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


1

U-132: Apache Wicket Input Validation Flaw in 'wicket:pageMapName'  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2: Apache Wicket Input Validation Flaw in 'wicket:pageMapName' 2: Apache Wicket Input Validation Flaw in 'wicket:pageMapName' Parameter Permits Cross-Site Scripting Attacks U-132: Apache Wicket Input Validation Flaw in 'wicket:pageMapName' Parameter Permits Cross-Site Scripting Attacks March 23, 2012 - 7:42am Addthis PROBLEM: Apache Wicket Input Validation Flaw in 'wicket:pageMapName' Parameter Permits Cross-Site Scripting Attacks PLATFORM: Apache Wicket 1.4.x ABSTRACT: A remote user can conduct cross-site scripting attacks. reference LINKS: Apache Wicket CVE-2012-0047 SecurityTracker Alert ID: 1026839 IMPACT ASSESSMENT: High Discussion: The software does not properly filter HTML code from user-supplied input in the 'wicket:pageMapName' request parameter before displaying the input. A remote user can cause arbitrary scripting code to be executed by the target

2

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

5: Apache Wicket Input Validation Flaw Permits Cross-Site 5: Apache Wicket Input Validation Flaw Permits Cross-Site Scripting Attacks U-255: Apache Wicket Input Validation Flaw Permits Cross-Site Scripting Attacks September 11, 2012 - 6:00am Addthis PROBLEM: Apache Wicket Input Validation Flaw Permits Cross-Site Scripting Attacks PLATFORM: Apache Software Foundation Apache Wicket 1.5.5 Apache Software Foundation Apache Wicket 1.5-RC5.1 Apache Software Foundation Apache Wicket 1.4.20 Apache Software Foundation Apache Wicket 1.4.18 Apache Software Foundation Apache Wicket 1.4.17 Apache Software Foundation Apache Wicket 1.4.16 ABSTRACT: A vulnerability was reported in Apache Wicket reference LINKS: Apache Wicket SecurityTracker Alert ID: 1027508 Bugtraq ID: 55445 CVE-2012-3373 IMPACT ASSESSMENT: Medium Discussion: The software does not properly filter HTML code from user-supplied input in

3

T-623: HP Business Availability Center Input Validation Hole...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

4

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

Energy.gov (U.S. Department of Energy (DOE)) 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...

5

Increased Software Reliability Through Input Validation Analysis and Testing  

Science Conference Proceedings (OSTI)

The Input Validation Testing (IVT) technique has been developed to address the problem of statically analyzing input command syntax as defined in English textual interface and requirements specifications and then generating test cases for input validation ... Keywords: Software reliability, requirements analysis, system testing, quality control and assurance, interfaces, input validation

Jane Huffman Hayes; A. Jefferson Offutt

1999-11-01T23:59:59.000Z

6

U-219: Symantec Web Gateway Input Validation Flaws Lets Remote...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

9: Symantec Web Gateway Input Validation Flaws Lets Remote Users Inject SQL Commands, Execute Arbitrary Commands, and Change User Passwords U-219: Symantec Web Gateway Input...

7

Semi-valid input coverage for fuzz testing  

Science Conference Proceedings (OSTI)

We define semi-valid input coverage (SVCov), the first coverage criterion for fuzz testing. Our criterion is applicable whenever the valid inputs can be defined by a finite set of constraints. SVCov measures to what extent the tests cover the domain ... Keywords: coverage criteria, fuzz testing, security testing

Petar Tsankov, Mohammad Torabi Dashti, David Basin

2013-07-01T23:59:59.000Z

8

T-623: HP Business Availability Center Input Validation Hole Permits  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

3: HP Business Availability Center Input Validation Hole 3: HP Business Availability Center Input Validation Hole Permits Cross-Site Scripting Attacks T-623: HP Business Availability Center Input Validation Hole Permits Cross-Site Scripting Attacks May 16, 2011 - 3:05pm Addthis PROBLEM: A vulnerability was reported in HP Business Availability Center. A remote user can conduct cross-site scripting attacks. PLATFORM: HP Business Availability Center software 8.06 and prior versions ABSTRACT: The software does not properly filter HTML code from user-supplied input before displaying the input. reference LINKS: SecurityTracker Alert ID:1025535 HP Knowledge Base CVE-2011-1856 Secunia ID: SA44569 HP Document ID:c02823184 | ESB-2011.0525 IMPACT ASSESSMENT: High Discussion: A remote user can cause arbitrary scripting code to be executed by the

9

T-693: Symantec Endpoint Protection Manager Input Validation Hole Permits  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

3: Symantec Endpoint Protection Manager Input Validation Hole 3: Symantec Endpoint Protection Manager 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 Scripting and Cross-Site Request Forgery Attacks August 15, 2011 - 3:42pm Addthis PROBLEM: Two vulnerabilities were reported in Symantec Endpoint Protection Manager. A remote user can conduct cross-site scripting attacks. A remote user can conduct cross-site request forgery attacks. PLATFORM: Version(s): 11.0 RU6(11.0.600x), 11.0 RU6-MP1(11.0.6100), 11.0 RU6-MP2(11.0.6200), 11.0 RU6-MP3(11.0.6300) ABSTRACT: Symantec Endpoint Protection Manager Input Validation Hole Permits Cross-Site Scripting and Cross-Site Request Forgery Attacks. reference LINKS:

10

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Sensitive Information U-270:Trend Micro Control Manager Input Validation Flaw in Ad Hoc Query Module Lets Remote Users Inject SQL Commands U-015: CiscoWorks Common Services Home...

11

V-192: Symantec Security Information Manager Input Validation Flaws Permit  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

92: Symantec Security Information Manager Input Validation Flaws 92: Symantec Security Information Manager Input Validation Flaws Permit Cross-Site Scripting, SQL Injection, and Information Disclosure Attacks V-192: Symantec Security Information Manager Input Validation Flaws Permit Cross-Site Scripting, SQL Injection, and Information Disclosure Attacks July 4, 2013 - 6:00am Addthis PROBLEM: Several vulnerabilities were reported in Symantec Security Information Manager PLATFORM: Symantec Security Information Manager Appliance Version 4.7.x and 4.8.0 ABSTRACT: Symantec was notified of multiple security issues impacting the SSIM management console REFERENCE LINKS: SecurityTracker Alert ID: 1028727 Symantec Security Advisory SYM13-006 CVE-2013-1613 CVE-2013-1614 CVE-2013-1615 IMPACT ASSESSMENT: Medium DISCUSSION: The console does not properly filter HTML code from user-supplied input

12

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

SciTech Connect

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 experiments from the IHECSBE, to include experiments from areas beyond criticality safety, such as reactor physics and shielding, and to include application models. In the future, external SCALE users may also obtain qualification under the VALID procedure and be involved in expanding the library. The VALID library provides a pathway for the criticality safety community to leverage modeling and analysis expertise at ORNL.

Marshall, William BJ J [ORNL; Rearden, Bradley T [ORNL

2013-01-01T23:59:59.000Z

13

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

Energy.gov (U.S. Department of Energy (DOE)) 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...

14

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

Energy.gov (U.S. Department of Energy (DOE)) 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...

15

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

Energy.gov (U.S. Department of Energy (DOE)) 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...

16

U-270:Trend Micro Control Manager Input Validation Flaw in Ad...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

0:Trend Micro Control Manager Input Validation Flaw in Ad Hoc Query Module Lets Remote Users Inject SQL Commands U-270:Trend Micro Control Manager Input Validation Flaw in Ad Hoc...

17

U-001:Symantec IM Manager Input Validation Flaws | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

U-001:Symantec IM Manager Input Validation Flaws U-001:Symantec IM Manager Input Validation Flaws U-001:Symantec IM Manager Input Validation Flaws October 3, 2011 - 12:45pm Addthis PROBLEM: Symantec IM Manager Input Validation Flaws Permit Cross-Site Scripting, SQL Injection, and Code Execution Attacks. PLATFORM: Version(s): prior to 8.4.18 ABSTRACT: Symantec IM Manager Input Validation Flaws Permit Cross-Site Scripting, SQL Injection, and Code Execution Attacks. reference LINKS: Security Advisory: SYM11-012 SecurityTracker Alert ID: 1026130 IMPACT ASSESSMENT: Medium Discussion: Several vulnerabilities were reported in Symantec IM Manager. A remote user can conduct cross-site scripting attacks. A remote user can inject SQL commands. Several scripts do not properly filter HTML code from user-supplied input before displaying the input [CVE-2011-0552]. A remote user can create a

18

T-698: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' Permits  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

8: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' 8: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' Permits Cross-Site Scripting Attacks T-698: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' Permits Cross-Site Scripting Attacks August 22, 2011 - 3:54pm Addthis PROBLEM: A vulnerability was reported in Adobe ColdFusion. A remote user can conduct cross-site scripting attacks. PLATFORM: Adobe ColdFusion 9.x ABSTRACT: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' Permits Cross-Site Scripting Attacks. reference LINKS: Adobe Vulnerability Report Adobe Security Bulletin ColdFusion Support SecurityTracker Alert ID: 1025957 IMPACT ASSESSMENT: Medium Discussion: The 'probe.cfm' script does not properly filter HTML code from user-supplied input in the 'name' parameter before displaying the input. A remote user can create a specially crafted URL that, when loaded by a

19

T-670: Skype Input Validation Flaw in 'mobile phone' Profile Entry Permits  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

0: Skype Input Validation Flaw in 'mobile phone' Profile Entry 0: Skype Input Validation Flaw in 'mobile phone' Profile Entry Permits Cross-Site Scripting Attacks T-670: Skype Input Validation Flaw in 'mobile phone' Profile Entry Permits Cross-Site Scripting Attacks July 18, 2011 - 7:09am Addthis PROBLEM: A vulnerability was reported in Skype. A remote user can conduct cross-site scripting attacks. PLATFORM: 5.3.0.120 and prior versions ABSTRACT: The software does not properly filter HTML code from user-supplied input in the The "mobile phone" profile entry before displaying the input. reference LINKS: SecurityTracker Alert ID: 1025789 Skype Security Advisory KoreSecure News H Security ID: 1279864 IMPACT ASSESSMENT: High Discussion: Skype suffers from a persistent Cross-Site Scripting vulnerability due to a lack of input validation and output sanitization of the "mobile phone"

20

T-698: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' Permits  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

8: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' 8: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' Permits Cross-Site Scripting Attacks T-698: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' Permits Cross-Site Scripting Attacks August 22, 2011 - 3:54pm Addthis PROBLEM: A vulnerability was reported in Adobe ColdFusion. A remote user can conduct cross-site scripting attacks. PLATFORM: Adobe ColdFusion 9.x ABSTRACT: Adobe ColdFusion Input Validation Flaw in 'probe.cfm' Permits Cross-Site Scripting Attacks. reference LINKS: Adobe Vulnerability Report Adobe Security Bulletin ColdFusion Support SecurityTracker Alert ID: 1025957 IMPACT ASSESSMENT: Medium Discussion: The 'probe.cfm' script does not properly filter HTML code from user-supplied input in the 'name' parameter before displaying the input. A remote user can create a specially crafted URL that, when loaded by a

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


21

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

4: Splunk Web Input Validation Flaw Permits Cross-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 PROBLEM: Splunk Web Input Validation Flaw Permits Cross-Site Scripting Attacks PLATFORM: Version(s): 4.3.0 through 4.3.5 ABSTRACT: A vulnerability was reported in Splunk Web. REFERENCE LINKS: SecurityTracker Alert ID: 1028371 Splunk IMPACT ASSESSMENT: High DISCUSSION: Splunk Web 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. The code will originate from the site running the Splunk Web software and will run in the security context of that site. As a result, the code will be able to access the

22

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2: Barracuda Web Filter Input Validation Flaws Permit 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 6, 2012 - 6:00am Addthis PROBLEM: Barracuda Web Filter Input Validation Flaws Permit Cross-Site Scripting Attacks PLATFORM: Barracuda Web Filter 5.0.015 is vulnerable; other versions may also be affected. ABSTRACT: Barracuda Web Filter Authentication Module Multiple HTML Injection Vulnerabilities reference LINKS: Barracuda Networks Barracuda Networks Security ID: BNSEC-279/BNYF-5533 SecurityTracker Alert ID: 1027500 Bugtraq ID: 55394 seclists.org IMPACT ASSESSMENT: Medium Discussion: Two scripts not properly filter HTML code from user-supplied input before displaying the input. A remote user can cause arbitrary scripting code to

23

T-670: Skype Input Validation Flaw in 'mobile phone' Profile Entry Permits  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

70: Skype Input Validation Flaw in 'mobile phone' Profile Entry 70: Skype Input Validation Flaw in 'mobile phone' Profile Entry Permits Cross-Site Scripting Attacks T-670: Skype Input Validation Flaw in 'mobile phone' Profile Entry Permits Cross-Site Scripting Attacks July 18, 2011 - 7:09am Addthis PROBLEM: A vulnerability was reported in Skype. A remote user can conduct cross-site scripting attacks. PLATFORM: 5.3.0.120 and prior versions ABSTRACT: The software does not properly filter HTML code from user-supplied input in the The "mobile phone" profile entry before displaying the input. reference LINKS: SecurityTracker Alert ID: 1025789 Skype Security Advisory KoreSecure News H Security ID: 1279864 IMPACT ASSESSMENT: High Discussion: Skype suffers from a persistent Cross-Site Scripting vulnerability due to a lack of input validation and output sanitization of the "mobile phone"

24

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

0: Adobe Flex SDK Input Validation Flaw Permits Cross-Site 0: Adobe Flex SDK Input Validation Flaw Permits Cross-Site Scripting Attacks U-050: Adobe Flex SDK Input Validation Flaw Permits Cross-Site Scripting Attacks December 2, 2011 - 5:24am Addthis PROBLEM: Adobe Flex SDK Input Validation Flaw Permits Cross-Site Scripting Attacks. PLATFORM: Adobe Flex SDK 4.5.1 and earlier 4.x versions for Windows, Macintosh and Linux Adobe Flex SDK 3.6 and earlier 3.x versions for Windows, Macintosh and Linux ABSTRACT: Flex applications created using the Flex SDK may not properly filter HTML code from user-supplied input before displaying the input. reference LINKS: Adobe Security Bulletin CVE-2011-2461 SecurityTracker Alert ID: 1026361 IMPACT ASSESSMENT: High Discussion: A remote user may be able to cause arbitrary scripting code to be executed

25

V-085: Cisco Unity Express Input Validation Hole Permits Cross-Site Request  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

5: Cisco Unity Express Input Validation Hole Permits Cross-Site 5: Cisco Unity Express Input Validation Hole Permits Cross-Site Request Forgery Attacks V-085: Cisco Unity Express Input Validation Hole Permits Cross-Site Request Forgery Attacks February 6, 2013 - 1:06am Addthis PROBLEM: Cisco Unity Express Input Validation Hole Permits Cross-Site Request Forgery Attacks PLATFORM: Cisco Unity Express prior to 8.0 ABSTRACT: A vulnerability was reported in Cisco Unity Express. REFERENCE LINKS: Cisco Security Notice SecurityTracker Alert ID: 1028075 CVE-2013-1120 IMPACT ASSESSMENT: Medium DISCUSSION: Cisco Unity Express software prior to version 8.0 contains vulnerabilities that could allow an unauthenticated, remote attacker to conduct cross site request forgery attacks. The vulnerabilities are due to insufficient input validation. An attacker could exploit these vulnerabilities by

26

V-139: Cisco Network Admission Control Input Validation Flaw Lets Remote  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

9: Cisco Network Admission Control Input Validation Flaw Lets 9: Cisco Network Admission Control Input Validation Flaw Lets Remote Users Inject SQL Commands V-139: Cisco Network Admission Control Input Validation Flaw Lets Remote Users Inject SQL Commands April 21, 2013 - 11:50pm Addthis 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 vulnerability was reported in Cisco Network Admission Control. REFERENCE LINKS: SecurityTracker Alert ID: 1028451 Cisco Advisory ID: cisco-sa-20130417-nac CVE-2013-1177 IMPACT ASSESSMENT: High DISCUSSION: The Cisco Network Admission Control (NAC) Manager does not properly validate user-supplied input. A remote user can supply a specially crafted parameter value to execute SQL commands on the underlying database.

27

U-204: HP Network Node Manager i Input Validation Hole Permits Cross-Site  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

204: HP Network Node Manager i Input Validation Hole Permits 204: HP Network Node Manager i Input Validation Hole Permits Cross-Site Scripting Attacks U-204: HP Network Node Manager i Input Validation Hole Permits Cross-Site Scripting Attacks July 3, 2012 - 7:00am Addthis PROBLEM: HP Network Node Manager i Input Validation Hole Permits Cross-Site Scripting Attacks PLATFORM: Version(s): 8.x, 9.0x, 9.1x ABSTRACT: 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). reference LINKS: The Vendor's Advisory SecurityTracker Alert ID: 1027215 CVE-2012-2018 IMPACT ASSESSMENT: Medium Discussion: A vulnerability was reported in HP Network Node Manager i. The software does not properly filter HTML code from user-supplied input before

28

U-204: HP Network Node Manager i Input Validation Hole Permits Cross-Site  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

4: HP Network Node Manager i Input Validation Hole Permits 4: HP Network Node Manager i Input Validation Hole Permits Cross-Site Scripting Attacks U-204: HP Network Node Manager i Input Validation Hole Permits Cross-Site Scripting Attacks July 3, 2012 - 7:00am Addthis PROBLEM: HP Network Node Manager i Input Validation Hole Permits Cross-Site Scripting Attacks PLATFORM: Version(s): 8.x, 9.0x, 9.1x ABSTRACT: 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). reference LINKS: The Vendor's Advisory SecurityTracker Alert ID: 1027215 CVE-2012-2018 IMPACT ASSESSMENT: Medium Discussion: A vulnerability was reported in HP Network Node Manager i. The software does not properly filter HTML code from user-supplied input before

29

U-139: IBM Tivoli Directory Server Input Validation Flaw | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

39: IBM Tivoli Directory Server Input Validation Flaw 39: IBM Tivoli Directory Server Input Validation Flaw U-139: IBM Tivoli Directory Server Input Validation Flaw April 3, 2012 - 7:00am Addthis PROBLEM: A vulnerability was reported in IBM Tivoli Directory Server. A remote user can conduct cross-site scripting attacks PLATFORM: Version(s): 6.2, 6.3 ABSTRACT: The Web Admin Tool does not properly filter HTML code from user-supplied input before displaying the input. Reference LINKS: Vendor Advisory Security Tracker ID 1026880 CVE-2012-0740 IMPACT ASSESSMENT: Medium Discussion: A remote user can create a specially crafted URL that, when loaded by a target user, will cause arbitrary scripting code to be executed by the target user's browser. The code will originate from the site running the IBM Tivoli Directory Server software and will run in the security context

30

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

V-229: IBM Lotus iNotes Input Validation Flaws Permit Cross-Site V-229: 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 Seclist.org CVE-2013-0590 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. A remote user can cause arbitrary scripting code to be executed by the target user's browser. The code will originate

31

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

68: Splunk Web Input Validation Flaw Permits Cross-Site 68: 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 PROBLEM: A vulnerability was reported in Splunk Web PLATFORM: Version(s) prior to 5.0.3 ABSTRACT: A reflected cross-site scripting vulnerability was identified in Splunk Web REFERENCE LINKS: SecurityTracker Alert ID: 1028605 Splunk Security Advisory SPL-59895 CVE-2012-6447 IMPACT ASSESSMENT: Medium DISCUSSION: The web interface does not properly filter HTML code from user-supplied input 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 by the target user's browser. The code will

32

U-102: Cisco IronPort Encryption Appliance Input Validation Flaw Permits  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2: Cisco IronPort Encryption Appliance Input Validation Flaw 2: Cisco IronPort Encryption Appliance Input Validation Flaw Permits Cross-Site Scripting Attacks U-102: Cisco IronPort Encryption Appliance Input Validation Flaw Permits Cross-Site Scripting Attacks February 14, 2012 - 8:00am Addthis PROBLEM: A vulnerability was reported in Cisco IronPort Encryption Appliance. PLATFORM: Version(s): prior to 6.5.3 ABSTRACT: A remote user can conduct cross-site scripting reference LINKS: Vendor URL CVE-2012-0340 Security Tracker ID:1026669 IMPACT ASSESSMENT: Medium Discussion: The interface does not properly filter HTML code from user-supplied input 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 by the target user's browser. The code will originate from

33

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

8: Splunk Web Input Validation Flaw Permits Cross-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 PROBLEM: A vulnerability was reported in Splunk Web PLATFORM: Version(s) prior to 5.0.3 ABSTRACT: A reflected cross-site scripting vulnerability was identified in Splunk Web REFERENCE LINKS: SecurityTracker Alert ID: 1028605 Splunk Security Advisory SPL-59895 CVE-2012-6447 IMPACT ASSESSMENT: Medium DISCUSSION: The web interface does not properly filter HTML code from user-supplied input 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 by the target user's browser. The code will

34

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

4:Juniper Secure Access Input Validation Flaw Permits 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, 2012 - 7:30am Addthis PROBLEM: A vulnerability was reported in Juniper Secure Access/Instant Virtual Extranet (IVE). A remote user can conduct cross-site scripting attacks. PLATFORM: Version(s): prior to 7.0R9 and 7.1R ABSTRACT: 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. reference LINKS: Vendor URL SecurityTracker Alert ID: 1026893 IMPACT ASSESSMENT: High Discussion: The code will originate from the interface and will run in the security

35

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

93: Barracuda SSL VPN Input Validation Hole Permits Cross-Site 93: 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 - 6:00am Addthis PROBLEM: A vulnerability was reported in Barracuda SSL VPN PLATFORM: Version(s) prior to 2.3.3.216 ABSTRACT: Several scripts do not properly filter HTML code from user-supplied input before displaying the input via several parameters REFERENCE LINKS: SecurityTracker Alert ID: 1028736 Barracuda SSL VPN Release Notes Zero Science Lab IMPACT ASSESSMENT: Medium DISCUSSION: The code will originate from the Barracuda SSL VPN interface 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

36

V-153: Symantec Brightmail Gateway Input Validation Flaw Permits Cross-Site  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

3: Symantec Brightmail Gateway Input Validation Flaw Permits 3: Symantec Brightmail Gateway Input Validation Flaw Permits Cross-Site Scripting Attacks V-153: Symantec Brightmail Gateway Input Validation Flaw Permits Cross-Site Scripting Attacks May 10, 2013 - 6:00am Addthis PROBLEM: A vulnerability was reported in Symantec Brightmail Gateway PLATFORM: The vulnerabilities are reported in versions prior to 9.5.x ABSTRACT: Symantec's Brightmail Gateway management console is susceptible to stored cross-site scripting (XSS) issues found in some of the administrative interface pages. REFERENCE LINKS: Security Tracker Alert ID: 1028530 Symantec Security Advisory CVE-2013-1611 IMPACT ASSESSMENT: Medium DISCUSSION: The administrative interface does not properly filter HTML code from user-supplied input before displaying the input. A remote user can cause

37

U-015: CiscoWorks Common Services Home Page Input Validation Flaw Lets  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

15: CiscoWorks Common Services Home Page Input Validation Flaw 15: CiscoWorks Common Services Home Page Input Validation Flaw Lets Remote Users Execute Arbitrary Commands U-015: CiscoWorks Common Services Home Page Input Validation Flaw Lets Remote Users Execute Arbitrary Commands October 20, 2011 - 7:30am Addthis PROBLEM: CiscoWorks Common Services Home Page Input Validation Flaw Lets Remote Users Execute Arbitrary Commands. PLATFORM: CiscoWorks Common Services-based products prior to version 4.1 running on Microsoft Windows ABSTRACT: 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. reference LINKS: Cisco Security Advisory ID: cisco-sa-20111019-cs Cisco Security Advisories and Responses

38

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2: IBM WebSphere Commerce Edition Input Validation Holes Permit 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 authentication cookies), if any, associated with the site running the IBM WebSphere 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. reference LINKS: IBM Recommended Fixes for WebSphere Commerce IBM Support SecurityTracker Alert ID: 1026074

39

V-112: Microsoft SharePoint Input Validation Flaws Permit Cross-Site  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2: Microsoft SharePoint Input Validation Flaws Permit 2: Microsoft SharePoint 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 of Service Attacks March 15, 2013 - 6:00am Addthis PROBLEM: Several vulnerabilities were reported in Microsoft SharePoint PLATFORM: Microsoft SharePoint 2010 SP1 ABSTRACT: This security update resolves four reported vulnerabilities in Microsoft SharePoint and Microsoft SharePoint Foundation. REFERENCE LINKS: Security Tracker Alert ID 1028278 MS Security Bulletin MS13-024 CVE-2013-0080 CVE-2013-0083 CVE-2013-0084 CVE-2013-0085 IMPACT ASSESSMENT: High DISCUSSION: The security update addresses the vulnerabilities correcting the way that Microsoft SharePoint Server validates URLs and user input.

40

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

0: HP Diagnostics Input Validation Hole Permits Cross-Site 0: HP Diagnostics Input Validation Hole Permits Cross-Site Scripting Attacks T-590: HP Diagnostics Input Validation Hole Permits Cross-Site Scripting Attacks March 29, 2011 - 3:05pm Addthis PROBLEM: HP Diagnostics Input Validation Hole Permits Cross-Site Scripting Attacks in ActiveSync Lets Remote Users Execute Arbitrary Code. PLATFORM: HP Diagnostics software: version(s) 7.5, 8.0 prior to 8.05.54.225 ABSTRACT: A potential security vulnerability has been identified in HP Diagnostics. The vulnerability could be exploited remotely resulting in cross site scripting (XSS). reference LINKS: HP Document ID: c02770512 SecurityTracker Alert ID: 1025255 CVE-2011-0892 Security Focus Document ID: c02770512 IMPACT ASSESSMENT: High Discussion: A vulnerability was reported in HP Diagnostics. A remote user can conduct

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


41

U-270:Trend Micro Control Manager Input Validation Flaw in Ad Hoc Query  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

0:Trend Micro Control Manager Input Validation Flaw in Ad Hoc 0:Trend Micro Control Manager Input Validation Flaw in Ad Hoc Query Module Lets Remote Users Inject SQL Commands U-270:Trend Micro Control Manager Input Validation Flaw in Ad Hoc Query Module Lets Remote Users Inject SQL Commands September 28, 2012 - 6:00am Addthis PROBLEM: Trend Micro Control Manager Input Validation Flaw in Ad Hoc Query Module Lets Remote Users Inject SQL Commands PLATFORM: Control Manager - 3.0, 3.5, 5.0, 5.5, 6.0 ABSTRACT: Trend Micro has been notified of a potential product vulnerability in Control Manager. reference LINKS: Trend Micro Technical Support ID 1061043 SecurityTracker Alert ID: 1027584 Secunia Advisory SA50760 CVE-2012-2998 IMPACT ASSESSMENT: Medium Discussion: A vulnerability has been reported in Trend Micro Control Manager, which can

42

U-015: CiscoWorks Common Services Home Page Input Validation Flaw Lets  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

5: CiscoWorks Common Services Home Page Input Validation Flaw 5: CiscoWorks Common Services Home Page Input Validation Flaw Lets Remote Users Execute Arbitrary Commands U-015: CiscoWorks Common Services Home Page Input Validation Flaw Lets Remote Users Execute Arbitrary Commands October 20, 2011 - 7:30am Addthis PROBLEM: CiscoWorks Common Services Home Page Input Validation Flaw Lets Remote Users Execute Arbitrary Commands. PLATFORM: CiscoWorks Common Services-based products prior to version 4.1 running on Microsoft Windows ABSTRACT: 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. reference LINKS: Cisco Security Advisory ID: cisco-sa-20111019-cs Cisco Security Advisories and Responses

43

U-219: Symantec Web Gateway Input Validation Flaws Lets Remote Users Inject  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

19: Symantec Web Gateway Input Validation Flaws Lets Remote 19: Symantec Web Gateway Input Validation Flaws Lets Remote Users Inject SQL Commands, Execute Arbitrary Commands, and Change User Passwords U-219: Symantec Web Gateway Input Validation Flaws Lets Remote Users Inject SQL Commands, Execute Arbitrary Commands, and Change User Passwords July 24, 2012 - 7:00am Addthis PROBLEM: Symantec Web Gateway Input Validation Flaws Lets Remote Users Inject SQL Commands, Execute Arbitrary Commands, and Change User Passwords PLATFORM: Symantec Web Gateway 5.0.x.x ABSTRACT: Several vulnerabilities were reported in Symantec Web Gateway. REFERENCE LINKS: Security Advisories Relating to Symantec Products SecurityTracker Alert ID: 1027289 Bugtraq ID: 54424 Bugtraq ID: 54425 Bugtraq ID: 54426 Bugtraq ID: 54427 Bugtraq ID: 54429 Bugtraq ID: 54430

44

T-701: Citrix Access Gateway Enterprise Edition Input Validation Flaw in  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

1: Citrix Access Gateway Enterprise Edition Input Validation 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 Validation Flaw in Logon Portal Permits Cross-Site Scripting Attacks August 25, 2011 - 3:33pm Addthis PROBLEM: A vulnerability was reported in Citrix Access Gateway Enterprise Edition. A remote user can conduct cross-site scripting attacks. PLATFORM: Citrix Access Gateway Enterprise Edition 9.2-49.8 and prior. Citrix Access Gateway Enterprise Edition version 9.3 is not affected by this vulnerability. ABSTRACT: Citrix Access Gateway Enterprise Edition Input Validation Flaw in Logon Portal Permits Cross-Site Scripting Attacks. reference LINKS: SecurityTracker Alert ID: 1025973 Citrix Document ID: CTX129971

45

U-195: PHPlist Input Validation Flaws Permit Cross-Site Scripting and SQL  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

5: PHPlist Input Validation Flaws Permit Cross-Site Scripting 5: PHPlist Input Validation Flaws Permit Cross-Site Scripting and SQL Injection Attacks U-195: PHPlist Input Validation Flaws Permit Cross-Site Scripting and SQL Injection Attacks June 20, 2012 - 7:00am Addthis PROBLEM: Two vulnerabilities were reported in PHPlist. A remote user can conduct cross-site scripting attacks. A remote authenticated user can inject SQL commands. PLATFORM: Version(s): prior to 2.10.18 ABSTRACT: 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. REFERENCE LINKS: Vendor Advisory Security Tracker ID 1027181 CVE-2012-2740, CVE-2012-2741

46

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

6: Microsoft MHTML Input Validation Hole May Permit Cross-Site 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 vulnerability was reported in Microsoft MHTML. A remote user can conduct cross-site scripting attacks. reference LINKS: Microsoft Security Advisory 2501696 Microsoft Support Security Tracker Alert CVE-2011-0096 IMPACT ASSESSMENT: Medium Discussion: The vulnerability exists due to the way MHTML interprets MIME-formatted requests for content blocks within a document. It is possible for this

47

U-238: HP Service Manager Input Validation Flaw Permits Cross-Site  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

8: HP Service Manager Input Validation Flaw Permits Cross-Site 8: HP Service Manager Input Validation Flaw Permits Cross-Site Scripting Attacks U-238: HP Service Manager Input Validation Flaw Permits Cross-Site Scripting Attacks August 17, 2012 - 7:00am Addthis PROBLEM: HP Service Manager Input Validation Flaw Permits Cross-Site Scripting Attacks PLATFORM: Version(s): 7.11, 9.21, 9.30 ABSTRACT: 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. REFERENCE LINKS: www2.hp.com http://www.securitytracker.com/id/1027399 CVE-2012-3251 IMPACT ASSESSMENT: Moderate Discussion: A vulnerability was reported in HP Service Manager. A remote user can conduct cross-site scripting attacks. The software does not properly filter

48

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

0: Apache VCL Input Validation Flaw Lets Remote Authenticated 0: 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 Privileges May 7, 2013 - 12:01am Addthis PROBLEM: Apache VCL Input Validation Flaw Lets Remote Authenticated Users Gain Elevated Privileges PLATFORM: Apache VCL Versions: 2.1, 2.2, 2.2.1, 2.3, 2.3.1 ABSTRACT: A vulnerability was reported in Apache VCL. REFERENCE LINKS: Apache Securelist SecurityTracker Alert ID: 1028515 CVE-2013-0267 IMPACT ASSESSMENT: Medium DISCUSSION: A remote authenticated administrative user with minimal administrative privileges (i.e., nodeAdmin, manageGroup, resourceGrant, or userGrant) can send specially crafted data via the web interface or XMLRPC API to gain additional administrative privileges.

