National Library of Energy BETA

Sample records for relative standard error

  1. Table 1b. Relative Standard Errors for Effective, Occupied, and...

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

    b.Relative Standard Errors Table 1b. Relative Standard Errors for Effective Occupied, and Vacant Square Footage, 1992 Building Characteristics All Buildings (thousand) Total...

  2. Table 2b. Relative Standard Errors for Electricity Consumption...

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

    2b. Relative Standard Errors for Electricity Table 2b. Relative Standard Errors for Electricity Consumption and Electricity Intensities, per Square Foot, Specific to Occupied and...

  3. Table 6b. Relative Standard Errors for Total Electricity Consumption...

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

    b. Relative Standard Errors for Total Electricity Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Electricity (thousand) Total...

  4. Table 4b. Relative Standard Errors for Total Fuel Oil Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    4b. Relative Standard Errors for Total Fuel Oil Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Fuel Oil (thousand) Total Fuel Oil...

  5. RSE Table 10.12 Relative Standard Errors for Table 10.12

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

    2 Relative Standard Errors for Table 10.12;" " Unit: Percents." ,,"LPG",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  6. RSE Table 10.13 Relative Standard Errors for Table 10.13

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

    3 Relative Standard Errors for Table 10.13;" " Unit: Percents." ,,"LPG(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  7. RSE Table 3.5 Relative Standard Errors for Table 3.5

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

    5 Relative Standard Errors for Table 3.5;" " Unit: Percents." " "," "," "," "," "," "," "," ","Waste",," " " "," "," ","Blast"," "," ","Pulping Liquor"," ","Oils/Tars" "NAICS"," ","

  8. RSE Table 7.6 Relative Standard Errors for Table 7.6

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

    6 Relative Standard Errors for Table 7.6;" " Unit: Percents." " "," " " "," ",,,,,,,,," " "NAICS"," "," ",,"Residual","Distillate","Natural ","LPG and",,"Coke" "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel

  9. RSE Table 8.2 Relative Standard Errors for Table 8.2

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

    2 Relative Standard Errors for Table 8.2;" " Unit: Percents." " "," ",,"Computer Control of Building Wide Evironment(c)",,,"Computer Control of Processes or Major Energy-Using Equipment(d)",,,"Waste Heat Recovery",,,"Adjustable - Speed Motors",,,"Oxy - Fuel Firing" " "," " "NAICS"," " "Code(a)","Subsector and

  10. RSE Table 10.10 Relative Standard Errors for Table 10.10

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

    0 Relative Standard Errors for Table 10.10;" " Unit: Percents." ,,"Coal",,,"Alternative Energy Sources(b)" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Gas","Fuel

  11. RSE Table 10.11 Relative Standard Errors for Table 10.11

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

    1 Relative Standard Errors for Table 10.11;" " Unit: Percents." ,,"Coal(b)",,,"Alternative Energy Sources(c)" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual" "Code(a)","Subsector and Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel

  12. RSE Table 2.1 Relative Standard Errors for Table 2.1

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

    2.1 Relative Standard Errors for Table 2.1;" " Unit: Percents." " "," " " "," " "NAICS"," "," ","Residual","Distillate","Natural ","LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","and

  13. RSE Table 5.1 Relative Standard Errors for Table 5.1

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

    1 Relative Standard Errors for Table 5.1;" " Unit: Percents." " "," " " "," "," ",," ","Distillate"," "," ",," " " "," ",,,,"Fuel Oil",,,"Coal" "NAICS"," "," ","Net","Residual","and","Natural ","LPG and","(excluding Coal"," "

  14. RSE Table 5.2 Relative Standard Errors for Table 5.2

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

    2 Relative Standard Errors for Table 5.2;" " Unit: Percents." " "," "," ",," ","Distillate"," "," ",," " " "," ",,,,"Fuel Oil",,,"Coal" "NAICS"," "," ","Net","Residual","and","Natural ","LPG and","(excluding Coal"," " "Code(a)","End

  15. RSE Table 5.4 Relative Standard Errors for Table 5.4

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

    4 Relative Standard Errors for Table 5.4;" " Unit: Percents." " "," ",," ","Distillate"," "," " " "," ","Net Demand",,"Fuel Oil",,,"Coal" "NAICS"," ","for ","Residual","and","Natural ","LPG and","(excluding Coal" "Code(a)","End Use","Electricity(b)","Fuel

  16. RSE Table 5.5 Relative Standard Errors for Table 5.5

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

    5 Relative Standard Errors for Table 5.5;" " Unit: Percents." " "," ",," ",," "," ",," " " ",,,,"Distillate" " "," ",,,"Fuel Oil",,,"Coal"," " " ",,"Net","Residual","and","Natural","LPG and","(excluding Coal" "End Use","Total","Electricity(a)","Fuel

  17. RSE Table 5.6 Relative Standard Errors for Table 5.6

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

    6 Relative Standard Errors for Table 5.6;" " Unit: Percents." " "," ",," ","Distillate"," "," ",," " " ",,,,"Fuel Oil",,,"Coal" " "," ","Net","Residual","and","Natural","LPG and","(excluding Coal"," " "End Use","Total","Electricity(a)","Fuel

  18. RSE Table 5.7 Relative Standard Errors for Table 5.7

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

    7 Relative Standard Errors for Table 5.7;" " Unit: Percents." " ",,,"Distillate" " ","Net Demand",,"Fuel Oil",,,"Coal" " ","for ","Residual","and","Natural ","LPG and","(excluding Coal" "End Use","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Gas(c)","NGL(d)","Coke and Breeze)"

  19. RSE Table 5.8 Relative Standard Errors for Table 5.8

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

    8 Relative Standard Errors for Table 5.8;" " Unit: Percents." " ",," ","Distillate"," "," " " ","Net Demand",,"Fuel Oil",,,"Coal" " ","for ","Residual","and","Natural ","LPG and","(excluding Coal" "End Use","Electricity(a)","Fuel Oil","Diesel

  20. RSE Table 7.4 Relative Standard Errors for Table 7.4

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

    4 Relative Standard Errors for Table 7.4;" " Unit: Percents." " ",," "," ",," "," " "Economic",,"Residual","Distillate","Natural ","LPG and" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal" ,"Total United States" "Value of Shipments and Receipts"

  1. RSE Table 7.5 Relative Standard Errors for Table 7.5

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

    5 Relative Standard Errors for Table 7.5;" " Unit: Percents." " ",," "," ",," "," " "Economic",,"Residual","Distillate","Natural ","LPG and" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal" ,"Total United States" "Value of Shipments and Receipts"

  2. RSE Table 7.9 Relative Standard Errors for Table 7.9

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

    9 Relative Standard Errors for Table 7.9;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " " "," " "NAICS"," "," ",,"Residual","Distillate","Natural ","LPG and",,"Coke"," " "Code(a)","Subsector and

  3. "RSE Table C1.1. Relative Standard Errors for Table C1.1;"

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

    .1. Relative Standard Errors for Table C1.1;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," "," " " "," ","Any",," "," ",," "," ",," ","Shipments" "NAICS"," ","Energy","Net","Residual","Distillate",,"LPG

  4. "RSE Table C10.2. Relative Standard Errors for Table C10.2;"

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

    2. Relative Standard Errors for Table C10.2;" " Unit: Percents." ,,,"Establishments" " "," ",,"with Any"," Steam Turbines","Supplied","by Either","Conventional","Combustion","Turbines"," "," "," ","Internal","Combustion","Engines"," Steam Turbines","Supplied","by Heat",," " "

  5. "RSE Table E1.1. Relative Standard Errors for Table E1.1;"

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

    .1. Relative Standard Errors for Table E1.1;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," " " "," ",," "," ",," "," ",," ","Shipments" "Economic",,"Net","Residual","Distillate",,"LPG and",,"Coke and"," ","of Energy

  6. "RSE Table E13.2. Relative Standard Errors for Table E13.2;"

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

    2. Relative Standard Errors for Table E13.2;" " Unit: Percents." " ",,,"Renewable Energy" ,,,"(excluding Wood" "Economic","Total Onsite",,"and" "Characteristic(a)","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)" ,"Total United States" "Value of Shipments and Receipts" "(million dollars)" " Under 20",15,15,58,37 "

  7. "RSE Table E13.3. Relative Standard Errors for Table E13.3;"

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

    3. Relative Standard Errors for Table E13.3;" " Unit: Percents." ,"Total of" "Economic","Sales and","Utility","Nonutility" "Characteristic(a)","Transfers Offsite","Purchaser(b)","Purchaser(c)" ,"Total United States" "Value of Shipments and Receipts" "(million dollars)" " Under 20",4,4,10 " 20-49",33,35,70 " 50-99",10,12,10 "

  8. "RSE Table E7.1. Relative Standard Errors for Table E7.1;"

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

    1. Relative Standard Errors for Table E7.1;" " Unit: Percents." ,,,"Consumption" " ",,"Consumption","per Dollar" "Economic","Consumption","per Dollar","of Value" "Characteristic(a)","per Employee","of Value Added","of Shipments" ,"Total United States" "Value of Shipments and Receipts" "(million dollars)" " Under 20",2,2,2

  9. "RSE Table E7.2. Relative Standard Errors for Table E7.2;"

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

    2. Relative Standard Errors for Table E7.2;" " Unit: Percents." " "," ",,,"Consumption" " "," ",,"Consumption","per Dollar" "NAICS",,"Consumption","per Dollar","of Value" "Code(a)","Economic Characteristic(b)","per Employee","of Value Added","of Shipments" ,,"Total United States" " 311 - 339","ALL

  10. "RSE Table N1.3. Relative Standard Errors for Table N1.3;"

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

    .3. Relative Standard Errors for Table N1.3;" " Unit: Percents." " "," " ,"Total" "Energy Source","First Use" ,"Total United States" "Coal ",3 "Natural Gas",1 "Net Electricity",1 " Purchases",1 " Transfers In",9 " Onsite Generation from Noncombustible Renewable Energy",15 " Sales and Transfers Offsite",3 "Coke and Breeze",2 "Residual Fuel

  11. "RSE Table N13.3. Relative Standard Errors for Table N13.3;"

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

    3. Relative Standard Errors for Table N13.3;" " Unit: Percents." " "," ","Total of" "NAICS"," ","Sales and","Utility","Nonutility" "Code(a)","Subsector and Industry","Transfers Offsite","Purchaser(b)","Purchaser(c)" ,,"Total United States" , 311,"Food",8,9,0 311221," Wet Corn Milling",0,0,0 312,"Beverage and Tobacco

  12. "RSE Table N5.2. Relative Standard Errors for Table N5.2;"

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

    2. Relative Standard Errors for Table N5.2;" " Unit: Percents." ,,"S e l e c t e d","W o o d","a n d","W o o d -","R e l a t e d","P r o d u c t s" ,,,,,"B i o m a s s" ,,,,,,"Wood Residues" ,,,,,,"and","Wood-Related" " "," ","Pulping Liquor"," "," ","Wood","Byproducts","and",," "

  13. RSE Table N8.1 and N8.2. Relative Standard Errors for Tables N8.1 and N8.2

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

    1 and N8.2. Relative Standard Errors for Tables N8.1 and N8.2;" " Unit: Percents." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected","Wood and Other","Biomass","Components" ,,,,,,,"Coal Components",,,"Coke",,"Electricity","Components",,,,,,,,,,,,,"Natural Gas","Components",,"Steam","Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood

  14. RSE Table E6.1 and E6.2. Relative Standard Errors for Tables E6.1 and E6.2

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

    E6.1 and E6.2. Relative Standard Errors for Tables E6.1 and E6.2;" " Unit: Percents." " "," ",," ","Distillate"," "," ",," " " ",,,,"Fuel Oil",,,"Coal" " "," ","Net","Residual","and",,"LPG and","(excluding Coal"," " "End Use","Total","Electricity(a)","Fuel

  15. RSE Table E8.1 and E8.2. Relative Standard Errors for Tables E8.1 and E8.2

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

    E8.1 and E8.2. Relative Standard Errors for Tables E8.1 and E8.2;" " Unit: Percents." " ",," "," ",," "," " "Economic",,"Residual","Distillate",,"LPG and" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal" ,"Total United States" "Value of Shipments and Receipts"

  16. RSE Table N1.1 and N1.2. Relative Standard Errors for Tables N1.1 and N1.2

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

    1 and N1.2. Relative Standard Errors for Tables N1.1 and N1.2;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," "," " " "," "," ",," "," ",," "," ",," ","Shipments" "NAICS"," ",,"Net","Residual","Distillate",,"LPG

  17. RSE Table N2.1 and N2.2. Relative Standard Errors for Tables N2.1 and N2.2

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

    N2.1 and N2.2. Relative Standard Errors for Tables N2.1 and N2.2;" " Unit: Percents." " "," " "NAICS"," "," ","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)"

  18. RSE Table N3.1 and N3.2. Relative Standard Errors for Tables N3.1 and N3.2

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

    N3.1 and N3.2. Relative Standard Errors for Tables N3.1 and N3.2;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " "NAICS"," "," ","Net","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and

  19. RSE Table N4.1 and N4.2. Relative Standard Errors for Tables N4.1 and N4.2

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

    N4.1 and N4.2. Relative Standard Errors for Tables N4.1 and N4.2;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " "NAICS"," "," ",,"Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and

  20. RSE Table N6.1 and N6.2. Relative Standard Errors for Tables N6.1 and N6.2

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

    1 and N6.2. Relative Standard Errors for Tables N6.1 and N6.2;" " Unit: Percents." " "," "," ",," ","Distillate"," "," ",," " " "," ",,,,"Fuel Oil",,,"Coal" "NAICS"," "," ","Net","Residual","and",,"LPG and","(excluding Coal"," " "Code(a)","End

  1. RSE Table N6.3 and N6.4. Relative Standard Errors for Tables N6.3 and N6.4

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

    3 and N6.4. Relative Standard Errors for Tables N6.3 and N6.4;" " Unit: Percents." " "," ",," ","Distillate"," "," " " "," ",,,"Fuel Oil",,,"Coal" "NAICS"," ","Net Demand","Residual","and",,"LPG and","(excluding Coal" "Code(a)","End Use","for Electricity(b)","Fuel

  2. RSE Table S1.1 and S1.2. Relative Standard Errors for Tables S1.1 and S1.2

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

    S1.1 and S1.2. Relative Standard Errors for Tables S1.1 and S1.2;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," "," " " "," "," ",," "," ",," "," ",," ","Shipments" "SIC"," ",,"Net","Residual","Distillate",,"LPG

  3. RSE Table S2.1 and S2.2. Relative Standard Errors for Tables S2.1 and S2.2

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

    S2.1 and S2.2. Relative Standard Errors for Tables S2.1 and S2.2;" " Unit: Percents." " "," "," ",," "," "," "," "," "," ",," " "SIC"," "," ","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Major Group and Industry","Total","Fuel Oil","Fuel

  4. RSE Table S3.1 and S3.2. Relative Standard Errors for Tables S3.1 and S3.2

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

    S3.1 and S3.2. Relative Standard Errors for Tables S3.1 and S3.2;" " Unit: Percents." " "," " "SIC"," "," ","Net","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Major Group and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural

  5. Confirmation of standard error analysis techniques applied to...

    Office of Scientific and Technical Information (OSTI)

    reported parameter errors are not reliable in many EXAFS studies in the literature. ... Country of Publication: United States Language: English Subject: 75; ABSORPTION; ACCURACY; ...

