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1

Cost and Performance Assumptions for Modeling Electricity Generation Technologies  

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

Cost and Performance Cost and Performance Assumptions for Modeling Electricity Generation Technologies Rick Tidball, Joel Bluestein, Nick Rodriguez, and Stu Knoke ICF International Fairfax, Virginia Subcontract Report NREL/SR-6A20-48595 November 2010 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 Cost and Performance Assumptions for Modeling Electricity Generation Technologies Rick Tidball, Joel Bluestein, Nick Rodriguez, and Stu Knoke ICF International Fairfax, Virginia NREL Technical Monitor: Jordan Macknick

2

Cost and Performance Assumptions for Modeling Electricity Generation Technologies  

Science Conference Proceedings (OSTI)

The goal of this project was to compare and contrast utility scale power plant characteristics used in data sets that support energy market models. Characteristics include both technology cost and technology performance projections to the year 2050. Cost parameters include installed capital costs and operation and maintenance (O&M) costs. Performance parameters include plant size, heat rate, capacity factor or availability factor, and plant lifetime. Conventional, renewable, and emerging electricity generating technologies were considered. Six data sets, each associated with a different model, were selected. Two of the data sets represent modeled results, not direct model inputs. These two data sets include cost and performance improvements that result from increased deployment as well as resulting capacity factors estimated from particular model runs; other data sets represent model input data. For the technologies contained in each data set, the levelized cost of energy (LCOE) was also evaluated, according to published cost, performance, and fuel assumptions.

Tidball, R.; Bluestein, J.; Rodriguez, N.; Knoke, S.

2010-11-01T23:59:59.000Z

3

AEO Assumptions  

Gasoline and Diesel Fuel Update (EIA)

for the for the Annual Energy Outlook 1997 December 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Energy Information Administration/Assumptions for the Annual Energy Outlook 1997 Contents Page Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Commercial Demand Module . . . . . . . . . . . . . . . . . .

4

Figure S.1  

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

2- Figures and Table 2.1 2- Figures and Table 2.1 Figure S.1 Figure 1.1 Figure 1.2 Figure 1.3 Figure 2.1 Figure 2.2 Figure 2.3 Figure 3.1 Figure 3.2 Figure 3.3 Figure 3.4 Figure 3.5 Figure 3.6 Figure 3.7 Figure 3.8 Figure 3.9 Figure 3.10 Figure 3.11 Figure 3.12 Figure 3.13 Figure 3.14 Figure 3.15 Figure 3.16 Figure 3.17 Figure 3.18 Figure 3.19 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 Figure 4.5 Figure 4.6 Figure 4.7 Figure 4.8 Figure 4.9 Figure 4.10 Figure 4.11 Figure 4.12 Figure 4.13 Figure 4.14 Figure 4.15 Figure 4.16 Figure 4.17 Figure 4.18 Figure 4.19 J.1 Lewiston Stage Contents Relationship (NOT AVAILABLE IN ELECTRONIC FORMAT) J.2 Keswick Stage Contents Relationship (NOT AVAILABLE IN ELECTRONIC FORMAT) J.3 Natoma Stage Contents Relationship (NOT AVAILABLE IN ELECTRONIC

5

Figure 3  

Science Conference Proceedings (OSTI)

skip to main content, National Institute of Standards and Technology. Home, Instruments, Science, Experiments, SiteMap. Back ...

6

Figure 2  

Science Conference Proceedings (OSTI)

skip to main content, National Institute of Standards and Technology. Home, Instruments, Science, Experiments, SiteMap. Back ...

7

Figure 1  

Science Conference Proceedings (OSTI)

skip to main content, National Institute of Standards and Technology. Home, Instruments, Science, Experiments, SiteMap. Back ...

8

Figure 1  

Science Conference Proceedings (OSTI)

Total = $759.2 billion. Source: Organisation for Economic Co-Operation and Development (OECD), Main Science and Technology Indicators, 2004. * Argentina...

9

Adapting Decisions, Optimizing Facts and Predicting Figures: Can Convergence of Concepts, Tools, Technologies and Standards Catalyze Innovation?  

E-Print Network (OSTI)

Managing uncertainty is key in decision systems, such as supply chain management or military readiness. We propose a reasonable confluence of existing concepts, tools, technologies and standards that may, collectively, ...

Datta, Shoumen

2008-07-31T23:59:59.000Z

10

APPENDIX A: FIGURES  

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

APPENDIX A: FIGURES Project Name: Archbold Area Schools Wind Turbine Source Information: USGS, TRG Survey Figure Name: Turbine Location Notes: Turbine Location TRG Archbold...

11

APPENDIX A: FIGURES  

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

APPENDIX A: FIGURES Project Name: Pettisville Local Schools Wind Turbine Source Information: USGS, TRG Survey Figure Name: Turbine Location Notes: Turbine Location TRG...

12

EIA - Assumptions to the Annual Energy Outlook 2010 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2010 International Energy Module Figure 2. World Oil Prices in Three Cases, 1995-2035 Figure 2. World Oil Prices in three Cases, 1995-2035 (2008 dollars per barrel). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 3. OPEC Total Liquids Production in the Reference Case, 1980-2035 Figure 3. OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1980-2035 Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800.

13

EIA - Assumptions to the Annual Energy Outlook 2009 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2009 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight, rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

14

Assumptions to the Annual Energy Outlook - Transportation Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumption to the Annual Energy Outlook Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, sport utility vehicles and vans), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

15

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2006 The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption isthe sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

16

EIA - Assumptions to the Annual Energy Outlook 2008 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2008 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

17

Figure 55. Residential delivered energy intensity in four ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 55. Residential delivered energy intensity in four cases, 2005-2035 (index, 2005 = 1) Best Available Technology case High Technology case

18

Figure 6 - TMS  

Science Conference Proceedings (OSTI)

Figure 6. In wet stretching, (a) the fiber is allowed to contract unrestrained up to the supercontracted length; (b) it is stretched to the selected length and the ends

19

EIA - Assumptions to the Annual Energy Outlook 2009 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2009 International Energy Module Figure 2. World Oil Prices in three Cases, 1995-2030 (2006 dollars per barrel). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 3. OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously global and U.S.A. petroleum liquids

20

Assumptions to the Annual Energy Outlook - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumption to the Annual Energy Outlook International Energy Module Figure 2. World Oil Prices in three Cases, 1970-2025. Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure Data Figure 3. OPEC Oil Production in the Reference Case, 1970-2025. Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure Data Figure 4. Non-OPEC Production in the Reference Case, 1970-2025. Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure Data Table 4. Worldwide Oil Reserves as of January 1, 2002 (Billion Barrels) Printer Friendly Version Region Proved Oil Reserves Western Hemisphere 313.6 Western‘Europe 18.1 Asia-Pacific 38.7

Note: This page contains sample records for the topic "technology assumptions figure" 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

MECS Fuel Oil Figures  

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

: Percentage of Total Purchased Fuels by Type of Fuel : Percentage of Total Purchased Fuels by Type of Fuel Figure 1. Percent of Total Purchased Fuel Sources: Energy Information Administration. Office of Energy Markets and End Use, Manufacturing Energy Consumption Survey (MECS): Consumption of Energy; U.S. Department of Commerce, Bureau of the Census, Annual Survey of Manufactures (ASM): Statistics for Industry Groups and Industries: Statistical Abstract of the United States. Note: The years below the line on the "X" Axis are interpolated data--not directly from the Manufacturing Energy Consumption Survey or the Annual Survey of Manufactures. Figure 2: Changes in the Ratios of Distillate Fuel Oil to Natural Gas Figure 2. Changes in the Ratios of Distillate Fuel Oil to Natural Gas Sources: Energy Information Administration. Office of

22

Climate Action Planning Tool Formulas and Assumptions  

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

CLIMATE ACTION PLANNING TOOL FORMULAS AND ASSUMPTIONS Climate Action Planning Tool Formulas and Assumptions The Climate Action Planning Tool calculations use the following formulas and assumptions to generate the business-as-usual scenario and the greenhouse gas emissions reduction goals for the technology options. Business-as-Usual Scenario All Scope 1 (gas, oil, coal, fleet, and electricity) and Scope 2 calculations increase at a rate equal to the building growth rate. Scope 3 calculations (commuters and business travel) increase at a rate equal to the population growth rate. Assumptions New buildings will consume energy at the same rate (energy use intensity) as existing campus buildings. Fleet operations will be proportional to total building area.

23

Wet-Etch Figuring Optical Figuring by Controlled Application of Liquid Etchant  

SciTech Connect

WET-ETCH FIGURING (WEF) is an automated method of precisely figuring optical materials by the controlled application of aqueous etchant solution. This technology uses surface-tension-gradient-driven flow to confine and stabilize a wetted zone of an etchant solution or other aqueous processing fluid on the surface of an object. This wetted zone can be translated on the surface in a computer-controlled fashion for precise spatial control of the surface reactions occurring (e.g. chemical etching). WEF is particularly suitable for figuring very thin optical materials because it applies no thermal or mechanical stress to the material. Also, because the process is stress-free the workpiece can be monitored during figuring using interferometric metrology, and the measurements obtained can be used to control the figuring process in real-time--something that cannot be done with traditional figuring methods.

Britten, J

2001-02-13T23:59:59.000Z

24

Figure 58. Residential sector adoption of renewable energy ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 58. Residential sector adoption of renewable energy technologies in two cases, 2005-2040 PV and wind (gigawatts) Heat pump ...

25

Figure 57. Change in residential delivered energy consumption ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 57. Change in residential delivered energy consumption for selected end uses in four cases, 2011-2040 (percent) Best Available Technology

26

Figure 59. Commercial delivered energy intensity in four cases ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 59. Commercial delivered energy intensity in four cases, 2005-2040 (index, 2005 = 1) Reference case 2011 Technology case

27

Assumptions  

Gasoline and Diesel Fuel Update (EIA)

1 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Petroleum Market Module. . . . . . . . . . . . .

28

Assumptions  

Gasoline and Diesel Fuel Update (EIA)

to the to the Annual Energy Outlook 1998 December 1997 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Household Expenditures Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Oil and Gas Supply Module

29

Assumptions to the Annual Energy Outlook 1999 - International...  

Annual Energy Outlook 2012 (EIA)

percent per year over the forecast periodas advances in both exploration and extraction technologies result in this upward trend (Figure 3). One fixed path for non-OPEC oil...

30

Annual Energy Outlook 96 Assumptions  

Gasoline and Diesel Fuel Update (EIA)

for for the Annual Energy Outlook 1996 January 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Introduction This paper presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 1996 (AEO96). In this context, assumptions include general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports listed in the Appendix. 1 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview. The National Energy Modeling System The projections

31

Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumption to the Annual Energy Outlook Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

32

EIA - Assumptions to the Annual Energy Outlook 2009 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2009 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the projection horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the projection horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

33

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

States. States. OGSM encompasses domestic crude oil and natural gas supply by both conventional and nonconventional recovery techniques. Nonconventional recovery includes unconventional gas recovery from low permeability formations of sandstone and shale, and coalbeds. Energy Information Administration/Assumptions to the Annual Energy Outlook 2007 93 Figure 7. Oil and Gas Supply Model Regions Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Report #:DOE/EIA-0554(2007) Release date: April 2007 Next release date: March 2008 Primary inputs for the module are varied. One set of key assumptions concerns estimates of domestic technically recoverable oil and gas resources. Other factors affecting the projection include the assumed

34

Silicon Nanoparticle Biocompatibility Figure 1  

Science Conference Proceedings (OSTI)

... Figure 2. Effect of SNs and SMs on cell survival percentage in RAW 264.7 cells based on trypan blue dye exclusion (A) and MTT (B) assay. ...

2012-10-01T23:59:59.000Z

35

Microsoft Word - Figure_15.docx  

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

Source: Energy Information Administration (EIA), Form EIA-191A, "Annual Underground Gas Storage Report." U.S. Energy Information Administration | Natural Gas Annual Figure 16....

36

Three prominent figures (3PF)  

Science Conference Proceedings (OSTI)

Three Prominent Figures, a sub-group of the VOLT Collective (http://www.voltcollective.com) is a performance piece combining live DJ-ing, video art, and physical computing to explore non-invasive musical expression. Three Prominent Figures will be presented ...

Roberto Osorio-Goenaga; Gregory Boland; Nathaniel Weiner

2007-06-01T23:59:59.000Z

37

EIA-Assumptions to the Annual Energy Outlook - Transportation Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2007 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption isthe sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

38

EIA - Assumptions to the Annual Energy Outlook 2009 - Oil and Gas Supply  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2009 Oil and Gas Supply Module Figure 7. Oil and Gas Supply Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. Table 9.1. Crude Oil Technically Recoverable Resources. Need help, contact the Naitonal Energy Information Center at 202-586-8800. printer-friendly version Table 9.2. Natural Gas Technically Recoverable Resources. Need help, contact the National Energy Information Center at 202-586-8800. Table 9.2. Continued printer-friendly version Table 9.3. Assumed Size and Initial Production year of Major Announced Deepwater Discoveries. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 9.4. Assumed Annual Rates of Technological Progress for Conventional Crude Oil and Natural Gas Sources. Need help, contact the National Energy Information Center at 202-586-8800.

39

Microsoft Word - figure_03.doc  

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

0 U.S. Energy Information Administration | Natural Gas Annual Figure 3. Marketed production of natural gas in the United States and the Gulf of Mexico, 2011 (million cubic feet)...

40

Microsoft Word - figure_24.doc  

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

1 Figure 25. Average price of natural gas delivered to U.S. onsystem industrial consumers, 2011 (dollars per thousand cubic feet) U.S. Energy Information Administration | Natural...

Note: This page contains sample records for the topic "technology assumptions figure" 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

Microsoft Word - figure_99.doc  

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

6 U.S. Energy Information Administration | Natural Gas Annual Figure 6. Natural gas processing in the United States and the Gulf of Mexico, 2011 (million cubic feet) None 1-15,000...

42

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2003, DOE/EIA-M068(2003) April 2003. Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

43

EIA - Assumptions to the Annual Energy Outlook 2010 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2010 Petroleum Market Module The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, bioesters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. Figure 9. Petroleum Administration for Defense Districts. The PMM contains a linear programming (LP) representation of U.S. refining activities in the five Petroleum Area Defense Districts (PADDs) (Figure 9),

44

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2006 Figure 7. Oil and Gas Supply Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply on a regional basis (Figure 7). A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2006), (Washington, DC, 2006). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural

45

The disciplined use of simplifying assumptions  

Science Conference Proceedings (OSTI)

Simplifying assumptions --- everyone uses them but no one's programming tool explicitly supports them. In programming, as in other kinds of engineering design, simplifying assumptions are an important method for dealing with complexity. Given a complex ...

Charles Rich; Richard C. Waters

1982-04-01T23:59:59.000Z

46

Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumption to the Annual Energy Outlook Petroleum Market Module Figure 8. Petroleum Administration for Defense Districts. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohols, ethers, and bioesters natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of U.S. refining

47

Assumptions to the Annual Energy Outlook - Household Expenditures Module  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module Assumption to the Annual Energy Outlook Household Expenditures Module Figure 5. United States Census Divisions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division (see

48

EIA - Assumptions to the Annual Energy Outlook 2009 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2009 Petroleum Market Module Figure 9., Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. Table 11.1. Petroleum Product Categories. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 11.2. Year Round Gasoline Specifications by Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 11.3. Gasolline Sulfur Content Assumptions, by Region and Gasoline Type, Parts per Million (PPM). Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version

49

Technolog  

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

Research in Research in Science and Technolog y Sandia pushes frontiers of knowledge to meet the nation's needs, today and tomorrow Sandia National Laboratories' fundamental science and technology research leads to greater understanding of how and why things work and is intrinsic to technological advances. Basic research that challenges scientific assumptions enables the nation to push scientific boundaries. Innovations and breakthroughs produced at Sandia allow it to tackle critical issues, from maintaining the safety, security and effectiveness of the nation's nuclear weapons and preventing domestic and interna- tional terrorism to finding innovative clean energy solutions, develop- ing cutting-edge nanotechnology and moving the latest advances to the marketplace. Sandia's expertise includes:

50

EIS-0268-Figures-1997.pdf  

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

DOFJ'EIS-0268 DOFJ'EIS-0268 - PKw.2F Figure 4-L L-Lake and environs. 4-3 -- =----- 90 --m--- -m- EAST o (C.nti""ed O"figure 4.4b) AA 320 1 300 1 Fourmile Indian Grave Upland Pen Branch Brench Formation Branch 280 ~ 280 240 : E -220 ~ L 200 180 I 160 140 1 I I 1 2 3 4 5 Miles Legend: _ _ Inferredcontact Note:TO converito kilometersmultiply by 1.609 to convetito metersmultiply by0.304e Figure 4-4a. Generalized geologic cross section from Fourmile Branch to L DO~IS-0268 I t" 1 I I t 4-8 DOE/EIS-0268 I 4-60 I t t i I I DOE/EIS-0268 ,. ,. 4-61 DOE/EIS-0268 ,. ,,.':, .. ,.. , 4-62 I 1 I I I DOE/EIS-0268 4-63 DOEI'EIS-0268 ., . . 4-64 I I 1 B I I I m 1 I I I I 1 I I I m I DOE~IS-0268 4-65 DO~IS-0268 Radon in homes: 200 millirem per year Notes me major contributor to the annual average individual dose in the United StaIeS, [ncluti"g residents of the Central Savannah River Area, is naturally occuning radiation

51

Assumptions to the Annual Energy Outlook 2012  

U.S. Energy Information Administration (EIA)

Assumptions to the Annual Energy Outlook 2012 August 2012 www.eia.gov U.S. Department of Energy Washington, DC 20585

52

EIA - Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

7 7 Assumptions to the Annual Energy Outlook 2007 This report summarizes the major assumptions used in the NEMS to generate the AEO2007 projections. Contents (Complete Report) Download complete Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Introduction Section to the Assumptions to the Annual Energy Outlook 2007 Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Section to the Assumptions to the Annual Energy Outlook 2007 Report. Need help, contact the National Energy Information Center at 202-586-8800. Macroeconomic Activity Module Macroeconomic Activity Module Section to the Assumptions to the Annual Energy Outlook 2007 Report. Need help, contact the National Energy Information Center at 202-586-8800.

53

Microsoft Word - figure_18.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 0 2 4 6 8 10 12 14 2001 2002 2003 2004 2005 Dollars per Thousand Cubic Feet 0 40 80 120 160 200 240 280 320 360 400 440 Dollars per Thousand Cubic Meters Residential Commercial Industrial Electric Power Vehicle Fuel Figure 18. Average Price of Natural Gas Delivered to Consumers in the United States, 2001-2005 Note: Coverage for prices varies by consumer sector. See Appendix A for further discussion on consumer prices. Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to Consumers"; Federal Energy Regulatory Commission (FERC), Form FERC-423, "Monthly Report of Cost and Quality of Fuels for

54

Microsoft Word - figure_13.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 13. Net Interstate Movements, Imports, and Exports of Natural Gas in the United States, 2007 (Million Cubic Feet) Nigeria Algeria 37,483 WA M T I D OR W Y ND SD C A N V UT CO NE KS AZ NM OK TX MN WI MI IA I L IN OH MO AR MS AL GA TN KY FL SC NC WV MD DE VA PA NJ NY CT RI MA VT NH ME LA HI AK Mexico C a n a d a C a n a d a Canada Canada Canada Canada Canada Algeria Canada Canada i i N g e r a Gulf of Mexico Gulf o f M e x i c o Gulf of Mexico Canada Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and the Office of Fossil Energy, Natural Gas Imports and Exports.