49

U-219: Symantec Web Gateway Input Validation Flaws Lets Remote Users Inject  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

19: Symantec Web Gateway Input Validation Flaws Lets Remote 19: Symantec Web Gateway Input Validation Flaws Lets Remote Users Inject SQL Commands, Execute Arbitrary Commands, and Change User Passwords U-219: Symantec Web Gateway Input Validation Flaws Lets Remote Users Inject SQL Commands, Execute Arbitrary Commands, and Change User Passwords July 24, 2012 - 7:00am Addthis PROBLEM: Symantec Web Gateway Input Validation Flaws Lets Remote Users Inject SQL Commands, Execute Arbitrary Commands, and Change User Passwords PLATFORM: Symantec Web Gateway 5.0.x.x ABSTRACT: Several vulnerabilities were reported in Symantec Web Gateway. REFERENCE LINKS: Security Advisories Relating to Symantec Products SecurityTracker Alert ID: 1027289 Bugtraq ID: 54424 Bugtraq ID: 54425 Bugtraq ID: 54426 Bugtraq ID: 54427 Bugtraq ID: 54429 Bugtraq ID: 54430

50

U-229: HP Network Node Manager i Input Validation Flaw Permits Cross-Site  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

9: HP Network Node Manager i Input Validation Flaw Permits 9: HP Network Node Manager i Input Validation Flaw Permits Cross-Site Scripting Attacks U-229: HP Network Node Manager i Input Validation Flaw Permits Cross-Site Scripting Attacks August 7, 2012 - 7:00am Addthis PROBLEM: HP Network Node Manager i Input Validation Flaw Permits Cross-Site Scripting Attacks PLATFORM: HP Network Node Manager I (NNMi) v8.x, v9.0x, v9.1x, v9.20 for HP-UX, Linux, Solaris, and Windows ABSTRACT: 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). Reference LINKS: HP Document ID: c03405705 SecurityTracker Alert ID: 1027345 Bugtraq ID: 54815 CVE-2012-2022 IMPACT ASSESSMENT:

51

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

0: HP Diagnostics Input Validation Hole Permits Cross-Site 0: HP Diagnostics Input Validation Hole Permits Cross-Site Scripting Attacks T-590: HP Diagnostics Input Validation Hole Permits Cross-Site Scripting Attacks March 29, 2011 - 3:05pm Addthis PROBLEM: HP Diagnostics Input Validation Hole Permits Cross-Site Scripting Attacks in ActiveSync Lets Remote Users Execute Arbitrary Code. PLATFORM: HP Diagnostics software: version(s) 7.5, 8.0 prior to 8.05.54.225 ABSTRACT: A potential security vulnerability has been identified in HP Diagnostics. The vulnerability could be exploited remotely resulting in cross site scripting (XSS). reference LINKS: HP Document ID: c02770512 SecurityTracker Alert ID: 1025255 CVE-2011-0892 Security Focus Document ID: c02770512 IMPACT ASSESSMENT: High Discussion: A vulnerability was reported in HP Diagnostics. A remote user can conduct

52

U-238: HP Service Manager Input Validation Flaw Permits Cross-Site  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

38: HP Service Manager Input Validation Flaw Permits Cross-Site 38: HP Service Manager Input Validation Flaw Permits Cross-Site Scripting Attacks U-238: HP Service Manager Input Validation Flaw Permits Cross-Site Scripting Attacks August 17, 2012 - 7:00am Addthis PROBLEM: HP Service Manager Input Validation Flaw Permits Cross-Site Scripting Attacks PLATFORM: Version(s): 7.11, 9.21, 9.30 ABSTRACT: 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. REFERENCE LINKS: www2.hp.com http://www.securitytracker.com/id/1027399 CVE-2012-3251 IMPACT ASSESSMENT: Moderate Discussion: A vulnerability was reported in HP Service Manager. A remote user can conduct cross-site scripting attacks. The software does not properly filter

53

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

6: Microsoft MHTML Input Validation Hole May Permit Cross-Site 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 vulnerability was reported in Microsoft MHTML. A remote user can conduct cross-site scripting attacks. reference LINKS: Microsoft Security Advisory 2501696 Microsoft Support Security Tracker Alert CVE-2011-0096 IMPACT ASSESSMENT: Medium Discussion: The vulnerability exists due to the way MHTML interprets MIME-formatted requests for content blocks within a document. It is possible for this

54

V-034: RSA Adaptive Authentication (On-Premise) Input Validation Flaws  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

4: RSA Adaptive Authentication (On-Premise) Input Validation 4: RSA Adaptive Authentication (On-Premise) Input Validation Flaws Permit Cross-Site Scripting Attacks V-034: RSA Adaptive Authentication (On-Premise) Input Validation Flaws Permit Cross-Site Scripting Attacks November 27, 2012 - 2:00am Addthis PROBLEM: RSA Adaptive Authentication (On-Premise) Input Validation Flaws Permit Cross-Site Scripting Attacks PLATFORM: RSA Adaptive Authentication (On-Premise) 6.x ABSTRACT: A vulnerability was reported in RSA Adaptive Authentication (On-Premise). REFERENCE LINKS: SecurityTracker Alert ID: 1027811 SecurityFocus Security Alert RSA Customer Support CVE-2012-4611 IMPACT ASSESSMENT: Medium DISCUSSION: A vulnerability was reported in RSA Adaptive Authentication (On-Premise). A remote user can conduct cross-site scripting attacks. The software does not

55

V-112: Microsoft SharePoint Input Validation Flaws Permit Cross-Site  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2: Microsoft SharePoint Input Validation Flaws Permit 2: Microsoft SharePoint 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 of Service Attacks March 15, 2013 - 6:00am Addthis PROBLEM: Several vulnerabilities were reported in Microsoft SharePoint PLATFORM: Microsoft SharePoint 2010 SP1 ABSTRACT: This security update resolves four reported vulnerabilities in Microsoft SharePoint and Microsoft SharePoint Foundation. REFERENCE LINKS: Security Tracker Alert ID 1028278 MS Security Bulletin MS13-024 CVE-2013-0080 CVE-2013-0083 CVE-2013-0084 CVE-2013-0085 IMPACT ASSESSMENT: High DISCUSSION: The security update addresses the vulnerabilities correcting the way that Microsoft SharePoint Server validates URLs and user input.

56

T-602: BlackBerry Enterprise Server Input Validation Flaw in BlackBerry Web  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

02: BlackBerry Enterprise Server Input Validation Flaw in 02: BlackBerry Enterprise Server Input Validation Flaw in BlackBerry Web Desktop Manager Permits Cross-Site Scripting Attacks T-602: BlackBerry Enterprise Server Input Validation Flaw in BlackBerry Web Desktop Manager Permits Cross-Site Scripting Attacks April 14, 2011 - 5:07am Addthis PROBLEM: BlackBerry Enterprise Server Input Validation Flaw in BlackBerry Web Desktop Manager Permits Cross-Site Scripting Attacks PLATFORM: BlackBerry Enterprise Server Express versions 5.0.1 and 5.0.2 for Microsoft Exchange, 5.0.2 for IBM Lotus Domino, 5.0.0 through 5.0.3 for Microsoft Exchange and IBM Lotus Domino, and version 5.0.1 for Novell GroupWise. OS Platform(s): Windows (2000), Windows (2003), Windows (2008) ABSTRACT: The BlackBerry Web Desktop Manager not properly filter HTML code from

57

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

7:WebSVN Input Validation Flaw in getLog() Permits Cross-Site 7:WebSVN Input Validation Flaw in getLog() Permits Cross-Site Scripting Attacks U-067:WebSVN Input Validation Flaw in getLog() Permits Cross-Site Scripting Attacks December 22, 2011 - 8:15am Addthis PROBLEM: WebSVN Input Validation Flaw in getLog() Permits Cross-Site Scripting Attacks PLATFORM: WebSVN 2.3.0 and prior versions ABSTRACT: 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. reference LINKS: SecurityTracker Alert ID: 1026438 WebSVN version update WebSVN News IMPACT ASSESSMENT: Medium Discussion: The getLog() function does not properly filter HTML code from user-supplied

58

U-254: Webmin Flaws Let Remote Authenticated Users Execute Arbitrary...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

System Multiple Vulnerabilities U-255: Apache Wicket Input Validation Flaw Permits Cross-Site Scripting Attacks V-104: Oracle Java Flaw Lets Remote Users Execute Arbitrary Code...

59

Application of the Neo-Deterministic Seismic Microzonation Procedure in Bulgaria and Validation of the Seismic Input Against Eurocode 8  

SciTech Connect

The earthquake record and the Code for design and construction in seismic regions in Bulgaria have shown that the territory of the Republic of Bulgaria is exposed to a high seismic risk due to local shallow and regional strong intermediate-depth seismic sources. The available strong motion database is quite limited, and therefore not representative at all of the real hazard. The application of the neo-deterministic seismic hazard assessment procedure for two main Bulgarian cities has been capable to supply a significant database of synthetic strong motions for the target sites, applicable for earthquake engineering purposes. The main advantage of the applied deterministic procedure is the possibility to take simultaneously and correctly into consideration the contribution to the earthquake ground motion at the target sites of the seismic source and of the seismic wave propagation in the crossed media. We discuss in this study the result of some recent applications of the neo-deterministic seismic microzonation procedure to the cities of Sofia and Russe. The validation of the theoretically modeled seismic input against Eurocode 8 and the few available records at these sites is discussed.

Ivanka, Paskaleva [CLSMEE--BAS, 3 Acad G. Bonchev str, 1113 Sofia (Bulgaria); Mihaela, Kouteva [CLSMEE-BAS, 3 Acad G. Bonchev str, 1113 Sofia (Bulgaria); ESP-SAND, ICTP, Trieste (Italy); Franco, Vaccari [DST-University of Trieste, Via E. Weiss 4, 34127 Trieste (Italy); Panza, Giuliano F. [DST-University of Trieste, Via E. Weiss 4, 34127 Trieste (Italy); ESP-SAND, ICTP, Trieste (Italy)

2008-07-08T23:59:59.000Z

60

TART input manual  

Science Conference Proceedings (OSTI)

The TART code is a Monte Carlo neutron/photon transport code that is only on the CRAY computer. All the input cards for the TART code are listed, and definitions for all input parameters are given. The execution and limitations of the code are described, and input for two sample problems are given. (WHK)

Kimlinger, J.R.; Plechaty, E.F.

1982-04-01T23:59:59.000Z

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


61

Efficient concurrency-bug detection across inputs  

Science Conference Proceedings (OSTI)

In the multi-core era, it is critical to efficiently test multi-threaded software and expose concurrency bugs before software release. Previous work has made significant progress in detecting and validating concurrency bugs under a given input. Unfortunately, ... Keywords: bug detection, concurrency bugs, multi-threaded software, software testing

Dongdong Deng, Wei Zhang, Shan Lu

2013-10-01T23:59:59.000Z

62

JC3 Bulletin Archive | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

11, 2012 11, 2012 U-256: Microsoft Security Bulletin Advance Notification for September 2012 Microsoft Security Bulletin Advance Notification for September 2012. Microsoft has posted 0 Critical Bulletins and 2 Important Bulletins. Bulletins with the Maximum Severity Rating and Vulnerability Impact of "Critical" may allow remote execution of code. Microsoft is hosting a webcast to address customer questions on these bulletins on September 12, 2012, at 11:00 AM Pacific Time (US & Canada). September 11, 2012 U-255: Apache Wicket Input Validation Flaw Permits Cross-Site Scripting Attacks A vulnerability was reported in Apache Wicket September 10, 2012 U-254: Webmin Flaws Let Remote Authenticated Users Execute Arbitrary Code and View Arbitrary Files Webmin Multiple Input Validation Vulnerabilities

63

Spatial Statistical Procedures to Validate Input Data in Energy Models  

DOE Green Energy (OSTI)

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 above-mentioned 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.

Lawrence Livermore National Laboratory

2006-01-27T23:59:59.000Z

64

INPUT VALIDATION TESTING: A SYSTEM LEVEL, EARLY LIFECYCLE TECHNIQUE  

E-Print Network (OSTI)

Johnston '12, chelsea Karpenko '12, Lauriane rougeau '13 and catherine White '12. Johnston was a member, a maintenance mechanic and material handler at Cornell for 30 years who served in many roles, including presi

Offutt, Jeff

65

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

or userGrant) can send specially crafted data via the web interface or XMLRPC API to gain additional administrative privileges. IMPACT: A remote authenticated user can...

66

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

in Symantec Security Information Manager PLATFORM: Symantec Security Information Manager Appliance Version 4.7.x and 4.8.0 ABSTRACT: Symantec was notified of multiple security...

67

U-238: HP Service Manager Input Validation Flaw Permits Cross...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

9.21, 9.30 ABSTRACT: 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...

68

Spatial Statistical Procedures to Validate Input Data in Energy Models  

DOE Green Energy (OSTI)

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.

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

2006-01-01T23:59:59.000Z

69

Code Completion From Abbreviated Input  

E-Print Network (OSTI)

Abbreviation Completion is a novel technique to improve the efficiency of code-writing by supporting code completion of multiple keywords based on non-predefined abbreviated input - a different approach from conventional ...

Miller, Robert C.

70

Groundwater Model Validation  

SciTech Connect

Models have an inherent uncertainty. The difficulty in fully characterizing the subsurface environment makes uncertainty an integral component of groundwater flow and transport models, which dictates the need for continuous monitoring and improvement. Building and sustaining confidence in closure decisions and monitoring networks based on models of subsurface conditions require developing confidence in the models through an iterative process. The definition of model validation is postulated as a confidence building and long-term iterative process (Hassan, 2004a). Model validation should be viewed as a process not an end result. Following Hassan (2004b), an approach is proposed for the validation process of stochastic groundwater models. The approach is briefly summarized herein and detailed analyses of acceptance criteria for stochastic realizations and of using validation data to reduce input parameter uncertainty are presented and applied to two case studies. During the validation process for stochastic models, a question arises as to the sufficiency of the number of acceptable model realizations (in terms of conformity with validation data). Using a hierarchical approach to make this determination is proposed. This approach is based on computing five measures or metrics and following a decision tree to determine if a sufficient number of realizations attain satisfactory scores regarding how they represent the field data used for calibration (old) and used for validation (new). The first two of these measures are applied to hypothetical scenarios using the first case study and assuming field data consistent with the model or significantly different from the model results. In both cases it is shown how the two measures would lead to the appropriate decision about the model performance. Standard statistical tests are used to evaluate these measures with the results indicating they are appropriate measures for evaluating model realizations. The use of validation data to constrain model input parameters is shown for the second case study using a Bayesian approach known as Markov Chain Monte Carlo. The approach shows a great potential to be helpful in the validation process and in incorporating prior knowledge with new field data to derive posterior distributions for both model input and output.

Ahmed E. Hassan

2006-01-24T23:59:59.000Z

71

Refinery and Blender Net Inputs  

Annual Energy Outlook 2012 (EIA)

Refinery and Blender Net Inputs Crude OIl ... 14.54 15.14 15.26 15.08 14.51 15.30 15.70 14.93 14.47 15.30 15.54 14.97 15.01...

72

3430 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 61, NO. 8, OCTOBER 2012 Experimental Validation of High-Voltage-Ratio  

E-Print Network (OSTI)

Validation of High-Voltage-Ratio Low-Input-Current-Ripple Converters for Hybrid Fuel Cell Supercapacitor

Simões, Marcelo Godoy

73

Verification and validation benchmarks.  

SciTech Connect

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 achievement in V&V activities, how closely related the V&V benchmarks are to the actual application of interest, and the quantification of uncertainties related to the application of interest.

Oberkampf, William Louis; Trucano, Timothy Guy

2007-02-01T23:59:59.000Z

74

Table 8. Capacity and Fresh Feed Input to Selected Downstream ...  

U.S. Energy Information Administration (EIA)

Capacity Inputs CapacityInputs Capacity Inputs Table 8. ... (EIA) Form EIA-820, "Annual Refinery Report." Inputs are from the form EIA-810, "Monthly Refinery Report."

75

DOE-2 Input File From WINDOW  

NLE Websites -- All DOE Office Websites (Extended Search)

an EnergyPlus input file from WINDOW 5 Last update: 12232008 01:54 PM Creating an EnergyPlus Input File for One Window In the WINDOW Window Library, which defines a complete...

76

DOE-2 Input File From WINDOW  

NLE Websites -- All DOE Office Websites (Extended Search)

a DOE2 input file from WINDOW 5 Last update: 02012008 01:19 PM Creating a DOE-2 Input File for One Window In the WINDOW Window Library, which defines a complete window including...

77

Model Validation  

Science Conference Proceedings (OSTI)

...thus establishing appropriate and important benchmarks. Benchmarking can go beyond validation and also measure relative computational speed, accuracy, and breadth for available modeling approaches and implementations, providing valuable information for users to discern the best models and for modelers...

78

BISON Validation | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Validation 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 recently completed VU study focused on a methodology by which experimental campaigns may be devised to improve code calibration. Specifically, a principal component analysis is performed on the input parameters of the experiments, and the experiments that offer the least residual error when reconstructed from the principal components are

79

Yankee Rowe simulator core model validation  

Science Conference Proceedings (OSTI)

This paper presents the validation of the Yankee Rowe simulator core model. Link-Miles Simulation Corporation is developing the Yankee Rowe simulator and Yankee Atomic Electric Company is involved in input and benchmark data generation, as well as simulator validation. Core model validation by Yankee comprises three tasks: (1) careful generation of fuel reactivity characteristics (B constants); (2) nonintegrated core model testing; and (3) fully integrated core model testing. Simulator core model validation and verification is a multistage process involving input and benchmark data generation as well as interactive debugging. Core characteristics were brought within acceptable criteria by this process. This process was achieved through constant communication between Link-Miles and Yankee engineers. Based on this validation, the Yankee Rowe simulator core model is found to be acceptable for training purposes.

Napolitano, M.E.

1990-01-01T23:59:59.000Z

80

Energy Input Output Calculator | Open Energy Information  

Open Energy Info (EERE)

Input Output Calculator Input Output Calculator Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Energy Input-Output Calculator Agency/Company /Organization: Department of Energy Sector: Energy Focus Area: Energy Efficiency Resource Type: Online calculator User Interface: Website Website: www2.eere.energy.gov/analysis/iocalc/Default.aspx Web Application Link: www2.eere.energy.gov/analysis/iocalc/Default.aspx OpenEI Keyword(s): Energy Efficiency and Renewable Energy (EERE) Tools Language: English References: EERE Energy Input-Output Calculator[1] The Energy Input-Output Calculator (IO Calculator) allows users to estimate the economic development impacts from investments in alternate electricity generating technologies. About the Calculator The Energy Input-Output Calculator (IO Calculator) allows users to estimate

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


81

Input apparatus for dynamic signature verification systems  

DOE Patents (OSTI)

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.

EerNisse, Errol P. (Albuquerque, NM); Land, Cecil E. (Albuquerque, NM); Snelling, Jay B. (Albuquerque, NM)

1978-01-01T23:59:59.000Z

82

EOS Land Validation Project  

NLE Websites -- All DOE Office Websites (Extended Search)

EOS Land Validation The EOS Land Validation Project Overview EOS Land Validation Logo The objective of the EOS Land Validation Project is to achieve consistency, completeness,...

83

Deriving input syntactic structure from execution  

Science Conference Proceedings (OSTI)

Program input syntactic structure is essential for a wide range of applications such as test case generation, software debugging and network security. However, such important information is often not available (e.g., most malware programs make use of ... Keywords: bottom-up grammar, control dependence, input lineage, reverse engineering, syntax tree, top-down grammar

Zhiqiang Lin; Xiangyu Zhang

2008-11-01T23:59:59.000Z

84

U.S. Weekly Inputs & Utilization  

U.S. Energy Information Administration (EIA)

Crude Oil Inputs: 16,237: 16,031: 15,965: 15,893: 15,611: 15,845: 1982-2013: Gross Inputs: 16,539: 16,448: 16,257: 16,200: 15,927: 16,209: 1990-2013: Operable ...

85

Designating required vs. optional input fields  

Science Conference Proceedings (OSTI)

This paper describes a study comparing different techniques for visually distingishing required from optional input fields in a form-filling application. Seven techniques were studied: no indication, bold field labels, chevrons in front of the labels, ... Keywords: data input, optional fields, required fields, visual design

Thomas S. Tullis; Ana Pons

1997-03-01T23:59:59.000Z

86

SWAT 2012 Input/Output Documentation  

E-Print Network (OSTI)

The Soil and Water Assessment Tool (SWAT) is a comprehensive model that requires a diversity of information in order to run. Novice users may feel overwhelmed by the variety and number of inputs when they first begin to use the model. This document provides a full description of model inputs. The inputs are organized by topic and emphasis is given to differentiating required inputs from optional inputs. The first chapter focuses on assisting the user in identifying inputs that must be defined for their particular dataset. The remaining chapters list variables by file and discuss methods used to measure or calculate values for the input parameters. SWAT is a public domain model jointly developed by USDA Agricultural Research Service (USDA-ARS) and Texas A&M AgriLife Research, part of The Texas A&M University System. SWAT is a small watershed to river basin-scale model to simulate the quality and quantity of surface and ground water and predict the environmental impact of land use, land management practices, and climate change. SWAT is widely used in assessing soil erosion prevention and control, non-point source pollution control and regional management in watersheds. Download the SWAT model, or read more information at the SWAT website.

Arnold, J.G.; Kiniry, J.R.; Srinivasan, R.; Williams, J.R.; Haney, E.B.; Neitsch, S.L.

2013-03-04T23:59:59.000Z

87

Identifying Steam Opportunity "Impact" Inputs for the Steam System Assessment Tool (SSAT)  

E-Print Network (OSTI)

The U.S. DOE BestPractices Steam "Steam System Assessment Tool" (SSAT) is a powerful tool for quantifying potential steam improvement opportunities in steam systems. However, all assessment tools are only as good as the validity of the modeling inputs.

Harrell, G.; Jendrucko, R.; Wright, A.

2004-01-01T23:59:59.000Z

88

National Climate Assessment: Available Technical Inputs  

NLE Websites -- All DOE Office Websites (Extended Search)

Available Technical Inputs Print E-mail Available Technical Inputs Print E-mail Technical inputs for the 2013 National Climate Assessment were due March 1, 2012. Please note that these reports were submitted independently to the National Climate Assessment for consideration and have not been reviewed by the National Climate Assessment Development and Advisory Committee. Links to agency-sponsored reports will be posted here as they are made available. Sectors National Climate Assessment Health Sector Literature Review and Bibliography. Technical Input for the Interagency Climate Change and Human Health Group, September 2012. Overview Bibliography Bibliography User's Guide Search Strategy and Results Walthall et al. 2012. Climate Change and Agriculture in the United States: Effects and Adaptation. USDA Technical Bulletin 1935. Washington, DC. 186 pages. | Report FAQs

89

Wind Energy Input to the Ekman Layer  

Science Conference Proceedings (OSTI)

Wind stress energy input through the surface ageostrophic currents is studied. The surface ageostrophic velocity is calculated using the classical formula of the Ekman spiral, with the Ekman depth determined from an empirical formula. The total ...

Wei Wang; Rui Xin Huang

2004-05-01T23:59:59.000Z

90

Neural Network Input Representations that Produce Accurate Consensus Sequences from DNA Fragment Assemblies  

E-Print Network (OSTI)

Motivation: Given inputs extracted from an aligned column of DNA bases and the underlying Perkin Elmer Applied Biosystems (ABI) fluorescent traces, our goal is to train a neural network to correctly determine the consensus base for the column. Choosing an appropriate network input representation is critical to success in this task. We empirically compare five representations; one uses only base calls and the others include trace information. Results: We attained the most accurate results from networks that incorporate trace information into their input representations. Based on estimates derived from using 10-fold cross-validation, the best network topology produces consensus accuracies ranging from 99.26% to over 99.98% for coverages from two to six aligned sequences. With a coverage of six, it makes only three errors in 20,000 consensus calls. In contrast, the network that only uses base calls in its input representation has over double that error rate -- eight errors in 20,000 cons...

C.F. Allex; J.W. Shavlik; F.R. Blattner

1999-01-01T23:59:59.000Z

91

Total Blender Net Input of Petroleum Products  

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

Input Input Product: Total Input Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquid Petroleum Gases Normal Butane Isobutane Other Liquids Oxygenates/Renewables Methyl Tertiary Butyl Ether (MTBE) Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Unfinished Oils (net) Unfinished Oils, Naphthas and Lighter Unfinished Oils, Kerosene and Light Gas Oils Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Components (MGBC) (net) MGBC - Reformulated MGBC - Reformulated - RBOB MGBC - Reformulated, RBOB for Blending w/ Alcohol MGBC - Reformulated, RBOB for Blending w/ Ether MGBC - Reformulated, GTAB MGBC - Conventional MGBC - Conventional, CBOB MGBC - Conventional, GTAB MGBC - Other Conventional Period-Unit: Monthly-Thousand Barrels Monthly-Thousand Barrels per Day Annual-Thousand Barrels Annual-Thousand Barrels per Day

92

Opportunities for Public Input Into DOE Projects  

NLE Websites -- All DOE Office Websites (Extended Search)

Opportunities for Public Input Into DOE Projects Opportunities for Public Input Into DOE Projects There are currently several DOE-proposed activities that citizens can comment on in the near future. Here is a summary of each, as well as a description of how to provide your input into the project: Hanford Draft Closure and Waste Management Environmental Impact Statement Idahoans might be interested in this document because one of the proposed actions involves sending a small amount of radioactive waste (approximately 5 cubic meters of special reactor components) to the Idaho Nuclear Technology and Engineering Center on DOE's Idaho Site for treatment. Here is a link to more information about the document: http://www.hanford.gov . A public hearing on the draft EIS will be held in Boise on Tuesday, Feb. 2 at the Owyhee Plaza Hotel. It begins at 6 p.m.

93

HMAC Validation List  

Science Conference Proceedings (OSTI)

Keyed-Hash Message Authentication Code (HMAC) Validation List. Last Update: 11/15/2013. HMAC Validation List. Overview. ...

94

PUBLIC INFORMATION AND INPUT ON WIPP  

E-Print Network (OSTI)

PUBLIC INFORMATION AND INPUT ON WIPP Get The Information You Need 1. Check the EPA Website, Fact Sheets and Issue Papers. EPA will make sure that key information is available on its WIPP Website. EPA the EPA WIPP Information Line at 1-800-331-WIPP (1-800-331-9477) to obtain information on upcoming events

95

Gravity Transform for Input Conditioning in  

E-Print Network (OSTI)

Gravity Transform for Input Conditioning in Brain Machine Interfaces António R. C. Paiva, José C. Motivation 2. Methods i. Gravity Transform ii. Modeling and output sensitivity analysis 3. Data Analysis #12;3 Outline 1. Motivation 2. Methods i. Gravity Transform ii. Modeling and output sensitivity analysis 3. Data

Paiva, António R. C.

96

Wind Energy Input to the Surface Waves  

Science Conference Proceedings (OSTI)

Wind energy input into the ocean is primarily produced through surface waves. The total rate of this energy source, integrated over the World Ocean, is estimated at 60 TW, based on empirical formulas and results from a numerical model of surface ...

Wei Wang; Rui Xin Huang

2004-05-01T23:59:59.000Z

97

Hydrogen Generation Rate Model Calculation Input Data  

DOE Green Energy (OSTI)

This report documents the procedures and techniques utilized in the collection and analysis of analyte input data values in support of the flammable gas hazard safety analyses. This document represents the analyses of data current at the time of its writing and does not account for data available since then.

KUFAHL, M.A.

2000-04-27T23:59:59.000Z

98

Repeat on input for data flow computers  

DOE Patents (OSTI)

A processing node for a data flow parallel processing computer is activated by an input token from the system. The token or the stored information in the node includes information to cause the node to repeat a specified sequence of operations upon initiation by the token, thereby increasing the efficiency system for some computing operations.

Grafe, V.G.; Hoch, J.E.

1989-12-27T23:59:59.000Z

99

Multiple Input Microcantilever Sensor with Capacitive Readout  

DOE Green Energy (OSTI)

A surface-micromachined MEMS process has been used to demonstrate multiple-input chemical sensing using selectively coated cantilever arrays. Combined hydrogen and mercury-vapor detection was achieved with a palm-sized, self-powered module with spread-spectrum telemetry reporting.

Britton, C.L., Jr.; Brown, G.M.; Bryan, W.L.; Clonts, L.G.; DePriest, J.C.; Emergy, M.S.; Ericson, M.N.; Hu, Z.; Jones, R.L.; Moore, M.R.; Oden, P.I.; Rochelle, J.M.; Smith, S.F.; Threatt, T.D.; Thundat, T.; Turner, G.W.; Warmack, R.J.; Wintenberg, A.L.

1999-03-11T23:59:59.000Z

100

On the Input Problem for Massive Modularity  

Science Conference Proceedings (OSTI)

Jerry Fodor argues that the massive modularity thesis -- the claim that (human) cognition is wholly served by domain specific, autonomous computational devices, i.e., modules -- is a priori ... Keywords: Fodor, Sperber, input problem, language faculty, massive modularity, theory of mind

J. Collins

2005-02-01T23:59:59.000Z

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


101

Evaluating capacitive touch input on clothes  

Science Conference Proceedings (OSTI)

Wearable computing and smart clothing have attracted a lot of attention in the last years. For a variety of applications, it can be seen as potential future direction of mobile user interfaces. In this paper, we concentrate on usability and applicability ... Keywords: capacitive touch, design guidelines, input on textiles, wearable controls

Paul Holleis; Albrecht Schmidt; Susanna Paasovaara; Arto Puikkonen; Jonna Hkkil

2008-09-01T23:59:59.000Z

102

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Seeks Input On Addressing Contractor Pension and Medical Benefits Liabilities DOE Seeks Input On Addressing Contractor Pension and Medical Benefits Liabilities March 27, 2007 -...

103

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

104

Documentation of Calculation Methodology, Input Data, and Infrastructu...  

NLE Websites -- All DOE Office Websites (Extended Search)

Documentation of Calculation Methodology, Input Data, and Infrastructure for the Home Energy Saver Web Site Title Documentation of Calculation Methodology, Input Data, and...

105

Multimodal interfaces with voice and gesture input  

SciTech Connect

The modalities of speech and gesture have different strengths and weaknesses, but combined they create synergy where each modality corrects the weaknesses of the other. We believe that a multimodal system such a one interwining speech and gesture must start from a different foundation than ones which are based solely on pen input. In order to provide a basis for the design of a speech and gesture system, we have examined the research in other disciplines such as anthropology and linguistics. The result of this investigation was a taxonomy that gave us material for the incorporation of gestures whose meanings are largely transparent to the users. This study describes the taxonomy and gives examples of applications to pen input systems.

Milota, A.D.; Blattner, M.M.

1995-07-20T23:59:59.000Z

106

East Coast (PADD 1) Gross Inputs to Atmospheric Crude Oil ...  

U.S. Energy Information Administration (EIA)

East Coast (PADD 1) Gross Inputs to Atmospheric Crude Oil Distillation Units (Thousand Barrels per Day)

107

Rocky Mountains (PADD 4) Gross Inputs to Refineries (Thousand ...  

U.S. Energy Information Administration (EIA)

Gross Input to Atmospheric Crude Oil Distillation Units ; PAD District 4 Refinery Utilization and Capacity ...

108

Refining District New Mexico Gross Inputs to Atmospheric Crude Oil ...  

U.S. Energy Information Administration (EIA)

Refining District New Mexico Gross Inputs to Atmospheric Crude Oil Distillation Units (Thousand Barrels per Day)

109

Land Validation web site  

NLE Websites -- All DOE Office Websites (Extended Search)

web site A web site is now available for the Land Validation project. It was created with the purpose of facilitating communication among MODIS Land Validation Principal...

110

U-229: HP Network Node Manager i Input Validation Flaw Permits...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Network Node Manager I (NNMi) v8.x, v9.0x, v9.1x, v9.20 for HP-UX, Linux, Solaris, and Windows ABSTRACT: Potential security vulnerabilities have been identified with HP Network...

111

Ground motion input in seismic evaluation studies  

Science Conference Proceedings (OSTI)

This report documents research pertaining to conservatism and variability in seismic risk estimates. Specifically, it examines whether or not artificial motions produce unrealistic evaluation demands, i.e., demands significantly inconsistent with those expected from real earthquake motions. To study these issues, two types of artificial motions are considered: (a) motions with smooth response spectra, and (b) motions with realistic variations in spectral amplitude across vibration frequency. For both types of artificial motion, time histories are generated to match target spectral shapes. For comparison, empirical motions representative of those that might result from strong earthquakes in the Eastern U.S. are also considered. The study findings suggest that artificial motions resulting from typical simulation approaches (aimed at matching a given target spectrum) are generally adequate and appropriate in representing the peak-response demands that may be induced in linear structures and equipment responding to real earthquake motions. Also, given similar input Fourier energies at high-frequencies, levels of input Fourier energy at low frequencies observed for artificial motions are substantially similar to those levels noted in real earthquake motions. In addition, the study reveals specific problems resulting from the application of Western U.S. type motions for seismic evaluation of Eastern U.S. nuclear power plants.

Sewell, R.T.; Wu, S.C.

1996-07-01T23:59:59.000Z

112

NASA Land Validation Campaign Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Products > Validation NASA Land Validation Campaign Data Land Validation Campaigns The goal of the EOS Validation Program is the comprehensive assessment of all EOS science data...

113

Development of MELCOR Input Techniques for High Temperature Gas-Cooled Reactor Analysis  

E-Print Network (OSTI)

High Temperature Gas-cooled Reactors (HTGRs) can provide clean electricity,as well as process heat that can be used to produce hydrogen for transportation and other sectors. A prototypic HTGR, the Next Generation Nuclear Plant (NGNP),will be built at Idaho National Laboratory.The need for HTGR analysis tools and methods has led to the addition of gas-cooled reactor (GCR) capabilities to the light water reactor code MELCOR. MELCOR will be used by the Nuclear Regulatory Commission licensing of the NGNP and other HTGRs. In the present study, new input techniques have been developed for MELCOR HTGR analysis. These new techniques include methods for modeling radiation heat transfer between solid surfaces in an HTGR, calculating fuel and cladding geometric parameters for pebble bed and prismatic block-type HTGRs, and selecting appropriate input parameters for the reflector component in MELCOR. The above methods have been applied to input decks for a water-cooled reactor cavity cooling system (RCCS); the 400 MW Pebble Bed Modular Reactor (PBMR), the input for which is based on a code-to-code benchmark activity; and the High Temperature Test Facility (HTTF), which is currently in the design phase at Oregon State University. RCCS results show that MELCOR accurately predicts radiation heat transfer rates from the vessel but may overpredict convective heat transfer rates and RCCS coolant flow rates. PBMR results show that thermal striping from hot jets in the lower plenum during steady-state operations, and in the upper plenum during a pressurized loss of forced cooling accident, may be a major design concern. Hot jets could potentially melt control rod drive mechanisms or cause thermal stresses in plenum structures. For the HTTF, results will provide data to validate MELCOR for HTGR analyses. Validation will be accomplished by comparing results from the MELCOR representation of the HTTF to experimental results from the facility. The validation process can be automated using a modular code written in Python, which is described here.

Corson, James

2010-05-01T23:59:59.000Z

114

On the Wind Power Input to the Ocean General Circulation  

Science Conference Proceedings (OSTI)

The wind power input to the ocean general circulation is usually calculated from the time-averaged wind products. Here, this wind power input is reexamined using available observations, focusing on the role of the synoptically varying wind. Power ...

Xiaoming Zhai; Helen L. Johnson; David P. Marshall; Carl Wunsch

2012-08-01T23:59:59.000Z

115

On the Wind Power Input to the Ocean General Circulation  

E-Print Network (OSTI)

The wind power input to the ocean general circulation is usually calculated from the time-averaged wind products. Here, this wind power input is reexamined using available observations, focusing on the role of the synoptically ...

Zhai, Xiaoming

116

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

Annual Energy Outlook 2012 (EIA)

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...

117

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

Gasoline and Diesel Fuel Update (EIA)

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...

118

Estimation of time-dependent input from neuronal membrane potential  

Science Conference Proceedings (OSTI)

The set of firing rates of the presynaptic excitatory and inhibitory neurons constitutes the input signal to the postsynaptic neuron. Estimation of the time-varying input rates from intracellularly recorded membrane potential is investigated here. For ...

Ryota Kobayashi; Shigeru Shinomoto; Petr Lansky

2011-12-01T23:59:59.000Z

119

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

Gasoline and Diesel Fuel Update (EIA)

Input Supplemental Fuels (Million Cubic Feet) New Mexico 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...

120

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

Gasoline and Diesel Fuel Update (EIA)

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...

