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Sample records for number recognition development

  1. Developing and Enhancing Workforce Training Programs: Number...

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

    Developing and Enhancing Workforce Training Programs: Number of Projects by State Developing and Enhancing Workforce Training Programs: Number of Projects by State Map of the ...

  2. Health Code Number (HCN) Development Procedure

    SciTech Connect (OSTI)

    Petrocchi, Rocky; Craig, Douglas K.; Bond, Jayne-Anne; Trott, Donna M.; Yu, Xiao-Ying

    2013-09-01

    This report provides the detailed description of health code numbers (HCNs) and the procedure of how each HCN is assigned. It contains many guidelines and rationales of HCNs. HCNs are used in the chemical mixture methodology (CMM), a method recommended by the department of energy (DOE) for assessing health effects as a result of exposures to airborne aerosols in an emergency. The procedure is a useful tool for proficient HCN code developers. Intense training and quality assurance with qualified HCN developers are required before an individual comprehends the procedure to develop HCNs for DOE.

  3. Property:NumberOfLowEmissionDevelopmentStrategiesExample | Open...

    Open Energy Info (EERE)

    issionDevelopmentStrategiesExample Property Type Number Retrieved from "http:en.openei.orgwindex.php?titleProperty:NumberOfLowEmissionDevelopmentStrategiesExample&oldid326472...

  4. Property:NumberOfLowEmissionDevelopmentStrategiesExamples | Open...

    Open Energy Info (EERE)

    sionDevelopmentStrategiesExamples Property Type Number Retrieved from "http:en.openei.orgwindex.php?titleProperty:NumberOfLowEmissionDevelopmentStrategiesExamples&oldid323715...

  5. Proposal for the development of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    SciTech Connect (OSTI)

    Deptuch, Gregory; Hoff, Jim; Kwan, Simon; Lipton, Ron; Liu, Ted; Ramberg, Erik; Todri, Aida; Yarema, Ray; Demarteua, Marcel,; Drake, Gary; Weerts, Harry; /Argonne /Chicago U. /Padua U. /INFN, Padua

    2010-10-01

    Future particle physics experiments looking for rare processes will have no choice but to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare process. The authors propose to develop a 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) chip for HEP applications, to advance the state-of-the-art for pattern recognition and track reconstruction for fast triggering.

  6. Developing and Enhancing Workforce Training Programs: Number of Projects by

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

    State | Department of Energy Developing and Enhancing Workforce Training Programs: Number of Projects by State Developing and Enhancing Workforce Training Programs: Number of Projects by State Map of the United States showing the location of Workforce Training Projects, funded through the American Recovery and Reinvestment Act PDF icon Developing and Enhancing Workforce Training Programs: Number of Projects by State More Documents & Publications Workforce Development Wind Projects

  7. Developement of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    SciTech Connect (OSTI)

    Deputch, G.; Hoff, J.; Lipton, R.; Liu, T.; Olsen, J.; Ramberg, E.; Wu, Jin-Yuan; Yarema, R.; Shochet, M.; Tang, F.; Demarteau, M.; /Argonne /INFN, Padova

    2011-04-13

    Many next-generation physics experiments will be characterized by the collection of large quantities of data, taken in rapid succession, from which scientists will have to unravel the underlying physical processes. In most cases, large backgrounds will overwhelm the physics signal. Since the quantity of data that can be stored for later analysis is limited, real-time event selection is imperative to retain the interesting events while rejecting the background. Scaling of current technologies is unlikely to satisfy the scientific needs of future projects, so investments in transformational new technologies need to be made. For example, future particle physics experiments looking for rare processes will have to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare processes. In this proposal, we intend to develop hardware-based technology that significantly advances the state-of-the-art for fast pattern recognition within and outside HEP using the 3D vertical integration technology that has emerged recently in industry. The ultimate physics reach of the LHC experiments will crucially depend on the tracking trigger's ability to help discriminate between interesting rare events and the background. Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing pattern recognition for a track trigger, requiring about three orders of magnitude more associative memory patterns than what was used in the original CDF SVT. Significant improvement in the architecture of associative memory structures is needed to run fast pattern recognition algorithms of this scale. We are proposing the development of 3D integrated circuit technology as a way to implement new associative memory structures for fast pattern recognition applications. Adding a 'third' dimension to the signal processing chain, as compared to the two-dimensional nature of printed circuit boards, Field Programmable Gate Arrays (FPGAs), etc., opens up the possibility for new architectures that could dramatically enhance pattern recognition capability. We are currently performing preliminary design work to demonstrate the feasibility of this approach. In this proposal, we seek to develop the design and perform the ASIC engineering necessary to realize a prototype device. While our focus here is on the Energy Frontier (e.g. the LHC), the approach may have applications in experiments in the Intensity Frontier and the Cosmic Frontier as well as other scientific and medical projects. In fact, the technique that we are proposing is very generic and could have wide applications far beyond track trigger, both within and outside HEP.

  8. Modeling the Number of Ignitions Following an Earthquake: Developing...

    Office of Environmental Management (EM)

    Developing Prediction Limits for Overdispersed Count Data Authors: Elizabeth J. Kelly and Raymond N. Tell PDF icon Modeling the Number of Ignitions Following an Earthquake:...

  9. Modeling the Number of Ignitions Following an Earthquake: Developing...

    Office of Environmental Management (EM)

    the likelihood of various fire scenarios. The first component of the approach is a statistical model to predict the number of ignitions for a new earthquake event. This model is...

  10. Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data

    Broader source: Energy.gov [DOE]

    Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data Elizabeth J. Kelly and Raymond N. Tell

  11. Buried Anode Device Development: Cooperative Research and Development Final Report, CRADA Number CRD-11-451

    SciTech Connect (OSTI)

    Tenent, R.

    2015-03-01

    The possibility of a reflecting electrochromic device is very attractive, and the 'Buried Anode' architecture developed at NREL could yield such a device. The subject of this cooperative agreement will be the development and refinement of a Buried Anode device process. This development will require the active involvement of NREL and US e-Chromic personnel, and will require the use of NREL equipment as much as possible. When this effort is concluded, US e-Chromic will have enough information to construct a pilot production line, where further development can continue.

  12. Electrochemical Behavior of Disposable Electrodes Prepared by Ion Beam Based Surface Modification for Biomolecular Recognition

    SciTech Connect (OSTI)

    Erdem, A.; Karadeniz, H.; Caliskan, A.; Urkac, E. Sokullu; Oztarhan, A.; Oks, E.; Nikolayev, A.

    2009-03-10

    Many important technological advances have been made in the development of technologies to monitor interactions and recognition events of biomolecules in solution and on solid substrates. The development of advanced biosensors could impact significantly the areas of genomics, proteomics, biomedical diagnostics and drug discovery. In the literature, there have recently appeared an impressive number of intensive designs for electrochemical monitoring of biomolecular recognition. Herein, the influence of ion implanted disposable graphite electrodes on biomolecular recognition and their electrochemical behaviour was investigated.

  13. Noncomposite Counterelectrode Development: Cooperative Research and Development Final Report, CRADA Number CRD-06-203

    SciTech Connect (OSTI)

    Engtrakul, C.

    2014-06-01

    New counter electrode materials under development at NREL have the potential to positively impact electrochromic window technology. The current generation of nanocomposite materials is designed to provide rapid transport of lithium ions to nanoparticles of anodic coloring materials. They may improve the coloration efficiency of the entire films stack while also improving the speed and depth of coloration. We expect an added benefit of greater film durability. To date, encouraging results have been obtained in the laboratory. Performance and durability tests will be carried out to characterize any improvements obtained as a result of the new counter electrode materials. In addition to process improvement, the project also has the secondary goal of improving the basic understanding of the electrochromic process in Sage?s counter electrode.

  14. Winnebago Resource Study: Cooperative Research and Development Final Report, CRADA Number CRD-09-329

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

    Winnebago Resource Study Cooperative Research and Development Final Report CRADA Number: CRD-09-329 NREL Technical Contacts: Antonio Jimenez and Robi Robichaud CRADA Report NREL/TP-7A40-63933 March 2015 NOTICE The submitted manuscript has been offered by an employee of the Alliance for Sustainable Energy, LLC (Alliance), a contractor of the US Government under Contract No. DE-AC36-08GO28308. Accordingly, the US Government and Alliance retain a nonexclusive royalty-free license to publish or

  15. Reporting and Recognition Template

    Broader source: Energy.gov [DOE]

    Better Buildings Residential Network Reporting and Recognition Template. Please submit your organization’s number of upgrades and associated benefits from fiscal year (FY) 2015 using this template by May 13, 2016 to bbresidentialnetwork@ee.doe.gov, or provide the information in another format, such as via email, a document, spreadsheet, graphic, or chart.

  16. Equipment Loan: Cooperative Research and Development Final Report, CRADA Number CRD-07-250

    SciTech Connect (OSTI)

    Stoffel, T.

    2013-08-01

    Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NREL mission: establish a national 30-year climatological database of measured solar irradiances; provide high quality ground-truth data for satellite remote sensing validation; support development of radiative transfer models for estimating solar irradiance from available meteorological observations; provide solar resource information needed for technology deployment and operations.

  17. Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data

    Office of Environmental Management (EM)

    Department of Energy Model Documents for an Energy Savings Performance Contract Project Model Documents for an Energy Savings Performance Contract Project This page contains a model contract template and companion documents to help you launch energy efficiency projects through Energy Savings Performance Contracting (ESPC). Read about how these documents were developed. The ESPC Model Documents were prepared as resources that can be used when developing or updating procurement and contracting

  18. Transportation energy strategy: Project {number_sign}5 of the Hawaii Energy Strategy Development Program

    SciTech Connect (OSTI)

    1995-08-01

    This study was prepared for the State Department of Business, Economic Development and Tourism (DBEDT) as part of the Hawaii Energy Strategy program. Authority and responsibility for energy planning activities, such as the Hawaii Energy Strategy, rests with the State Energy Resources Coordinator, who is the Director of DBEDT. Hawaii Energy Strategy Study No. 5, Transportation Energy Strategy Development, was prepared to: collect and synthesize information on the present and future use of energy in Hawaii`s transportation sector, examine the potential of energy conservation to affect future energy demand; analyze the possibility of satisfying a portion of the state`s future transportation energy demand through alternative fuels; and recommend a program targeting energy use in the state`s transportation sector to help achieve state goals. The analyses and conclusions of this report should be assessed in relation to the other Hawaii Energy Strategy Studies in developing a comprehensive state energy program. 56 figs., 87 tabs.

  19. Evaluation of Hydrogen Sensors: Cooperative Research and Development Final Report, CRADA Number CRD-14-547

    SciTech Connect (OSTI)

    Buttner, William

    2015-10-01

    In preparation for the projected 2015 release of commercial hydrogen fuel cell vehicles, KPA has been contracted by Toyota Motors to develop a hydrogen safety system for vehicle repair facilities. Repair facility safety designs will include hydrogen sensors. KPA will identify critical sensor specifications for vehicle repair facilities. In collaboration with NREL, KPA will select and purchase commercial hydrogen sensors that meet or nearly meet requirements for deployment in vehicle repair facility. A two-phase field deployment plan to verify sensor performance has been developed.

  20. Winnebago Resource Study. Cooperative Research and Development Final Report, CRADA Number CRD-09-329

    SciTech Connect (OSTI)

    Jimenez, A.; Robichaud, R.

    2015-03-01

    Since 2005 the NREL Native American Tall Tower Loan program has assisted Native American tribes to assess their wind resource by lending tall (30m - 50m) anemometer. This program has allowed tribes a lower risk way to gather financeable wind data for potential utility scale wind energy projects. These projects offer Tribes a significant economic development opportunity.

  1. Fiber Optic Hydrogen Sensor Development: Cooperative Research and Development Final Report, CRADA number CRD-05-00158

    SciTech Connect (OSTI)

    Ringer, M.

    2010-07-01

    NREL and Nuclear Filter Technology collaborated to develop a prototype product for a hydrogen threshold sensor that was used to monitor hydrogen production in the transport of nuclear waste transport containers.

  2. DEDALOS NREL: Cooperative Research and Development Final Report, CRADA Number CRD-07-237

    SciTech Connect (OSTI)

    Friedman, D.

    2013-06-01

    Currently High Concentration Photovoltaic (HCPV) terrestrial modules are based on the combination of optic elements that concentrate the sunlight into much smaller GaAs space cells to produce electricity. GaAs cell technology has been well developed for space applications during the last two decades, but the use of GaAs cells under concentrated sunlight in terrestrial applications leaves unanswered questions about performance, durability and reliability. The work to be performed under this CRADA will set the basis for the design of high-performance, durable and reliable HCPV terrestrial modules that will bring down electricity production costs in the next five years.

  3. Integrated Biorefinery Project: Cooperative Research and Development Final Report, CRADA Number CRD-10-390

    SciTech Connect (OSTI)

    Chapeaux, A.; Schell, D.

    2013-06-01

    The Amyris-NREL CRADA is a sub-project of Amyris?s DOE-funded pilot-scale Integrated Biorefinery (IBR). The primary product of the Amyris IBR is Amyris Renewable Diesel. Secondary products will include lubricants, polymers and other petro-chemical substitutes. Amyris and its project partners will execute on a rapid project to integrate and leverage their collective expertise to enable the conversion of high-impact biomass feedstocks to these advanced, infrastructure-compatible products. The scope of the Amyris-NREL CRADA includes the laboratory development and pilot scale-up of bagasse pretreatment and enzymatic saccharification conditions by NREL for subsequent conversion of lignocellulosic sugar streams to Amyris Diesel and chemical products by Amyris. The CRADA scope also includes a techno-economic analysis of the overall production process of Amyris products from high-impact biomass feedstocks.

  4. Isothermal Battery Calorimeter Technology Transfer and Development: Cooperative Research and Development Final Report, CRADA Number CRD-12-461

    SciTech Connect (OSTI)

    Pesaran, A.; Keyser, M.

    2014-12-01

    During the last 15 years, NREL has been utilizing its unique expertise and capabilities to work with industry partners on battery thermal testing and electric and hybrid vehicle simulation and testing. Further information and publications about NREL's work and unique capabilities in battery testing and modeling can be found at NREL's Energy Storage website: http://www.nrel.gov/vehiclesandfuels/energystorage/. Particularly, NREL has developed and fabricated a large volume isothermal battery calorimeter that has been made available for licensing and potential commercialization (http://techportal.eere.energy.gov/technology.do/techID=394). In summer of 2011, NREL developed and fabricated a smaller version of the large volume isothermal battery calorimeter, called hereafter 'cell-scale LVBC.' NETZSCH Instruments North America, LLC is a leading company in thermal analysis, calorimetry, and determination of thermo-physical properties of materials (www.netzsch-thermal-analysis.com). NETZSCH is interested in evaluation and eventual commercialization of the NREL large volume isothermal battery calorimeter.

  5. Event identification by acoustic signature recognition

    SciTech Connect (OSTI)

    Dress, W.B.; Kercel, S.W.

    1995-07-01

    Many events of interest to the security commnnity produce acoustic emissions that are, in principle, identifiable as to cause. Some obvious examples are gunshots, breaking glass, takeoffs and landings of small aircraft, vehicular engine noises, footsteps (high frequencies when on gravel, very low frequencies. when on soil), and voices (whispers to shouts). We are investigating wavelet-based methods to extract unique features of such events for classification and identification. We also discuss methods of classification and pattern recognition specifically tailored for acoustic signatures obtained by wavelet analysis. The paper is divided into three parts: completed work, work in progress, and future applications. The completed phase has led to the successful recognition of aircraft types on landing and takeoff. Both small aircraft (twin-engine turboprop) and large (commercial airliners) were included in the study. The project considered the design of a small, field-deployable, inexpensive device. The techniques developed during the aircraft identification phase were then adapted to a multispectral electromagnetic interference monitoring device now deployed in a nuclear power plant. This is a general-purpose wavelet analysis engine, spanning 14 octaves, and can be adapted for other specific tasks. Work in progress is focused on applying the methods previously developed to speaker identification. Some of the problems to be overcome include recognition of sounds as voice patterns and as distinct from possible background noises (e.g., music), as well as identification of the speaker from a short-duration voice sample. A generalization of the completed work and the work in progress is a device capable of classifying any number of acoustic events-particularly quasi-stationary events such as engine noises and voices and singular events such as gunshots and breaking glass. We will show examples of both kinds of events and discuss their recognition likelihood.

  6. Blade Testing Equipment Development and Commercialization: Cooperative Research and Development Final Report, CRADA Number CRD-09-346

    SciTech Connect (OSTI)

    Snowberg, D.; Hughes, S.

    2013-04-01

    Blade testing is required to meet wind turbine design standards, reduce machine cost, and reduce the technical and financial risk of deploying mass-produced wind turbine models. NREL?s National Wind Technology Center (NWTC) in Colorado is the only blade test facility in the U.S. capable of performing full-scale static and fatigue testing of multi-megawatt-scale wind turbine blades. Rapid growth in wind turbine size over the past two decades has outstripped the size capacity of the NWTC blade test facility leaving the U.S. wind industry without a suitable means of testing blades for large land-based and offshore turbines. This CRADA will develop and commercialize testing technologies and test equipment, including scaling up, value engineering, and testing of equipment to be used at blade testing facilities in the U.S. and around the world.

  7. Southern California Edison Grid Integration Evaluation: Cooperative Research and Development Final Report, CRADA Number CRD-10-376

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

    Southeastern Power Administration Southeastern Power Administration Southeastern Power Administration View All Maps Addthis

    Southern California Edison Grid Integration Evaluation Cooperative Research and Development Final Report CRADA Number: CRD-10-376 NREL Technical Contact: Barry Mather CRADA Report NREL/TP-5D00-64556 July 2015 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency

  8. Improved Rotating Shadowband Radiometer Measurement Performance: Cooperative Research and Development Final Report, CRADA Number CRD-08-294

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

    Improved Rotating Shadowband Radiometer Measurement Performance Cooperative Research and Development Final Report CRADA Number: CRD-08-294 NREL Technical Contact: Afshin M. Andreas CRADA Report NREL/TP-5D00-63769 February 2015 NOTICE The submitted manuscript has been offered by an employee of the Alliance for Sustainable Energy, LLC (Alliance), a contractor of the US Government under Contract No. DE-AC36-08GO28308. Accordingly, the US Government and Alliance retain a nonexclusive royalty-free

  9. New N-Type Polymers for Organic Photovoltaics: Cooperative Research and Development Final Report, CRADA Number CRD-06-177

    SciTech Connect (OSTI)

    Olson, D.

    2014-08-01

    This CRADA will develop improved thin film organic solar cells using a new n-type semiconducting polymer. High efficiency photovoltaics (PVs) based on inorganic semiconductors have good efficiencies (up to 30%) but are extremely expensive to manufacture. Organic PV technology has the potential to overcome this problem through the use of high-throughput production methods like reel-to-reel printing on flexible substrates. Unfortunately, today's best organic PVs have only a few percent efficiency, a number that is insufficient for virtually all commercial applications. The limited choice of stable n-type (acceptor) organic semiconductor materials is one of the key factors that prevent the further improvement of organic PVs. TDA Research, Inc. (TDA) previously developed a new class of electron-deficient (n-type) conjugated polymers for use in organic light emitting diodes (OLEDs). During this project TDA in collaboration with the National Renewable Energy Laboratory (NREL) will incorporate these electron-deficient polymers into organic photovoltaics and investigate their performance. TDA Research, Inc. (TDA) is developing new materials and polymers to improve the performance of organic solar cells. Materials being developed at TDA include spin coated transparent conductors, charge injection layers, fullerene derivatives, electron-deficient polymers, and three-phase (fullerene/polythiophene/dye) active layer inks.

  10. 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

  11. 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.

  12. Solar Resource Measurements at FPL Energy - Equipment Only. Cooperative Research and Development Final Report, CRADA Number CRD-08-283

    SciTech Connect (OSTI)

    Dooraghi, Mike

    2015-05-07

    Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NREL mission: Establish a national 30-year climatological database of measured solar irradiances; Provide high quality ground-truth data for satellite remote sensing validation; Support development of radiative transfer models for estimating solar irradiance from available meteorological observations; Provide solar resource information needed for technology deployment and operations.

  13. Organic Based Nanocomposite Solar Cells: Cooperative Research and Development Final Report, CRADA Number CRD-04-145

    SciTech Connect (OSTI)

    Olson, D.

    2013-01-01

    This CRADA will focus on the development of organic-based solar cells. Key interfacial issues in these cells will be investigated. In this rapidly emerging technology, it is increasingly clear that cell architecture will need to be at the nanoscale and the interfacial issues between organic elements (small molecule and polymer), transparent conducting oxides, and contact metallizations are critical. Thus this work will focus on the development of high surface area and nanostructured nanocarpets of inorganic oxides, the development of appropriate surface binding/acceptor molecules for the inorganic/organic interface, and the development of next-generation organic materials. Work will be performed in all three areas jointly at NREL and Konarka (with their partner in the third area of the University of Delaware). Results should be more rapid progress toward cheap large-area photovoltaic cells.

  14. Optimization of Lattice Mismatched Heteroepitaxial Layers -- Equipment Only. Cooperative Research and Development Final Report, CRADA Number CRD-09-331

    SciTech Connect (OSTI)

    Friedman, D.

    2015-06-01

    The primary objective of this effort is to develop the capability to apply new single molecule imaging methods to the study of plant cell structure and the dynamics of cellulase enzyme activity.

  15. Solar Technology Validation Project - Solargen (Met Station): Cooperative Research and Development Final Report, CRADA Number CRD-09-367-06

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-08-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  16. Solar Technology Validation Project - RES Americas: Cooperative Research and Development Final Report, CRADA Number CRD-09-367-11

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-08-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  17. Solar Technology Validation Project - USS Data, LLC: Cooperative Research and Development Final Report, CRADA Number CRD-09-367-04

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-08-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  18. Solar Technology Validation Project - Iberdrola Renewables, Inc.: Cooperative Research and Development Final Report, CRADA Number CRD-08-298-3

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-08-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  19. Solar Technology Validation Project - Loyola Marymount University: Cooperative Research and Development Final Report, CRADA Number CRD-09-367-03

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-08-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  20. Solar Technology Validation Project - Amonix, Inc.: Cooperative Research and Development Final Report, CRADA Number CRD-09-367-13

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-08-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  1. Solar Thermal Conversion of Biomass to Synthesis Gas: Cooperative Research and Development Final Report, CRADA Number CRD-09-00335

    SciTech Connect (OSTI)

    Netter, J.

    2013-08-01

    The CRADA is established to facilitate the development of solar thermal technology to efficiently and economically convert biomass into useful products (synthesis gas and derivatives) that can replace fossil fuels. NREL's High Flux Solar Furnace will be utilized to validate system modeling, evaluate candidate reactor materials, conduct on-sun testing of the process, and assist in the development of solar process control system. This work is part of a DOE-USDA 3-year, $1M grant.

  2. Advanced emissions control development program. Quarterly technical progress report {number_sign}4, July 1--September 30, 1995

    SciTech Connect (OSTI)

    Farthing, G.A.

    1995-12-31

    Babcock and Wilcox (B and W) is conducting a five-year project aimed at the development of practical, cost-effective strategies for reducing the emissions of hazardous air pollutants (commonly called air toxics) from coal-fired electric utility plants. The need for air toxic emissions controls will likely arise as the US Environmental Protection Agency proceeds with implementation of Title III of the Clean Air Act Amendments of 1990. Data generated during the program will provide utilities with the technical and economic information necessary to reliably evaluate various air toxics emissions compliance options such as fuel switching, coal cleaning, and flue gas treatment. The development work is being carried out using B and W`s new Clean Environment Development Facility (CEDF) wherein air toxics emissions control strategies can be developed under controlled conditions, and with proven predictability to commercial systems. Tests conducted in the CEDF will provide high quality, repeatable, comparable data over a wide range of coal properties, operating conditions, and emissions control systems. The specific objectives of the project are to: (1) measure and understand the production and partitioning of air toxics species for a variety of steam coals, (2) optimize the air toxics removal performance of conventional flue gas cleanup systems (ESPs, baghouses, scrubbers), (3) develop advanced air toxics emissions control concepts, (4) develop and validate air toxics emissions measurement and monitoring techniques, and (5) establish a comprehensive, self-consistent air toxics data library. Development work is currently concentrated on the capture of mercury, fine particulate, and a variety of inorganic species such as the acid gases (hydrogen chloride, hydrogen fluoride, etc.).

  3. (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

  4. Improved Rotating Shadowband Radiometer Measurement Performance: Cooperative Research and Development Final Report, CRADA Number CRD-08-294

    SciTech Connect (OSTI)

    Andreas, A. M.

    2015-02-01

    Under this Agreement, NREL will work with Participant to improve rotating shadowband radiometer (RSR) performance characterizations. This work includes, but is not limited to, research and development for making the RSR a more accurate and fully characterized instrument for solar power technology development and commercial solar power project site assessment. Cooperative R&D is proposed in three areas: instrument calibration, instrument field configuration and operation, and measurement extrapolation and interpolation using satellite images. This work will be conducted at NREL and Participant facilities.

  5. Platform Li-Ion Battery Risk Assessment Tool: Cooperative Research and Development Final Report, CRADA Number CRD-10-407

    SciTech Connect (OSTI)

    Smith, K.

    2012-01-01

    Creare was awarded a Phase 1 STTR contract from the US Office of Naval Research, with a seven month period of performance from 6/28/2010 to 1/28/2011. The objectives of the STTR were to determine the feasibility of developing a software package for estimating reliability of battery packs, and develop a user interface to allow the designer to assess the overall impact on battery packs and host platforms for cell-level faults. NREL served as sub-tier partner to Creare, providing battery modeling and battery thermal safety expertise.

  6. Advanced Load Identification and Management for Buildings: Cooperative Research and Development Final Report, CRADA Number: CRD-11-422

    SciTech Connect (OSTI)

    Gentile-Polese, L.

    2014-05-01

    The goal of this CRADA work is to support Eaton Innovation Center (Eaton) efforts to develop advanced load identification, management technologies, and solutions to reduce building energy consumption by providing fine granular visibility of energy usage information and safety protection of miscellaneous electric loads (MELs) in commercial and residential buildings. MELs load identification and prediction technology will be employed in a novel 'Smart eOutlet*' to provide critical intelligence and information to improve the capability and functionality of building load analysis and design tools and building power management systems. The work scoped in this CRADA involves the following activities: development and validation of business value proposition for the proposed technologies through voice of customer investigation, market analysis, and third-party objective assessment; development and validation of energy saving impact as well as assessment of environmental and economic benefits; 'smart eOutlet' concept design, prototyping, and validation; field validation of the developed technologies in real building environments. (*Another name denoted as 'Smart Power Strip (SPS)' will be used as an alternative of the name 'Smart eOutlet' for a clearer definition of the product market position in future work.)

  7. Southern California Edison Grid Integration Evaluation: Cooperative Research and Development Final Report, CRADA Number CRD-10-376

    SciTech Connect (OSTI)

    Mather, Barry

    2015-07-09

    The objective of this project is to use field verification to improve DOE’s ability to model and understand the impacts of, as well as develop solutions for, high penetration PV deployments in electrical utility distribution systems. The Participant will work with NREL to assess the existing distribution system at SCE facilities and assess adding additional PV systems into the electric power system.

  8. Liquid-Liquid Separation Process: Cooperative Research and Development Final Report, CRADA Number CRD-09-362

    SciTech Connect (OSTI)

    Schell, D.

    2014-06-01

    The 3M Company, in collaboration with the National Renewable Energy Laboratory (NREL) and others, will develop the concept of the membrane solvent-extraction (MSE) technology for water removal and verify the technology at a pilot scale for bio-ethanol production to increase energy and water savings.

  9. Sorghum to Ethanol Research Initiative: Cooperative Research and Development Final Report, CRADA Number CRD-08-291

    SciTech Connect (OSTI)

    Wolfrum, E.

    2011-10-01

    The goal of this project was to investigate the feasibility of using sorghum to produce ethanol. The work performed included a detailed examination of the agronomics and composition of a large number of sorghum varieties, laboratory experiments to convert sorghum to ethanol, and economic and life-cycle analyses of the sorghum-to-ethanol process. This work showed that sorghum has a very wide range of composition, which depended on the specific sorghum cultivar as well as the growing conditions. The results of laboratory- and pilot-scale experiments indicated that a typical high-biomass sorghum variety performed very similarly to corn stover during the multi-step process required to convert biomass feedstocks to ethanol; yields of ethanol for sorghum were very similar to the corn stover used as a control in these experiments. Based on multi-year agronomic data and theoretical ethanol production, sorghum can achieve more than 1,300 gallons of ethanol per acre given the correct genetics and environment. In summary, sorghum may be a compelling dedicated bioenergy crop that could help provide a portion of the feedstocks required to produce renewable domestic transportation fuels.

  10. Acciona Solar Technology Performance Evaluation: Cooperative Research and Development Final Report, CRADA Number CRD-10-384

    SciTech Connect (OSTI)

    Mehos, M. S.

    2014-01-01

    Under this agreement, NREL will work with Acciona to conduct joint testing, evaluation, and data collection related to Acciona's solar technologies and systems. This work includes, but is not limited to, testing and evaluation of solar component and system technologies, data collection and monitoring, performance evaluation, reliability testing, and analysis. This work will be conducted at Acciona's Nevada Solar One (NSO) power plant and NREL test facilities. Specific projects will be developed on a task order basis. Each task order will identify the name of the project and deliverables to be produced under the task order. Each task order will delineate an estimated completion date based on a project's schedule. Any reports developed under this CRADA must be reviewed by both NREL and Acciona and approved by each organization prior to publication of results or documents.

