National Library of Energy BETA

Sample records for number peak kilowatts

  1. Table 10.9 Photovoltaic Cell and Module Shipments by Sector and End Use, 1989-2010 (Peak Kilowatts )

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

    Photovoltaic Cell and Module Shipments by Sector and End Use, 1989-2010 (Peak Kilowatts 1 ) Year By Sector By End Use Total Residential Commercial 3 Industrial 4 Electric Power 5 Other 6 Grid-Connected 2 Off-Grid 2 Centralized 7 Distributed 8 Domestic 9 Non-Domestic 10 Total Shipments of Photovoltaic Cells and Modules 11<//td> 1989 1,439 6,057 [R] 3,993 785 551 [12] 1,251 [12] 2,620 8,954 12,825 1990 1,701 8,062 [R] 2,817 826 432 [12] 469 [12] 3,097 10,271 13,837 1991 3,624 5,715 [R] 3,947

  2. Vehicle Technologies Office Merit Review 2015: 88 Kilowatt Automotive

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

    Inverter with New 900 Volt Silicon Carbide MOSFET Technology | Department of Energy 88 Kilowatt Automotive Inverter with New 900 Volt Silicon Carbide MOSFET Technology Vehicle Technologies Office Merit Review 2015: 88 Kilowatt Automotive Inverter with New 900 Volt Silicon Carbide MOSFET Technology Presentation given by Cree at 2015 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Office Annual Merit Review and Peer Evaluation Meeting about 88 kilowatt automotive inverter with new

  3. Vehicle Technologies Office Merit Review 2015: 88 Kilowatt Automotive...

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

    Automotive Inverter with New 900 Volt Silicon Carbide MOSFET Technology Vehicle Technologies Office Merit Review 2015: 88 Kilowatt Automotive Inverter with New 900 Volt ...

  4. Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Demonstration...

    Office of Scientific and Technical Information (OSTI)

    (KRUSTY) Demonstration. CEDT Phase 1 Preliminary Design Documentation Citation Details In-Document Search Title: Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Demonstration. ...

  5. Vehicle Technologies Office Merit Review 2016: 88 Kilowatt Automotive

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

    Inverter with New 900 Volt Silicon Carbide MOSFET Technology | Department of Energy 88 Kilowatt Automotive Inverter with New 900 Volt Silicon Carbide MOSFET Technology Vehicle Technologies Office Merit Review 2016: 88 Kilowatt Automotive Inverter with New 900 Volt Silicon Carbide MOSFET Technology Presentation given by Cree at the 2016 DOE Vehicle Technologies Office and Hydrogen and Fuel Cells Program Annual Merit Review and Peer Evaluation Meeting about Electric Drive Systems

  6. Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Demonstration. CEDT

    Office of Scientific and Technical Information (OSTI)

    Phase 1 Preliminary Design Documentation (Technical Report) | SciTech Connect Technical Report: Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Demonstration. CEDT Phase 1 Preliminary Design Documentation Citation Details In-Document Search Title: Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Demonstration. CEDT Phase 1 Preliminary Design Documentation The intent of the integral experiment request IER 299 (called KiloPower by NASA) is to assemble and evaluate the operational

  7. Desert Peak EGS Project

    Broader source: Energy.gov [DOE]

    Desert Peak EGS Project presentation at the April 2013 peer review meeting held in Denver, Colorado.

  8. Aluminum-blade development for the Mod-0A 200-kilowatt wind turbine

    SciTech Connect (OSTI)

    Linscott, B.S.; Shaltens, R.K.; Eggers, A.G.

    1981-12-01

    This report documents the operating experience with two aluminum blades used on the DOE/NASA Mod-0A 200-kilowatt wind turbine located at Clayton, New Mexico. Each Mod-0A aluminum blade is 59.9 feet long and weighs 2360 pounds. The aluminum Mod-0A blade design requirements, the selected design, fabrication procedures, and the blade analyses are discussed. A detailed chronology is presented on the operating experience of the Mod-0A aluminum blades used at Clayton, New Mexico. Blade structural damage was experienced. Inspection and damage assessment were required. Structural modifications that were incorporated to the blades successfully extended the useful operating life of the blades. The aluminum blades completed the planned 2 years of operation of the Clayton wind turbine. The blades were removed from service in August 1980 to allow testing of advanced technology wood composite blades.

  9. Bandwidth Historical Peak Days

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

    Bandwidth Historical Peak Days Bandwidth Historical Peak Days These plots show yearly peak days from 2000 to the present. BE CAREFUL because the graphs are autoscaling - check the scales on each axis before you compare graphs. Note that the graph for current year shows the data for the year-to-date peak. Transfer Rate vs. Size Transfer Rate vs. Size Transfer Rate vs. Size Transfer Rate vs. Size Transfer Rate vs. Size Transfer Rate vs. Size Transfer Rate vs. Size Transfer Rate vs. Size Transfer

  10. Peak power ratio generator

    DOE Patents [OSTI]

    Moyer, Robert D.

    1985-01-01

    A peak power ratio generator is described for measuring, in combination with a conventional power meter, the peak power level of extremely narrow pulses in the gigahertz radio frequency bands. The present invention in a preferred embodiment utilizes a tunnel diode and a back diode combination in a detector circuit as the only high speed elements. The high speed tunnel diode provides a bistable signal and serves as a memory device of the input pulses for the remaining, slower components. A hybrid digital and analog loop maintains the peak power level of a reference channel at a known amount. Thus, by measuring the average power levels of the reference signal and the source signal, the peak power level of the source signal can be determined.

  11. Peak power ratio generator

    DOE Patents [OSTI]

    Moyer, R.D.

    A peak power ratio generator is described for measuring, in combination with a conventional power meter, the peak power level of extremely narrow pulses in the gigahertz radio frequency bands. The present invention in a preferred embodiment utilizes a tunnel diode and a back diode combination in a detector circuit as the only high speed elements. The high speed tunnel diode provides a bistable signal and serves as a memory device of the input pulses for the remaining, slower components. A hybrid digital and analog loop maintains the peak power level of a reference channel at a known amount. Thus, by measuring the average power levels of the reference signal and the source signal, the peak power level of the source signal can be determined.

  12. Overview of Multi-Kilowatt Free-Piston Stirling Power Conversion Research at GRC

    SciTech Connect (OSTI)

    Geng, Steven M.; Mason, Lee S.; Dyson, Rodger W.; Penswick, L. Barry

    2008-01-21

    As a step towards development of Stirling power conversion for potential use in Fission Surface Power (FSP) systems, a pair of commercially available 1 kW class free-piston Stirling convertors and a pair of commercially available pressure wave generators (which will be plumbed together to create a high power Stirling linear alternator test rig) have been procured for in-house testing at Glenn Research Center. Delivery of both the Stirling convertors and the linear alternator test rig is expected by October, 2007. The 1 kW class free-piston Stirling convertors will be tested at GRC to map and verify performance. The convertors will later be modified to operate with a NaK liquid metal pumped loop for thermal energy input. The high power linear alternator test rig will be used to map and verify high power Stirling linear alternator performance and to develop power management and distribution (PMAD) methods and techniques. This paper provides an overview of the multi-kilowatt free-piston Stirling power conversion work being performed at GRC.

  13. monthly_peak_2005.xls

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

    3a . January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Council Region, 2005 and Projected 2006 through 2010 (Megawatts and 2005 Base Year) Projected Monthly Base Year Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid FRCC MRO NPCC RFC SERC SPP ERCOT WECC Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW) Peak

  14. PEAK READING VOLTMETER

    DOE Patents [OSTI]

    Dyer, A.L.

    1958-07-29

    An improvement in peak reading voltmeters is described, which provides for storing an electrical charge representative of the magnitude of a transient voltage pulse and thereafter measuring the stored charge, drawing oniy negligible energy from the storage element. The incoming voltage is rectified and stored in a condenser. The voltage of the capacitor is applied across a piezoelectric crystal between two parallel plates. Amy change in the voltage of the capacitor is reflected in a change in the dielectric constant of the crystal and the capacitance between a second pair of plates affixed to the crystal is altered. The latter capacitor forms part of the frequency determlning circuit of an oscillator and means is provided for indicating the frequency deviation which is a measure of the peak voltage applied to the voltmeter.

  15. PEAK LIMITING AMPLIFIER

    DOE Patents [OSTI]

    Goldsworthy, W.W.; Robinson, J.B.

    1959-03-31

    A peak voltage amplitude limiting system adapted for use with a cascade type amplifier is described. In its detailed aspects, the invention includes an amplifier having at least a first triode tube and a second triode tube, the cathode of the second tube being connected to the anode of the first tube. A peak limiter triode tube has its control grid coupled to thc anode of the second tube and its anode connected to the cathode of the second tube. The operation of the limiter is controlled by a bias voltage source connected to the control grid of the limiter tube and the output of the system is taken from the anode of the second tube.

  16. monthly_peak_2006.xls

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

    6 Released: February 7, 2008 Next Update: October 2008 Table 3a . January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region 2006 and Projected 2007 through 2011 (Megawatts and 2006 Base Year) Projected Monthly Base Year Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid FRCC MRO NPCC RFC SERC SPP ERCOT WECC Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW) Peak

  17. Aggregate Transfers Historical Yearly Peak

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

    Transfers Historical Yearly Peak Aggregate Transfers Historical Yearly Peak These plots show the yearly peak days from 2000 to the present. BE CAREFUL because the graphs are autoscaling - check the scales on each axis before you compare graphs. Note that the graph for current year shows the data for the year-to-date peak. Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate

  18. Concurrent Transfers Historical Yearly Peak

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

    Transfers Historical Yearly Peak Concurrent Transfers Historical Yearly Peak These plots show the yearly peak days from 2000 to present. BE CAREFUL because the graphs are autoscaling - check the scales on each axis before you compare graphs. Note that the graph for current year shows the data for the year-to-date peak. Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage

  19. Transfer Activity Historical Yearly Peak

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

    Activity Historical Yearly Peak Transfer Activity Historical Yearly Peak The plots below show the yearly peak days from 2000 to the present. BE CAREFUL because the graphs are autoscaling - check the scales on each axis before you compare graphs. Note that the graph for the current year shows the data for the year-to-date peak. Transfers Started/In Progress Transfers Started/In Progress Transfers Started/In Progress Transfers Started/In Progress Transfers Started/In Progress Transfers Started/In

  20. monthly_peak_2003.xls

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

    O Form EIA-411 for 2005 Released: February 7, 2008 Next Update: October 2007 Table 3a . January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Council Region, 1996 through 2003 and Projected 2004 through 2005 (Megawatts and 2003 Base Year) Projected Monthly Base Year Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid ECAR FRCC MAAC MAIN MAPP/MR NPCC SERC SPP ERCOT WECC Peak Hour Demand (MW) Peak Hour Demand (MW) Peak Hour Demand (MW)

  1. Concurrent Transfers Historical Yearly Peak

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

    the graph for current year shows the data for the year-to-date peak. Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily...

  2. Table 9. U.S. photovoltaic module shipments by state/territory, 2014 (peak kilow

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

    photovoltaic module shipments by state/territory, 2014 (peak kilowatts)" "State","Total","Percent of U.S. total" "Alabama",482,0 "Alaska",81,0 "Arizona",194476,0.033 "Arkansas",336,0 "California",3163120,0.53 "Colorado",47240,0.008 "Connecticut",50745,0.009 "Delaware",6600,0.001 "District of Columbia",751,0 "Florida",18593,0.003 "Georgia",47660,0.008

  3. summer_peak_2004.xls

    Gasoline and Diesel Fuel Update (EIA)

    2009 (Megawatts and 2004 Base Year) Summer Noncoincident Peak Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC...

  4. summer_peak_2003.xls

    Gasoline and Diesel Fuel Update (EIA)

    2008 (Megawatts and 2003 Base Year) Summer Noncoincident Peak Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC...

  5. Desert Peak Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    Desert Peak Geothermal Area (Redirected from Desert Peak Area) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Desert Peak Geothermal Area Contents 1 Area Overview 2...

  6. Peak finding using biorthogonal wavelets

    SciTech Connect (OSTI)

    Tan, C.Y.

    2000-02-01

    The authors show in this paper how they can find the peaks in the input data if the underlying signal is a sum of Lorentzians. In order to project the data into a space of Lorentzian like functions, they show explicitly the construction of scaling functions which look like Lorentzians. From this construction, they can calculate the biorthogonal filter coefficients for both the analysis and synthesis functions. They then compare their biorthogonal wavelets to the FBI (Federal Bureau of Investigations) wavelets when used for peak finding in noisy data. They will show that in this instance, their filters perform much better than the FBI wavelets.

  7. Stochastic acceleration in peaked spectrum

    SciTech Connect (OSTI)

    Zasenko, V.; Zagorodny, A.; Weiland, J.

    2005-06-15

    Diffusion in velocity space of test particles undergoing external random electric fields with spectra varying from low intensive and broad to high intensive and narrow (peaked) is considered. It is shown that to achieve consistency between simulation and prediction of the microscopic model, which is reduced to Fokker-Planck-type equation, it is necessary, in the case of peaked spectrum, to account for temporal variation of diffusion coefficient occurring in the early stage. An analytical approximation for the solution of the Fokker-Planck equation with a time and velocity dependent diffusion coefficients is proposed.

  8. winter_peak_2003.xls

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

    ) Form EIA-411 for 2005 Released: February 7, 2008 Next Update: October 2007 Table 2b . Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, 1990 through 2003 and Projected 2004 through 2008 (Megawatts and 2003 Base Year) Winter Noncoincident Peak Load Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN MAPP (U.S. NPCC (U.S.) SERC SPP ERCOT WECC (U.S.) 1990/1991 484,231 67,097

  9. winter_peak_2004.xls

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

    b . Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, 1990 through 2004 and Projected 2005 through 2009 (Megawatts and 2004 Base Year) Winter Noncoincident Peak Load Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN MAPP/MRO (U.S.) NPCC (U.S.) SERC SPP ERCOT WECC (U.S.) 1990/1991 484,231 67,097 30,800 36,551 32,461 21,113 40,545 86,648 38,949 35,815 94,252 1991/1992 485,761

  10. winter_peak_2005.xls

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

    2b . Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, 2005 and Projected 2006 through 2010 (Megawatts and 2005 Base Year) Winter Noncoincident Peak Load Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year FRCC MRO (U.S.) NPCC (U.S.) RFC SERC SPP ERCOT WECC (U.S.) 2005/2006 626,365 42,657 33,748 46,828 151,600 164,638 31,260 48,141 107,493 Contiguous U.S. Projected FRCC MRO (U.S.) NPCC (U.S.)

  11. METHOD OF PEAK CURRENT MEASUREMENT

    DOE Patents [OSTI]

    Baker, G.E.

    1959-01-20

    The measurement and recording of peak electrical currents are described, and a method for utilizing the magnetic field of the current to erase a portion of an alternating constant frequency and amplitude signal from a magnetic mediums such as a magnetic tapes is presented. A portion of the flux from the current carrying conductor is concentrated into a magnetic path of defined area on the tape. After the current has been recorded, the tape is played back. The amplitude of the signal from the portion of the tape immediately adjacent the defined flux area and the amplitude of the signal from the portion of the tape within the area are compared with the amplitude of the signal from an unerased portion of the tape to determine the percentage of signal erasure, and thereby obtain the peak value of currents flowing in the conductor.

  12. Silver Peak Innovative Exploration Project

    Broader source: Energy.gov [DOE]

    DOE Geothermal Peer Review 2010 - Presentation. Project objectives: Reduce the high level of risk during the early stages of geothermal project development by conducting a multi-faceted and innovative exploration and drilling program at Silver Peak. Determine the combination of techniques that are most useful and cost-effective in identifying the geothermal resource through a detailed, post-project evaluation of the exploration and drilling program.

