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Note: This page contains sample records for the topic "rse column factors" from the National Library of EnergyBeta (NLEBeta).
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1

2003 CBECS RSE Tables  

Gasoline and Diesel Fuel Update (EIA)

cbecs/cbecs2003/detailed_tables_2003/2003rsetables_files/plainlink.css" cbecs/cbecs2003/detailed_tables_2003/2003rsetables_files/plainlink.css" type=text/css rel=stylesheet> Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > 2003 Detailed Tables > RSE Tables 2003 CBECS Relative Standard Error (RSE) Tables Released: Dec 2006 Next CBECS will be conducted in 2007 Standard error is a measure of the reliability or precision of the survey statistic. The value for the standard error can be used to construct confidence intervals and to perform hypothesis tests by standard statistical methods. Relative Standard Error (RSE) is defined as the standard error (square root of the variance) of a survey estimate, divided by the survey estimate and multiplied by 100. (More information on RSEs)

2

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

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

Heating, Ventilation, and Air Conditioning '(Facility HVAC)' excludes" "steam and hot water." " NFNo applicable RSE rowcolumn factor." " * Estimate less than 0.5." "...

3

" Row: NAICS Codes; Column: Energy Sources;"  

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

2. Fuel Consumption, 1998;" 2. Fuel Consumption, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,,"RSE" "NAICS"," "," ","Net","Residual","Distillate",,"LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)","Factors"

4

" Row: Selected SIC Codes; Column: Energy Sources;"  

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

2. Fuel Consumption, 1998;" 2. Fuel Consumption, 1998;" " Level: National Data; " " Row: Selected SIC Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,,"RSE" "SIC"," "," ","Net","Residual","Distillate",,"LPG and",,"Coke"," ","Row" "Code(a)","Major Group and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)","Factors"

5

" Row: NAICS Codes; Column: Energy Sources;"  

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

2 Fuel Consumption, 2002;" 2 Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,,"RSE" "NAICS"," "," ","Net","Residual","Distillate","Natural","LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Gas(d)","NGL(e)","Coal","and Breeze","Other(f)","Factors"

6

" Row: NAICS Codes; Column: Electricity Components;"  

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

1 Electricity: Components of Net Demand, 2002;" 1 Electricity: Components of Net Demand, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," ",,,,,," " " "," ",,,"Total ","Sales and","Net Demand","RSE" "NAICS"," ",,"Transfers ","Onsite","Transfers","for","Row" "Code(a)","Subsector and Industry","Purchases"," In(b)","Generation(c)","Offsite","Electricity(d)","Factors" ,,"Total United States"

7

" Row: NAICS Codes; Column: Electricity Components;"  

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

1. Electricity: Components of Net Demand, 1998;" 1. Electricity: Components of Net Demand, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," ",,,,,," " " "," ",,,,"Sales and","Net Demand","RSE" "NAICS"," ",,,"Total Onsite","Transfers","for","Row" "Code(a)","Subsector and Industry","Purchases","Transfers In(b)","Generation(c)","Offsite","Electricity(d)","Factors" ,,"Total United States"

8

2003 Commercial Buildings Energy Consumption - What is an RSE  

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

Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > 2003 Detailed Tables > What is an RSE? What is an RSE? The estimates in the...

9

" Row: NAICS Codes; Column: Energy Sources;"  

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

2 Offsite-Produced Fuel Consumption, 2002;" 2 Offsite-Produced Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,,"RSE" "NAICS"," "," ",,"Residual","Distillate","Natural","LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Gas(d)","NGL(e)","Coal","and Breeze","Other(f)","Factors"

10

" Row: NAICS Codes; Column: Energy Sources;"  

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

4 Number of Establishments by Offsite-Produced Fuel Consumption, 2002;" 4 Number of Establishments by Offsite-Produced Fuel Consumption, 2002;" " Level: National Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Establishment Counts." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ","Any",,,,,,,,,"RSE" "NAICS"," ","Energy",,"Residual","Distillate","Natural","LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Gas(e)","NGL(f)","Coal","and Breeze","Other(g)","Factors"

11

" Column: Energy-Consumption Ratios;"  

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

3 Consumption Ratios of Fuel, 2002;" 3 Consumption Ratios of Fuel, 2002;" " Level: National Data; " " Row: Values of Shipments within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." " "," ",,,"Consumption"," " " "," ",,"Consumption","per Dollar" " "," ","Consumption","per Dollar","of Value","RSE" "NAICS",,"per Employee","of Value Added","of Shipments","Row" "Code(a)","Economic Characteristic(b)","(million Btu)","(thousand Btu)","(thousand Btu)","Factors"

12

" Row: NAICS Codes; Column: Energy Sources;"  

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

4 Number of Establishments by Fuel Consumption, 2002;" 4 Number of Establishments by Fuel Consumption, 2002;" " Level: National Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Establishment Counts." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ","Any",,,,,,,,,"RSE" "NAICS"," ","Energy","Net","Residual","Distillate","Natural","LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Gas(e)","NGL(f)","Coal","and Breeze","Other(g)","Factors"

13

" Row: Selected SIC Codes; Column: Energy Sources;"  

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

2. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" 2. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" " Level: National Data; " " Row: Selected SIC Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,"RSE" "SIC"," "," ","Residual","Distillate",,"LPG and",,"Coke"," ","Row" "Code(a)","Major Group and Industry","Total","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)","Factors"

14

" Row: NAICS Codes; Column: Energy-Consumption Ratios;"  

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

N7.1. Consumption Ratios of Fuel, 1998;" N7.1. Consumption Ratios of Fuel, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy-Consumption Ratios;" " Unit: Varies." " "," ",,,"Consumption"," " " "," ",,"Consumption","per Dollar"," " " "," ","Consumption","per Dollar","of Value","RSE" "NAICS"," ","per Employee","of Value Added","of Shipments","Row" "Code(a)","Subsector and Industry","(million Btu)","(thousand Btu)","(thousand Btu)","Factors"

15

" Row: NAICS Codes; Column: Energy-Consumption Ratios;"  

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

1 Consumption Ratios of Fuel, 2002;" 1 Consumption Ratios of Fuel, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy-Consumption Ratios;" " Unit: Varies." " "," ",,,"Consumption"," " " "," ",,"Consumption","per Dollar"," " " "," ","Consumption","per Dollar","of Value","RSE" "NAICS"," ","per Employee","of Value Added","of Shipments","Row" "Code(a)","Subsector and Industry","(million Btu)","(thousand Btu)","(thousand Btu)","Factors"

16

" Row: NAICS Codes (3-Digit Only); Column: Energy Sources;"  

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

2. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" 2. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" " Level: National Data; " " Row: NAICS Codes (3-Digit Only); Column: Energy Sources;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,"RSE" "NAICS"," "," ","Residual","Distillate",,"LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)","Factors"

17

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

2. End Uses of Fuel Consumption, 1998;" 2. End Uses of Fuel Consumption, 1998;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," "," " " ",,,,"Fuel Oil",,,"Coal",,"RSE" " "," ","Net","Residual","and",,"LPG and","(excluding Coal"," ","Row" "End Use","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Natural Gas(c)","NGL(d)","Coke and Breeze)","Other(e)","Factors"

18

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

6 End Uses of Fuel Consumption, 2002;" 6 End Uses of Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," "," " " ",,,,"Fuel Oil",,,"Coal",,"RSE" " "," ","Net","Residual","and","Natural ","LPG and","(excluding Coal"," ","Row" "End Use","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Gas(c)","NGL(d)","Coke and Breeze)","Other(e)","Factors"

19

RSE Pulp & Chemical, LLC (Subsidiary of Red Shield Environmental...  

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

facility in an existing pulp mill to demonstrate the production of cellulosic ethanol from lignocellulosic (wood) extract. RSE Pulp & Chemical, LLC (Subsidiary of Red...

20

Table 10.1 Nonswitchable Minimum and Maximum Consumption,...  

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

50 percent." " NANot available." " Notes: To obtain the RSE percentage for any table cell, multiply the cell's" "corresponding RSE column and RSE row factors. Totals may not...

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


21

Re: NBP RFI: CommunicationRse quirements | Department of Energy  

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

RFI: CommunicationRse quirements Pepco Holdings, Inc. (PHI) is pleased to respond to the U.S Department of Energy request for comments regarding the communications requirements of...

22

" Row: NAICS Codes; Column: Energy Sources...  

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

","Row" "Code(a)","Subsector and Industry","Source(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)","Factors" ,,"Total United States" ,"RSE...

23

2003 Commercial Buildings Energy Consumption - What is an RSE  

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

Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > 2003 Detailed Tables > What is an RSE? What is an RSE? The estimates in the Commercial Buildings Energy Consumption Survey (CBECS) are based on data reported by representatives of a statistically-designed subset of the entire commercial building population in the United States, or a "sample". Consequently, the estimates differ from the true population values. However, the sample design permits us to estimate the sampling error in each value. It is important to understand: CBECS estimates should not be considered as finite point estimates, but as estimates with some associated error in each direction. The standard error is a measure of the reliability or precision of the survey statistic. The value for the standard error can be used to construct confidence intervals and to perform hypothesis tests by standard statistical methods. Relative Standard Error (RSE) is defined as the standard error (square root of the variance) of a survey estimate, divided by the survey estimate and multiplied by 100.

24

" Row: Selected SIC Codes; Column: Energy Sources;"  

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

1. Fuel Consumption, 1998;" 1. Fuel Consumption, 1998;" " Level: National Data; " " Row: Selected SIC Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,"Coke" " "," "," ","Net","Residual","Distillate","Natural Gas(d)","LPG and","Coal","and Breeze"," ","RSE" "SIC"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","NGL(e)","(million","(million","Other(f)","Row"

25

" Row: Selected SIC Codes; Column: Energy Sources;"  

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

S5.1. Selected Byproducts in Fuel Consumption, 1998;" S5.1. Selected Byproducts in Fuel Consumption, 1998;" " Level: National Data; " " Row: Selected SIC Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," ","Waste"," ",," " " "," "," ","Blast"," "," ","Pulping Liquor"," ","Oils/Tars","RSE" "SIC"," "," ","Furnace/Coke"," ","Petroleum","or","Wood Chips,","and Waste","Row"

26

" Row: NAICS Codes; Column: Energy Sources;"  

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

1 Offsite-Produced Fuel Consumption, 2002;" 1 Offsite-Produced Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,"Coke" " "," "," ",,"Residual","Distillate","Natural","LPG and","Coal","and Breeze"," ","RSE" "NAICS"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Gas(d)","NGL(e)","(million","(million","Other(f)","Row"

27

" Row: NAICS Codes; Column: Energy Sources;"  

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

1 Fuel Consumption, 2002;" 1 Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,"Coke" " "," "," ","Net","Residual","Distillate","Natural","LPG and","Coal","and Breeze"," ","RSE" "NAICS"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Gas(d)","NGL(e)","(million","(million","Other(f)","Row"

28

" Row: NAICS Codes; Column: Energy Sources;"  

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

1. Fuel Consumption, 1998;" 1. Fuel Consumption, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,"Coke" " "," "," ","Net","Residual","Distillate","Natural Gas(d)","LPG and","Coal","and Breeze"," ","RSE" "NAICS"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","NGL(e)","(million","(million","Other(f)","Row"

29

S:\\VM3\\RX97\\TBL_LIST.WPD [PFP#201331587  

Annual Energy Outlook 2012 (EIA)

b. Air Conditioning by Four Most Populated States, Percent of U.S. Households, 1997 Air Conditioning Characteristics RSE Column Factor: Total Four Most Populated States RSE Row...

30

Table HC3-1a. Space Heating by Climate Zone, Million U.S ...  

U.S. Energy Information Administration (EIA)

Table HC3-1a. Space Heating by Climate Zone, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Climate Zone1 RSE

31

char_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

9a. Household Characteristics by Northeast Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row...

32

table11.6_02.xls  

Annual Energy Outlook 2012 (EIA)

than 50 percent. NANot available. Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding RSE column and RSE row factors. Totals may not equal...

33

table7.1_02.xls  

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

is not applicable. Notes: To obtain the RSE percentage for any table cell, multiply the cell corresponding RSE column and RSE row factors. Totals may not equal su components...

34

" Row: Selected SIC Codes; Column: Energy Sources and Shipments;"  

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

2. First Use of Energy for All Purposes (Fuel and Nonfuel), 1998;" 2. First Use of Energy for All Purposes (Fuel and Nonfuel), 1998;" " Level: National Data; " " Row: Selected SIC Codes; Column: Energy Sources and Shipments;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," "," "," "," ",," " " "," "," ",," "," ",," "," ",," ","Shipments","RSE" "SIC"," ",,"Net","Residual","Distillate",,"LPG and",,"Coke and"," ","of Energy Sources","Row"

35

" Row: Selected SIC Codes; Column: Energy Sources and Shipments;"  

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

1. First Use of Energy for All Purposes (Fuel and Nonfuel), 1998;" 1. First Use of Energy for All Purposes (Fuel and Nonfuel), 1998;" " Level: National Data; " " Row: Selected SIC Codes; Column: Energy Sources and Shipments;" " Unit: Physical Units or Btu." " "," "," "," "," "," "," "," "," "," "," ",," " " "," "," ",," "," ",," "," ","Coke and"," ","Shipments"," " " "," ",,"Net","Residual","Distillate","Natural Gas(e)","LPG and","Coal","Breeze"," ","of Energy Sources","RSE"

36

" Row: Selected SIC Codes; Column: Energy Sources;"  

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

1. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" 1. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" " Level: National Data; " " Row: Selected SIC Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," "," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,"Coke" " "," "," ","Residual","Distillate","Natural Gas(c)","LPG and","Coal","and Breeze"," ","RSE" "SIC"," ","Total","Fuel Oil","Fuel Oil(b)","(billion","NGL(d)","(million","(million","Other(e)","Row"

37

" Row: NAICS Codes; Column: Energy Sources;"  

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

6 Quantity of Purchased Energy Sources, 2002;" 6 Quantity of Purchased Energy Sources, 2002;" " Level: National and Regional Data;" " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,"Coke" " "," "," ",,"Residual","Distillate","Natural","LPG and","Coal","and Breeze"," ","RSE" "NAICS"," ","Total","Electricity","Fuel Oil","Fuel Oil(b)"," Gas(c)","NGL(d)","(million","(million ","Other(e)","Row"

38

" Row: Selected SIC Codes; Column: Energy Sources;"  

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

S4.1. Offsite-Produced Fuel Consumption, 1998;" S4.1. Offsite-Produced Fuel Consumption, 1998;" " Level: National Data; " " Row: Selected SIC Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,"Coke" " "," "," ",,"Residual","Distillate","Natural Gas(d)","LPG and","Coal","and Breeze"," ","RSE" "SIC"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","NGL(e)","(million","(million","Other(f)","Row"

39

T15a_asc - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Q = Data withheld either because the Relative Standard Error (RSE) ... multiply the corresponding column and row factors. · Because of rounding, ...

40

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

Table CE4-1e. Water-Heating Energy Expenditures in U.S. Households by Climate Zone, 1997 RSE Column Factor: Total Climate Zone1 RSE Row Factors Fewer than 2,000 CDD ...

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


41

ac_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total...

42

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

Table CE5-1e. Appliances1 Energy Expenditures in U.S. Households by Climate Zone, 1997 RSE Column Factor: Total Climate Zone2 RSE Row Factors Fewer than 2,000 CDD and --

43

Table CE1-1c. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE1-1c. Total Energy Consumption in U.S. Households by Climate Zone, 2001 RSE Column Factor: Total Climate Zone1 RSE Row Factors Fewer than 2,000 CDD and --

44

S:\\VM3\\RX97\\TBL_LIST.WPD [PFP#201331587  

Gasoline and Diesel Fuel Update (EIA)

1997 Home Office Equipment RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.1 1.5 1.3 Total ......

45

" Row: NAICS Codes (3-Digit Only); Column: Energy Sources;"  

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

1. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" 1. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" " Level: National Data; " " Row: NAICS Codes (3-Digit Only); Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," "," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,"Coke" " "," "," ","Residual","Distillate","Natural Gas(c)","LPG and","Coal","and Breeze"," ","RSE" "NAICS"," ","Total","Fuel Oil","Fuel Oil(b)","(billion","NGL(d)","(million","(million","Other(e)","Row"

46

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

1. End Uses of Fuel Consumption, 1998;" 1. End Uses of Fuel Consumption, 1998;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ","Coal"," "," " " ",,,,"Fuel Oil",,,"(excluding Coal" " "," ","Net","Residual","and","Natural Gas(c)","LPG and","Coke and Breeze)"," ","RSE" " ","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","(billion","NGL(d)","(million","Other(e)","Row"

47

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

5 End Uses of Fuel Consumption, 2002;" 5 End Uses of Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ",," "," " " ",,,,"Fuel Oil",,,"Coal" " "," ","Net","Residual","and","Natural ","LPG and","(excluding Coal"," ","RSE" " ","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Gas(c)","NGL(d)","Coke and Breeze)","Other(e)","Row"

48

" Row: NAICS Codes (3-Digit Only); Column: Energy Sources;"  

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

N4.1. Offsite-Produced Fuel Consumption, 1998;" N4.1. Offsite-Produced Fuel Consumption, 1998;" " Level: National Data; " " Row: NAICS Codes (3-Digit Only); Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,"Coke" " "," "," ",,"Residual","Distillate","Natural Gas(d)","LPG and","Coal","and Breeze"," ","RSE" "NAICS"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","NGL(e)","(million","(million","Other(f)","Row"

49

" Row: NAICS Codes; Column: Energy Sources and Shipments;"  

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

.1. Number of Establishments by First Use of Energy for All Purposes (Fuel and Nonfuel), 1998;" .1. Number of Establishments by First Use of Energy for All Purposes (Fuel and Nonfuel), 1998;" " Level: National Data; " " Row: NAICS Codes; Column: Energy Sources and Shipments;" " Unit: Establishment Counts." " "," "," "," "," "," "," "," "," "," "," ",," " " "," ","Any",," "," ",," "," ",," ","Shipments","RSE" "NAICS"," ","Energy","Net","Residual","Distillate",,"LPG and",,"Coke and"," ","of Energy Sources","Row"

50

Table CE1-10c. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE1-10c. Total Energy Consumption in U.S. Households by Midwest Census Region, 2001 RSE Column Factor: Total U.S. Midwest Census Region RSE Row

51

Table CE3-1c. Electric Air-Conditioning Energy Consumption in U.S ...  

U.S. Energy Information Administration (EIA)

Table CE3-1c. Electric Air-Conditioning Energy Consumption in U.S. Households by Climate Zone, 2001 RSE Column Factor: Total Climate Zone1 RSE Row

52

Table CE5-2c. Appliances Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE5-2c. Appliances1 Energy Consumption in U.S. Households by Year of Construction, 2001 RSE Column Factor: Total Year of Construction RSE Row

53

Table 4. LPG Consumption and Expeditures in U.S. Households by End ...  

U.S. Energy Information Administration (EIA)

Table 4. LPG Consumption and Expeditures in U.S. Households by End Uses and Census Region, 2001 RSE Column Factor: Total U.S. Census Region RSE Row

54

Buildings and Energy in the 1980's  

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

and Industry Total Net Electricity b Residual Fuel Oil Distillate Fuel Oil c Natural Gas d LPG Coal Coke and Breeze Other e RSE Row Factors Total United States RSE Column...

55

Buildings and Energy in the 1980's  

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

Code a Industry Groups and Industry Total Residual Fuel Oil Distillate Fuel Oil b Natural Gas c LPG Coal Coke and Breeze Other d RSE Row Factors Total United States RSE Column...

56

Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments;  

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

Coke and Shipments Net Residual Distillate Natural LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) (trillion Btu) Total United States RSE Column Factors: 0.9 1 1.2 1.8 1 1.6 0.8 0.9 1.2 0.4 311 Food 1,123 67,521 2 3 567 1 8 * 89 0 311221 Wet Corn Milling 217 6,851 * * 59 * 5 0 11 0 31131 Sugar 112 725 * * 22 * 2 * 46 0 311421 Fruit and Vegetable Canning 47 1,960 * * 35 * 0 0 1 0 312 Beverage and Tobacco Products 105 7,639 * * 45 * 1 0 11 0 3121 Beverages 85 6,426 * * 41 * * 0 10 0 3122 Tobacco 20 1,213 * * 4 * * 0 1 0 313 Textile Mills 207 25,271 1 * 73 * 1 0 15 0 314

57

" Row: NAICS Codes;" " Column: Usage within General Energy-Saving Technologies;"  

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

2 Number of Establishments by Usage of General Energy-Saving Technologies, 2002;" 2 Number of Establishments by Usage of General Energy-Saving Technologies, 2002;" " Level: National Data; " " Row: NAICS Codes;" " Column: Usage within General Energy-Saving Technologies;" " Unit: Establishment Counts." " "," ",,"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",,," ",," " " "," ",,,,,,,,,,,,,,,,,"RSE" "NAICS"," ",,,,,,,,,,,,,,,,,"Row"

58

" Row: NAICS Codes;" " Column: Usage within General Energy-Saving Technologies;"  

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

1. Number of Establishments by Usage of General Energy-Saving Technologies, 1998;" 1. Number of Establishments by Usage of General Energy-Saving Technologies, 1998;" " Level: National Data; " " Row: NAICS Codes;" " Column: Usage within General Energy-Saving Technologies;" " Unit: Establishment Counts." " "," "," ",,,"Computer","Control of","Processes"," "," "," ",,,," ",," " " "," ","Computer Control","of Building-Wide","Environment(b)","or Major","Energy-Using","Equipment(c)","Waste","Heat","Recovery","Adjustable -","Speed","Motors","RSE"

59

Table HC1-8a. Housing Unit Characteristics by Urban/Rural Location ...  

U.S. Energy Information Administration (EIA)

Table HC1-8a. Housing Unit Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor:

60

Table 4. LPG Consumption and Expenditures in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may not sum to totals.

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


61

Table 3. Electricity Consumption and Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may ...

62

Table 2. Fuel Oil Consumption and Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may ...

63

Table 1. Natural Gas Consumption and Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may not sum to totals.

64

Table 1. Natural Gas Consumption and Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may ...

65

Table 5. Kerosene Consumption and Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may not sum to totals.

66

Table CE4-6.1u. Water-Heating Energy Consumption and Expenditures ...  

U.S. Energy Information Administration (EIA)

Table CE4-6.1u. Water-Heating Energy Consumption and Expenditures by Household Member and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

67

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Total Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total ... where the end use is electric air-conditioning, ...

68

Table CE3-3e. Electric Air-Conditioning Energy Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Electric Air-Conditioning Energy Expenditures in U.S. Households by Household Income, 2001 RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli-

69

Table HC4-12a. Air Conditioning by West Census Region, Million U.S ...  

U.S. Energy Information Administration (EIA)

Table HC4-12a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S.

70

Table CE3-6.1u. Electric Air-Conditioning Energy Consumption and ...  

U.S. Energy Information Administration (EIA)

Table CE3-6.1u. Electric Air-Conditioning Energy Consumption and Expenditures by Household Member and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

71

Table HC4-9a. Air Conditioning by Northeast Census Region, Million ...  

U.S. Energy Information Administration (EIA)

Table HC4-9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total

72

Table CE3-6.2u. Electric Air-Conditioning Energy Consumption and ...  

U.S. Energy Information Administration (EIA)

Table CE3-6.2u. Electric Air-Conditioning Energy Consumption and Expenditures by Square Feet and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

73

Table HC1-1a. Housing Unit Characteristics by Climate Zone ...  

U.S. Energy Information Administration (EIA)

Table HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Climate Zone1

74

R93HC.PDF  

Annual Energy Outlook 2012 (EIA)

3. Total Air-Conditioning in U.S. Households, 1993 Housing Unit and Household Characteristics RSE Column Factor: Total Households (millions) Cooled Floorspace (square feet per...

75

PRELIMINARY DATA Housing Unit and Household Characteristics  

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

PRELIMINARY DATA Housing Unit and Household Characteristics RSE Column Factor: Total Households (million) Households With Fans (million) Percent of Households With Fans Number of...

76

Table CE5-5.1u. Appliances Energy Consumption and Expenditures by ...  

U.S. Energy Information Administration (EIA)

Table CE5-5.1u. Appliances1 Energy Consumption and Expenditures by Household Member and Demographics, 2001 Household Demographics RSE Column Factor:

77

Table CE5-6.1u. Appliances Energy Consumption and Expenditures by ...  

U.S. Energy Information Administration (EIA)

Table CE5-6.1u. Appliances1 Energy Consumption and Expenditures by Household Member and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

78

Table HC5-7a. Appliances by Four Most Populated States, Million U ...  

U.S. Energy Information Administration (EIA)

Table HC5-7a. Appliances by Four Most Populated States, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total

79

RSE Table 8.2 Relative Standard Errors for Table 8.2  

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

The 'Establishments' column includes those units which reported any of the five listed" "energy-saving technologies in use anytime in 2002, plus those units where usage of those"...

80

Distillation Column Flooding Predictor  

SciTech Connect

The Flooding Predictor™ is a patented advanced control technology proven in research at the Separations Research Program, University of Texas at Austin, to increase distillation column throughput by over 6%, while also increasing energy efficiency by 10%. The research was conducted under a U. S. Department of Energy Cooperative Agreement awarded to George Dzyacky of 2ndpoint, LLC. The Flooding Predictor™ works by detecting the incipient flood point and controlling the column closer to its actual hydraulic limit than historical practices have allowed. Further, the technology uses existing column instrumentation, meaning no additional refining infrastructure is required. Refiners often push distillation columns to maximize throughput, improve separation, or simply to achieve day-to-day optimization. Attempting to achieve such operating objectives is a tricky undertaking that can result in flooding. Operators and advanced control strategies alike rely on the conventional use of delta-pressure instrumentation to approximate the column’s approach to flood. But column delta-pressure is more an inference of the column’s approach to flood than it is an actual measurement of it. As a consequence, delta pressure limits are established conservatively in order to operate in a regime where the column is never expected to flood. As a result, there is much “left on the table” when operating in such a regime, i.e. the capacity difference between controlling the column to an upper delta-pressure limit and controlling it to the actual hydraulic limit. The Flooding Predictor™, an innovative pattern recognition technology, controls columns at their actual hydraulic limit, which research shows leads to a throughput increase of over 6%. Controlling closer to the hydraulic limit also permits operation in a sweet spot of increased energy-efficiency. In this region of increased column loading, the Flooding Predictor is able to exploit the benefits of higher liquid/vapor traffic that produce increased contact area and lead to substantial increases in separation efficiency – which translates to a 10% increase in energy efficiency on a BTU/bbl basis. The Flooding Predictor™ operates on the principle that between five to sixty minutes in advance of a flooding event, certain column variables experience an oscillation, a pre-flood pattern. The pattern recognition system of the Flooding Predictor™ utilizes the mathematical first derivative of certain column variables to identify the column’s pre-flood pattern(s). This pattern is a very brief, highly repeatable, simultaneous movement among the derivative values of certain column variables. While all column variables experience negligible random noise generated from the natural frequency of the process, subtle pre-flood patterns are revealed among sub-sets of the derivative values of column variables as the column approaches its hydraulic limit. The sub-set of column variables that comprise the pre-flood pattern is identified empirically through in a two-step process. First, 2ndpoint’s proprietary off-line analysis tool is used to mine historical data for pre-flood patterns. Second, the column is flood-tested to fine-tune the pattern recognition for commissioning. Then the Flooding Predictor™ is implemented as closed-loop advanced control strategy on the plant’s distributed control system (DCS), thus automating control of the column at its hydraulic limit.

George E. Dzyacky

2010-11-23T23:59:59.000Z

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


81

Simplified distillation column controls  

SciTech Connect

A simple, energy efficient method of controlling single or double distillation columns for the production of ethyl alcohol is described. The control system is based on a material balance scheme centered around a thermostat actuated control valve to regulate reflux rate and product purity. Column bottom's levels are automatically regulated by vented suction lines on the pump inlets. Methods of minimizing control input variations are used including column insulation, stillage-to-beer heat exchanger, and a steam pressure regulator.

Badger, P.; Pile, R.; Lightsey, G.

1984-01-01T23:59:59.000Z

82

Bridge Column Inspection 1  

Science Conference Proceedings (OSTI)

... Concept of an Underwater Bridge Column Inspector RoboCrane. The platform is ballast controlled with a rotary joint and attached sonar sensor. ...

2011-08-25T23:59:59.000Z

83

PULSE COLUMN DESIGN  

SciTech Connect

A stagewise approach was used in a theoretical analysis of pulse columns. In the analysis the column was arbitrarily divided into discrete stages comprising that part of the column between two adjacent perforated plates. The operation of the pulse column was described mathematically using material balance equations, and a design method was derived which used two stage lines and two operating lines, one set for the pulse generator upstroke and one set for the downstroke. Assuming equilibrium contact, the effect of recycle in a pulse column was shown to cause a large decrease in the separation obtained as the pulse frequency was increased. Hold-up studies were made using isoamyl alcohol- water, and methyl isobutyl ketone water. The hold-up per cycle of the dispersed phase for both systems was found to be equal to the interstage flow per cycle of the dispersed phase. Hold-up behavior at high frequencies was different for the two systems. Extraction runs were also made using the system methyl isobutyl ketone - acetic acid-water. The effects of recycle were found to result in a drop in column separation efficiency with increased pulse frequency. It was found to be theoretically possible for a column to operate in a pinched-in region even though this is not apparert from an examination of the superficial flow ratio of the two streams being fed to the column Techniques for sampling interstage flow streams in a colurm operating in the mixer-settler region are described. (J.R.D.)

Burkhart, L.E.; Fahien, R.W.

1958-11-01T23:59:59.000Z

84

Nuclear reactor control column  

DOE Patents (OSTI)

The nuclear reactor control column comprises a column disposed within the nuclear reactor core having a variable cross-section hollow channel and containing balls whose vertical location is determined by the flow of the reactor coolant through the column. The control column is divided into three basic sections wherein each of the sections has a different cross-sectional area. The uppermost section of the control column has the greatest cross-sectional area, the intermediate section of the control column has the smallest cross-sectional area, and the lowermost section of the control column has the intermediate cross-sectional area. In this manner, the area of the uppermost section can be established such that when the reactor coolant is flowing under normal conditions therethrough, the absorber balls will be lifted and suspended in a fluidized bed manner in the upper section. However, when the reactor coolant flow falls below a predetermined value, the absorber balls will fall through the intermediate section and into the lowermost section, thereby reducing the reactivity of the reactor core and shutting down the reactor.

Bachovchin, Dennis M. (Plum Borough, PA)

1982-01-01T23:59:59.000Z

85

"Table A17. Components of Onsite Electricity Generation by Census Region,"  

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

7. Components of Onsite Electricity Generation by Census Region," 7. Components of Onsite Electricity Generation by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," "," ","RSE" "SIC"," "," "," "," "," ","Row" "Code(a)","Industry Groups and Industry","Total","Cogeneration","Renewables","Other(b)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.8,0.8,1.4,1.2

86

Table HC1-4a. Housing Unit Characteristics by Type of Housing Unit,  

U.S. Energy Information Administration (EIA)

... | | | | Row RSE Column Factor: | 0.5 | 0.5 | 1.5 | 1.3 | 1.9 |Factors ... Q = Data withheld either because the Relative Standard Error ...

87

Table E13.2. Electricity: Components of Onsite Generation, 1998  

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

Onsite",,"and",,"Row" "Characteristic(a)","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:",0.9,0.9,1.5,0....

88

2003 CBECS RSE Tables  

Gasoline and Diesel Fuel Update (EIA)

detailedtables20032003rsetablesfilesplainlink.css" typetextcss relstylesheet> Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey...

89

Single-Column Modeling  

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

C.J. Somerville and S. F. lacobellis C.J. Somerville and S. F. lacobellis Climate Research Division Scripps Institution of Oceanography University of California, San Diego La Jolla, CA 92093-0224 Our project is centered around a computationally efficient and economical one-dimensional (vertical) model, resembling a single column of a general circulation model (GCM) grid, applied to the experimental site of the Atmospheric Radiation Measurement (ARM) Program. The model contains a full set of modern GCM parameterizations of subgrid physical processes. To force the model, the advective terms in the budget equations are specified observationally from operational numerical weather prediction analyses. These analyses, based on four-dimensional data assimilation techniques, provide dynamically consistent wind fields and horizontal gradients

90

Table 4  

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

125 69 112 131 137 158 7.36 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

91

Table 4  

Gasoline and Diesel Fuel Update (EIA)

378 913 993 1,130 1,316 1,625 8.24 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

92

S:\\VM3\\RX97\\TBL_LIST.WPD  

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

rather than White, Black, or other. Notes: * To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. * Because of rounding, data may not...

93

Table CE4-7c. Water-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE4-7c. Water-Heating Energy Consumption in U.S. Households by Four Most Populated States, 1997 RSE Column Factor: Total U.S. Four Most Populated States

94

Table CE3-10e. Electric Air-Conditioning Energy Expenditures in U ...  

U.S. Energy Information Administration (EIA)

Table CE3-10e. Electric Air-Conditioning Energy Expenditures in U.S. Households by Midwest Census Region, 2001 RSE Column Factor: Total U.S. Midwest Census Region

95

Table CE1-6.2u. Total Energy Consumption and Expenditures by ...  

U.S. Energy Information Administration (EIA)

Table CE1-6.2u. Total Energy Consumption and Expenditures by Square Feet and Usage Indicators, 2001 Usage Indicators RSE Column Factor: Total End-Use Energy

96

Table CE3-4c. Electric Air-Conditioning Energy Consumption in U.S ...  

U.S. Energy Information Administration (EIA)

Table CE3-4c. Electric Air-Conditioning Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total Type of Housing Unit

97

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households by Household Income, 2001 RSE Column Factor: Total 2001 Household Income Below Poverty

98

Table CE2-7e. Space-Heating Energy Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE2-7e. Space-Heating Energy Expenditures in U.S. Households by Four Most Populated States, 2001 RSE Column Factor: Total U.S. Four Most Populated States

99

Table 11.3 Electricity: Components of Onsite Generation, 2002  

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

3 Electricity: Components of Onsite Generation, 2002;" 3 Electricity: Components of Onsite Generation, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Onsite-Generation Components;" " Unit: Million Kilowatthours." " "," ",,,"Renewable Energy",," " " "," ",,,"(excluding Wood",,"RSE" "NAICS"," ","Total Onsite",,"and",,"Row" "Code(a)","Subsector and Industry","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.9,0.8,1.1,1.3

100

Table N13.2. Electricity: Components of Onsite Generation, 1998  

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

2. Electricity: Components of Onsite Generation, 1998;" 2. Electricity: Components of Onsite Generation, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Onsite-Generation Components;" " Unit: Million Kilowatthours." " "," ",,,"Renewable Energy",," " " "," ",,,"(excluding Wood",,"RSE" "NAICS"," ","Total Onsite",,"and",,"Row" "Code(a)","Subsector and Industry","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)","Factors" ,,"Total United States" ,"RSE Column Factors:",1,0.8,1.5,0.9

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


101

Table E13.3. Electricity: Sales to Utility and Nonutility Purchasers, 1998  

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

3. Electricity: Sales to Utility and Nonutility Purchasers, 1998;" 3. Electricity: Sales to Utility and Nonutility Purchasers, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Utility and Nonutility Purchasers;" " Unit: Million Kilowatthours." ,"Total of",,,"RSE" "Economic","Sales and","Utility","Nonutility","Row" "Characteristic(a)","Transfers Offsite","Purchaser(b)","Purchaser(c)","Factors" ,"Total United States" "RSE Column Factors:",0.9,1,1.1 "Value of Shipments and Receipts"

102

Table 11.6 Electricity: Sales to Utility and Nonutility Purchasers, 2002  

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

Electricity: Sales to Utility and Nonutility Purchasers, 2002;" Electricity: Sales to Utility and Nonutility Purchasers, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Utility and Nonutility Purchasers;" " Unit: Million Kilowatthours." ,"Total of",,,"RSE" "Economic","Sales and","Utility","Nonutility","Row" "Characteristic(a)","Transfers Offsite","Purchaser(b)","Purchaser(c)","Factors" ,"Total United States" "RSE Column Factors:",0.9,1.3,0.9 "Value of Shipments and Receipts" "(million dollars)"

103

Table 11.4 Electricity: Components of Onsite Generation, 2002  

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

4 Electricity: Components of Onsite Generation, 2002;" 4 Electricity: Components of Onsite Generation, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Onsite-Generation Components;" " Unit: Million Kilowatthours." " ",,,"Renewable Energy" ,,,"(excluding Wood",,"RSE" "Economic","Total Onsite",,"and",,"Row" "Characteristic(a)","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:",0.8,0.8,1.1,1.4 "Value of Shipments and Receipts"

104

Two-Column Aerosol Project  

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

Climate Research Facility is conducting the Two-Column Aerosol Project (TCAP) at Cape Cod National Seashore. From July 2012 to June 2013, the ARM Mobile Facility-a portable...

105

Self-regenerating column chromatography  

DOE Patents (OSTI)

The present invention provides a process for treating both cations and anions by using a self-regenerating, multi-ionic exchange resin column system which requires no separate regeneration steps. The process involves alternation ion-exchange chromatography for cations and anions in a multi-ionic exchange column packed with a mixture of cation and anion exchange resins. The multi-ionic mixed-charge resin column works as a multifunction column, capable of independently processing either cationic or anionic exchange, or simultaneously processing both cationic and anionic exchanges. The major advantage offered by the alternating multifunction ion exchange process is the self-regeneration of the resins. Applications are to separation of nitrogen and sulfur isotopes.

Park, Woo K.

1994-12-31T23:59:59.000Z

106

TWO-COLUMN FORMATTING GUIDE  

Science Conference Proceedings (OSTI)

This is a guide designed to cover the details of paper preparation to ensure uniformity and continuity for two-column ... printed in black and white. It is best to:.

107

Benzene rectifying column performance optimization  

Science Conference Proceedings (OSTI)

Benzene rectifying column control at the actual petroleum refinery is studied. Certain approaches to increase the performance of precise rectification of benzene and toluene are suggested. An algorithm of evaluating the optimal regulation parameters ...

D. A. Smirnova; V. I. Fedorov; N. V. Lisitsyn

2011-01-01T23:59:59.000Z

108

Binary distillation column design using mathematica  

Science Conference Proceedings (OSTI)

The accurate design of distillation columns is a very important topic in chemical industry. In this paper, we describe a Mathematica program for the design of distillation columns for binary mixtures. For simplicity, it is assumed that the columns are ...