  11. Mobile Ocean Test Berth Support: Cooperative Research and Development Final Report, CRADA Number CRD-10-413

    SciTech Connect (OSTI)

    LiVecchi, Albert

    2015-12-01

    The Northwest National Marine Renewable Energy Center (NNMREC), headquartered at the Oregon State University, is establishing the capabilities to test prototype wave energy conversion devices in the ocean. This CRADA will leverage the technical expertise and resources at NREL in the wind industry and in ocean engineering to support and enhance the development of the NNMREC Mobile Ocean Test Berth (MOTB). This CRADA will provide direct support to NNMREC by providing design evaluation and review of the MOTB, developing effective protocols for testing of the MOTB and wave energy conversion devices in the ocean, assisting in the specification of appropriate instrumentation and data acquisition packages, and providing guidance on obtaining and maintaining A2LA (American Association for Laboratory Accreditation) accreditation.

  12. Solar Resources Measurements in Houston, TX -- Equipment Only: Cooperative Research and Development Final Report, CRADA Number CRD-06-204

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-09-01

    Loaning Texas Southern University equipment in order to perform site-specific, long-term, continuous, and high-resolution measurements of solar irradiance is important for developing renewable resource data. These data are used for several research and development activities consistent with the NREL mission: (1) establish a national 30-year climatological database of measured solar irradiances; (2) provide high quality ground-truth data for satellite remote sensing validation; (3) support development of radiative transfer models for estimating solar irradiance from available meteorological observations; (4) provide solar resource information needed for technology deployment and operations. Data acquired under this agreement will be available to the public through NREL's Measurement & Instrumentation Data Center - MIDC (http://www.nrel.gov/midc) Or the Renewable Resource Data Center - RReDC (http://rredc.nrel.gov). The MIDC offers a variety of standard data display, access, and analysis tools designed to address the needs of a wide user audience (e.g., industry, academia, and government interests).

  13. Berkeley Lab Climate Software Honored for Pattern Recognition Advances

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

    Climate Software Honored for Pattern Recognition Advances Berkeley Lab Climate Software Honored for Pattern Recognition Advances September 17, 2015 Contact: Kathy Kincade, +1 510 495 2124, kkincade@lbl.gov The Toolkit for Extreme Climate Analysis (TECA), developed at Lawrence Berkeley National Laboratory to help climate researchers detect extreme weather events in large datasets, has been recognized for its achievements in solving large-scale pattern recognition problems. "TECA: Petascale

  14. WindFloat Feasibility Study Support. Cooperative Research and Development Final Report, CRADA Number CRD-11-419

    SciTech Connect (OSTI)

    Sirnivas, Senu

    2015-05-07

    This shared resource CRADA defines research collaborations between the National Renewable Energy Laboratory and Principle Power, Inc. and its subsidiaries (“Principle Power”). Under the terms and conditions described in this CRADA agreement, NREL and Principle Power will collaborate on the DEMOWFLOAT project, a full-scale 2-MW demonstration project of a novel floating support structure for large offshore wind turbines, called WindFloat. The purpose of the project is to demonstrate the longterm field performance of the WindFloat design, thus enabling the future commercialized deployment of floating deepwater offshore wind power plants. NREL is the leading U.S. Department of Energy (DOE) laboratory for the development and advancement of renewable energy and has a strong interest in offshore wind and the development of deepwater offshore wind systems. NREL will provide expertise and resources to the DEMOWFLOAT project in assessing the environmental impacts, independent technical performance validation, and engineering analysis. Principle Power is a Seattle, Washington-based renewable energy company that owns all the intellectual property associated with the WindFloat. In return for NREL’s support of the DEMOWFLOAT project, Principle Power will provide NREL with valuable test data from the project that will be used to validate the numerical tools developed by NREL for analyzing offshore wind turbines. In addition, NREL will gain experience and knowledge in offshore wind designs and testing methods through this collaboration. 2 This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. NREL and Principle Power will work together to advance floating offshore wind technology, and demonstrate its viability for supplying the world with a new clean energy source.

  15. Microalgal Production of Jet Fuel: Cooperative Research and Development Final Report, CRADA Number CRD-07-208

    SciTech Connect (OSTI)

    Jarvis, E. E.; Pienkos, P. T.

    2012-06-01

    Microalgae are photosynthetic microorganisms that can use CO2 and sunlight to generate the complex biomolecules necessary for their survival. These biomolecules include energy-rich lipid compounds that can be converted using existing refinery equipment into valuable bio-derived fuels, including jet fuel for military and commercial use. Through a dedicated and thorough collaborative research, development and deployment program, the team of the National Renewable Energy Laboratory (NREL) and Chevron will identify a suitable algae strain that will surpass the per-acre biomass productivity of terrestrial plant crops.

  16. Metallic Inks for Solar Cells: Cooperative Research and Development Final Report, CRADA Number CRD-10-370

    SciTech Connect (OSTI)

    van Hest, M.

    2013-04-01

    This document describes the statement of work for National Renewable Energy Laboratory (NREL) as a subcontractor for Applied Nanotech, Inc. (ANI) for the Phase II SBIR contract with the Department of Energy to build silicon solar cells using non-contact printed, nanoparticle-based metallic inks. The conductive inks are based upon ANI's proprietary method for nanoparticle dispersion. The primary inks under development are aluminum for silicon solar cell back plane contacts and copper for top interdigitated contacts. The current direction of silicon solar cell technology is to use thinner silicon wafers. The reduction in wafer thickness reduces overall material usage and can increase efficiency. These thin silicon wafers are often very brittle and normal methods used for conductive feed line application, such as screen-printing, are detrimental. The Phase II program will be focused on materials development for metallic inks that can be applied to a silicon solar cell using non-contact methods. Uniform BSF (Back Surface Field) formation will be obtained by optimizing ink formulation and curing conditions to improve cell efficiency.

  17. CRADA Final Report for CRADA Number NFE-10-02991 "Development and Commercialization of Alternative Carbon Precursors and Conversion Technologies"

    SciTech Connect (OSTI)

    Norris, Rober; Paulauskas, Felix; Naskar, Amit; Kaufman, Michael; Yarborough, Ken; Derstine, Chris

    2013-10-01

    The overall objective of the collaborative research performed by the Oak Ridge National Laboratory (ORNL) and the Dow Chemical Company under this Cooperative Research And Development Agreement (CRADA NFE-10-02991) was to develop and establish pathways to commercialize new carbon fiber precursor and conversion technology. This technology is to produce alternative polymer fiber precursor formulations as well as scaled energy-efficient advanced conversion technology to enable continuous mode conversion to obtain carbonized fibers that are technically and economically viable in industrial markets such as transportation, wind energy, infrastructure and oil drilling applications. There have been efforts in the past to produce a low cost carbon fiber. These attempts have to be interpreted against the backdrop of the market needs at the time, which were strictly military aircraft and high-end aerospace components. In fact, manufacturing costs have been reduced from those days to current practice, where both process optimization and volume production have enabled carbon fiber to become available at prices below $20/lb. However, the requirements of the lucrative aerospace market limits further price reductions from current practice. This approach is different because specific industrial applications are targeted, most specifically wind turbine blade and light vehicle transportation, where aircraft grade carbon fiber is not required. As a result, researchers are free to adjust both manufacturing process and precursor chemistry to meet the relaxed physical specifications at a lower cost. This report documents the approach and findings of this cooperative research in alternative precursors and advanced conversion for production of cost-effective carbon fiber for energy missions. Due to export control, proprietary restrictions, and CRADA protected data considerations, specific design details and processing parameters are not included in this report.

  18. Commercialization of High-Temperature Solar Selective Coating: Cooperative Research and Development Final Report, CRADA Number CRD-08-300

    SciTech Connect (OSTI)

    Gray, M. H.

    2014-01-01

    The goal for Concentrating Solar Power (CSP) technologies is to produce electricity at 15 cents/kilowatt-hour (kWh) with six hours of thermal storage in 2015 (intermediate power) and close to 10 cents/kWh with 12-17 hours of thermal storage in 2020 (baseload power). Cost reductions of up to 50% to the solar concentrator are targeted through technology advances. The overall solar-to-electric efficiency of parabolic-trough solar power plants can be improved and the cost of solar electricity can be reduced by improving the properties of the selective coating on the receiver and increasing the solar-field operating temperature to >450 degrees C. New, more-efficient selective coatings will be needed that have both high solar absorptance and low thermal emittance at elevated temperatures. Conduction and convection losses from the hot absorber surface are usually negligible for parabolic trough receivers. The objective is to develop new, more-efficient selective coatings with both high solar absorptance (..alpha.. > 0.95) and low thermal emittance (..epsilon.. < 0.08 @ 450 degrees C) that are thermally stable above 450 degrees C, ideally in air, with improved durability and manufacturability, and reduced cost.

  19. Frito-Lay North America/NREL CRADA: Cooperative Research and Development Final Report, CRADA Number CRD-06-176

    SciTech Connect (OSTI)

    Walker, A.

    2013-06-01

    Frito Lay North America (FLNA) requires technical assistance for the evaluation and implementation of renewable energy and energy efficiency projects in production facilities and distribution centers across North America. Services provided by NREL do not compete with those available in the private sector, but rather provide FLNA with expertise to create opportunities for the private sector renewable/efficiency industries and to inform FLNA decision making regarding cost-effective projects. Services include: identifying the most cost-effective project locations based on renewable energy resource data, utility data, incentives and other parameters affecting projects; assistance with feasibility studies; procurement specifications; design reviews; and other services to support FNLA in improving resource efficiency at facilities. This Cooperative Research and Development Agreement (CRADA) establishes the terms and conditions under which FLNA may access capabilities unique to the laboratory and required by FLNA. Each subsequent task issued under this umbrella agreement would include a scope-of-work, budget, schedule, and provisions for intellectual property specific to that task.

  20. Pyrolysis Oil Stabilization: Hot-Gas Filtration; Cooperative Research and Development Final Report, CRADA Number CRD-09-333

    SciTech Connect (OSTI)

    Baldwin, R.

    2012-07-01

    The hypothesis that was tested in this task was that separation of char, with its associated mineral matter from pyrolysis vapors before condensation, will lead to improved oil quality and stability with respect to storage and transportation. The metric used to evaluate stability in this case was a 10-fold reduction in the rate of increase of viscosity as determined by ASTM D445 (the accelerated aging test). The primary unit operation that was investigated for this purpose was hot-gas filtration. A custom-built heated candle filter system was fabricated by the Pall Corporation and furnished to NREL for this test campaign. This system consisted of a candle filter element in a containment vessel surrounded by heating elements on the external surface of the vessel. The filter element and housing were interfaced to NREL?s existing 0.5 MTD pyrolysis Process Development Unit (PDU). For these tests the pyrolysis reactor of the PDU was operated in the entrained-flow mode. The HGF test stand was installed on a slipstream from the PDU so that both hot-gas filtered oil and bio-oil that was not hot-gas filtered could be collected for purposes of comparison. Two filter elements from Pall were tested: (1) porous stainless steel (PSS) sintered metal powder; (2) sintered ceramic powder. An extremely sophisticated bio-oil condensation and collection system was designed and fabricated at NREL and interfaced to the filter unit.

  1. Development of Black Silicon Antireflection Control and Passivation Technology for Commercial Application: Cooperative Research and Development Final Report, CRADA Number CRD-12-475

    SciTech Connect (OSTI)

    Yuan, H. C.

    2014-06-01

    The work involves the development of a commercial manufacturing process for both multicrystalline and monocrystalline solar cells that combines Natcore's patent pending passivation technology.

  2. Development of Inorganic Precursors for Manufacturing of Photovoltaic Devices: Cooperative Research and Development Final Report, CRADA Number CRD-08-308

    SciTech Connect (OSTI)

    van Hest, M.; Ginley, D.

    2013-06-01

    Both NREL and Rohm and Haas Electronic Materials are interested in the development of solution phase metal and semiconductive precursors for the manufacturing of photovoltaic devices. In particular, we intend to develop material sets for atmospheric deposition processes. The cooperation between these two parties will enable high value materials and processing solutions for the manufacturing of low cost, roll-to-roll photovoltaics.

  3. Development of Commercial Technology for Thin Film Silicon Solar Cells on Glass: Cooperative Research and Development Final Report, CRADA Number CRD-07-209

    SciTech Connect (OSTI)

    Sopori, B.

    2013-03-01

    NREL has conducted basic research relating to high efficiency, low cost, thin film silicon solar cell design and the method of making solar cells. Two patents have been issued to NREL in the above field. In addition, specific process and metrology tools have been developed by NREL. Applied Optical Sciences Corp. (AOS) has expertise in the manufacture of solar cells and has developed its own unique concentrator technology. AOS wants to complement its solar cell expertise and its concentrator technology by manufacturing flat panel thin film silicon solar cell panels. AOS wants to take NREL's research to the next level, using it to develop commercially viable flat pane, thin film silicon solar cell panels. Such a development in equipment, process, and metrology will likely produce the lowest cost solar cell technology for both commercial and residential use. NREL's fundamental research capability and AOS's technology and industrial background are complementary to achieve this product development.

  4. CENER/NREL Collaboration in Testing Facility and Code Development: Cooperative Research and Development Final Report, CRADA Number CRD-06-207

    SciTech Connect (OSTI)

    Moriarty, P.

    2014-11-01

    Under the funds-in CRADA agreement, NREL and CENER will collaborate in the areas of blade and drivetrain testing facility development and code development. The project shall include NREL assisting in the review and instruction necessary to assist in commissioning the new CENER blade test and drivetrain test facilities. In addition, training will be provided by allowing CENER testing staff to observe testing and operating procedures at the NREL blade test and drivetrain test facilities. CENER and NREL will exchange blade and drivetrain facility and equipment design and performance information. The project shall also include exchanging expertise in code development and data to validate numerous computational codes.

  5. Development of Advanced CdTe Solar Cells Based on High Temperature Corning Glass Substrates: Cooperative Research and Development Final Report, CRADA Number CRD-10-373

    SciTech Connect (OSTI)

    Barnes, T.

    2013-08-01

    NREL has developed advanced processes for CdTe solar cells, but because of the temperature limitations of conventional soda lime glass, many of these processes have not been transferred to manufacturing. Corning is developing high temperature substrate glasses that are believed to be manufacturable and will lead to lower $/watt modules costs. The purpose of this CRADA is to evaluate these glasses in the advanced NREL processes. In addition, the CRADA seeks to develop manufacturable processes for transparent conductive oxide layers based on cadmium stannate.

  6. Development of Novel Nanocrystal-based Solar Cell to Exploit Multiple Exciton Generation: Cooperative Research and Development Final Report, CRADA Number CRD-07-00227

    SciTech Connect (OSTI)

    Ellingson, R.

    2010-08-01

    The purpose of the project was to develop new design and fabrication techniques for NC solar cells with the goal of demonstrating enhanced photocurrent and efficiency by exploiting multiple exciton generation and to investigate multiple exciton generation and charge carrier dynamics in semiconductor NC films used in NC-based solar cells.

  7. Development of Abrasion-Resistant Coating for Solar Reflective Films. Cooperative Research and Development Final Report, CRADA Number CRD-07-247

    SciTech Connect (OSTI)

    Gray, Matthew

    2015-10-01

    The purpose of this CRADA is to develop an abrasion-resistant coating, suitable for use on polymeric-based reflective films (e.g., the ReflecTech reflective film), that allows for improved scratch resistance and enables the use of aggressive cleaning techniques (e.g., direct contact methods like brushing) without damaging the specular reflectance properties of the reflective film.

  8. Development of Thin Film Silicon Solar Cell Using Inkjet Printed Silicon and Other Inkjet Processes: Cooperative Research and Development Final Report, CRADA Number CRD-07-260

    SciTech Connect (OSTI)

    Sopori, B.

    2012-04-01

    The cost of silicon photovoltaics (Si-PV) can be greatly lowered by developing thin-film crystalline Si solar cells on glass or an equally lower cost substrate. Typically, Si film is deposited by thermal evaporation, plasma enhanced chemical vapor deposition, and sputtering. NREL and Silexos have worked under a CRADA to develop technology to make very low cost solar cells using liquid organic precursors. Typically, cyclopentasilane (CPS) is deposited on a glass substrate and then converted into an a-Si film by UV polymerization followed by low-temperature optical process that crystallizes the amorphous layer. This technique promises to be a very low cost approach for making a Si film.

  9. Xylo-Oligosaccharide Process Development, Composition, and Techno-Economic Analysis. Cooperative Research and Development Final Report, CRADA Number CRD-12-483

    SciTech Connect (OSTI)

    Shekiro, Joe; Elander, Richard

    2015-12-01

    The purpose of this cooperative work agreement between General Mills Inc. (GMI) and NREL is to determine the feasibility of producing a valuable food ingredient (xylo-oligosaccharides or XOS), a highly soluble fiber material, from agricultural waste streams, at an advantaged cost level relative to similar existing ingredients. The scope of the project includes pilot-scale process development (Task 1), compositional analysis (Task 2), and techno-economic analysis (Task 3).

  10. Development of a High Volume Capable Process to Manufacture High Performance Photovoltaic Cells: Cooperative Research and Development Final Report, CRADA Number CRD-08-322

    SciTech Connect (OSTI)

    Geisz, J. F.

    2012-11-01

    The intent of the work is for RFMD and NREL to cooperate in the development of a commercially viable and high volume capable process to manufacture high performance photovoltaic cells, based on inverted metamorphic (IMM) GaAs technology. The successful execution of the agreement will result in the production of a PV cell using technology that is capable of conversion efficiency at par with the market at the time of release (reference 2009: 37-38%), using RFMD's production facilities. The CRADA work has been divided into three phases: (1) a foundation phase where the teams will demonstrate the manufacturing of a basic PV cell at RFMD's production facilities; (2) a technology demonstration phase where the teams will demonstrate the manufacturing of prototype PV cells using IMM technology at RFMD's production facilities, and; (3) a production readiness phase where the teams will demonstrate the capability to manufacture PV cells using IMM technology with high yields, high reliability, high reproducibility and low cost.

  11. George Washington Carver Recognition Day

    Broader source: Energy.gov [DOE]

    In commemoration of George Washington Carver’s life and work, Congress declared January 5 as George Washington Carver Recognition Day.

  12. Innovative Manufacturing Initiative Recognition Day

    Broader source: Energy.gov [DOE]

    The Innovative Manufacturing Initiative (IMI) Recognition Day (held in Washington, DC on June 20, 2012) showcased IMI projects selected by the Energy Department to help American manufacturers...

  13. Catalysis for Mixed Alcohol Synthesis from Biomass Derived Syngas: Cooperative Research and Development Final Report, CRADA Number CRD-08-292

    SciTech Connect (OSTI)

    Hensley, J.

    2013-04-01

    The Dow Chemical Company (Dow) developed and tested catalysts for production of mixed alcohols from synthesis gas (syngas), under research and development (R&D) projects that were discontinued a number of years ago. Dow possesses detailed laboratory notebooks, catalyst samples, and technical expertise related to this past work. The National Renewable Energy Laboratory (NREL) is conducting R&D in support of the United States Department of Energy (DOE) to develop methods for economically producing ethanol from gasified biomass. NREL is currently conducting biomass gasification research at an existing 1/2 ton/day thermochemical test platform. Both Dow and NREL believe that the ability to economically produce ethanol from biomass-derived syngas can be enhanced through collaborative testing, refinement, and development of Dow's mixed-alcohol catalysts at NREL's and/or Dow's bench- and pilot-scale facilities. Dow and NREL further agree that collaboration on improvements in catalysts as well as gasifier operating conditions (e.g., time, temperature, upstream gas treatment) will be necessary to achieve technical and economic goals for production of ethanol and other alcohols.

  14. Substrate Recognition Strategy for Botulinum Neurotoxin

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

    Substrate Recognition Strategy for Botulinum Neurotoxin Substrate Recognition Strategy for Botulinum Neurotoxin Print Wednesday, 25 May 2005 00:00 Clostridal neurotoxins (CNTs) are...

  15. Employee Performance and Recognition Program - DOE Directives...

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

    31.1D, Employee Performance and Recognition Program by Lorrenda Buckner Functional areas: Employee Recognition, Performance Management The Order establishes requirements and...

  16. Detection and recognition of analytes based on their crystallization patterns

    DOE Patents [OSTI]

    Morozov, Victor; Bailey, Charles L.; Vsevolodov, Nikolai N.; Elliott, Adam

    2008-05-06

    The invention contemplates a method for recognition of proteins and other biological molecules by imaging morphology, size and distribution of crystalline and amorphous dry residues in droplets (further referred to as "crystallization pattern") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. It has been shown that changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. It was also found that both the character of changer in the crystallization patter and the fact of such changes can be used as recognition elements in analysis of protein molecules.

  17. Thin Film Materials and Processing Techniques for a Next Generation Photovoltaic Device: Cooperative Research and Development Final Report, CRADA Number CRD-12-470

    SciTech Connect (OSTI)

    van Hest, M.

    2013-08-01

    This research extends thin film materials and processes relevant to the development and production of a next generation photovoltaic device.

  18. Vindicator Lidar Assessment for Wind Turbine Feed-Forward Control Applications: Cooperative Research and Development Final Report, CRADA Number CRD-09-352

    SciTech Connect (OSTI)

    Wright, A.

    2014-01-01

    Collaborative development and testing of feed-forward and other advanced wind turbine controls using a laser wind sensor.

  19. Cooperative Research Between NREL and Ampulse on III-V PV: Cooperative Research and Development Final Report, CRADA Number CRD-12-464

    SciTech Connect (OSTI)

    Ptak, A.

    2013-04-01

    NREL and Ampulse will engage in cooperative research to develop III-V photovoltaics on alternative substrates.

  20. Wind Energy R&D Collaboration between NIRE and NREL: Cooperative Research and Development Final Report, CRADA Number CRD-11-437

    SciTech Connect (OSTI)

    Moriarty, P.

    2015-01-01

    This work includes, but is not limited to, research and development of joint technology development and certification efforts in the wind power sector; providing access to commercial wind farm and federal facilities to enhance R&D; identification of workforce development best practices. This work will be done at Contractor and Participant facilities.

  1. Visual Empirical Region of Influence (VERI) Pattern Recognition Algorithms

    Energy Science and Technology Software Center (OSTI)

    2002-05-01

    We developed new pattern recognition (PR) algorithms based on a human visual perception model. We named these algorithms Visual Empirical Region of Influence (VERI) algorithms. To compare the new algorithm's effectiveness against othe PR algorithms, we benchmarked their clustering capabilities with a standard set of two-dimensional data that is well known in the PR community. The VERI algorithm succeeded in clustering all the data correctly. No existing algorithm had previously clustered all the pattens inmore » the data set successfully. The commands to execute VERI algorithms are quite difficult to master when executed from a DOS command line. The algorithm requires several parameters to operate correctly. From our own experiences we realized that if we wanted to provide a new data analysis tool to the PR community we would have to provide a new data analysis tool to the PR community we would have to make the tool powerful, yet easy and intuitive to use. That was our motivation for developing graphical user interfaces (GUI's) to the VERI algorithms. We developed GUI's to control the VERI algorithm in a single pass mode and in an optimization mode. We also developed a visualization technique that allows users to graphically animate and visually inspect multi-dimensional data after it has been classified by the VERI algorithms. The visualization technique that allows users to graphically animate and visually inspect multi-dimensional data after it has been classified by the VERI algorithms. The visualization package is integrated into the single pass interface. Both the single pass interface and optimization interface are part of the PR software package we have developed and make available to other users. The single pass mode only finds PR results for the sets of features in the data set that are manually requested by the user. The optimization model uses a brute force method of searching through the cominations of features in a data set for features that produce the best pattern recognition results. With a small number of features in a data set an exact solution can be determined. However, the number of possible combinations increases exponentially with the number of features and an alternate means of finding a solution must be found. We developed and implemented a technique for finding solutions in data sets with both small and large numbers of features. The VERI interface tools were written using the Tcl/Tk GUI programming language, version 8.1. Although the Tcl/Tk packages are designed to run on multiple computer platforms, we have concentrated our efforts to develop a user interface for the ubiquitous DOS environment. The VERI algorithms are compiled, executable programs. The interfaces run the VERI algorithms in Leave-One-Out mode using the Euclidean metric.« less

  2. Visual Empirical Region of Influence (VERI) Pattern Recognition Algorithms

    SciTech Connect (OSTI)

    2002-05-01

    We developed new pattern recognition (PR) algorithms based on a human visual perception model. We named these algorithms Visual Empirical Region of Influence (VERI) algorithms. To compare the new algorithm's effectiveness against othe PR algorithms, we benchmarked their clustering capabilities with a standard set of two-dimensional data that is well known in the PR community. The VERI algorithm succeeded in clustering all the data correctly. No existing algorithm had previously clustered all the pattens in the data set successfully. The commands to execute VERI algorithms are quite difficult to master when executed from a DOS command line. The algorithm requires several parameters to operate correctly. From our own experiences we realized that if we wanted to provide a new data analysis tool to the PR community we would have to provide a new data analysis tool to the PR community we would have to make the tool powerful, yet easy and intuitive to use. That was our motivation for developing graphical user interfaces (GUI's) to the VERI algorithms. We developed GUI's to control the VERI algorithm in a single pass mode and in an optimization mode. We also developed a visualization technique that allows users to graphically animate and visually inspect multi-dimensional data after it has been classified by the VERI algorithms. The visualization technique that allows users to graphically animate and visually inspect multi-dimensional data after it has been classified by the VERI algorithms. The visualization package is integrated into the single pass interface. Both the single pass interface and optimization interface are part of the PR software package we have developed and make available to other users. The single pass mode only finds PR results for the sets of features in the data set that are manually requested by the user. The optimization model uses a brute force method of searching through the cominations of features in a data set for features that produce the best pattern recognition results. With a small number of features in a data set an exact solution can be determined. However, the number of possible combinations increases exponentially with the number of features and an alternate means of finding a solution must be found. We developed and implemented a technique for finding solutions in data sets with both small and large numbers of features. The VERI interface tools were written using the Tcl/Tk GUI programming language, version 8.1. Although the Tcl/Tk packages are designed to run on multiple computer platforms, we have concentrated our efforts to develop a user interface for the ubiquitous DOS environment. The VERI algorithms are compiled, executable programs. The interfaces run the VERI algorithms in Leave-One-Out mode using the Euclidean metric.

  3. Innovative Manufacturing Initiative Recognition Day, Advanced...

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

    More Documents & Publications Innovative Manufacturing Initiative Recognition Day Advanced Manufacturing Office Overview Unlocking the Potential of Additive Manufacturing in the ...

  4. NaREC Offshore and Drivetrain Test Facility Collaboration: Cooperative Research and Development Final Report, CRADA Number CRD-04-140

    SciTech Connect (OSTI)

    Musial, W.

    2014-08-01

    The National Renewable Energy Laboratory (NREL) and the National Renewable Energy Centre (NaREC) in the United Kingdom (UK) have a mutual interest in collaborating in the development of full-scale offshore wind energy and drivetrain testing facilities. NREL and NaREC will work together to share resources and experiences in the development of future wind energy test facilities. This Cooperative Research and Development Agreement (CRADA) includes sharing of test protocols, infrastructure cost data, test plans, pro forma contracting instruments, and safe operating strategies. Furthermore, NREL and NaREC will exchange staff for training and development purposes.

  5. Cooperation Reliability Testing of the Clipper Windpower Liberty 2.5 MW Turbine: Cooperative Research and Development Final Report, CRADA Number CRD-07-210

    SciTech Connect (OSTI)

    Hughes, S.

    2012-05-01

    Clipper Windpower (CWP) has developed the Liberty 2.5 MW wind turbine. The development, manufacturing, and certification process depends heavily on being able to validate the full-scale system design and performance under load in both an accredited structural test facility and through accredited field testing. CWP requested that DOE/ NREL upgrade blade test capabilities to perform a scope of work including structural testing of the C-96 blade used on the CWP Liberty turbine. This funds-in CRADA was developed to upgrade NREL blade test capability, while enabling certification testing of the C-96 blade through the facility and equipment upgrades. NREL shared resource funds were used to develop hardware necessary to structurally attach a large wind turbine to the test stand at the NWTC. Participant funds-in monies were used for developing the test program.

  6. 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...

  7. Optical Materials, Adhesive and Encapsulant, III-V, and Optical Characterization Evaluation: Cooperative Research and Development Final Report, CRADA Number CRD-07-216

    SciTech Connect (OSTI)

    Kempe, M.

    2012-11-01

    SolFocus is currently developing solar technology for utility scale application using Winston collector based concentrating photovoltaics (CPV). Part of that technology development includes small mirror dishes and front surface reflectors, and bonding the separate parts to the assembly. Mirror panels must meet rigid optical specifications in terms of radius of curvature, slope errors and specularity. The reflective surfaces must demonstrate long term durability and maintain high reflectivity. Some bonded surfaces must maintain adhesion and transparency under high concentrations and high temperatures. Others will experience moderate temperatures and do not require transparency. NREL researchers have developed methods and tools that address these related areas.

  8. Solar Resource Measurements in El Paso, Texas (Equipment CRADA Only): Cooperative Research and Development Final Report, CRADA Number CRD-08-273

    SciTech Connect (OSTI)

    Andreas, A.

    2013-11-01

    Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NREL mission: establish a national 30-year climatological database of measured solar irradiances; provide high quality ground-truth data for satellite remote sensing validation; support development of radiative transfer models for estimating solar irradiance from available meteorological observations; provide solar resource information needed for technology deployment and operations.

  9. Super-Resolution Optical Imaging of Biomass Chemical-Spatial Structure: Cooperative Research and Development Final Report, CRADA Number CRD-10-410

    SciTech Connect (OSTI)

    Ding, S. Y.

    2013-06-01

    The overall objective for this project is to characterize and develop new methods to visualize the chemical spatial structure of biomass at varying stages of the biomass degradation processes in situ during the process.

  10. Defining the Interactions of Cellobiohydrolase with Substrate through Structure Function Studies: Cooperative Research and Development Final Report, CRADA Number CRD-10-409

    SciTech Connect (OSTI)

    Beckham, G. T.; Himmel, M. E.

    2013-07-01

    NREL researchers will use their expertise and skilled resources in numerical computational modeling to generate structure-function relationships for improved cellulase variant enzymes to support the development of cellulases with improved performance in biomass conversion.