  13. Texas Nuclear Profile - Comanche Peak

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

    Comanche Peak" "Unit","Summer capacity (mw)","Net generation (thousand mwh)","Summer capacity factor (percent)","Type","Commercial operation date","License expiration date" 1,"1,209","9,677",91.4,"PWR","application/vnd.ms-excel","application/vnd.ms-excel"

  14. Table 8.11b Electric Net Summer Capacity: Electric Power Sector, 1949-2011 (Subset of Table 8.11a; Kilowatts)

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

    b Electric Net Summer Capacity: Electric Power Sector, 1949-2011 (Subset of Table 8.11a; Kilowatts) Year Fossil Fuels Nuclear Electric Power Hydro- electric Pumped Storage Renewable Energy Other 9 Total Coal 1 Petroleum 2 Natural Gas 3 Other Gases 4 Total Conventional Hydroelectric Power 5 Biomass Geo- thermal Solar/PV 8 Wind Total Wood 6 Waste 7 1949 NA NA NA NA 44,887,000 0 [5] 18,500,000 13,000 [10] NA NA NA 18,513,000 NA 63,400,000 1950 NA NA NA NA 49,987,000 0 [5] 19,200,000 13,000 [10] NA

  15. Table 8.11c Electric Net Summer Capacity: Electric Power Sector by Plant Type, 1989-2011 (Breakout of Table 8.11b; Kilowatts)

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

    c Electric Net Summer Capacity: Electric Power Sector by Plant Type, 1989-2011 (Breakout of Table 8.11b; Kilowatts) Year Fossil Fuels Nuclear Electric Power Hydro- electric Pumped Storage Renewable Energy Other 8 Total Coal 1 Petroleum 2 Natural Gas 3 Other Gases 4 Total Conventional Hydroelectric Power Biomass Geo- thermal Solar/PV 7 Wind Total Wood 5 Waste 6 Electricity-Only Plants 9<//td> 1989 296,541,828 77,966,348 119,304,288 364,000 494,176,464 98,160,610 18,094,424 73,579,794

  16. Table 8.11d Electric Net Summer Capacity: Commercial and Industrial Sectors, 1989-2011 (Subset of Table 8.11a; Kilowatts)

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

    d Electric Net Summer Capacity: Commercial and Industrial Sectors, 1989-2011 (Subset of Table 8.11a; Kilowatts) Year Fossil Fuels Nuclear Electric Power Hydro- electric Pumped Storage Renewable Energy Other 8 Total Coal 1 Petroleum 2 Natural Gas 3 Other Gases 4 Total Conventional Hydroelectric Power Biomass Geo- thermal Solar/PV 7 Wind Total Wood 5 Waste 6 Commercial Sector 9<//td> 1989 258,193 191,487 578,797 – 1,028,477 [–] – 17,942 13,144 166,392 [–] – – 197,478 – 1,225,955 1990

  17. Peak Underground Working Natural Gas Storage Capacity

    Gasoline and Diesel Fuel Update (EIA)

    Previous Articles Previous Articles Estimates of Peak Underground Working Gas Storage Capacity in the United States, 2009 Update (Released, 8312009) Estimates of Peak Underground...

  18. Peak Treatment Systems | Open Energy Information

    Open Energy Info (EERE)

    Treatment Systems Jump to: navigation, search Name: Peak Treatment Systems Place: Golden, CO Website: www.peaktreatmentsystems.com References: Peak Treatment Systems1 Information...

  19. peak_load_2010.xls

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

    2. Noncoincident Peak Load, by North American Electric Reliability Corporation Assessment Area, 1990-2010 Actual, 2011-2015 Projected (Megawatts) Interconnection NERC Regional Assesment Area 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 FRCC 27,266 28,818 30,601 32,823 32,904 34,524 35,444 35,375 38,730 37,493 37,194 39,062 40,696 40,475 42,383 46,396 45,751 46,676 44,836 NPCC 44,116 46,594 43,658 46,706 47,581 47,705 45,094 49,269 49,566 52,855

  20. SnowPeak Energy | Open Energy Information

    Open Energy Info (EERE)

    SnowPeak Energy Place: Reno, Nevada Zip: 89502 Product: Nevada-based concentrator PV module maker. References: SnowPeak Energy1 This article is a stub. You can help OpenEI by...

  1. Table 8.11a Electric Net Summer Capacity: Total (All Sectors), 1949-2011 (Sum of Tables 8.11b and 8.11d; Kilowatts)

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

    a Electric Net Summer Capacity: Total (All Sectors), 1949-2011 (Sum of Tables 8.11b and 8.11d; Kilowatts) Year Fossil Fuels Nuclear Electric Power Hydro- electric Pumped Storage Renewable Energy Other 9 Total Coal 1 Petroleum 2 Natural Gas 3 Other Gases 4 Total Conventional Hydroelectric Power 5 Biomass Geo- thermal Solar/PV 8 Wind Total Wood 6 Waste 7 1949 NA NA NA NA 44,887,000 0 [5] 18,500,000 13,000 [10] NA NA NA 18,513,000 NA 63,400,000 1950 NA NA NA NA 49,987,000 0 [5] 19,200,000 13,000

  2. Peak Doctor v 1.0.0 Labview Version

    Energy Science and Technology Software Center (OSTI)

    2014-05-29

    PeakDoctor software works interactively with its user to analyze raw gamma-ray spectroscopic data. The goal of the software is to produce a list of energies and areas of all of the peaks in the spectrum, as accurately as possible. It starts by performing an energy calibration, creating a function that describes how energy can be related to channel number. Next, the software determines which channels in the raw histogram are in the Compton continuum andmore » which channels are parts of a peak. Then the software fits the Compton continuum with cubic polynomials. The last step is to fit all of the peaks with Gaussian functions, thus producing the list.« less

  3. Note: Proton irradiation at kilowatt-power and neutron production from a free-surface liquid-lithium target

    SciTech Connect (OSTI)

    Halfon, S.; Feinberg, G.; Arenshtam, A.; Kijel, D.; Weissman, L.; Aviv, O.; Berkovits, D.; Dudovitch, O.; Eisen, Y.; Eliyahu, I.; Haquin, G.; Hazenshprung, N.; Kreisel, A.; Mardor, I.; Shimel, G.; Shor, A.; Silverman, I.; Yungrais, Z.; Paul, M. Tessler, M.

    2014-05-15

    The free-surface Liquid-Lithium Target, recently developed at Soreq Applied Research Accelerator Facility (SARAF), was successfully used with a 1.9 MeV, 1.2 mA (2.3 kW) continuous-wave proton beam. Neutrons (∼2 × 10{sup 10} n/s having a peak energy of ∼27 keV) from the {sup 7}Li(p,n){sup 7}Be reaction were detected with a fission-chamber detector and by gold activation targets positioned in the forward direction. The setup is being used for nuclear astrophysics experiments to study neutron-induced reactions at stellar energies and to demonstrate the feasibility of accelerator-based boron neutron capture therapy.

  4. Passive radio frequency peak power multiplier

    DOE Patents [OSTI]

    Farkas, Zoltan D.; Wilson, Perry B.

    1977-01-01

    Peak power multiplication of a radio frequency source by simultaneous charging of two high-Q resonant microwave cavities by applying the source output through a directional coupler to the cavities and then reversing the phase of the source power to the coupler, thereby permitting the power in the cavities to simultaneously discharge through the coupler to the load in combination with power from the source to apply a peak power to the load that is a multiplication of the source peak power.

  5. Peak Underground Working Natural Gas Storage Capacity

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

    Capacity Peak Underground Working Natural Gas Storage Capacity Released: September 3, 2010 for data as of April 2010 Next Release: August 2011 References Methodology Definitions...

  6. Monthly Generation System Peak (pbl/generation)

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

    Generation > Generation Hydro Power Wind Power Monthly GSP BPA White Book Dry Year Tools Firstgov Monthly Generation System Peak (GSP) This site is no longer maintained. Page last...

  7. Request Number:

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

    3023307 Name: Madeleine Brown Organization: nJa Address: --- -------- -------- -- Country: Phone Number: United States Fax Number: n/a E-mail: --- -------- --------_._------ --- Reasonably Describe Records Description: Please send me a copy of the emails and records relating to the decision to allow the underage son of Bill Gates to tour Hanford in June 2010. Please also send the emails and records that justify the Department of Energy to prevent other minors from visiting B Reactor. Optional

  8. Request Number:

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

    1074438 Name: Gayle Cooper Organization: nla Address: _ Country: United States Phone Number: Fax Number: nla E-mail: . ~===--------- Reasonably Describe Records Description: Information pertaining to the Department of Energy's cost estimate for reinstating pension benefit service years to the Enterprise Company (ENCO) employees who are active plan participants in the Hanford Site Pension Plan. This cost estimate was an outcome of the DOE's Worker Town Hall Meetings held on September 17-18, 2009.

  9. (Document Number)

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

    A TA-53 TOUR FORM/RADIOLOGICAL LOG (Send completed form to MS H831) _____________ _____________________________ _________________________________ Tour Date Purpose of Tour or Tour Title Start Time and Approximate Duration ___________________________ ______________ _______________________ _________________ Tour Point of Contact/Requestor Z# (if applicable) Organization/Phone Number Signature Locations Visited: (Check all that apply, and list any others not shown. Prior approval must be obtained

  10. QER- Comment of Cloud Peak Energy Inc

    Office of Energy Efficiency and Renewable Energy (EERE)

    Dear Ms Pickett Please find attached comments from Cloud Peak Energy as input to the Department of Energy’s Quadrennial Energy Review. If possible I would appreciate a confirmation that this email has been received Thank you.

  11. Peak Underground Working Natural Gas Storage Capacity

    Gasoline and Diesel Fuel Update (EIA)

    not necessarily coincide. As such, the noncoincident peak for any region is at least as big as any monthly volume in the historical record. Data from Form EIA-191M, "Monthly...

  12. LNG production for peak shaving operations

    SciTech Connect (OSTI)

    Price, B.C.

    1999-07-01

    LNG production facilities are being developed as an alternative or in addition to underground storage throughout the US to provide gas supply during peak gas demand periods. These facilities typically involved a small liquefaction unit with a large LNG storage tank and gas sendout facilities capable of responding to peak loads during the winter. Black and Veatch is active in the development of LNG peak shaving projects for clients using a patented mixed refrigerant technology for efficient production of LNG at a low installed cost. The mixed refrigerant technology has been applied in a range of project sizes both with gas turbine and electric motor driven compression systems. This paper will cover peak shaving concepts as well as specific designs and projects which have been completed to meet this market need.

  13. Storm Peak Lab Cloud Property Validation

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

    Peak Lab Cloud Property Validation Experiment (STORMVEX) Operated by the Atmospheric Radiation Measurement (ARM) Climate Research Facility for the U.S. Department of Energy, the second ARM Mobile Facility (AMF2) begins its inaugural deployment November 2010 in Steamboat Springs, Colorado, for the Storm Peak Lab Cloud Property Validation Experiment, or STORMVEX. For six months, the comprehensive suite of AMF2 instruments will obtain measurements of cloud and aerosol properties at various sites

  14. Measured Peak Equipment Loads in Laboratories

    SciTech Connect (OSTI)

    Mathew, Paul A.

    2007-09-12

    This technical bulletin documents measured peak equipment load data from 39 laboratory spaces in nine buildings across five institutions. The purpose of these measurements was to obtain data on the actual peak loads in laboratories, which can be used to rightsize the design of HVAC systems in new laboratories. While any given laboratory may have unique loads and other design considerations, these results may be used as a 'sanity check' for design assumptions.

  15. TESTING THE E {sub peak}-E {sub iso} RELATION FOR GRBs DETECTED BY SWIFT AND SUZAKU-WAM

    SciTech Connect (OSTI)

    Krimm, H. A.; Sakamoto, T.; Yamaoka, K.; Sugita, S.; Ohno, M.; Sato, G.; Hara, R.; Ohmori, N.; Tanaka, H.; Yamauchi, M.; Norris, J. P.; Onda, K.; Tashiro, M.

    2009-10-20

    One of the most prominent, yet controversial associations derived from the ensemble of prompt-phase observations of gamma-ray bursts (GRBs) is the apparent correlation in the source frame between the peak energy (E {sub peak}) of the nuF(nu) spectrum and the isotropic radiated energy, E {sub iso}. Since most GRBs have E {sub peak} above the energy range (15-150 keV) of the Burst Alert Telescope (BAT) on Swift, determining accurate E {sub peak} values for large numbers of Swift bursts has been difficult. However, by combining data from Swift/BAT and the Suzaku Wide-band All-Sky Monitor (WAM), which covers the energy range from 50 to 5000 keV, for bursts which are simultaneously detected, one can accurately fit E {sub peak} and E {sub iso} and test the relationship between them for the Swift sample. Between the launch of Suzaku in 2005 July and the end of 2009 April, there were 48 GRBs that triggered both Swift/BAT and WAM, and an additional 48 bursts that triggered Swift and were detected by WAM, but did not trigger. A BAT-WAM team has cross-calibrated the two instruments using GRBs, and we are now able to perform joint fits on these bursts to determine their spectral parameters. For those bursts with spectroscopic redshifts, we can also calculate the isotropic energy. Here, we present the results of joint Swift/BAT-Suzaku/WAM spectral fits for 91 of the bursts detected by the two instruments. We show that the distribution of spectral fit parameters is consistent with distributions from earlier missions and confirm that Swift bursts are consistent with earlier reported relationships between E {sub peak} and isotropic energy. We show through time-resolved spectroscopy that individual burst pulses are also consistent with this relationship.

  16. The PEAK experience in South Carolina

    SciTech Connect (OSTI)

    1998-11-01

    The PEAK Institute was developed to provide a linkage for formal (schoolteachers) and nonformal educators (extension agents) with agricultural scientists of Clemson University`s South Carolina Agricultural Experiment Station System. The goal of the Institute was to enable teams of educators and researchers to develop and provide PEAK science and math learning experiences related to relevant agricultural and environmental issues of local communities for both classroom and 4-H Club experiences. The Peak Institute was conducted through a twenty day residential Institute held in June for middle school and high school teachers who were teamed with an Extension agent from their community. These educators participated in hands-on, minds-on sessions conducted by agricultural researchers and Clemson University Cooperative Extension specialists. Participants were given the opportunity to see frontier science being conducted by scientists from a variety of agricultural laboratories.

  17. ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern...

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

    Historical Noncoincident Summer Peak Load, Actual by North American Electric Reliability Council Region, 1990 through 2004 " ,"(Megawatts)" ,,,,," " ,"Summer Noncoincident Peak ...

  18. Peak to Peak Charter Wins Colorado Science Bowl - News Releases | NREL

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

    Peak to Peak Charter Wins Colorado Science Bowl Lafayette School Heads to Washington D.C. to Challenge for National Title February 13, 2010 Students from Peak to Peak Charter School won the Colorado High School Science Bowl today. They will go on to the 20th National Science Bowl in Washington D.C. on April 29 - May 4, where they will compete for the national title against more than 450 students from 68 high schools. The U.S. Department of Energy began the Science Bowl tradition in 1991 as a way

  19. Beyond Kilowatts: Utility Business Innovation

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

    Sharing Smart Grid Experiences Through Performance Feedback Joe Miller, Smart Grid Implementation Strategy Team September 15, 2011 Prepared by: National Energy Technology Laboratory This presentation was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness,

  20. Beyond Kilowatts: Utility Business Innovation

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

    Sharing Smart Grid Experiences Through Performance Feedback Joe Miller, Smart Grid Implementation Strategy Team September 15, 2011 Prepared by: National Energy Technology...

