National Library of Energy BETA

Sample records for manager input validation

  1. T-693: Symantec Endpoint Protection Manager Input Validation...

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

    Input Validation Hole Permits Cross-Site Scripting and Cross-Site Request Forgery Attacks T-693: Symantec Endpoint Protection Manager Input Validation Hole Permits Cross-Site...

  2. U-001:Symantec IM Manager Input Validation Flaws

    Broader source: Energy.gov [DOE]

    Symantec IM Manager Input Validation Flaws Permit Cross-Site Scripting, SQL Injection, and Code Execution Attacks.

  3. V-192: Symantec Security Information Manager Input Validation...

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

    Flaws Permit Cross-Site Scripting, SQL Injection, and Information Disclosure Attacks V-192: Symantec Security Information Manager Input Validation Flaws Permit Cross-Site...

  4. T-693: Symantec Endpoint Protection Manager Input Validation Hole Permits Cross-Site Scripting and Cross-Site Request Forgery Attacks

    Broader source: Energy.gov [DOE]

    Symantec Endpoint Protection Manager Input Validation Hole Permits Cross-Site Scripting and Cross-Site Request Forgery Attacks .

  5. U-204: HP Network Node Manager i Input Validation Hole Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Potential security vulnerabilities have been identified with HP Network Node Manager I (NNMi) for HP-UX, Linux, Solaris, and Windows. The vulnerabilities could be remotely exploited resulting in cross site scripting (XSS).

  6. U-229: HP Network Node Manager i Input Validation Flaw Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Potential security vulnerabilities have been identified with HP Network Node Manager i (NNMi) for HP-UX, Linux, Solaris, and Windows. The vulnerabilities could be remotely exploited resulting in cross site scripting (XSS).

  7. U-238: HP Service Manager Input Validation Flaw Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Cross-site scripting (XSS) vulnerability in HP Service Manager Web Tier 7.11, 9.21, and 9.30, and HP Service Center Web Tier 6.28, allows remote attackers to inject arbitrary web script or HTML via unspecified vectors.

  8. V-139: Cisco Network Admission Control Input Validation Flaw...

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

    PROBLEM: Cisco Network Admission Control Input Validation Flaw Lets Remote Users Inject SQL Commands PLATFORM: Cisco NAC Manager versions prior to 4.8.3.1 and 4.9.2 ABSTRACT: A...

  9. V-150: Apache VCL Input Validation Flaw Lets Remote Authenticated...

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

    Apache VCL Input Validation Flaw Lets Remote Authenticated Users Gain Elevated Privileges V-150: Apache VCL Input Validation Flaw Lets Remote Authenticated Users Gain Elevated...

  10. V-153: Symantec Brightmail Gateway Input Validation Flaw Permits...

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

    3: Symantec Brightmail Gateway Input Validation Flaw Permits Cross-Site Scripting Attacks V-153: Symantec Brightmail Gateway Input Validation Flaw Permits Cross-Site Scripting...

  11. U-252: Barracuda Web Filter Input Validation Flaws Permit Cross...

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

    2: Barracuda Web Filter Input Validation Flaws Permit Cross-Site Scripting Attacks U-252: Barracuda Web Filter Input Validation Flaws Permit Cross-Site Scripting Attacks September...

  12. T-602: BlackBerry Enterprise Server Input Validation Flaw in...

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

    02: BlackBerry Enterprise Server Input Validation Flaw in BlackBerry Web Desktop Manager Permits Cross-Site Scripting Attacks T-602: BlackBerry Enterprise Server Input Validation...

  13. U-147:Red Hat Enterprise MRG Grid Input Validation Flaw

    Office of Energy Efficiency and Renewable Energy (EERE)

    The MRG Management Console (Cumin) does not properly filter HTML code from user-supplied input before displaying the input.

  14. T-701: Citrix Access Gateway Enterprise Edition Input Validation...

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

    1: Citrix Access Gateway Enterprise Edition Input Validation Flaw in Logon Portal Permits Cross-Site Scripting Attacks T-701: Citrix Access Gateway Enterprise Edition Input...

  15. V-193: Barracuda SSL VPN Input Validation Hole Permits Cross...

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

    3: Barracuda SSL VPN Input Validation Hole Permits Cross-Site Scripting Attacks V-193: Barracuda SSL VPN Input Validation Hole Permits Cross-Site Scripting Attacks July 5, 2013 -...

  16. U-144:Juniper Secure Access Input Validation Flaw Permits Cross...

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

    4:Juniper Secure Access Input Validation Flaw Permits Cross-Site Scripting Attacks U-144:Juniper Secure Access Input Validation Flaw Permits Cross-Site Scripting Attacks April 10,...

  17. T-602: BlackBerry Enterprise Server Input Validation Flaw in BlackBerry Web Desktop Manager Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    The BlackBerry Web Desktop Manager not properly filter HTML code from user-supplied input before displaying the input. A remote user can cause arbitrary scripting code to be executed by the target user's browser. The code will originate from the site running the BlackBerry Web Desktop Manager software and will run in the security context of that site. As a result, the code will be able to access the target user's cookies (including authentication cookies), if any, associated with the site, access data recently submitted by the target user via web form to the site, or take actions on the site acting as the target user.

  18. The SCALE Verified, Archived Library of Inputs and Data - VALID

    SciTech Connect (OSTI)

    Marshall, William BJ J; Rearden, Bradley T

    2013-01-01

    The Verified, Archived Library of Inputs and Data (VALID) at ORNL contains high quality, independently reviewed models and results that improve confidence in analysis. VALID is developed and maintained according to a procedure of the SCALE quality assurance (QA) plan. This paper reviews the origins of the procedure and its intended purpose, the philosophy of the procedure, some highlights of its implementation, and the future of the procedure and associated VALID library. The original focus of the procedure was the generation of high-quality models that could be archived at ORNL and applied to many studies. The review process associated with model generation minimized the chances of errors in these archived models. Subsequently, the scope of the library and procedure was expanded to provide high quality, reviewed sensitivity data files for deployment through the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE). Sensitivity data files for approximately 400 such models are currently available. The VALID procedure and library continue fulfilling these multiple roles. The VALID procedure is based on the quality assurance principles of ISO 9001 and nuclear safety analysis. Some of these key concepts include: independent generation and review of information, generation and review by qualified individuals, use of appropriate references for design data and documentation, and retrievability of the models, results, and documentation associated with entries in the library. Some highlights of the detailed procedure are discussed to provide background on its implementation and to indicate limitations of data extracted from VALID for use by the broader community. Specifically, external users of data generated within VALID must take responsibility for ensuring that the files are used within the QA framework of their organization and that use is appropriate. The future plans for the VALID library include expansion to include additional

  19. U-139: IBM Tivoli Directory Server Input Validation Flaw

    Broader source: Energy.gov [DOE]

    The Web Admin Tool does not properly filter HTML code from user-supplied input before displaying the input.

  20. V-112: Microsoft SharePoint Input Validation Flaws Permit Cross...

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

    Input Validation Flaws Permit Cross-Site Scripting and Denial of Service Attacks V-112: Microsoft SharePoint Input Validation Flaws Permit Cross-Site Scripting and Denial...

  1. V-168: Splunk Web Input Validation Flaw Permits Cross-Site Scripting...

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

    8: Splunk Web Input Validation Flaw Permits Cross-Site Scripting Attacks V-168: Splunk Web Input Validation Flaw Permits Cross-Site Scripting Attacks May 31, 2013 - 6:00am Addthis...

  2. V-124: Splunk Web Input Validation Flaw Permits Cross-Site Scripting...

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

    4: Splunk Web Input Validation Flaw Permits Cross-Site Scripting Attacks V-124: Splunk Web Input Validation Flaw Permits Cross-Site Scripting Attacks April 2, 2013 - 1:13am Addthis...

  3. Method of validating measurement data of a process parameter from a plurality of individual sensor inputs

    DOE Patents [OSTI]

    Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

    1998-01-01

    A method for generating a validated measurement of a process parameter at a point in time by using a plurality of individual sensor inputs from a scan of said sensors at said point in time. The sensor inputs from said scan are stored and a first validation pass is initiated by computing an initial average of all stored sensor inputs. Each sensor input is deviation checked by comparing each input including a preset tolerance against the initial average input. If the first deviation check is unsatisfactory, the sensor which produced the unsatisfactory input is flagged as suspect. It is then determined whether at least two of the inputs have not been flagged as suspect and are therefore considered good inputs. If two or more inputs are good, a second validation pass is initiated by computing a second average of all the good sensor inputs, and deviation checking the good inputs by comparing each good input including a present tolerance against the second average. If the second deviation check is satisfactory, the second average is displayed as the validated measurement and the suspect sensor as flagged as bad. A validation fault occurs if at least two inputs are not considered good, or if the second deviation check is not satisfactory. In the latter situation the inputs from each of all the sensors are compared against the last validated measurement and the value from the sensor input that deviates the least from the last valid measurement is displayed.

  4. U-144:Juniper Secure Access Input Validation Flaw Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    The VPN management interface does not properly filter HTML code from user-supplied input before displaying the input. A remote user can cause arbitrary scripting code to be executed by the target user's browser.

  5. T-546: Microsoft MHTML Input Validation Hole May Permit Cross-Site

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

    Scripting Attacks Arbitrary Code | Department of Energy 6: Microsoft MHTML Input Validation Hole May Permit Cross-Site Scripting Attacks Arbitrary Code T-546: Microsoft MHTML Input Validation Hole May Permit Cross-Site Scripting Attacks Arbitrary Code January 31, 2011 - 7:00am Addthis PROBLEM: Microsoft MHTML Input Validation Hole May Permit Cross-Site Scripting Attacks Arbitrary Code. PLATFORM: Microsoft 2003 SP2, Vista SP2, 2008 SP2, XP SP3, 7; and prior service packs ABSTRACT: A

  6. T-722: IBM WebSphere Commerce Edition Input Validation Holes Permit

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

    Cross-Site Scripting Attacks | Department of Energy 2: IBM WebSphere Commerce Edition Input Validation Holes Permit Cross-Site Scripting Attacks T-722: IBM WebSphere Commerce Edition Input Validation Holes Permit Cross-Site Scripting Attacks September 21, 2011 - 8:15am Addthis PROBLEM: IBM WebSphere Commerce Edition Input Validation Holes Permit Cross-Site Scripting Attacks. PLATFORM: WebSphere Commerce Edition V7.0 ABSTRACT: A remote user can access the target user's cookies (including

  7. T-701: Citrix Access Gateway Enterprise Edition Input Validation Flaw in Logon Portal Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Citrix Access Gateway Enterprise Edition Input Validation Flaw in Logon Portal Permits Cross-Site Scripting Attacks.

  8. V-229: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site Scripting

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

    Attacks | Department of Energy 9: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site Scripting Attacks V-229: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site Scripting Attacks August 28, 2013 - 6:00am Addthis PROBLEM: Several vulnerabilities were reported in IBM Lotus iNotes PLATFORM: IBM Lotus iNotes 8.5.x ABSTRACT: IBM Lotus iNotes 8.5.x contains four cross-site scripting vulnerabilities REFERENCE LINKS: Security Tracker Alert ID 1028954 IBM Security Bulletin 1647740

  9. U-195: PHPlist Input Validation Flaws Permit Cross-Site Scripting and SQL Injection Attacks

    Broader source: Energy.gov [DOE]

    The 'public_html/lists/admin' pages do not properly validate user-supplied input in the 'sortby' parameter [CVE-2012-2740]. A remote authenticated administrative user can supply a specially crafted parameter value to execute SQL commands on the underlying database.

  10. Pre-Validated Signal Database Management System

    Energy Science and Technology Software Center (OSTI)

    1996-12-18

    SPRT/DBMS is a pre-validated experimental database management system for industries where large volumes of process signals are acquired and archived. This system implements a new and powerful pattern recognition method, the spectrum transformed sequential testing (STST or ST2) procedure. A network of interacting ST2 modules deployed in parallel is integrated with a relational DBMS to fully validate process signals as they are archived. This reliable, secure DBMS then provides system modelers, code developers, and safetymore » analysts with an easily accessible source of fully validated process data.« less

  11. V-193: Barracuda SSL VPN Input Validation Hole Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Several scripts do not properly filter HTML code from user-supplied input before displaying the input via several parameters

  12. T-623: HP Business Availability Center Input Validation Hole Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    The software does not properly filter HTML code from user-supplied input before displaying the input.

  13. U-050: Adobe Flex SDK Input Validation Flaw Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Flex applications created using the Flex SDK may not properly filter HTML code from user-supplied input before displaying the input.

  14. V-229: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site...

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

    CVE-2013-0591 CVE-2013-0595 IMPACT ASSESSMENT: Medium DISCUSSION: The software does not properly filter HTML code from user-supplied input before displaying the input. ...

  15. U-255: Apache Wicket Input Validation Flaw Permits Cross-Site...

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

    in ajax links before displaying the input. A remote user can create a specially crafted URL that, when loaded by a target user, will cause arbitrary scripting code to be executed...

  16. V-153: Symantec Brightmail Gateway Input Validation Flaw Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    Symantec’s Brightmail Gateway management console is susceptible to stored cross-site scripting (XSS) issues found in some of the administrative interface pages.

  17. T-670: Skype Input Validation Flaw in 'mobile phone' Profile Entry Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    The software does not properly filter HTML code from user-supplied input in the The "mobile phone" profile entry before displaying the input.

  18. EO 13690: Establishing a Federal Flood Risk Management Standard and a Process for Further Soliciting and Considering Stakeholder Input (2015)

    Office of Energy Efficiency and Renewable Energy (EERE)

    Executive Order (E.O.) 13690, Establishing a Federal Flood Risk Management Standard [FFRMS] and a Process for Further Soliciting and Considering Stakeholder Input (2015) amends E.O. 11988,...

  19. EO 13690 (2015): Establishing a Federal Flood Risk Management Standard and a Process for Further Soliciting and Considering Stakeholder Input

    Broader source: Energy.gov [DOE]

    Executive Order (E.O.) 13690, Establishing a Federal Flood Risk Management Standard [FFRMS] and a Process for Further Soliciting and Considering Stakeholder Input (2015) amends E.O. 11988,...