55

Microsoft Word - figure_15.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 0 2 4 6 8 10 2003 2004 2005 2006 2007 Trillion Cubic Feet 0 50 100 150 200 250 Billion Cubic Meters Residential Commercial Industrial Electric Power Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-906, "Power Plant Report"; Form EIA-920, "Combined Heat and Power Plant Report"; and Form EIA-923, "Power Plant Operations Report." Figure 15. Natural Gas Delivered to Consumers in the United States, 2003-2007 Cautionary Note: Number of Residential and Commercial Consumers The Energy Information Administration (EIA) expects that there may be some double counting in the number of residential and commercial customers reported for 2003 through 2007.

56

PHOBOS Experiment: Figures and Data  

DOE Data Explorer (OSTI)

PHOBOS consists of many silicon detectors surrounding the interaction region. With these detectors physicists can count the total number of produced particles and study the angular distributions of all the products. Physicists know from other branches of physics that a characteristic of phase transitions are fluctuations in physical observables. With the PHOBOS array they look for unusual events or fluctuations in the number of particles and angular distribution. The articles that have appeared in refereed science journals are listed here with separate links to the supporting data plots, figures, and tables of numeric data. See also supporting data for articles in technical journals at http://www.phobos.bnl.gov/Publications/Technical/phobos_technical_publications.htm and from conference proceedings at http://www.phobos.bnl.gov/Publications/Proceedings/phobos_proceedings_publications.htm

The PHOBOS Collaboration

57

Microsoft Word - figure_20.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 0 2 4 6 8 10 12 14 16 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 Sources: Nominal dollars: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-910, "Monthly Natural Gas Marketer Survey." Constant dollars: Prices were converted to 2005 dollars using the chain-type price indexes for Gross Domestic Product (2005 = 1.0) as published by the U.S. Department of Commerce, Bureau of Economic Analysis. dollars per thousand cubic feet base year Figure 21. Average price of natural gas delivered to residential consumers, 1980-2011 nominal dollars

58

Microsoft Word - figure_15.doc  

Gasoline and Diesel Fuel Update (EIA)

38 38 0 2 4 6 8 10 2002 2003 2004 2005 2006 Trillion Cubic Feet 0 50 100 150 200 250 Billion Cubic Meters Residential Commercial Industrial Electric Power Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-906, "Power Plant Report." Figure 15. Natural Gas Delivered to Consumers in the United States, 2002-2006 Cautionary Note: Number of Residential and Commercial Consumers The Energy Information Administration (EIA) expects that there may be some double counting in the number of residential and commercial customers reported for 2002 through 2006. EIA collects information on the number of residential and commercial consumers through a survey of companies that deliver gas

59

Microsoft Word - figure_15.doc  

Gasoline and Diesel Fuel Update (EIA)

38 38 0 2 4 6 8 10 2001 2002 2003 2004 2005 Trillion Cubic Feet 0 50 100 150 200 250 Billion Cubic Meters Residential Commercial Industrial Electric Power Figure 15. Natural Gas Delivered to Consumers in the United States, 2001-2005 Sources: Energy Information Administration (EIA), Form EIA -176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-906, "Power Plant Report." Cautionary Note: Number of Residential and Commercial Consumers The Energy Information Administration (EIA) expects that there may be some double counting in the number of residential and commercial customers reported for 2001 through 2005. EIA collects information on the number of residential and commercial consumers through a survey of companies that deliver gas

60

Figure 6. Electricity Market Model Supply Regions  

E-Print Network (OSTI)

The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submoduleselectricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2010, DOE/EIA-M068(2010). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

unknown authors

2010-01-01T23:59:59.000Z

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While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
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61

Hierarchy of Mesoscale Flow Assumptions and Equations  

Science Conference Proceedings (OSTI)

The present research proposes a standard nomenclature for mesoscale meteorological concepts and integrates existing concepts of atmospheric space scales, flow assumptions, governing equations, and resulting motions into a hierarchy useful in ...

P. Thunis; R. Bornstein

1996-02-01T23:59:59.000Z

62

EIA - Assumptions to the Annual Energy Outlook 2010 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2010 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and

63

EIA - Assumptions to the Annual Energy Outlook 2009 - Electricity Market  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2009 Electricity Market Module figure 6. Electricity Market Model Supply Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2009, DOE/EIA-M068(2009). Based on fuel prices and electricity demands provided by the other modules

64

EIA - Assumptions to the Annual Energy Outlook 2008 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2008 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

65

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2006 The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 12 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS27 data.

66

EIA - Assumptions to the Annual Energy Outlook 2008 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2008 Petroleum Market Module Figure 9. Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, bioesters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining

67

EIA - Assumptions to the Annual Energy Outlook 2009 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2009 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

68

EIA - Assumptions to the Annual Energy Outlook 2008 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2008 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module projects energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region projection using the SEDS1 data.

69

EIA - Assumptions to the Annual Energy Outlook 2010 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2010 Residential Demand Module Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" by appliance (or UEC-in million Btu per household per year). The projection process adds new housing units to the stock,

70

Assumptions to the Annual Energy Outlook - Natural Gas Transmission and  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumption to the Annual Energy Outlook Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

71

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2006 Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment

72

Microsoft Word - figure_17.doc  

Gasoline and Diesel Fuel Update (EIA)

3 3 Commercial All Other States Wisconsin M innesota Pennsylvania Ohio M ichigan Texas New Jersey California New York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion C ubic Feet Residential Colorado Indiana Texas New Jersey Pennsylvania Ohio M ichigan Illinois California All Other States New York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion C ubic Feet Figure 18. Natural gas delivered to consumers in the United States, 2011 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet Residential 4,713,695 21% Commercial 3,153,605 14% Industrial 6,904,843 31% Electric Power 7,573,863 34% Industrial All Other States M innesota Iowa Oklahoma Pennsylvania Ohio Illinois Indiana Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Electric Power

73

Microsoft Word - figure_16.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 Commercial All Other States Wisconsin Minnesota Pennsylvania Ohio Texas Michigan New Jersey California New York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Residential Wisconsin Indiana Texas New Jersey Pennsylvania Ohio Michigan Illinois California All Other States New York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Figure 16. Natural Gas Delivered to Consumers in the United States, 2007 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet Electric Pow er 6,841,408 33% Industrial 6,624,846 31% Commercial 3,017,105 14% Residential 4,717,311 22% Industrial All Other States Georgia Oklahom a Michigan Pennsylvania Illinois Indiana Ohio Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Electric Power All Other States Alabam a

74

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 2. Natural Gas Supply and Disposition in the United States, 20088 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 25.8 0.7 0.2 3.6 3.589 0.267 0.012 0.365 0.590 0.050 20.3 1.0 3.4 3.4 1.9 3.1 6.7 0.03 6.7 0.055 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-914, "Monthly Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to

75

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 Egypt Algeria Figure 2. Natural Gas Supply and Disposition in the United States, 2006 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 23.5 0.7 0.1 3.3 3.590 0.389 0.017 0.057 0.322 0.341 0.061 18.5 0.9 3.0 2.5 1.7 4.4 2.8 6.5 0.02 6.2 0.120 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895A, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to Consumers"; Form EIA-816, "Monthly Natural Gas Liquids

76

Microsoft Word - figure_13.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 13. Net Interstate Movements, Imports, and Exports of Natural Gas in the United States, 2008 (Million Cubic Feet) Norway Trinidad/ Tobago Interstate Movements Not Shown on Map From Volume To From Volume To CT RI RI MA MA CT VA DC MD DC 45,772 WA M T I D OR W Y ND SD C A N V UT CO NE KS AZ NM OK TX MN WI MI IA I L IN OH MO AR MS AL GA TN KY FL SC NC WV MD DE VA PA NJ NY CT RI MA VT NH ME LA HI AK Mexico C a n a d a C a n a d a Canada Canada Canada Canada Canada Canada Canada i i N g e r a Gulf of Mexico Gulf o f M e x i c o Gulf of Mexico Canada Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," the Office of Fossil Energy, Natural Gas Imports and Exports, and EIA estimates.

77

Microsoft Word - figure_13.doc  

Gasoline and Diesel Fuel Update (EIA)

,833 ,833 35 Egypt Figure 13. Net Interstate Movements, Imports, and Exports of Natural Gas in the United States, 2009 (Million Cubic Feet) Norway Trinidad/ Tobago Trinidad/ Tobago Egypt Interstate Movements Not Shown on Map From Volume To From Volume To CT RI RI MA MA CT VA DC MD DC 111,144 WA M T I D OR W Y ND SD C A N V UT CO NE KS AZ NM OK TX MN WI MI IA I L IN OH MO AR MS AL GA TN KY FL SC NC WV MD DE VA PA NJ NY CT RI MA VT NH ME LA HI AK Mexico C a n a d a C a n a d a Canada Canada Canada Canada Canada Canada Canada i i N g e r a Gulf of Mexico Gulf o f M e x i c o Gulf of Mexico Canada Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," the Office of Fossil Energy, Natural Gas Imports and Exports, and EIA estimates

78

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 2. Natural Gas Supply and Disposition in the United States, 2010 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 26.8 0.8 0.2 3.4 3.280 0.190 0.042 0.333 0.739 0.033 21.3 1.1 3.3 3.3 2.0 3.1 6.5 0.03 7.4 0.073 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-914, "Monthly Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to

79

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 2. Natural Gas Supply and Disposition in the United States, 2009 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 26.0 0.7 0.2 3.5 3.271 0.236 0.013 0.338 0.701 0.031 20.6 1.0 3.4 3.0 1.9 3.1 6.2 0.03 6.9 0.160 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-914, "Monthly Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to

80

Microsoft Word - figure_02.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Algeria Figure 2. Natural Gas Supply and Disposition in the United States, 2007 (Trillion Cubic Feet) Extraction Loss Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Nigeria Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 24.6 0.6 0.2 3.8 3.783 0.448 0.077 0.095 0.292 0.482 0.047 19.1 0.9 3.2 3.4 1.8 3.0 6.6 0.03 6.8 0.115 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895A, "Annual Quantity and Value of Natural Gas Production Report"; Form EIA-914, "Monthly Natural Gas Production Report"; Form EIA-857, "Monthly Report of Natural Gas Purchases and Deliveries to

Note: This page contains sample records for the topic "technology assumptions figure" 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

Microsoft Word - figure_14.doc  

Gasoline and Diesel Fuel Update (EIA)

Egypt Figure 14. Net Interstate Movements, Imports, and Exports of Natural Gas in the United States, 2010 (Million Cubic Feet) Norway India Trinidad/ Tobago Egypt Yemen Japan Interstate Movements Not Shown on Map From Volume To From Volume To CT RI RI MA MA CT VA DC MD DC 53,122 WA M T I D OR W Y ND SD C A N V UT CO NE KS AZ NM OK TX MN WI MI IA I L IN OH MO AR MS AL GA TN KY FL SC NC WV MD DE VA PA NJ NY CT RI MA VT NH ME LA HI AK Mexico C a n a d a C a n a d a Canada Canada Canada Canada Canada Canada Canada Gulf of Mexico Canada Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," the Office of Fossil Energy, Natural Gas Imports and Exports, and EIA estimates based on historical data. Energy Information

82

Microsoft Word - figure_17.doc  

Gasoline and Diesel Fuel Update (EIA)

5 5 C ommercial All O ther States W isconsin Minnesota Pennsylvania Michigan O hio N ew Jersey Texas California N ew York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion C ubic Feet Residential Indiana G eorgia N ew Jersey Pennsylvania Texas O hio Michigan Illinois California All O ther States N ew York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion C ubic Feet Figure 17. Natural Gas Delivered to Consumers in the United States, 2010 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet E lectric P ower 7,387,184 34% Industrial 6,517,477 30% C om m ercial 3,101,675 14% R esidential 4,787,320 22% Industrial All O ther States Minnesota Iowa Pennsylvania O klahoma Illinois O hio Indiana Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 E lectric Power All O ther States Arizona Mississippi Louisiana Alabama

83

Microsoft Word - figure_16.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 Commercial All Other States Wisconsin Minnesota Pennsylvania Texas Ohio New Jersey Michigan California New York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Residential Wisconsin Indiana Texas New Jersey Pennsylvania Ohio Michigan Illinois California All Other States New York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Figure 16. Natural Gas Delivered to Consumers in the United States, 2008 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet Electric Pow er 6,668,379 31% Industrial 6,650,276 31% Commercial 3,135,852 15% Residential 4,872,107 23% Industrial All Other States Georgia Iow a Oklahom a Pennsylvania Illinois Indiana Ohio Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Electric Power All Other States Mississippi New Jersey Louisiana

84

Microsoft Word - figure_16.doc  

Gasoline and Diesel Fuel Update (EIA)

4 4 Commercial All Other States Wisconsin Minnesota Pennsylvania Ohio Michigan Texas New Jersey California New York Illinois 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Residential Minnesota Indiana Texas New Jersey Pennsylvania Ohio Michigan Illinois California All Other States New York 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Trillion Cubic Feet Figure 16. Natural Gas Delivered to Consumers in the United States, 2009 Volumes in Million Cubic Feet Trillion Cubic Feet Trillion Cubic Feet Electric Pow er 6,872,049 33% Industrial 6,167,193 29% Commercial 3,118,833 15% Residential 4,778,478 23% Industrial All Other States Georgia Iow a Pennsylvania Oklahom a Ohio Illinois Indiana Louisiana Texas California 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Electric Power All Other States Nevada Pennsylvania Alabam a Arizona

85

Assumptions to the Annual Energy Outlook 2013  

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

Introduction Introduction This page inTenTionally lefT blank 3 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2013 [1] (AEO2013), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System Projections in the AEO2013 are generated using the NEMS, developed and maintained by the Office of Energy Analysis of the U.S.

86

Assumptions to the Annual Energy Outlook 2013  

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

Assumptions to the Annual Assumptions to the Annual Energy Outlook 2013 May 2013 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. Table of Contents Introduction .................................................................................................................................................. 3

87

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

2 2 The commercial module forecasts consumption by fuel 13 at the Census division level using prices from the NEMS energy supply modules, and macroeconomic variables from the NEMS Macroeconomic Activity Module (MAM), as well as external data sources (technology characterizations, for example). Energy demands are forecast for ten end-use services 14 for eleven building categories 15 in each of the nine Census divisions (see Figure 5). The model begins by developing forecasts of floorspace for the 99 building category and Census division combinations. Next, the ten end-use service demands required for the projected floorspace are developed. The electricity generation and water and space heating supplied by distributed generation and combined heat and power technologies are projected. Technologies are then

88

Figure 37. Carbon dioxide emissions from electricity ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 37. Carbon dioxide emissions from electricity generation in three cases, 2005-2040 (million metric tons carbon dioxide ...

89

Energy Efficiency Report: Chapter 3 Figures (Residential)  

U.S. Energy Information Administration (EIA)

Figure 3.1. Total Site Residential Energy Consumption and Personal Consumption Expenditures Indices, 1980 to 1993. Notes: Personal consumption expenditures used ...

90

Figure 70. Delivered energy consumption for transportation ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 70. Delivered energy consumption for transportation by mode, 2011 and 2040 (quadrillion Btu) Total Rail Pipeline Marine ...

91

Figure F2. Electricity market module regions  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration Annual Energy Outlook 2013 227 Regional maps Figure F2. Electricity market module regions Source: U.S. Energy Information ...

92

Figure 4.17 Geothermal Resources  

U.S. Energy Information Administration (EIA)

Figure 4.17 Geothermal Resources 124 U.S. Energy Information Administration / Annual Energy Review 2011 Notes: Data are for locations of identified hydrothermal ...

93

Assumptions to the Annual Energy Outlook 2008  

Gasoline and Diesel Fuel Update (EIA)

8) 8) Release date: June 2008 Next release date: March 2009 Assumptions to the Annual Energy Outlook 2008 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Natural Gas Transmission and Distribution Module. . . . . . . . . . . . . . . . . . . . . . 113 Petroleum Market Module

94

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7, DOE/EIA- 7, DOE/EIA- M068(2007). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described. EMM Regions The supply regions used in EMM are based on the North American Electric Reliability Council regions and

95

EIA - Assumptions to the Annual Energy Outlook 2009 - Renewable Fuels  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2009 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind1. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy.

96

Assumptions to the Annual Energy Outlook 2013  

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

Energy Module Energy Module This page inTenTionally lefT blank 21 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 International Energy Module The LFMM International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the LFMM IEM computes BRENT and WTI prices, provides a supply curve of world crude-like liquids, and generates a worldwide oil supply- demand balance with regional detail. The IEM also provides, for each year of the projection period, endogenous and

97

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2004 Assumptions to the Annual Energy Outlook 2004 143 Appendix A: Handling of Federal and Selected State Legislation and Regulation in the Annual Energy Outlook Legislation Brief Description AEO Handling Basis Residential Sector A. National Appliance Energy Conservation Act of 1987 Requires Secretary of Energy to set minimum efficiency standards for 10 appliance categories a. Room Air Conditioners Current standard of 8.82 EER Federal Register Notice of Final Rulemaking, b. Other Air Conditioners (<5.4 tons) Current standard 10 SEER for central air conditioner and heat pumps, increasing to 12 SEER in 2006. Federal Register Notice of Final Rulemaking, c. Water Heaters Electric: Current standard .86 EF, incr easing to .90 EF in 2004. Gas: Curren

98

Assumptions to the Annual Energy Outlook - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumption to the Annual Energy Outlook Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20041 (AEO2004), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview3, which is updated once every two years. The National Energy Modeling System The projections in the AEO2004 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the midterm time period and perform policy analyses requested by decisionmakers in the U.S. Congress, the Administration, including DOE Program Offices, and other government agencies.

99

Supply-side Resources & Planning Assumptions  

E-Print Network (OSTI)

modeling 146/19/2013 #12;6/19/2013 8 Commercial w/Limited PNW availability Proposed resources: ­ Biogas technologies Raft River Geothermal (ID)Biogas technologies Landfill Wastewater treatment Animal, commercial

100

Assumptions to the Annual Energy Outlook - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumption to the Annual Energy Outlook Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2004, DOE/EIA- M068(2004). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

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101

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2006 The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2006, DOE/EIA- M068(2006). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

102

EIA - Assumptions to the Annual Energy Outlook 2008 - Electricity Market  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2008 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2008, DOE/EIA-M068(2008). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

103

Essays on University Technology Management  

E-Print Network (OSTI)

Figure 3. Number of invention disclosures by technology typeFigure 1. Number of inventions by disclosure year. Figure 2.and the flow of invention disclosures to the OTT. By

Drivas, Kyriakos

2011-01-01T23:59:59.000Z

104

Microsoft Word - Figure_03_04.doc  

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

8 8 0 2 4 6 8 10 12 14 16 18 20 22 2010 2011 2012 2013 2014 Residential Commercial Industrial Electric Power Citygate dollars per thousand cubic feet Figure 3 and 4 0 2 4 6 8 10 12 14 16 18 20 22 2010 2011 2012 2013 2014 NGPL Composite Spot Price NG Spot Price at Henry Hub dollars per thousand c ubic feet Note: Prices are in nominal dollars. Source: Table 3. Figure 3. Average citygate and consumer prices of natural gas in the United States, 2010-2013 Figure 4. Spot prices of natural gas and natural gas plant liquids in the United States, 2010-2013

105

Kaganovich et al Supplementary Figure S1  

E-Print Network (OSTI)

n n Kaganovich et al Supplementary Figure S1 WT+MG13237°Ccim3-1 Ubc9 ts Ubc9 ts 37°C a b n n cim3 al Supplementary Figure S2 c b ts cim3-1 (min): 0 5 10 15 60 60 GFP-Ubc9 + 20M Benomyltime at 37 °C Figure S3 GFP-VHL T S P T S P 30°C 37°C 1hr Ub-GFP Sup-Pellet assay cim3-1 GFP-VHL a b VHL in cim3

Bedwell, David M.