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


121

A survey of design issues in spatial input  

Science Conference Proceedings (OSTI)

We present a survey of design issues for developing effective free-space three-dimensional (3D) user interfaces. Our survey is based upon previous work in 3D interaction, our experience in developing free-space interfaces, and our informal observations ... Keywords: 3D interaction, ergonomics of virtual manipulation, haptic input, spatial input, two-handed input, virtual reality

Ken Hinckley; Randy Pausch; John C. Goble; Neal F. Kassell

1994-11-01T23:59:59.000Z

122

U.S. Blender Net Input  

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

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Total Input 1,184,435 1,522,193 1,850,204 2,166,784 2,331,109 2,399,318 2005-2012 Natural Gas Plant Liquids and Liquefied Refinery Gases 3,445 5,686 6,538 7,810 10,663 2008-2012 Pentanes Plus 2,012 474 1,808 1,989 2,326 4,164 2005-2012 Liquid Petroleum Gases 2,971 3,878 4,549 5,484 6,499 2008-2012 Normal Butane 2,943 2,971 3,878 4,549 5,484 6,499 2005-2012 Isobutane 2005-2006 Other Liquids 1,518,748 1,844,518 2,160,246 2,323,299 2,388,655 2008-2012 Oxygenates/Renewables 234,047 274,974 286,837 295,004 2009-2012 Methyl Tertiary Butyl Ether (MTBE) 2005-2006 Renewable Fuels (incl. Fuel Ethanol) 234,047 274,974 286,837 295,004 2009-2012 Fuel Ethanol 131,810 182,772 232,677 273,107 281,507 287,433 2005-2012

123

U.S. Blender Net Input  

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

Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History Total Input 206,541 217,867 212,114 216,075 219,783 208,203 2005-2013 Natural Gas Plant Liquids and Liquefied Refinery Gases 891 352 376 196 383 1,397 2008-2013 Pentanes Plus 261 301 313 67 287 393 2005-2013 Liquid Petroleum Gases 630 51 63 129 96 1,004 2008-2013 Normal Butane 630 51 63 129 96 1,004 2005-2013 Isobutane 2005-2006 Other Liquids 205,650 217,515 211,738 215,879 219,400 206,806 2008-2013 Oxygenates/Renewables 25,156 26,576 26,253 26,905 27,788 25,795 2009-2013 Methyl Tertiary Butyl Ether (MTBE) 2005-2006 Renewable Fuels (incl. Fuel Ethanol) 25,156 26,576 26,253 26,905 27,788 25,795 2009-2013 Fuel Ethanol 24,163 25,526 24,804 25,491 25,970 24,116 2005-2013

124

Press Release: DOE Seeks Public Input for Depleted Uranium Hexafluorid...  

NLE Websites -- All DOE Office Websites (Extended Search)

Perry, (865) 576-0885 September 24, 2001 www.oakridge.doe.gov DOE SEEKS PUBLIC INPUT FOR DEPLETED URANIUM HEXAFLUORIDE ENVIRONMENTAL IMPACT STATEMENT Public Meetings Planned in...

125

EOS Land Validation Presentations  

NLE Websites -- All DOE Office Websites (Extended Search)

EOS Land Validation Presentations EOS Land Validation Presentations Meeting: Land Cover Validation Workshop Date: February 2, 2004 Place: Boston, MA Title: Validation Data Support Activities at the ORNL DAAC (Power Point) Presenter: Bob Cook Meeting: Fall 2003 American Geophysical Union (AGU) Meeting Date: December 9, 2003 Place: San Francisco, CA Title: Ground-Based Data Supporting the Validation of MODIS Land Products (Power Point) Presenter: Larry Voorhees Meeting: Terra and Aqua Products Review Date: March 2003 Place: NASA HQ Title: Supporting the Validation of MODIS Land Products (Power Point) Presenter: Larry Voorhees Meeting: Terra and Aqua Products Review Date: March 2003 Place: NASA HQ Title: MODIS Land Summary (Power Point) Presenter: Chris Justice, University of Maryland Meeting: Spring 2002 American Geophysical Union (AGU) Meeting

126

FCT Technology Validation: Contacts  

NLE Websites -- All DOE Office Websites (Extended Search)

Technology Validation: Contacts on AddThis.com... Home Transportation Projects StationaryDistributed Generation Projects Integrated Projects Quick Links Hydrogen Production...

127

SCAP Validation FAQ - NIST  

Science Conference Proceedings (OSTI)

... The SCAP capabilities offered in the SCAP 1.2 program are authenticated configuration scanner (ACS) with optional CVE and OCIL validation. ...

2013-08-12T23:59:59.000Z

128

PREDICTING THE TIME RESPONSE OF A BUILDING UNDER HEAT INPUT CONDITIONS FOR ACTIVE SOLAR HEATING SYSTEMS  

E-Print Network (OSTI)

solar space heating system with heat input and building loadBUILDING UNDER HEAT INPUT CONDITIONS FOR ACTIVE SOLAR HEATINGBUILDING UNDER HEAT INPUT CONDITIONS FOR ACTIVE SOLAR HEATING

Warren, Mashuri L.

2013-01-01T23:59:59.000Z

129

Finding input sub-spaces for polymorphic fuzzy signatures  

Science Conference Proceedings (OSTI)

A significant feature of fuzzy signatures is its applicability for complex and sparse data. To create Polymorphic Fuzzy Signatures (PFS) for sparse data, sparse input sub-spaces (ISSs) should be considered. Finding the optimal ISSs manually is not a ... Keywords: WRAO, fuzzy C-means, fuzzy signatures, input subspace clustering, polymorphic fuzzy signatures, trapezoidal approximation

A. H. Hadad; T. D. Gedeon; B. S. U. Mendis

2009-08-01T23:59:59.000Z

130

Ancient runes: using text input for interaction in mobile games  

Science Conference Proceedings (OSTI)

Mobile phones are often carried in the pocket making them available for gaming any time. Mobile games typically rely on the joystick for input, but quality of the joystick is very different in the different devices. This paper presents Ancient Runes, ... Keywords: mobile multiplayer gaming, playability, text input

Elina M. I. Koivisto; Riku Suomela; Ari Koivisto

2006-07-01T23:59:59.000Z

131

Manual deskterity: an exploration of simultaneous pen + touch direct input  

Science Conference Proceedings (OSTI)

Manual Deskterity is a prototype digital drafting table that supports both pen and touch input. We explore a division of labor between pen and touch that flows from natural human skill and differentiation of roles of the hands. We also explore the simultaneous ... Keywords: bimanual input, gestures, pen, tabletop, tablets, touch

Ken Hinckley; Koji Yatani; Michel Pahud; Nicole Coddington; Jenny Rodenhouse; Andy Wilson; Hrvoje Benko; Bill Buxton

2010-04-01T23:59:59.000Z

132

Kernel principal component analysis for stochastic input model generation  

Science Conference Proceedings (OSTI)

Stochastic analysis of random heterogeneous media provides useful information only if realistic input models of the material property variations are used. These input models are often constructed from a set of experimental samples of the underlying random ... Keywords: Data-driven models, Flow in random porous media, Kernel principal component analysis, Non-linear model reduction, Stochastic partial differential equations

Xiang Ma; Nicholas Zabaras

2011-08-01T23:59:59.000Z

133

Skeletal input for user interaction in X3D  

Science Conference Proceedings (OSTI)

Recent developments in depth sensor technology enable developers to use skeletal input in interactive 3D environments with high user fluctuation like museum exhibits. However, the question of how to use natural user input and body movement to control ... Keywords: Kinect, X3D, natural interaction

Manuel Olbrich; Tobias Franke; Jens Keil; Sven Hertling

2013-06-01T23:59:59.000Z

134

BeThere: 3D mobile collaboration with spatial input  

Science Conference Proceedings (OSTI)

We present BeThere, a proof-of-concept system designed to explore 3D input for mobile collaborative interactions. With BeThere, we explore 3D gestures and spatial input which allow remote users to perform a variety of virtual interactions ... Keywords: around device interaction, augmented reality, collaboration, depth sensors

Rajinder S. Sodhi; Brett R. Jones; David Forsyth; Brian P. Bailey; Giuliano Maciocci

2013-04-01T23:59:59.000Z

135

Twinkle box: a three-dimensional computer input device  

Science Conference Proceedings (OSTI)

During the past fifteen years, use of two-dimensional computer input/output devices has become commonplace. Since the earliest uses of the light pen for target identification in air defense systems it has been obvious that two-dimensional input would ...

Robert P. Burton; Ivan E. Sutherland

1974-05-01T23:59:59.000Z

136

Input--output capital coefficients for energy technologies. [Input-output model  

DOE Green Energy (OSTI)

Input-output capital coefficients are presented for five electric and seven non-electric energy technologies. They describe the durable goods and structures purchases (at a 110 sector level of detail) that are necessary to expand productive capacity in each of twelve energy source sectors. Coefficients are defined in terms of 1967 dollar purchases per 10/sup 6/ Btu of output from new capacity, and original data sources include Battelle Memorial Institute, the Harvard Economic Research Project, The Mitre Corp., and Bechtel Corp. The twelve energy sectors are coal, crude oil and gas, shale oil, methane from coal, solvent refined coal, refined oil products, pipeline gas, coal combined-cycle electric, fossil electric, LWR electric, HTGR electric, and hydroelectric.

Tessmer, R.G. Jr.

1976-12-01T23:59:59.000Z

137

DOE Seeks Industry Input on Nickel Disposition Strategy | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Industry Input on Nickel Disposition Strategy 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, financial, and product market information to review the feasibility of technologies capable of decontaminating the nickel to a level indistinguishable from what is commercially available, such that it could be safely recycled and reused. The EOI scope is for 6,400 tons of nickel to be recovered from the uranium enrichment process

138

DOE Seeks Industry Input on Nickel Disposition Strategy | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

DOE Seeks Industry Input on Nickel Disposition Strategy DOE Seeks 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, financial, and product market information to review the feasibility of technologies capable of decontaminating the nickel to a level indistinguishable from what is commercially available, such that it could be safely recycled and reused. The EOI scope is for 6,400 tons of nickel to be recovered from the uranium enrichment process

139

Input to the 2012-2021 Strategic Plan  

NLE Websites -- All DOE Office Websites (Extended Search)

Related Federal Climate Efforts Related Federal Climate Efforts Input to the 2012-2021 Strategic Plan Print E-mail Engaging Stakeholders The USGCRP is dedicated to engaging stakeholders in strategic planning efforts. Our community outreach activities created a dialogue with our stakeholders through various communication channels, such as opportunities for interagency collaboration, town hall meetings, public presentations and listening sessions. These channels alongside our 60 day public comment period enabled the program to incorporate stakeholder input int the process of drafting this decadal plan. In addition, we welcome input - particularly on the future direction of USGCRP and on the climate information you need and use. Please send your comments to input@usgcrp.gov. Listening Sessions

140

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Abandoned Uranium Mines Report to Congress: LM Wants Your Input 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 input on an abandoned uranium mines report to Congress. On January 2, 2013, President Obama signed into law the National Defense Authorization Act for Fiscal Year 2013, which requires the Secretary of Energy, in consultation with the Secretary of the U.S Department of the Interior (DOI) and the Administrator

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


141

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

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

,,"(202) 586-8800",,,"7242013 11:46:42 PM" "Back to Contents","Data 1: U.S. Refinery Crude Oil Input Qualities" "Sourcekey","MCRS1US2","MCRAPUS2" "Date","U.S. Sulfur...

142

Speech recognition as a computer graphics input technique (Panel Session)  

Science Conference Proceedings (OSTI)

Richard Rabin Interactive graphics systems typically require intense hands busy/eyes busy and brains busy activity on the part of the system user/operator. Voice input by means of automatic speech recognition equipment, offers major potential ...

Alan R. Strass; Mark Robillard; Sue Schedler; Matthew Peterson / Richard Rabin

1982-07-01T23:59:59.000Z

143

Comparison of wind stress algorithms, datasets and oceanic power input  

E-Print Network (OSTI)

If the ocean is in a statistically steady state, energy balance is a strong constraint, suggesting that the energy input into the world ocean is dissipated simultaneously at the same rate. Energy conservation is one of the ...

Yuan, Shaoyu

2009-01-01T23:59:59.000Z

144

Constructing Verifiable Random Functions with Large Input Spaces Susan Hohenberger  

E-Print Network (OSTI)

idea is to apply a simulation technique where the large space of VRF inputs is collapsed into a small, the verification should remain secure even if the public commitment were setup in a malicious manner. The VRF

145

On the Energy Input from Wind to Surface Waves  

Science Conference Proceedings (OSTI)

A basic model relating the energy dissipation in the ocean mixed layer to the energy input into the surface wave field is combined with recent measurements of turbulent kinetic energy dissipation to determine the average phase speed of the waves ...

J. R. Gemmrich; T. D. Mudge; V. D. Polonichko

1994-11-01T23:59:59.000Z

146

Eclat : automatic generation and classification of test inputs  

E-Print Network (OSTI)

This thesis describes a technique that selects, from a large set of test inputs, a small subset likely to reveal faults in the software under test. The technique takes a program or software component, plus a set of correct ...

Pacheco, Carlos, S.M. Massachusetts Institute of Technology

2005-01-01T23:59:59.000Z

147

IMPACT OF HIGH-INPUT PRODUCTION PRACTICES ON SOYBEAN YIELD.  

E-Print Network (OSTI)

??High-input management practices are often heavily marketed to producers to increase soybean [Glycine max (L) Merr.] yield in already high-yielding environments. Field research was conducted (more)

Jordan, Daniel L.

2010-01-01T23:59:59.000Z

148

Indiana, Illinois, Kentucky Refinery District Gross Inputs to ...  

U.S. Energy Information Administration (EIA)

Indiana, Illinois, Kentucky Refinery District Gross Inputs to Refineries (Thousand Barrels per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1985: 1,739 ...

149

FCT Technology Validation: Transportation Projects  

NLE Websites -- All DOE Office Websites (Extended Search)

Transportation Projects to someone by E-mail Share FCT Technology Validation: Transportation Projects on Facebook Tweet about FCT Technology Validation: Transportation Projects on...

150

EOS Validation Data Archival Policy  

NLE Websites -- All DOE Office Websites (Extended Search)

FIFE Follow-On LBA (Amazon) NACP (North America) OTTER (Oregon) SAFARI 2000 (S.Africa) SNF (Minnesota) Validation BIGFOOT Canopy Chemistry (ACCP) EOS Land Validation...

151

Validation of PG+W  

Science Conference Proceedings (OSTI)

Validation of PG+W. ... More Information. Calibration of Turbine Meters. Validation of PG+W. Propylene Glycol vs. Stoddard Solvent. ...

2012-08-09T23:59:59.000Z

152

Fuel Cell Technologies Office: Technology Validation  

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

Information Technology Validation Search Search Help Technology Validation EERE Fuel Cell Technologies Office Technology Validation Printable Version Share this resource...

153

Model Validation Bernie Lesieutre  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Model Validation Model Validation Bernie Lesieutre University of Wisconsin lesieutre@wisc.edu 27 June 2013 Washington, DC DOE/OE Transmission Reliability Program 2 Project Objectives To Develop techniques and tools for PMU- and feature-based power system model validation. Background: Our prior proof-of-concept research demonstrated that feature-based sensitivity models can be used to calibrate power system dynamic models. This was applied to the WECC composite load model for oscillatory and FIDVR events. 3 Project Objectives PSLF simulation features features Sensitivity Model (parameters) Measured Data Simulated Data Features Error Adjust Parameters Technical Approach 4 Project Objectives Current Research: Use PMU data to calibrate power plant models. Four Tasks:

154

validation | OpenEI  

Open Energy Info (EERE)

validation validation Dataset Summary Description (Abstract): 31Conclusiones y recomendacionesEl método de cálculo de la radiación solar global desarrollado ha obtenido resultadoscomparables a otros métodos revisados en la bibliografía. A diferencia de muchos deestos métodos, que han sido ajustados y refinados por sus autores a lo largo de variosaños de trabajo, este es completamente nuevo y parte de un enfoque diferente, por loque tiene un gran potencial de ajuste y sintonización.Algunos cambios que pueden sugerirse son tomar distribuciones espaciales ytemporales Source Instituto de Meteorología de Cuba Date Released November 30th, 2005 (9 years ago) Date Updated November 07th, 2007 (7 years ago) Keywords América Latina Cuba documentation solar SWERA validation

155

Accelerated Testing Validation  

NLE Websites -- All DOE Office Websites (Extended Search)

Testing Validation Testing Validation Rangachary Mukundan (PI), Rodney Borup, John Davey, Roger Lujan Los Alamos National Laboratory Adam Z. Weber Lawrence Berkeley National Laboratory Greg James Ballard Power Systems, Inc Mike Brady Oak Ridge National Laboratory Steve Grot Ion Power, Inc This presentation does not contain any proprietary or confidential information Objective/Barrier/Target The objectives of this project are 3-fold 1. Correlation of the component lifetimes measured in an AST to real-world behavior of that component. 2. Validation of existing ASTs for Catalyst layers and Membranes 3. Development of new ASTs for GDLs, bipolar plates and interfaces Technical Barrier Addressed: A. Durability * Durability of fuel cell systems operating over automotive drive cycles has not

156

New Hampshire Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 774 720 582 328 681 509 362 464 492 592 1990's 205 128 96 154 160 90 147 102 103 111 2000's 180 86 66 58 91 84 92 9 0 0 2010's 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas New Hampshire Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

157

OECD Input-Output Tables | Open Energy Information  

Open Energy Info (EERE)

OECD Input-Output Tables OECD Input-Output Tables Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Input-Output Tables Agency/Company /Organization: Organisation for Economic Co-Operation and Development Topics: Co-benefits assessment, Market analysis, Co-benefits assessment, Pathways analysis Resource Type: Dataset Website: www.oecd.org/document/3/0,3343,en_2649_34445_38071427_1_1_1_1,00.html Country: Sweden, Finland, Japan, South Korea, Argentina, Australia, China, Israel, United Kingdom, Portugal, Romania, Greece, Poland, Slovakia, Chile, India, Canada, New Zealand, United States, Denmark, Norway, Spain, Austria, Italy, Netherlands, Ireland, France, Belgium, Brazil, Czech Republic, Estonia, Germany, Hungary, Luxembourg, Mexico, Slovenia, South Africa, Turkey, Indonesia, Switzerland, Taiwan, Russia

158

Connecticut Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Connecticut Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

159

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

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas South Carolina Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

160

Tennessee Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Tennessee Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply & Disposition

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


161

Washington Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 15 13 15 11 11 9 10 21 79 154 1990's 181 154 180 4 0 0 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Washington Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply & Disposition

162

Minnesota Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 48 106 337 1 3 11 2 1 385 315 1990's 56 49 52 78 289 194 709 172 50 64 2000's 101 118 13 42 71 154 13 54 46 47 2010's 12 20 9 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Minnesota Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

163

District of Columbia Natural Gas Input Supplemental Fuels (Million Cubic  

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

Input Supplemental Fuels (Million Cubic 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas District of Columbia Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply & Disposition)

164

Maryland Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 484 498 984 352 332 373 155 136 743 899 1990's 24 72 126 418 987 609 882 178 80 498 2000's 319 186 48 160 124 382 41 245 181 170 2010's 115 89 116 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Maryland Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

165

Iowa Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 57 64 68 23 53 45 44 40 34 82 1990's 81 46 45 84 123 96 301 137 17 12 2000's 44 39 23 143 30 31 46 40 27 3 2010's 2 1 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Iowa Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply & Disposition

166

Pennsylvania Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Pennsylvania Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

167

Possible Magmatic Input to the Dixie Valley Geothermal Field, and  

Open Energy Info (EERE)

Possible Magmatic Input to the Dixie Valley Geothermal Field, and Possible Magmatic Input to the Dixie Valley Geothermal Field, and Implications for District-Scale Resource Exploration, Inferred from Magnetotelluric (MT) Resistivity Surveying Jump to: navigation, search OpenEI Reference LibraryAdd to library Journal Article: Possible Magmatic Input to the Dixie Valley Geothermal Field, and Implications for District-Scale Resource Exploration, Inferred from Magnetotelluric (MT) Resistivity Surveying Abstract Magnetotelluric (MT) profiling in northwestern Nevadais used to test hypotheses on the main sources of heat andhydrothermal fluid for the Dixie Valley-Central NevadaSeismic Belt area. The transect reveals families of resistivitystructures commonly dominated by steeply-dipping features,some of which may be of key geothermal significance. Mostnotably, 2-D inversion

168

Missouri Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 65 60 2,129 1,278 326 351 1 1 2 1,875 1990's 0 0 0 0 371 4 785 719 40 207 2000's 972 31 62 1,056 917 15 78 66 6 10 2010's 18 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Missouri Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

169

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

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Rhode Island Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

170

DOE Seeks Input On Addressing Contractor Pension and Medical Benefits  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Input On Addressing Contractor Pension and Medical 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 Management and Operating and other site management contracts, DOE reimburses its contractors for allowable costs incurred in providing contractor employee pension and medical benefits to current employees and retirees. In FY2006, these costs reached approximately $1.1 billion - a more than 226 percent increase since FY2000 - and are expected to grow in future years.

171

Georgia Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Georgia Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

172

Delaware Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Delaware Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply & Disposition

173

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

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas South Dakota Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply & Disposition

174

Incorporating uncertainty in RADTRAN 6.0 input files.  

SciTech Connect

Uncertainty may be introduced into RADTRAN analyses by distributing input parameters. The MELCOR Uncertainty Engine (Gauntt and Erickson, 2004) has been adapted for use in RADTRAN to determine the parameter shape and minimum and maximum of the distribution, to sample on the distribution, and to create an appropriate RADTRAN batch file. Coupling input parameters is not possible in this initial application. It is recommended that the analyst be very familiar with RADTRAN and able to edit or create a RADTRAN input file using a text editor before implementing the RADTRAN Uncertainty Analysis Module. Installation of the MELCOR Uncertainty Engine is required for incorporation of uncertainty into RADTRAN. Gauntt and Erickson (2004) provides installation instructions as well as a description and user guide for the uncertainty engine.

Dennis, Matthew L.; Weiner, Ruth F.; Heames, Terence John (Alion Science and Technology)

2010-02-01T23:59:59.000Z

175

Optical device with conical input and output prism faces  

DOE Patents (OSTI)

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.

Brunsden, Barry S. (Chicago, IL)

1981-01-01T23:59:59.000Z

176

Table 3. U.S. Inputs to Biodiesel Production  

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

U.S. Inputs to Biodiesel Production U.S. Inputs to Biodiesel Production (million pounds) 2011 January 8 17 - W 150 W 14 11 February 26 13 - W 150 W 14 11 March 68 14 - W 190 W 19 27 April 88 20 - W 236 W 15 47 May 113 21 - W 264 W 16 36 June 75 34 - W 311 W 23 49 July 77 35 - W 367 W 26 64 August 84 37 W W 398 W 34 38 September 84 27 W W 430 W

177

Environmental issues of material input in CDTE-module manufacturing  

DOE Green Energy (OSTI)

The goal of a low-cost and high-volume photovoltaic (PV) module fabrication demands an optimized process sequence to guarantee product quality and module stability on a long-term basis. Nevertheless, large-scale module manufacturing uses several input and auxiliary materials and generates waste from processing output materials. The mining and refining of the PV manufacturing material consumes input and auxiliary material and also creates waste. Therefore, investigations into these materials were conducted with respect to their risk potential for environment and health.

Steinberger, H.; Hochwimmer, R.; Schmid, H. [Fraunhofer Inst. fuer Festkoerpertechnologie, Muenchen (Germany); Thumm, W.; Kettrup, A. [GSF, Oberschleissheim (Germany). Inst. fuer Oekologische Chemie; Moskowitz, P. [Brookhaven National Lab., Upton, NY (United States). Biomedical and Environmental Assessment Group

1995-12-31T23:59:59.000Z

178

Electricity Regulation in California and Input Market Distortions  

E-Print Network (OSTI)

We provide an analysis of the soft price cap regulation that occurred in Californias electricity market between December 2000 and June 2001. We demonstrate the incentive it created to distort the prices of electricity inputs. After introducing a theoretical model of the incentive, we present empirical data from two important input markets: pollution emissions permits and natural gas. We find substantial evidence that generators manipulated these costs in a way that allowed them to justify bids in excess of the price cap and earn higher rents than they could otherwise. Our analysis suggests that the potential benefits of soft price cap regulation were likely undone by such behavior. 1

Mark R. Jacobsen; Azeem M. Shaikh

2004-01-01T23:59:59.000Z

179

A toolbox for calculating net anthropogenic nitrogen inputs (NANI)  

Science Conference Proceedings (OSTI)

The ''Net Anthropogenic Nitrogen Input'' (NANI) to a region represents an estimate of anthropogenic net nitrogen (N) fluxes across its boundaries, and is thus a measure of the effect of human activity on the regional nitrogen cycle. NANI accounts for ... Keywords: Anthropogenic, Nitrogen, Synthesis, Toolbox, Watershed

Bongghi Hong; Dennis P. Swaney; Robert W. Howarth

2011-05-01T23:59:59.000Z

180

PV array simulator development and validation.  

Science Conference Proceedings (OSTI)

The ability to harvest all available energy from a photovoltaic (PV) array is essential if new system developments are to meet levelized cost of energy targets and achieve grid parity with conventional centralized utility power. Therefore, exercising maximum power point tracking (MPPT) algorithms, dynamic irradiance condition operation and startup and shutdown routines and evaluating inverter performance with various PV module fill-factor characteristics must be performed with a repeatable, reliable PV source. Sandia National Laboratories is collaborating with Ametek Programmable Power to develop and demonstrate a multi-port TerraSAS PV array simulator. The simulator will replicate challenging PV module profiles, enabling the evaluation of inverter performance through analyses of the parameters listed above. Energy harvest algorithms have traditionally implemented methods that successfully utilize available energy. However, the quantification of energy capture has always been difficult to conduct, specifically when characterizing the inverter performance under non-reproducible dynamic irradiance conditions. Theoretical models of the MPPT algorithms can simulate capture effectiveness, but full validation requires a DC source with representative field effects. The DC source being developed by Ametek and validated by Sandia is a fully integrated system that can simulate an IV curve from the Solar Advisor Model (SAM) module data base. The PV simulator allows the user to change the fill factor by programming the maximum power point voltage and current parameters and the open circuit voltage and short circuit current. The integrated PV simulator can incorporate captured irradiance and module temperature data files for playback, and scripted profiles can be generated to validate new emerging hardware embedded with existing and evolving MPPT algorithms. Since the simulator has multiple independent outputs, it also has the flexibility to evaluate an inverter with multiple MPPT DC inputs. The flexibility of the PV simulator enables the validation of the inverter's capability to handle vastly different array configurations.

Kuszmaul, Scott S.; Gonzalez, Sigifredo; Lucca, Roberto (Ametek Programmable Power, San Diego, CA); Deuel, Don (Ametek Programmable Power, San Diego, CA)

2010-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "wicket input validation" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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181

Validation Program - The Security Content Automation ...  

Science Conference Proceedings (OSTI)

... Information technology Laboratory (ITL). Security Content Automation Protocol (SCAP) Validation Program. The SCAP Validation ...

2013-12-10T23:59:59.000Z

182

Flight code validation simulator  

Science Conference Proceedings (OSTI)

An End-To-End Simulation capability for software development and validation of missile flight software on the actual embedded computer has been developed utilizing a 486 PC, i860 DSP coprocessor, embedded flight computer and custom dual port memory interface hardware. This system allows real-time interrupt driven embedded flight software development and checkout. The flight software runs in a Sandia Digital Airborne Computer (SANDAC) and reads and writes actual hardware sensor locations in which IMU (Inertial Measurements Unit) data resides. The simulator provides six degree of freedom real-time dynamic simulation, accurate real-time discrete sensor data and acts on commands and discretes from the flight computer. This system was utilized in the development and validation of the successful premier flight of the Digital Miniature Attitude Reference System (DMARS) in January 1995 at the White Sands Missile Range on a two stage attitude controlled sounding rocket.

Sims, B.A.

1995-08-01T23:59:59.000Z

183

CIPS Validation Data Plan  

SciTech Connect

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.

Nam Dinh

2012-03-01T23:59:59.000Z

184

CIPS Validation Data Plan  

SciTech Connect

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.

Nam Dinh

2012-03-01T23:59:59.000Z

185

FCT Technology Validation: Integrated Projects  

NLE Websites -- All DOE Office Websites (Extended Search)

Integrated Projects to Integrated Projects to someone by E-mail Share FCT Technology Validation: Integrated Projects on Facebook Tweet about FCT Technology Validation: Integrated Projects on Twitter Bookmark FCT Technology Validation: Integrated Projects on Google Bookmark FCT Technology Validation: Integrated Projects on Delicious Rank FCT Technology Validation: Integrated Projects on Digg Find More places to share FCT Technology Validation: Integrated Projects on AddThis.com... Home Transportation Projects Stationary/Distributed Generation Projects Integrated Projects DOE Projects Non-DOE Projects Quick Links Hydrogen Production Hydrogen Delivery Hydrogen Storage Fuel Cells Manufacturing Codes & Standards Education Systems Analysis Contacts Integrated Projects To maximize overall system efficiencies, reduce costs, and optimize

186

Total Refinery Net Input of Crude Oil and Petroleum Products  

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

Input Input Product: Total Crude Oil & Petroleum Products Crude Oil Natural Gas Plant Liquids Pentanes Plus Liquefied Petroleum Gases Normal Butane Isobutane Other Liquids Hydrogen/Oxygenates/Renewables/Other Hydrocarbons Hydrogen Oxygenates (excl. Fuel Ethanol) Methyl Tertiary Butyl Ether (MTBE) All Other Oxygenates Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Other Hydrocarbons Unfinished Oils (net) Unfinished Oils, Naphthas and Lighter Unfinished Oils, Kerosene and Light Gas Oils Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Components (MGBC) (net) MGBC - Reformulated MGBC - Reformulated - RBOB MGBC - Reformulated, RBOB for Blending w/ Alcohol MGBC - Reformulated, RBOB for Blending w/ Ether MGBC - Conventional MGBC - CBOB MGBC - Conventional, GTAB MGBC - Other Conventional Aviation Gasoline Blending Components (net) Alaskan Crude Oil Receipts Period-Unit: Monthly-Thousand Barrels Monthly-Thousand Barrels per Day Annual-Thousand Barrels Annual-Thousand Barrels per Day

187

Refinery & Blenders Net Input of Crude Oil  

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

Input Input Product: Total Crude Oil & Petroleum Products Crude Oil Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquefied Petroleum Gases Ethane Normal Butane Isobutane Other Liquids Hydrogen/Oxygenates/Renewables/Other Hydrocarbons Hydrogen Oxygenates (excl. Fuel Ethanol) Methyl Tertiary Butyl Ether (MTBE) All Other Oxygenates Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Other Hydrocarbons Unfinished Oils (net) Unfinished Oils, Naphthas and Lighter Unfinished Oils, Kerosene and Light Gas Oils Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Components (MGBC) (net) MGBC - Reformulated MGBC - Reformulated - RBOB MGBC - Reformulated, RBOB for Blending w/ Alcohol MGBC - Reformulated, RBOB for Blending w/ Ether MGBC - Reformulated, GTAB MGBC - Conventional MGBC - CBOB MGBC - Conventional, GTAB MGBC - Other Conventional Aviation Gasoline Blending Components (net) Period-Unit: Monthly-Thousand Barrels Monthly-Thousand Barrels per Day Annual-Thousand Barrels Annual-Thousand Barrels per Day

188

Agricultural and Environmental Input Parameters for the Biosphere Model  

SciTech Connect

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.

K. Rasmuson; K. Rautenstrauch

2004-09-14T23:59:59.000Z

189

Documentation of Calculation Methodology, Input Data, and Infrastructure  

NLE Websites -- All DOE Office Websites (Extended Search)

Documentation of Calculation Methodology, Input Data, and Infrastructure Documentation of Calculation Methodology, Input Data, and Infrastructure for the Home Energy Saver Web Site Title Documentation of Calculation Methodology, Input Data, and Infrastructure for the Home Energy Saver Web Site Publication Type Report LBNL Report Number LBNL-51938 Year of Publication 2005 Authors Pinckard, Margaret J., Richard E. Brown, Evan Mills, James D. Lutz, Mithra M. Moezzi, Celina S. Atkinson, Christopher A. Bolduc, Gregory K. Homan, and Katie Coughlin Document Number LBNL-51938 Pagination 108 Date Published July 13 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract The Home Energy Saver (HES, http://HomeEnergySaver.lbl.gov) is an interactive web site designed to help residential consumers make decisions about energy use in their homes. This report describes the underlying methods and data for estimating energy consumption. Using engineering models, the site estimates energy consumption for six major categories (end uses); heating, cooling, water heating, major appliances, lighting, and miscellaneous equipment. The approach taken by the Home Energy Saver is to provide users with initial results based on a minimum of user input, allowing progressively greater control in specifying the characteristics of the house and energy consuming appliances. Outputs include energy consumption (by fuel and end use), energy-related emissions (carbon dioxide), energy bills (total and by fuel and end use), and energy saving recommendations. Real-world electricity tariffs are used for many locations, making the bill estimates even more accurate. Where information about the house is not available from the user, default values are used based on end-use surveys and engineering studies. An extensive body of qualitative decision-support information augments the analytical results.

190

North Dakota Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) Input Supplemental Fuels (Million Cubic Feet) North 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 196 417 102 0 8,335 40,370 49,847 51,543 49,014 54,408 1990's 53,144 52,557 58,496 57,680 57,127 57,393 55,867 53,179 54,672 53,185 2000's 49,190 51,004 53,184 53,192 47,362 51,329 54,361 51,103 50,536 53,495 2010's 54,813 51,303 52,541 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas

191

Illinois Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Illinois Supplemental Supplies of Natural Gas

192

New Jersey Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) Input Supplemental Fuels (Million Cubic Feet) New Jersey 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 9,574 11,504 9,786 9,896 8,616 13,421 12,099 13,774 14,846 14,539 1990's 9,962 14,789 14,362 14,950 7,737 7,291 6,778 6,464 9,082 5,761 2000's 8,296 12,330 3,526 473 530 435 175 379 489 454 2010's 457 392 139 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas New Jersey Supplemental Supplies of Natural Gas

193

Nebraska Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Nebraska Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

194

Michigan Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 3 3,038 2,473 2,956 2,773 2,789 2,754 2,483 2,402 2,402 1990's 19,106 15,016 14,694 12,795 13,688 21,378 21,848 22,238 21,967 20,896 2000's 12,423 4,054 0 0 0 0 0 0 0 0 2010's 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Michigan Supplemental Supplies of Natural Gas

195

Colorado Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Colorado Supplemental Supplies of Natural Gas

196

Ohio Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Ohio Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

197

Hawaii Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Hawaii Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

198

Massachusetts Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 15,366 21,828 17,586 10,732 6,545 3,668 2,379 1,404 876 692 1990's 317 120 105 61 154 420 426 147 68 134 2000's 26 16 137 324 80 46 51 15 13 10 2010's 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Massachusetts Supplemental Supplies of Natural Gas Supplies of Natural Gas Supplemental Fuels (Annual Supply &

199

Indiana Natural Gas Input Supplemental Fuels (Million Cubic Feet)  

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

Input Supplemental Fuels (Million Cubic Feet) 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 Year-8 Year-9 1960's 0 0 0 1970's 0 0 0 0 0 0 0 0 0 0 1980's 1,602 5,056 3,496 4,142 4,027 2,711 2,351 3,890 4,243 3,512 1990's 3,015 3,077 3,507 3,232 2,457 3,199 3,194 3,580 3,149 5,442 2000's 5,583 5,219 1,748 2,376 2,164 1,988 1,642 635 30 1 2010's 1 5 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Total Supplemental Supply of Natural Gas Indiana Supplemental Supplies of Natural Gas

200

PERSPECTIVES ON A DOE CONSEQUENCE INPUTS FOR ACCIDENT ANALYSIS APPLICATIONS  

Science Conference Proceedings (OSTI)

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.