Akemi Gálvez; Andrés Iglesias

2003-06-01T23:59:59.000Z

109

Optimization Online - Column Generation for Extended Formulations  

E-Print Network (OSTI)

Jul 8, 2011 ... We compare numerically a direct handling of the extended formulation, a standard column generation approach, and the ``column-and-row ...

110

Cumulative mass approach for column testing  

Science Conference Proceedings (OSTI)

A cumulative mass approach for laboratory column testing using an analytical solution for miscible transport through soil is presented. The cumulative mass approach differs from the more traditional approach for column testing in that the analysis of the measured data is in terms of mass of solute instead of solute concentration. The potential advantages of the cumulative mass approach are: (1) The influence of increment in effluent sample volume on the measured concentrations is removed from consideration; (2) the effluent sampling procedure is less labor-intensive, and therefore potentially more cost-effective; and (3) the retardation factor and effective porosity can be evaluated directly from plots of the test results. A comparison of analyses of measured data based on the cumulative mass approach with the more traditional concentration-based approach indicates slight differences (less than 3%) in the regressed values of the dispersion coefficient and retardation factor. These differences are attributed to greater scatter in the data for the more traditional approach and to slight errors involved in the traditional approach due to plotting the average, incremental concentrations at the pore volumes of flow corresponding to the middle of the sampling interval.

Shackelford, C.D. [Colorado State Univ., Fort Collins, CO (United States)] [Colorado State Univ., Fort Collins, CO (United States)

1995-10-01T23:59:59.000Z

111

Table A39. Total Expenditures for Purchased Electricity and Steam  

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

9. Total Expenditures for Purchased Electricity and Steam" 9. Total Expenditures for Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" ," Electricity",," Steam" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,"Total United States" "RSE Column Factors:",0.3,2,1.6,1.2

112

" Generation by Census Region, Industry Group, Selected Industries, Presence of"  

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

4. Total Inputs of Energy for Heat, Power, and Electricity" 4. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Census Region, Industry Group, Selected Industries, Presence of" " General Technologies, and Industry-Specific Technologies for Selected" " Industries, 1991" " (Estimates in Trillion Btu)" ,,," Census Region",,,,"RSE" "SIC","Industry Groups",," -------------------------------------------",,,,"Row" "Code(a)","and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.3,1,0.9,1.3

113

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

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

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

114

"Table A27. Components of Onsite Electricity Generation by Census Region,"  

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

Components of Onsite Electricity Generation by Census Region," Components of Onsite Electricity Generation by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Million Kilowatthours)" ," "," "," "," " " "," "," "," ",," ","RSE" "SIC"," "," "," ",," ","Row" "Code(a)","Industry Group and Industry","Total","Cogeneration","Renewables","Other(b)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.8,0.8,1.6,1 , 20,"Food and Kindred Products",6962,6754,90,118,11.2

115

Table A19. Components of Total Electricity Demand by Census Region and  

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

Components of Total Electricity Demand by Census Region and" Components of Total Electricity Demand by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,1.4,1.3,1.9,0.5 "Value of Shipments and Receipts" "(million dollars)"

116

Table A30. Quantity of Electricity Sold to Utility and Nonutility Purchasers  

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

Quantity of Electricity Sold to Utility and Nonutility Purchasers" Quantity of Electricity Sold to Utility and Nonutility Purchasers" " by Census Region, Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," "," ","RSE" "SIC"," "," ","Utility ","Nonutility","Row" "Code(a)","Industry Group and Industry","Total Sold","Purchaser(b)","Purchaser(c)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.9,1.1,1 , 20,"Food and Kindred Products",1829," W "," W ",28

117

Table A26. Components of Total Electricity Demand by Census Region, Census Di  

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

Components of Total Electricity Demand by Census Region, Census Division, and" Components of Total Electricity Demand by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,2.1,1.2,2,0.4 "Value of Shipments and Receipts"

118

Method for packed column separations and purifications  

DOE Patents (OSTI)

The invention encompasses a method of packing and unpacking a column chamber. A mixture of a fluid and a matrix material are introduced through a column chamber inlet so that the matrix material is packed within a column chamber to form a packed column. The column chamber having the column chamber inlet or first port for receiving the mixture further has an outlet port and an actuator port. The outlet port is partially closed for capturing the matrix material and permitting the fluid to flow therepast by rotating relative one to the other of a rod placed in the actuator port. Further rotation relative one to the other of the rod and the column chamber opens the outlet and permits the matrix material and the fluid to flow therethrough thereby unpacking the matrix material from the column chamber.

Holman, David A. (Richland, WA); Bruckner-Lea, Cynthia J. (Richland, WA); Brockman, Fred J. (Kennewick, WA); Chandler, Darrell P. (Richland, WA)

2006-08-15T23:59:59.000Z

119

Modeling Tropical Precipitation in a Single Column  

Science Conference Proceedings (OSTI)

A modified formulation of the traditional single column model for representing a limited area near the equator is proposed. This formulation can also be considered a two-column model in the limit as the area represented by one of the columns ...

Adam H. Sobel; Christopher S. Bretherton

2000-12-01T23:59:59.000Z

120

Property:Water Column Location | Open Energy Information  

Open Energy Info (EERE)

Column Location Jump to: navigation, search Property Name Water Column Location Property Type Text Pages using the property "Water Column Location" Showing 1 page using this...

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


121

President’s s Column  

E-Print Network (OSTI)

Please allow me to begin my final president's column with a bit of venting. As with any industry organization such as SIPES, the more one becomes involved the more one becomes cognizant of public perception and government involvement as it affects the members of the organization. It can be frustrating to be at the receiving end of constant degradation and unappreciation for the professional sacrifices and financial risks one takes for the betterment of mankind. Explain to me why the independent oil and gas companies are consistently herded into the same corral as "Big Oil. " Why mom-and–pop oil and gas companies are subject to the same ridicule Alison and David Eyler with First Lady Laura Bush at the opening of the Bush

David A. Eyler

2006-01-01T23:59:59.000Z

122

geo column legal.ai  

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

Teapot Dome Teapot Dome Geologic Column Natrona County, Wyoming T 38 & 39 N R 78 W Period Formation L i t h o l o g y T h i c k n e s s D e p t h ( f t ) P r o d u c t i v e Quaternary Alluvium Fox Hills Sandstone Lewis Shale Niobrara Shale Carlisle Shale Mesaverde Group Morrison Mowry Shale Muddy Sandstone Thermopolis Shale Dakota Lakota Goose Egg Tensleep Amsden Madison Undifferentiated Granite Steele Shale Frontier Sundance Chugwater Group Teapot Ss "Pumpkin Buttes shale" Parkman Ss Sussex Ss Shannon Ss 1st Wall Creek 2nd Wall Creek 3rd Wall Creek Upper Lower Crow Mountain Alcova LS Red Peak Outcropping units 195 515 635 1990 2440 3840 3975 4060 4070 4340 4435 4585 4665 4685 5205 5525 5845 6005 6305 7085 3825 3595 3330 3325 3150 3085 2840 2680 0-50 600 100 50 325 470 1355 195 30 290 120 480 160 245 65 240 450 265 230 15 135 85 5 175 80 150 95 270 10 160 320 320 520

123

table10.1_021.xls  

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

Nonswitchable Minimum and Maximum Consumption, 2002; Nonswitchable Minimum and Maximum Consumption, 2002; Level: National and Regional Data; Row: Energy Sources; Column: Consumption Potential; Unit: Physical Units. RSE Actual Minimum Maximum Row Energy Sources Consumption Consumption(a) Consumption(b) Factors Total United States RSE Column Factors: 1 1 1 Electricity Receipts(c) (million kilowatthours) 855,160 668,467 894,613 2 Natural Gas (billion cubic feet) 5,641 3,536 6,108 2 Distillate Fuel Oil (thousand barrels) 24,446 13,621 118,299 5 Residual Fuel Oil (thousand barrels) 33,132 14,781 84,800 3 Coal (thousand short tons) 60,310 34,999 62,947 8.3 LPG (thousand barrels) 26,547 8,661 142,736 4.8 Northeast Census Region RSE Column Factors:

124

Tritium Isotope Separation Using Adsorption-Distillation Column  

Science Conference Proceedings (OSTI)

In order to miniaturize the height of a distillation tower for the detritiation of waste water from fusion reactors, two experiments were conducted: (1) liquid frontal chromatography of tritium water eluting through an adsorption column and (2) water distillation using a column packed with adsorbent particles. The height of the distillation tower depends on the height equivalent to a theoretical plate, HETP, and the equilibrium isotope separation factor, {alpha}{sub H-T}{sup equi}. The adsorption action improved not only HETP but also {alpha}{sub H-T}{sup equi}. Since the adsorption-distillation method proposed here can shorten the tower height with keeping advantages of the distillation, it may bring an excellent way for miniaturizing the distillation tower to detritiate a large amount of waste water from fusion reactors.

Fukada, Satoshi [Kyushu University (Japan)

2005-07-15T23:59:59.000Z

125

Dynamic Stabilization of Atmospheric Single Column Models  

Science Conference Proceedings (OSTI)

Single column models (SCMs) provide an economical framework for assessing the sensitivity of atmospheric temperature and humidity to natural and imposed perturbations, and also for developing improved representations of diabatic processes in ...

John W. Bergman; Prashant D. Sardeshmukh

2004-03-01T23:59:59.000Z

126

Table N1.3. First Use of Energy for All Purposes (Fuel and Nonfuel), 1998  

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

.3. First Use of Energy for All Purposes (Fuel and Nonfuel), 1998;" .3. First Use of Energy for All Purposes (Fuel and Nonfuel), 1998;" " Level: National Data; " " Row: Energy Sources and Shipments, including Further Classification of 'Other' Energy Sources;" " Column: First Use per Energy Sources and Shipments;" " Unit: Trillion Btu." " "," "," " " "," ","RSE" ,"Total","Row" "Energy Source","First Use","Factors" ,"Total United States" "RSE Column Factor:",1 "Coal ",1814,3 "Natural Gas",7426,1 "Net Electricity",3035,1 " Purchases",3044,1

127

Table 1.5 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002  

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

5 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002;" 5 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002;" " Level: National Data; " " Row: Energy Sources and Shipments, including Further Classification of 'Other' Energy Sources;" " Column: First Use per Energy Sources and Shipments;" " Unit: Trillion Btu." " "," "," " " "," ","RSE" ,"Total","Row" "Energy Source","First Use","Factors" ,"Total United States" "RSE Column Factor:",1 "Coal ",1959,10 "Natural Gas",6468,1.3 "Net Electricity",2840,1.4 " Purchases",2882,1.4

128

" Row: Industry-Specific Technologies within Selected NAICS Codes;"  

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

3. Number of Establishments by Usage of Energy-Saving Technologies for Specific Industries, 1998;" 3. Number of Establishments by Usage of Energy-Saving Technologies for Specific Industries, 1998;" " Level: National Data; " " Row: Industry-Specific Technologies within Selected NAICS Codes;" " Column: Usage;" " Unit: Establishment Counts." ,,,,,"RSE" "NAICS"," ",,,,"Row" "Code(a)","Industry-Specific Technology","In Use(b)","Not in Use","Don't Know","Factors" ,,"Total United States" ,"RSE Column Factors:",1.3,0.5,1.5 , 311,"FOOD" ," Infrared Heating",762,13727,2064,1.8 ," Microwave Drying",270,14143,2140,2.5

129

Optimization Online - Simultaneous Column-and-Row Generation ...  

E-Print Network (OSTI)

Nov 14, 2010 ... Simultaneous Column-and-Row Generation for Large-Scale Linear Programs with Column-Dependent- ... Entry Last Modified: 05/17/2012.

130

Impact of Flow Dependence, Column Covariance, and Forecast Model Type on Surface-Observation Assimilation for Probabilistic PBL Profile Nowcasts  

Science Conference Proceedings (OSTI)

A probabilistic verification and factor-separation analysis (FSA) elucidate skillful nowcasts of planetary boundary layer (PBL) temperature, moisture, and wind profiles with a single-column model (SCM) and ensemble filter (EF) assimilation of ...

Dorita Rostkier-Edelstein; Joshua P. Hacker

2013-02-01T23:59:59.000Z

131

Integrated Thermal and Hydraulic Analysis of Distillation Columns  

E-Print Network (OSTI)

This paper outlines the implementation of column thermal and hydraulic analysis in a simulation environment. The methodology is described using a separations example. Column Thermal Analysis has been discussed in the literature extensively. The paper outlines how bringing together the column thermal and hydraulics analysis provides significant additional insights to help screen the options for distillation column revamps.

Samant, K.; Sinclair, I.; Keady, G.

2002-04-01T23:59:59.000Z

132

ARM - Field Campaign - Two-Column Aerosol Project (TCAP)  

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

govCampaignsTwo-Column Aerosol Project (TCAP) govCampaignsTwo-Column Aerosol Project (TCAP) Campaign Links TCAP website Related Campaigns Two-Column Aerosol Project (TCAP): Field Evaluation of Real-time Cloud OD Sensor TWST 2013.04.15, Scott, AMF Two-Column Aerosol Project (TCAP): Winter Aerosol Effects on Cloud Formation 2013.02.04, Cziczo, AMF Two-Column Aerosol Project (TCAP): CU GMAX-DOAS Deployment 2012.07.15, Volkamer, AMF Two-Column Aerosol Project (TCAP): Aerosol Light Extinction Measurements 2012.07.15, Dubey, AMF Two-Column Aerosol Project (TCAP): Aerial Campaign 2012.07.07, Berg, AAF Two-Column Aerosol Project (TCAP): Aerodynamic Particle Sizer 2012.07.01, Berg, AMF Two-Column Aerosol Project (TCAP): KASPRR Engineering Tests 2012.07.01, Mead, AMF Two-Column Aerosol Project (TCAP): Airborne HSRL and RSP Measurements

133

Thermal Analysis of LANL Ion Exchange Column  

Science Conference Proceedings (OSTI)

This document reports results from an ion exchange column heat transfer analysis requested by Los Alamos National Laboratory (LANL). The object of the analysis is to demonstrate that the decay heat from the Pu-238 will not cause resin bed temperatures to increase to a level where the resin significantly degrades.

Laurinat, J.E.

1999-06-16T23:59:59.000Z

134

BNL | Two-Column Aerosol Program (TCAP)  

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

Two-Column Aerosol Project (TCAP) Two-Column Aerosol Project (TCAP) There remain many key knowledge gaps despite advances in the scientific understanding of how aerosols and clouds evolve and affect climate. Many climatically important processes depend on particles that undergo continuous changes within a size range spanning a few nanometers to a few microns, and with compositions that consist of a variety of carbonaceous materials, soluble inorganic salts and acids and insoluble mineral dust. Primary particles, which are externally-mixed when emitted, are subject to coagulation and chemical changes associated with the condensation of semi-volatile gases to their surface resulting in a spectrum of compositions or mixing-states with a range of climate-affecting optical and hygroscopic properties. The numerical treatments of aerosol transformation

135

Query execution in column-oriented database systems  

E-Print Network (OSTI)

There are two obvious ways to map a two-dimension relational database table onto a one-dimensional storage interface: store the table row-by-row, or store the table column-by-column. Historically, database system implementations ...

Abadi, Daniel J

2008-01-01T23:59:59.000Z

136

Table 3.3 Fuel Consumption, 2002  

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

3 Fuel Consumption, 2002;" 3 Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," "," "," "," " " "," ",," "," ",," "," ",," ","RSE" "Economic",,"Net","Residual","Distillate","Natural ","LPG and",,"Coke and"," ","Row" "Characteristic(a)","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Gas(d)","NGL(e)","Coal","Breeze","Other(f)","Factors"

137

Table N13.3. Electricity: Sales to Utility and Nonutility Purchasers, 1998  

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

3. Electricity: Sales to Utility and Nonutility Purchasers, 1998;" 3. Electricity: Sales to Utility and Nonutility Purchasers, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: Utility and Nonutility Purchasers;" " Unit: Million Kilowatthours." " "," ",,,," " " "," ","Total of",,,"RSE" "NAICS"," ","Sales and","Utility","Nonutility","Row" "Code(a)","Subsector and Industry","Transfers Offsite","Purchaser(b)","Purchaser(c)","Factors" ,,"Total United States"

138

Cross flow cyclonic flotation column for coal and minerals beneficiation  

SciTech Connect

An apparatus and process for the separation of coal from pyritic impurities using a modified froth flotation system. The froth flotation column incorporates a helical track about the inner wall of the column in a region intermediate between the top and base of the column. A standard impeller located about the central axis of the column is used to generate a centrifugal force thereby increasing the separation efficiency of coal from the pyritic particles and hydrophillic tailings.

Lai, Ralph W. (Upper St. Clair, PA); Patton, Robert A. (Pittsburgh, PA)

2000-01-01T23:59:59.000Z

139

Cross flow flotation column for coal and minerals beneficiation  

DOE Patents (OSTI)

An apparatus and process are disclosed for the separation of coal from pyritic impurities using a modified froth flotation system. The froth flotation column incorporates a helical track about the inner wall of the column in a region intermediate between the top and base of the column. A standard impeller located about the central axis of the column is used to generate a centrifugal force thereby increasing the separation efficiency of coal from the pyritic particles and hydrophilic tailings.

Lai, Ralph W.; Patton, Robert A.

1997-12-01T23:59:59.000Z

140

Control of binary distillation column using fuzzy PI controllers  

Science Conference Proceedings (OSTI)

In this paper the automatic control of a binary distillation column is described. This control is done with fuzzy logic controllers. After a short explanation of the function and dynamic of a binary distillation column, it's operating and control strategies ... Keywords: binary distillation column, fuzzy inference system, simulation

Shahram Javadi; Jabber Hosseini

2009-08-01T23:59:59.000Z

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


141

Application for testing control configurations of binary distillation columns  

Science Conference Proceedings (OSTI)

The paper addresses the problem of testing various control configurations for binary distillation columns. Analyzing from plantwide control point of view the place of distillation column within the plant, the result will be the best control configuration. ... Keywords: composition control, distillation columns, dynamic simulations, plantwide control

Sanda Mihalache; Marian Popescu

2007-08-01T23:59:59.000Z

142

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

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

A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Industry Group, Selected Industries, and Type of" " Energy-Management Program, 1994" " (Estimates in Trillion Btu)" ,,,," Census Region",,,"RSE" "SIC",,,,,,,"Row" "Code(a)","Industry Group and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.2,1.1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",12605,1209,3303,6386,1706,2.9

143

"Table A7. Shell Storage Capacity of Selected Petroleum Products by Census"  

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

Shell Storage Capacity of Selected Petroleum Products by Census" Shell Storage Capacity of Selected Petroleum Products by Census" " Region, Industry Group, and Selected Industries, 1991" " (Estimates in Thousand Barrels)" " "," "," "," "," ","Other","RSE" "SIC"," ","Motor","Residual"," ","Distillate","Row" "Code(a)","Industry Groups and Industry","Gasoline","Fuel Oil","Diesel","Fuel Oil","Factors" ,,"Total United States" ,"RSE Column Factors:",1,0.9,1,1.1 , 20,"Food and Kindred Products",38,1448,306,531,12.1 2011," Meat Packing Plants",1,229,40,13,13.2

144

Table A12. Selected Combustible Inputs of Energy for Heat, Power, and  

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

Type" Type" " and End Use, 1994: Part 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,"Residual","Distillate",,,"(excluding","RSE" "SIC",,"Net Demand","Fuel","Fuel Oil and","Natural",,"Coal Coke","Row" "Code(a)","End-Use Categories","for Electricity(b)","Oil","Diesel Fuel(c)","Gas(d)","LPG","and Breeze)","Factors" "20-39","ALL INDUSTRY GROUPS" ,"RSE Column Factors:",0.5,1.4,1.4,0.8,1.2,1.2 ,"TOTAL INPUTS",3132,441,152,6141,99,1198,2.4

145

"Table A52. Nonswitchable Minimum Requirements and Maximum Consumption"  

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

2. Nonswitchable Minimum Requirements and Maximum Consumption" 2. Nonswitchable Minimum Requirements and Maximum Consumption" " Potential by Census Region, 1991" " (Estimates in Physical Units)" ,,,,"RSE" ,"Actual","Minimum","Maximum","Row" "Type of Energy","Consumption","Consumption(a)","Consumption(b)","Factors" "RSE Column Factors:",1,1.2,0.8 ," Total United States" ,"-","-","-" "Electricity Receipts(c) (million kilowatthours)",718480,701478,766887,2 "Natural Gas (billion cubic feet)",5345,3485,5887,2 "Distillate Fuel Oil (thousand barrels)",23885,19113,201081,3.7 "Residual Fuel Oil (thousand barrels)",65837,36488,201921,2.6

146

" Electricity Generation by Employment Size Categories, Industry Group,"  

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

Total Consumption of Offsite-Produced Energy for Heat, Power, and" Total Consumption of Offsite-Produced Energy for Heat, Power, and" " Electricity Generation by Employment Size Categories, Industry Group," " and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," "," Employment Size(b)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",1000,"Row" "Code(a)","Industry Group and Industry","Total","Under 50","50-99","100-249","250-499","500-999","and Over","Factors" ,"RSE Column Factors:",0.6,1.4,1.5,1,0.9,1,1

147

"Table A41. Average Prices of Selected Purchased Energy Sources by Census Region,"  

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

1" 1" " (Estimates in Dollars per Physical Units)" " "," ","Residual","Distillate ","Natural"," "," ","RSE" " ","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","Row" "Economic Characteristics(a)","(kWh)","(gallons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors" ,"Total United States" "RSE Column Factors:",0.6,0.8,1.2,0.7,2.5,0.9 "Value of Shipments and Receipts" "(million dollars)" " Under 20",0.065,0.43,0.77,3.71,0.76,39.15, 2.4

148

"Table A25 Average Prices of Selected Purchased Energy Sources by Census"  

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

Average Prices of Selected Purchased Energy Sources by Census" Average Prices of Selected Purchased Energy Sources by Census" " Region, Industry Group, and Selected Industries, 1991: Part 2" " (Estimates in Dollars per Million Btu)" ,,,,,,,,"RSE" "SIC"," "," ","Residual","Distillate"," "," "," ","Row" "Code(a)","Industry Groups and Industry","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","LPG","Coal","Factors" ,,"Total United States" ,"RSE Column Factors:",0.7,0.8,1,2.8,1,0.7 20,"Food and Kindred Products",15.789,2.854,6.064,2.697,7.596,1.433,4.5

149

" Electricity Sales/Transfers Out",96,4  

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

4. Total First Use (formerly Primary Consumption) of Energy for All Purposes" 4. Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Selected Energy Sources, 1994" " (Estimates in Trillion Btu)" ,,"RSE" ,,"Row" "Selected Energy Sources","Total","Factors" ,"Total United States" "RSE Column Factor:",1 "Coal ",2105,4 "Natural Gas",6835,3 "Net Electricity",2656,2 " Purchased Electricity",2689,1 " Transfers In",53,4 " Generation from Noncombustible",," " " Renewable Resources",10,10 " Electricity Sales/Transfers Out",96,4 "Coke and Breeze",449,8 "Residual Fuel Oil",490,3

150

Table HC1-11a. Housing Unit Characteristics by South Census Region,  

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

1a. Housing Unit Characteristics by South Census Region, 1a. Housing Unit Characteristics by South Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.4 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- -- NF New England ............................................. 5.4 -- -- -- -- NF Middle Atlantic ........................................... 14.8 -- -- -- -- NF Midwest ....................................................... 24.5 -- -- -- -- NF East North Central .....................................

151

1992 CBECS BC  

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

8. Principal Building Activity, Number of Buildings 8. Principal Building Activity, Number of Buildings and Floorspace, 1992 Building Characteristics RSE Column Factor: All Buildings (thousand) Total Floorspace (million square feet) RSE Row Factor 0.9 1.1 All Buildings ........................................................ 4,806 67,876 3.7 Principal Building Activity Education ............................................................ 301 8,470 7.5 Food Sales ......................................................... 130 757 14.5 Food Service ..................................................... 260 1,491 8.7 Health Care Inpatient ............................................................. 19 1,287 18.7 Outpatient .......................................................... 44 476 17.8 Laboratory

152

S:\VM3\RX97\TBL_LIST.WPD  

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

Million U.S. Households, 1997 Housing Unit Characteristics RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.1 1.2 1.7 Total .............................................................. 101.5 6.8 11.5 7.0 5.9 NF Census Region and Division Northeast ..................................................... 19.7 6.8 -- -- -- NF New England ............................................. 5.3 Q -- -- -- NF Middle Atlantic ........................................... 14.4 6.8 -- -- -- NF Midwest ....................................................... 24.1 -- -- -- -- NF East North Central ..................................... 16.9 -- -- -- -- NF West North Central .................................... 7.2 -- -- -- -- NF South ...........................................................

153

Table A21. Quantity of Electricity Sold to Utility and Nonutility Purchasers  

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

1. Quantity of Electricity Sold to Utility and Nonutility Purchasers" 1. Quantity of Electricity Sold to Utility and Nonutility Purchasers" " by Census Region and Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" ,,,,"RSE" " "," ","Utility ","Nonutility","Row" "Economic Characteristics(a)","Total Sold","Purchaser(b)","Purchaser(c)","Factors" ,"Total United States",,, "RSE Column Factors:",1,1.1,1 "Value of Shipments and Receipts" "(million dollars)" " Under 20",188,122,66,35.6 " 20-49",2311,1901,410,39.5 " 50-99",2951,2721,230,9.6 " 100-249",6674,5699,974,7.1

154

Table A37. Total Inputs of Energy for Heat, Power, and Electricity  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" "Total United States" "RSE Column Factors:","NF",0.4,1.6,1.5,0.7,1,1.6,"NF" "TOTAL INPUTS",15027,2370,414,139,5506,105,1184,5309,3 "Boiler Fuel","--","W",296,40,2098,18,859,"--",3.6

155

"Table A40. Average Prices of Selected Purchased Energy Sources by Census"  

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

Region, Census Division, Industry Group, and Selected Industries, 1994: Part 1" Region, Census Division, Industry Group, and Selected Industries, 1994: Part 1" " (Estimates in Dollars per Physical Units)" ,,,,," " " "," "," ","Residual","Distillate","Natural Gas(c)"," "," ","RSE" "SIC"," ","Electricity","Fuel Oil","Fuel Oil(b)","(1000","LPG","Coal","Row" "Code(a)","Industry Group and Industry","(kWh)","(gallons)","(gallons)","cu ft)","(gallons)","(short tons)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.8,1,1.3,0.8,1.6,0.8

156

Table A28. Components of Onsite Electricity Generation by Census Region, Cens  

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

Components of Onsite Electricity Generation by Census Region, Census Division, and" Components of Onsite Electricity Generation by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" ,,,"Renewables" ,,,"(excluding Wood",,"RSE" " "," "," ","and"," ","Row" "Economic Characteristics(a)","Total","Cogeneration(b)","Other Biomass)(c)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:",0.6,0.6,1.8,1.4 "Value of Shipments and Receipts" "(million dollars)" " Under 20",1098,868," W "," W ",22.3

157

Table HC1-12a. Housing Unit Characteristics by West Census Region,  

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

2a. Housing Unit Characteristics by West Census Region, 2a. Housing Unit Characteristics by West Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- NF New England ............................................. 5.4 -- -- -- NF Middle Atlantic ........................................... 14.8 -- -- -- NF Midwest ....................................................... 24.5 -- -- -- NF East North Central ..................................... 17.1 -- -- -- NF West North Central ....................................

158

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

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

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

159

"Table A24. Total Expenditures for Purchased Energy Sources by Census Region,"  

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

4. Total Expenditures for Purchased Energy Sources by Census Region," 4. Total Expenditures for Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Groupsc and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors" ,,"Total United States" ,"RSE Column Factors:","0.6 ",0.6,1.3,1.3,0.7,1.2,1.2,1.5,1.1

160

Table A20. Components of Onsite Electricity Generation by Census Region and  

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

Components of Onsite Electricity Generation by Census Region and" Components of Onsite Electricity Generation by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" ,,,,,"RSE" " "," "," "," "," ","Row" "Economic Characteristics(a)","Total","Cogeneration","Renewables","Other(b)","Factors" ,"Total United States" "RSE Column Factors:",0.8,0.8,1.2,1.3 "Value of Shipments and Receipts" "(million dollars)" " Under 20",562,349,"W","W",23 " 20-49",4127,3917,79,131,20.1 " 50-99",8581,7255,955,371,10

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


161

Table A18. Quantity of Electricity Sold to Utility and Nonutility Purchasers  

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

8. Quantity of Electricity Sold to Utility and Nonutility Purchasers" 8. Quantity of Electricity Sold to Utility and Nonutility Purchasers" " by Census Region, Industry Group, and Selected Industries, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," "," ","RSE" "SIC"," "," ","Utility ","Nonutility","Row" "Code(a)","Industry Groups and Industry","Total Sold","Purchaser(b)","Purchaser(c)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.9,1,1 , 20,"Food and Kindred Products",988,940,48,16.2 2011," Meat Packing Plants",0,0,0,"NF"

162

Table A38. Selected Combustible Inputs of Energy for Heat, Power, and  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,"Net Demand","Residual","Distillate",,,"(excluding","RSE" "SIC",,"for Electri-","Fuel","Fuel Oil and","Natural",,"Coal Coke","Row" "Code","End-Use Categories","city(b)","Oil","Diesel Fuel(c)","Gas(d)","LPG","and Breeze)","Factors" "20-39","ALL INDUSTRY GROUPS" ,"RSE Column Factors:",0.4,1.7,1.5,0.7,1,1.6 ,"TOTAL INPUTS",2799,414,139,5506,105,1184,3 ,"Boiler Fuel",32,296,40,2098,18,859,3.6 ,"Total Process Uses",2244,109,34,2578,64,314,4.1

163

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

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

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

164

"Table A29. Average Prices of Selected Purchased Energy Sources by Census"  

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

1" 1" " (Estimates in Dollars per Physical Unit)" " "," ","Residual","Distillate ","Natural"," "," ","RSE" " ","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","Row" "Economic Characteristics(a)","(kWh)","(gallon)","(gallon)","(1000 cu ft)","(gallon)","(short ton)","Factors" ,"Total United States" "RSE Column Factors:",0.7,1.2,1.1,0.8,1.2,1 "Value of Shipments and Receipts " "(million dollars)" " Under 20",0.066,0.404,0.813,3.422,0.705,37.024,3.4

165

Table A31. Quantity of Electricity Sold to Utility and Nonutility Purchasers  

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

Quantity of Electricity Sold to Utility and Nonutility Purchasers by Census Region," Quantity of Electricity Sold to Utility and Nonutility Purchasers by Census Region," " Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" ,,,,"RSE" " "," ","Utility ","Nonutility","Row" "Economic Characteristics(a)","Total Sold","Purchaser(b)","Purchaser(c)","Factors" ,"Total United States",,, "RSE Column Factors:",0.9,1.1,1 "Value of Shipments and Receipts" "(million dollars)" " Under 20",222,164," Q ",23.3 " 20-49",1131,937,194,17.2

166

Table A17. Total First Use (formerly Primary Consumption) of Energy for All P  

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

Total First Use (formerly Primary Consumption) of Energy for All Purposes" Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Employment Size Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," "," Employment Size(b)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",1000,"Row" "Code(a)","Industry Group and Industry","Total","Under 50","50-99","100-249","250-499","500-999","and Over","Factors" ,"RSE Column Factors:",0.6,1.5,1.5,1,0.9,0.9,0.9 , 20,"Food and Kindred Products",1193,119,207,265,285,195,122,6

167

"Table A41. Average Prices of Selected Purchased Energy Sources by Census Region,"  

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

2" 2" " (Estimates in Dollars per Million Btu)" " "," "," "," "," "," "," ","RSE" " "," ","Residual","Distillate","Natural"," "," ","Row" "Economic Characteristics(a)","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","Factors" ,"Total United States" "RSE Column Factors:",0.6,0.8,1.2,0.7,2.5,0.9 "Value of Shipments and Receipts" "(million dollars)" " Under 20",18.96,2.9,5.56,3.6,8.66,1.74, 2.4 " 20-49",15.07,2.53,4.9,2.8,5.87,1.81, 2.7

168

Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:"," NF",0.5,1.3,1.4,0.8,1.2,1.2," NF" "TOTAL INPUTS",16515,2656,441,152,6141,99,1198,5828,2.7 "Indirect Uses-Boiler Fuel"," --",28,313,42,2396,15,875," --",4

169

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

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

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

170

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

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

A41. Total Inputs of Energy for Heat, Power, and Electricity" A41. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Census Region, Industry Group, Selected Industries, and Type of" " Energy Management Program, 1991" " (Estimates in Trillion Btu)" ,,," Census Region",,,,"RSE" "SIC","Industry Groups",," -------------------------------------------",,,,"Row" "Code(a)","and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.3,1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",10743,1150,2819,5309,1464,2.6,,,"/WIR{D}~"

171

Hydrogen isotope exchange in metal hydride columns  

DOE Green Energy (OSTI)

Several metal hydrides were shown to act as chromatographic media for hydrogen isotopes. The procedure was to equilibrate a column of hydride with flowing hydrogen, inject a small quantity of tritium tracer, and observe its elution behavior. Characteristic retention times were found. From these and the extent of widening of the tritium band, the heights equivalent to a theoretical plate could be calculated. Values of around 1 cm were obtained. The following are the metals whose hydrides were studied, together with the temperature ranges in which chromatographic behavior was observed: vanadium, 0 to 70/sup 0/C; zirconium, 500 to 600/sup 0/C; LaNi/sub 5/, -78 to +30/sup 0/C; Mg/sub 2/Ni, 300 to 375/sup 0/C; palladium, 0 to 70/sup 0/C. A dual-temperature isotope separation process based on hydride chromatography was demonstrated. In this, a column was caused to cycle between two temperatures while being supplied with a constant stream of tritium-traced hydrogen. Each half-cycle was continued until ''breakthrough,'' i.e., until the tritium concentration in the effluent was the same as that in the feed. Up to that point, the effluent was enriched or depleted in tritium, by up to 20%.

Wiswall, R; Reilly, J; Bloch, F; Wirsing, E

1977-11-21T23:59:59.000Z

172

Comparison between a spray column and a sieve tray column operating as liquid-liquid heat exchangers  

DOE Green Energy (OSTI)

The performance of a spray column and a sieve tray column was compared as a liquid-liquid heat exchanger. In carrying out these studies a 15.2 cm (6.0 in.) diameter column, 183 cm (6.0 ft) tall was utilized. The performance of the spray column as a heat exchanger was shown to correlate with the model of Letan-Kehat which has as a basis that the heat transfer is dominated by the wakeshedding characteristics of the drops over much of the column length. This model defines several hydrodynamic zones along the column of which the wake formation zone at the bottom appears to have the most efficient heat transfer. The column was also operated with four perforated plates spaced two column diameters apart in order to take advantage of the wake formation zone heat transfer. The plates induce coalescence of the dispersed phase and reformation of the drops, and thus cause a repetition of the wake formation zone. It is shown that the overall volumetric heat transfer coefficient in a perforated plate column is increased by a minimum of eleven percent over that in a spray column. A hydrodynamic model that predicts the performance of a perforated plate column is suggested.

Keller, A.; Jacobs, H.R.; Boehm, R.F.

1980-12-01T23:59:59.000Z

173

MANUAL FOR USING LATEX TEMPLATE: TMS TWO-COLUMN ...  

Science Conference Proceedings (OSTI)

Title of Publication Edited by. TMS (The Minerals, Metals & Materials Society), Year. MANUAL FOR USING LATEX TEMPLATE: TMS TWO-COLUMN ...

174

manual for using latex template: tms two-column proceedings ...  

Science Conference Proceedings (OSTI)

MANUAL FOR USING LATEX TEMPLATE: TMS TWO-COLUMN PROCEEDINGS PUBLICATIONS. TMS. 1. , Jane Doe. 2. , John Doe. 2. 1. TMS (The Minerals ...

175

manual for using latex template: tms one-column proceedings ...  

Science Conference Proceedings (OSTI)

TMS ONE-COLUMN PROCEEDINGS PUBLICATIONS. TMS. 1. , Jane Doe. 2. , John Doe. 2. 1. TMS (The Minerals Metals & Materials Society); 184 Thorn Hill ...

176

Predicting the products of crude oil distillation columns.  

E-Print Network (OSTI)

??Crude oil distillation systems, consisting of crude oil distillation columns and the associated heat recovery systems, are highly energy intensive. Heat-integrated design of crude oil… (more)

Liu, Jing

2012-01-01T23:59:59.000Z

177

Model predictive control of a Kaibel distillation column.  

E-Print Network (OSTI)

?? Model predictive control (MPC) of a Kaibel distillation column is the main focus of this thesis. A model description together with a model extension… (more)

Kvernland, Martin Krister

2009-01-01T23:59:59.000Z

178

Table 4  

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

4. Mean Annual Electricity Expenditures for Lighting, by Number of 4. Mean Annual Electricity Expenditures for Lighting, by Number of Household Members by Number of Rooms, 1993 (Dollars) Number of Rooms Number of Household Members All Households One to Three Four Five Six Seven Eight or More RSE Column Factors: 0.5 1.8 1.1 0.9 0.9 1.0 1.2 RSE Row Factors All Households................................... 83 49 63 76 87 104 124 2.34 One..................................................... 55 44 51 54 69 78 87 5.33 Two..................................................... 80 56 63 77 82 96 107 3.38 Three.................................................. 92 60 73 82 95 97 131 4.75 Four.................................................... 106 64 78 93 96 124 134 4.53 Five or More....................................... 112 70 83 98 99 117 150 5.89 Notes: -- To obtain the RSE percentage for any table cell, multiply the

179

Lyman ? Absorption as a Sensitive Probe of the H I Column in Cooling Flows  

E-Print Network (OSTI)

Abstract. X-ray spectra of a significant fraction of cooling flow (CF) clusters of galaxies indicate the presence of large columns of “cold ” absorbing gas. The physical nature of the absorbing medium remains a mystery. Searches for H I absorption using the 21 cm hyperfine structure line yielded null results in most cases. The purpose of this contribution is to point out that the Lyman ? absorption cross section is ? 10 7 times larger than for the 21 cm line, it can therefore be used as a very sensitive probe of the H I column in clusters, and can thus place stringent constraints on the nature of the X-ray absorber. This method is applied to the Perseus CF cluster where a medium resolution ( ? 250 km s ?1) UV spectrum is available. The upper limit on the H I column obtained using Lyman ? is at least ? 50 times smaller than the 21 cm detection, and ? 5,000 smaller than implied by X-ray spectra, indicating that the X-ray absorber is exceedingly devoid of H I. Higher resolution UV spectra with HST may improve the H I column limits by an additional factor of ? 4,000. This method can be applied to strongly constrain the nature of the X-ray absorbing medium in a significant fraction of CF clusters.