  20. Data Management Plan for The Controlled Hydrogen Fleet and Infrastructure Demonstration and Validation Project

    Broader source: Energy.gov [DOE]

    The Data Management Plan describes how DOE will handle data submitted by recipients as deliverables under the Controlled Hydrogen Fleet and Infrastructure Demonstration and Validation Project.

  1. Validation

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

    Validation in fusion research: Towards guidelines and best practices P. W. Terry, 1 M. Greenwald, 2 J.-N. Leboeuf, 3 G. R. McKee, 4 D. R. Mikkelsen, 5 W. M. Nevins, 6 D. E. Newman, ...

  2. Validating

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

    Validating extended MHD models for fusion plasmas K. J. McCollam (kmccollam@wisc.edu), D. J. Den Hartog, C. M. Jacobson, J. A. Reusch, J. S. Sarff, and the MST Team, University of Wisconsin-Madison, April 2015 Submitted to the DOE Workshop on Integrated Simulations for Magnetic Fusion Energy Sciences Primary topic: A (Disruptions); Secondary topic: C (Whole device modeling) Oral presentation requested if time available Motivation: That predictive capability is a major gap in fusion plasma

  3. Refiner Crude Oil Inputs

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

    Net Inputs (Refiner and Blender) of RBOB Blending Components Net Inputs (Refiner and Blender) of CBOB Blending Components Net Inputs (Refiner and Blender) of GTAB Blending ...

  4. T-648: Avaya IP Office Manager TFTP Server Lets Remote Users Traverse the Directory

    Broader source: Energy.gov [DOE]

    The software does not properly validate user-supplied input. A remote user can supply a specially crafted request to view files on target system running the IP Office Manager software.

  5. W-026, Waste Receiving and Processing Facility data management system validation and verification report

    SciTech Connect (OSTI)

    Palmer, M.E.

    1997-12-05

    This V and V Report includes analysis of two revisions of the DMS [data management system] System Requirements Specification (SRS) and the Preliminary System Design Document (PSDD); the source code for the DMS Communication Module (DMSCOM) messages; the source code for selected DMS Screens, and the code for the BWAS Simulator. BDM Federal analysts used a series of matrices to: compare the requirements in the System Requirements Specification (SRS) to the specifications found in the System Design Document (SDD), to ensure the design supports the business functions, compare the discreet parts of the SDD with each other, to ensure that the design is consistent and cohesive, compare the source code of the DMS Communication Module with the specifications, to ensure that the resultant messages will support the design, compare the source code of selected screens to the specifications to ensure that resultant system screens will support the design, compare the source code of the BWAS simulator with the requirements to interface with DMS messages and data transfers relating to the BWAS operations.

  6. FIMS Data Validation | Department of Energy

    Energy Savers [EERE]

    Information Systems FIMS Data Validation FIMS Data Validation FIMS Data Validation The Facility Information Management System (FIMS) is the Department's official repository of ...

  7. Influential input classification in probabilistic multimedia models

    SciTech Connect (OSTI)

    Maddalena, Randy L.; McKone, Thomas E.; Hsieh, Dennis P.H.; Geng, Shu

    1999-05-01

    Monte Carlo analysis is a statistical simulation method that is often used to assess and quantify the outcome variance in complex environmental fate and effects models. Total outcome variance of these models is a function of (1) the uncertainty and/or variability associated with each model input and (2) the sensitivity of the model outcome to changes in the inputs. To propagate variance through a model using Monte Carlo techniques, each variable must be assigned a probability distribution. The validity of these distributions directly influences the accuracy and reliability of the model outcome. To efficiently allocate resources for constructing distributions one should first identify the most influential set of variables in the model. Although existing sensitivity and uncertainty analysis methods can provide a relative ranking of the importance of model inputs, they fail to identify the minimum set of stochastic inputs necessary to sufficiently characterize the outcome variance. In this paper, we describe and demonstrate a novel sensitivity/uncertainty analysis method for assessing the importance of each variable in a multimedia environmental fate model. Our analyses show that for a given scenario, a relatively small number of input variables influence the central tendency of the model and an even smaller set determines the shape of the outcome distribution. For each input, the level of influence depends on the scenario under consideration. This information is useful for developing site specific models and improving our understanding of the processes that have the greatest influence on the variance in outcomes from multimedia models.

  8. US Nuclear Regulatory Commission Input to DOE Request for Information Smart

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

    Grid Implementation Input | Department of Energy US Nuclear Regulatory Commission Input to DOE Request for Information Smart Grid Implementation Input US Nuclear Regulatory Commission Input to DOE Request for Information Smart Grid Implementation Input US Nuclear Regulatory Commission Input to DOE Request for Information Smart Grid Implementation Input. Comments relevant to the following two sections of the RFI: "Long Term Issues: Managing a Grid with High Penetration of New

  9. Prioritization Tool Measurement Input Form

    Office of Energy Efficiency and Renewable Energy (EERE)

    BTO encourages stakeholders to recommend updates and improvements to the Prioritization Tool by using the below Measure Input Form.

  10. Independent Verification and Validation Of SAPHIRE 8 Risk Management Project Number: N6423 U.S. Nuclear Regulatory Commission

    SciTech Connect (OSTI)

    Kent Norris

    2009-11-01

    This report provides an evaluation of the risk management. Risk management is intended to ensure a methodology for conducting risk management planning, identification, analysis, responses, and monitoring and control activities associated with the SAPHIRE project work, and to meet the contractual commitments prepared by the sponsor; the Nuclear Regulatory Commission.

  11. Strategic Defense Initiative Demonstration/Validation program environmental assessment. Battle management/command, control, and communications (BM/C3)

    SciTech Connect (OSTI)

    Brown, G.

    1987-08-01

    The Strategic Defense Initiative Organization (SDIO) and its proponents (U.S. Army and U.S. Air Force) plan to conduct Demonstration/Validation tests of the BM/C3 technology. These tests will demonstrate the ability of the technology to perform the required tasks, and will validate a future decision on whether to proceed with Full-Scale Development. Demonstration/Validation tests would be conducted at the Advanced Research Center, Electronic Systems Division, National Test Facility, Rome Air Development Center, Nevada Test Site, Harry Diamond Laboratories, and at contractor facilities. Tests would include analyses, simulations, and component/assembly tests. This document addresses the potential environmental consequences of the Demonstration/Validation testing of the BM/C3 technology.

  12. Spatial Statistical Procedures to Validate Input Data in Energy Models

    SciTech Connect (OSTI)

    Johannesson, G.; Stewart, J.; Barr, C.; Brady Sabeff, L.; George, R.; Heimiller, D.; Milbrandt, A.

    2006-01-01

    Energy modeling and analysis often relies on data collected for other purposes such as census counts, atmospheric and air quality observations, economic trends, and other primarily non-energy related uses. Systematic collection of empirical data solely for regional, national, and global energy modeling has not been established as in the abovementioned fields. Empirical and modeled data relevant to energy modeling is reported and available at various spatial and temporal scales that might or might not be those needed and used by the energy modeling community. The incorrect representation of spatial and temporal components of these data sets can result in energy models producing misleading conclusions, especially in cases of newly evolving technologies with spatial and temporal operating characteristics different from the dominant fossil and nuclear technologies that powered the energy economy over the last two hundred years. Increased private and government research and development and public interest in alternative technologies that have a benign effect on the climate and the environment have spurred interest in wind, solar, hydrogen, and other alternative energy sources and energy carriers. Many of these technologies require much finer spatial and temporal detail to determine optimal engineering designs, resource availability, and market potential. This paper presents exploratory and modeling techniques in spatial statistics that can improve the usefulness of empirical and modeled data sets that do not initially meet the spatial and/or temporal requirements of energy models. In particular, we focus on (1) aggregation and disaggregation of spatial data, (2) predicting missing data, and (3) merging spatial data sets. In addition, we introduce relevant statistical software models commonly used in the field for various sizes and types of data sets.

  13. T-546: Microsoft MHTML Input Validation Hole May Permit Cross...

    Office of Environmental Management (EM)

    a client-side script in the response of a Web request run in the context of the victim's ... action that the user could take on the affected Web site on behalf of the targeted user. ...

  14. DOE Seeks Industry Input on Nickel Disposition Strategy | Department of

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

    Energy Industry Input on Nickel Disposition Strategy DOE Seeks Industry Input on Nickel Disposition Strategy March 23, 2012 - 12:00pm Addthis WASHINGTON, D.C. - The Energy Department's prime contractor, Fluor-B&W Portsmouth (FBP), managing the Portsmouth Gaseous Diffusion Plant (GDP), issued a request for Expressions of Interest (EOI) seeking industry input to support the development of an acquisition strategy for potential disposition of DOE nickel. The EOI requests technical,

  15. Validation in the Absence of Observed Events

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

    Lathrop, John; Ezell, Barry

    2015-07-22

    Here our paper addresses the problem of validating models in the absence of observed events, in the area of Weapons of Mass Destruction terrorism risk assessment. We address that problem with a broadened definition of “Validation,” based on “backing up” to the reason why modelers and decision makers seek validation, and from that basis re-define validation as testing how well the model can advise decision makers in terrorism risk management decisions. We develop that into two conditions: Validation must be based on cues available in the observable world; and it must focus on what can be done to affect thatmore » observable world, i.e. risk management. That in turn leads to two foci: 1.) the risk generating process, 2.) best use of available data. Based on our experience with nine WMD terrorism risk assessment models, we then describe three best use of available data pitfalls: SME confidence bias, lack of SME cross-referencing, and problematic initiation rates. Those two foci and three pitfalls provide a basis from which we define validation in this context in terms of four tests -- Does the model: … capture initiation? … capture the sequence of events by which attack scenarios unfold? … consider unanticipated scenarios? … consider alternative causal chains? Finally, we corroborate our approach against three key validation tests from the DOD literature: Is the model a correct representation of the simuland? To what degree are the model results comparable to the real world? Over what range of inputs are the model results useful?« less

  16. Validation in the Absence of Observed Events

    SciTech Connect (OSTI)

    Lathrop, John; Ezell, Barry

    2015-07-22

    Here our paper addresses the problem of validating models in the absence of observed events, in the area of Weapons of Mass Destruction terrorism risk assessment. We address that problem with a broadened definition of “Validation,” based on “backing up” to the reason why modelers and decision makers seek validation, and from that basis re-define validation as testing how well the model can advise decision makers in terrorism risk management decisions. We develop that into two conditions: Validation must be based on cues available in the observable world; and it must focus on what can be done to affect that observable world, i.e. risk management. That in turn leads to two foci: 1.) the risk generating process, 2.) best use of available data. Based on our experience with nine WMD terrorism risk assessment models, we then describe three best use of available data pitfalls: SME confidence bias, lack of SME cross-referencing, and problematic initiation rates. Those two foci and three pitfalls provide a basis from which we define validation in this context in terms of four tests -- Does the model: … capture initiation? … capture the sequence of events by which attack scenarios unfold? … consider unanticipated scenarios? … consider alternative causal chains? Finally, we corroborate our approach against three key validation tests from the DOD literature: Is the model a correct representation of the simuland? To what degree are the model results comparable to the real world? Over what range of inputs are the model results useful?

  17. Independent Verification and Validation Of SAPHIRE 8 Software Configuration Management Plan Project Number: N6423 U.S. Nuclear Regulatory Commission

    SciTech Connect (OSTI)

    Kent Norris

    2010-02-01

    The purpose of the Independent Verification and Validation (IV&V) role in the evaluation of the SAPHIRE configuration management is to assess the activities that results in the process of identifying and defining the baselines associated with the SAPHIRE software product; controlling the changes to baselines and release of baselines throughout the life cycle; recording and reporting the status of baselines and the proposed and actual changes to the baselines; and verifying the correctness and completeness of baselines.. The IV&V team began this endeavor after the software engineering and software development of SAPHIRE had already been in production.

  18. Independent Verification and Validation Of SAPHIRE 8 Software Configuration Management Plan Project Number: N6423 U.S. Nuclear Regulatory Commission

    SciTech Connect (OSTI)

    Kent Norris

    2009-10-01

    The purpose of the Independent Verification and Validation (IV&V) role in the evaluation of the SAPHIRE configuration management is to assess the activities that results in the process of identifying and defining the baselines associated with the SAPHIRE software product; controlling the changes to baselines and release of baselines throughout the life cycle; recording and reporting the status of baselines and the proposed and actual changes to the baselines; and verifying the correctness and completeness of baselines.. The IV&V team began this endeavor after the software engineering and software development of SAPHIRE had already been in production.

  19. Reviews and Validations | Department of Energy

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

    Reviews and Validations Reviews and Validations External Independent Review (EIR) Procedures Under DOE O 413.3B, Program and Project Management for the Acquisition of Capital ...

  20. Object-Oriented Database for Managing Building Modeling Components and Metadata: Preprint

    SciTech Connect (OSTI)

    Long, N.; Fleming, K.; Brackney, L.

    2011-12-01

    Building simulation enables users to explore and evaluate multiple building designs. When tools for optimization, parametrics, and uncertainty analysis are combined with analysis engines, the sheer number of discrete simulation datasets makes it difficult to keep track of the inputs. The integrity of the input data is critical to designers, engineers, and researchers for code compliance, validation, and building commissioning long after the simulations are finished. This paper discusses an application that stores inputs needed for building energy modeling in a searchable, indexable, flexible, and scalable database to help address the problem of managing simulation input data.

  1. Generation Inputs Workshop June 25, 2014

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

    Inputs Workshop 25 June 2014 BPA's Centralized Wind Power Forecasting Initiative Scott Winner June 25, 2014 Generation Inputs Workshop Predecisional. For Discussion Purposes Only....