  11. Optical and Durability Evaluation for Silvered Polymeric Mirrors and Reflectors: Cooperative Research and Development Final Report, CRADA Number, CRD-08-316

    SciTech Connect (OSTI)

    Gray, M.

    2014-08-01

    3M is currently developing silvered polymeric mirror reflectors as low-cost replacements for glass mirrors in concentrating solar power (CSP) systems. This effort is focused on development of reflectors comprising both metallized polymeric mirror films based on improved versions of ECP-305+ or other durable mirror film concepts and appropriate mechanically robust substrates. The objectives for this project are to reduce the system capital and operating costs and to lower the levelized cost of energy for CSP installations. The development of mirror reflectors involves work on both full reflectors and mirror films with and without coatings. Mirror reflectors must meet rigid optical specifications in terms of radius of curvature, slope errors and specularity. Mirror films must demonstrate long-term durability and maintain high reflectivity. 3M would like to augment internal capabilities to validate product performance with methods and tools developed at NREL to address these areas.

  12. Solar Technology Validation Project - Tri-State G&T: Cooperative Research and Development Final Report, CRADA Number CRD-09-367-12

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-08-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  13. Solar Technology Validation Project - Utah State Energy Program (Met Station): Cooperative Research and Development Final Report, CRADA Number CRD-09-367-09

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-08-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  14. Solar Technology Validation Project - Hualapai Valley Solar (Met Station): Cooperative Research and Development Final Report, CRADA Number CRD-09-367-02

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-07-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  15. Solar Technology Validation Project - Southwest Solar (Met Station): Cooperative Research and Development Final Report, CRADA Number CRD-09-367-08

    SciTech Connect (OSTI)

    Wilcox, S.

    2013-08-01

    Under this Agreement, NREL will work with Participant to improve concentrating solar power system performance characterizations. This work includes, but is not limited to, research and development of methods for acquiring renewable resource characterization information using site-specific measurements of solar radiation and meteorological conditions; collecting system performance data; and developing tools for improving the design, installation, operation, and maintenance of solar energy conversion systems. This work will be conducted at NREL and Participant facilities.

  16. Innovative Manufacturing Initiative Recognition Day

    Broader source: Energy.gov [DOE]

    The Innovative Manufacturing Initiative (IMI) Recognition Day (held in Washington, DC on June 20, 2012) showcased IMI projects selected by the Energy Department to help American manufacturers dramatically increase the energy efficiency of their operations and reduce costs. Each project will advance transformational technologies and materials that can benefit a broad cross-section of the domestic economy. This event created a platform for inter-agency and industry networking and also raised awareness among congressional staff and private investors.

  17. recognition for outstanding lifetime achievement

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

    recognition for outstanding lifetime achievement - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense Waste

  18. Advanced Emissions Control Development Program. Quarterly Technical Progress Report {number_sign}5 for the period October 1 to December 31, 1995

    SciTech Connect (OSTI)

    Farthing, George A.

    1996-12-31

    Babcock {ampersand} Wilcox (B{ampersand}W) is conducting a five year project aimed at the development of practical, cost- effective strategies for reducing the emissions of hazardous air pollutants (commonly called air toxics) from coal-fired electric utility plants. The need for air toxic emissions controls will likely arise as the U. S. Environmental Protection Agency proceeds with implementation of Title III of the Clean Air Act Amendments of 1990. Data generated during the program will provide utilities with the technical and economic information necessary to reliably evaluate various air toxics emissions compliance options such as fuel switching, coal cleaning, and flue gas treatment. The development work is being carried out using B&W`s new Clean Environment Development Facility (CEDF) wherein air toxics emissions control strategies can be developed under controlled conditions, and with proven predictability to commercial systems. Tests conducted in the CEDF will provide high quality, repeatable, comparable data over a wide range of coal properties, operating conditions, and emissions control systems. The specific objectives of the project are to: (1) measure and understand the production and partitioning of air toxics species for a variety of steam coals, (2) optimize the air toxics removal performance of conventional flue gas cleanup systems (ESPs, baghouses, scrubbers), (3) develop advanced air toxics emissions control concepts, (4) develop and validate air toxics emissions measurement and monitoring techniques, and (5) establish a comprehensive, self-consistent air toxics data library. Development work is currently concentrated on the capture of mercury, fine particulate, and a variety of inorganic species such as the acid gases (hydrogen chloride, hydrogen fluoride, etc.).

  19. Advanced Emissions Control Development Program. Quarterly Technical Progress Report {number_sign}6 for the period: January 1 to March 31, 1996

    SciTech Connect (OSTI)

    Farthing, George A.

    1996-12-31

    Babcock {ampersand} Wilcox (B{ampersand}W) is conducting a five-year project aimed at the development of practical, cost-effective strategies for reducing the emissions of hazardous air pollutants (commonly called air toxics) from coal-fired electric utility plants. The need for air toxic emissions controls will likely arise as the U. S. Environmental Protection Agency proceeds with implementation of Title III of the clean Air Act Amendments of 1990. Data generated during the program will provide utilities with the technical and economic information necessary to reliably evaluate various air toxics emissions compliance options such as fuel switching, coal cleaning, and flue gas treatment. The development work is being carried out using B{ampersand}W`s new Clean Environment Development Facility (CEDF) wherein air toxics emissions control strategies can be developed under controlled conditions, and with proven predictability to commercial systems. Tests conducted in the CEDF will provide high quality, repeatable, comparable data over a wide range of coal properties, operating conditions, and emissions control systems. The specific objectives of the project are to: (1) measure and understand the production and partitioning of air toxics species for a variety of steam coals, (2) optimize the air toxics removal performance of conventional flue gas cleanup systems (ESPs, baghouses, scrubbers), (3) develop advanced air toxics emissions control concepts, (4) develop and validate air toxics emissions measurement and monitoring techniques, and (5) establish a comprehensive, self- consistent air toxics data library. Development work is currently concentrated on the capture of mercury, fine particulate, and a variety of inorganic species such as the acid gases (hydrogen chloride, hydrogen fluoride, etc.).

  20. Advanced Emissions Control Development Program. Quarterly Technical Progress Report {number_sign}7 for the period: April 1 to June 30, 1996

    SciTech Connect (OSTI)

    Evans, A.P.

    1996-12-31

    Babcock {ampersand} Wilcox (B{ampersand}W) is conducting a five-year project aimed at the development of practical, cost- effective strategies for reducing the emissions of hazardous air pollutants (commonly called air toxics) from coal-fired electric utility plants. The need for air toxic emissions controls may arise as the U. S. Environmental Protection Agency proceeds with implementation of Title III of the Clean Air Act Amendment (CAAA) of 1990. Data generated during the program will provide utilities with the technical and economic information necessary to reliably evaluate various air toxics emissions compliance options such as fuel switching, coal cleaning, and flue gas treatment. The development work is being carried out using B{ampersand}W`s new Clean Environment Development Facility (CEDF) wherein air toxics emissions control strategies can be developed under controlled conditions, and with proven predictability to commercial systems. Tests conducted in the CEDF provide high quality, repeatable, comparable data over a wide range of coal properties, operating conditions, and emissions control systems. Development work to date has concentrated on the capture of mercury, other trace metals, fine particulate, and the inorganic species hydrogen chloride and hydrogen fluoride.

  1. Spectroscopic Studies of Photosynthetic Systems and Their Application in Photovoltaic Devices - Equipment Only: Cooperative Research and Development Final Report, CRADA Number CRD-06-175

    SciTech Connect (OSTI)

    Seibert, M.

    2014-09-01

    Spectral hole-burning (SHB) and single photosynthetic complex spectroscopy (SPCS) will be used to study the excitonic structure and excitation energy transfer (EET) processes of several photosynthetic protein complexes at low temperatures. The combination of SHB on bulk samples and SPCS is a powerful frequency domain approach for obtaining data that will address a number of issues that are key to understanding excitonic structure and energy transfer dynamics. The long-term goal is to reach a better understanding of the ultrafast solar energy driven primary events of photosynthesis as they occur in higher plants, cyanobacteria, purple bacteria, and green algae. A better understanding of the EET and charge separation (CS) processes taking place in photosynthetic complexes is of great interest, since photosynthetic complexes might offer attractive architectures for a future generation of circuitry in which proteins are crystallized.

  2. 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

  3. Solar Resource Measurements in Canyon, Texas - Equipment Only Loan: Cooperative Research and Development Final Report, CRADA Number CRD-07-233

    SciTech Connect (OSTI)

    Andreas, A.

    2014-07-01

    Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NREL mission: establish a national 30-year climatological database of measured solar irradiances; provide high-quality ground-truth data for satellite remote sensing validation; support development of radiative transfer models for estimating solar irradiance from available meteorological observations; and provide solar resource information needed for technology deployment and operations. Data acquired under this agreement will be available to the public through NREL's Measurement & Instrumentation Data Center (MIDC) or the Renewable Resource Data Center (RReDC). The MIDC offers a variety of standard data display, access, and analysis tools designed to address the needs of a wide user audience (e.g., industry, academia, and government interests).

  4. Solar Resource Measurements in Humboldt State University, Arcata, California: Cooperative Research and Development Final Report, CRADA Number CRD-08-262

    SciTech Connect (OSTI)

    Stoffel, T.; Andreas, A.

    2014-01-01

    Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NREL mission: establish a national 30-year climatological database of measured solar irradiances; provide high quality ground-truth data for satellite remote sensing validation; support development of radiative transfer models for estimating solar irradiance from available meteorological observations; provide solar resource information needed for technology deployment and operations. Data acquired under this agreement will be available to the public through NREL's Measurement & Instrumentation Data Center - MIDC (www.nrel.gov/midc) or the Renewable Resource Data Center - RReDC (http://rredc.nrel.gov). The MIDC offers a variety of standard data display, access, and analysis tools designed to address the needs of a wide user audience (e.g., industry, academia, and government interests).

  5. Solar Resources Measurements in Elizabeth City, North Carolina - Equipment Only: Cooperative Research and Development Final Report, CRADA Number CRD-07-217

    SciTech Connect (OSTI)

    Stoffel, T.; Andreas, A.

    2014-01-01

    Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NREL mission: establish a national 30-year climatological database of measured solar irradiances; provide high quality ground-truth data for satellite remote sensing validation; support development of radiative transfer models for estimating solar irradiance from available meteorological observations; provide solar resource information needed for technology deployment and operations. Data acquired under this agreement will be available to the public through NREL's Measurement & Instrumentation Data Center - MIDC (www.nrel.gov/midc). The MIDC offers a variety of standard data display, access, and analysis tools designed to address the needs of a wide user audience (e.g., industry, academia, and government interests).

  6. NREL/University of Delaware Offshore Wind R&D Collaboration: Cooperative Research and Development Final Report, CRADA Number CRD-10-393

    SciTech Connect (OSTI)

    Musial, Walt

    2015-11-12

    Specifically, the work under this CRADA includes, but is not limited to, the development of test procedures for an offshore test site in Delaware waters; testing of installed offshore wind turbines; performance monitoring of those turbines; and a program of research and development on offshore wind turbine blades, components, coatings, foundations, installation and construction of bottom-fixed structures, environmental impacts, policies, and more generally on means to enhance the reliability, facilitate permitting, and reduce costs for offshore wind turbines. This work will be conducted both at NREL's National Wind Technology Center and participant facilities, as well as the established offshore wind test sites.

  7. Preliminary Structural Design Conceptualization for Composite Rotor for Verdant Power Water Current: Cooperative Research and Development Final Report, CRADA Number CRD-08-296

    SciTech Connect (OSTI)

    Hughes, S.

    2011-02-01

    The primary thrust of the CRADA will be to develop a new rotor design that will allow higher current flows (>4m/s), greater swept area (6-11m), and in the process, will maximize performance and energy capture.

  8. Improved Battery Pack Thermal Management to Reduce Cost and Increase Energy Density: Cooperative Research and Development Final Report, CRADA Number CRD-12-499

    SciTech Connect (OSTI)

    Smith, K.

    2013-10-01

    Under this CRADA NREL will support Creare's project for the Department of Energy entitled 'Improved Battery Pack Thermal Management to Reduce Cost and Increase Energy Density' which involves the development of an air-flow based cooling product that increases energy density, safety, and reliability of hybrid electric vehicle battery packs.

  9. Infrastructure, Components and System Level Testing and Analysis of Electric Vehicles: Cooperative Research and Development Final Report, CRADA Number CRD-09-353

    SciTech Connect (OSTI)

    Neubauer, J.

    2013-05-01

    Battery technology is critical for the development of innovative electric vehicle networks, which can enhance transportation sustainability and reduce dependence on petroleum. This cooperative research proposed by Better Place and NREL will focus on predicting the life-cycle economics of batteries, characterizing battery technologies under various operating and usage conditions, and designing optimal usage profiles for battery recharging and use.

  10. Develop the dual fuel conversion system for high output, medium speed diesel engines. Quarterly report number 4, July--September, 1997

    SciTech Connect (OSTI)

    1997-09-23

    This quarter started out with fresh ability to perform sustained engine operation on gas because of the successful operation of the gas compressor last quarter. The authors have completed baseline tests recording emissions and efficiency numbers. This gives the authors data that they have never before been able to acquire in the facility. In addition to the baseline data they have recorded data with a host of additional engine variables. These variables include the adjustments of ignition timing, air fuel ratio, air inlet temperatures and some propane seeding of the injected gas. With the background data on record they will be able to properly measure the level of positive impact that the port gas injection system provides. The remaining time in this quarter has been focused on completing the application of the port style gas injection system. The next steps in this project all pivot on the application of this port injection system. They have also progressed in the evaluation of the cylinder/engine monitoring system.

  11. Wind Turbine Blade Test Definition of the DeWind DW90 Rotor Blade: Cooperative Research and Development Final Report, CRADA Number CRD-09-326

    SciTech Connect (OSTI)

    Hughes, S.

    2012-05-01

    This CRADA was developed as a funds-in CRADA with DeWind to assess the suitability of facilities and equipment at the NWTC for performing certification blade testing on wind turbine blades made from advanced materials. DeWind produces a wind turbine blade which includes the use of high-strength and stiffness materials. NREL and DeWind had a mutual interest in defining the necessary facilities, equipment, and test methods for testing large wind turbine blades which incorporate advanced materials and adaptive structures, as the demands on test equipment and infrastructure are greater than current capabilities. Work under this CRADA would enable DeWind to verify domestic capability for certification-class static and fatigue testing, while NREL would be able to identify and develop specialized test capabilities based on the test requirements.

  12. Improved Tools for Wind Resource Assessment with Remote Sensing Sodar Device: Cooperative Research and Development Final Report, CRADA Number: CRD-09-363

    SciTech Connect (OSTI)

    Clifton, A.

    2015-02-01

    Under this Agreement, NREL will work with the Participant to characterize wind resource assessment measurement systems needed for the design, construction, and integration of wind energy conversion systems to produce electricity for utility grid applications. This work includes, but is not limited to, research and development of hardware and software systems needed to advance wind energy resource assessment technology at speed and scale for use by electric utilities and wind power system integrators.

  13. Solar Resource Measurements in 1400 JR Lynch Street, Jackson, Mississippi: Cooperative Research and Development Final Report, CRADA Number CRD-07-254

    SciTech Connect (OSTI)

    Stoffel, T.

    2014-01-01

    Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NREL mission: Equipment will be used by Jackson State University for solar radiation data monitoring. This is a continuing effort of the Historically Black Colleges and Universities Solar Measurement Network; Provide high quality ground-truth data for satellite remote sensing validation; Support development of radiative transfer models for estimating solar irradiance from available meteorological observations; Provide solar resource information needed for technology deployment and operations. Data acquired under this agreement will be available to the public through NREL's Measurement & Instrumentation Data Center (MIDC) (www.nrel.gov/midc) or the Renewable Resource Data Center (RReDC ) (http://rredc.nrel.gov). The MIDC offers a variety of standard data display, access, and analysis tools designed to address the needs of a wide user audience (e.g., industry, academia, and government interests.

  14. Solar Resource Measurements in Cocoa, Florida (FSEC) - Equipment Loaned to NREL: Cooperative Research and Development Final Report, CRADA Number CRD-08-318

    SciTech Connect (OSTI)

    Stoffel, T.; Afshin, A.

    2014-01-01

    Site-specific measurements of global and diffuse solar irradiance components, passively separated by alternate shading and unshading of a pyranometer mounted under a shading band with alternating opaque and open panels (for a site other than NREL) are needed to verify the underlying theory and mathematical techniques for developing direct, global and diffuse renewable resource data from such a system. These data are used for several research and development activities consistent with the NREL mission: Establish a national 30-year climatological database of measured solar irradiances; Support development of radiative transfer models for estimating solar irradiance from available meteorological observations; Provide solar resource information needed for technology deployment and operations. NREL will provide the supporting equipment (Shadow Bank Stand) for the specially designed shading band. FSEC will provide the calibrated pyranometer and perform data acquisition of the radiometer signal. Data acquired under this agreement will be shared with the NREL Principle Investigator for the purposes of validating techniques for estimating direct radiation from global and diffuse components measured with the ZEBRA system.

  15. Overcoming the Recalcitrance of Cellulosic Biomass by Value Prior to Pulping: Cooperative Research and Development Final Report, CRADA Number CRD-07-221

    SciTech Connect (OSTI)

    Lowell, A.

    2012-04-01

    The Value Prior to Pulping (VPP) project goal was to demonstrate the technical and commercial feasibility of introducing a new value stream into existing pulp and paper mills. Essentially the intent was to transfer the energy content of extracted hemicellulose from electricity and steam generated in the recovery boiler to a liquid transportation fuel. The hemicellulose fraction was extracted prior to pulping, fractionated, or conditioned if necessary, and fermented to ethanol. Commercial adaptation of the process to wood hemicelluloses was a prerequisite for using this less currently valued component available from biomass and wood. These hemicelluloses are predominately glucurono-xylan in hardwoods and galactoglucomannan in softwoods (with a significant softwood component of an arabino-xylan) and will yield fermentation substrates different from cellulose. NREL provided its expertise in the area of fermentation host evaluation using its Zymomonas strains on the CleanTech Partner's (CTP) VPP project. The project was focused on the production of fuel ethanol and acetic acid from hemicellulose streams generated from wood chips of industrially important hardwood and softwood species. NREL was one of four partners whose ethanologen was tested on the hydrolyzed extracts. The use of commercially available enzymes to treat oligomeric sugar extracts was also investigated and coupled with fermentation. Fermentations by NREL were conducted with the Zymomonas mobilis organism with most of the work being performed with the 8b strain. The wood extracts hydrolyzed and/or fermented by NREL were those derived from maple, mixed southern hardwoods, and loblolly pine. An unhydrolyzed variant of the mixed southern hardwood extract possessed a large concentration of oligomeric sugars and enzymatic hydrolysis was performed with a number of enzymes, followed by fermentation. The fermentation of the wood extracts was carried out at bench scale in flasks or small bioreactors, with a maximum volume of 500 mL.

  16. Evaluation of Solar Grade Silicon Produced by the Institute of Physics and Technology: Cooperative Research and Development Final Report, CRADA Number CRD-07-211

    SciTech Connect (OSTI)

    Page, M.

    2013-02-01

    NREL and Solar Power Industries will cooperate to evaluate technology for producing solar grade silicon from industrial waste of the phosphorus industry, as developed by the Institute of Physics and Technology (IPT), Kazakhstan. Evaluation will have a technical component to assess the material quality and a business component to assess the economics of the IPT process. The total amount of silicon produced by IPT is expected to be quite limited (50 kg), so evaluations will need to be done on relatively small quantities (? 5 kg/sample).

  17. Low Cost Thin Film Building-Integrated PV Systems: Cooperative Research and Development Final Report, CRADA Number CRD-07-239

    SciTech Connect (OSTI)

    Stradins, P.

    2011-10-01

    In this CRADA, NREL's Silicon group members performed the following research activities: (1) investigation of the role of hydrogen in growth of a mixed-phase nc-Si:H/a-Si:H material; (2) role of hydrogen in light-induced degradation of a-Si:H and development of Staebler-Wronski effect resistive a-Si:H; and (3) performing characterizations of UniSolar's a-Si:H and nc-Si materials, with goal to help optimizing large-area uniformity and quality of the UniSolar's nanocrystalline Si:H.

  18. Equipment Loan for Concentrated PV Cavity Converter (PVCC) Research: Cooperative Research and Development Final Report, CRADA Number CRD-08-285

    SciTech Connect (OSTI)

    Netter, Judy

    2015-07-28

    Interest in High Concentration Photovoltaics (HCPV) for terrestrial applications has significantly grown in recent years. A major driver behind this growth trend is the availability of high efficiency multi-junction (MJ) cells that promise reliable operation under high concentrations (500 to 1000 suns). The primary impact of HCPV on the solar electricity cost is the dramatic reduction in cell cost. For terrestrial HCPV systems, operating at concentrations ≥ 500 suns, the expensive MJ cells are marginally affordable. Most recently, triple-junction test cells have achieved a conversion efficiency of over 40% under concentrated sunlight. Photovoltaic Cavity Converter (PVCC) is a multi-bandgap, high concentration PV device developed by United Innovations, Inc., under subcontract to NREL. The lateral- (2- dimensional) structure of PVCC, as opposed to vertical multi-junction (MJ) structure, helps to circumvent most of the developmental challenges MJ technology has yet to overcome. This CRADA will allow the continued development of this technology by United Innovations. This project was funded by the California Energy Commission and is the second phase of a twopart demonstration program. The key advantage of the design was the use of a PVCC as the receiver. PVCCs efficiently process highly concentrated solar radiation into electricity by recycling photons that are reflected from the surface of the cells. Conventional flat, twodimensional receivers cannot recycle photons and the reflected photons are lost to the conversion process.

  19. Low Cost High Efficiency InP-Based Solar Cells: Cooperative Research and Development Final Report, CRADA Number CRD-09-344

    SciTech Connect (OSTI)

    Wanlass, M.

    2012-07-01

    NREL will develop a method of growing and fabricating single junction InP solar cells on 2-inch InP substrates on which a release layer has been deposited by MicroLink Devices. NREL will transfer to MicroLink the details of the InP solar cell layer structure and test results in order that the 2-inch results can be replicated on 4-inch InP substrates. NREL will develop a method of growing and fabricating single junction InP solar cells, including a metamorphic layer, on 2-inch GaAs substrates on which a release layer has been deposited by MicroLink Devices. NREL will transfer to MicroLink the details of the InP solar cell layer structure and test results in order that the 2-inch results can be replicated on 6-inch GaAs substrates. NREL will perform characterization measurements of the solar cells, including I-V and quantum efficiency measurements at AM1.5 1-sun.

  20. Pilot Scale Integrated Biorefinery for Producing Ethanol from Hybrid Algae: Cooperative Research and Development Final Report, CRADA Number CRD-10-389

    SciTech Connect (OSTI)

    Pienkos, P. T.

    2013-11-01

    This collaboration between Algenol Biofuels Inc. and NREL will provide valuable information regarding Direct to Ethanol technology. Specifically, the cooperative R&D will analyze the use of flue gas from industrial sources in the Direct to Ethanol process, which may demonstrate the potential to significantly reduce greenhouse gas emissions while simultaneously producing a valuable product, i.e., ethanol. Additionally, Algenol Biofuels Inc. and NREL will develop both a techno-economic model with full material and energy balances and an updated life-cycle analysis to identify greenhouse gas emissions relative to gasoline, each of which will provide a better understanding of the Direct to Ethanol process and further demonstrate that it is a breakthrough technology with varied and significant benefits.

  1. Novel Biological Conversion of Hydrogen and Carbon Dioxide Directly into Biodiesel: Cooperative Research and Development Final Report, CRADA Number: CRD-10-408

    SciTech Connect (OSTI)

    Maness, P. C.

    2014-06-01

    OPX Biotechnologies, Inc. (OPX), the National Renewable Energy Laboratory (NREL), and Johnson Matthey will develop and optimize a novel, engineered microorganism that directly produces biodiesel from renewable hydrogen (H2) and carbon dioxide (CO2). The proposed process will fix CO2 utilizing H2 to generate an infrastructure-compatible, energy-dense fuel at costs of less than $2.50 per gallon, with water being produced as the primary byproduct. NREL will perform metabolic engineering on the bacterium Cupriavidus necator (formerly Ralstonia eutropha) and a techno-economic analysis to guide future scale-up work. H2 and CO2 uptakes rates will be genetically increased, production of free fatty acids will be enhanced and their degradation pathway blocked in order to meet the ultimate program goals.

  2. Application of Robust Design and Advanced Computer Aided Engineering Technologies: Cooperative Research and Development Final Report, CRADA Number CRD-04-143

    SciTech Connect (OSTI)

    Thornton, M.

    2013-06-01

    Oshkosh Corporation (OSK) is taking an aggressive approach to implementing advanced technologies, including hybrid electric vehicle (HEV) technology, throughout their commercial and military product lines. These technologies have important implications for OSK's commercial and military customers, including fleet fuel efficiency, quiet operational modes, additional on-board electric capabilities, and lower thermal signature operation. However, technical challenges exist with selecting the optimal HEV components and design to work within the performance and packaging constraints of specific vehicle applications. SK desires to use unique expertise developed at the Department of Energy?s (DOE) National Renewable Energy Laboratory (NREL), including HEV modeling and simulation. These tools will be used to overcome technical hurdles to implementing advanced heavy vehicle technology that meet performance requirements while improving fuel efficiency.

  3. NREL Wind Turbine Blade Structural Testing of the Modular Wind Energy MW45 Blade: Cooperative Research and Development Final Report, CRADA Number CRD-09-354

    SciTech Connect (OSTI)

    Hughes, S.

    2012-05-01

    This CRADA was a purely funds-in CRADA with Modular Wind Energy (MWE). MWE had a need to perform full-scale testing of a 45-m wind turbine blade. NREL/NWTC provided the capabilities, facilities, and equipment to test this large-scale MWE wind turbine blade. Full-scale testing is required to demonstrate the ability of the wind turbine blade to withstand static design load cases and demonstrate the fatigue durability. Structural testing is also necessary to meet international blade testing certification requirements. Through this CRADA, MWE would obtain test results necessary for product development and certification, and NREL would benefit by working with an industrial partner to better understand the unique test requirements for wind turbine blades with advanced structural designs.

  4. Improving Translation Models for Predicting the Energy Yield of Photovoltaic Power Systems. Cooperative Research and Development Final Report, CRADA Number CRD-13-526

    SciTech Connect (OSTI)

    Emery, Keith

    2015-08-04

    The project under this CRADA will analyze field data of various flat-plate and concentrator module technologies and cell measurements at the laboratory level. The field data will consist of current versus voltage data collected over many years on a latitude tilt test bed for Si, CdTe, amorphous silicon, and CIGS technologies. The concentrator data will be for mirror- and lens-based module designs using multijunction cells. The laboratory data will come from new measurements of cell performance with systematic variation of irradiance, temperature and spectral composition. These measurements will be labor-intensive and the aim will be to cover the widest possible parameter space for as many different PV samples as possible. The data analysis will require software tools to be developed. These tools will be customized for use with the specific NREL datasets and will be unsuitable for commercial release. The tools will be used to evaluate different translation equations against NREL outdoor datasets.

  5. Big Numbers | Jefferson Lab

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

    Big Numbers Big Numbers May 16, 2011 This article has some numbers in it. In principle, numbers are just language, like English or Japanese. Nevertheless, it is true that not everyone is comfortable or facile with numbers and may be turned off by too many of them. To those people, I apologize that this article pays less attention to maximizing the readership than some I do. But sometimes it's just appropriate to indulge one's self, so here goes. When we discuss the performance of some piece of

  6. Development of a catalyst for conversion of syngas-derived materials to isobutylene. Quarterly report number 19, October 1--December 31, 1995

    SciTech Connect (OSTI)

    Spehlmann, B.C.

    1996-07-01

    The goals of this project are to develop a catalyst and process for the conversion of syngas to isobutanol. After identification and optimization of key catalyst and process characteristics, the commercial potential of the process is to be evaluated by an economic analysis. From independent process variable studies to investigate the conversion of a methanol/ethanol feed to isobutanol, the best performance to date has been achieved with the 2% Pt on Zn/Mn/Zr oxide catalyst. Using Hyprotech Hysim v2.5 process simulation software, and considering both gas and liquid recycle loops in the process flow diagram, the overall carbon conversion is 98% with 22% selectivity to isobutanol. The expected production of isobutanol is 92 MT/day from 500 MT/day of methanol and 172 MT/day of ethanol feed. An additional 13 MT/day of isobutryaldehyde intermediate is recovered in the liquid product and vent streams. Because of the low selectivity (22%) of the methanol conversion catalyst to isobutanol, the process is uneconomical, even if the isobutanol is valued as a solvent ($903/MT) and not as isobutylene for MTBE production ($352/MT).

  7. Base-Catalyzed Depolymerization of Lignin with Heterogeneous Catalysts: Cooperative Research and Development Final Report, CRADA Number CRD-13-513

    SciTech Connect (OSTI)

    Beckham, Gregg T.

    2015-08-04

    We will synthesize and screen solid catalysts for the depolymerization of lignin to monomeric and oligomeric oxygenated species, which could be fractionated and integrated into refinery intermediate streams for selective upgrading, or catalytically upgraded to fuels and chemicals. This work will primarily focus on the synthesis and application of layered double hydroxides (LDHs) as recyclable, heterogeneous catalysts for depolymerization of lignin model compounds and softwood lignin. LDHs have been shown in our group to offer good supports and catalysts to promote base-catalyzed depolymerization of lignin model compounds and in preliminary experiments for the depolymerization of lignin from an Organosolv process. We will also include additional catalyst supports such as silica, alumina, and carbon as identified in ongoing and past efforts at NREL. This work will consist of two tasks. Overall, this work will be synergistic with ongoing efforts at NREL, funded by the DOE Biomass Program, on the development of catalysts for lignin depolymerization in the context of biochemical and thermochemical conversion of corn stover and other biomass feedstocks to advanced fuels and chemicals.

