Sample records for analysis system sas

  1. UBC Social Ecological Economic Development Studies (SEEDS) Student Report An Investigation into ECO-TEK's Solar Aquatics System (SAS) for

    E-Print Network [OSTI]

    -TEK's Solar Aquatics System (SAS) for the UBC Farm Centre Building Asad Khan Harshanvit Singh Sean Henderson of a project/report". #12; APSC 262 FINAL REPORT An Investigation into ECO-TEK's Solar Aquatics System (SAS) for the UBC Farm Centre Building Asad Khan Harshanvit Singh Sean Henderson Wesley Shuen Tutorial Instructor

  2. Validation of the integration of CFD and SAS4A/SASSYS-1: Analysis of EBR-II shutdown heat removal test 17

    SciTech Connect (OSTI)

    Thomas, J. W.; Fanning, T. H.; Vilim, R.; Briggs, L. L. [Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL 60439-4842 (United States)

    2012-07-01T23:59:59.000Z

    Recent analyses have demonstrated the need to model multidimensional phenomena, particularly thermal stratification in outlet plena, during safety analyses of loss-of-flow transients of certain liquid-metal cooled reactor designs. Therefore, Argonne's reactor systems safety code SAS4A/SASSYS-1 is being enhanced by integrating 3D computational fluid dynamics models of the plena. A validation exercise of the new tool is being performed by analyzing the protected loss-of-flow event demonstrated by the EBR-II Shutdown Heat Removal Test 17. In this analysis, the behavior of the coolant in the cold pool is modeled using the CFD code STAR-CCM+, while the remainder of the cooling system and the reactor core are modeled with SAS4A/SASSYS-1. This paper summarizes the code integration strategy and provides the predicted 3D temperature and velocity distributions inside the cold pool during SHRT-17. The results of the coupled analysis should be considered preliminary at this stage, as the exercise pointed to the need to improve the CFD model of the cold pool tank. (authors)

  3. Shielding analysis of the NAC-MPC storage system

    SciTech Connect (OSTI)

    Napolitano, D.G.; Romano, N.J. [NAC International, Norcross, GA (United States); Hertel, N.E. [Georgia Institute of Technology, Atlanta, GA (United States)] [and others

    1997-12-01T23:59:59.000Z

    This paper presents the shielding analyses of the NAC-MPC dry cask storage system. The NAC-MPC dry cask storage system consists of a transportable storage canister, a transfer cask, and a vertical concrete storage cask. The NAC-MPC is designed to accommodate 36 {open_quotes}Yankee Class{close_quotes} fuel assemblies with a maximum burnup of 36,000 MWd/tonne U burnup and 8 yr cooling time. The shielding analysis is performed with the SCALE 4.3 code package which includes SAS2H for source term generation and SAS4A, a modification of SAS4, for shielding evaluations. SAS4 utilizes a one-dimensional XSDRNPM adjoint calculation of the cask to generate biasing parameters for a three-dimensional MORSE-SGC Monte Carlo model of the cask geometry.

  4. Behavior of an heterogeneous annular FBR core during an unprotected loss of flow accident: Analysis of the primary phase with SAS-SFR

    SciTech Connect (OSTI)

    Massara, S.; Schmitt, D.; Bretault, A.; Lemasson, D.; Darmet, G.; Verwaerde, D. [EDF R and D, 1, Avenue du General de Gaulle, 92141 Clamart (France); Struwe, D.; Pfrang, W.; Ponomarev, A. [Karlsruher Institut fuer Technologie KIT, Institut fuer Neutronenphysik und Reaktortechnik INR, Hermann-von-Helmholtz-Platz 1, Gebaude 521, 76344 Eggenstein-Leopoldshafen (Germany)

    2012-07-01T23:59:59.000Z

    In the framework of a substantial improvement on FBR core safety connected to the development of a new Gen IV reactor type, heterogeneous core with innovative features are being carefully analyzed in France since 2009. At EDF R and D, the main goal is to understand whether a strong reduction of the Na-void worth - possibly attempting a negative value - allows a significant improvement of the core behavior during an unprotected loss of flow accident. Also, the physical behavior of such a core is of interest, before and beyond the (possible) onset of Na boiling. Hence, a cutting-edge heterogeneous design, featuring an annular shape, a Na-plena with a B{sub 4}C plate and a stepwise modulation of fissile core heights, was developed at EDF by means of the SDDS methodology, with a total Na-void worth of -1 $. The behavior of such a core during the primary phase of a severe accident, initiated by an unprotected loss of flow, is analyzed by means of the SAS-SFR code. This study is carried-out at KIT and EDF, in the framework of a scientific collaboration on innovative FBR severe accident analyses. The results show that the reduction of the Na-void worth is very effective, but is not sufficient alone to avoid Na-boiling and, hence, to prevent the core from entering into the primary phase of a severe accident. Nevertheless, the grace time up to boiling onset is greatly enhanced in comparison to a more traditional homogeneous core design, and only an extremely low fraction of the fuel (<0.1%) enters into melting at the end of this phase. A sensitivity analysis shows that, due to the inherent neutronic characteristics of such a core, the gagging scheme plays a major role on the core behavior: indeed, an improved 4-zones gagging scheme, associated with an enhanced control rod drive line expansion feed-back effect, finally prevents the core from entering into sodium boiling. This major conclusion highlights both the progress already accomplished and the need for more detailed future analyses, particularly concerning: the neutronic burn-up scheme, the modeling of the diagrid effect and the control rod drive line expansion feed-backs, as well as the primary/secondary systems thermal-hydraulics behavior. (authors)

  5. CITBA & SAS SAS Enterprise Miner Training-Oct 18 & 19

    E-Print Network [OSTI]

    de Lijser, Peter

    , easy-to-use set of integrated capabilities for creating and sharing insights that can be used to drive for Technometrics, American Statistician, and Journal of the American Statistical Society. He has also served exhaust emission data. André de Waal, PhD, Instructor SAS Enterprise Miner: André was born in South Africa

  6. Sunvie SAS | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit with formSoutheastern ILSunseeker Energy Holding AG Jump to:SunstroomSunvie SAS

  7. Application for SAS Certificate Advanced Statistics

    E-Print Network [OSTI]

    Dahl, David B.

    Application for SAS Certificate Advanced Statistics ___________________________________________________________________________________ Student Signature _________________________________________ Date I am a Statistics Major at Brigham Young of Statistics to access my academic information. Brigham Young University Department of Statistics offers

  8. Tank vapor sampling and analysis data package for tank 241-C-106 waste retrieval sluicing system process test phase III

    SciTech Connect (OSTI)

    LOCKREM, L.L.

    1999-08-13T23:59:59.000Z

    This data package presents sampling data and analytical results from the March 28, 1999, vapor sampling of Hanford Site single-shell tank 241-C-106 during active sluicing. Samples were obtained from the 296-C-006 ventilation system stack and ambient air at several locations. Characterization Project Operations (CPO) was responsible for the collection of all SUMMATM canister samples. The Special Analytical Support (SAS) vapor team was responsible for the collection of all triple sorbent trap (TST), sorbent tube train (STT), polyurethane foam (PUF), and particulate filter samples collected at the 296-C-006 stack. The SAS vapor team used the non-electrical vapor sampling (NEVS) system to collect samples of the air, gases, and vapors from the 296-C-006 stack. The SAS vapor team collected and analyzed these samples for Lockheed Martin Hanford Corporation (LMHC) and Tank Waste Remediation System (TWRS) in accordance with the sampling and analytical requirements specified in the Waste Retrieval Sluicing System Vapor Sampling and Analysis Plan (SAP) for Evaluation of Organic Emissions, Process Test Phase III, HNF-4212, Rev. 0-A, (LMHC, 1999). All samples were stored in a secured Radioactive Materials Area (RMA) until the samples were radiologically released and received by SAS for analysis. The Waste Sampling and Characterization Facility (WSCF) performed the radiological analyses. The samples were received on April 5, 1999.

  9. Hanau Energies SAS | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdfGetec AG| Open EnergyGuntersvilleHallandaleHamlinHanau Energies SAS Jump to:

  10. Nass Wind SAS | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluatingGroup |JilinLu anMicrogreenMoonNASA/AmesNSNanotectureNarayanpurNass Wind SAS

  11. The effect of SAS shoes on standing fatigue in light fabrication workers

    E-Print Network [OSTI]

    Bradley, Lee Norman

    1996-01-01T23:59:59.000Z

    the day. Next, the SAS shoes were compared to the participant's normal working shoes. Results showed significant differences (p wearing SAS shoes and became more...

  12. Systems Analysis Workshop Purpose

    Broader source: Energy.gov [DOE]

    Presentation on SAW purpose to the DOE Systems Analysis Workshop held in Washington, D.C. July 28-29, 2004 to discuss and define role of systems analysis in DOE Hydrogen Program.

  13. Extension of the supercritical carbon dioxide brayton cycle to low reactor power operation: investigations using the coupled anl plant dynamics code-SAS4A/SASSYS-1 liquid metal reactor code system.

    SciTech Connect (OSTI)

    Moisseytsev, A.; Sienicki, J. J. (Nuclear Engineering Division)

    2012-05-10T23:59:59.000Z

    Significant progress has been made on the development of a control strategy for the supercritical carbon dioxide (S-CO{sub 2}) Brayton cycle enabling removal of power from an autonomous load following Sodium-Cooled Fast Reactor (SFR) down to decay heat levels such that the S-CO{sub 2} cycle can be used to cool the reactor until decay heat can be removed by the normal shutdown heat removal system or a passive decay heat removal system such as Direct Reactor Auxiliary Cooling System (DRACS) loops with DRACS in-vessel heat exchangers. This capability of the new control strategy eliminates the need for use of a separate shutdown heat removal system which might also use supercritical CO{sub 2}. It has been found that this capability can be achieved by introducing a new control mechanism involving shaft speed control for the common shaft joining the turbine and two compressors following reduction of the load demand from the electrical grid to zero. Following disconnection of the generator from the electrical grid, heat is removed from the intermediate sodium circuit through the sodium-to-CO{sub 2} heat exchanger, the turbine solely drives the two compressors, and heat is rejected from the cycle through the CO{sub 2}-to-water cooler. To investigate the effectiveness of shaft speed control, calculations are carried out using the coupled Plant Dynamics Code-SAS4A/SASSYS-1 code for a linear load reduction transient for a 1000 MWt metallic-fueled SFR with autonomous load following. No deliberate motion of control rods or adjustment of sodium pump speeds is assumed to take place. It is assumed that the S-CO{sub 2} turbomachinery shaft speed linearly decreases from 100 to 20% nominal following reduction of grid load to zero. The reactor power is calculated to autonomously decrease down to 3% nominal providing a lengthy window in time for the switchover to the normal shutdown heat removal system or for a passive decay heat removal system to become effective. However, the calculations reveal that the compressor conditions are calculated to approach surge such that the need for a surge control system for each compressor is identified. Thus, it is demonstrated that the S-CO{sub 2} cycle can operate in the initial decay heat removal mode even with autonomous reactor control. Because external power is not needed to drive the compressors, the results show that the S-CO{sub 2} cycle can be used for initial decay heat removal for a lengthy interval in time in the absence of any off-site electrical power. The turbine provides sufficient power to drive the compressors. Combined with autonomous reactor control, this represents a significant safety advantage of the S-CO{sub 2} cycle by maintaining removal of the reactor power until the core decay heat falls to levels well below those for which the passive decay heat removal system is designed. The new control strategy is an alternative to a split-shaft layout involving separate power and compressor turbines which had previously been identified as a promising approach enabling heat removal from a SFR at low power levels. The current results indicate that the split-shaft configuration does not provide any significant benefits for the S-CO{sub 2} cycle over the current single-shaft layout with shaft speed control. It has been demonstrated that when connected to the grid the single-shaft cycle can effectively follow the load over the entire range. No compressor speed variation is needed while power is delivered to the grid. When the system is disconnected from the grid, the shaft speed can be changed as effectively as it would be with the split-shaft arrangement. In the split-shaft configuration, zero generator power means disconnection of the power turbine, such that the resulting system will be almost identical to the single-shaft arrangement. Without this advantage of the split-shaft configuration, the economic benefits of the single-shaft arrangement, provided by just one turbine and lower losses at the design point, are more important to the overall cycle performance. Therefore, the single-shaft

  14. Between automation and exploration: SAS graphing techniques for visualization of survey data

    E-Print Network [OSTI]

    Yu, Alex

    Between automation and exploration: SAS graphing techniques for visualization of survey data Chong of survey data. There is always a tension between automation and exploration. Automation is a common to automate the graphing processes via SAS/Macros and SAS/Graph. However, hidden patterns of the data may

  15. Coal systems analysis

    SciTech Connect (OSTI)

    Warwick, P.D. (ed.)

    2005-07-01T23:59:59.000Z

    This collection of papers provides an introduction to the concept of coal systems analysis and contains examples of how coal systems analysis can be used to understand, characterize, and evaluate coal and coal gas resources. Chapter are: Coal systems analysis: A new approach to the understanding of coal formation, coal quality and environmental considerations, and coal as a source rock for hydrocarbons by Peter D. Warwick. Appalachian coal assessment: Defining the coal systems of the Appalachian Basin by Robert C. Milici. Subtle structural influences on coal thickness and distribution: Examples from the Lower Broas-Stockton coal (Middle Pennsylvanian), Eastern Kentucky Coal Field, USA by Stephen F. Greb, Cortland F. Eble, and J.C. Hower. Palynology in coal systems analysis The key to floras, climate, and stratigraphy of coal-forming environments by Douglas J. Nichols. A comparison of late Paleocene and late Eocene lignite depositional systems using palynology, upper Wilcox and upper Jackson Groups, east-central Texas by Jennifer M.K. O'Keefe, Recep H. Sancay, Anne L. Raymond, and Thomas E. Yancey. New insights on the hydrocarbon system of the Fruitland Formation coal beds, northern San Juan Basin, Colorado and New Mexico, USA by W.C. Riese, William L. Pelzmann, and Glen T. Snyder.

  16. TERRORISM AND WAR (SAS 7) UC Davis; Spring, 2013

    E-Print Network [OSTI]

    Seybold, Steven J.

    1 TERRORISM AND WAR (SAS 7) UC Davis; Spring, 2013 INSTRUCTORS OFFICE HOUR (VIRTUAL) Prof. James R to varying degrees in major conflicts around the world, issues of terrorism and war are heavily debated deeply about terrorism and war and question your assumptions. You will be asked to understand

  17. Design, Simulation, and Analysis of Substation Automation Networks

    E-Print Network [OSTI]

    Kembanur Natarajan, Elangovan

    2012-07-16T23:59:59.000Z

    on the Substation Automation Systems (SAS). Substations are nodes in the smart grid infrastructure that help the in transportation of power by connecting the transmission and distribution lines. The SAS applications are con figured to operate with minimal human...

  18. Sandia National Laboratories: Systems Analysis

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

    Photovoltaic, Photovoltaic Systems Evaluation Laboratory (PSEL), Renewable Energy, Solar, Solar Newsletter, Systems Analysis The PV Performance Modeling Collaborative (PVPMC)...

  19. Sandia National Laboratories: Systems Analysis

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

    Grid Integration, Infrastructure Security, Microgrid, News, News & Events, Renewable Energy, Systems Analysis, Systems Engineering, Transmission Grid Integration A lot that...

  20. SAS Honors Seminar 256: Extraterrestrial Life

    E-Print Network [OSTI]

    Baker, Andrew J.

    /29) Bennett & Shostak 3.3, 3.5, 4.6 ­ background on solar system Stevenson (2001) ­ background on Jupiter solar system bodies... After reading the guidelines for naming minor planets, explain your views) bird's eye view of the Milky Way #12; Star formation in the Carina Nebula sulfur hydrogen oxygen D

  1. SAS Honors Seminar 259: Extraterrestrial Life

    E-Print Network [OSTI]

    Baker, Andrew J.

    : a white dwarf in a binary system is pushed "over the edge" (Chandrasekhar limit = 1.4 solar masses) Institute of Marine and Coastal Sciences (Cook Campus) Meet by 4:35pm in main lobby, or (if late) look for next Monday (9/29) Bennett & Shostak 3.3, 3.5, 4.6 ­ background on solar system Stevenson (2001

  2. Using SAS to generate DDI-Codebook XML from Information Managed in Excel Spreadsheets

    E-Print Network [OSTI]

    Wright, Philip A.

    2013-04-02T23:59:59.000Z

    \\fem_variable_formats.txt' delimiter = '09'x MISSOVER DSD lrecl = 32767 firstobs = 2 ; input VARIABLE $ FORMAT $ ; run ; There is more than one way to import information from Excel into SAS External File Interface Import Wizard Proc Import Excel Library... into SAS Proc Import There is more than one way to import information from Excel into SAS proc import datafile = "C:\\worksheets\\female_metadata.xls" out = user.female_metadata dbms = excel ; range = "'FINAL SECTION J'" ; getnames = yes ; mixed...

  3. Sandia Energy - Transportation Energy Systems Analysis

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

    Transportation Energy Systems Analysis Home Transportation Energy Predictive Simulation of Engines Transportation Energy Systems Analysis Transportation Energy Systems AnalysisTara...

  4. Silicium de Provence SAS Silpro | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries Pvt LtdShawangunk, New York:SiG Solar GmbH JumpSilicium de Provence SAS Silpro Jump

  5. Enel Erelis formerly Erelis SAS | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOEHazel Crest,Energy InformationEmily,EmpowerErelis formerly Erelis SAS Jump

  6. SUGI 15, April, 1990 SAS/GRAPH SOFTWARE MEETS THE LOGO TURTLE

    E-Print Network [OSTI]

    Friendly, Michael

    SUGI 15, April, 1990 SAS/GRAPH® SOFTWARE MEETS THE LOGO TURTLE Michael Friendly, York University Abstract What is Logo? This talk describes a set of SAS macros which provide the ability to Logo of the Logo language, rather setting. Part of its appeal is an extremely simple yet flexible than absolute X

  7. Analysis Models and Tools: Systems Analysis of Hydrogen and Fuel...

    Office of Environmental Management (EM)

    and Fuel Cells Analysis Models and Tools: Systems Analysis of Hydrogen and Fuel Cells The Fuel Cell Technologies Office's systems analysis program uses a consistent set of models...

  8. Process Cooling Pumping Systems Analysis

    E-Print Network [OSTI]

    Sherman, C.

    2008-01-01T23:59:59.000Z

    An analysis of the mill water pumping systems at a North American manufacturing facility was conducted late las year and the following issues were observed: 1. Overpumping – Both systems were overpumped to a significant degree against...

  9. Miniaturized flow injection analysis system

    DOE Patents [OSTI]

    Folta, James A. (Livermore, CA)

    1997-01-01T23:59:59.000Z

    A chemical analysis technique known as flow injection analysis, wherein small quantities of chemical reagents and sample are intermixed and reacted within a capillary flow system and the reaction products are detected optically, electrochemically, or by other means. A highly miniaturized version of a flow injection analysis system has been fabricated utilizing microfabrication techniques common to the microelectronics industry. The microflow system uses flow capillaries formed by etching microchannels in a silicon or glass wafer followed by bonding to another wafer, commercially available microvalves bonded directly to the microflow channels, and an optical absorption detector cell formed near the capillary outlet, with light being both delivered and collected with fiber optics. The microflow system is designed mainly for analysis of liquids and currently measures 38.times.25.times.3 mm, but can be designed for gas analysis and be substantially smaller in construction.