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

2008-07-30T23:59:59.000Z

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


201

ALEGRA -- code validation: Experiments and simulations  

SciTech Connect

In this study, the authors are providing an experimental test bed for validating features of the ALEGRA code over a broad range of strain rates with overlapping diagnostics that encompass the multiple responses. A unique feature of the Arbitrary Lagrangian Eulerian Grid for Research Applications (ALEGRA) code is that it allows simultaneous computational treatment, within one code, of a wide range of strain-rates varying from hydrodynamic to structural conditions. This range encompasses strain rates characteristic of shock-wave propagation (10{sup 7}/s) and those characteristic of structural response (10{sup 2}/s). Most previous code validation experimental studies, however, have been restricted to simulating or investigating a single strain-rate regime. What is new and different in this investigation is that the authors have performed well-instrumented experiments which capture features relevant to both hydrodynamic and structural response in a single experiment. Aluminum was chosen for use in this study because it is a well characterized material--its EOS and constitutive material properties are well defined over a wide range of loading rates. The current experiments span strain rate regimes of over 10{sup 7}/s to less than 10{sup 2}/s in a single experiment. The input conditions are extremely well defined. Velocity interferometers are used to record the high strain-rate response, while low strain rate data were collected using strain gauges.

Chhabildas, L.C.; Konrad, C.H.; Mosher, D.A.; Reinhart, W.D; Duggins, B.D.; Rodeman, R.; Trucano, T.G.; Summers, R.M.; Peery, J.S.

1998-03-16T23:59:59.000Z

202

Current mode instrumentation amplifier with rail-to-rail input and output  

Science Conference Proceedings (OSTI)

A Current Mode Instrumentation Amplifier with rail-to-rail input and output is presented. It is based on constant gm input stages, and cascode output stages. Although this CMIA structure has a good Input Common Mode Voltage, it suffers from a poor output ... Keywords: analog integrated circuits, current mode instrumentation amplifier, rail-to-rail input and output

Filipe Costa Beber Vieira; Cesar Augusto Prior; Cesar Ramos Rodrigues; Leonardo Perin; Joao Baptista dos Santos Martins

2007-09-01T23:59:59.000Z

203

Navy Technology Validation (Techval)  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Technology Technology Validation (Techval) FUPWG Spring Meeting 2008 April 15, 2008 Destin, FL Paul Kistler, PE CEM NAVFAC Engineering Service Center Port Hueneme CA Navy Techval CURRENT PROJECTS * Cool Roof reflective roof coating  NS Pearl Harbor HI * Thermal Destratifiers  NAS Oceana VA * Boiler Combustion Controls  USNA Annapolis MD * Sand Filters  NAS Lemoore CA * Spectrally Enhanced Lighting  Navy Yard Washington DC * Desuperheater  NS Norfolk VA  NAS North Island CA * HVAC CO2 Controls  NAB Little Creek VA  NAVSUPPACT Mid-South TN  NB Kitsap Bremerton WA *HVAC Occupancy Controls NAS Oceana VA *Electromagnetic Pulse Water Treatment NADEP San Diego CA NSY Puget Sound WA *LED Parking Lot Lighting NBVC Port Hueneme CA Techval

204

Design and analysis tool validation  

DOE Green Energy (OSTI)

The Solar Energy Research Institute (SERI) is developing a procedure for the validation of Building Energy Analysis Simulation Codes (BEAS). These codes are being used increasingly in the building design process, both directly and as the basis for simplified design tools and guidelines. The importance of the validity of the BEAS in predicting building energy performance is obvious when one considers the money and energy that could be wasted by energy-inefficient designs. However, to date, little or no systematic effort has been made to ensure the validity of the various BEAS. The validation work at SERI consists of three distinct parts: Comparative Study, Analytical Verification, and Empirical Validation. The procedures have been developed for the first two parts and have been implemented on a sampling of the major BEAS; results have shown major problems in one of the BEAS tested. Furthermore, when one building design was run using several of the BEAS, large differences were found in the predicted annual cooling and heating loads. The empirical validation procedure has been developed, and five two-zone test cells have been constructed for validation; a summer validation run will take place as soon as the data acquisition system is completed. Additionally, a test validation exercise is now in progress using the low-cal house to fine-tune the empirical validation procedure and better define monitoring data requirements.

Judkoff, R.

1981-07-01T23:59:59.000Z

205

Characterization of industrial process waste heat and input heat streams  

SciTech Connect

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)

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.

1984-05-01T23:59:59.000Z

206

US Nuclear Regulatory Commission Input to DOE Request for Information Smart  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

US Nuclear Regulatory Commission Input to DOE Request for 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 Technologies" and "Reliability and Cyber-Security," US Nuclear Regulatory Commission Input to DOE Request for Information Smart Grid Implementation Input More Documents & Publications Comments of DRSG to DOE Smart Grid RFI: Addressing Policy and Logistical Challenges Reply Comments of Entergy Services, Inc. Progress Energy draft regarding Smart Grid RFI: Addressing Policy and

207

Residential oil burners with low input and two stages firing  

SciTech Connect

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.

Butcher, T.; Krajewski, R.; Leigh, R. [and others

1997-12-31T23:59:59.000Z

208

Design of the spoke cavity ED&D input coupler.  

DOE Green Energy (OSTI)

The current design of the Accelerator Driven Test Facility (ADTF) accelerator contains multiple {beta}, superconducting, resonant cavities. Spoke-type resonators ({beta} = 0.175 and {beta} = 0.34) are proposed for the low energy linac immediately following the radio frequency quadrupole. A continuous wave power requirement of 8.5 - 211.8 kW, 350 MHz has been established for the input couplers of these spoke cavities. The coupler design approach was to have a single input coupler design for beam currents of 13.3 mA and 100 mA and both cavity {beta}'s. The baseline design consists of a half-height WR2300 waveguide section merged with a shorted coaxial conductor. At the transition is a 4.8-mm thick cylindrical ceramic window creating the air/vacuum barrier. The coax is 103-mm inner diameter, 75 Ohm. The coax extends from the short through the waveguide and terminates with an antenna tip in the sidewall of the cavity. A full diameter pumping port is located in the quarter-wave stub to facilitate good vacuum. The coaxial geometry chosen was based on multipacting and thermal design considerations. The coupling coefficient is adjusted by statically adjusting the outer conductor length. The RF-physics, thermal, vacuum, and structural design considerations will be discussed in this paper, in addition to future room temperature testing plans.

Schmierer, E. N. (Eric N.); Chan, K. D. (Kwok-Chi D.); Gentzlinger, R.C. (Robert C.); Haynes, W. B. (William B.); Krawczyk, F. L. (Frank L.); Montoya, D. I. (Debbie I.); Roybal, P. L. (Phillip L.); Schrage, D. L. (Dale L.); Tajima, T. (Tsuyoshi)

2001-01-01T23:59:59.000Z

209

Separate Training Influences Relative Validity  

E-Print Network (OSTI)

concurrent inhibitory training of B were to alter respondingComparative Psychology Separate Training Influences RelativeDuring relative validity training, X was reinforced when

Mehta, Rick; Dumont, Jamie-Lynne; Combiadakis, Sharon; Williams, Douglas A.

2004-01-01T23:59:59.000Z

210

Validation of the RESRAD-RECYCLE computer code.  

SciTech Connect

The RESRAD-RECYCLE computer code was developed by Argonne National Laboratory under the sponsorship of the U.S. Department of Energy. It was designed to analyze potential radiation exposures resulting from the reuse and recycling of radioactively contaminated scrap metal and equipment. It was one of two codes selected in an international model validation study concerning recycling of radioactively contaminated metals. In the validation study, dose measurements at various stages of melting a spent nuclear fuel rack at Studsvik RadWaste AB, Sweden, were collected and compared with modeling results. The comparison shows that the RESRAD-RECYCLE results agree fairly well with the measurement data. Among the scenarios considered, dose results and measurement data agree within a factor of 6. Discrepancies may be explained by the geometrical limitation of the RESRAD-RECYCLE's external exposure model, the dynamic nature of the recycling activities, and inaccuracy in the input parameter values used in dose calculations.

Cheng, J.-J.; Yu, C.; Williams, W. A.; Murphie, W.

2002-02-01T23:59:59.000Z

211

Input-output theory for waveguide QED with an ensemble of inhomogeneous atoms  

E-Print Network (OSTI)

We study the collective effects that emerge in waveguide quantum electrodynamics where several (artificial) atoms are coupled to a one-dimensional (1D) superconducting transmission line. Since single microwave photons can travel without loss for a long distance along the line, real and virtual photons emitted by one atom can be reabsorbed or scattered by a second atom. Depending on the distance between the atoms, this collective effect can lead to super- and subradiance or to a coherent exchange-type interaction between the atoms. Changing the artificial atoms transition frequencies, something which can be easily done with superconducting qubits (two levels artificial atoms), is equivalent to changing the atom-atom separation and thereby opens the possibility to study the characteristics of these collective effects. To study this waveguide quantum electrodynamics system, we extend previous work and present an effective master equation valid for an ensemble of inhomogeneous atoms. Using input-output theory, we compute analytically and numerically the elastic and inelastic scattering and show how these quantities reveal information about collective effects. These theoretical results are compatible with recent experimental results using transmon qubits coupled to a superconducting one-dimensional transmission line [A.F. van Loo {\\it et al.} (2013)].

Kevin Lalumire; Barry C. Sanders; Arjan F. van Loo; Arkady Fedorov; Andreas Wallraff; Alexandre Blais

2013-05-30T23:59:59.000Z

212

Simplified modeling of solar process heating systems using stochastic weather input  

SciTech Connect

A model has been developed which accurately predicts solar district heating and industrial process heating collection performance on a daily basis. The model is system specific with no storage and constant load return temperature. This model was tested for its statistical significance and found to be highly significant. Performance data to construct the model were generated through numerous TRNSYS runs. Physically important variables were then chosen for inclusion in a statistical regression analysis. The variables, which are readily available on a daily basis, were daily radiation, mean twenty-four hour temperature, and collector and system characteristics. The weather input to the model may be real measured radiation values or artificially generated radiation values. The temperature may be daily averages when real radiation values are used or monthly averages when artificial radiation is used. It is shown that there is little difference in prediction when monthly temperature is used rather than the daily values. The performance model was developed from six months of Toronto, Canada, hourly data. The validation was performed with meteorological year locations, Albuquerque, Seattle, and Miami, chosen for climate diversity. The accuracy was excellent, even on a daily basis. A model was then developed from data of all four locations. The artificial data was tested for prediction accuracy for Toronto. Where the beta distribution fit well, the accuracy was good. Where the beta distribution did not fit as well, the accuracy was acceptable.

Boardman, E.C.

1986-01-01T23:59:59.000Z

213

MULTIPLE INPUT BINARY ADDER EMPLOYING MAGNETIC DRUM DIGITAL COMPUTING APPARATUS  

DOE Patents (OSTI)

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.

Cooke-Yarborough, E.H.

1960-12-01T23:59:59.000Z

214

U.S. Natural Gas Input Supplemental Fuels (Million Cubic Feet...  

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

Input Supplemental Fuels (Million Cubic Feet) U.S. 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...

215

Integrating surprisal and uncertain-input models in online sentence comprehension: formal techniques and empirical results  

Science Conference Proceedings (OSTI)

A system making optimal use of available information in incremental language comprehension might be expected to use linguistic knowledge together with current input to revise beliefs about previous input. Under some circumstances, such an error-correction ...

Roger Levy

2011-06-01T23:59:59.000Z

216

Prototype Validation Exercise (PROVE) Project  

NLE Websites -- All DOE Office Websites (Extended Search)

Validation > PROVE Validation > PROVE The Prototype Validation Exercise (PROVE) Project Overview The Prototype Validation Exercise (PROVE) was a mini field campaign conducted at the Jornada Experimental Range in the Chihuahuan Desert, near Las Cruces, New Mexico in May 1997. The goals of PROVE were to: Gain experience in the collection and use of field data for EOS product validation Develop protocols for coordination, measurement, and data archival Compile a synoptic land and atmospheric data set for testing algorithms The remote-sensing portion of PROVE involved investigators from three NASA Earth Observing System (EOS) instrument teams: MODIS (Moderate-Resolution Imaging Spectrometer) ASTER (Advanced Space-borne Thermal Emission and Reflectance Radiometer) MISR (Multi-Angle Imaging Spectro Radiometer)

217

Validation of Hybrid2 with the Froeya Island data set  

DOE Green Energy (OSTI)

To validate the simulation model Hybrid2, the authors simulated the performance of the Froeya system and compared it to measured data. The hybrid system, located on the Norwegian island of Froeya, is a wind/diesel with short-term battery storage and a dump load. Almost 17 days of system operation data are available from EFI, the Norwegian Electrical Research Institute of Norway. The same data set has been used to validate the European Wind Diesel Logistic Modeling Package (WDL) (Infield 1993, 1994). The authors input the measured time series of primary load and wind speed for this validation. As was the case for the validation of WDL, they modified the primary load to account for a gap in the measured energy balance. The wind speed was also corrected to account for the temporary unavailability of the wind turbine. When the Hybrid2 simulation is performed using the EFI input parameters for these components, the simulated energy production of the wind turbine and diesel is within 2% of the measured values. The simulated battery efficiency is much lower than was indicated in the measurements (which may be the case because the Alcad battery that was used in the simulation is not the same as the battery used in the Froeya system). Even so, the role of this short-term storage and the dispatch strategy is well represented, as shown by the good correspondence of 31% between the measured and simulated number of diesel starts. In addition, simulated fuel consumption was within 2% of the measured value, an accuracy sufficient for most design studies.

Dijk, V. van; Baring-Gould, E.I.

1996-06-01T23:59:59.000Z

218

A CMOS Voltage Comparator with Rail-to-Rail Input-Range  

Science Conference Proceedings (OSTI)

A simple new continuous-time CMOS comparator circuit with rail-to-rail input common-mode range and rail-to-rail output is presented. This design uses parallel complementary decision paths to accommodate power-supply-valued inputs. The 2 decision results ... Keywords: CMOS continuous-time voltage comparator, rail-to-rail input range

Wei-Shang Chu; K. Wayne Current

1999-05-01T23:59:59.000Z

219

Proper input phase-space filling for accurate beam-dynamics codes  

Science Conference Proceedings (OSTI)

In the future, more attention will be required concerning the filling of the input phase space used by particle-simulation codes. The prospect of greatly improved particle-tracking codes implies that code input distributions must be accurate models of real input distributions. Much of present simulation work is done using artificial phase-space distributions (K-V, waterbag, etc.). Real beams can differ dramatically from such ideal input. We have already developed a method for deriving code input distributions from measurements. This paper addresses the problem of determining the number of pseudoparticles needed to model the measured distribution properly.

Boicourt, G.P.; Vasquez, M.C.

1986-01-01T23:59:59.000Z

220

Gross Input to Atmospheric Crude Oil Distillation Units  

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

Day) 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 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History U.S. 15,283 15,709 16,327 16,490 16,306 16,162 1985-2013 PADD 1 1,134 1,188 1,178 1,142 1,122 1,130 1985-2013 East Coast 1,077 1,103 1,080 1,058 1,031 1,032 1985-2013 Appalachian No. 1 57 85 98 84 90 97 1985-2013 PADD 2 3,151 3,087 3,336 3,572 3,538 3,420 1985-2013 Ind., Ill. and Ky. 2,044 1,947 2,069 2,299 2,330 2,266 1985-2013

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221

,"U.S. Blender Net Input"  

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

Monthly","9/2013","1/15/2005" Monthly","9/2013","1/15/2005" ,"Release Date:","11/27/2013" ,"Next Release Date:","Last Week of December 2013" ,"Excel File Name:","pet_pnp_inpt3_dc_nus_mbbl_m.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_pnp_inpt3_dc_nus_mbbl_m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov" ,,"(202) 586-8800",,,"11/25/2013 11:22:43 AM" "Back to Contents","Data 1: U.S. Blender Net Input" "Sourcekey","MTXRB_NUS_1","M_EPL0_YIB_NUS_MBBL","MPPRB_NUS_1","M_EPLL_YIB_NUS_MBBL","MBNRB_NUS_1","MBIRB_NUS_1","M_EPOL_YIB_NUS_MBBL","M_EPOOXR_YIB_NUS_MBBL","MMTRB_NUS_1","M_EPOOR_YIB_NUS_MBBL","MFERB_NUS_1","M_EPOORD_YIB_NUS_MBBL","M_EPOORO_YIB_NUS_MBBL","M_EPPU_YIB_NUS_MBBL","M_EPOUN_YIB_NUS_MBBL","M_EPOUK_YIB_NUS_MBBL","M_EPOUH_YIB_NUS_MBBL","M_EPOUR_YIB_NUS_MBBL","MBCRB_NUS_1","MO1RB_NUS_1","M_EPOBGRR_YIB_NUS_MBBL","MO3RB_NUS_1","MO4RB_NUS_1","MO2RB_NUS_1","MO5RB_NUS_1","MO6RB_NUS_1","MO7RB_NUS_1","MO9RB_NUS_1"

222

Interface module for transverse energy input to dye laser modules  

SciTech Connect

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.

English, Jr., Ronald E. (Tracy, CA); Johnson, Steve A. (Tracy, CA)

1994-01-01T23:59:59.000Z

223

Interface module for transverse energy input to dye laser modules  

DOE Patents (OSTI)

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.

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

1994-10-11T23:59:59.000Z

224

KEPLER INPUT CATALOG: PHOTOMETRIC CALIBRATION AND STELLAR CLASSIFICATION  

Science Conference Proceedings (OSTI)

We describe the photometric calibration and stellar classification methods used by the Stellar Classification Project to produce the Kepler Input Catalog (KIC). The KIC is a catalog containing photometric and physical data for sources in the Kepler mission field of view; it is used by the mission to select optimal targets. Four of the visible-light (g, r, i, z) magnitudes used in the KIC are tied to Sloan Digital Sky Survey magnitudes; the fifth (D51) is an AB magnitude calibrated to be consistent with Castelli and Kurucz (CK) model atmosphere fluxes. We derived atmospheric extinction corrections from hourly observations of secondary standard fields within the Kepler field of view. For these filters and extinction estimates, repeatability of absolute photometry for stars brighter than magnitude 15 is typically 2%. We estimated stellar parameters {l_brace}T{sub eff}, log (g), log (Z), E{sub B-V}{r_brace} using Bayesian posterior probability maximization to match observed colors to CK stellar atmosphere models. We applied Bayesian priors describing the distribution of solar-neighborhood stars in the color-magnitude diagram, in log (Z), and in height above the galactic plane. Several comparisons with samples of stars classified by other means indicate that for 4500 K {data archive.

Brown, Timothy M. [Las Cumbres Observatory Global Telescope, Goleta, CA 93117 (United States); Latham, David W.; Esquerdo, Gilbert A. [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138 (United States); Everett, Mark E., E-mail: tbrown@lcogt.net, E-mail: latham@cfa.harvard.edu, E-mail: gesquerd@cfa.harvard.edu, E-mail: everett@noao.edu [National Optical Astronomy Observatories, Tucson, AZ 85721 (United States)

2011-10-15T23:59:59.000Z

225

On the Value of Input-Efficiency, Capacity-Efficiency, and the Flexibility to Rebalance Them  

E-Print Network (OSTI)

Abstract: A common characteristic of basic material manufacturers (which account for 85 % of all industrial energy use) and of cleantech manufacturers is that they are price-takers in their input and output markets. Variability in those prices has implications for how much a manufacturer should invest in three fundamental types of process improvement. Input price variability reduces the value of improving input-efficiency (output produced per unit input) but increases that of capacityefficiency (the rate at which a production facility can convert input into output). Output price variability increases the value of capacity-efficiency, but it increases the value of input-efficiency if and only if the expected margin is small. Moreover, as the expected input cost rises, the value of input-efficiency decreases. A third type of process improvement is to develop flexibility in inputefficiency versus capacity-efficiency (the ability to respond to a rise in input cost or fall in output price by increasing input-efficiency at the expense of capacity-efficiency). The value of this flexibility decreases with variability in input and output prices, if and only if the expected margin is thin. Together, these results suggest that a carbon tax or cap-and-trade system may reduce investment by basic material manufacturers in improving energy-efficiency.

Erica L. Plambeck; Terry A. Taylor

2013-01-01T23:59:59.000Z

226

Validation of Polarimetric Hail Detection  

Science Conference Proceedings (OSTI)

This study describes, illustrates, and validates hail detection by a simplified version of the National Severe Storms Laboratorys fuzzy logic polarimetric hydrometeor classification algorithm (HCA). The HCA uses four radar variables: ...

Pamela L. Heinselman; Alexander V. Ryzhkov

2006-10-01T23:59:59.000Z

227

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

Science Conference Proceedings (OSTI)

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.

I. Wong

2004-11-05T23:59:59.000Z

228

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

DOE Green Energy (OSTI)

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.

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

2012-09-01T23:59:59.000Z

229

Verification and validation of simulation models  

Science Conference Proceedings (OSTI)

In this paper we discuss verification and validation of simulation models. Four different approaches to deciding model validity are described; two different paradigms that relate verification and validation to the model development process are presented; ...

Robert G. Sargent

2009-12-01T23:59:59.000Z

230

,"U.S. Refinery Net Input"  

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

2,"Annual",2012,"6/30/2005" 2,"Annual",2012,"6/30/2005" ,"Data 2","Alaskan Crude Oil Receipts",1,"Annual",2012,"6/30/1986" ,"Release Date:","9/27/2013" ,"Next Release Date:","9/26/2014" ,"Excel File Name:","pet_pnp_inpt2_dc_nus_mbbl_a.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_pnp_inpt2_dc_nus_mbbl_a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov" ,,"(202) 586-8800",,,"11/25/2013 11:21:04 AM" "Back to Contents","Data 1: Refinery Net Input" "Sourcekey","MTTRO_NUS_1","MCRRO_NUS_1","MNGRO_NUS_1","MPPRO_NUS_1","MLPRO_NUS_1","MBNRO_NUS_1","MBIRO_NUS_1","MOLRO_NUS_1","MOHRO_NUS_1","M_EPOOOH_YIY_NUS_MBBL","M_EPOOXXFE_YIY_NUS_MBBL","MMTRO_NUS_1","MOORO_NUS_1","M_EPOOR_YIY_NUS_MBBL","MFERO_NUS_1","M_EPOORD_YIY_NUS_MBBL","M_EPOOOXH_YIY_NUS_MBBL","MUORO_NUS_1","MNLRO_NUS_1","MKORO_NUS_1","MH1RO_NUS_1","MRURO_NUS_1","MBCRO_NUS_1","MO1RO_NUS_1","M_EPOBGRR_YIY_NUS_MBBL","MO3RO_NUS_1","MO4RO_NUS_1","MO5RO_NUS_1","MO6RO_NUS_1","MO7RO_NUS_1","MO9RO_NUS_1","MBARO_NUS_1"

231

,"U.S. Refinery Net Input"  

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

3,"Monthly","9/2013","1/15/2005" 3,"Monthly","9/2013","1/15/2005" ,"Data 2","Alaskan Crude Oil Receipts",1,"Monthly","9/2013","1/15/1986" ,"Release Date:","11/27/2013" ,"Next Release Date:","Last Week of December 2013" ,"Excel File Name:","pet_pnp_inpt2_dc_nus_mbbl_m.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_pnp_inpt2_dc_nus_mbbl_m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov" ,,"(202) 586-8800",,,"11/25/2013 11:21:05 AM" "Back to Contents","Data 1: Refinery Net Input" "Sourcekey","MTTRO_NUS_1","MCRRO_NUS_1","MNGRO_NUS_1","MPPRO_NUS_1","MLPRO_NUS_1","MBNRO_NUS_1","MBIRO_NUS_1","MOLRO_NUS_1","MOHRO_NUS_1","M_EPOOOH_YIY_NUS_MBBL","M_EPOOXXFE_YIY_NUS_MBBL","MMTRO_NUS_1","MOORO_NUS_1","M_EPOOR_YIY_NUS_MBBL","MFERO_NUS_1","M_EPOORD_YIY_NUS_MBBL","M_EPOORO_YIY_NUS_MBBL","M_EPOOOXH_YIY_NUS_MBBL","MUORO_NUS_1","MNLRO_NUS_1","MKORO_NUS_1","MH1RO_NUS_1","MRURO_NUS_1","MBCRO_NUS_1","MO1RO_NUS_1","M_EPOBGRR_YIY_NUS_MBBL","MO3RO_NUS_1","MO4RO_NUS_1","MO5RO_NUS_1","MO6RO_NUS_1","MO7RO_NUS_1","MO9RO_NUS_1","MBARO_NUS_1"

232

FIMS Data Validation | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

FIMS Data Validation FIMS Data Validation Aviation Management Executive Secretariat Energy Reduction at HQ Facilities and Infrastructure Federal Advisory Committee Management...

233

FIMS Data Validation | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Information Systems FIMS Data Validation FIMS Data Validation Aviation Management Executive Secretariat Energy Reduction at HQ Facilities and Infrastructure Federal Advisory...

234

Fuel Cell Technologies Office: Technology Validation  

NLE Websites -- All DOE Office Websites (Extended Search)

Fuel Cell Technologies Office: Technology Validation to someone by E-mail Share Fuel Cell Technologies Office: Technology Validation on Facebook Tweet about Fuel Cell Technologies...

235

Validation of Innovative Exploration Technologies for Newberry...  

Open Energy Info (EERE)

Validation of Innovative Exploration Technologies for Newberry Volcano Geothermal Project Jump to: navigation, search Last modified on July 22, 2011. Project Title Validation of...

236

Validation of Criticality Safety Calculations with SCALE 6.2  

SciTech Connect

SCALE 6.2 provides numerous updates in nuclear data, nuclear data processing, and computational tools utilized in the criticality safety calculational sequences relative to SCALE 6.1. A new 252-group ENDF/B-VII.0 multigroup neutron library, improved ENDF/B-VII.0 continuous energy data, as well as the previously deployed 238-group ENDF/B-VII.0 neutron library are included in SCALE 6.2 for criticality safety analysis. The performance of all three libraries for keff calculations is examined with a broad sampling of critical experiment models covering a range of fuels and moderators. Critical experiments from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE) that are available in the SCALE Verified, Archived Library of Inputs and Data (VALID) are used in this validation effort. Over 300 cases are used in the validation of KENO V.a, and a more limited set of approximately 50 configurations are used for KENO-VI validation. Additionally, some KENO V.a cases are converted to KENO-VI models so that an equivalent set of experiments can be used to validate both codes. For continuous-energy calculations, SCALE 6.2 provides improved performance relative to SCALE 6.1 in most areas with notable improvements in fuel pin lattice cases, particularly those with mixed oxide fuel. Multigroup calculations with the 252-group library also demonstrate improved performance for fuel lattices, uranium (high and intermediate enrichment) and plutonium metal experiments, and plutonium solution systems. Overall, SCALE 6.2 provides equivalent or smaller biases than SCALE 6.1, and the two versions of KENO provide similar results on the same suite of problems.

Marshall, William BJ J [ORNL; Wiarda, Dorothea [ORNL; Celik, Cihangir [ORNL; Rearden, Bradley T [ORNL

2013-01-01T23:59:59.000Z

237

MARMOT Validation | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Validation 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 offers faster convergence. A manuscript summarizing these results has been submitted for publication. Work is also continuing on implementing a J2 von-Mises' time-dependent and independent plasticity into the Marmot phase-field algorithm. The current studies do not include adoptive meshing,

238

Measures of agreement between computation and experiment:validation metrics.  

SciTech Connect

With the increasing role of computational modeling in engineering design, performance estimation, and safety assessment, improved methods are needed for comparing computational results and experimental measurements. Traditional methods of graphically comparing computational and experimental results, though valuable, are essentially qualitative. Computable measures are needed that can quantitatively compare computational and experimental results over a range of input, or control, variables and sharpen assessment of computational accuracy. This type of measure has been recently referred to as a validation metric. We discuss various features that we believe should be incorporated in a validation metric and also features that should be excluded. We develop a new validation metric that is based on the statistical concept of confidence intervals. Using this fundamental concept, we construct two specific metrics: one that requires interpolation of experimental data and one that requires regression (curve fitting) of experimental data. We apply the metrics to three example problems: thermal decomposition of a polyurethane foam, a turbulent buoyant plume of helium, and compressibility effects on the growth rate of a turbulent free-shear layer. We discuss how the present metrics are easily interpretable for assessing computational model accuracy, as well as the impact of experimental measurement uncertainty on the accuracy assessment.

Barone, Matthew Franklin; Oberkampf, William Louis

2005-08-01T23:59:59.000Z

239

Validation of a Geothermal Simulator  

DOE Green Energy (OSTI)

A geothermal simulator, TETRAD, is validated against the Stanford Geothermal Problem Set. The governing equations, formulation, and solution technique employed by TETRAD are first outlined. Each problem in the Stanford Problem Set is then discussed in detail, and results from the simulations are presented. The results obtained using TETRAD are compared against several other geothermal simulators. Favorable comparison between results indicates that TETRAD is capable of solving the highly non-linear equations describing the flow of mass and energy in porous media. This validation exercise allows for the use of TETRAD in studying geothermal problems with a high degree of confidence.

Shook, G.M.; Faulder, D.D.

1991-10-01T23:59:59.000Z

240

[Composite analysis E-area vaults and saltstone disposal facilities]. PORFLOW and FACT input files  

Science Conference Proceedings (OSTI)

This diskette contains the PORFLOW and FACT input files described in Appendix B of the accompanying report `Composite Analysis E-Area Vaults and Saltstone Disposal Facilities`.

Cook, J.R.

1997-09-01T23:59:59.000Z

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


241

SRTC input to DOE-HQ R and D database for FY99  

SciTech Connect

This is a database of the Savannah River Site input to the DOE Research and Development database. The report contains approximately 50 project abstracts.

Chandler, L.R. Jr.

2000-01-05T23:59:59.000Z

242

Table A4. Total Inputs of Energy for Heat, Power, and Electricity...  

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

"Table A4. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Census Division, Industry Group, and Selected Industries, 1994: Part 2" "...

243

Table A36. Total Inputs of Energy for Heat, Power, and Electricity  

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

"Table A36. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Fuel Type, Industry Group, Selected Industries, and End Use, 1991:" " Part 2" " (Estimates in...

244

Table A10. Total Inputs of Energy for Heat, Power, and Electricity...  

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

"Table A10. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Fuel Type, Industry Group, Selected Industries, and End Use, 1994:" " Part 2" " (Estimates in...

245

Use of probabilistic inversion to model qualitative expert input when selecting a new nuclear reactor technology.  

E-Print Network (OSTI)

?? Complex investment decisions by corporate executives often require the comparison of dissimilar attributes and competing technologies. A technique to evaluate qualitative input from experts (more)

Merritt, Charles R., Jr.

2008-01-01T23:59:59.000Z

246

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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...

247

Table A12. Total Inputs of Energy for Heat, Power, and Electricity...  

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

2. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region and Economic Characteristics of the Establishment, 1991" " (Estimates in Btu or Physical...

248

Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian framework  

E-Print Network (OSTI)

Calibrated probabilistic forecasting using ensemble modelSutcliffe (1970), River flow forecasting through conceptuala Distributed Flood Forecasting Model with Input Uncertainty

Li, M.

2013-01-01T23:59:59.000Z

249

Fossil energy use in conventional and low-external-input cropping systems.  

E-Print Network (OSTI)

??The production of fossil fuels will crest within the next decade and with reliance of modern conventional agriculture on fossil fuel energy inputs, food production (more)

Cruse, Michael James

2009-01-01T23:59:59.000Z

250

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

SciTech Connect

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.

Marshall, William BJ J [ORNL; Rearden, Bradley T [ORNL

2012-01-01T23:59:59.000Z

251

SunShot Initiative: Technology Validation  

NLE Websites -- All DOE Office Websites (Extended Search)

Technology Validation to someone Technology Validation to someone by E-mail Share SunShot Initiative: Technology Validation on Facebook Tweet about SunShot Initiative: Technology Validation on Twitter Bookmark SunShot Initiative: Technology Validation on Google Bookmark SunShot Initiative: Technology Validation on Delicious Rank SunShot Initiative: Technology Validation on Digg Find More places to share SunShot Initiative: Technology Validation on AddThis.com... Concentrating Solar Power Photovoltaics Systems Integration Research, Development, & Demonstration Distribution Grid Integration Transmission Grid Integration Solar Resource Assessment Technology Validation Power Electronics & Balance of System Hardware Technologies Competitive Awards Balance of Systems Technology Validation To reduce solar technology risks, DOE and its partners evaluate the

252

Methodology supporting architecture validations (MAVS)  

Science Conference Proceedings (OSTI)

Defense Information Technology Architecture is a complex business. Furthermore, the multitude and magnitude of the tasks and operations that are executed simultaneously on a battlefield to conduct a single mission are simply staggering. From the performance ... Keywords: DEVS, DoDAF, executable architectures, modeling and simulation, validation

Johnny Garcia

2010-04-01T23:59:59.000Z

253

Directional Validation of Wave Predictions  

Science Conference Proceedings (OSTI)

A methodology for quantitative, directional validation of a long-term wave model hindcast is described and applied. Buoy observations are used as ground truth and the method does not require the application of a parametric model or data-adaptive ...

W. Erick Rogers; David W. C. Wang

2007-03-01T23:59:59.000Z

254

Methodology for Validating Building Energy Analysis Simulations  

SciTech Connect

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.

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

2008-04-01T23:59:59.000Z

255

Validation:  

Science Conference Proceedings (OSTI)

... Measurements. Lewis Publishers: Chelsea, MI, p. 193 Page 15. ... hands. I've trusted system manufacturers to handle this. Should I have? ...

2007-09-07T23:59:59.000Z

256

Sensitivity of crop model predictions to entire meteorological and soil input datasets highlights vulnerability to drought  

Science Conference Proceedings (OSTI)

Crop growth models are increasingly used as part of research into areas such as climate change and bioenergy, so it is particularly important to understand the effects of environmental inputs on model results. Rather than investigating the effects of ... Keywords: Crop growth model, Drought, Input data, Parameterisation, Sensitivity analysis, Soil water

Mark Pogson; Astley Hastings; Pete Smith

2012-03-01T23:59:59.000Z

257

Technical communication: Extending the analog input capabilities of the DS1102 DSP controller board  

Science Conference Proceedings (OSTI)

The paper deals with an extention of the number of analog inputs of the DS1102 controller board which is commonly used in the area of electric machines. Manufactured with just four analog inputs, the DS1102 has been found inadequate for the implementation ... Keywords: Analog multiplexing, Analog to digital converters, Digital signal processor, Doubly-fed machine, Field oriented control

Badreddine Louhichi; Ahmed Masmoudi; Luc Loron

2005-01-01T23:59:59.000Z

258

Simulation for Performance Analysis of Grid-Connected Induction Generators with Input Voltage Control  

Science Conference Proceedings (OSTI)

With the increasing application of wind energy, various technologies are developed for analyzing the performance of grid-connected induction generator (GIG) based wind energy conversion systems (WECSs). Input voltage control is one among them. In the ... Keywords: grid-connected induction generators (GIGs), wind energy conversion systems (WECSs), input voltage control, performance analysis, MATLAB

Farhad Ilahi Bakhsh, Shirazul Islam, Sayeed Ahmad

2013-04-01T23:59:59.000Z

259

Call for White Papers: Soliciting Community Input for Alternate Science Investigations for the Kepler Spacecraft  

E-Print Network (OSTI)

Call for White Papers: Soliciting Community Input for Alternate Science Investigations of this call for white papers is to solicit community input for alternate science investigations that may project office personnel and expertise already in place. All white papers submitted in response

Rodriguez, Carlos

260

SOFTWARE VERIFICATION AND VALIDATION Evaluation of ...  