106

Assumptions to Annual Energy Outlook - Energy Information Administrati...  

Annual Energy Outlook 2012 (EIA)

Assumptions to AEO2013 Release Date: May 14, 2013 | Next Release Date: May 2014 | full report Introduction This report presents the major assumptions of the National Energy...

107

Assumptions to the Annual Energy Outlook - Table 41  

Annual Energy Outlook 2012 (EIA)

> Forecasts >Assumptions to the Annual Energy Outlook> Download Report Assumption to the Annual Energy Outlook Adobe Acrobat Reader Logo Adobe Acrobat Reader is required for PDF...

108

Figure ES1. Map of Northern Alaska  

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

Figure ES1. Map of Northern Alaska figurees1.jpg (61418 bytes) Source: Edited from U.S. Geological Survey, "The Oil and Gas Resource Potential of the Arctic National Wildlife...

109

arXiv.org help - Bitmapping Figures  

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

Bitmapping Figures Many graphics and plotting programs do not take into account that people might want to send their output over the internet instead of to a local printer. These...

110

Microsoft Word - figure_08_2008.doc  

Annual Energy Outlook 2012 (EIA)

9 48.5 Egypt Japan Canada Mexico Figure 8. Flow of Natural Gas Imports and Exports, 2007 (Billion Cubic Feet) Note: U.S. exports to Canada and Mexico include liquefied natural gas...

111

Microsoft Word - Figure_8_Oct2009.doc  

Gasoline and Diesel Fuel Update (EIA)

19 50 Japan Canada Mexico Figure 8. Flow of Natural Gas Imports and Exports, 2008 (Billion Cubic Feet) Note: U.S. exports to Canada and Mexico include liquefied natural gas (LNG)....

112

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, and (4) the implementation of recent regulatory reform. A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, Model Documentation 2003, DOE/EIA- M062(2003) (Washington, DC, January 2003).

113

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20031 (AEO2003), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2003 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the midterm time period and perform policy analyses requested by decisionmakers and analysts in the U.S. Congress, the Department of Energy’s Office of Policy and International Affairs, other DOE offices, and other government agencies.

114

Assumptions to the Annual Energy Outlook 1999 - Table 1  

Gasoline and Diesel Fuel Update (EIA)

Summary of AEO99 Cases Summary of AEO99 Cases Case Name Description Integration mode Reference Baseline economic growth, world oil price, and technology assumptions Fully Integrated Low Economic Growth Gross Domestic product grows at an average annual rate of 1.5 percent, compared to the reference case growth of 2.1 percent. Fully Integrated High Economic Growth Gross domestic product grows at an average annual rate of 2.6 percent, compared to the reference case growth of 2.1 percent. Fully Integrated Low World Oil Price World oil prices are $14.57 per barrel in 2020, compared to $22.73 per barrel in the reference case. Partially Integrated High World Oil Price World oil prices are $29.35 per barrel in 2020, compared to $22.73 per barrel in the reference case. Partially Integrated Residential: 1999 Technology

115

EIS-0023-FEIS-Figures-1979.pdf  

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

NORTM NORTM CAROLINA 2 -- r /'- 3Charlo,te Gree,v:; I, o s. \ '~ ( % SOUTH CAROLINA ".4 o " .Alkenoco'"mb'a A1l.a,to \ August. ( SRP O Macon \ GEORGIA ? Charleston 50 MI ".* / 100 Ml 150 Mi 1 \ ATLANTIC OCEAN Sov.nn.h / FIGURE III-1. Location of SRP Relative to Surrounding Population Centers III-2 --- - FIGURE III-2. The Savannah River Plant III-3 FIGURE 'III-3. Profile of Geologic Formation Beneath the Savannah River Plant . III-5 ,-, -,.. . . . . . 5 .-- -612 CRYSTALLINE ROCK . II rfoce FIGURE III-4. Hydrostatic Head in Ground Water Near H Area III-8 ~'z 'Kw ) -.- ________ Alu EN F PLATEAU ";<--'-----% \ ~//i.s,t,,7 --- I '220--- Heed in Tuscaloosa ft H20 obove me.. $,0 level - 5 0 5 10 ,5 MILES FIGURE III-5. Flow in Tuscaloosa Aquifer (Ongoing hydrographic measurements indicate that this flow pattern has remained the same under the SRP site since the early 1950' s.) 111-10 . FIGURE

116

Assumptions to the Annual Energy Outlook 2013  

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

Demand Module Demand Module This page inTenTionally lefT blank 39 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2040. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial.

117

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for each Census Division using the assumptions and methods described below.106

118

Assumptions to the Annual Energy Outlook - Contacts  

Gasoline and Diesel Fuel Update (EIA)

Contacts Contacts Assumption to the Annual Energy Outlook Contacts Specific questions about the information in this report may be directed to: Introduction Paul D. Holtberg 202/586-1284 Macroeconomic Activity Module Ronald F. Earley Yvonne Taylor 202/586-1398 202/586-1398 International Energy Module G. Daniel Butler 202/586-9503 Household Expenditures Module/ Residential Demand Module John H. Cymbalsky 202/586-4815 Commercial Demand Module Erin E. Boedecker 202/586-4791 Industrial Demand Module T. Crawford Honeycutt 202/586-1420 Transportation Demand Module John D. Maples 202/586-1757 Electricity Market Module Laura Martin 202/586-1494 Oil and Gas Supply Module/Natural Gas Transmission and Distribution Module Joseph Benneche 202/586-6132 Petroleum Market Module Bill Brown 202/586-8181

119

Assumptions to the Annual Energy Outlook 2013  

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

Demand Module Demand Module This page inTenTionally lefT blank 27 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" (UEC) by appliance (in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing

120

Assumptions to the Annual Energy Outlook 2013  

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

Industrial Demand Module Industrial Demand Module This page inTenTionally lefT blank 53 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Industrial Demand Module The NEMS Industrial Demand Module (IDM) estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are subdivided further into the energy- intensive manufacturing industries and non-energy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure. The non-manufacturing industries are modeled with less detail because processes are simpler and there is less available data. The petroleum refining

Note: This page contains sample records for the topic "technology assumptions figure" 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

Assumptions to the Annual Energy Outlook 2013  

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

Macroeconomic Activity Module Macroeconomic Activity Module This page inTenTionally lefT blank 17 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents interactions between the U.S. economy and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP), is a key determinant of growth in the demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected

122

Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Tools Tools Printable Version Share this resource Send a link to Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology to someone by E-mail Share Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Facebook Tweet about Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Twitter Bookmark Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Google Bookmark Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Delicious Rank Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Digg Find More places to share Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on AddThis.com...

123

EIA - Assumptions to the Annual Energy Outlook 2008 - Renewable Fuels  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2008 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind1. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost energy storage systems.

124

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division. Key Assumptions The historical input data used to develop the HEM version for the AEO2003 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2003 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS).

125

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2003, DOE/EIA-M060(2003) (Washington, DC, January 2003). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of capacity utilization of mines, mining capacity, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

126

Assumptions to the Annual Energy Outlook 2001 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Key Assumptions Macroeconomic Sector Inputs

127

Assumptions to the Annual Energy Outlook - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumption to the Annual Energy Outlook Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).109 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

128

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).119 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

129

EIA-Assumptions to the Annual Energy Outlook - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2007 Oil and Gas Supply Module Figure 7. Oil and Gas Supply Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply on a regional basis (Figure 7). A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2006), (Washington, DC, 2006). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural

130

EIA - Assumptions to the Annual Energy Outlook 2008 - Oil and Gas Supply  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2008 Oil and Gas Supply Module Figure 7. Oil and Gas Supply Module. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply on a regional basis (Figure 7). A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2007), (Washington, DC, 2007). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural

131

EIA - Assumptions to the Annual Energy Outlook 2010 - Oil and Gas Supply  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2010 Oil and Gas Supply Module Figure 8. Natural Gas Transmission and Distribution Model Regions. The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas natural gas exploration and development on a regional basis (Figure 7). The OGSM is organized into 4 submodules: Onshore Lower 48 Oil and Gas Supply Submodule, Offshore Oil and Gas Supply Submodule, Oil Shale Supply submodule, and Alaska Oil and Gas Supply Submodule. A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2010), (Washington, DC, 2010). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural

132

EIS-0317-S1: Environmental Impact Statement, Maps and Figures...  

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

Environmental Impact Statement, Maps and Figures Kangley-Echo Lake Transmission Line Project Maps and Figures Bonneville Power Administration is proposing to build a new...

133

Sheet Metal Forming: A Review - Figure 18 - TMS  

Science Conference Proceedings (OSTI)

Figure 18. Fracture and local necking strains in aluminum alloy 5154. Under balanced biaxial tension, failure occurs by fracture before local necking. Figure 18...

134

Figure 2. Energy Consumption of Vehicles, Selected Survey Years  

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

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure 2 Figure 2. Energy Consumption of Vehicles, Selected Survey Years...

135

Microsoft Word - Figure_14_15.doc  

Gasoline and Diesel Fuel Update (EIA)

44 0 2 4 6 8 10 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 Dollars per Thousand Cubic Feet 0 40 80 120 160 200 240 280 320 Dollars per Thousand Cubic Meters Constant Dollars Nominal Dollars Figure 14. Average Price of Natural Gas Delivered to Residential Consumers, 1980-2002 Figure 15. Average City Gate Price of Natural Gas in the United States, 2002 (Dollars per Thousand Cubic Feet) Sources: Nominal dollars: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-910, "Monthly Natural Gas Marketer Survey." Constant dollars: Prices were converted to 2002 dollars using the chain-type price indexes for Gross Domestic Product (1996 = 1.0) as published by the U.S. Department of Commerce, Bureau of Economic Analysis.

136

Figure and finish of grazing incidence mirrors  

SciTech Connect

Great improvement has been made in the past several years in the quality of optical components used in synchrotron radiation (SR) beamlines. Most of this progress has been the result of vastly improved metrology techniques and instrumentation permitting rapid and accurate measurement of the surface finish and figure on grazing incidence optics. A significant theoretical effort has linked the actual performance of components used as x-ray wavelengths to their topological properties as measured by surface profiling instruments. Next-generation advanced light sources will require optical components and systems to have sub-arc second surface figure tolerances. This paper will explore the consequences of these requirements in terms of manufacturing tolerances to see if the present manufacturing state-of-the-art is capable of producing the required surfaces. 15 refs., 14 figs., 2 tabs.

Takacs, P.Z. (Brookhaven National Lab., Upton, NY (USA)); Church, E.L. (Picatinny Arsenal, Dover, NJ (USA). Army Armament Research, Development and Engineering Center)

1989-08-01T23:59:59.000Z

137

Figure correction of multilayer coated optics  

DOE Patents (OSTI)

A process is provided for producing near-perfect optical surfaces, for EUV and soft-x-ray optics. The method involves polishing or otherwise figuring the multilayer coating that has been deposited on an optical substrate, in order to correct for errors in the figure of the substrate and coating. A method such as ion-beam milling is used to remove material from the multilayer coating by an amount that varies in a specified way across the substrate. The phase of the EUV light that is reflected from the multilayer will be affected by the amount of multilayer material removed, but this effect will be reduced by a factor of 1-n as compared with height variations of the substrate, where n is the average refractive index of the multilayer.

Chapman; Henry N. (Livermore, CA), Taylor; John S. (Livermore, CA)

2010-02-16T23:59:59.000Z

138

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

139

Assumptions to the Annual Energy Outlook 2000 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Key Assumptions Macroeconomic Sector Inputs

140

Assumptions to the Annual Energy Outlook - Commercial Demand...  

Annual Energy Outlook 2012 (EIA)

categories16 in each of the nine Census divisions (see Figure 5). The model begins by developing forecasts of floorspace for the 99 building category and Census division...

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141

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

142

Short-Term Energy Outlook Figures  

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

Independent Statistics & Analysis" Independent Statistics & Analysis" ,"U.S. Energy Information Administration" ,"Short-Term Energy Outlook Figures, December 2013" ,"U.S. Prices" ,,"West Texas Intermediate (WTI) Crude Oil Price" ,,"U.S. Gasoline and Crude Oil Prices" ,,"U.S. Diesel Fuel and Crude Oil Prices" ,,"Henry Hub Natural Gas Price" ,,"U.S. Natural Gas Prices" ,"World Liquid Fuels" ,,"World Liquid Fuels Production and Consumption Balance" ,,"Estimated Unplanned Crude Oil Production Outages Among OPEC Producers" ,,"Estimated Unplanned Crude Oil Production Disruptions Among non-OPEC Producers" ,,"World Liquid Fuels Consumption" ,,"World Liquid Fuels Consumption Growth"

143

Biennial Assessment of the Fifth Power Plan Gas Turbine Power Plant Planning Assumptions  

E-Print Network (OSTI)

Biennial Assessment of the Fifth Power Plan Gas Turbine Power Plant Planning Assumptions October 17, 2006 Simple- and combined-cycle gas turbine power plants fuelled by natural gas are among the bulk-emission and efficient gas turbine technology made combined-cycle gas turbine power plants the "resource of choice

144

Microsoft Word - Figure_18_19.doc  

Gasoline and Diesel Fuel Update (EIA)

9 9 0.00-2.49 2.50-4.49 4.50-6.49 6.50-8.49 8.50-10.49 10.50+ WA ID MT OR CA NV UT AZ NM CO WY ND SD MN WI NE IA KS MO TX IL IN OH MI OK AR TN WV VA KY PA WI NY VT NH MA CT ME RI NJ DE DC NC SC GA AL MS LA FL HI AK MD 0.00-2.49 2.50-4.49 4.50-6.49 6.50-8.49 8.50-10.49 10.50+ WA ID MT OR CA NV UT AZ NM CO WY ND SD MN WI NE IA KS MO TX IL IN OH MI OK AR TN WV VA KY MD PA WI NY VT NH MA CT ME RI NJ DE DC NC SC GA AL MS LA FL HI AK Figure 18. Average Price of Natural Gas Delivered to U.S. Onsystem Industrial Consumers, 2004 (Dollars per Thousand Cubic Feet) Figure 19. Average Price of Natural Gas Delivered to U.S. Electric Power Consumers, 2004 (Dollars per Thousand Cubic Feet) Source: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition." Note: States where the electric power price has been withheld (see Table 23) are included in the $0.00-$2.49 price category.

145

Microsoft Word - Figure_14_15.doc  

Gasoline and Diesel Fuel Update (EIA)

5 5 0.00-2.49 2.50-4.49 4.50-6.49 6.50-8.49 8.50-10.49 10.50+ WA ID MT OR CA NV UT AZ NM CO WY ND SD MN WI NE IA KS MO TX IL IN OH MI OK AR TN WV VA KY MD PA WI NY VT NH MA CT ME RI NJ DC NC SC GA AL MS LA FL HI AK DE 0 2 4 6 8 10 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 Dollars per Thousand Cubic Feet 0 40 80 120 160 200 240 280 320 360 Dollars per Thousand Cubic Meters Constant Dollars Nominal Dollars Figure 14. Average Price of Natural Gas Delivered to Residential Consumers, 1980-2004 Figure 15. Average City Gate Price of Natural Gas in the United States, 2004 (Dollars per Thousand Cubic Feet) Sources: Nominal dollars: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," and Form EIA-910, "Monthly Natural Gas Marketer Survey." Constant dollars: Prices were converted to 2004 dollars using the chain-type price indexes for Gross Domestic Product

146

EIA - Assumptions to the Annual Energy Outlook 2010  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2010 This report summarizes the major assumptions used in the NEMS to generate the AEO2010 projections. Introduction Macroeconomic Activity Module International Energy Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Renewable Fuels Module PDF (GIF) Appendix A: Handling of Federal and Selected State Legislation and Regulation In the Annual Energy Outlook Past Assumptions Editions Download the Report Assumptions to the Annual Energy Outlook 2010 Report Cover. Need help, contact the National Energy Information Center at 202-586-8800.

147

EIA - Assumptions to the Annual Energy Outlook 2009 - Coal Market...  

Annual Energy Outlook 2012 (EIA)

of mining equipment, the cost of factor inputs (labor and fuel), and other mine supply costs. The key assumptions underlying the coal production modeling are: As capacity...

148

Assumptions to the Annual Energy Outlook - Macroeconomic Activity...  

Annual Energy Outlook 2012 (EIA)

Macroeconomic Activity Module Assumption to the Annual Energy Outlook Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the...

149

Microsoft Word - Figure_3_4.doc  

Gasoline and Diesel Fuel Update (EIA)

7 7 None 1-15,000 15,001-100,000 100,001-200,000 200,001-500,000 500,001-and over WA ID MT OR CA NV UT AZ NM CO WY ND SD MN WI NE IA KS MO TX IL IN OH MI OK AR TN WV VA KY MD PA WI NY VT NH MA CT ME RI NJ DE DC NC SC GA AL MS LA FL HI AK GOM 0 1 2 3 4 5 6 7 T e x a s G u l f o f M e x i c o N e w M e x i c o O k l a h o m a W y o m i n g L o u i s i a n a C o l o r a d o A l a s k a K a n s a s A l a b a m a A l l O t h e r S t a t e s Trillion Cubic Feet 0 30 60 90 120 150 180 Billion Cubic Meters 2002 2003 2002 Figure 4. Marketed Production of Natural Gas in Selected States and the Gulf of Mexico, 2002-2003 Figure 3. Marketed Production of Natural Gas in the United States and the Gulf of Mexico, 2003 (Million Cubic Feet) GOM = Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA-895, "Monthly and Annual Quantity and Value of Natural Gas Report," and the United States Mineral Management

150

Assumption-Commitment Support for CSP Model Checking  

E-Print Network (OSTI)

AVoCS 2006 Assumption-Commitment Support for CSP Model Checking Nick Moffat1 Systems Assurance using CSP. In our formulation, an assumption-commitment style property of a process SYS takes the form-Guarantee, CSP, Model Checking, Compositional Reasoning 1 Introduction The principle of compositional program

Paris-Sud XI, Université de

151

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

6 6 Assumptions to the Annual Energy Outlook 2006 This report presents major assumptions of NEMS that are used to generate the projections in the AEO2006. Contents (Complete Report) Download complete Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Introduction Section to the Assumptions to the Annual Energy Outlook 2006 Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Section to the Assumptions to the Annual Energy Outlook 2006 Report. Need help, contact the National Energy Information Center at 202-586-8800. Macroeconomic Activity Module Macroeconomic Activity Module Section to the Assumptions to the Annual Energy Outlook 2006 Report. Need help, contact the National Energy Information Center at 202-586-8800.