A. Laor

1996-01-01T23:59:59.000Z

180

Lyman $?$ Absorption as a Sensitive Probe of the H I Column in Cooling Flows  

E-Print Network (OSTI)

X-ray spectra of a significant fraction of cooling flow (CF) clusters of galaxies indicate the presence of a large column of ``cold'' absorbing gas. The physical nature of the absorbing medium remains a mystery. Searches for H I absorption using the 21 cm hyperfine structure line yielded null results in most cases. The purpose of this contribution is to point out that the Lyman $\\alpha$ absorption cross section is ~10^7 times larger than for the 21 cm line, it can therefore be used as a very sensitive probe of the H I column in clusters, and can thus place stringent constraints on the nature of the X-ray absorber. This method is applied to the Perseus CF cluster where a medium resolution (~250 km/s) UV spectrum is available. The upper limit on the H I column obtained using Lyman $\\alpha$ is at least ~50 times smaller than the 21 cm detection, and ~5,000 smaller than implied by X-ray spectra, indicating that the X-ray absorber is exceedingly devoid of H I. Higher resolution UV spectra with HST may improve the H I column limits by an additional factor of ~4,000. This method can be applied to strongly constrain the nature of the X-ray absorbing medium in a significant fraction of CF clusters .

Ari Laor

1996-09-24T23:59:59.000Z

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


181

HEAT TRANSFER ANALYSIS FOR ION-EXCHANGE COLUMN SYSTEM  

SciTech Connect

Models have been developed to simulate the thermal characteristics of Crystalline Silicotitanate (CST) ion exchange media fully loaded with radioactive cesium in a column configuration and distributed within a waste storage tank. This work was conducted to support the Small Column Ion Exchange (SCIX) program which is focused on processing dissolved, high-sodium salt waste for the removal of specific radionuclides (including Cs-137, Sr-90, and actinides) within a High Level Waste (HLW) storage tank at the Savannah River Site. The SCIX design includes CST columns inserted and supported in the tank top risers for cesium removal. Temperature distributions and maximum temperatures across the column were calculated with a focus on process upset conditions. A two-dimensional computational modeling approach for the in-column ion-exchange domain was taken to include conservative, bounding estimates for key parameters such that the results would provide the maximum centerline temperatures achievable under the design configurations using a feed composition known to promote high cesium loading on CST. The current full-scale design for the CST column includes one central cooling pipe and four outer cooling tubes. Most calculations assumed that the fluid within the column was stagnant (i.e. no buoyancy-induced flow) for a conservative estimate. A primary objective of these calculations was to estimate temperature distributions across packed CST beds immersed in waste supernate or filled with dry air under various accident scenarios. Accident scenarios evaluated included loss of salt solution flow through the bed, inadvertent column drainage, and loss of active cooling in the column. The modeling results demonstrate that the baseline design using one central and four outer cooling tubes provides a highly efficient cooling mechanism for reducing the maximum column temperature.

Lee, S.; King, W.

2011-05-23T23:59:59.000Z

182

Novel techniques for slurry bubble column hydrodynamics  

Science Conference Proceedings (OSTI)

The objective of this cooperative research effort between Washington University, Ohio State University and Exxon Research Engineering Company was to improve the knowledge base for scale-up and operation of slurry bubble column reactors for syngas conversion and other coal conversion processes by increased reliance on experimentally verified hydrodynamic models. During the first year (July 1, 1995--June 30, 1996) of this three year program novel experimental tools (computer aided radioactive particle tracking (CARPT), particle image velocimetry (PIV), heat probe, optical fiber probe and gamma ray tomography) were developed and tuned for measurement of pertinent hydrodynamic quantities, such as velocity field, holdup distribution, heat transfer and bubble size. The accomplishments were delineated in the First Technical Annual Report. The second year (July, 1996--June 30, 1997) was spent on further development and tuning of the novel experimental tools (e.g., development of Monte Carlo calibration for CARPT, optical probe development), building up the hydrodynamic data base using these tools and comparison of the two techniques (PIV and CARPT) for determination of liquid velocities. A phenomenological model for gas and liquid backmixing was also developed. All accomplishments were summarized in the Second Annual Technical Report. During the third and final year of the program (July 1, 1997--June 30, 1998) and during the nine months no cost extension, the high pressure facility was completed and a set of data was taken at high pressure conditions. Both PIV, CT and CARPT were used. More fundamental hydrodynamic modeling was also undertaken and model predictions were compared to data. The accomplishments for this period are summarized in this report.

Dudukovic, M.P.

1999-05-14T23:59:59.000Z

183

High Performance Trays and Heat Exchangers in Heat Pumped Distillation Columns  

E-Print Network (OSTI)

Vapor recompression of distillation columns overheads, followed by subsequent condensation in the reboiler results in substantial operating cost savings compared to conventional steam driven reboiler systems. The use of high performance heat exchangers and distillation trays permits additional energy savings by lower reboiler temperature differences, and reduced reflux requirements for a fixed column height, due to closer tray spacings. This paper surveys the heat pump systems currently in operation using high performance UCC MD trays and High Flux tubing. Design considerations for high or low pressure level towers, with single or dual stage compression equipment are discussed, along with the various control methods. Factors affecting startup, part load, and off design operation of the equipment are also reviewed.

Wisz, M. W.; Antonelli, R.; Ragi, E. G.

1981-01-01T23:59:59.000Z

184

ARM - Publications: Science Team Meeting Documents: Ensemble Single Column  

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

Ensemble Single Column Modelling (ESCM) in the Tropical Western Pacific Ensemble Single Column Modelling (ESCM) in the Tropical Western Pacific Hume, Timothy Bureau of Meteorology Research Centre Jakob, Christian BMRC Single column models (SCMs) are useful tools for the evaluation of parameterisations of radiative and moist processes used in general circulation models. Most SCM studies to date have concentrated on regions where there is a sufficiently dense observational network to derive the required forcing data, such as the Southern Great Plains. This poster describes an ensemble single column modelling (ESCM) approach, where an ensemble of SCM forcing data sets are derived from numerical weather prediction (NWP) analyses. The technique is applied to SCM runs at the Manus Island and Nauru ARM sites in the Tropical Western Pacific (TWP). It

185

Assessment of Solution Uncertainties in Single-Column Modeling Frameworks  

Science Conference Proceedings (OSTI)

Single-column models (SCMs) have been extensively promoted in recent years as an effective means to develop and test physical parameterizations targeted for more complex three-dimensional climate models. Although there are some clear advantages ...

James J. Hack; John A. Pedretti

2000-01-01T23:59:59.000Z

186

Compression and query execution within column oriented databases  

E-Print Network (OSTI)

Compression is a known technique used by many database management systems ("DBMS") to increase performance[4, 5, 14]. However, not much research has been done in how compression can be used within column oriented architectures. ...

Ferreira, Miguel C. (Miguel Cacela Rosa Lopes Ferreira)

2005-01-01T23:59:59.000Z

187

Dynamic Radiative–Convective Equilibria Using GCM Column Physics  

Science Conference Proceedings (OSTI)

The behavior of a GCM column physics package in a nonrotating, doubly periodic, homogeneous setting with prescribed SSTs is examined. This radiative–convective framework is proposed as a useful tool for studying some of the interactions between ...

Isaac M. Held; Ming Zhao; Bruce Wyman

2007-01-01T23:59:59.000Z

188

Column generation based heuristic for a helicopter routing problem  

Science Conference Proceedings (OSTI)

This work presents a column generation based heuristic algorithm for the problem of planning the flights of helicopters to attend transport requests among airports in the continent and offshore platforms on the Campos basin for the Brazilian State Oil ...

Lorenza Moreno; Marcus Poggi de Aragão; Eduardo Uchoa

2006-05-01T23:59:59.000Z

189

Column Water Vapor Content in Clear and Cloudy Skies  

Science Conference Proceedings (OSTI)

With radiosonde data from 15 Northern Hemisphere stations, surface-to-400-mb column water vapor is computed from daytime soundings for 1988–1990. On the basis of simultaneous surface visual cloud observations, the data are categorized according ...

Dian J. Gaffen; William P. Elliott

1993-12-01T23:59:59.000Z

190

ARM - Field Campaign - Summer Single Column Model IOP  

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

govCampaignsSummer Single Column Model IOP govCampaignsSummer Single Column Model IOP Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Summer Single Column Model IOP 1997.06.18 - 1997.07.18 Lead Scientist : David Randall Data Availability Actual data files for a number of past SCM IOPs are available from the ARM Archive IOP Server Cloud and Radiation Products Derived from Satellite Data Colorado State's Single Column Modeling Home Page For data sets, see below. Summary During the IOP, 1180 sondes were launched, with 4 missing data due to weather related problems and 24 terminating before 10,000 m (10 km). Description The Summer 1997 SCM IOP was scheduled with the SGP97 Campaign. With additional NASA funding, the IOP was extended so that the total IOP covered

191

ARM - Field Campaign - Winter Single Column Model IOP  

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

govCampaignsWinter Single Column Model IOP govCampaignsWinter Single Column Model IOP Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Winter Single Column Model IOP 1999.01.19 - 1999.02.08 Lead Scientist : David Randall Data Availability Actual data files for a number of past SCM IOPs are available from the ARM Archive under IOPs/UAV. Cloud and Radiation Products Derived from Satellite Data Colorado State's Single Column Modeling Home Page For data sets, see below. Description A second winter SCM IOP was conducted (1/19 - 2/8/99) to provide additional sampling of winter weather conditions. This was the first SCM IOP where AERIs and ceilometers were installed at the boundary facilities to give retrievals of temperature and moisture to supplement the sounding data. A

192

The Downwind Spread of an Initially Vertical Column of Particles in a Sheared Environment  

Science Conference Proceedings (OSTI)

The effects of particle fallspeeds on the downwind spread of initially vertical columns or curtains are examined in environments with wind shear. Sets of equations describing the column width as a function of time and distance below column top ...

Ronald E. Stewart; John D. Marwitz

1982-08-01T23:59:59.000Z

193

Installation of the Pulse-Plate Column Pilot Plant  

Science Conference Proceedings (OSTI)

There are three primary types of solvent extraction equipment utilized in the nuclear industry for reprocessing of used nuclear fuel; pulse columns, mixer-settlers, and centrifugal contactors. Considerable research and development has been performed at the INL and throughout the DOE complex on the application of centrifugal contactors for used fuel reprocessing and these contactors offer many significant advantages. However, pulse columns have been used extensively in the past in throughout the world for aqueous separations processes and remain the preferred equipment by many commercial entities. Therefore, a pulse-plate column pilot plant has been assembled as part of the Advanced Fuel Cycle Initiative to support experimentation and demonstration of pulse column operation. This will allow the training of personnel in the operation of pulse columns. Also, this capability will provide the equipment to allow for research to be conducted in the operation of pulse columns with advanced solvents and processes developed as part of the fuel cycle research and development being performed in the AFCI program.

Nick R. Mann

2009-07-01T23:59:59.000Z

194

Single-Column Modeling R. B. Stull  

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

B. Stull B. Stull University of Wisconsin Madison, WI 53706 Oncley's data will become available during March 1993. Data from other research flights over the ARM/CART sites will be used as they become available. Calibration of Subgrid Statistics During the HAPEX experiment. one frequently flown flight track was an S-shaped pattern, shown in Figure 1. The track passed over 12 different regions of land use, which can be grouped into five broad classes. From 8 May through 24 July 1986, the NCAR King Air aircraft flew the Variations in surface albedo, moisture, soil type, vegetation coverage, and other factors cause surface-layer air (air within 50 m of surface) to be horizontally heterogeneous over land surfaces. This heterogeneity causes patchiness in boundary layer cloud coverage because clouds are

195

Model predictive control of a Kaibel distillation column  

E-Print Network (OSTI)

A Kaibel distillation column separates a feed into four products with significant lower energy consumption than a conventional sequence of binary columns. Optimal operation and control of such systems is an important task in order to obtain the potential energy savings. A laboratory column has been built at NTNU, Department of Chemical Engineering. At the time of the diploma work the laboratory column has unfortunately not been available for MPC experiments. In practical operation a control structure based on temperature measurements is chosen for the given case. This structure gives a four-by-four multivariable system. The candidate shall base his work on a model developed by Jens Strandberg. Tasks: 1. Describe the model and extend it to include an efficiency parameter describing insufficient mixing at stages 2. Describe a general linear MPC approach for the system 3. Analyze sensitivity of model errors 4. Evaluate alternative MPC approaches 5. Implement the MPC in MATLAB and illustrate the performance by simulations 6. Prepare a setup for connecting the MPC to the actual laboratory column

Martin Krister Kvernland; Supervisor Ole; Morten Aamo; Co-supervisor Ivar Halvorsen; Sigurd Skogestad Ikp; Jim Morrison Vii

2009-01-01T23:59:59.000Z

196

Single Column Model Simulations of Cloud Sensitivity to Forcing  

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

Single-Column Model Simulations Single-Column Model Simulations of Cloud Sensitivity to Forcing A. D. Del Genio National Aeronautics and Space Administration Goddard Institute for Space Studies New York, New York A. B. Wolf National Aeronautics and Space Administration SGT, Inc., Goddard Institute for Space Studies New York, New York Introduction The Atmospheric Radiation Measurement (ARM) Program single-column modeling (SCM) framework has to date used several fairly brief intensive observing periods (IOPs) to evaluate the performance of climate model parameterizations. With only a few weather events in each IOP, it is difficult to separate errors associated with the instantaneous dynamical forcing from errors in parameterization. It is also impossible to determine whether model errors are systematic and climatically significant. This

197

the Fractional Flotation of Flotation Column Particles Opportunity  

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

Enhancing Selectivity and Recovery in Enhancing Selectivity and Recovery in the Fractional Flotation of Flotation Column Particles Opportunity Although research is currently inactive on the patented technology "Method for Enhancing Selectivity and Recovery in the Fractional Flotation of Flotation Column Particles," the technology is available for licensing from the U.S. Department of Energy's National Energy Technology Laboratory (NETL). Disclosed in this patent is a method of particle separation from a feed stream comprised of particles of varying hydrophobicity by injecting the feed stream directly into the froth zone of a vertical flotation column in the presence of a counter-current reflux stream. The current invention allows the height of the feed stream injection and the reflux ratio to be

198

ARM - Field Campaign - Summer 1994 Single Column Model IOP  

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

govCampaignsSummer 1994 Single Column Model IOP govCampaignsSummer 1994 Single Column Model IOP Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Summer 1994 Single Column Model IOP 1994.07.01 - 1994.07.31 Lead Scientist : David Randall Data Availability Data Plots from Colorado State University Data Plots from Livermore National Laboratory Actual data files for a number of past SCM IOPs are available from the ARM Archive. For data sets, see below. Description These seasonal SCM IOPs are conducted at the Southern Great Plains to enhance the frequency of observations for SCM uses, particularly vertical soundings of temperature, water vapor, and winds. The SCM IOPs are conducted for a period of 21 days. During that time, radiosondes are launched at the Central Facility and the four boundary facilities eight

199

ARM - Field Campaign - Winter 1994 Single Column Model IOP  

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

govCampaignsWinter 1994 Single Column Model IOP govCampaignsWinter 1994 Single Column Model IOP Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Winter 1994 Single Column Model IOP 1994.01.01 - 1994.01.31 Lead Scientist : David Randall Data Availability Data Plots from Colorado State University Data Plots from Livermore National Laboratory Actual data files for a number of past SCM IOPs are available from the ARM Archive. For data sets, see below. Description These seasonal SCM IOPs are conducted at the Southern Great Plains to enhance the frequency of observations for SCM uses, particularly vertical soundings of temperature, water vapor, and winds. The SCM IOPs are conducted for a period of 21 days. During that time, radiosondes are launched at the Central Facility and the four boundary facilities eight

200

ARM - Field Campaign - Fall 1995 Single Column Model IOP  

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

Single Column Model IOP Single Column Model IOP Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Fall 1995 Single Column Model IOP 1995.09.01 - 1995.10.31 Lead Scientist : David Randall Data Availability Data Plots from Colorado State University Data Plots from Livermore National Laboratory Actual data files for a number of past SCM IOPs are available from the ARM Archive. For data sets, see below. Description These seasonal SCM IOPs are conducted at the Southern Great Plains to enhance the frequency of observations for SCM uses, particularly vertical soundings of temperature, water vapor, and winds. The SCM IOPs are conducted for a period of 21 days. During that time, radiosondes are launched at the Central Facility and the four boundary facilities eight

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


201

The Monte Carlo Independent Column Approximation Model Intercomparison  

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

The Monte Carlo Independent Column Approximation Model Intercomparison The Monte Carlo Independent Column Approximation Model Intercomparison Project (McMIP) Barker, Howard Meteorological Service of Canada Cole, Jason Meteorological Service of Canada Raisanen, Petri Finnish Meteorological Institute Pincus, Robert NOAA-CIRES Climate Diagnostics Center Morcrette, Jean-Jacques European Centre for Medium-Range Weather Forecasts Li, Jiangnan Canadian Center for Climate Modelling Stephens, Graeme Colorado State University Vaillancourt, Paul Environment Canada Oreopoulos, Lazaros JCET/UMBC and NASA/GSFC Siebesma, Pier KNMI Los, Alexander KNMI Clothiaux, Eugene The Pennsylvania State University Randall, David Colorado State University Iacono, Michael Atmospheric & Environmental Research, Inc. Category: Radiation The Monte Carlo Independent Column Approximation (McICA) method for

202

ENGINEERING DEVELOPMENT OF SLURRY BUBBLE COLUMN REACTOR (SBCR)TECHNOLOGY  

SciTech Connect

The major technical objectives of this program are threefold: (1) to develop the design tools and a fundamental understanding of the fluid dynamics of a slurry bubble column 0reactor to maximize reactor productivity, (2) to develop the mathematical reactor design models and gain an understanding of the hydrodynamic fundamentals under industrially relevant process conditions, and (3) to develop an understanding of the hydrodynamics and their interaction with the chemistries occurring in the bubble column reactor. Successful completion of these objectives will permit more efficient usage of the reactor column and tighter design criteria, increase overall reactor efficiency, and ensure a design that leads to stable reactor behavior when scaling up to large diameter reactors.

Bernard A. Toseland, Ph.D

2000-06-01T23:59:59.000Z

203

ENGINEERING DEVELOPMENT OF SLURRY BUBBLE COLUMN REACTOR (SBCR) TECHNOLOGY  

SciTech Connect

The major technical objectives of this program are threefold: (1) to develop the design tools and a fundamental understanding of the fluid dynamics of a slurry bubble column reactor to maximize reactor productivity, (2) to develop the mathematical reactor design models and gain an understanding of the hydrodynamic fundamentals under industrially relevant process conditions, and (3) to develop an understanding of the hydrodynamics and their interaction with the chemistries occurring in the bubble column reactor. Successful completion of these objectives will permit more efficient usage of the reactor column and tighter design criteria, increase overall reactor efficiency, and ensure a design that leads to stable reactor behavior when scaling up to large diameter reactors.

Bernard A. Toseland, Ph.D.

1999-01-01T23:59:59.000Z

204

An instrument for the measurement and determination of chemical pulse column parameters  

DOE Patents (OSTI)

This invention pertains to an instrument for monitoring and measuring pneumatic driving force pulse parameters applied to chemical separation pulse columns obtains real time pulse frequency and root mean square amplitude values, calculates column inch values and compares these values against preset limits to alert column operators to the variations of pulse column operational parameters beyond desired limits. 2 figs.

Marchant, N.J.; Morgan, J.P.

1988-08-31T23:59:59.000Z

205

table11.5_02.xls  

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

5 Electricity: Sales to Utility and Nonutility Purchasers, 2002; 5 Electricity: Sales to Utility and Nonutility Purchasers, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Utility and Nonutility Purchasers; Unit: Million Kilowatthours. Total of RSE NAICS Sales and Utility Nonutility Row Code(a) Subsector and Industry Transfers Offsite Purchaser(b) Purchaser(c) Factors Total United States RSE Column Factors: 1 0.9 1 311 Food 708 380 328 31 311221 Wet Corn Milling 248 W W 20.1 31131 Sugar 8 8 0 1 311421 Fruit and Vegetable Canning 28 W W 1 312 Beverage and Tobacco Products W W W 1 3121 Beverages W W W 1 3122 Tobacco W W 0 1 313 Textile Mills W W W 1.8 314 Textile Product Mills 0 0 0 0 315 Apparel 0 0 0 0 316 Leather and Allied Products

206

table8.1_02.xls  

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

1 Number of Establishments by Participation in Energy-Management Activity, 2002 1 Number of Establishments by Participation in Energy-Management Activity, 2002 Level: National Data; Row: Energy-Management Activities within NAICS Codes; Column: Participation and Source of Financial Support for Activity; Unit: Establishment Counts. RSE NAICS Row Code(a) Energy-Management Activity No Participation Participation(b) In-house Other Don't Know Factors Total United States RSE Column Factors: 0.9 1.4 0.9 0.9 1 311 - 339 ALL MANUFACTURING INDUSTRIES Participation in One or More of the Following Types of Activities 120,362 80,348 -- -- -- 1 Energy Audits 165,216 35,494 14,845 15,890 4,760 2.3 Direct Electricity Load Control 171,940 28,770 13,652 9,986 5,132 2.5 Special Rate Schedule (c)

207

table5.1_02  

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

End Uses of Fuel Consumption, 2002; End Uses of Fuel Consumption, 2002; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Fuel Oil Coal Net Residual and Natural LPG and (excluding Coal RSE NAICS Total Electricity(b) Fuel Oil Diesel Fuel(c) Gas(d) NGL(e) Coke and Breeze) Other(f) Row Code(a) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) (million short tons) (trillion Btu) Factors Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES RSE Column Factors: 0.3 1 1 2.4 1.1 1.4 1 NF TOTAL FUEL CONSUMPTION 16,273 832,257 33 24 5,641 26 53 6,006 3.4 Indirect Uses-Boiler Fuel -- 3,540 20 6

208

table7.10_02.xls  

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

0 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2002; 0 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: Million U.S. Dollars. Electricity Components Natural Gas Components Steam Components Electricity Natural Gas Steam Electricity from Sources Natural Gas from Sources Steam from Sources RSE NAICS Electricity from Local Other than Natural Gas from Local Other than Steam from Local Other than Row Code(a) Subsector and Industry Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Factors Total United States RSE Column Factors: 0.9 1 1.3 1 1.4

209

table1.5_02.xls  

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

5 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; 5 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National Data; Row: Energy Sources and Shipments, including Further Classification of 'Other' Energy Sources; Column: First Use per Energy Sources and Shipments; Unit: Trillion Btu. RSE Total Row Energy Source First Use Factors Total United States RSE Column Factor: 1.0 Coal 1,959 10.0 Natural Gas 6,468 1.3 Net Electricity 2,840 1.4 Purchases 2,882 1.4 Transfers In 35 2.6 Onsite Generation from Noncombustible Renewable Energy 8 1.5 Sales and Transfers Offsite 86 0.7 Coke and Breeze 385 1.7 Residual Fuel Oil 255 2.3 Distillate Fuel Oil 151 5.6 Liquefied Petroleum Gases and Natural Gas Liquids 3,070 0.6

210

table9.1_02.xls  

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

1 Enclosed Floorspace and Number of Establishment Buildings, 2002; 1 Enclosed Floorspace and Number of Establishment Buildings, 2002; Level: National Data; Row: NAICS Codes; Column: Floorspace and Buildings; Unit: Floorspace Square Footage and Building Counts. Approximate Approximate Average Enclosed Floorspace Average Number Number of All Buildings Enclosed Floorspace of All Buildings of Buildings Onsite RSE NAICS Onsite Establishments(b) per Establishment Onsite per Establishment Row Code(a) Subsector and Industry (million sq ft) (counts) (sq ft) (counts) (counts) Factors Total United States RSE Column Factors: 0 0 0 0 0 311 Food 751 15,089 102,589.2 26,438 3.0 0 311221 Wet Corn Milling 5 49 239,993.7 428 13.0 0 31131 Sugar 17 77 418,497.0 821 15.2 0

211

table5.3_02  

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

3 End Uses of Fuel Consumption, 2002; 3 End Uses of Fuel Consumption, 2002; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Net Demand Fuel Oil Coal for Residual and Natural LPG and (excluding Coal RSE NAICS Electricity(b) Fuel Oil Diesel Fuel(c) Gas(d) NGL(e) Coke and Breeze) Row Code(a) End Use (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) (million short tons) Factors Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES RSE Column Factors: NF 1 2.4 1.1 1.4 1 TOTAL FUEL CONSUMPTION 966,231 33 24 5,641 26 53 3.4 Indirect Uses-Boiler Fuel 6,714 20 6 2,105 2 35 5.3 Conventional Boiler Use

212

" Row: NAICS Codes; Column: Energy Sources;"  

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

2 Fuel Consumption, 2010;" 2 Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," ",," "," "," "," "," "," "," " " "," " "NAICS"," "," ","Net","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)"

213

" Row: NAICS Codes; Column: Energy Sources;"  

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

1 Fuel Consumption, 2010;" 1 Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",," "," "," "," "," "," "," " " "," ",,,,,,,,"Coke" " "," "," ","Net","Residual","Distillate","Natural Gas(d)","LPG and","Coal","and Breeze"," " "NAICS"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","NGL(e)","(million","(million","Other(f)"

214

" Row: NAICS Codes; Column: Energy Sources;"  

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

6 Quantity of Purchased Energy Sources, 2010;" 6 Quantity of Purchased Energy Sources, 2010;" " Level: National and Regional Data;" " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",," "," "," "," "," "," "," " " "," ",,,,,,,,"Coke" " "," "," ",,"Residual","Distillate","Natural Gas(c)","LPG and","Coal","and Breeze"," " "NAICS"," ","Total","Electricity","Fuel Oil","Fuel Oil(b)","(billion","NGL(d)","(million","(million","Other(e)"

215

Thermal Analysis for Ion-Exchange Column System  

Science Conference Proceedings (OSTI)

Models have been developed to simulate the thermal characteristics of crystalline silicotitanate ion exchange media fully loaded with radioactive cesium either in a column configuration or distributed within a waste storage tank. This work was conducted to support the design and operation of a waste treatment process focused on treating dissolved, high-sodium salt waste solutions for the removal of specific radionuclides. The ion exchange column will be installed inside a high level waste storage tank at the Savannah River Site. After cesium loading, the ion exchange media may be transferred to the waste tank floor for interim storage. Models were used to predict temperature profiles in these areas of the system where the cesium-loaded media is expected to lead to localized regions of elevated temperature due to radiolytic decay. Normal operating conditions and accident scenarios (including loss of solution flow, inadvertent drainage, and loss of active cooling) were evaluated for the ion exchange column using bounding conditions to establish the design safety basis. The modeling results demonstrate that the baseline design using one central and four outer cooling tubes provides a highly efficient cooling mechanism for reducing the maximum column temperature. In-tank modeling results revealed that an idealized hemispherical mound shape leads to the highest tank floor temperatures. In contrast, even large volumes of CST distributed in a flat layer with a cylindrical shape do not result in significant floor heating.

Lee, S.

2012-12-20T23:59:59.000Z

216

2005 ASHRAE. 109 Groundwater heat pump systems using standing column  

E-Print Network (OSTI)

©2005 ASHRAE. 109 ABSTRACT Groundwater heat pump systems using standing column wells Carl D. Orio Carl N. Johnson, PhD, PE Simon J. Rees, PhD Member ASHRAE Member ASHRAE Member ASHRAE A. Chiasson, PhD, PE Zheng Deng, PhD Jeffrey D. Spitler, PhD, PE Member ASHRAE Student Member ASHRAE Fellow

217

" Row: NAICS Codes; Column: Energy Sources;"  

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

1 Offsite-Produced Fuel Consumption, 2006;" 1 Offsite-Produced Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." " "," "," ",,,," "," "," ",," "," "," "," "," " " "," ",,,,,,,,,,,"Coke" " "," "," ",,,,"Residual","Distillate","Natural Gas(d)",,"LPG and","Coal","and Breeze"," " "NAICS"," ","Total",,"Electricity(b)",,"Fuel Oil","Fuel Oil(c)","(billion",,"NGL(e)","(million","(million","Other(f)"

218

THE VALVE-ACTUATED PULSE COLUMN DESIGN AND OPERATION  

SciTech Connect

A countercurrent extraction column is described which employs timed solenoid valves and pressurized feeds to provide a pulsing action to disperse the phases. The steps in the pulsing cycle are independent and thus provide greater separation of the operating variables than is possible with conventional pulse columns. The column described is particularly useful as a resesrch tool for the study of extraction mechanism although a larger installation operating on the same principles should be quite workable. The 4-stage-cycle or mixersettler type column operation has an inherent advantage in that the rapid coalescence and redispersion of phases are believed to lead to greater extraction than simple movement of a dispersed phase through a continuous medium. In addition, the sharp pulse provided should produce greater turbulence than the more conventional pulsing arrangement. Some results of operation on the extraction and stripping of uranyl nitrate using tributyl phosphate as a solvent are included. These data correspond to Metal Recovery and Erex type systems. (auth)

Burger, L.L.; Clark, L.H.

1951-12-01T23:59:59.000Z

219

Heat transfer investigations in a slurry bubble column  

SciTech Connect

Slurry bubble columns, for use in Fisher-Tropsch synthesis, have been investigated. Two bubble columns (0.108 and 0.305 m internal diameter) were set up and experiments were conducted to determine gas holdup and heat transfer coefficients. These columns were equipped with either single heat transfer probes of different diameters, or bundles of five-, seven- or thirty-seven tubes. The experiments were conducted for two- and three-phase systems; employing for gas phase: air and nitrogen, liquid phase: water and Therminol-66, and solid phase: red iron oxide (1.02, 1.70 and 2.38 {mu}m), glass beads (50.0, 90.0, 119.0 and 143.3 {mu}m), silica sand (65 {mu}), and magnetite (28.0, 35.7, 46.0, 58.0, 69.0, 90.5, 115.5, and 137.5 {mu}m). The column temperature was varied between 298--523 K, gas velocity between 0--40 cm/s, and solids concentration between 0--50 weight percent. The holdup and heat transfer data as a function of operating and system parameters were employed to assess the available correlations and semitheoretical models, and to develop new correlations. Information concerning the design and scale-up of larger units is presented. Specific research work that need to be undertaken to understand the phenomena of heat transfer and gas holdup is outlined so that efficient gas conversion and catalyst usage may be accomplished in slurry bubble columns. 130 refs., 177 figs., 54 tabs.

Saxena, S.C.; Rao, N.S.; Vadivel, R.; Shrivastav, S.; Saxena, A.C.; Patel, B.B.; Thimmapuram, P.R.; Kagzi, M.Y.; Khan, I.A.; Verma, A.K.

1991-02-01T23:59:59.000Z

220

Table 7.5 Average Prices of Selected Purchased Energy Sources, 2002  

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

5 Average Prices of Selected Purchased Energy Sources, 2002;" 5 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate","Natural ","LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

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


221

Table 2.2 Nonfuel (Feedstock) Use of Combustible Energy, 2002  

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

2 Nonfuel (Feedstock) Use of Combustible Energy, 2002;" 2 Nonfuel (Feedstock) Use of Combustible Energy, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,"RSE" "NAICS"," "," ","Residual","Distillate","Natural","LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","and Breeze","Other(e)","Factors"

222

" Row: End Uses within NAICS Codes;"  

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

2 End Uses of Fuel Consumption, 2002;" 2 End Uses of Fuel Consumption, 2002;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," "," ",," ","Distillate"," "," ",," "," " " "," ",,,,"Fuel Oil",,,"Coal",,"RSE" "NAICS"," "," ","Net","Residual","and","Natural ","LPG and","(excluding Coal"," ","Row" "Code(a)","End Use","Total","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Gas(d)","NGL(e)","Coke and Breeze)","Other(f)","Factors"

223

Table E13.1. Electricity: Components of Net Demand, 1998  

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

1. Electricity: Components of Net Demand, 1998;" 1. Electricity: Components of Net Demand, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Electricity Components;" " Unit: Million Kilowatthours." " ",," "," ",," " ,,,,"Sales and","Net Demand","RSE" "Economic",,,"Total Onsite","Transfers","for","Row" "Characteristic(a)","Purchases","Transfers In(b)","Generation(c)","Offsite","Electricity(d)","Factors" ,"Total United States"

224

" Row: End Uses;"  

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

8 End Uses of Fuel Consumption, 2002;" 8 End Uses of Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Trillion Btu." " ",," ","Distillate"," "," ",," " " ","Net Demand",,"Fuel Oil",,,"Coal","RSE" " ","for ","Residual","and","Natural ","LPG and","(excluding Coal","Row" "End Use","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Gas(c)","NGL(d)","Coke and Breeze)","Factors"

225

Table 7.9 Expenditures for Purchased Energy Sources, 2002  

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

9 Expenditures for Purchased Energy Sources, 2002;" 9 Expenditures for Purchased Energy Sources, 2002;" " Level: National and Regional Data;" " Row: NAICS Codes; Column: Energy Sources;" " Unit: Million U.S. Dollars." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,,"RSE" "NAICS"," "," ",,"Residual","Distillate","Natural ","LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","and Breeze","Other(e)","Factors"

226

Table 6.2 Consumption Ratios of Fuel, 2002  

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

2 Consumption Ratios of Fuel, 2002;" 2 Consumption Ratios of Fuel, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." ,,,"Consumption" " ",,"Consumption","per Dollar"," " " ","Consumption","per Dollar","of Value","RSE" "Economic","per Employee","of Value Added","of Shipments","Row" "Characteristic(a)","(million Btu)","(thousand Btu)","(thousand Btu)","Factors"

227

Table 2.3 Nonfuel (Feedstock) Use of Combustible Energy, 2002  

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

3 Nonfuel (Feedstock) Use of Combustible Energy, 2002;" 3 Nonfuel (Feedstock) Use of Combustible Energy, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," "," "," " " "," "," "," ",," "," ",," ","RSE" "Economic",,"Residual","Distillate","Natural ","LPG and",,"Coke and"," ","Row" "Characteristic(a)","Total","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Breeze","Other(e)","Factors"

228

" Row: End Uses within NAICS Codes;"  

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

2. End Uses of Fuel Consumption, 1998;" 2. End Uses of Fuel Consumption, 1998;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," "," ",," ","Distillate"," "," ",," "," " " "," ",,,,"Fuel Oil",,,"Coal",,"RSE" "NAICS"," "," ","Net","Residual","and",,"LPG and","(excluding Coal"," ","Row" "Code(a)","End Use","Total","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Natural Gas(d)","NGL(e)","Coke and Breeze)","Other(f)","Factors"

229

Table 7.4 Average Prices of Selected Purchased Energy Sources, 2002  

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

4 Average Prices of Selected Purchased Energy Sources, 2002;" 4 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Physical Units." " ",," "," ",," "," " ,,"Residual","Distillate","Natural ","LPG and",,"RSE" "Economic","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Row" "Characteristic(a)","(kWh)","(gallons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors"

230

" Row: Energy-Management Activities within NAICS Codes;"  

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

1 Number of Establishments by Participation in Energy-Management Activity, 2002;" 1 Number of Establishments by Participation in Energy-Management Activity, 2002;" " Level: National Data; " " Row: Energy-Management Activities within NAICS Codes;" " Column: Participation and Source of Financial Support for Activity;" " Unit: Establishment Counts." " "," "," ",,,,," " " "," ",,," Source of Financial Support for Activity",,,"RSE" "NAICS"," "," ",,,,,"Row" "Code(a)","Energy-Management Activity","No Participation","Participation(b)","In-house","Other","Don't Know","Factors"

231

" Row: Employment Sizes within NAICS Codes;"  

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

3. Consumption Ratios of Fuel, 1998;" 3. Consumption Ratios of Fuel, 1998;" " Level: National Data; " " Row: Employment Sizes within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." " "," ",,,"Consumption"," " " "," ",,"Consumption","per Dollar" " "," ","Consumption","per Dollar","of Value","RSE" "NAICS",,"per Employee","of Value Added","of Shipments","Row" "Code(a)","Economic Characteristic(b)","(million Btu)","(thousand Btu)","(thousand Btu)","Factors"

232

" Level: National Data;" " Row: NAICS Codes;"  

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

1 Number of Establishments with Capability to Switch Coal to Alternative Energy Sources, 2002;" 1 Number of Establishments with Capability to Switch Coal to Alternative Energy Sources, 2002;" " Level: National Data;" " Row: NAICS Codes;" " Column: Energy Sources;" " Unit: Establishment Counts." ,,"Coal(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,,"RSE" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,,"Row" "Code(a)","Subsector and Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel Oil","Fuel Oil","LPG","Other(f)","Factors"

233

Table E3.1. Fuel Consumption, 1998  

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

E3.1. Fuel Consumption, 1998;" E3.1. Fuel Consumption, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," "," "," "," " " "," ",," "," ",," "," ",," ","RSE" "Economic",,"Net","Residual","Distillate",,"LPG and",,"Coke and"," ","Row" "Characteristic(a)","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","Breeze","Other(f)","Factors"

234

"Table E8.1. Average Prices of Selected Purchased Energy Sources, 1998;"  

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

1. Average Prices of Selected Purchased Energy Sources, 1998;" 1. Average Prices of Selected Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Physical Units." " ",," "," ",," "," " ,,"Residual","Distillate",,"LPG and",,"RSE" "Economic","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Row" "Characteristic(a)","(kWh)","(gallons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors"

235

" Row: End Uses within NAICS Codes;"  

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

4 End Uses of Fuel Consumption, 2002;" 4 End Uses of Fuel Consumption, 2002;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," " " "," ","Net Demand",,"Fuel Oil",,,"Coal","RSE" "NAICS"," ","for ","Residual","and","Natural ","LPG and","(excluding Coal","Row" "Code(a)","End Use","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Gas(d)","NGL(e)","Coke and Breeze)","Factors"

236

" Row: Employment Sizes within NAICS Codes;"  

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

4 Consumption Ratios of Fuel, 2002;" 4 Consumption Ratios of Fuel, 2002;" " Level: National Data; " " Row: Employment Sizes within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." " "," ",,,"Consumption"," " " "," ",,"Consumption","per Dollar" " "," ","Consumption","per Dollar","of Value","RSE" "NAICS",,"per Employee","of Value Added","of Shipments","Row" "Code(a)","Economic Characteristic(b)","(million Btu)","(thousand Btu)","(thousand Btu)","Factors"

237

Table 4.3 Offsite-Produced Fuel Consumption, 2002  

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

3 Offsite-Produced Fuel Consumption, 2002;" 3 Offsite-Produced Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," "," "," "," " " "," ",," "," ",," "," ",," ","RSE" "Economic",,,"Residual","Distillate","Natural ","LPG and",,"Coke and"," ","Row" "Characteristic(a)","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Gas(d)","NGL(e)","Coal","Breeze","Other(f)","Factors"

238

"Table E8.2. Average Prices of Selected Purchased Energy Sources, 1998;"  

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

2. Average Prices of Selected Purchased Energy Sources, 1998;" 2. Average Prices of Selected Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate",,"LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

239

Using solvent extraction to process nitrate anion exchange column effluents  

SciTech Connect

Octyl(phenyl)-N,N-diisobutylcarbamoylmethylphosphine oxide (CMPO), a new organophosphorous extractant, and a new centrifugal mixer-settler both recently developed at Argonne were evaluated for their potential use in the recovery of actinides from nitrate anion exchange column effluents. The performance of the extractant was evaluated by measuring the extraction coefficient values as a function of acid and salt concentration. Additional performance parameters include extraction coefficient behavior as a function of the total metal concentration in the organic phase, and comparison of different stripping and organic scrubbing techniques. A simulated effluent stream was used to evaluate the performance of the centrifugal mixer-settlers by comparing experimental and calculated interstage concentration profiles. Both the CMPO extractant and the centrifugal mixer-settlers have potential for processing nitrate column effluents, particularly if the stripping behavior can be improved. Details of the proposed process are presented in the flowsheet and contactor design analyses.