  2. Verification and validation benchmarks.

    SciTech Connect (OSTI)

    Oberkampf, William Louis; Trucano, Timothy Guy

    2007-02-01

    Verification and validation (V&V) are the primary means to assess the accuracy and reliability of computational simulations. V&V methods and procedures have fundamentally improved the credibility of simulations in several high-consequence fields, such as nuclear reactor safety, underground nuclear waste storage, and nuclear weapon safety. Although the terminology is not uniform across engineering disciplines, code verification deals with assessing the reliability of the software coding, and solution verification deals with assessing the numerical accuracy of the solution to a computational model. Validation addresses the physics modeling accuracy of a computational simulation by comparing the computational results with experimental data. Code verification benchmarks and validation benchmarks have been constructed for a number of years in every field of computational simulation. However, no comprehensive guidelines have been proposed for the construction and use of V&V benchmarks. For example, the field of nuclear reactor safety has not focused on code verification benchmarks, but it has placed great emphasis on developing validation benchmarks. Many of these validation benchmarks are closely related to the operations of actual reactors at near-safety-critical conditions, as opposed to being more fundamental-physics benchmarks. This paper presents recommendations for the effective design and use of code verification benchmarks based on manufactured solutions, classical analytical solutions, and highly accurate numerical solutions. In addition, this paper presents recommendations for the design and use of validation benchmarks, highlighting the careful design of building-block experiments, the estimation of experimental measurement uncertainty for both inputs and outputs to the code, validation metrics, and the role of model calibration in validation. It is argued that the understanding of predictive capability of a computational model is built on the level of

  3. ,"U.S. Blender Net Input"

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

    11:31:21 PM" "Back to Contents","Data 1: U.S. Blender Net Input" "Sourcekey","MTXRBNUS...NUS1","MO7RBNUS1","MO9RBNUS1" "Date","U.S. Blender Net Input of Total Petroleum ...

  4. ,"U.S. Refinery Net Input"

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

    ...RONUS1","MO9RONUS1","MBARONUS1" "Date","U.S. Refinery Net Input of Crude Oil and Petroleum Products (Thousand Barrels)","U.S. Refinery Net Input of Crude Oil (Thousand ...

  5. BISON Validation | Department of Energy

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

    Validation BISON Validation January 29, 2013 - 11:54am Addthis BISON Validation Predictive Maturity Work continued on the previously developed discovery, accumulation, and assessment (DAA) process to plan, track, assess, and communicate VU activities and results. DAA was applied to the BISON sensitivity analysis described above, and the results were exported to Synopsis, the DAA management tool. [SNL, LANL, INL] Building on previous sensitivity studies of the LIFE-IV nuclear fuels code, a

  6. Abandoned Uranium Mines Report to Congress: LM Wants Your Input |

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

    Department of Energy Abandoned Uranium Mines Report to Congress: LM Wants Your Input Abandoned Uranium Mines Report to Congress: LM Wants Your Input April 11, 2013 - 1:33pm Addthis C-SR-10 Uintah Mine, Colorado, LM Uranium Lease Tracts C-SR-10 Uintah Mine, Colorado, LM Uranium Lease Tracts What does this project do? Goal 4. Optimize the use of land and assets Abandoned Uranium Mines Report to Congress The U.S. Department of Energy (DOE) Office of Legacy Management (LM) is seeking stakeholder

  7. Recommendation 177: Facilitating Early Public Input

    Broader source: Energy.gov [DOE]

    DOE should initiate consultation meetings with stake holders immediately to allow early public input into the planning for IFDP

  8. Guidance for Fiscal Year 2015 Facilities Information Management...

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

    Fiscal Year 2015 Facilities Information Management System Data Validations Guidance for Fiscal Year 2015 Facilities Information Management System Data Validations FIMS VALIDATION ...

  9. Guidance for FY2014 Facilities Information Management System...

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

    FY2014 Facilities Information Management System Data Validations Guidance for FY2014 Facilities Information Management System Data Validations FY 2014 FIMS Data Validation Guidance ...

  10. management

    National Nuclear Security Administration (NNSA)

    5%2A en Management and Budget http:www.nnsa.energy.govaboutusouroperationsmanagementandbudget

  11. management

    National Nuclear Security Administration (NNSA)

    5%2A en Management and Budget http:nnsa.energy.govaboutusouroperationsmanagementandbudget

    P...

  12. ,"Washington Natural Gas Input Supplemental Fuels (MMcf)"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Washington Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","09...

  13. decreasing water input and waste generation

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

    decreasing water input and waste generation - Sandia Energy Energy Search Icon Sandia Home ... Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 ...

  14. ,"Hawaii Natural Gas Input Supplemental Fuels (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Hawaii Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","0930...

  15. ,"Maine Natural Gas Input Supplemental Fuels (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Maine Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","0930...

  16. ,"U.S. Refinery Net Input"

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

    ...petpnpinpt2dcnusmbbla.htm" ,"Source:","Energy Information Administration" ,"For Help, ... Barrels)","U.S. Refinery Net Input of Hydrogen (Thousand Barrels)","U.S. Refinery Net ...

  17. ,"Texas Natural Gas Input Supplemental Fuels (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","0930...

  18. Input apparatus for dynamic signature verification systems

    DOE Patents [OSTI]

    EerNisse, Errol P.; Land, Cecil E.; Snelling, Jay B.

    1978-01-01

    The disclosure relates to signature verification input apparatus comprising a writing instrument and platen containing piezoelectric transducers which generate signals in response to writing pressures.

  19. SANSMIC Validation.

    SciTech Connect (OSTI)

    Weber, Paula D.; Rudeen, David Keith; Lord, David

    2014-08-01

    SANSMIC is solution mining software that was developed and utilized by SNL in its role as geotechnical advisor to the US DOE SPR for planning purposes. Three SANSMIC leach modes - withdrawal, direct, and reverse leach - have been revalidated with multiple test cases for each mode. The withdrawal mode was validated using high quality data from recent leach activity while the direct and reverse modes utilized data from historical cavern completion reports. Withdrawal results compared very well with observed data, including the location and size of shelves due to string breaks with relative leached volume differences ranging from 6 - 10% and relative radius differences from 1.5 - 3%. Profile comparisons for the direct mode were very good with relative leached volume differences ranging from 6 - 12% and relative radius differences from 5 - 7%. First, second, and third reverse configurations were simulated in order to validate SANSMIC over a range of relative hanging string and OBI locations. The first-reverse was simulated reasonably well with relative leached volume differences ranging from 1 - 9% and relative radius differences from 5 - 12%. The second-reverse mode showed the largest discrepancies in leach profile. Leached volume differences ranged from 8 - 12% and relative radius differences from 1 - 10%. In the third-reverse, relative leached volume differences ranged from 10 - 13% and relative radius differences were ~4 %. Comparisons to historical reports were quite good, indicating that SANSMIC is essentially the same as documented and validated in the early 1980's.

  20. ,"U.S. Blender Net Input"

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

    10:21:53 PM" "Back to Contents","Data 1: U.S. Blender Net Input" "Sourcekey","MTXRBNUS1...US1","MO7RBNUS1","MO9RBNUS1" "Date","U.S. Blender Net Input of Total Petroleum ...

  1. Criticality Safety Validation of SCALE 6.1 with ENDF/B-VII.0 Libraries

    SciTech Connect (OSTI)

    Marshall, William BJ J; Rearden, Bradley T

    2012-01-01

    ANSI/ANS-8.1-1998;2007, Nuclear Criticality Safety in Operations with Fissionable Material Outside Reactors, and ANSI/ANS-8.24-2007, Validation of Neutron Transport Methods for Nuclear Criticality Safety Calculations, require validation of a computer code and the associated data through benchmark evaluations based on physical experiments. The performance of the code and data are validated by comparing the calculated and the benchmark results. A SCALE procedure has been established to generate a Verified, Archived Library of Inputs and Data (VALID). This procedure provides a framework for preparing, peer reviewing, and controlling models and data sets derived from benchmark definitions so that the models and data can be used with confidence. The procedure ensures that the models and data were correctly generated using appropriate references with documented checks and reviews. Configuration management is implemented to prevent inadvertent modification of the models and data or inclusion of models that have not been subjected to the rigorous review process. VALID entries for criticality safety are based on critical experiments documented in the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE). The findings of a criticality safety validation of SCALE 6.1 utilizing the benchmark models vetted in the VALID library at Oak Ridge National Laboratory are summarized here.

  2. US Nuclear Regulatory Commission Input to DOE Request for Information...

    Energy Savers [EERE]

    US Nuclear Regulatory Commission Input to DOE Request for Information Smart Grid Implementation Input US Nuclear Regulatory Commission Input to DOE Request for Information Smart ...

  3. FIMS Data Validation | Department of Energy

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

    Information Systems » FIMS Data Validation FIMS Data Validation FIMS Data Validation The Facility Information Management System (FIMS) is the Department's official repository of real property data. The Department relies on the FIMS data for real property decision-making and accounting of its $86B in assets. Maintaining accurate and credible data in FIMS is critical to efficient operations and resource planning. Department of Energy Order 430.1B Real Property Asset Management requires FIMS data

  4. Wireless, relative-motion computer input device

    DOE Patents [OSTI]

    Holzrichter, John F.; Rosenbury, Erwin T.

    2004-05-18

    The present invention provides a system for controlling a computer display in a workspace using an input unit/output unit. A train of EM waves are sent out to flood the workspace. EM waves are reflected from the input unit/output unit. A relative distance moved information signal is created using the EM waves that are reflected from the input unit/output unit. Algorithms are used to convert the relative distance moved information signal to a display signal. The computer display is controlled in response to the display signal.

  5. Reviews and Validations | Department of Energy

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

    Services » Project Management » Reviews and Validations Reviews and Validations External Independent Review (EIR) Procedures Under DOE O 413.3B, Program and Project Management for the Acquisition of Capital Assets, the Office of Acquisition and Project Management (OAPM) must perform a Performance Baseline External Independent Review (EIR) prior to Critical Decision (CD) 2, and a Construction/Execution Readiness EIR for all Major System projects prior to CD-3. The EIR Standard Operating

  6. Summary, Attendee Input, and Day 1 Wrap Up | Department of Energy

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

    Day 1 Wrap Up Summary, Attendee Input, and Day 1 Wrap Up Addthis Description Summary and wrap up of day 1 presentations and preview of day 2 by DOE Integrated Safety Management Co-champions Patricia R. Worthington, HSS Director, Office of Health and Safety; and and Ray J. Corey, Assistant Manager for Safety and Environment, DOE Richland Operations Office

  7. Summary, Attendee Input, and Final Day 2 Wrap up | Department of Energy

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

    Final Day 2 Wrap up Summary, Attendee Input, and Final Day 2 Wrap up Addthis Description Summary and wrap up by DOE Integrated Safety Management Co-champions Patricia R. Worthington, HSS Director, Office of Health and Safety; and and Ray J. Corey, Assistant Manager for Safety and Environment, DOE Richland Operations Office of day 2 presentations and discussions

  8. U.S. Weekly Inputs & Utilization

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

    Area: U.S. East Coast (PADD 1) Midwest (PADD 2) Gulf Coast (PADD 3) Rocky Mountain (PADD 4) West Coast (PADD 5) Period: Weekly 4-Week Average Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 07/29/16 08/05/16 08/12/16 08/19/16 08/26/16 09/02/16 View History Refiner Inputs and Utilization Crude Oil Inputs 16,852 16,597 16,865 16,679 16,615 16,930 1982-2016 Gross Inputs 17,097 16,883 17,127 16,937

  9. Microsoft Word - SmartGrid - NRC Input to DOE Requestrvjcomments.docx

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

    Nuclear Regulatory Commission Input to DOE Request for Information/RFI (Federal Register / Vol. 75, No. 180 / Friday, September 17, 2010/Pages 57006-57011 / Notices) / Smart Grid Implementation Input - NRC Contact: Kenn A. Miller, Office of Nuclear Reactor Regulation, 301-415-3152 Comments relevant to the following two sections of the RFI: "Long Term Issues: Managing a Grid with High Penetration of New Technologies" and "Reliability and Cyber-Security," Page 57010. Nuclear

  10. Guidance for Fiscal Year 2015 Facilities Information Management...

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

    Guidance for Fiscal Year 2015 Facilities Information Management System Data Validations Guidance for Fiscal Year 2015 Facilities Information Management System Data Validations PDF...

  11. Developing a low input and sustainable switchgrass feedstock...

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

    Developing a low input and sustainable switchgrass feedstock production system utilizing beneficial bacterial endophytes Developing a low input and sustainable switchgrass ...

  12. Tribal Leaders Provide White House with Input on Bolstering Climate...

    Office of Environmental Management (EM)

    Leaders Provide White House with Input on Bolstering Climate Resilience Tribal Leaders Provide White House with Input on Bolstering Climate Resilience January 7, 2015 - 10:29am ...

  13. Addressing Uncertainties in Design Inputs: A Case Study of Probabilist...

    Office of Environmental Management (EM)

    Addressing Uncertainties in Design Inputs: A Case Study of Probabilistic Settlement Evaluations for Soft Zone Collapse at SWPF Addressing Uncertainties in Design Inputs: A Case ...

  14. New York Natural Gas Input Supplemental Fuels (Million Cubic...

    Gasoline and Diesel Fuel Update (EIA)

    Input Supplemental Fuels (Million Cubic Feet) New York Natural Gas Input Supplemental ... Referring Pages: Total Supplemental Supply of Natural Gas New York Supplemental Supplies ...

  15. New Mexico Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) New Mexico Natural Gas Input Supplemental ... Referring Pages: Total Supplemental Supply of Natural Gas New Mexico Supplemental Supplies ...

  16. New Jersey Natural Gas Input Supplemental Fuels (Million Cubic...

    Gasoline and Diesel Fuel Update (EIA)

    Input Supplemental Fuels (Million Cubic Feet) New Jersey Natural Gas Input Supplemental ... Referring Pages: Total Supplemental Supply of Natural Gas New Jersey Supplemental Supplies ...

  17. North Carolina Natural Gas Input Supplemental Fuels (Million...

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

    Input Supplemental Fuels (Million Cubic Feet) North Carolina Natural Gas Input ... Referring Pages: Total Supplemental Supply of Natural Gas North Carolina Supplemental ...

  18. North Dakota Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) North Dakota Natural Gas Input Supplemental ... Referring Pages: Total Supplemental Supply of Natural Gas North Dakota Supplemental ...

  19. Table 3. U.S. Inputs to biodiesel production

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

    U.S. Inputs to biodiesel production" "million pounds" ,"Feedstock inputs" ,"Vegetable ... Administration, Form EIA-22M ""Monthly Biodiesel Production Survey""" "U.S. Energy ...