  10. SUBSURFACE VISUAL ALARM SYSTEM ANALYSIS

    SciTech Connect (OSTI)

    D.W. Markman

    2001-08-06T23:59:59.000Z

    The ''Subsurface Fire Hazard Analysis'' (CRWMS M&O 1998, page 61), and the document, ''Title III Evaluation Report for the Surface and Subsurface Communication System'', (CRWMS M&O 1999a, pages 21 and 23), both indicate the installed communication system is adequate to support Exploratory Studies Facility (ESF) activities with the exception of the mine phone system for emergency notification purposes. They recommend the installation of a visual alarm system to supplement the page/party phone system The purpose of this analysis is to identify data communication highway design approaches, and provide justification for the selected or recommended alternatives for the data communication of the subsurface visual alarm system. This analysis is being prepared to document a basis for the design selection of the data communication method. This analysis will briefly describe existing data or voice communication or monitoring systems within the ESF, and look at how these may be revised or adapted to support the needed data highway of the subsurface visual alarm. system. The existing PLC communication system installed in subsurface is providing data communication for alcove No.5 ventilation fans, south portal ventilation fans, bulkhead doors and generator monitoring system. It is given that the data communication of the subsurface visual alarm system will be a digital based system. It is also given that it is most feasible to take advantage of existing systems and equipment and not consider an entirely new data communication system design and installation. The scope and primary objectives of this analysis are to: (1) Briefly review and describe existing available data communication highways or systems within the ESF. (2) Examine technical characteristics of an existing system to disqualify a design alternative is paramount in minimizing the number of and depth of a system review. (3) Apply general engineering design practices or criteria such as relative cost, and degree of difficulty and complexity in determining requirements in adapting existing data communication highways to support the subsurface visual alarm system. These requirements would include such things as added or new communication cables, added Programmable Logic Controller (PLC), Inputs and Outputs (I/O), and communication hardware components, and human machine interfaces and their software operating system. (4) Select the best data communication highway system based on this review of adapting or integrating with existing data communication systems.

  11. NETL: SOFC Systems Analysis

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Saleshttp://www.fnal.gov/directorate/nalcal/nalcal02_07_05_files/nalcal.gif Directorate1, Issue 23 NETL ScientistFeed SystemsSystems

  12. The ALICE analysis train system

    E-Print Network [OSTI]

    Markus Zimmermann; for the ALICE collaboration

    2015-02-23T23:59:59.000Z

    In the ALICE experiment hundreds of users are analyzing big datasets on a Grid system. High throughput and short turn-around times are achieved by a centralized system called the LEGO trains. This system combines analysis from different users in so-called analysis trains which are then executed within the same Grid jobs thereby reducing the number of times the data needs to be read from the storage systems. The centralized trains improve the performance, the usability for users and the bookkeeping in comparison to single user analysis. The train system builds upon the already existing ALICE tools, i.e. the analysis framework as well as the Grid submission and monitoring infrastructure. The entry point to the train system is a web interface which is used to configure the analysis and the desired datasets as well as to test and submit the train. Several measures have been implemented to reduce the time a train needs to finish and to increase the CPU efficiency.

  13. Space elevator systems level analysis

    SciTech Connect (OSTI)

    Laubscher, B. E. (Bryan E.)

    2004-01-01T23:59:59.000Z

    The Space Elevator (SE) represents a major paradigm shift in space access. It involves new, untried technologies in most of its subsystems. Thus the successful construction of the SE requires a significant amount of development, This in turn implies a high level of risk for the SE. This paper will present a systems level analysis of the SE by subdividing its components into their subsystems to determine their level of technological maturity. such a high-risk endeavor is to follow a disciplined approach to the challenges. A systems level analysis informs this process and is the guide to where resources should be applied in the development processes. It is an efficient path that, if followed, minimizes the overall risk of the system's development. systems level analysis is that the overall system is divided naturally into its subsystems, and those subsystems are further subdivided as appropriate for the analysis. By dealing with the complex system in layers, the parameter space of decisions is kept manageable. Moreover, A rational way to manage One key aspect of a resources are not expended capriciously; rather, resources are put toward the biggest challenges and most promising solutions. This overall graded approach is a proven road to success. The analysis includes topics such as nanotube technology, deployment scenario, power beaming technology, ground-based hardware and operations, ribbon maintenance and repair and climber technology.

  14. Electron Spectrometer: Scanning Multiprobe Surface Analysis System...

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

    Scanning Multiprobe Surface Analysis System - Versaprobe Electron Spectrometer: Scanning Multiprobe Surface Analysis System - Versaprobe The SMSAS is a multi-technique surface...

  15. Integrated Vehicle Thermal Management Systems (VTMS) Analysis...

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

    Systems (VTMS) AnalysisModeling Integrated Vehicle Thermal Management Systems (VTMS) AnalysisModeling 2009 DOE Hydrogen Program and Vehicle Technologies Program Annual Merit...

  16. Numerical bifurcation analysis of piecewise smooth systems

    E-Print Network [OSTI]

    ( ) ( ) ( ) ( ), , outoutinin inin xffxff xhhxgg xxxx == == #12;Numerical bifurcation analysis of piecewise smooth systems INRIA

  17. System for analysis of explosives

    DOE Patents [OSTI]

    Haas, Jeffrey S. (San Ramon, CA)

    2010-06-29T23:59:59.000Z

    A system for analysis of explosives. Samples are spotted on a thin layer chromatography plate. Multi-component explosives standards are spotted on the thin layer chromatography plate. The thin layer chromatography plate is dipped in a solvent mixture and chromatography is allowed to proceed. The thin layer chromatography plate is dipped in reagent 1. The thin layer chromatography plate is heated. The thin layer chromatography plate is dipped in reagent 2.

  18. Systems Analysis | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels Data CenterEnergyGlossaryProgramRussiaSpaceNewsSustainableSystems Analysis

  19. Tank waste remediation system (TWRS) mission analysis

    SciTech Connect (OSTI)

    Rieck, R.H.

    1996-10-03T23:59:59.000Z

    The Tank Waste Remediation System Mission Analysis provides program level requirements and identifies system boundaries and interfaces. Measures of success appropriate to program level accomplishments are also identified.

  20. Systems Analysis Workshop List of Attendees

    Broader source: Energy.gov [DOE]

    List of Attendees from DOE Systems Analysis Workshop held in Washington, D.C. July 28-29, 2004 to discuss and define role of systems analysis in DOE Hydrogen Program.

  1. Cost Analysis of Hydrogen Storage Systems

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

    Cost Analysis of Hydrogen Cost Analysis of Hydrogen Storage Systems Storage Systems TIAX LLC 15 Acorn Park Cambridge, MA 02140-2390 Tel. 617- 498-5000 Fax 617-498-7200...

  2. DOE Hydrogen Program Systems Analysis Workshop

    E-Print Network [OSTI]

    ) · Define analysis scenarios NREL SYSTEMS INTEGRATION · Accountable for analysis activities · Provide inputs · Coordinate and provide ideas/recommendations to SI on cross-cutting analysis · Manage analysis tasks internal to DOE (Labs/FFRDCs only) · Perform analysis of technoeconomic topics for TA and SI · Perform subprogram

  3. SMACS. Probabilistic Seismic Analysis System

    SciTech Connect (OSTI)

    Johnson, J.J.; Maslenikov, O.R.; Tiong, L.W.; Mraz, M.J. [EQE Incorporated, San Ramon, CA (United States); Bumpus, S.; Gerhard, M.A. [Lawrence Livermore National Lab., CA (United States)

    1992-01-14T23:59:59.000Z

    The SMACS (Seismic Methodology Analysis Chain with Statistics) system of computer programs is one of the major computational tools of the U.S. NRC Seismic Safety Margins Research Program (SSMRP). SMACS is comprised of the core program SMAX, which performs the SSI response analyses, five preprocessing programs, and two postprocessors. The preprocessing programs include: GLAY and CLAN, which generate the nominal impedance matrices and wave scattering vectors for surface-founded structures; INSSIN, which projects the dynamic properties of structures to the foundation in the form of modal participation factors and mass matrices; SAPPAC, which projects the dynamic and pseudostatic properties of multiply-supported piping systems to the support locations, and LNGEN, which can be used to generate the multiplication factors to be applied to the nominal soil, structural, and subsystem properties for each of the response calculations in accounting for random variations of these properties. The postprocessors are: PRESTO, which performs statistical operations on the raw data from the response vectors that SMAX produces to calculate best fit lognormal distributions for each response location, and CHANGO, which manipulates the data produced by PRESTO to produce other results of interest to the user. Also included is the computer program SAP4 (a modified version of the University of California, Berkeley SAPIV program), a general linear structural analysis program used for eigenvalue extractions and pseudostatic mode calculations of the models of major structures and subsystems. SAP4 is used to prepare input to the INSSIN and SAPPAC preprocessing programs. The GLAY and CLAN programs were originally developed by J.E. Luco (UCSD) and H.L. Wong (USC).

  4. Bifurcation Analysis of Various Power System Models

    E-Print Network [OSTI]

    Cañizares, Claudio A.

    modeling, voltage collapse. I. Introduction Voltage stability problems in power systems may occurBifurcation Analysis of Various Power System Models William D. Rosehart Claudio A. Ca This paper presents the bifurcation analysis of a detailed power system model composed of an aggregated

  5. System architecture analysis and selection under uncertainty

    E-Print Network [OSTI]

    Smaling, Rudolf M

    2005-01-01T23:59:59.000Z

    A system architecture analysis and selection methodology is presented that builds on the Multidisciplinary Analysis and Optimization framework. It addresses a need and opportunity to extend the MAO techniques to include a ...

  6. Reachability Analysis of Stochastic Hybrid Systems: A Biodiesel Production System

    E-Print Network [OSTI]

    Koutsoukos, Xenofon D.

    Reachability Analysis of Stochastic Hybrid Systems: A Biodiesel Production System Derek Riley problem because it provides a formal framework to analyze complex systems. Biodiesel production is a realistic biochemical process that can be modeled and analyzed using SHS methods. Analysis of a biodiesel

  7. IT Specialist (Systems Analysis/Applications Software)

    Broader source: Energy.gov [DOE]

    The incumbent in this position will serve as a Senior IT Specialist (Systems Analysis/Applications Support) and Technical Lead in the Enterprise Applications Support organization of Software...

  8. Energy Systems Analysis | Argonne National Laboratory

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

    Energy Systems Analysis All stages of energy production have inputs and outputs. Argonne researchers analyze the total production picture and develop tools for members of the...

  9. Systems analysis of multiple regulator perturbations allows discoveryo...

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

    Systems analysis of multiple regulator perturbations allows discoveryof virulence factors in Salmonella. Systems analysis of multiple regulator perturbations allows discoveryof...

  10. ADVANCED POWER SYSTEMS ANALYSIS TOOLS

    SciTech Connect (OSTI)

    Robert R. Jensen; Steven A. Benson; Jason D. Laumb

    2001-08-31T23:59:59.000Z

    The use of Energy and Environmental Research Center (EERC) modeling tools and improved analytical methods has provided key information in optimizing advanced power system design and operating conditions for efficiency, producing minimal air pollutant emissions and utilizing a wide range of fossil fuel properties. This project was divided into four tasks: the demonstration of the ash transformation model, upgrading spreadsheet tools, enhancements to analytical capabilities using the scanning electron microscopy (SEM), and improvements to the slag viscosity model. The ash transformation model, Atran, was used to predict the size and composition of ash particles, which has a major impact on the fate of the combustion system. To optimize Atran key factors such as mineral fragmentation and coalescence, the heterogeneous and homogeneous interaction of the organically associated elements must be considered as they are applied to the operating conditions. The resulting model's ash composition compares favorably to measured results. Enhancements to existing EERC spreadsheet application included upgrading interactive spreadsheets to calculate the thermodynamic properties for fuels, reactants, products, and steam with Newton Raphson algorithms to perform calculations on mass, energy, and elemental balances, isentropic expansion of steam, and gasifier equilibrium conditions. Derivative calculations can be performed to estimate fuel heating values, adiabatic flame temperatures, emission factors, comparative fuel costs, and per-unit carbon taxes from fuel analyses. Using state-of-the-art computer-controlled scanning electron microscopes and associated microanalysis systems, a method to determine viscosity using the incorporation of grey-scale binning acquired by the SEM image was developed. The image analysis capabilities of a backscattered electron image can be subdivided into various grey-scale ranges that can be analyzed separately. Since the grey scale's intensity is dependent on the chemistry of the particle, it is possible to map chemically similar areas which can also be related to the viscosity of that compound at temperature. A second method was also developed to determine the elements associated with the organic matrix of the coals, which is currently determined by chemical fractionation. Mineral compositions and mineral densities can be determined for both included and excluded minerals, as well as the fraction of the ash that will be represented by that mineral on a frame-by-frame basis. The slag viscosity model was improved to provide improved predictions of slag viscosity and temperature of critical viscosity for representative Powder River Basin subbituminous and lignite coals.

  11. Power Systems Analysis ELEN4511 Spring 2013

    E-Print Network [OSTI]

    Lavaei, Javad

    Power Systems Analysis ELEN4511 Spring 2013 Project Paper: Communication Systems and Standards along the power grid. The grid comprised solely of electro- mechanical systems that could of communication systems on the power grid enables devices to communicate more efficiently, and also allows

  12. Mandatory Photovoltaic System Cost Analysis

    Broader source: Energy.gov [DOE]

    The Arizona Corporation Commission requires electric utilities to conduct a cost/benefit analysis to compare the cost of line extension with the cost of installing a stand-alone photovoltaic (PV)...

  13. Modeling and Analysis ofModeling and Analysis of Hybrid Control SystemsHybrid Control Systems

    E-Print Network [OSTI]

    Johansson, Karl Henrik

    control systems, MOVEP, Bordeaux, 2006 Automatic gear boxAutomatic gear box #12;Karl H. Johansson, HybridModeling and Analysis ofModeling and Analysis of Hybrid Control SystemsHybrid Control Systems Karl.kth.se/~kallej MOVEP 2006, Bordeaux, France Karl H. Johansson, Hybrid control systems, MOVEP, Bordeaux

  14. Sandia National Laboratories: Systems Analysis

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

    Increasing the Scaled Wind Farm Technology Facility's Power Production On April 7, 2014, in Energy, Facilities, News, News & Events, Partnership, Renewable Energy, SWIFT, Systems...

  15. Satellite System Safety Analysis Using STPA

    E-Print Network [OSTI]

    Dunn, Nicholas Connor

    2013-01-01T23:59:59.000Z

    Traditional hazard analysis techniques based on failure models of accident causality, such as the probabilistic risk assessment (PRA) method currently used at NASA, are inadequate for analyzing safety at the system level. ...

  16. Energy, Environmental & Economic Systems Analysis

    E-Print Network [OSTI]

    for analyzing integrated energy and electricity systems. Worldwide Use of ENPEP ENPEP is used around the world and government analysts are using the model for energy planning. Further, the World Bank and other lending and consumption activities independently, each optimizing individual objectives. ENPEP-BALANCE finds its solution

  17. Analysis of Fuel Cell Systems Rangan Banerjee

    E-Print Network [OSTI]

    Banerjee, Rangan

    Analysis of Fuel Cell Systems Rangan Banerjee Energy Systems Engineering IIT Bombay Lecture in CEP Course on `Fuel Cell' at IIT 14th November 2007 #12;Overview of Talk Energy Crisis ­ Motivation for fuel biological Hydrogen Gasification Fermentation Cracking + Shift Reaction Fuel Cell #12;ENERGY FLOW DIAGRAM

  18. Energy Engineering & Systems Analysis Success Stories

    E-Print Network [OSTI]

    Kemner, Ken

    Energy Engineering & Systems Analysis Success Stories Helping Make the U.S. Power Grid Smarter-way communication technologies into the power grid, the nation will have a more robust and efficient system it delivered. The Challenge President Barack Obama has called for one million plug-in hybrid electric vehicles

  19. Energy, Environmental, and Economic Systems Analysis

    E-Print Network [OSTI]

    and deregulated, shifting control from a single decision maker (i.e., a single, government-owned electric utility determining electricity consumption (customer agents), unit commitment (generation companies), bilateralEnergy, Environmental, and Economic Systems Analysis Electricity Market Complex Adaptive System

  20. Systems Analysis | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels Data CenterEnergyGlossaryProgramRussiaSpaceNewsSustainableSystems

  1. VISION 21 SYSTEMS ANALYSIS METHODOLOGIES

    SciTech Connect (OSTI)

    G.S. Samuelsen; A. Rao; F. Robson; B. Washom

    2003-08-11T23:59:59.000Z

    Under the sponsorship of the U.S. Department of Energy/National Energy Technology Laboratory, a multi-disciplinary team led by the Advanced Power and Energy Program of the University of California at Irvine is defining the system engineering issues associated with the integration of key components and subsystems into power plant systems that meet performance and emission goals of the Vision 21 program. The study efforts have narrowed down the myriad of fuel processing, power generation, and emission control technologies to selected scenarios that identify those combinations having the potential to achieve the Vision 21 program goals of high efficiency and minimized environmental impact while using fossil fuels. The technology levels considered are based on projected technical and manufacturing advances being made in industry and on advances identified in current and future government supported research. Included in these advanced systems are solid oxide fuel cells and advanced cycle gas turbines. The results of this investigation will serve as a guide for the U. S. Department of Energy in identifying the research areas and technologies that warrant further support.

  2. PLT data acquisition and analysis system

    SciTech Connect (OSTI)

    Murphy, J.A.; Gibney, T.R.

    1986-08-01T23:59:59.000Z

    The data acquisition and analysis system for PLT (Princeton Large Torus) is being moved from a DEC-10 to a VAX 11/785. Most of the major diagnostics are currently running on the VAX, with approximately 1 Mbyte of data being taken each shot. The system uses the MIT model data system (MDS) for acquisition and archival of data and the PPPL event-controlled scheduler (ECS) for scheduling. The analysis programs use the MDS data retrieval subroutines which deliver correctly calibrated results to the user program.

  3. Waste Feed Delivery Transfer System Analysis

    SciTech Connect (OSTI)

    JULYK, L.J.

    2000-05-05T23:59:59.000Z

    This document provides a documented basis for the required design pressure rating and pump pressure capacity of the Hanford Site waste-transfer system in support of the waste feed delivery to the privatization contractor for vitrification. The scope of the analysis includes the 200 East Area double-shell tank waste transfer pipeline system and the associated transfer system pumps for a11 Phase 1B and Phase 2 waste transfers from AN, AP, AW, AY, and A2 Tank Farms.

  4. Hydrogen Storage Systems Analysis Meeting: Summary Report, March...

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

    Meeting: Summary Report, March 29, 2005 Hydrogen Storage Systems Analysis Meeting: Summary Report, March 29, 2005 This report highlights DOE's systems analysis work related to...

  5. Hydrgoen Storage Systems Analysis Working Group Meeting Summary...

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

    Hydrgoen Storage Systems Analysis Working Group Meeting Summary Report Hydrgoen Storage Systems Analysis Working Group Meeting Summary Report Summary report from the May 17, 2007...