  6. Finite Bandwidth Related Errors in Noise Parameter Determination of PHEMTs

    SciTech Connect (OSTI)

    Wiatr, Wojciech

    2005-08-25

    We analyze errors in the determination of the four noise parameters due to finite measurement bandwidth and the delay time in the source circuit. The errors are especially large when characterizing low-noise microwave transistors at low microwave frequencies. They result from the spectral noise density variation across the measuring receiver band, due to resonant interaction of the highly mismatched transistor input with the source termination. We show also effects of virtual de-correlation of transistor's noise waves due to finite delay time at the input.

  7. Department of Energy Labor Relations and Standards

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2014-02-06

    The change would be to remove Chapter I, Labor Relations, and Chapter II Labor Standards from DOE O 350.1 and develop DOE O DOE O 350.3, which will cancel and supersede Chapters I and II in DOE O 350.1. Content of the two chapters will be updated to reflect the Secretarial determination transferring functions for contractor labor relations and labor standards from the Office of Legacy Management to the Office of General Counsel. CRDs for those chapters will also be removed.

  8. "RSE Table C10.1. Relative Standard Errors for Table C10.1;...

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

    Know" ,,"Total United States" , 311,"Food",3,1,4,2,1,2... 324110," Petroleum Refineries",15,10,36,15,25,44,15,3... Know" ,,"Total United States" , ...

  9. "RSE Table N5.1. Relative Standard Errors for Table N5.1;...

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

    ","FurnaceCoke"," ","Petroleum","or","Wood ... ,,"Total United States" , 311,"Food",2,0,1,0,0,0... 324110," Petroleum Refineries",4,0,3,6,0,0,24 ...

  10. "RSE Table N7.1. Relative Standard Errors for Table N7.1;...

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

    Shipments" ,,"Total United States" , 311,"Food",1,1,1 311221," ... Printing",4,5,4 324,"Petroleum and Coal Products",4,3,3 324110," Petroleum Refineries",3,3,3 ...

  11. "RSE Table C2.1. Relative Standard Errors for Table C2.1;...

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

    ,,"Total United States" , 311,"Food",4,0,3,0,1,0... 324,"Petroleum and Coal Products ... "produced at refineries or natural gas ...

  12. "RSE Table E2.1. Relative Standard Errors for Table E2.1;...

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

    by petroleum" "refineries (e.g., crude oil ... ,"Total United States" "Value of Shipments and ... Examples of Liquefied Petroleum Gases '(LPG)' are ...

  13. "RSE Table N11.2. Relative Standard Errors for Table N11.2;...

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

    ... by" "petroleum refineries, rather than purchased ... ,,"Total United States" , 311,"Food",1,1,3,3,1,1... 324,"Petroleum and Coal ...

  14. "RSE Table C12.1. Relative Standard Errors for Table C12.1;...

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

    ,,"Total United States" , 311,"Food",2,0,2,1,1 ... 324110," Petroleum Refineries",4,0,15,5,12 ... Establishment" ,,"Total United States" , ...

  15. "RSE Table C4.1. Relative Standard Errors for Table C4.1;...

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

    ,,"Total United States" , 311,"Food",0,0,3,4,1,3... 324,"Petroleum and Coal ... "produced at refineries or natural gas ...

  16. Table 3b. Relative Standard Errors for Total Natural Gas Consumption...

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

    13 13 200,001 to 500,000 11 21 16 16 Over 500,000 15 27 22 23 Principal Building Activity Education 12 11 9 8 Food Sales and Service 8 12 10 9 Health Care 15 21 17 13 Lodging 12 22...

  17. Table 5b. Relative Standard Errors for Total District Heat Consumption...

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

    35 36 200,001 to 500,000 22 31 26 27 Over 500,000 42 26 14 10 Principal Building Activity Education 17 29 22 23 Food Sales and Service 67 93 207 150 Health Care 35 26 25 14 Lodging...

  18. "RSE Table C3.1. Relative Standard Errors for Table C3.1;...

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

    ... and Office of Oil and Gas, Petroleum" "Supply Division, Form EIA-810, 'Monthly Refinery Report' for 1998." ... and",,"Coke"," " "Code(a)","Subsector and ...

  19. "RSE Table E13.1. Relative Standard Errors for Table E13.1;...

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

    ... for which" "payment was not made, quantities purchased centrally within the company but separate" "from the reporting establishment, and quantities for which payment was made ...

  20. "RSE Table N11.3. Relative Standard Errors for Table N11.3;...

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

    ... for which" "payment was not made, quantities purchased centrally within the company but separate" "from the reporting establishment, and quantities for which payment was made ...

  1. "RSE Table C11.3. Relative Standard Errors for Table C11.3;...

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

    ... for which" "payment was not made, quantities purchased centrally within the company but separate" "from the reporting establishment, and quantities for which payment was made ...

  2. "RSE Table N11.1. Relative Standard Errors for Table N11.1;...

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

    ... office offsite, and quantities for which payment" "is made in-kind." " Source: Energy ... by a central purchasing office offsite, and quantities for which payment" "is made in-kind

  3. "RSE Table N11.4. Relative Standard Errors for Table N11.4;...

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

    ... for which" "payment was not made, quantities purchased centrally within the company but separate" "from the reporting establishment, and quantities for which payment was made ...

  4. "RSE Table N8.3. Relative Standard Errors for Table N8.3;...

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

    ... for which" "payment was not made, quantities purchased centrally within the company but separate" "from the reporting establishment, and quantities for which payment was made ...

  5. "RSE Table N13.1. Relative Standard Errors for Table N13.1;...

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

    ... for which" "payment was not made, quantities purchased centrally within the company but separate" "from the reporting establishment, and quantities for which payment was made ...

  6. RSE Table 1.1 Relative Standard Errors for Table 1.1

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

    Oil","Fuel Oil(d)","Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,,"Total United States" 311,"Food",4,5,25,20,5,27,6,0,10,0 311221," Wet Corn ...

  7. RSE Table 1.2 Relative Standard Errors for Table 1.2

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

    Oil","Fuel Oil(d)","Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,,"Total United States" 311,"Food",4,5,25,20,5,27,6,0,10,0 311221," Wet Corn ...

  8. RSE Table 4.2 Relative Standard Errors for Table 4.2

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

    Corn Milling",1,0,0,1,3,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ... Corn Milling",0,0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ...

  9. RSE Table 7.10 Relative Standard Errors for Table 7.10

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

    Corn Milling",1,1,0,3,0,4,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ... Corn Milling",0,0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ...

  10. RSE Table 7.7 Relative Standard Errors for Table 7.7

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

    Corn Milling",0,0,0,3,0,3,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ... Corn Milling",0,0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ...

  11. RSE Table 7.3 Relative Standard Errors for Table 7.3

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

    Corn Milling",0,0,0,3,0,3,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ... Corn Milling",0,0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ...

  12. RSE Table 3.1 Relative Standard Errors for Table 3.1

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

    Corn Milling",1,2,0,1,3,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ... Corn Milling",0,0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ...

  13. RSE Table 3.2 Relative Standard Errors for Table 3.2

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

    Corn Milling",1,2,0,1,3,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ... Corn Milling",0,0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ...

  14. RSE Table 4.1 Relative Standard Errors for Table 4.1

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

    Corn Milling",1,0,0,1,3,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ... Corn Milling",0,0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and ...

  15. "RSE Table C10.3. Relative Standard Errors for Table C10.3;...

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

    ," Membrane Hyperfiltration to Separate Water from Food Products",4,1,3 311221," Wet ... ," Membrane Hyperfiltration to Separate Water from Food Products",0,0,0 312,"BEVERAGE ...

  16. "RSE Table C9.1. Relative Standard Errors for Table C9.1;...

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

    ," U.S. Environmental Protection Agency's Energy Star Program",1,10,0,0,0,0 ," U.S. Environmental Protection Agency's Green Lights Program",1,9,0,0,0,0 ," U.S. Department of ...

  17. Error Page

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

    script writes out the header html. We are sorry to report that an error has occurred. Internal identifier for doc type not found. Return to RevCom | Return to Web Portal Need help? Email Technical Support. This site managed by the Office of Management / US Department of Energy Directives | Regulations | Technical Standards | Reference Library | DOE Forms | About Us | Privacy & Security Notice This script breaks up the email address to avoid spam

  18. Comparisons of ANS, ASME, AWS, and NFPA standards cited in the NRC standard review plan, NUREG-0800, and related documents

    SciTech Connect (OSTI)

    Ankrum, A.R.; Bohlander, K.L.; Gilbert, E.R.; Spiesman, J.B.

    1995-11-01

    This report provides the results of comparisons of the cited and latest versions of ANS, ASME, AWS and NFPA standards cited in the NRC Standard Review Plan for the Review of Safety Analysis Reports for Nuclear Power Plants (NUREG 0800) and related documents. The comparisons were performed by Battelle Pacific Northwest Laboratories in support of the NRC`s Standard Review Plan Update and Development Program. Significant changes to the standards, from the cited version to the latest version, are described and discussed in a tabular format for each standard. Recommendations for updating each citation in the Standard Review Plan are presented. Technical considerations and suggested changes are included for related regulatory documents (i.e., Regulatory Guides and the Code of Federal Regulations) citing the standard. The results and recommendations presented in this document have not been subjected to NRC staff review.

  19. Inventory of Safety-Related Codes and Standards for Energy Storage Systems and Related Experiences with System Approval and Acceptance

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

    PNNL-23618 Inventory of Safety-related Codes and Standards for Energy Storage Systems with some Experiences related to Approval and Acceptance DR Conover September 2014 Prepared for the U.S. Department of Energy Energy Storage Program under Contract DE-AC05-76RL01830 Pacific Northwest National Laboratory Richland, Washington 99352 i ii Summary Purpose The purpose of this document is to identify laws; rules; model codes; and codes, standards, regulations (CSR) specifications related to safety

  20. Error abstractions

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

    Error and fault abstractions Mattan Erez UT Austin *Who should care about faults and errors? *Ideally, only system cares about masked faults? - Assuming application bugs are not...

  1. Summary of HI Standards Relating to Energy Efficency | Department of Energy

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

    HI Standards Relating to Energy Efficency Summary of HI Standards Relating to Energy Efficency This guideline discusses the effects of operating a rotodynamic pump at rates of flow that are greater than or less than the rate of flow at the pump's best efficiency point (BEP). These effects influence the power consumption and life of pump components and, therefore, considering the operating rate of flow is essential to reliable, efficient pump operation.

  2. Inventory of Safety-related Codes and Standards for Energy Storage Systems with some Experiences related to Approval and Acceptance

    SciTech Connect (OSTI)

    Conover, David R.

    2014-09-11

    The purpose of this document is to identify laws, rules, model codes, codes, standards, regulations, specifications (CSR) related to safety that could apply to stationary energy storage systems (ESS) and experiences to date securing approval of ESS in relation to CSR. This information is intended to assist in securing approval of ESS under current CSR and to identification of new CRS or revisions to existing CRS and necessary supporting research and documentation that can foster the deployment of safe ESS.

  3. Technical Review of Law Enforcement Standards and Guides Relative to Incident Management

    SciTech Connect (OSTI)

    Stenner, Robert D.; Salter, R.; Stanton, J. R.; Fisher, D.

    2009-03-24

    In an effort to locate potential law enforcement-related standards that support incident management, a team from the Pacific Northwest National Laboratory (PNNL) contacted representatives from the National Institute of Standards-Office of Law Enforcement Standards (NIST-OLES), National Institute of Justice (NIJ), Federal Bureau of Investigation (FBI), Secret Service, ASTM International committees that have a law enforcement focus, and a variety of individuals from local and regional law enforcement organizations. Discussions were held with various state and local law enforcement organizations. The NIJ has published several specific equipment-related law enforcement standards that were included in the review, but it appears that law enforcement program and process-type standards are developed principally by organizations that operate at the state and local level. Input is provided from state regulations and codes and from external non-government organizations (NGOs) that provide national standards. The standards that are adopted from external organizations or developed independently by state authorities are available for use by local law enforcement agencies on a voluntary basis. The extent to which they are used depends on the respective jurisdictions involved. In some instances, use of state and local disseminated standards is mandatory, but in most cases, use is voluntary. Usually, the extent to which these standards are used appears to depend on whether or not jurisdictions receive certification from a “governing” entity due to their use and compliance with the standards. In some cases, these certification-based standards are used in principal but without certification or other compliance monitoring. In general, these standards appear to be routinely used for qualification, selection for employment, and training. In these standards, the term “Peace Officer” is frequently used to refer to law enforcement personnel. This technical review of national law

  4. EIA - Sorry! Unexpected Error

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

    Cold Fusion Error Unexpected Error Sorry An error was encountered. This error could be due to scheduled maintenance. Information about the error has been routed to the appropriate...

  5. EIA - Sorry! Unexpected Error

    Gasoline and Diesel Fuel Update (EIA)

    Cold Fusion Error Unexpected Error Sorry An error was encountered. This error could be due to scheduled maintenance. Information about the error has been routed to the appropriate ...

  6. Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms

    SciTech Connect (OSTI)

    Hou, Zhangshuan; Makarov, Yuri V.; Samaan, Nader A.; Etingov, Pavel V.

    2013-03-19

    Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (stochastic) model with the weather forecast model (deterministic) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

  7. Labor Standards Compliance, Contractor Labor Relations, and Contractor Workforce Restructuring Programs

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2014-09-29

    To ensure that contractors pursue collective bargaining practices that promote efficiency and economy in contract operations, judicious expenditure of public funds, equitable resolution of disputes, and effective collective bargaining relationships; that contractor relations/human resources specialists achieve consultations with management and operating contractors; and that appropriate labor standards are included in DOE/NNSA contracts and subcontracts. Cancels Chapters I-III of DOE O 350.1 Chg 4. Does not cancel other directives.

  8. Energy conservation standards for new federal residential buildings: A decision analysis study using relative value discounting

    SciTech Connect (OSTI)

    Harvey, C. . Coll. of Business Administration); Merkhofer, M.M.; Hamm, G.L. )

    1990-07-02

    This report presents a reassessment of the proposed standard for energy conservation in new federal residential buildings. The analysis uses the data presented in the report, Economic Analysis: In Support of Interim Energy Conservation Standards for New Federal Residential Buildings (June 1988)-to be referred to as the EASIECS report. The reassessment differs from that report in several respects. In modeling factual information, it uses more recent forecasts of future energy prices and it uses data from the Bureau of the Census in order to estimate the distribution of lifetimes of residential buildings rather than assuming a hypothetical 25-year lifetime. In modeling social preferences decision analysis techniques are used in order to examine issues of public values that often are not included in traditional cost-benefit analyses. The present report concludes that the public would benefit from the proposed standard. Several issues of public values regarding energy use are illustrated with methods to include them in a formal analysis of a proposed energy policy. The first issue places a value on costs and benefits that will occur in the future as an irreversible consequence of current policy choices. This report discusses an alternative method, called relative value discounting which permits flexible discounting of future events-and the possibility of placing greater values on future events. The second issue places a value on the indirect benefits of energy savings so that benefits accrue to everyone rather than only to the person who saves the energy. This report includes non-zero estimates of the indirect benefits. The third issue is how the costs and benefits discussed in a public policy evaluation should be compared. In summary, selection of individual projects with larger benefit to cost ratios leads to a portfolio of projects with the maximum benefit to cost difference. 30 refs., 6 figs., 16 tabs. (JF)

  9. Errors of Nonobservation

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

    Errors of Nonobservation Finally, several potential sources of nonsampling error and bias result from errors of nonobservation. The 1994 MECS represents, in terms of sampling...