Yarbro, S.L.

1987-10-01T23:59:59.000Z

240

Method of recovering adsorbed liquid compounds from molecular sieve columns  

DOE Patents (OSTI)

Molecularly adsorbed volatile liquid compounds are recovered from molecular sieve adsorbent columns by directionally applying microwave energy to the bed of the adsorbent to produce a mixed liquid-gas effluent. The gas portion of the effluent generates pressure within the bed to promote the discharge of the effluent from the column bottoms. Preferably the discharged liquid-gas effluent is collected in two to three separate fractions, the second or intermediate fraction having a substantially higher concentration of the desorbed compound than the first or third fractions. The desorption does not need to be assisted by passing a carrier gas through the bed or by applying reduced pressure to the outlet from the bed.

Burkholder, Harvey R. (Ames, IA); Fanslow, Glenn E. (Ames, IA)

1983-01-01T23:59:59.000Z

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


241

" Row: NAICS Codes; Column: Energy Sources;"  

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

3.4 Number of Establishments by Fuel Consumption, 2006;" 3.4 Number of Establishments by Fuel Consumption, 2006;" " Level: National Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Establishment Counts." " "," "," ",," "," "," "," "," "," "," ",," " " "," ","Any" "NAICS"," ","Energy","Net","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","and Breeze","Other(g)"

242

" Row: NAICS Codes; Column: Electricity Components;"  

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

1.1 Electricity: Components of Net Demand, 2010;" 1.1 Electricity: Components of Net Demand, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," " " "," ",,,"Total ","Sales and","Net Demand" "NAICS"," ",,"Transfers ","Onsite","Transfers","for" "Code(a)","Subsector and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)" ,,"Total United States" 311,"Food",75652,21,5666,347,80993

243

" Column: Energy-Consumption Ratios;"  

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

3 Consumption Ratios of Fuel, 2006;" 3 Consumption Ratios of Fuel, 2006;" " Level: National Data; " " Row: Values of Shipments within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." ,,,,"Consumption" ,,,"Consumption","per Dollar" ,,"Consumption","per Dollar","of Value" "NAICS",,"per Employee","of Value Added","of Shipments" "Code(a)","Economic Characteristic(b)","(million Btu)","(thousand Btu)","(thousand Btu)" ,,"Total United States" " 311 - 339","ALL MANUFACTURING INDUSTRIES"

244

" Row: NAICS Codes; Column: Energy Sources;"  

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

2.4 Number of Establishments by Nonfuel (Feedstock) Use of Combustible Energy, 2006;" 2.4 Number of Establishments by Nonfuel (Feedstock) Use of Combustible Energy, 2006;" " Level: National Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Establishment Counts." " "," "," "," "," "," "," "," "," "," ",," " " "," ","Any Combustible" "NAICS"," ","Energy","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Source(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)"

245

" Row: NAICS Codes; Column: Electricity Components;"  

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

1.1 Electricity: Components of Net Demand, 2006;" 1.1 Electricity: Components of Net Demand, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," " " "," ",,,"Total ","Sales and","Net Demand" "NAICS"," ",,"Transfers ","Onsite","Transfers","for" "Code(a)","Subsector and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)" ,,"Total United States" 311,"Food",73242,309,4563,111,78003

246

EXPERIMENTAL ION EXCHANGE COLUMN WITH SUPERLIG 639 AND SIMULANT FORMULATION  

SciTech Connect

SuperLig®639 ion exchange resin was tested as a retrieval mechanism for pertechnetate, through decontamination of a perrhenate spiked 5M Simple Average Na{sup +} Mass Based Simulant. Testing included batch contacts and a three-column ion exchange campaign. A decontamination of perrhenate exceeding 99% from the liquid feed was demonstrated. Analysis of the first formulation of a SBS/WESP simulant found unexpectedly low concentrations of soluble aluminum. Follow-on work will complete the formulation.

Morse, Megan; Nash, C.

2013-08-26T23:59:59.000Z

247

Engineered Barrier Systems Thermal-Hydraulic-Chemical Column Test Report  

SciTech Connect

The Engineered Barrier System (EBS) Thermal-Hydraulic-Chemical (THC) Column Tests provide data needed for model validation. The EBS Degradation, Flow, and Transport Process Modeling Report (PMR) will be based on supporting models for in-drift THC coupled processes, and the in-drift physical and chemical environment. These models describe the complex chemical interaction of EBS materials, including granular materials, with the thermal and hydrologic conditions that will be present in the repository emplacement drifts. Of particular interest are the coupled processes that result in mineral and salt dissolution/precipitation in the EBS environment. Test data are needed for thermal, hydrologic, and geochemical model validation and to support selection of introduced materials (CRWMS M&O 1999c). These column tests evaluated granular crushed tuff as potential invert ballast or backfill material, under accelerated thermal and hydrologic environments. The objectives of the THC column testing are to: (1) Characterize THC coupled processes that could affect performance of EBS components, particularly the magnitude of permeability reduction (increases or decreases), the nature of minerals produced, and chemical fractionation (i.e., concentrative separation of salts and minerals due to boiling-point elevation). (2) Generate data for validating THC predictive models that will support the EBS Degradation, Flow, and Transport PMR, Rev. 01.

W.E. Lowry

2001-12-13T23:59:59.000Z

248

A new warmstarting strategy for the primal-dual column generation ...  

E-Print Network (OSTI)

June 22, 2012. Keywords: interior point methods, warmstarting, column generation, linear programming, cutting stock problem. Abstract. This paper presents a ...

249

Estimation of seismic-induced demands on column splices with a neural network model  

Science Conference Proceedings (OSTI)

The current seismic design specification (AISC 341-05) requires that column splices in moment frames, when not made using complete joint penetration (CJP) welds, be designed to develop the flexural strength of the smaller connected column and the shear ... Keywords: Column splice, Neural network, Seismic design, Steel moment frame

Bulent Akbas; Jay Shen; Thomas A. Sabol

2011-12-01T23:59:59.000Z

250

THE COLUMN DENSITY VARIANCE-M{sub s} RELATIONSHIP  

SciTech Connect

Although there is a wealth of column density tracers for both the molecular and diffuse interstellar medium, there are few observational studies investigating the relationship between the density variance ({sigma}{sup 2}) and the sonic Mach number (M{sub s}). This is in part due to the fact that the {sigma}{sup 2}-M{sub s} relationship is derived, via MHD simulations, for the three-dimensional (3D) density variance only, which is not a direct observable. We investigate the utility of a 2D column density {sigma}{sub {Sigma}/{Sigma}0}{sup 2}-M{sub s} relationship using solenoidally driven isothermal MHD simulations and find that the best fit follows closely the form of the 3D density {sigma}{sub {rho}/{rho}0}{sup 2}-M{sub s} trend but includes a scaling parameter A such that {sigma}{sub ln({Sigma}/{Sigma}o)} = A x ln(1+b{sup 2} M{sub s}{sup 2}), where A = 0.11 and b = 1/3. This relation is consistent with the observational data reported for the Taurus and IC 5146 molecular clouds with b = 0.5 and A = 0.16, and b = 0.5 and A = 0.12, respectively. These results open up the possibility of using the 2D column density values of {sigma}{sup 2} for investigations of the relation between the sonic Mach number and the probability distribution function (PDF) variance in addition to existing PDF sonic Mach number relations.

Burkhart, Blakesley; Lazarian, A. [Astronomy Department, University of Wisconsin, Madison, 475 N. Charter St., WI 53706 (United States)

2012-08-10T23:59:59.000Z

251

" Row: NAICS Codes; Column: Energy Sources;"  

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

1 Fuel Consumption, 2006;" 1 Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." ,,,,,,,,,,,,"Coke" ,,,,"Net",,"Residual","Distillate","Natural Gas(d)",,"LPG and","Coal","and Breeze" "NAICS",,"Total",,"Electricity(b)",,"Fuel Oil","Fuel Oil(c)","(billion",,"NGL(e)","(million","(million","Other(f)" "Code(a)","Subsector and Industry","(trillion Btu)",,"(million kWh)",,"(million bbl)","(million bbl)","cu ft)",,"(million bbl)","short tons)","short tons)","(trillion Btu)"

252

" Row: NAICS Codes; Column: Energy Sources;"  

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

2 Fuel Consumption, 2006;" 2 Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." "NAICS",,,,"Net",,"Residual","Distillate",,,"LPG and",,,"Coke" "Code(a)","Subsector and Industry","Total",,"Electricity(b)",,"Fuel Oil","Fuel Oil(c)","Natural Gas(d)",,"NGL(e)",,"Coal","and Breeze","Other(f)" ,,"Total United States" 311,"Food",1186,,251,,26,16,635,,3,,147,1,107 3112," Grain and Oilseed Milling",317,,53,,2,1,118,,"*",,114,0,30

253

" Row: NAICS Codes; Column: Energy Sources;"  

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

1 Offsite-Produced Fuel Consumption, 2010;" 1 Offsite-Produced Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." ,,,,,,,,,"Coke" ,,,,"Residual","Distillate","Natural Gas(d)","LPG and","Coal","and Breeze" "NAICS",,"Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","NGL(e)","(million","(million","Other(f)" "Code(a)","Subsector and Industry","(trillion Btu)","(million kWh)","(million bbl)","(million bbl)","cu ft)","(million bbl)","short tons)","short tons)","(trillion Btu)"

254

" Row: NAICS Codes; Column: Energy Sources;"  

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

2 Offsite-Produced Fuel Consumption, 2010;" 2 Offsite-Produced Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." "NAICS",,,,"Residual","Distillate",,"LPG and",,"Coke" "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)" ,,"Total United States" 311,"Food",1113,258,12,22,579,5,182,2,54 3112," Grain and Oilseed Milling",346,57,"*",1,121,"*",126,0,41

255

" Row: NAICS Codes; Column: Energy Sources;"  

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

2 Offsite-Produced Fuel Consumption, 2006;" 2 Offsite-Produced Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." "NAICS",,,,,,"Residual","Distillate",,,"LPG and",,,"Coke" "Code(a)","Subsector and Industry","Total",,"Electricity(b)",,"Fuel Oil","Fuel Oil(c)","Natural Gas(d)",,"NGL(e)",,"Coal","and Breeze","Other(f)" ,,"Total United States" 311,"Food",1124,,251,,26,16,635,,3,,147,1,45 3112," Grain and Oilseed Milling",316,,53,,2,1,118,,"*",,114,0,28

256

Basic design and hydrodynamic analysis of three-column TLP and comparison with ISSC TLP  

E-Print Network (OSTI)

Three-column TLP is a new design variation of the common four-column TLP. The objective of this study is to find the hydrodynamic feasibility of the three-column TLP. This accomplished by comparing the three-column design to the ISSC TLP. The ISSC TLP is chosen as the parent TLP and the column diameter, distance between column centers, water depth, environment and pontoon dimensions are kept the same for the ISSC TLP. The initial design shows a satisfactory hydrodynamic characteristic set for the three-column. A detailed coupled analysis of the platform is done using Higher Order Boundary Element Application (HOBEM). The wave excitation forces, responses and average drift forces are computed for wave heading 0 degree and 30 degree. A non-linear quasi-static study is done for the tendons. The three-column design is compared with the four-column design and the comparison shows the two are hydrodynamically similar. Three-column TLP can be considered as a viable alternative for four-column TLP.

Sebastian, Abhilash

2000-01-01T23:59:59.000Z

257

AN ORIFICE PLATE PULSE COLUMN FOR LIQUID-LIQUID EXTRACTION (thesis)  

SciTech Connect

A study was made of the performance of an orifice plate pulse column which is essentially a spray column containing internal constrictions in the form of orifices. The chemical system studied was acetic acid-waterhexone, and the variables considered were pulse frequency, throughput, phase continuity, and direction of solute transfer. For comparison purposes, several runs were made with a conventional spray column. Curves are presented showing the effect of the column variables on the column efficiency (HTU). The trends observed are explained as being due principally to the competing effects of the area for mass transfer and back-mixing. Photographs of a typical column section show qualitatively the effect of the important column variables. (auth)

O' Brien, D.C.

1954-08-23T23:59:59.000Z

258

The Two-Column Aerosol Project (TCAP) Science Plan  

Science Conference Proceedings (OSTI)

The Two-Column Aerosol Project (TCAP) field campaign will provide a detailed set of observations with which to (1) perform radiative and cloud condensation nuclei (CCN) closure studies, (2) evaluate a new retrieval algorithm for aerosol optical depth (AOD) in the presence of clouds using passive remote sensing, (3) extend a previously developed technique to investigate aerosol indirect effects, and (4) evaluate the performance of a detailed regional-scale model and a more parameterized global-scale model in simulating particle activation and AOD associated with the aging of anthropogenic aerosols. To meet these science objectives, the Atmospheric Radiation Measurement (ARM) Climate Research Facility will deploy the ARM Mobile Facility (AMF) and the Mobile Aerosol Observing System (MAOS) on Cape Cod, Massachusetts, for a 12-month period starting in the summer of 2012 in order to quantify aerosol properties, radiation, and cloud characteristics at a location subject to both clear and cloudy conditions, and clean and polluted conditions. These observations will be supplemented by two aircraft intensive observation periods (IOPs), one in the summer and a second in the winter. Each IOP will deploy one, and possibly two, aircraft depending on available resources. The first aircraft will be equipped with a suite of in situ instrumentation to provide measurements of aerosol optical properties, particle composition and direct-beam irradiance. The second aircraft will fly directly over the first and use a multi-wavelength high spectral resolution lidar (HSRL) and scanning polarimeter to provide continuous optical and cloud properties in the column below.

Berkowitz, CM; Berg, LK; Cziczo, DJ; Flynn, CJ; Kassianov, EI; Fast, JD; Rasch, PJ; Shilling, JE; Zaveri, RA; Zelenyuk, A; Ferrare, RA; Hostetler, CA; Cairns, B; Russell, PB; Ervens, B

2011-07-27T23:59:59.000Z

259

Spatial and temporal variations of aerosols around Beijing in summer 2006: 2. Local and column aerosol optical properties  

SciTech Connect

Weather Research and Forecasting (WRF)-chem model calculations were conducted to study aerosol optical properties around Beijing, China, during the Campaign of Air Quality Research in Beijing and Surrounding Region 2006 (CAREBeijing-2006) period. In this paper, we interpret aerosol optical properties in terms of aerosol mass concentrations and their chemical compositions by linking model calculations with measurements. In general, model calculations reproduced observed features of spatial and temporal variations of various surface and column aerosol optical parameters in and around Beijing. Spatial and temporal variations of aerosol absorption, scattering, and extinction coefficient corresponded well to those of elemental carbon (primary aerosol), sulfate (secondary aerosol), and the total aerosol mass concentration, respectively. These results show that spatial and temporal variations of the absorption coefficient are controlled by local emissions (within 100 km around Beijing during the preceding 24 h), while those of the scattering coefficient are controlled by regional-scale emissions (within 500 km around Beijing during the preceding 3 days) under synoptic-scale meteorological conditions, as discussed in our previous study of aerosol mass concentration. Vertical profiles of aerosol extinction revealed that the contribution of secondary aerosols and their water uptake increased with altitude within the planetary boundary layer, leading to a considerable increase in column aerosol optical depth (AOD) around Beijing. These effects are the main factors causing differences in regional and temporal variations between particulate matter (PM) mass concentration at the surface and column AOD over a wide region in the northern part of the Great North China Plain.

Matsui, Hitoshi; Koike, Makoto; Kondo, Yutaka; Takegawa, Nobuyuki; Fast, Jerome D.; Poschl, U.; Garland, R. M.; Andreae, M. O.; Wiedensohler, A.; Sugimoto, N.; Zhu, T.

2010-11-23T23:59:59.000Z

260

COMPUTATIONAL AND EXPERIMENTAL MODELING OF SLURRY BUBBLE COLUMN REACTORS  

Science Conference Proceedings (OSTI)

The objective of this study was to develop a predictive experimentally verified computational fluid dynamics (CFD) model for gas-liquid-solid flow. A three dimensional transient computer code for the coupled Navier-Stokes equations for each phase was developed and is appended in this report. The principal input into the model is the viscosity of the particulate phase which was determined from a measurement of the random kinetic energy of the 800 micron glass beads and a Brookfield viscometer. The details are presented in the attached paper titled ''CFD Simulation of Flow and Turbulence in a Slurry Bubble Column''. This phase of the work is in press in a referred journal (AIChE Journal, 2002) and was presented at the Fourth International Conference on Multiphase Flow (ICMF 2001) in New Orleans, May 27-June 1, 2001 (Paper No. 909). The computed time averaged particle velocities and concentrations agree with Particle Image Velocimetry (PIV) measurements of velocities and concentrations, obtained using a combination of gamma-ray and X-ray densitometers, in a slurry bubble column, operated in the bubbly-coalesced fluidization regime with continuous flow of water. Both the experiment and the simulation show a down-flow of particles in the center of the column and up-flow near the walls and nearly uniform particle concentration. Normal and shear Reynolds stresses were constructed from the computed instantaneous particle velocities. The PIV measurement and the simulation produced instantaneous particle velocities. The PIV measurement and the simulation produced similar nearly flat horizontal profiles of turbulent kinetic energy of particles. To better understand turbulence we studied fluidization in a liquid-solid bed. This work was also presented at the Fourth International Conference on Multiphase Flow (ICMF 2001, Paper No. 910). To understand turbulence in risers, measurements were done in the IIT riser with 530 micron glass beads using a PIV technique. This report summarizes the measurements and simulations completed so far. This work will continue under the sponsorship of the National Science Foundation and Dow Corning Corporation. This phase of the work is part of the DOE/Industry/University Multiphase Fluid Dynamics Research Consortium. Optimization of the LaPorte pilot plant reactor was attempted by rearranging the heat exchangers. The paper accepted for presentation at the Sixth World Congress of Chemical Engineering, Melbourne, Australia, September 23-27, 2001 is a part of this report.

Paul C.K. Lam; Isaac K. Gamwo; Dimitri Gidaspow

2002-05-01T23:59:59.000Z

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


261

Small Column Ion Exchange Design and Safety Strategy  

SciTech Connect

Small Column Ion Exchange (SCIX) is a transformational technology originally developed by the Department of Energy (DOE) Environmental Management (EM-30) office and is now being deployed at the Savannah River Site (SRS) to significantly increase overall salt processing capacity and accelerate the Liquid Waste System life-cycle. The process combines strontium and actinide removal using Monosodium Titanate (MST), Rotary Microfiltration, and cesium removal using Crystalline Silicotitanate (CST, specifically UOP IONSIV{reg_sign}IE-911 ion exchanger) to create a low level waste stream to be disposed in grout and a high level waste stream to be vitrified. The process also includes preparation of the streams for disposal, e.g., grinding of the loaded CST material. These waste processing components are technically mature and flowsheet integration studies are being performed including glass formulations studies, application specific thermal modeling, and mixing studies. The deployment program includes design and fabrication of the Rotary Microfilter (RMF) assembly, ion-exchange columns (IXCs), and grinder module, utilizing an integrated system safety design approach. The design concept is to install the process inside an existing waste tank, Tank 41H. The process consists of a feed pump with a set of four RMFs, two IXCs, a media grinder, three Submersible Mixer Pumps (SMPs), and all supporting infrastructure including media receipt and preparation facilities. The design addresses MST mixing to achieve the required strontium and actinide removal and to prevent future retrieval problems. CST achieves very high cesium loadings (up to 1,100 curies per gallon (Ci/gal) bed volume). The design addresses the hazards associated with this material including heat management (in column and in-tank), as detailed in the thermal modeling. The CST must be size reduced for compatibility with downstream processes. The design addresses material transport into and out of the grinder and includes provisions for equipment maintenance including remote handling. The design includes a robust set of nuclear safety controls compliant with DOE Standard (STD)-1189, Integration of Safety into the Design Process. The controls cover explosions, spills, boiling, aerosolization, and criticality. Natural Phenomena Hazards (NPH) including seismic event, tornado/high wind, and wildland fire are considered. In addition, the SCIX process equipment was evaluated for impact to existing facility safety equipment including the waste tank itself. SCIX is an innovative program which leverages DOE's technology development capabilities to provide a basis for a successful field deployment.

Huff, T.; Rios-Armstrong, M.; Edwards, R.; Herman, D.

2011-02-07T23:59:59.000Z

262

Dependence of Gas Phase Abundances in the ISM on Column Density  

E-Print Network (OSTI)

Sightlines through high- and intermediate-velocity clouds allow measurements of ionic gas phase abundances, A, at very low values of HI column density, N(HI). Present observations cover over 4 orders of magnitude in N(HI). Remarkably, for several ions we find that the A vs N(HI) relation is the same at high and low column density and that the abundances have a relatively low dispersion (factors of 2-3) at any particular N(HI). Halo gas tends to have slightly higher values of A than disk gas at the same N(HI), suggesting that part of the dispersion may be attributed to the environment. We note that the dispersion is largest for NaI; using NaI as a predictor of N(HI) can lead to large errors. Important implications of the low dispersions regarding the physical nature of the ISM are: (a) because of clumping, over sufficiently long pathlengths N(HI) is a reasonable measure of the_local_ density of_most_ of the H atoms along the sight line; (b) the destruction of grains does not mainly take place in catastrophic events such as strong shocks, but is a continuous function of the mean density; (c) the cycling of the ions becoming attached to grains and being detached must be rapid, and the two rates must be roughly equal under a wide variety of conditions; (d) in gas that has a low average density the attachment should occur within denser concentrations.

B. P. Wakker; J. S. Mathis

2000-10-02T23:59:59.000Z

263

appl_household2001.pdf  

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

9a. Appliances by Northeast Census Region, 9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1 .............................................................. 95.2 18.2 13.3 4.9 1.1 2 or More ................................................. 6.5 1.4 1.1 0.3 11.7 Most Used Oven ...................................... 101.7 19.6 14.5 5.2 1.1 Electric .....................................................

264

spaceheat_household2001.pdf  

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

1a. Space Heating by South Census Region, 1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home ....................................... 1.0 Q Q Q Q 20.1 No Heating Equipment ................................ 0.5 Q Q Q Q 39.8 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q Q 39.0 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0

265

spaceheat_household2001.pdf  

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

9a. Space Heating by Northeast Census Region, 9a. Space Heating by Northeast Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 20.3 14.8 5.4 NE Heat Home .................................................... 106.0 20.1 14.7 5.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.9 No Heating Equipment ................................ 0.5 Q Q Q 39.5 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.7 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 20.1 14.7 5.4 NE Natural Gas .................................................

266

Table A52. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" 2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" " Categories and Presence of General Technologies and Cogeneration Technologies, 1994" " (Estimates in Trillion Btu)" ,,,,"Employment Size(a)" ,,,,,,,,"RSE" ,,,,,,,"1000 and","Row" "General/Cogeneration Technologies","Total","Under 50","50-99","100-249","250-499","500-999","Over","Factors" "RSE Column Factors:",0.5,2,2.1,1,0.7,0.7,0.9 "One or More General Technologies Present",14601,387,781,2054,2728,3189,5462,3.1 " Computer Control of Building Environment (b)",5079,64,116,510,802,1227,2361,5

267

Table HC1-10a. Housing Unit Characteristics by Midwest Census Region,  

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

0a. Housing Unit Characteristics by Midwest Census Region, 0a. Housing Unit Characteristics by Midwest Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.8 Total .............................................................. 107.0 24.5 17.1 7.4 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- NF New England ............................................. 5.4 -- -- -- NF Middle Atlantic ........................................... 14.8 -- -- -- NF Midwest ....................................................... 24.5 24.5 17.1 7.4 NF East North Central ..................................... 17.1 17.1

268

char_household2001.pdf  

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

2a. Household Characteristics by West Census Region, 2a. Household Characteristics by West Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.8 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Household Size 1 Person ...................................................... 28.2 5.6 1.8 3.8 5.4 2 Persons .................................................... 35.1 7.3 1.9 5.5 4.9 3 Persons .................................................... 17.0 3.5 0.9 2.6 7.6 4 Persons .................................................... 15.6 3.5 1.1 2.4 6.4 5 Persons .................................................... 7.1 2.0 0.6 1.4 9.7 6 or More Persons

269

spaceheat_household2001.pdf  

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

0a. Space Heating by Midwest Census Region, 0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No Heating Equipment ................................ 0.5 Q Q Q 39.2 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.4 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 24.5 17.1 7.4 NE Natural Gas

270

homeoffice_household2001.pdf  

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

0a. Home Office Equipment by Midwest Census Region, 0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0 14.1 9.9 4.2 3.7 Number of Desktop PCs 1 ................................................................ 45.1 10.4 7.2 3.2 3.7 2 or more ................................................... 9.1 2.3 1.6 0.7 10.1 Number of Laptop PCs 1 ................................................................

271

S:\VM3\RX97\TBL_LIST.WPD  

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

b. Housing Unit Characteristics by Four Most Populated States, b. Housing Unit Characteristics by Four Most Populated States, Percent of U.S. Households, 1997 Housing Unit Characteristics RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.1 1.2 1.7 Total .............................................................. 100.0 100.0 100.0 100.0 100.0 0.0 Census Region and Division Northeast ..................................................... 19.4 100.0 -- -- -- NF New England ............................................. 5.2 Q -- -- -- NF Middle Atlantic ........................................... 14.2 100.0 -- -- -- NF Midwest ....................................................... 23.7 -- -- -- -- NF East North Central ..................................... 16.7 --

272

spaceheat_household2001.pdf  

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

2a. Space Heating by West Census Region, 2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment ................................ 0.5 0.4 Q 0.4 18.1 Have Equipment But Do Not Use It ............................................... 0.4 0.2 Q 0.2 27.5 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 22.6 6.7 15.9 NE Natural Gas .................................................

273

appl_household2001.pdf  

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

2a. Appliances by West Census Region, 2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1 .............................................................. 95.2 20.9 6.4 14.5 1.1 2 or More ................................................. 6.5 1.2 0.2 1.0 14.6 Most Used Oven ...................................... 101.7 22.1 6.6 15.5 1.1 Electric .....................................................

274

Manufacturing Consumption of Energy 1994  

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

A24. A24. Total Inputs of Energy for Heat, Power, and Electricity Generation by Program Sponsorship, Industry Group, Selected Industries, and Type of Energy- Management Program, 1994: Part 1 (Estimates in Trillion Btu) See footnotes at end of table. Energy Information Administration/Manufacturing Consumption of Energy 1994 285 SIC Management Any Type of Sponsored Self-Sponsored Sponsored Sponsored Code Industry Group and Industry Program Sponsorship Involvement Involvement Involvement Involvement a No Energy Electric Utility Government Third Party Type of Sponsorship of Management Programs (1992 through 1994) RSE Row Factors Federal, State, or Local RSE Column Factors: 0.7 1.1 1.0 0.7 1.9 0.9 20-39 ALL INDUSTRY GROUPS Participation in One or More of the Following Types of Programs . .

275

Manufacturing Consumption of Energy 1994  

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

A9. A9. Total Inputs of Energy for Heat, Power, and Electricity Generation by Fuel Type, Census Region, and End Use, 1994: Part 1 (Estimates in Btu or Physical Units) See footnotes at end of table. Energy Information Administration/Manufacturing Consumption of Energy 1994 166 End-Use Categories (trillion Btu) kWh) (1000 bbl) (1000 bbl) cu ft) (1000 bbl) tons) (trillion Btu) Total (million Fuel Oil Diesel Fuel (billion LPG (1000 short Other Net Distillate Natural and Electricity Residual Fuel Oil and Gas Breeze) a b c Coal (excluding Coal Coke d RSE Row Factors Total United States RSE Column Factors: NF 0.5 1.3 1.4 0.8 1.2 1.2 NF TOTAL INPUTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16,515 778,335 70,111 26,107 5,962 25,949 54,143 5,828 2.7 Indirect Uses-Boiler Fuel . . . . . . . . . . . . . . . . . . . . . . . --

276

homeoffice_household2001.pdf  

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

9a. Home Office Equipment by Northeast Census Region, 9a. Home Office Equipment by Northeast Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total .............................................................. 107.0 20.3 14.8 5.4 NE Households Using Office Equipment ......................................... 96.2 17.9 12.8 5.0 1.3 Personal Computers 1 ................................. 60.0 10.9 7.7 3.3 3.1 Number of Desktop PCs 1 ................................................................ 45.1 8.7 6.2 2.5 3.7 2 or more ................................................... 9.1 1.4 0.9 0.5 12.9 Number of Laptop PCs 1 ................................................................

277

Table HC1-9a. Housing Unit Characteristics by Northeast Census Region,  

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

9a. Housing Unit Characteristics by Northeast Census Region, 9a. Housing Unit Characteristics by Northeast Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Census Region and Division Northeast ..................................................... 20.3 20.3 14.8 5.4 NF New England ............................................. 5.4 5.4 Q 5.4 NF Middle Atlantic ........................................... 14.8 14.8 14.8 Q NF Midwest ....................................................... 24.5 -- -- -- NF East North Central ..................................... 17.1 -- -- -- NF

278

S:\VM3\RX97\TBL_LIST.WPD [PFP#201331587]  

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

b. Usage Indicators by Four Most Populated States, b. Usage Indicators by Four Most Populated States, Percent of U.S. Households, 1997 Usage Indicators RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.2 1.1 1.3 1.5 Total .............................................................. 100.0 100.0 100.0 100.0 100.0 0.0 Weekday Home Activities Home Used for Business Yes ............................................................ 7.2 7.4 7.5 6.0 6.4 13.5 No .............................................................. 92.8 92.6 92.5 94.0 93.6 2.2 Energy-Intensive Activity Yes ............................................................ 2.4 Q 3.2 2.1 Q 26.0 No .............................................................. 97.6 98.3 96.8 97.9 97.1 1.5

279

char_household2001.pdf  

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

0a. Household Characteristics by Midwest Census Region, 0a. Household Characteristics by Midwest Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 24.5 17.1 7.4 NE Household Size 1 Person ...................................................... 28.2 6.7 4.7 2.0 6.2 2 Persons .................................................... 35.1 8.0 5.4 2.6 5.0 3 Persons .................................................... 17.0 3.8 2.7 1.1 7.9 4 Persons .................................................... 15.6 3.5 2.5 1.0 8.1 5 Persons .................................................... 7.1 1.7

280

S:\VM3\RX97\TBL_LIST.WPD [PFP#201331587]  

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

Million U.S. Households, 1997 Usage Indicators RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.2 1.1 1.3 1.5 Total .............................................................. 101.5 6.8 11.5 7.0 5.9 NF Weekday Home Activities Home Used for Business Yes ............................................................ 7.4 0.5 0.9 0.4 0.4 13.5 No .............................................................. 94.1 6.3 10.6 6.5 5.6 2.2 Energy-Intensive Activity Yes ............................................................ 2.4 Q 0.4 0.1 Q 26.0 No .............................................................. 99.1 6.7 11.1 6.8 5.8 1.5 Someone Home All Day Yes ............................................................

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


281

Manufacturing Consumption of Energy 1994  

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

0. 0. Number of Establishments that Actually Switched Fuels from Natural Gas to Residual Fuel Oil, by Industry Group and Selected Industries, 1994 369 Energy Information Administration/Manufacturing Consumption of Energy 1994 SIC Residual Fuel Oil Total Code Industry Group and Industry (billion cu ft) Factors (counts) (counts) (percents) (counts) (percents) a Natural Gas Switchable to Establishments RSE Row Able to Switch Actually Switched RSE Column Factors: 1.3 0.1 1.4 1.7 1.6 1.8 20 Food and Kindred Products . . . . . . . . . . . . . . . . . . . . . . . . . 81 14,698 702 4.8 262 1.8 5.6 2011 Meat Packing Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 759 23 3.0 10 1.3 9.0 2033 Canned Fruits and Vegetables . . . . . . . . . . . . . . . . . . . . . 9 531 112 21.2 33 6.2 11.6 2037 Frozen Fruits and Vegetables . . . . . . . . . . . . . . . . . . . . . . 5 232 Q 5.3

282

Level: National Data; Row: NAICS Codes; Column: Energy Sources;  

Gasoline and Diesel Fuel Update (EIA)

Next MECS will be fielded in 2015 Table 3.4 Number of Establishments by Fuel Consumption, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Any NAICS Energy Net Residual Distillate LPG and Coke Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal and Breeze Other(g) Total United States 311 Food 13,269 13,265 144 2,416 10,373 4,039 64 7 1,538 3112 Grain and Oilseed Milling 602 602 9 204 489 268 30 0 140 311221 Wet Corn Milling 59 59 W 28 50 36 15 0 29 31131 Sugar Manufacturing 73 73 3 36 67 12 W 7 14 3114 Fruit and Vegetable Preserving and Specialty Foods 987 987 17 207 839 503 W 0 210 3115 Dairy Products 998 998 12 217 908

283

Level: National Data; Row: NAICS Codes; Column: Floorspace and Buildings;  

Gasoline and Diesel Fuel Update (EIA)

9.1 Enclosed Floorspace and Number of Establishment Buildings, 2010; 9.1 Enclosed Floorspace and Number of Establishment Buildings, 2010; Level: National Data; Row: NAICS Codes; Column: Floorspace and Buildings; Unit: Floorspace Square Footage and Building Counts. Approximate Approximate Average Enclosed Floorspace Average Number Number of All Buildings Enclosed Floorspace of All Buildings of Buildings Onsite NAICS Onsite Establishments(b) per Establishment Onsite per Establishment Code(a) Subsector and Industry (million sq ft) (counts) (sq ft) (counts) (counts) Total United States 311 Food 1,115 13,271 107,293.7 32,953 3.1 3112 Grain and Oilseed Milling 126 602 443,178.6 5,207 24.8 311221 Wet Corn Milling 14 59 270,262.7 982 18.3 31131 Sugar Manufacturing

284

COMPUTATIONAL AND EXPERIMENTAL MODELING OF SLURRY BUBBLE COLUMN REACTORS  

SciTech Connect

The objective if this study was to develop a predictive experimentally verified computational fluid dynamics (CFD) model for gas-liquid-solid flow. A three dimensional transient computer code for the coupled Navier-Stokes equations for each phase was developed. The principal input into the model is the viscosity of the particulate phase which was determined from a measurement of the random kinetic energy of the 800 micron glass beads and a Brookfield viscometer. The computed time averaged particle velocities and concentrations agree with PIV measurements of velocities and concentrations, obtained using a combination of gamma-ray and X-ray densitometers, in a slurry bubble column, operated in the bubbly-coalesced fluidization regime with continuous flow of water. Both the experiment and the simulation show a down-flow of particles in the center of the column and up-flow near the walls and nearly uniform particle concentration. Normal and shear Reynolds stresses were constructed from the computed instantaneous particle velocities. The PIV measurement and the simulation produced instantaneous particle velocities. The PIV measurement and the simulation produced similar nearly flat horizontal profiles of turbulent kinetic energy of particles. This phase of the work was presented at the Chemical Reaction Engineering VIII: Computational Fluid Dynamics, August 6-11, 2000 in Quebec City, Canada. To understand turbulence in risers, measurements were done in the IIT riser with 530 micron glass beads using a PIV technique. The results together with simulations will be presented at the annual meeting of AIChE in November 2000.

Paul Lam; Dimitri Gidaspow

2000-09-01T23:59:59.000Z

285

Small Column Ion Exchange at Savannah River Site Technology Readiness Assessment Report  

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

Small Column Ion Exchange Technology at Small Column Ion Exchange Technology at Savannah River Site U.S. Department of Energy Office of Environmental Management Office of Technology Innovation and Development Technology Readiness Assessment Report November 2011 U.S. DOE-EM Office of Technology Innovation and Development November 11, 2011 Small Column Ion Exchange Program Technology Readiness Assessment Page 2 of 112 This page intentionally left blank November 11, 2011 U.S. DOE-EM Office of Technology Innovation and Development Small Column Ion Exchange Program Technology Readiness Assessment Page 3 of 112 APPROVALS ________________________ _ Harry D. Harmon Date

286

Modeling of FRP-jacketed RC columns subject to combined axial and lateral loads  

E-Print Network (OSTI)

Prisms Strengthened Using Carbon Fiber Reinforced PolymerStrengthening Effects with Carbon Fiber Sheet for ConcreteColumns with Continuous Carbon Fiber Jackets: Volume II,

Lee, Chung-Sheng

2006-01-01T23:59:59.000Z

287

Insitu expanding foam based carbon/epoxy sandwich jackets for column retrofit  

E-Print Network (OSTI)

RC Columns with Continuous Carbon Fiber Jackets, Journal ofC. Pantelides, J. Gergely, Carbon Fiber Reinforced Polymerand processing type (i.e. carbon fiber reinforced epoxy with

Danyeur, Alicia

2008-01-01T23:59:59.000Z

288

A new warmstarting strategy for the primal-dual column generation ...  

E-Print Network (OSTI)

Jun 24, 2012 ... Abstract: This paper presents a new warmstarting technique in the context of a primal-dual column generation method applied to solve a ...

289

Development of a Fuzzy Logic Controller for a Distillation Column using Rockwell Software.  