Science Conference Proceedings (OSTI)

... 5 null 86 "mousedown" true true window 5 5 ... possible input combinations exist to cover even a ... of tests generated in combinatorial covering arrays is ...

2012-10-11T23:59:59.000Z

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


261

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Seeking Input on Alternative Uses of Nickel Inventory 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 assist in DOE's evaluation of restricted uses of its nickel material for controlled radiological applications. These restricted uses could include use in commercial nuclear power plants, DOE nuclear facilities, or by the U.S. Navy. The Department will solicit input through May 8, 2007.

262

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

DOE Seeking Input on Alternative Uses of Nickel Inventory DOE 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 assist in DOE's evaluation of restricted uses of its nickel material for controlled radiological applications. These restricted uses could include use in commercial nuclear power plants, DOE nuclear facilities, or by the U.S. Navy. The Department will solicit input through May 8, 2007.

263

Oak Ridge's EM Program Seeks Public Input on Cleanup | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Seeks Public Input on Cleanup Seeks Public Input on Cleanup Oak Ridge's EM Program Seeks Public Input on Cleanup April 25, 2013 - 12:00pm Addthis Oak Ridge’s EM leadership informed members of the public about projects and goals and answered questions during a public workshop this week. Oak Ridge's EM leadership informed members of the public about projects and goals and answered questions during a public workshop this week. Local residents and other stakeholders listen to Oak Ridge's EM senior leadership in a public workshop to learn about EM and provide input about future mission work. Local residents and other stakeholders listen to Oak Ridge's EM senior leadership in a public workshop to learn about EM and provide input about future mission work. Oak Ridge EM Manager Mark Whitney addresses participants on EM’s mission and priorities.

264

How are basement walls input in REScheck? | Building Energy Codes Program  

NLE Websites -- All DOE Office Websites (Extended Search)

basement walls input in REScheck? basement walls input in REScheck? After selecting a basement wall type, a basement wall illustration will appear with input boxes for the basement wall height, depth below grade, and depth of insulation. The illustration helps identify the dimensions being requested. You may enter basement wall dimensions directly into this illustration and select the OK button to have them transferred to the corresponding row in the table on the Envelope screen. If you prefer to enter the dimensions directly into the table on the Envelope screen, you can select Cancel to remove the illustration without entering dimensions. To view the basement wall illustration and inputs at a later time, click the right-mouse button anywhere on the basement row and select Edit Basement Inputs from the popup menu.

265

Oak Ridge's EM Program Seeks Public Input on Cleanup | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Oak Ridge's EM Program Seeks Public Input on Cleanup Oak Ridge's EM Program Seeks Public Input on Cleanup Oak Ridge's EM Program Seeks Public Input on Cleanup April 25, 2013 - 12:00pm Addthis Oak Ridge’s EM leadership informed members of the public about projects and goals and answered questions during a public workshop this week. Oak Ridge's EM leadership informed members of the public about projects and goals and answered questions during a public workshop this week. Local residents and other stakeholders listen to Oak Ridge's EM senior leadership in a public workshop to learn about EM and provide input about future mission work. Local residents and other stakeholders listen to Oak Ridge's EM senior leadership in a public workshop to learn about EM and provide input about future mission work. Oak Ridge EM Manager Mark Whitney addresses participants on EM’s mission and priorities.

266

Validation of a Hot Water Distribution Model Using Laboratory and Field Data  

SciTech Connect

Characterizing the performance of hot water distribution systems is a critical step in developing best practice guidelines for the design and installation of high performance hot water systems. Developing and validating simulation models is critical to this effort, as well as collecting accurate input data to drive the models. In this project, the ARBI team validated the newly developed TRNSYS Type 604 pipe model against both detailed laboratory and field distribution system performance data. Validation efforts indicate that the model performs very well in handling different pipe materials, insulation cases, and varying hot water load conditions. Limitations of the model include the complexity of setting up the input file and long simulation run times. In addition to completing validation activities, this project looked at recent field hot water studies to better understand use patterns and potential behavioral changes as homeowners convert from conventional storage water heaters to gas tankless units. Based on these datasets, we conclude that the current Energy Factor test procedure overestimates typical use and underestimates the number of hot water draws. This has implications for both equipment and distribution system performance. Gas tankless water heaters were found to impact how people use hot water, but the data does not necessarily suggest an increase in usage. Further study in hot water usage and patterns is needed to better define these characteristics in different climates and home vintages.

Backman, C.; Hoeschele, M.

2013-07-01T23:59:59.000Z

267

Webinar - Software Verification & Validation? - 2012-08-04  

Science Conference Proceedings (OSTI)

Webinar - Software Verification & Validation [1200]. Purpose: Webinar - Software Verification & Validation [1200]. At the ...

2013-06-03T23:59:59.000Z

268

Assessing Forecast Skill through Cross Validation  

Science Conference Proceedings (OSTI)

This study explains the method of cross validation for assessing forecast skill of empirical prediction models. Cross validation provides a relatively accurate measure of an empirical procedure's ability to produce a useful prediction rule from a ...

J. B. Elsner; C. P. Schmertmann

1994-12-01T23:59:59.000Z

269

,"Arkansas Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sar_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sar_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:49 AM"

270

,"Illinois Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sil_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sil_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:51 AM"

271

,"Catalytic Reforming Downstream Processing of Fresh Feed Input"  

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

Catalytic Reforming Downstream Processing of Fresh Feed Input" Catalytic Reforming Downstream Processing of Fresh Feed Input" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Catalytic Reforming Downstream Processing of Fresh Feed Input",16,"Monthly","9/2013","1/15/2010" ,"Release Date:","11/27/2013" ,"Next Release Date:","Last Week of December 2013" ,"Excel File Name:","pet_pnp_dwns_a_(na)_ydr_mbblpd_m.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_pnp_dwns_a_(na)_ydr_mbblpd_m.htm" ,"Source:","Energy Information Administration"

272

,"Pennsylvania Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_spa_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_spa_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:55 AM"

273

,"Iowa Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Iowa Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sia_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sia_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:51 AM"

274

,"Alabama Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sal_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sal_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:49 AM"

275

,"North Dakota Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_snd_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_snd_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:53 AM"

276

,"South Carolina Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Carolina Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_ssc_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_ssc_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:56 AM"

277

,"Massachusetts Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Massachusetts Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sma_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sma_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:52 AM"

278

,"Nevada Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nevada Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_snv_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_snv_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:54 AM"

279

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

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_stx_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_stx_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:56 AM"

280

,"U.S. Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9090us2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9090us2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:57:08 AM"

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


281

,"Colorado Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sco_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sco_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:49 AM"

282

,"Oregon Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sor_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sor_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:55 AM"

283

,"Florida Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sfl_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sfl_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:50 AM"

284

,"Vermont Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Vermont Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_svt_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_svt_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:57 AM"

285

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

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Maine Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sme_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sme_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:52 AM"

286

,"Maryland Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_smd_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_smd_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:52 AM"

287

,"New Jersey Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Jersey Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_snj_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_snj_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:54 AM"

288

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

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Hawaii Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_shi_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_shi_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:51 AM"

289

,"Rhode Island Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Rhode Island Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sri_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sri_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:55 AM"

290

,"Louisiana Natural Gas Input Supplemental Fuels (Million Cubic Feet)"  

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

Input Supplemental Fuels (Million Cubic Feet)" Input Supplemental Fuels (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Input Supplemental Fuels (Million Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","nga_epg0_ovi_sla_mmcfa.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/nga_epg0_ovi_sla_mmcfa.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

291

,"North Carolina Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Carolina Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_snc_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_snc_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:53 AM"

292

,"Alaska Natural Gas Input Supplemental Fuels (Million Cubic Feet)"  

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

Input Supplemental Fuels (Million Cubic Feet)" Input Supplemental Fuels (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Natural Gas Input Supplemental Fuels (Million Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na_epg0_ovi_sak_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na_epg0_ovi_sak_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

293

,"Connecticut Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Connecticut Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sct_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sct_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:50 AM"

294

,"Minnesota Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Minnesota Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_smn_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_smn_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:53 AM"

295

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

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_snm_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_snm_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:54 AM"

296

,"Wyoming Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_swy_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_swy_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:57 AM"

297

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

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Washington Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_swa_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_swa_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:57 AM"

298

,"Wisconsin Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wisconsin Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_swi_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_swi_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:57 AM"

299

,"New Hampshire Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Hampshire Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_snh_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_snh_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:54 AM"

300

,"Kentucky Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sky_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sky_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:51 AM"

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


301

,"Tennessee Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_stn_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_stn_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:56 AM"

302

,"Indiana Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sin_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sin_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:51 AM"

303

,"Michigan Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_smi_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_smi_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:52 AM"

304

,"Virginia Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sva_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sva_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:57 AM"

305

,"Georgia Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Georgia Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sga_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sga_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:50 AM"

306

,"South Dakota Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Dakota Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_ssd_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_ssd_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:56 AM"

307

,"Nebraska Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sne_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sne_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:53 AM"

308

,"Delaware Natural Gas Input Supplemental Fuels (MMcf)"  

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

Input Supplemental Fuels (MMcf)" Input Supplemental Fuels (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Delaware Natural Gas Input Supplemental Fuels (MMcf)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1400_sde_2a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1400_sde_2a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/19/2013 6:58:50 AM"

309

Advanced Encryption Standard Algorithm Validation List  

Science Conference Proceedings (OSTI)

Advanced Encryption Standard Algorithm Validation List. Last Update: 8/28/2013. The page provides technical information ...

310

Process Monitoring & Signal Validation - Nuclear Engineering...  

NLE Websites -- All DOE Office Websites (Extended Search)

Process Monitoring & Signal Validation Capabilities Nuclear Systems Technologies Nuclear Criticality Safety Research Reactor Analysis Decontamination and Decommissioning Systems...

311

Security Testing, Validation and Measurement Group  

Science Conference Proceedings (OSTI)

Security Testing, Validation and Measurement Group. Welcome. ... The overall security of an enterprise network cannot be Contact. ...

2013-01-17T23:59:59.000Z

312

PREDICTING THE TIME RESPONSE OF A BUILDING UNDER HEAT INPUT CONDITIONS FOR ACTIVE SOLAR HEATING SYSTEMS  

E-Print Network (OSTI)

INPUT CONDITIONS FOR ACTIVE SOLAR HEATING SYSTEMS Mashuri L.CONDITIONS FOR ACTIVE SOLAR HEATING SYSTEMS * Mashuri L.consists of a hydronic solar space heating system with heat

Warren, Mashuri L.

2013-01-01T23:59:59.000Z

313

U.S. Crude Input Rising -- Still Need +1 MMB/D Through Mid-Summer  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: Refineries in fourth quarter 1999 and first quarter 2000 were running at fairly low input rates compared to prior years, despite higher demand. U.S. refineries typically increase their crude inputs during the second quarter over the first quarter as they return from maintenance and turnaround schedules to ramp up for the high demand gasoline season. The year began with low refining margins and a low level of crude inputs in January and February. This created a lower base than last year from which to grow into the summer gasoline season, when inputs will need to peak at higher levels than in 1998 or 1999. The good news is that crude runs have been increasing strongly as expected during March the first quarter. Keep in mind that they still need an additional 1 million barrels per day of crude oil between now and mid

314

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

DOE Seeks Public Input on an Integrated, Interagency DOE 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 Federal Register Notice is available now for downloading. Comments must be received on or before September 30, 2013. As comments are received, they will be posted online. The proposed IIP Process is intended to improve interagency and intergovernmental coordination focused on ensuring that project proponents develop and submit accurate and complete information early in the project

315

DOE Seeks Additional Input on Next Generation Nuclear Plant | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Seeks Additional Input on Next Generation Nuclear Plant Seeks Additional Input on Next Generation Nuclear Plant DOE Seeks Additional Input on Next Generation Nuclear Plant April 17, 2008 - 10:49am Addthis WASHINGTON, DC -The U.S. Department of Energy (DOE) today announced it is seeking public and industry input on how to best achieve the goals and meet the requirements for the Next Generation Nuclear Plant (NGNP) demonstration project work at DOE's Idaho National Laboratory. DOE today issued a Request for Information and Expressions of Interest from prospective participants and interested parties on utilizing cutting-edge high temperature gas reactor technology in the effort to reduce greenhouse gas emissions by enabling nuclear energy to replace fossil fuels used by industry for process heat. "This is an opportunity to advance the development of safe, reliable, and

316

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Seeks Public Input on an Integrated, Interagency 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 Federal Register Notice is available now for downloading. Comments must be received on or before September 30, 2013. As comments are received, they will be posted online. The proposed IIP Process is intended to improve interagency and intergovernmental coordination focused on ensuring that project proponents develop and submit accurate and complete information early in the project

317

Documentation of Calculation Methodology, Input data, and Infrastructure for the Home Energy Saver Web Site  

E-Print Network (OSTI)

Water Heater Analysis. 26 3.3 Major Appliances 28 3.3.1 Refrigerator Energy Consumption . 28 3.3.1.1 User Inputs to the Refrigerator Model .

2005-01-01T23:59:59.000Z

318

Using Genetic Algorithms to Optimize Bathymetric Sampling for Predictive Model Input  

Science Conference Proceedings (OSTI)

This paper describes the use of an optimization method to effectively reduce the required bathymetric sampling for forcing a numerical forecast model by using the models sensitivity to this input. A genetic algorithm is developed to gradually ...

Dinesh Manian; James M. Kaihatu; Emily M. Zechman

2012-03-01T23:59:59.000Z

319

Documentation of Calculation Methodology, Input data, and Infrastructure for the Home Energy Saver Web Site  

E-Print Network (OSTI)

U.S. Census Bureau. 2004. ZIP Code Tabulation Area (ZCTA)4 Figure 2. Initial Simple Inputs Page with ZIP Code BasedGreg Homan, Maggie Pinckard Zip code to Weather Tape

2005-01-01T23:59:59.000Z

320

On the Patterns of Wind-Power Input to the Ocean Circulation  

E-Print Network (OSTI)

Pathways of wind-power input into the ocean general circulation are analyzed using Ekman theory. Direct rates of wind work can be calculated through the wind stress acting on the surface geostrophic flow. However, because ...

Roquet, Fabien

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


321

On the Patterns of Wind-Power Input to the Ocean Circulation  

Science Conference Proceedings (OSTI)

Pathways of wind-power input into the ocean general circulation are analyzed using Ekman theory. Direct rates of wind work can be calculated through the wind stress acting on the surface geostrophic flow. However, because that energy is ...

Fabien Roquet; Carl Wunsch; Gurvan Madec

2011-12-01T23:59:59.000Z

322

Three papers on input-ouput [sic] energy and environmental accounting  

E-Print Network (OSTI)

The input-output model, a framework for national accounting and economic modeling, has been popular among regional economists for studying energy and emissions due to its focus on interindustry linkages. In a series of ...

Huang, Sonya (Sonya Y.)

2013-01-01T23:59:59.000Z

323

Table 16. Refinery Input of Crude Oil and Petroleum Products by ...  

U.S. Energy Information Administration (EIA)

Atmospheric Crude Oil Distillation Gross Input (daily average) ..... 575 3,599 2,900 142 81 7,297 531 2,872 15,508 Operable Capacity (daily ...

324

New continuous-input current charge pump power-factor-correction electronic ballast  

SciTech Connect

Continuous-input current charge pump power-factor-correction (CIC-CPPFC) electronic ballasts are proposed in this paper. The CPPFC circuit and unity power factor condition using the charge pump concept are derived and analyzed. The average lamp current control with switching frequency modulation was developed so that the low crest factor and constant lamp power operation can be achieved. The developed electronic ballast has continuous input current, so that a small line input filter can be used. The proposed CIC-CPPFC electronic ballast was implemented and tested with two 45-W fluorescent lamps. It is shown that the measured line input current harmonics satisfy IEC 1000-3-2 Class C requirements.

Qian, J.; Lee, F.C. [Virginia Polytechnic Inst. and State Univ., Blacksburg, VA (United States); Yamauchi, Tokushi [Matsushita Electric Works, Ltd., Osaka (Japan). Lighting Research and Development Center

1999-03-01T23:59:59.000Z

325

Table A31. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1991" " (Continued)" " (Estimates in Trillion Btu)",,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"

326

Table A54. Number of Establishments by Total Inputs of Energy for Heat, Powe  

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

Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of General Technologies, 1994: Part 2" ,," "," ",," "," ",," "," "," "," " ,,,,"Computer Control" ,," "," ","of Processes"," "," ",," "," ",," " ,," ","Computer Control","or Major",,,"One or More"," ","RSE" "SIC"," ",,"of Building","Energy-Using","Waste Heat"," Adjustable-Speed","General Technologies","None","Row"

327

Table A45. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Enclosed Floorspace, Percent Conditioned Floorspace, and Presence of Computer" " Controls for Building Environment, 1991" " (Estimates in Trillion Btu)" ,,"Presence of Computer Controls" ,," for Buildings Environment",,"RSE" "Enclosed Floorspace and"," ","--------------","--------------","Row" "Percent Conditioned Floorspace","Total","Present","Not Present","Factors" " "," " "RSE Column Factors:",0.8,1.3,0.9 "ALL SQUARE FEET CATEGORIES" "Approximate Conditioned Floorspace"

328

Review: Independent component analysis for multiple-input multiple-output wireless communication systems  

Science Conference Proceedings (OSTI)

Independent component analysis (ICA), an efficient higher order statistics (HOS) based blind source separation technique, has been successfully applied in various fields. In this paper, we provide an overview of the applications of ICA in multiple-input ... Keywords: Frequency-domain equalization (FDE), I/Q imbalance, Independent component analysis (ICA), Multiple-input multiple-output (MIMO), Orthogonal frequency-division multiplexing (OFDM), Peak-to-average power ratio (PAPR)

J. Gao; X. Zhu; A. K. Nandi

2011-04-01T23:59:59.000Z

329

Validation of an Integrated Hydrogen Energy Station  

SciTech Connect

This report presents the results of a 10-year project conducted by Air Products and Chemicals, Inc. (Air Products) to determine the feasibility of coproducing hydrogen with electricity. The primary objective was to demonstrate the technical and economic viability of a hydrogen energy station using a high-temperature fuel cell designed to produce power and hydrogen. This four-phase project had intermediate go/no-go decisions and the following specific goals: ?¢???¢ Complete a technical assessment and economic analysis of the use of high-temperature fuel cells, including solid oxide and molten carbonate, for the co-production of power and hydrogen (energy park concept). ?¢???¢ Build on the experience gained at the Las Vegas H2 Energy Station and compare/contrast the two approaches for co-production. ?¢???¢ Determine the applicability of co-production from a high-temperature fuel cell for the existing merchant hydrogen market and for the emerging hydrogen economy. ?¢???¢ Demonstrate the concept on natural gas for six months at a suitable site with demand for both hydrogen and electricity. ?¢???¢ Maintain safety as the top priority in the system design and operation. ?¢???¢ Obtain adequate operational data to provide the basis for future commercial activities, including hydrogen fueling stations. Work began with the execution of the cooperative agreement with DOE on 30 September 2001. During Phase 1, Air Products identified high-temperature fuel cells as having the potential to meet the coproduction targets, and the molten carbonate fuel cell system from FuelCell Energy, Inc. (FuelCell Energy) was selected by Air Products and DOE following the feasibility assessment performed during Phase 2. Detailed design, construction and shop validation testing of a system to produce 250 kW of electricity and 100 kilograms per day of hydrogen, along with site selection to include a renewable feedstock for the fuel cell, were completed in Phase 3. The system also completed six months of demonstration operation at the 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.

Edward C. Heydorn

2012-10-26T23:59:59.000Z

330

Benchmarks for GADRAS performance validation.  

SciTech Connect

The performance of the Gamma Detector Response and Analysis Software (GADRAS) was validated by comparing GADRAS model results to experimental measurements for a series of benchmark sources. Sources for the benchmark include a plutonium metal sphere, bare and shielded in polyethylene, plutonium oxide in cans, a highly enriched uranium sphere, bare and shielded in polyethylene, a depleted uranium shell and spheres, and a natural uranium sphere. The benchmark experimental data were previously acquired and consist of careful collection of background and calibration source spectra along with the source spectra. The calibration data were fit with GADRAS to determine response functions for the detector in each experiment. A one-dimensional model (pie chart) was constructed for each source based on the dimensions of the benchmark source. The GADRAS code made a forward calculation from each model to predict the radiation spectrum for the detector used in the benchmark experiment. The comparisons between the GADRAS calculation and the experimental measurements are excellent, validating that GADRAS can correctly predict the radiation spectra for these well-defined benchmark sources.

Mattingly, John K.; Mitchell, Dean James; Rhykerd, Charles L., Jr.

2009-09-01T23:59:59.000Z

331

Validation Workshop Developmental Validation Aug. 24, 2005 at NFSTC Prepared by John M. Butler 1  

E-Print Network (OSTI)

Validation? · Who? (SWGDAM Revised Validation Guidelines 1.2.1) ­ Manufacturer ­ Technical Organization http://www.fbi.gov/hq/lab/fsc/backissu/july2004/standards/2004_03_standards02.htm #12;Validation manual. SWGDAM Revised Validation Guidelines http://www.fbi.gov/hq/lab/fsc/backissu/july2004/standards

332

FIMS Data Validation Schedule FY 2010_090729.xls | Department...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

FIMS Data Validation Schedule FY 2010090729.xls FIMS Data Validation Schedule FY 2010090729.xls FIMS Data Validation Schedule FY 2010090729.xls More Documents & Publications...

333

Reliable Solution of a Unilateral Frictionless Contact Problem in Quasi-Coupled Thermo-Elasticity with Uncertain Input Data  

Science Conference Proceedings (OSTI)

A unilateral contact problem without friction in quasi-coupled thermo-elasticity and with uncertain input data is analysed. The worst scenario method is used to find the most "dangerous" admissible input data.

Ivan Hlavcek; Jir Nedoma

2002-04-01T23:59:59.000Z

334

Estimates of wind energy input to the Ekman layer in the Southern Ocean from surface drifter data  

E-Print Network (OSTI)

Estimates of wind energy input to the Ekman layer in the Southern Ocean from surface drifter data the contribution from the anticyclonic frequencies dominate the wind energy input. The latitudinal and seasonal variations of the wind energy input to the Ekman layer are closely related to the variations of the wind

Gille, Sarah T.

335

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

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

Annual",2012,"6/30/1987" Annual",2012,"6/30/1987" ,"Release Date:","9/27/2013" ,"Next Release Date:","9/26/2014" ,"Excel File Name:","pet_pnp_dwns_dc_nus_mbblpd_a.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_pnp_dwns_dc_nus_mbblpd_a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov" ,,"(202) 586-8800",,,"11/25/2013 11:17:28 AM" "Back to Contents","Data 1: U.S. Downstream Processing of Fresh Feed Input" "Sourcekey","M_NA_YDR_NUS_MBBLD","MCRCCUS2","MCRCHUS2","MCRDFUS2" "Date","U.S. Downstream Processing of Fresh Feed Input by Catalytic Reforming Units (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 by Catalytic Hydrocracking Units (Thousand Barrels per Day)","U.S. Downstream Processing of Fresh Feed Input by Delayed and Fluid Coking Units (Thousand Barrels per Day)"

336

Hydromechanical transmission with two planetary assemblies that are clutchable to both the input and output shafts  

DOE Patents (OSTI)

A power transmission having two planetary assemblies, each having its own carrier and its own planet, sun, and ring gears. A speed-varying module is connected in driving relation to the input shaft and in driving relationship to the two sun gears, which are connected together. The speed-varying means may comprise a pair of hydraulic units hydraulically interconnected so that one serves as a pump while the other serves as a motor and vice versa, one of the units having a variable stroke and being connected in driving relation to the input shaft, the other unit, which may have a fixed stroke, being connected in driving relation to the sun gears. A brake grounds the first carrier in the first range and in reverse and causes drive to be delivered to the output shaft through the first ring gear in a hydrostatic mode, the first ring gear being rigidly connected to the output shaft. The input shaft also is clutchable to either the carrier or the ring gear of the second planetary assembly. The output shaft is also clutchable to the carrier of the second planetary assembly when the input is clutched to the ring gear of the second planetary assembly, and is clutchable to the ring gear of the second planetary assembly when the input is clutched to the carrier thereof.

Orshansky, Jr., deceased, Elias (LATE OF San Francisco, CA); Weseloh, William E. (San Diego, CA)

1979-01-01T23:59:59.000Z

337

FIMS Data Validation | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Operational Management » Facilities and Infrastructure » FIMS Operational Management » Facilities and Infrastructure » 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 be accurately populated and validated once each fiscal year between December 15th and June 30th. The desired outcome of the validation program is to demonstrate, at a 90% confidence level, that the validated FIMS data elements are being

338

FIMS Data Validation | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Information Systems » FIMS Data 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 be accurately populated and validated once each fiscal year between December 15th and June 30th. The desired outcome of the validation program is to demonstrate, at a 90% confidence level, that the validated FIMS data elements are being maintained without material variance when compared to known accurate source

339

The FIPS 186-4 Digital Signature Algorithm Validation System ...  

Science Conference Proceedings (OSTI)

... pass for formal validation, and general instruction for interfacing ... 5 Design Philosophy of the Digital Signature Algorithm Validation System ...

2013-09-17T23:59:59.000Z

340

Southeast Regional Carbon Sequestration Partnership--Validation...  

NLE Websites -- All DOE Office Websites (Extended Search)

Southeast Regional Carbon Sequestration Partnership-Validation Phase Background The U.S. Department of Energy (DOE) has selected seven partnerships, through its Regional Carbon...

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


341

Incremental validity of the Psychopathic Personality Inventory.  

E-Print Network (OSTI)

??The current study examined the incremental validity of the Psychopathic Personality Inventory-Revised in relation to the Psychological Inventory of Criminal Thinking Styles and Personality Assessment (more)

McCoy, Katrina.

2011-01-01T23:59:59.000Z

342

Security Content Automation Protocol Validated Products  

Science Conference Proceedings (OSTI)

... Validation Date. Expiration Date. 104, CIS - Configuration Audit Tool, 2.2.0, Microsoft Windows XP Professional SP3: Domain-joined and Standalone ...

343

MIT validation probe acceptance test procedure  

SciTech Connect

As part of the Multi-Functional Instrument Trees (MITs) a Validation Probe is being fabricated by Los Alamos National Laboratories (LANL). The Validation Probe assembly is equipped with a Winch, depth counter, and a Resistance Temperature Detector (RTD) which will render a means for verifying the temperature readings of which will render a means for verifying the temperature readings of the MIT thermocouples. The purpose of this Acceptance Test Procedure (ATP) is to provide verification that the Validation Probe functions properly and accordingly to LANL design and specification. This ATP will be used for all Validation Probes procured from LANL. The ATP consists of a receiving inspection, RTD ambient temperature; RTD electrical failure, RTD insulation resistance, and accurate depth counter operation inspections. The Validation Probe is composed of an intank probe, a cable and winching system, and a riser extension (probe guide) which bolts onto the MIT. The validation`s thermal sensor is an RTD that is housed in a 0.062 inch diameter, magnesium oxide fill, 316 stainless steel tube. The sheath configuration provides a means for spring loading the sensor firmly against the validation tube`s inner wall. A 45 pound cylindrical body is connected above the sheath and is used as a force to lower the probe into the tank. This cylindrical body also provides the means to interconnect both electrically and mechanically to the winch system which lowers the probe to a specified location within the validation tube located in the tank.

Escamilla, S.A.

1994-08-23T23:59:59.000Z

344

Fuel Cell Backup Power Technology Validation (Presentation)  

DOE Green Energy (OSTI)

Presentation about fuel cell backup power technology validation activities at the U.S. Department of Energy's National Renewable Energy Laboratory.

Kurtz, J.; Sprik, S.; Ramsden, T.; Saur, G.

2012-10-01T23:59:59.000Z

345

,"Sulfur Content, Weighted Average Refinery Crude Oil Input Qualities"  

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

Sulfur Content, Weighted Average Refinery Crude Oil Input Qualities" Sulfur Content, Weighted Average Refinery Crude Oil Input Qualities" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Sulfur Content, Weighted Average Refinery Crude Oil Input Qualities",16,"Monthly","9/2013","1/15/1985" ,"Release Date:","11/27/2013" ,"Next Release Date:","Last Week of December 2013" ,"Excel File Name:","pet_pnp_crq_a_epc0_ycs_pct_m.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_pnp_crq_a_epc0_ycs_pct_m.htm" ,"Source:","Energy Information Administration"

346

USDA, Departments of Energy and Navy Seek Input from Industry to Advance  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

USDA, Departments of Energy and Navy Seek Input from Industry to USDA, Departments of Energy and Navy Seek Input from 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 Commercial Transportation August 30, 2011 - 12:23pm Addthis WASHINGTON, Aug. 30, 2011 -Secretary of Agriculture Tom Vilsack, Secretary of Energy Steven Chu, and Secretary of the Navy Ray Mabus today announced the next step in the creation of a public-private partnership to develop drop-in advanced biofuels. The Secretaries issued a Request for Information (RFI) laying out the Administration's goals, assumptions, and tools and requesting from industry specific ideas for how to leverage private capital markets to establish a commercially viable drop-in biofuels

347

DEPARTMENT OF ENERGY SOLICITS PUBLIC INPUT TO INFORM DEVELOPMENT OF A  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

DEPARTMENT OF ENERGY SOLICITS PUBLIC INPUT TO INFORM DEVELOPMENT OF DEPARTMENT OF ENERGY SOLICITS PUBLIC INPUT TO INFORM DEVELOPMENT OF A PREFERRED ALTERNATIVE FOR DISPOSAL OF GREATER-THAN-CLASS C WASTE DEPARTMENT OF ENERGY SOLICITS PUBLIC INPUT TO INFORM DEVELOPMENT OF A PREFERRED ALTERNATIVE FOR DISPOSAL OF GREATER-THAN-CLASS C WASTE March 1, 2011 - 12:00pm Addthis During the months of April and May, 2011 the Department of Energy's Office of Environmental Management will be holding nine public hearings on the Draft Environmental Impact Statement (EIS) for the Disposal of Greater-Than-Class C (GTCC) Low-Level Radioactive Waste and GTCC-Like Waste. Hearings will be held at the each of the sites being considered for disposal of GTCC wastes and in Washington, DC. DOE does not have a preferred alternative at this time. These hearings will

348

DOE Seeks Further Public Input on How Best To Streamline Existing  

NLE Websites -- All DOE Office Websites (Extended Search)

Further Public Input on How Best To Streamline Existing Further Public Input on How Best To Streamline Existing Regulations DOE Seeks Further Public Input on How Best To Streamline Existing Regulations December 7, 2011 - 12:34pm Addthis The Department of Energy (DOE) has announced a further step to implementing the President's Executive Order on Improving Regulatory Review. The Executive Order directs federal agencies to review existing regulations and determine whether they are still necessary and crafted effectively to solve current problems. Engaging the public in an open, transparent process is a crucial step in DOE's regulatory review process. Because public comments in response to the Request for Information (RFI) issued in January were important in the development of DOE's plan for retrospective regulatory review, DOE issued a second RFI this week asking the public how

349

Criticality Safety Validation of Scale 6.1  

SciTech Connect

The computational bias of criticality safety computer codes must be established through the validation of the codes to critical experiments. A large collection of suitable experiments has been vetted by the International Criticality Safety Benchmark Experiment Program (ICSBEP) and made available in the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE). A total of more than 350 cases from this reference have been prepared and reviewed within the Verified, Archived Library of Inputs and Data (VALID) maintained by the Reactor and Nuclear Systems Division at Oak Ridge National Laboratory. The performance of the KENO V.a and KENO-VI Monte Carlo codes within the Scale 6.1 code system with ENDF/B-VII.0 cross-section data in 238-group and continuous energy is assessed using the VALID models of benchmark experiments. The TSUNAMI tools for sensitivity and uncertainty analysis are utilized to examine some systems further in an attempt to identify potential causes of unexpected results. The critical experiments available for validation of the KENO V.a code cover eight different broad categories of systems. These systems use a range of fissile materials including a range of uranium enrichments, various plutonium isotopic vectors, and mixed uranium-plutonium oxides. The physical form of the fissile material also varies and is represented as metal, solutions, or arrays of rods or plates in a water moderator. The neutron energy spectra of the systems also vary and cover both fast and thermal spectra. Over 300 of the total cases used utilize the KENO V.a code. The critical experiments available for the validation of the KENO-VI code cover three broad categories of systems. The fissile materials in the systems vary and include high and intermediate-enrichment uranium and mixed uranium/plutonium oxides. The physical form of the fissile material is either metal or rod arrays in water. As with KENO V.a, both fast and thermal neutron energy spectra are represented in the systems considered. The results indicate generally good performance of both the KENO V.a and KENO-VI codes across the range of systems analyzed. The bias of calculated k{sub eff} from expected values is less than 0.9% {Delta}k in all cases. All eight categories of experiments show biases of less than 0.5% {Delta}k in KENO V.a with the exception of intermediate enrichment metal systems using the 238-group library. The continuous energy library generally manifests lower biases than the multi-group data. The KENO-VI results show slightly larger biases, though this may primarily be the result of modeling systems with more geometric complexity, which are more difficult to describe accurately, even with a generalized geometry code like KENO-VI. Several additional conclusions can be drawn from the results of this validation effort. These conclusions include that the TSUNAMI tools can be used successfully to explain the cause of aberrant results, that some evaluations in the IHECSBE should be updated to provide more rigorous expected k{sub eff} values and uncertainties, and that potential cross-section errors can be identified by detailed review of the results of this validation. It also appears that the overall cross-section uncertainty as quantified through the Scale covariance library is overestimated. Overall, the KENO V.a and KENO-VI codes are shown to provide consistent, low bias results for a wide range of physical systems of potential interest in criticality safety applications.