  6. Earned Value Management System (EVMS) and Project Analysis Standard...

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

    Earned Value Management System (EVMS) and Project Analysis Standard Operating Procedure (EPASOP)- March 2014 Earned Value Management System (EVMS) and Project Analysis Standard...

  7. Top Hat Pressure System Hyperbaric Test Analysis | Department...

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

    Top Hat Pressure System Hyperbaric Test Analysis Top Hat Pressure System Hyperbaric Test Analysis This file contains data from pressure measurements inside Top Hat 4....

  8. New airport liquid analysis system undergoes testing at Albuquerque...

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

    New airport liquid analysis system New airport liquid analysis system undergoes testing at Albuquerque International Sunport A new tool that distinguishes potential-threat liquids...

  9. Security Analysis and Project Management Systems | ornl.gov

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

    Security Analysis and Project Management Systems SHARE Security Analysis and Project Management Systems ORNL brings together the subject matter experts with programmers to design,...

  10. RAMS (Risk Analysis - Modular System) methodology

    SciTech Connect (OSTI)

    Stenner, R.D.; Strenge, D.L.; Buck, J.W. [and others

    1996-10-01T23:59:59.000Z

    The Risk Analysis - Modular System (RAMS) was developed to serve as a broad scope risk analysis tool for the Risk Assessment of the Hanford Mission (RAHM) studies. The RAHM element provides risk analysis support for Hanford Strategic Analysis and Mission Planning activities. The RAHM also provides risk analysis support for the Hanford 10-Year Plan development activities. The RAMS tool draws from a collection of specifically designed databases and modular risk analysis methodologies and models. RAMS is a flexible modular system that can be focused on targeted risk analysis needs. It is specifically designed to address risks associated with overall strategy, technical alternative, and `what if` questions regarding the Hanford cleanup mission. RAMS is set up to address both near-term and long-term risk issues. Consistency is very important for any comparative risk analysis, and RAMS is designed to efficiently and consistently compare risks and produce risk reduction estimates. There is a wide range of output information that can be generated by RAMS. These outputs can be detailed by individual contaminants, waste forms, transport pathways, exposure scenarios, individuals, populations, etc. However, they can also be in rolled-up form to support high-level strategy decisions.

  11. Life-Cycle Analysis Results of Geothermal Systems in Comparison...

    Office of Environmental Management (EM)

    Life-Cycle Analysis Results of Geothermal Systems in Comparison to Other Power Systems Life-Cycle Analysis Results of Geothermal Systems in Comparison to Other Power Systems A...

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.3.

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.3..

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3. Revenue

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.8.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.8.9.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -2.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -2.3.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA. Net

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.A.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.A.B.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. Net

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. Net

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. NetB.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. NetB.A.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6. Net

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6. Net7.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9. Net

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.1.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.1.2.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5. Net

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5. Net6.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8. Net

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.0.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.0.1.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful4.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful4..

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.5.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.5.6.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer Capacity

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9. Total

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.2.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.2.3.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B. Coal:

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.E.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.E.F.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B. Petroleum

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B. PetroleumC.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E. Petroleum

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.D.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.D.E.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:B.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:B.C.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE. Natural

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D. Wood

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.A.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.A.B.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill Gas:

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill Gas:E.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.B.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.B.C.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. Biogenic

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. BiogenicF.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. BiogenicF.D.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other Waste

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.1.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.1.2.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1. Stocks

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1. Stocks2

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..3.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..3.4.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost, and

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost, and7

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,9.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,9.0.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.5.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.5.6.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost of

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost0.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost0.1.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.5.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.5.1.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity and

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity and4.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.2.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.2.3.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5. Demand-Side

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy8.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy8.9.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1. Sulfur

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1. Sulfur2.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.4.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.4.5. Unit

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997Million

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor U.S.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor U.S.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable Coal Reserves

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable Coal

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverableRecoverable

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of Employees at

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of Employees

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3. Coal

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3. Coal4.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6. U.S.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.8.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.8.9.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average Sales

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average Sales1.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.4.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.4.Coal

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.Coal Production

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.Coal

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.CoalCoal

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.CoalCoalMajor

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average

  4. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3. Revenue

  5. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.

  6. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.

  7. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.A.

  8. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.A.B.

  9. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.A.B.A.

  10. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  11. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  12. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  13. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  14. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  15. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  16. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835 2.812Average

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average Price

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average Steam

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835AverageU.S.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9,

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. Coal

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. CoalAverage

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. CoalAverageCoal

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S. Coke

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2. Coal

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2. CoalU.S.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2.Quantity

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.Average Price of

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.Average Price of

  18. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane780 2.835 2.8124.

  19. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane780 2.835 2.8124..

  20. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane780 2.835 2.8124..1.

  1. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane780 2.835 2.8124..1.2.

  2. Fuel Cycle System Analysis Handbook

    SciTech Connect (OSTI)

    Steven J. Piet; Brent W. Dixon; Dirk Gombert; Edward A. Hoffman; Gretchen E. Matthern; Kent A. Williams

    2009-06-01T23:59:59.000Z

    This Handbook aims to improve understanding and communication regarding nuclear fuel cycle options. It is intended to assist DOE, Campaign Managers, and other presenters prepare presentations and reports. When looking for information, check here. The Handbook generally includes few details of how calculations were performed, which can be found by consulting references provided to the reader. The Handbook emphasizes results in the form of graphics and diagrams, with only enough text to explain the graphic, to ensure that the messages associated with the graphic is clear, and to explain key assumptions and methods that cause the graphed results. Some of the material is new and is not found in previous reports, for example: (1) Section 3 has system-level mass flow diagrams for 0-tier (once-through), 1-tier (UOX to CR=0.50 fast reactor), and 2-tier (UOX to MOX-Pu to CR=0.50 fast reactor) scenarios - at both static and dynamic equilibrium. (2) To help inform fast reactor transuranic (TRU) conversion ratio and uranium supply behavior, section 5 provides the sustainable fast reactor growth rate as a function of TRU conversion ratio. (3) To help clarify the difference in recycling Pu, NpPu, NpPuAm, and all-TRU, section 5 provides mass fraction, gamma, and neutron emission for those four cases for MOX, heterogeneous LWR IMF (assemblies mixing IMF and UOX pins), and a CR=0.50 fast reactor. There are data for the first 10 LWR recycle passes and equilibrium. (4) Section 6 provides information on the cycle length, planned and unplanned outages, and TRU enrichment as a function of fast reactor TRU conversion ratio, as well as the dilution of TRU feedstock by uranium in making fast reactor fuel. (The recovered uranium is considered to be more pure than recovered TRU.) The latter parameter impacts the required TRU impurity limits specified by the Fuels Campaign. (5) Section 7 provides flows for an 800-tonne UOX separation plant. (6) To complement 'tornado' economic uncertainty diagrams, which show at a glance combined uncertainty information, section 9.2 has a new set of simpler graphs that show the impact on fuel cycle costs for once through, 1-tier, and 2-tier scenarios as a function of key input parameters.

  3. Dynamical Analysis of a Networked Control System

    E-Print Network [OSTI]

    Guofeng Zhang; Guanrong Chen; Tongwen Chen; Maria D'Amico

    2014-05-18T23:59:59.000Z

    A new network data transmission strategy was proposed in Zhang \\& Chen [2005] (arXiv:1405.2404), where the resulting nonlinear system was analyzed and the effectiveness of the transmission strategy was demonstrated via simulations. In this paper, we further generalize the results of Zhang \\& Chen [2005] in the following ways: 1) Construct first-return maps of the nonlinear systems formulated in Zhang \\& Chen [2005] and derive several existence conditions of periodic orbits and study their properties. 2) Formulate the new system as a hybrid system, which will ease the succeeding analysis. 3) Prove that this type of hybrid systems is not structurally stable based on phase transition which can be applied to higher-dimensional cases effortlessly. 4) Simulate a higher-dimensional model with emphasis on their rich dynamics. 5) Study a class of continuous-time hybrid systems as the counterparts of the discrete-time systems discussed above. 6) Propose new controller design methods based on this network data transmission strategy to improve the performance of each individual system and the whole network. We hope that this research and the problems posed here will rouse interests of researchers in such fields as control, dynamical systems and numerical analysis.

  4. Integrated systems analysis of the PIUS reactor

    SciTech Connect (OSTI)

    Fullwood, F.; Kroeger, P.; Higgins, J. [Brookhaven National Lab., Upton, NY (United States)] [and others

    1993-11-01T23:59:59.000Z

    Results are presented of a systems failure analysis of the PIUS plant systems that are used during normal reactor operation and postulated accidents. This study was performed to provide the NRC with an understanding of the behavior of the plant. The study applied two diverse failure identification methods, Failure Modes Effects & Criticality Analysis (FMECA) and Hazards & Operability (HAZOP) to the plant systems, supported by several deterministic analyses. Conventional PRA methods were also used along with a scheme for classifying events by initiator frequency and combinations of failures. Principal results of this study are: (a) an extensive listing of potential event sequences, grouped in categories that can be used by the NRC, (b) identification of support systems that are important to safety, and (c) identification of key operator actions.

  5. Dynamical System Analysis for a phantom model

    E-Print Network [OSTI]

    Nilanjana Mahata; Subenoy Chakraborty

    2014-04-24T23:59:59.000Z

    The paper deals with a dynamical system analysis related to phantom cosmological model . Here gravity is coupled to phantom scalar field having scalar coupling function and a potential. The field equations are reduced to an autonomous dynamical system by a suitable redefinition of the basic variables and assuming some suitable form of the potential function. Finally, critical points are evaluated, their nature have been analyzed and corresponding cosmological scenario has been discussed.

  6. SteamMaster: Steam System Analysis Software

    E-Print Network [OSTI]

    Wheeler, G.

    tool to facilitate the process. SteamMaster is based on an Excel spreadsheet with a Visual Basic interface to simplify system modeling and analysis. SteamMaster has many features and capabilities, including energy and cost savings calculations for five...

  7. Systems Long Term Exposure Program: Analysis of the First Year...

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

    Model (SAPM) 7 or the System Advisor Model (SAM) 8 were generated for use in future system analysis. A. System Descriptions The three technologies under investigation...

  8. analysis pgaa system: Topics by E-print Network

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

    Complex Adaptive System Division Center for Energy, Environmental & Economic Systems Analysis Energy systems are being privatized. Approach Argonne's Center for Energy,...

  9. analysis penetrometer system: Topics by E-print Network

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

    Complex Adaptive System Division Center for Energy, Environmental & Economic Systems Analysis Energy systems are being privatized. Approach Argonne's Center for Energy,...

  10. Jacobi stability analysis of the Lorenz system

    E-Print Network [OSTI]

    Tiberiu Harko; Chor Yin Ho; Chun Sing Leung; Stan Yip

    2015-04-11T23:59:59.000Z

    We perform the study of the stability of the Lorenz system by using the Jacobi stability analysis, or the Kosambi-Cartan-Chern (KCC) theory. The Lorenz model plays an important role for understanding hydrodynamic instabilities and the nature of the turbulence, also representing a non-trivial testing object for studying non-linear effects. The KCC theory represents a powerful mathematical method for the analysis of dynamical systems. In this approach we describe the evolution of the Lorenz system in geometric terms, by considering it as a geodesic in a Finsler space. By associating a non-linear connection and a Berwald type connection, five geometrical invariants are obtained, with the second invariant giving the Jacobi stability of the system. The Jacobi (in)stability is a natural generalization of the (in)stability of the geodesic flow on a differentiable manifold endowed with a metric (Riemannian or Finslerian) to the non-metric setting. In order to apply the KCC theory we reformulate the Lorenz system as a set of two second order non-linear differential equations. The geometric invariants associated to this system (nonlinear and Berwald connections), and the deviation curvature tensor, as well as its eigenvalues, are explicitly obtained. The Jacobi stability of the equilibrium points of the Lorenz system is studied, and the condition of the stability of the equilibrium points is obtained. Finally, we consider the time evolution of the components of the deviation vector near the equilibrium points.

  11. Distribution System Analysis Tools for Studying High Penetration of PV

    E-Print Network [OSTI]

    Distribution System Analysis Tools for Studying High Penetration of PV with Grid Support Features Electric Energy System #12;#12;Distribution System Analysis Tools for Studying High Penetration of PV project titled "Distribution System Analysis Tools for Studying High Penetration of PV with Grid Support

  12. Analysis of complex systems using neural networks

    SciTech Connect (OSTI)

    Uhrig, R.E. [Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering]|[Oak Ridge National Lab., TN (United States)

    1992-12-31T23:59:59.000Z

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems.

  13. Analysis of complex systems using neural networks

    SciTech Connect (OSTI)

    Uhrig, R.E. (Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering Oak Ridge National Lab., TN (United States))

    1992-01-01T23:59:59.000Z

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems.

  14. Apparatus and system for multivariate spectral analysis

    DOE Patents [OSTI]

    Keenan, Michael R. (Albuquerque, NM); Kotula, Paul G. (Albuquerque, NM)

    2003-06-24T23:59:59.000Z

    An apparatus and system for determining the properties of a sample from measured spectral data collected from the sample by performing a method of multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used by a spectrum analyzer to process X-ray spectral data generated by a spectral analysis system that can include a Scanning Electron Microscope (SEM) with an Energy Dispersive Detector and Pulse Height Analyzer.

  15. K West integrated water treatment system subproject safety analysis document

    SciTech Connect (OSTI)

    SEMMENS, L.S.

    1999-02-24T23:59:59.000Z

    This Accident Analysis evaluates unmitigated accident scenarios, and identifies Safety Significant and Safety Class structures, systems, and components for the K West Integrated Water Treatment System.

  16. NREL's System Advisor Model Simplifies Complex Energy Analysis...

    Office of Scientific and Technical Information (OSTI)

    NREL's System Advisor Model Simplifies Complex Energy Analysis (Fact Sheet) Re-direct Destination: NREL has developed a tool -- the System Advisor Model (SAM) -- that can help...

  17. Life-Cycle Analysis Results of Geothermal Systems in Comparison...

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

    & Publications Life-Cycle Analysis Results of Geothermal Systems in Comparison to Other Power Systems Water Use in the Development and Operation of Geothermal Power Plants Water...

  18. analysis system midas: Topics by E-print Network

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

    data of the CHAMP satellite. Comparisons are made between vertical electron 14 Systems Analysis Systems Integration Renewable Energy Websites Summary: Domestic energy-based...

  19. analysis system modeling: Topics by E-print Network

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

    Newcastle upon Tyne, University of 98 EquationFree System-Level Dynamic Modeling and Analysis in Energy Processing Engineering Websites Summary: Equation-Free System-Level...

  20. An Assessment of Economic Analysis Methods for Cogeneration Systems

    E-Print Network [OSTI]

    Bolander, J. N.; Murphy, W. E.; Turner, W. D.

    1985-01-01T23:59:59.000Z

    Cogeneration feasibility studies were conducted for eleven state agencies of Texas. A net present value (NPV) analysis was used to evaluate candidate cogeneration systems and select the optimum system. CELCAP, an hour-by-hour cogeneration analysis...

  1. Automotive and MHE Fuel Cell System Cost Analysis (Text Version...

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

    on previous fuel cell cost analysis studies that we've done for the Department of Energy, beginning with a market analysis, and then completing a system design. The system...

  2. Incorporating HVDC's into monitoring and power system analysis

    E-Print Network [OSTI]

    Krishnaswamy, Vikram

    2002-01-01T23:59:59.000Z

    This thesis attempts to study the effect of incorporating HVDC's into monitoring and power system analysis. Power system analysis, including load flow and stability studies, and monitoring defines a complete cycle of the impact of HVDC in a power...

  3. Analysis of a piping system for requalification

    SciTech Connect (OSTI)

    Hsieh, B.J.; Tang, Yu.

    1992-01-01T23:59:59.000Z

    This paper discusses the global stress analysis required for the seismic/structural requalification of a reactor secondary piping system in which minor defects (flaws) were discovered during a detailed inspection. The flaws in question consisted of weld imperfections. Specifically, it was necessary to establish that the stresses at the flawed sections did not exceed the allowables and that the fatigue life remained within acceptable limits. At the same time the piping system had to be qualified for higher earthquake loads than those used in the original design. To accomplish these objectives the nominal stress distributions in the piping system under the various loads (dead load, thermal load, wind load and seismic load) were determined. First a best estimate finite element model was developed and calculations were performed using the piping analysis modules of the ANSYS Computer Code. Parameter studies were then performed to assess the effect of physically reasonable variations in material, structural, and boundary condition characteristics. The nominal stresses and forces so determined, provided input for more detailed analyses of the flawed sections. Based on the reevaluation, the piping flaws were judged to be benign, i.e., the piping safety margins were acceptable inspite of the increased seismic demand. 13 refs.

  4. Analysis of a piping system for requalification

    SciTech Connect (OSTI)

    Hsieh, B.J.; Tang, Yu

    1992-05-01T23:59:59.000Z

    This paper discusses the global stress analysis required for the seismic/structural requalification of a reactor secondary piping system in which minor defects (flaws) were discovered during a detailed inspection. The flaws in question consisted of weld imperfections. Specifically, it was necessary to establish that the stresses at the flawed sections did not exceed the allowables and that the fatigue life remained within acceptable limits. At the same time the piping system had to be qualified for higher earthquake loads than those used in the original design. To accomplish these objectives the nominal stress distributions in the piping system under the various loads (dead load, thermal load, wind load and seismic load) were determined. First a best estimate finite element model was developed and calculations were performed using the piping analysis modules of the ANSYS Computer Code. Parameter studies were then performed to assess the effect of physically reasonable variations in material, structural, and boundary condition characteristics. The nominal stresses and forces so determined, provided input for more detailed analyses of the flawed sections. Based on the reevaluation, the piping flaws were judged to be benign, i.e., the piping safety margins were acceptable inspite of the increased seismic demand. 13 refs.

  5. System Analysis Projects | Department of Energy

    Office of Environmental Management (EM)

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

  6. Systems Analysis Success Stories | Department of Energy

    Office of Environmental Management (EM)

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

  7. ELECTRICITY CASE: RISK ANALYSIS OF INFRASTRUCTURE SYSTEMS-DIFFERENT

    E-Print Network [OSTI]

    Wang, Hai

    of infrastructure systems. The discussion is applied to electric power delivery systems, i.e. transmissionELECTRICITY CASE: RISK ANALYSIS OF INFRASTRUCTURE SYSTEMS-DIFFERENT APPROACHES FOR RISK ANALYSIS OF ELECTRIC POWER SYSTEMS Holmgren, A. CREATE REPORT Under FEMA Grant EMW-2004-GR-0112 May 31, 2005 Center

  8. Generalized Lyapunov Function for Stability Analysis of Interconnected Power Systems

    E-Print Network [OSTI]

    Pota, Himanshu Roy

    Generalized Lyapunov Function for Stability Analysis of Interconnected Power Systems M. A. Mahmud for formulating generalized Lyapunov function for the stability analysis of interconnected power systems. Lyapunov function is formulated based on the total energy of power system where the system is considered as a single

  9. Hazard Analysis of Complex Spacecraft Using Systems-Theoretic Process Analysis

    E-Print Network [OSTI]

    Ishimatsu, Takuto

    A new hazard analysis technique, called systems-theoretic process analysis, is capable of identifying potential hazardous design flaws, including software and system design errors and unsafe interactions among multiple ...