E-Print Network (OSTI)

??In this thesis, an alternative control method based on Fuzzy Inference System (FIS) is proposed to keep the product composition of a distillation column constant.… (more)

Nizami, Muhammad

2011-01-01T23:59:59.000Z

290

2005 RSE's - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

Eileen O'Brien Eileen.O'Brien@eia.doe.gov Survey Manager Phone: (202) 586-1122 FAX: (202) 586-0018 ...

291

DUST EXTINCTION BIAS IN THE COLUMN DENSITY DISTRIBUTION OF GAMMA-RAY BURSTS: HIGH COLUMN DENSITY, LOW-REDSHIFT GRBs ARE MORE HEAVILY OBSCURED  

SciTech Connect

The afterglows of gamma-ray bursts (GRBs) have more soft-X-ray absorption than expected from the foreground gas column in the Galaxy. While the redshift of the absorption can in general not be constrained from current X-ray observations, it has been assumed that the absorption is due to metals in the host galaxy of the GRB. The large sample of X-ray afterglows and redshifts now available allows the construction of statistically meaningful distributions of the metal column densities. We construct such a sample and show, as found in previous studies, that the typical absorbing column density (N{sub H{sub X}}) increases substantially with redshift, with few high column density objects found at low-to-moderate redshifts. We show, however, that when highly extinguished bursts are included in the sample, using redshifts from their host galaxies, high column density sources are also found at low-to-moderate redshift. We infer from individual objects in the sample and from observations of blazars that the increase in column density with redshift is unlikely to be related to metals in the intergalactic medium or intervening absorbers. Instead we show that the origin of the apparent increase with redshift is primarily due to dust extinction bias: GRBs with high X-ray absorption column densities found at z {approx}< 4 typically have very high dust extinction column densities, while those found at the highest redshifts do not. It is unclear how such a strongly evolving N{sub H{sub X}}/A{sub V} ratio would arise, and based on current data, remains a puzzle.

Watson, Darach [Dark Cosmology Centre, Niels Bohr Institute, University of Copenhagen, Juliane Maries Vej 30, DK-2100 Copenhagen O (Denmark); Jakobsson, Pall, E-mail: darach@dark-cosmology.dk, E-mail: pja@raunvis.hi.is [Centre for Astrophysics and Cosmology, Science Institute, University of Iceland, Dunhaga 5, IS-107 Reykjavik (Iceland)

2012-08-01T23:59:59.000Z

292

Level: National Data; Row: NAICS Codes; Column: Energy Sources  

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

3.4 Number of Establishments by Fuel Consumption, 2006; 3.4 Number of Establishments by Fuel Consumption, 2006; Level: National Data; Row: NAICS Codes; Column: Energy Sources Unit: Establishment Counts. Any NAICS Energy Net Residual Distillate LPG and Coke Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal and Breeze Other(g) Total United States 311 Food 14,128 14,113 326 1,462 11,395 2,920 67 13 1,240 3112 Grain and Oilseed Milling 580 580 15 174 445 269 35 0 148 311221 Wet Corn Milling 47 47 W 17 44 19 18 0 18 31131 Sugar Manufacturing 78 78 11 43 61 35 26 13 45 3114 Fruit and Vegetable Preserving and Specialty Food 1,125 1,125 13 112 961 325 W 0 127 3115 Dairy Product 1,044 1,044 25 88 941 147 W 0 104 3116 Animal Slaughtering and Processing

293

Level: National Data; Row: NAICS Codes; Column: Energy Sources;  

Gasoline and Diesel Fuel Update (EIA)

4.4 Number of Establishments by Offsite-Produced Fuel Consumption, 2010; 4.4 Number of Establishments by Offsite-Produced Fuel Consumption, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Any NAICS Energy Residual Distillate LPG and Coke Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal and Breeze Other(g) Total United States 311 Food 13,269 13,265 144 2,413 10,373 4,039 64 W 1,496 3112 Grain and Oilseed Milling 602 602 9 201 489 268 30 0 137 311221 Wet Corn Milling 59 59 W 26 50 36 15 0 28 31131 Sugar Manufacturing 73 73 3 36 67 12 11 W 11 3114 Fruit and Vegetable Preserving and Specialty Foods 987 987 17 207 839 503 W 0 207 3115 Dairy Products 998 998 12 217 908 161 W 0 79 3116 Animal Slaughtering and Processing

294

Cometabolic degradation of trichloroethylene in a bubble column bioscrubber  

SciTech Connect

A bubble column bioreactor was used as bioscrubber to carry out a feasibility study for the cometabolic degradation of trichloroethylene (TCE). Phenol was used as cosubstrate and inducer. The bioreactor was operated like a conventional chemostat with regard to the cosubstrate and low dilution rates were used to minimize the liquid outflow. TCE degradation measurements were carried out using superficial gas velocities between 0.47 and 4.07 cm s{sup {minus}1} and TCE gas phase loads between 0.07 and 0.40 mg L{sup {minus}1}. Depending on the superficial gas velocity used, degrees of conversion between 30% and 80% were obtained. A simplified reactor model using plug flow for the gas phase, mixed flow for the liquid phase, and pseudo first order reaction kinetics for the conversion of TCE was established. The model is able to give a reasonable approximation of the experimental data. TCE degradation at the used experimental conditions is mainly limited by reaction rate rather than by mass transfer rate. The model can be used to calculate the reactor value and the biomass concentration for a required conversion.

Hecht, V.; Brebbermann, D.; Bremer, P.; Deckwer, W.D. [Bereich Bioverfahrenstechnik, Braunschweig (Germany). Gesellschaft fuer Biotechnologische Forschung mbH

1995-08-20T23:59:59.000Z

295

Experimental characterization of slurry bubble-column reactor hydrodynamics  

DOE Green Energy (OSTI)

Sandia`s program to develop, implement, and apply diagnostics for hydrodynamic characterization of slurry bubble column reactors (SBCRs) at industrially relevant conditions is discussed. Gas liquid flow experiments are performed on an industrial scale. Gamma densitometry tomography (GDT) is applied to measure radial variations in gas holdup at one axial location. Differential pressure (DP) measurements are used to calculate volume averaged gas holdups along the axis of the vessel. The holdups obtained from DP show negligible axial variation for water but significant variations for oil, suggesting that the air water flow is fully developed (minimal flow variations in the axial direction) but that the air oil flow is still developing at the GDT measurement location. The GDT and DP gas holdup results are in good agreement for the air water flow but not for the air oil flow. Strong flow variations in the axial direction may be impacting the accuracy of one or both of these techniques. DP measurements are also acquired at high sampling frequencies (250 Hz) and are interpreted using statistical analyses to determine the physical mechanism producing each frequency component in the flow. This approach did not yield the information needed to determine the flow regime in these experiments. As a first step toward three phase material distribution measurements, electrical impedance tomography (EIT) and GDT are applied to a liquid solid flow to measure solids holdup. Good agreement is observed between both techniques and known values.

Shollenberger, K.A.; Torczynski, J.R.; Jackson, N.B.; O`Hern, T.J.

1997-09-01T23:59:59.000Z

296

CBECS 1992 - Building Characteristics, Detailed Tables  

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

Detailed Tables Detailed Tables Detailed Tables Percent of Buildings and Floorspace by Census Region, 1992 Percent of Buildings and Floorspace by Census Region, 1992 The following 70 tables present extensive cross-tabulations of commercial buildings characteristics. These data are from the Buildings Characteristics Survey portion of the 1992 CBECS. The "Quick-Reference Guide," indicates the major topics of each table. Directions for calculating an approximate relative standard error (RSE) for each estimate in the tables are presented in Figure A1, "Use of RSE Row and Column Factor." The Glossary contains the definitions of the terms used in the tables. See the preceding "At A Glance" section for highlights of the detailed tables. Table Organization

297

Column Studies of Anaerobic Carbon Tetrachloride Biotransformation with Hanford Aquifer Material  

E-Print Network (OSTI)

on CT transformations in Hanford soil. This work assessed the potential for in situ CT biotransColumn Studies of Anaerobic Carbon Tetrachloride Biotransformation with Hanford Aquifer Material a column reactor system containing Hanford Aquifer material in order to assess the potential of in situ

Semprini, Lewis

298

THE POWER SUPPLY SYSTEM FOR THE ACCELERATING COLUMN OF THE 2 MEV ELECTRON COOLER FOR COSY  

E-Print Network (OSTI)

filter, and various power supplies for these elements. The cascade transformer is to provide a requiredTHE POWER SUPPLY SYSTEM FOR THE ACCELERATING COLUMN OF THE 2 MEV ELECTRON COOLER FOR COSY D a high-energy electron beam. The power supply for the accelerating column of the electron cooling system

Kozak, Victor R.

299

Optimal Allocation of Heat Exchanger Inventory in a Serial Type Diabatic Distillation Column  

E-Print Network (OSTI)

Optimal Allocation of Heat Exchanger Inventory in a Serial Type Diabatic Distillation Column Edward the column . We have previously shown (Jimenez et al. 2003) that optimaloperation of serial heat exchangers total heat exchanger area in different trays and calculate the optimal allocation of a given heat

Salamon, Peter

300

Flexural buckling load prediction of aluminium alloy columns using soft computing techniques  

Science Conference Proceedings (OSTI)

This paper presents the application of soft computing techniques for strength prediction of heat-treated extruded aluminium alloy columns failing by flexural buckling. Neural networks (NN) and genetic programming (GP) are presented as soft computing ... Keywords: Aluminium alloy columns, Flexural buckling, Genetic programming, Neural networks, Soft computing

Abdulkadir Cevik; Nihat Atmaca; Talha Ekmekyapar; Ibrahim H. Guzelbey

2009-04-01T23:59:59.000Z

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


301

Control of absorption columns in the bioethanol process: Influence of measurement uncertainties  

Science Conference Proceedings (OSTI)

The alcohol lost by evaporation during the bioethanol fermentation process may be collected and recovered using an absorption column. This equipment is also used in the carbonic gas treatment, a by-product from the sugar cane fermentation. In the present ... Keywords: Absorption column, Artificial neural network control, Bioethanol, Concentration measurement uncertainty, Fermentation

Eduardo Eyng; Ana M. F. Fileti

2010-03-01T23:59:59.000Z

302

Brief paper: Self-tuning regulator applied to a binary distillation column  

Science Conference Proceedings (OSTI)

Utilization of a self-tuning regulator (STR) for control of top product composition of a binary distillation column has been investigated. Results from simulation studies and experimental evaluation of the STR on a pilot scale column are compared with ... Keywords: Adaptive control, chemical variables control, computer control, control engineering computer applications, petro-chemical control, self-adjusting systems, stochastic control

V. A. Sastry; D. E. Seborg; R. K. Wood

1977-07-01T23:59:59.000Z

303

Small scale ethanol production demonstration: comparison of packed versus plate rectifying column  

DOE Green Energy (OSTI)

The Johnson Environmental and Energy Center with assistance from the Madison County Farm Bureau Association received a grant in 1980 from the US Department of Energy to design, fabricate, and evaluate a small scale continuous ethanol plant. In 1981, the Center received a second DOE grant to compare the economics of replacing the plate rectifying column in the initial unit with a packed rectifying column. The results of the study indicate that the distillation unit with the packed rectifying column is capable of producing 14 gallons per hour of 170 proof ethanol. The energy ratio for distillation was a positive 2:1. Cost of the packed column was considerably less than the plate column. 1 reference, 19 figures, 9 tables.

Adcock, II, L E; Eley, M H; Schroer, B J

1982-07-01T23:59:59.000Z

304

ROTARY FILTER FINES TESTING FOR SMALL COLUMN ION EXCHANGE  

SciTech Connect

SRNL was requested to quantify the amount of 'fines passage' through the 0.5 micron membranes currently used for the rotary microfilter (RMF). Testing was also completed to determine if there is any additional benefit to utilizing a 0.1 micron filter to reduce the amount of fines that could pass through the filter. Quantifying of the amount of fines that passed through the two sets of membranes that were tested was accomplished by analyzing the filtrate by Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES) for titanium. Even with preparations to isolate the titanium, all samples returned results of less than the instrument's detection limit of 0.184 mg/L. Test results show that the 0.5 micron filters produced a significantly higher flux while showing a negligible difference in filtrate clarity measured by turbidity. The first targeted deployment of the RMF is with the Small Column Ion Exchange (SCIX) at the Savannah River Site (SRS). SCIX uses crystalline silicotitanate (CST) to sorb cesium to decontaminate a clarified salt solution. The passage of fine particles through the filter membranes in sufficient quantities has the potential to impact the downstream facilities. To determine the amount of fines passage, a contract was established with SpinTek Filtration to operate a 3-disk pilot scale unit with prototypic filter disk and various feeds and two different filter disk membranes. SpinTek evaluated a set of the baseline 0.5 micron filter disks as well as a set of 0.1 micron filter disks to determine the amount of fine particles that would pass the membrane and to determine the flux each set produced. The membrane on both disk sets is manufactured by the Pall Corporation (PMM 050). Each set of disks was run with three feed combinations: prototypically ground CST, CST plus monosodium titanate (MST), and CST, MST, plus Sludge Batch 6 (SB6) simulant. Throughout the testing, samples of the filtrate were collected, measured for turbidity, and sent back to SRNL for analysis to quantify the amount of fines that passed through the membrane. It should be noted that even though ground CST was tested, it will be transferred to the Defense Waste Processing Facility (DWPF) feed tank and is not expected to require filtration.

Herman, D.

2011-08-03T23:59:59.000Z

305

THERMAL MODELING ANALYSIS OF CST MEDIA IN THE SMALL COLUMN ION EXCHANGE PROJECT  

SciTech Connect

Models have been developed to simulate the thermal characteristics of Crystalline Silicotitanate (CST) ion exchange media fully loaded with radioactive cesium in a column configuration and distributed within a waste storage tank. This work was conducted to support the Small Column Ion Exchange (SCIX) program which is focused on processing dissolved, high-sodium salt waste for the removal of specific radionuclides (including Cs-137, Sr-90, and actinides) within a High Level Waste (HLW) storage tank at the Savannah River Site. The SCIX design includes CST columns inserted and supported in the tank top risers for cesium removal. Temperature distributions and maximum temperatures across the column were calculated with a focus on process upset conditions. A two-dimensional computational modeling approach for the in-column ion-exchange domain was taken to include conservative, bounding estimates for key parameters such that the results would provide the maximum centerline temperatures achievable under the design configurations using a feed composition known to promote high cesium loading on CST. One salt processing scenario includes the transport of the loaded (and possibly ground) CST media to the treatment tank floor. Therefore, additional thermal modeling calculations were conducted using a three-dimensional approach to evaluate temperature distributions for the entire in-tank domain including distribution of the spent CST media either as a mound or a flat layer on the tank floor. These calculations included mixtures of CST with HLW sludge or loaded Monosodium Titanate (MST) media used for strontium/actinide sorption. The current full-scale design for the CST column includes one central cooling pipe and four outer cooling tubes. Most calculations assumed that the fluid within the column was stagnant (i.e. no buoyancy-induced flow) for a conservative estimate. A primary objective of these calculations was to estimate temperature distributions across packed CST beds immersed in waste supernate or filled with dry air under various accident scenarios. Accident scenarios evaluated included loss of salt solution flow through the bed (a primary heat transfer mechanism), inadvertent column drainage, and loss of active cooling in the column. The calculation results showed that for a wet CST column with active cooling through one central and four outer tubes and 35 C ambient external air, the peak temperature for the fully-loaded column is about 63 C under the loss of fluid flow accident, which is well below the supernate boiling point. The peak temperature for the naturally-cooled (no active, engineered cooling) wet column is 156 C under fully-loaded conditions, exceeding the 130 C boiling point. Under these conditions, supernate boiling would maintain the column temperature near 130 C until all supernate was vaporized. Without active engineered cooling and assuming a dry column suspended in unventilated air at 35 C, the fully-loaded column is expected to rise to a maximum of about 258 C due to the combined loss-of coolant and column drainage accidents. The modeling results demonstrate that the baseline design using one central and four outer cooling tubes provides a highly efficient cooling mechanism for reducing the maximum column temperature. Results for the in-tank modeling calculations clearly indicate that when realistic heat transfer boundary conditions are imposed on the bottom surface of the tank wall, as much as 450 gallons of ground CST (a volume equivalent to two ion exchange processing cycles) in an ideal hemispherical shape (the most conservative geometry) can be placed in the tank without exceeding the 100 C wall temperature limit. Furthermore, in the case of an evenly-distributed flat layer, the tank wall reaches the temperature limit after the ground CST material reaches a height of approximately 8 inches.

Lee, S.

2010-11-01T23:59:59.000Z

306

Design of Slurry Bubble Column Reactors: Novel Technique for Optimum Catalyst Size Selection  

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

Slurry Bubble Column Reactors: Novel Technique Slurry Bubble Column Reactors: Novel Technique for Optimum Catalyst Size Selection Opportunity The Department of Energy's National Energy Technology Laboratory (NETL) is seeking licensing partners interested in implementing United States Patent Number 7,619,011 entitled "Design of Slurry Bubble Column Reactors: Novel Technique for Optimum Catalyst Size Selection." Disclosed in this patent is a method to determine the optimum catalyst particle size for application in a fluidized bed reactor, such as a slurry bubble column reactor (SBCR), to convert synthesis gas into liquid fuels. The reactor can be gas-solid, liquid- solid, or gas-liquid-solid. The method considers the complete granular temperature balance based on the kinetic theory of

307

Small Column Ion Exchange Technology at Savannah River Site | Department of  

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

Small Column Ion Exchange Technology at Savannah River Site Small Column Ion Exchange Technology at Savannah River Site Small Column Ion Exchange Technology at Savannah River Site The Small Column Ion Exchange (SCIX) system being developed for deployment at the Savannah River Site (SRS) is a supplementary salt waste processing technology that, if implemented, will augment the baseline Salt Waste Processing Facility (SWPF) capability. An opportunity exists to shorten the SRS radioactive waste system lifecycle by 6 years, and significantly reduce life cycle costs, by accelerating salt processing to earlier completion, simultaneous with sludge vitrification. As described in the Enhanced Tank Waste Strategy, which is part of the Department of Energy (DOE) Office of Environmental Management (EM) Roadmap - EM Journey to Excellence,

308

Engineering development of slurry bubble column reactor (SBCR) technology. Quarterly report, January 1--March 31, 1996  

DOE Green Energy (OSTI)

The major technical objectives of this program are threefold: (1) to develop the design tools and a fundamental understanding of the fluid dynamics of a slurry bubble column reactor to maximize reactor productivity; (2) to develop the mathematical reactor design models and gain an understanding of the hydrodynamic fundamentals under industrially relevant process conditions; and (3) to develop an understanding of the hydrodynamics and their interaction with the chemistries occurring in the bubble column reactor. Successful completion of these objectives will permit more efficient usage of the reactor column and tighter design criteria, increase overall reactor efficiency, and ensure a design that leads to stable reactor behavior when scaling up to large diameter reactors. The main part of this report describes tracer studies of slurry bubble column hydrodynamics during methanol synthesis.

Toseland, B.A.; Tischer, R.E.

1997-12-31T23:59:59.000Z

309

A method for evaluating bias in global measurements of CO2 total columns from space  

E-Print Network (OSTI)

on North American carbon dioxide exchange: CarbonTracker,over Kitt Peak. I – Carbon dioxide and methane from 1979 toD. , and Daube, B. : Carbon dioxide column abundances at the

Wunch, D.

2013-01-01T23:59:59.000Z

310

About Us Nanotechnology News Columns Products Directories Career Center My Account Google Search  

E-Print Network (OSTI)

About Us Nanotechnology News Columns Products Directories Career Center My Account Google Search. Bookmark: The latest news from around the world, FREE Subscribe Ads by Google Teleportation Nanotechnology.fluigent.com Ads by Google Nanotechnology Now - Press Release

Leigh, David A.

311

Usefulness of Single Column Model Diagnosis through Short-Term Predictions  

Science Conference Proceedings (OSTI)

Single column models (SCMs) provide an economical framework for developing and diagnosing representations of diabatic processes in weather and climate models. Their economy is achieved at the price of ignoring interactions with the circulation ...

John W. Bergman; Prashant D. Sardeshmukh

2003-11-01T23:59:59.000Z

312

Test of a Convective Wake Parameterization in the Single-Column Version of CCM3  

Science Conference Proceedings (OSTI)

A convective wake parameterization incorporated into the single-column (SCM) version of the NCAR Community Climate Model CCM3 is tested using observational data from 12 squall line cases to determine whether it can successfully reproduce ...

John J. Rozbicki; George S. Young; Liying Qian

1999-06-01T23:59:59.000Z

313

The Long-Term Coupling between Column Ozone and Tropopause Properties  

Science Conference Proceedings (OSTI)

The observational data of the vertical temperature distribution and column ozone, obtained from 10 main stations in the Northern Hemisphere, are analyzed in order to explore the tropopause variations in conjunction with the dynamical variability ...

Costas Varotsos; Costas Cartalis; Andrew Vlamakis; Chris Tzanis; Iphigenia Keramitsoglou

2004-10-01T23:59:59.000Z

314

Inexpensive Near-IR Sun Photometer for Measuring Total Column Water Vapor  

Science Conference Proceedings (OSTI)

An inexpensive two-channel near-IR sun photometer for measuring total atmospheric column water vapor (precipitable water) has been developed for use by the Global Learning and Observations to Benefit the Environment (GLOBE) environmental science ...

David R. Brooks; Forrest M. Mims III; Richard Roettger

2007-07-01T23:59:59.000Z

315

A Technique for Deriving Column-integrated Water Content Using VAS Split-Window Data  

Science Conference Proceedings (OSTI)

An algorithm is examined that uses Visible?Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) 11- and 12-µm (split-window) data to derive column-integrated water content (IWC) at mesoscale resolution. The algorithm is physically ...

Anthony R. Guillory; Gary J. Jedlovec; Henry E. Fuelberg

1993-07-01T23:59:59.000Z

316

Soft Sensing Based on LS-SVM and Its Application to a Distillation Column  

Science Conference Proceedings (OSTI)

Dry point of aviation kerosene in the atmospheric distillation column is a very important process value for quality controlling. But unfortunately few on-line hardware sensors are available to this value or such sensors are difficult to maintain. This ...

Yafen Li; Qi Li; Huijuan Wang; Ningsheng Ma

2006-10-01T23:59:59.000Z

317

Buildings and Energy in the 1980's  

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

a Primary Consumption for All Purposes Inputs for Heat, Power, and Generation of Electricity Primary Consumption for Nonfuel Purposes RSE Row Factors LPG Distillate b...

318

Buildings and Energy in the 1980's  

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

Industry Primary Consumption for All Purposes Inputs for Heat, Power, and Generation of Electricity Primary Consumption for Nonfuel Purposes RSE Row Factors LPG Distillate b...

319

Buildings and Energy in the 1980's  

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

. . . . . . . . . . 79 1,464 732 460 8.9 a See Appendices B and F for descriptions of the Standard Industrial Classification system. NFNo applicable RSE rowcolumn factor. *...

320

" Row: End Uses within NAICS Codes;"  

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

Heating, Ventilation, and Air Conditioning '(Facility HVAC)' excludes" "steam and hot water." " NFNo applicable RSE rowcolumn factor." " * Estimate less than 0.5." "...

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


321

Table 2. Fuel Oil Consumption and Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

1 A small amount of fuel oil used for appliances is included in "Fuel Oil" under "All Uses." NF = No applicable RSE row factor.

322

Buildings and Energy in the 1980's  

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

in Billion Cubic Feet) SIC Code a Industry Groups and Industry Natural Gas Alternative Types of Energy b RSE Row Factors Total Consumed c Switchable Not Switchable Electricity...

323

Buildings and Energy in the 1980's  

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

in Thousand Short Tons) SIC Code a Industry Groups and Industry Coal Alternative Types of Energy b RSE Row Factors Total Consumed c Switchable Not Switchable Electricity...

324

Buildings and Energy in the 1980's  

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

Thousand Barrels) SIC Code a Industry Groups and Industry Residual Fuel Oil Alternative Types of Energy b RSE Row Factors Total Consumed c Switchable Not Switchable Electricity...

325

Buildings and Energy in the 1980's  

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

(Estimates in Thousand Barrels) SIC Code a Industry Groups and Industry LPG Alternative Types of Energy b RSE Row Factors Total Consumed c Switchable Not Switchable Electricity...

326

Buildings and Energy in the 1980's  

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

Thousand Barrels) SIC Code a Industry Groups and Industry Distillate Fuel Oil Alternative Types of Energy b RSE Row Factors Total Consumed c Switchable Not Switchable Electricity...

327

Buildings and Energy in the 1980's  

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

Kilowatthours) SIC Code a Industry Groups and Industry Electricity Receipts Alternative Types of Energy b RSE Row Factors Total Receipts c Switchable Not Switchable Natural Gas...

328

Conversion Factor  

Gasoline and Diesel Fuel Update (EIA)

Conversion Factor (Btu per cubic foot) Production Marketed... 1,110 1,106 1,105 1,106 1,109 Extraction Loss ......

329

APPLICATION OF COLUMN EXTRACTION METHOD FOR IMPURITIES ANALYSIS ON HB-LINE PLUTONIUM OXIDE IN SUPPORT OF MOX FEED PRODUCT SPECIFICATIONS  

SciTech Connect

The current mission at H-Canyon involves the dissolution of an Alternate Feedstocks 2 (AFS-2) inventory that contains plutonium metal. Once dissolved, HB-Line is tasked with purifying the plutonium solution via anion exchange, precipitating the Pu as oxalate, and calcining to form plutonium oxide (PuO{sub 2}). The PuO{sub 2} will provide feed product for the Mixed Oxide (MOX) Fuel Fabrication Facility, and the anion exchange raffinate will be transferred to H-Canyon. The results presented in this report document the potential success of the RE resin column extraction application on highly concentrated Pu samples to meet MOX feed product specifications. The original 'Hearts Cut' sample required a 10000x dilution to limit instrument drift on the ICP-MS method. The instrument dilution factors improved to 125x and 250x for the sample raffinate and sample eluent, respectively. As noted in the introduction, the significantly lower dilutions help to drop the total MRL for the analyte. Although the spike recoveries were half of expected in the eluent for several key elements, they were between 94-98% after Nd tracer correction. It is seen that the lower ICD limit requirements for the rare earths are attainable because of less dilution. Especially important is the extremely low Ga limit at 0.12 {mu}g/g Pu; an ICP-MS method is now available to accomplish this task on the sample raffinate. While B and V meet the column A limits, further development is needed to meet the column B limits. Even though V remained on the RE resin column, an analysis method is ready for investigation on the ICP-MS, but it does not mean that V cannot be measured on the ICP-ES at a low dilution to meet the column B limits. Furthermore, this column method can be applicable for ICP-ES as shown in Table 3-2, in that it trims the sample of Pu, decreasing and sometimes eliminating Pu spectral interferences.

Jones, M.; Diprete, D.; Wiedenman, B.

2012-03-20T23:59:59.000Z

330

Douglas Factors  

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

The Merit Systems Protection Board in its landmark decision, Douglas vs. Veterans Administration, 5 MSPR 280, established criteria that supervisors must consider in determining an appropriate penalty to impose for an act of employee misconduct. These twelve factors are commonly referred to as “Douglas Factors” and have been incorporated into the Federal Aviation Administration (FAA) Personnel Management System and various FAA Labor Agreements.

331

The "True" Column Density Distribution in Star-Forming Molecular Clouds  

E-Print Network (OSTI)

We use the COMPLETE Survey's observations of the Perseus star-forming region to assess and intercompare three methods for measuring column density in molecular clouds: extinction mapping (NIR); thermal emission mapping (FIR); and mapping the intensity of CO isotopologues. The structures shown by all three tracers are morphologically similar, but important differences exist. Dust-based measures give similar, log-normal, distributions for the full Perseus region, once careful calibration corrections are made. We also compare dust- and gas-based column density distributions for physically-meaningful sub-regions of Perseus, and we find significant variations in the distributions for those regions. Even though we have used 12CO data to estimate excitation temperatures, and we have corrected for opacity, the 13CO maps seem unable to give column distributions that consistently resemble those from dust measures. We have edited out the effects of the shell around the B-star HD 278942. In that shell's interior and in the parts where it overlaps the molecular cloud, there appears to be a dearth of 13CO, likely due either to 13CO not yet having had time to form in this young structure, and/or destruction of 13CO in the molecular cloud. We conclude that the use of either dust or gas measures of column density without extreme attention to calibration and artifacts is more perilous than even experts might normally admit. And, the use of 13CO to trace total column density in detail, even after proper calibration, is unavoidably limited in utility due to threshold, depletion, and opacity effects. If one's main aim is to map column density, then dust extinction seems the best probe. Linear fits amongst column density tracers are given, quantifying the inherent uncertainties in using one tracer (when compared with others). [abridged

Alyssa A. Goodman; Jaime E. Pineda; Scott L. Schnee

2008-06-20T23:59:59.000Z

332

COMPUTATIONAL AND EXPERIMENTAL MODELING OF THREE-PHASE SLURRY-BUBBLE COLUMN REACTOR  

SciTech Connect

Considerable progress has been achieved in understanding three-phase reactors from the point of view of kinetic theory. In a paper in press for publication in Chemical Engineering Science (Wu and Gidaspow, 1999) we have obtained a complete numerical solution of bubble column reactors. In view of the complexity of the simulation a better understanding of the processes using simplified analytical solutions is required. Such analytical solutions are presented in the attached paper, Large Scale Oscillations or Gravity Waves in Risers and Bubbling Beds. This paper presents analytical solutions for bubbling frequencies and standing wave flow patterns. The flow patterns in operating slurry bubble column reactors are not optimum. They involve upflow in the center and downflow at the walls. It may be possible to control flow patterns by proper redistribution of heat exchangers in slurry bubble column reactors. We also believe that the catalyst size in operating slurry bubble column reactors is not optimum. To obtain an optimum size we are following up on the observation of George Cody of Exxon who reported a maximum granular temperature (random particle kinetic energy) for a particle size of 90 microns. The attached paper, Turbulence of Particles in a CFB and Slurry Bubble Columns Using Kinetic Theory, supports George Cody's observations. However, our explanation for the existence of the maximum in granular temperature differs from that proposed by George Cody. Further computer simulations and experiments involving measurements of granular temperature are needed to obtain a sound theoretical explanation for the possible existence of an optimum catalyst size.

Isaac K. Gamwo; Dimitri Gidaspow

1999-09-01T23:59:59.000Z

333

" Level: National Data;" " Row: NAICS Codes;"  

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

9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002;" 9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002;" " Level: National Data;" " Row: NAICS Codes;" " Column: Energy Sources;" " Unit: Establishment Counts." ,,"Distillate Fuel Oil(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total"," ","Not","Electricity","Natural","Residual",,,"and",,"Row" "Code(a)","Subsector and Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel Oil","Coal","LPG","Breeze","Other(f)","Factors"

334

" Level: National Data;" " Row: NAICS Codes;"  

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

3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2002;" 3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2002;" " Level: National Data;" " Row: NAICS Codes;" " Column: Energy Sources;" " Unit: Establishment Counts." ,,"LPG(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and",,"Row" "Code(a)","Subsector and Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel Oil","Fuel Oil","Coal","Breeze","Other(f)","Factors"

335

" Level: National Data and Regional Totals;"  

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

4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002;" 4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Residual Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate",,,"and",,"Row" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Gas","Fuel Oil","Coal","LPG","Breeze","Other(e)","Factors"

336

" Level: National Data and Regional Totals;"  

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

2 Capability to Switch LPG to Alternative Energy Sources, 2002; " 2 Capability to Switch LPG to Alternative Energy Sources, 2002; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"LPG",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and",,"Row" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Gas","Fuel Oil","Fuel Oil","Coal","Breeze","Other(e)","Factors"

337

" Level: National Data and Regional Totals;"  

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

8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; " 8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Distillate Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total"," ","Not","Electricity","Natural","Residual",,,"and",,"Row" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Gas","Fuel Oil","Coal","LPG","Breeze","Other(e)","Factors"

338

" Level: National Data and Regional Totals;"  

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

2 Capability to Switch Natural Gas to Alternative Energy Sources, 2002;" 2 Capability to Switch Natural Gas to Alternative Energy Sources, 2002;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Billion Cubic Feet." ,,"Natural Gas",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total"," ","Not","Electricity","Distillate","Residual",,,"and",,"Row" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Fuel Oil","Fuel Oil","Coal","LPG","Breeze","Other(e)","Factors"

339

" Row: Energy-Management Activities within NAICS Codes;"  

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

C9.1. Number of Establishments by Participation in Energy-Management Activity, 1998;" C9.1. Number of Establishments by Participation in Energy-Management Activity, 1998;" " Level: National Data; " " Row: Energy-Management Activities within NAICS Codes;" " Column: Participation and General Amounts of Establishment-Paid Activity Cost;" " Unit: Establishment Counts." " "," "," ",,,,,," " " "," ",,,"General","Amount of ","Establishment-Paid","Activity Cost","RSE" "NAICS"," "," ",,,,,,"Row" "Code(a)","Energy-Management Activity","No Participation","Participation(b)","All","Some","None","Don't Know","Factors"

340

" Level: National Data;" " Row: NAICS Codes;"  

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

5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002;" 5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002;" " Level: National Data;" " Row: NAICS Codes;" " Column: Energy Sources;" " Unit: Establishment Counts." ,,"Residual Fuel Oil(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate",,,"and",,"Row" "Code(a)","Subsector and Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel Oil","Coal","LPG","Breeze","Other(f)","Factors"

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


341

Tests of Monte Carlo Independent Column Approximation With a Mixed-Layer Ocean Model  

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

Tests of Monte Carlo Independent Column Tests of Monte Carlo Independent Column Approximation With a Mixed-Layer Ocean Model Petri Simo Järvenoja Heikki Järvinen Räisänen Finnish Meteorological Institute Figure 1. Root-mean-square sampling errors in local instant- aneous total (LW+SW) net flux at the surface and total radiative heating rate for the 1COL, CLDS, and REF approaches. Global rms values are given at the upper right hand corner of the plots. 1. Introduction The Monte Carlo Independent Column Approximation (McICA) separates the description of unresolved cloud structure from the radiative transfer solver very flexible ! unbiased with respect to ICA ! However, the radiative fluxes and heating rates contain conditional random errors ("McICA noise"). ? The topic of this poster: All previous tests of McICA

342

Tests of Monte Carlo Independent Column Approximation in the ECHAM5  

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

Tests of Monte Carlo Independent Column Approximation in the ECHAM5 Tests of Monte Carlo Independent Column Approximation in the ECHAM5 Atmospheric GCM Raisanen, Petri Finnish Meteoroligical Institute Jarvenoja, Simo Finnish Meteorological Institute Jarvinen, Heikki Finnish Meteorological Institute Category: Modeling The Monte Carlo Independent Column Approximation (McICA) was recently introduced as a new approach for parametrizing broadband radiative fluxes in global climate models (GCMs). The McICA allows a flexible description of unresolved cloud structure, and it is unbiased with respect to the full ICA, but its results contain conditional random errors (i.e., noise). In this work, McICA and a stochastic cloud generator have been implemented to the Max Planck Institute for Meteorology's ECHAM5 atmospheric GCM. The

343

One ARM, Two Columns and a Whole Lot of Aerosols | Department of Energy  

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

ARM, Two Columns and a Whole Lot of Aerosols ARM, Two Columns and a Whole Lot of Aerosols One ARM, Two Columns and a Whole Lot of Aerosols July 25, 2012 - 5:49pm Addthis This observatory is part of an air particles research initiative at Cape Cod National Seashore in Massachusetts, and includes dozens of sophisticated instruments that take continuous ground-based measurements of clouds, aerosols, and other atmospheric properties. | Photo courtesy of the ARM Climate Research Facility. This observatory is part of an air particles research initiative at Cape Cod National Seashore in Massachusetts, and includes dozens of sophisticated instruments that take continuous ground-based measurements of clouds, aerosols, and other atmospheric properties. | Photo courtesy of the ARM Climate Research Facility.

344

An Experimental Verification, with Krypton, of the Theory of the Thermal Diffusion Column for Multicomponent Systems  

SciTech Connect

The extended form of the Jones and Furry theory, which describes the behavior of a multicomponent heavy isotopic gas in a Clusius-Dickel thermal diffusion column, is tested. Experimental and theoretical values of the thermal diffusion column transport equation coefficients Hsub{ik},Ksub{c}, and Ksub{d}, are determined for krypton, a heavy isotopic gas with six isotopes. The experiments are carried out in a column of the hotwire type, at three wire temperatures: Tsub{H}=350 degrees C, 500 degrees C and 800 degrees C. Good agreement is found between the theoretical and experimental values of the coefficients. Seven of nine of the experimentally determined values of the coefficients agree within +- 10% with the corressponding theoretical values. The remaining two experimental values agree within +- 20% with the corresponding theoretical values.

Roos, W. J.

1967-12-01T23:59:59.000Z

345

First Commissioning of a Cryogenic Distillation Column for Low Radioactivity Underground Argon  

E-Print Network (OSTI)

We report on the performance and commissioning of a cryogenic distillation column for low radioactivity underground argon at Fermi National Accelerator Laboratory. The distillation column is designed to accept a mixture of argon, helium, and nitrogen and return pure argon with a nitrogen contamination less than 10 ppm. In the first commissioning, we were able to run the distillation column in a continuous mode and produce argon that is 99.9% pure. After running in a batch mode, the argon purity was increased to 99.95%, with 500 ppm of nitrogen remaining. The efficiency of collecting the argon from the gas mixture was between 70% and 81%, at an argon production rate of 0.84-0.98 kg/day.

H. O. Back; T. Alexander; A. Alton; C. Condon; E. de Haas; C. Galbiati; A. Goretti; T. Hohmann; An. Ianni; C. Kendziora; B. Loer; D. Montanari; P. Mosteiro; S. Pordes

2012-04-26T23:59:59.000Z

346

MSN YYYYMM Value Column Order Description Unit FFPRBUS Total Fossil Fuels Production Quadrillion Btu  

Gasoline and Diesel Fuel Update (EIA)

MSN YYYYMM Value Column Order Description Unit MSN YYYYMM Value Column Order Description Unit FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu FFPRBUS Total Fossil Fuels Production Quadrillion Btu

347

Anthropogenic NO2 in the Atmosphere: Estimates of the Column Content and Radiative Forcing  

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

Anthropogenic NO Anthropogenic NO 2 in the Atmosphere: Estimates of the Column Content and Radiative Forcing A. N. Rublev Institution of Molecular Physics Russian Research Center Kurchatov Institute Moscow, Russia N Chubarova Meteorological Observatory of Moscow State University Moscow, Russia G. Gorchakov Obukhov Institute of Atmospheric Physics Russian Academy of Sciences Moscow, Russia Introduction The work summarizes the different methodical aspects, firstly, the use of atmosphere optical depths presented in Aerosol Robotic Network (AERONET) data for NO 2 column retrievals, and, secondly, its radiative forcing calculated as difference between integral solar fluxes absorbed in the atmosphere with and without NO 2 under given air mass or the sun zenith angle.