  1. summer_peak_1990_2004.xls

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

    c . Historical Noncoincident Summer Peak Load, Actual by North American Electric Reliability Council Region, 1990 through 2004 (Megawatts) Summer Noncoincident Peak Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Year ECAR FRCC MAAC MAIN MAPP/MRO (U.S.) NPCC (U.S.) SERC SPP ERCOT WECC (U.S.) 1990 546,331 79,258 27,266 42,613 40,740 24,994 44,116 94,677 52,541 42,737 97,389 1991 551,418 81,224 28,818 45,937 41,598 25,498 46,594 95,968 51,885 41,870 92,026 1992 548,707

  2. winter_peak_1990_2004.xls

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

    d . Historical Noncoincident Winter Peak Load, Actual by North American Electric Reliability Council Region, 1990 through 2004 (Megawatts) Winter Noncoincident Peak Load Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Year ECAR FRCC MAAC MAIN MAPP/MRO (U.S.) NPCC (U.S.) SERC SPP ERCOT WECC (U.S.) 1990/1991 484,231 67,097 30,800 36,551 32,461 21,113 40,545 86,648 38,949 35,815 94,252 1991/1992 485,761 71,181 31,153 37,983 33,420 21,432 41,866 88,422 38,759 35,448 86,097

  3. Ionoacoustic characterization of the proton Bragg peak with submillimeter accuracy

    SciTech Connect (OSTI)

    Assmann, W. Reinhardt, S.; Lehrack, S.; Edlich, A.; Thirolf, P. G.; Parodi, K.; Kellnberger, S.; Omar, M.; Ntziachristos, V.; Moser, M.; Dollinger, G.

    2015-02-15

    Purpose: Range verification in ion beam therapy relies to date on nuclear imaging techniques which require complex and costly detector systems. A different approach is the detection of thermoacoustic signals that are generated due to localized energy loss of ion beams in tissue (ionoacoustics). Aim of this work was to study experimentally the achievable position resolution of ionoacoustics under idealized conditions using high frequency ultrasonic transducers and a specifically selected probing beam. Methods: A water phantom was irradiated by a pulsed 20 MeV proton beam with varying pulse intensity and length. The acoustic signal of single proton pulses was measured by different PZT-based ultrasound detectors (3.5 and 10 MHz central frequencies). The proton dose distribution in water was calculated by Geant4 and used as input for simulation of the generated acoustic wave by the matlab toolbox k-WAVE. Results: In measurements from this study, a clear signal of the Bragg peak was observed for an energy deposition as low as 10{sup 12} eV. The signal amplitude showed a linear increase with particle number per pulse and thus, dose. Bragg peak position measurements were reproducible within 30 ?m and agreed with Geant4 simulations to better than 100 ?m. The ionoacoustic signal pattern allowed for a detailed analysis of the Bragg peak and could be well reproduced by k-WAVE simulations. Conclusions: The authors have studied the ionoacoustic signal of the Bragg peak in experiments using a 20 MeV proton beam with its correspondingly localized energy deposition, demonstrating submillimeter position resolution and providing a deep insight in the correlation between the acoustic signal and Bragg peak shape. These results, together with earlier experiments and new simulations (including the results in this study) at higher energies, suggest ionoacoustics as a technique for range verification in particle therapy at locations, where the tumor can be localized by ultrasound imaging

  4. ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern...

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

    f. Historical Noncoincident Winter Peak Load, Actual by North American Electric Reliability Corporation Region, 2005 through 2010 " ,"(Megawatts)" ,"Winter Noncoincident Peak ...

  5. ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern...

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

    d. Historical Noncoincident Winter Peak Load, Actual by North American Electric Reliability Council Region, 1990 through 2004 " ,"(Megawatts)" ,"Winter Noncoincident Peak ...

  6. Twin Peaks Motel Space Heating Low Temperature Geothermal Facility...

    Open Energy Info (EERE)

    Peaks Motel Space Heating Low Temperature Geothermal Facility Jump to: navigation, search Name Twin Peaks Motel Space Heating Low Temperature Geothermal Facility Facility Twin...

  7. Magnetotellurics At Silver Peak Area (DOE GTP) | Open Energy...

    Open Energy Info (EERE)

    Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Magnetotellurics At Silver Peak Area (DOE GTP) Exploration Activity...

  8. Geothermometry At Silver Peak Area (DOE GTP) | Open Energy Information

    Open Energy Info (EERE)

    Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Silver Peak Area (DOE GTP) Exploration Activity...

  9. Cuttings Analysis At Silver Peak Area (DOE GTP) | Open Energy...

    Open Energy Info (EERE)

    Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Cuttings Analysis At Silver Peak Area (DOE GTP) Exploration Activity...

  10. Ground Magnetics At Silver Peak Area (DOE GTP) | Open Energy...

    Open Energy Info (EERE)

    Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Ground Magnetics At Silver Peak Area (DOE GTP) Exploration Activity...

  11. Core Analysis At Desert Peak Area (Laney, 2005) | Open Energy...

    Open Energy Info (EERE)

    Desert Peak Area (Laney, 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Core Analysis At Desert Peak Area (Laney, 2005) Exploration...

  12. Gas Flux Sampling At Desert Peak Area (Lechler And Coolbaugh...

    Open Energy Info (EERE)

    Desert Peak Area (Lechler And Coolbaugh, 2007) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Gas Flux Sampling At Desert Peak Area (Lechler And...

  13. Cuttings Analysis At Desert Peak Area (Laney, 2005) | Open Energy...

    Open Energy Info (EERE)

    Desert Peak Area (Laney, 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Cuttings Analysis At Desert Peak Area (Laney, 2005) Exploration...

  14. Masked Areas in Shear Peak Statistics: A Forward Modeling Approach...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Masked Areas in Shear Peak Statistics: A Forward Modeling Approach Citation Details In-Document Search Title: Masked Areas in Shear Peak Statistics: A Forward ...

  15. Development Wells At Silver Peak Area (DOE GTP) | Open Energy...

    Open Energy Info (EERE)

    Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Development Wells At Silver Peak Area (DOE GTP) Exploration Activity...

  16. Emcore/SunPeak Solar Power Plant | Open Energy Information

    Open Energy Info (EERE)

    Solar Power Plant Facility EmcoreSunPeak Sector Solar Facility Type Concentrating Photovoltaic Developer SunPeak Solar Location Albuquerque, New Mexico Coordinates 35.0844909,...

  17. Pressure Temperature Log At Silver Peak Area (DOE GTP) | Open...

    Open Energy Info (EERE)

    navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Pressure Temperature Log At Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak...

  18. monthly_peak_byarea_2010.xls

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

    B.1. FRCC Monthly Peak Hour Demand, by North American Electric Reliability Corporation Assesment Area, 1996-2010 Actual, 2011-2012 Projected (Megawatts) FRCC Year January February March April May June July August September October November December 1996 39,860 41,896 32,781 28,609 32,059 33,886 35,444 34,341 34,797 30,037 29,033 34,191 1997 37,127 28,144 27,998 28,458 33,859 34,125 35,356 35,375 33,620 31,798 27,669 31,189 1998 27,122 28,116 29,032 28,008 32,879 37,153 36,576 38,730 34,650

  19. monthly_peak_bymonth_2010.xls

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

    A.1. January Monthly Peak Hour Demand, by North American Electric Reliability Corporation Assesment Area, 1996-2010 Actual, 2011-2012 Projected (Megawatts) January NERC Regional Assesment Area 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011E 2012E FRCC 39,860 37,127 27,122 38,581 37,521 40,258 39,675 45,033 35,545 41,247 34,464 38,352 41,705 44,945 53,093 46,839 47,613 NPCC 41,680 41,208 40,009 44,199 45,227 43,553 42,039 45,987 66,215 47,041 43,661 45,002 46,803

  20. Sample distribution in peak mode isotachophoresis

    SciTech Connect (OSTI)

    Rubin, Shimon; Schwartz, Ortal; Bercovici, Moran

    2014-01-15

    We present an analytical study of peak mode isotachophoresis (ITP), and provide closed form solutions for sample distribution and electric field, as well as for leading-, trailing-, and counter-ion concentration profiles. Importantly, the solution we present is valid not only for the case of fully ionized species, but also for systems of weak electrolytes which better represent real buffer systems and for multivalent analytes such as proteins and DNA. The model reveals two major scales which govern the electric field and buffer distributions, and an additional length scale governing analyte distribution. Using well-controlled experiments, and numerical simulations, we verify and validate the model and highlight its key merits as well as its limitations. We demonstrate the use of the model for determining the peak concentration of focused sample based on known buffer and analyte properties, and show it differs significantly from commonly used approximations based on the interface width alone. We further apply our model for studying reactions between multiple species having different effective mobilities yet co-focused at a single ITP interface. We find a closed form expression for an effective-on rate which depends on reactants distributions, and derive the conditions for optimizing such reactions. Interestingly, the model reveals that maximum reaction rate is not necessarily obtained when the concentration profiles of the reacting species perfectly overlap. In addition to the exact solutions, we derive throughout several closed form engineering approximations which are based on elementary functions and are simple to implement, yet maintain the interplay between the important scales. Both the exact and approximate solutions provide insight into sample focusing and can be used to design and optimize ITP-based assays.

  1. Method of multi-dimensional moment analysis for the characterization of signal peaks

    DOE Patents [OSTI]

    Pfeifer, Kent B; Yelton, William G; Kerr, Dayle R; Bouchier, Francis A

    2012-10-23

    A method of multi-dimensional moment analysis for the characterization of signal peaks can be used to optimize the operation of an analytical system. With a two-dimensional Peclet analysis, the quality and signal fidelity of peaks in a two-dimensional experimental space can be analyzed and scored. This method is particularly useful in determining optimum operational parameters for an analytical system which requires the automated analysis of large numbers of analyte data peaks. For example, the method can be used to optimize analytical systems including an ion mobility spectrometer that uses a temperature stepped desorption technique for the detection of explosive mixtures.

  2. ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern...

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

    e. Historical Noncoincident Summer Peak Load, Actual by North American Electric Reliability Corporation Region, 2005 through 2009 " ,"(Megawatts)" ,,,,," " ,"Summer Noncoincident ...

  3. Modeling-Computer Simulations At Desert Peak Area (Wisian & Blackwell...

    Open Energy Info (EERE)

    navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Modeling-Computer Simulations At Desert Peak Area (Wisian & Blackwell, 2004) Exploration Activity...

  4. Mask effects on cosmological studies with weak-lensing peak statistics

    SciTech Connect (OSTI)

    Liu, Xiangkun; Pan, Chuzhong; Fan, Zuhui; Wang, Qiao

    2014-03-20

    With numerical simulations, we analyze in detail how the bad data removal, i.e., the mask effect, can influence the peak statistics of the weak-lensing convergence field reconstructed from the shear measurement of background galaxies. It is found that high peak fractions are systematically enhanced because of the presence of masks; the larger the masked area is, the higher the enhancement is. In the case where the total masked area is about 13% of the survey area, the fraction of peaks with signal-to-noise ratio ? ? 3 is ?11% of the total number of peaks, compared with ?7% of the mask-free case in our considered cosmological model. This can have significant effects on cosmological studies with weak-lensing convergence peak statistics, inducing a large bias in the parameter constraints if the effects are not taken into account properly. Even for a survey area of 9 deg{sup 2}, the bias in (? {sub m}, ?{sub 8}) is already intolerably large and close to 3?. It is noted that most of the affected peaks are close to the masked regions. Therefore, excluding peaks in those regions in the peak statistics can reduce the bias effect but at the expense of losing usable survey areas. Further investigations find that the enhancement of the number of high peaks around the masked regions can be largely attributed to the smaller number of galaxies usable in the weak-lensing convergence reconstruction, leading to higher noise than that of the areas away from the masks. We thus develop a model in which we exclude only those very large masks with radius larger than 3' but keep all the other masked regions in peak counting statistics. For the remaining part, we treat the areas close to and away from the masked regions separately with different noise levels. It is shown that this two-noise-level model can account for the mask effect on peak statistics very well, and the bias in cosmological parameters is significantly reduced if this model is applied in the parameter fitting.

  5. CORRELATION BETWEEN PEAK ENERGY AND PEAK LUMINOSITY IN SHORT GAMMA-RAY BURSTS

    SciTech Connect (OSTI)

    Zhang, Z. B.; Chen, D. Y. [Department of Physics, College of Sciences, Guizhou University, Guiyang 550025 (China); Huang, Y. F., E-mail: sci.zbzhang@gzu.edu.cn, E-mail: hyf@nju.edu.cn [Department of Astronomy, Nanjing University, Nanjing 210093 (China)

    2012-08-10

    A correlation between the peak luminosity and the peak energy has been found by Yonetoku et al. as L{sub p} {proportional_to}E{sup 2.0}{sub p,i} for 11 pre-Swift long gamma-ray bursts (GRBs). In this study, for a greatly expanded sample of 148 long GRBs in the Swift era, we find that the correlation still exists, but most likely with a slightly different power-law index, i.e., L{sub p} {proportional_to} E{sup 1.7}{sub p,i}. In addition, we have collected 17 short GRBs with necessary data. We find that the correlation of L{sub p} {proportional_to} E{sup 1.7}{sub p,i} also exists for this sample of short events. It is argued that the radiation mechanism of both long and short GRBs should be similar, i.e., of quasi-thermal origin caused by the photosphere, with the dissipation occurring very near the central engine. Some key parameters of the process are constrained. Our results suggest that the radiation processes of both long and short bursts may be dominated by thermal emission, rather than by the single synchrotron radiation. This might put strong physical constraints on the theoretical models.

  6. NOISY WEAK-LENSING CONVERGENCE PEAK STATISTICS NEAR CLUSTERS OF GALAXIES AND BEYOND

    SciTech Connect (OSTI)

    Fan Zuhui; Shan Huanyuan; Liu Jiayi

    2010-08-20

    Taking into account noise from intrinsic ellipticities of source galaxies, in this paper, we study the peak statistics in weak-lensing convergence maps around clusters of galaxies and beyond. We emphasize how the noise peak statistics is affected by the density distribution of nearby clusters, and also how cluster-peak signals are changed by the existence of noise. These are the important aspects to be thoroughly understood in weak-lensing analyses for individual clusters as well as in cosmological applications of weak-lensing cluster statistics. We adopt Gaussian smoothing with the smoothing scale {theta} {sub G} = 0.5arcmin in our analyses. It is found that the noise peak distribution near a cluster of galaxies sensitively depends on the density profile of the cluster. For a cored isothermal cluster with the core radius R{sub c} , the inner region with R {<=} R{sub c} appears noisy containing on average {approx}2.4 peaks with {nu} {>=} 5 for R{sub c} = 1.7arcmin and the true peak height of the cluster {nu} = 5.6, where {nu} denotes the convergence signal-to-noise ratio. For a Navarro-Frenk-White (NFW) cluster of the same mass and the same central {nu}, the average number of peaks with {nu} {>=} 5 within R {<=} R{sub c} is {approx}1.6. Thus a high peak corresponding to the main cluster can be identified more cleanly in the NFW case. In the outer region with R{sub c} < R {<=} 5R{sub c} , the number of high noise peaks is considerably enhanced in comparison with that of the pure noise case without the nearby cluster. For {nu} {>=} 4, depending on the treatment of the mass-sheet degeneracy in weak-lensing analyses, the enhancement factor f is in the range of {approx}5 to {approx}55 for both clusters as their outer density profiles are similar. The properties of the main-cluster-peak identified in convergence maps are also significantly affected by the presence of noise. Scatters as well as a systematic shift for the peak height are present. The height distribution is

  7. Track B - Critical Guidance for Peak Performance Homes | Department of

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

    Energy B - Critical Guidance for Peak Performance Homes Track B - Critical Guidance for Peak Performance Homes Presentations from Track B, Critical Guidance for Peak Performance Homes of the U.S. Department of Energy Building America program's 2012 Residential Energy Efficiency Stakeholder Meeting are provided below as Adobe Acrobat PDFs. These presentations for this track covered the following topics: Ventilation Strategies in High Performance Homes; Combustion Safety in Tight Houses;

  8. Number | Open Energy Information

    Open Energy Info (EERE)

    Property:NumOfPlants Property:NumProdWells Property:NumRepWells Property:Number of Color Cameras Property:Number of Devices Deployed Property:Number of Plants included in...