  10. NEW - DOE O 350.3, Labor Standards Compliance, Contractor Labor Relations, and Contractor Workforce Restructuring Programs

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    To ensure that contractors pursue collective bargaining practices that promote efficiency and economy in contract operations, judicious expenditure of public funds, equitable resolution of disputes, and effective collective bargaining relationships; that contractor relations/human resources specialists achieve consultations with management and operating contractors; and that appropriate labor standards are included in DOE/NNSA contracts and subcontracts. Cancels Chapters I-III of DOE O 350.1 Chg 4. Does not cancel other directives.

  11. Reducing collective quantum state rotation errors with reversible dephasing

    SciTech Connect (OSTI)

    Cox, Kevin C.; Norcia, Matthew A.; Weiner, Joshua M.; Bohnet, Justin G.; Thompson, James K.

    2014-12-29

    We demonstrate that reversible dephasing via inhomogeneous broadening can greatly reduce collective quantum state rotation errors, and observe the suppression of rotation errors by more than 21?dB in the context of collective population measurements of the spin states of an ensemble of 2.110{sup 5} laser cooled and trapped {sup 87}Rb atoms. The large reduction in rotation noise enables direct resolution of spin state populations 13(1) dB below the fundamental quantum projection noise limit. Further, the spin state measurement projects the system into an entangled state with 9.5(5) dB of directly observed spectroscopic enhancement (squeezing) relative to the standard quantum limit, whereas no enhancement would have been obtained without the suppression of rotation errors.

  12. Error handling strategies in multiphase inverse modeling

    SciTech Connect (OSTI)

    Finsterle, S.; Zhang, Y.

    2010-12-01

    Parameter estimation by inverse modeling involves the repeated evaluation of a function of residuals. These residuals represent both errors in the model and errors in the data. In practical applications of inverse modeling of multiphase flow and transport, the error structure of the final residuals often significantly deviates from the statistical assumptions that underlie standard maximum likelihood estimation using the least-squares method. Large random or systematic errors are likely to lead to convergence problems, biased parameter estimates, misleading uncertainty measures, or poor predictive capabilities of the calibrated model. The multiphase inverse modeling code iTOUGH2 supports strategies that identify and mitigate the impact of systematic or non-normal error structures. We discuss these approaches and provide an overview of the error handling features implemented in iTOUGH2.

  13. Error detection method

    DOE Patents [OSTI]

    Olson, Eric J.

    2013-06-11

    An apparatus, program product, and method that run an algorithm on a hardware based processor, generate a hardware error as a result of running the algorithm, generate an algorithm output for the algorithm, compare the algorithm output to another output for the algorithm, and detect the hardware error from the comparison. The algorithm is designed to cause the hardware based processor to heat to a degree that increases the likelihood of hardware errors to manifest, and the hardware error is observable in the algorithm output. As such, electronic components may be sufficiently heated and/or sufficiently stressed to create better conditions for generating hardware errors, and the output of the algorithm may be compared at the end of the run to detect a hardware error that occurred anywhere during the run that may otherwise not be detected by traditional methodologies (e.g., due to cooling, insufficient heat and/or stress, etc.).

  14. Trouble Shooting and Error Messages

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

    ... Check the error code of your application. error obtaining user credentials system Resubmit. Contact consultants for repeated problems. nemgnierrorhandler(): a transaction error ...

  15. runtime error message: "readControlMsg: System returned error...

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

    readControlMsg: System returned error Connection timed out on TCP socket fd" runtime error message: "readControlMsg: System returned error Connection timed out on TCP socket fd"...

  16. Verification of unfold error estimates in the unfold operator code

    SciTech Connect (OSTI)

    Fehl, D.L.; Biggs, F.

    1997-01-01

    Spectral unfolding is an inverse mathematical operation that attempts to obtain spectral source information from a set of response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the unfold operator (UFO) code written at Sandia National Laboratories. In addition to an unfolded spectrum, the UFO code also estimates the unfold uncertainty (error) induced by estimated random uncertainties in the data. In UFO the unfold uncertainty is obtained from the error matrix. This built-in estimate has now been compared to error estimates obtained by running the code in a Monte Carlo fashion with prescribed data distributions (Gaussian deviates). In the test problem studied, data were simulated from an arbitrarily chosen blackbody spectrum (10 keV) and a set of overlapping response functions. The data were assumed to have an imprecision of 5{percent} (standard deviation). One hundred random data sets were generated. The built-in estimate of unfold uncertainty agreed with the Monte Carlo estimate to within the statistical resolution of this relatively small sample size (95{percent} confidence level). A possible 10{percent} bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetermined problems, for which the error matrix method does not apply. UFO has been applied to the diagnosis of low energy x rays emitted by Z-pinch and ion-beam driven hohlraums. {copyright} {ital 1997 American Institute of Physics.}

  17. Trouble Shooting and Error Messages

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

    ... Check the error code of your application. error obtaining user credentials system Resubmit. Contact consultants for repeated problems. NERSC and Cray are working on this issue. ...

  18. Trouble Shooting and Error Messages

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

    not be a problem. Check the error code of your application. error obtaining user credentials system Resubmit. Contact consultants for repeated problems. Last edited: 2015-01-16 ...

  19. Modular error embedding

    DOE Patents [OSTI]

    Sandford, II, Maxwell T.; Handel, Theodore G.; Ettinger, J. Mark

    1999-01-01

    A method of embedding auxiliary information into the digital representation of host data containing noise in the low-order bits. The method applies to digital data representing analog signals, for example digital images. The method reduces the error introduced by other methods that replace the low-order bits with auxiliary information. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user through use of a digital key. The modular error embedding method includes a process to permute the order in which the host data values are processed. The method doubles the amount of auxiliary information that can be added to host data values, in comparison with bit-replacement methods for high bit-rate coding. The invention preserves human perception of the meaning and content of the host data, permitting the addition of auxiliary data in the amount of 50% or greater of the original host data.

  20. Error 404 - Document not found

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

    govErrors ERROR 404 - URL Not Found We are sorry but the URL that you have requested cannot be found or it is linked to a file that no longer exists. Please check the spelling or...

  1. Trouble Shooting and Error Messages

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

    Trouble Shooting and Error Messages Trouble Shooting and Error Messages Error Messages Message or Symptom Fault Recommendation job hit wallclock time limit user or system Submit job for longer time or start job from last checkpoint and resubmit. If your job hung and produced no output contact consultants. received node failed or halted event for nid xxxx system resubmit the job error with width parameters to aprun user Make sure #PBS -l mppwidth value matches aprun -n value new values for

  2. Evaluating operating system vulnerability to memory errors.

    SciTech Connect (OSTI)

    Ferreira, Kurt Brian; Bridges, Patrick G.; Pedretti, Kevin Thomas Tauke; Mueller, Frank; Fiala, David; Brightwell, Ronald Brian

    2012-05-01

    Reliability is of great concern to the scalability of extreme-scale systems. Of particular concern are soft errors in main memory, which are a leading cause of failures on current systems and are predicted to be the leading cause on future systems. While great effort has gone into designing algorithms and applications that can continue to make progress in the presence of these errors without restarting, the most critical software running on a node, the operating system (OS), is currently left relatively unprotected. OS resiliency is of particular importance because, though this software typically represents a small footprint of a compute node's physical memory, recent studies show more memory errors in this region of memory than the remainder of the system. In this paper, we investigate the soft error vulnerability of two operating systems used in current and future high-performance computing systems: Kitten, the lightweight kernel developed at Sandia National Laboratories, and CLE, a high-performance Linux-based operating system developed by Cray. For each of these platforms, we outline major structures and subsystems that are vulnerable to soft errors and describe methods that could be used to reconstruct damaged state. Our results show the Kitten lightweight operating system may be an easier target to harden against memory errors due to its smaller memory footprint, largely deterministic state, and simpler system structure.

  3. Register file soft error recovery

    DOE Patents [OSTI]

    Fleischer, Bruce M.; Fox, Thomas W.; Wait, Charles D.; Muff, Adam J.; Watson, III, Alfred T.

    2013-10-15

    Register file soft error recovery including a system that includes a first register file and a second register file that mirrors the first register file. The system also includes an arithmetic pipeline for receiving data read from the first register file, and error detection circuitry to detect whether the data read from the first register file includes corrupted data. The system further includes error recovery circuitry to insert an error recovery instruction into the arithmetic pipeline in response to detecting the corrupted data. The inserted error recovery instruction replaces the corrupted data in the first register file with a copy of the data from the second register file.

  4. Standard Terms and Conditions | NREL

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

    Standard Terms and Conditions Documents related to NREL's standard terms and conditions for subcontracts or purchase orders are available below. Standard Terms and Conditions - ...

  5. Department of Energy Standards Index

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

    ... NFPA 97 Standard Glossary of Terms Relating to Chimney, Vents, Heat Producing Appliances NFPA 99 Standard for Health Care Facilities NFPA 99B Standard for Hypobaric Facilities NFPA ...

  6. Neutron multiplication error in TRU waste measurements

    SciTech Connect (OSTI)

    Veilleux, John [Los Alamos National Laboratory; Stanfield, Sean B [CCP; Wachter, Joe [CCP; Ceo, Bob [CCP

    2009-01-01

    more realistic and accurate. To do so, measurements of standards and waste drums were performed with High Efficiency Neutron Counters (HENC) located at Los Alamos National Laboratory (LANL). The data were analyzed for multiplication effects and new estimates of the multiplication error were computed. A concluding section will present alternatives for reducing the number of rejections of TRU waste containers due to neutron multiplication error.

  7. Confidence limits and their errors

    SciTech Connect (OSTI)

    Rajendran Raja

    2002-03-22

    Confidence limits are common place in physics analysis. Great care must be taken in their calculation and use especially in cases of limited statistics. We introduce the concept of statistical errors of confidence limits and argue that not only should limits be calculated but also their errors in order to represent the results of the analysis to the fullest. We show that comparison of two different limits from two different experiments becomes easier when their errors are also quoted. Use of errors of confidence limits will lead to abatement of the debate on which method is best suited to calculate confidence limits.

  8. Shared dosimetry error in epidemiological dose-response analyses

    SciTech Connect (OSTI)

    Stram, Daniel O.; Preston, Dale L.; Sokolnikov, Mikhail; Napier, Bruce; Kopecky, Kenneth J.; Boice, John; Beck, Harold; Till, John; Bouville, Andre; Zeeb, Hajo

    2015-03-23

    Radiation dose reconstruction systems for large-scale epidemiological studies are sophisticated both in providing estimates of dose and in representing dosimetry uncertainty. For example, a computer program was used by the Hanford Thyroid Disease Study to provide 100 realizations of possible dose to study participants. The variation in realizations reflected the range of possible dose for each cohort member consistent with the data on dose determinates in the cohort. Another example is the Mayak Worker Dosimetry System 2013 which estimates both external and internal exposures and provides multiple realizations of "possible" dose history to workers given dose determinants. This paper takes up the problem of dealing with complex dosimetry systems that provide multiple realizations of dose in an epidemiologic analysis. In this paper we derive expected scores and the information matrix for a model used widely in radiation epidemiology, namely the linear excess relative risk (ERR) model that allows for a linear dose response (risk in relation to radiation) and distinguishes between modifiers of background rates and of the excess risk due to exposure. We show that treating the mean dose for each individual (calculated by averaging over the realizations) as if it was true dose (ignoring both shared and unshared dosimetry errors) gives asymptotically unbiased estimates (i.e. the score has expectation zero) and valid tests of the null hypothesis that the ERR slope ? is zero. Although the score is unbiased the information matrix (and hence the standard errors of the estimate of ?) is biased for ??0 when ignoring errors in dose estimates, and we show how to adjust the information matrix to remove this bias, using the multiple realizations of dose. The use of these methods in the context of several studies including, the Mayak Worker Cohort, and the U.S. Atomic Veterans Study, is discussed.

  9. Shared dosimetry error in epidemiological dose-response analyses

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

    Stram, Daniel O.; Preston, Dale L.; Sokolnikov, Mikhail; Napier, Bruce; Kopecky, Kenneth J.; Boice, John; Beck, Harold; Till, John; Bouville, Andre; Zeeb, Hajo

    2015-03-23

    Radiation dose reconstruction systems for large-scale epidemiological studies are sophisticated both in providing estimates of dose and in representing dosimetry uncertainty. For example, a computer program was used by the Hanford Thyroid Disease Study to provide 100 realizations of possible dose to study participants. The variation in realizations reflected the range of possible dose for each cohort member consistent with the data on dose determinates in the cohort. Another example is the Mayak Worker Dosimetry System 2013 which estimates both external and internal exposures and provides multiple realizations of "possible" dose history to workers given dose determinants. This paper takesmore » up the problem of dealing with complex dosimetry systems that provide multiple realizations of dose in an epidemiologic analysis. In this paper we derive expected scores and the information matrix for a model used widely in radiation epidemiology, namely the linear excess relative risk (ERR) model that allows for a linear dose response (risk in relation to radiation) and distinguishes between modifiers of background rates and of the excess risk due to exposure. We show that treating the mean dose for each individual (calculated by averaging over the realizations) as if it was true dose (ignoring both shared and unshared dosimetry errors) gives asymptotically unbiased estimates (i.e. the score has expectation zero) and valid tests of the null hypothesis that the ERR slope β is zero. Although the score is unbiased the information matrix (and hence the standard errors of the estimate of β) is biased for β≠0 when ignoring errors in dose estimates, and we show how to adjust the information matrix to remove this bias, using the multiple realizations of dose. The use of these methods in the context of several studies including, the Mayak Worker Cohort, and the U.S. Atomic Veterans Study, is discussed.« less

  10. Error studies for SNS Linac. Part 1: Transverse errors

    SciTech Connect (OSTI)

    Crandall, K.R.

    1998-12-31

    The SNS linac consist of a radio-frequency quadrupole (RFQ), a drift-tube linac (DTL), a coupled-cavity drift-tube linac (CCDTL) and a coupled-cavity linac (CCL). The RFQ and DTL are operated at 402.5 MHz; the CCDTL and CCL are operated at 805 MHz. Between the RFQ and DTL is a medium-energy beam-transport system (MEBT). This error study is concerned with the DTL, CCDTL and CCL, and each will be analyzed separately. In fact, the CCL is divided into two sections, and each of these will be analyzed separately. The types of errors considered here are those that affect the transverse characteristics of the beam. The errors that cause the beam center to be displaced from the linac axis are quad displacements and quad tilts. The errors that cause mismatches are quad gradient errors and quad rotations (roll).

  11. Error 404 - Document not found

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

    govErrors ERROR 404 - URL Not Found We are sorry but the URL that you have requested cannot be found or it is linked to a file that no longer exists. Please check the spelling or send e-mail to WWW Administrator

  12. Verification of unfold error estimates in the UFO code

    SciTech Connect (OSTI)

    Fehl, D.L.; Biggs, F.

    1996-07-01

    Spectral unfolding is an inverse mathematical operation which attempts to obtain spectral source information from a set of tabulated response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the UFO (UnFold Operator) code. In addition to an unfolded spectrum, UFO also estimates the unfold uncertainty (error) induced by running the code in a Monte Carlo fashion with prescribed data distributions (Gaussian deviates). In the problem studied, data were simulated from an arbitrarily chosen blackbody spectrum (10 keV) and a set of overlapping response functions. The data were assumed to have an imprecision of 5% (standard deviation). 100 random data sets were generated. The built-in estimate of unfold uncertainty agreed with the Monte Carlo estimate to within the statistical resolution of this relatively small sample size (95% confidence level). A possible 10% bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetemined problems, for which the error matrix method does not apply. UFO has been applied to the diagnosis of low energy x rays emitted by Z-Pinch and ion-beam driven hohlraums.