348

Gas generation and bubble formation model for crystalline silicotitanate ion exchange columns  

SciTech Connect

The authors developed a transient model to describe the process of gas generation due to radiolysis and bubble formation in crystalline silicotitanate (CST) ion exchange (IX) columns using the Aspen Custom Modeler (ACM) software package. The model calculates gas concentrations and onset of bubble formation for large CST IX columns. The calculations include cesium loading as a function of time, gas generation as a function of cesium loading, and bubble formation as a function of gas solubility. This report summarizes the model development and predictions.

Hang, T.

2000-07-19T23:59:59.000Z

349

Two-Phase Hydraulics State Identification using linear and non-linear time series analysis: Distillation Column Flooding Sensor.  

E-Print Network (OSTI)

??A novel sensor to detect and predict hydraulic flooding in the distillation column was developed in this research. High speed (1000 Hz) differential pressure data… (more)

Patel, Alok Maheshbhai

2007-01-01T23:59:59.000Z

350

Use of Batch and Column Methodologies to Assess Utility Waste Leaching and Subsurface Chemical Attenuation  

Science Conference Proceedings (OSTI)

Often, a combination of batch and column methods is used in the laboratory to test wastes for leaching and attenuation potentials. This literature review addresses the strengths and limitations of using these two methods to predict leachate generation and subsequent attenuation at coal combustion waste management sites.

1991-05-13T23:59:59.000Z

351

Rapid Estimation of Column-Averaged CO2 Concentration Using a Correlation Algorithm  

Science Conference Proceedings (OSTI)

Measurement of XCO2, the column-averaged mole fraction of CO2, using reflected sunlight in the near-infrared bands of CO2, is strongly influenced by photons that are scattered in the atmosphere because scattering can either decrease or increase ...

Igor Polonsky; D. M. O’Brien

2010-12-01T23:59:59.000Z

352

A new post-column reactor-laser induced fluorescence detector for capillary electrophoresis  

Science Conference Proceedings (OSTI)

Capillary zone electrophoresis (CZE), a powerful separation method based on the differential migration of charged species under the influence of an electric field, has been widely used for separations covering from small ions to big biomolecules. Chapter 1 describes the method, then discusses detection of the separated analytes by laser induced fluorescence and by chemical derivatization, and the use of O-phthaldialdehyde (OPA) as a post-column reagent. Chapter 2 describes a post-column reactor which uses two narrow bore capillaries connected coaxially. This reactor differs from other coaxial reactors in terms of capillary dimensions, reagent flow control, ease of construction and most importantly, better limits of detection. The derivatization reagent is electroosmotically driven into the reaction capillary and the reagent flow rate is independently controlled by a high voltage power supply. Amino acids, amines and proteins, derivatized by OPA/2-mercaptoethanol using this post-column reactor coupled with LIF detection, show low attomole mass limits of detection, and for the first time, the authors demonstrate single cell capability with a post-column derivatization scheme. The single cell capability shows that this reactor could find applications in assaying non-fluorescent or electrochemically inactive components in individual biological cells in the future.

Zhang Liling

1996-01-02T23:59:59.000Z

353

2004 ASHRAE. 3 Standing column wells can be used as highly efficient  

E-Print Network (OSTI)

©2004 ASHRAE. 3 ABSTRACT Standing column wells can be used as highly efficient ground heat Performance Simon J. Rees, Ph.D. Jeffrey D. Spitler, Ph.D., P.E. Zheng Deng Member ASHRAE Member ASHRAE Student Member ASHRAE Carl D. Orio Carl N. Johnson, Ph.D. Member ASHRAE Member ASHRAE Simon J. Rees

354

Numerical Analysis of a Multi-Row Multi-Column Compact Heat Exchanger  

E-Print Network (OSTI)

Numerical Analysis of a Multi-Row Multi-Column Compact Heat Exchanger Ashkan Motamedi1, Arturo of a compact heat exchanger to analyze the interaction between the fluid and its geometry. The overall as the inner-tube fluid. Two heat exchanger configurations, in which the tube arrangement is either in

Pacheco, Jose Rafael

355

Liquid-phase thermal diffusion isotope separation apparatus and method having tapered column  

DOE Patents (OSTI)

A thermal diffusion counterflow method and apparatus for separating isotopes in solution in which the solution is confined in a long, narrow, vertical slit which tapers from bottom to top. The variation in the width of the slit permits maintenance of a stable concentration distribution with relatively long columns, thus permitting isotopic separation superior to that obtained in the prior art.

Rutherford, W.M.

1985-12-04T23:59:59.000Z

356

An Improved Quality Control for AIRS Total Column Ozone Observations within and around Hurricanes  

Science Conference Proceedings (OSTI)

Atmospheric Infrared Sounder (AIRS) provides twice-daily global observations from which total column ozone data can be retrieved. However, 20% ~ 30% of AIRS ozone data are flagged to be of bad quality. Most of the flagged data were identified to ...

H. Wang; X. Zou; G. Li

2012-03-01T23:59:59.000Z

357

Static Analysis on the Detached Column Substructure of Offshore Wind Power Based on Ansys  

Science Conference Proceedings (OSTI)

With the rapid development of wind power technology, offshore wind power has become one of the hottest topics in the world’s energy field. Basic research on wind power attracts more and more attention. This paper uses Ansys software to do static ... Keywords: ansys, etached column, extreme environmental loads, static analysis

Li Fenhua; Guo Weizhao; Liu Yuan; Xing Jian

2010-06-01T23:59:59.000Z

358

Measuring Total Column Water Vapor by Pointing an Infrared Thermometer at the Sky  

Science Conference Proceedings (OSTI)

A 2-yr study affirms that the temperature indicated by an inexpensive ($20–$60) IR thermometer pointed at the cloud-free zenith sky (Tz) is a proxy for total column water vapor [precipitable water (PW)]. From 8 September 2008 to 18 October 2010 Tz was ...

Forrest M. Mims III; Lin Hartung Chambers; David R. Brooks

2011-10-01T23:59:59.000Z

359

Dynamic analysis and control of sieve tray gas absorption column using MATALB and SIMULINK  

Science Conference Proceedings (OSTI)

The present work highlights the powerful combination of SIMULINK/MATLAB software as an effective flowsheeting tool which was used to simulate steady state, open and closed loop dynamics of a sieve tray gas absorption column. A complete mathematical model, ... Keywords: Control, Dynamic modelling, Gas absorption, MATLAB, SIMULINK

Menwer Attarakih; Mazen Abu-Khader; Hans-JöRg Bart

2013-02-01T23:59:59.000Z

360

Lagrangean relaxation with clusters and column generation for the manufacturer's pallet loading problem  

Science Conference Proceedings (OSTI)

We consider in this paper a new lagrangean relaxation with clusters for the Manufacturer's Pallet Loading Problem (MPLP). The relaxation is based on the MPLP formulated as a Maximum Independent Set Problem (MISP) and represented in a conflict graph that ... Keywords: Column generation, Lagrangean relaxation, Pallet loading

Glaydston Mattos Ribeiro; Luiz Antonio Nogueira Lorena

2007-09-01T23:59:59.000Z

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


361

LLNL-JRNL-410333 The Role of the n=1 Column  

E-Print Network (OSTI)

LLNL-JRNL-410333 The Role of the n=1 Column Mode in Spheromak Formation Bruce Cohen, Carlos Romero Livermore National Laboratory under contracts DE-AC52-07NA27344. LLNL-JRNL-410333 #12;2 I. INTRODUCTION to interface NIMROD with VisIt and W. H. Meyer for assistance implementing the Python script at LLNL

362

Small-Column Cesium Ion Exchange Elution Testing of Spherical Resorcinol-Formaldehyde  

Science Conference Proceedings (OSTI)

This report summarizes the work performed to evaluate multiple, cesium loading, and elution cycles for small columns containing SRF resin using a simple, high-level waste (HLW) simulant. Cesium ion exchange loading and elution curves were generated for a nominal 5 M Na, 2.4E-05 M Cs, 0.115 M Al loading solution traced with 134Cs followed by elution with variable HNO3 (0.02, 0.07, 0.15, 0.23, and 0.28 M) containing variable CsNO3 (5.0E-09, 5.0E-08, and 5.0E-07 M) and traced with 137Cs. The ion exchange system consisted of a pump, tubing, process solutions, and a single, small ({approx}15.7 mL) bed of SRF resin with a water-jacketed column for temperature-control. The columns were loaded with approximately 250 bed volumes (BVs) of feed solution at 45 C and at 1.5 to 12 BV per hour (0.15 to 1.2 cm/min). The columns were then eluted with 29+ BVs of HNO3 processed at 25 C and at 1.4 BV/h. The two independent tracers allowed analysis of the on-column cesium interaction between the loading and elution solutions. The objective of these tests was to improve the correlation between the spent resin cesium content and cesium leached out of the resin in subsequent loading cycles (cesium leakage) to help establish acid strength and purity requirements.

Brown, Garrett N.; Russell, Renee L.; Peterson, Reid A.

2011-10-21T23:59:59.000Z

363

Receptive field self-organization in a model of the fine structure in v1 cortical columns  

Science Conference Proceedings (OSTI)

We study a dynamical model of processing and learning in the visual cortex, which reflects the anatomy of V1 cortical columns and properties of their neuronal receptive fields. Based on recent results on the fine-scale structure of columns in V1, we ...

Jörg Lücke

2009-10-01T23:59:59.000Z

364

EMS Column  

E-Print Network (OSTI)

disbelief arid the like havc been dredged up in a search forSenator Speier. SB-117 would havc allowcd direct billing ofDepartlnent and the Police havc. Legislators deliberating

Michaels, Howard

2001-01-01T23:59:59.000Z

365

Posters Single-Column Model and Cumulus Ensemble Model Simulations of GATE Data  

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

3 3 Posters Single-Column Model and Cumulus Ensemble Model Simulations of GATE Data D. A. Randall and K.-M Xu Colorado State University Department of Atmospheric Science Fort Collins, Colorado Introduction Our project for the Atmospheric Radiation Measurement (ARM) Program consists of developing and demonstrating improved cloud formation parameterizations using a single-column model (SCM), a cumulus ensemble model (CEM), and ARM data. These two models can be driven with large-scale forcing (e.g., vertical motion) as observed in ARM. Each model produces a field of clouds and the associated radiation and precipitation fields. The SCM does so through its physical parameterizations, while the CEM does so by directly simulating convective cloud circulations. The improved parameterizations tested in this way will be

366

PULSE COLUMN DESIGN By Lawrence E. Burkhart R.W. Fahien  

Office of Scientific and Technical Information (OSTI)

PULSE COLUMN DESIGN PULSE COLUMN DESIGN By Lawrence E. Burkhart R.W. Fahien November 1958 Ames Laboratory Iowa State College Ames, Iowa UNITED STATES ATOMIC ENERGY COMMISSION Technical Information Service DISCLAIMER Portions of this document may be illegible in electronic image products. Images are produced from the best available original document. F. H. Spedding, Director, Ames Laboratory. Work performed under Contract No. W-7405-Eng-82. L E G A L N O T I C E This report was prepared as an account of Government sponsored work. Neither the United States, nor the Commission, nor any person acting on behalf of the Commission: A. Makes any warranty or representation, expressed or implied, with respect to the accu- racy, completeness, or usefulness of the information contained in this report, or that the use

367

Summary - Small Column Ion Exchange (SCIX)Technology at the SRS  

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

ETR ETR R Un Baseline The Sm being The SC operat which Sr, and waste critical the SC deploy Specif exchan [CST]) CST, a (mono and so (RMF) maturi readin design moving The pu techni projec Site: S roject: S E Report Date: F ited States Sma Why DOE e SCIX System Pr mall Column Io developed at S CIX system is tions (ion excha function to rem d actinides) fro and prepare th l technology ele CIX system tha yment and thes fically the critica nge on a selec ) housed in an actinide and Sr osodium titanat olids/liquid sepa ). The objectiv ty of the SCIX ess of the proc n, and to provid g towards deta To view the full E http://www.em.doe. urpose of an Externa ical risk associated w ct decisions. Technic Savannah Rive Small Column Exchange/SCIX Feb. 2011 Departmen ll Colum E-EM Did This rocess Diagram on Exchange (S

368

A Minimum Column Density of 1 g cm^-2 for Massive Star Formation  

E-Print Network (OSTI)

Massive stars are very rare, but their extreme luminosities make them both the only type of young star we can observe in distant galaxies and the dominant energy sources in the universe today. They form rarely because efficient radiative cooling keeps most star-forming gas clouds close to isothermal as they collapse, and this favors fragmentation into stars ~ 1 g cm^-2 can avoid fragmentation and form massive stars. This threshold, and the environmental variation of the stellar initial mass function (IMF) that it implies, naturally explain the characteristic column densities of massive star clusters and the difference between the radial profiles of Halpha and UV emission in galactic disks. The existence of a threshold also implies that there should be detectable variations in the IMF with environment within the Galaxy and in the characteristic column densities of massive star clusters between galaxies, and that star formation rates in some galactic environments may have been systematically underestimated.

Mark R. Krumholz; Christopher F. McKee

2008-01-02T23:59:59.000Z

369

Development of dynamic models of reactive distillation columns for simulation and determination of control  

E-Print Network (OSTI)

Dynamic models of a reactive distillation column have been developed and implemented in this work. A model describing the steady state behavior of the system has been built in a first step. The results from this steady state model have been compared to data provided from an industrial collaborator and the reconciled model formed the basis for the development of a dynamic model. Four controlled and four manipulated variables have been determined in a subsequent step and step tests for the manipulated variables were simulated. The data generated by the step responses was used for fitting transfer functions between the manipulated and the controlled variables. RGA analysis was performed to find the optimal pairing for controller design. Feedback controllers of PID type were designed between the paired variables found from RGA and the controllers were implemented on the column model. Both servo and regulatory problems have been considered and tested.

Chakrabarty, Arnab

2004-12-01T23:59:59.000Z

370

Formation, Manipulation, and Elasticity Measurement of a Nanometric Column of Water Molecules  

E-Print Network (OSTI)

Nanometer-sized columns of condensed water molecules are created by an atomic-resolution force microscope operated in ambient conditions. Unusual stepwise decrease of the force gradient associated with the thin water bridge in the tip-substrate gap is observed during its stretch, exhibiting regularity in step heights (~0.5 N/m) and plateau lengths (~1 nm). Such "quantized" elasticity is indicative of the atomic-scale stick-slip at the tip-water interface. A thermodynamic-instability-induced rupture of the water meniscus (5-nm long and 2.6-nm wide) is also found. This work opens a high-resolution study of the structure and the interface dynamics of a nanometric aqueous column.

H. Choe; M. -H. Hong; Y. Seo; K. Lee; G. Kim; Y. Cho; J. Ihm; and W. Jhe

2005-03-21T23:59:59.000Z

371

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

6 End Uses of Fuel Consumption, 2006;" 6 End Uses of Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," " " ",,,,"Fuel Oil",,,"Coal" " "," ","Net","Residual","and",,"LPG and","(excluding Coal"," " "End Use","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Natural Gas(c)","NGL(d)","Coke and Breeze)","Other(e)"

372

" Row: NAICS Codes (3-Digit Only); Column: Energy Sources;"  

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

4.4 Number of Establishments by Offsite-Produced Fuel Consumption, 2006;" 4.4 Number of Establishments by Offsite-Produced Fuel Consumption, 2006;" " Level: National Data; " " Row: NAICS Codes (3-Digit Only); Column: Energy Sources;" " Unit: Establishment Counts." " "," "," ",," "," "," "," "," "," "," ",," " " "," ","Any" "NAICS"," ","Energy",,"Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","and Breeze","Other(g)"

373

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

5 End Uses of Fuel Consumption, 2010;" 5 End Uses of Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ","Coal"," " " ",,,,"Fuel Oil",,,"(excluding Coal" " "," ","Net","Residual","and","Natural Gas(c)","LPG and","Coke and Breeze)"," " " ","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","(billion","NGL(d)","(million","Other(e)"

374

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

6 End Uses of Fuel Consumption, 2010;" 6 End Uses of Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," " " ",,,,"Fuel Oil",,,"Coal" " "," ","Net","Residual","and",,"LPG and","(excluding Coal"," " "End Use","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Natural Gas(c)","NGL(d)","Coke and Breeze)","Other(e)"

375

Seismic fragility estimates for corroded reinforced concrete bridge structures with two-column bents  

E-Print Network (OSTI)

To assess the losses associated with future earthquakes, seismic vulnerability functions are commonly used to correlate the damage or loss of a structure to the level of seismic intensity. A common procedure in seismic vulnerability assessment is to estimate the seismic fragility, which is defined as the conditional probability that a structure fails to meet the specific performance level for given level of seismic intensity. This dissertation proposes a methodology to estimate the fragility of corroded reinforced concrete (RC) bridges with two-column bents subject to seismic excitation. Seismic fragility functions are first developed for the RC bridges with two-column bents. All available information from science/engineering laws, numerical analysis, laboratory experiments, and field measurements has been used to construct the proper form of the fragility functions. The fragility functions are formulated, at the individual column, bent, and bridge levels, in terms of the spectral acceleration and the ratio between the peak ground velocity and the peak ground acceleration. The developed fragility functions properly account for the prevailing uncertainties in fragility estimation. The probabilistic capacity and demand models are then combined with the probabilistic models for chloride-induced corrosion and the time-dependent corrosion rate. The fragility estimates for corroded RC bridges incorporates the uncertainties in the parameters of capacity and demand models, and the inexactness (or model error) in modeling the material deterioration, structural capacity, and seismic demands. The proposed methodology is illustrated by developing the fragility functions for an example RC bridge with 11 two-column bents representing current construction in California. The developed fragility functions provide valuable information to allocate and spend available funds for the design, maintenance, and retrofitting of structures and networks. This study regarding the vulnerability of corroding RC bridges will be of direct value to those making decisions about the condition assessment, residual life, and the ability of lifeline structures to withstand future seismic demands.

Zhong, Jinquan

2008-12-01T23:59:59.000Z

376

Processes and catalysts for conducting Fischer-Tropsch synthesis in a slurry bubble column reactor  

DOE Patents (OSTI)

Processes and catalysts are disclosed for conducting Fischer-Tropsch synthesis in a slurry bubble column reactor (SBCR). One aspect of the invention involves the use of cobalt catalysts without noble metal promotion in an SBCR. Another aspect involves using palladium promoted cobalt catalysts in an SBCR. Methods for preparing noble metal promoted catalysts via totally aqueous impregnation and procedures for producing attrition resistant catalysts are also provided. 1 fig.

Singleton, A.H.; Oukaci, R.; Goodwin, J.G.

1999-08-17T23:59:59.000Z

377

Processes and catalysts for conducting fischer-tropsch synthesis in a slurry bubble column reactor  

DOE Patents (OSTI)

Processes and catalysts for conducting Fischer-Tropsch synthesis in a slurry bubble column reactor (SBCR). One aspect of the invention involves the use of cobalt catalysts without noble metal promotion in an SBCR. Another aspect involves using palladium promoted cobalt catalysts in an SBCR. Methods for preparing noble metal promoted catalysts via totally aqueous impregnation and procedures for producing attrition resistant catalysts are also provided.

Singleton, Alan H. (Marshall Township, Allegheny County, PA); Oukaci, Rachid (Allison Park, PA); Goodwin, James G. (Cranberry Township, PA)

1999-01-01T23:59:59.000Z

378

Experimental techniques for hydrodynamic characterization of multiphase flows in slurry-phase bubble-column reactors  

DOE Green Energy (OSTI)

Slurry-phase bubble-column Fischer-Tropsch (FT) reactors are recognized as one of the more promising technologies for converting synthesis gas from coal into liquid fuel products (indirect liquefaction). However, hydrodynamic effects must be considered when attempting to scale these reactors to sizes of industrial interest. The objective of this program is to facilitate characterization of reactor hydrodynamics by developing and applying noninvasive tomographic diagnostics capable of measuring gas holdup spatial distribution in these reactors.

Torczynski, J.R.; O`Hern, T.J.; Adkins, D.R.; Shollenberger, K.A.; Mondy, L.A.; Jackson, N.B.

1994-09-01T23:59:59.000Z

379

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

5 End Uses of Fuel Consumption, 2006;" 5 End Uses of Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ","Coal"," " " ",,,,"Fuel Oil",,,"(excluding Coal" " "," ","Net","Residual","and","Natural Gas(c)","LPG and","Coke and Breeze)"," " " ","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","(billion","NGL(d)","(million","Other(e)"

380

IMPACT OF THE SMALL COLUMN ION EXCHANGE PROCESS ON THE DEFENSE WASTE PROCESSING FACILITY - 12112  

SciTech Connect

The Savannah River Site (SRS) is investigating the deployment of a parallel technology to the Salt Waste Processing Facility (SWPF, presently under construction) to accelerate high activity salt waste processing. The proposed technology combines large waste tank strikes of monosodium titanate (MST) to sorb strontium and actinides with two ion exchange columns packed with crystalline silicotitanate (CST) resin to sorb cesium. The new process was designated Small Column Ion Exchange (SCIX), since the ion exchange columns were sized to fit within a waste storage tank riser. Loaded resins are to be combined with high activity sludge waste and fed to the Defense Waste Processing Facility (DWPF) for incorporation into the current glass waste form. Decontaminated salt solution produced by SCIX will be fed to the SRS Saltstone Facility for on-site immobilization as a grout waste form. Determining the potential impact of SCIX resins on DWPF processing was the basis for this study. Accelerated salt waste treatment is projected to produce a significant savings in the overall life cycle cost of waste treatment at SRS.

Koopman, D.; Lambert, D.; Fox, K.; Stone, M.

2011-11-07T23:59:59.000Z

Note: This page contains sample records for the topic "rse column factors" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
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381

THE COLUMN DENSITY VARIANCE IN TURBULENT INTERSTELLAR MEDIA: A FRACTAL MODEL APPROACH  

Science Conference Proceedings (OSTI)

Fractional Brownian motion structures are used to investigate the dependency of column density variance ({sigma}{sup 2}{sub lnN}) in the turbulent interstellar medium on the variance of three-dimensional density ({sigma}{sup 2}{sub ln{rho}}) and the power-law slope of the density power spectrum. We provide quantitative expressions to infer the three-dimensional density variance, which is not directly observable, from the observable column density variance and spectral slope. We also investigate the relationship between the column density variance and sonic Mach number (M{sub s}) in the hydrodynamic (HD) regime by assuming the spectral slope and density variance to be functions of sonic Mach number, as obtained from the HD turbulence simulations. They are related by the expression {sigma}{sup 2}{sub lnN} = A{sigma}{sub ln{rho}} {sup 2} = Aln (1 + b {sup 2} M{sup 2}{sub s}), suggested by Burkhart and Lazarian for the magnetohydrodynamic case. The proportional constant A varies from Almost-Equal-To 0.2 to Almost-Equal-To 0.4 in the HD regime as the turbulence forcing parameter b increases from 1/3 (purely solenoidal forcing) to 1 (purely compressive forcing). It is also discussed that the parameter A is lowered in the presence of a magnetic field.

Seon, Kwang-Il, E-mail: kiseon@kasi.re.kr [Korea Astronomy and Space Science Institute, Daejeon 305-348 (Korea, Republic of); Astronomy and Space Science Major, University of Science and Technology, Daejeon 305-350 (Korea, Republic of)

2012-12-20T23:59:59.000Z

382

The setup of an extraction system coupled to a hydrogen isotopes distillation column  

Science Conference Proceedings (OSTI)

Among the most difficult problems of cryogenic distillation one stands apart: the extraction of the heavy fraction. By an optimal design of the cycle scheme, this problem could be avoided. A 'worst case scenario' is usually occurring when the extracted fraction consists of one prevalent isotope such as hydrogen and small amounts of the other two hydrogen isotopes (deuterium and/or tritium). This situation is further complicated by two parameters of the distillation column: the extraction flow rate and the hold-up. The present work proposes the conceptual design of an extraction system associated to the cryogenic distillation column used in hydrogen separation processes. During this process, the heavy fraction (DT, T{sub 2}) is separated, its concentration being the highest at the bottom of the distillation column. From this place the extraction of the gaseous phase can now begin. Being filled with adsorbent, the extraction system is used to temporarily store the heavy fraction. Also the extraction system provides samples for the gas Chromatograph. The research work is focused on the existent pilot plant for tritium and deuterium separation from our institute to validate the experiments carried out until now. (authors)

Zamfirache, M.; Bornea, A.; Stefanescu, I.; Bidica, N.; Balteanu, O.; Bucur, C. [INC-DTCI, ICSIRm. Valcea, Uzinei Street 4, Rm. Valcea (Romania)

2008-07-15T23:59:59.000Z

383

The "True" Column Density Distribution in Star-Forming Molecular Clouds  

E-Print Network (OSTI)

We use the COMPLETE Survey's observations of the Perseus star-forming region to assess and intercompare three methods for measuring column density in molecular clouds: extinction mapping (NIR); thermal emission mapping (FIR); and mapping the intensity of CO isotopologues. The structures shown by all three tracers are morphologically similar, but important differences exist. Dust-based measures give similar, log-normal, distributions for the full Perseus region, once careful calibration corrections are made. We also compare dust- and gas-based column density distributions for physically-meaningful sub-regions of Perseus, and we find significant variations in the distributions for those regions. Even though we have used 12CO data to estimate excitation temperatures, and we have corrected for opacity, the 13CO maps seem unable to give column distributions that consistently resemble those from dust measures. We have edited out the effects of the shell around the B-star HD 278942. In that shell's interior and in t...

Goodman, Alyssa A; Schnee, Scott L

2008-01-01T23:59:59.000Z

384

Experimental results of hydrogen distillation at the low power cryogenic column for the production of deuterium depleted hydrogen  

Science Conference Proceedings (OSTI)

The Deuterium Removal Unit (DRU) has been designed and built at the Petersburg Nuclear Physics Inst. (PNPI) to produce isotopically pure hydrogen with deuterium content less than 1 ppm. The cryogenic distillation column of 2.2 cm inner diameter and 155 cm packing height is the main element of the DRU. Column performances at different hydrogen distillation operating modes have been measured. The height equivalent to theoretical plate (HETP) for the column is 2.2 cm and almost constant over a wide range of vapour flow rates. Deuterium depleted hydrogen with a deuterium content of less than 0.1 ppm was produced in required quantity. (authors)

Alekseev, I.; Fedorchenko, O.; Kravtsov, P.; Vasilyev, A.; Vznuzdaev, M. [Petersburg Nuclear Physics Inst., Leningrad district, Gatchina, 188300 (Russian Federation)

2008-07-15T23:59:59.000Z

385

table5.6_02  

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

6 End Uses of Fuel Consumption, 2002; 6 End Uses of Fuel Consumption, 2002; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal RSE Net Residual and Natural LPG and (excluding Coal Row End Use Total Electricity(a) Fuel Oil Diesel Fuel(b) Gas(c) NGL(d) Coke and Breeze) Other(e) Factors Total United States RSE Column Factors: 1 1 2.4 1.1 1.3 1 0 0 TOTAL FUEL CONSUMPTION 16,273 2,840 208 141 5,794 103 1,182 6,006 3.3 Indirect Uses-Boiler Fuel -- 12 127 35 2,162 8 776 -- 5.5 Conventional Boiler Use -- 9 76 25 1,306 8 255 -- 5.6 CHP and/or Cogeneration Process -- 4 51 10 857 * 521 -- 3.7 Direct Uses-Total Process -- 2,218 60 43 2,986 64 381 -- 2.9 Process Heating -- 343

386

table2.4_02.xls  

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

4 Number of Establishments by Nonfuel (Feedstock) Use of Combustible Energy, 2002; 4 Number of Establishments by Nonfuel (Feedstock) Use of Combustible Energy, 2002; Level: National Data; Row: NAICS Codes (3-Digit Only); Column: Energy Sources; Unit: Establishment Counts. Any Combustible RSE NAICS Energy Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Source(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) Coal and Breeze Other(f) Factors Total United States RSE Column Factors: 1.5 0.6 1.1 1 1.1 0.7 1 1.4 311 Food 406 W 152 185 0 0 4 83 9.6 311221 Wet Corn Milling W 0 W 0 0 0 0 W 0.8 31131 Sugar 6 0 W W 0 0 4 W 0.9 311421 Fruit and Vegetable Canning 14 W 6 0 0 0 0 9 5.6 312 Beverage and Tobacco Products 31 W 5 W 0 0 0 15 12.4 3121 Beverages Q W 5 0 0 0 0 12 31.9 3122 Tobacco W 0 0 W 0 0 0 W 0.8

387

table10.3_02.xls  

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

3 Number of Establishments with Capability to Switch Natural Gas to Alternative Energy Sources, 2002; 3 Number of Establishments with Capability to Switch Natural Gas to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Electricity Distillate Residual and Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Fuel Oil Fuel Oil Coal LPG Breeze Other(f) Factors Total United States RSE Column Factors: 0.6 1.1 0.7 1.2 1.1 1.1 1.2 1.1 0.9 1.1 311 Food 12,018 2,210 10,674 532 1,170 413 75 862 3 25 9.9 311221 Wet Corn Milling 47 16 39 4 6 W W 6 0 W 1 31131 Sugar 62 23 51 W 4 13 4 0 W 0 1 311421 Fruit and Vegetable Canning 416 113 337 4 67 49 W 32 W W 5.5 312 Beverage and Tobacco Products

388

table10.10_02.xls  

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

0 Capability to Switch Coal to Alternative Energy Sources, 2002; 0 Capability to Switch Coal to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Short Tons. RSE NAICS Total Not Electricity Natural Distillate Residual Row Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Gas Fuel Oil Fuel Oil LPG Other(e) Factors Total United States RSE Column Factors: 1.4 1.1 1.5 0.7 1.1 0.8 1.2 1.5 0.5 311 Food 8,290 1,689 7,112 0 1,410 Q 212 313 7 8.5 311221 Wet Corn Milling 5,462 771 5,201 0 766 0 0 249 6 0.9 31131 Sugar 1,648 388 1,260 0 243 0 W 0 2 0.9 311421 Fruit and Vegetable Canning 0 0 0 0 0 0 0 0 0 0 312 Beverage and Tobacco Products

389

table10.4_02.xls  

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

4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002; 4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Barrels. Coal Coke RSE NAICS Total Not Electricity Natural Distillate and Row Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Gas Fuel Oil Coal LPG Breeze Other(e) Factors Total United States RSE Column Factors: 1.9 1.4 1.9 0.6 1.5 0.6 0.6 0.9 0 0.7 311 Food 2,125 1,411 508 0 819 W W Q 0 Q 11.1 311221 Wet Corn Milling 61 W 45 0 0 W 0 0 0 0 0.8 31131 Sugar 346 193 98 0 169 0 W 0 0 0 0.7 311421 Fruit and Vegetable Canning 153 29 Q 0 29 * 0 0 0 0 24.6 312 Beverage and Tobacco Products

390

table3.4_02.xls  

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

4 Number of Establishments by Fuel Consumption, 2002; 4 Number of Establishments by Fuel Consumption, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Any RSE NAICS Energy Net Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) Coal and Breeze Other(g) Factors Total United States RSE Column Factors: 0.7 0.7 1.3 1.1 0.9 1.2 1.2 1 1.2 311 Food 15,089 15,045 274 2,418 12,018 3,159 91 19 1,858 5.1 311221 Wet Corn Milling 49 49 3 20 47 14 19 0 15 1 31131 Sugar 77 77 18 40 62 31 24 19 44 1 311421 Fruit and Vegetable Canning 468 468 38 123 416 229 0 0 146 7.8 312 Beverage and Tobacco Products 1,595 1,595 35 251 1,132 630 17 0 184 11 3121 Beverages 1,517 1,517

391

table11.4_02.xls  

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

4 Electricity: Components of Onsite Generation, 2002; 4 Electricity: Components of Onsite Generation, 2002; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Onsite-Generation Components; Unit: Million Kilowatthours. Renewable Energy (excluding Wood RSE Economic Total Onsite and Row Characteristic(a) Generation Cogeneration(b) Other Biomass)(c) Other(d) Factors Total United States RSE Column Factors: 0.8 0.8 1.1 1.4 Value of Shipments and Receipts (million dollars) Under 20 609 379 W W 25.2 20-49 4,155 4,071 27 58 13.3 50-99 6,356 6,296 * 61 6.5 100-249 19,027 16,033 1,185 1,809 2.2 250-499 36,752 32,991 W W 2.2 500 and Over 69,334 66,458 W W 1.2 Total 136,233 126,228 2,381 7,625 2 Employment Size Under 50 3,927 3,713

392

table4.3_02.xls  

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

Offsite-Produced Fuel Consumption, 2002; Offsite-Produced Fuel Consumption, 2002; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: Trillion Btu. RSE Economic Residual Distillate Natural LPG and Coke and Row Characteristic(a) Total Electricity(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) Coal Breeze Other(f) Factors Total United States RSE Column Factors: 0.6 0.6 1.3 2.2 0.7 1.4 1.5 0.6 1 Value of Shipments and Receipts (million dollars) Under 20 1,276 437 15 50 598 W 47 W 97 14.5 20-49 1,258 417 28 22 590 W 112 W 72 6.1 50-99 1,463 401 17 W 731 7 185 W 97 4.9 100-249 2,041 571 43 17 968 8 253 7 175 4.6 250-499 1,962 475 54 W 826 W 326 W 255 5.6 500 and Over 3,971 618 38 W 2,077 37 259 W 607 1.5 Total 11,970

393

table5.5_02  

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

5 End Uses of Fuel Consumption, 2002; 5 End Uses of Fuel Consumption, 2002; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Fuel Oil Coal Net Residual and Natural LPG and (excluding Coal RSE Total Electricity(a) Fuel Oil Diesel Fuel(b) Gas(c) NGL(d) Coke and Breeze) Other(e) Row End Use (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) (million short tons) (trillion Btu) Factors Total United States RSE Column Factors: 1 1 2.4 1.1 1.4 1 0 0 TOTAL FUEL CONSUMPTION 16,273 832,257 33 24 5,641 26 53 6,006 3.4 Indirect Uses-Boiler Fuel -- 3,540 20 6 2,105 2 35 -- 5.3 Conventional Boiler Use -- 2,496 12 4 1,271 2 11 -- 5.6

394

table5.2_02  

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

2 End Uses of Fuel Consumption, 2002; 2 End Uses of Fuel Consumption, 2002; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal RSE NAICS Net Residual and Natural LPG and (excluding Coal Row Code(a) End Use Total Electricity(b) Fuel Oil Diesel Fuel(c) Gas(d) NGL(e) Coke and Breeze) Other(f) Factors Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES RSE Column Factors: 0.3 1 1 2.4 1.1 1.3 1 NF TOTAL FUEL CONSUMPTION 16,273 2,840 208 141 5,794 103 1,182 6,006 3.3 Indirect Uses-Boiler Fuel -- 12 127 25 2,162 8 776 -- 5.5 Conventional Boiler Use -- 9 76 25 1,306 8 255 -- 5.6 CHP and/or Cogeneration Process -- 4 51 10 857 * 521 -- 3.7 Direct Uses-Total Process

395

table10.5_02.xls  

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

5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002; 5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Electricity Natural Distillate and Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Factors Total United States RSE Column Factors: 1.3 1 1.5 0.7 1 0.8 0.6 1.2 1.4 0.8 311 Food 274 183 108 0 119 72 W Q 0 15 15.2 311221 Wet Corn Milling 3 W W 0 0 W 0 0 0 0 0.9 31131 Sugar 18 9 9 0 9 0 W 0 0 0 1 311421 Fruit and Vegetable Canning 38 26 30 0 26 W 0 0 0 0 8.1 312 Beverage and Tobacco Products 35 17 Q 0 17 6 W 0 0 0 8

396

table5.8_02  

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

8 End Uses of Fuel Consumption, 2002; 8 End Uses of Fuel Consumption, 2002; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Net Demand Fuel Oil Coal RSE for Residual and Natural LPG and (excluding Coal Row End Use Electricity(a) Fuel Oil Diesel Fuel(b) Gas(c) NGL(d) Coke and Breeze) Factors Total United States RSE Column Factors: 0.3 2.4 1.1 1.3 1 0 TOTAL FUEL CONSUMPTION 3,297 208 141 5,794 103 1,182 3.3 Indirect Uses-Boiler Fuel 23 127 35 2,162 8 776 5.5 Conventional Boiler Use 11 76 25 1,306 8 255 5.6 CHP and/or Cogeneration Process 12 51 10 857 * 521 3.7 Direct Uses-Total Process 2,624 60 43 2,986 64 381 2.9 Process Heating 355 58 24 2,742 60 368 3.2

397

table6.1_02.xls  

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

1 Consumption Ratios of Fuel, 2002; 1 Consumption Ratios of Fuel, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value RSE NAICS per Employee of Value Added of Shipments Row Code(a) Subsector and Industry (million Btu) (thousand Btu) (thousand Btu) Factors Total United States RSE Column Factors: 1.1 0.9 1 311 Food 867.8 6.0 2.6 5.9 311221 Wet Corn Milling 24,113.7 65.7 26.2 1.8 31131 Sugar 8,414.5 54.2 17.9 1 311421 Fruit and Vegetable Canning 824.1 5.4 2.5 10.6 312 Beverage and Tobacco Products 670.4 1.6 1.0 2.7 3121 Beverages 658.6 2.8 1.3 3.9 3122 Tobacco 729.4 0.6 0.5 1 313 Textile Mills 798.7 11.2 4.3

398

table10.13_02.xls  

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

3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2002; 3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Electricity Natural Distillate Residual and Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Fuel Oil Coal Breeze Other(f) Factors Total United States RSE Column Factors: 0.6 0.8 0.6 0.9 0.7 0.8 1 2.8 2.7 0.7 311 Food 3,159 793 2,492 570 533 147 225 22 20 21 21.9 311221 Wet Corn Milling 14 W W W W 0 0 0 0 W 1.4 31131 Sugar 31 W W W 0 0 0 W 0 W 1.1 311421 Fruit and Vegetable Canning 229 15 215 11 4 W W 0 0 0 5.3 312 Beverage and Tobacco Products