  9. Desert Peak II Geothermal Facility | Open Energy Information

    Open Energy Info (EERE)

    Facility Desert Peak II Sector Geothermal energy Location Information Location Churchill, Nevada Coordinates 39.753854931241, -118.95378112793 Loading map......

  10. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2008 and Projected 2009 through 2013 " ,"(Megawatts and 2008 ...

  11. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2009 and Projected 2010 through 2014 " ,"(Megawatts and 2009 ...

  12. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    3 and Projected 2004 through 2008 " ,"(Megawatts and 2003 Base Year)",,,," " ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,..."Texas Power ...

  13. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2007 through 2011 " ,"(Megawatts and 2006 ...

  14. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    4 and Projected 2005 through 2009 " ,"(Megawatts and 2004 Base Year)",,,," " ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,..."Texas Power ...

  15. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2007 and Projected 2008 through 2012 " ,"(Megawatts and 2007 ...

  16. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2007 and Projected 2008 through 2012 " ,"(Megawatts and 2007 ...

  17. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2007 through 2011 " ,"(Megawatts and 2006 ...

  18. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, " ,"2005 and Projected 2006 through 2010 " ,"(Megawatts and 2005 Base ...

  19. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2009 and Projected 2010 through 2014 " ,"(Megawatts and 2009 ...

  20. Multispectral Imaging At Silver Peak Area (DOE GTP) | Open Energy...

    Open Energy Info (EERE)

    DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Multispectral Imaging At Silver Peak Area (DOE GTP) Exploration Activity Details...

  1. Jiminy Peak Ski Resort Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Energy Developments Energy Purchaser Jiminy Peak Mountain Resort Location Hancock MA Coordinates 42.5554, -73.2898 Show Map Loading map... "minzoom":false,"mappingservi...

  2. Desert Peak East EGS Project; 2010 Geothermal Technology Program...

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

    East EGS Project; 2010 Geothermal Technology Program Peer Review Report Desert Peak East EGS Project; 2010 Geothermal Technology Program Peer Review Report DOE 2010 Geothermal...

  3. Multispecies density peaking in gyrokinetic turbulence simulations of low collisionality Alcator C-Mod plasmas

    SciTech Connect (OSTI)

    Mikkelsen, D. R. Bitter, M.; Delgado-Aparicio, L.; Hill, K. W.; Greenwald, M.; Howard, N. T.; Hughes, J. W.; Rice, J. E.; Reinke, M. L.; Podpaly, Y.; Ma, Y.; Candy, J.; Waltz, R. E.

    2015-06-15

    Peaked density profiles in low-collisionality AUG and JET H-mode plasmas are probably caused by a turbulently driven particle pinch, and Alcator C-Mod experiments confirmed that collisionality is a critical parameter. Density peaking in reactors could produce a number of important effects, some beneficial, such as enhanced fusion power and transport of fuel ions from the edge to the core, while others are undesirable, such as lower beta limits, reduced radiation from the plasma edge, and consequently higher divertor heat loads. Fundamental understanding of the pinch will enable planning to optimize these impacts. We show that density peaking is predicted by nonlinear gyrokinetic turbulence simulations based on measured profile data from low collisionality H-mode plasma in Alcator C-Mod. Multiple ion species are included to determine whether hydrogenic density peaking has an isotope dependence or is influenced by typical levels of low-Z impurities, and whether impurity density peaking depends on the species. We find that the deuterium density profile is slightly more peaked than that of hydrogen, and that experimentally relevant levels of boron have no appreciable effect on hydrogenic density peaking. The ratio of density at r/a = 0.44 to that at r/a = 0.74 is 1.2 for the majority D and minority H ions (and for electrons), and increases with impurity Z: 1.1 for helium, 1.15 for boron, 1.3 for neon, 1.4 for argon, and 1.5 for molybdenum. The ion temperature profile is varied to match better the predicted heat flux with the experimental transport analysis, but the resulting factor of two change in heat transport has only a weak effect on the predicted density peaking.

  4. NSR Key Number Retrieval

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

    NSR Key Number Retrieval Pease enter key in the box Submit

  5. Measurements of ion stopping around the Bragg peak in high-energy-density plasmas

    SciTech Connect (OSTI)

    Frenje, J. A.; Grabowski, P. E.; Li, C. K.; Seguin, F. H.; Zylstra, A. B.; Gatu Johnson, M.; Petrasso, R. D.; Glebov, V. Yu; Sangster, T. C.

    2015-11-09

    For the first time, quantitative measurements of ion stopping at energies about the Bragg peak (or peak ion stopping, which occurs at an ion velocity comparable to the average thermal electron velocity), and its dependence on electron temperature (Te) and electron number density (ne) in the range of 0.5 – 4.0 keV and 3 × 1022 – 3 × 1023 cm-3 have been conducted, respectively. It is experimentally demonstrated that the position and amplitude of the Bragg peak varies strongly with Te with ne. As a result, the importance of including quantum diffraction is also demonstrated in the stopping-power modeling of High-Energy-Density Plasmas.

  6. Measurements of ion stopping around the Bragg peak in high-energy-density plasmas

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

    Frenje, J. A.; Grabowski, P. E.; Li, C. K.; Seguin, F. H.; Zylstra, A. B.; Gatu Johnson, M.; Petrasso, R. D.; Glebov, V. Yu; Sangster, T. C.

    2015-11-09

    For the first time, quantitative measurements of ion stopping at energies about the Bragg peak (or peak ion stopping, which occurs at an ion velocity comparable to the average thermal electron velocity), and its dependence on electron temperature (Te) and electron number density (ne) in the range of 0.5 – 4.0 keV and 3 × 1022 – 3 × 1023 cm-3 have been conducted, respectively. It is experimentally demonstrated that the position and amplitude of the Bragg peak varies strongly with Te with ne. As a result, the importance of including quantum diffraction is also demonstrated in the stopping-power modelingmore » of High-Energy-Density Plasmas.« less

  7. Two density peaks in low magnetic field helicon plasma

    SciTech Connect (OSTI)

    Wang, Y.; Zhao, G.; Ouyang, J. T. E-mail: lppmchenqiang@hotmail.com; Liu, Z. W.; Chen, Q. E-mail: lppmchenqiang@hotmail.com

    2015-09-15

    In this paper, we report two density peaks in argon helicon plasma under an axial magnetic field from 0 G to 250 G with Boswell-type antenna driven by radio frequency (RF) power of 13.56 MHz. The first peak locates at 40–55 G and the second one at 110–165 G, as the RF power is sustainably increased from 100 W to 250 W at Ar pressure of 0.35 Pa. The absorbed power of two peaks shows a linear relationship with the magnetic field. End views of the discharge taken by intensified charge coupled device reveal that, when the first peak appeared, the discharge luminance moves to the edge of the tube as the magnetic field increases. For the second peak, the strong discharge area is centered at the two antenna legs after the magnetic field reaches a threshold value. Comparing with the simulation, we suggest that the efficient power absorption of two peaks at which the efficient power absorption mainly appears in the near-antenna region is due to the mode conversion in bounded non-uniform helicon plasma. The two low-field peaks are caused, to some extent, by the excitation of Trivelpiece-Gould wave through non-resonance conversion.

  8. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    3 and Projected 2004 through 2008 " ,"(Megawatts and 2003 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,..."Texas Power Grid","Western ...

  9. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    4 and Projected 2005 through 2009 " ,"(Megawatts and 2004 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,..."Texas Power Grid","Western ...

  10. Silver Peak, Nevada: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    This article is a stub. You can help OpenEI by expanding it. Silver Peak is a city in Esmeralda County, Nevada. References USGS GNIS Retrieved from "http:en.openei.orgw...

  11. SunPeak Solar LLC | Open Energy Information

    Open Energy Info (EERE)

    search Name: SunPeak Solar LLC Place: Palm Desert, California Zip: 92260 Product: US project developer and asset manager, focussing on PV projects in the south-west....

  12. February most likely month for flu season to peak

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

    February most likely month for flu season to peak February most likely month for flu season to peak The Los Alamos team's model is an ongoing research project that forecasts the current flu season probabilistically, similar to best-practice forecasts of weather, presidential elections, and sporting events. December 20, 2015 The Los Alamos team's model is an ongoing research project that forecasts the current flu season probabilistically, similar to best-practice forecasts of weather,

  13. Peaking of world oil production: Impacts, mitigation, & risk management

    SciTech Connect (OSTI)

    Hirsch, R.L.; Bezdek, Roger; Wendling, Robert

    2005-02-01

    The peaking of world oil production presents the U.S. and the world with an unprecedented risk management problem. As peaking is approached, liquid fuel prices and price volatility will increase dramatically, and, without timely mitigation, the economic, social, and political costs will be unprecedented. Viable mitigation options exist on both the supply and demand sides, but to have substantial impact, they must be initiated more than a decade in advance of peaking.... The purpose of this analysis was to identify the critical issues surrounding the occurrence and mitigation of world oil production peaking. We simplified many of the complexities in an effort to provide a transparent analysis. Nevertheless, our study is neither simple nor brief. We recognize that when oil prices escalate dramatically, there will be demand and economic impacts that will alter our simplified assumptions. Consideration of those feedbacks will be a daunting task but one that should be undertaken. Our aim in this study is to-- • Summarize the difficulties of oil production forecasting; • Identify the fundamentals that show why world oil production peaking is such a unique challenge; • Show why mitigation will take a decade or more of intense effort; • Examine the potential economic effects of oil peaking; • Describe what might be accomplished under three example mitigation scenarios. • Stimulate serious discussion of the problem, suggest more definitive studies, and engender interest in timely action to mitigate its impacts.

  14. Wavelet Approach for Operational Gamma Spectral Peak Detection - Preliminary Assessment

    SciTech Connect (OSTI)

    ,

    2012-02-01

    Gamma spectroscopy for radionuclide identifications typically involves locating spectral peaks and matching the spectral peaks with known nuclides in the knowledge base or database. Wavelet analysis, due to its ability for fitting localized features, offers the potential for automatic detection of spectral peaks. Past studies of wavelet technologies for gamma spectra analysis essentially focused on direct fitting of raw gamma spectra. Although most of those studies demonstrated the potentials of peak detection using wavelets, they often failed to produce new benefits to operational adaptations for radiological surveys. This work presents a different approach with the operational objective being to detect only the nuclides that do not exist in the environment (anomalous nuclides). With this operational objective, the raw-count spectrum collected by a detector is first converted to a count-rate spectrum and is then followed by background subtraction prior to wavelet analysis. The experimental results suggest that this preprocess is independent of detector type and background radiation, and is capable of improving the peak detection rates using wavelets. This process broadens the doors for a practical adaptation of wavelet technologies for gamma spectral surveying devices.

  15. Silver Peak Innovative Exploration Project (Ram Power Inc.)

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

    Miller, Clay

    2010-01-01

    Data generated from the Silver Peak Innovative Exploration Project, in Esmeralda County, Nevada, encompasses a deep-circulation (amagmatic) meteoric-geothermal system circulating beneath basin-fill sediments locally blanketed with travertine in western Clayton Valley (lithium-rich brines from which have been mined for several decades). Spring- and shallow-borehole thermal-water geochemistry and geothermometry suggest that a Silver Peak geothermal reservoir is very likely to attain the temperature range 260- 300oF (~125-150oC), and may reach 300-340oF (~150-170oC) or higher (GeothermEx, Inc., 2006). Results of detailed geologic mapping, structural analysis, and conceptual modeling of the prospect (1) support the GeothermEx (op. cit.) assertion that the Silver Peak prospect has good potential for geothermal-power production; and (2) provide a theoretical geologic framework for further exploration and development of the resource. The Silver Peak prospect is situated in the transtensional (regional shearing coupled with extension) Walker Lane structural belt, and squarely within the late Miocene to Pliocene (11 Ma to ~5 Ma) Silver Peak-Lone Mountain metamorphic core complex (SPCC), a feature that accommodated initial displacement transfer between major right-lateral strike- slip fault zones on opposite sides of the Walker Lane. The SPCC consists essentially of a ductiley-deformed lower plate, or core, of Proterozoic metamorphic tectonites and tectonized Mesozoic granitoids separated by a regionally extensive, low-angle detachment fault from an upper plate of severely stretched and fractured structural slices of brittle, Proterozoic to Miocene-age lithologies. From a geothermal perspective, the detachment fault itself and some of the upper-plate structural sheets could function as important, if secondary, subhorizontal thermal-fluid aquifers in a Silver Peak hydrothermal system.

  16. Silver Peak Innovative Exploration Project (Ram Power Inc.)

    SciTech Connect (OSTI)

    Miller, Clay

    2010-01-01

    Data generated from the Silver Peak Innovative Exploration Project, in Esmeralda County, Nevada, encompasses a “deep-circulation (amagmatic)” meteoric-geothermal system circulating beneath basin-fill sediments locally blanketed with travertine in western Clayton Valley (lithium-rich brines from which have been mined for several decades). Spring- and shallow-borehole thermal-water geochemistry and geothermometry suggest that a Silver Peak geothermal reservoir is very likely to attain the temperature range 260- 300oF (~125-150oC), and may reach 300-340oF (~150-170oC) or higher (GeothermEx, Inc., 2006). Results of detailed geologic mapping, structural analysis, and conceptual modeling of the prospect (1) support the GeothermEx (op. cit.) assertion that the Silver Peak prospect has good potential for geothermal-power production; and (2) provide a theoretical geologic framework for further exploration and development of the resource. The Silver Peak prospect is situated in the transtensional (regional shearing coupled with extension) Walker Lane structural belt, and squarely within the late Miocene to Pliocene (11 Ma to ~5 Ma) Silver Peak-Lone Mountain metamorphic core complex (SPCC), a feature that accommodated initial displacement transfer between major right-lateral strike- slip fault zones on opposite sides of the Walker Lane. The SPCC consists essentially of a ductiley-deformed lower plate, or “core,” of Proterozoic metamorphic tectonites and tectonized Mesozoic granitoids separated by a regionally extensive, low-angle detachment fault from an upper plate of severely stretched and fractured structural slices of brittle, Proterozoic to Miocene-age lithologies. From a geothermal perspective, the detachment fault itself and some of the upper-plate structural sheets could function as important, if secondary, subhorizontal thermal-fluid aquifers in a Silver Peak hydrothermal system.

