maintenance, and Battery Life |

    Energy Savers [EERE]

    Department of Energy Electric Vehicle Basics » EV Everywhere: Electric Car Safety, Maintenance, and Battery Life EV Everywhere: Electric Car Safety, Maintenance, and Battery Life EV Everywhere: Electric Car Safety, Maintenance, and Battery Life Plug-in electric vehicles (also known as electric cars or EVs) are as safe and easy to maintain as conventional vehicles. While driving conditions and habits will impact vehicle operation and vehicle range, some best practices can help you maximize

  7. Technical Cost Modeling - Life Cycle Analysis Basis for Program Focus |

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

    Department of Energy 0 DOE Vehicle Technologies and Hydrogen Programs Annual Merit Review and Peer Evaluation Meeting, June 7-11, 2010 -- Washington D.C. PDF icon lm001_das_2010_o.pdf More Documents & Publications Technical Cost Modeling - Life Cycle Analysis Basis for Program Focus Technical Cost Modeling - Life Cycle Analysis Basis for Program Focus Life Cycle Modeling of Propulsion Materials

  8. Building Life Cycle Cost Programs | Department of Energy

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

    Building Life Cycle Cost Programs Building Life Cycle Cost Programs The National Institute of Standards and Technology (NIST) developed the Building Life Cycle Cost (BLCC) Programs to provide computational support for the analysis of capital investments in buildings. They include BLCC5, the Energy Escalation Rate Calculator, Handbook 135, and the Annual Supplement to Handbook 135. BLCC5 Program Register and download. BLCC 5.3-15 (for Windows or Mac OS X). BLCC version 5.3-15 contains the

  9. Federal Register Notice for Life Cycle Greenhouse Gas Perspective on

    Office of Environmental Management (EM)

    Exporting Liquefied Natural Gas from the United States | Department of Energy Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas from the United States Federal Register Notice for Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas from the United States The Office of Fossil Energy of the Department of Energy gives notice of the availability of the report Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas from the United States

  10. Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas

    Office of Environmental Management (EM)

    from the United States | Department of Energy Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas from the United States Life Cycle Greenhouse Gas Perspective on Exporting Liquefied Natural Gas from the United States This analysis calculates the life cycle greenhouse gas (GHG) emissions for regional coal and imported natural gas power in Europe and Asia. The primary research questions are as follows: *How does exported liquefied natural gas (LNG) from the U.S. compare

  11. National Ignition Facility Comes to Life

    SciTech Connect (OSTI)

    Moses, E

    2003-09-01

    First conceived of nearly 15 years ago, the National Ignition Facility (NIF) is up and running and successful beyond almost everyone's expectations. During commissioning of the first four laser beams, the laser system met design specifications for everything from beam quality to energy output. NIF will eventually have 192 laser beams. Yet with just 2% of its final beam configuration complete, NIF has already produced the highest energy laser shots in the world. In July, laser shots in the infrared wavelength using four beams produced a total of 26.5 kilojoules of energy per beam, not only meeting NIF's design energy requirement of 20 kilojoules per beam but also exceeding the energy of any other infrared laser beamline. In another campaign, NIF produced over 11.4 kilojoules of energy when the infrared light was converted to green light. An earlier performance campaign of laser light that had been frequency converted from infrared to ultraviolet really proved NIF's mettle. Over 10.4 kilojoules of ultraviolet energy were produced in about 4 billionths of a second. If all 192 beamlines were to operate at these levels, over 2 megajoules of energy would result. That much energy for the pulse duration of several nanoseconds is about 500 trillion watts of power, more than 500 times the US peak generating power.

  12. How loads affect coiled tubing life

    SciTech Connect (OSTI)

    Walker, E.J. Inc., AK )

    1992-01-01

    Fatigue testing was performed on 1-3/4-in OD, 0.125 in. wall thickness (WT) coiled tubing using a standard coiled tubing unit (CTU) as shown in this paper. Testing was conducted under Prudhoe Bay, Alaska oil well, conditions to determine the effects of axial load, internal pressure and bending stress on the longevity, or usable running footage, that can be expected with larger diameter tubing. The CTU was rigged up in a standard configuration with injector head 50 ft off the ground, the worst case for bending on most currently available North Slope units. Internal pressure was supplied by a small triplex pump and the end of tubing was closed off with a fishing neck and bull plug. Weight, for the first four tests, was suspended from the coiled tubing by a special clamp. The tubing was cycled up and over the guide arch until a loss of internal coiled tubing pressure (CTP) occurred, or until the tubing became stuck in the stripper brass.

  13. Life-Cycle Assessment of Energy and Environmental Impacts of...

    Office of Scientific and Technical Information (OSTI)

    Part 2: LED Manufacturing and Performance Scholand, Michael; Dillon, Heather E. 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; ENVIRONMENTAL IMPACTS; LIFE CYCLE;...

  14. NETL - Petroleum-Based Fuels Life Cycle Greenhouse Gas Analysis...

    Open Energy Info (EERE)

    search Tool Summary LAUNCH TOOL Name: NETL - Petroleum-Based Fuels Life Cycle Greenhouse Gas Analysis 2005 Baseline Model AgencyCompany Organization: National Energy Technology...

  15. Life-Cycle Analysis Results of Geothermal Systems in Comparison...

    Office of Environmental Management (EM)

    Systems in Comparison to Other Power Systems A life-cycle energy and greenhouse gas emissions analysis has been conducted with Argonne National Laboratory's GREET model...

  16. GREET Development and Applications for Life-Cycle Analysis of...

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

    More Documents & Publications Fuel-Cycle Energy and Emissions Analysis with the GREET Model Vehicle Technologies Office Merit Review 2015: Emissions Modeling: GREET Life Cycle...

  17. Crivelli, Silvia; Meza, Juan 60 APPLIED LIFE SCIENCES Ernest...

    Office of Scientific and Technical Information (OSTI)

    folding via divide-and-conquer optimization Oliva, Ricardo; Crivelli, Silvia; Meza, Juan 60 APPLIED LIFE SCIENCES Ernest Orlando Lawrence Berkeley NationalLaboratory, Berkeley, CA...

  18. Analysis of Energy, Environmental and Life Cycle Cost Reduction...

    Open Energy Info (EERE)

    Environmental and Life Cycle Cost Reduction Potential of Ground Source Heat Pump (GSHP) in Hot and Humid Climate Geothermal Project Jump to: navigation, search Last modified on...

  19. Battery Life Estimation (BLE) and Data Analysis - Energy Innovation...

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

    Energy Storage Energy Analysis Energy Analysis Find More Like This Return to Search Battery Life Estimation (BLE) and Data Analysis Argonne National Laboratory Contact ANL About...

  20. Life-Cycle Assessment of Energy and Environmental Impacts of...

    Office of Scientific and Technical Information (OSTI)

    Lighting Products Part 2: LED Manufacturing and Performance Citation Details In-Document Search Title: Life-Cycle Assessment of Energy and Environmental Impacts of LED Lighting ...