152

Microsoft Word - Figure_3_4.doc  

Gasoline and Diesel Fuel Update (EIA)

7 7 0 1 2 3 4 5 6 7 T e x a s G u l f o f M e x i c o O k l a h o m a N e w M e x i c o W y o m i n g L o u i s i a n a C o l o r a d o A l a s k a K a n s a s C a l i f o r n i a A l l O t h e r S t a t e s Trillion Cubic Feet 0 30 60 90 120 150 180 Billion Cubic Meters 2003 2004 2003 Figure 4. Marketed Production of Natural Gas in Selected States and the Gulf of Mexico, 2003-2004 GOM = Gulf of Mexico Sources: Energy Information Administration (EIA), Form EIA -895, "Monthly Quantity and Value of Natural Gas Report," and the United States Mineral Management Service. Sources: Energy Information Administration (EIA), Form EIA -895, "Monthly Quantity and Value of Natural Gas Report," and the United States Mineral Management Service. None 1-15,000 15,001-100,000 100,001-200,000 200,001-500,000 500,001-and over

153

EIA - Assumptions to the Annual Energy Outlook 2009  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2009 The Early Release for next year's Annual Energy Outlook will be presented at the John Hopkins Kenney Auditorium on December 14th This report summarizes the major assumptions used in the NEMS to generate the AEO2009 projections. Introduction Macroeconomic Activity Module International Energy Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Renewable Fuels Module PDF (GIF) Appendix A: Handling of Federal and Selected State Legislation and Regulation In the Annual Energy Outlook Past Assumptions Editions

154

Assumptions to Annual Energy Outlook - Energy Information Administration  

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

Assumptions to AEO2013 Assumptions to AEO2013 Release Date: May 14, 2013 | Next Release Date: May 2014 | full report Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2013 [1] (AEO2013), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System Projections in the AEO2013 are generated using the NEMS, developed and maintained by the Office of Energy Analysis of the U.S. Energy Information Administration (EIA). In addition to its use in developing the Annual

155

Assumptions to Annual Energy Outlook - Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to AEO2012 Assumptions to AEO2012 Release Date: August 2, 2012 | Next Release Date: August 2013 | Full report Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2012 [1] (AEO2012), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System The projections in AEO2012 are generated using the NEMS, developed and maintained by the Office of Energy Analysis (OEA) of the U.S. Energy Information Administration (EIA). In addition to its use in developing the

156

Notes 01. The fundamental assumptions and equations of lubrication theory  

E-Print Network (OSTI)

The fundamental assumption in Lubrication Theory. Derivation of thin film flow equations from Navier-Stokes equations. Importance of fluid inertia effects in thin film flows. Some fluid physical properties

San Andres, Luis

2009-01-01T23:59:59.000Z

157

Prognostic Evaluation of Assumptions Used by Cumulus Parameterizations  

Science Conference Proceedings (OSTI)

Using a spectral-type cumulus parameterization that includes moist downdrafts within a three-dimensional mesoscale model, various disparate closure assumptions are systematically tested within the generalized framework of dynamic control, static ...

Georg A. Grell

1993-03-01T23:59:59.000Z

158

Computational soundness for standard assumptions of formal cryptography  

E-Print Network (OSTI)

This implementation is conceptually simple, and relies only on general assumptions. Specifically, it can be thought of as a 'self-referential' variation on a well-known encryption scheme. 4. Lastly, we show how the ...

Herzog, Jonathan, 1975-

2004-01-01T23:59:59.000Z

159

LBL-34045 UC-1600 Residential HVAC Data, Assumptions and Methodology  

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

5 UC-1600 Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1 Francis X. Johnson, Richard E. Brown, James W. Hanford, Alan H. Sanstad and...

160

Assumptions to the Annual Energy Outlook 1999 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

bullet1.gif (843 bytes) Feedback link.gif (1946 bytes) bullet1.gif (843 bytes) Assumptions to the AEO99 bullet1.gif (843 bytes) Interactive Data Queries to the AEO99 bullet1.gif...

Note: This page contains sample records for the topic "technology assumptions figure" 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

Idaho National Engineering Laboratory installation roadmap assumptions document. Revision 1  

SciTech Connect

This document is a composite of roadmap assumptions developed for the Idaho National Engineering Laboratory (INEL) by the US Department of Energy Idaho Field Office and subcontractor personnel as a key element in the implementation of the Roadmap Methodology for the INEL Site. The development and identification of these assumptions in an important factor in planning basis development and establishes the planning baseline for all subsequent roadmap analysis at the INEL.

Not Available

1993-05-01T23:59:59.000Z

162

EIA-Assumptions to the Annual Energy Outlook - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2007 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS25 data.

163

EIA-Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2007 Petroleum Market Module Figure 9. Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, and bioesters), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining

164

EIA-Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2007 Residential Demand Module Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" by appliance (or UEC-in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new

165

EIA-Assumptions to the Annual Energy Outlook - National Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2007 National Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

166

Assumptions to the Annual Energy Outlook - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumption to the Annual Energy Outlook Oil and Gas Supply Module Figure 7. Oil and Gas Supply Model Regions. Having problems, call our National Energy Information Center at 202-586-8800 for help. Table 50. Crude Oil Technically Recoverable Resources (Billion barrels) Printer Friendly Version Crude Oil Resource Category As of January 1, 2002 Undiscovered 56.02 Onshore 19.33 Northeast 1.47 Gulf Coast 4.76 Midcontinent 1.12 Southwest 3.25 Rocky Moutain 5.73 West Coast 3.00 Offshore 36.69 Deep (>200 meter W.D.) 35.01 Shallow (0-200 meter W.D.) 1.69 Inferred Reserves 49.14 Onshore 37.78 Northeast 0.79 Gulf Coast 0.80 Midcontinent 3.73 Southwest 14.61 Rocky Mountain 9.91 West Coast 7.94

167

Technologies  

Technologies Materials. Aggregate Spray for Air Particulate; Actuators Made From Nanoporous Materials; Ceramic Filters; Energy Absorbing Material; Diode Arrays for ...

168

Technologies  

Science & Technology. Weapons & Complex Integration. News Center. News Center. Around the Lab. Contacts. For Reporters. Livermore Lab Report. ...

169

Technologies  

Technologies Energy. Advanced Carbon Aerogels for Energy Applications; Distributed Automated Demand Response; Electrostatic Generator/Motor; Modular Electromechanical ...

170

Technologies  

Technologies Energy, Utilities, & Power Systems. Advanced Carbon Aerogels for Energy Applications; Distributed Automated Demand Response; Electrostatic Generator/Motor

171

Technologies  

Technologies Research Tools. Cell-Free Assembly of NanoLipoprotein Particles; Chemical Prism; Lawrence Livermore Microbial Detection Array (LLMDA) ...

172

Figure 5. Percentage change in natural gas dry production and ...  

U.S. Energy Information Administration (EIA)

Figure 5. Percentage change in natural gas dry production and number of gas wells in the United States, 2007?2011 annual ...

173

Figure 8. Renewable energy share of U.S. electricity ...  

U.S. Energy Information Administration (EIA)

Title: Figure 8. Renewable energy share of U.S. electricity generation in four cases, 2000-2040 (percent) Subject: Annual Energy Outlook 2013 Author

174

Figure 79. Electricity sales and power sector generating ...  

U.S. Energy Information Administration (EIA)

Title: Figure 79. Electricity sales and power sector generating capacity, 1949-2040 (index, 1949 = 1.0) Subject: Annual Energy Outlook 2013 Author

175

Figure 15. Renewable electricity generation in three cases ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 15. Renewable electricity generation in three cases, 2005-2040 (billion kilowatthours) Extended Policies No Sunset ...

176

Figure 17. Electricity generation from natural gas in ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 17. Electricity generation from natural gas in three cases, 2005-2040 (billion kilowatthours) Extended Policies No Sunset

177

Figure 14. Lease condensate and natural gas plant liquids ...  

U.S. Energy Information Administration (EIA)

Figure 14 Date % LC % NGPL NGL Reserves Bn Barrels OGR-Brent Average 2009-2011 Liquids Reserves NGPL Reserves Condensate Reserves % Lease condensate ...

178

Figure 38. Levelized costs of nuclear electricity generation in ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 38. Levelized costs of nuclear electricity generation in two cases, 2025 (2011 dollars per megawatthour) Reference Small Modular Reactor

179

Figure 18. Energy-related carbon dioxide emissions in three ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 18. Energy-related carbon dioxide emissions in three cases, 2005-2040 (million metric tons) Extended Policies No Sunset

180

Ayn Rand, Alberti and the Authorial Figure of the Architect  

E-Print Network (OSTI)

Authorial Figure of the Architect Marvin Trachtenberg Whatnor was it written by an architect, historian, or critic. InRoark, an aspiring architect who, echoing the megalomania of

Trachtenberg, Marvin

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "technology assumptions figure" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
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181

Figure 1. Microsupercapacitors developed with novel carbon nano-  

E-Print Network (OSTI)

Figure 1. Microsupercapacitors developed with novel carbon nano- onion electrodes exhibit extremely resolution (Balke et al, Nano Letters 10, 3420, 2010). #12;

182

Mobility of Ions in Lanthanum Fluoride Nanoclusters--Figure 9  

Science Conference Proceedings (OSTI)

c, d. Figure 9. Shows the r-dependence of this function at several different temperatures. At each temperature the upper graph represents the F- van Hove...

183

Figure 64. Industrial energy consumption by fuel, 2011, 2025, and ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 64. Industrial energy consumption by fuel, 2011, 2025, and 2040 (quadrillion Btu) Natural Gas Petroleum and other liquids

184

Figure 63. Industrial delivered energy consumption by application ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 63. Industrial delivered energy consumption by application, 2011-2040 (quadrillion Btu) Manufacturing heat and power Nonmanufacturing heat ...

185

Figure 51. World production of liquids from biomass, coal ...  

U.S. Energy Information Administration (EIA)

Title: Figure 51. World production of liquids from biomass, coal, and natural gas in three cases, 2011 and 2040 (million barrels per day) Subject

186

Annual Energy Outlook with Projections to 2025-Figure 1. Energy...  

Gasoline and Diesel Fuel Update (EIA)

With Projections to 2025 Figure 1. Energy price projectionsm 2001-2025: AEO2002 and AEO2003 compared (2001 dollars). For more detailed information, contact the National Energy...

187

Figure 34. Ratio of average per megawatthour fuel costs ...  

U.S. Energy Information Administration (EIA)

Title: Figure 34. Ratio of average per megawatthour fuel costs for natural gas combined-cycle plants to coal-fired steam turbines in the RFC west ...

188

Figure 77. Electricity generation capacity additions by fuel type ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 77. Electricity generation capacity additions by fuel type, including combined heat and power, 2012-2040 (gigawatts) Coal

189

Figure 6. Type of Homes by Insulation, 2001  

U.S. Energy Information Administration (EIA)

Home >>Residential Home Page>>Insulation > Figure 6. Type of Homes by Insulation, 2001. To Top. Contacts: Specific questions may be directed to:

190

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2006 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20061 (AEO2006), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview3, which is updated once every few years. The National Energy Modeling System

191

Assumptions to the Annual Energy Outlook 1999 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

link.gif (1946 bytes) link.gif (1946 bytes) bullet1.gif (843 bytes) Assumptions to the AEO99 bullet1.gif (843 bytes) Supplemental Tables to the AEO99 bullet1.gif (843 bytes) To Forecasting Home Page bullet1.gif (843 bytes) EIA Homepage introduction.gif (4117 bytes) This paper presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 19991 (AEO99), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3

192

Technologies  

High Performance Computing (HPC) Technologies; Industrial Partnerships Office P.O. Box 808, L-795 Livermore, CA 94551 Phone: (925) 422-6416 Fax: (925) ...

193

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7) 7) Release date: April 2007 Next release date: March 2008 Assumptions to the Annual Energy Outlook 2007 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Natural Gas Transmission and Distribution Module. . . . . . . . . . . . . . . . . . . . . . 107 Petroleum Market Module

194

A Comparison of the Free Ride and CISK Assumptions  

Science Conference Proceedings (OSTI)

In a recent paper Fraedrich and McBride have studied the relation between the free ride and CISK (conditional instability of the second kind) assumptions in a well-known two-layer model. Here the comparison is extended to a more general case. ...

Torben Strunge Pedersen

1991-08-01T23:59:59.000Z

195

2008 Geothermal Technologies Market Report  

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

the Middle East and Africa Asian and Oceanic Countries 2008 Geothermal Technologies Market Report | July 2009 9 The information shown in Figure 3 comes from industry surveys...

196

2008 Solar Technologies Market Report  

E-Print Network (OSTI)

72 Figure 3.20. Generic parabolic trough CSP costwhich is dominated by parabolic trough technology, troughsMarket (GW) Share Parabolic trough Tower Dish-engine Total

Price, S.

2010-01-01T23:59:59.000Z

197

Technology  

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

Technology Computers and the internet play an increasingly larger role in the lives of students. In this activity, students must use various web sites to locate specific pieces of...

198

Assumption Parish, Louisiana: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Assumption Parish, Louisiana: Energy Resources Assumption Parish, Louisiana: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 29.9232544°, -91.09694° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":29.9232544,"lon":-91.09694,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

199

PROJECT MANGEMENT PLAN EXAMPLES Policy & Operational Decisions, Assumptions  

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

Policy & Operational Decisions, Assumptions Policy & Operational Decisions, Assumptions and Strategies Examples 1 & 2 Example 1 1.0 Summary The 322-M Metallurgical Laboratory is currently categorized as a Radiological Facility. It is inactive with no future DOE mission. In May of 1998 it was ranked Number 45 in the Inactive Facilities Risk Ranking database which the Facilities Decommissioning Division maintains. A short-term surveillance and maintenance program is in-place while the facility awaits final deactivation. Completion of the end points described in this deactivation project plan will place the 322-M facility into an End State that can be described as "cold and dark". The facility will be made passively safe requiring minimal surveillance and no scheduled maintenance.

200

Assumptions to the Annual Energy Outlook 2002 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20021 (AEO2002), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2002 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of

Note: This page contains sample records for the topic "technology assumptions figure" 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

Assumptions to the Annual Energy Outlook 2001 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Outlook2001 Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20011 (AEO2001), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2001 were produced with the National Energy

202

Assumptions to the Annual Energy Outlook 2000 - Errata  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2000 Assumptions to the Annual Energy Outlook 2000 as of 4/4/2000 1. On table 20 "the fractional fuel efficiency change for 4-Speed Automatic" should be .045 instead of .030. On table 20 "the fractional fuel efficiency change for 5-Speed Automatic" should be .065 instead of .045. (Change made on 3/6/2000) 2. Table 28 should be labeled: "Alternative-Fuel Vehicle Attribute Inputs for Compact Cars for Two Stage Logit Model". (Change made on 3/6/2000) 3. The capital costs in Table 29 should read 1998 dollars not 1988 dollars. (Change made on 3/6/2000) 4. Table 37 changed the label "Year Available" to "First Year Completed." Changed the second sentence of Footnote 1 to read "these estimates are costs of new projects

203

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Key Assumptions Key Assumptions The historical input data used to develop the HEM version for the AEO2000 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2000 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and transportation sectors as inputs to the disaggregation algorithm that results in the direct fuel expenditure analysis. Household end-use and personal transportation service consumption are obtained by HEM from the NEMS Residential and Transportation Demand Modules. Household disposable income is adjusted with forecasts of total disposable income from the NEMS Macroeconomic Activity Module.

204

Effects of internal gain assumptions in building energy calculations  

DOE Green Energy (OSTI)

The utilization of direct solar gains in buildings can be affected by operating profiles, such as schedules for internal gains, thermostat controls, and ventilation rates. Building energy analysis methods use various assumptions about these profiles. The effects of typical internal gain assumptions in energy calculations are described. Heating and cooling loads from simulations using the DOE 2.1 computer code are compared for various internal-gain inputs: typical hourly profiles, constant average profiles, and zero gain profiles. Prototype single-family-detached and multi-family-attached residential units are studied with various levels of insulation and infiltration. Small detached commercial buildings and attached zones in large commercial buildings are studied with various levels of internal gains. The results of this study indicate that calculations of annual heating and cooling loads are sensitive to internal gains, but in most cases are relatively insensitive to hourly variations in internal gains.

Christensen, C.; Perkins, R.

1981-01-01T23:59:59.000Z

205

EIA - Assumptions to the Annual Energy Outlook 2009 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2009 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2009 (AEO2009),1 including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 The National Energy Modeling System The projections in the AEO2009 were produced with the NEMS, which is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and perform policy analyses requested by decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE Program Offices, and other government agencies. The Annual Energy Outlook (AEO) projections are also used by analysts and planners in other government agencies and outside organizations.

206

EIA - Assumptions to the Annual Energy Outlook 2010 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2010 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2010 [1] (AEO2010), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System The projections in the AEO2010 were produced with the NEMS, which is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and perform policy analyses requested by decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE Program Offices, and other government agencies. The Annual Energy Outlook (AEO) projections are also used by analysts and planners in other government agencies and outside organizations.

207

EIA - Assumptions to the Annual Energy Outlook 2008 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2008 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20081 (AEO2008), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 The National Energy Modeling System The projections in the AEO2008 were produced with the NEMS, which is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and perform policy analyses requested by decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE Program Offices, and other government agencies. The AEO projections are also used by analysts and planners in other government agencies and outside organizations.

208

Health Effects from Advanced Combustion and Fuel Technologies  

SciTech Connect

This document requires a separate file for the figures. It is for DOE's Office of Vehicle Technologies Annual Report

Barone, Teresa L [ORNL; Parks, II, James E [ORNL; Lewis Sr, Samuel Arthur [ORNL; Connatser, Raynella M [ORNL

2010-01-01T23:59:59.000Z

209

Figure 33. Ratio of average per megawatthour fuel costs for ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 33. Ratio of average per megawatthour fuel costs for natural gas combined-cycle plants to coal-fired steam turbines in the SERC southeast ...

210

Figure 27. Ratio of average per megawatthour fuel costs for ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 27. Ratio of average per megawatthour fuel costs for natural gas combined-cycle plants to coal-fired steam turbines in five cases, 2008-2040

211

Figure 6. Transportation energy consumption by fuel, 1990-2040 ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 6. Transportation energy consumption by fuel, 1990-2040 (quadrillion Btu) Motor Gasoline, no E85 Pipeline Other E85 Jet Fuel

212

Figure 5. Energy-related carbon dioxide emissions in four ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Reference High Oil/Gas Resouce CO2$15 CO2$15HR Released: May 2, 2013 Figure 5. Energy-related carbon dioxide emissions in four ...

213

Figure 88. Annual average Henry Hub spot prices for natural ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 88. Annual average Henry Hub spot prices for natural gas in five cases, 1990-2040 (2011 dollars per million Btu) Reference

214

Figure 86. Annual average Henry Hub spot natural gas prices ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 86. Annual average Henry Hub spot natural gas prices, 1990-2040 (2011 dollars per million Btu) Henry Hub Spot Price 1990.00

215

A system-wide productivity figure of merit  

Science Conference Proceedings (OSTI)

The goal of this note is to combine productivity and performance benchmark measurement and subjective evaluations into a single system-wide figure of merit that could, for example, be used for budget justifications and procurements. With simplifying ...

Declan Murphy; Thomas Nash; Lawrence Votta

2006-01-01T23:59:59.000Z

216

Figure 3 from "Plutonium: Coping with Instability" by Siegfried S ...  