  17. Silver Peak Innovative Exploration Project (Ram Power Inc.)

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

    Miller, Clay

    Data generated from the Silver Peak Innovative Exploration Project, in Esmeralda County, Nevada, encompasses a deep-circulation (amagmatic) meteoric-geothermal system circulating beneath basin-fill sediments locally blanketed with travertine in western Clayton Valley (lithium-rich brines from which have been mined for several decades). Spring- and shallow-borehole thermal-water geochemistry and geothermometry suggest that a Silver Peak geothermal reservoir is very likely to attain the temperature range 260- 300oF (~125-150oC), and may reach 300-340oF (~150-170oC) or higher (GeothermEx, Inc., 2006). Results of detailed geologic mapping, structural analysis, and conceptual modeling of the prospect (1) support the GeothermEx (op. cit.) assertion that the Silver Peak prospect has good potential for geothermal-power production; and (2) provide a theoretical geologic framework for further exploration and development of the resource. The Silver Peak prospect is situated in the transtensional (regional shearing coupled with extension) Walker Lane structural belt, and squarely within the late Miocene to Pliocene (11 Ma to ~5 Ma) Silver Peak-Lone Mountain metamorphic core complex (SPCC), a feature that accommodated initial displacement transfer between major right-lateral strike- slip fault zones on opposite sides of the Walker Lane. The SPCC consists essentially of a ductiley-deformed lower plate, or core, of Proterozoic metamorphic tectonites and tectonized Mesozoic granitoids separated by a regionally extensive, low-angle detachment fault from an upper plate of severely stretched and fractured structural slices of brittle, Proterozoic to Miocene-age lithologies. From a geothermal perspective, the detachment fault itself and some of the upper-plate structural sheets could function as important, if secondary, subhorizontal thermal-fluid aquifers in a Silver Peak hydrothermal system.

  18. New York Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) New York Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New York Number of Natural Gas ...

  19. New Mexico Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Consumers (Number of Elements) New Mexico Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New Mexico Number of Natural ...

  20. North Dakota Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) North Dakota Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers North Dakota Number of Natural ...

  1. Quantum random number generator

    DOE Patents [OSTI]

    Pooser, Raphael C.

    2016-05-10

    A quantum random number generator (QRNG) and a photon generator for a QRNG are provided. The photon generator may be operated in a spontaneous mode below a lasing threshold to emit photons. Photons emitted from the photon generator may have at least one random characteristic, which may be monitored by the QRNG to generate a random number. In one embodiment, the photon generator may include a photon emitter and an amplifier coupled to the photon emitter. The amplifier may enable the photon generator to be used in the QRNG without introducing significant bias in the random number and may enable multiplexing of multiple random numbers. The amplifier may also desensitize the photon generator to fluctuations in power supplied thereto while operating in the spontaneous mode. In one embodiment, the photon emitter and amplifier may be a tapered diode amplifier.

  2. Peak Dose Assessment for Proposed DOE-PPPO Authorized Limits

    SciTech Connect (OSTI)

    Maldonado, Delis

    2012-06-01

    The Oak Ridge Institute for Science and Education (ORISE), a U.S. Department of Energy (DOE) prime contractor, was contracted by the DOE Portsmouth/Paducah Project Office (DOE-PPPO) to conduct a peak dose assessment in support of the Authorized Limits Request for Solid Waste Disposal at Landfill C-746-U at the Paducah Gaseous Diffusion Plant (DOE-PPPO 2011a). The peak doses were calculated based on the DOE-PPPO Proposed Single Radionuclides Soil Guidelines and the DOE-PPPO Proposed Authorized Limits (AL) Volumetric Concentrations available in DOE-PPPO 2011a. This work is provided as an appendix to the Dose Modeling Evaluations and Technical Support Document for the Authorized Limits Request for the C-746-U Landfill at the Paducah Gaseous Diffusion Plant, Paducah, Kentucky (ORISE 2012). The receptors evaluated in ORISE 2012 were selected by the DOE-PPPO for the additional peak dose evaluations. These receptors included a Landfill Worker, Trespasser, Resident Farmer (onsite), Resident Gardener, Recreational User, Outdoor Worker and an Offsite Resident Farmer. The RESRAD (Version 6.5) and RESRAD-OFFSITE (Version 2.5) computer codes were used for the peak dose assessments. Deterministic peak dose assessments were performed for all the receptors and a probabilistic dose assessment was performed only for the Offsite Resident Farmer at the request of the DOE-PPPO. In a deterministic analysis, a single input value results in a single output value. In other words, a deterministic analysis uses single parameter values for every variable in the code. By contrast, a probabilistic approach assigns parameter ranges to certain variables, and the code randomly selects the values for each variable from the parameter range each time it calculates the dose (NRC 2006). The receptor scenarios, computer codes and parameter input files were previously used in ORISE 2012. A few modifications were made to the parameter input files as appropriate for this effort. Some of these changes

  3. Cost-effective retrofit technology for reducing peak power demand in small and medium commercial buildings

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

    Nutaro, James J.; Fugate, David L.; Kuruganti, Teja; Sanyal, Jibonananda; Starke, Michael R.

    2015-05-27

    We describe a cost-effective retrofit technology that uses collective control of multiple rooftop air conditioning units to reduce the peak power consumption of small and medium commercial buildings. The proposed control uses a model of the building and air conditioning units to select an operating schedule for the air conditioning units that maintains a temperature set point subject to a constraint on the number of units that may operate simultaneously. A prototype of this new control system was built and deployed in a large gymnasium to coordinate four rooftop air conditioning units. Based on data collected while operating this prototype,more » we estimate that the cost savings achieved by reducing peak power consumption is sufficient to repay the cost of the prototype within a year.« less

  4. Cost-effective retrofit technology for reducing peak power demand in small and medium commercial buildings

    SciTech Connect (OSTI)

    Nutaro, James J.; Fugate, David L.; Kuruganti, Teja; Sanyal, Jibonananda; Starke, Michael R.

    2015-05-27

    We describe a cost-effective retrofit technology that uses collective control of multiple rooftop air conditioning units to reduce the peak power consumption of small and medium commercial buildings. The proposed control uses a model of the building and air conditioning units to select an operating schedule for the air conditioning units that maintains a temperature set point subject to a constraint on the number of units that may operate simultaneously. A prototype of this new control system was built and deployed in a large gymnasium to coordinate four rooftop air conditioning units. Based on data collected while operating this prototype, we estimate that the cost savings achieved by reducing peak power consumption is sufficient to repay the cost of the prototype within a year.

  5. Report number codes

    SciTech Connect (OSTI)

    Nelson, R.N.

    1985-05-01

    This publication lists all report number codes processed by the Office of Scientific and Technical Information. The report codes are substantially based on the American National Standards Institute, Standard Technical Report Number (STRN)-Format and Creation Z39.23-1983. The Standard Technical Report Number (STRN) provides one of the primary methods of identifying a specific technical report. The STRN consists of two parts: The report code and the sequential number. The report code identifies the issuing organization, a specific program, or a type of document. The sequential number, which is assigned in sequence by each report issuing entity, is not included in this publication. Part I of this compilation is alphabetized by report codes followed by issuing installations. Part II lists the issuing organization followed by the assigned report code(s). In both Parts I and II, the names of issuing organizations appear for the most part in the form used at the time the reports were issued. However, for some of the more prolific installations which have had name changes, all entries have been merged under the current name.

  6. Fact #738: July 30, 2012 Number of New Light Vehicle Dealerships Decreasing

    Office of Energy Efficiency and Renewable Energy (EERE)

    The number of franchised new light vehicle dealerships peaked in 1949 with more than 49,000 dealers. By 2012, the number is less than half of that – 17,540 dealers.

  7. Quantum random number generation

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

    Ma, Xiongfeng; Yuan, Xiao; Cao, Zhu; Zhang, Zhen; Qi, Bing

    2016-06-28

    Here, quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness -- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at amore » high speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.« less

  8. ALARA notes, Number 8

    SciTech Connect (OSTI)

    Khan, T.A.; Baum, J.W.; Beckman, M.C.

    1993-10-01

    This document contains information dealing with the lessons learned from the experience of nuclear plants. In this issue the authors tried to avoid the `tyranny` of numbers and concentrated on the main lessons learned. Topics include: filtration devices for air pollution abatement, crack repair and inspection, and remote handling equipment.

  9. Saving Power at Peak Hours (LBNL Science at the Theater)

    ScienceCinema (OSTI)

    Piette, Mary Ann

    2011-04-28

    California needs new, responsive, demand-side energy technologies to ensure that periods of tight electricity supply on the grid don't turn into power outages. Led by Berkeley Lab's Mary Ann Piette, the California Energy Commission (through its Public Interest Energy Research Program) has established a Demand Response Research Center that addresses two motivations for adopting demand responsiveness: reducing average electricity prices and preventing future electricity crises. The research seeks to understand factors that influence "what works" in Demand Response. Piette's team is investigating the two types of demand response, load response and price response, that may influence and reduce the use of peak electric power through automated controls, peak pricing, advanced communications, and other strategies.

  10. Reducing Peak Demand to Defer Power Plant Construction in Oklahoma

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

    Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Located in the heart of "Tornado Alley," Oklahoma Gas & Electric Company's (OG&E) electric grid faces significant challenges from severe weather, hot summers, and about 2% annual load growth. To better control costs and manage electric reliability under these conditions, OG&E is pursuing demand response strategies made possible by implementation of smart grid technologies, tools, and techniques from

  11. Desert Peak East EGS Project; 2010 Geothermal Technology Program Peer

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

    Review Report | Department of Energy East EGS Project; 2010 Geothermal Technology Program Peer Review Report Desert Peak East EGS Project; 2010 Geothermal Technology Program Peer Review Report DOE 2010 Geothermal Technologies Program Peer Review egs_008_zemach.pdf (182.67 KB) More Documents & Publications Feasibility of EGS Development at Bradys Hot Springs, Nevada Concept Testing and Development at the Raft River Geothermal Field, Idaho Creation of an Enhanced Geothermal System

  12. EA-2023: Crossman Peak Communications Facility; Mohave County, Arizona

    Broader source: Energy.gov [DOE]

    Western Area Power Administration is preparing an EA that assesses the potential environmental impacts of a proposed new microwave communication facility to be located adjacent to a privately-owned one near Crossman Peak, east of Lake Havasu City in Mohave County, Arizona. The proposal would consist of a microwave communication facility, an access road, and an approximately 8-mile electrical service distribution line across private land and land administered by the Bureau of Land Management.

  13. Material Handling Fuel Cells for Building Electric Peak Shaving Applications

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

    Material Handling Fuel Cells for Building Electric Peak Shaving Applications U.S. Department of Energy Fuel Cell Technologies Office August 11, 2015 Presenter: Michael Penev of NREL DOE Host: Pete Devlin 2 Question and Answer * Please type your question into the question box hydrogenandfuelcells.energy.gov 3 Acknowledgments Fuel Cell Technologies Office, DOE EERE For providing funding for this project and for supporting sustainable hydrogen technology development through analysis, demonstration,

  14. Deconvolution of mixed gamma emitters using peak parameters

    SciTech Connect (OSTI)

    Gadd, Milan S; Garcia, Francisco; Magadalena, Vigil M

    2011-01-14

    When evaluating samples containing mixtures of nuclides using gamma spectroscopy the situation sometimes arises where the nuclides present have photon emissions that cannot be resolved by the detector. An example of this is mixtures of {sup 241}Am and plutonium that have L x-ray emissions with slightly different energies which cannot be resolved using a high-purity germanium detector. It is possible to deconvolute the americium L x-rays from those plutonium based on the {sup 241}Am 59.54 keV photon. However, this requires accurate knowledge of the relative emission yields. Also, it often results in high uncertainties in the plutonium activity estimate due to the americium yields being approximately an order of magnitude greater than those for plutonium. In this work, an alternative method of determining the relative fraction of plutonium in mixtures of {sup 241}Am and {sup 239}Pu based on L x-ray peak location and shape parameters is investigated. The sensitivity and accuracy of the peak parameter method is compared to that for conventional peak decovolution.

  15. Document Details Document Number

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

    Document Details Document Number Date of Document Document Title/Description [Links below to each document] D195066340 Not listed. N/A REVISIONS IN STRATIGRAPHIC NOMENCLATURE OF COLUMBIA RIVER BASALT GROUP D196000240 Not listed. N/A EPA DENIAL OF LINER LEACHATE COLLECTION SYSTEM REQUIREMENTS D196005916 Not listed. N/A LATE CENOZOIC STRATIGRAPHY AND TECTONIC EVOLUTION WITHIN SUBSIDING BASIN SOUTH CENTRAL WASHINGTON D196025993 RHO-BWI-ST-14 N/A SUPRABASALT SEDIMENTS OF COLD CREEK SYNCLINE AREA

  16. Fossil fuel-fired peak heating for geothermal greenhouses

    SciTech Connect (OSTI)

    Rafferty, K.

    1997-01-01

    Greenhouses are a major application of low-temperature geothermal resources. In virtually all operating systems, the geothermal fluid is used in a hot water heating system to meet 100% of both the peak and annual heating requirements of the structure. This strategy is a result of the relatively low costs associated with the development of most US geothermal direct-use resources and past tax credit programs which penalized systems using any conventional fuel sources. Increasingly, greenhouse operations will encounter limitations in available geothermal resource flow due either to production or disposal considerations. As a result, it will be necessary to operate additions at reduced water temperatures reflective of the effluent from the existing operations. Water temperature has a strong influence on heating system design. Greenhouse operators tend to have unequivocal preferences regarding heating system equipment. Many growers, particularly cut flower and bedding plant operators, prefer the {open_quotes}bare tube{close_quotes} type heating system. This system places small diameter plastic tubes under the benches or adjacent to the plants. Hot water is circulated through the tubes providing heat to the plants and the air in the greenhouse. Advantages include the ability to provide the heat directly to the plants, low cost, simple installation and the lack of a requirement for fans to circulate air. The major disadvantage of the system is poor performance at low (<140{degrees}F) water temperatures, particularly in cold climates. Under these conditions, the quantity of tubing required to meet the peak heating load is substantial. In fact, under some conditions, it is simply impractical to install sufficient tubing in the greenhouse to meet the peak heating load.

  17. REGULATION OF THE SPECTRAL PEAK IN GAMMA-RAY BURSTS

    SciTech Connect (OSTI)

    Beloborodov, Andrei M.

    2013-02-20

    Observations indicate that the peak of a gamma-ray burst spectrum forms in the opaque region of an ultrarelativistic jet. Recent radiative transfer calculations support this picture and show that the spectral peak is inherited from initially thermal radiation, which is changed by heating into a broad photon distribution with a high-energy tail. We discuss the processes that regulate the observed position of the spectral peak E {sub pk}. The opaque jet has three radial zones: (1) the Planck zone r < R {sub P} where a blackbody spectrum is enforced; this zone ends where the Thomson optical depth decreases to {tau} Almost-Equal-To 10{sup 5}, (2) the Wien zone R {sub P} < r < R {sub W} with a Kompaneets parameter y >> 1 where radiation has a Bose-Einstein spectrum, and (3) the Comptonization zone r > R {sub W} where the radiation spectrum develops a high-energy tail. Besides the initial jet temperature, an important factor regulating E {sub pk} is internal dissipation (of bulk motions and magnetic energy) at large distances from the central engine. Dissipation in the Planck zone reduces E {sub pk}, and dissipation in the Wien zone can increase E {sub pk}. In jets with subdominant magnetic fields, the predicted E {sub pk} varies around 1 MeV up to a maximum value of about 10 MeV. If the jet carries an energetically important magnetic field, E {sub pk} can be additionally increased by dissipation of magnetic energy. This increase is suggested by observations, which show E {sub pk} up to about 20 MeV. We also consider magnetically dominated jets; then a simple model of magnetic dissipation gives E {sub pk} Almost-Equal-To 30 {Gamma}{sub W} keV where {Gamma}{sub W} is the jet Lorentz factor at the Wien radius R {sub W}.