  13. Trouble Shooting and Error Messages

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

    Trouble Shooting and Error Messages Trouble Shooting and Error Messages Error Messages Message or Symptom Fault Recommendation job hit wallclock time limit user or system Submit job for longer time or start job from last checkpoint and resubmit. If your job hung and produced no output contact consultants. received node failed or halted event for nid xxxx system One of the compute nodes assigned to the job failed. Resubmit the job PtlNIInit failed : PTL_NOT_REGISTERED user The executable is from

  14. error | netl.doe.gov

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

    error Sorry, there is no www.netl.doe.gov web page that matches your request. It may be possible that you typed the address incorrectly. Connect to National Energy Technology...

  15. Technical Standards

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

    Review for Technical Standards of Interest Legend: Red = Technical Standards Program Activities and Responsibilities Blue = Directives Program Activities and Responsibilities

  16. Interconnection Standards

    Office of Energy Efficiency and Renewable Energy (EERE)

    Note: The North Carolina Utilities Commission approved revised interconnection standards in May 2015. The new standards used the Federal Energy Regulatory Commission's most recent Small Generator...

  17. Standards, Ethics

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

    Standards, Ethics Ombuds Standards and Ethics Committed to the fair and equitable treatment of all employees, contractors, and persons doing business with the Laboratory. Contact...

  18. Improving Memory Error Handling Using Linux

    SciTech Connect (OSTI)

    Carlton, Michael Andrew; Blanchard, Sean P.; Debardeleben, Nathan A.

    2014-07-25

    As supercomputers continue to get faster and more powerful in the future, they will also have more nodes. If nothing is done, then the amount of memory in supercomputer clusters will soon grow large enough that memory failures will be unmanageable to deal with by manually replacing memory DIMMs. "Improving Memory Error Handling Using Linux" is a process oriented method to solve this problem by using the Linux kernel to disable (offline) faulty memory pages containing bad addresses, preventing them from being used again by a process. The process of offlining memory pages simplifies error handling and results in reducing both hardware and manpower costs required to run Los Alamos National Laboratory (LANL) clusters. This process will be necessary for the future of supercomputing to allow the development of exascale computers. It will not be feasible without memory error handling to manually replace the number of DIMMs that will fail daily on a machine consisting of 32-128 petabytes of memory. Testing reveals the process of offlining memory pages works and is relatively simple to use. As more and more testing is conducted, the entire process will be automated within the high-performance computing (HPC) monitoring software, Zenoss, at LANL.

  19. Errors in determination of soil water content using time-domain reflectometry caused by soil compaction around wave guides

    SciTech Connect (OSTI)

    Ghezzehei, T.A.

    2008-05-29

    Application of time domain reflectometry (TDR) in soil hydrology often involves the conversion of TDR-measured dielectric permittivity to water content using universal calibration equations (empirical or physically based). Deviations of soil-specific calibrations from the universal calibrations have been noted and are usually attributed to peculiar composition of soil constituents, such as high content of clay and/or organic matter. Although it is recognized that soil disturbance by TDR waveguides may have impact on measurement errors, to our knowledge, there has not been any quantification of this effect. In this paper, we introduce a method that estimates this error by combining two models: one that describes soil compaction around cylindrical objects and another that translates change in bulk density to evolution of soil water retention characteristics. Our analysis indicates that the compaction pattern depends on the mechanical properties of the soil at the time of installation. The relative error in water content measurement depends on the compaction pattern as well as the water content and water retention properties of the soil. Illustrative calculations based on measured soil mechanical and hydrologic properties from the literature indicate that the measurement errors of using a standard three-prong TDR waveguide could be up to 10%. We also show that the error scales linearly with the ratio of rod radius to the interradius spacing.

  20. Interconnection Standards

    Broader source: Energy.gov [DOE]

    Connecticut's interconnection guidelines, like FERC's standards, include provisions for three levels of systems:

  1. Technical Standards Newsletter - January 2012 | Department of...

    Energy Savers [EERE]

    Revisions New DOE Standards Projects DOE Handbook of Operational Safety and Analysis Techniques Nuclear Safety- Related Standards Activity PDF icon Technical Standards Newsletter -...

  2. Intel C++ compiler error: stl_iterator_base_types.h

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

    C++ compiler error: stl_iterator_base_types.h Intel C++ compiler error: stl_iterator_base_types.h December 7, 2015 by Scott French Because the system-supplied version of GCC is relatively old (4.3.4) it is common practice to load the gcc module on our Cray systems when C++11 support is required under the Intel C++ compilers. While this works as expected under the GCC 4.8 and 4.9 series compilers, the 5.x series can cause Intel C++ compile-time errors similar to the following:

  3. DOE technical standards list: Department of Energy standards index

    SciTech Connect (OSTI)

    1999-05-01

    This Department of Energy (DOE) technical standards list (TSL) has been prepared by the Office of Nuclear Safety Policy and Standards (EH-31) on the basis of currently available technical information. Periodic updates of this TSL will be issued as additional information is received on standardization documents being issued, adopted, or canceled by DOE. This document was prepared for use by personnel involved in the selection and use of DOE technical standards and other Government and non-Government standards. This TSL provides listings of current DOE technical standards, non-Government standards that have been adopted by DOE, other standards-related documents in which DOE has a recorded interest, and canceled DOE technical standards. Information on new DOE technical standards projects, technical standards released for coordination, recently published DOE technical standards, and activities of non-Government standards bodies that may be of interest to DOE is published monthly in Standards Actions.

  4. Catastrophic photometric redshift errors: Weak-lensing survey requirements

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

    Bernstein, Gary; Huterer, Dragan

    2010-01-11

    We study the sensitivity of weak lensing surveys to the effects of catastrophic redshift errors - cases where the true redshift is misestimated by a significant amount. To compute the biases in cosmological parameters, we adopt an efficient linearized analysis where the redshift errors are directly related to shifts in the weak lensing convergence power spectra. We estimate the number Nspec of unbiased spectroscopic redshifts needed to determine the catastrophic error rate well enough that biases in cosmological parameters are below statistical errors of weak lensing tomography. While the straightforward estimate of Nspec is ~106 we find that using onlymore » the photometric redshifts with z ≤ 2.5 leads to a drastic reduction in Nspec to ~ 30,000 while negligibly increasing statistical errors in dark energy parameters. Therefore, the size of spectroscopic survey needed to control catastrophic errors is similar to that previously deemed necessary to constrain the core of the zs – zp distribution. We also study the efficacy of the recent proposal to measure redshift errors by cross-correlation between the photo-z and spectroscopic samples. We find that this method requires ~ 10% a priori knowledge of the bias and stochasticity of the outlier population, and is also easily confounded by lensing magnification bias. In conclusion, the cross-correlation method is therefore unlikely to supplant the need for a complete spectroscopic redshift survey of the source population.« less

  5. Slope Error Measurement Tool for Solar Parabolic Trough Collectors: Preprint

    SciTech Connect (OSTI)

    Stynes, J. K.; Ihas, B.

    2012-04-01

    The National Renewable Energy Laboratory (NREL) has developed an optical measurement tool for parabolic solar collectors that measures the combined errors due to absorber misalignment and reflector slope error. The combined absorber alignment and reflector slope errors are measured using a digital camera to photograph the reflected image of the absorber in the collector. Previous work using the image of the reflection of the absorber finds the reflector slope errors from the reflection of the absorber and an independent measurement of the absorber location. The accuracy of the reflector slope error measurement is thus dependent on the accuracy of the absorber location measurement. By measuring the combined reflector-absorber errors, the uncertainty in the absorber location measurement is eliminated. The related performance merit, the intercept factor, depends on the combined effects of the absorber alignment and reflector slope errors. Measuring the combined effect provides a simpler measurement and a more accurate input to the intercept factor estimate. The minimal equipment and setup required for this measurement technique make it ideal for field measurements.

  6. Interconnection Standards

    Broader source: Energy.gov [DOE]

    West Virginia's interconnection standards include two levels of review. The qualifications and application fees for each level are as follows:...

  7. Field errors in hybrid insertion devices

    SciTech Connect (OSTI)

    Schlueter, R.D.

    1995-02-01

    Hybrid magnet theory as applied to the error analyses used in the design of Advanced Light Source (ALS) insertion devices is reviewed. Sources of field errors in hybrid insertion devices are discussed.

  8. Interconnection Standards

    Broader source: Energy.gov [DOE]

    In response to state legislation enacted in 2001, in September 2004 the Minnesota Public Utilities Commission (MPUC) adopted an order establishing generic standards for utility tariffs for...

  9. Interconnection Standards

    Broader source: Energy.gov [DOE]

    NOTE: On March 2016, the NY Public Service Commission (PSC) modified the Standard Interconnection Requirements (SIR) increasing the maximum threshold for interconnection capacity of distributed...

  10. Interconnection Standards

    Broader source: Energy.gov [DOE]

    Technical screens have been established for each level, and the Institute of Electrical and Electronics Engineers 1547 technical standard is used for all interconnections. Reasonable time frames ...

  11. Interconnection Standards

    Office of Energy Efficiency and Renewable Energy (EERE)

    Massachusetts' interconnection standards apply to all forms of distributed generation (DG), including renewables, and to all customers of the state's three investor-owned utilities (Unitil,...

  12. Interconnection Standards

    Office of Energy Efficiency and Renewable Energy (EERE)

    The interconnection standards approved by the PUC also updated Nevada's net-metering policy, originally enacted in 1997. Previously, Nevada Revised Statute 704.774 addressed basic interconnection...

  13. Interconnection Standards

    Office of Energy Efficiency and Renewable Energy (EERE)

    Virginia has two interconnection standards: one for net-metered systems and one for systems that are not net-metered.

  14. Clover: Compiler directed lightweight soft error resilience

    SciTech Connect (OSTI)

    Liu, Qingrui; Lee, Dongyoon; Jung, Changhee; Tiwari, Devesh

    2015-05-01

    This paper presents Clover, a compiler directed soft error detection and recovery scheme for lightweight soft error resilience. The compiler carefully generates soft error tolerant code based on idem-potent processing without explicit checkpoint. During program execution, Clover relies on a small number of acoustic wave detectors deployed in the processor to identify soft errors by sensing the wave made by a particle strike. To cope with DUE (detected unrecoverable errors) caused by the sensing latency of error detection, Clover leverages a novel selective instruction duplication technique called tail-DMR (dual modular redundancy). Once a soft error is detected by either the sensor or the tail-DMR, Clover takes care of the error as in the case of exception handling. To recover from the error, Clover simply redirects program control to the beginning of the code region where the error is detected. Lastly, the experiment results demonstrate that the average runtime overhead is only 26%, which is a 75% reduction compared to that of the state-of-the-art soft error resilience technique.

  15. Clover: Compiler directed lightweight soft error resilience

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

    Liu, Qingrui; Lee, Dongyoon; Jung, Changhee; Tiwari, Devesh

    2015-05-01

    This paper presents Clover, a compiler directed soft error detection and recovery scheme for lightweight soft error resilience. The compiler carefully generates soft error tolerant code based on idem-potent processing without explicit checkpoint. During program execution, Clover relies on a small number of acoustic wave detectors deployed in the processor to identify soft errors by sensing the wave made by a particle strike. To cope with DUE (detected unrecoverable errors) caused by the sensing latency of error detection, Clover leverages a novel selective instruction duplication technique called tail-DMR (dual modular redundancy). Once a soft error is detected by either themore » sensor or the tail-DMR, Clover takes care of the error as in the case of exception handling. To recover from the error, Clover simply redirects program control to the beginning of the code region where the error is detected. Lastly, the experiment results demonstrate that the average runtime overhead is only 26%, which is a 75% reduction compared to that of the state-of-the-art soft error resilience technique.« less

  16. Approximate error conjugation gradient minimization methods

    DOE Patents [OSTI]

    Kallman, Jeffrey S

    2013-05-21

    In one embodiment, a method includes selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, calculating an approximate error using the subset of rays, and calculating a minimum in a conjugate gradient direction based on the approximate error. In another embodiment, a system includes a processor for executing logic, logic for selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, logic for calculating an approximate error using the subset of rays, and logic for calculating a minimum in a conjugate gradient direction based on the approximate error. In other embodiments, computer program products, methods, and systems are described capable of using approximate error in constrained conjugate gradient minimization problems.

  17. Impact of Measurement Error on Synchrophasor Applications

    SciTech Connect (OSTI)

    Liu, Yilu; Gracia, Jose R.; Ewing, Paul D.; Zhao, Jiecheng; Tan, Jin; Wu, Ling; Zhan, Lingwei

    2015-07-01

    Phasor measurement units (PMUs), a type of synchrophasor, are powerful diagnostic tools that can help avert catastrophic failures in the power grid. Because of this, PMU measurement errors are particularly worrisome. This report examines the internal and external factors contributing to PMU phase angle and frequency measurement errors and gives a reasonable explanation for them. It also analyzes the impact of those measurement errors on several synchrophasor applications: event location detection, oscillation detection, islanding detection, and dynamic line rating. The primary finding is that dynamic line rating is more likely to be influenced by measurement error. Other findings include the possibility of reporting nonoscillatory activity as an oscillation as the result of error, failing to detect oscillations submerged by error, and the unlikely impact of error on event location and islanding detection.

  18. Model Validation and Testing: The Methodological Foundation of ASHRAE Standard 140; Preprint

    SciTech Connect (OSTI)

    Judkoff, R.; Neymark, J.

    2006-07-01

    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.

  19. Model Validation and Testing: The Methodological Foundation of ASHRAE Standard 140

    SciTech Connect (OSTI)

    Judkoff, R.; Neymark, J.

    2006-01-01

    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.

  20. The impact of response measurement error on the analysis of designed experiments

    SciTech Connect (OSTI)

    Anderson-Cook, Christine Michaela; Hamada, Michael Scott; Burr, Thomas Lee

    2015-12-21

    This study considers the analysis of designed experiments when there is measurement error in the true response or so-called response measurement error. We consider both additive and multiplicative response measurement errors. Through a simulation study, we investigate the impact of ignoring the response measurement error in the analysis, that is, by using a standard analysis based on t-tests. In addition, we examine the role of repeat measurements in improving the quality of estimation and prediction in the presence of response measurement error. We also study a Bayesian approach that accounts for the response measurement error directly through the specification of the model, and allows including additional information about variability in the analysis. We consider the impact on power, prediction, and optimization. Copyright © 2015 John Wiley & Sons, Ltd.

  1. The impact of response measurement error on the analysis of designed experiments

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

    Anderson-Cook, Christine Michaela; Hamada, Michael Scott; Burr, Thomas Lee

    2015-12-21

    This study considers the analysis of designed experiments when there is measurement error in the true response or so-called response measurement error. We consider both additive and multiplicative response measurement errors. Through a simulation study, we investigate the impact of ignoring the response measurement error in the analysis, that is, by using a standard analysis based on t-tests. In addition, we examine the role of repeat measurements in improving the quality of estimation and prediction in the presence of response measurement error. We also study a Bayesian approach that accounts for the response measurement error directly through the specification ofmore » the model, and allows including additional information about variability in the analysis. We consider the impact on power, prediction, and optimization. Copyright © 2015 John Wiley & Sons, Ltd.« less

  2. Interconnection Standards

    Broader source: Energy.gov [DOE]

    The PSC has published two sets of standard forms for interconnection, available on the program web site. One set pertains to systems smaller than 20 kW while the second set applies to larger syst...