Science Conference Proceedings (OSTI)

This figure shows the (a) U.S. and (b) Russian versions of the Pu-Ga phase diagram. The Russian version, with a eutectoid point of 97C and 7.9 at.% Ga, is

217

Figure ES2. Annual Indices of Real Disposable Income, Vehicle...  

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

ES2 Figure ES2. Annual Indices of Real Disposable Income, Vehicle-Miles Traveled, Consumer Price Index (CPI-U), and Real Average Retail Gasoline Price, 1978-2004, 1985100...

218

Figure 7.9 Coal Prices - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Figure 7.9 Coal Prices Total, 1949-2011 By Type, 1949-2011 By Type, 2011 214 U.S. Energy Information Administration / Annual Energy Review 2011

219

Figure 10.1 Renewable Energy Consumption (Quadrillion Btu)  

U.S. Energy Information Administration (EIA)

Figure 10.1 Renewable Energy Consumption (Quadrillion Btu) Total and Major Sources, 19492012 By Source, 2012 By Sector, 2012 Compared With Other Resources, 19492012

220

Particle Data Group - Figures from 2012 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson (rev.) Fig. 1 Fig. 2 Higgs Bosons:...

Note: This page contains sample records for the topic "technology assumptions figure" 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

Particle Data Group - Figures from 2009 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson (Rev.) Fig. 1 Fig. 2 Higgs Bosons:...

222

Particle Data Group - Figures from 2007 web update of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass of the W Boson Fig. 1 Searches for Higgs Bosons Fig. 1 Fig. 2...

223

Particle Data Group - Figures from 2008 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson Fig. 1 Fig. 2 Higgs Bosons: Theory and...

224

Particle Data Group - Figures from 2010 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson (rev.) Fig. 1 Fig. 2 Higgs Bosons:...

225

Particle Data Group - Figures from 2011 edition of RPP  

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

Leptons Quarks Mesons Baryons Searches Figures from the Reviews in the Gauge and Higgs Boson Listings: The Mass and Width of the W Boson (2010) Fig. 1 Fig. 2 Higgs Bosons:...

226

Sheet Metal Forming: A Review - Figure 6 - TMS  

Science Conference Proceedings (OSTI)

Figure 6. Forming-limit diagram for low-carbon steel. Data of Reference 6 have been replotted and a dashed line has been added for maximum tension (T = st),...

227

Figure SR2. Net Imports as Percentage of Domestic Consumption ...  

U.S. Energy Information Administration (EIA)

Figure SR2 of the U.S. Natural Gas Imports & Exports: 2009. This report provides an overview of U.S. international natural gas trade in 2009. Natural gas import and ...

228

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

T T he NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS 25 data.

229

EIA-Assumptions to the Annual Energy Outlook - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2007 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2007, DOE/EIA- M068(2007). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

230

Program Record 13006 (Offices of Vehicle Technologies and Fuel Cell Technologies: Life-Cycle Costs of Mid-Size Light-Duty Vehicles  

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

Program Record (Offices of Vehicle Technologies & Fuel Cell Program Record (Offices of Vehicle Technologies & Fuel Cell Technologies) Record #: 13006 Date: April 24, 2013 Title: Life-cycle Costs of Mid-Size Light-Duty Vehicles Originator: Tien Nguyen & Jake Ward Approved by: Sunita Satyapal Pat Davis Date: April 25, 2013 Items: DOE is pursuing a portfolio of technologies with the potential to significantly reduce greenhouse gases (GHG) emissions and petroleum consumption while being cost-effective. This record documents the assumptions and results of analyses conducted to estimate the life-cycle costs resulting from several fuel/vehicle pathways, for a future mid-size car. The results are summarized graphically in the following figure. Costs of Operation for Future Mid-Size Car

231

Assumptions to the Annual Energy Outlook 2000 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, (4) the implementation of recent regulatory reform, and (5) the implementation of provisions of the Climate Change Action Plan (CCAP). A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, Model Documentation 2000, DOE/EIA-M062(2000), January 2000.

232

Assumptions to the Annual Energy Outlook 2000 - Electricity Market Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module (EMM) represents the planning, operations, and pricing of electricity in the United States. It is composed of four primary submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. In addition, nonutility generation and supply and electricity transmission and trade are represented in the planning and dispatching submodules. Electricity Market Module (EMM) represents the planning, operations, and pricing of electricity in the United States. It is composed of four primary submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. In addition, nonutility generation and supply and electricity transmission and trade are represented in the planning and dispatching submodules. Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. The major assumptions are summarized below.

233

Assumptions to the Annual Energy Outlook 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction This paper presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20001 (AEO2000), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2000 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the midterm time period and perform policy analyses requested by decisionmakers and analysts in the U.S. Congress, the Department of Energy’s Office of Policy, other DOE offices, and other government agencies.

234

Assumptions to the Annual Energy Outlook 1999 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by obtaining market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, (4) the implementation of recent regulatory reform, and (5) the implementation of provisions of the Climate Change Action Plan (CCAP). A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation Report: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, DOE/EIA-MO62/1, January 1999.

235

Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumption to the Annual Energy Outlook Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2004, DOE/EIA-M060(2004) (Washington, DC, 2004). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of capacity utilization of mines, mining capacity, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

236

Assumptions to the Annual Energy Outlook 2000-Table 1. Summary of the  

Gasoline and Diesel Fuel Update (EIA)

0 Cases 0 Cases Case Name Description Integration mode Reference Baseline economic growth, world oil price, and technology assumptions Fully Integrated Low Economic Growth Gross Domestic product grows at an average annual rate of 1.7 percent, compared to the reference case growth of 2.2 percent. Fully Integrated High Economic Growth Gross domestic product grows at an average annual rate of 2.6 percent, compared to the reference case growth of 2.2 percent. Fully Integrated Low World Oil Price World oil prices are $14.90 per barrel in 2020, compared to $22.04 per barrel in the reference case. Fully Integrated High World Oil Price World oil prices are $28.04 per barrel in 2020, compared to $22.04 per barrel in the reference case. Fully Integrated Residential: 2000 Technology

237

Assumptions to the Annual Energy Outlook 2001 - Table 1. Summary of AEO2001  

Gasoline and Diesel Fuel Update (EIA)

1 Cases 1 Cases Case name Description Integration mode Reference Baseline economic growth, world oil price, and technology assumptions Fully integrated Low Economic Growth Gross domestic product grows at an average annual rate of 2.5 percent, compared to the reference case growth of 3.0 percent. Fully integrated High Economic Growth Gross domestic product grows at an average annual rate of 3.5 percent, compared to the reference case growth of 3.0 percent. Fully integrated Low World Oil Price World oil prices are $15.10 per barrel in 2020, compared to $22.41 per barrel in the reference case. Fully integrated High World Oil Price World oil prices are $28.42 per barrel in 2020, compared to $22.41 per barrel in the reference case. Fully integrated Residential: 2001 Technology

238

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

unfinished oil imports, other refinery inputs (including alcohols, unfinished oil imports, other refinery inputs (including alcohols, ethers, and bioesters), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining activities in the five Petroleum Area Defense Districts (PADDs) (Figure 9). The LP model is created by aggregating individual refineries within a PADD into one representative refinery, and linking all five PADD's via crude and product transit links. This representation provides the marginal costs of production for a number of conventional and new petroleum products. In order to interact with other NEMS modules with different regional representations,

239

BILIWG: Consistent "Figures of Merit" (Presentation)  

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

BILIWG: Consistent "Figures of Merit" BILIWG: Consistent "Figures of Merit" A finite set of results reported in consistent units * To track progress of individual projects on a consistent basis * To enable comparing projects in a transparent manner Potential BILIWG Figures of Merit Key BILI Distributed Reforming Targets * Cost ($/kg of H2): H2A analysis - Distributed reforming station,1000 kg/day ave./daily dispensed, 5000/6250 psi (and 10,000/12,000 psi) dispensing, 500 units/yr. * nth unit vs. 500 units/yr ? * production unit only (with 300 psi outlet pressure) ? * Production unit efficiency: LHV H2 out/(LHV of feedstocks and all other energy in) GTG - WTG efficiency? - Feedstock conversion energy efficiency? * Production unit capital cost: Distributed reforming station,1000 kg/day ave./daily dispensed, 300 psi outlet pressure

240

Assumptions to the Annual Energy Outlook - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumption to the Annual Energy Outlook Industrial Demand Module Table 17. Industry Categories Printer Friendly Version Energy-Intensive Manufacturing Nonenergy-Intensive Manufacturing Nonmanufacturing Industries Food and Kindred Products (NAICS 311) Metals-Based Durables (NAICS 332-336) Agricultural Production -Crops (NAICS 111) Paper and Allied Products (NAICS 322) Balance of Manufacturing (all remaining manufacturing NAICS) Other Agriculture Including Livestock (NAICS112- 115) Bulk Chemicals (NAICS 32B) Coal Mining (NAICS 2121) Glass and Glass Products (NAICS 3272) Oil and Gas Extraction (NAICS 211) Hydraulic Cement (NAICS 32731) Metal and Other Nonmetallic Mining (NAICS 2122- 2123) Blast Furnaces and Basic Steel (NAICS 331111) Construction (NAICS233-235)

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We encourage you to perform a real-time search of NLEBeta
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241

EIA - Assumptions to the Annual Energy Outlook 2009 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

242

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

clothes drying, ceiling fans, coffee makers, spas, home security clothes drying, ceiling fans, coffee makers, spas, home security systems, microwave ovens, set-top boxes, home audio equipment, rechargeable electronics, and VCR/DVDs. In addition to the major equipment-driven end-uses, the average energy consumption per household is projected for other electric and nonelectric appliances. The module's output includes number Energy Information Administration/Assumptions to the Annual Energy Outlook 2007 19 Pacific East South Central South Atlantic Middle Atlantic New England West South Central West North Central East North Central Mountain AK WA MT WY ID NV UT CO AZ NM TX OK IA KS MO IL IN KY TN MS AL FL GA SC NC WV PA NJ MD DE NY CT VT ME RI MA NH VA WI MI OH NE SD MN ND AR LA OR CA HI Middle Atlantic New England East North Central West North Central Pacific West South Central East South Central

243

EIA - Assumptions to the Annual Energy Outlook 2010 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services [1].

244

Assumptions to the Annual Energy Outlook 1999 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

petroleum.gif (4999 bytes) petroleum.gif (4999 bytes) The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for each Census Division using the assumptions and methods described below. 75

245

EIA - Assumptions to the Annual Energy Outlook 2009 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2009 Industrial Demand Module Table 6.1. Industry Categories. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 6.2.Retirement Rates. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process flow or end use accounting

246

EIA-Assumptions to the Annual Energy Outlook - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2007 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2007), (Washington, DC, January 2007).

247

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2006 The International Energy Module determines changes in the world oil price and the supply prices of crude oils and petroleum products for import to the United States in response to changes in U.S. import requirements. A market clearing method is used to determine the price at which worldwide demand for oil is equal to the worldwide supply. The module determines new values for oil production and demand for regions outside the United States, along with a new world oil price that balances supply and demand in the international oil market. A detailed description of the International Energy Module is provided in the EIA publication, Model Documentation Report: The International Energy Module of the National Energy Modeling System, DOE/EIA-M071(06), (Washington, DC, February 2006).

248

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7 7 1 (AEO2007), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant to formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports. 2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview 3 , which is updated once every few years. The National Energy Modeling System The projections in the AEO2007 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and

249

EIA - Assumptions to the Annual Energy Outlook 2009 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2010 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Document>ation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2009), (Washington, DC, January 2009).

250

Assumptions to the Annual Energy Outlook 2001 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Completed Copy in PDF Format Completed Copy in PDF Format Related Links Annual Energy Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Household Expenditures Module Key Assumptions The historical input data used to develop the HEM version for the AEO2001 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2001 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and

251

Assumptions to the Annual Energy Outlook 1999 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

coal.gif (4423 bytes) coal.gif (4423 bytes) The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Model Documentation: Coal Market Module of the National Energy Modeling System, DOE/EIA-MO60. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

252

Assumptions to the Annual Energy Outlook 2001 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2001, DOE/EIA-M060(2001) January 2001. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

253

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7), 7), (Washington, DC, January 2007). Key Assumptions The output of the U.S. economy, measured by GDP, is expected to increase by 2.9 percent between 2005 and 2030 in the reference case. Two key factors help explain the growth in GDP: the growth rate of nonfarm employment and the rate of productivity change associated with employment. As Table 3 indicates, for the Reference Case GDP growth slows down in each of the periods identified, from 3.0 percent between 2005 and 2010, to 2.9 percent between 2010 and 2020, to 2.8 percent in the between 2020 and 2030. In the near term from 2005 through 2010, the growth in nonfarm employment is low at 1.2 percent compared with 2.4 percent in the second half of the 1990s, while the economy is expected to experiencing relatively strong

254

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2006 The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.14

255

EIA - Assumptions to the Annual Energy Outlook 2008 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2008 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2007), (Washington, DC, January 2007).

256

EIA - Assumptions to the Annual Energy Outlook 2009 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2009 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2008), (Washington, DC, January 2008).

257

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7, DOE/EIA-M060(2007) (Washington, 7, DOE/EIA-M060(2007) (Washington, DC, 2007). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

258

EIA - Assumptions to the Annual Energy Outlook 2008 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2008 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

259

Assumptions to the Annual Energy Outlook 2002 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2002, DOE/EIA-M060(2002) (Washington, DC, January 2002). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

260

EIA - Assumptions to the Annual Energy Outlook 2010 - Transportation...  

Gasoline and Diesel Fuel Update (EIA)

per vehicle. EIA assumes that credit allowances for PZEVs will be met with conventional vehicle technology, hybrid vehicles will be sold to meet the AT-PZEV allowances, and that...

Note: This page contains sample records for the topic "technology assumptions figure" 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

EIA-Assumptions to the Annual Energy Outlook - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2007 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind.112 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost energy storage systems.

262

List of Figures xii List of Tables xv  

E-Print Network (OSTI)

. . . . . . . . . . . . . . . . . . . . . . . . 137 II Energy Supply Chains 139 6 Electric Power Supply Chains 141 6.1 The Supply Chain ModelContents List of Figures xii List of Tables xv Preface xvi I Supply Chain Networks 1 1 Introduction and Overview 3 2 Supply Chain Networks 9 2.1 The Supply Chain Network Model . . . . . . . . . . . . . . . 11 2

Nagurney, Anna

263

Figure 62. Additions to electricity generation capacity in the ...  

U.S. Energy Information Administration (EIA)

Microturbines Wind Solar photovoltaics Released: April 30, 2013 No Sunset $0.90 $0.80 $2.27 $2.15 $5.04 $4.65 $2.96 $0.66 $13.72 $10.17. Title: Figure 62.

264

Thermoelectric figure of merit of LSCoO-Mn perovskites  

Science Conference Proceedings (OSTI)

Oxide ceramics with nominal composition of La"0"."8Sr"0"."2Co"1"-"xMn"xO"3(0= Keywords: 72.20.Pa, 84.60.Bk, 84.60.Rb, 85.80.Fi, LSCoO compounds, Thermoelectric figure of merit, Thermoelectric materials

J. E. Rodrguez; D. Cadavid; L. C. Moreno

2008-11-01T23:59:59.000Z

265

Object Recognition by Sequential Figure-Ground Ranking  

Science Conference Proceedings (OSTI)

We present an approach to visual object-class segmentation and recognition based on a pipeline that combines multiple figure-ground hypotheses with large object spatial support, generated by bottom-up computational processes that do not exploit knowledge ... Keywords: Learning and ranking, Object recognition, Semantic segmentation

Joo Carreira; Fuxin Li; Cristian Sminchisescu

2012-07-01T23:59:59.000Z

266

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind108. Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind108. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost energy storage systems.

267

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

12 12 . Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost

268

Assumptions to the Annual Energy Outlook 2000 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

269

EIA - Assumptions to the Annual Energy Outlook 2008 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2008 International Energy Module The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously global and U.S.A. petroleum liquids supply and demand curves (1 curve per year; 2008-2030; approximated, isoelastic fit to previous NEMS results). These quantities are not modeled directly in NEMS. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2008 with IEO2007 and the STEO some functionality was removed from IEM while a new algorithm was implemented. Based on the difference between U.S. total petroleum liquids production (consumption) and the expected U.S. total liquids production (consumption) at the current WTI price, curves for global petroleum liquids consumption (production) were adjusted for each year. According to previous operations, a new WTI price path was generated. An exogenous oil supply module, Generate World Oil Balances (GWOB), was also used in IEM to provide annual regional (country) level production detail for conventional and unconventional liquids.

270

Assumptions to the Annual Energy Outlook 2000 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for each Census Division using the assumptions and methods described below.100

271

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2006, DOE/EIA-M060(2006) (Washington, DC, 2006). Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2006, DOE/EIA-M060(2006) (Washington, DC, 2006). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

272

Design assumptions and bases for small D-T-fueled spherical tokamak (ST) fusion core  

SciTech Connect

Recent progress in defining the assumptions and clarifying the bases for a small D-T-fueled ST fusion core are presented. The paper covers several issues in the physics of ST plasmas, the technology of neutral beam injection, the engineering design configuration, and the center leg material under intense neutron irradiation. This progress was driven by the exciting data from pioneering ST experiments, a heightened interest in proof-of-principle experiments at the MA level in plasma current, and the initiation of the first conceptual design study of the small ST fusion core. The needs recently identified for a restructured fusion energy sciences program have provided a timely impetus for examining the subject of this paper. Our results, though preliminary in nature, strengthen the case for the potential realism and attractiveness of the ST approach.

Peng, Yueng Kay Martin [ORNL; Haines, J.R. [Oak Ridge National Laboratory (ORNL)

1996-01-01T23:59:59.000Z

273

NOvA (Fermilab E929) Official Plots and Figures  

DOE Data Explorer (OSTI)

The NOvA collaboration, consisting of 180 researchers across 28 institutions and managed by the Fermi National Accelerator Laboratory (FNAL), is developing instruments for a neutrino-focused experiment that will attempt to answer three fundamental questions in neutrino physics: 1) Can we observe the oscillation of muon neutrinos to electron neutrinos; 2) What is the ordering of the neutrino masses; and 3) What is the symmetry between matter and antimatter? The collaboration makes various data plots and figures available. These are grouped under five headings, with brief descriptions included for each individual figure: Neutrino Spectra, Detector Overview, Theta12 Mass Hierarchy CP phase, Theta 23 Delta Msqr23, and NuSterile.