  18. Methods and apparatus for reducing peak wind turbine loads

    DOE Patents [OSTI]

    Moroz, Emilian Mieczyslaw

    2007-02-13

    A method for reducing peak loads of wind turbines in a changing wind environment includes measuring or estimating an instantaneous wind speed and direction at the wind turbine and determining a yaw error of the wind turbine relative to the measured instantaneous wind direction. The method further includes comparing the yaw error to a yaw error trigger that has different values at different wind speeds and shutting down the wind turbine when the yaw error exceeds the yaw error trigger corresponding to the measured or estimated instantaneous wind speed.

  19. Gasoline prices peak, expected to fall through end of 2016

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

    Gasoline prices peak, expected to fall through end of 2016 It's all downhill for U.S. drivers at least far as the outlook for gasoline prices is concerned. Gasoline prices are expected to gradually fall through the end of this year. In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular-grade gasoline averaged $2.37 per gallon in June. That's down 43 cents from the same month last year. The average monthly pump price is expected to drop to $2.01

  20. Modular redundant number systems

    SciTech Connect (OSTI)

    1998-05-31

    With the increased use of public key cryptography, faster modular multiplication has become an important cryptographic issue. Almost all public key cryptography, including most elliptic curve systems, use modular multiplication. Modular multiplication, particularly for the large public key modulii, is very slow. Increasing the speed of modular multiplication is almost synonymous with increasing the speed of public key cryptography. There are two parts to modular multiplication: multiplication and modular reduction. Though there are fast methods for multiplying and fast methods for doing modular reduction, they do not mix well. Most fast techniques require integers to be in a special form. These special forms are not related and converting from one form to another is more costly than using the standard techniques. To this date it has been better to use the fast modular reduction technique coupled with standard multiplication. Standard modular reduction is much more costly than standard multiplication. Fast modular reduction (Montgomery`s method) reduces the reduction cost to approximately that of a standard multiply. Of the fast multiplication techniques, the redundant number system technique (RNS) is one of the most popular. It is simple, converting a large convolution (multiply) into many smaller independent ones. Not only do redundant number systems increase speed, but the independent parts allow for parallelization. RNS form implies working modulo another constant. Depending on the relationship between these two constants; reduction OR division may be possible, but not both. This paper describes a new technique using ideas from both Montgomery`s method and RNS. It avoids the formula problem and allows fast reduction and multiplication. Since RNS form is used throughout, it also allows the entire process to be parallelized.

  1. Gamma Log At Silver Peak Area (DOE GTP) | Open Energy Information

    Open Energy Info (EERE)

    Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Gamma Log At Silver Peak Area (DOE GTP) Exploration Activity Details...

  2. Neutron Log At Silver Peak Area (DOE GTP) | Open Energy Information

    Open Energy Info (EERE)

    Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Neutron Log At Silver Peak Area (DOE GTP) Exploration Activity Details...

  3. Slim Holes At Silver Peak Area (DOE GTP) | Open Energy Information

    Open Energy Info (EERE)

    Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Slim Holes At Silver Peak Area (DOE GTP) Exploration Activity Details...

  4. Core Analysis At Silver Peak Area (DOE GTP) | Open Energy Information

    Open Energy Info (EERE)

    Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Core Analysis At Silver Peak Area (DOE GTP) Exploration Activity...

  5. 2-M Probe At Silver Peak Area (DOE GTP) | Open Energy Information

    Open Energy Info (EERE)

    GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: 2-M Probe At Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak...

  6. InSAR At Desert Peak Area (Laney, 2005) | Open Energy Information

    Open Energy Info (EERE)

    United States by developing basic measurements and interpretations that will assist reservoir management and expansion at Bradys, Desert Peak and the Desert Peak EGS study...

  7. Rock Density At Silver Peak Area (DOE GTP) | Open Energy Information

    Open Energy Info (EERE)

    to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Rock Density At Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area...

  8. Density Log at Silver Peak Area (DOE GTP) | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Density Log at Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak...

  9. Flow Test At Silver Peak Area (DOE GTP) | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Flow Test At Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area...

  10. ,"Table 3A.1. January Monthly Peak Hour Demand, by North American...

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

    A.1. January Monthly Peak Hour Demand, by North American Electric Reliability Corporation ... February Monthly Peak Hour Demand, by North American Electric Reliability Corporation ...

  11. ,"Table 3B.1. FRCC Monthly Peak Hour Demand, by North American...

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

    B.1. FRCC Monthly Peak Hour Demand, by North American Electric Reliability Corporation ... 3B.2. NPCC Monthly Peak Hour Demand, by North American Electric Reliability Corporation ...

  12. AlphaSpectrum ASPECT analysis code for background correction & peak integration

    Energy Science and Technology Software Center (OSTI)

    2005-04-13

    The ASPECT code provides a means for rapid analysis of energy-resolved spectra obtained by multi-channel pulse-height analysis (MCA) during (or after) counting of alpha-emissions from a filter air sample (or other suitably prepared sample) utilizing a solid-state detector, or other detector having sufficient energy resolution indiviual radioisotope peaks indentified in a spectrum are fitted using a peak shape algorithm by non-linear least-square fitting procedures that minimize Chi-square differences between the data and a fitted peakmore » function. The code accomplishes the identification of all significant peaks present in the spectrum with automatic recalibration to the 7.68 Po-214 alpha peak from the Radon-222 decay chain, the subtraction of all radon progeny interference overlaps with lower energy peaks in the energy range of Pu-238, Am-241, Pu-239, and U-234/Th-232, and the integration of the counts in any peak identified for these transuranic radionuclides. The output is therefore in the form of isotope specific net transuranic CPM, DPM or concentration, available in near real-time during air sampling. In this "copyright" version, the assumption is made that the alpha spectra to be analyzed have been stored by unique name in sequential form: "FileName(i)", where "FileName" can be any name and i is the index number of the file saved (e.g., i = 1,2, ..., n). this format is one automatically generated by the alpha Environmental Continuous Air Monitor (ECAM), developed by Los Alamos National Laboratory, and manufactured by Canberra Industries, a Laboratory Industrial Partner for this technology. It is assumed in this version of the code that the alpha spectrum data are stored in a 256 channel spectrum, although a larger num ber of channels could be easily accommodated by small code changes. The ECAM data output format is RADNET compliant (an inidustry standard developed at Los Alamos), and include, in addition to a 256-channel alpha spectrum, data on the

  13. AlphaSpectrum ASPECT analysis code for background correction & peak integration

    Energy Science and Technology Software Center (OSTI)

    2005-04-13

    The ASPECT code provides a means for rapid analysis of energy-resolved spectra obtained by multi-channel pulse-height analysis (MCA) during (or after) counting of alpha-emissions from a filter air sample (or other suitably prepared sample) utilizing a solid-state detector, or other detector having sufficient energy resolution indiviual radioisotope peaks indentified in a spectrum are fitted using a peak shape algorithm by non-linear least-square fitting procedures that minimize Chi-square differences between the data and a fitted peakmorefunction. The code accomplishes the identification of all significant peaks present in the spectrum with automatic recalibration to the 7.68 Po-214 alpha peak from the Radon-222 decay chain, the subtraction of all radon progeny interference overlaps with lower energy peaks in the energy range of Pu-238, Am-241, Pu-239, and U-234/Th-232, and the integration of the counts in any peak identified for these transuranic radionuclides. The output is therefore in the form of isotope specific net transuranic CPM, DPM or concentration, available in near real-time during air sampling. In this "copyright" version, the assumption is made that the alpha spectra to be analyzed have been stored by unique name in sequential form: "FileName(i)", where "FileName" can be any name and i is the index number of the file saved (e.g., i = 1,2, ..., n). this format is one automatically generated by the alpha Environmental Continuous Air Monitor (ECAM), developed by Los Alamos National Laboratory, and manufactured by Canberra Industries, a Laboratory Industrial Partner for this technology. It is assumed in this version of the code that the alpha spectrum data are stored in a 256 channel spectrum, although a larger num ber of channels could be easily accommodated by small code changes. The ECAM data output format is RADNET compliant (an inidustry standard developed at Los Alamos), and include, in addition to a 256-channel alpha spectrum, data on the count

  14. Evidence is growing on demand side of an oil peak

    SciTech Connect (OSTI)

    2009-07-15

    After years of continued growth, the number of miles driven by Americans started falling in December 2007. Not only are the number of miles driven falling, but as cars become more fuel efficient, they go further on fewer gallons - further reducing demand for gasoline. This trend is expected to accelerate. Drivers include, along with higher-efficiency cars, mass transit, reversal in urban sprawl, biofuels, and plug-in hybrid vehicles.

  15. New Hampshire Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Consumers (Number of Elements) New Hampshire Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  16. New Hampshire Natural Gas Number of Industrial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Industrial Consumers (Number of Elements) New Hampshire Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  17. New Hampshire Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) New Hampshire Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  18. Virginia Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  19. Utah Natural Gas Number of Industrial Consumers (Number of Elements...

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

    Industrial Consumers (Number of Elements) Utah Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  20. Wisconsin Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) Wisconsin Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  1. Virginia Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  2. Utah Natural Gas Number of Residential Consumers (Number of Elements...

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

    Residential Consumers (Number of Elements) Utah Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  3. Vermont Natural Gas Number of Residential Consumers (Number of...

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

    Residential Consumers (Number of Elements) Vermont Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  4. Utah Natural Gas Number of Commercial Consumers (Number of Elements...

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

    Commercial Consumers (Number of Elements) Utah Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  5. Virginia Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  6. West Virginia Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) West Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  7. Wisconsin Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Wisconsin Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  8. Vermont Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) Vermont Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  9. West Virginia Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) West Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  10. Washington Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) Washington Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  11. Washington Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Washington Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  12. Washington Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) Washington Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  13. Wisconsin Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) Wisconsin Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  14. Vermont Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Vermont Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  15. West Virginia Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) West Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  16. New York Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) New York Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  17. New Mexico Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Residential Consumers (Number of Elements) New Mexico Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  18. New Jersey Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Residential Consumers (Number of Elements) New Jersey Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  19. New Mexico Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) New Mexico Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  20. North Carolina Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) North Carolina Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  1. North Carolina Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) North Carolina Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  2. North Dakota Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) North Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  3. North Dakota Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) North Dakota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  4. North Carolina Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) North Carolina Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  5. XRD acquisition parameters for detection of weak peaks

    SciTech Connect (OSTI)

    Seabaugh, P.W.; Sullenger, D.B.; Hudgens, C.R.; Nichols, M.C.; Boehme, D.R.; Sandia National Labs., Albuquerque, NM )

    1989-01-01

    The use of high intensity x-ray sources provides opportunities as well as special problems in the detection of minor XRD peaks. Scattering contributions from slits along with other factors can become important and may interfere with the analysis. This further complexity can best be resolved by using nonconventional data collection and analysis strategies. To study these factors, an experimental design plan was formulated and implemented which was used to determine operating parameters for a high intensity x-ray diffraction unit. Major issues studied included the extraction of a weak signal from a noisy background, the reduction of background noise, the volume of data to be collected, the time allocated for background characterization, the control sample, and the impact of the quality'' of the sample. 4 figs.

  6. New runners to boost peak output at Niagara Falls

    SciTech Connect (OSTI)

    Reason, J.

    1990-01-01

    Retrofitted Francis turbines will improve the value of power generated from Niagara Falls by increasing the peak output of the hydroturbine units at the Robert Moses hydroelectric plant. The computer-designed runners are expected to add 330 MW to the peak capacity of the 28-yr-old plant and significantly increase the efficiency at high flow rates. Next year, the first new runner will be retrofit to the highly instrumented Unit 4. If the retrofit unit meets it increased-performance expectations, the other 12 units will be upgraded between 1993 and 1998. The work is part of an overall expansion of the Niagara Power Project designed to made better use of the power value of Niagara river water, within the constraints of a treaty with Canada and the scenic value of the falls. These constraints, together with varying flows and heads, introduced enormous complexities into the selection and design of the new runners. The alterations being made to Unit 4, in addition to replacing the turbine runner, include modifying the draft tube-liners, increasing the wicket-gate stroke, replacing the turbine discharge ring (to accommodate longer blades), making various electrical modifications to the generator, and replacing the transformer. But the key to the retrofit is the computer-designed runner. Charles Grose, senior project manager, New York Power Authority, White Plains, NY, emphasizes that such computer design techniques were not available a few years ago; neither were the computer-controlled machining techniques necessary to manufacture the new runners. Other aspects of the upgrading that were analyzed include runner stability, resonance, shaft torsional stress, and runaway speed.

  7. Modeling of GE Appliances in GridLAB-D: Peak Demand Reduction

    SciTech Connect (OSTI)

    Fuller, Jason C.; Vyakaranam, Bharat GNVSR; Prakash Kumar, Nirupama; Leistritz, Sean M.; Parker, Graham B.

    2012-04-29

    The widespread adoption of demand response enabled appliances and thermostats can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. GE has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information from the utility grid, often in the form of price. However due to a number of factors, including the number of demand response enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors can be modeled and simulated in open-source software, GridLAB-D, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. This report is the first in a series of three reports describing the potential of GE's demand response enabled appliances to provide benefits to the utility grid. The first report will describe the modeling methodology used to represent the GE appliances in the GridLAB-D simulation environment and the estimated potential for peak demand reduction at various deployment levels. The second and third reports will explore the potential of aggregated group actions to positively impact grid stability, including frequency and voltage regulation and spinning reserves, and the impacts on distribution feeder voltage regulation, including mitigation of fluctuations caused by high penetration of photovoltaic distributed generation and the effects on volt-var control schemes.

  8. Calculating survival curves in spread-peaks of heavy ion beams and comparison with experiment

    SciTech Connect (OSTI)

    Curtis, S.B.; Chu, W.T.; Llacer, J.; Renner, T.R.; Rodriguez, A.; Yang, T.C.H.

    1995-08-01

    In preparing for treating patients with high-energy ion beams, it is important first to determine the composition of the beam, that is, the relative mixes of the various primary and secondary particles and their LET spectra, and secondly to estimate the cell killing expected during a treatment schedule. This requires measurements of the beam composition at various depths through the spread-peak region, and a calculation of cell survival using a cell-killing model designed to accommodate the mixed LET nature of the beam in the spread-peak region. This talk presents results of an experiment in which a particle identification telescope, the BEPKLET, was used to measure the LET spectra of the primary and secondary particles at two positions in a 12-cm-spread-peak of a 585 MeV/amu neon ion beam at the Bevalac. Cell survival measurements were made at the same positions at which the LET-spectra were measured. The survival curves obtained were compared with calculations using the LPL (Lethal, Potentially Lethal) model of cell-killing. Results agree quite well at doses up to about 4 Gy. A quantity proportional to the RBE at 10% survival, when plotted against dose-averaged LET for a number of different beams and energies, appears to be a fairly good predictor of biological effect. This would not be expected if the difference in biological effect due to differences in track structure between various ions at the same LET played a significant role in modifying cell-killing in the range of LETs covered by this experiment.