399

table10.8_02.xls  

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

8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; 8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Barrels. Coal Coke RSE NAICS Total Not Electricity Natural Residual and Row Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Gas Fuel Oil Coal LPG Breeze Other(e) Factors Total United States RSE Column Factors: 1.7 1.6 1.7 0.9 1.5 0.6 0.7 1.7 0.3 0.8 311 Food 3,177 986 767 Q 297 Q 1 Q 0 Q 10.4 311221 Wet Corn Milling 14 4 10 * 3 0 1 2 0 * 0.8 31131 Sugar 169 W 143 W W 0 0 0 0 0 0.7 311421 Fruit and Vegetable Canning 242 Q 121 0 Q 0 0 0 0 * 27.1 312 Beverage and Tobacco Products

400

table1.2_02  

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

2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; 2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments RSE NAICS Net Residual Distillate Natural LPG and Coke and of Energy Sources Row Code(a) Subsector and Industry Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Factors Total United States RSE Column Factors: 0.9 1 1.2 1.8 1 1.6 0.8 0.9 1.2 0.4 311 Food 1,123 230 13 19 582 5 184 1 89 0 6.8 311221 Wet Corn Milling 217 23 * * 61 * 121 0 11 0 1.1 31131 Sugar 112 2 2 1 22 * 37 1 46 0 0.9 311421 Fruit and Vegetable Canning 47 7 1 1 36 Q 0 0 1 0 11 312 Beverage and Tobacco Products 105 26 2 2 46 1 17 0 11

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


401

table10.9_02.xls  

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

9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; 9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Electricity Natural Residual and Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Factors Total United States RSE Column Factors: 1 1.3 1 0.9 1.2 1 0.8 1.3 0.8 0.9 311 Food 2,418 789 1,899 129 447 176 W 280 0 40 12.4 311221 Wet Corn Milling 20 7 15 W 4 0 W W 0 W 1 31131 Sugar 40 W W W W 0 0 0 0 0 0.9 311421 Fruit and Vegetable Canning 123 6 117 0 5 0 0 0 0 W 6.9 312 Beverage and Tobacco Products 251 30 227

402

table7.6_02.xls  

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

6 Quantity of Purchased Energy Sources, 2002; 6 Quantity of Purchased Energy Sources, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural LPG and Coal and Breeze RSE NAICS Total Electricity Fuel Oil Fuel Oil(b) Gas(c) NGL(d) (million (million Other(e) Row Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) Factors Total United States RSE Column Factors: 0.9 0.9 1.2 1.5 0.9 1.5 0.8 0.6 1.1 311 Food 1,082 W 2 3 566 1 9 * 40 8.2 311221 Wet Corn Milling 220 W * * 59 * 6 0 9 1.1 31131 Sugar 71 733 * * 22 * 2 * 3 1 311421 Fruit and Vegetable Canning 47 1,987 * * 35 * 0 0 1 12.6

403

table6.4_02.xls  

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

4 Consumption Ratios of Fuel, 2002; 4 Consumption Ratios of Fuel, 2002; Level: National Data; Row: Employment Sizes within NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value RSE NAICS per Employee of Value Added of Shipments Row Code(a) Economic Characteristic(b) (million Btu) (thousand Btu) (thousand Btu) Factors Total United States RSE Column Factors: 1.1 1 1 311 - 339 ALL MANUFACTURING INDUSTRIES Employment Size Under 50 395.7 4.3 2.3 3.6 50-99 663.4 6.8 3.3 5 100-249 905.8 7.9 3.8 3.6 250-499 1,407.1 11.1 5.1 4.3 500-999 1,999.6 12.4 5.9 5.6 1000 and Over 1,597.7 8.5 3.9 2.5 Total 1,172.2 8.9 4.2 2 311 FOOD Employment Size Under 50 893.5 6.6 2.4

404

table10.11_02.xls  

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

1 Number of Establishments with Capability to Switch Coal to Alternative Energy Sources, 2002; 1 Number of Establishments with Capability to Switch Coal to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. RSE NAICS Total Not Electricity Natural Distillate Residual Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Fuel Oil LPG Other(f) Factors Total United States RSE Column Factors: 1.5 1.2 1.5 0.7 1.1 0.8 1.1 1 0.5 311 Food 91 50 92 0 26 Q Q W W 10.7 311221 Wet Corn Milling 19 8 17 0 7 0 0 W W 0.9 31131 Sugar 24 13 22 0 11 0 4 0 W 0.9 311421 Fruit and Vegetable Canning 0 0 0 0 0 0 0 0 0 0 312 Beverage and Tobacco Products 17 8 12 0 7 W 5 0 0 5.3 3121 Beverages 9 5 5 0 W W W 0 0 8.5

405

table11.3_02.xls  

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

3 Electricity: Components of Onsite Generation, 2002; 3 Electricity: Components of Onsite Generation, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Onsite-Generation Components; Unit: Million Kilowatthours. Renewable Energy (excluding Wood RSE NAICS Total Onsite and Row Code(a) Subsector and Industry Generation Cogeneration(b) Other Biomass)(c) Other(d) Factors Total United States RSE Column Factors: 0.9 0.8 1.1 1.3 311 Food 5,622 5,375 0 247 12.5 311221 Wet Corn Milling 2,755 2,717 0 38 2.6 31131 Sugar 1,126 1,077 0 48 1 311421 Fruit and Vegetable Canning 388 W 0 W 1 312 Beverage and Tobacco Products W W * 1 1.6 3121 Beverages W W * * 3.8 3122 Tobacco W W 0 1 1 313 Textile Mills W 138 W W 11.9 314 Textile Product Mills 55 49 Q * 2.1

406

table3.3_02.xls  

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

Fuel Consumption, 2002; Fuel Consumption, 2002; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: Trillion Btu. RSE Economic Net Residual Distillate Natural LPG and Coke and Row Characteristic(a) Total Electricity(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) Coal Breeze Other(f) Factors Total United States RSE Column Factors: 0.6 0.7 1.3 2.1 0.7 1.4 1.5 0.7 0.9 Value of Shipments and Receipts (million dollars) Under 20 1,312 436 15 50 598 W 47 W 132 13.9 20-49 1,465 407 28 22 590 W 112 W 289 6.9 50-99 1,598 394 17 W 731 7 185 W 237 4.5 100-249 2,385 561 43 17 972 8 253 7 525 4.2 250-499 2,598 458 57 W 826 W 326 W 906 5.4 500 and Over 6,914 584 47 21 2,077 55 259 530 3,342 1.5 Total 16,273 2,840

407

table4.2_02.xls  

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

Offsite-Produced Fuel Consumption, 2002; Offsite-Produced Fuel Consumption, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. RSE NAICS Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Total Electricity(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) Coal and Breeze Other(f) Factors Total United States RSE Column Factors: 0.8 0.8 1.1 1.6 0.9 1.8 0.7 0.7 1.2 311 Food 1,079 233 13 19 575 5 184 1 50 8 311221 Wet Corn Milling 217 24 * * 61 * 121 0 11 1.1 31131 Sugar 74 3 2 1 22 * 37 1 8 1 311421 Fruit and Vegetable Canning 47 7 1 1 36 Q 0 0 1 12.4 312 Beverage and Tobacco Products 104 27 2 2 46 1 17 0 9 4.3 3121 Beverages 84 22 1 2 42 1 8 0 9 5.9 3122 Tobacco 19 5 1 * 4 * 10 0 * 0.9 313 Textile Mills 206 87 4 2 74 2

408

table5.4_02  

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

4 End Uses of Fuel Consumption, 2002; 4 End Uses of Fuel Consumption, 2002; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Net Demand Fuel Oil Coal RSE NAICS for Residual and Natural LPG and (excluding Coal Row Code(a) End Use Electricity(b) Fuel Oil Diesel Fuel(c) Gas(d) NGL(e) Coke and Breeze) Factors Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES RSE Column Factors: NF 1 2.4 1.1 1.3 1 TOTAL FUEL CONSUMPTION 3,297 208 141 5,794 103 1,182 3.3 Indirect Uses-Boiler Fuel 23 127 25 2,162 8 776 5.5 Conventional Boiler Use 11 76 25 1,306 8 255 5.6 CHP and/or Cogeneration Process 12 51 10 857 * 521 3.7 Direct Uses-Total Process 2,624

409

table10.6_02.xls  

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

6 Capability to Switch Electricity to Alternative Energy Sources, 2002; 6 Capability to Switch Electricity to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Million Kilowatthours. Coal Coke RSE NAICS Total Not Natural Distillate Residual and Row Code(a) Subsector and Industry Receipts(c) Switchable Switchable Gas Fuel Oil Fuel Oil Coal LPG Breeze Other(d) Factors Total United States RSE Column Factors: 0.9 1.4 0.9 1.6 1.7 0.6 0.8 1.7 0.5 0.9 311 Food 68,230 2,270 49,890 239 2,125 17 9 72 0 Q 12.2 311221 Wet Corn Milling 7,098 77 6,062 77 0 0 0 0 0 0 0.9 31131 Sugar 733 21 602 * 11 9 9 0 0 * 1 311421 Fruit and Vegetable Canning 1,987 Q 1,764 Q Q 0 0 25

410

table5.7_02.xls  

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

7 End Uses of Fuel Consumption, 2002; 7 End Uses of Fuel Consumption, 2002; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Net Demand Fuel Oil Coal for Residual and Natural LPG and (excluding Coal RSE Electricity(a) Fuel Oil Diesel Fuel(b) Gas(c) NGL(d) Coke and Breeze) Row End Use (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) (million short tons) Factors Total United States RSE Column Factors: 0.3 2.4 1.1 1.4 1 0 TOTAL FUEL CONSUMPTION 966,231 33 24 5,641 26 53 3.4 Indirect Uses-Boiler Fuel 6,714 20 6 2,105 2 35 5.3 Conventional Boiler Use 3,199 12 4 1,271 2 11 5.6 CHP and/or Cogeneration Process 3,515 8 2

411

table7.4_02.xls  

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

4 Average Prices of Selected Purchased Energy Sources, 2002; 4 Average Prices of Selected Purchased Energy Sources, 2002; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: U.S. Dollars per Physical Units. Residual Distillate Natural LPG and RSE Economic Electricity Fuel Oil Fuel Oil(b) Gas(c) NGL(d) Coal Row Characteristic(a) (kWh) (gallons) (gallons) (1000 cu ft) (gallons) (short tons) Factors Total United States RSE Column Factors: 0.7 1.2 2.2 0.7 0.5 1.6 Value of Shipments and Receipts (million dollars) Under 20 0.067 0.6 1.01 5.05 0.9 60.2 11.2 20-49 0.056 0.55 0.89 4.69 0.88 40.36 6.5 50-99 0.05 0.61 0.91 4.21 0.62 47.85 4.7 100-249 0.043 0.59 0.92 3.84 0.45 41.33 5.5 250-499 0.038 0.52 0.79 3.94

412

table10.2_02.xls  

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

2 Capability to Switch Natural Gas to Alternative Energy Sources, 2002; 2 Capability to Switch Natural Gas to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Billion Cubic Feet. Coal Coke RSE NAICS Total Not Electricity Distillate Residual and Row Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Fuel Oil Fuel Oil Coal LPG Breeze Other(e) Factors Total United States RSE Column Factors: 0.8 1 0.9 1.6 1 1 1.1 1.1 0.5 1.3 311 Food 560 155 298 20 70 40 2 63 * Q 12 311221 Wet Corn Milling 59 11 41 3 3 3 * 4 0 * 2 31131 Sugar 22 7 10 * 2 5 * 0 * 0 1 311421 Fruit and Vegetable Canning 35 10 19 2 6 2 * 1 * * 5.5 312 Beverage and Tobacco Products

413

table7.5_02.xls  

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

5 Average Prices of Selected Purchased Energy Sources, 2002; 5 Average Prices of Selected Purchased Energy Sources, 2002; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: U.S. Dollars per Million Btu. RSE Economic Residual Distillate Natural LPG and Row Characteristic(a) Electricity Fuel Oil Fuel Oil(b) Gas(c) NGL(d) Coal Factors Total United States RSE Column Factors: 0.7 1.2 2.2 0.7 0.5 1.6 Value of Shipments and Receipts (million dollars) Under 20 19.67 3.98 7.29 4.91 9.79 2.57 11.3 20-49 16.48 3.64 6.42 4.57 9.97 1.77 6.5 50-99 14.79 4.07 6.53 4.1 7.14 2.11 4.7 100-249 12.72 3.94 6.6 3.74 5.2 1.87 5.5 250-499 11.2 3.46 5.69 3.84 5.97 1.74 4.6 500 and Over 11.64 3.88 5.23 3.48 5.83 1.84 1.7 Total 14.13

414

table2.2_02.xls  

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

2 Nonfuel (Feedstock) Use of Combustible Energy, 2002; 2 Nonfuel (Feedstock) Use of Combustible Energy, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. RSE NAICS Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Total Fuel Oil Fuel Oil(b) Gas(c) NGL(d) Coal and Breeze Other(e) Factors Total United States RSE Column Factors: 1.4 0.4 1.6 1.2 1.2 1.1 0.7 1.2 311 Food 8 * Q 7 0 0 * * 10.2 311221 Wet Corn Milling * 0 * 0 0 0 0 * 0.7 31131 Sugar * 0 * * 0 0 * * 0.9 311421 Fruit and Vegetable Canning * * * 0 0 0 0 * 1.7 312 Beverage and Tobacco Products 1 * * * 0 0 0 1 2.3 3121 Beverages * * * 0 0 0 0 * 28.9 3122 Tobacco 1 0 0 * 0 0 0 1 0.8 313 Textile Mills 1 0 * 1 0 0 0 * 0.8 314 Textile Product Mills * 0 0 * 0 * 0 * 2 315 Apparel

415

table6.3_02.xls  

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

3 Consumption Ratios of Fuel, 2002; 3 Consumption Ratios of Fuel, 2002; Level: National Data; Row: Values of Shipments within NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value RSE NAICS per Employee of Value Added of Shipments Row Code(a) Economic Characteristic(b) (million Btu) (thousand Btu) (thousand Btu) Factors Total United States RSE Column Factors: 1 1 1 311 - 339 ALL MANUFACTURING INDUSTRIES Value of Shipments and Receipts (million dollars) Under 20 281.0 3.9 2.2 3 20-49 583.7 6.1 3.0 4.6 50-99 889.2 8.1 3.8 4.9 100-249 1,268.8 8.7 4.1 4.6 250-499 2,146.6 11.2 5.3 7.6 500 and Over 3,807.1 12.5 5.4 2.3 Total 1,172.2 8.9 4.2 2 311 FOOD Value of Shipments and Receipts

416

table7.9_02.xls  

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

9 Expenditures for Purchased Energy Sources, 2002; 9 Expenditures for Purchased Energy Sources, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Million U.S. Dollars. RSE NAICS Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Total Electricity Fuel Oil Fuel Oil(b) Gas(c) NGL(d) Coal and Breeze Other(e) Factors Total United States RSE Column Factors: 0.9 0.9 1.1 1.5 0.9 1.4 0.8 0.7 1.2 311 Food 6,943 3,707 58 135 2,546 38 276 8 175 8 311221 Wet Corn Milling 683 252 2 1 237 * 165 0 26 1.1 31131 Sugar 224 39 11 8 84 * 63 8 10 1 311421 Fruit and Vegetable Canning 333 139 5 8 168 Q 0 0 4 13.5 312 Beverage and Tobacco Products 780 479 8 18 201 9 40 0 25 5.8 3121 Beverages 665 413 4 Q 182 8 16 0 25 5.6 3122 Tobacco 115

417

table4.1_02.xls  

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

1 Offsite-Produced Fuel Consumption, 2002; 1 Offsite-Produced Fuel Consumption, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural LPG and Coal and Breeze RSE NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) (million (million Other(f) Row Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) Factors Total United States RSE Column Factors: 0.8 0.8 1.1 1.6 0.9 1.8 0.7 0.7 1.2 311 Food 1,079 68,230 2 3 560 1 8 * 50 8 311221 Wet Corn Milling 217 7,098 * * 59 * 5 0 11 1.1 31131 Sugar 74 733 * * 22 * 2 * 8 1 311421 Fruit and Vegetable Canning 47 1,987 * * 35 * 0

418

table10.7_02.xls  

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

7 Number of Establishments with Capability to Switch Electricity to Alternative Energy Sources, 2002; 7 Number of Establishments with Capability to Switch Electricity to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Natural Distillate Residual and Row Code(a) Subsector and Industry Receipts(d) Switchable Switchable Gas Fuel Oil Fuel Oil Coal LPG Breeze Other(e) Factors Total United States RSE Column Factors: 0.6 1.2 0.6 1.2 1.3 1 0.8 1.4 1.3 1.2 311 Food 15,045 582 14,905 185 437 30 W 170 0 55 11.4 311221 Wet Corn Milling 49 W W W 0 0 0 0 0 0 1.2 31131 Sugar 77 8 74 W 4 W W 0 0 W 1.1 311421 Fruit and Vegetable Canning 468 37 443 Q 34 0 0 13 0 0 10.4 312 Beverage and Tobacco Products 1,595 70 1,556

419

Predicting structure in nonsymmetric sparse matrix factorizations  

Science Conference Proceedings (OSTI)

Many computations on sparse matrices have a phase that predicts the nonzero structure of the output, followed by a phase that actually performs the numerical computation. We study structure prediction for computations that involve nonsymmetric row and column permutations and nonsymmetric or non-square matrices. Our tools are bipartite graphs, matchings, and alternating paths. Our main new result concerns LU factorization with partial pivoting. We show that if a square matrix A has the strong Hall property (i.e., is fully indecomposable) then an upper bound due to George and Ng on the nonzero structure of L + U is as tight as possible. To show this, we prove a crucial result about alternating paths in strong Hall graphs. The alternating-paths theorem seems to be of independent interest: it can also be used to prove related results about structure prediction for QR factorization that are due to Coleman, Edenbrandt, Gilbert, Hare, Johnson, Olesky, Pothen, and van den Driessche.

Gilbert, J.R. (Xerox Palo Alto Research Center, CA (United States)); Ng, E.G. (Oak Ridge National Lab., TN (United States))

1992-10-01T23:59:59.000Z

420

A Satellite Study of the Relationship between Sea Surface Temperature and Column Water Vapor over Tropical and Subtropical Oceans  

Science Conference Proceedings (OSTI)

The known characteristics of the relationship between sea surface temperature (SST) and column water vapor (CWV) are reevaluated with recent satellite observations over tropical and subtropical oceans. Satellite data acquired by the Aqua Advanced ...

Kaya Kanemaru; Hirohiko Masunaga

2013-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "rse column factors" from the National Library of EnergyBeta (NLEBeta).
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to obtain the most current and comprehensive results.


421

Intercomparison and Interpretation of Single-Column Model Simulations of a Nocturnal Stratocumulus-Topped Marine Boundary Layer  

Science Conference Proceedings (OSTI)

Ten single-column models (SCMs) from eight groups are used to simulate a nocturnal nonprecipitating marine stratocumulus-topped mixed layer as part of an intercomparison organized by the Global Energy and Water Cycle Experiment Cloud System Study,...

Ping Zhu; Christopher S. Bretherton; Martin Köhler; Anning Cheng; Andreas Chlond; Quanzhen Geng; Phil Austin; Jean-Christophe Golaz; Geert Lenderink; Adrian Lock; Bjorn Stevens

2005-09-01T23:59:59.000Z

422

Lipid Analysis and Lipidomics: New Techniques & ApplicationChapter 10 Lipid Separations Using Packed-Column Supercritical Fluid Chromatography  

Science Conference Proceedings (OSTI)

Lipid Analysis and Lipidomics: New Techniques & Application Chapter 10 Lipid Separations Using Packed-Column Supercritical Fluid Chromatography Methods and Analyses eChapters Methods - Analyses Books AOCS Press Downloadabl

423

Extreme Chromatography: Faster, Hotter, SmallerChapter 5 High-efficiency Liquid Chromatography Separations Achieved by Monolithic Silica Columns  

Science Conference Proceedings (OSTI)

Extreme Chromatography: Faster, Hotter, Smaller Chapter 5 High-efficiency Liquid Chromatography Separations Achieved by Monolithic Silica Columns Methods and Analyses eChapters Methods - Analyses Books AOCS Press Downloada

424

Adaptive Soil Moisture Profile Filtering for Horizontal Information Propagation in the Independent Column-Based CLM2.0  

Science Conference Proceedings (OSTI)

Data assimilation aims to provide an optimal estimate of the overall system state, not only for an observed state variable or location. However, large-scale land surface models are typically column-based and purely random ensemble perturbation of ...

Gabriëlle J. M. De Lannoy; Paul R. Houser; Niko E. C. Verhoest; Valentijn R. N. Pauwels

2009-06-01T23:59:59.000Z

425

Column Water Vapor Statistics and Their Relationship to Deep Convection, Vertical and Horizontal Circulation, and Moisture Structure at Nauru  

Science Conference Proceedings (OSTI)

Relationships among relatively high-frequency probability distribution functions (pdfs) of anomalous column water vapor (cwv), precipitating deep convection, and the vertical and horizontal structures of circulation and tropospheric moisture are ...

Benjamin R. Lintner; Christopher E. Holloway; J. David Neelin

2011-10-01T23:59:59.000Z

426

Enrichment of heavy water in flat-plate thermal diffusion columns of the Frazier scheme inclined for improved performance  

SciTech Connect

A separation theory for the enrichment of heavy water in flat-plate thermal diffusion columns of the Frazier scheme inclined for improved performance has been developed. Equations for the best angle of inclination and maximum separation have been derived. Considerable improvement in separation is obtainable if the columns are inclined at the best angle, so that the convective strength can be properly reduced and controlled, resulting in suppression of the undesirable remixing effect while still preserving the desirable cascading effect.

Ho-Ming Yeh [Tamkang Univ., Taiwan (China)

1995-04-01T23:59:59.000Z

427

Cost/performance comparison between pulse columns and centrifugal contactors designed to process Clinch River Breeder Reactor fuel  

Science Conference Proceedings (OSTI)

A comparison between pulse columns and centrifugal contactors was made to determine which type of equipment was more advantageous for use in the primary decontamination cycle of a remotely operated fuel reprocessing plant. Clinch River Breeder Reactor (CRBR) fuel was chosen as the fuel to be processed in the proposed 1 metric tonne/day reprocessing facility. The pulse columns and centrifugal contactors were compared on a performance and total cost basis. From this comparison, either the pulse columns or the centrifugal contactors will be recommended for use in a fuel reprocessing plant built to reprocess CRBR fuel. The reliability, solvent exposure to radiation, required time to reach steady state, and the total costs were the primary areas of concern for the comparison. The pulse column units were determined to be more reliable than the centrifugal contactors. When a centrifugal contactor motor fails, it can be remotely changed in less than one eight hour shift. Pulse columns expose the solvent to approximately five times as much radiation dose as the centrifugal contactor units; however, the proposed solvent recovery system adequately cleans the solvent for either case. The time required for pulse columns to reach steady state is many times longer than the time required for centrifugal contactors to reach steady state. The cost comparison between the two types of contacting equipment resulted in centrifugal contactors costing 85% of the total cost of pulse columns when the contactors were stacked on three levels in the module. If the centrifugal contactors were all positioned on the top level of a module with the unoccupied volume in the module occupied by other equipment, the centrifugal contactors cost is 66% of the total cost of pulse columns. Based on these results, centrifugal contactors are recommended for use in a remotely operated reprocessing plant built to reprocess CRBR fuel.

Ciucci, J.A. Jr.

1983-12-01T23:59:59.000Z

428

A cost-effective differential mobility analyzer (cDMA) for multiple DMA column applications  

Science Conference Proceedings (OSTI)

In aerosol research and applications, a differential mobility analyzer (DMA) is now considered the standard tool for sizing and classifying monodisperse particles in the sub-micrometer and nanometer size ranges. However, DMA application at the pilot or industrial production scale remains infeasible because of the low mass throughput. A simple way to scale up DMA operation is to use multiple DMA columns. The manufacture and maintenance costs of existing DMAs, however, limit such a scale-up. A cost-effective DMA column (named cDMA) has thus been developed in this work to address the above issue. To reduce its manufacturing cost, the prototype was constructed using parts requiring little machining. The cDMA column was also designed for easy maintenance and easy variation of the classification length for any application-specified size range. In this study, prototypes with two particle classification lengths, 1.75 and 4.50 cm, were constructed and their performance was experimentally evaluated at sheath-to-aerosol flowrate ratios of 5:1, 10:1, and 15:1 via the tandem DMA (TDMA) technique. It was concluded that both prototype cDMAs, operated at a sheath/aerosol flowrate ratio less than 15:1 and with a polydisperse aerosol flowrate of 1.0 lpm, achieved sizing resolution comparable to that offered by Nano-DMA. The longer cDMA had comparable transmission efficiency to that of Nano-DMA, and the shorter cDMA exceeded the performance of Nano-DMA. Hence, the cDMA with the shorter (1.75 cm) classification length is better suited for the characterization of macromolecular samples.

Mei, F.; Fu, H.; Chen, D.-R.

2011-05-04T23:59:59.000Z

429

Heavy Oil Process Monitor: Automated On-Column Asphaltene Precipitation and Re-Dissolution  

Science Conference Proceedings (OSTI)

An automated separation technique was developed that provides a new approach to measuring the distribution profiles of the most polar, or asphaltenic components of an oil, using a continuous flow system to precipitate and re-dissolve asphaltenes from the oil. Methods of analysis based on this new technique were explored. One method based on the new technique involves precipitation of a portion of residua sample in heptane on a polytetrafluoroethylene-packed (PTFE) column. The precipitated material is re-dissolved in three steps using solvents of increasing polarity: cyclohexane, toluene, and methylene chloride. The amount of asphaltenes that dissolve in cyclohexane is a useful diagnostic of the thermal history of oil, and its proximity to coke formation. For example, about 40 % (w/w) of the heptane asphaltenes from unpyrolyzed residua dissolves in cyclohexane. As pyrolysis progresses, this number decrease to below 15% as coke and toluene insoluble pre-coke materials appear. Currently, the procedure for the isolation of heptane asphaltenes and the determination of the amount of asphaltenes soluble in cyclohexane spans three days. The automated procedure takes one hour. Another method uses a single solvent, methylene chloride, to re-dissolve the material that precipitates on heptane on the PTFE-packed column. The area of this second peak can be used to calculate a value which correlates with gravimetric asphaltene content. Currently the gravimetric procedure to determine asphaltenes takes about 24 hours. The automated procedure takes 30 minutes. Results for four series of original and pyrolyzed residua were compared with data from the gravimetric methods. Methods based on the new on-column precipitation and re-dissolution technique provide significantly more detail about the polar constituent's oils than the gravimetric determination of asphaltenes.

John F. Schabron; Joseph F. Rovani; Mark Sanderson

2007-03-31T23:59:59.000Z

430

ADVANCED DIAGNOSTIC TECHNIQUES FOR THREE-PHASE SLURRY BUBBLE COLUMN REACTORS(SBCR)  

SciTech Connect

The objectives set for this cooperative project between Washington University (WU), Ohio State University (OSU), and Air Products and Chemicals, Inc. (APCI) to advance the understanding of the Fischer-Tropsch (FT) slurry bubble column reactor hydrodynamics for proper design and scale-up via advanced diagnostic techniques have been accomplished successfully despite the unexpected challenging technical difficulties in implementing the advanced techniques in high pressure stainless steel slurry bubble column. In this work, a detailed review of the aspects of high pressure phenomena of bubbles in liquids and liquid-solids suspension was performed. All the challenging technical problems mentioned above were resolved and the advanced measurement techniques were successfully used in this project. The effects of reactor pressure, superficial gas velocity, solids loading, and liquid physical properties on the overall gas holdup, holdups distribution, recirculation velocity, turbulent parameters, bubble dynamics (size and rise velocity) were investigated via advanced measurement techniques that includes optical probe, Laser Doppler Anemometry (LDA), Computed Tomography (CT), Computer Automated Radioactive Particle Tracking (CARPT). The findings are discussed and analyzed in this report. In attempt to advance the design and scale-up of bubble columns, new correlations have been developed based on a large bank of data collected at a wide range of operating and design conditions. These correlations are for prediction of radial gas holdup profile, axial liquid velocity profile, overall gas holdup based on Neural Network and gas-liquid mass transfer coefficient. Despite the noticeable advances made on FT SBCR as a part of this project, there are still many parameters and challenging issues that need to be further and properly investigated and understood before this technology will be readily used for alternative fuel development technology.

M.H. Al-Dahhan; L.S. Fan; M.P. Dudukovic

2003-08-01T23:59:59.000Z

431

" Row: NAICS Codes; Column: Energy-Consumption Ratios;"  

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

1 Consumption Ratios of Fuel, 2006;" 1 Consumption Ratios of Fuel, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy-Consumption Ratios;" " Unit: Varies." ,,,,"Consumption" ,,,"Consumption","per Dollar" ,,"Consumption","per Dollar","of Value" "NAICS",,"per Employee","of Value Added","of Shipments" "Code(a)","Subsector and Industry","(million Btu)","(thousand Btu)","(thousand Btu)" ,,"Total United States" 311,"Food",879.8,5,2.2 3112," Grain and Oilseed Milling",6416.6,17.5,5.7

432

Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected;  

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

Table 7.1 Average Prices of Purchased Energy Sources, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Physical Units. Selected Wood and Other Biomass Components Coal Components Coke Electricity Components Natural Gas Components Steam Components Total Wood Residues Bituminous Electricity Diesel Fuel Motor Natural Gas Steam and Wood-Related and Electricity from Sources and Gasoline Pulping Liquor Natural Gas from Sources Steam from Sources Waste Gases Waste Oils Industrial Wood Byproducts and Coal Subbituminous Coal Petroleum Electricity from Local Other than Distillate Diesel Distillate Residual Blast Furnace Coke Oven (excluding or LPG and Natural Gas

433

Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected;  

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

Next MECS will be conducted in 2010 Table 7.2 Average Prices of Purchased Energy Sources, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Million Btu. Selected Wood and Other Biomass Components Coal Components Coke Electricity Components Natural Gas Components Steam Components Total Wood Residues Bituminous Electricity Diesel Fuel Motor Natural Gas Steam and Wood-Related and Electricity from Sources and Gasoline Pulping Liquor Natural Gas from Sources Steam from Sources Waste Gases Waste Oils Industrial Wood Byproducts and Coal Subbituminous Coal Petroleum Electricity from Local Other than Distillate Diesel Distillate Residual Blast Furnace

434

Working Group Reports Summary of Single-Column Model Intensive Observation  

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

Working Group Reports Summary of Single-Column Model Intensive Observation Period Workshop at Annual Atmospheric Radiation Measurement Science Team Meeting D. A. Randall Department of Atmospheric Science Colorado State University Fort Collins, Colorado R. T. Cederwall Lawrence Livermore National Laboratory Livermore, California * Study previous observation simulation system experiments (OSSEs) (i.e., Bill Frank, Pennsylvania State University [PSU]) and conduct OSSEs as necessary to evaluate data network. * Implement additional "boundary" facilities and investigate possible interim capabilities for upcoming SCM IOPs. * Improve resolution of wind profiles observed in lowest 1 km, using data sources such as towers of opportunity, doppler sodar, and doppler radar.

435

Field-error induced transport in a pure electron plasma column  

SciTech Connect

The long confinement times achieved in experiments on pure electron plasmas are explainable in terms of the conservation of canonical angular momentum in azimuthally symmetic systems. A low-density, pure electron plasma is considered, and the effect of disrupting the system's symmetry by introducing a small, magnetic field error is investigated. It is found that this external perturbation can resonantly drive low-frequency waves that couple back to the field error and produce a change in the plasma's angular momentum. This results in changing the radius of the column.

Keinigs, R.

1984-06-01T23:59:59.000Z

436

Final Report - Advanced Hydraulic and Mass Transfer Models for Distillation Column Optimization and Design  

Science Conference Proceedings (OSTI)

The project successfully developed a computational fluid dynamics (CFD) based simulation of the hydrodynamics of flow in a commercial structured packing element. This result fulfilled the prime objective of the research program. The simulation utilized commercial CFD code marketed by Fluent Inc. in combination with a novel graphical interface developed by Oak Ridge National Lab. The end product will allow the design of next generation column internals without the need for extensive experimental validation and will expand the fundamental understanding of the vapor-liquid contacting process.

Eldridge, Robert, B.

2005-10-13T23:59:59.000Z

437

Nonlinear wave loads on a three-column TLP in real seas  

E-Print Network (OSTI)

Nonlinear wave loads are essential in design of offshore structures. In this study an analysis model for nonlinear wave loads was improved by introducing a quasi-linear transfer function which incorporates both linear- and quadratic- transfer functions. The analysis model is first demonstrated by computing wave loads on a truncated column in experimental regular wave and irregular waves. The general trend of the quasi-linear transfer function LTF* is investigated. Time series of wave forces are computed and compared with experimental results. The model was confirmed through good agreement between experiment and prediction results. The analysis model is then applied to a three-column TLP. A real field wave, which is quite non-Gaussian, is used as input. Linear and second-order force time series in surge, pitch and heave directions are predicted. Time series of nonlinear force is obtained, and statistics of the wave loads are investigated. Second order wave loads in higher and lower frequency are highlighted. Finally, the nonlinear wave loads are applied to the TLP finite element analysis model to simulate the nonlinear motion and tendon tensions. The time domain simulations are transformed to the frequency amplitude spectra, from which high-frequency resonance and slowly-varying motion are investigated.

Wang, Zhongmin

2000-01-01T23:59:59.000Z

438

PLUTONIUM LOADING CAPACITY OF REILLEX HPQ ANION EXCHANGE COLUMN - AFS-2 PLUTONIUM FLOWSHEET FOR MOX  

SciTech Connect

Radioactive plutonium (Pu) anion exchange column experiments using scaled HB-Line designs were performed to investigate the dependence of column loading performance on the feed composition in the H-Canyon dissolution process for plutonium oxide (PuO{sub 2}) product shipped to the Mixed Oxide (MOX) Fuel Fabrication Facility (MFFF). These loading experiments show that a representative feed solution containing {approx}5 g Pu/L can be loaded onto Reillex{trademark} HPQ resin from solutions containing 8 M total nitrate and 0.1 M KF provided that the F is complexed with Al to an [Al]/[F] molar ratio range of 1.5-2.0. Lower concentrations of total nitrate and [Al]/[F] molar ratios may still have acceptable performance but were not tested in this study. Loading and washing Pu losses should be relatively low (<1%) for resin loading of up to 60 g Pu/L. Loading above 60 g Pu/L resin is possible, but Pu wash losses will increase such that 10-20% of the additional Pu fed may not be retained by the resin as the resin loading approaches 80 g Pu/L resin.

Kyser, E.; King, W.; O'Rourke, P.

2012-07-26T23:59:59.000Z

439

table2.1_02.xls  

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

1 Nonfuel (Feedstock) Use of Combustible Energy, 2002; 1 Nonfuel (Feedstock) Use of Combustible Energy, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural LPG and Coal and Breeze NAICS Total Fuel Oil Fuel Oil(b) Gas(c) NGL(d) (million (million Other(e) Code(a) Subsector and Industry (trillion Btu) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States RSE Column Factors: 1.4 0.4 1.6 1.2 1.2 1.1 0.7 1.2 311 Food 8 * * 7 0 0 * * 311221 Wet Corn Milling * 0 * 0 0 0 0 * 31131 Sugar * 0 * * 0 0 * * 311421 Fruit and Vegetable Canning * * * 0 0 0 0 * 312 Beverage and Tobacco Products 1 * * * 0 0 0 1 3121 Beverages * * * 0 0 0 0 *

440

Conversion factors for energy equivalents: All factors  

Science Conference Proceedings (OSTI)

... Conversion factors for energy equivalents Return to online conversions. Next page of energy equivalents. Definition of uncertainty ...