  20. STCH Annual Merit Review Input - EERE Hydrogen Program. (Conference...

    Office of Scientific and Technical Information (OSTI)

    STCH Annual Merit Review Input - EERE Hydrogen Program. Citation Details In-Document Search Title: STCH Annual Merit Review Input - EERE Hydrogen Program. Abstract not provided. ...

  1. PADD 2 Weekly Inputs & Utilization

    Gasoline and Diesel Fuel Update (EIA)

    3 3,834 3,663 3,734 3,734 3,802 1992-2016 Gross Inputs 3,719 3,835 3,666 3,734 3,752 3,806 1990-2016 Operable Capacity (Calendar Day) 3,924 3,924 3,924 3,924 3,924 3,924 2010-2016 Percent Operable Utilization 94.8 97.7 93.4 95.2 95.6 97.0 2010-2016 Refiner and Blender Net Inputs Motor Gasoline Blending Components 473 498 590 583 331 302 2004-2016 RBOB 68 52 121 69 -1 56 2010-2016 CBOB 331 433 450 513 227 261 2004-2016 GTAB 0 0 0 0 0 0 2004-2016 All Other 74 13 19 1 105 -15 2004-2016 Fuel Ethanol

  2. XBox Input -Version 1.0

    Energy Science and Technology Software Center (OSTI)

    2012-10-03

    Contains class for connecting to the Xbox 360 controller, displaying the user inputs {buttons, triggers, analog sticks), and controlling the rumble motors. Also contains classes for converting the raw Xbox 360 controller inputs into meaningful commands for the following objects: • Robot arms - Provides joint control and several tool control schemes • UGV's - Provides translational and rotational commands for "skid-steer" vehicles • Pan-tilt units - Provides several modes of control including velocity, position,more » and point-tracking • Head-mounted displays (HMO)- Controls the viewpoint of a HMO • Umbra frames - Controls the position andorientation of an Umbra posrot object • Umbra graphics window - Provides several modes of control for the Umbra OSG window viewpoint including free-fly, cursor-focused, and object following.« less

  3. CASIM input parameters for various materials

    SciTech Connect (OSTI)

    Malensek, A.J.; Elwyn, A.J.

    1994-07-14

    During the past year, the computer program CASIM has been placed in a common area from which copies can be obtained by a wide array of users. The impetus for this arrangement was the need to have a standard code that could be maintained and transported to other platforms. In addition, an historical record would be kept of each version as the program evolved. CASIM requires a series of parameters (input by the user) that describe the medium in which the cascade develops. Presently a total of 9 materials can be defined. Occasions arise when one needs to know the properties of materials (elements, compounds, and mixtures) that have not been defined. Because it is desirable to have a uniform set of values for all CASIM users, this note presents a methodology for obtaining the input parameters for an arbitrary material. They are read in by the Subroutine CASIM{underscore}PROG from the user supplied file CASIM.DAT.

  4. U-015: CiscoWorks Common Services Home Page Input Validation...

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

    commands on the target system. A remote user can submit a specially crafted URL via TCP port 443 or 1741 to execute arbitrary commands on the target system. The commands will...

  5. T-590: HP Diagnostics Input Validation Hole Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    A potential security vulnerability has been identified in HP Diagnostics. The vulnerability could be exploited remotely resulting in cross site scripting (XSS).

  6. T-722: IBM WebSphere Commerce Edition Input Validation Holes...

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

    recently submitted by the target user via web form to the site, or take actions on the ... recently submitted by the target user via web form to the site, or take actions on the ...

  7. PADD 3 Weekly Inputs & Utilization

    Gasoline and Diesel Fuel Update (EIA)

    8,788 8,791 8,855 8,956 8,712 8,580 1992-2016 Gross Inputs 8,889 8,871 8,976 9,014 8,783 8,817 1990-2016 Operable Capacity (Calendar Day) 9,515 9,515 9,515 9,515 9,515 9,515 2010-2016 Percent Operable Utilization 93.4 93.2 94.3 94.7 92.3 92.7 2010-2016 Refiner and Blender Net Inputs Motor Gasoline Blending Components -2,249 -1,993 -2,117 -2,108 -2,293 -2,034 2004-2016 RBOB -419 -380 -321 -406 -471 -291 2010-2016 CBOB -1,794 -1,684 -1,852 -1,798 -1,870 -1,981 2004-2016 GTAB 0 0 0 0 0 0 2004-2016

  8. Multiple-Input Multiple-Output (MIMO) Linear Systems Extreme Inputs/Outputs

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

    Smallwood, David O.

    2007-01-01

    A linear structure is excited at multiple points with a stationary normal random process. The response of the structure is measured at multiple outputs. If the autospectral densities of the inputs are specified, the phase relationships between the inputs are derived that will minimize or maximize the trace of the autospectral density matrix of the outputs. If the autospectral densities of the outputs are specified, the phase relationships between the outputs that will minimize or maximize the trace of the input autospectral density matrix are derived. It is shown that other phase relationships and ordinary coherence less than one willmore » result in a trace intermediate between these extremes. Least favorable response and some classes of critical response are special cases of the development. It is shown that the derivation for stationary random waveforms can also be applied to nonstationary random, transients, and deterministic waveforms.« less

  9. U.S. Blender Net Input

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

    Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History Total Input 242,396 238,655 257,960 253,448 266,176 262,899 2005-2016 Natural Gas Plant Liquids and Liquefied Refinery Gases 2,044 1,531 1,783 1,315 339 414 2008-2016 Pentanes Plus 489 347 423 177 194 276 2005-2016 Liquid Petroleum Gases 1,555 1,184 1,360 1,138 145 138 2008-2016 Normal Butane 1,555 1,184 1,360 1,138 145 138 2005-2016 Isobutane 2005-2015 Other Liquids 240,352 237,124 256,177 252,133 265,837 262,485 2008-2016

  10. U.S. Blender Net Input

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

    2010 2011 2012 2013 2014 2015 View History Total Input 2,166,784 2,331,109 2,399,318 2,539,812 2,824,480 2,987,634 2005-2015 Natural Gas Plant Liquids and Liquefied Refinery Gases 6,538 7,810 10,663 12,304 14,038 16,334 2008-2015 Pentanes Plus 1,989 2,326 4,164 4,241 3,184 2,554 2005-2015 Liquid Petroleum Gases 4,549 5,484 6,499 8,063 10,854 13,780 2008-2015 Normal Butane 4,549 5,484 6,499 8,063 10,823 13,741 2005-2015 Isobutane 31 39 2005-2015 Other Liquids 2,160,246 2,323,299 2,388,655

  11. Environmental geological input into urban construction planning

    SciTech Connect (OSTI)

    Berry, W.B.N. . Dept. of Geology and Geophysics)

    1992-01-01

    Environmental issues resulting from planning new construction in urban areas requires understanding of geological processes at many steps in project development. Steps include: assessments of geological characteristics of the proposed construction site, building design features in light of the geological characteristics, development of the geology component of the EIR as well as any mitigations required, and writing special environmental geological concerns into specifications required of the contractor. The latter step may be exemplified in planning a new underground library being constructed in the center of the Berkeley Campus. The site is within 50 yards of a creek that has been restored such that fish now live in it whereas none could three years ago. Runoff from paved parking lots and walkways around existing buildings goes into storm drains that empty directly into the creek. Because they do, creek water is monitored for chemical and solid wastes as well as turbidity. Based on geological input, special project procedures were written to which the contractor must adhere during site preparation and construction. These include: all liquid wastes must be contained in impermeable containers, all hazardous wastes must be removed under state waste removal guidelines, dewatering procedures were developed to remove groundwater that flows through permeable sands and gravels from the creek bed into the construction site and must be followed, and soil flux into the creek must be prevented. Mitigation of soil flux includes watering areas of the site as soil is excavated. Watering must be monitored because the contractor tends to overwater which flushes soil down nearby storm drains into the creek. As well, soil control monitoring includes preventing the contractor from sweeping soil into the storm drains and flushing it into the creek. Geological input has proven valuable in addressing different environmental concerns.

  12. FACILITIES INFORMATION MANAGEMENT SYSTEM (FIMS) DATA VALIDATION...

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

    ... 20, 2014 Data Element DOE Owned Building DOE Owned Trailer DOE Owned OSF DOE ... Bridge safety inspection frequency is as follows: Train bridges - one inspection per ...

  13. Sensor Data Management, Validation, Correction, and Provenance...

    Office of Scientific and Technical Information (OSTI)

    that use a wide range of sensors to develop and characterize building energy performance. ... Sponsoring Org: EE USDOE - Office of Energy Efficiency and Renewable Energy (EE) ...

  14. Field measurement of moisture-buffering model inputs for residential buildings

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

    Woods, Jason; Winkler, Jon

    2016-02-05

    Moisture adsorption and desorption in building materials impact indoor humidity. This effect should be included in building-energy simulations, particularly when humidity is being investigated or controlled. Several models can calculate this moisture-buffering effect, but accurate ones require model inputs that are not always known to the user of the building-energy simulation. This research developed an empirical method to extract whole-house model inputs for the effective moisture penetration depth (EMPD) model. The experimental approach was to subject the materials in the house to a square-wave relative-humidity profile, measure all of the moisture-transfer terms (e.g., infiltration, air-conditioner condensate), and calculate the onlymore » unmeasured term—the moisture sorption into the materials. We validated this method with laboratory measurements, which we used to measure the EMPD model inputs of two houses. After deriving these inputs, we measured the humidity of the same houses during tests with realistic latent and sensible loads and demonstrated the accuracy of this approach. Furthermore, these results show that the EMPD model, when given reasonable inputs, is an accurate moisture-buffering model.« less

  15. New Hampshire Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) New Hampshire Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  16. Clean Energy Investment Center Seeks Input to Enhance Its Services...

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

    Clean Energy Investment Center Seeks Input to Enhance Its Services Clean Energy Investment Center Seeks Input to Enhance Its Services March 2, 2016 - 9:21am Addthis On March 1, the ...

  17. Wyoming Natural Gas Input Supplemental Fuels (Million Cubic Feet...

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

    Input Supplemental Fuels (Million Cubic Feet) Wyoming Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  18. Missouri Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Missouri Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  19. Minnesota Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Minnesota Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  20. Indiana Natural Gas Input Supplemental Fuels (Million Cubic Feet...

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

    Input Supplemental Fuels (Million Cubic Feet) Indiana Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  1. Maine Natural Gas Input Supplemental Fuels (Million Cubic Feet...

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

    Input Supplemental Fuels (Million Cubic Feet) Maine Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  2. Kentucky Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Kentucky Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  3. Louisiana Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Louisiana Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  4. Michigan Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Michigan Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  5. Maryland Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Maryland Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  6. Iowa Natural Gas Input Supplemental Fuels (Million Cubic Feet...

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

    Input Supplemental Fuels (Million Cubic Feet) Iowa Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  7. Virginia Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Virginia Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  8. Alabama Natural Gas Input Supplemental Fuels (Million Cubic Feet...

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

    Input Supplemental Fuels (Million Cubic Feet) Alabama Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  9. Washington Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Washington Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  10. Massachusetts Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Massachusetts Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  11. Vermont Natural Gas Input Supplemental Fuels (Million Cubic Feet...

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

    Input Supplemental Fuels (Million Cubic Feet) Vermont Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  12. Wisconsin Natural Gas Input Supplemental Fuels (Million Cubic...

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

    Input Supplemental Fuels (Million Cubic Feet) Wisconsin Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  13. ,"U.S. Downstream Processing of Fresh Feed Input"

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

    (Thousand Barrels per Day)","U.S. Downstream Processing of Fresh Feed Input by Catalytic Cracking Units (Thousand Barrels per Day)","U.S. Downstream Processing of Fresh Feed Input ...

  14. ,"U.S. Refinery Crude Oil Input Qualities"

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

    Content (Weighted Average) of Crude Oil Input to Refineries (Percent)","U.S. API Gravity (Weighted Average) of Crude Oil Input to Refineries (Degrees)" 31062,0.88,32.64 ...

  15. ,"U.S. Refinery Crude Oil Input Qualities"

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

    Content (Weighted Average) of Crude Oil Input to Refineries (Percent)","U.S. API Gravity (Weighted Average) of Crude Oil Input to Refineries (Degrees)" 31228,0.91,32.46 ...

  16. Input File Creation for the Molecular Dynamics Program LAMMPS.

    Energy Science and Technology Software Center (OSTI)

    2001-05-30

    The program creates an input data file for the molecular dynamics program LAMMPS. The input file created is a liquid mixture between two walls explicitly composed of particles. The liquid molecules are modeled as a bead-spring molecule. The input data file specifies the position and topology of the starting state. The data structure of input allows for dynamic bond creation (cross-linking) within the LAMMPS code.

  17. Refinery Input by PADD - Petroleum Supply Annual (2004)

    SciTech Connect (OSTI)

    2009-01-18

    Table showing refinery input of crude oil and petroleum products by Petroleum Administration for Defense Districts (PADD).

  18. Analysis of Stochastic Response of Neural Networks with Stochastic Input

    Energy Science and Technology Software Center (OSTI)

    1996-10-10

    Software permits the user to extend capability of his/her neural network to include probablistic characteristics of input parameter. User inputs topology and weights associated with neural network along with distributional characteristics of input parameters. Network response is provided via a cumulative density function of network response variable.

  19. Input visualization for the Cyclus nuclear fuel cycle simulator: CYClus Input Control

    SciTech Connect (OSTI)

    Flanagan, R.; Schneider, E.