  10. Cost analysis of energy storage systems for electric utility applications

    SciTech Connect (OSTI)

    Akhil, A. [Sandia National Lab., Albuquerque, NM (United States); Swaminathan, S.; Sen, R.K. [R.K. Sen & Associates, Inc., Bethesda, MD (United States)

    1997-02-01T23:59:59.000Z

    Under the sponsorship of the Department of Energy, Office of Utility Technologies, the Energy Storage System Analysis and Development Department at Sandia National Laboratories (SNL) conducted a cost analysis of energy storage systems for electric utility applications. The scope of the study included the analysis of costs for existing and planned battery, SMES, and flywheel energy storage systems. The analysis also identified the potential for cost reduction of key components.

  11. Extending and automating a systems-theoretic hazard analysis for requirements generation and analysis

    E-Print Network [OSTI]

    Thomas, John P., IV

    2013-01-01T23:59:59.000Z

    Systems Theoretic Process Analysis (STPA) is a powerful new hazard analysis method designed to go beyond traditional safety techniques-such as Fault Tree Analysis (FTA)-that overlook important causes of accidents like ...

  12. EA Systems Examples Induction and Recursion Length Measuring the Universe Analysis Number systems of different lengths,

    E-Print Network [OSTI]

    Forster, T.E.

    EA Systems Examples Induction and Recursion Length Measuring the Universe Analysis Number systems of Mathematics University of Bristol April 21, 2008 Richard.Pettigrew@bris.ac.uk Natural number systems and infinitesimal analysis #12;EA Systems Examples Induction and Recursion Length Measuring the Universe Analysis

  13. Investigation of microstructure of disordered colloidal systems by small-angle scattering

    E-Print Network [OSTI]

    Chiang, Wei-Shan

    2014-01-01T23:59:59.000Z

    Small-angle scattering (SAS) has been widely applied to study the microstructure of colloidal systems. Although colloids cover a wide range of materials, in general they can simply be viewed as basic building particles ...

  14. Reachability of Delayed Hybrid Systems Using Level-set Methods Renault SAS, Guyancourt, France.

    E-Print Network [OSTI]

    Boyer, Edmond

    energy source in addition to its main energy source ­ a high voltage battery. As an important feature control whose value function allows a characterization of the reachable set. The value function is in turn characterized by a dynamic programming algorithm. This algorithm is implemented and some numerical examples

  15. Local Fourier analysis for staggered systems of PDEs

    E-Print Network [OSTI]

    MacLachlan, Scott

    Local Fourier analysis for staggered systems of PDEs Scott MacLachlan scott.maclachlan@tufts.edu Tufts University and Kees Oosterlee TU-Delft and CWI April 10, 2008 Local Fourier analysis for staggered of complementary processes · Relaxation · Coarse-grid correction Local Fourier analysis for staggered systems

  16. Stochastic Control Analysis for Biochemical Reaction Systems

    E-Print Network [OSTI]

    Kyung Hyuk Kim; Herbert M. Sauro

    2009-08-21T23:59:59.000Z

    In this paper, we investigate how stochastic reaction processes are affected by external perturbations. We describe an extension of the deterministic metabolic control analysis (MCA) to the stochastic regime. We introduce stochastic sensitivities for mean and covariance values of reactant concentrations and reaction fluxes and show that there exist MCA-like summation theorems among these sensitivities. The summation theorems for flux variances are shown to depend on the size of the measurement time window ($\\epsilon$), within which reaction events are counted for measuring a single flux. The degree of the $\\epsilon$-dependency can become significant for processes involving multi-time-scale dynamics and is estimated by introducing a new measure of time scale separation. This $\\epsilon$-dependency is shown to be closely related to the power-law scaling observed in flux fluctuations in various complex networks. We propose a systematic way to control fluctuations of reactant concentrations while minimizing changes in mean concentration levels. Such orthogonal control is obtained by introducing a control vector indicating the strength and direction of parameter perturbations leading to a sensitive control. We also propose a possible implication in the control of flux fluctuation: The control distribution for flux fluctuations changes with the measurement time window size, $\\epsilon$. When a control engineer applies a specific control operation on a reaction system, the system can respond contrary to what is expected, depending on the time window size $\\epsilon$.

  17. Traffic Analysis: From Stateful Firewall to Network Intrusion Detection System

    E-Print Network [OSTI]

    Chiueh, Tzi-cker

    1 Traffic Analysis: From Stateful Firewall to Network Intrusion Detection System Fanglu Guo Tzi normalization. Index Terms Packet (traffic) analysis, stateful firewall, network intrusion detection system intrusion detection system (NIDS). Stateful firewall analyzes packets up to their layer 4 headers while NIDS

  18. Systems Analysis Department Annual Report 2001

    E-Print Network [OSTI]

    benchmarking analysis to the Danish district heating sector Technology Scenarios 17 Sensor Technology Foresight

  19. Hydrogen Storage Systems Analysis Working Group Meeting: Summary...

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

    Summary of June 11, 2008, biannual meeting of the Hydrogen Storage Systems Analysis Working Group. ssawgsummaryreport0608.pdf More Documents & Publications Hydrgoen Storage...

  20. Hydrogen Storage Systems Analysis Working Group Meeting: Summary...

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

    to bring together the DOE research community involved in systems analysis of hydrogen storage materials and processes. ssawgsummaryreport.pdf More Documents & Publications...

  1. analysis system tool: Topics by E-print Network

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

    to analyse LCA variability of energy systems Physics Websites Summary: variability in LCA are sensitivity analysis (SA). However, when dealing with environmental impact...

  2. Office of Energy Policy and Systems Analysis Site Upgrade

    Broader source: Energy.gov [DOE]

    Office of Energy Policy and Systems Analysis site is currently being upgraded to better serve on audience. Please check back shortly.

  3. advanced system analysis: Topics by E-print Network

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

    based on metric Balazinska, Magdalena 3 Advanced holographic nondestructive testing system for residual stress analysis CERN Preprints Summary: The design and operating of a...

  4. Webinar: Automotive and MHE Fuel Cell System Cost Analysis

    Broader source: Energy.gov [DOE]

    Video recording and text version of the webinar titled, Automotive and MHE Fuel Cell System Cost Analysis, originally presented on April 16, 2013.

  5. Hydrogen Storage Systems Analysis Working Group Meeting: Summary...

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

    Hydrogen Storage Systems Analysis Working Group Meeting Argonne DC Offices L'Enfant Plaza, Washington, DC December 4, 2007 SUMMARY REPORT Compiled by Romesh Kumar Argonne National...

  6. applied systems analysis: Topics by E-print Network

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

    Evgeny Katz 2011-10-08 7 A macro-micro system architecture analysis framework applied to Smart Grid meter data management systems by Sooraj Prasannan. MIT - DSpace Summary: This...

  7. Technology Portfolio Planning by Weighted Graph Analysis of System Architectures

    E-Print Network [OSTI]

    de Weck, Olivier L.

    Technology Portfolio Planning by Weighted Graph Analysis of System Architectures Peter Davison and Bruce Cameron Massachusetts Institute of Technology, Cambridge, MA 02139 Edward F. Crawley Skolkovo Institute of Science and Technology, Skolkovo 143025, Russia Abstract5 Many systems undergo significant

  8. analysis system retas: Topics by E-print Network

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

    para toda sequencia (xn)nN em D(f)x0, com lim n Oquendo, Higidio Portillo 3 Systems Analysis Systems Integration Renewable Energy Websites Summary: Domestic energy-based...

  9. Availability Analysis of the Ventilation Stack CAM Interlock System

    E-Print Network [OSTI]

    Young, J

    2000-01-01T23:59:59.000Z

    Ventilation Stack Continuous Air Monitor (CAM) Interlock System failure modes, failure frequencies, and system availability have been evaluated for the RPP. The evaluation concludes that CAM availability is as high as assumed in the safety analysis and that the current routine system surveillance is adequate to maintain this availability credited in the safety analysis, nor is such an arrangement predicted to significantly improve system availability.

  10. Visualizations for Power System Contingency Analysis Data

    E-Print Network [OSTI]

    whether the system is secure. With the global trend towards deregulation in the power system industry increasing. Not only has deregulation resulted in much larger system model sizes, but also CA is computed

  11. Sensitivity analysis of oscillating hybrid systems

    E-Print Network [OSTI]

    Saxena, Vibhu Prakash

    2010-01-01T23:59:59.000Z

    Many models of physical systems oscillate periodically and exhibit both discrete-state and continuous-state dynamics. These systems are called oscillating hybrid systems and find applications in diverse areas of science ...

  12. Power System Probabilistic and Security Analysis on Commodity High Performance Computing Systems

    E-Print Network [OSTI]

    Franchetti, Franz

    power system infrastructures also requires merging of offline security analyses into on- line operationPower System Probabilistic and Security Analysis on Commodity High Performance Computing Systems tools for power system probabilistic and security analysis: 1) a high performance Monte Carlo simulation

  13. THREE DIMENSIONAL VISUALIZATIONS FOR POWER SYSTEM CONTINGENCY ANALYSIS VOLTAGE DATA

    E-Print Network [OSTI]

    that the power systems are now often operated closer to their limits to maximum transmission system utilizationTHREE DIMENSIONAL VISUALIZATIONS FOR POWER SYSTEM CONTINGENCY ANALYSIS VOLTAGE DATA Y. Sun IEEE security assessment is critical for detecting underlying problems in a power system. More frequent CA

  14. UNCORRECTED 2 Coordination in irrigation systems: An analysis

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    UNCORRECTED PROOF 1 2 Coordination in irrigation systems: An analysis 3 of the Lansing­Kremer model;UNCORRECTED PROOF 25 argued that a central control was inevitable for larger irrigation systems and hypoth- 26, there are various examples of complex irrigation systems and drainage systems 28 that have evolved without central

  15. AC system stability analysis and assessment for Shipboard Power Systems 

    E-Print Network [OSTI]

    Qi, Li

    2006-04-12T23:59:59.000Z

    The electric power systems in U.S. Navy ships supply energy to sophisticated systems for weapons, communications, navigation and operation. The reliability and survivability of a Shipboard Power System (SPS) are critical ...

  16. AC system stability analysis and assessment for Shipboard Power Systems

    E-Print Network [OSTI]

    Qi, Li

    2006-04-12T23:59:59.000Z

    The electric power systems in U.S. Navy ships supply energy to sophisticated systems for weapons, communications, navigation and operation. The reliability and survivability of a Shipboard Power System (SPS) are critical to the mission of a Navy...

  17. Solar Energy Systems - Research - Systems Analysis - Smart Grid...

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

    Solar Energy Systems U.S. Department of Energy Search Argonne ... Search Argonne Home > SES Home Research Home Photovoltaics Transparent Conductors Concentrating Sunlight Systems...

  18. Performance Validation and Energy Analysis of HVAC Systems using Simulation

    E-Print Network [OSTI]

    Diamond, Richard

    monitored system outputs for performance validation and energy analysis. The paper presents results from1 Performance Validation and Energy Analysis of HVAC Systems using Simulation Tim Salsbury and Rick Francisco. 1 Introduction Significant potential exists with the current technology of energy management

  19. Towards Interactive Timing Analysis for Designing Reactive Systems

    E-Print Network [OSTI]

    Towards Interactive Timing Analysis for Designing Reactive Systems Insa Fuhrmann David Broman Steven Smyth Reinhard von Hanxleden Electrical Engineering and Computer Sciences University of California Interactive Timing Analysis for Designing Reactive Systems Insa Fuhrmann1 , David Broman2,3 , Steven Smyth1

  20. 15-11-061ETSAP Energy Technology Systems Analysis

    E-Print Network [OSTI]

    15-11-061ETSAP Energy Technology Systems Analysis Programme (ETSAP) ­ Annex X ETSAP Semi · Global Energy Supply: Model-based Scenario Analysis of Resource Use and Energy Trade. Uwe Remme, Maryse Policy Scenario to address energy security and environmental concerns. Based on the detailed analysis

  1. Safety System Oversight Staffing Analysis (Instructions, Blank...

    Office of Environmental Management (EM)

    modifications since changes to the worksheet format may inadvertently change included formula referenced cells. SSO Alternate Staffing Analysis - Instructions SSO Alternate...

  2. FAQS Gap Analysis Qualification Card – Mechanical Systems

    Broader source: Energy.gov [DOE]

    Functional Area Qualification Standard Gap Analysis Qualification Cards outline the differences between the last and latest version of the FAQ Standard.

  3. Safety Analysis Of Automated Highway Systems

    E-Print Network [OSTI]

    Leveson, Nancy G.

    1997-01-01T23:59:59.000Z

    Lee. Towards an automated fmea assis- tant. In Applicationsmodes and effects analysis (FMEA) is employed to determineof multiple failures. ) FMEA was developed Potential Part

  4. An analysis of distributed solar fuel systems

    E-Print Network [OSTI]

    Thomas, Alex, S.M. Massachusetts Institute of Technology

    2012-01-01T23:59:59.000Z

    While solar fuel systems offer tremendous potential to address global clean energy needs, most existing analyses have focused on the feasibility of large centralized systems and applications. Not much research exists on ...

  5. Analysis of radiation measurement data of the BUSS cask

    SciTech Connect (OSTI)

    Liu, Y.Y. [Argonne National Lab., IL (United States); Tang, J.S. [Oak Ridge National Lab., TN (United States)

    1995-12-31T23:59:59.000Z

    The Beneficial Uses Shipping System (BUSS) is a Type-B packaging developed for shipping nonfissile, special-form radioactive materials to facilities such as sewage, food, and medical-product irradiators. The primary purpose of the BUSS cask is to provide shielding and confinement, as well as impact, puncture, and thermal protection for its certified special-form contents under both normal transport and hypothetical accident conditions. A BUSS cask that contained 16 CsCl capsules (2.723 {times} 10{sup 4} TBq total activity) was recently subjected to radiation survey measurements at a Westinghouse Hanford facility, which provided data that could be used to validate computer codes. Two shielding analysis codes, MICROSHIELD (User`s Manual 1988) and SAS4 (Tan 1993), that are used at Argonne National Laboratory to evaluate the safety of packaging of radioactive materials during transportation, have been selected for analysis of radiation data obtained from the BUSS cask. MICROSHIELD, which performs only gamma radiation shielding calculation, is based on a point-kernel model with idealized geometry, whereas SAS4 is a control module in the SCALE code system (1995) that can perform three-dimensional Monte Carlo shielding calculation for photons and neutrons, with built-in procedures for cross-section data processing and automated variance reduction. The two codes differ in how they model the details of the physics of gamma photon attenuation in materials, and this difference is reflected in the associated engineering cost of the analysis. One purpose of the analysis presented in this paper, therefore, is to examine the effects of the major modeling assumptions in the two codes on calculated dose rates, and to use the measured dose rates for comparison. The focus in this paper is on analysis of radiation dose rates measured on the general body of the cask and away from penetrations.

  6. SteamMaster: Steam System Analysis Software 

    E-Print Network [OSTI]

    Wheeler, G.

    2003-01-01T23:59:59.000Z

    recommendations to increase steam system effic iency. Steam System Opportunities ]n nearly 400 industrial assessments, we have recommended 210 steam system improvements, excluding heat recovery, that would save $1.5 million/year with a O.4-year payback. 75...

  7. Failure analysis issues in microelectromechanical systems (MEMS).

    SciTech Connect (OSTI)

    Walraven, Jeremy Allen

    2005-07-01T23:59:59.000Z

    Failure analysis and device characterization of MEMS components are critical steps in understanding the root causes of failure and improving device performance. At the wafer and die level these tasks can be performed with little or no sample preparation. Larger challenges occur after fabrication when the device is packaged, capped, sealed, or otherwise obstructed from view. The challenges and issues of MEMS failure analysis lie in identifying the root cause of failure for these packaged, capped, and sealed devices without perturbing the device or its immediate environment. Novel methods of gaining access to the device or preparing the device for analysis are crucial to accurately determining the root cause of failure. This paper will discuss issues identified in performing root cause failure analysis of packaged MEMS devices, as well as the methods employed to analyze them.

  8. Microcomputer Analysis of Pumping System Performance

    E-Print Network [OSTI]

    Bierschenk, J. L.; Schmidt, P. S.

    With today’s emphasis on efficient use and conservation of energy, selecting the correct pump for a given application requires not only a concise performance evaluation but also detailed economic analysis. A microcomputer program entitled PUMPCALC...

  9. A systems approach to food accident analysis

    E-Print Network [OSTI]

    Helferich, John D

    2011-01-01T23:59:59.000Z

    Food borne illnesses lead to 3000 deaths per year in the United States. Some industries, such as aviation, have made great strides increasing safety through careful accident analysis leading to changes in industry practices. ...

  10. Process of system design and analysis

    SciTech Connect (OSTI)

    Gardner, B.

    1995-09-01T23:59:59.000Z

    The design of an effective physical protection system includes the determination of the physical protection system objectives, the initial design of a physical protection system, the evaluation of the design, and, probably, a redesign or refinement of the system. To develop the objectives, the designer must begin by gathering information about facility operations and conditions, such as a comprehensive description of the facility, operating states, and the physical protection requirements. The designer then needs to define the threat. This involves considering factors about potential adversaries: Class of adversary, adversary`s capabilities, and range of adversary`s tactics. Next, the designer should identify targets. Determination of whether or not nuclear materials are attractive targets is based mainly on the ease or difficulty of acquisition and desirability of the materiaL The designer now knows the objectives of the physical protection system, that is, ``What to protect against whom.`` The next step is to design the system by determining how best to combine such elements as fences, vaults, sensors, procedures, communication devices, and protective force personnel to meet the objectives of the system. Once a physical protection system is designed, it must be analyzed and evaluated to ensure it meets the physical protection objectives. Evaluation must allow for features working together to assure protection rather than regarding each feature separately. Due to the complexity of protection systems, an evaluation usually requires modeling techniques. If any vulnerabilities are found, the initial system must be redesigned to correct the vulnerabilities and a reevaluation conducted.

  11. Fuel Cell System Improvement for Model-Based Diagnosis Analysis

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Fuel Cell System Improvement for Model-Based Diagnosis Analysis Philippe Fiani & Michel Batteux of a model of a fuel cell system, in order to make it usable for model- based diagnosis methods. A fuel cell for the fuel cell stack but also for the system environment. In this paper, we present an adapted library which

  12. Cost Analysis of Fuel Cell Systems for Transportation

    E-Print Network [OSTI]

    Cost Analysis of Fuel Cell Systems for Transportation Compressed Hydrogen and PEM Fuel Cell System Discussion Fuel Cell Tech Team FreedomCar Detroit. MI October 20, 2004 TIAX LLC Acorn Park Cambridge Estimates Task 3: Identify Opportunities for System Cost Reduction Tasks 4, 5, 6 & 7: Annual Updates Develop

  13. Modal Analysis of Continuous Structrual System with Tapered Cantilevered Members

    E-Print Network [OSTI]

    Kim, Yoon Mo

    2012-02-14T23:59:59.000Z

    OF CONVENTIONAL CONTINUOUS SYSTEM ............ 9 2.1. Transverse Vibration in Conventional Continuous System Model .................... 9 2.2. Equation of Motion for Flexural Member .......................................................... 9 2.3 Boundary.......................................... 19 2.6 Conclusion ........................................................................................................ 20 3. MODAL ANALYSIS OF DISCRETIZED CONTINUOUS SYSTEM ............... 21 3.1. Transverse Vibration in Discretized Continuous...