  3. Find Standards

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

    API ASCE ASHRAE ASME ASME-BPVC ASQ ASSE ASTM AWS CGA standards - contact Timothy Lopez (timlopez@lanl.gov), Ben Swartz (abswartz@lanl.gov), or Roberto Trujillo (robertot@lanl.gov) ...

  4. EOS standards

    SciTech Connect (OSTI)

    Greeff, Carl W

    2011-01-12

    An approach to creating accurate EOS for pressure standards is described. Applications to Cu, Au, and Ta are shown. Extension of the method to high compressions using DFT is illustrated. Comparisons with modern functionals show promise.

  5. Interconnection Standards

    Broader source: Energy.gov [DOE]

    The PUC standards generally apply to investor-owned utilities (IOUs) with 40,000 or more customers and all electric cooperatives. Municipal utilities with 5,000 customers or more are required to ...

  6. Interconnection Standards

    Broader source: Energy.gov [DOE]

    The revised standards provide for three separate levels of interconnection based on system capacity and other requirements. The first level, Tier 1 systems, applies generally to systems up to 25...

  7. Interconnection Standards

    Broader source: Energy.gov [DOE]

    Utah’s interconnection rules are based on the Federal Energy Regulatory Commission’s (FERC) interconnection standards for small generators, adopted in May 2005 by FERC Order 2006. Utah's rules fo...

  8. (Terminology standardization)

    SciTech Connect (OSTI)

    Strehlow, R.A.

    1990-10-19

    Terminological requirements in information management was but one of the principal themes of the 2nd Congress on Terminology and Knowledge Engineering. The traveler represented the American Society for Testing and Materials' Committee on Terminology, of which he is the Chair. The traveler's invited workshop emphasized terminology standardization requirements in databases of material properties as well as practical terminology standardizing methods. The congress included six workshops in addition to approximately 82 lectures and papers from terminologists, artificial intelligence practitioners, and subject specialists from 18 countries. There were approximately 292 registrants from 33 countries who participated in the congress. The congress topics were broad. Examples were the increasing use of International Standards Organization (ISO) Standards in legislated systems such as the USSR Automated Data Bank of Standardized Terminology, the enhanced Physics Training Program based on terminology standardization in Physics in the Chinese province of Inner Mongolia, and the technical concept dictionary being developed at the Japan Electronic Dictionary Research Institute, which is considered to be the key to advanced artificial intelligence applications. The more usual roles of terminology work in the areas of machine translation. indexing protocols, knowledge theory, and data transfer in several subject specialties were also addressed, along with numerous special language terminology areas.

  9. Group representations, error bases and quantum codes

    SciTech Connect (OSTI)

    Knill, E

    1996-01-01

    This report continues the discussion of unitary error bases and quantum codes. Nice error bases are characterized in terms of the existence of certain characters in a group. A general construction for error bases which are non-abelian over the center is given. The method for obtaining codes due to Calderbank et al. is generalized and expressed purely in representation theoretic terms. The significance of the inertia subgroup both for constructing codes and obtaining the set of transversally implementable operations is demonstrated.

  10. Application of ISO-TAG4 to the reporting of limit of error on the inventory difference

    SciTech Connect (OSTI)

    Murdock, C.; Suda, S.

    1993-07-01

    A standard reference does not exist for evaluating and expressing systematic and random uncertainty, thus, there is no basis for comparing measurement uncertainties at different facilities. Based on recommendations of the International Committee for Weights and Measures, the National Center for Standards and Certification Information, which is responsible for information on standardization programs and related activities, has published ISO-TAG4, Guide to the Expression of Uncertainty in Measurement (1993). The guide establishes general rules for evaluating and expressing uncertainty in physical measurements by presenting definitions, basic concepts and examples. it focuses on the methods of evaluating uncertainty components rather than categorizing the components, thus avoiding the ambiguity encountered when categorizing uncertainty components as ``random`` and ``systematic.`` This paper presents an overview of the terms specific to the guide, including standard and combined standard uncertainty, Type A and Type B evaluation, expanded uncertainty, and coverage factor. It illustrates Type A and Type B evaluation of random and systematic errors in forms relating to nuclear material accountability work. This guide could be adapted by the MC&A community.

  11. Linux Kernel Error Detection and Correction

    Energy Science and Technology Software Center (OSTI)

    2007-04-11

    EDAC-utils consists fo a library and set of utilities for retrieving statistics from the Linux Kernel Error Detection and Correction (EDAC) drivers.

  12. runtime error message: "readControlMsg: System returned error Connection

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

    timed out on TCP socket fd" readControlMsg: System returned error Connection timed out on TCP socket fd" runtime error message: "readControlMsg: System returned error Connection timed out on TCP socket fd" June 30, 2015 Symptom User jobs with sinlge or multiple apruns in a batch script may get this run time error: "readControlMsg: System returned error Connection timed out on TCP socket fd". This problem is intermittent, sometimes resubmit works. This error

  13. Global residential appliance standards

    SciTech Connect (OSTI)

    Turiel, I.; McMahon, J.E.; Lebot, B.

    1993-03-01

    In most countries, residential electricity consumption typically ranges from 20% to 40% of total electricity consumption. This energy is used for heating, cooling, refrigeration and other end-uses. Significant energy savings are possible if new appliance purchases are for models with higher efficiency than that of existing models. There are several ways to ensure or encourage such an outcome, for example, appliance rebates, innovative procurement, and minimum efficiency standards. This paper focuses on the latter approach. At the present time, the US is the only country with comprehensive appliance energy efficiency standards. However, many other countries, such as Australia, Canada, the European Community (EC), Japan and Korea, are considering enacting standards. The greatest potential impact of minimum efficiency standards for appliances is in the developing countries (e.g., China and India), where saturations of household appliances are relatively low but growing rapidly. This paper discusses the potential savings that could be achieved from global appliance efficiency standards for refrigerators and freezers. It also could be achieved from global appliance efficiency standards for refrigerators and freezers. It also discusses the impediments to establishing common standards for certain appliance types, such as differing test procedures, characteristics, and fuel prices. A methodology for establishing global efficiency standards for refrigerators and freezers is described.

  14. Wind Power Forecasting Error Distributions over Multiple Timescales (Presentation)

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01

    This presentation presents some statistical analysis of wind power forecast errors and error distributions, with examples using ERCOT data.

  15. Error recovery to enable error-free message transfer between nodes of a computer network

    DOE Patents [OSTI]

    Blumrich, Matthias A.; Coteus, Paul W.; Chen, Dong; Gara, Alan; Giampapa, Mark E.; Heidelberger, Philip; Hoenicke, Dirk; Takken, Todd; Steinmacher-Burow, Burkhard; Vranas, Pavlos M.

    2016-01-26

    An error-recovery method to enable error-free message transfer between nodes of a computer network. A first node of the network sends a packet to a second node of the network over a link between the nodes, and the first node keeps a copy of the packet on a sending end of the link until the first node receives acknowledgment from the second node that the packet was received without error. The second node tests the packet to determine if the packet is error free. If the packet is not error free, the second node sets a flag to mark the packet as corrupt. The second node returns acknowledgement to the first node specifying whether the packet was received with or without error. When the packet is received with error, the link is returned to a known state and the packet is sent again to the second node.

  16. Quantum error-correcting codes and devices

    DOE Patents [OSTI]

    Gottesman, Daniel

    2000-10-03

    A method of forming quantum error-correcting codes by first forming a stabilizer for a Hilbert space. A quantum information processing device can be formed to implement such quantum codes.

  17. Standards Development Organizations | Department of Energy

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

    Standards Development Organizations Standards Development Organizations Many standards development organizations (SDOs) are working to develop codes and standards needed to prepare for the commercialization of alternative fuel vehicle technologies. The following graphic templates show the SDOs responsible for leading the support and development of key codes and standards for hydrogen-related technologies. National Template: Stationary & Portable Fuel Cell Systems National Template: Hydrogen

  18. Error and uncertainty in Raman thermal conductivity measurements

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

    Thomas Edwin Beechem; Yates, Luke; Graham, Samuel

    2015-04-22

    We investigated error and uncertainty in Raman thermal conductivity measurements via finite element based numerical simulation of two geometries often employed -- Joule-heating of a wire and laser-heating of a suspended wafer. Using this methodology, the accuracy and precision of the Raman-derived thermal conductivity are shown to depend on (1) assumptions within the analytical model used in the deduction of thermal conductivity, (2) uncertainty in the quantification of heat flux and temperature, and (3) the evolution of thermomechanical stress during testing. Apart from the influence of stress, errors of 5% coupled with uncertainties of ±15% are achievable for most materialsmore » under conditions typical of Raman thermometry experiments. Error can increase to >20%, however, for materials having highly temperature dependent thermal conductivities or, in some materials, when thermomechanical stress develops concurrent with the heating. A dimensionless parameter -- termed the Raman stress factor -- is derived to identify when stress effects will induce large levels of error. Together, the results compare the utility of Raman based conductivity measurements relative to more established techniques while at the same time identifying situations where its use is most efficacious.« less

  19. The role of variation, error, and complexity in manufacturing defects

    SciTech Connect (OSTI)

    Hinckley, C.M.; Barkan, P.

    1994-03-01

    Variation in component properties and dimensions is a widely recognized factor in product defects which can be quantified and controlled by Statistical Process Control methodologies. Our studies have shown, however, that traditional statistical methods are ineffective in characterizing and controlling defects caused by error. The distinction between error and variation becomes increasingly important as the target defect rates approach extremely low values. Motorola data substantiates our thesis that defect rates in the range of several parts per million can only be achieved when traditional methods for controlling variation are combined with methods that specifically focus on eliminating defects due to error. Complexity in the product design, manufacturing processes, or assembly increases the likelihood of defects due to both variation and error. Thus complexity is also a root cause of defects. Until now, the absence of a sound correlation between defects and complexity has obscured the importance of this relationship. We have shown that assembly complexity can be quantified using Design for Assembly (DFA) analysis. High levels of correlation have been found between our complexity measures and defect data covering tens of millions of assembly operations in two widely different industries. The availability of an easily determined measure of complexity, combined with these correlations, permits rapid estimation of the relative defect rates for alternate design concepts. This should prove to be a powerful tool since it can guide design improvement at an early stage when concepts are most readily modified.

  20. Error and uncertainty in Raman thermal conductivity measurements

    SciTech Connect (OSTI)

    Thomas Edwin Beechem; Yates, Luke; Graham, Samuel

    2015-04-22

    We investigated error and uncertainty in Raman thermal conductivity measurements via finite element based numerical simulation of two geometries often employed -- Joule-heating of a wire and laser-heating of a suspended wafer. Using this methodology, the accuracy and precision of the Raman-derived thermal conductivity are shown to depend on (1) assumptions within the analytical model used in the deduction of thermal conductivity, (2) uncertainty in the quantification of heat flux and temperature, and (3) the evolution of thermomechanical stress during testing. Apart from the influence of stress, errors of 5% coupled with uncertainties of ±15% are achievable for most materials under conditions typical of Raman thermometry experiments. Error can increase to >20%, however, for materials having highly temperature dependent thermal conductivities or, in some materials, when thermomechanical stress develops concurrent with the heating. A dimensionless parameter -- termed the Raman stress factor -- is derived to identify when stress effects will induce large levels of error. Together, the results compare the utility of Raman based conductivity measurements relative to more established techniques while at the same time identifying situations where its use is most efficacious.

  1. Trends in Commercial Buildings--Overview

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

    Buildings > Commercial Buildings Energy Consumption Survey Survey Methodology Sampling Error, Standard Errors, and Relative Standard Errors The Commercial Buildings Energy...

  2. Superdense coding interleaved with forward error correction

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

    Humble, Travis S.; Sadlier, Ronald J.

    2016-05-12

    Superdense coding promises increased classical capacity and communication security but this advantage may be undermined by noise in the quantum channel. We present a numerical study of how forward error correction (FEC) applied to the encoded classical message can be used to mitigate against quantum channel noise. By studying the bit error rate under different FEC codes, we identify the unique role that burst errors play in superdense coding, and we show how these can be mitigated against by interleaving the FEC codewords prior to transmission. As a result, we conclude that classical FEC with interleaving is a useful methodmore » to improve the performance in near-term demonstrations of superdense coding.« less

  3. Laser Phase Errors in Seeded FELs

    SciTech Connect (OSTI)

    Ratner, D.; Fry, A.; Stupakov, G.; White, W.; /SLAC

    2012-03-28

    Harmonic seeding of free electron lasers has attracted significant attention from the promise of transform-limited pulses in the soft X-ray region. Harmonic multiplication schemes extend seeding to shorter wavelengths, but also amplify the spectral phase errors of the initial seed laser, and may degrade the pulse quality. In this paper we consider the effect of seed laser phase errors in high gain harmonic generation and echo-enabled harmonic generation. We use simulations to confirm analytical results for the case of linearly chirped seed lasers, and extend the results for arbitrary seed laser envelope and phase.

  4. Intel C++ compiler error: stl_iterator_base_types.h

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

    C++ compiler error: stliteratorbasetypes.h Intel C++ compiler error: stliteratorbasetypes.h December 7, 2015 by Scott French Because the system-supplied version of GCC is...

  5. Error estimates for fission neutron outputs (Conference) | SciTech...

    Office of Scientific and Technical Information (OSTI)

    Error estimates for fission neutron outputs Citation Details In-Document Search Title: Error estimates for fission neutron outputs You are accessing a document from the...

  6. Internal compiler error for function pointer with identically...

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

    Internal compiler error for function pointer with identically named arguments Internal compiler error for function pointer with identically named arguments June 9, 2015 by Scott...

  7. V-235: Cisco Mobility Services Engine Configuration Error Lets...

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

    5: Cisco Mobility Services Engine Configuration Error Lets Remote Users Login Anonymously V-235: Cisco Mobility Services Engine Configuration Error Lets Remote Users Login ...

  8. Error Estimation for Fault Tolerance in Numerical Integration...

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

    Error Estimation for Fault Tolerance in Numerical Integration Solvers Event Sponsor: ... In numerical integration solvers, approximation error can be estimated at a low cost. We ...

  9. A posteriori error analysis of parameterized linear systems using...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: A posteriori error analysis of parameterized linear systems using spectral methods. Citation Details In-Document Search Title: A posteriori error analysis of ...

  10. Accounting for Model Error in the Calibration of Physical Models...

    Office of Scientific and Technical Information (OSTI)

    Accounting for Model Error in the Calibration of Physical Models. Citation Details In-Document Search Title: Accounting for Model Error in the Calibration of Physical Models. ...

  11. Error Analysis in Nuclear Density Functional Theory (Journal...

    Office of Scientific and Technical Information (OSTI)

    Error Analysis in Nuclear Density Functional Theory Citation Details In-Document Search Title: Error Analysis in Nuclear Density Functional Theory Authors: Schunck, N ; McDonnell,...

  12. Error Analysis in Nuclear Density Functional Theory (Journal...

    Office of Scientific and Technical Information (OSTI)

    Error Analysis in Nuclear Density Functional Theory Citation Details In-Document Search Title: Error Analysis in Nuclear Density Functional Theory You are accessing a document...

  13. Raman Thermometry: Comparing Methods to Minimize Error. (Conference...

    Office of Scientific and Technical Information (OSTI)

    Raman Thermometry: Comparing Methods to Minimize Error. Citation Details In-Document Search Title: Raman Thermometry: Comparing Methods to Minimize Error. Abstract not provided....