  8. Recognition and Awards Program - Hanford Site

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

    About Us Hanford Site Wide Programs DOE Human Resources Management Recognition and Awards Program About Us DOE Human Resources Management Division DOE Employment Recognition and Awards Program Gold Awards Silver Award Federal Employees Union (AFGE Local 788) Work Schedules / Pay and Leave Benefits and Services EEO & Diversity Recognition and Awards Program Email Email Page | Print Print Page |Text Increase Font Size Decrease Font Size Welcome to DOE Human Resources Management Division

  9. Mechanism and Substrate Recognition of 2-Hydroxyethylphosphonate...

    Office of Scientific and Technical Information (OSTI)

    SciTech Connect Search Results Journal Article: Mechanism and Substrate Recognition of ... Publication Date: 2011-09-20 OSTI Identifier: 1024499 Resource Type: Journal Article ...

  10. Substrate Recognition Strategy for Botulinum Neurotoxin

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

    Substrate Recognition Strategy for Botulinum Neurotoxin Print Clostridal neurotoxins (CNTs) are the causative agents of the neuroparalytic diseases botulism and tetanus. By...

  11. Reciprocal Recognition of Existing Personnel Security Clearances

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

    2006-07-20

    Provides direction for implementing actions required by the Office of Management and Budget memorandum, Reciprocal Recognition of Existing Personnel Security Clearances.

  12. Robotic CCD microscope for enhanced crystal recognition

    DOE Patents [OSTI]

    Segelke, Brent W.; Toppani, Dominique

    2007-11-06

    A robotic CCD microscope and procedures to automate crystal recognition. The robotic CCD microscope and procedures enables more accurate crystal recognition, leading to fewer false negative and fewer false positives, and enable detection of smaller crystals compared to other methods available today.

  13. Innovative Manufacturing Initiative Recognition Day - Final Participant

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

    Listing | Department of Energy Day - Final Participant Listing Innovative Manufacturing Initiative Recognition Day - Final Participant Listing PDF icon imi_recogitionday_participants.pdf More Documents & Publications Innovative Manufacturing Initiative Recognition Day 2015 AMO Peer Review Agenda CX-100154 Categorical Exclusion Determination

  14. Innovative Manufacturing Initiative Recognition Day, Advanced Manufacturing

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

    Office (AMO) | Department of Energy Day, Advanced Manufacturing Office (AMO) Innovative Manufacturing Initiative Recognition Day, Advanced Manufacturing Office (AMO) PDF icon imi_recogitionday_leo_june2012.pdf More Documents & Publications Innovative Manufacturing Initiative Recognition Day Advanced Manufacturing Office Overview Unlocking the Potential of Additive Manufacturing in the Fuel Cells Industry

  15. Savannah River Site Cleanup By the Numbers | Department of Energy

    Office of Environmental Management (EM)

    Site Cleanup By the Numbers Savannah River Site Cleanup By the Numbers Savannah River Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites ...

  16. California Natural Gas Number of Commercial Consumers (Number...

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

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

  17. Innovative Manufacturing Initiatives Recognition Day Agenda | Department of

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

    Energy Initiatives Recognition Day Agenda Innovative Manufacturing Initiatives Recognition Day Agenda PDF icon imi_recogitionday_agenda.pdf More Documents & Publications Innovative Manufacturing Initiative Recognition Day Manufacturing Demonstration Facilities Workshop Agenda, March 2012 Critical Materials Workshop Agenda

  18. Characterizing Loop Dynamics and Ligand Recognition in Human...

    Office of Scientific and Technical Information (OSTI)

    Characterizing Loop Dynamics and Ligand Recognition in Human- and Avian-Type Influenza ... Recognition in Human- and Avian-Type Influenza Neuraminidases via Generalized Born ...

  19. Berkeley Lab Climate Software Honored for Pattern Recognition...

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

    Climate Software Honored for Pattern Recognition Advances Berkeley Lab Climate Software Honored for Pattern Recognition Advances September 17, 2015 Contact: Kathy Kincade, +1 510 ...

  20. Los Alamos National Laboratory receives Star Status recognition...

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

    LANL receives recognition for safety excellence Los Alamos National Laboratory receives Star Status recognition for safety excellence from Department of Energy Los Alamos becomes...

  1. Lemelson Recognition and Mentoring Programme L RAMP | Open Energy...

    Open Energy Info (EERE)

    Lemelson Recognition and Mentoring Programme L RAMP Jump to: navigation, search Name: Lemelson Recognition and Mentoring Programme (L-RAMP) Place: India Sector: Services Product:...

  2. Development of New Absorber Materials to Achieve Organic Photovoltaic Commercial Modules with 15% Efficiency and 20 Years Lifetime: Cooperative Research and Development Final Report, CRADA Number CRD-12-498

    SciTech Connect (OSTI)

    Olson, D.

    2014-08-01

    Under this CRADA the parties will develop intermediates or materials that can be employed as the active layer in dye sensitized solar cells printed polymer systems, or small molecule organic photovoltaics.

  3. 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.

  4. 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.

  5. Visual cluster analysis and pattern recognition methods

    DOE Patents [OSTI]

    Osbourn, Gordon Cecil; Martinez, Rubel Francisco

    2001-01-01

    A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

  6. Webinar: Leadership Recognition with Housing Innovation Awards

    Broader source: Energy.gov [DOE]

    Title: Leadership Recognition with Housing Innovation Awards             Date: Wednesday, May 21, 2014Time: 12:00PM - 1:00 PM EST

  7. Innovative Manufacturing Initiatives Recognition Day Agenda

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

    Innovative Manufacturing Initiatives Recognition Day June 20, 2012 The Embassy Row Hotel - 2015 Massachusetts Ave, NW 9:00-9:05am Welcome - Dr. Leo Christodoulou, DOE AMO Program...

  8. The structural basis for receptor recognition of human interleukin-18

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

    Tsutsumi, Naotaka; Kimura, Takeshi; Arita, Kyohei; Ariyoshi, Mariko; Ohnishi, Hidenori; Yamamoto, Takahiro; Zuo, Xiaobing; Maenaka, Katsumi; Park, Enoch Y.; Kondo, Naomi; et al

    2014-12-15

    Interleukin (IL)-18 is a proinflammatory cytokine that belongs to the IL-1 family and plays an important role in inflammation. The uncontrolled release of this cytokine is associated with severe chronic inflammatory disease. IL-18 forms a signalling complex with the IL-18 receptor α (Rα) and β (Rβ) chains at the plasma membrane, which induces multiple inflammatory cytokines. Here, we present a crystal structure of human IL-18 bound to the two receptor extracellular domains. Generally, the receptors’ recognition mode for IL-18 is similar to IL-1β; however, certain notable differences were observed. The architecture of the IL-18 receptor second domain (D2) is uniquemore » among the other IL-1R family members, which presumably distinguishes them from the IL-1 receptors that exhibit a more promiscuous ligand recognition mode. The structures and associated biochemical and cellular data should aid in developing novel drugs to neutralize IL-8 activity.« less

  9. The structural basis for receptor recognition of human interleukin-18

    SciTech Connect (OSTI)

    Tsutsumi, Naotaka; Kimura, Takeshi; Arita, Kyohei; Ariyoshi, Mariko; Ohnishi, Hidenori; Yamamoto, Takahiro; Zuo, Xiaobing; Maenaka, Katsumi; Park, Enoch Y.; Kondo, Naomi; Shirakawa, Masahiro; Tochio, Hidehito; Kato, Zenichiro

    2014-12-15

    Interleukin (IL)-18 is a proinflammatory cytokine that belongs to the IL-1 family and plays an important role in inflammation. The uncontrolled release of this cytokine is associated with severe chronic inflammatory disease. IL-18 forms a signalling complex with the IL-18 receptor α (Rα) and β (Rβ) chains at the plasma membrane, which induces multiple inflammatory cytokines. Here, we present a crystal structure of human IL-18 bound to the two receptor extracellular domains. Generally, the receptors’ recognition mode for IL-18 is similar to IL-1β; however, certain notable differences were observed. The architecture of the IL-18 receptor second domain (D2) is unique among the other IL-1R family members, which presumably distinguishes them from the IL-1 receptors that exhibit a more promiscuous ligand recognition mode. The structures and associated biochemical and cellular data should aid in developing novel drugs to neutralize IL-8 activity.

  10. New Lab facility receives green building recognition

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

    New Lab Facility Receives Green Building Recognition Community Connections: Your link to news and opportunities from Los Alamos National Laboratory Latest Issue:May 2016 all issues All Issues » submit New Lab facility receives green building recognition The Radiological Laboratory Utility Office Building is the first to achieve Leadership in Energy and Environmental Design status and LEED Gold certification from the U.S. Green Building Council. August 1, 2012 dummy image Read our archives

  11. Substrate Recognition Strategy for Botulinum Neurotoxin

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

    Substrate Recognition Strategy for Botulinum Neurotoxin Substrate Recognition Strategy for Botulinum Neurotoxin Print Wednesday, 25 May 2005 00:00 Clostridal neurotoxins (CNTs) are the causative agents of the neuroparalytic diseases botulism and tetanus. By inhibiting release of the neurotransmitter acetylcholine, for example, the neurotoxin produced by the bacterium Clostridium botulinum interferes with nerve impulses and causes a paralysis of respiratory and skeletal muscles that can cause

  12. Mechanism and Substrate Recognition of 2-Hydroxyethylphosphonate

    Office of Scientific and Technical Information (OSTI)

    Dioxygenase (Journal Article) | SciTech Connect SciTech Connect Search Results Journal Article: Mechanism and Substrate Recognition of 2-Hydroxyethylphosphonate Dioxygenase Citation Details In-Document Search Title: Mechanism and Substrate Recognition of 2-Hydroxyethylphosphonate Dioxygenase HEPD belongs to the superfamily of 2-His-1-carboxylate non-heme iron-dependent dioxygenases. It converts 2-hydroxyethylphosphonate (2-HEP) to hydroxymethylphosphonate (HMP) and formate. Previously

  13. Recognition Ceremony to Highlight Students' Success

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

    Recognition Ceremony to Highlight Students' Success For more information contact: Syl Morgan-Smith (303) 275-3001 e:mail: Public Affairs Golden, Colo., June 2, 1998 — A recognition ceremony June 3 featuring special guest Vinny Castilla of the Colorado Rockies will commemorate the success of a pilot tutor program involving about 200 students in 17 Denver Public Schools. The Coalition for Learning Opportunities and United Tutors (CLOUT) paired volunteers with fourth graders who needed help with

  14. Door latching recognition apparatus and process

    DOE Patents [OSTI]

    Eakle, Jr., Robert F.

    2012-05-15

    An acoustic door latch detector is provided in which a sound recognition sensor is integrated into a door or door lock mechanism. The programmable sound recognition sensor can be trained to recognize the acoustic signature of the door and door lock mechanism being properly engaged and secured. The acoustic sensor will signal a first indicator indicating that proper closure was detected or sound an alarm condition if the proper acoustic signature is not detected within a predetermined time interval.

  15. Fast transient security evaluation of power systems by using pattern recognition techniques

    SciTech Connect (OSTI)

    Mokhtari, S.

    1983-01-01

    A power system is a dynamic system. The reaction of a power network to the same set of disturbances is different for various initial equilibrium states. For a given set of contingencies, some of the initial equilibrium states are stable and some of them are unstable. The purpose of this dissertation is to identify if a given operating conditions of the system is stable (secure) or unstable (insecure) for certain disturbances by using real time data. The time required for on-line security analysis can be reduced if pattern recognition techniques are employed. The use of a pattern recognition technique in on-line transient security analysis of power systems is examined. Load magnitudes are treated as random variables with an assumed statistical distribution having a standard deviation of 10%. The simulation technique is applied, off-line, to check system security for the defined set of contingencies. For each initial system condition, the potentially good variables are identified. The number of variables is reduced and variables with the highest discriminatory power are identified. Two decision rules are then developed by using Generalized Square Distance and K-Nearest Neighbor classification techniques. Next, the performance of each classifier is evaluated by using two risk estimating techniques, Jackknife Risk Estimation and Independent Test Risk estimation. The best classifier is identified. Finally, using this classifier, a computer program is developed. This program is capable of predicting, on-line, the security and insecurity of the given power system for any initial system condition within the range defined for the training set. The important features of this program are its accuracy, speed, adaptability and up-dating scheme.

  16. DOE/ID-Number

    Energy Savers [EERE]

    ... automation industry is the Industrial Process Monitoring (IPM) profile, which is under development by ... recommended best practice to pre-load the keys into the ZigBee devices ...

  17. DOE/ID-Number

    Office of Environmental Management (EM)

    data from short-term tests. To collect the necessary data as part of the R&D program and engineering-scale demonstration, more effective monitoring systems must be developed to...

  18. DOE/ID-Number

    Energy Savers [EERE]

    Disposal Options for Research and Development for Spent Nuclear Fuel and High Basis for Identification of Disposal Options for Research and Development for Spent Nuclear Fuel and High-Level Waste Prepared for U.S. Department of Energy Used Fuel Disposition Campaign Rob P. Rechard Barry Goldstein Larry H. Brush Sandia National Laboratories James A. Blink Mark Sutton Lawrence Livermore National Laboratory Frank V. Perry Los Alamos National Laboratory March FCRD-USED-2011-0000 asis for

  19. DOE/ID-Number

    Office of Environmental Management (EM)

    Disposal Options for Research and Development for Spent Nuclear Fuel and High Basis for Identification of Disposal Options for Research and Development for Spent Nuclear Fuel and High-Level Waste Prepared for U.S. Department of Energy Used Fuel Disposition Campaign Rob P. Rechard Barry Goldstein Larry H. Brush Sandia National Laboratories James A. Blink Mark Sutton Lawrence Livermore National Laboratory Frank V. Perry Los Alamos National Laboratory March FCRD-USED-2011-0000 asis for

  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. Economic Development

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

    Economic Development Economic Development Los Alamos is committed to investing and partnering in economic development initiatives and programs that have a positive impact to stimulate business growth that creates jobs and strengthens communities in Northern New Mexico. September 20, 2013 LANS Venture Acceleration Fund (VAF) award enabled Ideum to develop motion recognition software for international release. Jim Spadaccini (R) has tapped into the Lab's economic development programs: VAF, NMSBA,

  2. New Jersey Natural Gas Number of Industrial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Industrial Consumers (Number of Elements) New Jersey 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...

  3. Kentucky Natural Gas Number of Industrial Consumers (Number of...

    Gasoline and Diesel Fuel Update (EIA)

    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...

  4. Oregon Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Oregon 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...

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

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

    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...

  6. Wyoming Natural Gas Number of Industrial Consumers (Number of...

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

    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...

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

    Annual Energy Outlook [U.S. Energy Information Administration (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...

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

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

    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...

  9. Maryland Natural Gas Number of Industrial Consumers (Number of...

    Gasoline and Diesel Fuel Update (EIA)

    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...

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

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

    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...

  11. Michigan Natural Gas Number of Industrial Consumers (Number of...

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

    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...

  12. Ohio Natural Gas Number of Industrial Consumers (Number of Elements...

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

    Industrial Consumers (Number of Elements) Ohio 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...

  13. Mississippi Natural Gas Number of Industrial Consumers (Number...

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

    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...

  14. New York Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) New York 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. Montana Natural Gas Number of Industrial Consumers (Number of...

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

    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...

  16. Missouri Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Missouri 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...

  17. Maine Natural Gas Number of Industrial Consumers (Number of Elements...

    Gasoline and Diesel Fuel Update (EIA)

    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...

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

    Gasoline and Diesel Fuel Update (EIA)

    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...

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

    Gasoline and Diesel Fuel Update (EIA)

    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...

  1. Nebraska Natural Gas Number of Industrial Consumers (Number of...

    Gasoline and Diesel Fuel Update (EIA)

    Industrial Consumers (Number of Elements) Nebraska 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...

  2. Minnesota Natural Gas Number of Industrial Consumers (Number...

    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 ...

  3. Minnesota Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    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 ...

  4. Minnesota Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    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 ...

  5. Connecticut Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) Connecticut 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...

  6. Connecticut Natural Gas Number of Residential Consumers (Number...

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

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

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

    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...

  8. California Natural Gas Number of Residential Consumers (Number...

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

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

  9. California Natural Gas Number of Industrial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Industrial Consumers (Number of Elements) California 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 ...

  10. Arizona Natural Gas Number of Residential Consumers (Number of...

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

    Residential Consumers (Number of Elements) Arizona 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...

  11. Arizona Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) Arizona 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...

  12. ZERH Webinar: Sales and Value Recognition of Zero Energy Ready...

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

    ZERH Webinar: Sales and Value Recognition of Zero Energy Ready Homes ZERH Webinar: Sales and Value Recognition of Zero Energy Ready Homes December 18, 2014 12:00PM to 1:15PM EST ...

  13. PM Workshop 2012 Awards Recognition - Secretary's Awards | Department of

    Energy Savers [EERE]

    Energy Workshop 2012 Awards Recognition - Secretary's Awards PM Workshop 2012 Awards Recognition - Secretary's Awards 2014 DOE Project Management Workshop PDF icon 29a_PM Workshop 2012 Awards Recognition.pdf More Documents & Publications 2012 Awards for Project Management Secretary's Achievement Award Secretary's 2014 Award of Excellence

  14. Searching for pulsars using image pattern recognition

    SciTech Connect (OSTI)

    Zhu, W. W.; Berndsen, A.; Madsen, E. C.; Tan, M.; Stairs, I. H.; Brazier, A.; Lazarus, P.; Lynch, R.; Scholz, P.; Stovall, K.; Cohen, S.; Dartez, L. P.; Lunsford, G.; Martinez, J. G.; Mata, A.; Ransom, S. M.; Banaszak, S.; Biwer, C. M.; Flanigan, J.; Rohr, M. E-mail: berndsen@phas.ubc.ca; and others

    2014-02-01

    In the modern era of big data, many fields of astronomy are generating huge volumes of data, the analysis of which can sometimes be the limiting factor in research. Fortunately, computer scientists have developed powerful data-mining techniques that can be applied to various fields. In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surveys by using image pattern recognition with deep neural nets—the PICS (Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interference by looking for patterns from candidate plots. Different from other pulsar selection programs that search for expected patterns, the PICS AI is taught the salient features of different pulsars from a set of human-labeled candidates through machine learning. The training candidates are collected from the Pulsar Arecibo L-band Feed Array (PALFA) survey. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of image data with up to thousands of pixels. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its ∼9000 neurons. The deep neural networks in this AI system grant it superior ability to recognize various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated with a large set of candidates from a different pulsar survey, the Green Bank North Celestial Cap survey. In this completely independent test, the PICS ranked 264 out of 277 pulsar-related candidates, including all 56 previously known pulsars and 208 of their harmonics, in the top 961 (1%) of 90,008 test candidates, missing only 13 harmonics. The first non-pulsar candidate appears at rank 187, following 45 pulsars and 141 harmonics. In other words, 100% of the pulsars were ranked in the top 1% of all candidates, while 80% were ranked higher than any noise or interference. The performance of this system can be improved over time as more training data are accumulated. This AI system has been integrated into the PALFA survey pipeline and has discovered six new pulsars to date.

  15. Feature recognition applications in mesh generation

    SciTech Connect (OSTI)

    Tautges, T.J.; Liu, S.S.; Lu, Y.; Kraftcheck, J.; Gadh, R.

    1997-06-01

    The use of feature recognition as part of an overall decomposition-based hexahedral meshing approach is described in this paper. The meshing approach consists of feature recognition, using a c-loop or hybrid c-loop method, and the use of cutting surfaces to decompose the solid model. These steps are part of an iterative process, which proceeds either until no more features can be recognized or until the model has been completely decomposed into meshable sub-volumes. This method can greatly reduce the time required to generate an all-hexahedral mesh, either through the use of more efficient meshing algorithms on more of the geometry or by reducing the amount of manual decomposition required to mesh a volume.

  16. Number

    Office of Legacy Management (LM)

    H. E, Stokinger Be: Trip Report - Mayvood Chemical Works A trip vas made Nednesday, August 24th vith Messrs. Robert W ilson and George Sprague to the Mayvood Chemical Forks, ...

  17. Substrate Recognition Strategy for Botulinum Neurotoxin

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

    Substrate Recognition Strategy for Botulinum Neurotoxin Print Clostridal neurotoxins (CNTs) are the causative agents of the neuroparalytic diseases botulism and tetanus. By inhibiting release of the neurotransmitter acetylcholine, for example, the neurotoxin produced by the bacterium Clostridium botulinum interferes with nerve impulses and causes a paralysis of respiratory and skeletal muscles that can cause death. Researchers from Stanford University have now determined the first structure of a

  18. Substrate Recognition Strategy for Botulinum Neurotoxin

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

    Substrate Recognition Strategy for Botulinum Neurotoxin Print Clostridal neurotoxins (CNTs) are the causative agents of the neuroparalytic diseases botulism and tetanus. By inhibiting release of the neurotransmitter acetylcholine, for example, the neurotoxin produced by the bacterium Clostridium botulinum interferes with nerve impulses and causes a paralysis of respiratory and skeletal muscles that can cause death. Researchers from Stanford University have now determined the first structure of a

  19. Substrate Recognition Strategy for Botulinum Neurotoxin

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

    Substrate Recognition Strategy for Botulinum Neurotoxin Print Clostridal neurotoxins (CNTs) are the causative agents of the neuroparalytic diseases botulism and tetanus. By inhibiting release of the neurotransmitter acetylcholine, for example, the neurotoxin produced by the bacterium Clostridium botulinum interferes with nerve impulses and causes a paralysis of respiratory and skeletal muscles that can cause death. Researchers from Stanford University have now determined the first structure of a

  20. Report: Employee Recruitment and Service Recognition

    Office of Environmental Management (EM)

    Employee Recruitment and Service Recognition September 30, 2009 Submitted by the EMAB Human Capital Subcommittee Background: In Fiscal Year (FY) 2009, the Environmental Management Advisory Board (EMAB) was tasked by Assistant Secretary Triay to continue identifying and sharing corporate experiences, strategies, and programs that are adaptable to EM's diversity and employee recruitment and retention initiatives. In order to pursue this charge, EMAB extended the operation of its Human Capital

  1. Substrate Recognition Strategy for Botulinum Neurotoxin

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

    Substrate Recognition Strategy for Botulinum Neurotoxin Print Clostridal neurotoxins (CNTs) are the causative agents of the neuroparalytic diseases botulism and tetanus. By inhibiting release of the neurotransmitter acetylcholine, for example, the neurotoxin produced by the bacterium Clostridium botulinum interferes with nerve impulses and causes a paralysis of respiratory and skeletal muscles that can cause death. Researchers from Stanford University have now determined the first structure of a

  2. Reducing the size of a data base by using pattern-recognition techniques

    SciTech Connect (OSTI)

    Clapp, N.E. Jr.

    1982-01-01

    An on-line surveillance system at a nuclear power plant samples data and calculates the power spectral density. A method of reducing the amount of stored data by screening the data using a pattern recognition technique was developed. The system stores only the spectra that differ from normal, plus the corresponding plant operating conditions. 7 figures.

  3. Development of Pattern Recognition Options for Combining Safeguards Subsystems

    SciTech Connect (OSTI)

    Burr, Thomas L.; Hamada, Michael S.

    2012-08-24

    This talk reviews project progress in combining process monitoring data and nuclear material accounting data to improve the over nuclear safeguards system. Focus on 2 subsystems: (1) nuclear materials accounting (NMA); and (2) process monitoring (PM).

  4. 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: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Number of Natural Gas

  5. 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: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Number of Natural Gas Industrial

  6. Lessons learned bulletin. Number 2

    SciTech Connect (OSTI)

    Not Available

    1994-05-01

    During the past four years, the Department of Energy -- Savannah River Operations Office and the Westinghouse Savannah River Company (WSRC) Environmental Restoration (ER) Program completed various activities ranging from waste site investigations to closure and post closure projects. Critiques for lessons learned regarding project activities are performed at the completion of each project milestone, and this critique interval allows for frequent recognition of lessons learned. In addition to project related lessons learned, ER also performs lessons learned critiques. T`he Savannah River Site (SRS) also obtains lessons learned information from general industry, commercial nuclear industry, naval nuclear programs, and other DOE sites within the complex. Procedures are approved to administer the lessons learned program, and a database is available to catalog applicable lessons learned regarding environmental remediation, restoration, and administrative activities. ER will continue to use this database as a source of information available to SRS personnel.

  7. Verification Challenges at Low Numbers

    SciTech Connect (OSTI)

    Benz, Jacob M.; Booker, Paul M.; McDonald, Benjamin S.

    2013-06-01

    Many papers have dealt with the political difficulties and ramifications of deep nuclear arms reductions, and the issues of “Going to Zero”. Political issues include extended deterrence, conventional weapons, ballistic missile defense, and regional and geo-political security issues. At each step on the road to low numbers, the verification required to ensure compliance of all parties will increase significantly. Looking post New START, the next step will likely include warhead limits in the neighborhood of 1000 . Further reductions will include stepping stones at1000 warheads, 100’s of warheads, and then 10’s of warheads before final elimination could be considered of the last few remaining warheads and weapons. This paper will focus on these three threshold reduction levels, 1000, 100’s, 10’s. For each, the issues and challenges will be discussed, potential solutions will be identified, and the verification technologies and chain of custody measures that address these solutions will be surveyed. It is important to note that many of the issues that need to be addressed have no current solution. In these cases, the paper will explore new or novel technologies that could be applied. These technologies will draw from the research and development that is ongoing throughout the national laboratory complex, and will look at technologies utilized in other areas of industry for their application to arms control verification.

  8. Frontal view reconstruction for iris recognition

    DOE Patents [OSTI]

    Santos-Villalobos, Hector J; Bolme, David S; Boehnen, Chris Bensing

    2015-02-17

    Iris recognition can be accomplished for a wide variety of eye images by correcting input images with an off-angle gaze. A variety of techniques, from limbus modeling, corneal refraction modeling, optical flows, and genetic algorithms can be used. A variety of techniques, including aspherical eye modeling, corneal refraction modeling, ray tracing, and the like can be employed. Precomputed transforms can enhance performance for use in commercial applications. With application of the technologies, images with significantly unfavorable gaze angles can be successfully recognized.

  9. Pattern recognition monitoring of PEM fuel cell

    DOE Patents [OSTI]

    Meltser, Mark Alexander

    1999-01-01

    The CO-concentration in the H.sub.2 feed stream to a PEM fuel cell stack is monitored by measuring current and voltage behavior patterns from an auxiliary cell attached to the end of the stack. The auxiliary cell is connected to the same oxygen and hydrogen feed manifolds that supply the stack, and discharges through a constant load. Pattern recognition software compares the current and voltage patterns from the auxiliary cell to current and voltage signature determined from a reference cell similar to the auxiliary cell and operated under controlled conditions over a wide range of CO-concentrations in the H.sub.2 fuel stream.

  10. Pattern recognition monitoring of PEM fuel cell

    DOE Patents [OSTI]

    Meltser, M.A.

    1999-08-31

    The CO-concentration in the H{sub 2} feed stream to a PEM fuel cell stack is monitored by measuring current and voltage behavior patterns from an auxiliary cell attached to the end of the stack. The auxiliary cell is connected to the same oxygen and hydrogen feed manifolds that supply the stack, and discharges through a constant load. Pattern recognition software compares the current and voltage patterns from the auxiliary cell to current and voltage signature determined from a reference cell similar to the auxiliary cell and operated under controlled conditions over a wide range of CO-concentrations in the H{sub 2} fuel stream. 4 figs.

  11. 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.

  12. 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

  13. 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: 4/29/2016

  14. 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 Year-9 1980's 551 627 550 1990's 1,508 631 783 345 252 713 923 3,379 3,597 3,625 2000's 3,576 3,535 949 924 312 191 274 278 313 293 2010's 293 286 302 323 328 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  15. Vermont Natural Gas Number of Industrial Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 22 21 14 1990's 15 13 18 20 24 23 27 30 36 37 2000's 38 36 38 41 43 41 35 37 35 36 2010's 38 36 38 13 13 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages:

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 463 208 211 1990's 182 198 159 197 191 192 182 173 217 147 2000's 207 213 184 142 137 145 155 114 109 101 2010's 102 94 97 95 92 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  17. 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: 4/29/2016 Next Release Date:

  18. 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: 4/29/2016 Next Release Date:

  19. 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: 4/29/2016 Next Release Date:

  20. 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: 4/29/2016 Next Release Date: 5/31/2016

  1. Automatic TLI recognition system, programmer`s guide

    SciTech Connect (OSTI)

    Lassahn, G.D.

    1997-02-01

    This report describes the software of an automatic target recognition system (version 14), from a programmer`s point of view. The intent is to provide information that will help people who wish to modify the software. In separate volumes are a general description of the ATR system, Automatic TLI Recognition System, General Description, and a user`s manual, Automatic TLI Recognition System, User`s Guide. 2 refs.

  2. Signal Recognition Particle-Receptor Complex Structure Solved

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

    Signal Recognition Particle-Receptor Complex Structure Solved Signal Recognition Particle-Receptor Complex Structure Solved Print Monday, 27 February 2012 15:06 The signal recognition particle (SRP) is a ubiquitous ribonucleoprotein (RNP) complex that delivers membrane and secretory proteins to the cell membrane in prokaryotes and in eukaryotes to the endoplasmic reticulum (ER), an organelle that forms a network of protein and lipid synthesizing factories. This process, called co-translational

  3. New Mexico Image Recognition Startup Spun Off From A Government...

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

    Image Recognition Startup Spun Off From A Government Lab Far from Silicon Valley, Descartes Labs aims to turn a national research facility's AI research into new ways of...

  4. Y-12 Steam Plant Project Received National Recognition for Project...

    National Nuclear Security Administration (NNSA)

    Steam Plant Project Received National Recognition for Project Management Excellence | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS People Mission ...

  5. Fast Company covers "Just Your Typical New Mexico Image Recognition...

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

    Fast Company covers "Just Your Typical New Mexico Image Recognition Startup Spun Off From A ... covers new technique that may make solar panel production less expensive The ...