  9. Peak Ground Velocities for Seismic Events at Yucca Mountain, Nevada

    SciTech Connect (OSTI)

    K. Coppersmith; R. Quittmeyer

    2005-02-16

    This report describes a scientific analysis to bound credible horizontal peak ground velocities (PGV) for the repository waste emplacement level at Yucca Mountain. Results are presented as a probability distribution for horizontal PGV to represent uncertainties in the analysis. The analysis also combines the bound to horizontal PGV with results of ground motion site-response modeling (BSC 2004 [DIRS 170027]) to develop a composite hazard curve for horizontal PGV at the waste emplacement level. This result provides input to an abstraction of seismic consequences (BSC 2004 [DIRS 169183]). The seismic consequence abstraction, in turn, defines the input data and computational algorithms for the seismic scenario class of the total system performance assessment (TSPA). Planning for the analysis is documented in Technical Work Plan TWP-MGR-GS-000001 (BSC 2004 [DIRS 171850]). The bound on horizontal PGV at the repository waste emplacement level developed in this analysis complements ground motions developed on the basis of PSHA results. In the PSHA, ground motion experts characterized the epistemic uncertainty and aleatory variability in their ground motion interpretations. To characterize the aleatory variability they used unbounded lognormal distributions. As a consequence of these characterizations, as seismic hazard calculations are extended to lower and lower annual frequencies of being exceeded, the ground motion level increases without bound, eventually reaching levels that are not credible (Corradini 2003 [DIRS 171191]). To provide credible seismic inputs for TSPA, in accordance with 10 Code of Federal Regulations (CFR) 63.102(j) [DIRS 156605], this complementary analysis is carried out to determine reasonable bounding values of horizontal PGV at the waste emplacement level for annual frequencies of exceedance as low as 10{sup -8}. For each realization of the TSPA seismic scenario, the results of this analysis provide a constraint on the values sampled from the

  10. Nuclear Hydrogen for Peak Electricity Production and Spinning Reserve

    SciTech Connect (OSTI)

    Forsberg, C.W.

    2005-01-20

    Nuclear energy can be used to produce hydrogen. The key strategic question is this: ''What are the early markets for nuclear hydrogen?'' The answer determines (1) whether there are incentives to implement nuclear hydrogen technology today or whether the development of such a technology could be delayed by decades until a hydrogen economy has evolved, (2) the industrial partners required to develop such a technology, and (3) the technological requirements for the hydrogen production system (rate of production, steady-state or variable production, hydrogen purity, etc.). Understanding ''early'' markets for any new product is difficult because the customer may not even recognize that the product could exist. This study is an initial examination of how nuclear hydrogen could be used in two interconnected early markets: the production of electricity for peak and intermediate electrical loads and spinning reserve for the electrical grid. The study is intended to provide an initial description that can then be used to consult with potential customers (utilities, the Electric Power Research Institute, etc.) to better determine the potential real-world viability of this early market for nuclear hydrogen and provide the starting point for a more definitive assessment of the concept. If this set of applications is economically viable, it offers several unique advantages: (1) the market is approximately equivalent in size to the existing nuclear electric enterprise in the United States, (2) the entire market is within the utility industry and does not require development of an external market for hydrogen or a significant hydrogen infrastructure beyond the utility site, (3) the technology and scale match those of nuclear hydrogen production, (4) the market exists today, and (5) the market is sufficient in size to justify development of nuclear hydrogen production techniques independent of the development of any other market for hydrogen. These characteristics make it an ideal

  11. Peak fitting applied to low-resolution enrichment measurements

    SciTech Connect (OSTI)

    Bracken, D.; McKown, T.; Sprinkle, J.K. Jr.; Gunnink, R.; Kartoshov, M.; Kuropatwinski, J.; Raphina, G.; Sokolov, G.

    1998-12-01

    Materials accounting at bulk processing facilities that handle low enriched uranium consists primarily of weight and uranium enrichment measurements. Most low enriched uranium processing facilities draw separate materials balances for each enrichment handled at the facility. The enrichment measurement determines the isotopic abundance of the {sup 235}U, thereby determining the proper strata for the item, while the weight measurement generates the primary accounting value for the item. Enrichment measurements using the passive gamma radiation from uranium were developed for use in US facilities a few decades ago. In the US, the use of low-resolution detectors was favored because they cost less, are lighter and more robust, and don`t require the use of liquid nitrogen. When these techniques were exported to Europe, however, difficulties were encountered. Two of the possible root causes were discovered to be inaccurate knowledge of the container wall thickness and higher levels of minor isotopes of uranium introduced by the use of reactor returns in the enrichment plants. the minor isotopes cause an increase in the Compton continuum under the 185.7 keV assay peak and the observance of interfering 238.6 keV gamma rays. The solution selected to address these problems was to rely on the slower, more costly, high-resolution gamma ray detectors when the low-resolution method failed. Recently, these gamma ray based enrichment measurement techniques have been applied to Russian origin material. The presence of interfering gamma radiation from minor isotopes was confirmed. However, with the advent of fast portable computers, it is now possible to apply more sophisticated analysis techniques to the low-resolution data in the field. Explicit corrections for Compton background, gamma rays from {sup 236}U daughters, and the attenuation caused by thick containers can be part of the least squares fitting routine. Preliminary results from field measurements in Kazakhstan will be

  12. Number

    Office of Legacy Management (LM)

    engaged in the production of thorium compounds. The purpose of the trip vas to: l 1. Learn the type of chemical processes employed in the thorium industry (thorium nitrate). 2. ...

  13. Back-Up/ Peak Shaving Fuel Cell System

    SciTech Connect (OSTI)

    Staudt, Rhonda L.

    2008-05-28

    This Final Report covers the work executed by Plug Power from 8/11/03 10/31/07 statement of work for Topic 2: advancing the state of the art of fuel cell technology with the development of a new generation of commercially viable, stationary, Back-up/Peak-Shaving fuel cell systems, the GenCore II. The Program cost was $7.2 M with the Department of Energy share being $3.6M and Plug Powers share being $3.6 M. The Program started in August of 2003 and was scheduled to end in January of 2006. The actual program end date was October of 2007. A no cost extension was grated. The Department of Energy barriers addressed as part of this program are: Technical Barriers for Distributed Generation Systems: o Durability o Power Electronics o Start up time Technical Barriers for Fuel Cell Components: o Stack Material and Manufacturing Cost o Durability o Thermal and water management Background The next generation GenCore backup fuel cell system to be designed, developed and tested by Plug Power under the program is the first, mass-manufacturable design implementation of Plug Powers GenCore architected platform targeted for battery and small generator replacement applications in the telecommunications, broadband and UPS markets. The next generation GenCore will be a standalone, H2 in-DC-out system. In designing the next generation GenCore specifically for the telecommunications market, Plug Power is teaming with BellSouth Telecommunications, Inc., a leading industry end user. The final next generation GenCore system is expected to represent a market-entry, mass-manufacturable and economically viable design. The technology will incorporate: A cost-reduced, polymer electrolyte membrane (PEM) fuel cell stack tailored to hydrogen fuel use An advanced electrical energy storage system A modular, scalable power conditioning system tailored to market requirements A scaled-down, cost-reduced balance of plant (BOP) Network Equipment Building Standards (NEBS), UL and CE

  14. Peak CO2? China's Emissions Trajectories to 2050

    SciTech Connect (OSTI)

    Zhou, Nan; Fridley, David G.; McNeil, Michael; Zheng, Nina; Ke, Jing; Levine, Mark

    2011-05-01

    As a result of soaring energy demand from a staggering pace of economic growth and the related growth of energy-intensive industry, China overtook the United States to become the world's largest contributor to CO{sub 2} emissions in 2007. At the same time, China has taken serious actions to reduce its energy and carbon intensity by setting both short-term energy intensity reduction goal for 2006 to 2010 as well as long-term carbon intensity reduction goal for 2020. This study focuses on a China Energy Outlook through 2050 that assesses the role of energy efficiency policies in transitioning China to a lower emission trajectory and meeting its intensity reduction goals. In the past years, LBNL has established and significantly enhanced the China End-Use Energy Model based on the diffusion of end-use technologies and other physical drivers of energy demand. This model presents an important new approach for helping understand China's complex and dynamic drivers of energy consumption and implications of energy efficiency policies through scenario analysis. A baseline ('Continued Improvement Scenario') and an alternative energy efficiency scenario ('Accelerated Improvement Scenario') have been developed to assess the impact of actions already taken by the Chinese government as well as planned and potential actions, and to evaluate the potential for China to control energy demand growth and mitigate emissions. It is a common belief that China's CO{sub 2} emissions will continue to grow throughout this century and will dominate global emissions. The findings from this research suggest that this will not likely be the case because of saturation effects in appliances, residential and commercial floor area, roadways, railways, fertilizer use, and urbanization will peak around 2030 with slowing population growth. The baseline and alternative scenarios also demonstrate that the 2020 goals can be met and underscore the significant role that policy-driven energy efficiency

  15. Technical Basis for Peak Reactivity Burnup Credit for BWR Spent Nuclear Fuel in Storage and Transportation Systems

    SciTech Connect (OSTI)

    Marshall, William BJ J; Ade, Brian J; Bowman, Stephen M; Gauld, Ian C; Ilas, Germina; Mertyurek, Ugur; Radulescu, Georgeta

    2015-01-01

    Oak Ridge National Laboratory and the United States Nuclear Regulatory Commission have initiated a multiyear project to investigate application of burnup credit for boiling-water reactor (BWR) fuel in storage and transportation casks. This project includes two phases. The first phase (1) investigates applicability of peak reactivity methods currently used in spent fuel pools (SFPs) to storage and transportation systems and (2) evaluates validation of both reactivity (keff) calculations and burnup credit nuclide concentrations within these methods. The second phase will focus on extending burnup credit beyond peak reactivity. This paper documents the first phase, including an analysis of lattice design parameters and depletion effects, as well as both validation components. Initial efforts related to extended burnup credit are discussed in a companion paper. Peak reactivity analyses have been used in criticality analyses for licensing of BWR fuel in SFPs over the last 20 years. These analyses typically combine credit for the gadolinium burnable absorber present in the fuel with a modest amount of burnup credit. Gadolinium burnable absorbers are used in BWR assemblies to control core reactivity. The burnable absorber significantly reduces assembly reactivity at beginning of life, potentially leading to significant increases in assembly reactivity for burnups less than 15–20 GWd/MTU. The reactivity of each fuel lattice is dependent on gadolinium loading. The number of gadolinium-bearing fuel pins lowers initial lattice reactivity, but it has a small impact on the burnup and reactivity of the peak. The gadolinium concentration in each pin has a small impact on initial lattice reactivity but a significant effect on the reactivity of the peak and the burnup at which the peak occurs. The importance of the lattice parameters and depletion conditions are primarily determined by their impact on the gadolinium depletion. Criticality code validation for BWR burnup

  16. Production of Hydrogen at the Forecourt Using Off-Peak Electricity: June 2005 (Milestone Report)

    SciTech Connect (OSTI)

    Levene, J. I.

    2007-02-01

    This milestone report provides information about the production of hydrogen at the forecourt using off-peak electricity as well as the Hydrogen Off-Peak Electricity (HOPE) model.

  17. HOPE Release 3 Pitch Angle Sneak Peak (Technical Report) | SciTech...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: HOPE Release 3 Pitch Angle Sneak Peak Citation Details In-Document Search Title: HOPE Release 3 Pitch Angle Sneak Peak This report describes how the HOPE ...

  18. Alaska Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Alaska Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10 11 8 1990's 8 8 10 11 11 9 202 7 7 9 2000's 9 8 9 9 10 12 11 11 6 3 2010's 3 5 3 3 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Number of Natural

  19. Hawaii Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Hawaii Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 27 26 29 2000's 28 28 29 29 29 28 26 27 27 25 2010's 24 24 22 22 23 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Number of Natural Gas Industrial

  20. WE-D-BRF-02: Acoustic Signal From the Bragg Peak for Range Verification in Proton Therapy

    SciTech Connect (OSTI)

    Reinhardt, S; Assmann, W; Fink, A; Thirolf, P; Parodi, K; Kellnberger, S; Omar, M; Ntziachristos, V; Gaebisch, C; Moser, M; Dollinger, G; Sergiadis, G

    2014-06-15

    Purpose: Range verification in ion beam therapy relies to date on nuclear imaging techniques which require complex and costly detector systems. A different approach is the detection of thermoacoustic signals that are generated due to localized energy loss of ion beams. Aim of this work is to study the feasibility of determining the ion range with sub-mm accuracy by use of high frequency ultrasonic (US) transducers and to image the Bragg peak by tomography. Methods: A water phantom was irradiated by a pulsed 20 MeV proton beam with varying pulse intensity, length and repetition rate. The acoustic signal of single proton pulses was measured by different PZT-based US detectors (3.5 MHz and 10 MHz central frequencies). For tomography a 64 channel US detector array was used and moved along the ion track by a remotely controlled motor stage. Results: A clear signal of the Bragg peak was visible for an energy deposition as low as 10{sup 12} eV. The signal amplitude showed a linear increase with particle number per pulse and thus, dose. Range measurements were reproducible within +/? 20 micrometer and agreed well with Geant4 simulations. The tomographic reconstruction does not only allow to measure the ion range but also the beam spot size at the Bragg peak position. Conclusion: Range verification by acoustic means is a promising new technique for treatment modalities where the tumor can be localized by US imaging. Further improvement of sensitivity is required to account for higher attenuation of the US signal in tissue, as well as lower energy density in the Bragg peak in realistic treatment cases due to higher particle energy and larger spot sizes. Nevertheless, the acoustic range verification approach could offer the possibility of combining anatomical US imaging with Bragg Peak imaging in the near future. The work was funded by the DFG cluster of excellence Munich Centre for Advanced Photonics (MAP)

  1. ARM - Measurement - Particle number concentration

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

    number concentration ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Particle number concentration The number of particles present in any given volume of air. Categories Aerosols Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those

  2. Total Number of Operable Refineries

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

    Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge

  3. Compendium of Experimental Cetane Numbers

    SciTech Connect (OSTI)

    Yanowitz, J.; Ratcliff, M. A.; McCormick, R. L.; Taylor, J. D.; Murphy, M. J.

    2014-08-01

    This report is an updated version of the 2004 Compendium of Experimental Cetane Number Data and presents a compilation of measured cetane numbers for pure chemical compounds. It includes all available single compound cetane number data found in the scientific literature up until March 2014 as well as a number of unpublished values, most measured over the past decade at the National Renewable Energy Laboratory. This Compendium contains cetane values for 389 pure compounds, including 189 hydrocarbons and 201 oxygenates. More than 250 individual measurements are new to this version of the Compendium. For many compounds, numerous measurements are included, often collected by different researchers using different methods. Cetane number is a relative ranking of a fuel's autoignition characteristics for use in compression ignition engines; it is based on the amount of time between fuel injection and ignition, also known as ignition delay. The cetane number is typically measured either in a single-cylinder engine or a constant volume combustion chamber. Values in the previous Compendium derived from octane numbers have been removed, and replaced with a brief analysis of the correlation between cetane numbers and octane numbers. The discussion on the accuracy and precision of the most commonly used methods for measuring cetane has been expanded and the data has been annotated extensively to provide additional information that will help the reader judge the relative reliability of individual results.