  14. Technical Standards Managers

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

    FACILITYADDRESS LOC CODE DOE TECHNICAL STANDARD MANAGERS AU-30 DOE Technical Standards ... FACILITYADDRESS LOC CODE DOE TECHNICAL STANDARD MANAGERS DOE-CTA TSM Gustave E. (Bud) ...

  15. An Integrated Signaling-Encryption Mechanism to Reduce Error Propagation in Wireless Communications: Performance Analyses

    SciTech Connect (OSTI)

    Olama, Mohammed M; Matalgah, Mustafa M; Bobrek, Miljko

    2015-01-01

    Traditional encryption techniques require packet overhead, produce processing time delay, and suffer from severe quality of service deterioration due to fades and interference in wireless channels. These issues reduce the effective transmission data rate (throughput) considerably in wireless communications, where data rate with limited bandwidth is the main constraint. In this paper, performance evaluation analyses are conducted for an integrated signaling-encryption mechanism that is secure and enables improved throughput and probability of bit-error in wireless channels. This mechanism eliminates the drawbacks stated herein by encrypting only a small portion of an entire transmitted frame, while the rest is not subject to traditional encryption but goes through a signaling process (designed transformation) with the plaintext of the portion selected for encryption. We also propose to incorporate error correction coding solely on the small encrypted portion of the data to drastically improve the overall bit-error rate performance while not noticeably increasing the required bit-rate. We focus on validating the signaling-encryption mechanism utilizing Hamming and convolutional error correction coding by conducting an end-to-end system-level simulation-based study. The average probability of bit-error and throughput of the encryption mechanism are evaluated over standard Gaussian and Rayleigh fading-type channels and compared to the ones of the conventional advanced encryption standard (AES).

  16. Error propagation equations for estimating the uncertainty in high-speed wind tunnel test results

    SciTech Connect (OSTI)

    Clark, E.L.

    1994-07-01

    Error propagation equations, based on the Taylor series model, are derived for the nondimensional ratios and coefficients most often encountered in high-speed wind tunnel testing. These include pressure ratio and coefficient, static force and moment coefficients, dynamic stability coefficients, and calibration Mach number. The error equations contain partial derivatives, denoted as sensitivity coefficients, which define the influence of free-steam Mach number, M{infinity}, on various aerodynamic ratios. To facilitate use of the error equations, sensitivity coefficients are derived and evaluated for five fundamental aerodynamic ratios which relate free-steam test conditions to a reference condition.

  17. Analysis of Solar Two Heliostat Tracking Error Sources

    SciTech Connect (OSTI)

    Jones, S.A.; Stone, K.W.

    1999-01-28

    This paper explores the geometrical errors that reduce heliostat tracking accuracy at Solar Two. The basic heliostat control architecture is described. Then, the three dominant error sources are described and their effect on heliostat tracking is visually illustrated. The strategy currently used to minimize, but not truly correct, these error sources is also shown. Finally, a novel approach to minimizing error is presented.

  18. Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)

    SciTech Connect (OSTI)

    Hodge, B. M.; Ela, E.; Milligan, M.

    2011-10-01

    This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

  19. WIPP Weatherization: Common Errors and Innovative Solutions Presentation

    Broader source: Energy.gov [DOE]

    This presentation contains information on WIPP Weatherization: Common Errors and Innovative Solutions.

  20. June 2008 Standards Forum and Standards Actions

    Office of Environmental Management (EM)

    Standards Forum And Standards Actions U.S. Department of Energy Office of Nuclear Safety, Quality Assurance and Environment June 2008 Technical Standards Program (http://www.hss.energy.gov/nuclearsafety/techstds/) Technical Standards Program Manager's Note As of this issue, our publication has a new look and focus. This is part of our effort to continuously improve the Technical Standards Program (TSP) processes and products. We have updated the TSP newsletter to make it more organized and user

  1. Errors in response calculations for beams

    SciTech Connect (OSTI)

    Wada, H.; Wurburton, G.B.

    1985-05-01

    When the finite element method is used to idealize a structure, its dynamic response can be determined from the governing matrix equation by the normal mode method or by one of the many approximate direct integration methods. In either method the approximate data of the finite element idealization are used, but further assumptions are introduced by the direct integration scheme. It is the purpose of this paper to study these errors for a simple structure. The transient flexural vibrations of a uniform cantilever beam, which is subjected to a transverse force at the free end, are determined by the Laplace transform method. Comparable responses are obtained for a finite element idealization of the beam, using the normal mode and Newmark average acceleration methods; the errors associated with the approximate methods are studied. If accuracy has priority and the quantity of data is small, the normal mode method is recommended; however, if the quantity of data is large, the Newmark method is useful.

  2. Detecting Soft Errors in Stencil based Computations

    SciTech Connect (OSTI)

    Sharma, V.; Gopalkrishnan, G.; Bronevetsky, G.

    2015-05-06

    Given the growing emphasis on system resilience, it is important to develop software-level error detectors that help trap hardware-level faults with reasonable accuracy while minimizing false alarms as well as the performance overhead introduced. We present a technique that approaches this idea by taking stencil computations as our target, and synthesizing detectors based on machine learning. In particular, we employ linear regression to generate computationally inexpensive models which form the basis for error detection. Our technique has been incorporated into a new open-source library called SORREL. In addition to reporting encouraging experimental results, we demonstrate techniques that help reduce the size of training data. We also discuss the efficacy of various detectors synthesized, as well as our future plans.

  3. Redundancy and Error Resilience in Boolean Networks

    SciTech Connect (OSTI)

    Peixoto, Tiago P.

    2010-01-29

    We consider the effect of noise in sparse Boolean networks with redundant functions. We show that they always exhibit a nonzero error level, and the dynamics undergoes a phase transition from nonergodicity to ergodicity, as a function of noise, after which the system is no longer capable of preserving a memory of its initial state. We obtain upper bounds on the critical value of noise for networks of different sparsity.

  4. Systematic errors in long baseline oscillation experiments

    SciTech Connect (OSTI)

    Harris, Deborah A.; /Fermilab

    2006-02-01

    This article gives a brief overview of long baseline neutrino experiments and their goals, and then describes the different kinds of systematic errors that are encountered in these experiments. Particular attention is paid to the uncertainties that come about because of imperfect knowledge of neutrino cross sections and more generally how neutrinos interact in nuclei. Near detectors are planned for most of these experiments, and the extent to which certain uncertainties can be reduced by the presence of near detectors is also discussed.

  5. Common Errors and Innovative Solutions Transcript | Department of Energy

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

    Common Errors and Innovative Solutions Transcript Common Errors and Innovative Solutions Transcript An example of case studies, mainly by showing photos of errors and good examples, then discussing the purpose of the home energy professional guidelines and certification. There may be more examples of what not to do only because these were good learning opportunities. common_errors_innovative_solutions.doc (41.5 KB) More Documents & Publications WIPP Weatherization: Common Errors and

  6. DOE standard: Radiological control

    SciTech Connect (OSTI)

    Not Available

    1999-07-01

    The Department of Energy (DOE) has developed this Standard to assist line managers in meeting their responsibilities for implementing occupational radiological control programs. DOE has established regulatory requirements for occupational radiation protection in Title 10 of the Code of Federal Regulations, Part 835 (10 CFR 835), ``Occupational Radiation Protection``. Failure to comply with these requirements may lead to appropriate enforcement actions as authorized under the Price Anderson Act Amendments (PAAA). While this Standard does not establish requirements, it does restate, paraphrase, or cite many (but not all) of the requirements of 10 CFR 835 and related documents (e.g., occupational safety and health, hazardous materials transportation, and environmental protection standards). Because of the wide range of activities undertaken by DOE and the varying requirements affecting these activities, DOE does not believe that it would be practical or useful to identify and reproduce the entire range of health and safety requirements in this Standard and therefore has not done so. In all cases, DOE cautions the user to review any underlying regulatory and contractual requirements and the primary guidance documents in their original context to ensure that the site program is adequate to ensure continuing compliance with the applicable requirements. To assist its operating entities in achieving and maintaining compliance with the requirements of 10 CFR 835, DOE has established its primary regulatory guidance in the DOE G 441.1 series of Guides. This Standard supplements the DOE G 441.1 series of Guides and serves as a secondary source of guidance for achieving compliance with 10 CFR 835.

  7. Fractional charge and spin errors in self-consistent Greens function theory

    SciTech Connect (OSTI)

    Phillips, Jordan J. Kananenka, Alexei A.; Zgid, Dominika

    2015-05-21

    We examine fractional charge and spin errors in self-consistent Greens function theory within a second-order approximation (GF2). For GF2, it is known that the summation of diagrams resulting from the self-consistent solution of the Dyson equation removes the divergences pathological to second-order Mller-Plesset (MP2) theory for strong correlations. In the language often used in density functional theory contexts, this means GF2 has a greatly reduced fractional spin error relative to MP2. The natural question then is what effect, if any, does the Dyson summation have on the fractional charge error in GF2? To this end, we generalize our previous implementation of GF2 to open-shell systems and analyze its fractional spin and charge errors. We find that like MP2, GF2 possesses only a very small fractional charge error, and consequently minimal many electron self-interaction error. This shows that GF2 improves on the critical failings of MP2, but without altering the positive features that make it desirable. Furthermore, we find that GF2 has both less fractional charge and fractional spin errors than typical hybrid density functionals as well as random phase approximation with exchange.

  8. Error Reduction for Weigh-In-Motion

    SciTech Connect (OSTI)

    Hively, Lee M; Abercrombie, Robert K; Scudiere, Matthew B; Sheldon, Frederick T

    2009-01-01

    Federal and State agencies need certifiable vehicle weights for various applications, such as highway inspections, border security, check points, and port entries. ORNL weigh-in-motion (WIM) technology was previously unable to provide certifiable weights, due to natural oscillations, such as vehicle bouncing and rocking. Recent ORNL work demonstrated a novel filter to remove these oscillations. This work shows further filtering improvements to enable certifiable weight measurements (error < 0.1%) for a higher traffic volume with less effort (elimination of redundant weighing).

  9. Error Reduction in Weigh-In-Motion

    Energy Science and Technology Software Center (OSTI)

    2007-09-21

    Federal and State agencies need certifiable vehicle weights for various applications, such as highway inspections, border security, check points, and port entries. ORNL weigh-in-motion (WIM) technology was previously unable to provide certifiable weights, due to natural oscillations, such as vehicle bounding and rocking. Recent ORNL work demonstrated a novel filter to remove these oscillations. This work shows further filtering improvements to enable certifiable weight measurements (error < 0.1%) for a higher traffic volume with lessmore » effort (elimination of redundant weighing)« less

  10. HUMAN ERROR QUANTIFICATION USING PERFORMANCE SHAPING FACTORS IN THE SPAR-H METHOD

    SciTech Connect (OSTI)

    Harold S. Blackman; David I. Gertman; Ronald L. Boring

    2008-09-01

    This paper describes a cognitively based human reliability analysis (HRA) quantification technique for estimating the human error probabilities (HEPs) associated with operator and crew actions at nuclear power plants. The method described here, Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method, was developed to aid in characterizing and quantifying human performance at nuclear power plants. The intent was to develop a defensible method that would consider all factors that may influence performance. In the SPAR-H approach, calculation of HEP rates is especially straightforward, starting with pre-defined nominal error rates for cognitive vs. action-oriented tasks, and incorporating performance shaping factor multipliers upon those nominal error rates.

  11. Stability and error analysis of nodal expansion method for convection-diffusion equation

    SciTech Connect (OSTI)

    Deng, Z.; Rizwan-Uddin; Li, F.; Sun, Y.

    2012-07-01

    The development, and stability and error analyses of nodal expansion method (NEM) for one dimensional steady-state convection diffusion equation is presented. Following the traditional procedure to develop NEM, the discrete formulation of the convection-diffusion equation, which is similar to the standard finite difference scheme, is derived. The method of discrete perturbation analysis is applied to this discrete form to study the stability of the NEM. The scheme based on the NEM is found to be stable for local Peclet number less than 4.644. A maximum principle is proved for the NEM scheme, followed by an error analysis carried out by applying the Maximum principle together with a carefully constructed comparison function. The scheme for the convection diffusion equation is of second-order. Numerical experiments are carried and the results agree with the conclusions of the stability and error analyses. (authors)

  12. The Residual Setup Errors of Different IGRT Alignment Procedures for Head and Neck IMRT and the Resulting Dosimetric Impact

    SciTech Connect (OSTI)

    Graff, Pierre; Radiation-Oncology, Alexis Vautrin Cancer Center, Vandoeuvre-Les-Nancy; Doctoral School BioSE , Nancy ; Kirby, Neil; Weinberg, Vivian; Department of Biostatistics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California ; Chen, Josephine; Yom, Sue S.; Lambert, Louise; Radiation-Oncology, Montreal University Centre, Montreal ; Pouliot, Jean

    2013-05-01

    Purpose: To assess residual setup errors during head and neck radiation therapy and the resulting consequences for the delivered dose for various patient alignment procedures. Methods and Materials: Megavoltage cone beam computed tomography (MVCBCT) scans from 11 head and neck patients who underwent intensity modulated radiation therapy were used to assess setup errors. Each MVCBCT scan was registered to its reference planning kVCT, with seven different alignment procedures: automatic alignment and manual registration to 6 separate bony landmarks (sphenoid, left/right maxillary sinuses, mandible, cervical 1 [C1]-C2, and C7-thoracic 1 [T1] vertebrae). Shifts in the different alignments were compared with each other to determine whether there were any statistically significant differences. Then, the dose distribution was recalculated on 3 MVCBCT images per patient for every alignment procedure. The resulting dose-volume histograms for targets and organs at risk (OARs) were compared to those from the planning kVCTs. Results: The registration procedures produced statistically significant global differences in patient alignment and actual dose distribution, calling for a need for standardization of patient positioning. Vertically, the automatic, sphenoid, and maxillary sinuses alignments mainly generated posterior shifts and resulted in mean increases in maximal dose to OARs of >3% of the planned dose. The suggested choice of C1-C2 as a reference landmark appears valid, combining both OAR sparing and target coverage. Assuming this choice, relevant margins to apply around volumes of interest at the time of planning to take into account for the relative mobility of other regions are discussed. Conclusions: Use of different alignment procedures for treating head and neck patients produced variations in patient setup and dose distribution. With concern for standardizing practice, C1-C2 reference alignment with relevant margins around planning volumes seems to be a valid

  13. SU-D-204-05: Quantitative Comparison of a High Resolution Micro-Angiographic Fluoroscopic (MAF) Detector with a Standard Flat Panel Detector (FPD) Using the New Metric of Generalized Measured Relative Object Detectability (GM-ROD)

    SciTech Connect (OSTI)

    Russ, M; Ionita, C; Bednarek, D; Rudin, S

    2015-06-15

    Purpose: In endovascular image-guided neuro-interventions, visualization of fine detail is paramount. For example, the ability of the interventionist to visualize the stent struts depends heavily on the x-ray imaging detector performance. Methods: A study to examine the relative performance of the high resolution MAF-CMOS (pixel size 75µm, Nyquist frequency 6.6 cycles/mm) and a standard Flat Panel Detector (pixel size 194µm, Nyquist frequency 2.5 cycles/mm) detectors in imaging a neuro stent was done using the Generalized Measured Relative Object Detectability (GM-ROD) metric. Low quantum noise images of a deployed stent were obtained by averaging 95 frames obtained by both detectors without changing other exposure or geometric parameters. The square of the Fourier transform of each image is taken and divided by the generalized normalized noise power spectrum to give an effective measured task-specific signal-to-noise ratio. This expression is then integrated from 0 to each of the detector’s Nyquist frequencies, and the GM-ROD value is determined by taking a ratio of the integrals for the MAF-CMOS to that of the FPD. The lower bound of integration can be varied to emphasize high frequencies in the detector comparisons. Results: The MAF-CMOS detector exhibits vastly superior performance over the FPD when integrating over all frequencies, yielding a GM-ROD value of 63.1. The lower bound of integration was stepped up in increments of 0.5 cycles/mm for higher frequency comparisons. As the lower bound increased, the GM-ROD value was augmented, reflecting the superior performance of the MAF-CMOS in the high frequency regime. Conclusion: GM-ROD is a versatile metric that can provide quantitative detector and task dependent comparisons that can be used as a basis for detector selection. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.