  6. Protein Structure Recognition: From Eigenvector Analysis to Structural...

    Office of Scientific and Technical Information (OSTI)

    SciTech Connect Search Results ThesisDissertation: Protein Structure Recognition: From ... include the domain partition and a new structural threading method as well as ...

  7. WPN 03-5: Weatherization Assistance Program National Recognition Awards

    Broader source: Energy.gov [DOE]

    To provide criteria and guidelines for the Weatherization Assistance Program's National Recognition Awards being presented at the 2003 National Weatherization Training Conference in Phoenix, Arizona.

  8. Cooperative control of vehicle swarms for acoustic target recognition...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Cooperative control of vehicle swarms for acoustic target recognition by energy flows. Citation Details In-Document Search Title: Cooperative control of vehicle ...

  9. 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.

  10. 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.

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 8,831 9,159 10,237 1990's 10,521 11,088 11,383 11,726 12,240 12,450 12,755 13,225 13,512 13,932 2000's 14,219 15,068 15,130 15,047 15,429 16,266 16,139 16,150 41,332 16,937 2010's 16,645 17,186 17,758 17,298 17,421 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 60,078 61,969 64,059 1990's 65,310 67,991 69,356 70,938 72,656 74,232 75,175 77,092 78,786 80,958 2000's 82,813 84,760 87,147 88,170 88,600 94,473 94,600 94,963 67,945 96,924 2010's 95,361 97,400 99,738 98,715 99,146 - = No Data Reported; -- = Not Applicable; NA = Not Available;

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 56,191 60,663 63,562 1990's 68,088 70,207 72,647 76,386 80,739 84,041 93,504 97,629 100,251 104,294 2000's 107,566 107,656 102,505 107,506 105,163 109,205 111,127 112,092 111,868 113,630 2010's 113,900 115,609 117,155 118,257 120,111 - = No Data Reported; -- = Not Applicable; NA =

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 435,826 472,928 492,821 1990's 520,140 539,321 575,096 607,388 652,307 678,147 699,159 740,013 777,805 815,908 2000's 858,004 891,227 905,816 953,732 948,283 992,906 1,022,430 1,063,871 1,095,362 1,102,001 2010's 1,115,532 1,128,963 1,142,947 1,161,398 1,183,152 - = No Data

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

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

    Elements) Commercial Consumers (Number of Elements) North Dakota 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 11,905 12,104 12,454 1990's 12,742 12,082 12,353 12,650 12,944 13,399 13,789 14,099 14,422 15,050 2000's 15,531 15,740 16,093 16,202 16,443 16,518 16,848 17,013 17,284 17,632 2010's 17,823 18,421 19,089 19,855 20,687 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 83,517 84,059 84,643 1990's 85,646 87,880 89,522 91,237 93,398 95,818 97,761 98,326 101,930 104,051 2000's 105,660 106,758 108,716 110,048 112,206 114,152 116,615 118,100 120,056 122,065 2010's 123,585 125,392 130,044 133,975 137,972 - = No Data Reported; -- = Not Applicable; NA =

  17. Ohio Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Ohio 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 213,601 219,257 225,347 1990's 233,075 236,519 237,861 240,684 245,190 250,223 259,663 254,991 258,076 266,102 2000's 269,561 269,327 271,160 271,203 272,445 277,767 270,552 272,555 272,899 270,596 2010's 268,346 268,647 267,793 269,081 269,758 - = No Data Reported; -- = Not Applicable; NA = Not

  18. Ohio Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Ohio 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 2,648,972 2,678,838 2,714,839 1990's 2,766,912 2,801,716 2,826,713 2,867,959 2,921,536 2,967,375 2,994,891 3,041,948 3,050,960 3,111,108 2000's 3,178,840 3,195,584 3,208,466 3,225,908 3,250,068 3,272,307 3,263,062 3,273,791 3,262,716 3,253,184 2010's 3,240,619 3,236,160 3,244,274 3,271,074 3,283,869 -

  19. Oklahoma Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Oklahoma 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 87,824 86,666 86,172 1990's 85,790 86,744 87,120 88,181 87,494 88,358 89,852 90,284 89,711 80,986 2000's 80,558 79,045 80,029 79,733 79,512 78,726 78,745 93,991 94,247 94,314 2010's 92,430 93,903 94,537 95,385 96,004 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  20. Oklahoma Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Oklahoma 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 2,772 2,689 2,877 1990's 2,889 2,840 2,859 2,912 2,853 2,845 2,843 2,531 3,295 3,040 2000's 2,821 3,403 3,438 3,367 3,283 2,855 2,811 2,822 2,920 2,618 2010's 2,731 2,733 2,872 2,958 3,063 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  1. Oklahoma Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Oklahoma 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 809,171 805,107 806,875 1990's 814,296 824,172 832,677 842,130 845,448 856,604 866,531 872,454 877,236 867,922 2000's 859,951 868,314 875,338 876,420 875,271 880,403 879,589 920,616 923,650 924,745 2010's 914,869 922,240 927,346 931,981 937,237 - = No Data Reported; -- = Not Applicable; NA = Not

  2. Oregon Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Oregon 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 40,967 41,998 43,997 1990's 47,175 55,374 50,251 51,910 53,700 55,409 57,613 60,419 63,085 65,034 2000's 66,893 68,098 69,150 74,515 71,762 73,520 74,683 80,998 76,868 76,893 2010's 77,370 77,822 78,237 79,276 80,480 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

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

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

    Residential Consumers (Number of Elements) Oregon 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 280,670 288,066 302,156 1990's 326,177 376,166 354,256 371,151 391,845 411,465 433,638 456,960 477,796 502,000 2000's 523,952 542,799 563,744 625,398 595,495 626,685 647,635 664,455 674,421 675,582 2010's 682,737 688,681 693,507 700,211 707,010 - = No Data Reported; -- = Not Applicable; NA = Not

  4. Pennsylvania Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Pennsylvania 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 166,901 172,615 178,545 1990's 186,772 191,103 193,863 198,299 206,812 209,245 214,340 215,057 216,519 223,732 2000's 228,037 225,911 226,957 227,708 231,051 233,132 231,540 234,597 233,462 233,334 2010's 233,751 233,588 235,049 237,922 239,681 - = No Data Reported; -- = Not

  5. Pennsylvania Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Pennsylvania 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 2,237,877 2,271,801 2,291,242 1990's 2,311,795 2,333,377 2,363,575 2,386,249 2,393,053 2,413,715 2,431,909 2,452,524 2,493,639 2,486,704 2000's 2,519,794 2,542,724 2,559,024 2,572,584 2,591,458 2,600,574 2,605,782 2,620,755 2,631,340 2,635,886 2010's 2,646,211 2,667,392 2,678,547

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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;

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

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

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

    Residential Consumers (Number of Elements) Missouri 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 1,180,546 1,194,985 1,208,523 1990's 1,213,305 1,211,342 1,220,203 1,225,921 1,281,007 1,259,102 1,275,465 1,293,032 1,307,563 1,311,865 2000's 1,324,282 1,326,160 1,340,726 1,343,614 1,346,773 1,348,743 1,353,892 1,354,173 1,352,015 1,348,781 2010's 1,348,549 1,342,920 1,389,910 1,357,740

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

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

    Commercial Consumers (Number of Elements) Montana 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 21,382 22,246 22,219 1990's 23,331 23,185 23,610 24,373 25,349 26,329 26,374 27,457 28,065 28,424 2000's 29,215 29,429 30,250 30,814 31,357 31,304 31,817 32,472 33,008 33,731 2010's 34,002 34,305 34,504 34,909 35,205 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  2. Montana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Montana 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 167,883 171,785 171,156 1990's 174,384 177,726 182,641 188,879 194,357 203,435 205,199 209,806 218,851 222,114 2000's 224,784 226,171 229,015 232,839 236,511 240,554 245,883 247,035 253,122 255,472 2010's 257,322 259,046 259,957 262,122 265,849 - = No Data Reported; -- = Not Applicable; NA = Not

  3. Nebraska Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Nebraska 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 60,707 61,365 60,377 1990's 60,405 60,947 61,319 60,599 62,045 61,275 61,117 51,661 63,819 53,943 2000's 55,194 55,692 56,560 55,999 57,087 57,389 56,548 55,761 58,160 56,454 2010's 56,246 56,553 56,608 58,005 57,191 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  4. Nebraska Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Nebraska 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 400,218 403,657 406,723 1990's 407,094 413,354 418,611 413,358 428,201 427,720 439,931 444,970 523,790 460,173 2000's 475,673 476,275 487,332 492,451 497,391 501,279 499,504 494,005 512,013 512,551 2010's 510,776 514,481 515,338 527,397 522,408 - = No Data Reported; -- = Not Applicable; NA = Not

  5. Nevada Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Nevada 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 18,294 18,921 19,924 1990's 20,694 22,124 22,799 23,207 24,521 25,593 26,613 27,629 29,030 30,521 2000's 31,789 32,782 33,877 34,590 35,792 37,093 38,546 40,128 41,098 41,303 2010's 40,801 40,944 41,192 41,710 42,338 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

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

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

    Residential Consumers (Number of Elements) Nevada 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 213,422 219,981 236,237 1990's 256,119 283,307 295,714 305,099 336,353 364,112 393,783 426,221 458,737 490,029 2000's 520,233 550,850 580,319 610,756 648,551 688,058 726,772 750,570 758,315 760,391 2010's 764,435 772,880 782,759 794,150 808,970 - = No Data Reported; -- = Not Applicable; NA = Not

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

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

    Commercial Consumers (Number of Elements) Alabama 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 53 54,306 55,400 56,822 1990's 56,903 57,265 58,068 57,827 60,320 60,902 62,064 65,919 76,467 64,185 2000's 66,193 65,794 65,788 65,297 65,223 65,294 66,337 65,879 65,313 67,674 2010's 68,163 67,696 67,252 67,136 67,806 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

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

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

    Industrial Consumers (Number of Elements) Alabama 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 2,313 2,293 2,380 1990's 2,431 2,523 2,509 2,458 2,477 2,491 2,512 2,496 2,464 2,620 2000's 2,792 2,781 2,730 2,743 2,799 2,787 2,735 2,704 2,757 3,057 2010's 3,039 2,988 3,045 3,143 3,244 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

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

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

    Residential Consumers (Number of Elements) Alabama 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 656 662,217 668,432 683,528 1990's 686,149 700,195 711,043 730,114 744,394 751,890 766,322 781,711 788,464 775,311 2000's 805,689 807,770 806,389 809,754 806,660 809,454 808,801 796,476 792,236 785,005 2010's 778,985 772,892 767,396 765,957 769,418 - = No Data Reported; -- = Not Applicable; NA = Not

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

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

    Commercial Consumers (Number of Elements) Alaska 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 11 11,484 11,649 11,806 1990's 11,921 12,071 12,204 12,359 12,475 12,584 12,732 12,945 13,176 13,409 2000's 13,711 14,002 14,342 14,502 13,999 14,120 14,384 13,408 12,764 13,215 2010's 12,998 13,027 13,133 13,246 13,399 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  11. Alaska Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Alaska 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 66 67,648 68,612 69,540 1990's 70,808 72,565 74,268 75,842 77,670 79,474 81,348 83,596 86,243 88,924 2000's 91,297 93,896 97,077 100,404 104,360 108,401 112,269 115,500 119,039 120,124 2010's 121,166 121,736 122,983 124,411 126,416 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  12. Wyoming Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Wyoming 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 15,342 15,093 14,012 1990's 13,767 14,931 15,064 15,315 15,348 15,580 17,036 15,907 16,171 16,317 2000's 16,366 16,027 16,170 17,164 17,490 17,904 18,016 18,062 19,286 19,843 2010's 19,977 20,146 20,387 20,617 20,894 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  13. Wyoming Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Wyoming 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 113,175 112,126 113,129 1990's 113,598 113,463 114,793 116,027 117,385 119,544 131,910 125,740 127,324 127,750 2000's 129,274 129,897 133,445 135,441 137,434 140,013 142,385 143,644 152,439 153,062 2010's 153,852 155,181 157,226 158,889 160,896 - = No Data Reported; -- = Not Applicable; NA = Not

  14. Rhode Island Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Rhode Island 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 15,128 16,096 16,924 1990's 17,765 18,430 18,607 21,178 21,208 21,472 21,664 21,862 22,136 22,254 2000's 22,592 22,815 23,364 23,270 22,994 23,082 23,150 23,007 23,010 22,988 2010's 23,049 23,177 23,359 23,742 23,934 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  15. Rhode Island Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Rhode Island 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 180,656 185,861 190,796 1990's 195,100 196,438 197,926 198,563 200,959 202,947 204,259 212,777 208,208 211,097 2000's 214,474 216,781 219,769 221,141 223,669 224,320 225,027 223,589 224,103 224,846 2010's 225,204 225,828 228,487 231,763 233,786 - = No Data Reported; -- = Not

  16. South Carolina Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) South 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 Year-7 Year-8 Year-9 1980's 35,414 37,075 38,856 1990's 39,904 39,999 40,968 42,191 45,487 47,293 48,650 50,817 52,237 53,436 2000's 54,794 55,257 55,608 55,909 56,049 56,974 57,452 57,544 56,317 55,850 2010's 55,853 55,846 55,908 55,997 56,172 - = No Data Reported; -- = Not Applicable; NA = Not Available; W

  17. South Carolina Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) South 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 Year-7 Year-8 Year-9 1980's 1,256 1,273 1,307 1990's 1,384 1,400 1,568 1,625 1,928 1,802 1,759 1,764 1,728 1,768 2000's 1,715 1,702 1,563 1,574 1,528 1,535 1,528 1,472 1,426 1,358 2010's 1,325 1,329 1,435 1,452 1,426 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  18. South Carolina Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) South 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 Year-7 Year-8 Year-9 1980's 302,321 313,831 327,527 1990's 339,486 344,763 357,818 370,411 416,773 412,259 426,088 443,093 460,141 473,799 2000's 489,340 501,161 508,686 516,362 527,008 541,523 554,953 570,213 561,196 565,774 2010's 570,797 576,594 583,633 593,286 604,743 - = No Data Reported; -- = Not

  19. South Dakota Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) South Dakota 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 12,480 12,438 12,771 1990's 13,443 13,692 14,133 16,523 15,539 16,285 16,880 17,432 17,972 18,453 2000's 19,100 19,378 19,794 20,070 20,457 20,771 21,149 21,502 21,819 22,071 2010's 22,267 22,570 22,955 23,214 23,591 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  20. South Dakota Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) South 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 Year-7 Year-8 Year-9 1980's 101,468 102,084 103,538 1990's 105,436 107,846 110,291 128,029 119,544 124,152 127,269 130,307 133,095 136,789 2000's 142,075 144,310 147,356 150,725 148,105 157,457 160,481 163,458 165,694 168,096 2010's 169,838 170,877 173,856 176,204 179,042 - = No Data Reported; -- = Not

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

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

    Commercial Consumers (Number of Elements) Tennessee 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 77,104 81,159 84,040 1990's 88,753 89,863 91,999 94,860 97,943 101,561 103,867 105,925 109,772 112,978 2000's 115,691 118,561 120,130 131,916 125,042 124,755 126,970 126,324 128,007 127,704 2010's 127,914 128,969 130,139 131,091 131,001 - = No Data Reported; -- = Not Applicable; NA = Not Available;

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

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

    Industrial Consumers (Number of Elements) Tennessee 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 2,206 2,151 2,555 1990's 2,361 2,369 2,425 2,512 2,440 2,393 2,306 2,382 5,149 2,159 2000's 2,386 2,704 2,657 2,755 2,738 2,498 2,545 2,656 2,650 2,717 2010's 2,702 2,729 2,679 2,581 2,595 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

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

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

    Residential Consumers (Number of Elements) Tennessee 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 534,882 565,856 599,042 1990's 627,031 661,105 696,140 733,363 768,421 804,724 841,232 867,793 905,757 937,896 2000's 969,537 993,363 1,009,225 1,022,628 1,037,429 1,049,307 1,063,328 1,071,756 1,084,102 1,083,573 2010's 1,085,387 1,089,009 1,084,726 1,094,122 1,106,681 - = No Data Reported; -- =

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

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

    Commercial Consumers (Number of Elements) Texas 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 294,879 284,013 270,227 1990's 268,181 269,411 292,990 297,516 306,376 325,785 329,287 332,077 320,922 314,598 2000's 315,906 314,858 317,446 320,786 322,242 322,999 329,918 326,812 324,671 313,384 2010's 312,277 314,041 314,811 314,036 317,217 - = No Data Reported; -- = Not Applicable; NA = Not

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

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

    Industrial Consumers (Number of Elements) Texas 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 4,852 4,427 13,383 1990's 13,659 13,770 5,481 5,823 5,222 9,043 8,796 5,339 5,318 5,655 2000's 11,613 10,047 9,143 9,015 9,359 9,136 8,664 11,063 5,568 8,581 2010's 8,779 8,713 8,953 8,525 8,406 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

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

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

    Residential Consumers (Number of Elements) Texas 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 3,155,948 3,166,168 3,201,316 1990's 3,232,849 3,274,482 3,285,025 3,346,809 3,350,314 3,446,120 3,501,853 3,543,027 3,600,505 3,613,864 2000's 3,704,501 3,738,260 3,809,370 3,859,647 3,939,101 3,984,481 4,067,508 4,156,991 4,205,412 4,248,613 2010's 4,288,495 4,326,156 4,370,057 4,424,103 4,469,282 -

  7. 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 Year-9 1980's 31,329 32,637 32,966 1990's 34,697 35,627 36,145 37,816 39,183 40,101 40,107 40,689 42,054 43,861 2000's 47,201 47,477 50,202 51,063 51,503 55,174 55,821 57,741 59,502 60,781 2010's 61,976 62,885 63,383 64,114 65,134 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  8. 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 Year-8 Year-9 1980's 414,020 418,569 432,377 1990's 453,023 455,649 467,664 484,438 503,583 523,622 562,343 567,786 588,364 609,603 2000's 641,111 657,728 660,677 678,833 701,255 743,761 754,554 778,644 794,880 810,442 2010's 821,525 830,219 840,687 854,389 869,052 - = No Data Reported; -- = Not Applicable; NA = Not

  9. Vermont Natural Gas Number of Commercial Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 2,447 2,698 2,768 1990's 2,949 3,154 3,198 3,314 3,512 3,649 3,790 3,928 4,034 4,219 2000's 4,316 4,416 4,516 4,602 4,684 4,781 4,861 4,925 4,980 5,085 2010's 5,137 5,256 5,535 5,441 5,589 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  10. Vermont Natural Gas Number of Residential Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 15,553 16,616 16,920 1990's 18,300 19,879 20,468 21,553 22,546 23,523 24,383 25,539 26,664 27,931 2000's 28,532 29,463 30,108 30,856 31,971 33,015 34,081 34,937 35,929 37,242 2010's 38,047 38,839 39,917 41,152 42,231 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  11. Virginia Natural Gas Number of Commercial Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 54,071 54,892 61,012 1990's 63,751 67,997 69,629 70,161 72,188 74,690 77,284 78,986 77,220 80,500 2000's 84,646 84,839 86,328 87,202 87,919 90,577 91,481 93,015 94,219 95,704 2010's 95,401 96,086 96,503 97,499 98,741 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

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

    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 Year-8 Year-9 1980's 877 895 895 1990's 929 1,156 1,101 2,706 2,740 2,812 2,822 2,391 2,469 2,984 2000's 1,749 1,261 1,526 1,517 1,217 1,402 1,256 1,271 1,205 1,126 2010's 1,059 1,103 1,132 1,132 1,123 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  13. Virginia Natural Gas Number of Residential Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 550,318 573,731 601,906 1990's 622,883 651,203 664,500 690,061 721,495 753,003 789,985 812,866 847,938 893,887 2000's 907,855 941,582 982,521 996,564 1,029,389 1,066,302 1,085,509 1,101,863 1,113,016 1,124,717 2010's 1,133,103 1,145,049 1,155,636 1,170,161 1,183,894 - = No Data Reported; -- = Not

  14. Washington Natural Gas Number of Commercial Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 51,365 56,487 55,231 1990's 58,148 60,887 63,391 65,810 68,118 70,781 73,708 75,550 77,770 80,995 2000's 83,189 84,628 85,286 87,082 93,559 92,417 93,628 95,615 97,799 98,965 2010's 99,231 99,674 100,038 100,939 101,730 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  15. Washington Natural Gas Number of Industrial Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 3,355 3,564 3,365 1990's 3,428 3,495 3,490 3,448 3,586 3,544 3,587 3,748 3,848 4,040 2000's 4,007 3,898 3,928 3,775 3,992 3,489 3,428 3,630 3,483 3,428 2010's 3,372 3,353 3,338 3,320 3,355 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  16. Washington Natural Gas Number of Residential Consumers (Number of Elements)

    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 Year-7 Year-8 Year-9 1980's 392,469 413,008 425,624 1990's 458,013 492,189 528,913 565,475 604,315 638,603 673,357 702,701 737,208 779,104 2000's 813,319 841,617 861,943 895,800 926,510 966,199 997,728 1,025,171 1,047,319 1,059,239 2010's 1,067,979 1,079,277 1,088,762 1,102,318 1,118,193 - = No Data Reported; -- = Not

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 31,283 33,192 33,880 1990's 32,785 32,755 33,289 33,611 33,756 36,144 33,837 33,970 35,362 35,483 2000's 41,949 35,607 35,016 35,160 34,932 36,635 34,748 34,161 34,275 34,044 2010's 34,063 34,041 34,078 34,283 34,339 - = No Data Reported; -- = Not Applicable; NA = Not Available; W

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 351,024 349,765 349,347 1990's 349,673 350,489 352,463 352,997 352,929 353,629 358,049 362,432 359,783 362,292 2000's 360,471 363,126 361,171 359,919 358,027 374,301 353,292 347,433 347,368 343,837 2010's 344,131 342,069 340,256 340,102 338,652 - = No Data Reported; -- = Not

  19. Wisconsin Natural Gas Number of Commercial Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 96,760 99,157 102,492 1990's 106,043 109,616 112,761 115,961 119,788 125,539 129,146 131,238 134,651 135,829 2000's 140,370 144,050 149,774 150,128 151,907 155,109 159,074 160,614 163,026 163,843 2010's 164,173 165,002 165,657 166,845 167,901 - = No Data Reported; -- = Not Applicable; NA = Not

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

    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 Year-8 Year-9 1980's 7,411 7,218 7,307 1990's 7,154 7,194 7,396 7,979 7,342 6,454 5,861 8,346 9,158 9,756 2000's 9,630 9,864 9,648 10,138 10,190 8,484 5,707 5,999 5,969 6,396 2010's 6,413 6,376 6,581 6,677 7,000 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  1. Wisconsin Natural Gas Number of Residential Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 1,054,347 1,072,585 1,097,514 1990's 1,123,557 1,151,939 1,182,834 1,220,500 1,253,333 1,291,424 1,324,570 1,361,348 1,390,068 1,426,909 2000's 1,458,959 1,484,536 1,514,700 1,541,455 1,569,719 1,592,621 1,611,772 1,632,200 1,646,644 1,656,614 2010's 1,663,583 1,671,834 1,681,001 1,692,891

  2. Arkansas Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Arkansas 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 60 60,355 61,630 61,848 1990's 61,530 61,731 62,221 62,952 63,821 65,490 67,293 68,413 69,974 71,389 2000's 72,933 71,875 71,530 71,016 70,655 69,990 69,475 69,495 69,144 69,043 2010's 67,987 67,815 68,765 68,791 69,011 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  3. Arkansas Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Arkansas 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 1,410 1,151 1,412 1990's 1,396 1,367 1,319 1,364 1,417 1,366 1,488 1,336 1,300 1,393 2000's 1,414 1,122 1,407 1,269 1,223 1,120 1,120 1,055 1,104 1,025 2010's 1,079 1,133 990 1,020 1,009 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  4. Arkansas Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Arkansas 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 475 480,839 485,112 491,110 1990's 488,850 495,148 504,722 513,466 521,176 531,182 539,952 544,460 550,017 554,121 2000's 560,055 552,716 553,192 553,211 554,844 555,861 555,905 557,966 556,746 557,355 2010's 549,970 551,795 549,959 549,764 549,034 - = No Data Reported; -- = Not Applicable; NA =

  5. Colorado Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Colorado 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 108 109,770 110,769 112,004 1990's 112,661 113,945 114,898 115,924 115,994 118,502 121,221 123,580 125,178 129,041 2000's 131,613 134,393 136,489 138,621 138,543 137,513 139,746 141,420 144,719 145,624 2010's 145,460 145,837 145,960 150,145 150,235 - = No Data Reported; -- = Not Applicable; NA = Not

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

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

    Industrial Consumers (Number of Elements) Colorado 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 1 896 923 976 1990's 1,018 1,074 1,108 1,032 1,176 1,528 2,099 2,923 3,349 4,727 2000's 4,994 4,729 4,337 4,054 4,175 4,318 4,472 4,592 4,816 5,084 2010's 6,232 6,529 6,906 7,293 7,823 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  7. Colorado Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Colorado 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 925 942,571 955,810 970,512 1990's 983,592 1,002,154 1,022,542 1,044,699 1,073,308 1,108,899 1,147,743 1,183,978 1,223,433 1,265,032 2000's 1,315,619 1,365,413 1,412,923 1,453,974 1,496,876 1,524,813 1,558,911 1,583,945 1,606,602 1,622,434 2010's 1,634,587 1,645,716 1,659,808 1,672,312 1,690,581 -

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

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

    Industrial Consumers (Number of Elements) Connecticut 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 2,709 2,818 2,908 1990's 3,061 2,921 2,923 2,952 3,754 3,705 3,435 3,459 3,441 3,465 2000's 3,683 3,881 3,716 3,625 3,470 3,437 3,393 3,317 3,196 3,138 2010's 3,063 3,062 3,148 4,454 4,217 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  9. Delaware Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Delaware 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 6 6,180 6,566 7,074 1990's 7,485 7,895 8,173 8,409 8,721 9,133 9,518 9,807 10,081 10,441 2000's 9,639 11,075 11,463 11,682 11,921 12,070 12,345 12,576 12,703 12,839 2010's 12,861 12,931 12,997 13,163 13,352 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

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

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

    Residential Consumers (Number of Elements) Delaware 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 81 82,829 84,328 86,428 1990's 88,894 91,467 94,027 96,914 100,431 103,531 106,548 109,400 112,507 115,961 2000's 117,845 122,829 126,418 129,870 133,197 137,115 141,276 145,010 147,541 149,006 2010's 150,458 152,005 153,307 155,627 158,502 - = No Data Reported; -- = Not Applicable; NA = Not

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

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

    Commercial Consumers (Number of Elements) Florida 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 41 42,376 43,178 43,802 1990's 43,674 45,012 45,123 47,344 47,851 46,459 47,578 48,251 46,778 50,052 2000's 50,888 53,118 53,794 55,121 55,324 55,479 55,259 57,320 58,125 59,549 2010's 60,854 61,582 63,477 64,772 67,460 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

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

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

    Residential Consumers (Number of Elements) Florida 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 442 444,848 446,690 452,544 1990's 457,648 467,221 471,863 484,816 497,777 512,365 521,674 532,790 542,770 556,628 2000's 571,972 590,221 603,690 617,373 639,014 656,069 673,122 682,996 679,265 674,090 2010's 675,551 679,199 686,994 694,210 703,535 - = No Data Reported; -- = Not Applicable; NA = Not

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

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

    Commercial Consumers (Number of Elements) Georgia 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 94 98,809 102,277 106,690 1990's 108,295 109,659 111,423 114,889 117,980 120,122 123,200 123,367 126,050 225,020 2000's 128,275 130,373 128,233 129,867 128,923 128,389 127,843 127,832 126,804 127,347 2010's 124,759 123,454 121,243 126,060 122,573 - = No Data Reported; -- = Not Applicable; NA = Not

  14. Georgia Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Georgia 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 3 3,034 3,144 3,079 1990's 3,153 3,124 3,186 3,302 3,277 3,261 3,310 3,310 3,262 5,580 2000's 3,294 3,330 3,219 3,326 3,161 3,543 3,053 2,913 2,890 2,254 2010's 2,174 2,184 2,112 2,242 2,481 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  15. Georgia Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Georgia 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 1,190 1,237,201 1,275,128 1,308,972 1990's 1,334,935 1,363,723 1,396,860 1,430,626 1,460,141 1,495,992 1,538,458 1,553,948 1,659,730 1,732,865 2000's 1,680,749 1,737,850 1,735,063 1,747,017 1,752,346 1,773,121 1,726,239 1,793,650 1,791,256 1,744,934 2010's 1,740,587 1,740,006 1,739,543 1,805,425

  16. Hawaii Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Hawaii 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 2,896 2,852 2,842 1990's 2,837 2,786 2,793 3,222 2,805 2,825 2,823 2,783 2,761 2,763 2000's 2,768 2,777 2,781 2,804 2,578 2,572 2,548 2,547 2,540 2,535 2010's 2,551 2,560 2,545 2,627 2,789 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

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

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

    Residential Consumers (Number of Elements) Hawaii 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 28,502 28,761 28,970 1990's 29,137 29,701 29,805 29,984 30,614 30,492 31,017 30,990 30,918 30,708 2000's 30,751 30,794 30,731 30,473 26,255 26,219 25,982 25,899 25,632 25,466 2010's 25,389 25,305 25,184 26,374 28,919 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

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

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

    Commercial Consumers (Number of Elements) Idaho 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 17,482 18,454 18,813 1990's 19,452 20,328 21,145 21,989 22,999 24,150 25,271 26,436 27,697 28,923 2000's 30,018 30,789 31,547 32,274 33,104 33,362 33,625 33,767 37,320 38,245 2010's 38,506 38,912 39,202 39,722 40,229 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  19. Idaho Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Idaho 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 104,824 111,532 113,898 1990's 113,954 126,282 136,121 148,582 162,971 175,320 187,756 200,165 213,786 227,807 2000's 240,399 251,004 261,219 274,481 288,380 301,357 316,915 323,114 336,191 342,277 2010's 346,602 350,871 353,963 359,889 367,394 - = No Data Reported; -- = Not Applicable; NA = Not

  20. Illinois Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Illinois 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 241,367 278,473 252,791 1990's 257,851 261,107 263,988 268,104 262,308 264,756 265,007 268,841 271,585 274,919 2000's 279,179 278,506 279,838 281,877 273,967 276,763 300,606 296,465 298,418 294,226 2010's 291,395 293,213 297,523 282,743 294,391 - = No Data Reported; -- = Not Applicable; NA = Not

  1. Illinois Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Illinois 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 19,460 20,015 25,161 1990's 25,991 26,489 27,178 27,807 25,788 25,929 29,493 28,472 28,063 27,605 2000's 27,348 27,421 27,477 26,698 29,187 29,887 26,109 24,000 23,737 23,857 2010's 25,043 23,722 23,390 23,804 23,829 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  2. Illinois Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Illinois 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 3,170,364 3,180,199 3,248,117 1990's 3,287,091 3,320,285 3,354,679 3,388,983 3,418,052 3,452,975 3,494,545 3,521,707 3,556,736 3,594,071 2000's 3,631,762 3,670,693 3,688,281 3,702,308 3,754,132 3,975,961 3,812,121 3,845,441 3,869,308 3,839,438 2010's 3,842,206 3,855,942 3,878,806 3,838,120

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. Development of an integrated in-situ remediation technology. Draft topical report for Task {number_sign}7.2 entitled ``Field scale test`` (January 10, 1996--December 31, 1997)

    SciTech Connect (OSTI)

    Athmer, C.; Ho, S.V.; Hughes, B.M.