274

LIST OF FIGURES ............................................... .. v LIST OF TABLES ..... ..... ..................................... vii  

E-Print Network (OSTI)

impatient for technological advances to occur, and they can construct the most Rube Goldburg contraptions

Oak Ridge National Laboratory

275

Assumptions to the Annual Energy Outlook 2002 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).117 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration,

276

Assumptions to the Annual Energy Outlook 2001 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).112 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration,

277

Assumptions to the Annual Energy Outlook 2000 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module (RFM) consists of five distinct submodules that represent the major renewable energy technologies. Although it is described here, conventional hydroelectric is included in the Electricity Market Module (EMM) and is not part of the RFM. Similarly, ethanol modeling is included in the Petroleum Market Module (PMM). Some renewables, such as municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not require the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using wind, solar, and geothermal energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

278

Assumptions to the Annual Energy Outlook 1999 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

renewable.gif (4875 bytes) renewable.gif (4875 bytes) The NEMS Renewable Fuels Module (RFM) consists of five distinct submodules that represent the major renewable energy technologies. Although it is described here, conventional hydroelectric is included in the Electricity Market Module (EMM) and is not part of the RFM. Similarly, ethanol modeling is included in the Petroleum Market Module (PMM). Some renewables, such as municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not require the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using wind, solar, and geothermal energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittence, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

279

A Statistical Analysis of the Dependency of Closure Assumptions in Cumulus Parameterization on the Horizontal Resolution  

Science Conference Proceedings (OSTI)

Simulated data from the UCLA cumulus ensemble model are used to investigate the quasi-universal validity of closure assumptions used in existing cumulus parameterizations. A closure assumption is quasi-universally valid if it is sensitive neither ...

Kuan-Man Xu

1994-12-01T23:59:59.000Z

280

Figure 30. Decomposition 4941 of Energy Use by Effect, 1988-1994 ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure 30

Note: This page contains sample records for the topic "technology assumptions figure" 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

Figure ES4. Sales-Weighted Inertia Weight and On-Road Fuel Mileage ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure ES4

282

Figure ES3. Sales-Weighted Horsepower and On-Road Fuel Mileage for ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure ES3

283

Figure ES1. Schema for Estimating Energy and Energy-Related ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure ES1

284

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

6 and 27) including incremental fuel 6 and 27) including incremental fuel efficiency improvement, incremental cost, first year of introduction, and fractional horsepower change. These assumed technology characterizations are scaled up or down to approximate the differences in each attribute for 6 Environmental Protection Administration (EPA) size classes of cars and light trucks. The vehicle sales share module holds the share of vehicle sales by import and domestic manufacturers constant within a vehicle size class at 1999 levels based on National Highway Traffic and Safety Administration data. 32 EPA size class sales shares are projected as a function of income per capita, fuel prices, and average predicted vehicle prices based on endogenous calculations within the MTCM

285

Assumptions to the Annual Energy Outlook 1999 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

transportation.gif (5318 bytes) transportation.gif (5318 bytes) The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

286

Comparison of risk-dominant scenario assumptions for several TRU waste facilities in the DOE complex  

Science Conference Proceedings (OSTI)

In order to gain a risk management perspective, the DOE Rocky Flats Field Office (RFFO) initiated a survey of other DOE sites regarding risks from potential accidents associated with transuranic (TRU) storage and/or processing facilities. Recently-approved authorization basis documents at the Rocky Flats Environmental Technology Site (RFETS) have been based on the DOE Standard 3011 risk assessment methodology with three qualitative estimates of frequency of occurrence and quantitative estimates of radiological consequences to the collocated worker and the public binned into three severity levels. Risk Class 1 and 2 events after application of controls to prevent or mitigate the accident are designated as risk-dominant scenarios. Accident Evaluation Guidelines for selection of Technical Safety Requirements (TSRs) are based on the frequency and consequence bin assignments to identify controls that can be credited to reduce risk to Risk Class 3 or 4, or that are credited for Risk Class 1 and 2 scenarios that cannot be further reduced. This methodology resulted in several risk-dominant scenarios for either the collocated worker or the public that warranted consideration on whether additional controls should be implemented. RFFO requested the survey because of these high estimates of risks that are primarily due to design characteristics of RFETS TRU waste facilities (i.e., Butler-type buildings without a ventilation and filtration system, and a relatively short distance to the Site boundary). Accident analysis methodologies and key assumptions are being compared for the DOE sites responding to the survey. This includes type of accidents that are risk dominant (e.g., drum explosion, material handling breach, fires, natural phenomena, external events, etc.), source term evaluation (e.g., radionuclide material-at-risk, chemical and physical form, damage ratio, airborne release fraction, respirable fraction, leakpath factors), dispersion analysis (e.g., meteorological assumptions, distance to receptors, plume meander, deposition, and other factors affecting the calculated {chi}/Q), dose assessments (specific activities, inhalation dose conversion factors, breathing rates), designated frequency of occurrence, and risk assignment per the DOE Standard 3011 methodology. Information from the sites is being recorded on a spreadsheet to facilitate comparisons. The first response from Westinghouse Safety Management Solutions for the Savannah River Site (SRS) also provided a detailed analysis of the major differences in methods and assumptions between RFETS and SRS, which forms much of the basis for this paper. Other sites responding to the survey include the Idaho National Engineering and Environmental Laboratory (INEEL), Hanford, and the Los Alamos National Laboratory (LANL).

Foppe, T.L. [Foppe and Associates, Inc., Golden, CO (United States); Marx, D.R. [Westinghouse Safety Management Solutions, Inc., Aiken, SC (United States)

1999-06-01T23:59:59.000Z

287

Fermilab E866 (NuSea) Figures and Data Plots  

DOE Data Explorer (OSTI)

The NuSea Experiment at Fermilab studied the internal structure of protons, in particular the difference between up quarks and down quarks. This experiment also addressed at least two other physics questions: nuclear effects on the production of charmonia states (bound states of charm and anti-charm quarks) and energy loss of quarks in nuclei from Drell-Yan measurements on nuclei. While much of the NuSea data are available only to the collaboration, figures, data plots, and tables are presented as stand-alone items for viewing or download. They are listed in conjunction with the published papers, theses, or presentations in which they first appeared. The date range is 1998 to 2008. To see these figures and plots, click on E866 publications or go directly to http://p25ext.lanl.gov/e866/papers/papers.html. Theses are at http://p25ext.lanl.gov/e866/papers/e866theses/e866theses.html and the presentations are found at http://p25ext.lanl.gov/e866/papers/e866talks/e866talks.html. Many of the items are postscript files.

E866 NuSea Collaboration

288

Evaluation of solar mirror figure by moire contouring  

DOE Green Energy (OSTI)

Moire topography is applied to the figure assessment of solar mirrors. The technique is demonstrated on component facets of a six-meter diameter, four-meter focal length, parabolic dish collector. The relative ease of experimental implementation and subsequent data analysis suggests distinct advantages over the more established laser ray trace or BCS/ICS technique for many applications. The theoretical and experimental considerations necessary to fully implement moire topography on mirror surfaces are detailed. A procedure to de-specularize the mirror is demonstrated which conserves the surface morphology without damaging the reflective surface. The moire fringe patterns observed for the actual mirror facets are compared with theoretical contours generated for representative dish facets using a computer simulation algorithm. A method for evaluating the figure error of the real facet is presented in which the error parameter takes the form of an average absolute deviation of the surface slope from theoretical. The experimental measurement system used for this study employs a 200 line/inch Ronchi transmission grating. The mirror surface is illuminated by a collimated beam at 60/sup 0/. The fringe observation is performed normal to the grating. These parameters yield contour intervals for the fringe patterns of 0.073 mm. The practical considerations for extending the techniques to higher resolution are discussed.

Griffin, J.W.; Lind, M.A.

1980-06-01T23:59:59.000Z

289

Assumptions to the Annual Energy Outlook 2000 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

290

Assumptions to the Annual Energy Outlook 1999 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

residential.gif (5487 bytes) residential.gif (5487 bytes) The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

291

2008 Solar Technologies Market Report  

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

JANUARY 2010 JANUARY 2010 Energy Efficiency & Renewable Energy 2008 SOLAR TECHNOLOGIES MARKET REPORT i Table of Contents Table of Contents ........................................................................................................................... i Figures ........................................................................................................................................... iii Tables ............................................................................................................................................. v Acknowledgments ........................................................................................................................ vi List of Acronyms ......................................................................................................................... vii

292

STAR (Solenoidal Tracker at RHIC) Figures and Data  

DOE Data Explorer (OSTI)

The primary physics task of STAR is to study the formation and characteristics of the quark-gluon plasma (QGP), a state of matter believed to exist at sufficiently high energy densities. STAR consists of several types of detectors, each specializing in detecting certain types of particles or characterizing their motion. These detectors work together in an advanced data acquisition and subsequent physics analysis that allows final statements to be made about the collision. The STAR Publications page provides access to all published papers by the STAR Collaboration, and many of them have separate links to the figures and data found in or supporting the paper. See also the data-rich summaries of the research at http://www.star.bnl.gov/central/physics/results/. [See also DDE00230

The STAR Collaboration

293

A1. Form EIA-176 Figure Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Form EIA-176 Form EIA-176 Figure Energy Information Administration / Natural Gas Annual 1996 214 EIA-176, ANNUAL REPORT OF NATURAL AND SUPPLEMENTAL GAS SUPPLY AND DISPOSITION, 19 PART IV: SUPPLY OF NATURAL AND SUPPLEMENTAL GAS RECEIVED WITHIN OR TRANSPORTED INTO REPORT STATE RESPONDENT COPY Page 2 PART III: TYPE OF COMPANY AND GAS ACTIVITIES OPERATED IN THE REPORT STATE 1.0 Type of Company (check one) 1.0 Control No. 2.0 Company Name 3.0 Report State 4.0 Resubmittal EIA Date: a b c d e Investor owned distributor Municipally owned distributor Interstate pipeline Intrastate pipeline Storage operator f g h i j SNG plant operator Integrated oil and gas Producer Gatherer Processor k Other (specify) 2.0 Gas Activities Operated On-system Within the Report State (check all that apply) a b c d e Produced Natural Gas

294

Noise figure and photon probability distribution in Coherent Anti-Stokes Raman Scattering (CARS)  

E-Print Network (OSTI)

The noise figure and photon probability distribution are calculated for coherent anti-Stokes Raman scattering (CARS) where an anti-Stokes signal is converted to Stokes. We find that the minimum noise figure is ~ 3dB.

Dimitropoulos, D; Jalali, B; Solli, D R

2006-01-01T23:59:59.000Z

295

A Review of Electric Vehicle Cost Studies: Assumptions, Methodologies, and Results  

E-Print Network (OSTI)

assumptions Battery costs and capacities: Lead acid batteryElectricity cost Battery cost and capacity: Lead acidElectricity cost Battery cost and capacity: N i C d

Lipman, Timothy

1999-01-01T23:59:59.000Z

296

Figure 1.6 State-Level Energy Consumption Estimates and Estimated ...  

U.S. Energy Information Administration (EIA)

Figure 1.6 State-Level Energy Consumption Estimates and Estimated Consumption per Capita, 2010 Consumption Consumption per Capita

297

Technology I, II, and III: Criteria for Understanding and Improving the Practice of Instructional Technology.  

E-Print Network (OSTI)

??In an earlier era of instructional technology, researchers proposed a set of criteria to help practitioners understand what assumptions about their work could help them (more)

McDonald, Jason K 1975-

2006-01-01T23:59:59.000Z

298

OVERVIEW OF ASSESSMENT PROBLEM FORMULATION 199 Figure 4.44 Five-Mile Creek SSO discharge during Figure 4.45 Five-Mile Creek under normal flow  

E-Print Network (OSTI)

for a significant portion of the dry-weather * Color figures follow page 370. #12;200 STORMWATER EFFECTS HANDBOOK-diameter plastic pipes (with coarse screening on the ends) for protection and anchored in the streams. Bags were

Pitt, Robert E.

299

Heterogeneous Correlation Modeling Based on the Wavelet Diagonal Assumption and on the Diffusion Operator  

Science Conference Proceedings (OSTI)

This article discusses several models for background error correlation matrices using the wavelet diagonal assumption and the diffusion operator. The most general properties of filtering local correlation functions, with wavelet formulations, are ...

Olivier Pannekoucke

2009-09-01T23:59:59.000Z

300

Microwave Properties of Ice-Phase Hydrometeors for Radar and Radiometers: Sensitivity to Model Assumptions  

Science Conference Proceedings (OSTI)

A simplified framework is presented for assessing the qualitative sensitivities of computed microwave properties, satellite brightness temperatures, and radar reflectivities to assumptions concerning the physical properties of ice-phase ...

Benjamin T. Johnson; Grant W. Petty; Gail Skofronick-Jackson

2012-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "technology assumptions figure" 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

NGNP: High Temperature Gas-Cooled Reactor Key Definitions, Plant Capabilities, and Assumptions  

SciTech Connect

This document provides key definitions, plant capabilities, and inputs and assumptions related to the Next Generation Nuclear Plant to be used in ongoing efforts related to the licensing and deployment of a high temperature gas-cooled reactor. These definitions, capabilities, and assumptions were extracted from a number of NGNP Project sources such as licensing related white papers, previously issued requirement documents, and preapplication interactions with the Nuclear Regulatory Commission (NRC).

Wayne Moe

2013-05-01T23:59:59.000Z

302

Figure 1.8 Motor Vehicle Fuel Economy, 1973-2011 (Miles per Gallon)  

U.S. Energy Information Administration (EIA)

Figure 1.8 Motor Vehicle Fuel Economy, 1973-2011 (Miles per Gallon) U.S. Energy Information Administration / Monthly Energy Review August 2013 17

303

Figure 4.16 Offshore Wind Resources - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Figure 4.16 Offshore Wind Resources U.S. Energy Information Administration / Annual Energy Review 2011 123 Notes: Data are annual average wind speed at 90 meters.

304

Figure SR4. U.S. Natural Gas Import & Export Prices, 2007-2008  

U.S. Energy Information Administration (EIA)

A run-up on natural gas prices began in the spring before a weakened economy drove prices below 2007 levels during the fall and winter. Figure Data:

305

Figure SR1. Flow of Natural Gas Imports and Exports, 2009  

U.S. Energy Information Administration (EIA)

Figure SR1 of the U.S. Natural Gas Imports & Exports: 2009. This report provides an overview of U.S. international natural gas trade in 2009. ...

306

Figure 9.4 Natural Gas Prices (Dollarsa per Thousand Cubic Feet)  

U.S. Energy Information Administration (EIA)

Figure 9.4 Natural Gas Prices (Dollarsa per Thousand Cubic Feet) Wellhead and Citygate, 19492012 Consuming Sectors, 19672012 Consuming Sectors, Monthly

307

Figure 52. Energy use per capita and per dollar of gross ...  

U.S. Energy Information Administration (EIA)

Title: Figure 52. Energy use per capita and per dollar of gross domestic product, 1980-2040 (index, 1980 = 1) Subject: Annual Energy Outlook 2013

308

Figure 9.1 Nuclear Generating Units - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Figure 9.1 Nuclear Generating Units Operable Units,1 1957-2011 Nuclear Net Summer Capacity Change, 1950-2011 Status of All Nuclear Generating Units, ...

309

Figure 2. Stratigraphic Summary of Ages, Names and Rock Types in ...  

U.S. Energy Information Administration (EIA)

Figure 2. Stratigraphic Summary of Ages, Names and Rock Types in the ANWR 1002 and Coastal Plain Area of the Alaska North Slope. Potentially Productive ...

310

Figure 102. U.S. motor gasoline and diesel fuel consumption ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 102. U.S. motor gasoline and diesel fuel consumption, 2000-2040 (million barrels per day) Motor Gasoline Petroleum Portion ...

311

Sensitivity of Utility-Scale Solar Deployment Projections in the SunShot Vision Study to Market and Performance Assumptions  

SciTech Connect

The SunShot Vision Study explored the potential growth of solar markets if solar prices decreased by about 75% from 2010 to 2020. The ReEDS model was used to simulate utility PV and CSP deployment for this present study, based on several market and performance assumptions - electricity demand, natural gas prices, coal retirements, cost and performance of non-solar renewable technologies, PV resource variability, distributed PV deployment, and solar market supply growth - in addition to the SunShot solar price projections. This study finds that utility-scale solar deployment is highly sensitive to solar prices. Other factors can have significant impacts, particularly electricity demand and natural gas prices.

Eurek, K.; Denholm, P.; Margolis, R.; Mowers, M.

2013-04-01T23:59:59.000Z

312

Effect of phonon confinement on the thermoelectric figure of merit of quantum wells  

E-Print Network (OSTI)

Effect of phonon confinement on the thermoelectric figure of merit of quantum wells Alexander in quantum wells and superlattices due to two-dimensional carrier confinement. We predict that the figure of merit can increase even further in quantum well structures with free-surface or rigid boundaries

313

Figure 1:Energy Consumption in USg gy p 1E Roberts, Energy in US  

E-Print Network (OSTI)

: High Voltage DC Charging of fa Nissan Leaf. E Roberts, Energy in US 53 NPC Future Transportation FuelsFigure 1:Energy Consumption in USg gy p 2008 1E Roberts, Energy in US Source: www.eia.gov #12;Figure 2: US Liquid Demand by Sector and Fuel 2E Roberts, Energy in US Source: EIA: Annual Energy Outlook

Sutton, Michael

314

Real-time motion effect enhancement based on fluid dynamics in figure animation  

Science Conference Proceedings (OSTI)

In fast figure animation, motion blur is often employed to generate fantastic effects of figure motion, for exaggerating the atmosphere one wants to convey. In the previous works for long time, the solution based on certain kind of image blending in ... Keywords: GPU geometric processing, fluid dynamics, motion blur, skeletal animation

Tian-Chen Xu; En-Hua Wu; Mo Chen; Ming Xie

2011-12-01T23:59:59.000Z

315

Keywords: Photovoltaic System, fault-tolerance, recon-figurable PV panel  

E-Print Network (OSTI)

1 Keywords: Photovoltaic System, fault-tolerance, recon- figurable PV panel Photovoltaic (PV plants, and satellites. The output power of a PV cell (also called solar cell) is dependent on the solar irradiance level and temperature. Figure 1 shows PV cell output current-voltage and power

Pedram, Massoud

316

Annual Energy Outlook 2001-Appendix G: Major Assumptions for the Forecasts  

Gasoline and Diesel Fuel Update (EIA)

Forecasts Forecasts Summary of the AEO2001 Cases/ Scenarios - Appendix Table G1 bullet1.gif (843 bytes) Model Results (Formats - PDF, ZIP) - Appendix Tables - Reference Case - 1998 to 2020 bullet1.gif (843 bytes) Download Report - Entire AEO2001 (PDF) - AEO2001 by Chapters (PDF) bullet1.gif (843 bytes) Acronyms bullet1.gif (843 bytes) Contacts Related Links bullet1.gif (843 bytes) Assumptions to the AEO2001 bullet1.gif (843 bytes) Supplemental Data to the AEO2001 (Only available on the Web) - Regional and more detailed AEO 2001 Reference Case Results - 1998, 2000 to 2020 bullet1.gif (843 bytes) NEMS Conference bullet1.gif (843 bytes) Forecast Homepage bullet1.gif (843 bytes) EIA Homepage Appendix G Major Assumptions for the Forecasts Component Modules Major Assumptions for the Annual Energy Outlook 2001

317

On the use of the parabolic concentration profile assumption for a rotary desiccant dehumidifier  

SciTech Connect

The current work describes a model for a desiccant dehumidifier which uses a parabolic concentration profile assumption to model the diffusion resistance inside the desiccant particle. The relative merits of the parabolic concentration profile model compared with widely utilized rotary desiccant wheel models are discussed. The periodic steady-state parabolic concentration profile model developed is efficient and can accommodate a variety of materials. These features make it an excellent tool for design studies requiring repetitive desiccant wheel simulations. A quartic concentration profile assumption was also investigated which yielded a 2.8 percent average improvement in prediction error over the parabolic model.