    2013-07-01

    This paper discusses and demonstrates the methods used for the graphical user interface for the Cyclus fuel cycle simulator being developed at the University of Wisconsin-Madison. Cyclus Input Control (CYCIC) is currently being designed with nuclear engineers in mind, but future updates to the program will be made to allow even non-technical users to quickly and efficiently simulate fuel cycles to answer the questions important to them. (authors)

  20. Letter: Incorporation of Input from the Environmental Management SSAB into Office of Legacy Management Activities

    Broader source: Energy.gov [DOE]

    From: Assistant Secretary, Jessie H. Roberson (EM-1) To: Mr. James C. Bierer, Chair, Fernald Citizens Advisory Board

  1. High-frequency matrix converter with square wave input

    SciTech Connect (OSTI)

    Carr, Joseph Alexander; Balda, Juan Carlos

    2015-03-31

    A device for producing an alternating current output voltage from a high-frequency, square-wave input voltage comprising, high-frequency, square-wave input a matrix converter and a control system. The matrix converter comprises a plurality of electrical switches. The high-frequency input and the matrix converter are electrically connected to each other. The control system is connected to each switch of the matrix converter. The control system is electrically connected to the input of the matrix converter. The control system is configured to operate each electrical switch of the matrix converter converting a high-frequency, square-wave input voltage across the first input port of the matrix converter and the second input port of the matrix converter to an alternating current output voltage at the output of the matrix converter.

  2. Verification and Validation Supporting...

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

    ... Rep. BAW-1810, The Babcock & Wilcox Company, 1984 3 N. Hoerlik, B. Herman, B. Forget, and K. Smith. "Benchmark for Evaluation and Validation of Reactor Simulations (BEAVRS)," ...

  3. Model Verification and Validation

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

    in the decision-making process. Validation should therefore involve the code developers, computer scientists, experimentalists, statisticians, analysts, and application owners....

  4. Guidance for Fiscal Year 2015 Facilities Information Management System Data

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

    Validations | Department of Energy Fiscal Year 2015 Facilities Information Management System Data Validations Guidance for Fiscal Year 2015 Facilities Information Management System Data Validations FIMS VALIDATION GUIDANCE_FY 2015 with MEMO 141120 FINAL.pdf (1.46 MB) More Documents & Publications Microsoft PowerPoint - FY09_10 Validations_Archiving_090804 Three-year Rolling Timeline Three

  5. NIDR (New Input Deck Reader) V2.0 2

    Energy Science and Technology Software Center (OSTI)

    2010-03-31

    NIDR (New Input Deck Reader) is a facility for processing block-structured input to large programs. NIDR was written to simplify maintenance of DAKOTA (a program for uncertainty quantification and optimization), to provide better error checking of input and to allow use of aliases in the input. While written to support DAKOTA input conventions, NIDR itself is independent of DAKOTA and can be used in many kinds of programs. The initial version of NIDR was copyrightedmore » in 2008. We have since extended NIDR to support a graphical user interface called Jaguar for DAKOTA. In the Review and Approval process for an updated paper on NIDR, the Classification Approver states that a new copyright assertion should be performed.processing input to programs. NIDR is not primarily for military applications.« less

  6. Table A41. Total Inputs of Energy for Heat, Power, and Electricity

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

    A41. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Census Region, Industry Group, Selected Industries, and Type of" " Energy Management Program, 1991" " (Estimates in Trillion Btu)" ,,," Census Region",,,,"RSE" "SIC","Industry Groups",," -------------------------------------------",,,,"Row" "Code(a)","and

  7. Table A50. Total Inputs of Energy for Heat, Power, and Electricity Generatio

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

    A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Industry Group, Selected Industries, and Type of" " Energy-Management Program, 1994" " (Estimates in Trillion Btu)" ,,,," Census Region",,,"RSE" "SIC",,,,,,,"Row" "Code(a)","Industry Group and

  8. Generates 2D Input for DYNA NIKE & TOPAZ

    Energy Science and Technology Software Center (OSTI)

    1996-07-15

    MAZE is an interactive program that serves as an input and two-dimensional mesh generator for DYNA2D, NIKE2D, TOPAZ2D, and CHEMICAL TOPAZ2D. MAZE also generates a basic template for ISLAND input. MAZE has been applied to the generation of input data to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.

  9. ADOPT: A Historically Validated Light Duty Vehicle Consumer Choice Model

    SciTech Connect (OSTI)

    Brooker, A.; Gonder, J.; Lopp, S.; Ward, J.

    2015-05-04

    The Automotive Deployment Option Projection Tool (ADOPT) is a light-duty vehicle consumer choice and stock model supported by the U.S. Department of Energy’s Vehicle Technologies Office. It estimates technology improvement impacts on U.S. light-duty vehicles sales, petroleum use, and greenhouse gas emissions. ADOPT uses techniques from the multinomial logit method and the mixed logit method estimate sales. Specifically, it estimates sales based on the weighted value of key attributes including vehicle price, fuel cost, acceleration, range and usable volume. The average importance of several attributes changes nonlinearly across its range and changes with income. For several attributes, a distribution of importance around the average value is used to represent consumer heterogeneity. The majority of existing vehicle makes, models, and trims are included to fully represent the market. The Corporate Average Fuel Economy regulations are enforced. The sales feed into the ADOPT stock model. It captures key aspects for summing petroleum use and greenhouse gas emissions This includes capturing the change in vehicle miles traveled by vehicle age, the creation of new model options based on the success of existing vehicles, new vehicle option introduction rate limits, and survival rates by vehicle age. ADOPT has been extensively validated with historical sales data. It matches in key dimensions including sales by fuel economy, acceleration, price, vehicle size class, and powertrain across multiple years. A graphical user interface provides easy and efficient use. It manages the inputs, simulation, and results.

  10. ,"New Mexico Natural Gas Input Supplemental Fuels (MMcf)"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2014 ,"Release Date:","0930...

  11. BETO Seeks Stakeholder Input on Achieving High Yields from Algal...

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

    BETO is seeking input from industry, academia, and other stakeholders regarding supply systems and services for the cultivation, logistics, and preprocessing of algal feedstocks. ...

  12. USDA, Departments of Energy and Navy Seek Input from Industry...

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

    Industry to Advance Biofuels for Military and Commercial Transportation USDA, Departments of Energy and Navy Seek Input from Industry to Advance Biofuels for Military and ...

  13. Developing a low input and sustainable switchgrass feedstock production

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

    system utilizing beneficial bacterial endophytes | Department of Energy Developing a low input and sustainable switchgrass feedstock production system utilizing beneficial bacterial endophytes Developing a low input and sustainable switchgrass feedstock production system utilizing beneficial bacterial endophytes Dr. Chuansheng Mei gave this presentation at the Symbiosis Conference. symbiosis_conference_mei.pdf (2.47 MB) More Documents & Publications Symbiosis Biofeedstock Conference:

  14. Web Feature Service Validator

    Energy Science and Technology Software Center (OSTI)

    2013-08-01

    This site allows state data contributors to validate their WFS services against a specified schema for tier 3 data. The application uses the USGIN models API at https://github.com/usgin/usginmodels.

  15. Wavelength meter having single mode fiber optics multiplexed inputs

    DOE Patents [OSTI]

    Hackel, R.P.; Paris, R.D.; Feldman, M.

    1993-02-23

    A wavelength meter having a single mode fiber optics input is disclosed. The single mode fiber enables a plurality of laser beams to be multiplexed to form a multiplexed input to the wavelength meter. The wavelength meter can provide a determination of the wavelength of any one or all of the plurality of laser beams by suitable processing. Another aspect of the present invention is that one of the laser beams could be a known reference laser having a predetermined wavelength. Hence, the improved wavelength meter can provide an on-line calibration capability with the reference laser input as one of the plurality of laser beams.

  16. Wavelength meter having single mode fiber optics multiplexed inputs

    DOE Patents [OSTI]

    Hackel, Richard P.; Paris, Robert D.; Feldman, Mark

    1993-01-01

    A wavelength meter having a single mode fiber optics input is disclosed. The single mode fiber enables a plurality of laser beams to be multiplexed to form a multiplexed input to the wavelength meter. The wavelength meter can provide a determination of the wavelength of any one or all of the plurality of laser beams by suitable processing. Another aspect of the present invention is that one of the laser beams could be a known reference laser having a predetermined wavelength. Hence, the improved wavelength meter can provide an on-line calibration capability with the reference laser input as one of the plurality of laser beams.

  17. Validation of an Integrated Hydrogen Energy Station

    SciTech Connect (OSTI)

    Heydorn, Edward C

    2012-10-26

    wastewater treatment facility operated by Orange County Sanitation District (OCSD, Fountain Valley, CA). As part of achieving the objective of operating on a renewable feedstock, Air Products secured additional funding via an award from the California Air Resources Board. The South Coast Air Quality Management District also provided cost share which supported the objectives of this project. System operation at OCSD confirmed the results from shop validation testing performed during Phase 3. Hydrogen was produced at rates and purity that met the targets from the system design basis, and coproduction efficiency exceeded the 50% target set in conjunction with input from the DOE. Hydrogen production economics, updated from the Phase 2 analysis, showed pricing of $5 to $6 per kilogram of hydrogen using current gas purification systems. Hydrogen costs under $3 per kilogram are achievable if next-generation electrochemical separation technologies become available.

  18. Method and apparatus for smart battery charging including a plurality of controllers each monitoring input variables

    SciTech Connect (OSTI)

    Hammerstrom, Donald J.

    2013-10-15

    A method for managing the charging and discharging of batteries wherein at least one battery is connected to a battery charger, the battery charger is connected to a power supply. A plurality of controllers in communication with one and another are provided, each of the controllers monitoring a subset of input variables. A set of charging constraints may then generated for each controller as a function of the subset of input variables. A set of objectives for each controller may also be generated. A preferred charge rate for each controller is generated as a function of either the set of objectives, the charging constraints, or both, using an algorithm that accounts for each of the preferred charge rates for each of the controllers and/or that does not violate any of the charging constraints. A current flow between the battery and the battery charger is then provided at the actual charge rate.

  19. Guidance for FY2014 Facilities Information Management System Data

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

    Validations | Department of Energy FY2014 Facilities Information Management System Data Validations Guidance for FY2014 Facilities Information Management System Data Validations FY 2014 FIMS Data Validation Guidance w MEMO.pdf (10.9 MB) More Documents & Publications Guidance for Fiscal Year 2015 Facilities Information Management System Data Validations Deputy Secretary Memo on Improving DOE-wide Recruitment and Hiring Processes FY2012 Three

  20. ,"U.S. Downstream Processing of Fresh Feed Input"

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

    Barrels per Day)","U.S. Downstream Processing of Fresh Feed Input by Delayed and Fluid Coking Units (Thousand Barrels per Day)" 31958,,4370,946,1265 32324,,4514,931,1364 ...

  1. NREL Seeks Industry Input to Illuminate Trends in Renewable Energy

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

    Financing - News Releases | NREL NREL Seeks Industry Input to Illuminate Trends in Renewable Energy Financing August 8, 2011 The U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) is seeking input from energy developers and financiers as part of an ongoing effort to collect and share quantitative data on renewable energy financing terms and to assess barriers to renewable energy development. The current Renewable Energy Finance Tracking Initiative (REFTI)

  2. DOE Seeks Input On Addressing Contractor Pension and Medical Benefits

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

    Liabilities | Department of Energy Input On Addressing Contractor Pension and Medical Benefits Liabilities DOE Seeks Input On Addressing Contractor Pension and Medical Benefits Liabilities March 27, 2007 - 12:10pm Addthis WASHINGTON, DC - The U.S. Department of Energy (DOE) today announced in the Federal Register that it is seeking public comment on how to address the increasing costs and liabilities of contractor employee pension and medical benefits. Under the Department of Energy's unique

  3. The Need for Validation from Concept to a Terrawatt | Department of Energy

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

    The Need for Validation from Concept to a Terrawatt The Need for Validation from Concept to a Terrawatt This presentation summaries the information given by CleanPath Ventures during the Photovoltaic Validation and Bankability Workshop in San Jose, California, on August 31, 2011. cleanpathv_williams_pv_validation_2011_aug.pdf (746.93 KB) More Documents & Publications Federal Energy Management Program Report Template PV Performance and Reliability Validation Capabilities at Sandia National

  4. Aging Management Program for Stainless Steel Dry Storage System Canisters

    SciTech Connect (OSTI)

    Dunn, Darrell S.; Lin, Bruce P.; Meyer, Ryan M.; Anderson, Michael T.

    2015-06-01

    This is a conference paper presenting an aging management program for stainless steel dry storage system canisters. NRC is lead author of paper. PNNL provided input.

  5. New Executive Order Establishes a Federal Flood Risk Management...

    Office of Environmental Management (EM)

    Executive Order Establishes a Federal Flood Risk Management Standard New Executive Order ... Input, on January 30, 2015. The new E.O. amends E.O. 11988, "Floodplain ...

  6. CIPS Validation Data Plan

    SciTech Connect (OSTI)

    Nam Dinh

    2012-03-01

    This report documents analysis, findings and recommendations resulted from a task 'CIPS Validation Data Plan (VDP)' formulated as an POR4 activity in the CASL VUQ Focus Area (FA), to develop a Validation Data Plan (VDP) for Crud-Induced Power Shift (CIPS) challenge problem, and provide guidance for the CIPS VDP implementation. The main reason and motivation for this task to be carried at this time in the VUQ FA is to bring together (i) knowledge of modern view and capability in VUQ, (ii) knowledge of physical processes that govern the CIPS, and (iii) knowledge of codes, models, and data available, used, potentially accessible, and/or being developed in CASL for CIPS prediction, to devise a practical VDP that effectively supports the CASL's mission in CIPS applications.

  7. Optical device with conical input and output prism faces

    DOE Patents [OSTI]

    Brunsden, Barry S.

    1981-01-01

    A device for radially translating radiation in which a right circular cylinder is provided at each end thereof with conical prism faces. The faces are oppositely extending and the device may be severed in the middle and separated to allow access to the central part of the beam. Radiation entering the input end of the device is radially translated such that radiation entering the input end at the perimeter is concentrated toward the output central axis and radiation at the input central axis is dispersed toward the output perimeter. Devices are disclosed for compressing beam energy to enhance drilling techniques, for beam manipulation of optical spatial frequencies in the Fourier plane and for simplification of dark field and color contrast microscopy. Both refracting and reflecting devices are disclosed.