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


441

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity;  

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

6 End Uses of Fuel Consumption, 2006; 6 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Residual and LPG and (excluding Coal End Use Total Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Other(e) Total United States TOTAL FUEL CONSUMPTION 15,658 2,850 251 129 5,512 79 1,016 5,820 Indirect Uses-Boiler Fue -- 41 133 23 2,119 8 547 -- Conventional Boiler Use 41 71 17 1,281 8 129 CHP and/or Cogeneration Process 0 62 6 838 1 417 Direct Uses-Total Process -- 2,244 62 52 2,788 39 412 -- Process Heating -- 346 59 19 2,487 32 345 -- Process Cooling and Refrigeration -- 206 * 1 32 * * -- Machine Drive

442

Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;  

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

2 End Uses of Fuel Consumption, 2006; 2 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Residual and LPG and (excluding Coal Code(a) End Use Total Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Other(f) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 15,658 2,850 251 129 5,512 79 1,016 5,820 Indirect Uses-Boiler Fuel -- 41 133 23 2,119 8 547 -- Conventional Boiler Use -- 41 71 17 1,281 8 129 -- CHP and/or Cogeneration Process -- -- 62 6 838 1 417 -- Direct Uses-Total Process -- 2,244 62 52 2,788 39 412 -- Process Heating -- 346 59 19 2,487

443

Global Collaboration in Clean Fossil Energy A Column from the Deputy Assistant Secretary  

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

6, Second Quarter, 2012 6, Second Quarter, 2012 www.fossil.energy.gov/news/energytoday.html HigHligHts inside 2 Global Collaboration in Clean Fossil Energy A Column from the Deputy Assistant Secretary for International Affairs 3 Exchanging CO 2 for Methane An Update on Methane Hydrate Testing on Alaska's North Slope 4 McConnell Confirmed Charles McConnell Sworn in As 12th Assistant Secretary for Fossil Energy in April 5 Hydrogen-Based Fuel Cells New Catalyst Technology Reduces Diesel Engine Idling 7 Petroleum Reserves Degas Program Ensures Crude Oil Always Ready for Use One of the world's fastest supercomputers will be installed at the National Energy Technology Laboratory this summer to help develop solutions to carbon capture, utilization and

444

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;  

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

Next MECS will be conducted in 2010 Table 5.8 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Demand Residual and LPG and (excluding Coal End Use for Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Total United States TOTAL FUEL CONSUMPTION 3,335 251 129 5,512 79 1,016 Indirect Uses-Boiler Fuel 84 133 23 2,119 8 547 Conventional Boiler Use 84 71 17 1,281 8 129 CHP and/or Cogeneration Process 0 62 6 838 1 417 Direct Uses-Total Process 2,639 62 52 2,788 39 412 Process Heating 379 59 19 2,487 32 345 Process Cooling and Refrigeration

445

Single-Column Modeling D. A. Randall and K.-M. Xu Colorado State University  

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

D. A. Randall and K.-M. Xu D. A. Randall and K.-M. Xu Colorado State University Department of Atmospheric Science Fort Collins, CO 80523 Introduction Our ARM project consists of developing and demonstrating improved cloud formation parameterizations by using both a single-column model (SCM) and a cumulus ensemble model (CEM), together with ARM data. These two models can be driven with "large-scale forcing" (e.g., vertical motion) as observed in ARM; each model produces a field of clouds and the associated radiation and precipitation fields. The SCM does so through its physical parameterizations, while the CEM does so by "directly simulating" convective cloud circulations. The improved parameterizations tested in this way will be further tested and applied in the Colorado State University (CSU) general

446

Level: National and Regional Data; Row: NAICS Codes; Column: Energy-Consumption Ratios;  

Gasoline and Diesel Fuel Update (EIA)

Next MECS will be fielded in 2015 Table 6.1 Consumption Ratios of Fuel, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value NAICS per Employee of Value Added of Shipments Code(a) Subsector and Industry (million Btu) (thousand Btu) (thousand Btu) Total United States 311 Food 871.7 4.3 1.8 3112 Grain and Oilseed Milling 6,239.5 10.5 3.6 311221 Wet Corn Milling 28,965.0 27.1 12.6 31131 Sugar Manufacturing 7,755.9 32.6 13.4 3114 Fruit and Vegetable Preserving and Specialty Foods 861.3 4.8 2.2 3115 Dairy Products 854.8 3.5 1.1 3116 Animal Slaughtering and Processing 442.9 3.5 1.2 312

447

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;  

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

7 End Uses of Fuel Consumption, 2006; 7 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(c) LPG and Coke and Breeze) for Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) Total United States TOTAL FUEL CONSUMPTION 977,338 40 22 5,357 21 46 Indirect Uses-Boiler Fuel 24,584 21 4 2,059 2 25 Conventional Boiler Use 24,584 11 3 1,245 2 6 CHP and/or Cogeneration Process 0 10 1 814 * 19 Direct Uses-Total Process 773,574 10 9 2,709 10 19 Process Heating

448

DOE/SC-ARM-11-017 The Two-Column Aerosol Project (TCAP) Science Plan  

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

7 7 The Two-Column Aerosol Project (TCAP) Science Plan CM Berkowitz Principal Investigator LK Berg RA Zaveri DJ Cziczo A Zelenyuk CJ Flynn RA Ferrare EI Kassianov CA Hostetler JD Fast B Cairns PJ Rasch PB Russell JE Shilling B Ervens July 2011 DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service

449

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity;  

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

5 End Uses of Fuel Consumption, 2006; 5 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(c) LPG and Coke and Breeze) Total Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million Other(e) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States TOTAL FUEL CONSUMPTION 15,658 835,382 40 22 5,357 21 46 5,820 Indirect Uses-Boiler Fuel -- 12,109 21 4 2,059 2 25 -- Conventional Boiler Use 12,109 11 3 1,245 2 6 CHP and/or Cogeneration Process 0 10 1 814 * 19 Direct Uses-Total Process

450

Level: National and Regional Data; Row: NAICS Codes; Column: Utility and Nonutility Purchasers;  

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

Next MECS will be conducted in 2010 Next MECS will be conducted in 2010 Table 11.5 Electricity: Sales to Utility and Nonutility Purchasers, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Utility and Nonutility Purchasers; Unit: Million Kilowatthours. Total of NAICS Sales and Utility Nonutility Code(a) Subsector and Industry Transfers Offsite Purchaser(b) Purchaser(c) Total United States 311 Food 111 86 25 3112 Grain and Oilseed Milling 72 51 21 311221 Wet Corn Milling 55 42 13 31131 Sugar Manufacturing 7 3 4 3114 Fruit and Vegetable Preserving and Specialty Foods 13 13 0 3115 Dairy Products 0 0 0 3116 Animal Slaughtering and Processing 0 0 0 312 Beverage and Tobacco Products * * 0 3121 Beverages

451

ARM - Midlatitude Continental Convective Clouds - Single Column Model Forcing (xie-scm_forcing)  

Science Conference Proceedings (OSTI)

The constrained variational objective analysis approach described in Zhang and Lin [1997] and Zhang et al. [2001]was used to derive the large-scale single-column/cloud resolving model forcing and evaluation data set from the observational data collected during Midlatitude Continental Convective Clouds Experiment (MC3E), which was conducted during April to June 2011 near the ARM Southern Great Plains (SGP) site. The analysis data cover the period from 00Z 22 April - 21Z 6 June 2011. The forcing data represent an average over the 3 different analysis domains centered at central facility with a diameter of 300 km (standard SGP forcing domain size), 150 km and 75 km, as shown in Figure 1. This is to support modeling studies on various-scale convective systems.

Shaocheng Xie; Renata McCoy; Yunyan Zhang

2012-10-25T23:59:59.000Z

452

Comparative study of two chromatographic columns used in the GLC determination of methylmercury  

SciTech Connect

A large effort has gone into finding an adequate analytical method for the determinations of methylmercury. Various stationary phases in GC determination have been tested. It was obvious with every method that the stationary phase had to be saturated to give a stable response without tailing the peaks or walking the retention time. To accomplish this several authors have reported treatments which included the injection of the solutions containing inorganic or organic mercuric chloride metoxyethylmercuric iodide, or large amount of potassium iodide. The authors report here a simple and efficient way to obtain satisfactory stable response from the chromatographic column based on the use of 10% diethyleneglycol adipate (DEGA) and 3% polyethyleneglycol (Carbowax 20 M).

Najdek, M.; Bazulic, D.

1985-02-01T23:59:59.000Z

453

Electron energy distribution functions in low-pressure oxygen plasma columns sustained by propagating surface waves  

Science Conference Proceedings (OSTI)

Electron energy distribution functions (EEDFs) were measured in a 50 mTorr oxygen plasma column sustained by propagating surface waves. Trace-rare-gas-optical-emission spectroscopy was used to derive EEDFs by selecting lines to extract ''electron temperature''(T{sub e}) corresponding to either lower energy electrons that excite high-lying levels through stepwise excitation via metastable states or higher energy electrons that excite emission directly from the ground state. Lower energy T{sub e}'s decreased from 8 to 5.5 eV with distance from the wave launcher, while T{sub e}{approx_equal}6 eV for higher energy electrons and T{sub e}>20 eV for a high-energy tail. Mechanisms for such EEDFs are discussed.

Stafford, L.; Margot, J.; Moisan, M. [Departement de Physique, Universite de Montreal, Montreal, Quebec H3C 3J7 (Canada); Khare, R.; Donnelly, V. M. [Department of Chemical and Biomolecular Engineering, University of Houston, Houston, Texas 77204 (United States)

2009-01-12T23:59:59.000Z

454

Mapping Metal-Enriched High Velocity Clouds to Very Low HI Column Densities  

E-Print Network (OSTI)

Our galaxy is the nearest known quasar absorption line system, and it uniquely provides us with an opportunity to probe multiple lines of sight through the same galaxy. This is essential for our interpretations of the complex kinematic profiles seen in the MgII absorption due to lines of sight through intermediate redshift galaxies. The Milky Way halo has never been probed for high velocity clouds below the 21-cm detection threshold of N(HI)~10^18 cm-2. Through a survey of MgII absorption looking toward the brightest AGNs and quasars, it will be possible to reach down a few orders of magnitude in HI column density. The analogs to the high velocity components of the MgII absorption profiles due to intermediate redshift galaxies should be seen. We describe a program we are undertaking, and present some preliminary findings.

Chris Churchill; Jane Charlton; Joe Masiero

2001-08-13T23:59:59.000Z

455

Method for enhancing selectivity and recovery in the fractional flotation of particles in a flotation column  

DOE Patents (OSTI)

The method relates to particle separation from a feed stream. The feed stream is injected directly into the froth zone of a vertical flotation column in the presence of a counter-current reflux stream. A froth breaker generates a reflux stream and a concentrate stream, and the reflux stream is injected into the froth zone to mix with the interstitial liquid between bubbles in the froth zone. Counter-current flow between the plurality of bubbles and the interstitial liquid facilitates the attachment of higher hydrophobicity particles to bubble surfaces as lower hydrophobicity particles detach. The height of the feed stream injection and the reflux ratio may be varied in order to optimize the concentrate or tailing stream recoveries desired based on existing operating conditions.

Klunder, Edgar B. (Bethel Park, PA)

2011-08-09T23:59:59.000Z

456

ARM - Midlatitude Continental Convective Clouds - Single Column Model Forcing (xie-scm_forcing)  

DOE Data Explorer (OSTI)

The constrained variational objective analysis approach described in Zhang and Lin [1997] and Zhang et al. [2001]was used to derive the large-scale single-column/cloud resolving model forcing and evaluation data set from the observational data collected during Midlatitude Continental Convective Clouds Experiment (MC3E), which was conducted during April to June 2011 near the ARM Southern Great Plains (SGP) site. The analysis data cover the period from 00Z 22 April - 21Z 6 June 2011. The forcing data represent an average over the 3 different analysis domains centered at central facility with a diameter of 300 km (standard SGP forcing domain size), 150 km and 75 km, as shown in Figure 1. This is to support modeling studies on various-scale convective systems.

Shaocheng Xie; Renata McCoy; Yunyan Zhang

457

Hydrodynamic characterization of slurry bubble-column reactors for Fischer-Tropsch synthesis  

DOE Green Energy (OSTI)

In the Fischer-Tropsch approach to indirect liquefaction, slurry bubble-column reactors (SBCRs) are used to convert coal syngas into the desired product. Sandia`s program to develop, implement, and apply diagnostics for hydrodynamic characterization of SBCRs at industrially relevant conditions is discussed.Gas-liquid flow experiments are performed in an industrial-scale stainless steel vessel. Gamma-densitometry tomography (GDT) is applied to make spatially resolved gas holdup measurements. Both water and Drakeol 10 with air sparging are examined at ambient and elevated pressures. Gas holdup increases with gas superficial velocity and pressure, and the GDT values are in good agreement with values from differential pressure (DP) measurements.

Jackson, N.B.; Torczynski, J.R.; Shollenberger, K.A.; O`Hern, T.J.; Adkins, D.R.

1996-08-01T23:59:59.000Z

458

Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;  

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

1 End Uses of Fuel Consumption, 2006; 1 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS Total Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Other(f) Code(a) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 15,658 835,382 40 22 5,357 21 46 5,820 Indirect Uses-Boiler Fuel -- 12,109 21 4 2,059 2 25 -- Conventional Boiler Use -- 12,109 11 3 1,245 2 6 -- CHP and/or Cogeneration Process

459

Level: National and Regional Data; Row: NAICS Codes; Column: Onsite-Generation Components;  

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

3 Electricity: Components of Onsite Generation, 2006; 3 Electricity: Components of Onsite Generation, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Onsite-Generation Components; Unit: Million Kilowatthours. Renewable Energy (excluding Wood NAICS Total Onsite and Code(a) Subsector and Industry Generation Cogeneration(b) Other Biomass)(c) Other(d) Total United States 311 Food 4,563 4,249 * 313 3112 Grain and Oilseed Milling 2,845 2,819 0 27 311221 Wet Corn Milling 2,396 2,370 0 27 31131 Sugar Manufacturing 951 951 0 * 3114 Fruit and Vegetable Preserving and Specialty Foods 268 268 0 * 3115 Dairy Products 44 31 * Q 3116 Animal Slaughtering and Processing 17 0 0 17 312 Beverage and Tobacco Products 659 623 Q * 3121 Beverages 587 551 Q * 3122 Tobacco 72

460

Hydrodynamic models for slurry bubble column reactors. Seventh technical progress report, January--March 1996  

DOE Green Energy (OSTI)

The objective of this investigation is to convert our ``learning gas solid-liquid`` fluidization model into a predictive design model. The IIT hydrodynamic model computes the phase velocities and the volume fractions of gas, liquid and particulate phase. Model verification involves a comparison of these computed velocities and volume fractions to experimental values. A hydrodynamic model for multiphase flows, based on the principles of mass, momentum and energy conservation for each phase, was developed and applied to model gas-liquid, gas-liquid-solid fluidization and gas-solid-solid separation. To simulate the industrial slurry bubble column reactors, a computer program based on the hydrodynamic model was written with modules for chemical reactions (e.g. the synthesis of methanol), phase changes and heat exchangers. In the simulations of gas-liquid two phases flow system, the gas hold-ups, computed with a variety of operating conditions such as temperature, pressure, gas and liquid velocities, agree well with the measurements obtained at Air Products` pilot plant. The hydrodynamic model has more flexible features than the previous empirical correlations in predicting the gas hold-up of gas-liquid two-phase flow systems. In the simulations of gas-liquid-solid bubble column reactors with and without slurry circulation, the code computes volume fractions, temperatures and velocity distributions for the gas, the liquid and the solid phases, as well as concentration distributions for the species (CO, H{sub 2}, CH{sub 3}0H, ... ), after startup from a certain initial state. A kinetic theory approach is used to compute a solid viscosity due to particle collisions. Solid motion and gas-liquid-solid mixing are observed on a color PCSHOW movie made from computed time series data. The steady state and time average catalyst concentration profiles, the slurry height and the rates of methanol production agree well with the measurements obtained at an Air Products` pilot plant.

Gidaspow, D.

1996-04-01T23:59:59.000Z

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


461

Report on Qiagen Columns with Precipitation versus Packed Bed Technology for Trace Amounts of DNA  

SciTech Connect

The assured limit of detection (LOD), where 100% of the PCR assays are successful, for the Qiagen spin column is dramatically improved when combined with an ethanol precipitation step of the eluted sample. A detailed SOP for the ethanol precipitation was delivered as a separate report. A key finding in the precipitation work was to incubate the ethanol precipitation at -20{sup o}C overnight when concentrating low copy number samples. Combining this modified ethanol precipitation with the Qiagen spin columns, the limit of assured detection was improved by 1-2 orders of magnitude, for the aliquot and assay variables used. The lower limit of detection (defined as when at least 1 assay of 1 aliquot was positive) was only improved by approximately 1 order of magnitude. The packed bed process has the potential of a 20-fold improvement in the limit of detection compared to Qiagen plus precipitation, based on a mass balance analysis for the entire DNA concentration and purification processes. Figure ES1 shows a mass balance for all the DNA processing steps. The packed bed process minimizes losses from elution, precipitation, and pipetting (aliquoting and transferring). Figure ES1 assumes that 100 copies of DNA serve as the input sample. Efficiencies for each step have been estimated based on our experiences or a worst case scenario (for example, a 50% loss was assumed for pipetting). Table ES1 summarizes the number of copies that are the input template for PCR assuming 100 copies of DNA are processed through the three options detailed in Figure ES1.Theoretically a 20-fold increase in the number of starting copies in the PCR reaction is gained when the DNA is concentrated, purified and then amplified directly on the surface of the beads in the packed bed.

Wheeler, E K; Erler, A M; Seiler, A

2008-02-05T23:59:59.000Z

462

Engineering Development of Slurry Bubble Column Reactor (SBCR) Technology: Final quarterly technical progress no. 2, 1 July - 30 September 1995  

DOE Green Energy (OSTI)

The major technical objectives of this program are threefold: (1) to develop the design tools and a fundamental understanding of the fluid dynamics of a slurry bubble column reactor to maximize reactor productivity, (2) to develop the mathematical reactor design models and gain an understanding of the hydrodynamic fundamentals under industrially relevant process conditions, and (3) to develop an understanding of the hydrodynamics and their interaction with the chemistries occurring in the bubble column reactor. Successful completion of these objectives will permit more efficient usage of the reactor column and tighter design criteria, increase overall reactor efficiency, and ensure a design that leads to stable reactor behavior when scaling up to large diameter reactors.

Toseland, B.A.; Tischer, R.E.

1997-12-31T23:59:59.000Z

463

Conversion factors for energy equivalents: All factors  

Science Conference Proceedings (OSTI)

... Previous page of energy equivalents. Definition of uncertainty notation eg, 123(45) | Basis of conversion factors for energy equivalents. Top. ...

464

A hybrid model for particle transport and electron energy distributions in positive column electrical discharges using equivalent species transport  

E-Print Network (OSTI)

A hybrid model for particle transport and electron energy distributions in positive column the fluid portion of the model. Transport coefficients, source functions, and energy distributions for all field has motivated a num- ber of investigations into its effect on the `electron energy distribution

Kushner, Mark

465

A comparison study of column flotation technologies for cleaning Illinois coal. [Quarterly] technical report, December 1, 1993--February 28, 1994  

Science Conference Proceedings (OSTI)

The objectives of this research project are to optimize the performance of six commercially available column technologies for the treatment of Illinois Basin coal fines and to compare their performance on the basis of the recovery-grade curve and column throughput capacity. A statistically-designed, experimental program will be conducted to optimize the critical operating performance values of each flotation column. During the previous reporting period, construction and installation of the six flotation columns were completed. The flotation feed sample that will be used for the tests in this investigation was collected from a coal preparation plant treating the Illinois No. 5 seam coal. During this reporting period, the flotation feed sample was characterized on a size-by-size basis for its ash, total sulfur, and BTU content. A release analysis was also conducted to obtain the best possible recovery versus product grade curve that can be achieved by a froth flotation process for the treatment of the Illinois No. 5 flotation feed sample. Experiments were initiated on the Jameson Cell. The preliminary results indicate that the Jameson Cell achieves a separation performance that is close to the release data. The experimental program on the Jameson Cell and the other flotation technologies will be performed during the next reporting period.

Honaker, R.Q.; Paul, B.C. [Southern Illinois Univ., Carbondale, IL (United States). Dept. of Mining Engineering

1994-06-01T23:59:59.000Z

466

Table 4  

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

4. Light Usage by Total Number of Rooms, Percent of U.S. 4. Light Usage by Total Number of Rooms, Percent of U.S. Households, 1993 Total Number of Rooms Housing Unit and Household Characteristics Total 1 or 2 3 to 5 6 to 8 9 or More RSE Column Factors: 0.5 2.6 0.7 0.7 1.6 RSE Row Factor Total....................................................... 100.0 100.0 100.0 100.0 100.0 0.0 Indoor Electric Lights Total Number Lights 1 to 4 Hours None................................................. 10.0 16.8 10.5 9.4 5.8 11.52 1 ....................................................... 22.9 36.5 27.7 17.8 10.7 5.96 2 ....................................................... 28.4 29.3 31.4 25.8 21.1 5.33 3 ....................................................... 17.4 11.1 16.5 18.7 19.0 7.20 4 ....................................................... 9.5 Q 6.7 12.8 13.5 10.03 5 or More ..........................................

467

Table 4  

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

9. Mean Annual Electricity Consumption for Lighting, by Family 9. Mean Annual Electricity Consumption for Lighting, by Family Income by Number of Household Members, 1993 (Kilowatthours) Number of Household Members Family Income All Households One Two Three Four Five or More RSE Column Factors: 0.6 1.4 0.8 1.2 1.0 1.3 RSE Row Factors All Households...................................... 940 604 923 1,023 1,198 1,265 2.02 Less than $10,000................................. 668 557 657 793 952 943 5.35 $10,000 to $14,999................................ 753 547 789 905 968 986 6.02 $15,000 to $19,999................................ 888 695 831 865 1,227 1,321 5.89 $20,000 to $24,999................................ 856 641 889 921 976 1,208 5.97 $25,000 to $34,999................................ 962 630 1,000 1,015 1,095 1,247 4.64 $35,000 to $49,999................................

468

appl_household2001.pdf  

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

a. Appliances by Climate Zone, a. Appliances by Climate Zone, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.1 Total .................................................. 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Kitchen Appliances Cooking Appliances Oven .............................................. 101.7 9.1 27.9 23.1 19.4 22.2 7.8 1 ................................................... 95.2 8.7 26.0 21.6 17.7 21.2 7.9 2 or More ..................................... 6.5 0.4 1.9 1.5 1.7 1.0 14.7 Most Used Oven ........................... 101.7 9.1 27.9 23.1 19.4 22.2

469

ac_household2001.pdf  

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

3a. Air Conditioning by Household Income, 3a. Air Conditioning by Household Income, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.9 1.5 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 12.3 17.4 21.5 31.7 9.6 23.4 3.9 Air Conditioners Not Used ............ 2.1 0.4 0.7 0.5 0.5 0.4 0.9 20.8 Households Using Electric Air-Conditioning 2 .......................... 80.8 11.9 16.7 21.0 31.2 9.1 22.6 3.9 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 .............. 57.5 6.2 10.7 15.2 25.3 4.5 12.4 5.3 Without a Heat Pump .................. 46.2 4.9 9.1 12.1 20.1 3.6 10.4 6.1 With a Heat Pump

470

Table 4  

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

7. Total Annual Electricity Expenditures for Lighting, by Number 7. Total Annual Electricity Expenditures for Lighting, by Number of Household Members, Million U.S. Households, 1993 Number of Household Members Electricity Expenditures (Dollars) Total One Two Three Four Five or More RSE Column Factors: 0.5 1.1 0.8 1.2 1.3 1.4 RSE Row Factors All Households................................... 96.6 23.5 31.7 16.6 14.6 10.2 2.56 25 or Less ........................................... 9.2 5.7 2.5 0.5 0.2 0.2 13.05 26 to 50 ............................................... 21.0 7.8 7.5 3.1 1.5 1.1 6.34 51 to 75 ............................................... 21.7 4.7 7.8 4.0 3.3 2.0 5.30 76 to 100 ............................................. 16.1 2.4 5.1 3.2 3.2 2.1 6.57 101 to 125 ........................................... 11.1 1.3 3.7 2.4 2.1 1.5 8.06 126 to 150 ...........................................

471

homeoffice_household2001.pdf  

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

2a. Home Office Equipment by Year of Construction, 2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.4 1.1 1.1 1.2 1.2 1.0 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Households Using Office Equipment .......................... 96.2 14.9 16.7 17.0 12.2 13.0 22.4 4.4 Personal Computers 2 ................... 60.0 11.0 11.6 10.3 7.2 7.8 12.0 5.3 Number of Desktop PCs 1 .................................................. 45.1 8.0 9.0 7.7 5.3 6.1 9.1 5.8 2 or more .................................... 9.1 1.8 1.6 2.0 1.1 1.0 1.6 11.8 Number of Laptop PCs 1 ..................................................

472

Table HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit,  

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

5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, 5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.4 0.4 1.8 2.1 1.4 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Census Region and Division Northeast ...................................... 13.0 10.8 1.1 0.5 0.6 11.4 New England .............................. 3.5 3.1 0.2 Q 0.1 16.9 Middle Atlantic ............................ 9.5 7.7 0.9 0.4 0.4 13.4 Midwest ......................................... 17.5 16.0 0.3 Q 1.0 10.3 East North Central ......................

473

untitled  

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

4a. Home Office Equipment by Type of Housing Unit, 4a. Home Office Equipment by Type of Housing Unit, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.5 2.2 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.1 Households Using Office Equipment .......................... 96.2 68.2 8.5 13.8 5.8 4.5 Personal Computers 1 ................... 60.0 46.4 4.1 6.8 2.7 5.9 Number of Desktop PCs 1 .................................................. 45.1 34.4 3.3 5.2 2.2 6.3 2 or more .................................... 9.1 7.7 0.3 0.8 0.3 15.0 Number of Laptop PCs 1 .................................................. 12.0 9.4 0.8

474

char_household2001.pdf  

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

5a. Household Characteristics by Type of Owner-Occupied Housing Unit, 5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.3 0.4 2.0 2.9 1.3 Total Owner-Occupied Units ....... 72.7 63.2 2.1 1.8 5.7 6.7 Household Size 1 Person ....................................... 15.8 12.5 0.8 0.9 1.6 10.3 2 Persons ...................................... 25.9 23.4 0.5 0.5 1.5 10.1 3 Persons ...................................... 11.6 9.6 0.5 Q 1.3 12.1 4 Persons ...................................... 11.8 10.9 Q Q 0.7 15.7 5 Persons ...................................... 5.1 4.5 Q Q 0.4 24.2 6 or More Persons

475

char_household2001.pdf  

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

1a. Household Characteristics by South Census Region, 1a. Household Characteristics by South Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.5 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Household Size 1 Person ...................................................... 28.2 9.9 5.0 1.8 3.1 6.3 2 Persons .................................................... 35.1 13.0 6.7 2.5 3.8 4.2 3 Persons .................................................... 17.0 6.6 3.7 1.2 1.7 8.8 4 Persons .................................................... 15.6 6.0 3.3 0.8 1.9 10.7 5 Persons ....................................................

476

S:\VM3\RX97\TBL_LIST.WPD [PFP#201331587]  

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

1997 1997 Appliance Types and Characteristics RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.3 1.2 1.2 1.4 Total .............................................................. 101.5 6.8 11.5 7.0 5.9 NF Households With Electric Air-Conditioning Equipment ...................... 73.6 4.3 4.8 6.4 5.7 3.5 Central Equipment Not Used ....................... 0.3 Q 0.1 (*) 0.1 29.3 Room Air Conditioners Not Used ................ 0.7 Q Q Q 0.1 36.9 Households Using Electric Air-Conditioning 1 ........................................ 72.6 4.2 4.6 6.3 5.6 3.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 47.5 1.3 3.2 4.8 4.9 5.4 Without a Heat Pump ................................ 36.9 1.2 2.9 4.1 2.5 10.6 With a Heat Pump

477

Table 4  

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

. Light Usage by Heated Floorspace Category, Million U.S. . Light Usage by Heated Floorspace Category, Million U.S. Households, 1993 Heated Floorspace Category (square feet) Housing Unit and Household Characteristics Total Fewer than 600 600 to 999 1,000 to 1,599 1,600 to 1,999 2,000 to 2,399 2,400 to 2,999 3,000 or More RSE Column Factors: 0.4 1.7 0.9 0.8 1.1 1.2 1.2 1.2 RSE Row Factors Total................................................. 96.6 7.5 21.8 27.8 12.4 9.6 8.2 9.3 3.62 Indoor Electric Lights Total Number Lights 1 to 4 Hours None........................................... 9.6 1.2 2.2 2.7 1.1 0.9 0.7 0.6 11.83 1 ................................................. 22.1 2.4 6.7 6.5 2.5 1.5 1.5 1.1 7.39 2 ................................................. 27.4 2.4 6.9 8.0 3.6 2.4 2.1 2.0 6.60 3 ................................................. 16.8 0.8 3.4 5.2 2.2 2.0

478

ac_household2001.pdf  

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

0a. Air Conditioning by Midwest Census Region, 0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 20.2 13.4 6.7 2.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 14.3 9.5 4.8 3.8 Without a Heat Pump ................................ 46.2 13.6 9.0 4.6 3.9 With a Heat Pump .....................................

479

ac_household2001.pdf  

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

8a. Air Conditioning by Urban/Rural Location, 8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 36.8 13.6 18.9 13.6 4.3 Air Conditioners Not Used ........................... 2.1 1.2 0.2 0.4 0.3 21.4 Households Using Electric Air-Conditioning 2 ........................................ 80.8 35.6 13.4 18.6 13.3 4.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 ............................ 57.5 23.6 8.6 15.8 9.4 5.1 Without a Heat Pump ................................ 46.2 19.3 7.4 13.1 6.4 6.3 With a Heat Pump ..................................... 11.3 4.4

480

appl_household2001.pdf  

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

4a. Appliances by Type of Housing Unit, 4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.6 1.9 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 69.1 9.4 16.7 6.6 4.3 1 ................................................ 95.2 63.7 8.9 16.2 6.3 4.3 2 or More .................................. 6.5 5.4 0.4 0.4 0.2 15.9 Most Used Oven ........................ 101.7 69.1 9.4 16.7 6.6 4.3 Electric ...................................... 63.0 43.3 5.2 10.9 3.6

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481

S:\VM3\RX97\TBL_LIST.WPD [PFP#201331587]  

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

b. Appliances by Four Most Populated States, b. Appliances by Four Most Populated States, Percent of U.S. Households, 1997 Appliance Types and Characteristics RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.3 1.2 1.2 1.4 Total .............................................................. 100.0 100.0 100.0 100.0 100.0 0.0 Households With Electric Air-Conditioning Equipment ...................... 72.5 62.6 41.4 91.7 96.0 3.5 Central Equipment Not Used ....................... 0.3 Q 1.2 0.5 1.1 29.3 Room Air Conditioners Not Used ................ 0.7 Q Q Q 1.1 36.9 Households Using Electric Air-Conditioning 1 ........................................ 71.6 62.2 39.9 91.2 94.3 3.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................

482

Table 4  

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

1. Mean Annual Electricity Consumption for Lighting, by Number of 1. Mean Annual Electricity Consumption for Lighting, by Number of Household Members by Number of Rooms, 1993 (Kilowatthours) Number of Rooms Number of Household Members All Households One to Three Four Five Six Seven Eight or More RSE Column Factors: 0.5 2.0 1.1 0.9 0.8 1.0 1.1 RSE Row Factors All Households................................... 940 497 690 875 1,003 1,181 1,420 2.08 One..................................................... 604 443 545 629 745 910 1,028 4.76 Two..................................................... 923 580 705 884 968 1,141 1,264 3.35 Three.................................................. 1,023 611 789 914 1,059 1,104 1,446 4.40 Four.................................................... 1,198 544 854 1,066 1,113 1,365 1,522 4.36 Five or More....................................... 1,265

483

ac_household2001.pdf  

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

2001 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditioning Equipment ...................... 82.9 4.9 6.0 7.4 6.2 2.4 Air Conditioners Not Used ........................... 2.1 0.1 0.8 Q 0.1 23.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 4.7 5.2 7.4 6.1 2.6 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 1.3 3.9 6.2 5.7 6.7 Without a Heat Pump ................................ 46.2 1.2 3.2 5.5 3.8 8.1 With a Heat Pump ..................................... 11.3 Q 0.8 0.6 1.9 14.7 Room Air-Conditioning ................................ 23.3 3.4 1.2 1.2 0.3 13.6 1 Unit

484

ac_household2001.pdf  

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

5a. Air Conditioning by Type of Owner-Occupied Housing Unit, 5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 59.5 58.7 6.5 12.4 5.3 5.2 Air Conditioners Not Used ............ 1.2 1.1 Q 0.6 Q 23.3 Households Using Electric Air-Conditioning 1 .......................... 58.2 57.6 6.3 11.8 5.1 5.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 44.7 43.6 3.2 7.1 3.5 7.0 Without a Heat Pump .................. 35.6 35.0 2.4 6.1 2.7 7.7 With a Heat Pump .......................

485

Table HC1-1a. Housing Unit Characteristics by Climate Zone,  

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

a. Housing Unit Characteristics by Climate Zone, a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.8 1.0 1.1 1.2 1.1 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 8.0 Census Region and Division Northeast ...................................... 20.3 1.9 10.0 8.4 Q Q 6.8 New England .............................. 5.4 1.4 4.0 Q Q Q 18.4 Middle Atlantic ............................ 14.8 0.5 6.0 8.4 Q Q 4.6 Midwest ......................................... 24.5 5.4 14.8 4.3 Q Q 19.0 East North Central ...................... 17.1

486

1992 CBECS BC  

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

Building Size, Number of Buildings, 1992 Building Size, Number of Buildings, 1992 (Thousand) Building Characteristics RSE Column Factor: All Buildings Buildings by Size RSE Row Factor 1,001 to 5,000 Square Feet 5,001 to 10,000 Square Feet 10,001 to 25,000 Square Feet 25,001 to 50,000 Square Feet 50,001 to 100,000 Square Feet 100,001 to 200,000 Square Feet 200,001 to 500,000 Square Feet Over 500,000 Square Feet 0.5 0.7 0.8 0.8 1.0 1.1 1.3 1.4 2.2 All Buildings ..................................... 4,806 2,681 975 647 280 116 71 26 9 6.9 Principal Building Activity Education ......................................... 301 112 43 57 40 30 12 6 Q 16.0 Food Sales ....................................... 130 103 Q Q Q Q Q Q Q 23.1 Food Service ................................... 260 179 51 21 Q Q Q Q Q 18.7 Health Care ......................................

487

spaceheat_household2001.pdf  

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

8a. Space Heating by Urban/Rural Location, 8a. Space Heating by Urban/Rural Location, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.6 0.9 1.3 1.3 1.2 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.3 Heat Home .................................................... 106.0 49.1 18.0 21.2 17.8 4.3 Do Not Heat Home ....................................... 1.0 0.7 0.1 0.1 0.1 25.8 No Heating Equipment ................................ 0.5 0.4 0.1 Q 0.1 33.2 Have Equipment But Do Not Use It ............................................... 0.4 0.3 Q Q Q 30.2 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 49.1 18.0 21.2 17.8 4.3 Natural Gas

488

1992 CBECS BC  

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

9. Energy Sources, Number of Buildings, 1992 9. Energy Sources, Number of Buildings, 1992 (Thousand) Building Characteristics RSE Column Factor: All Buildings All Buildings Using Any Energy Source Energy Sources Used (more than one may apply) RSE Row Factor Electricity Natural Gas Fuel Oil District Heat District Chilled Water Propane Wood 0.5 0.5 0.5 0.6 1.1 1.6 2.2 1.6 2.0 All Buildings ..................................... 4,806 4,620 4,616 2,665 559 95 28 337 103 7.7 Building Floorspace (Square Feet) 1,001 to 5,000 .................................. 2,681 2,543 2,539 1,331 288 18 Q 218 70 10.8 5,001 to 10,000 ................................ 975 954 954 574 125 11 Q 62 25 10.7 10,001 to 25,000 .............................. 647 628 628 420 62 28 8 32 Q 11.6 25,001 to 50,000 .............................. 280 275 275 181 39 16 9 15 Q 13.0 50,001 to 100,000

489

Table 4  

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

. Light Usage by Heated Floorspace Category, Percent of U.S. . Light Usage by Heated Floorspace Category, Percent of U.S. Households, 1993 Heated Floorspace Category (square feet) Housing Unit and Household Characteristics Total Fewer than 600 600 to 999 1,000 to 1,599 1,600 to 1,999 2,000 to 2,399 2,400 to 2,999 3,000 or More RSE Column Factors: 0.4 1.6 0.9 0.8 1.1 1.2 1.3 1.2 RSE Row Factor Total................................................. 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 0.0 Indoor Electric Lights Total Number Lights 1 to 4 Hours None........................................... 10.0 16.5 10.2 9.9 9.2 9.4 9.1 6.7 11.42 1 ................................................. 22.9 31.3 30.9 23.5 19.9 15.3 17.9 11.5 6.62 2 ................................................. 28.4 32.3 31.9 28.7 28.7 24.8 26.0 21.5 5.64 3 .................................................

490

ac_household2001.pdf  

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

6a. Air Conditioning by Type of Rented Housing Unit, 6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.8 0.5 1.4 1.2 1.6 Households With Electric Air-Conditioning Equipment ........ 23.4 58.7 6.5 12.4 5.3 6.1 Air Conditioners Not Used ............ 0.9 1.1 Q 0.6 Q 23.0 Households Using Electric Air-Conditioning 1 .......................... 22.5 57.6 6.3 11.8 5.1 6.2 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 12.7 43.6 3.2 7.1 3.5 8.5 Without a Heat Pump .................. 10.6 35.0 2.4 6.1 2.7 9.3 With a Heat Pump ....................... 2.2 8.6 0.8 1.0

491

1992 CBECS BC  

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

Census Region, Number of Buildings and Floorspace, 1992 Census Region, Number of Buildings and Floorspace, 1992 Building Characteristics RSE Column Factor: Number of Buildings (thousand) Total Floorspace (million square feet) RSE Row Factor All Buildings Northeast Midwest South West All Buildings Northeast Midwest South West 0.6 1.2 1.1 1.0 1.3 0.6 1.3 1.1 1.1 1.2 All Buildings ................................... 4,806 771 1,202 1,963 870 67,876 13,400 17,280 24,577 12,619 6.3 Building Floorspace (square feet) 1,001 to 5,000 ................................ 2,681 383 676 1,171 451 7,327 1,074 1,889 3,155 1,208 9.7 5,001 to 10,000 .............................. 975 180 241 370 184 7,199 1,337 1,763 2,723 1,376 7.6 10,001 to 25,000 ............................ 647 109 163 239 136 10,375 1,663 2,689 3,782 2,241 8.5 25,001 to 50,000 ............................ 280 54 66 106 56

492

1992 CBECS BC  

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

Employment Size Category, Number of Buildings, 1992 Employment Size Category, Number of Buildings, 1992 (Thousand) Building Characteristics RSE Column Factor: All Buildings Buildings by Number of Workers RSE Row Factor Less than 5 Workers 5 to 9 Workers 10 to 19 Workers 20 to 49 Workers 50 to 99 Workers 100 to 249 Workers 250 or More Workers 0.5 0.8 0.9 1.1 1.0 1.2 1.3 1.4 All Buildings ................................... 4,806 2,718 895 561 405 130 64 31 5.9 Building Floorspace (square feet) 1,001 to 5,000 ................................ 2,681 1,968 514 160 34 Q Q Q 10.1 5,001 to 10,000 .............................. 975 460 218 195 94 Q Q Q 8.5 10,001 to 25,000 ............................ 647 204 115 144 153 25 Q Q 9.3 25,001 to 50,000 ............................ 280 60 37 43 84 41 13 Q 13.8 50,001 to 100,000 .......................... 116 12

493

spaceheat_household2001.pdf  

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

3a. Space Heating by Household Income, 3a. Space Heating by Household Income, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Heat Home ..................................... 106.0 18.4 22.7 26.8 38.1 14.6 33.4 3.3 Do Not Heat Home ........................ 1.0 0.3 Q 0.3 0.3 0.3 0.4 23.4 No Heating Equipment .................. 0.5 Q Q Q 0.2 Q Q 35.0 Have Equipment But Do Not Use It ................................ 0.4 Q Q Q Q 0.2 0.3 22.8 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 18.4 22.7

494

char_household2001.pdf  

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

8a. Household Characteristics by Urban/Rural Location, 8a. Household Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Household Size 1 Person ...................................................... 28.2 14.6 5.3 4.8 3.6 6.4 2 Persons .................................................... 35.1 15.7 5.7 6.9 6.8 5.4 3 Persons .................................................... 17.0 7.6 2.8 3.5 3.1 7.2 4 Persons .................................................... 15.6 6.8 2.3 4.1 2.4 8.1 5 Persons .................................................... 7.1 3.1 1.3 1.3 1.4 12.3 6 or More Persons