    1997-11-01

    Contamination in low-permeability soils poses a significant technical challenge to in-situ remediation efforts. Poor accessibility to the contaminants and difficulty in delivery of treatment reagents have rendered existing in-situ treatments such as bioremediation, vapor extraction, and pump and treat rather ineffective when applied to low permeability soils present at many contaminated sites. The technology is an integrated in-situ treatment in which established geotechnical methods are used to install degradation zones directly in the contaminated soil and electro-osmosis is utilized to move the contaminants back and forth through those zones until the treatment is completed. The present Topical Report for Task {number_sign}7.2 summarizes the Field Scale Test conducted by Monsanto Company, DuPont, and General Electric.

  13. Y-12 Steam Plant Project Received National Recognition for Project

    National Nuclear Security Administration (NNSA)

    Management Excellence | National Nuclear Security Administration Steam Plant Project Received National Recognition for Project Management Excellence March 23, 2011 Y-12 steam plant project receives national recognition for project management excellence. Y-12's Steam Plant Life Extension Project (SPLE) has received the Secretary of Energy's Project Management Improvement Award. Microsoft Office document icon NR-03-28.doc

  14. Technical Support to SBIR Phase II Project: Improved Conversion of Cellulose Waste to Ethanol Using a Dual Bioreactor System: Cooperative Research and Development Final Report, CRADA Number CRD-08-310

    SciTech Connect (OSTI)

    Zhang, M.

    2013-04-01

    Over-dependence on fossil fuel has spurred research on alternative energy. Inedible plant materials such as grass and corn stover represent abundant renewable natural resources that can be transformed into biofuel. Problems in enzymatic conversion of biomass to sugars include the use of incomplete synergistic enzymes, end-product inhibition, and adsorption and loss of enzymes necessitating their use in large quantities. Technova Corporation will develop a defined consortium of natural microorganisms that will efficiently break down biomass to energy-rich soluble sugars, and convert them to cleaner-burning ethanol fuel. The project will also develop a novel biocatalytic hybrid reactor system dedicated to this bioprocess, which embodies recent advances in nanotechnology. NREL will participate to develop a continuous fermentation process.

  15. Robust Technique for Measuring and Simulating Silicon Wafer Quality Characteristics that Enable the Prediction of Solar Cell Electrical Performance of MEMC Silicon Wafer. Cooperative Research and Development Final Report, CRADA Number CRD-11-438

    SciTech Connect (OSTI)

    Sopori, Bhushan

    2015-12-01

    NREL and MEMC Electronic Materials are interested in developing a robust technique for monitoring material quality of mc-Si and mono-Si wafers -- a technique that can provide relevant data to accurately predict the performance of solar cells fabricated on them. Previous work, performed under two TSAs between NREL and MEMC, has established that dislocation clusters are the dominant performance-limiting factor in MEMC mc-Si solar cells. The work under this CRADA will go further in verifying these results on a larger data set, evaluate possibilities of faster method(s) for mapping dislocations in wafers/ingots, understanding dislocation generation during ingot casting, and helping MEMC to have an internal capability for basic characterization that will provide feedback needed for more accurate crystallization simulations. NREL has already developed dislocation mapping technique and developed a basic electronic model (called Network Model) that uses spatial distribution of dislocations to predict the cell performance. In this CRADA work, we will use these techniques to: (i) establish dislocation, grain size, and grain orientation distributions of the entire ingots (through appropriate DOE) and compare these with theoretical models developed by MEMC, (ii) determine concentrations of some relevant impurities in selected wafers, (iii) evaluate potential of using photoluminescence for dislocation mapping and identification of recombination centers, (iv) evaluate use of diode array analysis as a detailed characterization tool, and (v) establish dislocation mapping as a wafer-quality monitoring tool for commercial mc-Si production.

  16. Cellulosic Biomass Sugars to Advantage Jet Fuel: Catalytic Conversion of Corn Stover to Energy Dense, Low Freeze Point Paraffins and Naphthenes: Cooperative Research and Development Final Report, CRADA Number CRD-12-462

    SciTech Connect (OSTI)

    Elander, Rick

    2015-08-04

    NREL will provide scientific and engineering support to Virent Energy Systems in three technical areas: Process Development/Biomass Deconstruction; Catalyst Fundamentals; and Technoeconomic Analysis. The overarching objective of this project is to develop the first fully integrated process that can convert a lignocellulosic feedstock (e.g., corn stover) efficiently and cost effectively to a mix of hydrocarbons ideally suited for blending into jet fuel. The proposed project will investigate the integration of Virent Energy System’s novel aqueous phase reforming (APR) catalytic conversion technology (BioForming®) with deconstruction technologies being investigated by NREL at the 1-500L scale. Corn stover was chosen as a representative large volume, sustainable feedstock.

  17. Temporary EPA ID Number Request | Open Energy Information

    Open Energy Info (EERE)

    Temporary EPA ID Number RequestLegal Abstract A developer that may "generate hazardous waste only from an episodic event" may instead apply for a temporary hazardous waste...

  18. Automatic target recognition apparatus and method

    DOE Patents [OSTI]

    Baumgart, Chris W. (Santa Fe, NM); Ciarcia, Christopher A. (Los Alamos, NM)

    2000-01-01

    An automatic target recognition apparatus (10) is provided, having a video camera/digitizer (12) for producing a digitized image signal (20) representing an image containing therein objects which objects are to be recognized if they meet predefined criteria. The digitized image signal (20) is processed within a video analysis subroutine (22) residing in a computer (14) in a plurality of parallel analysis chains such that the objects are presumed to be lighter in shading than the background in the image in three of the chains and further such that the objects are presumed to be darker than the background in the other three chains. In two of the chains the objects are defined by surface texture analysis using texture filter operations. In another two of the chains the objects are defined by background subtraction operations. In yet another two of the chains the objects are defined by edge enhancement processes. In each of the analysis chains a calculation operation independently determines an error factor relating to the probability that the objects are of the type which should be recognized, and a probability calculation operation combines the results of the analysis chains.

  19. Visual cluster analysis and pattern recognition template and methods

    DOE Patents [OSTI]

    Osbourn, G.C.; Martinez, R.F.

    1999-05-04

    A method of clustering using a novel template to define a region of influence is disclosed. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques. 30 figs.

  20. Visual cluster analysis and pattern recognition template and methods

    DOE Patents [OSTI]

    Osbourn, Gordon Cecil; Martinez, Rubel Francisco

    1999-01-01

    A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

  1. Pattern Recognition and Image Analysis in Materials | GE Global...

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

    in new window) Pattern Recognition and Image Analysis in Materials Jim Grande 2012.09.25 Hi I'm Jim Grande and I've been working at GE Global Research in Niskayuna for over 33...

  2. Deconstructing the Peptide-MHC Specificity of T Cell Recognition...

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

    Deconstructing the Peptide-MHC Specificity of T Cell Recognition Saturday, May 31, 2014 T Cell Figure Figure 1. Overlay of TCR-pMHC structures for 2B4 recognizing MCC (PDB ID: ...

  3. Protein Structure Recognition: From Eigenvector Analysis to Structural

    Office of Scientific and Technical Information (OSTI)

    Threading Method (Thesis/Dissertation) | SciTech Connect SciTech Connect Search Results Thesis/Dissertation: Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method Citation Details In-Document Search Title: Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method In this work, they try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process.

  4. Cooperative control of vehicle swarms for acoustic target recognition by

    Office of Scientific and Technical Information (OSTI)

    energy flows. (Journal Article) | SciTech Connect Journal Article: Cooperative control of vehicle swarms for acoustic target recognition by energy flows. Citation Details In-Document Search Title: Cooperative control of vehicle swarms for acoustic target recognition by energy flows. Authors: Eisler, Gerald Richard ; Dohner, Jeffrey Lynn ; Hurtado, John Edward [1] ; Driessen, Brian James [2] + Show Author Affiliations (Texas A&M University, College Station, TX) (University of Alabama,

  5. Helping New Mexico small businesses earns recognition for Los Alamos

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

    National Lab employees Helping NM small businesses earns recognition for employees Helping New Mexico small businesses earns recognition for Los Alamos National Lab employees Don Quintana and Pulak Nath were recognized in an awards ceremony for providing their technical expertise and access to lab capabilities to help small businesses through the New Mexico Small Business Assistance Program. November 10, 2015 Don Quintana (left) and Pulak Nath (right) after winning their Principal

  6. Signal Recognition Particle-Receptor Complex Structure Solved

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

    Signal Recognition Particle-Receptor Complex Structure Solved Print The signal recognition particle (SRP) is a ubiquitous ribonucleoprotein (RNP) complex that delivers membrane and secretory proteins to the cell membrane in prokaryotes and in eukaryotes to the endoplasmic reticulum (ER), an organelle that forms a network of protein and lipid synthesizing factories. This process, called co-translational protein targeting, is an essential and evolutionarily conserved pathway for delivering nascent

  7. Signal Recognition Particle-Receptor Complex Structure Solved

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

    Signal Recognition Particle-Receptor Complex Structure Solved Print The signal recognition particle (SRP) is a ubiquitous ribonucleoprotein (RNP) complex that delivers membrane and secretory proteins to the cell membrane in prokaryotes and in eukaryotes to the endoplasmic reticulum (ER), an organelle that forms a network of protein and lipid synthesizing factories. This process, called co-translational protein targeting, is an essential and evolutionarily conserved pathway for delivering nascent

  8. Signal Recognition Particle-Receptor Complex Structure Solved

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

    Signal Recognition Particle-Receptor Complex Structure Solved Print The signal recognition particle (SRP) is a ubiquitous ribonucleoprotein (RNP) complex that delivers membrane and secretory proteins to the cell membrane in prokaryotes and in eukaryotes to the endoplasmic reticulum (ER), an organelle that forms a network of protein and lipid synthesizing factories. This process, called co-translational protein targeting, is an essential and evolutionarily conserved pathway for delivering nascent

  9. Structural basis for biomolecular recognition in overlapping binding sites

    Office of Scientific and Technical Information (OSTI)

    in a diiron enzyme system (Journal Article) | SciTech Connect Structural basis for biomolecular recognition in overlapping binding sites in a diiron enzyme system Citation Details In-Document Search Title: Structural basis for biomolecular recognition in overlapping binding sites in a diiron enzyme system Authors: Acheson, Justin F. ; Bailey, Lucas J. ; Elsen, Nathaniel L. ; Fox, Brian G. [1] + Show Author Affiliations UW Publication Date: 2016-01-22 OSTI Identifier: 1229904 Resource Type:

  10. DOE Headquarters Receives Energy Star Recognition from EPA | Department of

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

    Energy Headquarters Receives Energy Star Recognition from EPA DOE Headquarters Receives Energy Star Recognition from EPA July 9, 2008 - 2:15pm Addthis WASHINGTON - U.S. Secretary of Energy Samuel W. Bodman today accepted a plaque from the U.S. Environmental Protection Agency (EPA) certifying the Department of Energy's (DOE) James Forrestal Headquarters Building as an ENERGY STAR® building. The Forrestal building uses 40 percent less energy than the average office building, saving taxpayers

  11. Signal Recognition Particle-Receptor Complex Structure Solved

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

    Signal Recognition Particle-Receptor Complex Structure Solved Print The signal recognition particle (SRP) is a ubiquitous ribonucleoprotein (RNP) complex that delivers membrane and secretory proteins to the cell membrane in prokaryotes and in eukaryotes to the endoplasmic reticulum (ER), an organelle that forms a network of protein and lipid synthesizing factories. This process, called co-translational protein targeting, is an essential and evolutionarily conserved pathway for delivering nascent

  12. Signal Recognition Particle-Receptor Complex Structure Solved

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

    Signal Recognition Particle-Receptor Complex Structure Solved Print The signal recognition particle (SRP) is a ubiquitous ribonucleoprotein (RNP) complex that delivers membrane and secretory proteins to the cell membrane in prokaryotes and in eukaryotes to the endoplasmic reticulum (ER), an organelle that forms a network of protein and lipid synthesizing factories. This process, called co-translational protein targeting, is an essential and evolutionarily conserved pathway for delivering nascent

  13. Technology applications bulletins: Number one

    SciTech Connect (OSTI)

    Koncinski, W. Jr.

    1989-02-01

    Martin Marietta Energy Systems, Inc. (Energy Systems), operates five facilities for the US Department of Energy (DOE): the Oak Ridge National Laboratory (ORNL), which is a large, multidisciplinary research and development (R and D) center whose primary mission is energy research; the Oak Ridge Y-12 Plant, which engages in defense research, development, and production; and the uranium-enrichment plants at Oak Ridge; Paducah, Kentucky; and Portsmouth, Ohio. Much of the research carried out at these facilities is of interest to industry and to state or local governments. To make information about this research available, the Energy Systems Office of Technology Applications publishes brief descriptions of selected technologies and reports. These technology applications bulletins describe the new technology and inform the reader about how to obtain further information, gain access to technical resources, and initiate direct contact with Energy Systems researchers.

  14. A learning-pattern recognition system for static-line-loading security assessment of power system

    SciTech Connect (OSTI)

    Prasad, N.R.

    1989-01-01

    The methodologies explored in this dissertation address the topic static-line-loading security using a learning pattern recognition approach. A basic issue in the pattern recognition approach is to determine if, indeed, the patterns of power system behavior are separable in terms of secure and insecure classes. Class separability is studied from the viewpoint of both intraset clustering and interset dispersion using feature extraction methodologies. While interset dispersion is examined only to the extent of whether or not it exists, no specific attempts are made to optimize the dispersion through feature selection methodologies. The properties of pattern vectors to exhibit intraset clustering and interset dispersion are explored using two different techniques. These techniques are the Karhunen-Loeve Expansion Method which does not assume any specific statistical distribution for the patterns, and the Minimum Entropy Method which assumes patterns that exhibit Gaussian distributions. Although both methods are fundamentally based on the concept of entropy minimization, the transformational properties that yield clustering are distinctly different. The differences are due to assumptions made regarding the statistical distributions of patterns representing system behavior. The application of patterns based on engineering heuristics and a priori knowledge of the system behavior is shown to provide enhanced classification power in the pattern recognition system. Results for several test systems are documented. The feasibility of utilizing mathematical pattern recognition techniques as a primary information processing system for security assessment and a means to subsequently induce learning is demonstrated. As such, a framework for the development of decision making tools with subsequent inputs to rule-based expert systems is speculated in a learning environment.

  15. Idaho Site Cleanup By the Numbers | Department of Energy

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

    Idaho Site Cleanup By the Numbers Idaho Site Cleanup By the Numbers Idaho Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an underground repository Available for Download PDF icon Idaho Site Cleanup By the

  16. Paducah Site Cleanup By the Numbers | Department of Energy

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

    Paducah Site Cleanup By the Numbers Paducah Site Cleanup By the Numbers Paducah Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an underground repository Available for Download PDF icon Paducah Site Cleanup

  17. Portsmouth Site Cleanup By the Numbers | Department of Energy

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

    Portsmouth Site Cleanup By the Numbers Portsmouth Site Cleanup By the Numbers Portsmouth Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an underground repository Available for Download PDF icon Portsmouth

  18. Savannah River National Laboratory By the Numbers | Department of Energy

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

    National Laboratory By the Numbers Savannah River National Laboratory By the Numbers Savannah River National Laboratory By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an underground repository Available for Download PDF

  19. Hanford Site Cleanup By the Numbers | Department of Energy

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

    Hanford Site Cleanup By the Numbers Hanford Site Cleanup By the Numbers Hanford Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an underground repository Available for Download PDF icon Hanford Site Cleanup

  20. West Valley Demonstration Project Site Cleanup By the Numbers | Department

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

    of Energy West Valley Demonstration Project Site Cleanup By the Numbers West Valley Demonstration Project Site Cleanup By the Numbers West Valley Demonstration Project Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste

  1. Moab Site Cleanup By the Numbers | Department of Energy

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

    Moab Site Cleanup By the Numbers Moab Site Cleanup By the Numbers Moab Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an underground repository Available for Download PDF icon Moab Site Cleanup By the

  2. Oak Ridge Site Cleanup By the Numbers | Department of Energy

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

    Oak Ridge Site Cleanup By the Numbers Oak Ridge Site Cleanup By the Numbers Oak Ridge Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an underground repository Available for Download PDF icon Oak Ridge Site

  3. Identification of Export Control Classification Number - ITER

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

    Identification of Export Control Classification Number - ITER (April 2012) As the "Shipper of Record" please provide the appropriate Export Control Classification Number (ECCN) for...

  4. MicroChip Imager Module for Recognition of Microorganisms

    Energy Science and Technology Software Center (OSTI)

    2001-01-01

    The MicroChip Reader for Cereus Group takes the table of intensities of hybridization signals produced by the MicroChip Imager software and evokes a series of steps designed to recognize the pattern of intensities specific to a particular Cereus subgroup. Seven subgroups of the Cereus group can be identified by particular features of their RNA sequence. The Reader also provides statistics documenting how well its conclusion is confirmed by the hybridization signals. At the user’s request,more » the Reader can list every recognition step utilized so that the user can verify the recognition process manually if desired.« less

  5. MSU student researcher gets major recognition with JLab assistantship

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

    (Mississippi State University) | Jefferson Lab MSU student researcher gets major recognition with JLab assistantship (Mississippi State University) External Link: http://www.msstate.edu/web/media/detail.php?id=5607 By jlab_admin on Mon, 2012-06-1

  6. WPN 05-6: Weatherization Assistance Program National Recognition Awards

    Broader source: Energy.gov [DOE]

    To provide criteria and guidelines for the Weatherization Assistance Program’s National Recognition Awards being presented at the 2005 National Weatherization Training Conference in New Orleans, Louisiana. These awards acknowledge outstanding contributions that advance the goals of WAP through individual or group achievement, inspiration, or innovation.

  7. Structural Basis of UV DNA-Damage Recognition by the DDB1-DDB2...

    Office of Scientific and Technical Information (OSTI)

    Recognition by the DDB1-DDB2 Complex Citation Details In-Document Search Title: Structural Basis of UV DNA-Damage Recognition by the DDB1-DDB2 Complex Ultraviolet (UV) ...

  8. Climate Zone Number 5 | Open Energy Information

    Open Energy Info (EERE)

    Climate Zone Number 5 Jump to: navigation, search A type of climate defined in the ASHRAE 169-2006 standard. Climate Zone Number 5 is defined as Cool- Humid(5A) with IP Units 5400...

  9. ARM - Measurement - Cloud particle number concentration

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

    from you Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud particle number concentration The total number of cloud particles present in any given volume...

  10. Low Mach Number Models in Computational Astrophysics

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

    Ann Almgren Low Mach Number Models in Computational Astrophysics February 4, 2014 Ann Almgren. Berkeley Lab Downloads Almgren-nug2014.pdf | Adobe Acrobat PDF file Low Mach Number...

  11. Supramolecular Chemistry of Selective Anion Recognition for Anions of Environmental Relevance

    SciTech Connect (OSTI)

    Jonathan L. Sessler

    2007-09-21

    The major thrust of this project, led by the University of Kansas (Prof. Kristin Bowman-James), entails an exploration of the basic determinants of anion recognition and their application to the design, synthesis, and testing of novel sulfate extractants. A key scientific inspiration for the work comes from the need, codified in simple-to-appreciate terms by the Oak Ridge National Laboratory component of the team (viz. Dr. Bruce Moyer), for chemical entities that can help in the extractive removal of species that have low solubilities in borosilicate glass. Among such species, sulfate anion, has been identified as particularly insidious. Its presence interferes with the vitrification process, thus rendering the remediation of tank waste from, e.g., the Hanford site far more difficult and expensive. The availability of effective extractants, that would allow for the separation of separating sulfate from the major competing anions in the waste, especially nitrate, could allow for pre-vitrification removal of sulfate via liquid-liquid extraction. The efforts at The University of Texas, the subject of this report, have thus concentrated on the development of new sulfate receptors. These systems are designed to increase our basic understanding of anion recognition events and set the stage for the development of viable sulfate anion extractants. In conjunction with the Oak Ridge National Laboratory (ORNL) members of the research team, several of these new receptors were studied as putative extractants, with two of the systems being shown to act as promising synergists for anion exchange.

  12. Design Molecular Recognition Materials for Chiral Sensors, Separtations and Catalytic Materials

    SciTech Connect (OSTI)

    Jia, S.; Nenoff, T.M.; Provencio, P.; Qiu, Y.; Shelnutt, J.A.; Thoma, S.G.; Zhang, J.

    1998-11-01

    The goal is the development of materials that are highly sensitive and selective for chid chemicals and biochemical (such as insecticides, herbicides, proteins, and nerve agents) to be used as sensors, catalysts and separations membranes. Molecular modeling methods are being used to tailor chiral molecular recognition sites with high affinity and selectivity for specified agents. The work focuses on both silicate and non-silicate materials modified with chirally-pure fictional groups for the catalysis or separations of enantiomerically-pure molecules. Surfactant and quaternary amine templating is being used to synthesize porous frameworks, containing mesopores of 30 to 100 angstroms. Computer molecukw modeling methods are being used in the design of these materials, especially in the chid surface- modi~ing agents. Molecular modeling is also being used to predict the catalytic and separations selectivities of the modified mesoporous materials. The ability to design and synthesize tailored asymmetric molecular recognition sites for sensor coatings allows a broader range of chemicals to be sensed with the desired high sensitivity and selectivity. Initial experiments target the selective sensing of small molecule gases and non-toxic model neural compounds. Further efforts will address designing sensors that greatly extend the variety of resolvable chemical species and forming a predictive, model-based method for developing advanced sensors.

  13. Quantification of the transferability of a designed protein specificity switch reveals extensive epistasis in molecular recognition

    SciTech Connect (OSTI)

    Melero, Cristina; Ollikainen, Noah; Harwood, Ian; Karpiak, Joel; Kortemme, Tanja

    2014-10-13

    Re-engineering proteinprotein recognition is an important route to dissecting and controlling complex interaction networks. Experimental approaches have used the strategy of second-site suppressors, where a functional interaction is inferred between two proteins if a mutation in one protein can be compensated by a mutation in the second. Mimicking this strategy, computational design has been applied successfully to change protein recognition specificity by predicting such sets of compensatory mutations in proteinprotein interfaces. To extend this approach, it would be advantageous to be able to transplant existing engineered and experimentally validated specificity changes to other homologous proteinprotein complexes. Here, we test this strategy by designing a pair of mutations that modulates peptide recognition specificity in the Syntrophin PDZ domain, confirming the designed interaction biochemically and structurally, and then transplanting the mutations into the context of five related PDZ domainpeptide complexes. We find a wide range of energetic effects of identical mutations in structurally similar positions, revealing a dramatic context dependence (epistasis) of designed mutations in homologous proteinprotein interactions. To better understand the structural basis of this context dependence, we apply a structure-based computational model that recapitulates these energetic effects and we use this model to make and validate forward predictions. The context dependence of these mutations is captured by computational predictions, our results both highlight the considerable difficulties in designing proteinprotein interactions and provide challenging benchmark cases for the development of improved protein modeling and design methods that accurately account for the context.

  14. Quantification of the transferability of a designed protein specificity switch reveals extensive epistasis in molecular recognition

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

    Melero, Cristina; Ollikainen, Noah; Harwood, Ian; Karpiak, Joel; Kortemme, Tanja

    2014-10-13

    Re-engineering protein–protein recognition is an important route to dissecting and controlling complex interaction networks. Experimental approaches have used the strategy of “second-site suppressors,” where a functional interaction is inferred between two proteins if a mutation in one protein can be compensated by a mutation in the second. Mimicking this strategy, computational design has been applied successfully to change protein recognition specificity by predicting such sets of compensatory mutations in protein–protein interfaces. To extend this approach, it would be advantageous to be able to “transplant” existing engineered and experimentally validated specificity changes to other homologous protein–protein complexes. Here, we test thismore » strategy by designing a pair of mutations that modulates peptide recognition specificity in the Syntrophin PDZ domain, confirming the designed interaction biochemically and structurally, and then transplanting the mutations into the context of five related PDZ domain–peptide complexes. We find a wide range of energetic effects of identical mutations in structurally similar positions, revealing a dramatic context dependence (epistasis) of designed mutations in homologous protein–protein interactions. To better understand the structural basis of this context dependence, we apply a structure-based computational model that recapitulates these energetic effects and we use this model to make and validate forward predictions. The context dependence of these mutations is captured by computational predictions, our results both highlight the considerable difficulties in designing protein–protein interactions and provide challenging benchmark cases for the development of improved protein modeling and design methods that accurately account for the context.« less

  15. Idaho National Laboratory receives national recognition for Small Business

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

    Mentoring Program DOE-ID Tim Jackson, 208-526-8484 INL Misty Benjamin, 208-526-5940 Idaho National Laboratory receives national recognition for Small Business Mentoring Program IDAHO FALLS � The U.S. Department of Energy recognized Idaho National Laboratory as the 2009 Mentor of the Year for its commitment to mentoring small businesses. The DOE Mentor of the Year recognizes INL's Mentor-Prot�g� Program for enhancing the capabilities of small businesses to perform contracts and

  16. Antibody Recognition of the Influenza Hemagglutinin by Receptor Mimicry |

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

    Stanford Synchrotron Radiation Lightsource Antibody Recognition of the Influenza Hemagglutinin by Receptor Mimicry Sunday, November 30, 2014 There has been a long-standing interest in blocking agents against influenza entry, such as inhibitors that can target the receptor binding site on the hemagglutinin surface glycoprotein (HA) to prevent viral attachment to host cells. Molecules have been designed based on the sialic acid receptor, although with very little success since sialic acid only

  17. Conditional random fields for pattern recognition applied to structured data

    SciTech Connect (OSTI)

    Burr, Tom; Skurikhin, Alexei

    2015-07-14

    Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is manmade (such as a building) or natural (such as a tree). Suppose the label for a pixel patch is manmade; if the label for a nearby pixel patch is then more likely to be manmade there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features between parts of the model are often correlated. Therefore, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.

  18. Conditional random fields for pattern recognition applied to structured data

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

    Burr, Tom; Skurikhin, Alexei

    2015-07-14

    Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features between parts of the modelmore » are often correlated. Therefore, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.« less

  19. Wyoming Natural Gas Number of Gas and Gas Condensate Wells (Number...

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

    Gas and Gas Condensate Wells (Number of Elements) Wyoming Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  20. Nevada Natural Gas Number of Gas and Gas Condensate Wells (Number...

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

    Gas and Gas Condensate Wells (Number of Elements) Nevada Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  1. Arizona Natural Gas Number of Gas and Gas Condensate Wells (Number...

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

    Gas and Gas Condensate Wells (Number of Elements) Arizona Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  2. Calculating Atomic Number Densities for Uranium

    Energy Science and Technology Software Center (OSTI)

    1993-01-01

    Provides method to calculate atomic number densities of selected uranium compounds and hydrogenous moderators for use in nuclear criticality safety analyses at gaseous diffusion uranium enrichment facilities.

  3. Compendium of Experimental Cetane Number Data

    SciTech Connect (OSTI)

    Murphy, M. J.; Taylor, J. D.; McCormick, R. L.

    2004-09-01

    In this report, we present a compilation of reported cetane numbers for pure chemical compounds. The compiled database contains cetane values for 299 pure compounds, including 156 hydrocarbons and 143 oxygenates. Cetane number is a relative ranking of fuels based on the amount of time between fuel injection and ignition. The cetane number is typically measured either in a combustion bomb or in a single-cylinder research engine. This report includes cetane values from several different measurement techniques - each of which has associated uncertainties. Additionally, many of the reported values are determined by measuring blending cetane numbers, which introduces significant error. In many cases, the measurement technique is not reported nor is there any discussion about the purity of the compounds. Nonetheless, the data in this report represent the best pure compound cetane number values available from the literature as of August 2004.

  4. IMPACT OF CAPILLARY AND BOND NUMBERS ON RELATIVE PERMEABILITY

    SciTech Connect (OSTI)

    Kishore K. Mohanty

    2002-09-30

    Recovery and recovery rate of oil, gas and condensates depend crucially on their relative permeability. Relative permeability in turn depends on the pore structure, wettability and flooding conditions, which can be represented by a set of dimensionless groups including capillary and bond numbers. The effect of flooding conditions on drainage relative permeabilities is not well understood and is the overall goal of this project. This project has three specific objectives: to improve the centrifuge relative permeability method, to measure capillary and bond number effects experimentally, and to develop a pore network model for multiphase flows. A centrifuge has been built that can accommodate high pressure core holders and x-ray saturation monitoring. The centrifuge core holders can operate at a pore pressure of 6.9 MPa (1000 psi) and an overburden pressure of 17 MPa (2500 psi). The effect of capillary number on residual saturation and relative permeability in drainage flow has been measured. A pore network model has been developed to study the effect of capillary numbers and viscosity ratio on drainage relative permeability. Capillary and Reynolds number dependence of gas-condensate flow has been studied during well testing. A method has been developed to estimate relative permeability parameters from gas-condensate well test data.