  8. Georgia Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Georgia Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 24 57 151 84 28 121 124 248 241 292 1990's 209 185 166 199 123 130 94 14 16 12 2000's 73 51 7 14 5 0 3 2 52 2010's 732 701 660 642 635 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  9. South Carolina Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) South Carolina Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 74 184 63 73 62 87 31 22 191 201 1990's 17 47 26 34 154 62 178 10 0 18 2000's 63 6 3 15 2 86 75 0 2010's 0 0 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  10. UNCLASSIFIED Nuclear Materials Management & Safeguards System

    National Nuclear Security Administration (NNSA)

    Nuclear Materials Management & Safeguards System CHANGE OF PROJECT NUMBER UPDATE PROJECT Project Number: Title: Date Valid: Date Deactivated: Classification Codes: Project Number: ...

  11. Predictive Technology Development and Crash Energy Management...

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

    Predictive Technology Development and Crash Energy Management Predictive Technology ... Merit Review 2015: Validation of Material Models for Crash Simulation of Automotive Carbon ...

  12. Environmental Management FY 2006 Budget Request DRAFT

    Office of Environmental Management (EM)

    ... Validation * Independent reviews dramatically increased - All Recovery Act scope had EIR, IPR or Program Review - Five acquisition management reviews in 2009 (V&V in 2010) - EM ...

  13. V-112: Microsoft SharePoint Input Validation Flaws Permit Cross-Site Scripting and Denial of Service Attacks

    Broader source: Energy.gov [DOE]

    This security update resolves four reported vulnerabilities in Microsoft SharePoint and Microsoft SharePoint Foundation.

  14. U-015: CiscoWorks Common Services Home Page Input Validation Flaw Lets Remote Users Execute Arbitrary Commands

    Broader source: Energy.gov [DOE]

    Successful exploitation of this vulnerability may allow an authenticated, remote attacker to execute arbitrary commands on the affected system with the privileges of a system administrator.

  15. U-067:WebSVN Input Validation Flaw in getLog() Permits Cross-Site Scripting Attacks

    Broader source: Energy.gov [DOE]

    A remote user can access the target user's cookies (including authentication cookies), if any, associated with the site running the WebSVN software, access data recently submitted by the target user via web form to the site, or take actions on the site acting as the target user.

  16. Fee Determinations: Requirement to Obtain Acquisition Executive's Input

    Broader source: Energy.gov [DOE]

    On January 28, 2013, the Deputy Secretary issued the attached memorandum to the Department's senior officials requiring any Fee Determining Official whose contract falls under the cognizance of an Acquisition Executive to brief and obtain the input of that Acquisition Executive before determining earned fee under the contract.

  17. PV Validation and Bankability Workshop | Department of Energy

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

    presentation summarizes the information given by DOE during the Photovoltaic Validation and Bankability Workshop in San Jose, California, on August 31, 2011. doe_lynn_pv_validation_2011_aug.pdf (1.03 MB) More Documents & Publications Overcoming the Barrier to Achieving Large-Scale Production - A Case Study Federal Energy Management Program Report Template Systems Integration (Fact Sheet), SunShot Initiative, U.S. Department of Energy (DOE)

  18. Input for solar annual merit review. (Conference) | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    Input for solar annual merit review. Citation Details In-Document Search Title: Input for solar annual merit review. Abstract not provided. Authors: Siegel, Nathan Phillip ...

  19. Nebraska Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Nebraska Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 9 1,838 63 2,006 2,470 2,689 2,142 2,199 1,948 2,088 1990's 2,361 2,032 1,437 791 890 15 315 134 11 4 2000's 339 6 1 13 39 16 19 33 28 18 2010's 12 9 4 2 376 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  20. Nevada Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Nevada Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 4 0 2 2 2 4 11 11 32 37 1990's 125 0 30 38 9 0 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release

  1. Ohio Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Ohio Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 69,169 69,850 64,812 62,032 43,866 24,444 5,182 18 44 348 1990's 849 891 1,051 992 1,432 904 1,828 1,423 1,194 1,200 2000's 1,442 1,149 79 1,002 492 579 423 608 460 522 2010's 353 296 366 416 641 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  2. Oregon Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Oregon Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 24 3 6 6 10 10 6 3 1990's 3 4 2 3 2 2 2 2 2 3 2000's 2 2 5 5 2 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  3. Pennsylvania Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Pennsylvania Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 3,127 10,532 5,621 3,844 82 221 196 247 254 305 1990's 220 222 132 110 252 75 266 135 80 119 2000's 261 107 103 126 131 132 124 145 123 205 2010's 4 2 2 3 20 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  4. Microchannel cross load array with dense parallel input

    DOE Patents [OSTI]

    Swierkowski, Stefan P.

    2004-04-06

    An architecture or layout for microchannel arrays using T or Cross (+) loading for electrophoresis or other injection and separation chemistry that are performed in microfluidic configurations. This architecture enables a very dense layout of arrays of functionally identical shaped channels and it also solves the problem of simultaneously enabling efficient parallel shapes and biasing of the input wells, waste wells, and bias wells at the input end of the separation columns. One T load architecture uses circular holes with common rows, but not columns, which allows the flow paths for each channel to be identical in shape, using multiple mirror image pieces. Another T load architecture enables the access hole array to be formed on a biaxial, collinear grid suitable for EDM micromachining (square holes), with common rows and columns.

  5. Agricultural and Environmental Input Parameters for the Biosphere Model

    SciTech Connect (OSTI)

    K. Rasmuson; K. Rautenstrauch

    2004-09-14

    This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.

  6. Arizona Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Arizona Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 7 0 0 0 91 101 0 0 1990's 0 0 0 0 0 0 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  7. Arkansas Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Arkansas Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 7 8 6 0 0 0 0 0 0 0 1990's 0 0 0 0 0 0 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  8. Connecticut Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Connecticut Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 144 1,584 1,077 291 239 343 298 180 245 251 1990's 111 146 40 94 29 68 48 37 33 31 2000's 20 6 6 57 191 273 91 0 0 1 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  9. Delaware Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Delaware Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 55 135 56 20 13 12 9 0 2 18 1990's 4,410 4,262 3,665 3,597 3,032 1 1 2 0 0 2000's 6 0 0 7 17 0 W 5 2 2 2010's 1 0 6 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  10. District of Columbia Natural Gas Input Supplemental Fuels (Million Cubic

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

    Feet) Input Supplemental Fuels (Million Cubic Feet) District of Columbia Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 2 1 46 0 0 0 0 0 0 0 1990's 0 0 0 0 0 0 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016

  11. Florida Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Florida Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 1 3 1 0 3 0 0 0 0 1990's 0 0 0 0 0 0 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  12. Hawaii Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Hawaii Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,190 2,993 2,899 2,775 2,449 2,655 2,630 2,461 2,801 2,844 1990's 2,817 2,725 2,711 2,705 2,831 2,793 2,761 2,617 2,715 2,752 2000's 2,769 2,689 2,602 2,602 2,626 2,606 2,613 2,683 2,559 2,447 2010's 2,472 2,467 2,510 2,658 2,743 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  13. Illinois Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Illinois Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 36,713 29,509 19,005 19,734 17,308 19,805 22,980 12,514 9,803 9,477 1990's 8,140 6,869 8,042 9,760 7,871 6,256 3,912 4,165 2,736 2,527 2000's 1,955 763 456 52 14 15 13 11 15 20 2010's 17 1 1 63 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  14. Rhode Island Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Rhode Island Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 257 951 718 594 102 130 182 109 391 219 1990's 51 92 155 126 0 27 42 18 1 1 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  15. South Dakota Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) South Dakota Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 9 24 50 1 0 0 0 0 10 16 1990's 10 3 10 9 61 37 87 30 4 5 2000's 13 5 3 57 5 4 0 1 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next

  16. Tennessee Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Tennessee Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 12 42 90 39 25 36 13 26 36 78 1990's 3 8 12 13 84 33 73 19 4 11 2000's 13 0 1 1 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next

  17. Texas Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Texas Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 0 1 14 2 9 19 4 4 9 1990's 1,240 1,076 1 3 1 1 0 0 0 17 2000's 0 1,505 2 0 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release

  18. An input shaping controller enabling cranes to move without sway

    SciTech Connect (OSTI)

    Singer, N.; Singhose, W.; Kriikku, E.

    1997-06-01

    A gantry crane at the Savannah River Technology Center was retrofitted with an Input Shaping controller. The controller intercepts the operator`s pendant commands and modifies them in real time so that the crane is moved without residual sway in the suspended load. Mechanical components on the crane were modified to make the crane suitable for the anti-sway algorithm. This paper will describe the required mechanical modifications to the crane, as well as, a new form of Input Shaping that was developed for use on the crane. Experimental results are presented which demonstrate the effectiveness of the new process. Several practical considerations will be discussed including a novel (patent pending) approach for making small, accurate moves without residual oscillations.

  19. U.S. Total Weekly Inputs & Utilization

    Gasoline and Diesel Fuel Update (EIA)

    670 16,711 16,725 16,725 16,748 16,689 1982-2016 Gross Inputs 16,957 16,999 16,994 17,008 17,011 16,988 1990-2016 Operable Capacity (Calendar Day) 18,317 18,320 18,320 18,320 18,320 18,320 1990-2016 Percent Operable Utilization 92.6 92.8 92.8 92.8 92.9 92.7 1990-2016 Refiner and Blender Net Inputs Motor Gasoline Blending Components 790 821 948 1,053 1,041 989 2008-2016 RBOB 271 297 418 463 452 458 2010-2016 CBOB 8 90 145 174 167 39 2010-2016 GTAB 182 148 162 169 127 125 2010-2016 All Other 329

  20. Helstat: an anticipatory storage-heater input controller

    SciTech Connect (OSTI)

    McIntyre, D.A.

    1985-07-01

    A new charge input controller is described, for use with static emission or damper controlled storage radiators. The controller senses the inside surface temperature of an external wall at skirting level. The measurement position has the following advantages: it is influenced by both inside and outside temperatures; it dampens out external temperature fluctuations; and it is relatively insensitive to short-term internal air temperature variations.

  1. PERSPECTIVES ON A DOE CONSEQUENCE INPUTS FOR ACCIDENT ANALYSIS APPLICATIONS

    SciTech Connect (OSTI)

    , K; Jonathan Lowrie, J; David Thoman , D; Austin Keller , A

    2008-07-30

    Department of Energy (DOE) accident analysis for establishing the required control sets for nuclear facility safety applies a series of simplifying, reasonably conservative assumptions regarding inputs and methodologies for quantifying dose consequences. Most of the analytical practices are conservative, have a technical basis, and are based on regulatory precedent. However, others are judgmental and based on older understanding of phenomenology. The latter type of practices can be found in modeling hypothetical releases into the atmosphere and the subsequent exposure. Often the judgments applied are not based on current technical understanding but on work that has been superseded. The objective of this paper is to review the technical basis for the major inputs and assumptions in the quantification of consequence estimates supporting DOE accident analysis, and to identify those that could be reassessed in light of current understanding of atmospheric dispersion and radiological exposure. Inputs and assumptions of interest include: Meteorological data basis; Breathing rate; and Inhalation dose conversion factor. A simple dose calculation is provided to show the relative difference achieved by improving the technical bases.

  2. Appendix I: Federal Energy Management Program (FEMP) inputs for FY 2008 benefits estimates

    SciTech Connect (OSTI)

    None, None

    2009-01-18

    Document summarizes the results of the benefits analysis of EERE’s programs, as described in the FY 2008 Budget Request. EERE estimates benefits for its overall portfolio and nine Research, Development, Demonstration, and Deployment (RD3) programs.

  3. PV Validation and Bankability Workshop

    Broader source: Energy.gov [DOE]

    This document summarizes the information given on Aug. 29, 2011, on the survey results of the PV Validation and Bankability Workshop on Aug. 31, 2011.

  4. Collecting and Characterizing Validation Data

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

    Characterizing Validation Data to Support Advanced Simulation of Nuclear Reactor ... Boiling Flow Model Bayesian Framework for Data Integration Nuclear System Analysis - ...

  5. Addressing Uncertainties in Design Inputs: A Case Study of Probabilistic

    Office of Environmental Management (EM)

    Activities and Events Activities and Events Upcoming Events On September 15, 2016, the Department will host a meeting to summarize the input received in the initial phase of public engagement on consent-based siting and discuss next steps in designing a process. The meeting will be held in Washington, DC at the Embassy Suites by Hilton Washington, D.C. Convention Center (900 10th Street, NW, Washington, DC 20001). Meeting Information: To learn more about this event and view an agenda, please

  6. Characterization of industrial process waste heat and input heat streams

    SciTech Connect (OSTI)

    Wilfert, G.L.; Huber, H.B.; Dodge, R.E.; Garrett-Price, B.A.; Fassbender, L.L.; Griffin, E.A.; Brown, D.R.; Moore, N.L.

    1984-05-01

    The nature and extent of industrial waste heat associated with the manufacturing sector of the US economy are identified. Industry energy information is reviewed and the energy content in waste heat streams emanating from 108 energy-intensive industrial processes is estimated. Generic types of process equipment are identified and the energy content in gaseous, liquid, and steam waste streams emanating from this equipment is evaluated. Matchups between the energy content of waste heat streams and candidate uses are identified. The resultant matrix identifies 256 source/sink (waste heat/candidate input heat) temperature combinations. (MHR)

  7. Alaska Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Total Supplemental Supply of Natural Gas Alaska Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels

  8. Gross Input to Atmospheric Crude Oil Distillation Units

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

    Day) Process: Gross Input to Atmospheric Crude Oil Dist. Units Operable Capacity (Calendar Day) Operating Capacity Idle Operable Capacity Operable Utilization Rate Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Process Area Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S. 16,365 16,167 16,261 16,222 16,477 16,803 1985-2016 PADD 1 1,136 1,080 1,052 1,148 1,174 1,155 1985-2016 East

  9. Contaminant transport in unconfined aquifer, input to low-level tank waste interim performance assessment

    SciTech Connect (OSTI)

    Lu, A.H., Westinghouse Hanford

    1996-08-14

    This report describes briefly the Hanford sitewide groundwater model and its application to the Low-Level Tank Waste Disposal (LLTWD) interim Performance Assessment (PA). The Well Intercept Factor (WIF) or dilution factor from a given areal flux entering the aquifer released from the LLTWD site are calculated for base case and various sensitivity cases. In conjunction with the calculation for released fluxes through vadose zone transport,the dose at the compliance point can be obtained by a simple multiplication. The relative dose contribution from the upstream sources was also calculated and presented in the appendix for an equal areal flux at the LLTWD site. The results provide input for management decisions on remediation action needed for reduction of the released fluxes from the upstream facilities to the allowed level to meet the required dose criteria.