Marshall, William BJ J [ORNL; Rearden, Bradley T [ORNL

2011-11-01T23:59:59.000Z

350

Development of the fundamental attributes and inputs for proliferation resistance assessments of nuclear fuel cycles  

E-Print Network (OSTI)

Robust and reliable quantitative proliferation resistance assessment tools are critical to a strengthened nonproliferation regime and to the future deployment of nuclear fuel cycle technologies. Efforts to quantify proliferation resistance have thus far met with limited success due to the inherent subjectivity of the problem and interdependencies between attributes that contribute to proliferation resistance. This work focuses on the diversion of nuclear material by a state and defers other threats such as theft or terrorism to future work. A new approach is presented that assesses the problem through four stages of proliferation: the diversion of nuclear material, the transportation of nuclear material from an internationally safeguarded nuclear facility to an undeclared facility, the transformation of material into a weapons-usable metal, and weapon fabrication. A complete and concise set of intrinsic and extrinsic attributes of the nation, facility and material that could impede proliferation are identified. Quantifiable inputs for each of these attributes are defined. For example, the difficulty of handling the diverted material is captured with inputs like mass and bulk, radiation dose, heating rate and others. Aggregating these measurements into an overall value for proliferation resistance can be done in multiple ways based on well-developed decision theory. A preliminary aggregation scheme is provided along with results obtained from analyzing a small spent fuel reprocessing plant to demonstrate quantification of the attributes and inputs. This quantification effort shows that the majority of the inputs presented are relatively straightforward to work with while a few are not. These few difficult inputs will only be useful in special cases where the analyst has access to privileged, detailed or classified information. The stages, attributes and inputs of proliferation presented in this work provide a foundation for proliferation resistance assessments which may use multiple types of aggregation schemes. The overall results of these assessments are useful in comparing nuclear technologies and aiding decisions about development and deployment of that technology.

Giannangeli, Donald D. J., III

2003-05-01T23:59:59.000Z

351

ISOTHERMAL AIR INGRESS VALIDATION EXPERIMENTS  

SciTech Connect

Idaho National Laboratory carried out air ingress experiments as part of validating computational fluid dynamics (CFD) calculations. An isothermal test loop was designed and set to understand the stratified-flow phenomenon, which is important as the initial air flow into the lower plenum of the very high temperature gas cooled reactor (VHTR) when a large break loss-of-coolant accident occurs. The unique flow characteristics were focused on the VHTR air-ingress accident, in particular, the flow visualization of the stratified flow in the inlet pipe to the vessel lower plenum of the General Atomics Gas Turbine-Modular Helium Reactor (GT-MHR). Brine and sucrose were used as heavy fluids, and water was used to represent a light fluid, which mimics a counter current flow due to the density difference between the stimulant fluids. The density ratios were changed between 0.87 and 0.98. This experiment clearly showed that a stratified flow between simulant fluids was established even for very small density differences. The CFD calculations were compared with experimental data. A grid sensitivity study on CFD models was also performed using the Richardson extrapolation and the grid convergence index method for the numerical accuracy of CFD calculations . As a result, the calculated current speed showed very good agreement with the experimental data, indicating that the current CFD methods are suitable for predicting density gradient stratified flow phenomena in the air-ingress accident.

Chang H Oh; Eung S Kim

2011-09-01T23:59:59.000Z

352

Table A56. Number of Establishments by Total Inputs of Energy for Heat, Powe  

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

Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of Industry-Specific Technologies for Selected Industries, 1994: Part 2" ,,,"RSE" "SIC",,,"Row" "Code(a)","Industry Group and Industry","Total(b)","Factors" ,"RSE Column Factors:",1 20,"FOOD and KINDRED PRODUCTS" ,"Industry-Specific Technologies" ,"One or More Industry-Specific Technologies Present",2353,9 ," Infrared Heating",607,13 ," Microwave Drying",127,21 ," Closed-Cycle Heat Pump System Used to Recover Heat",786,19

353

Table A13. Selected Combustible Inputs of Energy for Heat, Power, and  

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

3. Selected Combustible Inputs of Energy for Heat, Power, and" 3. Selected Combustible Inputs of Energy for Heat, Power, and" " Electricity Generation and Net Demand for Electricity by Fuel Type," " Census Region, Census Division, and End Use, 1994: Part 1" " (Estimates in Btu or Physical Units)" ,,,,,,"Coal" ,,,"Distillate",,,"(excluding" ,"Net Demand",,"Fuel Oil",,,"Coal Coke" ,"for","Residual","and","Natural Gas(c)",,"and Breeze)","RSE" ,"Electricity(a)","Fuel Oil","Diesel Fuel(b)","(billion","LPG","(1000 short","Row"

354

Table A15. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry Group and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors" ,"RSE Column Factors:",0.6,1.3,1,1,0.9,1.2,1.2

355

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" 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 Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.3,1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",10743,1150,2819,5309,1464,2.6,,,"/WIR{D}~"

356

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" 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 Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.2,1.1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",12605,1209,3303,6386,1706,2.9

357

Table A55. Number of Establishments by Total Inputs of Energy for Heat, Powe  

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

Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of Cogeneration Technologies, 1994: Part 2" ,,,"Steam Turbines",,,,"Steam Turbines" ,," ","Supplied by Either","Conventional",,,"Supplied by","One or More",," " " "," ",,"Conventional","Combustion ","Combined-Cycle","Internal Combustion","Heat Recovered from","Cogeneration",,"RSE" "SIC"," ",,"or Fluidized","Turbines with","Combustion","Engines with","High-Temperature","Technologies","None","Row"

358

Table A39. Selected Combustible Inputs of Energy for Heat, Power, and  

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

9. Selected Combustible Inputs of Energy for Heat, Power, and" 9. Selected Combustible Inputs of Energy for Heat, Power, and" " Electricity Generation and Net Demand for Electricity by Fuel Type, Census" " Region, and End Use, 1991: Part 2" " (Estimates in Trillion Btu)" ,,,"Distillate",,,"Coal" ,"Net Demand",,"Fuel Oil",,,"(excluding","RSE" ,"for","Residual","and",,,"Coal Coke","Row" "End-Use Categories","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Natural Gas(c)","LPG","and Breeze)","Factors" "Total United States" "RSE Column Factors:",0.4,1.7,1.5,0.7,1,1.6

359

STARS: Sign tracking and recognition system using input-output HMMs  

Science Conference Proceedings (OSTI)

STARS is a vision based real time gestural interface that allows both communicative and manipulative 3D hand gestures, which vary in motion and appearance, to control target generic personal computer applications. This input-output HMM based framework ... Keywords: Adaptive threshold model, Gesture spotting, HCI, HCRF, Hand gesture recognition, IOHMM

C. Keskin; L. Akarun

2009-09-01T23:59:59.000Z

360

Energy conservation and power consumption analysis in China based on input-output method  

Science Conference Proceedings (OSTI)

To achieve the sustainable development of society, the 11th five-year plan of national economic and social development of China raised the energy-saving target of decreasing 20% energy consumption per unit GDP in 2010 than the end of 2005. Based on the ... Keywords: energy intensity, energy-saving, input-output model, power demand

He Yong-Xiu; Zhang Song-Lei; Tao Wei-Jun; Li Fu-Rong

2008-02-01T23:59:59.000Z

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


361

Multi-Input Floating Gate Differential Amplifier and Application to Intelligent Sensors  

Science Conference Proceedings (OSTI)

Multi-input floating gate differential amplifier (FGDA) is proposed which can perform any convolution operation with differential structure and feedback loop. All operations are in the voltage mode. Only one terminal is required for the negative feedback ... Keywords: DCT, floating gate, image compression, image sensor, signal processing

Takeyasu Sakai; Hiromasa Nagai; Takashi Matsumoto

2000-12-01T23:59:59.000Z

362

A Tight Lower Bound to the Outage Probability of Discrete-Input Block-Fading Channels  

Science Conference Proceedings (OSTI)

In this correspondence, a tight lower bound to the outage probability of discrete-input Nakagami-m block-fading channels is proposed. The approach permits an efficient method for numerical evaluation of the bound, providing an additional tool for system ... Keywords: Block-fading channel, diversity, error probability, outage probability, rate-diversity tradeoff, signal-to-noise ratio (SNR)-exponent

K. D. Nguyen; A. Guillen i Fabregas; L. K. Rasmussen

2007-11-01T23:59:59.000Z

363

Algorithm for stochastic approximation with trial input perturbation in the nonstationary problem of optimization  

Science Conference Proceedings (OSTI)

Consideration was given to the randomized stochastic approximation algorithm with simultaneous trial input perturbation and two measurements used to optimize the unconstrained nonstationary functional. The upper boundary of the mean-square residual was ... Keywords: 02.50.Sk, 02.60.Pn

A. T. Vakhitov; O. N. Granichin; L. S. Gurevich

2009-11-01T23:59:59.000Z

364

Unknown input estimation for a class of nonlinear systems and its application to automotive engine controls  

Science Conference Proceedings (OSTI)

System unmodeled dynamics and uncertainties are common issues in the design of model based controllers and observers. One way to deal with this is to design an unknown input observer to estimate those unknown variables. However it is not feasible, if ...

Chia-Shang Liu; Pingan He

2009-06-01T23:59:59.000Z

365

Distributed model-invariant detection of unknown inputs in networked systems  

Science Conference Proceedings (OSTI)

This work considers hypothesis testing in networked systems under severe lack of prior knowledge. In previous work we derived a centralized Uniformly Most Powerful Invariant (UMPI) approach to testing unknown inputs in unknown Linear Time Invariant (LTI) ... Keywords: invariant testing, networked systems

James Weimer; Damiano Varagnolo; Karl Henrik Johansson

2013-04-01T23:59:59.000Z

366

A condition-based maintenance policy and input parameters estimation for deteriorating systems under periodic inspection  

Science Conference Proceedings (OSTI)

This paper combines an optimization model and input parameters estimation from empirical data, in order to propose condition-based maintenance policies. The system deterioration is described by discrete states ordered from the state ''as good as new'' ... Keywords: Condition-based maintenance, Decision-making under uncertainty, Hidden Markov Models, Optimal control, Stochastic-dynamic programming

Maxstaley L. Neves; Leonardo P. Santiago; Carlos A. Maia

2011-10-01T23:59:59.000Z

367

U.S. Gross Inputs to Refineries (Thousand Barrels per Day)  

U.S. Energy Information Administration (EIA)

U.S. Gross Inputs to Refineries (Thousand Barrels per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1985: 11,583: 11,485: 11,484: 11,969: 12,269: 12,422 ...

368

On the Value of Input Efficiency, Capacity Efficiency, and the Flexibility to Rebalance Them  

Science Conference Proceedings (OSTI)

A common characteristic of basic material manufacturers which account for 85% of all industrial energy use and of cleantech manufacturers is that they are price takers in their input and output markets. Variability in those prices has implications for ... Keywords: energy efficiency, environment, flexibility, process improvement

Erica L. Plambeck, Terry A. Taylor

2013-10-01T23:59:59.000Z

369

Documentation of Calculation Methodology, Input data, and Infrastructure for the Home Energy Saver Web Site  

E-Print Network (OSTI)

Heating Equipment, Mobile Home Furnaces, Kitchen Ranges and Ovens,Oven fuel Climate zone Year house was built Number of stories HeatingHeating Energy. 36 3.3.5.3 User Inputs to the Dishwasher Models 37 3.3.6 Stove and Oven

2005-01-01T23:59:59.000Z

370

Personalized input: improving ten-finger touchscreen typing through automatic adaptation  

Science Conference Proceedings (OSTI)

Although typing on touchscreens is slower than typing on physical keyboards, touchscreens offer a critical potential advantage: they are software-based, and, as such, the keyboard layout and classification models used to interpret key presses can dynamically ... Keywords: adaptive interfaces, personalization, touchscreen text input

Leah Findlater; Jacob Wobbrock

2012-05-01T23:59:59.000Z

371

Nuclear norm system identification with missing inputs and outputs Zhang Liua,  

E-Print Network (OSTI)

Nuclear norm system identification with missing inputs and outputs Zhang Liua, , Anders Hanssonb,1 formulation and uses the nuclear norm heuristic for structured low-rank matrix approximation, with the missing of the alternating direc- tion method of multipliers (ADMM) to solve regularized or non-regularized nuclear norm

Vandenberghe, Lieven

372

Input Feature Extraction for Multilayered Perceptrons Using Supervised Principal Component Analysis  

Science Conference Proceedings (OSTI)

A method is proposed for constructing salient features from a set of features that are given as input to a feedforward neural network used for supervised learning. Combinations of the original features are formed that maximize the sensitivity of ... Keywords: feature extraction, feature selection, multilayered perceptron, principal components, saliency

Stavros J. Perantonis; Vassilis Virvilis

1999-12-01T23:59:59.000Z

373

Truncated predictor feedback for linear systems with long time-varying input delays  

Science Conference Proceedings (OSTI)

In this paper we study the problem of stabilizing a linear system with a single long time-varying delay in the input. Under the assumption that the open-loop system is stabilizable and not exponentially unstable, a finite dimensional static time-varying ... Keywords: Actuator saturation, Energy constraints, Semi-global stabilization, Stabilization, Time-varying delay, Truncated predictor feedback

Bin Zhou; Zongli Lin; Guang-Ren Duan

2012-10-01T23:59:59.000Z

374

Analytical input-output and supply chain study of China's coke and steel sectors  

E-Print Network (OSTI)

I design an input-output model to investigate the energy supply chain of coal-coke-steel in China. To study the demand, supply, and energy-intensity issues for coal and coke from a macroeconomic perspective, I apply the ...

Li, Yu, 1976-

2004-01-01T23:59:59.000Z

375

Using Economic Input/Output Tables to Predict a Countrys Nuclear Status  

Science Conference Proceedings (OSTI)

Both nuclear power and nuclear weapons programs should have (related) economic signatures which are detectible at some scale. We evaluated this premise in a series of studies using national economic input/output (IO) data. Statistical discrimination models using economic IO tables predict with a high probability whether a country with an unknown predilection for nuclear weapons proliferation is in fact engaged in nuclear power development or nuclear weapons proliferation. We analyzed 93 IO tables, spanning the years 1993 to 2005 for 37 countries that are either members or associates of the Organization for Economic Cooperation and Development (OECD). The 2009 OECD input/output tables featured 48 industrial sectors based on International Standard Industrial Classification (ISIC) Revision 3, and described the respective economies in current country-of-origin valued currency. We converted and transformed these reported values to US 2005 dollars using appropriate exchange rates and implicit price deflators, and addressed discrepancies in reported industrial sectors across tables. We then classified countries with Random Forest using either the adjusted or industry-normalized values. Random Forest, a classification tree technique, separates and categorizes countries using a very small, select subset of the 2304 individual cells in the IO table. A nations efforts in nuclear power, be it for electricity or nuclear weapons, are an enterprise with a large economic footprint -- an effort so large that it should discernibly perturb coarse country-level economics data such as that found in yearly input-output economic tables. The neoclassical economic input-output model describes a countrys or regions economy in terms of the requirements of industries to produce the current level of economic output. An IO table row shows the distribution of an industrys output to the industrial sectors while a table column shows the input required of each industrial sector by a given industry.

Weimar, Mark R.; Daly, Don S.; Wood, Thomas W.

2010-07-15T23:59:59.000Z

376

Estimating uncertainty of inference for validation  

SciTech Connect

We present a validation process based upon the concept that validation is an inference-making activity. This has always been true, but the association has not been as important before as it is now. Previously, theory had been confirmed by more data, and predictions were possible based on data. The process today is to infer from theory to code and from code to prediction, making the role of prediction somewhat automatic, and a machine function. Validation is defined as determining the degree to which a model and code is an accurate representation of experimental test data. Imbedded in validation is the intention to use the computer code to predict. To predict is to accept the conclusion that an observable final state will manifest; therefore, prediction is an inference whose goodness relies on the validity of the code. Quantifying the uncertainty of a prediction amounts to quantifying the uncertainty of validation, and this involves the characterization of uncertainties inherent in theory/models/codes and the corresponding data. An introduction to inference making and its associated uncertainty is provided as a foundation for the validation problem. A mathematical construction for estimating the uncertainty in the validation inference is then presented, including a possibility distribution constructed to represent the inference uncertainty for validation under uncertainty. The estimation of inference uncertainty for validation is illustrated using data and calculations from Inertial Confinement Fusion (ICF). The ICF measurements of neutron yield and ion temperature were obtained for direct-drive inertial fusion capsules at the Omega laser facility. The glass capsules, containing the fusion gas, were systematically selected with the intent of establishing a reproducible baseline of high-yield 10{sup 13}-10{sup 14} neutron output. The deuterium-tritium ratio in these experiments was varied to study its influence upon yield. This paper on validation inference is the first in a series of inference uncertainty estimations. While the methods demonstrated are primarily statistical, these do not preclude the use of nonprobabilistic methods for uncertainty characterization. The methods presented permit accurate determinations for validation and eventual prediction. It is a goal that these methods establish a standard against which best practice may evolve for determining degree of validation.

Booker, Jane M [Los Alamos National Laboratory; Langenbrunner, James R [Los Alamos National Laboratory; Hemez, Francois M [Los Alamos National Laboratory; Ross, Timothy J [UNM

2010-09-30T23:59:59.000Z

377

Assessment of the Value, Impact, and Validity of the Jobs and Economic Development Impacts (JEDI) Suite of Models  

SciTech Connect

The Jobs and Economic Development Impacts (JEDI) models, developed by the National Renewable Energy Laboratory (NREL) for the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE), use input-output methodology to estimate gross (not net) jobs and economic impacts of building and operating selected types of renewable electricity generation and fuel plants. This analysis provides the DOE with an assessment of the value, impact, and validity of the JEDI suite of models. While the models produce estimates of jobs, earnings, and economic output, this analysis focuses only on jobs estimates. This validation report includes an introduction to JEDI models, an analysis of the value and impact of the JEDI models, and an analysis of the validity of job estimates generated by JEDI model through comparison to other modeled estimates and comparison to empirical, observed jobs data as reported or estimated for a commercial project, a state, or a region.

Billman, L.; Keyser, D.

2013-08-01T23:59:59.000Z

378

Validation procedures used in the Background Soil Characterization Project on the Oak Ridge Reservation, Oak Ridge, Tennessee. Environmental Restoration Program  

SciTech Connect

The purpose of this report is (1) to document the data validation process developed for the Background Soil Characterization Project (BSCP); (2) to offer members of other project teams and potential data users the benefit of the experience gained in the BSCP in the area of developing project-specific data validation criteria and procedures based on best available guidance and technical information; and (3) to provide input and guidance to the efforts under way within Martin Marietta Energy Systems, Inc., to develop standard operating procedures to streamline and optimize the analytical laboratory data validation process for general use by making it more technically rigorous, consistent, and cost effective. Lessons learned from the BSCP are also provided to meet this end (Sect. 1.3).

1993-12-01T23:59:59.000Z

379

Data Validation & Conditioning Kenneth Martin  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Validation & Conditioning Validation & Conditioning Kenneth Martin martin@electricpowergroup.com June 27-28, 2013 Washington, DC DOE/OE Transmission Reliability Program 2 The Problem  Phasors are well known to engineers ... but synchrophasors are not  Synchrophasor value dependencies - Precise timing source, algorithms, & hardware  Systems dependent on real-time communications - Delay (latency), bandwidth, errors, & dropouts  Need comparability with established systems (SCADA)  Wide area, high-speed - faster actions Need assurance measurements are correct and... Detect and fix data problems 3 Introduction  Data Validation and Conditioning Project - RFP issued in June 2012 - Awarded to EPG in December 2012 - Completion by October 2014

380

Investigating the effects of the 1990 Clean Air Act Amendments on inputs to coal-fired power plants.  

E-Print Network (OSTI)

??This dissertation examines the effects of the 1990 Clean Air Act Amendments (CAAA) on inputs to coal-fired power plants. The 1990 CAAA established a system (more)

Lange, Ian

2005-01-01T23:59:59.000Z

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


381

Empirical validation using data from the SERI class-A validation house  

DOE Green Energy (OSTI)

A residential test building at the SERI Interim Field Site was monitored at the Class-A level during the spring of 1982. The building was also modeled on three building energy analysis simulations - DOE2.1A, Blast 3.0 and SERIRES - using measured weather data from the test period and the location. The measured energy performance data, and that predicted by the simulations, were compared. More correct input files for the codes were developed using measured values of input parameters, and the results were also compared with the measured performance data. The comparisons show that input errors can contribute to predicted auxiliary energy requirements which are on the order of 60% or more higher than the measured loads, and that improvements in input variables could reduce these errors significantly.

Judkoff, R.; Wortman, D.N.; Burch, J.

1983-04-01T23:59:59.000Z

382

MCNP5 CRITICALITY VALIDATION AND BIAS FOR INTERMEDIATE ENRICHED URANIUM SYSTEMS  

Science Conference Proceedings (OSTI)

The purpose of this analysis is to validate the Monte Carlo N-Particle 5 (MCNP5) code Version 1.40 (LA-UR-03-1987, 2005) and its cross-section database for k-code calculations of intermediate enriched uranium systems on INTEL{reg_sign} processor based PC's running any version of the WINDOWS operating system. Configurations with intermediate enriched uranium were modeled with the moderator range of 39 {le} H/Fissile {le} 1438. See Table 2-1 for brief descriptions of selected cases and Table 3-1 for the range of applicability for this validation. A total of 167 input cases were evaluated including bare and reflected systems in a single body or arrays. The 167 cases were taken directly from the previous (Version 4C [Lan 2005]) validation database. Section 2.0 list data used to calculate k-effective (k{sub eff}) for the 167 experimental criticality benchmark cases using the MCNP5 code v1.40 and its cross section database. Appendix B lists the MCNP cross-section database entries validated for use in evaluating the intermediate enriched uranium systems for criticality safety. The dimensions and atom densities for the intermediate enriched uranium experiments were taken from NEA/NSC/DOC(95)03, September 2005, which will be referred to as the benchmark handbook throughout the report. For these input values, the experimental benchmark k{sub eff} is approximately 1.0. The MCNP validation computer runs ran to an accuracy of approximately {+-} 0.001. For the cases where the reported benchmark k{sub eff} was not equal to 1.0000 the MCNP calculational results were normalized. The difference between the MCNP validation computer runs and the experimentally measured k{sub eff} is the MCNP5 v1.40 bias. The USLSTATS code (ORNL 1998) was utilized to perform the statistical analysis and generate an acceptable maximum k{sub eff} limit for calculations of the intermediate enriched uranium type systems.

FINFROCK SH

2009-12-10T23:59:59.000Z

383

The NOAA Products Validation System (NPROVS)  

Science Conference Proceedings (OSTI)

The following report summarizes the NOAA Products Validation System (NPROVS), operated at the NOAA National Environmental Satellite, Data, and Information Service (NESDIS) Center for Satellite Applications and Research (STAR). NPROVS provides ...

Tony Reale; Bomin Sun; Franklin H. Tilley; Michael Pettey

2012-05-01T23:59:59.000Z

384

ARM - Field Campaign - Aerosol Lidar Validation Experiment -...  

NLE Websites -- All DOE Office Websites (Extended Search)

govCampaignsAerosol Lidar Validation Experiment - ALIVE Campaign Links ALIVE Website Comments? We would love to hear from you Send us a note below or call us at 1-888-ARM-DATA....

385

Validation Testing of Hydrogen Generation Technology  

DOE Green Energy (OSTI)

This report describes the results of testing performed by ORNL for Photech Energies, Inc. The objective of the testing was to evaluate the efficacy of Photech's hydrogen generation reactor technology, which produces gaseous hydrogen through electrolysis. Photech provided several prototypes of their proprietary reactor for testing and the ancillary equipment, such as power supplies and electrolyte solutions, required for proper operation of the reactors. ORNL measured the production of hydrogen gas (volumetric flow of hydrogen at atmospheric pressure) as a function of input power and analyzed the composition of the output stream to determine the purity of the hydrogen content. ORNL attempted measurements on two basic versions of the prototype reactors-one version had a clear plastic outer cylinder, while another version had a stainless steel outer cylinder-but was only able to complete measurements on reactors in the plastic version. The problem observed in the stainless steel reactors was that in these reactors most of the hydrogen was produced near the anodes along with oxygen and the mixed gases made it impossible to determine the amount of hydrogen produced. In the plastic reactors the production of hydrogen gas increased monotonically with input power, and the flow rates increased faster at low input powers than they did at higher input powers. The maximum flow rate from the cathode port measured during the tests was 0.85 LPM at an input power of about 1100 W, an electrolyte concentration of 20%. The composition of the flow from the cathode port was primarily hydrogen and water vapor, with some oxygen and trace amounts of carbon dioxide. An operational mode that occurs briefly during certain operating conditions, and is characterized by flashes of light and violent bubbling near the cathode, might be attributable to the combustion of hydrogen and oxygen in the electrolyte solution.

Smith, Barton [ORNL; Toops, Todd J [ORNL

2007-12-01T23:59:59.000Z

386

Table A52. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" 2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" " Categories and Presence of General Technologies and Cogeneration Technologies, 1994" " (Estimates in Trillion Btu)" ,,,,"Employment Size(a)" ,,,,,,,,"RSE" ,,,,,,,"1000 and","Row" "General/Cogeneration Technologies","Total","Under 50","50-99","100-249","250-499","500-999","Over","Factors" "RSE Column Factors:",0.5,2,2.1,1,0.7,0.7,0.9 "One or More General Technologies Present",14601,387,781,2054,2728,3189,5462,3.1 " Computer Control of Building Environment (b)",5079,64,116,510,802,1227,2361,5

387

Wind Levelized Cost of Energy: A Comparison of Technical and Financing Input Variables  

NLE Websites -- All DOE Office Websites (Extended Search)

1 1 October 2009 Wind Levelized Cost of Energy: A Comparison of Technical and Financing Input Variables Karlynn Cory and Paul Schwabe National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Operated by the Alliance for Sustainable Energy, LLC Contract No. DE-AC36-08-GO28308 Technical Report NREL/TP-6A2-46671 October 2009 Wind Levelized Cost of Energy: A Comparison of Technical and Financing Input Variables Karlynn Cory and Paul Schwabe Prepared under Task No. WER9.3550 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government.

388

Updated U.S. Geothermal Supply Characterization and Representation for Market Penetration Model Input  

NLE Websites -- All DOE Office Websites (Extended Search)

Updated U.S. Geothermal Updated U.S. Geothermal Supply Characterization and Representation for Market Penetration Model Input C. Augustine Technical Report NREL/TP-6A20-47459 October 2011 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 Updated U.S. Geothermal Supply Characterization and Representation for Market Penetration Model Input C. Augustine Prepared under Task No. GT09.3002 Technical Report NREL/TP-6A20-47459 October 2011 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government.

389

Application of a Linear Input/Output Model to Tankless Water Heaters  

DOE Green Energy (OSTI)

In this study, the applicability of a linear input/output model to gas-fired, tankless water heaters has been evaluated. This simple model assumes that the relationship between input and output, averaged over both active draw and idle periods, is linear. This approach is being applied to boilers in other studies and offers the potential to make a small number of simple measurements to obtain the model parameters. These parameters can then be used to predict performance under complex load patterns. Both condensing and non-condensing water heaters have been tested under a very wide range of load conditions. It is shown that this approach can be used to reproduce performance metrics, such as the energy factor, and can be used to evaluate the impacts of alternative draw patterns and conditions.

Butcher T.; Schoenbauer, B.

2011-12-31T23:59:59.000Z

390

Using light emitting diode arrays as touchsensitive input and output devices  

E-Print Network (OSTI)

Light Emitting Diodes (LEDs) offer long life, low cost, efficiency, brightness, and a full range of colors. Because of these properties, they are widely used for simple displays in electronic devices. A previously characterized, but little known property of LEDs allows them to be used as photo sensors. In this paper, we show how this capability can be used to turn unmodified, off the shelf, LED arrays into touch sensitive input devices (while still remaining capable of producing output). The technique is simple and requires little or no extra hardware in some cases operating with the same micro-controller based circuitry normally used to produce output, requiring only software changes. We will describe a simple hybrid input/output device prototype implemented with this technique, and discuss the design opportunities that this type of device opens up. Categories and Subject Descriptors:

Scott E. Hudson

2004-01-01T23:59:59.000Z

391

A New Ensemble of Perturbed-Input-Parameter Simulations by the Community Atmosphere Model  

SciTech Connect

Uncertainty quantification (UQ) is a fundamental challenge in the numerical simulation of Earth's weather and climate, and other complex systems. It entails much more than attaching defensible error bars to predictions: in particular it includes assessing low-probability but high-consequence events. To achieve these goals with models containing a large number of uncertain input parameters, structural uncertainties, etc., raw computational power is needed. An automated, self-adapting search of the possible model configurations is also useful. Our UQ initiative at the Lawrence Livermore National Laboratory has produced the most extensive set to date of simulations from the US Community Atmosphere Model. We are examining output from about 3,000 twelve-year climate simulations generated with a specialized UQ software framework, and assessing the model's accuracy as a function of 21 to 28 uncertain input parameter values. Most of the input parameters we vary are related to the boundary layer, clouds, and other sub-grid scale processes. Our simulations prescribe surface boundary conditions (sea surface temperatures and sea ice amounts) to match recent observations. Fully searching this 21+ dimensional space is impossible, but sensitivity and ranking algorithms can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination. Bayesian statistical constraints, employing a variety of climate observations as metrics, also seem promising. Observational constraints will be important in the next step of our project, which will compute sea surface temperatures and sea ice interactively, and will study climate change due to increasing atmospheric carbon dioxide.

Covey, C; Brandon, S; Bremer, P T; Domyancis, D; Garaizar, X; Johannesson, G; Klein, R; Klein, S A; Lucas, D D; Tannahill, J; Zhang, Y

2011-10-27T23:59:59.000Z

392

The Net Effect of Exchange Rates on Agricultural Inputs and Outputs  

E-Print Network (OSTI)

For more than thirty years, studies about the effect of the exchange rate on exports have been conducted. However, few have considered the combined effect of the exchange rate on imported inputs into the agricultural system and the exports of final agricultural products those inputs produce. This work contributes to the agricultural economics literature by combining those effects. A current concern is for the net effect as the total value and quantity of inputs imported has increased. This research examines the effect of the exchange rate on imported inputs into the corn, wheat, and beef cattle production systems, breaking it down to a producer's budget, examining how the exchange rate affects profitability. Vector Autoregression (VAR) and Bayesian Averaging of Classical Estimates (BACE) models were estimated to evaluate the effects. Daily and weekly price data were used for corn, wheat, feeder steers, ethanol, diesel, ammonia, urea, di-ammonium phosphate, and the exchange rate. A VAR model was estimated to model the relationship between the variables. After having incongruous test results in determining the lag length structure it was decided that a BACE model would be approximated. After estimating the BACE model, the price responses of the commodities to the exchange rates were estimated. The price responses were used in demonstrating the effect of the exchange rate on a producer's profitability. It was determined that, generally, a strengthening exchange rate has a negative impact on prices. It was also found that the exchange rate has a greater impact on prices now than it did 14 years ago, implying that the exchange rate now has a greater affect on profitability. A one percent increase in the value of the dollar led to a decline in profitability ranging from $0.02/bu in wheat to $0.56/cwt in feeder steers. However, agricultural producers should not be overly concerned about a lower valued dollar from the perspective of their agricultural business.

Johnson, Myriah D.

2011-08-01T23:59:59.000Z

393

Wide input range DC-DC converter with digital control scheme  

E-Print Network (OSTI)

In this thesis analysis and design of a wide input range DC-DC converter is proposed along with a robust power control scheme. The proposed converter and its control is designed to be compatible to a fuel cell power source, which exhibits 2:1 voltage variation as well as a slow transient response. The proposed approach consists of two stages: a primary three-level boost converter stage cascaded with a high frequency, isolated boost converter topology, which provides a higher voltage gain and isolation from the input source. The function of the first boost converter stage is to maintain a constant voltage at the input of the cascaded DC-DC converter to ensure optimal performance characteristics with high efficiency. At the output of the first boost converter a battery or ultracapacitor energy storage is connected to take care of the fuel cell slow transient response (200 watts/min). The robust features of the proposed control system ensure a constant output DC voltage for a variety of load fluctuations, thus limiting the power being delivered by the fuel cell during a load transient. Moreover, the proposed configuration simplifies the power control management and can interact with the fuel cell controller. The simulation results and the experimental results confirm the feasibility of the proposed system.

Harfman Todorovic, Maja

2004-12-01T23:59:59.000Z

394

Precoding by Pairing Subchannels to Increase MIMO Capacity With Discrete Input Alphabets  

E-Print Network (OSTI)

AbstractWe consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a nondiagonal precoder based on the X-Codes in [1] to increase the mutual information. The MIMO channel is transformed into a set of parallel subchannels using singular value decomposition (SVD) and X-Codes are then used to pair the subchannels. X-Codes are fully characterized by the pairings and a 2 2 2 real rotation matrix for each pair (parameterized with a single angle). This precoding structure enables us to express the total mutual information as a sum of the mutual information of all the pairs. The problem of finding the optimal precoder with the above structure, which maximizes the total mutual information, is solved by: i) optimizing the rotation angle and the power allocation within each pair and ii) finding the optimal pairing and power allocation among the pairs. It is shown that the mutual information achieved with the proposed pairing scheme is very close to that achieved with the optimal precoder by Cruz et al., and is significantly better than Mercury/waterfilling strategy by Lozano et al. Our approach greatly simplifies both the precoder optimization and the detection complexity, making it suitable for practical applications. Index TermsCondition number, multiple-input multiple-output (MIMO), mutual information, orthogonal frequency division multiplexing (OFDM), precoding, singular value decomposition (SVD). I.

Saif Khan Mohammed; Emanuele Viterbo; Yi Hong; Senior Member; Ananthanarayanan Chockalingam; Senior Member

2010-01-01T23:59:59.000Z

395

A single inductor dual input dual output DC-DC converter with hybrid supplies for solar energy harvesting applications  

Science Conference Proceedings (OSTI)

A single inductor dual input dual output (SIDIDO) DC-DC converter is proposed for solar energy harvesting applications. The converter supports hybrid power supplies from both the photovoltaic (PV) cells and the rechargeable battery. Apart from the conventional ... Keywords: DC-DC converter, MPPT, PV cells, dual-input-dual-output, energy harvesting, single inductor

Hui Shao; Chi-Ying Tsui; Wing-Hung Ki

2009-08-01T23:59:59.000Z

396

On the Variability of Wind Power Input to the Oceans with a Focus on the Subpolar North Atlantic  

Science Conference Proceedings (OSTI)

Variations in power input to the ocean using a recent global reanalysis extending back to 1871 show a strong trend in the net power input since then, a trend dominated by the Southern Ocean region. This trend is interpreted as a spurious result ...