  5. Mo Year Report Period: EIA ID NUMBER:

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

    Mo Year Report Period: EIA ID NUMBER: http:www.eia.govsurveyformeia14instructions.pdf Mailing Address: Secure File Transfer option available at: (e.g., PO Box, RR) https:...

  6. LANL Site By The Numbers August 2015

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

    By the Numbers The Los Alamos National Laboratory (LANL) was established in 1943 as Site Y of the Manhattan Project for a single purpose: to design and build an atomic bomb. ...

  7. Identification of Export Control Classification Number - ITER

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

    Identification of Export Control Classification Number - ITER (April 2012) As the "Shipper of Record" please provide the appropriate Export Control Classification Number (ECCN) for the products (equipment, components and/or materials) and if applicable the nonproprietary associated installation/maintenance documentation that will be shipped from the United States to the ITER International Organization in Cadarache, France or to ITER Members worldwide on behalf of the Company. In rare

  8. Stockpile Stewardship Quarterly Volume 1, Number 4

    National Nuclear Security Administration (NNSA)

    1, Number 4 * February 2012 Message from the Assistant Deputy Administrator for Stockpile Stewardship, Chris Deeney Defense Programs Stockpile Stewardship in Action Volume 1, Number 4 Inside this Issue 2 Applying Advanced Simulation Models to Neutron Tube Ion Extraction 3 Advanced Optical Cavities for Subcritical and Hydrodynamic Experiments 5 Progress Toward Ignition on the National Ignition Facility 7 Commissioning URSA Minor: The First LTD-Based Accelerator for Radiography 8 Publication

  9. Ion Recognition Approach to Volume Reduction of Alkaline Tank Waste by Separation of Sodium Salts

    SciTech Connect (OSTI)

    Levitskaia, Tatiana G.; Lumetta, Gregg J.; Moyer, Bruce A.; Bonnesen, Peter V.

    2006-06-01

    The purpose of this research involving collaboration between Oak Ridge National Laboratory (ORNL) and Pacific Northwest National Laboratory (PNNL) is to explore new approaches to the separation of sodium hydroxide, sodium nitrate, and other sodium salts from high-level alkaline tank waste. The principal potential benefit is a major reduction in disposed waste volume, obviating the building of expensive new waste tanks and reducing the costs of low-activity waste immobilization. Principles of ion recognition are being researched toward discovery of liquid extraction systems that selectively separate sodium hydroxide and sodium nitrate from other waste components. The successful concept of pseudohydroxide extraction using fluorinated alcohols and phenols is being developed at ORNL and PNNL toward a greater understanding of the controlling equilibria, role of solvation, and of synergistic effects involving crown ethers. Studies at PNNL are directed toward new solvent formulation for the practical sodium pseudohydroxide extraction systems.

  10. Volume Decomposition and Feature Recognition for Hexahedral Mesh Generation

    SciTech Connect (OSTI)

    GADH,RAJIT; LU,YONG; TAUTGES,TIMOTHY J.

    1999-09-27

    Considerable progress has been made on automatic hexahedral mesh generation in recent years. Several automatic meshing algorithms have proven to be very reliable on certain classes of geometry. While it is always worth pursuing general algorithms viable on more general geometry, a combination of the well-established algorithms is ready to take on classes of complicated geometry. By partitioning the entire geometry into meshable pieces matched with appropriate meshing algorithm the original geometry becomes meshable and may achieve better mesh quality. Each meshable portion is recognized as a meshing feature. This paper, which is a part of the feature based meshing methodology, presents the work on shape recognition and volume decomposition to automatically decompose a CAD model into meshable volumes. There are four phases in this approach: (1) Feature Determination to extinct decomposition features, (2) Cutting Surfaces Generation to form the ''tailored'' cutting surfaces, (3) Body Decomposition to get the imprinted volumes; and (4) Meshing Algorithm Assignment to match volumes decomposed with appropriate meshing algorithms. The feature determination procedure is based on the CLoop feature recognition algorithm that is extended to be more general. Results are demonstrated over several parts with complicated topology and geometry.

  11. California Natural Gas Number of Gas and Gas Condensate Wells...

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

    Gas and Gas Condensate Wells (Number of Elements) California Natural Gas Number of Gas and ... Number of Producing Gas Wells Number of Producing Gas Wells (Summary) California Natural ...

  12. Sales and Value Recognition for Zero Energy Ready Home Webinar (Text Version)

    Broader source: Energy.gov [DOE]

    Below is the text version of the webinar, Sales and Value Recognition for Zero Energy Ready Home, presented in December 2014. Watch the presentation.

  13. Face recognition system and method using face pattern words and face pattern bytes

    DOE Patents [OSTI]

    Zheng, Yufeng

    2014-12-23

    The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

  14. Inverted Metamorphic Cell Development: Cooperative Research and Development Final Report, CRADA Number CRD-05-156

    SciTech Connect (OSTI)

    Wanlass, M.

    2012-05-01

    This CRADA targeted technology transfer of the inverted metamorphic multi-junction (IMM) solar cell innovation from NREL to Emcore Photovoltaics. The technology transfer was successfully completed. Additionally, NREL provided materials characterization of solar cell structures produced at Emcore.

  15. Probing lepton number violation on three frontiers

    SciTech Connect (OSTI)

    Deppisch, Frank F. [Department of Physics and Astronomy, University College London (United Kingdom)

    2013-12-30

    Neutrinoless double beta decay constitutes the main probe for lepton number violation at low energies, motivated by the expected Majorana nature of the light but massive neutrinos. On the other hand, the theoretical interpretation of the (non-)observation of this process is not straightforward as the Majorana neutrinos can destructively interfere in their contribution and many other New Physics mechanisms can additionally mediate the process. We here highlight the potential of combining neutrinoless double beta decay with searches for Tritium decay, cosmological observations and LHC physics to improve the quantitative insight into the neutrino properties and to unravel potential sources of lepton number violation.

  16. The New Element Curium (Atomic Number 96)

    DOE R&D Accomplishments [OSTI]

    Seaborg, G. T.; James, R. A.; Ghiorso, A.

    1948-00-00

    Two isotopes of the element with atomic number 96 have been produced by the helium-ion bombardment of plutonium. The name curium, symbol Cm, is proposed for element 96. The chemical experiments indicate that the most stable oxidation state of curium is the III state.

  17. North Carolina Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    ,102,001 1,115,532 1,128,963 1,142,947 1,161,398 1,183,152 1987-2014 Sales 1,115,532 1,128,963 1,142,947 1,161,398 1,183,152 1997-2014 Commercial Number of Consumers 113,630...

  18. Washington Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    059,239 1,067,979 1,079,277 1,088,762 1,102,318 1,118,193 1987-2014 Sales 1,067,979 1,079,277 1,088,762 1,102,318 1,118,193 1997-2014 Commercial Number of Consumers 98,965 99,231...

  19. New Mexico Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    560,479 559,852 570,637 561,713 572,224 614,313 1987-2014 Sales 559,825 570,592 561,652 572,146 614,231 1997-2014 Transported 27 45 61 78 82 1997-2014 Commercial Number of...

  20. Minnesota Number of Natural Gas Consumers

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

    423,703 1,429,681 1,436,063 1,445,824 1,459,134 1,472,663 1987-2014 Sales 1,429,681 1,436,063 1,445,824 1,459,134 1,472,663 1997-2014 Commercial Number of Consumers 131,801 132,163 ...

  1. The 17 GHz active region number

    SciTech Connect (OSTI)

    Selhorst, C. L.; Pacini, A. A.; Costa, J. E. R.; Gimnez de Castro, C. G.; Valio, A.; Shibasaki, K.

    2014-08-01

    We report the statistics of the number of active regions (NAR) observed at 17 GHz with the Nobeyama Radioheliograph between 1992, near the maximum of cycle 22, and 2013, which also includes the maximum of cycle 24, and we compare with other activity indexes. We find that NAR minima are shorter than those of the sunspot number (SSN) and radio flux at 10.7 cm (F10.7). This shorter NAR minima could reflect the presence of active regions generated by faint magnetic fields or spotless regions, which were a considerable fraction of the counted active regions. The ratio between the solar radio indexes F10.7/NAR shows a similar reduction during the two minima analyzed, which contrasts with the increase of the ratio of both radio indexes in relation to the SSN during the minimum of cycle 23-24. These results indicate that the radio indexes are more sensitive to weaker magnetic fields than those necessary to form sunspots, of the order of 1500 G. The analysis of the monthly averages of the active region brightness temperatures shows that its long-term variation mimics the solar cycle; however, due to the gyro-resonance emission, a great number of intense spikes are observed in the maximum temperature study. The decrease in the number of these spikes is also evident during the current cycle 24, a consequence of the sunspot magnetic field weakening in the last few years.

  2. Connecticut Number of Natural Gas Consumers

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

    489,349 490,185 494,970 504,138 513,492 522,658 1986-2014 Sales 489,380 494,065 503,241 512,110 521,460 1997-2014 Transported 805 905 897 1,382 1,198 1997-2014 Commercial Number of...

  3. Climate Zone Number 1 | Open Energy Information

    Open Energy Info (EERE)

    Zone Number 1 is defined as Very Hot - Humid(1A) with IP Units 9000 < CDD50F and SI Units 5000 < CDD10C Dry(1B) with IP Units 9000 < CDD50F and SI Units 5000 < CDD10C...

  4. Kansas Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    855,454 853,842 854,730 854,800 858,572 861,092 1987-2014 Sales 853,842 854,730 854,779 858,546 861,066 1997-2014 Transported 0 0 21 26 26 2004-2014 Commercial Number of Consumers...

  5. Geothermal progress monitor: Report Number 19

    SciTech Connect (OSTI)

    1997-12-01

    Short articles are presented related to activities in the federal government and the geothermal industry, international developments, state and local government activities, technology development, and technology transfer. Power plant tables and a directory of organizations involved in geothermal resource development are included.

  6. Speech coding, reconstruction and recognition using acoustics and electromagnetic waves

    DOE Patents [OSTI]

    Holzrichter, J.F.; Ng, L.C.

    1998-03-17

    The use of EM radiation in conjunction with simultaneously recorded acoustic speech information enables a complete mathematical coding of acoustic speech. The methods include the forming of a feature vector for each pitch period of voiced speech and the forming of feature vectors for each time frame of unvoiced, as well as for combined voiced and unvoiced speech. The methods include how to deconvolve the speech excitation function from the acoustic speech output to describe the transfer function each time frame. The formation of feature vectors defining all acoustic speech units over well defined time frames can be used for purposes of speech coding, speech compression, speaker identification, language-of-speech identification, speech recognition, speech synthesis, speech translation, speech telephony, and speech teaching. 35 figs.

  7. Speech coding, reconstruction and recognition using acoustics and electromagnetic waves

    DOE Patents [OSTI]

    Holzrichter, John F.; Ng, Lawrence C.

    1998-01-01

    The use of EM radiation in conjunction with simultaneously recorded acoustic speech information enables a complete mathematical coding of acoustic speech. The methods include the forming of a feature vector for each pitch period of voiced speech and the forming of feature vectors for each time frame of unvoiced, as well as for combined voiced and unvoiced speech. The methods include how to deconvolve the speech excitation function from the acoustic speech output to describe the transfer function each time frame. The formation of feature vectors defining all acoustic speech units over well defined time frames can be used for purposes of speech coding, speech compression, speaker identification, language-of-speech identification, speech recognition, speech synthesis, speech translation, speech telephony, and speech teaching.

  8. Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

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

    McClanahan, Richard; De Leon, Phillip L.

    2014-08-20

    The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, wemore » can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.« less

  9. Maria Goeppert Mayer, the Nuclear Shell Structure, and Magic Numbers

    Office of Scientific and Technical Information (OSTI)

    Maria Goeppert-Mayer, the Nuclear Shell Model, and Magic Numbers Resources with Additional Information Maria Goeppert-Mayer Courtesy Argonne National Laboratory While working at Argonne National Laboratory (ANL) in 1948, physicist Maria Goeppert-Mayer developed the explanation of how neutrons and protons within atomic nuclei are structured. Called the "nuclear shell model," her work explains why the nuclei of some atoms are more stable than others and why some elements have many

  10. Sensitivity in risk analyses with uncertain numbers.

    SciTech Connect (OSTI)

    Tucker, W. Troy; Ferson, Scott

    2006-06-01

    Sensitivity analysis is a study of how changes in the inputs to a model influence the results of the model. Many techniques have recently been proposed for use when the model is probabilistic. This report considers the related problem of sensitivity analysis when the model includes uncertain numbers that can involve both aleatory and epistemic uncertainty and the method of calculation is Dempster-Shafer evidence theory or probability bounds analysis. Some traditional methods for sensitivity analysis generalize directly for use with uncertain numbers, but, in some respects, sensitivity analysis for these analyses differs from traditional deterministic or probabilistic sensitivity analyses. A case study of a dike reliability assessment illustrates several methods of sensitivity analysis, including traditional probabilistic assessment, local derivatives, and a ''pinching'' strategy that hypothetically reduces the epistemic uncertainty or aleatory uncertainty, or both, in an input variable to estimate the reduction of uncertainty in the outputs. The prospects for applying the methods to black box models are also considered.

  11. Alaska Maximum Number of Active Crews Engaged in Seismic Surveying (Number

    Gasoline and Diesel Fuel Update (EIA)

    of Elements) Seismic Surveying (Number of Elements) Alaska Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 2 3 3 3 1 1 0 0 0 0 2001 0 0 0 0 2 2 0 0 0 0 0 0 2002 2 2 2 2 2 2 2 2 2 2 2 1 2003 0 0 2 2 2 2 2 2

  12. Volume, Number of Shipments Surpass Goals

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

    shatters records in first year of accelerated shipping effort October 3, 2012 Los Alamos National Laboratory shatters records in first year of accelerated shipping effort Volume, Number of Shipments Surpass Goals LOS ALAMOS, NEW MEXICO, October 3, 2012-In the first year of an effort to accelerate shipments of transuranic (TRU) waste to the Waste Isolation Pilot Plant (WIPP), Los Alamos National Laboratory shattered its own record with 59 more shipments than planned, and became one of the largest

  13. Stockpile Stewardship Quarterly, Volume 2, Number 1

    National Nuclear Security Administration (NNSA)

    1 * May 2012 Message from the Assistant Deputy Administrator for Stockpile Stewardship, Chris Deeney Defense Programs Stockpile Stewardship in Action Volume 2, Number 1 Inside this Issue 2 LANL and ANL Complete Groundbreaking Shock Experiments at the Advanced Photon Source 3 Characterization of Activity-Size-Distribution of Nuclear Fallout 5 Modeling Mix in High-Energy-Density Plasma 6 Quality Input for Microscopic Fission Theory 8 Fiber Reinforced Composites Under Pressure: A Case Study in

  14. U.S. Natural Gas Number of Underground Storage Acquifers Capacity (Number

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

    of Elements) Acquifers Capacity (Number of Elements) U.S. Natural Gas Number of Underground Storage Acquifers Capacity (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 49 2000's 49 39 38 43 43 44 44 43 43 43 2010's 43 43 44 47 46 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Number of

  15. Table B14. Number of Establishments in Building, Number of Buildings, 1999

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

    4. Number of Establishments in Building, Number of Buildings, 1999" ,"Number of Buildings (thousand)" ,"All Buildings","Number of Establishments in Building" ,,"One","Two to Five","Six to Ten","Eleven to Twenty","More than Twenty","Currently Unoccupied" "All Buildings ................",4657,3528,688,114,48,27,251 "Building Floorspace" "(Square Feet)" "1,001 to 5,000

  16. TU-C-17A-03: An Integrated Contour Evaluation Software Tool Using Supervised Pattern Recognition for Radiotherapy

    SciTech Connect (OSTI)

    Chen, H; Tan, J; Kavanaugh, J; Dolly, S; Gay, H; Thorstad, W; Anastasio, M; Altman, M; Mutic, S; Li, H

    2014-06-15

    Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-time and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding unnecessary manual verification for physicians/dosimetrists. In addition, its nature as a compact and stand-alone tool allows for future extensibility to include additional functions for physicians’ clinical needs.

  17. Amped Up! Volume 1 Number 6

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

    ... More on WAP's national evaluation. National Evaluation ... the coast of New Jersey. offshore wind development - a ... These technologies utilize directional drilling and ...

  18. Argonne scientists receive recognition for clean energy research...

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

    fuel into their cars, rather than plug in the entire system. Guzowski holds a number of leadership positions at Argonne, including director of strategy & research programs for...

  19. Regulation of chloroplast number and DNA synthesis in higher plants. Final report, August 1995--August 1996

    SciTech Connect (OSTI)

    Mullet, J.E.

    1997-06-17

    The long term objective of this research is to understand the process of chloroplast development and its coordination with leaf development in higher plants. This is important because the photosynthetic capacity of plants is directly related to leaf and chloroplast development. This research focused on obtaining a detailed description of leaf development and the early steps in chloroplast development including activation of plastid DNA synthesis, changes in plastid DNA copy number, activation of chloroplast transcription and increases in plastid number per cell. The research focused on the isolation of the plastid DNA polymerase, and identification of genetic mutants which are altered in their accumulation of plastid DNA and plastid number per cell.

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

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 615 717 624 481 563 655 728 848 NA 787 2010's 774

  1. ARM Evaluation Product : Droplet Number Concentration Value-Added...

    Office of Scientific and Technical Information (OSTI)

    Evaluation Product : Droplet Number Concentration Value-Added Product Title: ARM Evaluation Product : Droplet Number Concentration Value-Added Product Cloud droplet number ...

  2. Property:Number of Plants Included in Planned Estimate | Open...

    Open Energy Info (EERE)

    Number of Plants Included in Planned Estimate Jump to: navigation, search Property Name Number of Plants Included in Planned Estimate Property Type String Description Number of...

  3. Property:NumberOfLEDSTools | Open Energy Information

    Open Energy Info (EERE)

    Name NumberOfLEDSTools Property Type Number Retrieved from "http:en.openei.orgwindex.php?titleProperty:NumberOfLEDSTools&oldid322418" Feedback Contact needs updating Image...

  4. Property:Number of Color Cameras | Open Energy Information

    Open Energy Info (EERE)

    Color Cameras Jump to: navigation, search Property Name Number of Color Cameras Property Type Number Pages using the property "Number of Color Cameras" Showing 25 pages using this...

  5. OMB Control Number: 1910-5165

    Energy Savers [EERE]

    OMB Control Number: 1910-5165 Expires: xx/xx/201x SEMI-ANNUAL DAVIS-BACON ENFORCEMENT REPORT Please submit this Semi-Annual Davis-Bacon Enforcement Report to your site DOE/NNSA Contractor Human Resource Division (CHRD) Office. If you do not have a DOE/NNSA CHRD Office, please submit the report to: DBAEnforcementReports@hq.doe.gov. The following questions regarding enforcement activity (Davis-Bacon and Related Acts) by this Agency are required by 29 CFR, Part 5.7(b), and Department of Labor, All

  6. OMB Control Number: 1910-5165

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

    Number: 1910-5165 Expires: 04/30/2015 SEMI-ANNUAL DAVIS-BACON ENFORCEMENT REPORT Please submit the Semi-Annual Davis-Bacon Enforcement Report in the Performance and Accountability for Grants in Energy (PAGE) system. If you do not have access to the PAGE system, please submit this form to DBAEnforcementReports@hq.doe.gov. The following questions regarding enforcement activity (Davis-Bacon and Related Acts) by this Agency are required by 29 CFR, Part 5.7(b), and Department of Labor, All Agency

  7. The New Element Berkelium (Atomic Number 97)

    DOE R&D Accomplishments [OSTI]

    Seaborg, G. T.; Thompson, S. G.; Ghiorso, A.

    1950-04-26

    An isotope of the element with atomic number 97 has been discovered as a product of the helium-ion bombardment of americium. The name berkelium, symbol Bk, is proposed for element 97. The chemical separation of element 97 from the target material and other reaction products was made by combinations of precipitation and ion exchange adsorption methods making use of its anticipated (III) and (IV) oxidation states and its position as a member of the actinide transition series. The distinctive chemical properties made use of in its separation and the equally distinctive decay properties of the particular isotope constitute the principal evidence for the new element.

  8. The New Element Californium (Atomic Number 98)

    DOE R&D Accomplishments [OSTI]

    Seaborg, G. T.; Thompson, S. G.; Street, K. Jr.; Ghiroso, A.

    1950-06-19

    Definite identification has been made of an isotope of the element with atomic number 98 through the irradiation of Cm{sup 242} with about 35-Mev helium ions in the Berkeley Crocker Laboratory 60-inch cyclotron. The isotope which has been identified has an observed half-life of about 45 minutes and is thought to have the mass number 244. The observed mode of decay of 98{sup 244} is through the emission of alpha-particles, with energy of about 7.1 Mev, which agrees with predictions. Other considerations involving the systematics of radioactivity in this region indicate that it should also be unstable toward decay by electron capture. The chemical separation and identification of the new element was accomplished through the use of ion exchange adsorption methods employing the resin Dowex-50. The element 98 isotope appears in the eka-dysprosium position on elution curves containing berkelium and curium as reference points--that is, it precedes berkelium and curium off the column in like manner that dysprosium precedes terbium and gadolinium. The experiments so far have revealed only the tripositive oxidation state of eka-dysprosium character and suggest either that higher oxidation states are not stable in aqueous solutions or that the rates of oxidation are slow. The successful identification of so small an amount of an isotope of element 98 was possible only through having made accurate predictions of the chemical and radioactive properties.

  9. Genome-Wide Identification and 3D Modeling of Proteins involved in DNA Damage Recognition and Repair (Final Report)

    SciTech Connect (OSTI)

    Abagyan, Ruben; An, Jianghong

    2005-08-12

    DNA Damage Recognition and Repair (DDR&R) proteins play a critical role in cellular responses to low-dose radiation and are associated with cancer. We have performed a systematic, genome-wide computational analysis of genomic data for human genes involved in the DDR&R process. The significant achievements of this project include: 1) Construction of the computational pipeline for searching DDR&R genes, building and validation of 3D models of proteins involved in DDR&R; 2) Functional and structural annotation of the 3D models and generation of comprehensive lists of suggested knock-out mutations; and the development of a method to predict the effects of mutations. Large scale testing of technology to identify novel small binding pockets in protein structures leading to new DDRR inhibitor strategies 3) Improvements of macromolecular docking technology (see the CAPRI 1-3 and 4-5 results) 4) Development of a new algorithm for improved analysis of high-density oligonucleotide arrays for gene expression profiling; 5) Construction and maintenance of the DNA Damage Recognition and Repair Database; 6) Producing 15 research papers (12 published and 3 in preparation).

  10. North Dakota Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) North Dakota Natural Gas Number of Gas and Gas Condensate Wells (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 61 1990's 103 100 104 101 104 99 108 104 99 96 2000's 94 95 100 117 117 148 200 200 194 196 2010's 188 239 211 200 200 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016

  11. Oregon Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Oregon Natural Gas Number of Gas and Gas Condensate Wells (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 18 1990's 19 16 16 18 19 17 18 17 15 19 2000's 17 20 18 15 15 15 14 18 21 24 2010's 26 24 27 26 28 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date:

  12. Alaska Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Alaska Natural Gas Number of Gas and Gas Condensate Wells (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 108 1990's 111 110 112 113 104 100 102 141 148 99 2000's 152 170 165 195 224 227 231 239 261 261 2010's 269 277 185 159 170 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016

  13. South Dakota Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) South Dakota Natural Gas Number of Gas and Gas Condensate Wells (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 53 1990's 54 54 38 47 55 56 61 60 59 60 2000's 71 68 69 61 61 69 69 71 71 89 2010's 102 100 95 65 68 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date:

  14. Tennessee Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Tennessee Natural Gas Number of Gas and Gas Condensate Wells (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 700 1990's 690 650 600 505 460 420 2000's 380 350 400 430 280 400 330 305 285 310 2010's 230 210 212 1,089 1,024 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  15. Illinois Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Illinois Natural Gas Number of Gas and Gas Condensate Wells (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 1990's 356 373 382 385 390 372 370 372 185 300 2000's 280 300 225 240 251 316 316 43 45 51 2010's 50 40 40 34 36 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  16. New Mexico Image Recognition Startup Spun Off From A Government Lab"

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

    Company covers "Just Your Typical New Mexico Image Recognition Startup Spun Off From A Government Lab" July 30, 2015 Just Your Typical New Mexico Image Recognition Startup Spun Off From A Government Lab Far from Silicon Valley, Descartes Labs aims to turn a national research facility's AI research into new ways of understanding the world...The company in question is Descartes Labs, and there's a very good reason why it's in Los Alamos. It aims to commercialize image-recognition

  17. DOE Challenge Home Gaining Recognition as a Leader Webinar (Text Version) |

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

    Department of Energy DOE Challenge Home Gaining Recognition as a Leader Webinar (Text Version) DOE Challenge Home Gaining Recognition as a Leader Webinar (Text Version) Below is a text version of the webinar titled "Gaining Recognition as a Leader," originally presented in May 2013. In addition to this text version of the audio, you can access a recording of the webinar. Sam Rashkin: Slide 1: This is about the DOE Challenge Home as a way for builders to be recognized a leader.

  18. THE SUN MAKES YOU NUMBER ONE!

    Office of Scientific and Technical Information (OSTI)

    SUN MAKES YOU NUMBER ONE! (A S to ry From th e S3TEC Team) Hi friend! W here did you get the energy to make that lunch? Oh no! x H ow will I i°l be first now? the sun! Why, I got it from the same place as all the life around us.. M atter is also made of balls of energy. You see, light from the sun is made of balls of energy that move very fast. The sun's energy makes this food hot- and it / can make your little-car go forward! / W hen the fast-moving light balls knock into the matter balls,

  19. Structure recognition from high resolution images of ceramic composites

    SciTech Connect (OSTI)

    Ushizima, Daniela; Perciano, Talita; Krishnan, Harinarayan; Loring, Burlen; Bale, Hrishikesh; Parkinson, Dilworth; Sethian, James

    2015-01-05

    Fibers provide exceptional strength-to-weight ratio capabilities when woven into ceramic composites, transforming them into materials with exceptional resistance to high temperature, and high strength combined with improved fracture toughness. Microcracks are inevitable when the material is under strain, which can be imaged using synchrotron X-ray computed micro-tomography (mu-CT) for assessment of material mechanical toughness variation. An important part of this analysis is to recognize fibrillar features. This paper presents algorithms for detecting and quantifying composite cracks and fiber breaks from high-resolution image stacks. First, we propose recognition algorithms to identify the different structures of the composite, including matrix cracks and fibers breaks. Second, we introduce our package F3D for fast filtering of large 3D imagery, implemented in OpenCL to take advantage of graphic cards. Results show that our algorithms automatically identify micro-damage and that the GPU-based implementation introduced here takes minutes, being 17x faster than similar tools on a typical image file.

  20. Cyclodextrin supramolecular assemblies: Energy migration prompted by molecular recognition

    SciTech Connect (OSTI)

    Pikramenou, Z.; Nocera, D.G.

    1993-12-31

    New photoactive supramolecular assemblies featuring a cyclodextrin modified with a Eu{sup 3+}{contained_in}aza crown ether have been synthesized. The inclusion of a light harvesting guest (LHG) in the cyclodextrin is heralded by light emission for the Eu{sup 3+} center. The authors attribute the enhancement of the europium emission to an absorption-energy transfer-emission process from the aromatic donors in the cavity of cyclodextrin to the Eu{sup 3+} ion residing in the appended aza macrocycle. Different conformations of the aza attached to the cyclodextrin have been designed. The efficiency of the migration process from the LHG to the Eu{sup 3+} ions is intimately related to the structure of the supramolecular assembly as well as to the nature of the LHG. Hydrophobic recognition of the guest by the CD is cooperative with its interaction to the metal ion. This paper will show that specificity in binding coupled with shorter distances for energy transfer results in much brighter luminescence from the cyclodextrin supramolecule.

  1. Sandia Cognitive Rsch. Environ.: Associative Network and Situation Recognition C

    Energy Science and Technology Software Center (OSTI)

    2003-12-11

    The software implements core elements of the SCORE Cognitive Framework. This Associative Network and Situation Recognition core is implemented in the Umbra simulation and modular software framework, which is C++-based. An instance of the cognitive framework “kernel” is implemented as a network of Umbra modules (Gottlieb, et al, 2002) comprising a Concepts Database, an Associative Network, a Situation Recognizer, a Comparator, and a Situations-Concept Driver. At initialization, these modules load the data files that togethermore » specify all the components of a particular cognitive model, such as concept declarations, situation declarations, spreading activation weights, and situation-cue-patterns. The software also includes a Discrepancy Detector class for detecting, overtime, discrepancies between instances of situations and occurrences of actions, A Discrepancy Detector can be incorporated into a system that includes, in addition to the network of modules above, software that monitors when a user performs an action and that passes this information to the Discrepancy Detector module, At initialization, the Discrepancy Detector module in such a system reads in data file specifying action declarations, the expectations of action instances due to a situation instance, and actions that should be considered discrepant when an instance is not expected. The figure below illustrates a prototype system incorporating a Discrepancy Detector module.« less

  2. Detailed Chemical Kinetic Reaction Mechanisms for Primary Reference Fuels for Diesel Cetane Number and Spark-Ignition Octane Number

    SciTech Connect (OSTI)

    Westbrook, C K; Pitz, W J; Mehl, M; Curran, H J

    2010-03-03

    For the first time, a detailed chemical kinetic reaction mechanism is developed for primary reference fuel mixtures of n-hexadecane and 2,2,4,4,6,8,8-heptamethyl nonane for diesel cetane ratings. The mechanisms are constructed using existing rules for reaction pathways and rate expressions developed previously for the primary reference fuels for gasoline octane ratings, n-heptane and iso-octane. These reaction mechanisms are validated by comparisons between computed and experimental results for shock tube ignition and for oxidation under jet-stirred reactor conditions. The combined kinetic reaction mechanism contains the submechanisms for the primary reference fuels for diesel cetane ratings and submechanisms for the primary reference fuels for gasoline octane ratings, all in one integrated large kinetic reaction mechanism. Representative applications of this mechanism to two test problems are presented, one describing fuel/air autoignition variations with changes in fuel cetane numbers, and the other describing fuel combustion in a jet-stirred reactor environment with the fuel varying from pure 2,2,4,4,6,8,8-heptamethyl nonane (Cetane number of 15) to pure n-hexadecane (Cetane number of 100). The final reaction mechanism for the primary reference fuels for diesel fuel and gasoline is available on the web.