  14. Nonlinear analysis of a reaction-diffusion system: Amplitude equations

    SciTech Connect (OSTI)

    Zemskov, E. P., E-mail: zemskov@ccas.ru [Russian Academy of Sciences, Dorodnicyn Computing Center (Russian Federation)

    2012-10-15T23:59:59.000Z

    A reaction-diffusion system with a nonlinear diffusion term is considered. Based on nonlinear analysis, the amplitude equations are obtained in the cases of the Hopf and Turing instabilities in the system. Turing pattern-forming regions in the parameter space are determined for supercritical and subcritical instabilities in a two-component reaction-diffusion system.

  15. Hamiltonian control systems From modeling to analysis and control

    E-Print Network [OSTI]

    Knobloch,Jürgen

    Hamiltonian control systems From modeling to analysis and control Arjan van der Schaft Johann-based modeling 3 Definition of port-Hamiltonian systems 4 Scattering: from power variables to wave variables 5, University of Groningen, the Netherlands DiHamiltonian control systems Elgersburg School, March, 2012 1 / 108

  16. Full-System Power Analysis and Modeling for Server Environments

    E-Print Network [OSTI]

    Kozyrakis, Christos

    Full-System Power Analysis and Modeling for Server Environments Dimitris Economou, Suzanne Rivoire-density computer systems, have created a growing demand for better power management in server environments. Despite consumption trends and developing simple yet accurate models to predict full-system power. We study

  17. EMSL - Cell Isolation and Systems Analysis

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

    using fluorescence resonance energy transfer (FRET) in live cells. * Two SOLiD systems together with the Ion Proton(tm) provide unbiased global transcriptome analyses with...

  18. -Z:\\OIR Repository\\^ Reports\\^ Projects\\^ TN Dept of Labor and Workforce\\Earnings of Graduates.sas -University of Memphis Office of Institutional Research --15NOV13

    E-Print Network [OSTI]

    Dasgupta, Dipankar

    -Z:\\OIR Repository\\^ Reports\\^ Projects\\^ TN Dept of Labor and Workforce\\Earnings of Graduates.sas -University of Memphis Office of Institutional Research --15NOV13 -Graduation year includes summer, fall graduation, multiplied by 4. Source: Tennessee Dept. of Labor & Workforce data files. Excludes workers

  19. Route profile analysis system and method

    DOE Patents [OSTI]

    Mullenhoff, D.J.; Wilson, S.W.

    1982-07-29T23:59:59.000Z

    A system for recording terrain profile information is disclosed. The system accurately senses incremental distances traveled by a vehicle along with vehicle inclination, recording both with elapsed time. The incremental distances can subsequently be differentiated with respect to time to obtain acceleration. The computer acceleration can then be used to correct the sensed inclination.

  20. Extending and automating a Systems-Theoretic hazard analysis for requirements generation and analysis.

    SciTech Connect (OSTI)

    Thomas, John (Massachusetts Institute of Technology)

    2012-05-01T23:59:59.000Z

    Systems Theoretic Process Analysis (STPA) is a powerful new hazard analysis method designed to go beyond traditional safety techniques - such as Fault Tree Analysis (FTA) - that overlook important causes of accidents like flawed requirements, dysfunctional component interactions, and software errors. While proving to be very effective on real systems, no formal structure has been defined for STPA and its application has been ad-hoc with no rigorous procedures or model-based design tools. This report defines a formal mathematical structure underlying STPA and describes a procedure for systematically performing an STPA analysis based on that structure. A method for using the results of the hazard analysis to generate formal safety-critical, model-based system and software requirements is also presented. Techniques to automate both the analysis and the requirements generation are introduced, as well as a method to detect conflicts between the safety and other functional model-based requirements during early development of the system.

  1. POWER GRID DYNAMICS: ENHANCING POWER SYSTEM OPERATION THROUGH PRONY ANALYSIS

    SciTech Connect (OSTI)

    Ray, C.; Huang, Z.

    2007-01-01T23:59:59.000Z

    Prony Analysis is a technique used to decompose a signal into a series consisting of weighted complex exponentials and promises to be an effi cient way of recognizing sensitive lines during faults in power systems such as the U.S. Power grid. Positive Sequence Load Flow (PSLF) was used to simulate the performance of a simple two-area-four-generator system and the reaction of the system during a line fault. The Dynamic System Identifi cation (DSI) Toolbox was used to perform Prony analysis and use modal information to identify key transmission lines for power fl ow adjustment to improve system damping. The success of the application of Prony analysis methods to the data obtained from PSLF is reported, and the key transmission line for adjustment is identifi ed. Future work will focus on larger systems and improving the current algorithms to deal with networks such as large portions of the Western Electricity Coordinating Council (WECC) power grid.

  2. Hierarchical Task Analysis of Intrusion Detection Systems

    E-Print Network [OSTI]

    Blustein, J.

    .......................... 4 3. Hierarchical Task Analysis ............................ 6 3.1 Network Security Administrator .................... 7 3.2 Functions of Network Security Administrator ....... 7 4. Diagrams on a single or group of persons called Network Security Administrators. They use a wide variety of tools

  3. Safety System Oversight Staffing Analysis- Example

    Broader source: Energy.gov [DOE]

    This Staffing Analysis calculation is completed using an Excel worksheet. Information locations are identified by titles in column or row headings and worksheet locations based on the unmodified blank. Use caution when making worksheet modifications since changes to the worksheet format may inadvertently change included formula referenced cells.

  4. Big Data Visual Analytics for Exploratory Earth System Simulation Analysis

    SciTech Connect (OSTI)

    Steed, Chad A [ORNL; Ricciuto, Daniel M [ORNL; Shipman, Galen M [ORNL; Smith, Brian E [ORNL; Thornton, Peter E [ORNL; Wang, Dali [ORNL; Shi, Xiaoying [ORNL; Williams, Dean N. [Lawrence Livermore National Laboratory (LLNL)

    2013-01-01T23:59:59.000Z

    Rapid increases in high performance computing are feeding the development of larger and more complex data sets in climate research, which sets the stage for so-called big data analysis challenges. However, conventional climate analysis techniques are inadequate in dealing with the complexities of today s data. In this paper, we describe and demonstrate a visual analytics system, called the Exploratory Data analysis ENvironment (EDEN), with specific application to the analysis of complex earth system simulation data sets. EDEN represents the type of interactive visual analysis tools that are necessary to transform data into insight, thereby improving critical comprehension of earth system processes. In addition to providing an overview of EDEN, we describe real-world studies using both point ensembles and global Community Land Model Version 4 (CLM4) simulations.

  5. Enhancing the systems decision process with flexibility analysis for optimal unmanned aircraft system selection

    E-Print Network [OSTI]

    Bachmann, Chris H., III (Christopher Henry)

    2008-01-01T23:59:59.000Z

    Systems Engineers often conduct decision analysis in order to provide decision makers with a quantifiable means to make decisions. However, the field of Systems Engineering is often criticized for focusing on processes and ...

  6. Analysis of Bitcoin Pooled Mining Reward Systems

    E-Print Network [OSTI]

    Rosenfeld, Meni

    2011-01-01T23:59:59.000Z

    In this paper we describe the various scoring systems used to calculate rewards of participants in Bitcoin pooled mining, explain the problems each were designed to solve and analyze their respective advantages and disadvantages.

  7. Commonality analysis for exploration life support systems

    E-Print Network [OSTI]

    Cunio, Phillip M

    2008-01-01T23:59:59.000Z

    Commonality, defined practically as the use of similar technologies to deliver similar functions across a range of different complex systems, offers opportunities to improve the lifecycle costs of portfolios of complex ...

  8. Design and analysis of reconfigurable analog system

    E-Print Network [OSTI]

    Lajevardi, Payam

    2011-01-01T23:59:59.000Z

    A highly-configurable analog system is presented. A prototype chip is fabricated and an ADC and filter functionalities are demonstrated. The chip consists of eight identical programmable stages. In an ADC configuration, ...

  9. Uncertainty analysis of power systems using collocation

    E-Print Network [OSTI]

    Taylor, Joshua Adam

    2008-01-01T23:59:59.000Z

    The next-generation all-electric ship represents a class of design and control problems in which the system is too large to approach analytically, and even with many conventional computational techniques. Additionally, ...

  10. Analysis of Hybrid Hydrogen Systems: Final Report

    SciTech Connect (OSTI)

    Dean, J.; Braun, R.; Munoz, D.; Penev, M.; Kinchin, C.

    2010-01-01T23:59:59.000Z

    Report on biomass pathways for hydrogen production and how they can be hybridized to support renewable electricity generation. Two hybrid systems were studied in detail for process feasibility and economic performance. The best-performing system was estimated to produce hydrogen at costs ($1.67/kg) within Department of Energy targets ($2.10/kg) for central biomass-derived hydrogen production while also providing value-added energy services to the electric grid.

  11. Multiscale Analysis and Optimisation of Photosynthetic Solar Energy Systems

    E-Print Network [OSTI]

    Andrew K. Ringsmuth

    2014-02-24T23:59:59.000Z

    This work asks how light harvesting in photosynthetic systems can be optimised for economically scalable, sustainable energy production. Hierarchy theory is introduced as a system-analysis and optimisation tool better able to handle multiscale, multiprocess complexities in photosynthetic energetics compared with standard linear-process analysis. Within this framework, new insights are given into relationships between composition, structure and energetics at the scale of the thylakoid membrane, and also into how components at different scales cooperate under functional objectives of the whole photosynthetic system. Combining these reductionistic and holistic analyses creates a platform for modelling multiscale-optimal, idealised photosynthetic systems in silico.

  12. Analysis of Lyapunov Control for Hamiltonian Quantum Systems

    E-Print Network [OSTI]

    Xiaoting Wang; Sonia Schirmer

    2008-05-19T23:59:59.000Z

    We present detailed analysis of the convergence properties and effectiveness of Lyapunov control design for bilinear Hamiltonian quantum systems based on the application of LaSalle's invariance principle and stability analysis from dynamical systems and control theory. For a certain class of Hamiltonians, strong convergence results can be obtained for both pure and mixed state systems. The control Hamiltonians for realistic physical systems, however, generally do not fall in this class. It is shown that the effectiveness of Lyapunov control design in this case is significantly diminished.

  13. Multiscale Analysis and Optimisation of Photosynthetic Solar Energy Systems

    E-Print Network [OSTI]

    Ringsmuth, Andrew K

    2014-01-01T23:59:59.000Z

    This work asks how light harvesting in photosynthetic systems can be optimised for economically scalable, sustainable energy production. Hierarchy theory is introduced as a system-analysis and optimisation tool better able to handle multiscale, multiprocess complexities in photosynthetic energetics compared with standard linear-process analysis. Within this framework, new insights are given into relationships between composition, structure and energetics at the scale of the thylakoid membrane, and also into how components at different scales cooperate under functional objectives of the whole photosynthetic system. Combining these reductionistic and holistic analyses creates a platform for modelling multiscale-optimal, idealised photosynthetic systems in silico.

  14. Fuel Cells Vehicle Systems Analysis (Fuel Cell Freeze Investigation)

    SciTech Connect (OSTI)

    Pesaran, A.; Kim, G.; Markel, T.; Wipke, K.

    2005-05-01T23:59:59.000Z

    Presentation on Fuel Cells Vehicle Systems Analysis (Fuel Cell Freeze Investigation) for the 2005 Hydrogen, Fuel Cells & Infrastructure Technologies Program Annual Review held in Arlington, Virginia on May 23-26, 2005.

  15. analysis system design: Topics by E-print Network

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

    the IEA R&D Wind's Topical expert meeting on Material recycling and life cycle analysis (LCA) of wind turbines 336 Social Norm Design for Information Exchange Systems with Limited...

  16. analysis code system: Topics by E-print Network

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

    We define the user Erkip, Elza 2 A Network Approach to the French System of Legal codes Part I: Analysis Physics Websites Summary: vertices) of codes covering large domains...

  17. Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems

    E-Print Network [OSTI]

    Müller-Olm, Markus

    Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems Ahmed Bouajjani1, Markus M¨uller-Olm Bouajjani, Markus M¨uller-Olm, and Tayssir Touili parallel calls. In a multithreaded program such a command

  18. Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems

    E-Print Network [OSTI]

    Müller-Olm, Markus

    Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems Ahmed Bouajjani 1 , Markus MË?uller­Olm #12; 474 Ahmed Bouajjani, Markus MË?uller­Olm, and Tayssir Touili parallel calls. In a multithreaded

  19. Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems

    E-Print Network [OSTI]

    Touili, Tayssir

    Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems Ahmed Bouajjani 1 , Markus MË?uller­Olm Bouajjani, Markus MË?uller­Olm, and Tayssir Touili parallel calls. In a multithreaded program such a command

  20. Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems

    E-Print Network [OSTI]

    Müller-Olm, Markus

    Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems Ahmed Bouajjani1, Markus M¨uller-Olm #12;474 Ahmed Bouajjani, Markus M¨uller-Olm, and Tayssir Touili parallel calls. In a multithreaded

  1. Availability Analysis of Repairable Computer Systems and Stationarity Detection

    E-Print Network [OSTI]

    Sericola, Bruno

    Availability Analysis of Repairable Computer Systems and Stationarity Detection Bruno Sericola AbstractÐPoint availability and expected interval availability are dependability measures respectively in this paper a new algorithm to compute these two availability measures. This algorithm is based

  2. Analysis of transmission system faults in the phase domain

    E-Print Network [OSTI]

    Zhu, Jun

    2004-11-15T23:59:59.000Z

    In order to maintain a continuous power suppply, nowadays relays in transmission systems are required to be able to deal with complicated faults involving non-conventional connections, which poses a challenge to the short circuit analysis...

  3. air system analysis: Topics by E-print Network

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

    combined in extensive numerical ... Swan, William M. 1979-01-01 5 Compressed Air System Analysis and Retrofit for Energy Savings Texas A&M University - TxSpace Summary: This case...

  4. Thermodynamic Analysis of Combined Cycle District Heating System

    E-Print Network [OSTI]

    Suresh, S.; Gopalakrishnan, H.; Kosanovic, D.

    2011-01-01T23:59:59.000Z

    This paper presents a thermodynamic analysis of the University of Massachusetts' Combined Heat and Power (CHP) District Heating System. Energy and exergy analyses are performed based on the first and second laws of thermodynamics for power...

  5. Modeling and Analysis of CSP Systems (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2010-08-01T23:59:59.000Z

    Fact sheet describing NREL CSP Program capabilities in the area of modeling and analysis of CSP systems: assessing the solar resource, predicting performance and cost, studying environmental impact, and developing modeling software packages.

  6. Complete VAX/VMS DNA/protein sequence analysis system

    SciTech Connect (OSTI)

    Smith, D.W.

    1987-05-01T23:59:59.000Z

    A complete yet flexible system of programs and database libraries for analysis of DNA, RNA and protein sequences is implemented for VAX/VMS computers. Types of analysis include 1) construction and analysis of chimeric sequences (cloning in the VAX), 2) multiple analysis of one or more single sequences, 3) search and comparison studies using sequence libraries, and 4) direct input and analysis of experimental data. Published groups of programs, including the Staden, Los Alamos, Zuker, Pearson, and PHYLIP programs, are used. GenBank and EMBL DNA libraries and PIR and Doolittle NEWAT protein libraries are available, with associated programs. The system is tutorial, with online documentation for relevent VAX software, the programs, and the databases. The complete documentation is flexibly maintained on reserve via computer printout placed in 3-ring binders. Command files are used extensively; porting of the entire system to another VAX/VMS system requires modification of a single command. Users of the system are members of a VAX group, with automatic implementation of the system upon login. The present system occupies about 140,000 blocks, and is easily expanded, or contracted, as desired. The UCSD system is used extensively for both teaching and research purposes. Use of microcomputers emulating Tektronix 4014 graphics terminals permits saving of graphics output to disk for subsequent modification to generate high quality publishable figures.

  7. Analysis of Lyapunov Method for Control of Quantum Systems

    E-Print Network [OSTI]

    Xiaoting Wang; Sonia G. Schirmer

    2008-05-19T23:59:59.000Z

    We present a detailed analysis of the convergence properties of Lyapunov control for finite-dimensional quantum systems based on the application of the LaSalle invariance principle and stability analysis from dynamical systems and control theory. For a certain class of ideal Hamiltonians, convergence results are derived both pure-state and mixed-state control, and the effectiveness of the method for more realistic Hamiltonians is discussed.

  8. A simplified system of pressure surfaces for atmospheric analysis 

    E-Print Network [OSTI]

    Shay, Francis Schofield

    1959-01-01T23:59:59.000Z

    LIBRARY A g M COLLEGE OF TEXAS A SIMPLIFIED SYSTEM OF PRESSURE SURFACES FOR ATMOSPHERIC ANALYSIS A Thesis By FRANCIS S. SHAY + Captain USAF Submitted to the Graduate School of the Agricultural and Mechanical College of Texas in partial... fulfillment of the requirements for the degree of MASTER OP SCIENCE May 1959 Major Subject: Meteorology A SIMPLIFIED SYSTEM OF PRESSURE SURFACES FOR ATMOSPHERIC ANALYSIS A Thesis By FRANCIS S. SHAY Captain USAF jpp roved j as to style and content...

  9. Unit hydrograph application to stormwater collection system design and analysis

    E-Print Network [OSTI]

    Spinks, Melvin Gerald

    1987-01-01T23:59:59.000Z

    review of each model studied and its capabilities follows. Storm Water Management Model. ? The Storm Water Management Model (SWMM) was developed by the United States Environmental Protection Agency for the analysis of urban stormwater runoff... backwater analysis option uses the Direct Step Method to compute the water surface profiles in the storm sewer system. Two case studies with complex stormwater collection systems were modeled to verify and validate the hydrologic and hydraulic methods...

  10. Combined elevated pressure reactor and ultrahigh vacuum surface analysis system

    E-Print Network [OSTI]

    Goodman, Wayne

    Combined elevated pressure reactor and ultrahigh vacuum surface analysis system J&IOS Szanyi and D 19 February 1993; accepted for publication 20 April 1993) A combined elevated pressure reactor. The reaction cell is separated from the surface analysis chamber by a differentially pumped sliding seal

  11. Exploiting Behavior Models for Availability Analysis of Interactive Systems

    E-Print Network [OSTI]

    Cengarle, María Victoria

    Exploiting Behavior Models for Availability Analysis of Interactive Systems Maximilian Junker Technische Universit¨at M¨unchen Abstract--We propose an approach for availability analysis that directly are reduced effort as no dedicated availability models need to be created as well as precise results due

  12. Systems reliability analysis for the national ignition facility

    SciTech Connect (OSTI)

    Majumdar, K.C.; Annese, C.E.; MacIntyre, A.T.; Sicherman, A.

    1996-06-12T23:59:59.000Z

    A Reliability, Availability and Maintainability (RAM) analysis was initiated for the National Ignition Facility (NIF). The NIF is an inertial confinement fusion research facility designed to achieve controlled thermonuclear reaction; the preferred site for the NIF is the Lawrence Livermore National Laboratory (LLNL). The NIF RAM analysis has three purposes: (1) to allocate top level reliability and availability goals for the systems, (2) to develop an operability model for optimum maintainability, and (3) to determine the achievability of the allocated goals of the RAM parameters for the NIF systems and the facility operation as a whole. An allocation model assigns the reliability and availability goals for front line and support systems by a top-down approach; reliability analysis uses a bottom-up approach to determine the system reliability and availability from component level to system level.