Chant, E.E. [Univ. of Turabo, Gurabo (Puerto Rico); Jeter, S.M. [Georgia Inst. of Technology, Atlanta, GA (United States). George W. Woodruff School of Mechanical Engineering

1995-02-01T23:59:59.000Z

318

Sensitivity of Rooftop PV Projections in the SunShot Vision Study to Market Assumptions  

Science Conference Proceedings (OSTI)

The SunShot Vision Study explored the potential growth of solar markets if solar prices decreased by about 75% from 2010 to 2020. The SolarDS model was used to simulate rooftop PV demand for this study, based on several PV market assumptions--future electricity rates, customer access to financing, and others--in addition to the SunShot PV price projections. This paper finds that modeled PV demand is highly sensitive to several non-price market assumptions, particularly PV financing parameters.

Drury, E.; Denholm, P.; Margolis, R.

2013-01-01T23:59:59.000Z

319

Residential applliance data, assumptions and methodology for end-use forecasting with EPRI-REEPS 2.1  

Science Conference Proceedings (OSTI)

This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the US residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute. In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70% of electricity consumption and 30% of natural gas consumption in the US residential sector. Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific technologies within those end-uses, developing cost data for the various technologies, and specifying decision models to forecast future purchase decisions by households. Our implementation of the REEPS 2.1 modeling framework draws on the extensive technology, cost and market data assembled by LBL for the purpose of analyzing federal energy conservation standards. The resulting residential appliance forecasting model offers a flexible and accurate tool for analyzing the effect of policies at the national level.

Hwang, R.J,; Johnson, F.X.; Brown, R.E.; Hanford, J.W.; Kommey, J.G.

1994-05-01T23:59:59.000Z

320

External review of the thermal energy storage (TES) cogeneration study assumptions. Final report  

DOE Green Energy (OSTI)

This report is to provide a detailed review of the basic assumptions made in the design, sizing, performance, and economic models used in the thermal energy storage (TES)/cogeneration feasibility studies conducted by Pacific Northwest Laboratory (PNL) staff. This report is the deliverable required under the contract.

Lai, B.Y.; Poirier, R.N. [Chicago Bridge and Iron Technical Services Co., Plainfield, IL (United States)

1996-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "technology assumptions figure" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
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321

2011 Vehicle Technologies Market Report  

DOE Green Energy (OSTI)

This report details the major trends in U.S. light-duty vehicle and medium/heavy truck markets as well as the underlying trends that caused them. This report is supported by the U.S. Department of Energy s (DOE) Vehicle Technologies Program (VTP), and, in accord with its mission, pays special attention to the progress of high-efficiency and alternative-fuel technologies. This third edition since this report was started in 2008 offers several marked improvements relative to its predecessors. Most significantly, where earlier editions of this report focused on supplying information through an examination of market drivers, new vehicle trends, and supplier data, this edition uses a different structure. After opening with a discussion of energy and economics, this report features a section each on the light-duty vehicle and heavy/medium truck markets, and concluding with a section each on technology and policy. In addition to making this sectional re-alignment, this year s edition of the report also takes a different approach to communicating information. While previous editions relied heavily on text accompanied by auxiliary figures, this third edition relies primarily on charts and graphs to communicate trends. Any accompanying text serves to introduce the trends communication by the graphic and highlight any particularly salient observations. The opening section on Energy and Economics discusses the role of transportation energy and vehicle markets on a national (and even international) scale. For example, Figures 11 through 13 discuss the connections between global oil prices and U.S. GDP, and Figures 20 and 21 show U.S. employment in the automotive sector. The following section examines Light-Duty Vehicle use, markets, manufacture, and supply chains. Figures 26 through 33 offer snapshots of major light-duty vehicle brands in the U.S. and Figures 38 through 43 examine the performance and efficiency characteristics of vehicles sold. The discussion of Medium and Heavy Trucks offers information on truck sales (Figures 58 through 61) and fuel use (Figures 64 through 66). The Technology section offers information on alternative fuel vehicles and infrastructure (Figures 68 through 77), and the Policy section concludes with information on recent, current, and near-future Federal policies like the Cash for Clunkers program (Figures 87 and 88) and the Corporate Automotive Fuel Economy standard (Figures 90 through 99) and. In total, the information contained in this report is intended to communicate a fairly complete understanding of U.S. highway transportation energy through a series of easily digestible nuggets.

Davis, Stacy Cagle [ORNL; Boundy, Robert Gary [ORNL; Diegel, Susan W [ORNL

2012-02-01T23:59:59.000Z

322

Figure 71. Average fuel economy of new light-duty vehicles, 1980 ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 71. Average fuel economy of new light-duty vehicles, 1980-2040 (miles per gallon, CAFE compliance values) History Reference case

323

Figure 91. Natural gas production by source, 1990-2040 (trillion ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 91. Natural gas production by source, 1990-2040 (trillion cubic feet) Alaska Coalbed Methane Lower 48 Offshore Lower 48 Onshore Conventional

324

Figure 1. Net import share of U.S. liquids supply in two ...  

U.S. Energy Information Administration (EIA)

16.87 2040.00 11.96 18.95 18.08 16.80. Title: Figure 1. Net import share of U.S. liquids supply in two cases, 1970-2040 (percent) Subject: Annual ...

325

Figure 10. Annual change in U.S. wet natural gas proved reserves ...  

U.S. Energy Information Administration (EIA)

Figure 8 Bcf Shale Total Other Shale % Total Proved Reserves Change in Natural Gas Proved Reserves Tcf Natural Gas Proved Reserves shale other 2006.00 14182.00

326

Figure 11. Shale gas proved reserves by selected states, wet after ...  

U.S. Energy Information Administration (EIA)

Figure 11 Shale_History_Summary state Alabama AL Arkansas AR CA Colorado CO Kentucky KY Louisiana LA Michigan MI Montana MT North Dakota ND NM Oklahoma OK Pennsylvania

327

Figure 111. Energy-related carbon dioxide emissions in three cases ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 111. Energy-related carbon dioxide emissions in three cases with three levels of emissions fees, 2000-2040 (million metric tons)

328

Figure 97. Total U.S. tight oil production by geologic formation ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 97. Total U.S. tight oil production by geologic formation, 2011-2040 (million barrels per day) Permian Basin Bakken Eagle Ford

329

Mobility of Ions in Lanthanum Fluoride Nanoclusters---Figure 7 - TMS  

Science Conference Proceedings (OSTI)

... April 1997 edition of JOM-e. a, b. c, d. e, f. g, h. F (bulk) F (surface). La (bulk) La (surface). Figure 7. The MSD as a function of time for several temperatures.

330

Figure 41. U.S. Brent crude oil and Henry Hub natural gas spot ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 41. U.S. Brent crude oil and Henry Hub natural gas spot market prices in three cases, 2005-2040 Natural Gas Crude Oil Reference

331

Figure 98. API gravity of U.S. domestic and imported crude ...  

U.S. Energy Information Administration (EIA)

Title: Figure 98. API gravity of U.S. domestic and imported crude oil supplies, 1990-2040 (degrees) Subject: Annual Energy Outlook 2013 Author: U.S. E ...

332

Figure 8.1 Electricity Overview - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Figure 8.1 Electricity Overview Overview, 2011 Electricity Trade, 1949-2011 Net-Generation-to-End-Use Flow, 2011 (Billion Kilowatthours) 220 U.S. Energy Information ...

333

Figure 72. Vehicle miles traveled per licensed driver, 1970-2040 ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 72. Vehicle miles traveled per licensed driver, 1970-2040 (thousand miles) History Reference case 1970.00 $8.69 1971.00 $9.01

334

Figure 7. U.S. dry natural gas consumption by sector, 2005-2040 ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 7. U.S. dry natural gas consumption by sector, 2005-2040 (trllion cubic feet) Residential Commercial Transportation Gas to liquids

335

Figure 21. Annual average spot price for Brent crude oil in three ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 21. Annual average spot price for Brent crude oil in three cases, 1990-2040 (2011 dollars per barrel) Reference Low Oil Price

336

Figure 87. Ratio of Brent crude oil price to Henry Hub spot ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 87. Ratio of Brent crude oil price to Henry Hub spot natural gas price in energy-equivalent terms, 1990-2040 Ratio Released:April 15, 2013

337

Figure 49. Brent crude oil spot prices in three cases, 1990-2040 ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 49. Brent crude oil spot prices in three cases, 1990-2040 (2011 dollars per barrel) Reference High Oil Price Low Oil Price

338

Figure 3.1 Fossil Fuel Production Prices - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Figure 3.1 Fossil Fuel Production Prices Prices, 1949-2011 Fossil Fuel Composite Price, Change From Previous Year, 1950-2011 68 U.S. Energy Information ...

339

Figure 3.8 Value of Fossil Fuel Exports - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Figure 3.8 Value of Fossil Fuel Exports Total, 1949-2011 By Fuel, 1949-2011 By Fuel, 2011 82 U.S. Energy Information Administration / Annual Energy Review 2011

340

Figure 75. U.S. electricity demand growth, 1950-2040 (percent, 3 ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 75. U.S. electricity demand growth, 1950-2040 (percent, 3-year moving average) Year 3-year moving average Trendline 1950.00

Note: This page contains sample records for the topic "technology assumptions figure" 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

Figure 6.3 Natural Gas Imports, Exports, and Net Imports  

U.S. Energy Information Administration (EIA)

Figure 6.3 Natural Gas Imports, Exports, and Net Imports Trade Overview, 1949-2011 Trade, 2011 Net Imports as Share of Consumption, 1958-2011 182 U.S. ...

342

Figure SR3. U.S. Natural Gas Imports and Exports, 1994-2008  

U.S. Energy Information Administration (EIA)

Figure SR3 of the U.S. Natural Gas Imports & Exports: 2008. This report provides an overview of U.S. international natural gas trade in 2008. Natu ...

343

Figure SR1. Flow of Natural Gas Imports and Exports, 2008  

U.S. Energy Information Administration (EIA)

Figure SR1 of the U.S. Natural Gas Imports & Exports: 2008. ... In 2008 LNG exports went primarily to Japan, after a small amount went to Russia in 2007.

344

Paducah DUF6 Conversion Final EIS - Chapter 4: Environmental Impact Assessment Approach, Assumptions, and Methodology  

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

Paducah DUF Paducah DUF 6 Conversion Final EIS 4 ENVIRONMENTAL IMPACT ASSESSMENT APPROACH, ASSUMPTIONS, AND METHODOLOGY This EIS evaluates potential impacts on human health and the natural environment from building and operating a DUF 6 conversion facility at three alternative locations at the Paducah site and for a no action alternative. These impacts might be positive, in that they would improve conditions in the human or natural environment, or negative, in that they would cause a decline in those conditions. This chapter provides an overview of the methods used to estimate the potential impacts associated with the EIS alternatives, summarizes the major assumptions that formed the basis of the evaluation, and provides some background information on human health

345

NGNP: High Temperature Gas-Cooled Reactor Key Definitions, Plant Capabilities, and Assumptions  

SciTech Connect

This document is intended to provide a Next Generation Nuclear Plant (NGNP) Project tool in which to collect and identify key definitions, plant capabilities, and inputs and assumptions to be used in ongoing efforts related to the licensing and deployment of a high temperature gas-cooled reactor (HTGR). These definitions, capabilities, and assumptions are extracted from a number of sources, including NGNP Project documents such as licensing related white papers [References 1-11] and previously issued requirement documents [References 13-15]. Also included is information agreed upon by the NGNP Regulatory Affairs group's Licensing Working Group and Configuration Council. The NGNP Project approach to licensing an HTGR plant via a combined license (COL) is defined within the referenced white papers and reference [12], and is not duplicated here.

Phillip Mills

2012-02-01T23:59:59.000Z

346

EIA-Assumptions to the Annual Energy Outlook - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2007 International Energy Module The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously derived supply curves, initial price paths and international regional supply and demand levels into NEMS. These quantities are not modeled directly in NEMS because NEMS is not an international model. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2007 with the IEO2006 and the STEO some functionality was removed from the IEM. More analyst time was devoted to analyzing price relationships between marker crude oils and refined products. A new exogenous oil supply model, Generate World Oil Balances (GWOB), was also developed to incorporate actual investment occurring in the international oil market through 2015 and resource assumptions through 2030. The GWOB model provides annual country level oil production detail for eight conventional and unconventional oils.

347

GRI baseline projection: Methodology and assumptions 1996 edition. Topical report, January-December 1995  

Science Conference Proceedings (OSTI)

The report documents the methodology employed in producing the 1996 Edition of the GRI Baseline Projection. DRI/McGraw-Hill`s Energy Group (DRI) maintains an energy modeling system for the Gas Research Institute (GRI) that is used to produce an annual projection of the supply and demand for energy by regions in the United States. The 1996 Edition of the GRI Baseline Projection is produced using several different models. The models analyze various pieces of the U.S. energy markets and their solutions are based on a framework of exogenous assumptions provided by GRI. The report describes the integration and solution procedures of the models and the assumptions used to produce the final projection results.

Rhodes, M.R.; Baxter, R.P.; Nottingham, R.P.

1996-04-01T23:59:59.000Z

348

GRI baseline projection: Methodology and assumptions 1995 edition. Topical report, January-December 1994  

SciTech Connect

The report documents the methodology employed in producing the 1995 Edition of the GRI Baseline Projection. DRI/McGraw-Hill`s Energy Group (DRI) maintains an energy modeling system for the Gas Research Institute (GRI) that is used to produce an annual projection of the supply and demand for energy by regions in the United States. The 1995 Edition of the GRI Baseline Projection is produced using several different models. The models analyze various pieces of the U.S. energy markets and their solutions are based on a framework of exogeneous assumptions provided by GRI. The report describes the integration and solution procedures of the models and the assumptions used to produce the final projection results.

Baxter, R.P.; Silveira, T.S.; Harshbarger, S.L.

1995-02-01T23:59:59.000Z

349

A REVIEW OF ASSUMPTIONS AND ANALYSIS IN EPRI EA-3409,"HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPS BEHAVIORAL MODELS"  

SciTech Connect

This paper revises and extends EPRI report EA-3409, ''Household Appliance Choice: Revision of REEPS Behavioral Models.'' That paper reported the results of an econometric study of major appliance choice in new residential construction. Errors appeared in two tables of that report. We offer revised versions of those tables, and a brief analysis of the consequences and significance of the errors. The present paper also proposes several possible extensions and re-specifications of the models examined by EPRI. Some of these are judged to be highly successful; they both satisfy economic intuition more completely than the original specification and produce a better quality fit to the dependent variable. We feel that inclusion of these modifications produces a more useful set of coefficients for economic modeling than the original specification. This paper focuses on EPRI's models of residential space heating technology choice. That choice was modeled as a nested logit structure, with consumers choosing whether to have central air conditioning or not, and, given that choice, what kind of space heating system to have. The model included five space heating alternatives with central cooling (gas, oil, and electric forced-air; heat pumps; and electric baseboard) and eight alternatives without it (gas, oil, and electric forced-air; gas and oil boilers and non-central systems; and electric baseboard heat). The structure of the nested logit model is shown in Figure 1.

Wood, D.J.; Ruderman, H.; McMahon, J. E.

1989-05-01T23:59:59.000Z

350

Framework for energy policy and technology assessment in developing countries: a case study of Peru  

DOE Green Energy (OSTI)

The potential of various energy sources and technology options in meeting national economic and social development goals in developing countries is assessed. The resource options that are of interest are the development of indigenous resources. In general, two categories of options can be considered: those which correspond to the accelerated implementation of existing elements of the energy system and those which correspond to the introduction of a new technology, such as solar electricity. The various resource and technology options that must be analyzed with respect to a number of criteria or payoff functions are: total demand and fuel mix; reduction of oil consumption; national social goals; total energy costs; and environmental quality. First, a view is constructed of the energy implications of current national economic development plans. A consistent description of the future energy system of the country, under the assumption of current trends and policies is constructed for certain reference years in the future. The values of the payoff functions selected are then calculated for that reference case. The major resource and technology options are identified and the rates at which they can be implemented are determined. Finally, the impact on the various payoff functions of the implementation of each option is calculated. The basic element of the framework is the Reference Energy System, discussed in Secton 3. The energy policy analysis for Peru is used as a reference case. 11 references, 10 figures, 2 tables.

Mubayi, V.; Palmedo, P.F.; Doernberg, A.B.

1979-12-01T23:59:59.000Z

351

EM Leads with Advanced Simulation Capability Technology | Department of  

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

with Advanced Simulation Capability Technology with Advanced Simulation Capability Technology EM Leads with Advanced Simulation Capability Technology April 4, 2013 - 12:00pm Addthis Figure 1: Advanced Simulation Capability for Environmental Management Thrust Areas. Figure 1: Advanced Simulation Capability for Environmental Management Thrust Areas. Figure 2: Spatial distribution of technetium-99 after the releases from the BC cribs using VisIt software on the Hanford Central Plateau. Figure 2: Spatial distribution of technetium-99 after the releases from the BC cribs using VisIt software on the Hanford Central Plateau. Figure 3: Conceptual model of uranium attenuation processes in the Savannah River F Area Seepage Basins plume, including adsorption/desorption (1); dissolution/precipitation (2); mixing/dilution (3); aqueous reactions (4); microbial interactions (5); and abiotic organic interactions (6).

352

Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results  

E-Print Network (OSTI)

A comparison of national energy consumption by fuel typeenergy consumption in homes under differing assumptions, scenarios, and policies. At the national

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

353

Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results  

E-Print Network (OSTI)

G. Koomey. 1994. Residential Appliance Data, Assumptions andunits) Table A 3 : Number of Appliances in Existing Homes (sector, including appliances and heating, ventilation, and

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

354

Technology Transfer: Available Technologies  

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

Materials Biofuels Biofuels Biotechnology and Medecine Biotechnology & Medicine Chemistry Developing World Energy Efficient Technologies Energy Environmental Technologies...

355

Characterization of wind technology progress  

SciTech Connect

US DOE`s Wind Energy Program, NREL, and Sandia periodically re-evaluate the state of wind technology. Since 1995 marked the conclusion of a number of DOE-supported advanced turbine design efforts, and results from the next major round of research are expected near the latter part of the century, this paper discusses future trends for domestic wind farm applications (bulk power), incorporating recent turbine research efforts under different market assumptions from previous DOE estimates. Updated cost/performance projections are presented along with underlying assumptions and discussions of potential alternative wind turbine design paths. Issues on market valuation of wind technology in a restructured electricity market are also discussed.

Cadogan, J B [USDOE, Washington, DC (United States); Parsons, B [National Renewable Energy Lab., Golden, CO (United States); Cohen, J M; Johnson, B L [Princeton Economic Research, Inc., Rockville, MD (United States)

1996-07-01T23:59:59.000Z

356

Finding Six-Figure ROI From Energy Efficiency | Department of Energy  

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

Finding Six-Figure ROI From Energy Efficiency Finding Six-Figure ROI From Energy Efficiency Finding Six-Figure ROI From Energy Efficiency September 28, 2010 - 10:20am Addthis Kevin Craft What are the key facts? Recovery Act funded energy efficiency lighting upgrades in Huntington, New York. Street lighting accounts for 40% of town's electric costs. Huntington estimates $151,000 in annual savings through lighting changes. Return-on-investment -- that is the phrase town officials in Huntington, New York, carefully considered before commissioning several projects to improve municipal energy efficiency. "Saving town residents money on energy bills is one way to help stimulate the local economy. So we looked for projects that would save our residents as much money as possible," said Huntington Supervisor Frank Petrone.