  10. Evaluating the efficiency of municipalities in collecting and processing municipal solid waste: A shared input DEA-model

    SciTech Connect (OSTI)

    Rogge, Nicky; De Jaeger, Simon

    2012-10-15

    Highlights: Black-Right-Pointing-Pointer Complexity in local waste management calls for more in depth efficiency analysis. Black-Right-Pointing-Pointer Shared-input Data Envelopment Analysis can provide solution. Black-Right-Pointing-Pointer Considerable room for the Flemish municipalities to improve their cost efficiency. - Abstract: This paper proposed an adjusted 'shared-input' version of the popular efficiency measurement technique Data Envelopment Analysis (DEA) that enables evaluating municipality waste collection and processing performances in settings in which one input (waste costs) is shared among treatment efforts of multiple municipal solid waste fractions. The main advantage of this version of DEA is that it not only provides an estimate of the municipalities overall cost efficiency but also estimates of the municipalities' cost efficiency in the treatment of the different fractions of municipal solid waste (MSW). To illustrate the practical usefulness of the shared input DEA-model, we apply the model to data on 293 municipalities in Flanders, Belgium, for the year 2008.

  11. Summary of Input Request for Information DE-FOA-0001346 | Department of

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

    Energy Input Request for Information DE-FOA-0001346 Summary of Input Request for Information DE-FOA-0001346 September 2015 (140.96 KB) More Documents & Publications Summary of Stakeholder Input From May 2015 Request for Information Summary of Input Request for Information DE-FOA-0001346 DE-FOA-0001346 -- Request for Information (RFI) Summary of Input Request for Information DE-FOA-0001346

  12. US Nuclear Regulatory Commission Input to DOE Request for Information...

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

    Comments relevant to the following two sections of the RFI: "Long Term Issues: Managing a Grid with High Penetration of New Technologies" and "Reliability and Cyber-Security," US...

  13. RF Input Power Couplers for High Current SRF Applications

    SciTech Connect (OSTI)

    Khan, V. F.; Anders, W.; Burrill, Andrew; Knobloch, Jens; Kugeler, Oliver; Neumann, Axel; Wang, Haipeng

    2014-12-01

    High current SRF technology is being explored in present day accelerator science. The bERLinPro project is presently being built at HZB to address the challenges involved in high current SRF machines with the goal of generating and accelerating a 100 mA electron beam to 50 MeV in continuous wave (cw) mode at 1.3 GHz. One of the main challenges in this project is that of handling the high input RF power required for the photo-injector as well as booster cavities where there is no energy recovery process. A high power co-axial input power coupler is being developed to be used for the photo-injector and booster cavities at the nominal beam current. The coupler is based on the KEK–cERL design and has been modified to minimise the penetration of the coupler tip in the beam pipe without compromising on beam-power coupling (Qext ~105). Herein we report on the RF design of the high power (115 kW per coupler, dual couplers per cavity) bERLinPro (BP) coupler along with initial results on thermal calculations. We summarise the RF conditioning of the TTF-III couplers (modified for cw operation) performed in the past at BESSY/HZB. A similar conditioning is envisaged in the near future for the low current SRF photo-injector and the bERLinPro main linac cryomodule.

  14. Residential oil burners with low input and two stages firing

    SciTech Connect (OSTI)

    Butcher, T.; Krajewski, R.; Leigh, R.

    1997-12-31

    The residential oil burner market is currently dominated by the pressure-atomized, retention head burner. At low firing rates pressure atomizing nozzles suffer rapid fouling of the small internal passages, leading to bad spray patterns and poor combustion performance. To overcome the low input limitations of conventional burners, a low pressure air-atomized burner has been developed watch can operate at fining rates as low as 0.25 gallons of oil per hour (10 kW). In addition, the burner can be operated in a high/low fining rate mode. Field tests with this burner have been conducted at a fixed input rate of 0.35 gph (14 kW) with a side-wall vented boiler/water storage tank combination. At the test home, instrumentation was installed to measure fuel and energy flows and record trends in system temperatures. Laboratory efficiency testing with water heaters and boilers has been completed using standard single purpose and combined appliance test procedures. The tests quantify benefits due to low firing rates and other burner features. A two stage oil burner gains a strong advantage in rated efficiency while maintaining capacity for high domestic hot water and space heating loads.

  15. Colorado Natural Gas Input Supplemental Fuels (Million Cubic Feet)

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

    Input Supplemental Fuels (Million Cubic Feet) Colorado Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 9,868 9,133 8,877 7,927 9,137 8,934 8,095 8,612 10,322 9,190 1990's 15,379 6,778 7,158 8,456 8,168 7,170 6,787 6,314 5,292 4,526 2000's 4,772 5,625 5,771 5,409 5,308 5,285 6,149 6,869 6,258 7,527 2010's 5,148 4,268 4,412 4,077 4,120 - = No Data Reported; -- = Not

  16. Heat transfer analysis in Stirling engine heat input system

    SciTech Connect (OSTI)

    Chung, W.; Kim, S.

    1995-12-31

    One of the major factor in commercialization of Stirling engine is mass productivity, and the heat input system including tubular heater is one of the obstacles to mass production because of its complexity in shape and difficulty in manufacturing, which resulted from using oxidation-resistant, low-creep alloys which are not easy to machine and weld. Therefore a heater heat exchanger which is very simple in shape and easy to make has been devised, and a burner system appropriate to this heater also has been developed. In this paper specially devised heat input system which includes a heater shell shaped like U-cup and a flame tube located in the heater shell is analyzed in point of heat transfer processes to find optimum heat transfer. To enhance the heat transfer from the flame tube to the heater shell wall, it is required that the flame tube diameter be enlarged as close to the heater shell diameter as possible, and the flame tube temperature be raised as high as possible. But the enlargement of the flame tube diameter should be restricted by the state of combustion affected by hydraulic resistance of combustion gas, and the boost of the flame tube temperature should be considered carefully in the aspects of the flame tube`s service life.

  17. Software Verification and Validation Procedure

    SciTech Connect (OSTI)

    Olund, Thomas S.

    2008-09-15

    This Software Verification and Validation procedure provides the action steps for the Tank Waste Information Network System (TWINS) testing process. The primary objective of the testing process is to provide assurance that the software functions as intended, and meets the requirements specified by the client. Verification and validation establish the primary basis for TWINS software product acceptance.

  18. Using Whole-House Field Tests to Empirically Derive Moisture Buffering Model Inputs

    SciTech Connect (OSTI)

    Woods, J.; Winkler, J.; Christensen, D.; Hancock, E.

    2014-08-01

    Building energy simulations can be used to predict a building's interior conditions, along with the energy use associated with keeping these conditions comfortable. These models simulate the loads on the building (e.g., internal gains, envelope heat transfer), determine the operation of the space conditioning equipment, and then calculate the building's temperature and humidity throughout the year. The indoor temperature and humidity are affected not only by the loads and the space conditioning equipment, but also by the capacitance of the building materials, which buffer changes in temperature and humidity. This research developed an empirical method to extract whole-house model inputs for use with a more accurate moisture capacitance model (the effective moisture penetration depth model). The experimental approach was to subject the materials in the house to a square-wave relative humidity profile, measure all of the moisture transfer terms (e.g., infiltration, air conditioner condensate) and calculate the only unmeasured term: the moisture absorption into the materials. After validating the method with laboratory measurements, we performed the tests in a field house. A least-squares fit of an analytical solution to the measured moisture absorption curves was used to determine the three independent model parameters representing the moisture buffering potential of this house and its furnishings. Follow on tests with realistic latent and sensible loads showed good agreement with the derived parameters, especially compared to the commonly-used effective capacitance approach. These results show that the EMPD model, once the inputs are known, is an accurate moisture buffering model.

  19. MULTIPLE INPUT BINARY ADDER EMPLOYING MAGNETIC DRUM DIGITAL COMPUTING APPARATUS

    DOE Patents [OSTI]

    Cooke-Yarborough, E.H.

    1960-12-01

    A digital computing apparatus is described for adding a plurality of multi-digit binary numbers. The apparatus comprises a rotating magnetic drum, a recording head, first and second reading heads disposed adjacent to the first and second recording tracks, and a series of timing signals recorded on the first track. A series of N groups of digit-representing signals is delivered to the recording head at time intervals corresponding to the timing signals, each group consisting of digits of the same significance in the numbers, and the signal series is recorded on the second track of the drum in synchronism with the timing signals on the first track. The multistage registers are stepped cyclically through all positions, and each of the multistage registers is coupled to the control lead of a separate gate circuit to open the corresponding gate at only one selected position in each cycle. One of the gates has its input coupled to the bistable element to receive the sum digit, and the output lead of this gate is coupled to the recording device. The inputs of the other gates receive the digits to be added from the second reading head, and the outputs of these gates are coupled to the adding register. A phase-setting pulse source is connected to each of the multistage registers individually to step the multistage registers to different initial positions in the cycle, and the phase-setting pulse source is actuated each N time interval to shift a sum digit to the bistable element, where the multistage register coupled to bistable element is operated by the phase- setting pulse source to that position in its cycle N steps before opening the first gate, so that this gate opens in synchronism with each of the shifts to pass the sum digits to the recording head.

  20. Advanced Supply System Validation Workshop

    Broader source: Energy.gov [DOE]

    The Bioenergy Technologies Office (BETO) is hosting the Advanced Supply System Validation Workshop on February 3-4, 2015, in Golden, Colorado. The purpose of the workshop is to bring together a...

  1. Technology Validation | Department of Energy

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

    Technology Validation Technology Validation In addition to the technical challenges being addressed through research, design, and development, there are obstacles to successful implementation of fuel cells and the corresponding hydrogen infrastructure that can be addressed only by integrating the components into complete systems. After a technology achieves its technical targets in the laboratory, the next step is to show that it can work as designed within complete systems (i.e., fuel cell

  2. MARMOT Validation | Department of Energy

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

    Validation MARMOT Validation January 29, 2013 - 10:35am Addthis The composition-dependent mobility in the formulism of the phase-field modeling is implemented into the MARMOT phase-field algorithm. Benchmarking was done for the MARMOT, finite element (FE)-based phase-field framework that utilizes the new implementation of the variable splitting algorithm. The results indicate that while the variable splitting algorithm executes about eight times faster, the use of higher-order Hermite elements

  3. System maintenance verification and validation plan for the TWRS controlled baseline database system

    SciTech Connect (OSTI)

    Spencer, S.G.

    1998-09-23

    TWRS Controlled Baseline Database, formally known as the Performance Measurement Control System, is used to track and monitor TWRS project management baseline information. This document contains the verification and validation approach for system documentation changes within the database system.

  4. ALEGRA: User Input and Physics Descriptions Version 4.2 (Technical...

    Office of Scientific and Technical Information (OSTI)

    ALEGRA: User Input and Physics Descriptions Version 4.2 Citation Details In-Document Search Title: ALEGRA: User Input and Physics Descriptions Version 4.2 ALEGRA is an arbitrary ...

  5. ALEGRA: User Input and Physics Descriptions Version 4.2 (Technical...

    Office of Scientific and Technical Information (OSTI)

    ALEGRA: User Input and Physics Descriptions Version 4.2 Citation Details In-Document Search Title: ALEGRA: User Input and Physics Descriptions Version 4.2 You are accessing a ...

  6. EERE Seeks Stakeholder Input on the Co-Optimization of Fuels...

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

    EERE Seeks Stakeholder Input on the Co-Optimization of Fuels and Engines EERE Seeks Stakeholder Input on the Co-Optimization of Fuels and Engines December 18, 2015 - 1:00pm Addthis ...

  7. Impact of Battery Management on Fuel Efficiency Validity | Department of

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

    Using Small Modular Reactors | Department of Energy objective of this report is to provide DOE-NE support in evaluating future electrical generation deployment options for SMRs in areas with significant energy demand from the federal sector. The report identifies several locations with a high concentration of federal government agency electricity usage. One such location, the Hampton Roads area in Viriginia, will be studied in further detail with results documented in a separate report.

  8. Quality data validation: Comprehensive approach to environmental data validation

    SciTech Connect (OSTI)

    Matejka, L.A. Jr.

    1993-10-01

    Environmental data validation consists of an assessment of three major areas: analytical method validation; field procedures and documentation review; evaluation of the level of achievement of data quality objectives based in part on PARCC parameters analysis and expected applications of data. A program utilizing matrix association of required levels of validation effort and analytical levels versus applications of this environmental data was developed in conjunction with DOE-ID guidance documents to implement actions under the Federal Facilities Agreement and Consent Order in effect at the Idaho National Engineering Laboratory. This was an effort to bring consistent quality to the INEL-wide Environmental Restoration Program and database in an efficient and cost-effective manner. This program, documenting all phases of the review process, is described here.

  9. Geological input to reservoir simulation, Champion Field, offshore Brunei

    SciTech Connect (OSTI)

    Carter, R.; Salahudin, S.; Ho, T.C.

    1994-07-01

    Brunei Shell Petroleum's giant Champion field is in a mature stage of development with about 23 yr of production history to date. The field comprises a complex sequence of Miocene shallow marine and deltaic layered clastic reservoirs cut by numerous growth faults. This study was aimed at providing a quantified estimate of the effect of lateral and vertical discontinuities within the I and J reservoirs on the recovery for both depletion drive and in a waterflood, with a view to identifying the optimal method of completing the development of the oil reserves in this area. Geological input to the ECLIPSE simulator was aimed at quantifying two key parameters: (1) STOIIP connected to the well bore and (2) permeability contrast. Connected STOIIP is a function of the domain size of interconnected sand bodies, and this parameter was quantified by the use of detailed sedimentology resulting in sand-body facies maps for each reservoir sublayer. Permeability contrast was quantified by using a wireline-log based algorithm, calibrated against core data, which improved the existing accuracy of permeability estimates in this part of the field. Results of simulation runs illustrate the importance of quantifying geologic heterogeneity and provide valuable information for future field development planning.