  13. Modeling and analysis of energy conversion systems

    SciTech Connect (OSTI)

    Den Braven, K.R. (Idaho Univ., Moscow, ID (USA). Dept. of Mechanical Engineering); Stanger, S. (EG and G Idaho, Inc., Idaho Falls, ID (USA))

    1990-10-01T23:59:59.000Z

    An investigation was conducted to assess the need for and the feasibility of developing a computer code that could model thermodynamic systems and predict the performance of energy conversion systems. To assess the market need for this code, representatives of a few industrial organizations were contacted, including manufacturers, system and component designers, and research personnel. Researchers and small manufacturers, designers, and installers were very interested in the possibility of using the proposed code. However, large companies were satisfied with the existing codes that they have developed for their own use. Also, a survey was conduced of available codes that could be used or possibly modified for the desired purpose. The codes were evaluated with respect to a list of desirable features, which was prepared as a result of the survey. A few publicly available codes were found that might be suitable. The development, verification, and maintenance of such a code would require a substantial, ongoing effort. 21 refs.

  14. A Taxonomy and Evaluation for Systems Analysis Methodologies in a Workflow Context: Structured Systems

    E-Print Network [OSTI]

    Newcastle upon Tyne, University of

    Systems Analysis Design Method (SSADM), Unified Modelling Language (UML), Unified Process, Soft Systems taxonomy dealing with both hard- and soft-system aspects. The results show that there is no methodology that covers all of the taxonomic aspects identified. Organisational Process Modelling (OPM) and Soft Systems

  15. Reachability Analysis of a Biodiesel Production System Using Stochastic Hybrid Systems

    E-Print Network [OSTI]

    Koutsoukos, Xenofon D.

    Reachability Analysis of a Biodiesel Production System Using Stochastic Hybrid Systems Derek Riley defines the creation of biodiesel from soybean oil and methanol. Modeling and analyzing the biodiesel. In this paper we model a biodiesel production system as a stochastic hybrid system, and we present

  16. Dynamical Systems and Applications of Nonlinear Functional Analysis to Dynamical Systems

    E-Print Network [OSTI]

    Zhang, Meirong

    Dynamical Systems and Applications of Nonlinear Functional Analysis to Dynamical Systems Meirong consists of three parts. In Part 1 we introduce some basic concepts in dynamical systems, including limit sets, nonwandering sets, topological conjugacy, clas- sification of discrete dynamical systems under

  17. Multi Megawatt Power System Analysis Report

    SciTech Connect (OSTI)

    Longhurst, Glen Reed; Harvego, Edwin Allan; Schnitzler, Bruce Gordon; Seifert, Gary Dean; Sharpe, John Phillip; Verrill, Donald Alan; Watts, Kenneth Donald; Parks, Benjamin Travis

    2001-11-01T23:59:59.000Z

    Missions to the outer planets or to near-by planets requiring short times and/or increased payload carrying capability will benefit from nuclear power. A concept study was undertaken to evaluate options for a multi-megawatt power source for nuclear electric propulsion. The nominal electric power requirement was set at 15 MWe with an assumed mission profile of 120 days at full power, 60 days in hot standby, and another 120 days of full power, repeated several times for 7 years of service. Of the numerous options considered, two that appeared to have the greatest promise were a gas-cooled reactor based on the NERVA Derivative design, operating a closed cycle Brayton power conversion system; and a molten lithium-cooled reactor based on SP-100 technology, driving a boiling potassium Rankine power conversion system. This study examined the relative merits of these two systems, seeking to optimize the specific mass. Conclusions were that either concept appeared capable of approaching the specific mass goal of 3-5 kg/kWe estimated to be needed for this class of mission, though neither could be realized without substantial development in reactor fuels technology, thermal radiator mass efficiency, and power conversion and distribution electronics and systems capable of operating at high temperatures. Though the gas-Brayton systems showed an apparent advantage in specific mass, differences in the degree of conservatism inherent in the models used suggests expectations for the two approaches may be similar. Brayton systems eliminate the need to deal with two-phase flows in the microgravity environment of space.

  18. Analysis of a laser projection system

    E-Print Network [OSTI]

    Vangala, Prabhakar Srinivas

    1990-01-01T23:59:59.000Z

    in the various transforination parameters on the final beam location and data, indicating the results. Gatvanometers YO t aser Laser Or Global Coordinate System XO rilrr ors ZO Reflected Laser Beam SD PSD Internal Ply X Tool Or Fixture Y Coordinate... (D) ddt. 1 ? dtt, dy detr dd 1 d 0 0 0 1 Z2 Y2 Fixture Position 2 X2 ; ixture Position 1 X1 [T2 l YO Zi i aser Coordinate System ZO Figure T. Differential Transformation The Translational and Rotational errors can then be calculated...

  19. Energy Engineering & Systems Analysis Success Stories

    E-Print Network [OSTI]

    Kemner, Ken

    of increasing heat fluxes and power loads in applications as diverse as medical equipment, power electronics, improve energy efficiency and lengthen device lifetime. To satisfy these increasing thermal management for engine or power electronics thermal management. However, these systems contribute to the size and weight

  20. Analysis of LNG peakshaving-facility release-prevention systems

    SciTech Connect (OSTI)

    Pelto, P.J.; Baker, E.G.; Powers, T.B.; Schreiber, A.M.; Hobbs, J.M.; Daling, P.M.

    1982-05-01T23:59:59.000Z

    The purpose of this study is to provide an analysis of release prevention systems for a reference LNG peakshaving facility. An overview assessment of the reference peakshaving facility, which preceeded this effort, identified 14 release scenarios which are typical of the potential hazards involved in the operation of LNG peakshaving facilities. These scenarios formed the basis for this more detailed study. Failure modes and effects analysis and fault tree analysis were used to estimate the expected frequency of each release scenario for the reference peakshaving facility. In addition, the effectiveness of release prevention, release detection, and release control systems were evaluated.

  1. The TROPOS Analysis Process as Graph Transformation System Paolo Bresciani

    E-Print Network [OSTI]

    Trento-Povo, Italy Abstract Tropos is an agent-oriented methodology that covers soft- ware developmentThe TROPOS Analysis Process as Graph Transformation System Paolo Bresciani ITC-irst via Sommarive of the operational environment of the new software system. In earlier work we have characterized the process of early

  2. Preventing power outages Power system contingency analysis on the GPU

    E-Print Network [OSTI]

    Vuik, Kees

    problem. Moreover, the power system has to keep functioning properly even when a transmission line failsPreventing power outages Power system contingency analysis on the GPU To provide electricity generators, nuclear power plants, wind turbines, etc.) and a network of lines and cables to transmit

  3. Thermodynamic Analysis of Combined Cycle District Heating System 

    E-Print Network [OSTI]

    Suresh, S.; Gopalakrishnan, H.; Kosanovic, D.

    2011-01-01T23:59:59.000Z

    generation systems that include a 10 MW Solar combustion gas turbine, a 4-MW steam turbine, a 100,000 pph heat recovery steam generator (HRSG), three 125,000 pph package boilers, and auxiliary equipment. In the analysis, actual system data is used to assess...

  4. EXERGETIC ANALYSIS OF A STEAM-FLASHING THERMAL STORAGE SYSTEM

    E-Print Network [OSTI]

    Abstract Thermal energy storage is attractive in the design of concentrator solar thermal systems because-scale thermal energy storage via hot compressed liquid water. Such a cycle is potentially interesting becauseEXERGETIC ANALYSIS OF A STEAM-FLASHING THERMAL STORAGE SYSTEM Paul T. O'Brien 1 , and John Pye 2 1

  5. Preliminary Findings from an Analysis of Building Energy Information System

    E-Print Network [OSTI]

    -based energy monitoring, web-based energy management linked to controls, demand response, and enterprise energyLBNL-2224E Preliminary Findings from an Analysis of Building Energy Information System Technologies of Building Energy Information System Technologies Jessica Granderson Mary Ann Piette Girish Ghatikar Phillip

  6. Cyber Threat Trees for Large System Threat Cataloging and Analysis*

    E-Print Network [OSTI]

    Thornton, Mitchell

    Cyber Threat Trees for Large System Threat Cataloging and Analysis* P. Ongsakorn, K. Turney, M, kturney, mitch, nair, szygenda, manikas}@lyle.smu.edu Abstract--The implementation of cyber threat. Because large systems have many possible threats that may be interdependent, it is crucial

  7. Information-Theoretic Analysis of an Energy Harvesting Communication System

    E-Print Network [OSTI]

    Ulukus, Sennur

    Information-Theoretic Analysis of an Energy Harvesting Communication System Omur Ozel Sennur Ulukus@umd.edu ulukus@umd.edu Abstract--In energy harvesting communication systems, an exogenous recharge process supplies energy for the data trans- mission and arriving energy can be buffered in a battery before

  8. Building integrated photovoltaic systems analysis: Preliminary report

    SciTech Connect (OSTI)

    none,

    1993-08-01T23:59:59.000Z

    The National Renewable Energy Laboratory (NREL) has estimated that the deployment of photovoltaics (PV) in the commercial buildings sector has the potential to contribute as much as 40 gigawatts peak electrical generation capacity and displace up to 1.1 quads of primary fuel use. A significant portion of this potential exists for smaller buildings under 25,000 square feet (2,300 square meters) in size or two stories or less, providing a strong cross over potential for residential applications as well. To begin to achieve this potential, research is needed to define the appropriate match of PV systems to energy end-uses in the commercial building sector. This report presents preliminary findings for a technical assessment of several alternative paths to integrate PV with building energy systems.

  9. NREL: Transportation Research - Systems Analysis and Integration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for Renewable Energy: Grid IntegrationReportTransmissionResearchNews NRELSuccessSystems

  10. Multiple stellar systems under photometric and astrometric analysis

    E-Print Network [OSTI]

    P. Zasche

    2008-01-28T23:59:59.000Z

    The light-time effect method, its limitations and applications were studied. A powerful combined method of simultaneous analysis of the O-C diagrams and astrometric orbit in triple eclipsing-astrometric binaries was presented. Eleven eclipsing systems were studied in detail according to their O-C diagrams (RY Aqr, BF CMi, RW Cap, TY Cap, SS Cet, RR Dra, TY Del, TZ Eri, RV Per, UZ Sge, and BO Vul). The introduced method for studying the astrometric-eclipsing binaries was applied to QS Aql, VW Cep, Zeta Phe, V505 Sgr, HT Vir, and V2388 Oph. The algorithm for such an analysis was introduced and the its limitations were discussed. The catalogue of another systems, which contain eclipsing binaries in astrometric binaries, was presented. Such systems could be useful for prospective analysis. The method itself could be easily modified for estimation of the parallax of the individual systems.

  11. Task 11 - systems analysis of environmental management technologies

    SciTech Connect (OSTI)

    Musich, M.A.

    1997-06-01T23:59:59.000Z

    A review was conducted of three systems analysis (SA) studies performed by Lockheed Idaho Technologies Company (LITCO) on integrated thermal treatment systems (ITTs) and integrated nonthermal treatment systems (INTSs) for the remediation of mixed low-level waste (MLLW) stored throughout the U.S. Department of Energy (DOE) weapons complex. The review was performed by an independent team led by the Energy & Environment Research Center (EERC), including Science Applications International Corporation (SAIC), the Waste Policy Institute (WPI), and Virginia Tech.

  12. System Analysis Success Stories | Department of Energy

    Office of Environmental Management (EM)

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

  13. Policy Analysis System (Polysys) | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluatingGroupPerfectenergyInformation to Reduce Emissions from theSystem (Polysys)

  14. Ground Source Heat Pump System Data Analysis

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't YourTransport(Fact Sheet), GeothermalGrid Integration and the CarryingPeer Review GSHP System

  15. Pump Life Cycle Costs: A Guide to LCC Analysis for Pumping Systems...

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

    Life Cycle Costs: A Guide to LCC Analysis for Pumping Systems - Executive Summary Pump Life Cycle Costs: A Guide to LCC Analysis for Pumping Systems - Executive Summary This...

  16. Function analysis for waste information systems

    SciTech Connect (OSTI)

    Sexton, J.L.; Neal, C.T.; Heath, T.C.; Starling, C.D.

    1996-04-01T23:59:59.000Z

    This study has a two-fold purpose. It seeks to identify the functional requirements of a waste tracking information system and to find feasible alternatives for meeting those requirements on the Oak Ridge Reservation (ORR) and the Portsmouth (PORTS) and Paducah (PGDP) facilities; identify options that offer potential cost savings to the US government and also show opportunities for improved efficiency and effectiveness in managing waste information; and, finally, to recommend a practical course of action that can be immediately initiated. In addition to identifying relevant requirements, it also identifies any existing requirements that are currently not being completely met. Another aim of this study is to carry out preliminary benchmarking by contacting representative companies about their strategic directions in waste information. The information obtained from representatives of these organizations is contained in an appendix to the document; a full benchmarking effort, however, is beyond the intended scope of this study.

  17. Earthquake warning system for infrastructures : a scoping analysis.

    SciTech Connect (OSTI)

    Brodsky, Nancy S.; O'Connor, Sharon L.; Stamber, Kevin Louis; Kelic, Andjelka; Fogleman, William E. (GRIT, Inc., Albuquerque, NM); Vugrin, Eric D.; Corbet, Thomas Frank, Jr.; Brown, Theresa Jean

    2011-09-01T23:59:59.000Z

    This report provides the results of a scoping study evaluating the potential risk reduction value of a hypothetical, earthquake early-warning system. The study was based on an analysis of the actions that could be taken to reduce risks to population and infrastructures, how much time would be required to take each action and the potential consequences of false alarms given the nature of the action. The results of the scoping analysis indicate that risks could be reduced through improving existing event notification systems and individual responses to the notification; and production and utilization of more detailed risk maps for local planning. Detailed maps and training programs, based on existing knowledge of geologic conditions and processes, would reduce uncertainty in the consequence portion of the risk analysis. Uncertainties in the timing, magnitude and location of earthquakes and the potential impacts of false alarms will present major challenges to the value of an early-warning system.

  18. Life cycle analysis of energy systems: Methods and experience

    SciTech Connect (OSTI)

    Morris, S.C.

    1992-08-01T23:59:59.000Z

    Fuel-cycle analysis if not the same as life-cycle analysis, although the focus on defining a comprehensive system for analysis leads toward the same path. This approach was the basis of the Brookhaven Reference Energy System. It provided a framework for summing total effects over an explicitly defined fuel cycle. This concept was computerized and coupled with an extensive data base in ESNS -- the Energy Systems Network Simulator. As an example, ESNS was the analytical basis for a comparison of health and environmental effects of several coal conversion technologies. With advances in computer systems and methods, however, ESNS has not been maintained at Brookhaven. The RES approach was one of the bases of the OECD COMPASS Project and the UNEP comparative assessment of environmental impacts of energy sources. An RES model alone has limitations in analyzing complex energy systems, e.g., it is difficult to handle feedback in the network. The most recent version of a series of optimization models is MARKAL, a dynamic linear programming model now used to assess strategies to reduce greenhouse gas emissions from the energy system. MARKAL creates an optimal set of reference energy systems over multiple time periods, automatically incorporating dynamic feedback and allowing fuel switching and end-use conservation to meet useful energy demands.

  19. Life cycle analysis of energy systems: Methods and experience

    SciTech Connect (OSTI)

    Morris, S.C.

    1992-01-01T23:59:59.000Z

    Fuel-cycle analysis if not the same as life-cycle analysis, although the focus on defining a comprehensive system for analysis leads toward the same path. This approach was the basis of the Brookhaven Reference Energy System. It provided a framework for summing total effects over an explicitly defined fuel cycle. This concept was computerized and coupled with an extensive data base in ESNS -- the Energy Systems Network Simulator. As an example, ESNS was the analytical basis for a comparison of health and environmental effects of several coal conversion technologies. With advances in computer systems and methods, however, ESNS has not been maintained at Brookhaven. The RES approach was one of the bases of the OECD COMPASS Project and the UNEP comparative assessment of environmental impacts of energy sources. An RES model alone has limitations in analyzing complex energy systems, e.g., it is difficult to handle feedback in the network. The most recent version of a series of optimization models is MARKAL, a dynamic linear programming model now used to assess strategies to reduce greenhouse gas emissions from the energy system. MARKAL creates an optimal set of reference energy systems over multiple time periods, automatically incorporating dynamic feedback and allowing fuel switching and end-use conservation to meet useful energy demands.

  20. Active cooling for downhole instrumentation: Preliminary analysis and system selection

    SciTech Connect (OSTI)

    Bennett, G.A.

    1988-03-01T23:59:59.000Z

    A feasibility study and a series of preliminary designs and analyses were done to identify candidate processes or cycles for use in active cooling systems for downhole electronic instruments. A matrix of energy types and their possible combinations was developed and the energy conversion process for each pari was identified. The feasibility study revealed conventional as well as unconventional processes and possible refrigerants and identified parameters needing further clarifications. A conceptual design or series od oesigns for each system was formulated and a preliminary analysis of each design was completed. The resulting coefficient of performance for each system was compared with the Carnot COP and all systems were ranked by decreasing COP. The system showing the best combination of COP, exchangeability to other operating conditions, failure mode, and system serviceability is chosen for use as a downhole refrigerator. 85 refs., 48 figs., 33 tabs.

  1. Macro-System Model for Hydrogen Energy Systems Analysis in Transportation: Preprint

    SciTech Connect (OSTI)

    Diakov, V.; Ruth, M.; Sa, T. J.; Goldsby, M. E.

    2012-06-01T23:59:59.000Z

    The Hydrogen Macro System Model (MSM) is a simulation tool that links existing and emerging hydrogen-related models to perform rapid, cross-cutting analysis. It allows analysis of the economics, primary energy-source requirements, and emissions of hydrogen production and delivery pathways.

  2. Introduction to Geographic Information System (GIS) and Geospatial Analysis Instructor: Dr. I-Kuai Hung

    E-Print Network [OSTI]

    Hung, I-Kuai

    GIS 551 Introduction to Geographic Information System (GIS) and Geospatial Analysis Fall 2010 Outcomes: Students will demonstrate competency in the fundamentals of GIS and geospatial analysis system for the management, analysis, and display of geographic information. GIS includes a set

  3. Business Systems Analysis With ever increasing amounts of data, organizations are identifying

    E-Print Network [OSTI]

    Miles, Will

    , business systems analysis and design, enterprise resource planning, project management and business process Institute of Business Analysis, SAP, the Project Management InBusiness Systems Analysis With ever increasing amounts of data, organizations are identifying

  4. Societal Research Archives System : Retrieval, quality control and analysis

    E-Print Network [OSTI]

    White, Douglas R.