Xiaoming Zhai; Carl Wunsch

2013-06-01T23:59:59.000Z

397

Economic Effect on Agricultural Production of Alternative Energy Input Prices: Texas High Plains  

E-Print Network (OSTI)

The Arab oil embargo of 1973 awakened the world to the reality of energy shortages and higher fuel prices. Agriculture in the United States is highly mechanized and thus energy intensive. This study seeks to develop an evaluative capability to readily determine the short-run effect of rising energy prices on agricultural production. The results are measured in terms of demand schedules for each input investigated, net revenue adjustments, cropping pattern shifts, and changes in agricultural output. The High Plains of Texas was selected as a study area due to the heterogeneous nature of agricultural production in the region and highly energy intensive methods of production employed. The region is associated with a diversity in crops and production practices as well as a high degree of mechanization and irrigation, which means agriculture is very dependent upon energy inputs and, in turn, is significantly affected by energy price changes. The study area was defined by the Texas Agricultural Extension subregions of High Plains II, High Plains III, and High Plains IV. The crops chosen for study were cotton, grain sorghum, wheat, corn, and soybeans. The energy and energy-related inputs under investigation were diesel, herbicide, natural gas, nitrogen fertilizer, and water. Mathematical linear programming was used as the analytical technique with parametric programming techniques incorporated into the LP model to evaluate effect of varying input price parameters over a specified range. Thus, demand schedules were estimated. The objective function was constructed using variable costs only; no fixed costs are considered. Therefore, the objective function maximizes net revenue above variable costs and thus limits the study to the short run. The data bases for the model were crop enterprise budgets developed by the Texas Agricultural Extension Service. These budgets were modified to adapt them to the study. Particularly important was the substitution of owner-operated harvesting equipment for custom-harvesting costs. This procedure made possible the delineation of fuel use by crop and production alternative which was necessary information in the accounting of costs. The completed LP model was applied to 16 alternative situations made up of various input and product price combinations which are considered as feasible in the short run future. The results reveal that diesel consumption would change very little in the short run unless commodity prices simultaneously decline below the lowest prices since 1971 or unless diesel price approaches $2.00 per gallon. Under average commodity price conditions, natural gas consumption would not decline appreciably until the price rose above $4.00 per 1000 cubic feet (mcf). Even when using the least product prices since 1971, natural gas would be consumed in substantial amounts as long as the price was below $1.28 per Mcf. The findings regarding nitrogen indicate that present nitrogen prices are within a critical range such that consumption would be immediately affected by nitrogen price increases. Water price was considered as the price a farmer can afford to pay for water above pumping and distribution costs. Application of water was defined as the price that would be paid for imported water. Under average commodity price conditions, the study results show that as water price rises from zero dollars to $22 per acre foot there would be less than a 4 percent reduction in consumption. However, as the price continues to rise, consumption would decline dramatically reaching zero at a water price of $71.75 per acre foot. This study indicates that rising input prices would cause acreage shifts from irrigated to dryland; however, with average commodity prices, these shifts do not occur until diesel reaches $2.69 per gallon, or natural gas sells for $1.92 per Mcf, or nitrogen price is $.41 per pound, or water price reaches $14.69 per acre foot. In general, the first crops that would shift out of production as energy input prices rise woul

Adams, B. M.; Lacewell, R. D.; Condra, G. D.

1976-06-01T23:59:59.000Z

398

Cross Validation of Satellite Radiation Transfer Models during...  

Open Energy Info (EERE)

Cross Validation of Satellite Radiation Transfer Models during SWERA Project in Brazil (Abstract):This work describes the cross validation between two different...

399

Fact Sheet: Energy Storage Testing and Validation (October 2012...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Testing and Validation (October 2012) Fact Sheet: Energy Storage Testing and Validation (October 2012) At Sandia National Laboratories, the Energy Storage Analysis Laboratory, in...

400

Fact Sheet: Energy Storage Testing and Validation (October 2012...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

and Validation Independent testing of individual cell level to megawatt-scale electrical energy storage systems Testing and validating the performance of electrical equipment is a...

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401

Validation of the Window Model of the Modelica Buildings Library  

NLE Websites -- All DOE Office Websites (Extended Search)

Validation of the Window Model of the Modelica Buildings Library Title Validation of the Window Model of the Modelica Buildings Library Publication Type Report LBNL Report Number...

402

Reviews and Validations | Department of Energy  

NLE Websites -- All DOE Office Websites (Extended Search)

Reviews and 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 Procedures (SOP) discuss all elements of EIRs including review scope, review process, Corrective Action Plans, and OAPM's Performance Baseline Validation Process. The intent of the SOP is to make clear the OAPM expectations for both the CD-2 and CD-3 EIR, and thereby facilitate the project planning process. In particular, OAPM expects that the Scope of

403

Table A37. Total Inputs of Energy for Heat, Power, and Electricity  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" "Total United States" "RSE Column Factors:","NF",0.4,1.6,1.5,0.7,1,1.6,"NF" "TOTAL INPUTS",15027,2370,414,139,5506,105,1184,5309,3 "Boiler Fuel","--","W",296,40,2098,18,859,"--",3.6

404

Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:"," NF",0.5,1.3,1.4,0.8,1.2,1.2," NF" "TOTAL INPUTS",16515,2656,441,152,6141,99,1198,5828,2.7 "Indirect Uses-Boiler Fuel"," --",28,313,42,2396,15,875," --",4

405

Table A12. Selected Combustible Inputs of Energy for Heat, Power, and  

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

Type" Type" " and End Use, 1994: Part 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,"Residual","Distillate",,,"(excluding","RSE" "SIC",,"Net Demand","Fuel","Fuel Oil and","Natural",,"Coal Coke","Row" "Code(a)","End-Use Categories","for Electricity(b)","Oil","Diesel Fuel(c)","Gas(d)","LPG","and Breeze)","Factors" "20-39","ALL INDUSTRY GROUPS" ,"RSE Column Factors:",0.5,1.4,1.4,0.8,1.2,1.2 ,"TOTAL INPUTS",3132,441,152,6141,99,1198,2.4

406

Table A38. Selected Combustible Inputs of Energy for Heat, Power, and  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,"Net Demand","Residual","Distillate",,,"(excluding","RSE" "SIC",,"for Electri-","Fuel","Fuel Oil and","Natural",,"Coal Coke","Row" "Code","End-Use Categories","city(b)","Oil","Diesel Fuel(c)","Gas(d)","LPG","and Breeze)","Factors" "20-39","ALL INDUSTRY GROUPS" ,"RSE Column Factors:",0.4,1.7,1.5,0.7,1,1.6 ,"TOTAL INPUTS",2799,414,139,5506,105,1184,3 ,"Boiler Fuel",32,296,40,2098,18,859,3.6 ,"Total Process Uses",2244,109,34,2578,64,314,4.1

407

Procedure for developing biological input for the design, location, or modification of water-intake structures  

Science Conference Proceedings (OSTI)

To minimize adverse impact on aquatic ecosystems resulting from the operation of water intake structures, design engineers must have relevant information on the behavior, physiology and ecology of local fish and shellfish. Identification of stimulus/response relationships and the environmental factors that influence them is the first step in incorporating biological information in the design, location or modification of water intake structures. A procedure is presented in this document for providing biological input to engineers who are designing, locating or modifying a water intake structure. The authors discuss sources of stimuli at water intakes, historical approaches in assessing potential/actual impact and review biological information needed for intake design.

Neitzel, D.A.; McKenzie, D.H.

1981-12-01T23:59:59.000Z

408

RELAP5/MOD3 code manual: User`s guide and input requirements. Volume 2  

Science Conference Proceedings (OSTI)

The RELAP5 code has been developed for best estimate transient simulation of light water reactor coolant systems during postulated accidents. The code models the coupled behavior of the reactor coolant system and the core for loss-of-coolant accidents, and operational transients, such as anticipated transient without scram, loss of offsite power, loss of feedwater, and loss of flow. A generic modeling approach is used that permits simulating a variety of thermal hydraulic systems. Control system and secondary system components are included to permit modeling of plant controls, turbines, condensers, and secondary feedwater systems. Volume II contains detailed instructions for code application and input data preparation.

NONE

1995-08-01T23:59:59.000Z

409

Input Price Risk and Optimal Timing of Energy Investment: Choice between Fossil- and Biofuels  

E-Print Network (OSTI)

Ve consider energy investment, when a choice has to be made between fossil fuel and biomass fired production technologies. A dynamic model is presented to illustrate the effect of the different degrees of input price uncer- tainty on the choice of technolog2 and the timing of the investment. It is shown that when the choice of technology is irreversible, it may be optimal to postpone the investment even if it would otherwise be optimal to invest in one or both of the plant types. Ve provide a numerical example based on cost estimates of two different power plant types.

Pauli Murto; Gjermund Nese

2002-01-01T23:59:59.000Z

410

Marketing Plan for Demonstration and Validation Assets  

Science Conference Proceedings (OSTI)

The National Security Preparedness Project (NSPP), is to be sustained by various programs, including technology demonstration and evaluation (DEMVAL). This project assists companies in developing technologies under the National Security Technology Incubator program (NSTI) through demonstration and validation of technologies applicable to national security created by incubators and other sources. The NSPP also will support the creation of an integrated demonstration and validation environment. This report documents the DEMVAL marketing and visibility plan, which will focus on collecting information about, and expanding the visibility of, DEMVAL assets serving businesses with national security technology applications in southern New Mexico.

None

2008-05-30T23:59:59.000Z

411

PHYLOGENOMICS - GUIDED VALIDATION OF FUNCTION FOR CONSERVED UNKNOWN GENES  

SciTech Connect

Identifying functions for all gene products in all sequenced organisms is a central challenge of the post-genomic era. However, at least 30-50% of the proteins encoded by any given genome are of unknown function, or wrongly or vaguely annotated. Many of these 'unknown' proteins are common to prokaryotes and plants. We accordingly set out to predict and experimentally test the functions of such proteins. Our approach to functional prediction is integrative, coupling the extensive post-genomic resources available for plants with comparative genomics based on hundreds of microbial genomes, and functional genomic datasets from model microorganisms. The early phase is computer-assisted; later phases incorporate intellectual input from expert plant and microbial biochemists. The approach thus bridges the gap between automated homology-based annotations and the classical gene discovery efforts of experimentalists, and is much more powerful than purely computational approaches to identifying gene-function associations. Among Arabidopsis genes, we focused on those (2,325 in total) that (i) are unique or belong to families with no more than three members, (ii) are conserved between plants and prokaryotes, and (iii) have unknown or poorly known functions. Computer-assisted selection of promising targets for deeper analysis was based on homology .. independent characteristics associated in the SEED database with the prokaryotic members of each family, specifically gene clustering and phyletic spread, as well as availability of functional genomics data, and publications that could link candidate families to general metabolic areas, or to specific functions. In-depth comparative genomic analysis was then performed for about 500 top candidate families, which connected ~55 of them to general areas of metabolism and led to specific functional predictions for a subset of ~25 more. Twenty predicted functions were experimentally tested in at least one prokaryotic organism via reverse genetics, metabolic profiling, functional complementation, and recombinant protein biochemistry. Our approach predicted and validated functions for 10 formerly uncharacterized protein families common to plants and prokaryotes; none of these functions had previously been correctly predicted by computational methods. The functions of five more are currently being validated. Experimental testing of diverse representatives of these families combined with in silica analysis allowed accurate projection of the annotations to hundreds more sequenced genomes.

V, DE CRECY-LAGARD; D, HANSON A

2012-01-03T23:59:59.000Z

412

NIST Develops Experimental Validation Tool for Cell Phone ...  

Science Conference Proceedings (OSTI)

NIST Develops Experimental Validation Tool for Cell Phone Forensics. For Immediate Release: December 1, 2009. ...

2010-11-05T23:59:59.000Z

413

Temperature and heat flux datasets of a complex object in a fire plume for the validation of fire and thermal response codes.  

SciTech Connect

It is necessary to improve understanding and develop temporally- and spatially-resolved integral scale validation data of the heat flux incident to a complex object in addition to measuring the thermal response of said object located within the fire plume for the validation of the SIERRA/FUEGO/SYRINX fire and SIERRA/CALORE codes. To meet this objective, a complex calorimeter with sufficient instrumentation to allow validation of the coupling between FUEGO/SYRINX/CALORE has been designed, fabricated, and tested in the Fire Laboratory for Accreditation of Models and Experiments (FLAME) facility. Validation experiments are specifically designed for direct comparison with the computational predictions. Making meaningful comparison between the computational and experimental results requires careful characterization and control of the experimental features or parameters used as inputs into the computational model. Validation experiments must be designed to capture the essential physical phenomena, including all relevant initial and boundary conditions. This report presents the data validation steps and processes, the results of the penlight radiant heat experiments (for the purpose of validating the CALORE heat transfer modeling of the complex calorimeter), and the results of the fire tests in FLAME.

Jernigan, Dann A.; Blanchat, Thomas K.

2010-09-01T23:59:59.000Z

414

Input-independent, Scalable and Fast String Matching on the Cray XMT  

Science Conference Proceedings (OSTI)

String searching is at the core of many security and network applications like search engines, intrusion detection systems, virus scanners and spam ?lters. The growing size of on-line content and the increasing wire speeds push the need for fast, and often real- time, string searching solutions. For these conditions, many software implementations (if not all) targeting conventional cache-based microprocessors do not perform well. They either exhibit overall low performance or exhibit highly variable performance depending on the types of inputs. For this reason, real-time state of the art solutions rely on the use of either custom hardware or Field-Programmable Gate Arrays (FPGAs) at the expense of overall system ?exibility and programmability. This paper presents a software based implementation of the Aho-Corasick string searching algorithm on the Cray XMT multithreaded shared memory machine. Our so- lution relies on the particular features of the XMT architecture and on several algorith- mic strategies: it is fast, scalable and its performance is virtually content-independent. On a 128-processor Cray XMT, it reaches a scanning speed of ? 28 Gbps with a performance variability below 10 %. In the 10 Gbps performance range, variability is below 2.5%. By comparison, an Intel dual-socket, 8-core system running at 2.66 GHz achieves a peak performance which varies from 500 Mbps to 10 Gbps depending on the type of input and dictionary size.

Villa, Oreste; Chavarra-Miranda, Daniel; Maschhoff, Kristyn J.

2009-05-25T23:59:59.000Z

415

Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting  

SciTech Connect

Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow forecasting. In this study, we propose a Markov Chain Monte Carlo (MCMC) framework to incorporate the uncertainties associated with input, model structure, and parameter into BNNs. This framework allows the structure of the neural networks to change by removing or adding connections between neurons and enables scaling of input data by using rainfall multipliers. The results show that the new BNNs outperform the BNNs that only consider uncertainties associated with parameter and model structure. Critical evaluation of posterior distribution of neural network weights, number of effective connections, rainfall multipliers, and hyper-parameters show that the assumptions held in our BNNs are not well supported. Further understanding of characteristics of different uncertainty sources and including output error into the MCMC framework are expected to enhance the application of neural networks for uncertainty analysis of hydrologic forecasting.

Zhang, Xuesong; Liang, Faming; Yu, Beibei; Zong, Ziliang

2011-11-09T23:59:59.000Z

416

The Effect of Changing Input and Product Prices on the Demand for Irrigation Water in Texas  

E-Print Network (OSTI)

Agriculture is a major income-producing sector in the Texas economy and a large part of this economic activity originates in irrigated crop production. For example, in 1973, 50% of all grain sorghum and 46% of all cotton in Texas were produced on irrigated acreage [Texas Crop and Livestock Reporting Service]. These two crops alone produced 26% of the cash receipts from the sale of Texas farm commodities in 1973 [Texas Crop and Livestock Reporting Service]. There are several other crops in Texas including vegetables which generate significant levels of income and rely heavily on irrigation. Further there are several associated industries which rely on production from irrigated agriculture, such as the cattle feeding industry in the Texas Panhandle. It is evident from this rather cursory examination of statistics that irrigation plays a large role in Texas agriculture. Both producers and policy-makers have found themselves faced in the past two years with many uncertainties. The U.S., plagued in the past with surplus production and supply control problems, now finds itself in a world shortage of food products. The long range signals seem to call for increased production, yet the policy-maker faces decisions concerning not only how to increase production, but more basically, how to maintain current levels of production. Groundwater resources in many areas are being diminished and annual irrigation water supplies fully committed in other areas. Long run planning for Texas agriculture requires that interbasin transfers of water be evaluated. Texas holds a position of prominence in the production of U.S. food and fiber products, and the evaluation of these alternatives has implications not only for Texas, but for the U.S. and possibly the world. To objectively evaluate water transfer proposals, it is necessary that the value of irrigation water in different regions of Texas be established. The producer faces the same call for maintaining or increasing production as the policy-maker, but he does so with many uncertainties which often have not disturbed the policy-maker in evaluating alternatives. Product prices have risen and fallen at an unprecedented rate while input prices have steadily risen at rates which preclude realistic budgeting. For example, during the recent energy crisis, the prices of fuel and fertilizer have more than doubled. These variable input and product prices weigh heavily upon production decisions by the producer, and likewise must receive serious consideration in evaluation of resource allocation alternatives by policy-makers. The demand for irrigation water is derived from the production of crops and any change in production patterns, input prices or availability, and product prices directly affects this demand. Current and future water resources planning requires an estimate of the various quantities of water which will be used for irrigation under differing assumptions concerning price of water, other input prices, and product prices. Of particular importance are shifts in cropping patterns, changes in level of agricultural production and net effect on producers income. Since many policy decisions are made in relatively short periods of time, there is an urgent need for a capability to evaluate alternative policies and change input or product prices in a timely fashion.

Lacewell, R. D.; Condra, G. D.

1976-06-01T23:59:59.000Z

417

Distributed Energy System Validation, Commissioning and  

E-Print Network (OSTI)

Distributed Energy System Validation, Commissioning and Qualification Test Report Prepared Agreement No. DE-FC26-06NT42847 Hawai`i Distributed Energy Resource Technologies for Energy Security Subtask for the U.S. Department of Energy Office of Electricity Delivery and Energy Reliability Under Cooperative

418

Validation of the ATSR in Australian Waters  

Science Conference Proceedings (OSTI)

The Along Track Scanning Radiometer (ATSR) was launched on the ERS-1 satellite on 17 July 1991. During the following six months, a concentrated effort was made to validate the sea surface temperature (SST) derived from data supplied by this new ...

I. J. Barton; A. J. Prata; R. P. Cechet

1995-04-01T23:59:59.000Z

419

Feature extraction for structural dynamics model validation  

SciTech Connect

This study focuses on defining and comparing response features that can be used for structural dynamics model validation studies. Features extracted from dynamic responses obtained analytically or experimentally, such as basic signal statistics, frequency spectra, and estimated time-series models, can be used to compare characteristics of structural system dynamics. By comparing those response features extracted from experimental data and numerical outputs, validation and uncertainty quantification of numerical model containing uncertain parameters can be realized. In this study, the applicability of some response features to model validation is first discussed using measured data from a simple test-bed structure and the associated numerical simulations of these experiments. issues that must be considered were sensitivity, dimensionality, type of response, and presence or absence of measurement noise in the response. Furthermore, we illustrate a comparison method of multivariate feature vectors for statistical model validation. Results show that the outlier detection technique using the Mahalanobis distance metric can be used as an effective and quantifiable technique for selecting appropriate model parameters. However, in this process, one must not only consider the sensitivity of the features being used, but also correlation of the parameters being compared.

Hemez, Francois [Los Alamos National Laboratory; Farrar, Charles [Los Alamos National Laboratory; Park, Gyuhae [Los Alamos National Laboratory; Nishio, Mayuko [UNIV OF TOKYO; Worden, Keith [UNIV OF SHEFFIELD; Takeda, Nobuo [UNIV OF TOKYO

2010-11-08T23:59:59.000Z

420

Wave-Follower Field Measurements of the Wind-Input Spectral Function. Part I: Measurements and Calibrations  

Science Conference Proceedings (OSTI)

An experimental study of wind energy and momentum input into finite-depth wind waves was undertaken at Lake George, New South Wales, Australia. To measure microscale oscillations of induced pressure above surface waves, a high-precision wave-...

Mark A. Donelan; Alexander V. Babanin; Ian R. Young; Michael L. Banner; Cyril McCormick

2005-07-01T23:59:59.000Z

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


421

Wind-Generated Power Input to the Deep Ocean: An Estimate Using a 1/10 General Circulation Model  

Science Conference Proceedings (OSTI)

Recent studies on the wind-generated power input to the geostrophic and nongeostrophic ocean circulation components have used expressions derived from Ekman dynamics. The present work extends and unifies previous studies by deriving an expression ...

Jin-Song von Storch; Hideharu Sasaki; Jochem Marotzke

2007-03-01T23:59:59.000Z

422

Computer code input for thermal hydraulic analysis of Multi-Function Waste Tank Facility Title II design  

Science Conference Proceedings (OSTI)

The input files to the P/Thermal computer code are documented for the thermal hydraulic analysis of the Multi-Function Waste Tank Facility Title II design analysis.

Cramer, E.R.

1994-10-01T23:59:59.000Z

423

Experiments for foam model development and validation.  

Science Conference Proceedings (OSTI)

A series of experiments has been performed to allow observation of the foaming process and the collection of temperature, rise rate, and microstructural data. Microfocus video is used in conjunction with particle image velocimetry (PIV) to elucidate the boundary condition at the wall. Rheology, reaction kinetics and density measurements complement the flow visualization. X-ray computed tomography (CT) is used to examine the cured foams to determine density gradients. These data provide input to a continuum level finite element model of the blowing process.

Bourdon, Christopher Jay; Cote, Raymond O.; Moffat, Harry K.; Grillet, Anne Mary; Mahoney, James F. (Honeywell Federal Manufacturing and Technologies, Kansas City Plant, Kansas City, MO); Russick, Edward Mark; Adolf, Douglas Brian; Rao, Rekha Ranjana; Thompson, Kyle Richard; Kraynik, Andrew Michael; Castaneda, Jaime N.; Brotherton, Christopher M.; Mondy, Lisa Ann; Gorby, Allen D.

2008-09-01T23:59:59.000Z

424

Welding and Repair Technology Center: Development of Improved Weld Heat Input and Dilution Equations for Consumable Welding Processes  

Science Conference Proceedings (OSTI)

Predicting heat input into the substrate and weld dilution for consumable welding processes is a challenge due to the number of variables associated with these processes. Proper heat input and power ratio controls are critical to control weld dilution, particularly in dissimilar metal welds where low weld dilution is necessary to prevent solidification cracking or for cladding where weld dilution is minimized to maintain corrosion resistance of the clad material. This report discusses the ...

2013-11-27T23:59:59.000Z

425

Valid Inequalities Based on Demand Propagation for Chemical ...  

E-Print Network (OSTI)

The planning of chemical production often involves the optimization of the ... Production tasks convert a set of input materials into a set of output materials, and ...

426

Model Validation and Testing: The Methodological Foundation of ASHRAE Standard 140  

SciTech Connect

Ideally, whole-building energy simulation programs model all aspects of a building that influence energy use and thermal and visual comfort for the occupants. An essential component of the development of such computer simulation models is a rigorous program of validation and testing. This paper describes a methodology to evaluate the accuracy of whole-building energy simulation programs. The methodology is also used to identify and diagnose differences in simulation predictions that may be caused by algorithmic differences, modeling limitations, coding errors, or input errors. The methodology has been adopted by ANSI/ASHRAE Standard 140, Method of Test for the Evaluation of Building Energy Analysis Computer Programs (ASHRAE 2001a, 2004). A summary of the method is included in the 2005 ASHRAE Handbook--Fundamentals (ASHRAE 2005). This paper describes the ASHRAE Standard 140 method of test and its methodological basis. Also discussed are possible future enhancements to ASHRAE Standard 140 and related research recommendations.

Judkoff, R.; Neymark, J.

2006-01-01T23:59:59.000Z

427

Model Validation and Testing: The Methodological Foundation of ASHRAE Standard 140; Preprint  

Science Conference Proceedings (OSTI)

Ideally, whole-building energy simulation programs model all aspects of a building that influence energy use and thermal and visual comfort for the occupants. An essential component of the development of such computer simulation models is a rigorous program of validation and testing. This paper describes a methodology to evaluate the accuracy of whole-building energy simulation programs. The methodology is also used to identify and diagnose differences in simulation predictions that may be caused by algorithmic differences, modeling limitations, coding errors, or input errors. The methodology has been adopted by ANSI/ASHRAE Standard 140 (ANSI/ASHRAE 2001, 2004), Method of Test for the Evaluation of Building Energy Analysis Computer Programs. A summary of the method is included in the ASHRAE Handbook of Fundamentals (ASHRAE 2005). This paper describes the ANSI/ASHRAE Standard 140 method of test and its methodological basis. Also discussed are possible future enhancements to Standard 140 and related research recommendations.

Judkoff, R.; Neymark, J.

2006-07-01T23:59:59.000Z

428

Approaches used for Clearance of Lands from Nuclear Facilities among Several Countries: Evaluation for Regulatory Input  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

:14 :14 Report number: 2013:14 ISSN: 2000-0456 Available at www.stralsakerhetsmyndigheten.se Approaches used for Clearance of Lands from Nuclear Facilities among Several Countries Evaluation for Regulatory Input Robert A. Meck Author: SSM perspektiv SSM har nyligen beslutat om föreskrifter om friklassning av material, loka- ler, byggnader och mark vid verksamhet med joniserande strålning (SSMFS 201 1:2). Föreskrifterna innehåller bland annat krav på att tillståndshavare, vid avveckling av verksamhet med joniserande strålning, ska vidta åtgärder som möjliggör friklassning av lokaler, byggnader och mark. Föreskrifterna innehåller nuklidspecifika friklassningsnivåer i becquerel per m2 för lokaler och byggnader men ger ingen upplysning om vilka friklassningsnivåer som

429

Visualizations, Screen Shots, and Data Input Files from VisIT  

DOE Data Explorer (OSTI)

VisIt is a free interactive parallel visualization and graphical analysis tool for viewing scientific data on Unix and PC platforms. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images for presentations. VisIt contains a rich set of visualization features so that you can view your data in a variety of ways. It can be used to visualize scalar and vector fields defined on two- and three-dimensional (2D and 3D) structured and unstructured meshes. VisIt was designed to handle very large data set sizes in the terascale range and yet can also handle small data sets in the kilobyte range. The VisIT website provides a gallery of vizualizations, another set of screen shots, and allows downloads of data files for input and source codes and executables for the VisIT software suite.

430

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

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

Monthly","9/2013","1/15/1987" Monthly","9/2013","1/15/1987" ,"Release Date:","11/27/2013" ,"Next Release Date:","Last Week of December 2013" ,"Excel File Name:","pet_pnp_dwns_dc_nus_mbblpd_m.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_pnp_dwns_dc_nus_mbblpd_m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov" ,,"(202) 586-8800",,,"11/25/2013 11:17:28 AM" "Back to Contents","Data 1: U.S. Downstream Processing of Fresh Feed Input" "Sourcekey","M_NA_YDR_NUS_MBBLD","MCRCCUS2","MCRCHUS2","MCRDFUS2"

431

Summary of Input to DOE Request for Information DE-FOA-0000225  

NLE Websites -- All DOE Office Websites (Extended Search)

& & Renewable Energy Summary of Input to DOE Request for Information DE FOA 0000225 DE-FOA-0000225 Greg Kleen Greg Kleen Golden Golden Field Field O Office ffice Golden Golden Field Field Office Office US DOE Fuel Cells T US DOE Fuel Cells Technology echnology Program Program Lakewood, Colorado Lakewood, Colorado March 16, 2010 March 16, 2010 83 ses o 6 o a at o s RFI Summary Release Date: 12/29/2009 Release Date: 12/29/2009 Closing Date: 1/29/2010 Purpose: Obtain Feedback from the Fuel Cell Community Purpose: Obtain Feedback from the Fuel Cell Community Planned Funding Opportunity Announcement Tentative Release: Summer 2010 Tentative Release: Summer 2010 Tentative Awards Made: Fiscal Year 2011 183 responses from 61 org ganizations espo Responses covered: Most fuel cell types and applications

432

PREPAR: a user-friendly preprocessor to create AIRDOS-EPA input data sets  

SciTech Connect

PREPAR is a FORTRAN program designed to simplify the preparation of input for the AIRDOS-EPA computer code. PREPAR was designed to provide a method for data entry that is both logical and flexible. It also provides default values for all variables, so the user needs only to enter those data for which the defaults should be changed. Data are entered either unformatted or via a user-selected format. A separate file of the nuclide-specific data needed by AIRDOS-EPA is read by PREPAR. Two utility programs, EXTRAC and RADLST, were written to create and list this file. PREPAR writes the file needed to run AIRDOS-EPA and writes a listing of that file.

Sjoreen, A.L.; Miller, C.W.; Nelson, C.B.

1984-01-01T23:59:59.000Z

433

Cascode buffer for monolithic voltage conversion operating at high input supply voltages  

E-Print Network (OSTI)

A high-to-low switching DC-DC converter that operates at input supply voltages up to two times as high as the maximum voltage permitted in a nanometer CMOS technology is proposed in this paper. The circuit technique is based on a cascode bridge that maintains the steady-state voltage differences among the terminals of all of the transistors within a range imposed by a specific fabrication technology. The proposed circuit technique permits the full integration of active and passive devices of a switching DC-DC converter with a high voltage conversion ratio in a standard low voltage CMOS process. An efficiency of 87.8 % is achieved for 3.6 volts to 0.9 volts conversion assuming

Volkan Kursun; Gerhard Schrom; Vivek K. De; Eby G. Friedman; Siva G. Narendra

2005-01-01T23:59:59.000Z

434

Device for modular input high-speed multi-channel digitizing of electrical data  

DOE Patents (OSTI)

A multi-channel high-speed digitizer module converts a plurality of analog signals to digital signals (digitizing) and stores the signals in a memory device. The analog input channels are digitized simultaneously at high speed with a relatively large number of on-board memory data points per channel. The module provides an automated calibration based upon a single voltage reference source. Low signal noise at such a high density and sample rate is accomplished by ensuring the A/D converters are clocked at the same point in the noise cycle each time so that synchronous noise sampling occurs. This sampling process, in conjunction with an automated calibration, yields signal noise levels well below the noise level present on the analog reference voltages.

VanDeusen, Alan L. (Lee' s Summit, MO); Crist, Charles E. (Waxahachie, TX)

1995-09-26T23:59:59.000Z

435

Next generation input-output data format for HEP using Google's protocol buffers  

E-Print Network (OSTI)

We propose a data format for Monte Carlo (MC) events, or any structural data, including experimental data, in a compact binary form using variable-size integer encoding as implemented in the Google's Protocol Buffers package. This approach is implemented in the so-called ProMC library which produces smaller file sizes for MC records compared to the existing input-output libraries used in high-energy physics (HEP). Other important features are a separation of abstract data layouts from concrete programming implementations, self-description and random access. Data stored in ProMC files can be written, read and manipulated in a number of programming languages, such C++, Java and Python.

S. V. Chekanov

2013-06-27T23:59:59.000Z

436

Storm Peak Lab Cloud Property Validation  

NLE Websites -- All DOE Office Websites (Extended Search)

Storm Peak Lab Cloud Storm Peak Lab Cloud Property Validation Experiment (STORMVEX) Operated by the Atmospheric Radiation Measurement (ARM) Climate Research Facility for the U.S. Department of Energy, the second ARM Mobile Facility (AMF2) begins its inaugural deployment November 2010 in Steamboat Springs, Colorado, for the Storm Peak Lab Cloud Property Validation Experiment, or STORMVEX. For six months, the comprehensive suite of AMF2 instruments will obtain measurements of cloud and aerosol properties at various sites below the heavily instrumented Storm Peak Lab, located on Mount Werner at an elevation of 3220 meters. The correlative data sets that will be created from AMF2 and Storm Peak Lab will equate to between 200 and 300 in situ aircraft flight hours in liquid, mixed phase, and precipitating

437

Land Validation Holdings, PROVE, June 2001  

NLE Websites -- All DOE Office Websites (Extended Search)

PROVE Data and Images Released PROVE Data and Images Released Data and images are now available from the Prototype Validation Exercise (PROVE), a field campaign conducted in May 1997 at the Jornada Experimental Range near Las Cruces, New Mexico. The Jornada Experimental Range is an expansive plateau on the Chihuahuan Desert and hosts a complex mosaic of grasses and shrubs that were characterized during PROVE. PROVE researchers collected land and atmospheric measurements for use in validating data from Earth Observing System (EOS) satellites. Measurements included surface reflectance, surface temperature, albedo, and leaf area index, among other parameters. We anticipate that additional data associated with papers published in a recent special issue of Remote Sensing of the Environment (October 2000) will be registered in the ORNL

438

GRIMHX verification and validation action matrix summary  

Science Conference Proceedings (OSTI)

WSRC-RP-90-026, Certification Plan for Reactor Analysis Computer Codes, describes a series of action items to be completed for certification of reactor analysis computer codes used in Technical Specifications development and for other safety and production support calculations. Validation and verification of the code is an integral part of this process. This document identifies the work performed and documentation generated to satisfy these action items for the Reactor Physics computer code GRIMHX. Each action item is discussed with the justification for its completion. Specific details of the work performed are not included in this document but are found in the references. The publication of this document signals the validation and verification effort for the GRIMHX code is completed.

Trumble, E.F.

1991-12-01T23:59:59.000Z

439

Validation of Dose Calculation Codes for Clearance  

SciTech Connect

Various international and national bodies such as the International Atomic Energy Agency, the European Commission, the US Nuclear Regulatory Commission have put forward proposals or guidance documents to regulate the ''clearance'' from regulatory control of very low level radioactive material, in order to allow its recycling as a material management practice. All these proposals are based on predicted scenarios for subsequent utilization of the released materials. The calculation models used in these scenarios tend to utilize conservative data regarding exposure times and dose uptake as well as other assumptions as a safeguard against uncertainties. None of these models has ever been validated by comparison with the actual real life practice of recycling. An international project was organized in order to validate some of the assumptions made in these calculation models, and, thereby, better assess the radiological consequences of recycling on a practical large scale.

Menon, S.; Wirendal, B.; Bjerler, J.; Studsvik; Teunckens, L.