  10. Interface module for transverse energy input to dye laser modules

    DOE Patents [OSTI]

    English, R.E. Jr.; Johnson, S.A.

    1994-10-11

    An interface module for transverse energy input to dye laser modules is provided particularly for the purpose of delivering enhancing transverse energy beams in the form of illumination bar to the lasing zone of a dye laser device, in particular to a dye laser amplifier. The preferred interface module includes an optical fiber array having a plurality of optical fibers arrayed in a co-planar fashion with their distal ends receiving coherent laser energy from an enhancing laser source, and their proximal ends delivered into a relay structure. The proximal ends of the optical fibers are arrayed so as to be coplanar and to be aimed generally at a common point. The transverse energy beam array delivered from the optical fiber array is acted upon by an optical element array to produce an illumination bar which has a cross section in the form of a elongated rectangle at the position of the lasing window. The illumination bar is selected to have substantially uniform intensity throughout. 5 figs.

  11. Interface module for transverse energy input to dye laser modules

    DOE Patents [OSTI]

    English, Jr., Ronald E.; Johnson, Steve A.

    1994-01-01

    An interface module (10) for transverse energy input to dye laser modules is provided particularly for the purpose of delivering enhancing transverse energy beams (36) in the form of illumination bar (54) to the lasing zone (18) of a dye laser device, in particular to a dye laser amplifier (12). The preferred interface module (10) includes an optical fiber array (30) having a plurality of optical fibers (38) arrayed in a co-planar fashion with their distal ends (44) receiving coherent laser energy from an enhancing laser source (46), and their proximal ends (4) delivered into a relay structure (3). The proximal ends (42) of the optical fibers (38) are arrayed so as to be coplanar and to be aimed generally at a common point. The transverse energy beam array (36) delivered from the optical fiber array (30) is acted upon by an optical element array (34) to produce an illumination bar (54) which has a cross section in the form of a elongated rectangle at the position of the lasing window (18). The illumination bar (54) is selected to have substantially uniform intensity throughout.

  12. ARM - Field Campaign - Precision Gas Sampling (PGS) Validation Field

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

    Campaign govCampaignsPrecision Gas Sampling (PGS) Validation Field Campaign ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Precision Gas Sampling (PGS) Validation Field Campaign 2004.04.15 - 2004.12.15 Lead Scientist : Marc Fischer For data sets, see below. Abstract Accurate prediction of the regional responses of CO2 flux to changing climate, land use, and management requires models that are

  13. ARM - Field Campaign - Precision Gas Sampling (PGS) Validation Field

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

    Campaign govCampaignsPrecision Gas Sampling (PGS) Validation Field Campaign ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Precision Gas Sampling (PGS) Validation Field Campaign 2005.03.01 - 2006.01.08 Lead Scientist : Marc Fischer For data sets, see below. Abstract Accurate prediction of the regional responses of CO2 flux to changing climate, land use, and management requires models that are

  14. ARM - Field Campaign - Precision Gas Sampling (PGS) Validation Field

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

    Campaign govCampaignsPrecision Gas Sampling (PGS) Validation Field Campaign ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Precision Gas Sampling (PGS) Validation Field Campaign 2007.01.01 - 2007.12.31 Lead Scientist : Marc Fischer For data sets, see below. Abstract Accurate prediction of the regional responses of CO2 flux to changing climate, land use, and management requires models that are

  15. Validation Data Plan Implementation: Subcooled Flow Boiling

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

    Validation Data Plan Implementation: Subcooled Flow Boiling Case Study Anh Bui and Nam ... INLMIS-12-27303 September 2012 Validation Data Plan Implementation: Subcooled Flow ...

  16. Oil field management system

    DOE Patents [OSTI]

    Fincke, James R.

    2003-09-23

    Oil field management systems and methods for managing operation of one or more wells producing a high void fraction multiphase flow. The system includes a differential pressure flow meter which samples pressure readings at various points of interest throughout the system and uses pressure differentials derived from the pressure readings to determine gas and liquid phase mass flow rates of the high void fraction multiphase flow. One or both of the gas and liquid phase mass flow rates are then compared with predetermined criteria. In the event such mass flow rates satisfy the predetermined criteria, a well control system implements a correlating adjustment action respecting the multiphase flow. In this way, various parameters regarding the high void fraction multiphase flow are used as control inputs to the well control system and thus facilitate management of well operations.

  17. Advanced Supply System Validation Workshop

    Broader source: Energy.gov [DOE]

    The Bioenergy Technologies Office (BETO) hosted the Advanced Supply System Validation Workshop on February 3-4, 2015, in Golden, Colorado. The purpose of the workshop was to bring together a diverse group of stakeholders to examine, discuss, and validate analysis assumptions used to move beyond current feedstock supply systems designed to support the agriculture and forestry industries. Participants discussed assumptions relating to volume and transportation logistics, biomass quality, and operational risks. The outcome of the workshop includes a report summarizing the expert opinions shared during the workshop.

  18. PV Validation and Bankability Workshop

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

    PV Validation and Bankability Workshop August 31, 2011 Survey Results As of August 29, 2011 List of Questions * What is your market sector? * From product development through product launch, data must be collected at each step. If the Department of Energy can identify funds to provide some type of 3rd party validation/verification effort/study, what would be your priority for that effort? * What scale of module/system data is of interest and of use in making decisions in your market sector? *

  19. High Flux Isotope Reactor system RELAP5 input model

    SciTech Connect (OSTI)

    Morris, D.G.; Wendel, M.W.

    1993-01-01

    A thermal-hydraulic computational model of the High Flux Isotope Reactor (HFIR) has been developed using the RELAP5 program. The purpose of the model is to provide a state-of-the art thermal-hydraulic simulation tool for analyzing selected hypothetical accident scenarios for a revised HFIR Safety Analysis Report (SAR). The model includes (1) a detailed representation of the reactor core and other vessel components, (2) three heat exchanger/pump cells, (3) pressurizing pumps and letdown valves, and (4) secondary coolant system (with less detail than the primary system). Data from HFIR operation, component tests, tests in facility mockups and the HFIR, HFIR specific experiments, and other pertinent experiments performed independent of HFIR were used to construct the model and validate it to the extent permitted by the data. The detailed version of the model has been used to simulate loss-of-coolant accidents (LOCAs), while the abbreviated version has been developed for the operational transients that allow use of a less detailed nodalization. Analysis of station blackout with core long-term decay heat removal via natural convection has been performed using the core and vessel portions of the detailed model.

  20. Initial validation of FORCE2

    SciTech Connect (OSTI)

    Burge, S.W.

    1991-06-01

    Erosion has been identified as one of the significant design issues in fluid beds. A cooperative R&D venture of industry, research, and government organizations was recently formed to meet the industry need for a better understanding of erosion in fluid beds. Research focussed on bed hydrodynamics, which are considered to be the primary erosion mechanism. As part of this work, ANL developed an analytical model (FLUFIX) for bed hydrodynamics. Partial validation was performed using data from experiments sponsored by the research consortium. Development of a three-dimensional fluid bed hydrodynamic model was part of Asea-Babcock`s in-kind contribution to the R&D venture. This model, FORCE2, was developed by Babcock & Wilcox`s Research and Development Division existing B&W program and on the gas-solids modeling and was based on an existing B&W program and on the gas-solids modeling technology developed by ANL and others. FORCE2 contains many of the features needed to model plant size beds and, therefore can be used along with the erosion technology to assess metal wastage in industrial equipment. As part of the development efforts, FORCE2 was partially validated using ANL`s two-dimensional model, FLUFIX, and experimental data. Time constraints as well as the lack of good hydrodynamic data, particularly at the plant scale, prohibited a complete validation of FORCE2. This report describes this initial validation of FORCE2.

  1. Combined Effects of Gravity, Bending Moment, Bearing Clearance, and Input Torque on Wind Turbine Planetary Gear Load Sharing: Preprint

    SciTech Connect (OSTI)

    Guo, Y.; Keller, J.; LaCava, W.

    2012-09-01

    This computational work investigates planetary gear load sharing of three-mount suspension wind turbine gearboxes. A three dimensional multibody dynamic model is established, including gravity, bending moments, fluctuating mesh stiffness, nonlinear tooth contact, and bearing clearance. A flexible main shaft, planetary carrier, housing, and gear shafts are modeled using reduced degrees-of-freedom through modal compensation. This drivetrain model is validated against the experimental data of Gearbox Reliability Collaborative for gearbox internal loads. Planet load sharing is a combined effect of gravity, bending moment, bearing clearance, and input torque. Influences of each of these parameters and their combined effects on the resulting planet load sharing are investigated. Bending moments and gravity induce fundamental excitations in the rotating carrier frame, which can increase gearbox internal loads and disturb load sharing. Clearance in carrier bearings reduces the bearing load carrying capacity and thus the bending moment from the rotor can be transmitted into gear meshes. With bearing clearance, the bending moment can cause tooth micropitting and can induce planet bearing fatigue, leading to reduced gearbox life. Planet bearings are susceptible to skidding at low input torque.

  2. New Executive Order Establishes a Federal Flood Risk Management Standard

    Broader source: Energy.gov [DOE]

    President Obama signed Executive Order (E.O.) 13690, Establishing a Federal Flood Risk Management Standard and a Process for Further Soliciting and Considering Stakeholder Input, on January 30, 2015.

  3. Development of Earthquake Ground Motion Input for Preclosure Seismic Design and Postclosure Performance Assessment of a Geologic Repository at Yucca Mountain, NV

    SciTech Connect (OSTI)

    I. Wong

    2004-11-05

    This report describes a site-response model and its implementation for developing earthquake ground motion input for preclosure seismic design and postclosure assessment of the proposed geologic repository at Yucca Mountain, Nevada. The model implements a random-vibration theory (RVT), one-dimensional (1D) equivalent-linear approach to calculate site response effects on ground motions. The model provides results in terms of spectral acceleration including peak ground acceleration, peak ground velocity, and dynamically-induced strains as a function of depth. In addition to documenting and validating this model for use in the Yucca Mountain Project, this report also describes the development of model inputs, implementation of the model, its results, and the development of earthquake time history inputs based on the model results. The purpose of the site-response ground motion model is to incorporate the effects on earthquake ground motions of (1) the approximately 300 m of rock above the emplacement levels beneath Yucca Mountain and (2) soil and rock beneath the site of the Surface Facilities Area. A previously performed probabilistic seismic hazard analysis (PSHA) (CRWMS M&O 1998a [DIRS 103731]) estimated ground motions at a reference rock outcrop for the Yucca Mountain site (Point A), but those results do not include these site response effects. Thus, the additional step of applying the site-response ground motion model is required to develop ground motion inputs that are used for preclosure and postclosure purposes.

  4. Methodology for Validating Building Energy Analysis Simulations

    SciTech Connect (OSTI)

    Judkoff, R.; Wortman, D.; O'Doherty, B.; Burch, J.

    2008-04-01

    The objective of this report was to develop a validation methodology for building energy analysis simulations, collect high-quality, unambiguous empirical data for validation, and apply the validation methodology to the DOE-2.1, BLAST-2MRT, BLAST-3.0, DEROB-3, DEROB-4, and SUNCAT 2.4 computer programs. This report covers background information, literature survey, validation methodology, comparative studies, analytical verification, empirical validation, comparative evaluation of codes, and conclusions.

  5. Federal Energy Management Program Report Template | Department of Energy

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

    Federal Energy Management Program Report Template Federal Energy Management Program Report Template Template to create reports for the Federal Energy Management Program (FEMP) 53483.pdf (491.71 KB) More Documents & Publications Testing and Validation of Vehicle to Grid Communication Standards Risk Management Tool Attributes: Taking It from Brown to Green: Renewable Energy on Contaminated Lands

  6. A Requirement for Significant Reduction in the Maximum BTU Input Rate of

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

    Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers | Department of Energy A Requirement for Significant Reduction in the Maximum BTU Input Rate of Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers A Requirement for Significant Reduction in the Maximum BTU Input Rate of Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers Comment that a requirement to reduce the BTU input rate of existing decorative

  7. Water Power Calculator Temperature and Analog Input/Output Module Ambient Temperature Testing

    SciTech Connect (OSTI)

    Mark D. McKay

    2011-02-01

    Water Power Calculator Temperature and Analog input/output Module Ambient Temperature Testing A series of three ambient temperature tests were conducted for the Water Power Calculator development using the INL Calibration Laboratorys Tenney Environmental Chamber. The ambient temperature test results demonstrate that the Moore Industries Temperature Input Modules, Analog Input Module and Analog Output Module, ambient temperature response meet or exceed the manufactures specifications

  8. Rail-to-rail differential input amplification stage with main and surrogate differential pairs

    DOE Patents [OSTI]

    Britton, Jr., Charles Lanier; Smith, Stephen Fulton

    2007-03-06

    An operational amplifier input stage provides a symmetrical rail-to-rail input common-mode voltage without turning off either pair of complementary differential input transistors. Secondary, or surrogate, transistor pairs assume the function of the complementary differential transistors. The circuit also maintains essentially constant transconductance, constant slew rate, and constant signal-path supply current as it provides rail-to-rail operation.

  9. DOE Seeks Public Input on an Integrated, Interagency Pre-Application

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

    Process for Transmission Authorizations | Department of Energy Seeks Public Input on an Integrated, Interagency Pre-Application Process for Transmission Authorizations DOE Seeks Public Input on an Integrated, Interagency Pre-Application Process for Transmission Authorizations August 29, 2013 - 9:09am Addthis A Request for Information (RFI) seeking public input for a draft Integrated, Interagency Pre-application (IIP) Process was published in the Federal Register on August 29, 2013. The

  10. DOE Seeking Input on Alternative Uses of Nickel Inventory | Department of

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

    Energy Seeking Input on Alternative Uses of Nickel Inventory DOE Seeking Input on Alternative Uses of Nickel Inventory March 9, 2007 - 10:28am Addthis WASHINGTON, DC - The U.S. Department of Energy (DOE) is seeking input from industry representatives on the safe disposition of approximately 15,300 tons of nickel scrap recovered from uranium enrichment process equipment at the Department's Oak Ridge, TN, and Paducah, KY, facilities. The Expression of Interest (EOI), released today, will