  3. Y-12 technology brings licensee recognition | Y-12 National Security...

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

    ... Dip Strip was recently certified to a U.S. Air Force specification and received a national stock number that identifies it as a standardized aircraft paint remover recognized by ...

  4. Hawaii Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2010 0 0 0 0 0 0 0 0 0 0 0 0 2011 0 0 0 0 0 0 0 0 0 0 0 0 2012 0 0 0 0 0 0 0 0 0 0 0 0 2013 1 1 1 1 1 1 1 1 1 1 1 1 2014 1 1 1 1 1 1 1 1 1 1 1 1 2015 0 0 0 0 0 1 1 1 1 1 1 1 2016 1 1

    25,466 25,389 25,305 25,184 26,374 28,919 1987-2014 Sales 25,389 25,305 25,184 26,374 28,919 1998-2014 Commercial Number of Consumers 2,535 2,551 2,560 2,545 2,627 2,789 1987-2014 Sales 2,551 2,560 2,545 2,627 2,789 1998-2014 Average Consumption per Consumer

  5. Antibody Recognition of the Pandemic H1N1 Influenza Virus Hemagglutini...

    Office of Scientific and Technical Information (OSTI)

    H1N1 Influenza Virus Hemagglutinin Receptor Binding Site Citation Details In-Document Search Title: Antibody Recognition of the Pandemic H1N1 Influenza Virus Hemagglutinin ...

  6. The Energy Messenger, Number 1, Volume 4

    SciTech Connect (OSTI)

    Stancil, J.

    1995-01-01

    `The Energy Messenger` is a Department of Energy publication on energy activities of interest to American Indians. The first issue of 1995 (in a magazine format) includes articles on: tribes winning grants to develop energy resources, recruiting of internships for DOE, information about Title XXVI-Indian Energy Resources, American Indian Heritage Month, tribal perspective on DOE actions, joint ventures between tribes and the DOE, and brief description of recent DOE activities.

  7. SPRU by the Numbers August 2015

    Office of Environmental Management (EM)

    Resources » SBIR/STTR SBIR/STTR Congress established the SBIR and STTR programs to support scientific excellence and technological innovation through the investment of Federal research funds in critical American priorities to build a strong national economy. Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) are U.S. Government programs in which federal agencies with large research and development (R&D) budgets set aside a small fraction of their funding

  8. 3M's Model Rewards and Recognition Program Engages Employees and Drives

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

    Energy Savings Efforts | Department of Energy M's Model Rewards and Recognition Program Engages Employees and Drives Energy Savings Efforts 3M's Model Rewards and Recognition Program Engages Employees and Drives Energy Savings Efforts This case study provides information about 3M's approach to energy efficiency, profiling company efforts to implement more than 1,900 employee-inspired projects that have realized a 22% improvement in energy efficiency and yielded $100 million in energy

  9. Structural Basis of UV DNA-Damage Recognition by the DDB1-DDB2 Complex

    Office of Scientific and Technical Information (OSTI)

    (Journal Article) | SciTech Connect Structural Basis of UV DNA-Damage Recognition by the DDB1-DDB2 Complex Citation Details In-Document Search Title: Structural Basis of UV DNA-Damage Recognition by the DDB1-DDB2 Complex Ultraviolet (UV) light-induced pyrimidine photodimers are repaired by the nucleotide excision repair pathway. Photolesions have biophysical parameters closely resembling undamaged DNA, impeding discovery through damage surveillance proteins. The DDB1DDB2 complex serves in

  10. Structural Basis of UV DNA-Damage Recognition by the DDB1-DDB2 Complex

    Office of Scientific and Technical Information (OSTI)

    (Journal Article) | SciTech Connect Structural Basis of UV DNA-Damage Recognition by the DDB1-DDB2 Complex Citation Details In-Document Search Title: Structural Basis of UV DNA-Damage Recognition by the DDB1-DDB2 Complex Ultraviolet (UV) light-induced pyrimidine photodimers are repaired by the nucleotide excision repair pathway. Photolesions have biophysical parameters closely resembling undamaged DNA, impeding discovery through damage surveillance proteins. The DDB1DDB2 complex serves in

  11. Antibody Recognition of the Pandemic H1N1 Influenza Virus Hemagglutinin

    Office of Scientific and Technical Information (OSTI)

    Receptor Binding Site (Journal Article) | SciTech Connect Antibody Recognition of the Pandemic H1N1 Influenza Virus Hemagglutinin Receptor Binding Site Citation Details In-Document Search Title: Antibody Recognition of the Pandemic H1N1 Influenza Virus Hemagglutinin Receptor Binding Site Authors: Hong, Minsun ; Lee, Peter S. ; Hoffman, Ryan M.B. ; Zhu, Xueyong ; Krause, Jens C. ; Laursen, Nick S. ; Yoon, Sung-il ; Song, Langzhou ; Tussey, Lynda ; Crowe, Jr., James E. ; Ward, Andrew B. ;

  12. DOE ZERH Webinar: Sales and Value Recognition of ZERH | Department of

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

    Energy Sales and Value Recognition of ZERH DOE ZERH Webinar: Sales and Value Recognition of ZERH Watch the video or view the presentation slides below Net Zero Energy properties have unique, high-performance features that should be prominently presented during the listing and sales process. However, these features also present challenges for appraisers and lenders: Lenders are challenged to find appraisers with competency and competent appraisers are challenged with limited Net Zero Energy

  13. New Jersey Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) New Jersey 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 200,387 206,261 212,496 1990's 217,548 215,408 212,726 215,948 219,061 222,632 224,749 226,714 234,459 232,831 2000's 243,541 212,726 214,526 223,564 223,595 226,007 227,819 230,855 229,235 234,125 2010's 234,158 234,721 237,602 236,746 240,083 - = No Data Reported; -- = Not Applicable; NA = Not

  14. New Jersey Natural Gas Number of Residential Consumers (Number of Elements)

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

    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 Year-7 Year-8 Year-9 1980's 1,869,903 1,918,185 1,950,165 1990's 1,982,136 2,005,020 2,032,115 2,060,511 2,089,911 2,123,323 2,147,622 2,193,629 2,252,248 2,245,904 2000's 2,364,058 2,466,771 2,434,533 2,562,856 2,582,714 2,540,283 2,578,191 2,609,788 2,601,051 2,635,324 2010's 2,649,282 2,659,205 2,671,308 2,686,452

  15. New Mexico Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) New Mexico 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 36,444 36,940 36,960 1990's 38,026 38,622 40,312 40,166 39,846 38,099 37,796 38,918 42,067 43,834 2000's 44,164 44,306 45,469 45,491 45,961 47,745 47,233 48,047 49,235 48,846 2010's 48,757 49,406 48,914 50,163 55,689 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  16. New Mexico Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) New Mexico Natural Gas Number of Gas and Gas Condensate Wells (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 17,087 1990's 17,124 20,021 18,040 20,846 23,292 23,510 24,134 27,421 28,200 26,007 2000's 33,948 35,217 35,873 37,100 38,574 40,157 41,634 42,644 44,241 44,784 2010's 44,748 32,302 28,206 27,073 27,957 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  17. New Mexico Natural Gas Number of Industrial Consumers (Number of Elements)

    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 Year-8 Year-9 1980's 1,703 1,668 1,653 1990's 1,407 1,337 141 152 1,097 1,065 1,365 1,366 1,549 1,482 2000's 1,517 1,875 1,356 1,270 1,164 988 1,062 470 383 471 2010's 438 360 121 123 116 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  18. New Mexico Natural Gas Number of Residential Consumers (Number of Elements)

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

    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 Year-7 Year-8 Year-9 1980's 348,759 356,192 361,521 1990's 369,451 379,472 389,063 397,681 409,095 421,896 428,621 443,167 454,065 473,375 2000's 479,894 485,969 496,577 498,852 509,119 530,277 533,971 547,512 556,905 560,479 2010's 559,852 570,637 561,713 572,224 614,313 - = No Data Reported; -- = Not Applicable; NA = Not

  19. New York Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) New York 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 262,859 270,218 285,031 1990's 281,717 310,941 315,974 298,020 301,499 308,760 315,855 314,613 348,694 352,026 2000's 361,524 363,913 367,440 386,479 367,597 376,566 397,737 393,997 373,798 375,603 2010's 377,416 378,005 379,396 381,228 389,889 - = No Data Reported; -- = Not Applicable; NA = Not

  20. New York Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) New York Natural Gas Number of Gas and Gas Condensate Wells (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 5,304 1990's 5,525 5,737 5,906 5,757 5,884 6,134 6,208 5,731 5,903 6,422 2000's 5,775 5,913 6,496 5,878 5,781 5,449 5,985 6,680 6,675 6,628 2010's 6,736 6,157 7,176 6,902 7,119 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  1. New York Natural Gas Number of Residential Consumers (Number of Elements)

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

    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 Year-8 Year-9 1980's 3,810,577 3,839,952 3,859,413 1990's 3,917,354 4,472,005 4,522,274 3,990,564 4,008,868 4,030,702 4,048,166 4,077,385 4,117,307 4,150,731 2000's 4,162,450 4,243,130 4,258,205 4,218,180 4,199,456 4,232,374 4,315,203 4,379,937 4,303,342 4,308,592 2010's 4,335,006 4,353,668 4,364,169 4,387,456

  2. Ohio Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Ohio Natural Gas Number of Gas and Gas Condensate Wells (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 34,450 1990's 34,586 34,760 34,784 34,782 34,731 34,520 34,380 34,238 34,098 33,982 2000's 33,897 33,917 34,593 33,828 33,828 33,735 33,945 34,416 34,416 34,963 2010's 34,931 46,717 35,104 32,664 32,967 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  3. Oklahoma Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Oklahoma Natural Gas Number of Gas and Gas Condensate Wells (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 27,443 1990's 24,547 28,216 28,902 29,118 29,121 29,733 29,733 29,734 30,101 21,790 2000's 21,507 32,672 33,279 34,334 35,612 36,704 38,060 38,364 41,921 43,600 2010's 44,000 41,238 40,000 39,776 40,070 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  4. Pennsylvania Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Pennsylvania Natural Gas Number of Gas and Gas Condensate Wells (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 30,000 1990's 30,300 31,000 31,000 31,100 31,150 31,025 31,792 32,692 21,576 23,822 2000's 36,000 40,100 40,830 42,437 44,227 46,654 49,750 52,700 55,631 57,356 2010's 44,500 54,347 55,136 53,762 70,400 - = No Data Reported; -- = Not Applicable; NA = Not Available; W

  5. Montana Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Montana Natural Gas Number of Gas and Gas Condensate Wells (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 2,700 1990's 2,607 2,802 2,890 3,075 2,940 2,918 2,990 3,071 3,423 3,634 2000's 3,321 4,331 4,544 4,539 4,971 5,751 6,578 6,925 7,095 7,031 2010's 6,059 6,477 6,240 5,754 5,754 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure

  6. U.S. Natural Gas Number of Commercial Consumers - Transported (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Transported (Number of Elements) U.S. Natural Gas Number of Commercial Consumers - Transported (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 220,655 410,695 2000's 433,944 464,412 475,420 489,324 495,586 499,402 539,557 2010's 716,692 763,597 837,652 881,196 885,257 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  7. U.S. Natural Gas Number of Industrial Consumers - Sales (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Gas and Gas Condensate Wells (Number of Elements) U.S. Natural Gas Number of Gas and Gas Condensate Wells (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 262,483 1990's 269,790 276,987 276,014 282,152 291,773 298,541 301,811 310,971 316,929 302,421 2000's 341,678 373,304 387,772 393,327 406,147 425,887 440,516 452,945 476,652 493,100 2010's 487,627 514,637 482,822 484,994 514,786 - = No Data Reported; -- = Not Applicable; NA

  8. U.S. Natural Gas Number of Industrial Consumers - Transported (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Transported (Number of Elements) U.S. Natural Gas Number of Industrial Consumers - Transported (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 49,014 71,281 2000's 75,826 64,052 62,738 62,698 57,672 59,773 58,760 2010's 63,611 64,749 67,551 69,164 69,953 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date:

  9. U.S. Natural Gas Number of Residential Consumers - Sales (Number of

    Gasoline and Diesel Fuel Update (EIA)

    (Number of Elements) U.S. 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 47,710,444 48,474,449 49,309,593 1990's 50,187,178 51,593,206 52,331,397 52,535,411 53,392,557 54,322,179 55,263,673 56,186,958 57,321,746 58,223,229 2000's 59,252,728 60,286,364 61,107,254 61,871,450 62,496,134 63,616,827 64,166,280 64,964,769 65,073,996 65,329,582 2010's 65,542,345 65,940,522 66,375,134 66,812,393

  10. U.S. Natural Gas Number of Residential Consumers - Transported (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Transported (Number of Elements) U.S. Natural Gas Number of Residential Consumers - Transported (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 252,783 801,264 2,199,519 2000's 2,978,319 3,576,181 3,839,809 4,055,781 3,971,337 3,829,303 4,037,233 2010's 5,274,697 5,531,680 6,364,411 6,934,929 7,005,081 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  11. Alabama Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Alabama Natural Gas Number of Gas and Gas Condensate Wells (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 1,701 1990's 2,362 3,392 3,350 3,514 3,565 3,526 4,105 4,156 4,171 4,204 2000's 4,359 4,597 4,803 5,157 5,526 5,523 6,227 6,591 6,860 6,913 2010's 7,026 7,063 6,327 6,165 6,118 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure

  12. Texas Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Texas Natural Gas Number of Gas and Gas Condensate Wells (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 48,609 1990's 50,867 47,615 46,298 47,101 48,654 54,635 53,816 56,747 58,736 58,712 2000's 60,577 63,704 65,779 68,572 72,237 74,827 74,265 76,436 87,556 93,507 2010's 95,014 100,966 96,617 97,618 98,279 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  13. U.S. Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) U.S. 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 4,013,040 4,124,745 4,168,048 1990's 4,236,280 4,357,252 4,409,699 4,464,906 4,533,905 4,636,500 4,720,227 4,761,409 5,044,497 5,010,189 2000's 5,010,817 4,996,446 5,064,384 5,152,177 5,139,949 5,198,028 5,273,379 5,308,785 5,444,335 5,322,332 2010's 5,301,576 5,319,817 5,356,397 5,372,522 5,418,986 - =

  14. U.S. Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) U.S. Natural Gas Number of Gas and Gas Condensate Wells (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 262,483 1990's 269,790 276,987 276,014 282,152 291,773 298,541 301,811 310,971 316,929 302,421 2000's 341,678 373,304 387,772 393,327 406,147 425,887 440,516 452,945 476,652 493,100 2010's 487,627 514,637 482,822 484,994 514,786 - = No Data Reported; -- = Not Applicable; NA

  15. U.S. Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) U.S. 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 195,544 199,041 225,346 1990's 218,341 216,529 209,616 209,666 202,940 209,398 206,049 234,855 226,191 228,331 2000's 220,251 217,026 205,915 205,514 209,058 206,223 193,830 198,289 225,044 207,624 2010's 192,730 189,301 189,372 192,288 192,135 - = No Data Reported; -- = Not Applicable; NA = Not

  16. U.S. Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) U.S. 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 47,710,444 48,474,449 49,309,593 1990's 50,187,178 51,593,206 52,331,397 52,535,411 53,392,557 54,322,179 55,263,673 56,186,958 57,321,746 58,223,229 2000's 59,252,728 60,286,364 61,107,254 61,871,450 62,496,134 63,616,827 64,166,280 64,964,769 65,073,996 65,329,582 2010's 65,542,345 65,940,522

  17. Utah Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Utah Natural Gas Number of Gas and Gas Condensate Wells (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 834 1990's 822 913 1,006 1,061 1,303 1,127 1,339 1,475 1,643 1,978 2000's 4,178 4,601 3,005 3,220 3,657 4,092 4,858 5,197 5,578 5,774 2010's 6,075 6,469 6,900 7,030 7,275 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  18. Virginia Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Virginia Natural Gas Number of Gas and Gas Condensate Wells (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 752 1990's 819 886 1,153 1,426 1,470 1,671 1,671 2,046 2,388 2,752 2000's 3,051 3,521 3,429 3,506 3,870 4,132 5,179 5,735 6,426 7,303 2010's 7,470 7,903 7,843 7,956 7,961 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  19. West Virginia Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) West Virginia Natural Gas Number of Gas and Gas Condensate Wells (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 36,240 1990's 37,500 37,800 38,250 33,716 39,830 36,144 35,148 31,000 39,072 36,575 2000's 42,475 42,000 45,000 46,203 47,117 49,335 53,003 48,215 49,364 50,602 2010's 52,498 56,813 50,700 54,920 60,000 - = No Data Reported; -- = Not Applicable; NA = Not Available;

  20. Arkansas Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Arkansas Natural Gas Number of Gas and Gas Condensate Wells (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 2,830 1990's 2,952 2,780 3,500 3,500 3,500 3,988 4,020 3,700 3,900 3,650 2000's 4,000 4,825 6,755 7,606 3,460 3,462 3,814 4,773 5,592 6,314 2010's 7,397 8,388 8,538 9,843 10,150 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  1. Colorado Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Colorado Natural Gas Number of Gas and Gas Condensate Wells (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 5,125 1990's 5,741 5,562 5,912 6,372 7,056 7,017 8,251 12,433 13,838 13,838 2000's 22,442 22,117 23,554 18,774 16,718 22,691 20,568 22,949 25,716 27,021 2010's 28,813 30,101 32,000 32,468 38,346 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  2. District of Columbia Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) District of Columbia 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 11 14,683 11,370 11,354 1990's 11,322 11,318 11,206 11,133 11,132 11,089 10,952 10,874 10,658 12,108 2000's 11,106 10,816 10,870 10,565 10,406 10,381 10,410 9,915 10,024 10,288 2010's 9,879 10,050 9,771 9,963 10,049 - = No Data Reported; -- = Not Applicable; NA = Not

  3. District of Columbia Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) District of Columbia 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 134 130,748 134,758 134,837 1990's 136,183 136,629 136,438 135,986 135,119 135,299 135,215 134,807 132,867 137,206 2000's 138,252 138,412 143,874 136,258 138,134 141,012 141,953 142,384 142,819 143,436 2010's 144,151 145,524 145,938 146,712 147,877 - = No Data Reported; --

  4. Indiana Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Indiana Natural Gas Number of Gas and Gas Condensate Wells (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 1,310 1990's 1,307 1,334 1,333 1,336 1,348 1,347 1,367 1,458 1,479 1,498 2000's 1,502 1,533 1,545 2,291 2,386 2,321 2,336 2,350 525 563 2010's 620 914 819 921 895 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  5. Kansas Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Kansas Natural Gas Number of Gas and Gas Condensate Wells (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 13,935 1990's 16,980 17,948 18,400 19,472 19,365 22,020 21,388 21,500 21,000 17,568 2000's 15,206 15,357 16,957 17,387 18,120 18,946 19,713 19,713 17,862 21,243 2010's 22,145 25,758 24,697 23,792 24,354 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  6. Genome-Wide Identification and 3D Modeling of Proteins involved in DNA Damage Recognition and Repair (Final Report)

    SciTech Connect (OSTI)

    Ruben A. Abagyan, PhD

    2004-04-15

    OAK-B135 DNA Damage Recognition and Repair (DDR and R) proteins play a critical role in cellular responses to low-dose radiation and are associated with cancer. the authors have performed a systematic, genome-wide computational analysis of genomic data for human genes involved in the DDR and R process. The significant achievements of this project include: (1) Construction of the computational pipeline for searching DDR and R genes, building and validation of 3D models of proteins involved in DDR and R; (2) Functional and structural annotation of the 3D models and generation of comprehensive lists of suggested knock-out mutations; (3) Important improvement of macromolecular docking technology and its application to predict the DNA-Protein complex conformation; (4) Development of a new algorithm for improved analysis of high-density oligonucleotide arrays for gene expression profiling; (5) Construction and maintenance of the DNA Damage Recognition and Repair Database; and (6) Producing 14 research papers (10 published and 4 in preparation).

  7. Ion Recognition Approach to Volume Reduction of Alkaline Tank Waste by Separation of Sodium Salts

    SciTech Connect (OSTI)

    Levitskaia, Tatiana G.; Lumetta, Gregg J.; Moyer, Bruce A.; Bonnesen, Peter V.

    2005-06-01

    The purpose of this research involving collaboration between Oak Ridge National Laboratory (ORNL) and Pacific Northwest National Laboratory (PNNL) is to explore new approaches to the separation of sodium hydroxide, sodium nitrate, and other sodium salts from high-level alkaline tank waste. The principal potential benefit is a major reduction in disposed waste volume, obviating the building of expensive new waste tanks and reducing the costs of low-activity waste immobilization. Principles of ion recognition are being researched toward discovery of liquid-liquid extraction systems that selectively separate sodium hydroxide and sodium nitrate from other waste components. The successful concept of pseudohydroxide extraction using fluorinated alcohols and phenols is being developed at ORNL and PNNL toward a greater understanding of the controlling equilibria, role of solvation, and of synergistic effects involving crown ethers. Synthesis efforts are being directed toward enhanced sodium binding by crown ethers, both neutral and proton-ionizable. Studies with real tank waste at PNNL will provide feedback toward solvent compositions that have promising properties.

  8. Ion Recognition Approach to Volume Reduction of Alkaline Tank Waste by Separation of Sodium Salts

    SciTech Connect (OSTI)

    Moyer, Bruce A.; Bonnesen, Peter V.; Custelcean, Radu; Delmau, Laetitia H.; Engle, Nancy L.; Kang, Hyun-Ah; Keever, Tamara J.; Marchand, Alan P.; Gadthula, Srinivas; Gore, Vinayak K.; Huang, Zilin; Sivappa, Rasapalli; Tirunahari, Pavan K.; Levitskaia, Tatiana G.; Lumetta, Gregg J.

    2005-09-26

    The purpose of this research involving collaboration between Oak Ridge National Laboratory (ORNL) and Pacific Northwest National Laboratory (PNNL) is to explore new approaches to the separation of sodium hydroxide, sodium nitrate, and other sodium salts from high-level alkaline tank waste. The principal potential benefit is a major reduction in disposed waste volume, obviating the building of expensive new waste tanks and reducing the costs of vitrification. Principles of ion recognition are being researched toward discovery of liquid-liquid extraction systems that selectively separate sodium hydroxide and sodium nitrate from other waste components. The successful concept of pseudo hydroxide extraction using fluorinated alcohols and phenols is being developed at ORNL and PNNL toward a greater understanding of the controlling equilibria, role of solvation, and of synergistic effects involving crown ethers. Synthesis efforts are being directed toward enhanced sodium binding by crown ethers, both neutral and proton-ionizable. Studies with real tank waste at PNNL will provide feedback toward solvent compositions that have promising properties.

  9. Supramolecular Chemistry of Selective Anion Recognition for Anions of Environmental Relevance

    SciTech Connect (OSTI)

    Moyer, Bruce a.; Bostick, Debra A.; Fowler, Christopher J.; Kang, Hyun-Ah; Ruas, Alexandre; Delmau, Laetitia H.; Haverlock, Tamara J.; Llinares, Jose M.; Hossain, Alamgir; Kang, S. O.; Bowman-James, Kristin; Shriver, James A.; Marquez, Manuel; Sessler, Jonathan L.

    2005-09-22

    The major thrust of this project led by the University of Kansas (Prof. Kristin Bowman-Jones) entails the exploration of the principles of recognition and separation of sulfate by the design, synthesis, and testing of novel sulfate extractants. A key science need for the cleanup of tank wastes at Hanford has been identified in developing methods to separate those bulk waste components that have low solubilities in borosilicate glass. Sulfate has been identified as a particularly difficult and expensive problem in that its concentration in the waste is relatively high, its solubility in glass is especially low, and it interferes with the performance of both vitrification equipment and the glass waste form. The new extractants will be synthesized by the University of Kansas and the University of Texas, Austin. Oak Ridge National Laboratory (ORNL) is subjecting the new extractants to experiments that will determine their properties and effectiveness in separating sulfate from the major competing anions in the waste, especially nitrate. Such experiments will entail primarily liquid-liquid extraction. Current efforts focus on exciting new systems in which the anion receptors act as synergists for anion exchange.

  10. Structure of the Human MutSa DNA Lesion Recognition Complex

    SciTech Connect (OSTI)

    Warren,J.; Pohlhaus, T.; Changela, A.; Iyer, R.; Modrich, P.; Beese, L.

    2007-01-01

    Mismatch repair (MMR) ensures the fidelity of DNA replication, initiates the cellular response to certain classes of DNA damage, and has been implicated in the generation of immune diversity. Each of these functions depends on MutS{alpha} (MSH2{center_dot}MSH6 heterodimer). Inactivation of this protein complex is responsible for tumor development in about half of known hereditary nonpolyposis colorectal cancer kindreds and also occurs in sporadic tumors in a variety of tissues. Here, we describe a series of crystal structures of human MutS{alpha} bound to different DNA substrates, each known to elicit one of the diverse biological responses of the MMR pathway. All lesions are recognized in a similar manner, indicating that diversity of MutS{alpha}-dependent responses to DNA lesions is generated in events downstream of this lesion recognition step. This study also allows rigorous mapping of cancer-causing mutations and furthermore suggests structural pathways for allosteric communication between different regions within the heterodimer.

  11. Sulfate Recognition by Persistent Crystalline Capsules with Rigidified Hydrogen Bonding Cavities

    SciTech Connect (OSTI)

    Custelcean, Radu; Remy, Priscilla; Jiang, Deen; Bonnesen, Peter V; Moyer, Bruce A

    2008-01-01

    electivity is a fundamental property of pervasive importance in chemistry and biology as reflected in phenomena as diverse as membrane transport, catalysis, sensing, adsorption, complexation, and crystallization. Although the key principles of complementarity and preorganization governing the binding interactions underlying such phenomena were delineated long ago, truly profound selectivity has proven elusive by design in part because synthetic molecular architectures are neither maximally complementary for binding target species nor sufficiently rigid. Even if a host molecule possesses a high degree of complementarity for a guest species, it all too often can distort its structure or even rearrange its conformation altogether to accommodate competing guests. One approach taken by researchers to overcome this challenge has been to devise extremely rigid molecules that bind species within complementary cavities. Although examples have been reported to demonstrate the principle, such cases are not generally of practical utility, because of inefficient synthesis and often poor kinetics. Alternatively, flexible building blocks can be employed, but then the challenge becomes one of locking them in place. Taking a cue from natural binding agents that derive their rigidity from a network of molecular interactions, especially hydrogen bonding, we present herein an example of a crystalline, self-assembled capsule that binds sulfate by a highly complementary array of rigidified hydrogen bonds (H-bonds). Although covalent or self-assembled capsules have been previously employed as anion hosts, they typically lack the strict combination of complementarity and rigidity required for high selectivity. Furthermore, the available structural data for these systems is either restricted to a limited number of anions of similar size and shape, or varies significantly from one anion to another, which hampers the rationalization of the observed selectivity. We have been employing crystalline host environments functionalized with anion-coordinating groups as a means to obtain maximal three-dimensional complementarity and rigidity. In the present study, we focused on the problem of sulfate recognition and separation, motivated by its high relevance to environmental remediation and nuclear waste cleanup.

  12. Waste Isolation Pilot Plant (WIPP) Site Cleanup By the Numbers | Department

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

    of Energy (WIPP) Site Cleanup By the Numbers Waste Isolation Pilot Plant (WIPP) Site Cleanup By the Numbers Waste Isolation Pilot Plant (WIPP) Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an

  13. Los Alamos National Laboratory Site Cleanup By the Numbers | Department of

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

    Energy Laboratory Site Cleanup By the Numbers Los Alamos National Laboratory Site Cleanup By the Numbers Los Alamos National Laboratory Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an underground

  14. Nevada National Security Site Cleanup By the Numbers | Department of Energy

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

    Nevada National Security Site Cleanup By the Numbers Nevada National Security Site Cleanup By the Numbers Nevada National Security Site Cleanup By the Numbers In 2015, EM developed site infographics highlighting each sites history and important metrics including: Decontamination and demolition of facilities and waste sites Secure storage of spent fuel Retrieval of radioactive sludge and saltcake from tanks Treatment of contaminated groundwater Waste safely stored in an underground repository

  15. Nebraska Natural Gas Number of Gas and Gas Condensate Wells ...

    Gasoline and Diesel Fuel Update (EIA)

    Gas and Gas Condensate Wells (Number of Elements) Nebraska Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  16. Missouri Natural Gas Number of Gas and Gas Condensate Wells ...

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

    Gas and Gas Condensate Wells (Number of Elements) Missouri Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  17. Michigan Natural Gas Number of Gas and Gas Condensate Wells ...

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

    Gas and Gas Condensate Wells (Number of Elements) Michigan Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  18. Kentucky Natural Gas Number of Gas and Gas Condensate Wells ...

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

    Gas and Gas Condensate Wells (Number of Elements) Kentucky Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  19. Mississippi Natural Gas Number of Gas and Gas Condensate Wells...

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

    Gas and Gas Condensate Wells (Number of Elements) Mississippi Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

  20. Maryland Natural Gas Number of Gas and Gas Condensate Wells ...

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

    Gas and Gas Condensate Wells (Number of Elements) Maryland Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...