2003-02-27T23:59:59.000Z

440

NASA Remote Sensing Validation Data: Saudi Arabia  

DOE Data Explorer (OSTI)

Since 1995, the King Abdulaziz City for Science and Technology (KACST) and the National Renewable Energy Laboratory (NREL) have co-operated to establish a 12 station network of high quality solar radiation monitoring installations across the Kingdom of Saudi Arabia. NREL and KACST realized the value of accurate surface solar radiation flux measurements for validation of satellite derived surface and atmospheric solar radiation flux measurements, and is making this data available to support validation of satellite data products related to the NASA Mission to Planet Earth component of the Earth Science Enterprise Earth Observing System (EOS) project to evaluate long term climate trends based on measuements from EOS Terra Platforms. A CIMEL 8 channel sunphotometer for measuring aerosol optical depth at 6 wavelengths and total column water has been deployed at the Solar Village station since February 24, 1999. [Taken from http://rredc.nrel.gov/solar/new_data/Saudi_Arabia/

Myers, Daryl R. (NREL); Al-Abbadi,Naif (King Abdulaziz City for Science and Technology, Energy Research Institite); Wilcox, Steve (NREL)

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


441

Midwest Geological Sequestration Consortium--Validation Phase  

NLE Websites -- All DOE Office Websites (Extended Search)

Geological Sequestration Geological Sequestration Consortium-Validation Phase Background The U.S. Department of Energy (DOE) has selected seven partnerships, through its Regional Carbon Sequestration Partnership (RCSP) initiative, to determine the best approaches for capturing and permanently storing carbon dioxide (CO 2 ), a greenhouse gas (GHG) which can contribute to global climate change. The RCSPs are made up of state and local agencies, coal companies, oil and gas companies, electric utilities,

442

FCT Technology Validation: Stationary/Distributed Generation Projects  

NLE Websites -- All DOE Office Websites (Extended Search)

Stationary/Distributed Stationary/Distributed Generation Projects to someone by E-mail Share FCT Technology Validation: Stationary/Distributed Generation Projects on Facebook Tweet about FCT Technology Validation: Stationary/Distributed Generation Projects on Twitter Bookmark FCT Technology Validation: Stationary/Distributed Generation Projects on Google Bookmark FCT Technology Validation: Stationary/Distributed Generation Projects on Delicious Rank FCT Technology Validation: Stationary/Distributed Generation Projects on Digg Find More places to share FCT Technology Validation: Stationary/Distributed Generation Projects on AddThis.com... Home Transportation Projects Stationary/Distributed Generation Projects DOE Projects Non-DOE Projects Integrated Projects Quick Links Hydrogen Production

443

Security Technology Demonstration and Validation Sustainability Plan  

SciTech Connect

This report describes the process of creating continuity and sustainability for demonstration and validation (DEMVAL) assets at the National Security Technology Incubator (NSTI). The DEMVAL asset program is being developed as part of the National Security Preparedness Project (NSPP), funded by Department of Energy (DOE)/National Nuclear Security Administration (NNSA). The mission of the NSTI program is to identify, incubate, and accelerate technologies with national security applications at various stages of development by providing hands-on mentoring and business assistance to small businesses and emerging or growing companies. Part of this support is envisioned to be research and development of companies technology initiatives, at the same time providing robust test and evaluation of actual development activities. This program assists companies in developing technologies under the NSTI program through demonstration and validation of technologies applicable to national security created by incubators and other sources. The NSPP also will support the creation of an integrated demonstration and validation environment. Development of the commercial potential for national security technologies is a significant NSTI focus. As part of the process of commercialization, a comprehensive DEMVAL program has been recognized as an essential part of the overall incubator mission. A number of resources have been integrated into the NSTI program to support such a DEMVAL program.

None

2008-08-31T23:59:59.000Z

444

Review and validation of exposure assessment methods  

E-Print Network (OSTI)

The purpose of this research is twofold, to standardize and to validate exposure assessment methods. First, the attempt is made to standardize the manner in which exposure assessment methods are developed. Literature on the subject is reviewed and seven common elements discovered to be common are discussed. The seven elements are causative agents, exposure groups, exposure-modifying parameters, industrial hygiene measurement data, misclassification issues, validation issues, and reliability issues. It is believed that thinking in terms of these elements will yield more consistent and complete exposure assessment models. Three types of exposure estimation methods are reviewed in this form. These methods are selected because they are the most thorough and represent the most frequently used and referenced types of estimation strategies: the statistical model, the deterministic model, and the multiplicative model. Second, the paper reports on an attempt to validate a semiquantitative exposure assessment model against industrial hygiene data collected from employees of one firm in the maritime industry. The set of data contains 440 samples with 75 percent of them censored by the method limit of detection. Methods to calculate an average concentration with nondetectable data are discussed. It is concluded that (1) the model does not predict the data well, (2) the industrial hygiene data does not properly fit the tails of a lognormal distribution, and (3) that average exposure to benzene in the (un)loading of petrochemicals from tankers is decidedly below exposure limits.

Shaw, Eduardo

2001-01-01T23:59:59.000Z

445

Radiography Facility - Building 239 Independent Validation Review  

SciTech Connect

The purpose of this task was to perform an Independent Validation Review to evaluate the successful implementation and effectiveness of Safety Basis controls, including new and revised controls, to support the implementation of a new DSA/TSR for B239. This task addresses Milestone 2 of FY10 PEP 7.6.6. As the first IVR ever conducted on a LLNL nuclear facility, it was designated a pilot project. The review follows the outline developed for Milestone 1 of the PEP, which is based on the DOE Draft Guide for Performance of Independent Verification Review of Safety Basis Controls. A formal Safety Basis procedure will be developed later, based on the lessons learned with this pilot project. Note, this review is termed a ''Validation'' in order to be consistent with the PEP definition and address issues historically raised about verification mechanisms at LLNL. Validation is intended to confirm that implementing mechanisms realistically establish the ability of TSR LCO, administrative control or safety management program to accomplish its intended safety function and that the controls are being implemented. This effort should not, however, be confused with a compliance assessment against all relevant DOE requirements and national standards. Nor is it used as a vehicle to question the derivation of controls already approved by LSO unless a given TSR statement simply cannot be implemented as stated.

Altenbach, T J; Beaulieu, R A; Watson, J F; Wong, H J

2010-02-02T23:59:59.000Z

446

Nuclear data to support computer code validation  

SciTech Connect

The rate of plutonium disposition will be a key parameter in determining the degree of success of the Fissile Materials Disposition Program. Estimates of the disposition rate are dependent on neutronics calculations. To ensure that these calculations are accurate, the codes and data should be validated against applicable experimental measurements. Further, before mixed-oxide (MOX) fuel can be fabricated and loaded into a reactor, the fuel vendors, fabricators, fuel transporters, reactor owners and operators, regulatory authorities, and the Department of Energy (DOE) must accept the validity of design calculations. This report presents sources of neutronics measurements that have potential application for validating reactor physics (predicting the power distribution in the reactor core), predicting the spent fuel isotopic content, predicting the decay heat generation rate, certifying criticality safety of fuel cycle facilities, and ensuring adequate radiation protection at the fuel cycle facilities and the reactor. The U.S. in-reactor experience with MOX fuel is first presented, followed by information related to other aspects of the MOX fuel performance information that is valuable to this program, but the data base remains largely proprietary. Thus, this information is not reported here. It is expected that the selected consortium will make the necessary arrangements to procure or have access to the requisite information.

Fisher, S.E.; Broadhead, B.L.; DeHart, M.D.; Primm, R.T. III

1997-04-01T23:59:59.000Z

447

Verification and Validation of TMAP7  

DOE Green Energy (OSTI)

The Tritium Migration Analysis Program, Version 7 (TMAP7) code is an update of TMAP4, an earlier version that was verified and validated in support of the International Thermonuclear Experimental Reactor (ITER) program and of the intermediate version TMAP2000. It has undergone several revisions. The current one includes radioactive decay, multiple trap capability, more realistic treatment of heteronuclear molecular formation at surfaces, processes that involve surface-only species, and a number of other improvements. Prior to code utilization, it needed to be verified and validated to ensure that the code is performing as it was intended and that its predictions are consistent with physical reality. To that end, the demonstration and comparison problems cited here show that the code results agree with analytical solutions for select problems where analytical solutions are straightforward or with results from other verified and validated codes, and that actual experimental results can be accurately replicated using reasonable models with this code. These results and their documentation in this report are necessary steps in the qualification of TMAP7 for its intended service.

James Ambrosek; James Ambrosek

2008-12-01T23:59:59.000Z

448

In Situ Validation of a Correction for Time-Lag and Bias Errors in Vaisala RS80-H Radiosonde Humidity Measurements  

NLE Websites -- All DOE Office Websites (Extended Search)

In Situ Validation of a Correction for Time-Lag and In Situ Validation of a Correction for Time-Lag and Bias Errors in Vaisala RS80-H Radiosonde Humidity Measurements L. M. Miloshevich National Center for Atmospheric Research Boulder, Colorado H. Vömel and S. J. Oltmans National Oceanic and Atmospheric Administration Boulder, Colorado A. Paukkunen Vaisala Oy Helsinki, Finland Introduction Radiosonde relative humidity (RH) measurements are fundamentally important to Atmospheric Radiation Measurement (ARM) Program goals because they are used in a wide variety of both operational and research applications, including initialization of numerical models and evaluation of model results, validation of remote-sensor water vapor retrievals, construction of water vapor climatologies and studies of climate trends, parameterization of cloud processes, and as input to

449

Solar Energy Research Institute Validation Test House Site Handbook  

DOE Green Energy (OSTI)

The Validation Test House at the Solar Energy Research Institute in Golden, Colorado, is being used to collect performance data for analysis/design tool validation as part of the DOE Passive Solar Class A Performance Evaluation Program.

Burch, J.; Wortman, D.; Judkoff, R.; Hunn, B.

1985-05-01T23:59:59.000Z

450

Validation of Autodesk Ecotect accuracy for thermal and daylighting simulations  

Science Conference Proceedings (OSTI)

Autodesk Ecotect is an environmental analysis software which according to the U.S. Department of Energy, has not been validated yet. Therefore, the objectives of this research were to validate accuracy of Ecotect for thermal and daylighting ...

Prasanthi R. Vangimalla; Svetlana J. Olbina; Raymond R. Issa; Jimmie Hinze

2011-12-01T23:59:59.000Z

451

Ground Validation for the Tropical Rainfall Measuring Mission (TRMM)  

Science Conference Proceedings (OSTI)

An overview of the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) Program is presented. This ground validation (GV) program is based at NASA Goddard Space Flight Center in Greenbelt, Maryland, and is responsible for processing ...

David B. Wolff; D. A. Marks; E. Amitai; D. S. Silberstein; B. L. Fisher; A. Tokay; J. Wang; J. L. Pippitt

2005-04-01T23:59:59.000Z

452

A Ground Validation Network for the Global Precipitation Measurement Mission  

Science Conference Proceedings (OSTI)

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASAs Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. ...

Mathew R. Schwaller; K. Robert Morris

2011-03-01T23:59:59.000Z

453

Plug-In Hybrid Electric Vehicles - PHEV Modeling - Model Validation  

NLE Websites -- All DOE Office Websites (Extended Search)

Chevy Equinox, Ford Explorer) have been validated within 1% of fuel economy. Hybrid electric vehicles (e.g., Honda Insight, Toyota Prius, Lexus RX400h) have been validated...

454

Cross-Validation in Statistical Climate Forecast Models  

Science Conference Proceedings (OSTI)

Cross-validation is a statistical procedure that produces an estimate of forecast skill which is less biased than the usual hindcast skill estimates. The cross-validation method systematically deletes one or more cases in a dataset, derives a ...

Joel Michaelsen

1987-11-01T23:59:59.000Z

455

Empirical Validation of a Transient Computer Model for ...  

Science Conference Proceedings (OSTI)

Page 1. _ EMPIRICAL VALIDATION OF A lRANSIENT COMPUTER MODEL FOR COMBINED HEAT AND MOISTURE TRANSFER ...

1997-09-03T23:59:59.000Z

456

THE EXPERIMENTALLY VALIDATED Mg-C PHASE DIAGRAM AND ...  

Science Conference Proceedings (OSTI)

Jul 20, 2012 ... CARBON IN MG ALLOYS: THE EXPERIMENTALLY VALIDATED Mg-C PHASE DIAGRAM AND THERMODYNAMIC CALCULATIONS IN...

457

Controlled Hydrogen Fleet and Infrastructure Demonstration and Validation Project  

DOE Green Energy (OSTI)

Graphs of composite data products produced by DOE's Controlled Hydrogen Fleet and Infrastructure Demonstration and Validation project through September 2010.

Wipke, K.; Spirk, S.; Kurtz, J.; Ramsden, T.

2010-09-01T23:59:59.000Z

458

Run-time validation of knowledge-based systems  

Science Conference Proceedings (OSTI)

As knowledge bases become more complex it is increasingly unlikely that they will have been validated against all possible data and therefore an increasing risk of making errors. Run-time validation is checking whether the output of a knowledge base ... Keywords: anomalies, outliers, prudence, ripple-down rules, validation

Angela Finlayson, Paul Compton

2013-06-01T23:59:59.000Z

459

A four-way framework for validating a specification  

Science Conference Proceedings (OSTI)

The validation of a software specification may be viewed as a function of what the specification is to be used for and any comprehensive validation exercise needs to address possibly conflicting requirements. In this paper we develop a framework which ... Keywords: formal specification, requirements, spiral model, validation

Cyrille Dongmo; John A. van der Poll

2010-10-01T23:59:59.000Z

460

Validation of solar system simulation codes by the International Energy Agency  

DOE Green Energy (OSTI)

Validation of active solar energy system simulation codes by the International Energy Agency using data from the Los Alamos Study Center is described. Two rounds of comparisons of predicted to measured performance were completed. In the first round, all participants were given detailed system description data and a period of measured hourly weather and loads data with the corresponding measured hourly performance data. In the second round, the participants were given minor changes to the system description and a second period of measured weather and loads data without the corresponding measured hourly performance. In the first round, each of the participants was able to predict the results provided. However, this required an undocumented series of adjustments to the user input and the models and comparisons of measured and predicted results. Agreement of measured and predicted results were nearly as good in the second round except for two codes that predicted significantly erroneous results. As a result of this exercise, errors and shortcomings have been found and corrected in most of the codes and confidence in the ability of all codes to model real systems has been increased. However, the questions of a workable methodology for validation and the means of dealing with user error remain unanswered.

Hedstrom, J.C.; Freeman, T.L.

1980-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "wicket input validation" from the National Library of EnergyBeta (NLEBeta).
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461

Documentation of Calculation Methodology, Input data, and Infrastructure for the Home Energy Saver Web Site  

SciTech Connect

The Home Energy Saver (HES, http://HomeEnergySaver.lbl.gov) is an interactive web site designed to help residential consumers make decisions about energy use in their homes. This report describes the underlying methods and data for estimating energy consumption. Using engineering models, the site estimates energy consumption for six major categories (end uses); heating, cooling, water heating, major appliances, lighting, and miscellaneous equipment. The approach taken by the Home Energy Saver is to provide users with initial results based on a minimum of user input, allowing progressively greater control in specifying the characteristics of the house and energy consuming appliances. Outputs include energy consumption (by fuel and end use), energy-related emissions (carbon dioxide), energy bills (total and by fuel and end use), and energy saving recommendations. Real-world electricity tariffs are used for many locations, making the bill estimates even more accurate. Where information about the house is not available from the user, default values are used based on end-use surveys and engineering studies. An extensive body of qualitative decision-support information augments the analytical results.

Pinckard, Margaret J.; Brown, Richard E.; Mills, Evan; Lutz, James D.; Moezzi, Mithra M.; Atkinson, Celina; Bolduc, Chris; Homan, Gregory K.; Coughlin, Katie

2005-07-13T23:59:59.000Z

462

Development of a Novel Bi-Directional Isolated Multiple-Input DC-DC Converter  

DOE Green Energy (OSTI)

There is vital need for a compact, lightweight, and efficient energy-storage system that is both affordable and has an acceptable cycle life for the large-scale production of electric vehicles (EVs) and hybrid electric vehicles (HEVs). Most of the current research employs a battery-storage unit (BU) combined with a fuel cell (FC) stack in order to achieve the operating voltage-current point of maximum efficiency for the FC system. A system block diagram is shown in Fig.1.1. In such a conventional arrangement, the battery is sized to deliver the difference between the energy required by the traction drive and the energy supplied by the FC system. Energy requirements can increase depending on the drive cycle over which the vehicle is expected to operate. Peak-power transients result in an increase of losses and elevated temperatures which result in a decrease in the lifetime of the battery. This research will propose a novel two-input direct current (dc) dc to dc converter to interface an additional energy-storage element, an ultracapacitor (UC), which is shown in Fig.1.2. It will assist the battery during transients to reduce the peak-power requirements of the battery.

Li, H.

2005-10-24T23:59:59.000Z

463

LLNL Input to SNL L2 MS: Report on the Basis for Selection of Disposal Options  

Science Conference Proceedings (OSTI)

This mid-year deliverable has two parts. The first part is a synopsis of J. Blink's interview of the former Nevada Attorney General, Frankie Sue Del Papa, which was done in preparation for the May 18-19, 2010 Legal and Regulatory Framework Workshop held in Albuquerque. The second part is a series of sections written as input for the SNL L2 Milestone M21UF033701, due March 31, 2011. Disposal of high-level radioactive waste is categorized in this review into several categories. Section II discusses alternatives to geologic disposal: space, ice-sheets, and an engineered mountain or mausoleum. Section III discusses alternative locations for mined geologic disposal: islands, coastlines, mid-continent, and saturated versus unsaturated zone. Section IV discusses geologic disposal alternatives other than emplacement in a mine: well injection, rock melt, sub-seabed, and deep boreholes in igneous or metamorphic basement rock. Finally, Secton V discusses alternative media for mined geologic disposal: basalt, tuff, granite and other igneous/metamorphic rock, alluvium, sandstone, carbonates and chalk, shale and clay, and salt.

Sutton, M; Blink, J A; Halsey, W G

2011-03-02T23:59:59.000Z

464

Systematic approach to verification and validation: High explosive burn models  

SciTech Connect

Most material models used in numerical simulations are based on heuristics and empirically calibrated to experimental data. For a specific model, key questions are determining its domain of applicability and assessing its relative merits compared to other models. Answering these questions should be a part of model verification and validation (V and V). Here, we focus on V and V of high explosive models. Typically, model developers implemented their model in their own hydro code and use different sets of experiments to calibrate model parameters. Rarely can one find in the literature simulation results for different models of the same experiment. Consequently, it is difficult to assess objectively the relative merits of different models. This situation results in part from the fact that experimental data is scattered through the literature (articles in journals and conference proceedings) and that the printed literature does not allow the reader to obtain data from a figure in electronic form needed to make detailed comparisons among experiments and simulations. In addition, it is very time consuming to set up and run simulations to compare different models over sufficiently many experiments to cover the range of phenomena of interest. The first difficulty could be overcome if the research community were to support an online web based database. The second difficulty can be greatly reduced by automating procedures to set up and run simulations of similar types of experiments. Moreover, automated testing would be greatly facilitated if the data files obtained from a database were in a standard format that contained key experimental parameters as meta-data in a header to the data file. To illustrate our approach to V and V, we have developed a high explosive database (HED) at LANL. It now contains a large number of shock initiation experiments. Utilizing the header information in a data file from HED, we have written scripts to generate an input file for a hydro code, run a simulation, and generate a comparison plot showing simulated and experimental velocity gauge data. These scripts are then applied to several series of experiments and to several HE burn models. The same systematic approach is applicable to other types of material models; for example, equations of state models and material strength models.

Menikoff, Ralph [Los Alamos National Laboratory; Scovel, Christina A. [Los Alamos National Laboratory

2012-04-16T23:59:59.000Z

465

ISOTHERMAL AIR-INGRESS VALIDATION EXPERIMENTS  

Science Conference Proceedings (OSTI)

Idaho National Laboratory has conducted airingress experiments as part of a campaign to validate computational fluid dynamics (CFD) calculations for very high-temperature gas-cooled reactor (VHTR) analysis. An isothermal test loop was designed to recreate exchange or stratified flow that occurs in the lower plenum of VHTR after a break in the primary loop allows helium to leak out and reactor building air to enter the reactor core. The experiment was designed to measure stratified flow in the inlet pipe connecting to the lower plenum of the General Atomics gas turbinemodular helium reactor (GT-MHR). Instead of helium and air, brine and sucrose were used as heavy fluids, and water was used as the lighter fluid to create, using scaling laws, the appropriate flow characteristics of the lower plenum immediately after depressurization. These results clearly indicate that stratified flow is established even for very small density differences. Corresponding CFD results were validated with the experimental data. A grid sensitivity study on CFD models was also performed using the Richardson extrapolation and the grid convergence index method for the numerical accuracy of CFD calculations. The calculated current speed showed very good agreement with the experimental data, indicating that current CFD methods are suitable for simulating density gradient stratified flow phenomena in an air-ingress accident.

Chang H. Oh; Eung S. Kim

2013-01-01T23:59:59.000Z

466

Verification and validation for induction heating  

SciTech Connect

Truchas is a software package being developed at LANL within the Telluride project for predicting the complex physical processes in metal alloy casting. The software was designed to be massively parallel, multi-material, multi-physics, and to run on 3D, fully unstructured meshes. This work describes a Verification and Validation assessment of Truchas for simulating the induction heating phase of a casting process. We used existing data from a simple experiment involving the induction heating of a graphite cylinder, as graphite is a common material used for mold assemblies. Because we do not have complete knowledge of all the conditions and properties in this experiment (as is the case in many other experiments), we performed a parameter sensitivity study, modeled the uncertainties of the most sensitive parameters, and quantified how these uncertainties propagate to the Truchas output response. A verification analysis produced estimates of the numerical error of the Truchas solution to our computational model. The outputs from Truchas runs with randomly sampled parameter values were used for the validation study.

Lam, Kin [Los Alamos National Laboratory; Tippetts, Trevor B [Los Alamos National Laboratory; Allen, David W [NON LANL

2008-01-01T23:59:59.000Z

467

Validation of New Wind Resource Maps: Preprint  

DOE Green Energy (OSTI)

The National Renewable Energy Laboratory (NREL) recently led a project to validate updated state wind resource maps for the northwestern United States produced by a private U.S. company, TrueWind Solutions (TWS). The independent validation project was a cooperative activity among NREL, TWS, and meteorological consultants. It became clear that using a numerical modeling approach for wind resource mapping was rapidly gaining ground as a preferred technique and if the trend continues, it will soon become the most widely used technique around the world. The numerical modeling approach is a relatively fast application compared to older mapping methods and, in theory, should be quite accurate because it directly estimates the magnitude of boundary-layer processes that affect the wind resource of a particular location. Numerical modeling output combined with high-resolution terrain data can produce useful wind resource information at a resolution of 1 km or lower. However, because the use of the numerical modeling approach is new (last 3-5 years) and relatively unproven, meteorological consultants question the accuracy of the approach.

Elliott, D.; Schwartz, M.

2002-05-01T23:59:59.000Z

468

CASL Validation Data: An Initial Review  

SciTech Connect

The study aims to establish a comprehensive view of data needed for supporting implementation of the Consortium of Advanced Simulation of LWRs (CASL). Insights from this review (and its continual refinement), together with other elements developed in CASL, should provide the foundation for developing the CASL Validation Data Plan (VDP). VDP is instrumental to the development and assessment of CASL simulation tools as predictive capability. Most importantly, to be useful for CASL, the VDP must be devised (and agreed upon by all participating stakeholders) with appropriate account for nature of nuclear engineering applications, the availability, types and quality of CASL-related data, and novelty of CASL goals and its approach to the selected challenge problems. The initial review (summarized on the January 2011 report version) discusses a broad range of methodological issues in data review and Validation Data Plan. Such a top-down emphasis in data review is both needed to see a big picture on CASL data and appropriate when the actual data are not available for detailed scrutiny. As the data become available later in 2011, a revision of data review (and regular update) should be performed. It is expected that the basic framework for review laid out in this report will help streamline the CASL data review in a way that most pertinent to CASL VDP.

Nam Dinh

2011-01-01T23:59:59.000Z

469

US-CERT Control System Center Input/Output (I/O) Conceputal Design  

Science Conference Proceedings (OSTI)

This document was prepared for the US-CERT Control Systems Center of the National Cyber Security Division (NCSD) of the Department of Homeland Security (DHS). DHS has been tasked under the Homeland Security Act of 2002 to coordinate the overall national effort to enhance the protection of the national critical infrastructure. Homeland Security Presidential Directive HSPD-7 directs the federal departments to identify and prioritize critical infrastructure and protect it from terrorist attack. The US-CERT National Strategy for Control Systems Security was prepared by the NCSD to address the control system security component addressed in the National Strategy to Secure Cyberspace and the National Strategy for the Physical Protection of Critical Infrastructures and Key Assets. The US-CERT National Strategy for Control Systems Security identified five high-level strategic goals for improving cyber security of control systems; the I/O upgrade described in this document supports these goals. The vulnerability assessment Test Bed, located in the Information Operations Research Center (IORC) facility at Idaho National Laboratory (INL), consists of a cyber test facility integrated with multiple test beds that simulate the nation's critical infrastructure. The fundamental mission of the Test Bed is to provide industry owner/operators, system vendors, and multi-agency partners of the INL National Security Division a platform for vulnerability assessments of control systems. The Input/Output (I/O) upgrade to the Test Bed (see Work Package 3.1 of the FY-05 Annual Work Plan) will provide for the expansion of assessment capabilities within the IORC facility. It will also provide capabilities to connect test beds within the Test Range and other Laboratory resources. This will allow real time I/O data input and communication channels for full replications of control systems (Process Control Systems [PCS], Supervisory Control and Data Acquisition Systems [SCADA], and components). This will be accomplished through the design and implementation of a modular infrastructure of control system, communications, networking, computing and associated equipment, and measurement/control devices. The architecture upgrade will provide a flexible patching system providing a quick ''plug and play''configuration through various communication paths to gain access to live I/O running over specific protocols. This will allow for in-depth assessments of control systems in a true-to-life environment. The full I/O upgrade will be completed through a two-phased approach. Phase I, funded by DHS, expands the capabilities of the Test Bed by developing an operational control system in two functional areas, the Science & Technology Applications Research (STAR) Facility and the expansion of various portions of the Test Bed. Phase II (see Appendix A), funded by other programs, will complete the full I/O upgrade to the facility.

Not Available

2005-02-01T23:59:59.000Z

470

Energy Input and Mass Redistribution by Supernovae in the Interstellar Medium  

E-Print Network (OSTI)

We present the results of numerical studies of supernova remnant evolution and their effects on galactic and globular cluster evolution. We show that parameters such as the density and the metallicity of the environment significantly influence the evolution of the remnant, and thus change its effects on the global environment (e.g., globular clusters, galaxies) as a source of thermal and kinetic energy. We conducted our studies using a one-dimensional hydrodynamics code, in which we implemented a metallicity dependent cooling function. Global time-dependent quantities such as the total kinetic and thermal energies and the radial extent are calculated for a grid of parameter sets. The quantities calculated are the total energy, the kinetic energy, the thermal energy, the radial extent, and the mass. We distinguished between the hot, rarefied bubble and the cold, dense shell, as those two phases are distinct in their roles in a gas-stellar system. We also present power-law fits to those quantities as a function of environmental parameters after the extensive cooling has ceased. The power-law fits enable simple incorporation of improved supernova energy input and matter redistribution (including the effect of the local conditions) in galactic/globular cluster models. Our results for the energetics of supernova remnants in the late stages of their expansion give total energies ranging from 9e49 to 3e50 ergs, with a typical case being 1e50 erg, depending on the surrounding environment. About 8.5e49 erg of this energy can be found in the form of kinetic energy. Supernovae play an important role in the evolution of the interstellar medium

Katsuyo Thornton; Michael Gaudlitz; Hans-Thomas Janka; Matthias Steinmetz

1997-06-17T23:59:59.000Z

471

Quality assurance with the ISFH-Input/Output-Procedure 6-year-experience with 14 solar thermal systems  

E-Print Network (OSTI)

an auxiliary heater supplies the consumers with warm water even in the case of failures. In order to assureQuality assurance with the ISFH-Input/Output-Procedure 6-year-experience with 14 solar thermal of standard solar thermal systems usually don't recognise failures affecting the solar yield, because

472

Introduction to Solar Energy Conversion Solar energy represents the largest energy input into the terrestrial system. Despite its  

E-Print Network (OSTI)

of the resource to allow supply to meet demand at all times. Photovoltaic energy conversion efficiency hasIntroduction to Solar Energy Conversion Solar energy represents the largest energy input the global energy demand on its own. The challenges that need to be addressed to make solar energy viable

Nur, Amos

473

Modelling regional input markets with numerous processing plants: The case of green maize for biogas production in Germany  

Science Conference Proceedings (OSTI)

The location of first generation processing plants for biogas using bulky inputs is a prominent example of locational decisions of plants that face high per unit transport costs of feedstock and simultaneously depend to a large extent on feedstock availability. ... Keywords: Biogas, Biomass transportation, Competitive facility location, Modelling, Transport costs

Ruth Delzeit; Wolfgang Britz; Karin Holm-Mller

2012-06-01T23:59:59.000Z

474

Cross evaluation using weight restrictions in unitary input DEA models: theoretical aspects and application to olympic games ranking  

Science Conference Proceedings (OSTI)

There is no official method to establish a final ranking for the Olympic Games. The usual ranking is based on the Lexicographic Multicriteria Method, the main drawback of which is to overvalue gold medals. Furthermore, it does not take into account the ... Keywords: cross evaluation, data envelopment analysis, ranking, unitary input, weights restrictions

Joo Carlos Correia Baptista Soares De Mello; Eliane Gonalves Gomes; Lidia Angulo Meza; Luiz Biondi Neto

2008-01-01T23:59:59.000Z

475

Input devices in mental health applications: steering performance in a virtual reality paths with WiiMote  

Science Conference Proceedings (OSTI)

Recent studies present Virtual Reality (VR) as potentially effective technology in the Mental Health (MH) field. The objective of this paper is to evaluate two interaction techniques (traditional vs novel) using a popular and low-cost input device (WiiMote) ... Keywords: mental health, steering law, virtual reality

Maja Wrzesien; Mara Jos Ruprez; Mariano Alcaiz

2011-09-01T23:59:59.000Z

476

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

SciTech Connect

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.

Rogge, Nicky, E-mail: Nicky.Rogge@hubrussel.be [Hogeschool-Universiteit Brussel (HUBrussel), Center for Business Management Research (CBMR), Warmoesberg 26, 1000 Brussels (Belgium); Katholieke Universiteit Leuven (KULeuven), Faculty of Business and Economics, Naamsestraat 69, 3000 Leuven (Belgium); De Jaeger, Simon [Katholieke Universiteit Leuven (KULeuven), Faculty of Business and Economics, Naamsestraat 69, 3000 Leuven (Belgium); Hogeschool-Universiteit Brussel (HUBrussel), Center for Economics and Corporate Sustainability (CEDON), Warmoesberg 26, 1000 Brussels (Belgium)

2012-10-15T23:59:59.000Z

477

Uncertainties in Predicted Ozone Concentrations Due to Input Uncertainties for the UAM-V Photochemical Grid Model  

Science Conference Proceedings (OSTI)

Based on studies of ozone episodes in the eastern United States using the photochemical grid model, UAM-V, regulatory agencies have made decisions concerning emissions controls. This project analyzes effects of uncertainties in UAM-V input variables (emissions, initial and boundary conditions, meteorological variables, and chemical reactions) on uncertainties in UAM-V ozone predictions for the July 1995 episode.

2000-11-06T23:59:59.000Z

478

ELIMINATING CONSERVATISM IN THE PIPING SYSTEM ANALYSIS PROCESS THROUGH APPLICATION OF A SUITE OF LOCALLY APPROPRIATE SEISMIC INPUT MOTIONS  

SciTech Connect

Seismic analysis is of great importance in the evaluation of nuclear systems due to the heavy influence such loading has on their designs. Current Department of Energy seismic analysis techniques for a nuclear safety-related piping system typically involve application of a single conservative seismic input applied to the entire system [1]. A significant portion of this conservatism comes from the need to address the overlapping uncertainties in the seismic input and in the building response that transmits that input motion to the piping system. The approach presented in this paper addresses these two sources of uncertainty through the application of a suite of 32 input motions whose collective performance addresses the total uncertainty while each individual motion represents a single variation of it. It represents an extension of the soil-structure interaction analysis methodology of SEI/ASCE 43-05 [2] from the structure to individual piping components. Because this approach is computationally intensive, automation and other measures have been developed to make such an analysis efficient. These measures are detailed in this paper.

Anthony L. Crawford; Robert E. Spears, Ph.D.; Mark J. Russell

2009-07-01T23:59:59.000Z

479

Performance of joint transmit scheme assisted multiple-input multiple-output multi-carrier IDMA system  

Science Conference Proceedings (OSTI)

In this paper, we present the performance of a multiple-input multiple-output multi-carrier interleave division multiple access (MC-IDMA) system assisted by combined vertical Bell Laboratories layered space-time architecture and space-time block code ...

K. S. Vishvaksenan, R. Seshasayanan, Yuvaraj Krishnamoorthy

2013-04-01T23:59:59.000Z

480

DOE Lighting Program Update: LED Validation Activities  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

DOE Lighting Program Update DOE Lighting Program Update LED Validation Activities Kelly Gordon Pacific Northwest National Laboratory Federal Utility Partnership Working Group April 15, 2010 Providence, RI www.ssl.energy.gov 2 | Solid-State Lighting Program Legislative Mandate The DOE is directed by U.S. government policy (EPACT 2005, Section 912) to: "...support research, development, demonstration, and commercial application activities related to advanced solid-state lighting technologies based on white light emitting diodes." DOE Lighting Program www.ssl.energy.gov 3 | Solid-State Lighting Program SSL Energy Saving Potential By 2030: * Potential to cut U.S. lighting electricity use by 25% * Cumulative energy savings: $120 billion * Annual energy savings equivalent to:

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


481

Data Validation Procedure for Chemical Analysis  

E-Print Network (OSTI)

This report has been reproduced from the best available copy. Available in paper copy and microfiche. Available for a process ing fee to U.S. Department of Energy and its contractors from: U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62 Oak Ridge, TN 37831-0062 (865) 576-8401 fax: (865) 576-5728 email: reports@adonis.osti.gov online ordering: http://www.doe.gov/bridge Available for sale to the public, in paper, from: U.S. Department of Commerce National Technical Information Service 5285 Port Royal Road Springfield, VA 22161 (800) 553-6847 fax: (703) 605.6900 email: orders@ntis.fedworld.gov online ordering: http://www.ntis.gov/ordering.htm Printed in the United States of America DISCLM-5.CHP (11/99) BHI-01435 Rev. 0 Data Validation Procedure for Chemical Analysis Author

Uhsduhg Ir Uhsduhg

2000-01-01T23:59:59.000Z

482

Boron-10 Lined Proportional Counter Model Validation  

SciTech Connect

The Department of Energy Office of Nuclear Safeguards (NA-241) is supporting the project Coincidence Counting With Boron-Based Alternative Neutron Detection Technology at Pacific Northwest National Laboratory (PNNL) for the development of an alternative neutron coincidence counter. The goal of this project is to design, build and demonstrate a boron-lined proportional tube-based alternative system in the configuration of a coincidence counter. This report discusses the validation studies performed to establish the degree of accuracy of the computer modeling methods current used to simulate the response of boron-lined tubes. This is the precursor to developing models for the uranium neutron coincidence collar under Task 2 of this project.

Lintereur, Azaree T.; Siciliano, Edward R.; Kouzes, Richard T.

2012-06-30T23:59:59.000Z

483

Lindblad's epicycles - valid method or bad science?  

E-Print Network (OSTI)

The study of Galactic orbits in the last eighty years has been dominated by statistical assumptions made because of the lack of empirical evidence available in the early 20th century. Using evidence from Hipparcos and recent radial velocity surveys, Francis and Anderson recently showed that spiral structure is primarily a consequence of gravitational alignments of stellar orbits. I review the mechanism which creates spiral structure, consider the validity of widely held assumptions in galactic dynamics and the implications to notions such as the asymmetric drift and disc heating. I identify a number of fundamental mathematical and physical errors in L