    Societal Research Archives System : Retrieval, quality control and analysis of comparative data sample selection and data retrieval to correlation, data quality control, and testing for genetic, and White, 1967a). This represents 40 % of the approximate total number of such publications, but over 90

  5. Development of a Clinical Pathways Analysis System with Adaptive Bayesian

    E-Print Network [OSTI]

    Kopec, Danny

    Development of a Clinical Pathways Analysis System with Adaptive Bayesian Nets and Data Mining such analyses. The computation of "lift" (a measure of completed pathways improvement potential) leads us an artificial set of such records and use these for clinical pathways analyses. We use data mining software

  6. Wind Energy Conversion Systems Fault Diagnosis Using Wavelet Analysis

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Wind Energy Conversion Systems Fault Diagnosis Using Wavelet Analysis Elie Al-Ahmar1,2 , Mohamed El, induction generator, Discrete Wavelet Transform (DWT), failure diagnosis. I. Introduction Wind energy the condition of induction machines. Fig. 1. Worldwide growth of wind energy installed capacity [1]. 1 E. Al

  7. A DESIGN AND ANALYSIS TOOL FOR SOLAR ELECTRIC SYSTEMS

    E-Print Network [OSTI]

    Delaware, University of

    PV PLANNER A DESIGN AND ANALYSIS TOOL FOR SOLAR ELECTRIC SYSTEMS Updated User Manual May 2011 University of Delaware #12;Mailing Address: John Byrne Director Center for Energy and Environmental Policy) 831-3098 Website: http://ceep.udel.edu The Center for Energy and Environmental Policy conducts

  8. An Analysis of Heterogeneity in Futuristic Unmanned Vehicle Systems

    E-Print Network [OSTI]

    Cummings, Mary "Missy"

    and with enough automation aboard unmanned vehicles, inverting the multiple operators to single-vehicle control1 An Analysis of Heterogeneity in Futuristic Unmanned Vehicle Systems C.E. NEHME M.L. CUMMINGS paradigm is possible. These studies, however, have generally focused on homogeneous teams of vehicles

  9. Patent systems for encouraging innovation: Lessons from economic analysis1

    E-Print Network [OSTI]

    Boyer, Edmond

    1 Patent systems for encouraging innovation: Lessons from economic analysis1 David ENCAOUA (EUREQua version submitted October 2003) Abstract Economic theory views patents as policy instruments aimed. First, patents may not be the most effective means of protection for inventors to recover R

  10. Methods for air cleaning system design and accident analysis

    SciTech Connect (OSTI)

    Gregory, W.S.; Nichols, B.D.

    1986-01-01T23:59:59.000Z

    This paper describes methods, in the form of a handbook and five computer codes, that can be used for air cleaning system design and accident analysis. Four of the codes were developed primarily at the Los Alamos National Laboratory, and one was developed in France. Tools such as these are used to design ventilation systems in the mining industry but do not seem to be commonly used in the nuclear industry. For example, the Nuclear Air Cleaning Handbook is an excellent design reference, but it fails to include information on computer codes that can be used to aid in the design process. These computer codes allow the analyst to use the handbook information to form all the elements of a complete system design. Because these analysis methods are in the form of computer codes, they allow the analyst to investigate many alternative designs. In addition, the effects of many accident scenarios on the operation of the air cleaning system can be evaluated. These tools originally were intended for accident analysis, but they have been used mostly as design tools by several architect-engineering firms. The Cray, VAX, and personal computer versions of the codes, an accident analysis handbook, and the codes' availability will be discussed. The application of these codes to several design operations of nuclear facilities will be illustrated, and their use to analyze the effect of several accident scenarios also will be described.

  11. Transportation Policy Analysis and Systems Planning Fall 2009/2010

    E-Print Network [OSTI]

    Singh, Jaswinder Pal

    SYLLABUS WWS 527a Transportation Policy Analysis and Systems Planning Fall 2009/2010 Course Description Part 1. Perspective on the Transportation Sector of the Economy: Its Function, Its Players, Its of Course Elements of the transportation sector of the economy, the player, the technologies

  12. Analysis of Preventive Maintenance in Transactions Based Software Systems

    E-Print Network [OSTI]

    Telek, Miklós

    Analysis of Preventive Maintenance in Transactions Based Software Systems Sachin Garg 1 , Antonio''. However, it incurs some overhead. The necessity to do preventive maintenance not only in general purpose to illustrate the usefulness and applicability of the models. Keywords: Preventive Maintenance, Transactions

  13. Charles J. Vrsmarty & the UNH Water Systems Analysis Group

    E-Print Network [OSTI]

    Slatton, Clint

    .1 billion people lack clean drinking water 2.6 billion people lack basic sanitationCharles J. Vörösmarty & the UNH Water Systems Analysis Group Fall Water Institute Seminar Series Corridor #12;Goals for This Discussion · Describe chief forces shaping the contemporary and future water

  14. Selection of wavelets for analysis of power system disturbances

    E-Print Network [OSTI]

    Todorovic, Milos

    2002-01-01T23:59:59.000Z

    system applications . . . . . . . . . . . . . . 4 C. Summary, . 7 II WAVELET TRANSFORM . A. Introduction . . B. Wavelet transform and multiresolution analysis . . . C. Characteristic properties of wavelets. D. Summary . . . . . . . . 8... algorithm. . . . . . . I 3 3. Two-channel perfect reconstruction filter . . . 14 4. Typical voltage swell waveform. . . . . . . 22 5. Typical voltage sag waveform. . . . . 24 6. Typical voltage transinet disturbance waveform . . 7. Typical power...

  15. Hydrogen Storage Systems Analysis Working Group Meeting Argonne DC Offices

    E-Print Network [OSTI]

    Hydrogen Storage Systems Analysis Working Group Meeting Argonne DC Offices L'Enfant Plaza, Washington, DC December 4, 2007 SUMMARY REPORT Compiled by Romesh Kumar Argonne National Laboratory Working Group Meeting December 4, 2007 Argonne DC Offices, L'Enfant Plaza, Washington, DC Meeting

  16. Rewriting Modulo SMT and Open System Analysis Camilo Rocha1

    E-Print Network [OSTI]

    Muñoz, César A.

    Rewriting Modulo SMT and Open System Analysis Camilo Rocha1 , José Meseguer2 , and César Muñoz3, USA NASA Langley Research Center, Hampton VA, USA Abstract. This paper proposes rewriting modulo SMT, a new technique that combines the power of SMT solving, rewriting modulo theories, and model check- ing

  17. Response margins of the dynamic analysis of piping systems

    SciTech Connect (OSTI)

    Johnson, J.J.; Benda, B.J.; Chuang, T.Y.; Smith, P.D.

    1984-04-01T23:59:59.000Z

    This report is organized as follows: Section 2 describes the three piping systems of the Zion nuclear power plant which formed the basis of the present study. The auxiliary feedwater (AFW) piping from steam generator to containment, the residual heat removal (RHR) and safety injection piping in the auxiliary building, and the reactor coolant loops (RCL) including a portion of the branch lines were analyzed. Section 3 describes the analysis methods and the analyses performed. Section 4 presents the numerical results; the principal results presented as comparisons of response calculated by best estimate time history analysis methods vs. the SRP response spectrum technique. Section 5 draws conclusions from the results. Appendix A contains a brief description of the mathematical models that defined the structures containing the three piping systems. Response from these models provided input to the piping models. Appendix B provides a detailed derivation of the pseudostatic mode approach to the multisupport time history analysis method used in this study.

  18. Game theoretic analysis of physical protection system design

    SciTech Connect (OSTI)

    Canion, B.; Schneider, E. [Nuclear and Radiation Engineering Program, University of Texas, 204 E. Dean Keeton Street, Stop C2200, Austin, TX 78712 (United States); Bickel, E.; Hadlock, C.; Morton, D. [Operations Research Program, University of Texas, 204 E. Dean Keeton Street, Stop C2200, Austin, TX 78712 (United States)

    2013-07-01T23:59:59.000Z

    The physical protection system (PPS) of a fictional small modular reactor (SMR) facility have been modeled as a platform for a game theoretic approach to security decision analysis. To demonstrate the game theoretic approach, a rational adversary with complete knowledge of the facility has been modeled attempting a sabotage attack. The adversary adjusts his decisions in response to investments made by the defender to enhance the security measures. This can lead to a conservative physical protection system design. Since defender upgrades were limited by a budget, cost benefit analysis may be conducted upon security upgrades. One approach to cost benefit analysis is the efficient frontier, which depicts the reduction in expected consequence per incremental increase in the security budget.

  19. Time Series Analysis of Aviation Dr. Richard Xie

    E-Print Network [OSTI]

    is free · R is a language, not just a statistical tool · R makes graphics and visualization of the best, Mathematica, Maple ­ SAS, SPSS, STATA, R ­ ROOT, PAW, KNIME, Data Applied, etc. ­ Others #12;Use R! · R quality · A flexible statistical analysis toolkit · Access to powerful, cutting-edge analytics · A robust

  20. Control sensitivity indices for stability analysis of HVdc systems

    SciTech Connect (OSTI)

    Nayak, O.B.; Gole, A.M. [Univ. of Manitoba, Winnipeg, Manitoba (Canada)] [Univ. of Manitoba, Winnipeg, Manitoba (Canada); Chapman, D.G.; Davies, J.B. [Manitoba Hydro, Winnipeg, Manitoba (Canada)] [Manitoba Hydro, Winnipeg, Manitoba (Canada)

    1995-10-01T23:59:59.000Z

    This paper presents a new concept called the ``Control Sensitivity Index`` of CSI, for the stability analysis of HVdc converters connected to weak ac systems. The CSI for a particular control mode can be defined as the ratio of incremental changes in the two system variables that are most relevant to that control mode. The index provides valuable information on the stability of the system and, unlike other approaches, aids in the design of the controller. It also plays an important role in defining non-linear gains for the controller. This paper offers a generalized formulation of CSI and demonstrates its application through an analysis of the CSI for three modes of HVdc control. The conclusions drawn from the analysis are confirmed by a detailed electromagnetic transients simulation of the ac/dc system. The paper concludes that the CSI can be used to improve the controller design and, for an inverter in a weak ac system, the conventional voltage control mode is more stable than the conventional {gamma} control mode.

  1. NREL, CENTER FOR TRANSPORTATION TECHNOLOGIES AND SYSTEMS 1 Fuel Cell Vehicle Systems Analysis

    E-Print Network [OSTI]

    at 2003 Future Transportation Technology Conference 7/03* Expand database of fuel cell components 9NREL, CENTER FOR TRANSPORTATION TECHNOLOGIES AND SYSTEMS 1 Fuel Cell Vehicle Systems Analysis Tony Markel, Keith Wipke, Kristina Haraldsson, Ken Kelly, Andreas Vlahinos National Renewable Energy

  2. Application of System-Theoretic Process Analysis to Engineered Safety Features-Component Control System

    E-Print Network [OSTI]

    techniques identify. 1. Introduction Recent developments in safety-critical systems, such as nuclear powerC5.7 Application of System-Theoretic Process Analysis to Engineered Safety Features of Korea b,c Korea Atomic Energy Research Institute, 150 Deokjin, Yuseong Daejeon, 305-335, Republic

  3. Precursor Systems Analysis of Automated Highway Systems Activity Area J--Entry/Exit Implementation

    E-Print Network [OSTI]

    Varaiya, Pravin

    Precursor Systems Analysis of Automated Highway Systems Activity Area J--Entry/Exit Implementation This is the final report of a study of the following issues in the implementation of entry and exit in an Automated dedicated ramps; ffl Communication protocols for coordinating entry and exit maneuvers, and lateral

  4. GCtool for fuel cell systems design and analysis : user documentation.

    SciTech Connect (OSTI)

    Ahluwalia, R.K.; Geyer, H.K.

    1999-01-15T23:59:59.000Z

    GCtool is a comprehensive system design and analysis tool for fuel cell and other power systems. A user can analyze any configuration of component modules and flows under steady-state or dynamic conditions. Component models can be arbitrarily complex in modeling sophistication and new models can be added easily by the user. GCtool also treats arbitrary system constraints over part or all of the system, including the specification of nonlinear objective functions to be minimized subject to nonlinear, equality or inequality constraints. This document describes the essential features of the interpreted language and the window-based GCtool environment. The system components incorporated into GCtool include a gas flow mixer, splitier, heater, compressor, gas turbine, heat exchanger, pump, pipe, diffuser, nozzle, steam drum, feed water heater, combustor, chemical reactor, condenser, fuel cells (proton exchange membrane, solid oxide, phosphoric acid, and molten carbonate), shaft, generator, motor, and methanol steam reformer. Several examples of system analysis at various levels of complexity are presented. Also given are instructions for generating two- and three-dimensional plots of data and the details of interfacing new models to GCtool.

  5. Heat transfer analysis capabilities of the scale computational system

    SciTech Connect (OSTI)

    Parks, C.V.; Giles, G.E.; Childs, K.W.; Bryan, C.B.

    1986-01-01T23:59:59.000Z

    The heat transfer capabilities within the modular SCALE computational system are centered about the HEATING6 functional module. This paper reviews the features and modeling capabilities of HEATING6, discusses the supportive plotting capabilities of REGPLOT6 and HEATPLOT-S, and finally provides a general description of the Heat Transfer Analysis Sequence No.1 (HTASI) available in SCALE for performing thermal analyses of transport casks via HEATING6. The HTASI control module is an easy-to-use tool that allows an inexperienced HEATING6 user to obtain reliable thermal analysis results. A summary of the recent verification efforts undertaken for HEATING6 is also provided. 16 refs., 14 figs.

  6. PVUSA instrumentation and data analysis techniques for photovoltaic systems

    SciTech Connect (OSTI)

    Newmiller, J.; Hutchinson, P.; Townsend, T.; Whitaker, C.

    1995-10-01T23:59:59.000Z

    The Photovoltaics for Utility Scale Applications (PVUSA) project tests two types of PV systems at the main test site in Davis, California: new module technologies fielded as 20-kW Emerging Module Technology (EMT) arrays and more mature technologies fielded as 70- to 500-kW turnkey Utility-Scale (US) systems. PVUSA members have also installed systems in their service areas. Designed appropriately, data acquisition systems (DASs) can be a convenient and reliable means of assessing system performance, value, and health. Improperly designed, they can be complicated, difficult to use and maintain, and provide data of questionable validity. This report documents PVUSA PV system instrumentation and data analysis techniques and lessons learned. The report is intended to assist utility engineers, PV system designers, and project managers in establishing an objective, then, through a logical series of topics, facilitate selection and design of a DAS to meet the objective. Report sections include Performance Reporting Objectives (including operational versus research DAS), Recommended Measurements, Measurement Techniques, Calibration Issues, and Data Processing and Analysis Techniques. Conclusions and recommendations based on the several years of operation and performance monitoring are offered. This report is one in a series of 1994--1995 PVUSA reports documenting PVUSA lessons learned at the demonstration sites in Davis and Kerman, California. Other topical reports address: five-year assessment of EMTs; validation of the Kerman 500-kW grid support PV plant benefits; construction and safety experience in installing and operating PV systems; balance-of-system design and costs; procurement, acceptance, and rating practices for PV power plants; experience with power conditioning units and power quality.

  7. Safety analysis report for packaging (onsite) doorstop samplecarrier system

    SciTech Connect (OSTI)

    Obrien, J.H.

    1997-02-24T23:59:59.000Z

    The Doorstop Sample Carrier System consists of a Type B certified N-55 overpack, U.S. Department of Transportation (DOT) specification or performance-oriented 208-L (55-gal) drum (DOT 208-L drum), and Doorstop containers. The purpose of the Doorstop Sample Carrier System is to transport samples onsite for characterization. This safety analysis report for packaging (SARP) provides the analyses and evaluation necessary to demonstrate that the Doorstop Sample Carrier System meets the requirements and acceptance criteria for both Hanford Site normal transport conditions and accident condition events for a Type B package. This SARP also establishes operational, acceptance, maintenance, and quality assurance (QA) guidelines to ensure that the method of transport for the Doorstop Sample Carrier System is performed safely in accordance with WHC-CM-2-14, Hazardous Material Packaging and Shipping.

  8. Technical analysis of prospective photovoltaic systems in Utah.

    SciTech Connect (OSTI)

    Quiroz, Jimmy Edward; Cameron, Christopher P.

    2012-02-01T23:59:59.000Z

    This report explores the technical feasibility of prospective utility-scale photovoltaic system (PV) deployments in Utah. Sandia National Laboratories worked with Rocky Mountain Power (RMP), a division of PacifiCorp operating in Utah, to evaluate prospective 2-megawatt (MW) PV plants in different locations with respect to energy production and possible impact on the RMP system and customers. The study focused on 2-MW{sub AC} nameplate PV systems of different PV technologies and different tracking configurations. Technical feasibility was evaluated at three different potential locations in the RMP distribution system. An advanced distribution simulation tool was used to conduct detailed time-series analysis on each feeder and provide results on the impacts on voltage, demand, voltage regulation equipment operations, and flicker. Annual energy performance was estimated.

  9. On the Energy Consumption and Performance of Systems Software

    E-Print Network [OSTI]

    Zadok, Erez

    On the Energy Consumption and Performance of Systems Software Appears in the proceedings of the 4th,grosu,psehgal,sas,stoller,ezk}@cs.stonybrook.edu ABSTRACT Models of energy consumption and performance are necessary to understand and identify system. This paper considers the energy consumption and performance of servers running a relatively simple file

  10. Decision Analysis System for Selection of Appropriate Decontamination Technologies

    SciTech Connect (OSTI)

    Ebadian, M.A.; Boudreaux, J.F.; Chinta, S.; Zanakis, S.H.

    1998-01-01T23:59:59.000Z

    The principal objective for designing Decision Analysis System for Decontamination (DASD) is to support DOE-EM's endeavor to employ the most efficient and effective technologies for treating radiologically contaminated surfaces while minimizing personnel and environmental risks. DASD will provide a tool for environmental decision makers to improve the quality, consistency, and efficacy of their technology selection decisions. The system will facilitate methodical comparisons between innovative and baseline decontamination technologies and aid in identifying the most suitable technologies for performing surface decontamination at DOE environmental restoration sites.

  11. Spin system trajectory analysis under optimal control pulses

    E-Print Network [OSTI]

    Ilya Kuprov

    2012-12-18T23:59:59.000Z

    Several methods are proposed for the analysis, visualization and interpretation of high-dimensional spin system trajectories produced by quantum mechanical simulations. It is noted that expectation values of specific observables in large spin systems often feature fast, complicated and hard-to-interpret time dynamics and suggested that populations of carefully selected subspaces of states are much easier to analyze and interpret. As an illustration of the utility of the proposed methods, it is demonstrated that the apparent "noisy" appearance of many optimal control pulses in NMR and EPR spectroscopy is an illusion - the underlying spin dynamics is shown to be smooth, orderly and very tightly controlled.

  12. Spectral analysis for semi-infinite mass-spring systems

    E-Print Network [OSTI]

    Rafael del Rio; Luis O. Silva

    2014-07-29T23:59:59.000Z

    We study how the spectrum of a Jacobi operator changes when this operator is modified by a certain finite rank perturbation. The operator corresponds to an infinite mass-spring system and the perturbation is obtained by modifying one interior mass and one spring of this system. In particular, there are detailed results of what happens in the spectral gaps and which eigenvalues do not move under the modifications considered. These results were obtained by a new tecnique of comparative spectral analysis and they generalize and include previous results for finite and infinite Jacobi matrices.