  14. Resolved: "error while loading shared libraries: libalpslli.so...

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

    "error while loading shared libraries: libalpslli.so.0" with serial codes on login nodes Resolved: "error while loading shared libraries: libalpslli.so.0" with serial codes on...

  15. MPI errors from cray-mpich/7.3.0

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

    MPI errors from cray-mpich7.3.0 MPI errors from cray-mpich7.3.0 January 6, 2016 by Ankit Bhagatwala A change in the MPICH2 library that now strictly enforces non-overlapping...

  16. Sinusoidal Siemens star spatial frequency response measurement errors due to misidentified target centers

    SciTech Connect (OSTI)

    Birch, Gabriel Carisle; Griffin, John Clark

    2015-07-23

    Numerous methods are available to measure the spatial frequency response (SFR) of an optical system. A recent change to the ISO 12233 photography resolution standard includes a sinusoidal Siemens star test target. We take the sinusoidal Siemens star proposed by the ISO 12233 standard, measure system SFR, and perform an analysis of errors induced by incorrectly identifying the center of a test target. We show a closed-form solution for the radial profile intensity measurement given an incorrectly determined center and describe how this error reduces the measured SFR of the system. As a result, using the closed-form solution, we propose a two-step process by which test target centers are corrected and the measured SFR is restored to the nominal, correctly centered values.

  17. Sinusoidal Siemens star spatial frequency response measurement errors due to misidentified target centers

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

    Birch, Gabriel Carisle; Griffin, John Clark

    2015-07-23

    Numerous methods are available to measure the spatial frequency response (SFR) of an optical system. A recent change to the ISO 12233 photography resolution standard includes a sinusoidal Siemens star test target. We take the sinusoidal Siemens star proposed by the ISO 12233 standard, measure system SFR, and perform an analysis of errors induced by incorrectly identifying the center of a test target. We show a closed-form solution for the radial profile intensity measurement given an incorrectly determined center and describe how this error reduces the measured SFR of the system. As a result, using the closed-form solution, we proposemore » a two-step process by which test target centers are corrected and the measured SFR is restored to the nominal, correctly centered values.« less

  18. Regional Standards Enforcement

    Broader source: Energy.gov [DOE]

    Central air conditioners are now subject to a base national standard in the North and different, regional standards in the Southeast and Southwest. This page provides information about those standards and how DOE enforces them.

  19. Energy Efficiency Product Standards

    Broader source: Energy.gov [DOE]

    New Jersey Energy Efficiency Product Standards, enacted in 2005, include minimum standards for eight products, which were preempted by the federal Energy Policy Act of 2005. Future standards, if...

  20. Quantifying the Effect of Lidar Turbulence Error on Wind Power Prediction

    SciTech Connect (OSTI)

    Newman, Jennifer F.; Clifton, Andrew

    2016-01-01

    Currently, cup anemometers on meteorological towers are used to measure wind speeds and turbulence intensity to make decisions about wind turbine class and site suitability; however, as modern turbine hub heights increase and wind energy expands to complex and remote sites, it becomes more difficult and costly to install meteorological towers at potential sites. As a result, remote-sensing devices (e.g., lidars) are now commonly used by wind farm managers and researchers to estimate the flow field at heights spanned by a turbine. Although lidars can accurately estimate mean wind speeds and wind directions, there is still a large amount of uncertainty surrounding the measurement of turbulence using these devices. Errors in lidar turbulence estimates are caused by a variety of factors, including instrument noise, volume averaging, and variance contamination, in which the magnitude of these factors is highly dependent on measurement height and atmospheric stability. As turbulence has a large impact on wind power production, errors in turbulence measurements will translate into errors in wind power prediction. The impact of using lidars rather than cup anemometers for wind power prediction must be understood if lidars are to be considered a viable alternative to cup anemometers.In this poster, the sensitivity of power prediction error to typical lidar turbulence measurement errors is assessed. Turbulence estimates from a vertically profiling WINDCUBE v2 lidar are compared to high-resolution sonic anemometer measurements at field sites in Oklahoma and Colorado to determine the degree of lidar turbulence error that can be expected under different atmospheric conditions. These errors are then incorporated into a power prediction model to estimate the sensitivity of power prediction error to turbulence measurement error. Power prediction models, including the standard binning method and a random forest method, were developed using data from the aeroelastic simulator FAST

  1. IHS Standards Expert

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

    Standards » IHS IHS Standards Expert 1354608000000 IHS Standards Expert Los Alamos researchers can access IHS Standards from offsite via Remote Access. / / No / Question? 667-5809 library@lanl.gov IHS Standards Expert Los Alamos researchers can access IHS Standards from offsite via Remote Access. Login For each collection (society), one person may access pdfs at a time, per the Library's subscription license. Please free up the collection for another user when finished: download or print your

  2. Energy Efficiency Resource Standard

    Broader source: Energy.gov [DOE]

    Washington voters passed Initiative 937 in 2006, creating a renewable energy standard and an energy efficiency resource standard for the state's electric utilities. Initiative 937, enacted as th...

  3. April 2008 Standards Actions

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

    Visit the Technical Standards Program Web Site at http:www.hss.energy.govnuclear ... Standards Program (TSP) web page at http:hss.energy.govnuclear safetytechstds. ...

  4. Pressure Change Measurement Leak Testing Errors

    SciTech Connect (OSTI)

    Pryor, Jeff M; Walker, William C

    2014-01-01

    A pressure change test is a common leak testing method used in construction and Non-Destructive Examination (NDE). The test is known as being a fast, simple, and easy to apply evaluation method. While this method may be fairly quick to conduct and require simple instrumentation, the engineering behind this type of test is more complex than is apparent on the surface. This paper intends to discuss some of the more common errors made during the application of a pressure change test and give the test engineer insight into how to correctly compensate for these factors. The principals discussed here apply to ideal gases such as air or other monoatomic or diatomic gasses; however these same principals can be applied to polyatomic gasses or liquid flow rate with altered formula specific to those types of tests using the same methodology.

  5. Locked modes and magnetic field errors in MST

    SciTech Connect (OSTI)

    Almagri, A.F.; Assadi, S.; Prager, S.C.; Sarff, J.S.; Kerst, D.W.

    1992-06-01

    In the MST reversed field pinch magnetic oscillations become stationary (locked) in the lab frame as a result of a process involving interactions between the modes, sawteeth, and field errors. Several helical modes become phase locked to each other to form a rotating localized disturbance, the disturbance locks to an impulsive field error generated at a sawtooth crash, the error fields grow monotonically after locking (perhaps due to an unstable interaction between the modes and field error), and over the tens of milliseconds of growth confinement degrades and the discharge eventually terminates. Field error control has been partially successful in eliminating locking.

  6. A Bayesian Measurment Error Model for Misaligned Radiographic Data

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

    Lennox, Kristin P.; Glascoe, Lee G.

    2013-09-06

    An understanding of the inherent variability in micro-computed tomography (micro-CT) data is essential to tasks such as statistical process control and the validation of radiographic simulation tools. The data present unique challenges to variability analysis due to the relatively low resolution of radiographs, and also due to minor variations from run to run which can result in misalignment or magnification changes between repeated measurements of a sample. Positioning changes artificially inflate the variability of the data in ways that mask true physical phenomena. We present a novel Bayesian nonparametric regression model that incorporates both additive and multiplicative measurement error inmore » addition to heteroscedasticity to address this problem. We also use this model to assess the effects of sample thickness and sample position on measurement variability for an aluminum specimen. Supplementary materials for this article are available online.« less

  7. A Bayesian Measurment Error Model for Misaligned Radiographic Data

    SciTech Connect (OSTI)

    Lennox, Kristin P.; Glascoe, Lee G.

    2013-09-06

    An understanding of the inherent variability in micro-computed tomography (micro-CT) data is essential to tasks such as statistical process control and the validation of radiographic simulation tools. The data present unique challenges to variability analysis due to the relatively low resolution of radiographs, and also due to minor variations from run to run which can result in misalignment or magnification changes between repeated measurements of a sample. Positioning changes artificially inflate the variability of the data in ways that mask true physical phenomena. We present a novel Bayesian nonparametric regression model that incorporates both additive and multiplicative measurement error in addition to heteroscedasticity to address this problem. We also use this model to assess the effects of sample thickness and sample position on measurement variability for an aluminum specimen. Supplementary materials for this article are available online.

  8. Analysis of Errors in a Special Perturbations Satellite Orbit Propagator

    SciTech Connect (OSTI)

    Beckerman, M.; Jones, J.P.

    1999-02-01

    We performed an analysis of error densities for the Special Perturbations orbit propagator using data for 29 satellites in orbits of interest to Space Shuttle and International Space Station collision avoidance. We find that the along-track errors predominate. These errors increase monotonically over each 36-hour prediction interval. The predicted positions in the along-track direction progressively either leap ahead of or lag behind the actual positions. Unlike the along-track errors the radial and cross-track errors oscillate about their nearly zero mean values. As the number of observations per fit interval decline the along-track prediction errors, and amplitudes of the radial and cross-track errors, increase.

  9. Technical Standards Program

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2011-02-23

    The Order promotes DOE's use of Voluntary Consensus Standards (VCS) as the primary method for application of technical standards and establishes and manages the DOE Technical Standards Program (TSP) including technical standards development, information, activities, issues, and interactions. Admin Chg 1 dated 3-12-13.

  10. Technical Standards Program

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1999-11-19

    The Technical Standards Program (TSP) promotes the use of voluntary consensus standards by the Department of Energy (DOE), provides DOE with the means to develop needed technical standards, and manages overall technical standards information, activities, issues, and interactions. Cancels DOE O 1300.2A. Canceled by DOE O 252.1A

  11. NETL Focused Standards List

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

    1/6/14 Contact: Janet Lambert Reviewed: 3/5/14 Page 1 of 17 The National Energy Technology Laboratory (NETL) Focused Standards List is primarily derived from standard references contained in the requirements section of NETL's environment, safety, security, and health (ESS&H) and cyber security directives. All standards shall reference the most current edition/version of that standard. 1. DEPARTMENT OF ENERGY (DOE) AND OTHER GOVERNMENT STANDARDS AND REQUIREMENTS a. DOE Directives The

  12. Accurate description of torsion potentials in conjugated polymers using density functionals with reduced self-interaction error

    SciTech Connect (OSTI)

    Sutton, Christopher; Gray, Matthew T.; Brunsfeld, Max; Parrish, Robert M.; Sherrill, C. David; Sears, John S.; Brédas, Jean-Luc E-mail: thomas.koerzdoerfer@uni-potsdam.de; Körzdörfer, Thomas E-mail: thomas.koerzdoerfer@uni-potsdam.de; Computational Chemistry, Institute of Chemistry, University of Potsdam, D-14476 Potsdam

    2014-02-07

    We investigate the torsion potentials in two prototypical π-conjugated polymers, polyacetylene and polydiacetylene, as a function of chain length using different flavors of density functional theory. Our study provides a quantitative analysis of the delocalization error in standard semilocal and hybrid density functionals and demonstrates how it can influence structural and thermodynamic properties. The delocalization error is quantified by evaluating the many-electron self-interaction error (MESIE) for fractional electron numbers, which allows us to establish a direct connection between the MESIE and the error in the torsion barriers. The use of non-empirically tuned long-range corrected hybrid functionals results in a very significant reduction of the MESIE and leads to an improved description of torsion barrier heights. In addition, we demonstrate how our analysis allows the determination of the effective conjugation length in polyacetylene and polydiacetylene chains.

  13. Technical Standards Newsletter - August 2012 | Department of Energy

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

    August 2012 Technical Standards Newsletter - August 2012 The Standards Forum and Standards Actions, August 2012 Inside this issue: Featured DOE Technical Standards Activities DOE Technical Handbook, Accident Investigation and Prevention, Volumes I and II is Released Workshops and Events Nuclear Energy Standards Coordination Collaborative Meeting 2012 Chemical Safety and Life Cycle Management Workshop Nuclear Safety-Related Standards Activity Technical Standards, Newsletter-August 2012 (1.29 MB)

  14. A technique for human error analysis (ATHEANA)

    SciTech Connect (OSTI)

    Cooper, S.E.; Ramey-Smith, A.M.; Wreathall, J.; Parry, G.W.

    1996-05-01

    Probabilistic risk assessment (PRA) has become an important tool in the nuclear power industry, both for the Nuclear Regulatory Commission (NRC) and the operating utilities. Human reliability analysis (HRA) is a critical element of PRA; however, limitations in the analysis of human actions in PRAs have long been recognized as a constraint when using PRA. A multidisciplinary HRA framework has been developed with the objective of providing a structured approach for analyzing operating experience and understanding nuclear plant safety, human error, and the underlying factors that affect them. The concepts of the framework have matured into a rudimentary working HRA method. A trial application of the method has demonstrated that it is possible to identify potentially significant human failure events from actual operating experience which are not generally included in current PRAs, as well as to identify associated performance shaping factors and plant conditions that have an observable impact on the frequency of core damage. A general process was developed, albeit in preliminary form, that addresses the iterative steps of defining human failure events and estimating their probabilities using search schemes. Additionally, a knowledge- base was developed which describes the links between performance shaping factors and resulting unsafe actions.

  15. USE OF VOLUNTARY CONSENSUS STANDARDS AND INTERACTION WITH STANDARDS...

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

    USE OF VOLUNTARY CONSENSUS STANDARDS AND INTERACTION WITH STANDARDS DEVELOPMENT ORGANIZATIONS USE OF VOLUNTARY CONSENSUS STANDARDS AND INTERACTION WITH STANDARDS DEVELOPMENT ...

  16. Measurement uncertainty relations

    SciTech Connect (OSTI)

    Busch, Paul; Lahti, Pekka; Werner, Reinhard F.

    2014-04-15

    Measurement uncertainty relations are quantitative bounds on the errors in an approximate joint measurement of two observables. They can be seen as a generalization of the error/disturbance tradeoff first discussed heuristically by Heisenberg. Here we prove such relations for the case of two canonically conjugate observables like position and momentum, and establish a close connection with the more familiar preparation uncertainty relations constraining the sharpness of the distributions of the two observables in the same state. Both sets of relations are generalized to means of order ? rather than the usual quadratic means, and we show that the optimal constants are the same for preparation and for measurement uncertainty. The constants are determined numerically and compared with some bounds in the literature. In both cases, the near-saturation of the inequalities entails that the state (resp. observable) is uniformly close to a minimizing one.

  17. Polaractivation for classical zero-error capacity of qudit channels

    SciTech Connect (OSTI)

    Gyongyosi, Laszlo; Imre, Sandor

    2014-12-04

    We introduce a new phenomenon for zero-error transmission of classical information over quantum channels that initially were not able for zero-error classical communication. The effect is called polaractivation, and the result is similar to the superactivation effect. We use the Choi-Jamiolkowski isomorphism and the Schmidt-theorem to prove the polaractivation of classical zero-error capacity and define the polaractivator channel coding scheme.