  4. Table 8.12a Electric Noncoincident Peak Load and Capacity Margin: Summer Peak Period, 1986-2011 (Megawatts, Except as Noted)

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

    a Electric Noncoincident Peak Load and Capacity Margin: Summer Peak Period, 1986-2011 (Megawatts, Except as Noted) Year Noncoincident Peak Load 1 by North American Electric Reliability Corporation (NERC) 2 Regional Assessment Area Capacity Margin 21 (percent) Eastern Interconnection ERCOT 4 Western Inter- connection All Inter- connections FRCC 5 NPCC 6 Balance of Eastern Region 3 ECAR 7,8 MAAC 8,9 MAIN 8,10 MAPP 11 MISO 12 MRO 13 PJM 14 RFC 8,15 SERC 16 SPP 17 Subtotal TRE 18 WECC 19 Total 20

  5. Maine Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Maine Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 73 73 74 1990's 80 81 80 66 89 74 87 81 110 108 2000's 178 233 66 65 69 69 73 76 82 85 2010's 94 102 108 120 126 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring

  6. Montana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Montana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 435 435 428 1990's 457 452 459 462 453 463 466 462 454 397 2000's 71 73 439 412 593 716 711 693 693 396 2010's 384 381 372 372 369 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  7. Wyoming Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Wyoming Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 190 200 230 1990's 284 228 244 194 135 126 170 194 317 314 2000's 308 295 877 179 121 127 133 133 155 130 2010's 120 123 127 132 131 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  8. Nevada Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Nevada Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 93 98 100 1990's 100 113 114 117 119 120 121 93 93 109 2000's 90 90 96 97 179 192 207 220 189 192 2010's 184 177 177 195 218 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016

  9. Arizona Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Arizona Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 358 344 354 1990's 526 532 532 526 519 530 534 480 514 555 2000's 526 504 488 450 414 425 439 395 383 390 2010's 368 371 379 383 386 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  10. Delaware Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Delaware Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241 233 235 1990's 240 243 248 249 252 253 250 265 257 264 2000's 297 316 182 184 186 179 170 185 165 112 2010's 114 129 134 138 141 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  11. Florida Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Florida Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 575 552 460 1990's 452 377 388 433 481 515 517 561 574 573 2000's 520 518 451 421 398 432 475 467 449 607 2010's 581 630 507 528 520 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  12. Idaho Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Idaho Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 219 132 64 1990's 62 65 66 75 144 167 183 189 203 200 2000's 217 198 194 191 196 195 192 188 199 187 2010's 184 178 179 183 189 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  13. Rhode Island Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Rhode Island Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,158 1,152 1,122 1990's 1,135 1,107 1,096 1,066 1,064 359 363 336 325 302 2000's 317 283 54 236 223 223 245 256 243 260 2010's 249 245 248 271 266 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  14. South Dakota Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) South Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 261 267 270 1990's 275 283 319 355 381 396 444 481 464 445 2000's 416 402 533 526 475 542 528 548 598 598 2010's 580 556 574 566 575 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016

  15. Offset-free rail-to-rail derandomizing peak detect-and-hold circuit

    DOE Patents [OSTI]

    DeGeronimo, Gianluigi; O'Connor, Paul; Kandasamy, Anand

    2003-01-01

    A peak detect-and-hold circuit eliminates errors introduced by conventional amplifiers, such as common-mode rejection and input voltage offset. The circuit includes an amplifier, three switches, a transistor, and a capacitor. During a detect-and-hold phase, a hold voltage at a non-inverting in put terminal of the amplifier tracks an input voltage signal and when a peak is reached, the transistor is switched off, thereby storing a peak voltage in the capacitor. During a readout phase, the circuit functions as a unity gain buffer, in which the voltage stored in the capacitor is provided as an output voltage. The circuit is able to sense signals rail-to-rail and can readily be modified to sense positive, negative, or peak-to-peak voltages. Derandomization may be achieved by using a plurality of peak detect-and-hold circuits electrically connected in parallel.

  16. Departmental Business Instrument Numbering System

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

    2005-01-27

    The Order prescribes the procedures for assigning identifying numbers to all Department of Energy (DOE) and National Nuclear Security Administration (NNSA) business instruments. Cancels DOE O 540.1. Canceled by DOE O 540.1B.

  17. Departmental Business Instrument Numbering System

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

    2000-12-05

    To prescribe procedures for assigning identifying numbers to all Department of Energy (DOE), including the National Nuclear Security Administration, business instruments. Cancels DOE 1331.2B. Canceled by DOE O 540.1A.

  18. Indiana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Indiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 116,571 119,458 122,803 1990's 124,919 128,223 129,973 131,925 134,336 137,162 139,097 140,515 141,307 145,631 2000's 148,411 148,830 150,092 151,586 151,943 159,649 154,322 155,885 157,223 155,615 2010's 156,557 161,293 158,213 158,965 159,596 - = No Data Reported; -- = Not Applicable; NA = Not

  19. Indiana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Indiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,497 5,696 6,196 1990's 6,439 6,393 6,358 6,508 6,314 6,250 6,586 6,920 6,635 19,069 2000's 10,866 9,778 10,139 8,913 5,368 5,823 5,350 5,427 5,294 5,190 2010's 5,145 5,338 5,204 5,178 5,098 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  20. Indiana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Indiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,250,476 1,275,401 1,306,747 1990's 1,327,772 1,358,640 1,377,023 1,402,770 1,438,483 1,463,640 1,489,647 1,509,142 1,531,914 1,570,253 2000's 1,604,456 1,613,373 1,657,640 1,644,715 1,588,738 1,707,195 1,661,186 1,677,857 1,678,158 1,662,663 2010's 1,669,026 1,707,148 1,673,132 1,681,841 1,693,267

  1. Iowa Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Iowa Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 80,797 81,294 82,549 1990's 83,047 84,387 85,325 86,452 86,918 88,585 89,663 90,643 91,300 92,306 2000's 93,836 95,485 96,496 96,712 97,274 97,767 97,823 97,979 98,144 98,416 2010's 98,396 98,541 99,113 99,017 99,182 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  2. Iowa Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Iowa Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,033 1,937 1,895 1990's 1,883 1,866 1,835 1,903 1,957 1,957 2,066 1,839 1,862 1,797 2000's 1,831 1,830 1,855 1,791 1,746 1,744 1,670 1,651 1,652 1,626 2010's 1,528 1,465 1,469 1,491 1,572 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  3. Iowa Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Iowa Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 690,532 689,655 701,687 1990's 706,842 716,088 729,081 740,722 750,678 760,848 771,109 780,746 790,162 799,015 2000's 812,323 818,313 824,218 832,230 839,415 850,095 858,915 865,553 872,980 875,781 2010's 879,713 883,733 892,123 895,414 900,420 - = No Data Reported; -- = Not Applicable; NA = Not

  4. Kansas Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Kansas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 82,934 83,810 85,143 1990's 85,539 86,874 86,840 87,735 86,457 88,163 89,168 85,018 89,654 86,003 2000's 87,007 86,592 87,397 88,030 86,640 85,634 85,686 85,376 84,703 84,715 2010's 84,446 84,874 84,673 84,969 85,867 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  5. Kansas Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Kansas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 4,440 4,314 4,366 1990's 4,357 3,445 3,296 4,369 3,560 3,079 2,988 7,014 10,706 5,861 2000's 8,833 9,341 9,891 9,295 8,955 8,300 8,152 8,327 8,098 7,793 2010's 7,664 7,954 7,970 7,877 7,429 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  6. Kansas Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Kansas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 725,676 733,101 731,792 1990's 747,081 753,839 762,545 777,658 773,357 797,524 804,213 811,975 841,843 824,803 2000's 833,662 836,486 843,353 850,464 855,272 856,761 862,203 858,304 853,125 855,454 2010's 853,842 854,730 854,800 858,572 861,092 - = No Data Reported; -- = Not Applicable; NA = Not

  7. Kentucky Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Kentucky Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 63,024 63,971 65,041 1990's 67,086 68,461 69,466 71,998 73,562 74,521 76,079 77,693 80,147 80,283 2000's 81,588 81,795 82,757 84,110 84,493 85,243 85,236 85,210 84,985 83,862 2010's 84,707 84,977 85,129 85,999 85,318 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  8. Kentucky Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Kentucky Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,391 1,436 1,443 1990's 1,544 1,587 1,608 1,585 1,621 1,630 1,633 1,698 1,864 1,813 2000's 1,801 1,701 1,785 1,695 1,672 1,698 1,658 1,599 1,585 1,715 2010's 1,742 1,705 1,720 1,767 1,780 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  9. Kentucky Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Kentucky Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 596,320 606,106 614,058 1990's 624,477 633,942 644,281 654,664 668,774 685,481 696,989 713,509 726,960 735,371 2000's 744,816 749,106 756,234 763,290 767,022 770,080 770,171 771,047 753,531 754,761 2010's 758,129 759,584 757,790 761,575 760,131 - = No Data Reported; -- = Not Applicable; NA = Not

  10. Louisiana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Louisiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 67,382 66,472 64,114 1990's 62,770 61,574 61,030 62,055 62,184 62,930 62,101 62,270 63,029 62,911 2000's 62,710 62,241 62,247 63,512 60,580 58,409 57,097 57,127 57,066 58,396 2010's 58,562 58,749 63,381 59,147 58,611 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  11. Louisiana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Louisiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,617 1,503 1,531 1990's 1,504 1,469 1,452 1,592 1,737 1,383 1,444 1,406 1,380 1,397 2000's 1,318 1,440 1,357 1,291 1,460 1,086 962 945 988 954 2010's 942 920 963 916 883 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  12. Louisiana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Louisiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 952,079 946,970 934,472 1990's 934,007 936,423 940,403 941,294 945,387 957,558 945,967 962,786 962,436 961,925 2000's 964,133 952,753 957,048 958,795 940,400 905,857 868,353 879,612 886,084 889,570 2010's 893,400 897,513 963,688 901,635 899,378 - = No Data Reported; -- = Not Applicable; NA = Not

  13. Maine Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Maine Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,435 3,731 3,986 1990's 4,250 4,455 4,838 4,979 5,297 5,819 6,414 6,606 6,662 6,582 2000's 6,954 6,936 7,375 7,517 7,687 8,178 8,168 8,334 8,491 8,815 2010's 9,084 9,681 10,179 11,415 11,810 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  14. Maine Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Maine Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 12,134 11,933 11,902 1990's 12,000 12,424 13,766 13,880 14,104 14,917 14,982 15,221 15,646 15,247 2000's 17,111 17,302 17,921 18,385 18,707 18,633 18,824 18,921 19,571 20,806 2010's 21,142 22,461 23,555 24,765 27,047 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  15. Maryland Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Maryland Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 51,252 53,045 54,740 1990's 55,576 61,878 62,858 63,767 64,698 66,094 69,991 69,056 67,850 69,301 2000's 70,671 70,691 71,824 72,076 72,809 73,780 74,584 74,856 75,053 75,771 2010's 75,192 75,788 75,799 77,117 77,846 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  16. Maryland Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Maryland Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,222 5,397 5,570 1990's 5,646 520 514 496 516 481 430 479 1,472 536 2000's 329 795 1,434 1,361 1,354 1,325 1,340 1,333 1,225 1,234 2010's 1,255 1,226 1,163 1,173 1,179 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  17. Maryland Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Maryland Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 755,294 760,754 767,219 1990's 774,707 782,373 894,677 807,204 824,137 841,772 871,012 890,195 901,455 939,029 2000's 941,384 959,772 978,319 987,863 1,009,455 1,024,955 1,040,941 1,053,948 1,057,521 1,067,807 2010's 1,071,566 1,077,168 1,078,978 1,099,272 1,101,292 - = No Data Reported; -- = Not

  18. Massachusetts Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Massachusetts Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 84,636 93,005 92,252 1990's 85,775 88,746 85,873 102,187 92,744 104,453 105,889 107,926 108,832 113,177 2000's 117,993 120,984 122,447 123,006 125,107 120,167 126,713 128,965 242,693 153,826 2010's 144,487 138,225 142,825 144,246 139,556 - = No Data Reported; -- = Not Applicable;

  19. Massachusetts Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Massachusetts Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,626 7,199 13,057 1990's 6,539 5,006 8,723 7,283 8,019 10,447 10,952 11,058 11,245 8,027 2000's 8,794 9,750 9,090 11,272 10,949 12,019 12,456 12,678 36,928 19,208 2010's 12,751 10,721 10,840 11,063 10,946 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  20. Massachusetts Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Massachusetts Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,082,777 1,100,635 1,114,920 1990's 1,118,429 1,127,536 1,137,911 1,155,443 1,179,869 1,180,860 1,188,317 1,204,494 1,212,486 1,232,887 2000's 1,278,781 1,283,008 1,295,952 1,324,715 1,306,142 1,297,508 1,348,848 1,361,470 1,236,480 1,370,353 2010's 1,389,592 1,408,314 1,447,947

  1. Michigan Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Michigan Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 178,469 185,961 191,474 1990's 195,766 198,890 201,561 204,453 207,629 211,817 214,843 222,726 224,506 227,159 2000's 230,558 225,109 247,818 246,123 246,991 253,415 254,923 253,139 252,382 252,017 2010's 249,309 249,456 249,994 250,994 253,127 - = No Data Reported; -- = Not Applicable; NA = Not

  2. Michigan Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Michigan Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10,885 11,117 11,452 1990's 11,500 11,446 11,460 11,425 11,308 11,454 11,848 12,233 11,888 14,527 2000's 11,384 11,210 10,468 10,378 10,088 10,049 9,885 9,728 10,563 18,186 2010's 9,332 9,088 8,833 8,497 8,156 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  3. Michigan Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Michigan Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,452,554 2,491,149 2,531,304 1990's 2,573,570 2,609,561 2,640,579 2,677,085 2,717,683 2,767,190 2,812,876 2,859,483 2,903,698 2,949,628 2000's 2,999,737 3,011,205 3,110,743 3,140,021 3,161,370 3,187,583 3,193,920 3,188,152 3,172,623 3,169,026 2010's 3,152,468 3,153,895 3,161,033 3,180,349

  4. Minnesota Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Minnesota Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 88,789 90,256 92,916 1990's 95,474 97,388 99,707 93,062 102,857 103,874 105,531 108,686 110,986 114,127 2000's 116,529 119,007 121,751 123,123 125,133 126,310 129,149 128,367 130,847 131,801 2010's 132,163 132,938 134,394 135,557 136,382 - = No Data Reported; -- = Not Applicable; NA = Not Available;

  5. Minnesota Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Minnesota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,585 2,670 2,638 1990's 2,574 2,486 2,515 2,477 2,592 2,531 2,564 2,233 2,188 2,267 2000's 2,025 1,996 2,029 2,074 2,040 1,432 1,257 1,146 1,131 2,039 2010's 2,106 1,770 1,793 1,870 1,878 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  6. Minnesota Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Minnesota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 872,148 894,380 911,001 1990's 946,107 970,941 998,201 1,074,631 1,049,263 1,080,009 1,103,709 1,134,019 1,161,423 1,190,190 2000's 1,222,397 1,249,748 1,282,751 1,308,143 1,338,061 1,364,237 1,401,362 1,401,623 1,413,162 1,423,703 2010's 1,429,681 1,436,063 1,445,824 1,459,134 1,472,663 - = No

  7. Mississippi Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Mississippi Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 43,362 44,170 44,253 1990's 43,184 43,693 44,313 45,310 43,803 45,444 46,029 47,311 45,345 47,620 2000's 50,913 51,109 50,468 50,928 54,027 54,936 55,741 56,155 55,291 50,713 2010's 50,537 50,636 50,689 50,153 50,238 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  8. Mississippi Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Mississippi Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,312 1,263 1,282 1990's 1,317 1,314 1,327 1,324 1,313 1,298 1,241 1,199 1,165 1,246 2000's 1,199 1,214 1,083 1,161 996 1,205 1,181 1,346 1,132 1,141 2010's 980 982 936 933 943 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  9. Mississippi Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Mississippi Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 370,094 372,238 376,353 1990's 382,251 386,264 392,155 398,472 405,312 415,123 418,442 423,397 415,673 426,352 2000's 434,501 438,069 435,146 438,861 445,212 445,856 437,669 445,043 443,025 437,715 2010's 436,840 442,479 442,840 445,589 444,423 - = No Data Reported; -- = Not

  10. Missouri Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Missouri Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 96,711 97,939 99,721 1990's 105,164 117,675 125,174 125,571 132,378 130,318 133,445 135,553 135,417 133,464 2000's 133,969 135,968 137,924 140,057 141,258 142,148 143,632 142,965 141,529 140,633 2010's 138,670 138,214 144,906 142,495 143,024 - = No Data Reported; -- = Not Applicable; NA = Not