National Library of Energy BETA

Sample records for number recognition development

  1. 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.

  2. Property:NumberOfLowEmissionDevelopmentStrategiesExample | Open...

    Open Energy Info (EERE)

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

  3. Property:NumberOfLowEmissionDevelopmentStrategiesExamples | Open...

    Open Energy Info (EERE)

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

  4. 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.

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

    Office of Environmental Management (EM)

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

  6. 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.

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

    Energy Savers [EERE]

    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

  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. Number

    Office of Legacy Management (LM)

    ' , /v-i 2 -i 3 -A, This dow'at consists ~f--~-_,_~~~p.~,::, Number -------of.-&--copies, 1 Series.,-a-,-. ! 1 THE UNIVERSITY OF ROCHESTER 1; r-.' L INTRAMURALCORRESPONDENCE i"ks' 3 2.. September 25, 1947 Memo.tor Dr. A. H, Dovdy . From: Dr. 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 F!orks, Mayvood, New Jersey one of 2 plants in the U.S.A. engaged in the

  10. 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...

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

    Office of Environmental Management (EM)

    LA-UR-11-01857 Approved for public release; distribution I unlimited. Title: Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data Authors: Elizabeth J. Kelly and Raymond N. Tell Intended Use: Deliverable to SB-TS: Safety Basis Technical Services Los Alamos National Laboratory, an affirmative action/equal opportunity employer, is operated by the Los Alamos National Security, LLC for the National Nuclear Security Administration of the

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.).

  19. 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.

  20. 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.

  1. 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.)

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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).

  8. 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

  9. 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 (ā€œPrinciple Powerā€). 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 NRELā€™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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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).

  5. 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.

  6. George Washington Carver Recognition Day

    Broader source: Energy.gov [DOE]

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

  7. 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...

  8. 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.

  9. 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...

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

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

    DOE Patents [OSTI]

    Morozov, Victor (Manassas, VA); Bailey, Charles L. (Cross Junction, VA); Vsevolodov, Nikolai N. (Kensington, MD); Elliott, Adam (Manassas, VA)

    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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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 inmoreĀ Ā» 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.Ā«Ā less

  17. 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.

  18. 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 ...

  19. Innovative Manufacturing Initiatives Recognition Day Agenda

    Broader source: Energy.gov [DOE]

    Agenda for Innovative Manufacturing Initiatives Recognition Day held in Washington, D.C. on June 20, 2012

  20. Providing Rewards and Recognition | Department of Energy

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

    Rewards and Recognition Providing Rewards and Recognition This presentation focuses on rewarding and recognizing employees for industrial energy efficiency accomplishments. PDF icon Providing Rewards and Recognition (November 10, 2010) More Documents & Publications Communicating Accomplishments to All Stakeholders Build Replication into Corporate Culture Creating a Climate for Successful Project Implementation

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  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. 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

  14. 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.).

  15. 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.).

  16. 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.

  17. 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.

  18. 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).

  19. 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).

  20. 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).

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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).

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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).

  2. 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.

  3. 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...

  4. Recognition and Awards Program - Hanford Site

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

    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...

  5. 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 2-Hydroxyethylphosphonate Dioxygenase Citation Details In-Document Search Title: Mechanism ...

  6. Report: Employee Recruitment and Service Recognition

    Office of Environmental Management (EM)

    Recruitment and Service Recognition September 30, 2009 Submitted by the EMAB Human Capital Subcommittee Background: In Fiscal Year (FY) 2009, the Environmental Management...

  7. New Lab facility receives green building recognition

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

    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 ...

  8. 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.

  9. Big Numbers | Jefferson Lab

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

    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 equipment, we

  10. Robotic CCD microscope for enhanced crystal recognition

    DOE Patents [OSTI]

    Segelke, Brent W. (San Ramon, CA); Toppani, Dominique (Livermore, CA)

    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.

  11. 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

  12. 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

  13. 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:...

  14. 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.

  15. 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.

  16. Webinar: Leadership Recognition with Housing Innovation Awards

    Broader source: Energy.gov [DOE]

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

  17. Visual cluster analysis and pattern recognition methods

    DOE Patents [OSTI]

    Osbourn, Gordon Cecil (Albuquerque, NM); Martinez, Rubel Francisco (Albuquerque, NM)

    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.

  18. 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 Ī± (RĪ±) and Ī² (RĪ²) 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 receptorsā€™ recognition mode for IL-18 is similar to IL-1Ī²; 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.

  19. 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 Ī± (RĪ±) and Ī² (RĪ²) 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 receptorsā€™ recognition mode for IL-18 is similar to IL-1Ī²; however, certain notable differences were observed. The architecture of the IL-18 receptor second domain (D2) is uniquemoreĀ Ā» 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.Ā«Ā less

  20. 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

  1. Door latching recognition apparatus and process

    DOE Patents [OSTI]

    Eakle, Jr., Robert F. (New Ellenton, SC)

    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.

  2. 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

  3. Document Details Document Number

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

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

  4. 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...

  5. 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

  6. 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,

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

    Gasoline and Diesel Fuel Update (EIA)

    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...

  8. Texas Natural Gas Number of Commercial Consumers (Number of Elements...

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

    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...

  9. 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...

  10. 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...

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

    Gasoline and Diesel Fuel Update (EIA)

    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...

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

    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...

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

    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...

  15. 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

  16. 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 netsā€”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 āˆ¼9000 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.

  17. 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.

  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. 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

  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. 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.

  5. 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: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Number of Natural Gas

  6. 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: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Number of Natural Gas Industrial

  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 ā€œGoing to Zeroā€. 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, 100ā€™s of warheads, and then 10ā€™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, 100ā€™s, 10ā€™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. 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.

  9. Pattern recognition monitoring of PEM fuel cell

    DOE Patents [OSTI]

    Meltser, Mark Alexander (Pittsford, NY)

    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. 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 Manager 9:05-9:25am Dr. Dave Danielson, DOE EERE Assistant Secretary 9:25-9:40 Remarks from a Rep. Tim Ryan, OH 9:40-10:20am IMI Overview - Leo Christodoulou, AMO Program Manager 10:20-12:00pm First 15 Companies Present (5 minutes each) 12:00-1:15pm Networking Lunch 1:15-3:00pm Remaining Companies Present (5 minutes

  11. 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.

  12. Total Number of Operable Refineries

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

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

  13. 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.

  14. Innovative Manufacturing Initiative Recognition Day | Department of Energy

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

    Innovative Manufacturing Initiative Recognition Day Innovative Manufacturing Initiative Recognition Day June 20, 2012 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

  15. 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.

  16. 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

  17. Employee Performance Management and Recognition Program | Department of

    Office of Environmental Management (EM)

    Energy Employee Performance Management and Recognition Program Employee Performance Management and Recognition Program The purpose of this program is to establish requirements and responsibilities for the performance management program for all supervisory and non-supervisory employees at grades GS-15 and below or equivalent, employees in EJ and EK pay bands IV and V in the Excepted Service, and all wage grade employees. Desk Reference for Employee Performance Management and Recognition

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

    Office of Scientific and Technical Information (OSTI)

    ThesisDissertation: Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method Citation Details In-Document Search Title: Protein Structure ...

  19. 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.

  20. 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...

  1. 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 ...

  2. 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...

  3. 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: 2/29/2016 Next Release Date:

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

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

    Industrial Consumers (Number of Elements) Montana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 435 435 428 1990's 457 452 459 462 453 463 466 462 454 397 2000's 71 73 439 412 593 716 711 693 693 396 2010's 384 381 372 372 369 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date:

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

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

    Industrial Consumers (Number of Elements) Nevada Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 93 98 100 1990's 100 113 114 117 119 120 121 93 93 109 2000's 90 90 96 97 179 192 207 220 189 192 2010's 184 177 177 195 218 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 153 295 376 1990's 364 361 344 334 324 332 367 385 389 417 2000's 432 331 437 550 305 397 421 578 5,298 155 2010's 306 362 466 403 326 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 138 148 151 1990's 165 170 171 174 186 189 206 216 404 226 2000's 192 203 223 234 241 239 241 253 271 279 2010's 307 259 260 266 269 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016

  8. 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

  9. 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: 2/29/2016

  10. 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: 2/29/2016 Next Release

  11. 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: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages:

  12. 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: 2/29/2016 Next Release Date:

  13. 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: 2/29/2016 Next Release Date:

  14. 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: 2/29/2016 Next Release Date: 3/31/2016

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

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

    Industrial Consumers (Number of Elements) Maine Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 73 73 74 1990's 80 81 80 66 89 74 87 81 110 108 2000's 178 233 66 65 69 69 73 76 82 85 2010's 94 102 108 120 126 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring

  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: 2/29/2016 Next

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

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

    Industrial Consumers (Number of Elements) Wyoming Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 190 200 230 1990's 284 228 244 194 135 126 170 194 317 314 2000's 308 295 877 179 121 127 133 133 155 130 2010's 120 123 127 132 131 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date:

  18. 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.

  19. 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.

  20. Document ID Number: RL-721

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

    ---------------------------------------------------------- Document ID Number: RL-721 REV 4 NEPA REVIEW SCREENING FORM DOE/CX-00066 I. Project Title: Nesting Bird Deterrent Study at the 241-C Tank Farm CX B3.8, "Outdoor Terrestrial Ecological and Environmental Research" II. Project Description and Location (including Time Period over which proposed action will occur and Project Dimensions - e.g., acres displaced/disturbed, excavation length/depth, area/location/number of buildings,

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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 =

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

    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 Year-8 Year-9 1980's 46 46,702 46,636 46,776 1990's 47,292 53,982 47,781 47,678 48,568 49,145 49,693 50,115 51,712 53,022 2000's 54,056 54,724 56,260 56,082 56,186 56,572 57,091 57,169 57,586 57,191 2010's 56,676 56,547 56,532 56,585 56,649 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  8. Arizona Natural Gas Number of Residential Consumers (Number of Elements)

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

    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 Year-8 Year-9 1980's 545 567,962 564,195 572,461 1990's 586,866 642,659 604,899 610,337 635,335 661,192 689,597 724,911 764,167 802,469 2000's 846,016 884,789 925,927 957,442 993,885 1,042,662 1,088,574 1,119,266 1,128,264 1,130,047 2010's 1,138,448 1,146,286 1,157,688 1,172,003 1,186,794 - = No Data Reported; -- = Not

  9. 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

  10. 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

  11. 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 =

  12. 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;

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

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

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

  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 Industrial Consumers (Number of Elements)

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

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

  17. 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

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

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

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

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

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

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

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

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

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

  1. 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

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

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

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

  3. 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

  4. 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

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

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

    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 Year-8 Year-9 1980's 2,832 2,880 3,063 1990's 3,140 3,096 2,989 3,040 3,115 3,033 3,408 3,097 3,151 3,152 2000's 3,094 3,085 2,935 3,115 3,600 3,545 3,548 3,511 3,514 3,573 2010's 3,541 3,307 3,692 3,538 3,497 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  6. 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

  7. 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

  8. 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

  9. 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

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

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

    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 Year-8 Year-9 1980's 675 684 702 1990's 712 718 696 718 766 2,432 2,234 11,553 10,673 10,342 2000's 10,161 10,504 9,156 9,022 8,463 7,973 7,697 7,668 11,627 7,863 2010's 7,912 7,955 8,160 8,495 8,791 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  11. 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

  12. 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

  13. 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 =

  14. 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;

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 3,236 3,196 3,381 1990's 2,802 3,506 3,119 2,664 3,401 3,652 3,973 5,375 6,228 5,672 2000's 5,288 2,962 3,200 3,101 3,021 2,891 2,701 2,991 2,984 2,384 2010's 2,457 2,468 2,525 2,567 2,596 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  16. 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

  17. 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 =

  18. 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 =

  19. 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

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

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

    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 Year-9 1980's 7,929 8,163 8,356 1990's 8,301 8,479 8,573 8,678 8,655 8,650 8,672 7,779 8,112 8,136 2000's 8,267 8,515 8,111 8,098 7,899 8,328 6,929 6,858 6,806 6,712 2010's 6,571 6,482 6,381 6,554 6,526 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  1. 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 -

  2. 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

  3. 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

  4. 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

  5. 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

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

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

    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 Year-8 Year-9 1980's 676 1,034 738 1990's 699 787 740 696 765 791 799 704 695 718 2000's 717 821 842 926 907 1,118 1,060 1,136 1,075 1,051 2010's 1,053 1,066 1,076 1,085 1,099 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016

  7. 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

  8. 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

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

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

    Elements) 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 Year-7 Year-8 Year-9 1980's 6,089 6,070 6,023 1990's 6,238 6,344 6,496 6,407 6,388 6,328 6,441 6,492 6,736 7,080 2000's 6,330 6,159 5,880 5,577 5,726 5,577 5,241 4,868 4,772 4,745 2010's 4,624 5,007 5,066 5,024 5,084 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  10. 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

  11. 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 =

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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 =

  17. 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

  18. 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;

  19. 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

  20. 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; -- =

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

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

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

    Commercial Consumers (Number of Elements) California 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 413 404,507 407,435 410,231 1990's 415,073 421,278 412,467 411,648 411,140 411,535 408,294 406,803 588,224 416,791 2000's 413,003 416,036 420,690 431,795 432,367 434,899 442,052 446,267 447,160 441,806 2010's 439,572 440,990 442,708 444,342 443,115 - = No Data Reported; -- = Not Applicable; NA =

  13. California Natural Gas Number of Industrial Consumers (Number of Elements)

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

    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 Year-8 Year-9 1980's 31 44,764 44,680 46,243 1990's 46,048 44,865 40,528 42,748 38,750 38,457 36,613 35,830 36,235 36,435 2000's 35,391 34,893 33,725 34,617 41,487 40,226 38,637 39,134 39,591 38,746 2010's 38,006 37,575 37,686 37,996 37,548 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

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

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

    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 Year-7 Year-8 Year-9 1980's 7,626 7,904,858 8,113,034 8,313,776 1990's 8,497,848 8,634,774 8,680,613 8,726,187 8,790,733 8,865,541 8,969,308 9,060,473 9,181,928 9,331,206 2000's 9,370,797 9,603,122 9,726,642 9,803,311 9,957,412 10,124,433 10,329,224 10,439,220 10,515,162 10,510,950 2010's 10,542,584 10,625,190 10,681,916

  15. 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

  16. 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

  17. 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 -

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

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

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

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

  3. 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

  4. 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

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

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

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

  6. 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

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

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

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

  8. 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

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

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

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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. Battling bird flu by the numbers

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

    Battling bird flu by the numbers Battling bird flu by the numbers Lab theorists have developed a mathematical tool that could help health experts and crisis managers determine in real time whether an emerging infectious disease such as avian influenza H5N1 is poised to spread globally. May 27, 2008 Los Alamos National Laboratory sits on top of a once-remote mesa in northern New Mexico with the Jemez mountains as a backdrop to research and innovation covering multi-disciplines from bioscience,

  1. 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.

  2. 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...

  3. 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.

  4. 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...

  5. 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:...

  6. 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.

  7. Visual cluster analysis and pattern recognition template and methods

    DOE Patents [OSTI]

    Osbourn, Gordon Cecil (Albuquerque, NM); Martinez, Rubel Francisco (Albuquerque, NM)

    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.

  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. 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

  10. 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

  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. 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

  14. Preparing for Project Implementation: Providing Rewards and Recognition

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

    November 10, 2010 12 - Preparing for Project Implementation Providing Rewards and Recognition Save Energy Now LEADER Web Conference Project Implementation Seminar Series Save Energy Now LEADER Web Conference Agenda ļ‚§ Seminar Series Overview ļ‚§ Recap Seminar #11 - "Communicating" ļ‚§ Providing Rewards and Recognition Fred Schoeneborn - ORNL team Deb Kieper - 3M ļ‚§ Questions/Future Seminars Save Energy Now LEADER Web Conference Project Implementation Series ļ‚§ 12 One-hour seminars

  15. 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.

  16. Protein Structure Recognition: From Eigenvector Analysis to Structural

    Office of Scientific and Technical Information (OSTI)

    Threading Method (Thesis/Dissertation) | SciTech Connect 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. They found a strong correlation

  17. 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,

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

    Office of Scientific and Technical Information (OSTI)

    Avian-Type Influenza Neuraminidases via Generalized Born Molecular Dynamics and End-Point Free Energy Calculations (Journal Article) | SciTech Connect Journal Article: Characterizing Loop Dynamics and Ligand Recognition in Human- and Avian-Type Influenza Neuraminidases via Generalized Born Molecular Dynamics and End-Point Free Energy Calculations Citation Details In-Document Search Title: Characterizing Loop Dynamics and Ligand Recognition in Human- and Avian-Type Influenza Neuraminidases

  19. 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

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

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

    excellence from Department of Energy LANL receives recognition for safety excellence Los Alamos National Laboratory receives Star Status recognition for safety excellence from Department of Energy Los Alamos becomes the largest site in the DOE complex to receive VPP Star Status. October 8, 2014 Officials from the Department of Energy and the National Nuclear Security Administration joined Laboratory managers and employees at a VPP Star flag raising ceremony. Officials from the Department of

  1. Structural Insights into KCTD Protein Assembly and Cullin3 Recognition

    Office of Scientific and Technical Information (OSTI)

    (Journal Article) | SciTech Connect Structural Insights into KCTD Protein Assembly and Cullin3 Recognition Citation Details In-Document Search Title: Structural Insights into KCTD Protein Assembly and Cullin3 Recognition Authors: Ji, Alan X. ; Chu, Anh ; Nielsen, Tine Kragh ; Benlekbir, Samir ; Rubinstein, John L. ; PrivƩ, Gilbert G. [1] ; Toronto) [2] ; UHN) [2] + Show Author Affiliations HSC ( Publication Date: 2016-02-12 OSTI Identifier: 1236863 Resource Type: Journal Article Resource

  2. 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:

  3. National Lab Scientists Win Nobel Recognition | Department of Energy

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

    Scientists Win Nobel Recognition National Lab Scientists Win Nobel Recognition October 6, 2011 - 3:46pm Addthis Dr. Saul Perlmutter, who won the 2011 Nobel Prize in Physics, heads the Supernova Cosmology Project at Lawrence Berkeley National Laboratory. It was this team along with the High-z Supernova Search Team which found evidence of the accelerating expansion of the universe. Dr. Saul Perlmutter, who won the 2011 Nobel Prize in Physics, heads the Supernova Cosmology Project at Lawrence

  4. 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.

  5. 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 userĀ’s request,moreĀ Ā»the Reader can list every recognition step utilized so that the user can verify the recognition process manually if desired.Ā«Ā less

  6. California's Efforts for Advancing Ultrafine Particle Number...

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

    Efforts for Advancing Ultrafine Particle Number Measurements for Clean Diesel Exhaust California's Efforts for Advancing Ultrafine Particle Number Measurements for Clean Diesel...

  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...

  8. Parameterized reduced-order models using hyper-dual numbers....

    Office of Scientific and Technical Information (OSTI)

    This report presents a methodology for developing parameterized ROMs, which is based on ... DOE Contract Number: AC04-94AL85000 Resource Type: Technical Report Research Org: Sandia ...

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

    Broader source: Energy.gov [DOE]

    To provide criteria and guidelines for the Weatherization Assistance Programā€™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.

  10. 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 | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS People Mission Managing the Stockpile Preventing Proliferation Powering the Nuclear Navy Emergency Response Recapitalizing Our Infrastructure Countering Nuclear Terrorism About Our Programs Our History Who We Are Our Leadership Our Locations Budget Our Operations

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

    Office of Scientific and Technical Information (OSTI)

    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 ...

  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. 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.

  14. 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...

  15. 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 proteinā€“protein recognition is an important route to dissecting and controlling complex interaction networks. Experimental approaches have used the strategy of ā€œsecond-site suppressors,ā€ 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 proteinā€“protein interfaces. To extend this approach, it would be advantageous to be able to ā€œtransplantā€ existing engineered and experimentally validated specificity changes to other homologous proteinā€“protein complexes. Here, we test thismoreĀ Ā» 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 domainā€“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 proteinā€“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 proteinā€“protein interactions and provide challenging benchmark cases for the development of improved protein modeling and design methods that accurately account for the context.Ā«Ā less

  16. 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 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 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 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.

  17. 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

  18. SSLS Scientist Andy Armstrong Receives 2013 Employee Recognition Award

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

    Scientist Andy Armstrong Receives 2013 Employee Recognition Award - 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

  19. 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 ļæ½ 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-Protļæ½gļæ½ Program for enhancing the capabilities of small businesses to perform contracts and

  20. Idaho National Laboratory receives national recognition for Small Business

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

    Mentoring Program Media contacts: Erik Simpson (208) 360-0426 Idaho National Laboratory receives national recognition for Small Business Mentoring Program With the help of American Recovery and Reinvestment Act funds, the Idaho Cleanup Project continues work to protect the Snake River Plain Aquifer this week by injecting grout into 21 buried waste locations in the Subsurface Disposal Area (SDA) of the Radioactive Waste Management Complex (RWMC) at the Department of Energyļæ½s Idaho Site. The

  1. 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 ā€œmanmadeā€ (such as a building) or ā€œnaturalā€ (such as a tree). Suppose the label for a pixel patch is ā€œmanmadeā€; if the label for a nearby pixel patch is then more likely to be ā€œmanmadeā€ 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 modelmoreĀ Ā» 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.Ā«Ā less

  2. 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.

  3. Alabama 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) 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...

  4. Ohio 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) 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...

  5. 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...

  6. Texas 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) 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...

  7. Indiana 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) 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...

  8. Alaska 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) 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...

  9. Oregon Natural Gas Number of Gas and Gas Condensate Wells (Number...

    Gasoline and Diesel Fuel Update (EIA)

    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...

  10. U.S. Natural Gas Number of Gas and Gas Condensate Wells (Number...

    Gasoline and Diesel Fuel Update (EIA)

    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...

  11. 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...

  12. Utah 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) 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...

  13. ARM - Measurement - Cloud particle number concentration

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

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

  14. 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.

  15. OMB Control Number: 1910-5165

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

    damages assessed under Contract Work Hours and Safety Standards Act: Page 1 OMB Control Number: 1910-5165 Expires: 04302015 SEMI-ANNUAL DAVIS-BACON ENFORCEMENT REPORT...

  16. 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 Models in Computational Astrophysics - Ann Almgren, Berkeley Lab Last edited: 2016-02-01 08:06:52

  17. 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.

  18. 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.

  19. 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.

  20. Particle Number & Particulate Mass Emissions Measurements on...

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

    on a 'Euro VI' Heavy-duty Engine using the PMP Methodologies Particle Number & Particulate Mass Emissions Measurements on a 'Euro VI' Heavy-duty Engine using the PMP ...

  1. Sales and Value Recognition for Zero Energy Ready Home Webinar (Text

    Energy Savers [EERE]

    Version) | Department of Energy Sales and Value Recognition for Zero Energy Ready Home Webinar (Text Version) Sales and Value Recognition for Zero Energy Ready Home Webinar (Text Version) Below is the text version of the webinar, Sales and Value Recognition for Zero Energy Ready Home, presented in December 2014. Watch the presentation. GoToWebinar voice: The broadcast is now starting. All attendees are in listen-only mode. Lindsay Parker: Hi, everyone. Welcome to the DOE Zero Energy Ready

  2. 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

  3. 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

  4. 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.

  5. Microsoft PowerPoint - 12_BRIAN_HORN_NRC and DOE recognition...

    National Nuclear Security Administration (NNSA)

    3 Recognitions Brian Horn, NRC Pete Dessaules, DOENNSA NRC requirements for Inventory Reporting and Reconciliation Report Inventory to NMMSS * < 30 days - IAEA selected...

  6. 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.

  7. 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.

  8. 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.

  9. WIPP Documents - All documents by number

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

    Note: Documents that do not have document numbers are not included in this listing. Large file size alert This symbol means the document may be a large file size. All documents by number Common document prefixes DOE/CAO DOE/TRU DOE/CBFO DOE/WIPP DOE/EA NM DOE/EIS Other DOE/CAO Back to top DOE/CAO 95-1095, Oct. 1995 Remote Handled Transuranic Waste Study This study was conducted to satisfy the requirements defined by the WIPP Land Withdrawal Act and considered by DOE to be a prudent exercise in

  10. The 17 GHz active region number

    SciTech Connect (OSTI)

    Selhorst, C. L.; Pacini, A. A.; Costa, J. E. R.; Giménez 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.

  11. Pennsylvania Number of Natural Gas Consumers

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

    1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 618 606 604 540 627 666 1967-2014 Industrial Number of Consumers 4,745 4,624 5,007 5,066 5,024 5,084 1987-2014...

  12. 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.

  13. 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...

  14. Minnesota Number of Natural Gas Consumers

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

    1,436,063 1,445,824 1,459,134 1,472,663 1997-2014 Commercial Number of Consumers 131,801 132,163 132,938 134,394 135,557 136,382 1987-2014 Sales 131,986 132,697 134,165 135,235...

  15. West Virginia Number of Natural Gas Consumers

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

    343,837 344,131 342,069 340,256 340,102 338,652 1987-2014 Sales 344,125 342,063 340,251 340,098 338,649 1997-2014 Transported 6 6 5 4 3 1997-2014 Commercial Number of Consumers...

  16. 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...

  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. 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...

  19. Maine Number of Natural Gas Consumers

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

    20,806 21,142 22,461 23,555 24,765 27,047 1987-2014 Sales 21,141 22,461 23,555 24,765 27,047 1997-2014 Transported 1 0 0 0 0 2010-2014 Commercial Number of Consumers 8,815 9,084...

  20. South Dakota Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    173,856 176,204 179,042 1997-2014 Commercial Number of Consumers 22,071 22,267 22,570 22,955 23,214 23,591 1987-2014 Sales 22,028 22,332 22,716 22,947 23,330 1998-2014...

  1. 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.

  2. 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.

  3. 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.

  4. 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 GMMā€“UBM which uses Runnallsā€™ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, wemoreĀ Ā» 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 15Ɨ 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.Ā«Ā less

  5. 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.

  6. Maria Goeppert Mayer, the Nuclear Shell Structure, and Magic Numbers

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

    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

  7. Rhode Island Number of Natural Gas Consumers

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

    24,846 225,204 225,828 228,487 231,763 233,786 1987-2014 Sales 225,204 225,828 228,487 231,763 233,786 1997-2014 Commercial Number of Consumers 22,988 23,049 23,177 23,359 23,742 23,934 1987-2014 Sales 21,507 21,421 21,442 21,731 21,947 1998-2014 Transported 1,542 1,756 1,917 2,011 1,987 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 467 454 468 432 490 551 1967-2014 Industrial Number of Consumers 260 249 245 248 271 266 1987-2014 Sales 57 53 56 62 62 1998-2014 Transported 192

  8. South Carolina Number of Natural Gas Consumers

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

    565,774 570,797 576,594 583,633 593,286 604,743 1987-2014 Sales 570,797 576,594 583,633 593,286 604,743 1997-2014 Commercial Number of Consumers 55,850 55,853 55,846 55,908 55,997 56,172 1987-2014 Sales 55,776 55,760 55,815 55,902 56,074 1998-2014 Transported 77 86 93 95 98 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 393 432 396 383 426 452 1967-2014 Industrial Number of Consumers 1,358 1,325 1,329 1,435 1,452 1,426 1987-2014 Sales 1,139 1,137 1,215 1,223 1,199 1998-2014

  9. Tennessee Number of Natural Gas Consumers

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

    ,083,573 1,085,387 1,089,009 1,084,726 1,094,122 1,106,681 1987-2014 Sales 1,085,387 1,089,009 1,084,726 1,094,122 1,106,681 1997-2014 Commercial Number of Consumers 127,704 127,914 128,969 130,139 131,091 131,001 1987-2014 Sales 127,806 128,866 130,035 130,989 130,905 1998-2014 Transported 108 103 104 102 96 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 406 439 404 345 411 438 1967-2014 Industrial Number of Consumers 2,717 2,702 2,729 2,679 2,581 2,595 1987-2014 Sales 2,340

  10. Texas Number of Natural Gas Consumers

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

    4,248,613 4,288,495 4,326,156 4,370,057 4,424,103 4,469,282 1987-2014 Sales 4,287,929 4,326,076 4,369,990 4,424,037 4,469,220 1997-2014 Transported 566 80 67 66 62 1997-2014 Commercial Number of Consumers 313,384 312,277 314,041 314,811 314,036 317,217 1987-2014 Sales 310,842 312,164 312,574 311,493 313,971 1998-2014 Transported 1,435 1,877 2,237 2,543 3,246 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 534 605 587 512 553 583 1967-2014 Industrial Number of Consumers 8,581

  11. Kentucky Number of Natural Gas Consumers

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

    754,761 758,129 759,584 757,790 761,575 760,131 1987-2014 Sales 728,940 730,602 730,184 736,011 735,486 1997-2014 Transported 29,189 28,982 27,606 25,564 24,645 1997-2014 Commercial Number of Consumers 83,862 84,707 84,977 85,129 85,999 85,318 1987-2014 Sales 80,541 80,392 80,644 81,579 81,026 1998-2014 Transported 4,166 4,585 4,485 4,420 4,292 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 423 435 407 361 435 469 1967-2014 Industrial Number of Consumers 1,715 1,742 1,705 1,720

  12. Louisiana Number of Natural Gas Consumers

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

    889,570 893,400 897,513 963,688 901,635 899,378 1987-2014 Sales 893,400 897,513 963,688 901,635 899,378 1997-2014 Transported 0 0 0 0 0 1997-2014 Commercial Number of Consumers 58,396 58,562 58,749 63,381 59,147 58,611 1987-2014 Sales 58,501 58,685 63,256 58,985 58,438 1998-2014 Transported 61 64 125 162 173 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 405 461 441 415 488 532 1967-2014 Industrial Number of Consumers 954 942 920 963 916 883 1987-2014 Sales 586 573 628 570 546

  13. Maryland Number of Natural Gas Consumers

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

    067,807 1,071,566 1,077,168 1,078,978 1,099,272 1,101,292 1987-2014 Sales 923,870 892,844 867,627 852,555 858,352 1997-2014 Transported 147,696 184,324 211,351 246,717 242,940 1997-2014 Commercial Number of Consumers 75,771 75,192 75,788 75,799 77,117 77,846 1987-2014 Sales 54,966 53,778 52,383 52,763 53,961 1998-2014 Transported 20,226 22,010 23,416 24,354 23,885 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 912 898 891 846 923 961 1967-2014 Industrial Number of Consumers

  14. Mississippi Number of Natural Gas Consumers

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

    437,715 436,840 442,479 442,840 445,589 444,423 1987-2014 Sales 436,840 439,511 440,171 442,974 444,423 1997-2014 Transported 0 2,968 2,669 2,615 0 2010-2014 Commercial Number of Consumers 50,713 50,537 50,636 50,689 50,153 50,238 1987-2014 Sales 50,503 50,273 50,360 49,829 50,197 1998-2014 Transported 34 363 329 324 41 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 377 419 400 352 388 442 1967-2014 Industrial Number of Consumers 1,141 980 982 936 933 943 1987-2014 Sales 860 853

  15. Missouri Number of Natural Gas Consumers

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

    348,781 1,348,549 1,342,920 1,389,910 1,357,740 1,363,286 1987-2014 Sales 1,348,549 1,342,920 1,389,910 1,357,740 1,363,286 1997-2014 Transported 0 0 0 0 0 2010-2014 Commercial Number of Consumers 140,633 138,670 138,214 144,906 142,495 143,024 1987-2014 Sales 137,342 136,843 143,487 141,047 141,477 1998-2014 Transported 1,328 1,371 1,419 1,448 1,547 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 437 441 451 378 453 510 1967-2014 Industrial Number of Consumers 3,573 3,541 3,307

  16. Montana Number of Natural Gas Consumers

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

    255,472 257,322 259,046 259,957 262,122 265,849 1987-2014 Sales 256,841 258,579 259,484 261,637 265,323 1997-2014 Transported 481 467 473 485 526 2005-2014 Commercial Number of Consumers 33,731 34,002 34,305 34,504 34,909 35,205 1987-2014 Sales 33,652 33,939 33,967 34,305 34,558 1998-2014 Transported 350 366 537 604 647 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 699 602 651 557 601 612 1967-2014 Industrial Number of Consumers 396 384 381 372 372 369 1987-2014 Sales 312 304

  17. Utah Number of Natural Gas Consumers

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

    810,442 821,525 830,219 840,687 854,389 869,052 1987-2014 Sales 821,525 830,219 840,687 854,389 869,052 1997-2014 Commercial Number of Consumers 60,781 61,976 62,885 63,383 64,114 65,134 1987-2014 Sales 61,929 62,831 63,298 63,960 64,931 1998-2014 Transported 47 54 85 154 203 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 609 621 643 558 646 586 1967-2014 Industrial Number of Consumers 293 293 286 302 323 328 1987-2014 Sales 205 189 189 187 178 1998-2014 Transported 88 97 113

  18. Vermont Number of Natural Gas Consumers

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

    37,242 38,047 38,839 39,917 41,152 42,231 1987-2014 Sales 38,047 38,839 39,917 41,152 42,231 1997-2014 Commercial Number of Consumers 5,085 5,137 5,256 5,535 5,441 5,589 1987-2014 Sales 5,137 5,256 5,535 5,441 5,589 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 488 464 472 418 873 864 1967-2014 Industrial Number of Consumers 36 38 36 38 13 13 1987-2014 Sales 37 35 38 13 13 1998-2014 Transported 1 1 0 0 0 1999-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 80,290

  19. Virginia Number of Natural Gas Consumers

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

    1,124,717 1,133,103 1,145,049 1,155,636 1,170,161 1,183,894 1987-2014 Sales 1,076,080 1,081,581 1,088,340 1,102,646 1,114,224 1997-2014 Transported 57,023 63,468 67,296 67,515 69,670 1997-2014 Commercial Number of Consumers 95,704 95,401 96,086 96,503 97,499 98,741 1987-2014 Sales 85,521 85,522 85,595 86,618 87,470 1998-2014 Transported 9,880 10,564 10,908 10,881 11,271 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 707 722 669 624 699 731 1967-2014 Industrial Number of

  20. Washington Number of Natural Gas Consumers

    Annual Energy Outlook [U.S. Energy Information Administration (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 99,674 100,038 100,939 101,730 1987-2014 Sales 99,166 99,584 99,930 100,819 101,606 1998-2014 Transported 65 90 108 120 124 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 563 517 567 534 553 535 1967-2014 Industrial Number of Consumers 3,428 3,372 3,353 3,338 3,320 3,355 1987-2014 Sales 3,056 3,031

  1. Wisconsin Number of Natural Gas Consumers

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

    656,614 1,663,583 1,671,834 1,681,001 1,692,891 1,705,907 1987-2014 Sales 1,663,583 1,671,834 1,681,001 1,692,891 1,705,907 1997-2014 Transported 0 0 0 0 0 1997-2014 Commercial Number of Consumers 163,843 164,173 165,002 165,657 166,845 167,901 1987-2014 Sales 163,060 163,905 164,575 165,718 166,750 1998-2014 Transported 1,113 1,097 1,082 1,127 1,151 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 558 501 528 465 596 637 1967-2014 Industrial Number of Consumers 6,396 6,413 6,376

  2. Wyoming Number of Natural Gas Consumers

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

    153,062 153,852 155,181 157,226 158,889 160,896 1987-2014 Sales 117,735 118,433 118,691 117,948 118,396 1997-2014 Transported 36,117 36,748 38,535 40,941 42,500 1997-2014 Commercial Number of Consumers 19,843 19,977 20,146 20,387 20,617 20,894 1987-2014 Sales 14,319 14,292 14,187 14,221 14,452 1998-2014 Transported 5,658 5,854 6,200 6,396 6,442 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 523 558 580 514 583 583 1967-2014 Industrial Number of Consumers 130 120 123 127 132 131

  3. Nebraska Number of Natural Gas Consumers

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

    512,551 510,776 514,481 515,338 527,397 522,408 1987-2014 Sales 442,413 446,652 447,617 459,712 454,725 1997-2014 Transported 68,363 67,829 67,721 67,685 67,683 1997-2014 Commercial Number of Consumers 56,454 56,246 56,553 56,608 58,005 57,191 1987-2014 Sales 40,348 40,881 41,074 42,400 41,467 1998-2014 Transported 15,898 15,672 15,534 15,605 15,724 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 563 569 568 468 555 567 1967-2014 Industrial Number of Consumers 7,863 7,912 7,955

  4. Nevada Number of Natural Gas Consumers

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

    760,391 764,435 772,880 782,759 794,150 808,970 1987-2014 Sales 764,435 772,880 782,759 794,150 808,970 1997-2014 Commercial Number of Consumers 41,303 40,801 40,944 41,192 41,710 42,338 1987-2014 Sales 40,655 40,786 41,023 41,536 42,163 1998-2014 Transported 146 158 169 174 175 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 715 722 751 704 748 687 1967-2014 Industrial Number of Consumers 192 184 177 177 195 218 1987-2014 Sales 152 147 146 162 183 1998-2014 Transported 32 30 31

  5. New Hampshire Number of Natural Gas Consumers

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

    96,924 95,361 97,400 99,738 98,715 99,146 1987-2014 Sales 95,360 97,400 99,738 98,715 99,146 1997-2014 Transported 1 0 0 0 0 2010-2014 Commercial Number of Consumers 16,937 16,645 17,186 17,758 17,298 17,421 1987-2014 Sales 15,004 15,198 15,429 14,685 14,527 1998-2014 Transported 1,641 1,988 2,329 2,613 2,894 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 587 505 517 458 532 540 1967-2014 Industrial Number of Consumers 155 306 362 466 403 326 1987-2014 Sales 31 25 30 35 45

  6. New Mexico Number of Natural Gas Consumers

    Annual Energy Outlook [U.S. Energy Information Administration (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 Consumers 48,846 48,757 49,406 48,914 50,163 55,689 1987-2014 Sales 45,679 46,104 45,298 46,348 51,772 1998-2014 Transported 3,078 3,302 3,616 3,815 3,917 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 506 516 507 509 534 461 1967-2014 Industrial Number of Consumers 471 438 360 121 123 116 1987-2014 Sales 390

  7. North Dakota Number of Natural Gas Consumers

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

    22,065 123,585 125,392 130,044 133,975 137,972 1987-2014 Sales 123,585 125,392 130,044 133,975 137,972 1997-2014 Transported 0 0 0 0 0 2004-2014 Commercial Number of Consumers 17,632 17,823 18,421 19,089 19,855 20,687 1987-2014 Sales 17,745 18,347 19,021 19,788 20,623 1998-2014 Transported 78 74 68 67 64 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 623 578 596 543 667 677 1967-2014 Industrial Number of Consumers 279 307 259 260 266 269 1987-2014 Sales 255 204 206 211 210

  8. Oklahoma Number of Natural Gas Consumers

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

    924,745 914,869 922,240 927,346 931,981 937,237 1987-2014 Sales 914,869 922,240 927,346 931,981 937,237 1997-2014 Transported 0 0 0 0 0 1997-2014 Commercial Number of Consumers 94,314 92,430 93,903 94,537 95,385 96,004 1987-2014 Sales 88,217 89,573 90,097 90,861 91,402 1998-2014 Transported 4,213 4,330 4,440 4,524 4,602 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 439 452 430 382 464 489 1967-2014 Industrial Number of Consumers 2,618 2,731 2,733 2,872 2,958 3,063 1987-2014

  9. Oregon Number of Natural Gas Consumers

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

    675,582 682,737 688,681 693,507 700,211 707,010 1987-2014 Sales 682,737 688,681 693,507 700,211 707,010 1997-2014 Commercial Number of Consumers 76,893 77,370 77,822 78,237 79,276 80,480 1987-2014 Sales 77,351 77,793 78,197 79,227 80,422 1998-2014 Transported 19 29 40 49 58 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 387 352 390 368 386 353 1967-2014 Industrial Number of Consumers 1,051 1,053 1,066 1,076 1,085 1,099 1987-2014 Sales 821 828 817 821 839 1998-2014 Transported

  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. Colorado Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    ,622,434 1,634,587 1,645,716 1,659,808 1,672,312 1,690,581 1986-2014 Sales 1,634,582 1,645,711 1,659,803 1,672,307 1,690,576 1997-2014 Transported 5 5 5 5 5 1997-2014 Commercial Number of Consumers 145,624 145,460 145,837 145,960 150,145 150,235 1986-2014 Sales 145,236 145,557 145,563 149,826 149,921 1998-2014 Transported 224 280 397 319 314 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 429 396 383 355 392 386 1967-2014 Industrial Number of Consumers 5,084 6,232 6,529 6,906

  12. Delaware Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    9,006 150,458 152,005 153,307 155,627 158,502 1986-2014 Sales 150,458 152,005 153,307 155,627 158,502 1997-2014 Commercial Number of Consumers 12,839 12,861 12,931 12,997 13,163 13,352 1986-2014 Sales 12,706 12,656 12,644 12,777 12,902 1998-2014 Transported 155 275 353 386 450 1999-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 910 948 810 772 849 890 1967-2014 Industrial Number of Consumers 112 114 129 134 138 141 1987-2014 Sales 40 35 29 28 28 1998-2014 Transported 74 94 105 110

  13. Florida Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    674,090 675,551 679,199 686,994 694,210 703,535 1986-2014 Sales 661,768 664,564 672,133 679,191 687,766 1997-2014 Transported 13,783 14,635 14,861 15,019 15,769 1997-2014 Commercial Number of Consumers 59,549 60,854 61,582 63,477 64,772 67,460 1986-2014 Sales 41,750 41,068 41,102 40,434 41,303 1998-2014 Transported 19,104 20,514 22,375 24,338 26,157 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 846 888 869 861 926 929 1967-2014 Industrial Number of Consumers 607 581 630 507 528

  14. Georgia Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    1,744,934 1,740,587 1,740,006 1,739,543 1,805,425 1,755,847 1986-2014 Sales 321,290 321,515 319,179 377,652 315,562 1997-2014 Transported 1,419,297 1,418,491 1,420,364 1,427,773 1,440,285 1997-2014 Commercial Number of Consumers 127,347 124,759 123,454 121,243 126,060 122,573 1986-2014 Sales 32,318 32,162 31,755 36,556 31,845 1998-2014 Transported 92,441 91,292 89,488 89,504 90,728 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 421 482 458 428 454 482 1967-2014 Industrial Number

  15. Hawaii Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    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 (Thousand Cubic Ft.) 691 697 691 727 713 692 1980-2014 Industrial Number of Consumers 25 24 24 22 22 23 1997-2014 Sales 24 24 22 22 23 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 13,753 14,111 15,087 16,126 17,635 17,

  16. Idaho Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    42,277 346,602 350,871 353,963 359,889 367,394 1987-2014 Sales 346,602 350,871 353,963 359,889 367,394 1997-2014 Commercial Number of Consumers 38,245 38,506 38,912 39,202 39,722 40,229 1987-2014 Sales 38,468 38,872 39,160 39,681 40,188 1998-2014 Transported 38 40 42 41 41 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 412 390 433 404 465 422 1967-2014 Industrial Number of Consumers 187 184 178 179 183 189 1987-2014 Sales 108 103 105 109 115 1998-2014 Transported 76 75 74 74 74

  17. Iowa Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    875,781 879,713 883,733 892,123 895,414 900,420 1987-2014 Sales 879,713 883,733 892,123 895,414 900,420 1997-2014 Commercial Number of Consumers 98,416 98,396 98,541 99,113 99,017 99,182 1987-2014 Sales 96,996 97,075 97,580 97,334 97,409 1998-2014 Transported 1,400 1,466 1,533 1,683 1,773 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 576 525 526 442 572 579 1967-2014 Industrial Number of Consumers 1,626 1,528 1,465 1,469 1,491 1,572 1987-2014 Sales 1,161 1,110 1,042 1,074 1,135

  18. 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 84,715 84,446 84,874 84,673 84,969 85,867 1987-2014 Sales 78,310 78,559 78,230 78,441 79,231 1998-2014 Transported 6,136 6,315 6,443 6,528 6,636 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 384 377 378 301 391 425 1967-2014 Industrial Number of Consumers 7,793 7,664 7,954 7,970 7,877 7,429 1987-2014

  19. Alabama Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    785,005 778,985 772,892 767,396 765,957 769,418 1986-2014 Sales 778,985 772,892 767,396 765,957 769,418 1997-2014 Transported 0 0 0 0 0 1997-2014 Commercial Number of Consumers 67,674 68,163 67,696 67,252 67,136 67,806 1986-2014 Sales 68,017 67,561 67,117 67,006 67,677 1998-2014 Transported 146 135 135 130 129 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 359 397 371 320 377 406 1967-2014 Industrial Number of Consumers 3,057 3,039 2,988 3,045 3,143 3,244 1986-2014 Sales 2,758

  20. Alaska Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    120,124 121,166 121,736 122,983 124,411 126,416 1986-2014 Sales 121,166 121,736 122,983 124,411 126,416 1997-2014 Commercial Number of Consumers 13,215 12,998 13,027 13,133 13,246 13,399 1986-2014 Sales 12,673 12,724 13,072 13,184 13,336 1998-2014 Transported 325 303 61 62 63 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 1,258 1,225 1,489 1,515 1,411 1,338 1967-2014 Industrial Number of Consumers 3 3 5 3 3 1 1987-2014 Sales 2 2 3 2 1 1998-2014 Transported 1 3 0 1 0 1998-2014

  1. Arizona Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    ,130,047 1,138,448 1,146,286 1,157,688 1,172,003 1,186,794 1986-2014 Sales 1,138,448 1,146,280 1,157,682 1,171,997 1,186,788 1997-2014 Transported 0 6 6 6 6 1997-2014 Commercial Number of Consumers 57,191 56,676 56,547 56,532 56,585 56,649 1986-2014 Sales 56,510 56,349 56,252 56,270 56,331 1998-2014 Transported 166 198 280 315 318 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 563 564 577 558 581 538 1967-2014 Industrial Number of Consumers 390 368 371 379 383 386 1987-2014

  2. Arkansas Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    557,355 549,970 551,795 549,959 549,764 549,034 1986-2014 Sales 549,970 551,795 549,959 549,764 549,034 1997-2014 Commercial Number of Consumers 69,043 67,987 67,815 68,765 68,791 69,011 1986-2014 Sales 67,676 67,454 68,151 68,127 68,291 1998-2014 Transported 311 361 614 664 720 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 527 592 590 603 692 734 1967-2014 Industrial Number of Consumers 1,025 1,079 1,133 990 1,020 1,009 1986-2014 Sales 580 554 523 513 531 1998-2014 Transported

  3. 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

  4. Low Mach Number Models in Computational Astrophysics

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

    In memoriam: Michael Welcome 1957 - 2014 RIP Almgren CCSE Low Mach Number Models in Computational Astrophysics Ann Almgren Center for Computational Sciences and Engineering Lawrence Berkeley National Laboratory NUG 2014: NERSC@40 February 4, 2014 Collaborators: John Bell, Chris Malone, Andy Nonaka, Stan Woosley, Michael Zingale Almgren CCSE Introduction We often associate astrophysics with explosive phenomena: novae supernovae gamma-ray bursts X-ray bursts Type Ia Supernovae Largest

  5. Notices Total Estimated Number of Annual

    Energy Savers [EERE]

    372 Federal Register / Vol. 78, No. 181 / Wednesday, September 18, 2013 / Notices Total Estimated Number of Annual Burden Hours: 10,128. Abstract: Enrollment in the Federal Student Aid (FSA) Student Aid Internet Gateway (SAIG) allows eligible entities to securely exchange Title IV, Higher Education Act (HEA) assistance programs data electronically with the Department of Education processors. Organizations establish Destination Point Administrators (DPAs) to transmit, receive, view and update

  6. 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

  7. 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: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Number of

  8. 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...

  9. 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 ...

  10. DOE Award Number DE-SC0006012 Recipient: NCAR Project Title: The Interface between Earth System Models and Impacts on Society

    Office of Scientific and Technical Information (OSTI)

    Award Number DE-SC0006012 Recipient: NCAR Project Title: The Interface between Earth System Models and Impacts on Society Name of principal investigator: Jim Hurrell Executive Summary: This proposal funded planning activities to determine the readiness for a new working group on societal dimensions for the Community Earth System Model (CESM) project. This is in recognition of the potential that Earth System Models have to play a central role in the provision of information to support

  11. 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.

  12. 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...

  13. 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...

  14. 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...

  15. The numbers will follow | Jefferson Lab

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

    The numbers will follow September 26, 2008 As all of you well know, the safety performance of Jefferson Lab, our laboratory, has been nothing short of stellar over the past couple of years. To cap it all, you were subjected to what is usually rated as the toughest of the sit-down examinations, the HSS audit. Not only did you exceed expectations, but you did so by a large margin. A basis for this great result, as documented by the HSS team, was the engagement and commitment of the workforce, the

  16. Mo Year Report Period: EIA ID NUMBER:

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

    Mo Year Report Period: EIA ID NUMBER: http://www.eia.gov/survey/form/eia_14/instructions.pdf Mailing Address: Secure File Transfer option available at: (e.g., PO Box, RR) https://signon.eia.doe.gov/upload/noticeoog.jsp Electronic Transmission: The PC Electronic Zip Code - Data Reporting Option (PEDRO) is available. If interested in software, call (202) 586-9659. Email form to: OOG.SURVEYS@eia.doe.gov - - - - Fax form to: (202) 586-9772 Mail form to: Oil & Gas Survey Email address: U.S.

  17. Experimental Stations by Number | Stanford Synchrotron Radiation

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

    Lightsource Experimental Stations by Number Beam Line by Techniques Photon Source Parameters Station Type Techniques Energy Range Contact Person Experimental Station 1-5 X-ray Materials Small-angle X-ray Scattering (SAXS) focused 4600-16000 eV Christopher J. Tassone Tim J. Dunn Experimental Station 2-1 X-ray Powder diffraction Thin film diffraction Focused 5000 - 14500 eV Apurva Mehta Charles Troxel Jr Experimental Station 2-2 X-ray X-ray Absorption Spectroscopy 1000-40000 eV Ryan Davis

  18. 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

  19. What's Behind the Numbers? | Department of Energy

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

    What's Behind the Numbers? Dr. Richard Newell Dr. Richard Newell What does this mean for me? New website shows data on the why's, when's and how's of crude oil prices. Among the most visible prices that consumers may see on a daily basis are the ones found on the large signs at the gasoline stations alongside our streets and highways. The biggest single factor affecting gasoline prices is the cost of crude oil, the main raw material for gasoline production, which accounts for well over half the

  20. 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).

  1. SES CANDIDATE DEVELOPMENT PROGRAM

    Energy Savers [EERE]

    3 (11-03) SENIOR EXECUTIVE SERVICE CANDIDATE DEVELOPMENT PROGRAM (SESCDP) Developmental Assignment Opportunity DATE: NAME OF SES CANDIDATE: TITLE: ASSIGNMENT NUMBER: ASSIGNMENT BEGINS: ENDS: TELEPHONE NUMBER: FAX NUMBER: EMAIL ADDRESS: ASSIGNMENT LOCATION HOST ORGANIZATION: PURPOSE OF ASSIGNMENT: ASSIGNMENT POSITION: ASSIGNMENT DUTIES: EXECUTIVE COR QUALIFICATIONS TO BE ADDRESSED: OFFICE ADDRESS: TELEPHONE NUMBER: FAX NUMBER: E-MAIL ADDRESS: 1 U.S. DEPARTMENT OF ENERGY SENIOR EXECUTIVE SERVICE

  2. 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.

  3. 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

  4. Map of the State Recognition of the Auxiliary Power Weight Exemption |

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

    Department of Energy Map of the State Recognition of the Auxiliary Power Weight Exemption Map of the State Recognition of the Auxiliary Power Weight Exemption ā€  Allows the 400-lb exemption by enforcement policy rather than by law and has legislation in process to allow the 400-lb exemption by law Ā§ Allows the 400-lb exemption by law and a 550-lb exemption takes effect on October 1, 2014 State Recognition of the Auxiliary Power Weight Exemption to GVW Limit: 23 CFR 658.17(n) Does not

  5. Arizona 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) 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 Year-6 Year-7 Year-8 Year-9 1980's 3 1990's 5 6 6 6 6 7 7 8 8 8 2000's 9 8 7 9 6 6 7 7 6 6 2010's 5 5 5 5 5 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages:

  6. 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.

  7. 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 Ā“kernelĀ” 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 togethermoreĀ Ā» 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.Ā«Ā less

  8. 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.

  9. Michigan Number of Natural Gas Consumers

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

    3,169,026 3,152,468 3,153,895 3,161,033 3,180,349 3,192,807 1987-2014 Sales 2,952,550 2,946,507 2,939,693 2,950,315 2,985,315 1997-2014 Transported 199,918 207,388 221,340 230,034 207,492 1997-2014 Commercial Number of Consumers 252,017 249,309 249,456 249,994 250,994 253,127 1987-2014 Sales 217,325 213,995 212,411 213,532 219,240 1998-2014 Transported 31,984 35,461 37,583 37,462 33,887 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 649 611 656 578 683 736 1967-2014 Industrial

  10. New Jersey Number of Natural Gas Consumers

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

    2,635,324 2,649,282 2,659,205 2,671,308 2,686,452 2,705,274 1987-2014 Sales 2,556,514 2,514,492 2,467,520 2,428,664 2,482,281 1997-2014 Transported 92,768 144,713 203,788 257,788 222,993 1997-2014 Commercial Number of Consumers 234,125 234,158 234,721 237,602 236,746 240,083 1987-2014 Sales 200,680 196,963 192,913 185,030 186,591 1998-2014 Transported 33,478 37,758 44,689 51,716 53,492 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 771 775 817 735 726 842 1967-2014 Industrial

  11. Ohio Number of Natural Gas Consumers

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

    3,253,184 3,240,619 3,236,160 3,244,274 3,271,074 3,283,869 1987-2014 Sales 1,418,217 1,352,292 855,055 636,744 664,015 1997-2014 Transported 1,822,402 1,883,868 2,389,219 2,634,330 2,619,854 1997-2014 Commercial Number of Consumers 270,596 268,346 268,647 267,793 269,081 269,758 1987-2014 Sales 92,621 85,877 51,308 35,966 37,035 1998-2014 Transported 175,725 182,770 216,485 233,115 232,723 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 594 583 601 543 625 679 1967-2014

  12. California Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    0,510,950 10,542,584 10,625,190 10,681,916 10,754,908 10,781,720 1986-2014 Sales 10,469,734 10,545,585 10,547,706 10,471,814 10,372,973 1997-2014 Transported 72,850 79,605 134,210 283,094 408,747 1997-2014 Commercial Number of Consumers 441,806 439,572 440,990 442,708 444,342 443,115 1986-2014 Sales 399,290 390,547 387,760 387,806 385,878 1998-2014 Transported 40,282 50,443 54,948 56,536 57,237 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 561 564 558 572 574 536 1967-2014

  13. Illinois Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    ,839,438 3,842,206 3,855,942 3,878,806 3,838,120 3,868,501 1987-2014 Sales 3,568,120 3,594,047 3,605,796 3,550,217 3,570,339 1997-2014 Transported 274,086 261,895 273,010 287,903 298,162 1997-2014 Commercial Number of Consumers 294,226 291,395 293,213 297,523 282,743 294,391 1987-2014 Sales 240,197 241,582 244,480 225,913 235,097 1998-2014 Transported 51,198 51,631 53,043 56,830 59,294 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 757 680 735 632 816 837 1967-2014 Industrial

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

    Office of Environmental Management (EM)

    Contract Number: Contract Type: Total Estimated Contract Cost: Performance Period Total Fee Paid FY2004 $294,316 FY2005 $820,074 FY2006 $799,449 FY2007 $877,898 FY2008 $866,608 FY2009 $886,404 FY2010 $800,314 FY2011 $871,280 FY2012 $824,517 FY2013 Cumulative Fee Paid $7,040,860 $820,074 $799,449 $877,898 $916,130 $886,608 Computer Sciences Corporation DE-AC06-04RL14383 $895,358 $899,230 $907,583 Cost Plus Award Fee $134,100,336 $8,221,404 Fee Available Contract Period: Fee Information Minimum

  15. 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.

  16. 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

  17. Engineering of a Histone-Recognition Domain in Dnmt3a Alters the Epigenetic

    Office of Scientific and Technical Information (OSTI)

    Landscape and Phenotypic Features of Mouse ESCs (Journal Article) | SciTech Connect Engineering of a Histone-Recognition Domain in Dnmt3a Alters the Epigenetic Landscape and Phenotypic Features of Mouse ESCs Citation Details In-Document Search Title: Engineering of a Histone-Recognition Domain in Dnmt3a Alters the Epigenetic Landscape and Phenotypic Features of Mouse ESCs Authors: Noh, Kyung-Min ; Wang, Haibo ; Kim, Hyunjae R. ; Wenderski, Wendy ; Fang, Fang ; Li, Charles H. ; Dewell, Scott

  18. 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

  19. 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).

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. U.S. Natural Gas Number of Commercial Consumers - Sales (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) - Sales (Number of Elements) U.S. Natural Gas Number of Commercial Consumers - Sales (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 4,823,842 4,599,494 2000's 4,576,873 4,532,034 4,588,964 4,662,853 4,644,363 4,698,626 4,733,822 2010's 4,584,884 4,556,220 4,518,745 4,491,326 4,533,729 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  5. 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: 2/29/2016 Next Release

  6. U.S. Natural Gas Number of Industrial Consumers - Sales (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Sales (Number of Elements) U.S. Natural Gas Number of Industrial Consumers - Sales (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 182,424 157,050 2000's 157,806 152,974 143,177 142,816 151,386 146,450 135,070 2010's 129,119 124,552 121,821 123,124 122,182 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date:

  7. 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: 2/29/2016 Next Release Date:

  8. U.S. Natural Gas Number of Residential Consumers - Sales (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Sales (Number of Elements) U.S. Natural Gas Number of Residential Consumers - Sales (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 55,934,175 56,520,482 56,023,710 2000's 56,261,031 56,710,548 57,267,445 57,815,669 58,524,797 59,787,524 60,129,047 2010's 60,267,648 60,408,842 60,010,723 59,877,464 60,222,681 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  9. 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.

  10. 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

  11. 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

  12. New Jersey Natural Gas Number of Industrial Consumers (Number of Elements)

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

    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 Year-8 Year-9 1980's 6,265 6,123 6,079 1990's 5,976 8,444 11,474 11,224 10,608 10,362 10,139 17,625 16,282 10,089 2000's 9,686 9,247 8,473 9,027 8,947 8,500 8,245 8,036 7,680 7,871 2010's 7,505 7,391 7,290 7,216 7,157 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  13. 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

  14. 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

  15. 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 =

  16. 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

  17. 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

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

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

    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 Year-8 Year-9 1980's 23,276 24,654 27,426 1990's 25,008 28,837 28,198 23,833 21,833 22,484 15,300 23,099 5,294 6,136 2000's 6,553 6,501 3,068 2,984 2,963 3,752 3,642 7,484 7,080 6,634 2010's 6,236 6,609 5,910 6,311 6,313 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  19. 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 - =

  20. 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