  18. Internal compiler error for function pointer with identically named

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

    arguments Internal compiler error for function pointer with identically named arguments Internal compiler error for function pointer with identically named arguments June 9, 2015 by Scott French, NERSC USG Status: Bug 21435 reported to PGI For pgcc versions after 12.x (up through 12.9 is fine, but 13.x and 14.x are not), you may observe an internal compiler error associated with function pointer prototypes when named arguments are used. Specifically, if a function pointer type is defined

  19. Federal Appliance Standards

    Office of Energy Efficiency and Renewable Energy (EERE)

    Note: HR 6582 of 2012 made some modifications to the efficiency standards previously adopted for some appliance types. The bill did not adopt new standards for previously unregulated appliances,...

  20. August 2006 Standards Actions

    Energy Savers [EERE]

    Visit the Technical Standards Program Web Site at http:www.eh.doe.gov techstds ... on the Technical Standards Program (TSP) web page at http:www.eh.doe.govtechstds. ...

  1. February 2007 Standards Actions

    Energy Savers [EERE]

    Visit the Technical Standards Program Web Site at http:www.eh.doe.gov techstds ... on the Technical Standards Program (TSP) web page at http:www.eh.doe.govtechstds. ...

  2. Energy Efficiency Portfolio Standard

    Broader source: Energy.gov [DOE]

    On December 2015, the NY PSC issued an order extending the Energy Efficiency Portfolio Standard (EEPS) and Customer-Sited Tier (CST) of the Renewable Portfolio Standard (RPS) till Feb 29, 2016...

  3. Standard Form 120

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

    1 OF STANDARD FORM 120 REV. APRIL 1957 GEN. SERV. ADMIN. FPMR (41 CFR) 101-43.311 ... NUMBER FAIR % ITEM DESCRIPTION PER UNIT TOTAL NO. (a) (b) (f) (g) STANDARD FORM 120 REV. ...

  4. Appliance Energy Efficiency Standards

    Broader source: Energy.gov [DOE]

    In 2004 the Energy Efficiency Standards Act (EESA of 2004) became law in the State of Maryland. The General Assembly passed the EESA to establish minimum energy efficiency standards on nine...

  5. WIPP Weatherization: Common Errors and Innovative Solutions Presentati...

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

    More Documents & Publications Common Errors and Innovative Solutions Transcript Building ... America Best Practices Series: Volume 12. Energy Renovations-Insulation: A Guide for ...

  6. Output-Based Error Estimation and Adaptation for Uncertainty...

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

    Output-Based Error Estimation and Adaptation for Uncertainty Quantification Isaac M. Asher and Krzysztof J. Fidkowski University of Michigan US National Congress on Computational...

  7. Platform-Independent Method for Detecting Errors in Metagenomic...

    Office of Scientific and Technical Information (OSTI)

    Title: Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE Authors: Keegan, K. P. ; Trimble, W. L. ; Wilkening, J. ; Wilke, A. ; Harrison, T. ; ...

  8. Detecting and correcting hard errors in a memory array

    DOE Patents [OSTI]

    Kalamatianos, John; John, Johnsy Kanjirapallil; Gelinas, Robert; Sridharan, Vilas K.; Nevius, Phillip E.

    2015-11-19

    Hard errors in the memory array can be detected and corrected in real-time using reusable entries in an error status buffer. Data may be rewritten to a portion of a memory array and a register in response to a first error in data read from the portion of the memory array. The rewritten data may then be written from the register to an entry of an error status buffer in response to the rewritten data read from the register differing from the rewritten data read from the portion of the memory array.

  9. Info-Gap Analysis of Truncation Errors in Numerical Simulations...

    Office of Scientific and Technical Information (OSTI)

    Title: Info-Gap Analysis of Truncation Errors in Numerical Simulations. Authors: Kamm, James R. ; Witkowski, Walter R. ; Rider, William J. ; Trucano, Timothy Guy ; Ben-Haim, Yakov. ...

  10. Info-Gap Analysis of Numerical Truncation Errors. (Conference...

    Office of Scientific and Technical Information (OSTI)

    Title: Info-Gap Analysis of Numerical Truncation Errors. Authors: Kamm, James R. ; Witkowski, Walter R. ; Rider, William J. ; Trucano, Timothy Guy ; Ben-Haim, Yakov. Publication ...

  11. Accounting for Model Error in the Calibration of Physical Models

    Office of Scientific and Technical Information (OSTI)

    ... model error term in locations where key modeling assumptions and approximations are made ... to represent the truth o In this context, the data has no noise o Discrepancy ...

  12. Handling Model Error in the Calibration of Physical Models

    Office of Scientific and Technical Information (OSTI)

    ... model error term in locations where key modeling assumptions and approximations are made ... to represent the truth o In this context, the data has no noise o Discrepancy ...

  13. U-058: Apache Struts Conversion Error OGNL Expression Injection...

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

    in Apache Struts. A remote user can execute arbitrary commands on the target system. PLATFORM: Apache Struts 2.x ABSTRACT: Apache Struts Conversion Error OGNL Expression...

  14. Appliance and Equipment Standards

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

    Standards April 22, 2014 John Cymbalsky Program Manager 1 | Energy Efficiency and Renewable Energy eere.energy.gov 2 Appliance & Equipment Standards Mission The Appliance and Equipment Standards Program's Mission to Fulfill its Statutory Obligation to: * Develop and amend energy conservation standards that achieve the maximum energy efficiency that is technologically feasible and economically justified. * Develop and amend test procedures that are repeatable, reproducible, representative,

  15. Standards | Department of Energy

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

    Standards Standards FOREWARD This U.S. Department of Energy (DOE) standard supersedes DOE-STD-3020-97 and is approved for use by DOE and its contractors. This standard was developed primarily for application in DOE programs. It provides guidance to DOE contractors for procurement and required testing of High Efficiency Particulate Air (HEPA) filters used in DOE nuclear facilities. Required testing is performed by the filter manufacturer and by DOE at a designated Filter Test Facility (FTF). This

  16. Balancing energy conservation and occupant needs in ventilation rate standards for Big Box stores and other commercial buildings in California. Issues related to the ASHRAE 62.1 Indoor Air Quality Procedure

    SciTech Connect (OSTI)

    Mendell, Mark J.; Apte, Mike G.

    2010-10-31

    This report considers the question of whether the California Energy Commission should incorporate the ASHRAE 62.1 ventilation standard into the Title 24 ventilation rate (VR) standards, thus allowing buildings to follow the Indoor Air Quality Procedure. This, in contrast to the current prescriptive standard, allows the option of using ventilation rate as one of several strategies, which might include source reduction and air cleaning, to meet specified targets of indoor air concentrations and occupant acceptability. The research findings reviewed in this report suggest that a revised approach to a ventilation standard for commercial buildings is necessary, because the current prescriptive ASHRAE 62.1 Ventilation Rate Procedure (VRP) apparently does not provide occupants with either sufficiently acceptable or sufficiently healthprotective air quality. One possible solution would be a dramatic increase in the minimum ventilation rates (VRs) prescribed by a VRP. This solution, however, is not feasible for at least three reasons: the current need to reduce energy use rather than increase it further, the problem of polluted outdoor air in many cities, and the apparent limited ability of increasing VRs to reduce all indoor airborne contaminants of concern (per Hodgson (2003)). Any feasible solution is thus likely to include methods of pollutant reduction other than increased outdoor air ventilation; e.g., source reduction or air cleaning. The alternative 62.1 Indoor Air Quality Procedure (IAQP) offers multiple possible benefits in this direction over the VRP, but seems too limited by insufficient specifications and inadequate available data to provide adequate protection for occupants. Ventilation system designers rarely choose to use it, finding it too arbitrary and requiring use of much non-engineering judgment and information that is not readily available. This report suggests strategies to revise the current ASHRAE IAQP to reduce its current limitations. These

  17. Stationary Fuel Cell Application Codes and Standards: Overview and Gap Analysis

    SciTech Connect (OSTI)

    Blake, C. W.; Rivkin, C. H.

    2010-09-01

    This report provides an overview of codes and standards related to stationary fuel cell applications and identifies gaps and resolutions associated with relative codes and standards.

  18. NETL Focused Standards List

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

    6/12 Contact: Janet Lambert Reviewed: 10/4/12 Page 1 of 17 This Focused Standards List has been primarily derived from selected standard references contained in NETL issued directives. All standards shall reference the most current edition/ version of that standard. DOE and other Government Standards and Requirements DOE DIRECTIVES Note: The following DOE directives can be found at http://www.directives.doe.gov: DOE Policy 141.1, DOE Management of Cultural Resources DOE Order 142.1, Classified

  19. IEEE standards worldwide

    SciTech Connect (OSTI)

    Hammons, T.J. )

    1995-01-01

    This article presents North American views on the development and use of internationally acceptable standards through strengthened ties with global standards organizations. The key ingredient to enhance the international reputation of IEEE standards is, without doubt, greater participation of members around the world. Standards that will really have force are those that are recognized as preeminent and that are sought after by organizations worldwide. it will be necessary to develop enhanced liaisons with standards organizations around the world, such as the IEC. These are some of the issues that will be addressed by panelists representing standards organizations and users from North America, United States, Canada, and Mexico. Also discussed is the importance of standards in the NAFTA and GATT agreements on trade.

  20. ISA Approves Standard for Wireless Automation in Process Control

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

    Applications | Department of Energy ISA Approves Standard for Wireless Automation in Process Control Applications ISA Approves Standard for Wireless Automation in Process Control Applications On September 9, the Standards and Practices Board of the International Society for Automation (ISA) approved the ISA-100.11a wireless standard, "Wireless Systems for Industrial Automation: Process Control and Related Applications," making it an official ISA standard. ISA Approves Standard for

  1. Current Approaches to Safety, Codes and Standards | Department of Energy

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

    Safety, Codes & Standards » Current Approaches to Safety, Codes and Standards Current Approaches to Safety, Codes and Standards Current approaches to hydrogen and fuel cells safety, codes and standards are based on existing practices, guidelines, and codes and standards developed as a result of hydrogen's use in the chemical and aerospace industries. While some codes and standards for hydrogen and hydrogen-related systems are already available, in many cases they do not fully address the

  2. Error localization in RHIC by fitting difference orbits

    SciTech Connect (OSTI)

    Liu C.; Minty, M.; Ptitsyn, V.

    2012-05-20

    The presence of realistic errors in an accelerator or in the model used to describe the accelerator are such that a measurement of the beam trajectory may deviate from prediction. Comparison of measurements to model can be used to detect such errors. To do so the initial conditions (phase space parameters at any point) must be determined which can be achieved by fitting the difference orbit compared to model prediction using only a few beam position measurements. Using these initial conditions, the fitted orbit can be propagated along the beam line based on the optics model. Measurement and model will agree up to the point of an error. The error source can be better localized by additionally fitting the difference orbit using downstream BPMs and back-propagating the solution. If one dominating error source exist in the machine, the fitted orbit will deviate from the difference orbit at the same point.

  3. Nuclear Data Verification and Standardization

    SciTech Connect (OSTI)

    Karam, Lisa R.; Arif, Muhammad; Thompson, Alan K.

    2011-10-01

    The objective of this interagency program is to provide accurate neutron interaction verification and standardization data for the U.S. Department of Energy Division of Nuclear Physics programs which include astrophysics, radioactive beam studies, and heavy-ion reactions. The measurements made in this program are also useful to other programs that indirectly use the unique properties of the neutron for diagnostic and analytical purposes. These include homeland security, personnel health and safety, nuclear waste disposal, treaty verification, national defense, and nuclear based energy production. The work includes the verification of reference standard cross sections and related neutron data employing the unique facilities and capabilities at NIST and other laboratories as required; leadership and participation in international intercomparisons and collaborations; and the preservation of standard reference deposits. An essential element of the program is critical evaluation of neutron interaction data standards including international coordinations. Data testing of critical data for important applications is included. The program is jointly supported by the Department of Energy and the National Institute of Standards and Technology.

  4. Error Detection, Factorization and Correction for Multi-View Scene Reconstruction from Aerial Imagery

    SciTech Connect (OSTI)

    Hess-Flores, M

    2011-11-10

    Scene reconstruction from video sequences has become a prominent computer vision research area in recent years, due to its large number of applications in fields such as security, robotics and virtual reality. Despite recent progress in this field, there are still a number of issues that manifest as incomplete, incorrect or computationally-expensive reconstructions. The engine behind achieving reconstruction is the matching of features between images, where common conditions such as occlusions, lighting changes and texture-less regions can all affect matching accuracy. Subsequent processes that rely on matching accuracy, such as camera parameter estimation, structure computation and non-linear parameter optimization, are also vulnerable to additional sources of error, such as degeneracies and mathematical instability. Detection and correction of errors, along with robustness in parameter solvers, are a must in order to achieve a very accurate final scene reconstruction. However, error detection is in general difficult due to the lack of ground-truth information about the given scene, such as the absolute position of scene points or GPS/IMU coordinates for the camera(s) viewing the scene. In this dissertation, methods are presented for the detection, factorization and correction of error sources present in all stages of a scene reconstruction pipeline from video, in the absence of ground-truth knowledge. Two main applications are discussed. The first set of algorithms derive total structural error measurements after an initial scene structure computation and factorize errors into those related to the underlying feature matching process and those related to camera parameter estimation. A brute-force local correction of inaccurate feature matches is presented, as well as an improved conditioning scheme for non-linear parameter optimization which applies weights on input parameters in proportion to estimated camera parameter errors. Another application is in

  5. Standard Contracts Team | Department of Energy

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

    Standard Contracts Team Standard Contracts Team The Standard Contracts Team has responsibility to: Act as Federal contracting officer for contracts with the nuclear power utilities; Evaluate materials related to the on-going Applications for Allowable and Reasonable Costs (claims) pursuant to settlement agreements; Support proposed settlement discussions and litigation preparation and court proceedings for the Deputy General Counsel for Environment and Nuclear Programs and Department of Justice;

  6. Standards Development Support | Department of Energy

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

    Research & Development » Technology Application R&D » CALiPER Testing » Standards Development Support Standards Development Support photo of a meeting, with people seated around a table. CALiPER test results and analyses are used to support the development of standards and test procedures for SSL - especially those related to complex areas such as flicker, dimming, power quality, and long-term performance. In addition, DOE hosts annual CALiPER roundtables - attended by representatives

  7. STANDARD REVIEW PLAN

    Office of Environmental Management (EM)

    of Nuclear Facilities Standard Review Plan Safety Design Strategy January 2015 OFFICE OF ENVIRONMENTAL MANAGEMENT ... safety, environment, security, and quality assurance, ...

  8. Renewable Energy Portfolio Standard

    Office of Energy Efficiency and Renewable Energy (EERE)

    Maryland's Renewable Energy Portfolio Standard, enacted in May 2004 and revised numerous times since, requires electricity suppliers (all utilities and competitive retail suppliers) to use renewa...

  9. SSL Standards and Guidelines

    SciTech Connect (OSTI)

    none,

    2012-04-01

    Solid-state lighting program technology fact sheet that reviews the key performance and safety standards applicable to SSL-based lighting products.

  10. Standard Subject Classification System

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1979-08-14

    The order establishes the DOE Standard Subject Classification System for classifying documents and records by subject, including correspondence, directives, and forms.Cancels DOE O 0000.1.