  13. A new tool for accelerator system modeling and analysis

    SciTech Connect (OSTI)

    Gillespie, G.H.; Hill, B.W. [G.H. Gillespie Associates, Inc., Del Mar, CA (United States); Jameson, R.A. [Los Alamos National Lab., NM (United States)

    1994-09-01T23:59:59.000Z

    A novel computer code is being developed to generate system level designs of radiofrequency ion accelerators. The goal of the Accelerator System Model (ASM) code is to create a modeling and analysis tool that is easy to use, automates many of the initial design calculations, supports trade studies used in assessing alternate designs and yet is flexible enough to incorporate new technology concepts as they emerge. Hardware engineering parameters and beam dynamics are modeled at comparable levels of fidelity. Existing scaling models of accelerator subsystems were sued to produce a prototype of ASM (version 1.0) working within the Shell for Particle Accelerator Related Codes (SPARC) graphical user interface. A small user group has been testing and evaluating the prototype for about a year. Several enhancements and improvements are now being developed. The current version (1.1) of ASM is briefly described and an example of the modeling and analysis capabilities is illustrated.

  14. Simulated, Emulated, and Physical Investigative Analysis (SEPIA) of networked systems.

    SciTech Connect (OSTI)

    Burton, David P.; Van Leeuwen, Brian P.; McDonald, Michael James; Onunkwo, Uzoma A.; Tarman, Thomas David; Urias, Vincent E.

    2009-09-01T23:59:59.000Z

    This report describes recent progress made in developing and utilizing hybrid Simulated, Emulated, and Physical Investigative Analysis (SEPIA) environments. Many organizations require advanced tools to analyze their information system's security, reliability, and resilience against cyber attack. Today's security analysis utilize real systems such as computers, network routers and other network equipment, computer emulations (e.g., virtual machines) and simulation models separately to analyze interplay between threats and safeguards. In contrast, this work developed new methods to combine these three approaches to provide integrated hybrid SEPIA environments. Our SEPIA environments enable an analyst to rapidly configure hybrid environments to pass network traffic and perform, from the outside, like real networks. This provides higher fidelity representations of key network nodes while still leveraging the scalability and cost advantages of simulation tools. The result is to rapidly produce large yet relatively low-cost multi-fidelity SEPIA networks of computers and routers that let analysts quickly investigate threats and test protection approaches.

  15. Thermoacoustic instability - a dynamical system and time domain analysis

    E-Print Network [OSTI]

    Sayadi, Taraneh; Schmid, Peter; Richecoeur, Franck; Massot, Marc

    2013-01-01T23:59:59.000Z

    This study focuses on the Rijke tube problem, which includes features relevant to the modeling of thermoacoustic coupling in reactive flows: a compact acoustic source, an empirical model for the heat source, and nonlinearities. This system features both linear and nonlinear flow regimes with complex dynamical behavior. In order to synthesize accurate time-series, we tackle this problem from a numerical point-of-view, and start by proposing a dedicated solver designed for dealing with the underlying stiffness, in particular, the retarded time and the discontinuity at the location of the heat source. Stability analysis is performed on the limit of the low amplitude perturbations by means of the projection method proposed by Jarlebring (2008), which alleviates the linearization of the retarded term. The results are then compared to the analytical solution of the undamped system, in addition to the analysis based on Galerkin projection. The method provides insight into the consequence of the simplification due to...

  16. Systems analysis of past, present, and future chemical terrorism scenarios.

    SciTech Connect (OSTI)

    Hoette, Trisha Marie

    2012-03-01T23:59:59.000Z

    Throughout history, as new chemical threats arose, strategies for the defense against chemical attacks have also evolved. As a part of an Early Career Laboratory Directed Research and Development project, a systems analysis of past, present, and future chemical terrorism scenarios was performed to understand how the chemical threats and attack strategies change over time. For the analysis, the difficulty in executing chemical attack was evaluated within a framework of three major scenario elements. First, historical examples of chemical terrorism were examined to determine how the use of chemical threats, versus other weapons, contributed to the successful execution of the attack. Using the same framework, the future of chemical terrorism was assessed with respect to the impact of globalization and new technologies. Finally, the efficacy of the current defenses against contemporary chemical terrorism was considered briefly. The results of this analysis justify the need for continued diligence in chemical defense.

  17. Trajectory analysis and optimization system (TAOS) user`s manual

    SciTech Connect (OSTI)

    Salguero, D.E.

    1995-12-01T23:59:59.000Z

    The Trajectory Analysis and Optimization System (TAOS) is software that simulates point--mass trajectories for multiple vehicles. It expands upon the capabilities of the Trajectory Simulation and Analysis program (TAP) developed previously at Sandia National Laboratories. TAOS is designed to be a comprehensive analysis tool capable of analyzing nearly any type of three degree-of-freedom, point-mass trajectory. Trajectories are broken into segments, and within each segment, guidance rules provided by the user control how the trajectory is computed. Parametric optimization provides a powerful method for satisfying mission-planning constraints. Althrough TAOS is not interactive, its input and output files have been designed for ease of use. When compared to TAP, the capability to analyze trajectories for more than one vehicle is the primary enhancement, although numerous other small improvements have been made. This report documents the methods used in TAOS as well as the input and output file formats.

  18. Reliability analysis of electric power systems including time dependent sources 

    E-Print Network [OSTI]

    Kim, Younjong

    1987-01-01T23:59:59.000Z

    Chairman of Advisory Committee: Chanan Singh A method for reliability analysis of electric power systems with time dependent sources, such as photovoltaic and wind generation, is introduced. The fluctuating characteristic of unconventional generation... and active solar. wind, geothermal, and hydropower. Of all the renewable energy technologies that have been the focus of encouraging government and private R k D efforts, photovoltaic generation and wind turbine generation appear to be the leading...

  19. System and method for high precision isotope ratio destructive analysis

    DOE Patents [OSTI]

    Bushaw, Bruce A; Anheier, Norman C; Phillips, Jon R

    2013-07-02T23:59:59.000Z

    A system and process are disclosed that provide high accuracy and high precision destructive analysis measurements for isotope ratio determination of relative isotope abundance distributions in liquids, solids, and particulate samples. The invention utilizes a collinear probe beam to interrogate a laser ablated plume. This invention provides enhanced single-shot detection sensitivity approaching the femtogram range, and isotope ratios that can be determined at approximately 1% or better precision and accuracy (relative standard deviation).

  20. Safety analysis report for packaging (onsite) sample pig transport system

    SciTech Connect (OSTI)

    MCCOY, J.C.

    1999-03-16T23:59:59.000Z

    This Safety Analysis Report for Packaging (SARP) provides a technical evaluation of the Sample Pig Transport System as compared to the requirements of the U.S. Department of Energy, Richland Operations Office (RL) Order 5480.1, Change 1, Chapter III. The evaluation concludes that the package is acceptable for the onsite transport of Type B, fissile excepted radioactive materials when used in accordance with this document.

  1. Transportation Routing Analysis Geographic Information System (TRAGIS) User's Manual

    SciTech Connect (OSTI)

    Johnson, PE

    2003-09-18T23:59:59.000Z

    The Transportation Routing Analysis Geographic Information System (TRAGIS) model is used to calculate highway, rail, or waterway routes within the United States. TRAGIS is a client-server application with the user interface and map data files residing on the user's personal computer and the routing engine and network data files on a network server. The user's manual provides documentation on installation and the use of the many features of the model.

  2. NREL's System Advisor Model Simplifies Complex Energy Analysis (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2015-01-01T23:59:59.000Z

    NREL has developed a tool -- the System Advisor Model (SAM) -- that can help decision makers analyze cost, performance, and financing of any size grid-connected solar, wind, or geothermal power project. Manufacturers, engineering and consulting firms, research and development firms, utilities, developers, venture capital firms, and international organizations use SAM for end-to-end analysis that helps determine whether and how to make investments in renewable energy projects.

  3. Systems analysis of hydrogen supplementation in natural gas pipelines

    SciTech Connect (OSTI)

    Hermelee, A.; Beller, M.; D'Acierno, J.

    1981-11-01T23:59:59.000Z

    The potential for hydrogen supplementation in natural gas pipelines is analyzed for a specific site from both mid-term (1985) and long-term perspectives. The concept of supplementing natural gas with the addition of hydrogen in the existing gas pipeline system serves to provide a transport and storage medium for hydrogen while eliminating the high investment costs associated with constructing separate hydrogen pipelines. This paper examines incentives and barriers to the implementation of this concept. The analysis is performed with the assumption that current developmental programs will achieve a process for cost-effectively separating pure hydrogen from natural gas/hydrogen mixtures to produce a separable and versatile chemical and fuel commodity. The energy systems formulation used to evaluate the role of hydrogen in the energy infrastructure is the Reference Energy System (RES). The RES is a network diagram that provides an analytic framework for incorporating all resources, technologies, and uses of energy in a uniform manner. A major aspect of the study is to perform a market analysis of traditional uses of resources in the various consuming sectors and the potential for hydrogen substitution in these sectors. The market analysis will focus on areas of industry where hydrogen is used as a feedstock rather than for its fuel-use opportunities to replace oil and natural gas. The sectors of industry where hydrogen is currently used and where its use can be expanded or substituted for other resources include petroleum refining, chemicals, iron and steel, and other minor uses.

  4. A graph-based system for network-vulnerability analysis

    SciTech Connect (OSTI)

    Swiler, L.P.; Phillips, C.

    1998-06-01T23:59:59.000Z

    This paper presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The graph-based tool can identify the set of attack paths that have a high probability of success (or a low effort cost) for the attacker. The system could be used to test the effectiveness of making configuration changes, implementing an intrusion detection system, etc. The analysis system requires as input a database of common attacks, broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.

  5. Uncertainty and sensitivity analysis for photovoltaic system modeling.

    SciTech Connect (OSTI)

    Hansen, Clifford W.; Pohl, Andrew Phillip; Jordan, Dirk [National Center for Photovoltaics, National Renewable Energy Laboratory, Golden, CO] [National Center for Photovoltaics, National Renewable Energy Laboratory, Golden, CO

    2013-12-01T23:59:59.000Z

    We report an uncertainty and sensitivity analysis for modeling DC energy from photovoltaic systems. We consider two systems, each comprised of a single module using either crystalline silicon or CdTe cells, and located either at Albuquerque, NM, or Golden, CO. Output from a PV system is predicted by a sequence of models. Uncertainty in the output of each model is quantified by empirical distributions of each model's residuals. We sample these distributions to propagate uncertainty through the sequence of models to obtain an empirical distribution for each PV system's output. We considered models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane-of-array irradiance; (2) estimate effective irradiance from plane-of-array irradiance; (3) predict cell temperature; and (4) estimate DC voltage, current and power. We found that the uncertainty in PV system output to be relatively small, on the order of 1% for daily energy. Four alternative models were considered for the POA irradiance modeling step; we did not find the choice of one of these models to be of great significance. However, we observed that the POA irradiance model introduced a bias of upwards of 5% of daily energy which translates directly to a systematic difference in predicted energy. Sensitivity analyses relate uncertainty in the PV system output to uncertainty arising from each model. We found that the residuals arising from the POA irradiance and the effective irradiance models to be the dominant contributors to residuals for daily energy, for either technology or location considered. This analysis indicates that efforts to reduce the uncertainty in PV system output should focus on improvements to the POA and effective irradiance models.

  6. SAS2H Generated Isotopic Concentrations For B&W 15X15 PWR Assembly (SCPB:N/A)

    SciTech Connect (OSTI)

    J.W. Davis

    1996-08-29T23:59:59.000Z

    This analysis is prepared by the Mined Geologic Disposal System (MGDS) Waste Package Development Department (WPDD) to provide pressurized water reactor (PWR) isotopic composition data as a function of time for use in criticality analyses. The objectives of this evaluation are to generate burnup and decay dependant isotopic inventories and to provide these inventories in a form which can easily be utilized in subsequent criticality calculations.

  7. Analysis of Photovoltaic System Energy Performance Evaluation Method

    SciTech Connect (OSTI)

    Kurtz, S.; Newmiller, J.; Kimber, A.; Flottemesch, R.; Riley, E.; Dierauf, T.; McKee, J.; Krishnani, P.

    2013-11-01T23:59:59.000Z

    Documentation of the energy yield of a large photovoltaic (PV) system over a substantial period can be useful to measure a performance guarantee, as an assessment of the health of the system, for verification of a performance model to then be applied to a new system, or for a variety of other purposes. Although the measurement of this performance metric might appear to be straight forward, there are a number of subtleties associated with variations in weather and imperfect data collection that complicate the determination and data analysis. A performance assessment is most valuable when it is completed with a very low uncertainty and when the subtleties are systematically addressed, yet currently no standard exists to guide this process. This report summarizes a draft methodology for an Energy Performance Evaluation Method, the philosophy behind the draft method, and the lessons that were learned by implementing the method.

  8. SCALE 6: Comprehensive Nuclear Safety Analysis Code System

    SciTech Connect (OSTI)

    Bowman, Stephen M [ORNL

    2011-01-01T23:59:59.000Z

    Version 6 of the Standardized Computer Analyses for Licensing Evaluation (SCALE) computer software system developed at Oak Ridge National Laboratory, released in February 2009, contains significant new capabilities and data for nuclear safety analysis and marks an important update for this software package, which is used worldwide. This paper highlights the capabilities of the SCALE system, including continuous-energy flux calculations for processing multigroup problem-dependent cross sections, ENDF/B-VII continuous-energy and multigroup nuclear cross-section data, continuous-energy Monte Carlo criticality safety calculations, Monte Carlo radiation shielding analyses with automated three-dimensional variance reduction techniques, one- and three-dimensional sensitivity and uncertainty analyses for criticality safety evaluations, two- and three-dimensional lattice physics depletion analyses, fast and accurate source terms and decay heat calculations, automated burnup credit analyses with loading curve search, and integrated three-dimensional criticality accident alarm system analyses using coupled Monte Carlo criticality and shielding calculations.

  9. Analysis of reactor trips originating in balance of plant systems

    SciTech Connect (OSTI)

    Stetson, F.T.; Gallagher, D.W.; Le, P.T.; Ebert, M.W. (Science Applications International Corp., McLean, VA (USA))

    1990-09-01T23:59:59.000Z

    This report documents the results of an analysis of balance-of-plant (BOP) related reactor trips at commercial US nuclear power plants of a 5-year period, from January 1, 1984, through December 31, 1988. The study was performed for the Plant Systems Branch, Office of Nuclear Reactor Regulation, US Nuclear Regulatory Commission. The objectives of the study were: to improve the level of understanding of BOP-related challenges to safety systems by identifying and categorizing such events; to prepare a computerized data base of BOP-related reactor trip events and use the data base to identify trends and patterns in the population of these events; to investigate the risk implications of BOP events that challenge safety systems; and to provide recommendations on how to address BOP-related concerns in regulatory context. 18 refs., 2 figs., 27 tabs.

  10. A System Degradation Study of 445 Systems Using Year-Over-Year Performance Index Analysis

    Broader source: Energy.gov [DOE]

    This graphic summarizes the results of a study conducted by the SunPower Corporation, to assess the median degradation of a large number of systems. This is important because solar investors need proof of low degradation. The study, a project under DOE's SunShot Initiative, makes use of year-over-year performance index change analysis, a powerful and practical technique for assessing the median degradation of a large fleet of systems, which in this case includes a sample of 445.

  11. SAFETY ANALYSIS AND INTEGRATION FOR ROBOTIC SYSTEMS -APPLICATION TO A

    E-Print Network [OSTI]

    Guiochet, Jérémie

    Analysis (FMEA) and Fault Tree Analysis (FTA) which identify potential unit errors resulting in hazards

  12. RIVIER COLLEGE Spring 2006 BUS341A Information Systems Analysis Dr. Vladimir Riabov

    E-Print Network [OSTI]

    Riabov, Vladimir V.

    . A continuing case study that spans all phases of the system development life cycle (SDLC) is used to promote development life cycle (SDLC): Systems Planning; Systems Analysis; System Design; System Implementation the importance of communications, economic analysis, and project planning skills across all phases of the SDLC

  13. System Modeling, Analysis, and Optimization Methodology for Diesel Exhaust After-treatment Technologies

    E-Print Network [OSTI]

    de Weck, Olivier L.

    System Modeling, Analysis, and Optimization Methodology for Diesel Exhaust After;System Modeling, Analysis, and Optimization Methodology for Diesel Exhaust After-treatment Technologies Developing new aftertreatment technologies to meet emission regulations for diesel engines is a growing

  14. Fuel-Cycle Analysis of Hydrogen-Powered Fuel-Cell Systems with...

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

    Fuel-Cycle Analysis of Hydrogen-Powered Fuel-Cell Systems with the GREET Model Fuel-Cycle Analysis of Hydrogen-Powered Fuel-Cell Systems with the GREET Model This presentation by...

  15. Global Systems-Level Analysis of Hfq and SmpB Deletion Mutants...

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

    Systems-Level Analysis of Hfq and SmpB Deletion Mutants in Salmonella: Implications for Virulence and Global Protein Global Systems-Level Analysis of Hfq and SmpB Deletion Mutants...

  16. A shoe-integrated sensor system for wireless gait analysis and real-time therapeutic feedback

    E-Print Network [OSTI]

    Morris, Stacy J., 1974-

    2004-01-01T23:59:59.000Z

    Clinical gait analysis currently involves either an expensive analysis in a motion laboratory, using highly accurate, if cumbersome, kinematic systems, or a qualitative analysis with a physician or physical therapist making ...

  17. Challenges in the Modeling and Quantitative Analysis of Safety-Critical Automotive Systems!

    E-Print Network [OSTI]

    Leue, Stefan

    ! Probabilistic FMEA! Probabilistic Analysis of System Architectures! ! Conclusion! 3! #12;ISO 26262: Road! ,,identify Failures"! - Qualitative FMEA! ! - Qualitative Fault Tree Analysis! ! - Event Tree Analysis! Quantitative Methods! ,,predict frequency of failures"! - Quantitative FMEA! ! - Quantitative Fault Tree

  18. Enhanced Accident Tolerant Fuels for LWRS - A Preliminary Systems Analysis

    SciTech Connect (OSTI)

    Gilles Youinou; R. Sonat Sen

    2013-09-01T23:59:59.000Z

    The severe accident at Fukushima Daiichi nuclear plants illustrates the need for continuous improvements through developing and implementing technologies that contribute to safe, reliable and cost-effective operation of the nuclear fleet. Development of enhanced accident tolerant fuel contributes to this effort. These fuels, in comparison with the standard zircaloy – UO2 system currently used by the LWR industry, should be designed such that they tolerate loss of active cooling in the core for a longer time period (depending on the LWR system and accident scenario) while maintaining or improving the fuel performance during normal operations, operational transients, and design-basis events. This report presents a preliminary systems analysis related to most of these concepts. The potential impacts of these innovative LWR fuels on the front-end of the fuel cycle, on the reactor operation and on the back-end of the fuel cycle are succinctly described without having the pretension of being exhaustive. Since the design of these various concepts is still a work in progress, this analysis can only be preliminary and could be updated as the designs converge on their respective final version.

  19. System diagnostics using qualitative analysis and component functional classification

    DOE Patents [OSTI]

    Reifman, Jaques (Lisle, IL); Wei, Thomas Y. C. (Downers Grove, IL)

    1993-01-01T23:59:59.000Z

    A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system.

  20. System diagnostics using qualitative analysis and component functional classification

    DOE Patents [OSTI]

    Reifman, J.; Wei, T.Y.C.

    1993-11-23T23:59:59.000Z

    A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures.