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We encourage you to perform a real-time search of NLEBeta
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1

SAS4A LMFBR whole core accident analysis code  

SciTech Connect (OSTI)

To ensure that public health and safety are protected even under accident conditions in an LMFBR, many accidents are analyzed for their potential consequences. Extremely unlikely accidents that might lead to melting of reactor fuel and release of radioactive fission products are referred to as hypothetical core disruptive accidents (HCDAs). The evaluation of such accidents involves the simultaneous evaluation of thermal, mechanical, hydraulic and neutronic processes and their interactions. The complexity of this analysis requires the use of large, integrated computer codes which address the response of the reactor core and several important systems. The SAS family of codes, developed at Argonne National Laboratory, provides such an analysis capability. The SAS4A code, the latest generation of this series of codes, has recently been completed and released for use to the LMFBR safety community. This paper will summarize the important new capabilitites of this analysis tool and illustrate an application of the integrated capability, while highlighting the importance of specific phenomenological models.

Weber, D.P.; Birgersson, G.; Bordner, G.L.; Briggs, L.L.; Cahalan, J.E.; Dunn, F.E.; Kalimullah; Miles, K.J.; Prohammer, F.G.; Tentner, A.M.

1985-01-01T23:59:59.000Z

2

SAS4A validation and analysis of inpile experiments for slow ramp TOP's. [LMFBR  

SciTech Connect (OSTI)

In the licensing process for an LMFBR, the margins for safety are determined by considering many accident sequences that are within the design basis for the plant. However, to establish the safety margin beyond the design basis, also considered are accidents that have an extremely low probability of occurrence but the potential for significant consequences - such as hypothetical core-disruptive accidents (HCDAs). Assessments of the potential for HCDAs that would severely disrupt the reactor system and release radioactive material to the reactor containment (and possibly to the atmosphere) rely heavily on large-scale integrated computer codes such as SAS. The latest version of the SAS LMFBR accident analysis code, SAS4A, has recently been completed and released. One important activity which has been a part of SAS development is code validation for which a comprehensive plan has been formulated. Analysis of In Pile Experiments, mainly TREAT, form a large part of this.

Hill, D.J.

1985-01-01T23:59:59.000Z

3

SAsSy --Scrutable Autonomous Systems Nava Tintarev, Roman Kutlak, Nir Oren, Kees Van Deemter  

E-Print Network [OSTI]

SAsSy -- Scrutable Autonomous Systems Nava Tintarev, Roman Kutlak, Nir Oren, Kees Van Deemter Matt.tintarev@abdn.ac.uk Abstract. An autonomous system consists of physical or virtual systems that can perform tasks without continuous human guidance. Autonomous systems are becoming increasingly ubiquitous, rang- ing from unmanned

van Deemter, Kees

4

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

5

Application for SAS Certificate Applied Statistics and SAS Programming  

E-Print Network [OSTI]

# ________________________________________ BYU ID ________________________________________ ________________________________________ Year Name Year/Term Taken Grade Stat 124 1.0 SAS Certification 1 Stat 125 1.0 SAS Certification 2 Stat 224 2.0 Statistical Computing 1 Stat 230 3.0 Analysis of Variance Stat 330 3.0 Introduction to Regression Stat 424 3

Dahl, David B.

6

Application for SAS Certificate Applied Statistics and SAS Programming  

E-Print Network [OSTI]

# ________________________________________ BYU ID ________________________________________ ________________________________________ Year Name Year/Term Taken Grade Stat 124 1.5 SAS Base Programming Skills Stat 224 1.5 Applied SAS Programming Stat 230 3.0 Analysis of Variance Stat 330 3.0 Introduction to Regression Stat 424 3.0 Statistical

Dahl, David B.

7

SAS4A/SASSYS-1: Fast Reactor Safety Analysis Code | Argonne National...  

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

and systems analysis features are applicable to other liquid-metal cooled reactor concepts. Applications Safety analysis of fast reactors Simulations for...

8

Macroscopic cross section generation and application for coupled spatial kinetics and thermal hydraulics analysis with SAS-DIF3DK  

SciTech Connect (OSTI)

This paper discusses the importance of modeling the transient behavior of multigroup cross sections in the context of coupled reactor physics and thermal-hydraulic computations with the SAS-DIF3DK computer code. The MACOEF macroscopic cross section methodology is presented. Results from benchmark verification calculations with a continuous-energy Monte Carlo are reported. Analysis of the Chernobyl accident is made using correlated WIMS-D4M generated group constants with special emphasis placed on the impact of modeling assumptions on the progression of the accident simulation.

Turski, R.B.; Morris, E.E.; Taiwo, T.A.; Cahalan, J.E.

1997-08-01T23:59:59.000Z

9

SAS Output  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Bituminous Coal BIT Source: 1 205.30000 Distillate Fuel Oil DFO Source: 1 161.38600 Geothermal GEO Estimate from EIA, Office of Integrated Analysis and Forecasting 16.59983 Jet...

10

SAS Output  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

System Type Firing Configuration Tangential Boiler All Other Boiler Types Combustion Turbine Internal Combustion Engine Fuel EIA Fuel Code Source and Tables (As Appropriate)...

11

Shielding analysis of the NAC-MPC storage system  

SciTech Connect (OSTI)

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.

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

12

E-Print Network 3.0 - alarm system analysis Sample Search Results  

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

(SAS) to monitor scientific equipment that is critical to ongoing... Equipment System (AES): The notebook found at various alarm panels Scientific Alarm System (SAS... ): The...

13

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)

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)

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

14

SAS4A simulation of the OPERA-15 two-dimensional voiding experiment. [LMFBR  

SciTech Connect (OSTI)

A major effort is currently being pursued to validate the SAS4A LMFBR accident analysis code. Part of this effort involves SAS4A analysis of both in-pile and out-of-pile safety experiments. Such an experiment is the fifteen-pin Out-of-Pile Explusion and Reentry Apparatus (OPERA) test run at Argonne National Laboratory. This test uses a fifteen-pin triangular-shaped bundle of simulant fuel pins to demonstrate two-dimensional voiding behavior in a LMFBR subassembly during a Loss-of-Flow (LOF) accident. This experiment was chosen for SAS4A analysis both for its value in code validation and its usefulness in evaluating the limitations of the one-dimensional SAS4A sodium voiding model in accident analysis.

Briggs, L.L.

1984-01-01T23:59:59.000Z

15

Quality assurance management plan (QAPP) special analytical support (SAS)  

SciTech Connect (OSTI)

It is the policy of Special Analytical Support (SAS) that the analytical aspects of all environmental data generated and processed in the laboratory, subject to the Environmental Protection Agency (EPA), U.S. Department of Energy or other project specific requirements, be of known and acceptable quality. It is the intention of this QAPP to establish and assure that an effective quality controlled management system is maintained in order to meet the quality requirements of the intended use(s) of the data.

LOCKREM, L.L.

1999-05-20T23:59:59.000Z

16

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

SciTech Connect (OSTI)

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.

LOCKREM, L.L.

1999-08-13T23:59:59.000Z

17

SAS ® 9.3 Integration Technologies Directory Services Reference  

E-Print Network [OSTI]

For a hardcopy book: No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise, without the prior written permission of the publisher, SAS Institute Inc. For a Web download or e-book: Your use of this publication shall be governed by the terms established by the vendor at the time you acquire this publication. The scanning, uploading, and distribution of this book via the Internet or any other means without the permission of the publisher is illegal and punishable by law. Please purchase only authorized electronic editions and do not participate in or encourage electronic piracy of copyrighted materials. Your support of others ' rights is appreciated. U.S. Government Restricted Rights Notice: Use, duplication, or disclosure of this software and related documentation by the U.S. government is subject to the Agreement with SAS Institute and the restrictions set forth in FAR 52.227–19, Commercial Computer Software-Restricted Rights

unknown authors

18

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)

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

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

2012-05-10T23:59:59.000Z

19

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

E-Print Network [OSTI]

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

Yu, Alex

20

Coal systems analysis  

SciTech Connect (OSTI)

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.

Warwick, P.D. (ed.)

2005-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Design, Simulation, and Analysis of Substation Automation Networks  

E-Print Network [OSTI]

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...

Kembanur Natarajan, Elangovan

2012-07-16T23:59:59.000Z

22

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

E-Print Network [OSTI]

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

Seybold, Steven J.

23

SAS Honors Seminar 256: Extraterrestrial Life  

E-Print Network [OSTI]

/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

Baker, Andrew J.

24

SAS Honors Seminar 259: Extraterrestrial Life  

E-Print Network [OSTI]

: 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

Baker, Andrew J.

25

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

E-Print Network [OSTI]

\\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...

Wright, Philip A.

2013-04-02T23:59:59.000Z

26

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

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

Analysis Models and Tools: Systems Analysis of Hydrogen and Fuel Cells Analysis Models and Tools: Systems Analysis of Hydrogen and Fuel Cells The Fuel Cell Technologies Office's...

27

Workplace Charging Challenge Partner: SAS Institute | Department of Energy  

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

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "ofEarlyEnergyDepartment ofDepartment of Energyof EnergyEnergyHertzDepartmentRaytheon RaytheonSAS

28

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:Seadov Pty Ltd Jump to: navigation,Pvt LtdShrub Oak, NewSilicium de Provence SAS Silpro

29

Process Cooling Pumping Systems Analysis  

E-Print Network [OSTI]

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...

Sherman, C.

2008-01-01T23:59:59.000Z

30

Energy, Environmental & Economic Systems Analysis  

E-Print Network [OSTI]

Energy, Environmental & Economic Systems Analysis ENPEP-BALANCE: A Tool for Long-term Nuclear Power, Environmental & Economic Systems Analysis A resurgence of interest in nuclear energy is taking place Market Simulations Opportunity Decision and Information Sciences Division Center for Energy

31

Analyzing product test data in a relational database using SAS software  

SciTech Connect (OSTI)

SAS software is being used to analyze product test data stored in an INGRES relational database. The database has been implemented at Allied-Signal in Kansas City on a Digital Equipment Corporation (DEC) VAX computer. The INGRES application development has been a joint project between Sandia National Laboratories and Allied-Signal. Application screens have been developed so that the user can query the database for selected data. Fourth generation language procedures are used to retrieve all data requested. FORTRAN and VAX/VMS DCL (DIGITAL Control Language) procedures are invoked from the application to create SAS data sets and dynamically build SAS programs that are executed to build custom reports or graphically display the retrieved test data along with control and specification limits. A retrieval screen has also been developed which invokes SAS software to calculate the mean and standard deviation of the retrieved data. These parameters are passed back into the application for display and may then be used as an aid in setting new control limits for future test runs. Screens have been developed to provide an interface for the user to select from a library of SAS programs, edit the selected program, and run the program with a user-defined SAS data set as input. This paper will give a brief description of the application screens and provide details of how information is passed between the application and SAS programs.

Orman, J.L.

1991-01-01T23:59:59.000Z

32

SUBSURFACE VISUAL ALARM SYSTEM ANALYSIS  

SciTech Connect (OSTI)

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.

D.W. Markman

2001-08-06T23:59:59.000Z

33

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Opticalhttp://www.fnal.gov/directorate/nalcal/nalcal02_07_05_files/nalcal.gifAEnergy ScientistNETL-RUAProjectSystems

34

Advanced CSP 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUCProductstwrmrAre theAdministrator Referencesalkali metalsTiO2(110).CSP Systems

35

The ALICE analysis train system  

E-Print Network [OSTI]

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.

Markus Zimmermann; for the ALICE collaboration

2015-02-23T23:59:59.000Z

36

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

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

Safety System Oversight Staffing Analysis (Instructions, Blank Sheet and Example Sheet) Safety System Oversight Staffing Analysis (Instructions, Blank Sheet and Example Sheet) This...

37

New aspects in the analysis of loss-of-flow transients for homogeneous and heterogeneous LMFBR cores  

SciTech Connect (OSTI)

This paper presents the results of analyses of unprotected loss-of-flow (LOF) transients which have been performed to date using the new SAS4A code system. Accident histories for homogeneous and heterogeneous demo-sized cores (300 MWe) are compared and emphasis is placed on phenomena occurring after the initiation of fuel motion as described by LEVITATE. LEVITATE is the SAS4A model for the analysis of fuel and cladding dynamics under loss-of-flow (LOF) conditions and is believed to be the most-sophisticated computational tool currently available for fuel-motion analysis. The results of this analysis indicate that the initiation phase of an unprotected loss-of-flow accident has a considerably lower energetics potential in a heterogeneous core than in a homogeneous core. The difference is larger than previously indicated by SAS3D. Better phenomenological models implemented in SAS4A provide increased confidence in this aspect of safety evaluation of LMFBR cores.

Tentner, A.M.; Wider, H.U.

1982-01-01T23:59:59.000Z

38

Transportation Routing Analysis Geographic Information System (TRAGIS)  

E-Print Network [OSTI]

Transportation Routing Analysis Geographic Information System (TRAGIS) Model and Network Databases The Transportation Routing Analysis Geographic Information System (TRAGIS) model is a geographic information system tool for modeling transportation routing. TRAGIS offers numerous options for route calculation

39

Tank waste remediation system (TWRS) mission analysis  

SciTech Connect (OSTI)

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.

Rieck, R.H.

1996-10-03T23:59:59.000Z

40

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.

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

SMACS. Probabilistic Seismic Analysis System  

SciTech Connect (OSTI)

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).

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

42

System architecture analysis and selection under uncertainty  

E-Print Network [OSTI]

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 ...

Smaling, Rudolf M

2005-01-01T23:59:59.000Z

43

Transportation Routing Analysis Geographic Information System...  

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

Analysis Geographic Information System (TRAGIS) to Spent Fuel Routing Analysis P. E. Johnson R.R. Rawl Oak Ridge National Laboratory TRAGIS is being used by OCRWM to identify...

44

Reachability Analysis of Stochastic Hybrid Systems: A Biodiesel Production System  

E-Print Network [OSTI]

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

Koutsoukos, Xenofon D.

45

SWEPP assay system version 2.0 software requirements specification  

SciTech Connect (OSTI)

The INEL Stored Waste Examination Pilot Plant (SWEPP) operations staff use nondestructive analysis methods to characterize the radiological contents of contact-handled radioactive waste containers. Containers of waste from Rocky Flats Environmental Technology Site and other DOE sites are currently stored at SWEPP. Before these containers can be shipped to WIPP, SWEPP must verify compliance with storage, shipping, and disposal requirements. One part of the SWEPP program measures neutron emissions from the containers and estimates the mass of Pu and other transuranic isotopes present. The code NEUT2 was originally used to perform data acquisition and reduction; the SWEPP Assay System (SAS) code replaced NEUT2 in early 1994. This document specifies the requirements for the SAS software as installed at INEL and was written to comply with RWMC (INEL Radioactive Waste Management Complex) quality requirements.

Matthews, S.D.; East, L.V.; Marwil, E.S.; Ferguson, J.J.

1996-06-01T23:59:59.000Z

46

ADVANCED POWER SYSTEMS ANALYSIS TOOLS  

SciTech Connect (OSTI)

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.

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

2001-08-31T23:59:59.000Z

47

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...

48

NREL: Energy Analysis - Technology 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions and Achievements ofLiz Torres Photo of LizSchwabeTechnology Systems

49

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...

50

SWEPP Assay System Version 2.0 software test plan and report  

SciTech Connect (OSTI)

The Idaho National Engineering Laboratory (INEL) Stored Waste Examination Pilot Plant (SWEPP) operations staff use nondestructive analysis methods to characterize the radiological contents of contact- handled waste containers. Containers of waste from Rocky Flats Environmental Technology Site and other DOE sites are currently stored at SWEPP. Before these containers can be shipped to the Waste Isolation Pilot Plant (WIPP), SWEPP must verify compliance with storage, shipping, and disposal requirements. One part of the SWEPP program measures neutron emissions from the containers and estimates the mass of plutonium and other transuranic (TRU) isotopes present. A Passive/Active Neutron (PAN) assay system developed at the Los Alamos National Laboratory is used to perform these measurements. A computer program named NEUT2 was used to perform the data acquisition and reduction functions for the neutron measurements. NEUT2 uses the analysis methodology outlined, but no formal documentation exists on the software itself The SWEPP Assay System (SAS) computer program replaced the NEUT2 software. The SAS software was developed using an `object model` approach. The new software incorporates the basic analysis algorithms found in NEUT2. Additional improvements include an improved user interface, the ability to change analysis parameters without having to modify the code, and other features for maintainability. The primary purpose of this test plan and report is to document the test process and to verify that the requirements for the SAS are implemented correctly. This test plan and report satisfies the testing requirements of ASME NQA-1-1994 Supplement 11S-2 for a Quality Level 2 application. The intended audiences for this test plan are the developers and verification and validation analysts for the SAS.

Ferguson, J.J.; Overlin, T.K.

1996-07-01T23:59:59.000Z

51

Environmental applications of the particle analysis system  

SciTech Connect (OSTI)

This study demonstrates the applicability of particle counting technology for analysis of various water treatment systems at the Rocky Flats Plant. The Particle Analysis System described in this study determined the water quality of samples from environmental remediation, stormwater treatment, and drinking water treatment operations. Samples were measured in either discrete or on-line mode. This data showed filtration efficiencies, particle counts, particle size distributions, and real-time treatment system performance. Particle counting proved more sensitive than the turbidimetric measurement technique commonly used by the water treatment industry. Particle counting is a two-dimensional measurement of counts and sizes, whereas turbidity is a one-dimensional measurement of water clarity. Samples showing identical turbidities could be distinguished easily with the Particle Analysis System. The Particle Analysis System proved to be an efficient and reliable water quality measurement tool, and it is applicable to a variety of water treatment systems at the Rocky Flats Plant.

Moritz, E.J.; Hoffman, C.R.

1993-09-28T23:59:59.000Z

52

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)...

53

SteamMaster: Steam System Analysis Software  

E-Print Network [OSTI]

STEAMMASTER: STEAM SYSTEM ANALYSIS SOFTW ARE Greg Wheeler Associate Professor Oregon State University Corvallis, OR 9733 I ABSTRACT As director of Oregon's ]ndustrial Assessment Center, [ have encountered many industrial steam systems during... plant visits. We analyze steam systems and make recommendations to improve system efficiency. [n nearly 400 industrial assessments, we have recommended 210 steam system improvements, excluding heat recovery, that would save $1.5 million/year with a...

Wheeler, G.

54

Agricultural capital project analysis system  

E-Print Network [OSTI]

analysis. Three specific objectives were established: (1) To select the most suitable procedures for economic and finan- cial evaluation of agricultural projects in developing countries, in- cluding the incorporation of an appropriate sensitivity..., Mercedes and Segismundo Lopez. TABLE OF CONTENTS INTRODUCTION General Objectives Procedure Page 1 1 3 4 LITERATURE REVIEW Evaluation Financial Evaluation Payback Period Accounting Rate of Return Net Present Value Internal Rate of Return...

Lopez, Ramon Antonio

2012-06-07T23:59:59.000Z

55

Satellite System Safety Analysis Using STPA  

E-Print Network [OSTI]

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. ...

Dunn, Nicholas Connor

2013-01-01T23:59:59.000Z

56

Power System Transient Stability Analysis through a Homotopy Analysis Method  

SciTech Connect (OSTI)

As an important function of energy management systems (EMSs), online contingency analysis plays an important role in providing power system security warnings of instability. At present, N-1 contingency analysis still relies on time-consuming numerical integration. To save computational cost, the paper proposes a quasi-analytical method to evaluate transient stability through time domain periodic solutions’ frequency sensitivities against initial values. First, dynamic systems described in classical models are modified into damping free systems whose solutions are either periodic or expanded (non-convergent). Second, because the sensitivities experience sharp changes when periodic solutions vanish and turn into expanded solutions, transient stability is assessed using the sensitivity. Third, homotopy analysis is introduced to extract frequency information and evaluate the sensitivities only from initial values so that time consuming numerical integration is avoided. Finally, a simple case is presented to demonstrate application of the proposed method, and simulation results show that the proposed method is promising.

Wang, Shaobu; Du, Pengwei; Zhou, Ning

2014-04-01T23:59:59.000Z

57

Sandia National Laboratories: 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassiveSubmitted for US PatentOperationalforRenewableEnergySolarEnergyAnalysis

58

VISION 21 SYSTEMS ANALYSIS METHODOLOGIES  

SciTech Connect (OSTI)

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.

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

2003-08-11T23:59:59.000Z

59

Analysis of Fuel Cell Systems Rangan Banerjee  

E-Print Network [OSTI]

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

Banerjee, Rangan

60

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

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Energy Engineering & Systems Analysis Success Stories  

E-Print Network [OSTI]

Energy Engineering & Systems Analysis Success Stories For further information, contact: Dileep Singh, dsingh@anl.gov NOx/O2 Sensors for High Temperature Applications In vehicle engines, monitoring with an internal reference gas system. The Solution Using a unique deformation bonding method that joins

Kemner, Ken

62

Energy Engineering & Systems Analysis Success Stories  

E-Print Network [OSTI]

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 to the limit, requiring upgrades. The Solution A multidisciplinary mix of scientists and engineers from Argonne

Kemner, Ken

63

PLT data acquisition and analysis system  

SciTech Connect (OSTI)

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.

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

1986-08-01T23:59:59.000Z

64

Waste Feed Delivery Transfer System Analysis  

SciTech Connect (OSTI)

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.

JULYK, L.J.

2000-05-05T23:59:59.000Z

65

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,...

66

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

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

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

67

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....

68

Hybrid Ground Source System Analysis and Tool Development | Department...  

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

Hybrid Ground Source System Analysis and Tool Development Hybrid Ground Source System Analysis and Tool Development Project objectives: 1. Compile filtered hourly data for three...

69

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

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

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...

70

US DRIVE Vehicle Systems and Analysis Technical Team Roadmap...  

Energy Savers [EERE]

Vehicle Systems and Analysis Technical Team Roadmap US DRIVE Vehicle Systems and Analysis Technical Team Roadmap VSATT provides the analytic support and subsystem characterizations...

71

RAMS (Risk Analysis - Modular System) methodology  

SciTech Connect (OSTI)

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.

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

1996-10-01T23:59:59.000Z

72

Fuel Cycle System Analysis Handbook  

SciTech Connect (OSTI)

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.

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

2009-06-01T23:59:59.000Z

73

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

Energy Savers [EERE]

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...

74

Thermal analysis of the ATLAS dump system  

E-Print Network [OSTI]

The dump system of the ATLAS Magnet, situated on third level of the USA15 cavern is an assembly of diodes and dump resistors through which the energy stored in the Magnet is dissipated when running down the magnet current to zero. The dump system is permanently connected to the Magnet through a system of bus bars and is able to dissipate about 1.5 GJ of energy in 3 hours. The goal of this thermal analysis, performed by ST/CV, is to understand whether the heat released by the dump system can be removed by free convection into the PX15 shaft or if forced ventilation is needed

Wichrowska Polok, I

2003-01-01T23:59:59.000Z

75

Analysis of the cattle histocompatibility system  

E-Print Network [OSTI]

antilymphocytic sera (ALS) revealed a minimum of eight, two, four snd eight antibody specificities present in ALS 1, 2, 3 and 4, respectively. The heterogeneity of the histocompatibility system was demonstrated by red. and white blood cell absorptions... Antibodies in Normal Serum Titration Analysis of ALS Analysis of Red Blood Cell Absorptions Antigenic Relationship Between Sperm Cells and WBC Absorbing Properties of Sperm and WBC Solubilates Electrophoretic and Electrofocusing Characterization...

Bryan, Christopher Fulton

2012-06-07T23:59:59.000Z

76

Integrated systems analysis of the PIUS reactor  

SciTech Connect (OSTI)

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.

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

1993-11-01T23:59:59.000Z

77

Dynamical System Analysis for a phantom model  

E-Print Network [OSTI]

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.

Nilanjana Mahata; Subenoy Chakraborty

2014-04-24T23:59:59.000Z

78

SAS Output  

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

3. Summary Statistics for Coal Refining Plants, 2012 - 2014" "(thousand short tons)" "Year and","Coal Receipts","Average Price of Coal Receipts","Coal Used","Coal Stocks1"...

79

SAS Output  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

4. Nitrogen Oxides Control Technology Emissions Reduction Factors Nitrogen Oxides Control Technology EIA-Code(s) Reduction Factor Advanced Overfire Air AA 30% Alternate Burners BF...

80

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

Boiler Spreader Stoker Boiler Tangential Boiler All Other Boiler Types Combustion Turbine Internal Combustion Engine Agricultural Byproducts AB Source: 1 Lbs per ton 0.08 0.01...

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

SAS Output  

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

"(thousand short tons)" "Census Division","June 30 2014","March 31 2014","June 30 2013","Percent Change" "and State",,,,"(June 30)" ,,,,"2014 versus 2013" "Middle...

82

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State1",2014,2014,2013,,,"Change" "Middle Atlantic" "...

83

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Middle Atlantic",1222,1214,1247,2435,2460,-1...

84

SAS Output  

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

,,,,"Year to Date" "Commodity","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Coke" " Sales",1969,1865,1969,3834,3905,-1.8 "...

85

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Middle Atlantic",1599,1503,1622,3102,3178,-2.4...

86

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "Middle Atlantic",113.65,114.55,139.64,...

87

SAS Output  

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

,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "311 Food Manufacturing",2085,2575,2256,4660,4817,...

88

SAS Output  

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

Code" "(thousand short tons)" "NAICS Code","June 30 2014","March 31 2014","June 30 2013","Percent Change" ,,,,"(June 30)" ,,,,"2014 versus 2013" "311 Food...

89

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "New England",20,30,21,51,48,5.5 "...

90

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "Middle Atlantic",19,58,25,77,79,-2.7 "...

91

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "New England","w","w","w","w","w","w" "...

92

SAS Output  

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

"(thousand short tons)" "Census Division","June 30 2014","March 31 2014","June 30 2013","Percent Change" "and State",,,,"(June 30)" ,,,,"2014 versus 2013" "New...

93

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State1",2014,2014,2013,,,"Change" "New England" " Btu",13306,12964,13323...

94

SAS Output  

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

,"Sector1",,,"Institutional Users",,"Distributors" 2008 " March 31",146497,1462,4818,448,153225,34876,188101 " June 30",152542,1756,4983,478,159760,32086,191846 "...

95

SAS Output  

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

,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "311 Food Manufacturing",2111,2386,2214,4497,4570,...

96

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "Middle Atlantic",21,59,20,80,73,10.4 "...

97

SAS Output  

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

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "New England",21,29,22,50,48,3.1 "...

98

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3. Revenue

99

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3. Revenue4.

100

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.

102

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.

103

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.A. Net

104

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.A.

105

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.A.A.

106

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.A.A.B.

107

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working

108

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) WorkingB. Winter Net Internal

109

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) WorkingB. Winter Net

110

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) WorkingB. Winter NetB.

111

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) WorkingB. Winter NetB.4.5.

112

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline Blend.1.

113

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline Blend.1.2.

114

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline

115

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline. Number of

116

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline. Number

117

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline. Number3.

118

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline. Number3.5.

119

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.

120

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7. Average

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.

122

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.9.

123

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.9.0.

124

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.9.0.1.

125

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.9.0.1.2.

126

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional

127

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. Green Pricing

128

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. Green PricingA.

129

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. Green PricingA.B.

130

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. Green

131

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB. Net

132

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB. Net3.A.

133

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB. Net3.A.B.

134

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.

135

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B. Net

136

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B. NetA.

137

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B. NetA.B.

138

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.

139

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7. Net

140

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7. Net8.

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.

142

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.0. Net

143

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.0.

144

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.0.2.

145

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.0.2.3.

146

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.

147

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net Generation

148

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net Generation6.

149

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net

150

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net

151

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net9. Net

152

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net9.

153

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net9.1.

154

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net9.1.2.

155

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.

156

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4. Useful

157

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4. Useful.

158

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.

159

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.B.

160

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.B.3.

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.B.3.4.

162

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.B.3.4.5.

163

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.

164

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net Summer

165

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net SummerB.

166

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net SummerB.C.

167

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net

168

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0. Net

169

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0. Net1.

170

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0. Net1.2.

171

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.

172

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.4.

173

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.4.A.

174

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.4.A.B.

175

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.4.A.B.C.

176

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.

177

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E. Coal:

178

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E. Coal:F.

179

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E. Coal:F.A.

180

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E. Coal:F.A.B.

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.

182

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D. Petroleum

183

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.

184

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.

185

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.A.

186

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.A.B.

187

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.A.B.C.

188

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.A.B.C.D.

189

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on

190

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption for

191

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption forA.

192

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption forA.B.

193

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption forA.B.C.

194

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption forA.B.C.D.

195

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption

196

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF. Natural

197

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF. NaturalD.

198

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.

199

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. Wood /

200

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. Wood /A.

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. Wood

202

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. WoodC.

203

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. WoodC.D.

204

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.

205

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.F.

206

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.F.A.

207

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.F.A.B.

208

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.F.A.B.C.

209

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:

210

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. Biogenic Municipal

211

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. Biogenic MunicipalF.

212

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. Biogenic MunicipalF.D.

213

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. Biogenic

214

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other Waste

215

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other

216

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other0.

217

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other0.1.

218

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other0.1.2.

219

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.

220

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1. Stocks

222

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1. Stocks2

223

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.

224

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.4.

225

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.4..

226

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.4..3.

227

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.4..3.4.

228

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.

229

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts, Average

230

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts, Average7

231

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts, Average78.

232

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,

233

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.

234

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.1.

235

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.1.2.

236

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.1.2.3.

237

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.1.2.3.4.

238

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.

239

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts of

240

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts of7.

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts of7.8.

242

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts of7.8.9.

243

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts

244

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.

245

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.2.

246

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.2.3.

247

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.2.3.4.

248

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.2.3.4.5.

249

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.

250

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average Tested

251

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average Tested3.

252

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average

253

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.

254

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.2.

255

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.2.3.

256

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.2.3.4.

257

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.2.3.4.5.

258

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.

259

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.7. Energy

260

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.7. Energy8.

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.7. Energy8.9.

262

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.7. Energy8.9.A.5.

263

SAS Output  

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

1. U.S. Coal Summary Statistics, 2008 - 2014" "(thousand short tons)" "Year and","Production1","Imports","Waste Coal","Producer and","Consumption","Exports","Consumer","Losses and"...

264

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SAND 2011-39584. Average Retail Price

265

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SAND 2011-39584. Average Retail

266

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SAND 2011-39584. Average Retail1.

267

SAS Output  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SAND 2011-39584. Average Retail1.2.

268

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.Percent of U.S.Coal

269

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.Percent of

270

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.Percent ofProductive

271

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.Percent

272

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.PercentProductive

273

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of

274

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverable Coal Reserves

275

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverable Coal

276

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverable

277

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverableAverage Number

278

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverableAverage

279

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverableAverageand

280

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by State

282

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by State2.

283

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by

284

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4. Coal

285

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4.

286

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4.6.

287

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4.6.7.

288

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4.6.7.8.

289

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity

290

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal ProductivityUnderground

291

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal

292

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales Price

293

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales Price2.

294

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales

295

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales4.

296

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales4.Coal

297

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average

298

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. AverageCoal

299

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. AverageCoalCoal

300

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. AverageCoalCoalCoal

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1.

302

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1.Report No.: DOE/EIA

303

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1.Report No.: DOE/EIA0.

304

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreases The448

305

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreases The448U.S.

306

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreases The448U.S.Average

307

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreases

308

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam Coal Exports by

309

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam Coal Exports

310

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam Coal

311

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam CoalAverage

312

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam CoalAverageU.S.

313

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam

314

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoal Production,

315

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoal

316

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoalU.S. Coke

317

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoalU.S.

318

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoalU.S.by

319

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoalU.S.byU.S.

320

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price Quantity and Average Price of

322

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price Quantity and Average Price

323

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price Quantity and Average

324

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 on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price Quantity and Average U.S.

325

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

B. U.S. Transformer Sustained Automatic Outage Counts and Hours by High-Voltage Size and NERC Region, 2012 Sustained Automatic Outage Counts High-Side Voltage (kV) Eastern...

326

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

B. U.S. Transformer Outages by Type and NERC region, 2012 Outage Type Eastern Interconnection TRE WECC Contiguous U.S. Circuit Outage Counts Automatic Outages (Sustained) 16.00 --...

327

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

B. U.S. Transformer Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 Transformer Outage Counts Sustained Outage Causes FRCC MRO NPCC RFC SERC SPP...

328

SAS Output  

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

,109.81,115.95,110.07,117.4,-6.2 "315 Apparel Manufacturing","w","w","w","w","w","w" "321 Wood Product Manufacturing","w","-","w","w","w","w" "322 Paper Manufacturing",87.55,88.68,...

329

Network and adaptive system of systems modeling and analysis.  

SciTech Connect (OSTI)

This report documents the results of an LDRD program entitled ''Network and Adaptive System of Systems Modeling and Analysis'' that was conducted during FY 2005 and FY 2006. The purpose of this study was to determine and implement ways to incorporate network communications modeling into existing System of Systems (SoS) modeling capabilities. Current SoS modeling, particularly for the Future Combat Systems (FCS) program, is conducted under the assumption that communication between the various systems is always possible and occurs instantaneously. A more realistic representation of these communications allows for better, more accurate simulation results. The current approach to meeting this objective has been to use existing capabilities to model network hardware reliability and adding capabilities to use that information to model the impact on the sustainment supply chain and operational availability.

Lawton, Craig R.; Campbell, James E. Dr. (.; .); Anderson, Dennis James; Eddy, John P.

2007-05-01T23:59:59.000Z

330

ENGINEERING 12 SPRING 2008 PHYSICAL SYSTEMS ANALYSIS  

E-Print Network [OSTI]

on the primary and secondary coils. #12;ENGINEERING 12, SPRING 2008 2/3 LABORATORY 1 One of the most commonENGINEERING 12 SPRING 2008 PHYSICAL SYSTEMS ANALYSIS LABORATORY 1: TRANSFORMERS Objectives or counterclockwise). In the following discussion the subscript 1 will be used for the primary coil and the subscript

Moreshet, Tali

331

PRESSURE TRANSIENT ANALYSIS FOR COMPOSITE SYSTEMS  

E-Print Network [OSTI]

SGP-TR-117 PRESSURE TRANSIENT ANALYSIS FOR COMPOSITE SYSTEMS Ani1 Kumar Ambastha October 1988 my graduate studies. #12;f #12;ABSTRACT A composite reservoir model is used to analyze well. A composite reservoir is made up of two or more regions. Each region has its own rock and fluid properties

Stanford University

332

Energy Engineering & Systems Analysis Success Stories  

E-Print Network [OSTI]

Energy Engineering & Systems Analysis Success Stories For further information, contact: Seth Snyder greenhouse gas emissions, and lower energy costs," said biochemical engineer Seth Snyder. Resin Wafer for Excellence in Technology Transfer for this separations technology. A team led by Argonne biochemical engineer

Kemner, Ken

333

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,...

334

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,...

335

INTRODUCTION TO SAS Statistical analyses, in practice, are always carried out by computer software. In this class, I will  

E-Print Network [OSTI]

INTRODUCTION TO SAS STAT 512 Statistical analyses, in practice, are always carried out by computer. Logging in, type your career account ID in the "Login" field. Use the tab key or the mouse (point on the screen) and hit the enter key. Once logged in, you can access the course materials from the Stat 512 web

Levine, Michael "Mihail"

336

Function Analysis and Decomposistion using Function Analysis Systems Technique  

SciTech Connect (OSTI)

The "Father of Value Analysis", Lawrence D. Miles, was a design engineer for General Electric in Schenectady, New York. Miles developed the concept of function analysis to address difficulties in satisfying the requirements to fill shortages of high demand manufactured parts and electrical components during World War II. His concept of function analysis was further developed in the 1960s by Charles W. Bytheway, a design engineer at Sperry Univac in Salt Lake City, Utah. Charles Bytheway extended Mile's function analysis concepts and introduced the methodology called Function Analysis Systems Technique (FAST) to the Society of American Value Engineers (SAVE) at their International Convention in 1965 (Bytheway 1965). FAST uses intuitive logic to decompose a high level, or objective function into secondary and lower level functions that are displayed in a logic diagram called a FAST model. Other techniques can then be applied to allocate functions to components, individuals, processes, or other entities that accomplish the functions. FAST is best applied in a team setting and proves to be an effective methodology for functional decomposition, allocation, and alternative development.

Wixson, James Robert

1999-06-01T23:59:59.000Z

337

Function Analysis and Decomposistion using Function Analysis Systems Technique  

SciTech Connect (OSTI)

The "Father of Value Analysis", Lawrence D. Miles, was a design engineer for General Electric in Schenectady, New York. Miles developed the concept of function analysis to address difficulties in satisfying the requirements to fill shortages of high demand manufactured parts and electrical components during World War II. His concept of function analysis was further developed in the 1960s by Charles W. Bytheway, a design engineer at Sperry Univac in Salt Lake City, Utah. Charles Bytheway extended Mile's function analysis concepts and introduced the methodology called Function Analysis Systems Techniques (FAST) to the Society of American Value Engineers (SAVE) at their International Convention in 1965 (Bytheway 1965). FAST uses intuitive logic to decompose a high level, or objective function into secondary and lower level functions that are displayed in a logic diagram called a FAST model. Other techniques can then be applied to allocate functions to components, individuals, processes, or other entities that accomplish the functions. FAST is best applied in a team setting and proves to be an effective methodology for functional decomposition, allocation, and alternative development.

J. R. Wixson

1999-06-01T23:59:59.000Z

338

Tank waste remediation system mission analysis report  

SciTech Connect (OSTI)

This document describes and analyzes the technical requirements that the Tank Waste Remediation System (TWRS) must satisfy for the mission. This document further defines the technical requirements that TWRS must satisfy to supply feed to the private contractors` facilities and to store or dispose the immobilized waste following processing in these facilities. This document uses a two phased approach to the analysis to reflect the two-phased nature of the mission.

Acree, C.D.

1998-01-09T23:59:59.000Z

339

Systems Analysis Success Stories | 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: AlternativeEnvironment,Institutes and1 SpecialMaximizing Opportunities |batteriesSystems Analysis

340

Production-systems analysis for fractured wells  

SciTech Connect (OSTI)

Production-systems analysis has been in use for many years to design completion configurations on the basis of an expected reservoir capacity. The most common equations used for the reservoir calculations are for steady-state radial flow. Most hydraulically fractured wells require the use of an unsteady-state production simulator to predict the higher flow rates associated with the stimulated well. These high flow rates may present problems with excessive pressure drops through production tubing designed for radial-flow production. Therefore, the unsteady-state nature of fractured-well production precludes the use of steady-state radial-flow inflow performance relationships (IPR's) to calculate reservoir performance. An accurate prediction of fractured-well production must be made to design the most economically efficient production configuration. It has been suggested in the literature that a normalized reference curve can be used to generate the IPR's necessary for production-systems analysis. However, this work shows that the reference curve for fractured-well response becomes time-dependent when reservoir boundaries are considered. A general approach for constructing IPR curves is presented, and the use of an unsteady-state fractured-well-production simulator coupled with the production-systems-analysis approach is described. A field case demonstrates the application of this method to fractured wells.

Hunt, J.L. (Halliburton Services (US))

1988-11-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Hydrgoen Storage Systems Analysis Working Group Meeting Summary...  

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

Analysis Working Group Meeting Summary Report Summary report from the May 17, 2007 Hydrogen Storage Systems Analysis Working Group Meeting ssawgmaysummary.pdf More...

342

Apparatus and system for multivariate spectral analysis  

DOE Patents [OSTI]

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.

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

2003-06-24T23:59:59.000Z

343

Analysis of a piping system for requalification  

SciTech Connect (OSTI)

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.

Hsieh, B.J.; Tang, Yu.

1992-01-01T23:59:59.000Z

344

Analysis of a piping system for requalification  

SciTech Connect (OSTI)

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.

Hsieh, B.J.; Tang, Yu

1992-05-01T23:59:59.000Z

345

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...

346

K West integrated water treatment system subproject safety analysis document  

SciTech Connect (OSTI)

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.

SEMMENS, L.S.

1999-02-24T23:59:59.000Z

347

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...

348

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...

349

Incorporating HVDC's into monitoring and power system analysis  

E-Print Network [OSTI]

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...

Krishnaswamy, Vikram

2002-01-01T23:59:59.000Z

350

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions andData andFleet Test and Evaluation PhotoSystems Analysis and

351

Cost analysis of energy storage systems for electric utility applications  

SciTech Connect (OSTI)

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.

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

352

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

E-Print Network [OSTI]

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 ...

Thomas, John P., IV

2013-01-01T23:59:59.000Z

353

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

E-Print Network [OSTI]

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

Forster, T.E.

354

Reliability importance analysis of Markovian systems at steady state using perturbation analysis  

E-Print Network [OSTI]

Reliability importance analysis of Markovian systems at steady state using perturbation analysis for static systems, i.e. systems described by combinatorial reliability models (fault or event trees for steady state sensitivity analysis of Markov processes in reliability studies. Keywords: perturbation

Paris-Sud XI, Université de

355

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

E-Print Network [OSTI]

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 ...

Chiang, Wei-Shan

2014-01-01T23:59:59.000Z

356

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

E-Print Network [OSTI]

for the power management on board hybrid vehicles that allows the vehicle to reach its maximum range along class of hybrid vehicles, namely, range extender electric vehicles (REEV). This kind of hybridization departures from a full electric vehicle that has an additional module ­ the range extender (RE) ­ as an extra

Boyer, Edmond

357

Systems Analysis Department Annual Report 2001  

E-Print Network [OSTI]

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

358

A Spatial Planning and Analysis System for Wildland Fire Management  

E-Print Network [OSTI]

STARFIRE 11/29/2011 A Spatial Planning and Analysis System for Wildland Fire Management Welcome is an advanced and powerful spatial fire management planning and analysis system which is designed to provide visual and analytic support for fire management planning, decisions and communication. The system

359

Traffic Analysis: From Stateful Firewall to Network Intrusion Detection System  

E-Print Network [OSTI]

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

Chiueh, Tzi-cker

360

Decomposition algorithms for multi-area power system analysis  

E-Print Network [OSTI]

. This dissertation investigates decomposition algorithms for multi-area power system transfer capability analysis and economic dispatch analysis. All of the proposed algorithms assume that areas do not share their network operating and economic information among...

Min, Liang

2007-09-17T23:59:59.000Z

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Notes 11. Modal Analysis of MDOF Systems with Viscous Damping  

E-Print Network [OSTI]

? (3) where in general ? is a complex number. Substitution of Eq. (3) into Eq. (2) leads to the following characteristic equation: () () 2 0 ? ?? ?? ++ = = ?? MCK? f ? (4) MEEN 617 HD 11 Modal Analysis of MDOF... MEEN 617 HD 11 Modal Analysis of MDOF Systems with Viscous Damping L. San Andr?s ? 2008 1 MEEN 617 Handout #11 MODAL ANALYSIS OF MDOF Systems with VISCOUS DAMPING ^ Symmetric Motion of a n-DOF linear system...

San Andres, Luis

2008-01-01T23:59:59.000Z

362

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...

363

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

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

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

364

Supplement Analysis for the Transmission System Vegetation Management...  

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

14, 2001 REPLY TO ATTN OF: KEP-4 SUBJECT: Supplement Analysis for the Transmission System Vegetation Management Program FEIS (DOEEIS-0285SA-35) James Jellison - TFOOlympia...

365

Supplement Analysis for the Transmission System Vegetation Management...  

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

5, 2001 REPLY TO ATTN OF: KEPZ992 SUBJECT: Supplement Analysis for the Transmission System Vegetation Management Program FEIS (DOEEIS-0285SA-25) Elizabeth Johnson - TFRThe...

366

Space Dust Analysis Could Provide Clues to Solar System Origins  

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

of oxygen. Isotope analysis could help confirm that the dust originated outside the solar system, but it's a process that would destroy the precious samples. For now,...

367

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...

368

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.

369

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.

370

STABILITY ANALYSIS OF INTERCONNECTED POWER SYSTEMS COUPLED WITH MARKET DYNAMICS  

E-Print Network [OSTI]

STABILITY ANALYSIS OF INTERCONNECTED POWER SYSTEMS COUPLED WITH MARKET DYNAMICS F.L. Alvarado1 J of generators and network interconnections. This paper examines questions of stability in such coupled systems

371

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...

372

Technology Portfolio Planning by Weighted Graph Analysis of System Architectures  

E-Print Network [OSTI]

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

de Weck, Olivier L.

373

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...

374

Availability Analysis of the Ventilation Stack CAM Interlock System  

E-Print Network [OSTI]

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.

Young, J

2000-01-01T23:59:59.000Z

375

Safety Analysis Of Automated Highway Systems  

E-Print Network [OSTI]

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

Leveson, Nancy G.

1997-01-01T23:59:59.000Z

376

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.

377

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

378

Advanced Process and Chemical Complex Analysis Systems Derya Ozyurtb  

E-Print Network [OSTI]

157g Advanced Process and Chemical Complex Analysis Systems Derya Ozyurtb , Aimin Xub , Thomas for statements or opinions contained in papers or printed in its publications. #12;Abstract: The Advanced Process Analysis System is used to perform economic and environmental evaluations of a plant. The main components

Pike, Ralph W.

379

A theoretical systemic analysis of organizational tacit knowledge memorization  

E-Print Network [OSTI]

. Thus, individual learning will lead to organizational learning, which later will differentiate1 A theoretical systemic analysis of organizational tacit knowledge memorization Iskander ZOUAGHI halshs-00665703,version1-2Feb2012 #12;2 A theoretical systemic analysis of organizational tacit knowledge

Paris-Sud XI, Université de

380

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

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

An analysis of distributed solar fuel systems  

E-Print Network [OSTI]

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 ...

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

2012-01-01T23:59:59.000Z

382

Systems integration and analysis of advanced life support technologies  

E-Print Network [OSTI]

................................................................................... 17 3.1. Methodical Analysis of ALS Technologies.............................................. 17 3.2. Computer-Aided Analysis ........................................................................ 18 4 METHODS OF ANALYSIS... requirement of the system [kWth] Ceq Mass equivalency factor for the cooling infrastructure [kg/kWth] CT Total crewtime requirement of the system [CM-h/y] D Duration of the mission segment of interest [y] CTeq Mass equivalency factor for the crewtime...

Nworie, Grace A.

2009-06-02T23:59:59.000Z

383

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

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

Integrated Vehicle Thermal Management Power Electronic Thermal System Performance and Integration Characterization and Development of Advanced Heat Transfer Technologies...

384

Benchmark of SCALE (SAS2H) isotopic predictions of depletion analyses for San Onofre PWR MOX fuel  

SciTech Connect (OSTI)

The isotopic composition of mixed-oxide (MOX) fuel, fabricated with both uranium and plutonium, after discharge from reactors is of significant interest to the Fissile Materials Disposition Program. The validation of the SCALE (SAS2H) depletion code for use in the prediction of isotopic compositions of MOX fuel, similar to previous validation studies on uranium-only fueled reactors, has corresponding significance. The EEI-Westinghouse Plutonium Recycle Demonstration Program examined the use of MOX fuel in the San Onofre PWR, Unit 1, during cycles 2 and 3. Isotopic analyses of the MOX spent fuel were conducted on 13 actinides and {sup 148}Nd by either mass or alpha spectrometry. Six fuel pellet samples were taken from four different fuel pins of an irradiated MOX assembly. The measured actinide inventories from those samples has been used to benchmark SAS2H for MOX fuel applications. The average percentage differences in the code results compared with the measurement were {minus}0.9% for {sup 235}U and 5.2% for {sup 239}Pu. The differences for most of the isotopes were significantly larger than in the cases for uranium-only fueled reactors. In general, comparisons of code results with alpha spectrometer data had extreme differences, although the differences in the calculations compared with mass spectrometer analyses were not extremely larger than that of uranium-only fueled reactors. This benchmark study should be useful in estimating uncertainties of inventory, criticality and dose calculations of MOX spent fuel.

Hermann, O.W.

2000-02-01T23:59:59.000Z

385

Microcomputer Analysis of Pumping System Performance  

E-Print Network [OSTI]

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...

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

386

Failure analysis issues in microelectromechanical systems (MEMS).  

SciTech Connect (OSTI)

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.

Walraven, Jeremy Allen

2005-07-01T23:59:59.000Z

387

A systems approach to food accident analysis  

E-Print Network [OSTI]

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. ...

Helferich, John D

2011-01-01T23:59:59.000Z

388

Process of system design and analysis  

SciTech Connect (OSTI)

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.

Gardner, B.

1995-09-01T23:59:59.000Z

389

Electron Spectrometer: Scanning Multiprobe Surface Analysis System...  

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

based systems can be used as electrolytes to develop solid oxide fuel cells for clean energy production and to prevent air... Characterization of Amorphous Zinc Tin Oxide...

390

Fuel Cell System Improvement for Model-Based Diagnosis Analysis  

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

391

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 Presentation 3 A fuel cell vehicle would contain the PEMFC system modeled in this project along with additional

392

Nonlinear analysis of a reaction-diffusion system: Amplitude equations  

SciTech Connect (OSTI)

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.

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

2012-10-15T23:59:59.000Z

393

Modal Analysis of Continuous Structrual System with Tapered Cantilevered Members  

E-Print Network [OSTI]

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...

Kim, Yoon Mo

2012-02-14T23:59:59.000Z

394

Fuel Cell Power Systems Analysis Patrick DavisPatrick Davis  

E-Print Network [OSTI]

Power Systems · Balance-of-plant (compressors, humidifiers, heat exchangers, sensors, controls) · Cost hydrogen 500020001000HoursDurability 45125325$/kWCost 325250140W/LPower density Operating on Tier 2 · Fuel Cell Vehicle Systems Analysis · Cost Analyses of Fuel Cell Stacks/ Systems · DFMA Cost Estimates

395

Route profile analysis system and method  

DOE Patents [OSTI]

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.

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

1982-07-29T23:59:59.000Z

396

Bifurcation Analysis of Various Power System Models  

E-Print Network [OSTI]

generator and transmission system. Di erent modeling levels with their respective di erential-algebraic equa, the generation or system loading levels are used as bifurcation parameters, which are varied slowly, moving erent induction motor load models are considered. The loads were modeled as constant, linear

Cañizares, Claudio A.

397

An Experimental Metagenome Data Management and AnalysisSystem  

SciTech Connect (OSTI)

The application of shotgun sequencing to environmental samples has revealed a new universe of microbial community genomes (metagenomes) involving previously uncultured organisms. Metagenome analysis, which is expected to provide a comprehensive picture of the gene functions and metabolic capacity of microbial community, needs to be conducted in the context of a comprehensive data management and analysis system. We present in this paper IMG/M, an experimental metagenome data management and analysis system that is based on the Integrated Microbial Genomes (IMG) system. IMG/M provides tools and viewers for analyzing both metagenomes and isolate genomes individually or in a comparative context.

Markowitz, Victor M.; Korzeniewski, Frank; Palaniappan, Krishna; Szeto, Ernest; Ivanova, Natalia N.; Kyrpides, Nikos C.; Hugenholtz, Philip

2006-03-01T23:59:59.000Z

398

Hierarchical Task Analysis of Intrusion Detection Systems  

E-Print Network [OSTI]

.......................... 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

Blustein, J.

399

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

SciTech Connect (OSTI)

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.

Thomas, John (Massachusetts Institute of Technology)

2012-05-01T23:59:59.000Z

400

Commonality analysis for exploration life support systems  

E-Print Network [OSTI]

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 ...

Cunio, Phillip M

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Design and analysis of reconfigurable analog system  

E-Print Network [OSTI]

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, ...

Lajevardi, Payam

2011-01-01T23:59:59.000Z

402

Analysis of Bitcoin Pooled Mining Reward Systems  

E-Print Network [OSTI]

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.

Rosenfeld, Meni

2011-01-01T23:59:59.000Z

403

Vulnerability Analysis of Energy Delivery Control Systems  

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

coding practices can be found in new and old products alike, and the introduction of Web applications into SCADA systems has created more, as well as new, types of...

404

Uncertainty analysis of power systems using collocation  

E-Print Network [OSTI]

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, ...

Taylor, Joshua Adam

2008-01-01T23:59:59.000Z

405

Electron Spectrometer: Scanning Multiprobe Surface Analysis System...  

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

the system will include an intense He lamp for ultraviolet photoelectron spectroscopy (UPS), an argon ion gun for sputter depth profiling, and a C60 ion gun for high-resolution...

406

POWER GRID DYNAMICS: ENHANCING POWER SYSTEM OPERATION THROUGH PRONY ANALYSIS  

SciTech Connect (OSTI)

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.

Ray, C.; Huang, Z.

2007-01-01T23:59:59.000Z

407

Analysis of Hybrid Hydrogen Systems: Final Report  

SciTech Connect (OSTI)

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.

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

2010-01-01T23:59:59.000Z

408

-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]

-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

Dasgupta, Dipankar

409

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

E-Print Network [OSTI]

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 ...

Bachmann, Chris H., III (Christopher Henry)

2008-01-01T23:59:59.000Z

410

AC system stability analysis and assessment for Shipboard Power Systems  

E-Print Network [OSTI]

due to reconfiguration might cause voltage instability, such as progressive voltage decreases or voltage oscillations. SPS stability thus should be assessed to ensure the stable operation of a system during reconfiguration. In this dissertation, time...

Qi, Li

2006-04-12T23:59:59.000Z

411

Analysis of Lyapunov Control for Hamiltonian Quantum Systems  

E-Print Network [OSTI]

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.

Xiaoting Wang; Sonia Schirmer

2008-05-19T23:59:59.000Z

412

Multiscale Analysis and Optimisation of Photosynthetic Solar Energy Systems  

E-Print Network [OSTI]

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.

Andrew K. Ringsmuth

2014-02-24T23:59:59.000Z

413

Multiscale Analysis and Optimisation of Photosynthetic Solar Energy Systems  

E-Print Network [OSTI]

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.

Ringsmuth, Andrew K

2014-01-01T23:59:59.000Z

414

Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems  

E-Print Network [OSTI]

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

Müller-Olm, Markus

415

Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems  

E-Print Network [OSTI]

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

Müller-Olm, Markus

416

Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems  

E-Print Network [OSTI]

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

Touili, Tayssir

417

Regular Symbolic Analysis of Dynamic Networks of Pushdown Systems  

E-Print Network [OSTI]

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

Müller-Olm, Markus

418

Analysis of coupled body mooring and fender system  

E-Print Network [OSTI]

The hydrodynamic excitation and response behavior of multi-body systems with varying degrees of coupling presents many challenges for designers of offshore structures. In this study, attention is focused upon the analysis and interpretation...

Girija Sasidharan Pillai, Harish

2005-11-01T23:59:59.000Z

419

Fuel Cells Vehicle Systems Analysis (Fuel Cell Freeze Investigation)  

SciTech Connect (OSTI)

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.

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

2005-05-01T23:59:59.000Z

420

Modeling and Analysis of CSP Systems (Fact Sheet)  

SciTech Connect (OSTI)

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.

Not Available

2010-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

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...

422

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...

423

Complete VAX/VMS DNA/protein sequence analysis system  

SciTech Connect (OSTI)

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.

Smith, D.W.

1987-05-01T23:59:59.000Z

424

System performance analysis of stretched membrane heliostats  

SciTech Connect (OSTI)

The optical performance of both focused and unfocused stretched membrane heliostats was examined in the context of the overall cost and performance of central receiver systems. The sensitivity of optical performance to variations in design parameters such as the system size (capacity), delivery temperature, heliostat size, and heliostat surface quality was also examined. The results support the conclusion that focused stretched membrane systems provide an economically attractive alternative to current glass/metal heliostats over essentially the entire range of design parameters studied. In addition, unfocused stretched membrane heliostats may be attractive for a somewhat more limited range of applications, which would include the larger plant sizes (e.g., 450 MW) and lower delivery temperatures (e.g., 450/sup 0/C), or situations in which the heliostat size could economically be reduced.

Anderson, J.V.; Murphy, L.M.; Short, W.; Wendelin, T.

1985-12-01T23:59:59.000Z

425

Multi Megawatt Power System Analysis Report  

SciTech Connect (OSTI)

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.

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

426

EM threat analysis for wireless systems.  

SciTech Connect (OSTI)

Modern digital radio systems are complex and must be carefully designed, especially when expected to operate in harsh propagation environments. The ability to accurately predict the effects of propagation on wireless radio performance could lead to more efficient radio designs as well as the ability to perform vulnerability analyses before and after system deployment. In this report, the authors--experts in electromagnetic (EM) modeling and wireless communication theory--describe the construction of a simulation environment that is capable of quantifying the effects of wireless propagation on the performance of digital communication.

Burkholder, R. J. (Ohio State University Electroscience Laboratory); Mariano, Robert J.; Schniter, P. (Ohio State University Electroscience Laboratory); Gupta, I. J. (Ohio State University Electroscience Laboratory)

2006-06-01T23:59:59.000Z

427

Analysis of Lyapunov Method for Control of Quantum Systems  

E-Print Network [OSTI]

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.

Xiaoting Wang; Sonia G. Schirmer

2008-05-19T23:59:59.000Z

428

Interactive modeling and analysis of intruder detection systems  

E-Print Network [OSTI]

INTERACTIVE MODELING AND ANALYSIS OF INTRUDER DETECTION SYSTEMS A Thesis by MICHAEL WILLIAM JONES Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER... OF SCIENCE December 1991 Major Subject: Industrial Engineering INTERACTIVE MODELING AND ANALYSIS OF INTRUDER DETECTION SYSTEMS A Thesis by MICHAEL WILLIAM JONES Approved as to style and content by: Robert E . Shannon (Co ? Chair of Committee) Kav...

Jones, Michael William

1991-01-01T23:59:59.000Z

429

Interpolating dynamical systems: Applications to experimental data analysis  

SciTech Connect (OSTI)

Experimental data from Rayleigh-Benard convection is used to demonstrate new techniques in data analysis. The data, in the form of Poincare sections, are fit to a map of the plane as a function of a system control parameter. This provides a very useful method for interpolating experimental low-dimensional dynamical systems. The fitted map can then be studied using numerical bifurcation methods or other nonlinear dynamics analysis techniques. 16 refs., 3 figs., 1 tab.

Ecke, R.E.

1991-01-01T23:59:59.000Z

430

Unit hydrograph application to stormwater collection system design and analysis  

E-Print Network [OSTI]

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...

Spinks, Melvin Gerald

1987-01-01T23:59:59.000Z

431

Energy Engineering & Systems Analysis Success Stories  

E-Print Network [OSTI]

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

Kemner, Ken

432

Systems reliability analysis for the national ignition facility  

SciTech Connect (OSTI)

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.

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

1996-06-12T23:59:59.000Z

433

Reachability Analysis of a Biodiesel Production System Using Stochastic Hybrid Systems  

E-Print Network [OSTI]

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

Koutsoukos, Xenofon D.

434

Dynamical Systems and Applications of Nonlinear Functional Analysis to Dynamical Systems  

E-Print Network [OSTI]

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

Zhang, Meirong

435

Flow Analysis on a Limited Volume Chilled Water System  

SciTech Connect (OSTI)

LANL Currently has a limited volume chilled water system for use in a glove box, but the system needs to be updated. Before we start building our new system, a flow analysis is needed to ensure that there are no high flow rates, extreme pressures, or any other hazards involved in the system. In this project the piping system is extremely important to us because it directly affects the overall design of the entire system. The primary components necessary for the chilled water piping system are shown in the design. They include the pipes themselves (perhaps of more than one diameter), the various fitting used to connect the individual pipes to form the desired system, the flow rate control devices (valves), and the pumps that add energy to the fluid. Even the most simple pipe systems are actually quite complex when they are viewed in terms of rigorous analytical considerations. I used an 'exact' analysis and dimensional analysis considerations combined with experimental results for this project. When 'real-world' effects are important (such as viscous effects in pipe flows), it is often difficult or impossible to use only theoretical methods to obtain the desired results. A judicious combination of experimental data with theoretical considerations and dimensional analysis are needed in order to reduce risks to an acceptable level.

Zheng, Lin [Los Alamos National Laboratory

2012-07-31T23:59:59.000Z

436

SWEPP Assay System Version 2.0 software design description  

SciTech Connect (OSTI)

The Idaho National Engineering Laboratory (INEL) Stored Waste Examination Pilot Plant (SWEPP) operations staff use nondestructive analysis methods to characterize the radiological contents of contact-handled radioactive waste containers. Containers of waste from Rocky Flats Environmental Technology Site and other Department of Energy (DOE) sites are currently stored at SWEPP. Before these containers can be shipped to the Waste Isolation Pilot Plant (WIPP), SWEPP must verify compliance with storage, shipping, and disposal requirements. This program has been in operation since 1985 at the INEL Radioactive Waste Management Complex (RWMC). One part of the SWEPP program measures neutron emissions from the containers and estimates the mass of plutonium and other transuranic (TRU) isotopes present. A Passive/Active Neutron (PAN) assay system developed at the Los Alamos National Laboratory is used to perform these measurements. A computer program named NEUT2 was originally used to perform the data acquisition and reduction functions for the neutron measurements. This program was originally developed at Los Alamos and extensively modified by a commercial vendor of PAN systems and by personnel at the INEL. NEUT2 uses the analysis methodology outlined, but no formal documentation exists on the program itself. The SWEPP Assay System (SAS) computer program replaced the NEUT2 program in early 1994. The SAS software was developed using an `object model` approach and is documented in accordance with American National Standards Institute (ANSI) and Institute of Electrical and Electronic Engineers (IEEE) standards. The new program incorporates the basic analysis algorithms found in NEUT2. Additional functionality and improvements include a graphical user interface, the ability to change analysis parameters without program code modification, an `object model` design approach and other features for improved flexibility and maintainability.

East, L.V.; Marwil, E.S.

1996-08-01T23:59:59.000Z

437

Building integrated photovoltaic systems analysis: Preliminary report  

SciTech Connect (OSTI)

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.

none,

1993-08-01T23:59:59.000Z

438

Ris National Laboratory Systems Analysis Department  

E-Print Network [OSTI]

.risoe.dk/rispubl/art/2007_76.pdf Value of electric heat boilers and heat pumps for wind power integration Meibom, P.doi.org/10.1002/we.224 #12;1 Value of electric heat boilers and heat pumps for wind power integration 3HWHU 0: European Commission; Contract number: ENK5-CT-2002-00663. .H\\ZRUGV wind power, system integration, heat

439

Vehicle Systems Analysis Technical Team Roadmap  

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 RankCombustion |Energy Usage »of EnergyTheTwoVulnerabilities | DepartmentReactiveVehicle Systems

440

Analysis of LNG peakshaving-facility release-prevention systems  

SciTech Connect (OSTI)

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.

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

1982-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Water Rights Analysis Package (WRAP) Daily Modeling System  

E-Print Network [OSTI]

-2011) Contract 582-12-10220 (2011-2013) Technical Report No. 430 Texas Water Resources Institute The Texas A&M University System College Station, Texas 77843-2118 August 2012 ii iii TABLE OF CONTENTS Chapter 1 Water Rights Analysis... Package (WRAP) Modeling System .......................... 1 WRAP Documentation ..................................................................................................... 1 WRAP Programs...

Wurbs, R.; Hoffpauir, R.

2012-10-01T23:59:59.000Z

442

Thermodynamic Analysis of Combined Cycle District Heating System  

E-Print Network [OSTI]

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...

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

2011-01-01T23:59:59.000Z

443

FUEL SUPPLY SYSTEM ANALYSIS FOR ESF PACKAGE 1E  

SciTech Connect (OSTI)

The primary objective of this analysis is to capture new inputs relative to the design of the Fuel Supply System (FSS) at the Yucca Mountain Site Characterization Project (YMP) Exploratory Studies Facility (ESF). The new inputs are analyzed and changes to the Fuel Supply System are made as necessary.

D.F. Vanica

1995-06-14T23:59:59.000Z

444

Information-Theoretic Analysis of an Energy Harvesting Communication System  

E-Print Network [OSTI]

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

Ulukus, Sennur

445

Solar Energy Systems - Research - Systems Analysis - Smart Grid  

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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administrationcontroller systemsBiSite CulturalDepartment ofat

446

Task 11 - systems analysis of environmental management technologies  

SciTech Connect (OSTI)

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.

Musich, M.A.

1997-06-01T23:59:59.000Z

447

Multiple stellar systems under photometric and astrometric analysis  

E-Print Network [OSTI]

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.

P. Zasche

2008-01-28T23:59:59.000Z

448

Function analysis for waste information systems  

SciTech Connect (OSTI)

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.

Sexton, J.L.; Neal, C.T.; Heath, T.C.; Starling, C.D.

1996-04-01T23:59:59.000Z

449

SPSS and SAS procedures for estimating indirect effects in simple mediation models  

E-Print Network [OSTI]

Researchers often conduct mediation analysis in order to indirectly assess the effect of a proposed cause on some outcome through a proposed mediator. The utility of mediation analysis stems from its ability to go beyond ...

Preacher, K. J.; Hayes, A. F.

2004-01-01T23:59:59.000Z

450

E-Print Network 3.0 - analysis system applicable Sample Search...  

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

and Summary: Dynamic Systems Analysis and Simulation Dynamic Systems Analysis and Simulation (DSAS) Group... members have extensive experience developing novel applications...

451

Pump Life Cycle Costs: A Guide to LCC Analysis for Pumping Systems...  

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

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...

452

SciTech Connect: Cost analysis of energy storage systems for...  

Office of Scientific and Technical Information (OSTI)

Cost analysis of energy storage systems for electric utility applications Citation Details In-Document Search Title: Cost analysis of energy storage systems for electric utility...

453

Earthquake warning system for infrastructures : a scoping analysis.  

SciTech Connect (OSTI)

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.

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

454

Life cycle analysis of energy systems: Methods and experience  

SciTech Connect (OSTI)

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.

Morris, S.C.

1992-08-01T23:59:59.000Z

455

Life cycle analysis of energy systems: Methods and experience  

SciTech Connect (OSTI)

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.

Morris, S.C.

1992-01-01T23:59:59.000Z

456

Evaluation of energy system analysis techniques for identifying underground facilities  

SciTech Connect (OSTI)

This report describes the results of a study to determine the feasibility and potential usefulness of applying energy system analysis techniques to help detect and characterize underground facilities that could be used for clandestine activities. Four off-the-shelf energy system modeling tools were considered: (1) ENPEP (Energy and Power Evaluation Program) - a total energy system supply/demand model, (2) ICARUS (Investigation of Costs and Reliability in Utility Systems) - an electric utility system dispatching (or production cost and reliability) model, (3) SMN (Spot Market Network) - an aggregate electric power transmission network model, and (4) PECO/LF (Philadelphia Electric Company/Load Flow) - a detailed electricity load flow model. For the purposes of most of this work, underground facilities were assumed to consume about 500 kW to 3 MW of electricity. For some of the work, facilities as large as 10-20 MW were considered. The analysis of each model was conducted in three stages: data evaluation, base-case analysis, and comparative case analysis. For ENPEP and ICARUS, open source data from Pakistan were used for the evaluations. For SMN and PECO/LF, the country data were not readily available, so data for the state of Arizona were used to test the general concept.

VanKuiken, J.C.; Kavicky, J.A.; Portante, E.C. [and others

1996-03-01T23:59:59.000Z

457

Thermal hydraulic aspects in the analysis of LMFBR disrupted-core situations  

SciTech Connect (OSTI)

This paper presents the thermal-hydraulic aspects of current interest in the modeling of LMFBR hypothetical core-disruptive accidents, with special emphasis on the Loss of Flow situations. The models presented have been incorporated in LEVITATE, a code for the analysis of fuel and cladding dynamics under LOF conditions, which has recently become part of the SAS4A code system. The influence of different thermal-hydraulic models on fuel motion is illustrated by a comparison between the results calculated by LEVITATE, the data from the L7-TREAT experiment and the results calculated by SLUMPY. The results calculated by LEVITATE are in fair agreement with the experimentally observed early fuel dispersal. The marginally acceptable energetic events obtained in the analysis of high void-worth LMFBR cores during Loss-of-Flow transients coupled with uncertainties about some of the thermal-hydraulic parameters motivate, among other factors, the need for the design low void-worth LMFBR cores.

Tentner, A.M.; Wider, H.U.

1981-01-01T23:59:59.000Z

458

Macro-System Model for Hydrogen Energy Systems Analysis in Transportation: Preprint  

SciTech Connect (OSTI)

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.

Diakov, V.; Ruth, M.; Sa, T. J.; Goldsby, M. E.

2012-06-01T23:59:59.000Z

459

Methods for air cleaning system design and accident analysis  

SciTech Connect (OSTI)

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.

Gregory, W.S.; Nichols, B.D.

1986-01-01T23:59:59.000Z

460

Transportation Policy Analysis and Systems Planning Fall 2009/2010  

E-Print Network [OSTI]

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

Singh, Jaswinder Pal

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Analysis of Preventive Maintenance in Transactions Based Software Systems  

E-Print Network [OSTI]

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

Telek, Miklós

462

Societal Research Archives System : Retrieval, quality control and analysis  

E-Print Network [OSTI]

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

White, Douglas R.

463

A DESIGN AND ANALYSIS TOOL FOR SOLAR ELECTRIC SYSTEMS  

E-Print Network [OSTI]

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

Delaware, University of

464

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

465

An Analysis of Heterogeneity in Futuristic Unmanned Vehicle Systems  

E-Print Network [OSTI]

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

Cummings, Mary "Missy"

466

Performance Validation and Energy Analysis of HVAC Systems using Simulation  

E-Print Network [OSTI]

that energy savings of between 15% and 40% could be made in commercial buildings by closer monitoring and supervision of energy-usage and related data. An earlier study by Kao and Pierce (1983) showed that sensor1 Performance Validation and Energy Analysis of HVAC Systems using Simulation Tim Salsbury and Rick

Diamond, Richard

467

Development of a Clinical Pathways Analysis System with Adaptive Bayesian  

E-Print Network [OSTI]

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

Kopec, Danny

468

System Analysis and Design Spring 2011, Williston Campus  

E-Print Network [OSTI]

CIS4120 System Analysis and Design Spring 2011, Williston Campus Vermont Technical College Class Meeting: MW 2:25-3:40 BLP 201 Instructor: Craig A. Damon (cdamon@vtc.edu) BLP 424 Williston Office Hours am in Randolph TT and Williston MWF. Course Overview: This course gives students hands-on experience

Damon, Craig A.

469

Wind Energy Conversion Systems Fault Diagnosis Using Wavelet Analysis  

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

470

Patent systems for encouraging innovation: Lessons from economic analysis1  

E-Print Network [OSTI]

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

Boyer, Edmond

471

ARIES-CS MAINTENANCE SYSTEM DEFINITION AND ANALYSIS  

E-Print Network [OSTI]

ARIES-CS MAINTENANCE SYSTEM DEFINITION AND ANALYSIS LESTER M. WAGANER* and RICHARD J. PEIPERT, Jr in the electronic version. I. INTRODUCTION The ARIES studies, sponsored by the U.S. Depart- ment of Energy and led how the physics and coil definition determine and influence the power core elements. Especially

472

Analysis of transmission system faults in the phase domain  

E-Print Network [OSTI]

. With the advanced development of computers, there is a possibility to totally get rid of the sequence method. In this thesis, a short circuit analysis method based on phase domain is developed. After the three sequence admittance matrices of the system are built...

Zhu, Jun

2004-11-15T23:59:59.000Z

473

A MACHINE VISION SYSTEM FOR FORENSIC ANALYSIS Ovidiu Ghita1  

E-Print Network [OSTI]

A MACHINE VISION SYSTEM FOR FORENSIC ANALYSIS Ovidiu Ghita1 , René Gapert2 , Laura Monks1 , Jason Forensic Anthropology Unit, Department of Human Anatomy and Physiology, University College Dublin remains are analysed by forensic anthropologists in order to draw conclusions about the probable identity

Whelan, Paul F.

474

Response margins of the dynamic analysis of piping systems  

SciTech Connect (OSTI)

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.

Johnson, J.J.; Benda, B.J.; Chuang, T.Y.; Smith, P.D.

1984-04-01T23:59:59.000Z

475

Game theoretic analysis of physical protection system design  

SciTech Connect (OSTI)

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.

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

476

REVIEW OF NRC APPROVED DIGITAL CONTROL SYSTEMS ANALYSIS  

SciTech Connect (OSTI)

Preliminary design concepts for the proposed Subsurface Repository at Yucca Mountain indicate extensive reliance on modern, computer-based, digital control technologies. The purpose of this analysis is to investigate the degree to which the U. S. Nuclear Regulatory Commission (NRC) has accepted and approved the use of digital control technology for safety-related applications within the nuclear power industry. This analysis reviews cases of existing digitally-based control systems that have been approved by the NRC. These cases can serve as precedence for using similar types of digitally-based control technologies within the Subsurface Repository. While it is anticipated that the Yucca Mountain Project (YMP) will not contain control systems as complex as those required for a nuclear power plant, the review of these existing NRC approved applications will provide the YMP with valuable insight into the NRCs review process and design expectations for safety-related digital control systems. According to the YMP Compliance Program Guidance, portions of various NUREGS, Regulatory Guidelines, and nuclear IEEE standards the nuclear power plant safety related concept would be applied to some of the designs on a case-by-case basis. This analysis will consider key design methods, capabilities, successes, and important limitations or problems of selected control systems that have been approved for use in the Nuclear Power industry. An additional purpose of this analysis is to provide background information in support of further development of design criteria for the YMP. The scope and primary objectives of this analysis are to: (1) Identify and research the extent and precedence of digital control and remotely operated systems approved by the NRC for the nuclear power industry. Help provide a basis for using and relying on digital technologies for nuclear related safety critical applications. (2) Identify the basic control architecture and methods of key digital control systems approved for use in the nuclear power industry by the NRC. (3) Identify and discuss key design issues, features, benefits, and limitations of these NRC approved digital control systems that can be applied as design guidance and correlated to the Monitored Geologic Repository (MGR) design requirements. (4) Identify codes and standards used in the design of these NRC approved digital control systems and discuss their possible applicability to the design of a subsurface nuclear waste repository. (5) Evaluate the NRC approved digital control system's safety, reliability and maintainability features and issues. Apply these to MGR design methodologies and requirements. (6) Provide recommendations for use in developing design criteria in the System Description Documents for the digital control systems of the subsurface nuclear waste repository at Yucca Mountain. (7) Develop recommendations for applying NRC approval methods for digital control systems for the subsurface nuclear waste repository at Yucca Mountain. This analysis will focus on the development of the issues, criteria and methods used and required for identifying the appropriate requirements for digital based control systems. Attention will be placed on development of recommended design criteria for digital controls including interpretation of codes, standards and regulations. Attention will also focus on the use of digital controls and COTS (Commercial Off-the-shelf) technology and equipment in selected NRC approved digital control systems, and as referenced in applicable codes, standards and regulations. The analysis will address design issues related to COTS technology and how they were dealt with in previous NRC approved digital control systems.

D.W. Markman

1999-09-17T23:59:59.000Z

477

Fire Simulation, Evacuation Analysis and Proposal of Fire Protection Systems Inside an Underground Cavern  

E-Print Network [OSTI]

Fire Simulation, Evacuation Analysis and Proposal of Fire Protection Systems Inside an Underground Cavern

Stella, Carlo

478

Method for reliability analysis of complex reactor systems. [LMFBR  

SciTech Connect (OSTI)

A method and a computer code for efficient and accurate reliability analyses of complex reactor systems are described and illustrated through an example. The method permits realistic analyses through its ability to accurately model and evaluate instantaneous and average unavailabilities for large systems with dependencies. The component models can include continuously monitored, non-repairable, and periodically tested components which are subject to failures resulting from components which are subject to failures resulting from component demands, stand-by conditions, human errors associated with testing and repair, as well as failures during actual operation. The numerical process used is efficient and allows analysis of general system configurations with arbitrary scheduling of maintenance operations.

Elerath, J.G.; Vaurio, J.K.; Wood, A.P.

1982-01-01T23:59:59.000Z

479

Introduction to Geographic Information System (GIS) and Geospatial Analysis Instructor: Dr. I-Kuai Hung  

E-Print Network [OSTI]

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

Hung, I-Kuai

480

Control sensitivity indices for stability analysis of HVdc systems  

SciTech Connect (OSTI)

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.

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

Note: This page contains sample records for the topic "analysis system sas" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
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We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

GCtool for fuel cell systems design and analysis : user documentation.  

SciTech Connect (OSTI)

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.

Ahluwalia, R.K.; Geyer, H.K.

1999-01-15T23:59:59.000Z

482

Failure and Reliability Analysis for the Master Pump Shutdown System  

SciTech Connect (OSTI)

The Master Pump Shutdown System (MPSS) will be installed in the 200 Areas of the Hanford Site to monitor and control the transfer of liquid waste between tank farms and between the 200 West and 200 East areas through the Cross-Site Transfer Line. The Safety Function provided by the MPSS is to shutdown any waste transfer process within or between tank farms if a waste leak should occur along the selected transfer route. The MPSS, which provides this Safety Class Function, is composed of Programmable Logic Controllers (PLCs), interconnecting wires, relays, Human to Machine Interfaces (HMI), and software. These components are defined as providing a Safety Class Function and will be designated in this report as MPSS/PLC. Input signals to the MPSS/PLC are provided by leak detection systems from each of the tank farm leak detector locations along the waste transfer route. The combination of the MPSS/PLC, leak detection system, and transfer pump controller system will be referred to as MPSS/SYS. The components addressed in this analysis are associated with the MPSS/SYS. The purpose of this failure and reliability analysis is to address the following design issues of the Project Development Specification (PDS) for the MPSS/SYS (HNF 2000a): (1) Single Component Failure Criterion, (2) System Status Upon Loss of Electrical Power, (3) Physical Separation of Safety Class cables, (4) Physical Isolation of Safety Class Wiring from General Service Wiring, and (5) Meeting the MPSS/PLC Option 1b (RPP 1999) Reliability estimate. The failure and reliability analysis examined the system on a component level basis and identified any hardware or software elements that could fail and/or prevent the system from performing its intended safety function.

BEVINS, R.R.

2000-09-05T23:59:59.000Z

483

PVUSA instrumentation and data analysis techniques for photovoltaic systems  

SciTech Connect (OSTI)

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.

Newmiller, J.; Hutchinson, P.; Townsend, T.; Whitaker, C.

1995-10-01T23:59:59.000Z

484

Technical analysis of prospective photovoltaic systems in Utah.  

SciTech Connect (OSTI)

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.

Quiroz, Jimmy Edward; Cameron, Christopher P.

2012-02-01T23:59:59.000Z

485

Safety analysis report for packaging (onsite) doorstop samplecarrier system  

SciTech Connect (OSTI)

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.

Obrien, J.H.

1997-02-24T23:59:59.000Z

486

Notes 07. Undamped Modal Analysis of MDOF systems  

E-Print Network [OSTI]

(mathematical jargon): 12 where = and ? ? ? ? = = A?? ? MK (11) Eq.(9) is a set of n-homogenous algebraic equations. A nontrivial solution, ?? 0 exists if and only if the determinant ? of the system of equations is zero, i.e. 2 0??=? =M+K (12... in the direction of one DOF, say k, depends on or it is coupled to the motion in the other degrees of freedom, j=1,2?n. In the analysis below, for a proper choice of generalized coordinates, known as principal or natural coordinates, the system of n...

San Andres, Luis

2008-01-01T23:59:59.000Z

487

Spectral analysis for semi-infinite mass-spring systems  

E-Print Network [OSTI]

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.

Rafael del Rio; Luis O. Silva

2014-07-29T23:59:59.000Z

488

A new tool for accelerator system modeling and analysis  

SciTech Connect (OSTI)

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.

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

489

Simulated, Emulated, and Physical Investigative Analysis (SEPIA) of networked systems.  

SciTech Connect (OSTI)

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.

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

490

On the Energy Consumption and Performance of Systems Software  

E-Print Network [OSTI]

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

Zadok, Erez

491

Trajectory analysis and optimization system (TAOS) user`s manual  

SciTech Connect (OSTI)

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.

Salguero, D.E.

1995-12-01T23:59:59.000Z

492

Systems analysis of past, present, and future chemical terrorism scenarios.  

SciTech Connect (OSTI)

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.

Hoette, Trisha Marie

2012-03-01T23:59:59.000Z

493

NREL's System Advisor Model Simplifies Complex Energy Analysis (Fact Sheet)  

SciTech Connect (OSTI)

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.

Not Available

2015-01-01T23:59:59.000Z

494

Transportation Routing Analysis Geographic Information System (TRAGIS) User's Manual  

SciTech Connect (OSTI)

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.

Johnson, PE

2003-09-18T23:59:59.000Z

495

System and method for high precision isotope ratio destructive analysis  

DOE Patents [OSTI]

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).

Bushaw, Bruce A; Anheier, Norman C; Phillips, Jon R

2013-07-02T23:59:59.000Z

496

Safety analysis report for packaging (onsite) sample pig transport system  

SciTech Connect (OSTI)

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.

MCCOY, J.C.

1999-03-16T23:59:59.000Z

497

A graph-based system for network-vulnerability analysis  

SciTech Connect (OSTI)

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.

Swiler, L.P.; Phillips, C.

1998-06-01T23:59:59.000Z

498

Comparative analysis of net energy balance for satellite power systems (SPS) and other energy systems  

SciTech Connect (OSTI)

The net energy balance of seven electric energy systems is assessed: two coal-based, one nuclear, two terrestrial solar, and two solar power satellites, with principal emphasis on the latter two systems. Solar energy systems require much less operating energy per unit of electrical output. However, on the basis of the analysis used here, coal and nuclear systems are two to five times more efficient at extracting useful energy from the primary resource base than are the solar energy systems. The payback period for all systems is less than 1.5 years, except for the terrestrial photovoltaic (19.8 yr) and the solar power satellite system (6.4 yr), both of which rely on energy-intensive silicon cells.

Cirillo, R.R.; Cho, B.S.; Monarch, M.R.; Levine, E.P.

1980-04-01T23:59:59.000Z

499

Uncertainty and sensitivity analysis for photovoltaic system modeling.  

SciTech Connect (OSTI)

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.

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

500

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