357

Finding Six-Figure ROI From Energy Efficiency | Department of Energy  

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

Finding Six-Figure ROI From Energy Efficiency Finding Six-Figure ROI From Energy Efficiency Finding Six-Figure ROI From Energy Efficiency September 28, 2010 - 10:20am Addthis Kevin Craft What are the key facts? Recovery Act funded energy efficiency lighting upgrades in Huntington, New York. Street lighting accounts for 40% of town's electric costs. Huntington estimates $151,000 in annual savings through lighting changes. Return-on-investment -- that is the phrase town officials in Huntington, New York, carefully considered before commissioning several projects to improve municipal energy efficiency. "Saving town residents money on energy bills is one way to help stimulate the local economy. So we looked for projects that would save our residents as much money as possible," said Huntington Supervisor Frank Petrone.

358

Bases, Assumptions, and Results of the Flowsheet Calculations for the Decision Phase Salt Disposition Alternatives  

SciTech Connect

The High Level Waste (HLW) Salt Disposition Systems Engineering Team was formed on March 13, 1998, and chartered to identify options, evaluate alternatives, and recommend a selected alternative(s) for processing HLW salt to a permitted wasteform. This requirement arises because the existing In-Tank Precipitation process at the Savannah River Site, as currently configured, cannot simultaneously meet the HLW production and Authorization Basis safety requirements. This engineering study was performed in four phases. This document provides the technical bases, assumptions, and results of this engineering study.

Dimenna, R.A.; Jacobs, R.A.; Taylor, G.A.; Durate, O.E.; Paul, P.K.; Elder, H.H.; Pike, J.A.; Fowler, J.R.; Rutland, P.L.; Gregory, M.V.; Smith III, F.G.; Hang, T.; Subosits, S.G.; Campbell, S.G.

2001-03-26T23:59:59.000Z

359

Science with the Square Kilometer Array: Motivation, Key Science Projects, Standards and Assumptions  

E-Print Network (OSTI)

The Square Kilometer Array (SKA) represents the next major, and natural, step in radio astronomical facilities, providing two orders of magnitude increase in collecting area over existing telescopes. In a series of meetings, starting in Groningen, the Netherlands (August 2002) and culminating in a `science retreat' in Leiden (November 2003), the SKA International Science Advisory Committee (ISAC), conceived of, and carried-out, a complete revision of the SKA science case (to appear in New Astronomy Reviews). This preface includes: (i) general introductory material, (ii) summaries of the key science programs, and (iii) a detailed listing of standards and assumptions used in the revised science case.

C. Carilli; S. Rawlings

2004-09-12T23:59:59.000Z

360

New connections for new technologies  

SciTech Connect

New energy technologies are fast converging on utility electricity networks, but these networks are designed for alternating current (ac) power from large central power plants. Research is needed in direct current (dc)-to-ac power conditioning, appropriate generation planning, revised operation and control strategies, and institutional issues before technologies, such as fuel cells, storage batteries, photovoltaic arrays, and wind turbines can produce electricity for customers. 6 figures.

Lihach, N.; Ferraro, R.

1982-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "technology assumptions figure" 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

Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

LBL-34046 UC-350 Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting. DE-AC03-76SF00098 #12;i ABSTRACT This report details the data, assumptions and methodology for end-use provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which

362

EIA - Assumptions to the Annual Energy Outlook 2008 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2008 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2008, DOE/EIA-M060(2008) (Washington, DC, 2008). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the projection. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

363

EIA-Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2007 Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2007, DOE/EIA-M060(2007) (Washington, DC, 2007). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

364

Assumptions to the Annual Energy Outlook 2001 - Table 3. Coal-Related  

Gasoline and Diesel Fuel Update (EIA)

Coal-Related Methane Assumptions Coal-Related Methane Assumptions Northern Appalachia Central Appalachia Southern Appalachia Eastern Interior Western Fraction of underground coal production at: Gassy mines 0.885 0.368 0.971 0.876 0.681 Nongassy mines 0.115 0.632 0.029 0.124 0.319 Production from mines with degasification systems (fraction of underground production) 0.541 0.074 0.810 0.067 0.056 Emission factors (kilograms methane per short ton of coal produced) Underground Mining Gassy mines 6.047 5.641 27.346 2.988 6.027 Nongassy mines 0.362 0.076 15.959 0.285 0.245 Degassified mines 4.085 37.724 22.025 0.310 0.000 Surface Mining 0.706 0.706 0.706 0.706 0.706 Post-Mining, underground-mined 1.505 1.505 1.505 1.505 1.505 Post-Mining, surface-mined 0.061 0.061 0.061 0.061 0.061 Methane recovery at active coal mines

365

EIA - Assumptions to the Annual Energy Outlook 2010 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2010 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2010, DOE/EIA-M060(2010) (Washington, DC, 2010). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the projection. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, the cost of factor inputs (labor and fuel), and other mine supply costs.

366

Analysis of the Effects of Compositional and Configurational Assumptions on Product Costs for the Thermochemical Conversion of Lignocellulosic Biomass to Mixed Alcohols FY 2007 Progress Report  

DOE Green Energy (OSTI)

The purpose of this study was to examine alternative biomass-to-ethanol conversion process assumptions and configuration options to determine their relative effects on overall process economics. A process-flow-sheet computer model was used to determine the heat and material balance for each configuration that was studied. The heat and material balance was then fed to a costing spreadsheet to determine the impact on the ethanol selling price. By examining a number of operational and configuration alternatives and comparing the results to the base flow sheet, alternatives having the greatest impact the performance and cost of the overall system were identified and used to make decisions on research priorities. This report, which was originally published in December 2008, has been revised primarily to correct information presented in Appendix B -- Base Case Flow Sheets and Model Results. The corrections to Appendix B include replacement of several pages in Table B.1 that duplicated previous pages of the table. Other changes were made in Appendix B to correct inconsistencies between stream labels presented in the tables and the stream labels in the figures.

Zhu, Yunhua; Gerber, Mark A.; Jones, Susanne B.; Stevens, Don J.

2009-02-01T23:59:59.000Z

367

Sixth Northwest Conservation and Electric Power Plan Chapter 4: Conservation Supply Assumptions  

E-Print Network (OSTI)

-thirds of commercial savings are in lighting systems. New technologies like light-emitting diodes and improved lighting, recent advances in solid- state lighting--light-emitting diodes (LED) and organic light-emitting diodes. The availability of new lights such as light-emitting diodes (LED) and improved emerging technologies

368

Experimental Setup Measurements were made with the experimental configuration depicted in Figure 1. Tissue  

E-Print Network (OSTI)

depicted in Figure 1. Tissue samples were heated in an insulated tank that was filled with deionized water, which had been degassed by vacuum pumping in an appropriate vessel. Tissue was placed with a MetroTek pulser and echoes recorded. The transducer was moved to the next site of interest and a new

Arthur, R. Martin

369

AMS Copyright Notice Copyright 2010 American Meteorological Society (AMS). Permission to use figures,  

E-Print Network (OSTI)

-state vertical wind shear. The present work addresses a related assertion, that squall-line intensity ought, long-lived squall lines'' (often called ``RKW theory'') represented a paradigm shift. Although a number figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted

Parker, Matthew D. Brown

370

AMS Copyright Notice Copyright 2004 American Meteorological Society (AMS). Permission to use figures,  

E-Print Network (OSTI)

with inflow passing through their line-leading precipitation can be stable and long lived. Lower figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair

Parker, Matthew D. Brown

371

Data Sources for Figures ER2006-0227 C-1 April 2006  

E-Print Network (OSTI)

Appendix C Data Sources for Figures #12;#12;ER2006-0227 C-1 April 2006 Feature Data Source Laboratory, ENV­Environmental Remediation & Surveillance Program, ER2005-0496; 1:2,500 Scale Data; 22 Sept:2,500 Scale Data; 10 March 2006. Canyon Rim, Location of the, Townsite South Rim in 1991; in "Line Features

372

Thermoelectric figure of merit for bulk nanostructured composites with distributed parameters  

Science Conference Proceedings (OSTI)

The effective properties of composites whose structure includes nanocontacts between bulk-phase macrocrystallites are considered. A model for such a nanostructured composite is constructed. Effective values of the thermoelectric power, thermal and electrical conductivities, and thermoelectric figure of merit are calculated in the mean-field approximation.

Snarskii, A. A. [National Technical University 'Kyiv Polytechnic Institute' (Ukraine); Sarychev, A. K. [Russian Academy of Sciences, Institute for Theoretical and Applied Electromagnetics (Russian Federation); Bezsudnov, I. V., E-mail: biv@akuan.ru ['Nauka-Service' Scientific and Production Company (Russian Federation); Lagarkov, A. N. [Russian Academy of Sciences, Institute for Theoretical and Applied Electromagnetics (Russian Federation)

2012-05-15T23:59:59.000Z

373

NEC's Itanium prototype server (see Figure 1), code-named AzusA after a river  

E-Print Network (OSTI)

aimed at reliability, availability, and serviceability. These features include cell hot- plug capability 200 ns for a local memory access or local CPU cache hit, and less than 300 ns for a remote (other cell. Availability As in PCI cards, a cell in a partitioned con- figuration can be hot swapped while other domains

Skadron, Kevin

374

EIA-Assumptions to the Annual Energy Outlook - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2007 Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

375

Washington International Renewable Energy Conference 2008 Pledges: Methodology and Assumptions Summary  

Science Conference Proceedings (OSTI)

The 2008 Washington International Renewable Energy Conference (WIREC) was held in Washington, D.C., from March 4-6, 2008, and involved nearly 9,000 people from 125 countries. The event brought together worldwide leaders in renewable energy (RE) from governments, international organizations, nongovernmental organizations, and the private sector to discuss the role that renewables can play in alleviating poverty, growing economies, and passing on a healthy planet to future generations. The conference concluded with more than 140 governments, international organizations, and private-sector representatives pledging to advance the uptake of renewable energy. The U.S. government authorized the National Renewable Energy Laboratory (NREL) to estimate the carbon dioxide (CO2) savings that would result from the pledges made at the 2008 conference. This report describes the methodology and assumptions used by NREL in quantifying the potential CO2 reductions derived from those pledges.

Babiuch, B.; Bilello, D. E.; Cowlin, S. C.; Mann, M.; Wise, A.

2008-08-01T23:59:59.000Z

376

CRITICAL ASSUMPTIONS IN THE F-TANK FARM CLOSURE OPERATIONAL DOCUMENTATION REGARDING WASTE TANK INTERNAL CONFIGURATIONS  

SciTech Connect

The intent of this document is to provide clarification of critical assumptions regarding the internal configurations of liquid waste tanks at operational closure, with respect to F-Tank Farm (FTF) closure documentation. For the purposes of this document, FTF closure documentation includes: (1) Performance Assessment for the F-Tank Farm at the Savannah River Site (hereafter referred to as the FTF PA) (SRS-REG-2007-00002), (2) Basis for Section 3116 Determination for Closure of F-Tank Farm at the Savannah River Site (DOE/SRS-WD-2012-001), (3) Tier 1 Closure Plan for the F-Area Waste Tank Systems at the Savannah River Site (SRR-CWDA-2010-00147), (4) F-Tank Farm Tanks 18 and 19 DOE Manual 435.1-1 Tier 2 Closure Plan Savannah River Site (SRR-CWDA-2011-00015), (5) Industrial Wastewater Closure Module for the Liquid Waste Tanks 18 and 19 (SRRCWDA-2010-00003), and (6) Tank 18/Tank 19 Special Analysis for the Performance Assessment for the F-Tank Farm at the Savannah River Site (hereafter referred to as the Tank 18/Tank 19 Special Analysis) (SRR-CWDA-2010-00124). Note that the first three FTF closure documents listed apply to the entire FTF, whereas the last three FTF closure documents listed are specific to Tanks 18 and 19. These two waste tanks are expected to be the first two tanks to be grouted and operationally closed under the current suite of FTF closure documents and many of the assumptions and approaches that apply to these two tanks are also applicable to the other FTF waste tanks and operational closure processes.

Hommel, S.; Fountain, D.

2012-03-28T23:59:59.000Z

377

ENGINEERING TECHNOLOGY Engineering Technology  

E-Print Network (OSTI)

, Mechatronics Technology, and Renewable Energy Technology. Career Opportunities Graduates of four origin, gender, age, marital status, sexual orientation, status as a Vietnam-era veteran, or disability

378

Technology Transfer: Available Technologies  

Please refer to the list of technologies below for licensing and research collaboration availability. If you can't find the technology you ...

379

Computer modeling and experimental verification of figure-eight-shaped null-flux coil suspension system  

DOE Green Energy (OSTI)

This report discusses the computer modeling and experimental verification of the magnetic forces associated with a figure-eight-shaped null-flux coil suspension system. A set of computer codes called COILGDWY, were developed on the basis of the dynamic circuit model and verified by means of a laboratory model. The experimental verification was conducted with a rotating PVC drum, the surface of which held various types of figure-eight-shaped null-flux coils that interacted with a stationary permanent magnet. The transient and dynamic magnetic forces between the stationary magnet and the rotating conducting coils were measured and compared with results obtained from the computer model. Good agreement between the experimental results and computer simulations was obtained. The computer model can also be used to calculate magnetic forces in a large-scale magnetic-levitation system.

He, J.L.; Mulcahey, T.M.; Rote, D.M.; Kelly, T.

1994-12-01T23:59:59.000Z

380

Figure A1. Natural gas processing plant capacity in the United States, 2013 2012  

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

5 5 Figure A1. Natural gas processing plant capacity in the United States, 2013 2012 Table A2. Natural gas processing plant capacity, by state, 2013 (million cubic feet per day) Alabama 1,403 Arkansas 24 California 926 Colorado 5,450 Florida 90 Illinois 2,100 Kansas 1,818 Kentucky 240 Louisiana 10,737 Michigan 479 Mississippi 1,123

Note: This page contains sample records for the topic "technology assumptions figure" from the National Library of EnergyBeta (NLEBeta).
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they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

50-year-old assumptions about strength muscled aside | Argonne National  

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

C. David Williams with an X-ray diffraction apparatus used to measure lattice spacing of filaments in moth wing muscle samples. To view a larger version of the image, click on it. Credit: A. Kidder/University of Washington. C. David Williams with an X-ray diffraction apparatus used to measure lattice spacing of filaments in moth wing muscle samples. To view a larger version of the image, click on it. Credit: A. Kidder/University of Washington. C. David Williams with an X-ray diffraction apparatus used to measure lattice spacing of filaments in moth wing muscle samples. To view a larger version of the image, click on it. Credit: A. Kidder/University of Washington. To view a larger, downloadable version of the image, click on it. To view a larger, downloadable version of the image, click on it. 50-year-old assumptions about strength muscled aside July 11, 2013 Tweet EmailPrint LEMONT, Ill. - Doctors have a new way of thinking about how to treat heart and skeletal muscle diseases. Body builders have a new way of

382

Standard assumptions and methods for solar heating and cooling systems analysis  

DOE Green Energy (OSTI)

A set of inputs, assumptions, analytical methods, and a reporting format is presented to help compare the results of residential and commercial solar system analyses being performed by different investigators. By the common use of load data, meteorological data, economic parameters, and reporting format, researchers examining, for example, two types of collectors may more easily compare their results. For residential heating and cooling systems, three locations were selected. The weather data chosen to characterize these cities are the Typical Meteorological Year (TMY). A house for each location was defined that is typical of new construction in that locale. Hourly loads for each location were calculated using a computerized load model that interacts with the system specified inputs characterizing each house. Four locations for commercial cooling analyses were selected from among the existing sites for which TMYs were available. A light commercial (nominal 25-ton cooling load) office building was defined and is used in all four locations. Hourly cooling and heating loads were computed for each city and are available on magnetic tape from the Solar Energy Research Insititute (SERI).

Leboeuf, C.M.

1980-01-01T23:59:59.000Z

383

Advanced solar thermal technology  

SciTech Connect

The application of dish solar collectors to industrial process heat (IPH) has been reviewed. IPH represents a market for displacement of fossil fuels (10 quads/y). A 10% market penetration would indicate a substantial market for solar thermal systems. Apparently, parabolic dish systems can produce IPH at a lower cost than that of troughs or compound parabolic concentrators, even though dish fabrication costs per unit area are more expensive. Successful tests of point-focusing collectors indicate that these systems can meet the energy requirements for process heat applications. Continued efforts in concentrator and transport technology development are needed. 7 figures.

Leibowitz, L.P.; Hanseth, E.; Liu, T.M.

1982-06-01T23:59:59.000Z

384

Technology Search  

home \\ technologies \\ search. Technologies: Ready-to-Sign Licenses: Software: Patents: Technology Search. ... Operated by Lawrence Livermore National Security, LLC, ...

385

Building Technologies Office: Emerging Technologies  

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

Emerging Technologies Emerging Technologies Printable Version Share this resource Send a link to Building Technologies Office: Emerging Technologies to someone by E-mail Share Building Technologies Office: Emerging Technologies on Facebook Tweet about Building Technologies Office: Emerging Technologies on Twitter Bookmark Building Technologies Office: Emerging Technologies on Google Bookmark Building Technologies Office: Emerging Technologies on Delicious Rank Building Technologies Office: Emerging Technologies on Digg Find More places to share Building Technologies Office: Emerging Technologies on AddThis.com... About Take Action to Save Energy Partner with DOE Activities Technology Research, Standards, & Codes Popular Links Success Stories Previous Next Lighten Energy Loads with System Design.

386

Nuclear Detection Figure Of Merit (NDFOM) Version 1.2 User's Guide  

SciTech Connect

NDFOM is a detector database and detector evaluation system, accessible as a web service. It runs on the same server as the Patriot service, but uses port 8081. In this user's guide, we will use the example case that the patriot service is running on http://patriot.lanl.gov. Then the NDFOM service would be accessible at the URL http://patriot.lanl.gov:8081/ndfom. In addition to local server installations, common server locations are 1) a patriot server running on a virtual machine (use the virtual machine URL with :8081/ndfom), and 2) a patriot server running on a local machine (use http://localhost:8081/ndfom or http://127.0.0.1:8081/ndfom). The home screen provides panels to select detectors, a scenario, and a figure-of-merit. It also has an 'analyze' button, which will evaluate the selected figure-of-merit for the selected detectors, for the scenario selected by the user. The detector effectiveness evaluations are presented through the browser in a ranked list of detectors. The user does not need to log in to perform analysis with pre-supplied detectors, scenarios, and FOMs. The homepage view is shown in Figure 1. The first panel displays a list of the detectors in the current detector database. The user can select one, some, or all detectors to evaluate. On the right of each listed detector, there is a star icon. Clicking that icon will open a panel that displays the details about that detector, such as detector material, dimensions, thresholds, etc. The center panel displays the pre-supplied scenarios that are in the database. A scenario specifies the source of interest, the spectrum of the radiation, the background radiation spectrum, the distance or distance of closest approach, the allowable false positive rate, and the dwell time or speed. Scenario details can be obtained by clicking the star to the right of a scenario. A scenario can be selected by clicking it.

Stroud, Phillip D [Los Alamos National Laboratory; Dufresne, Thomas A. [Los Alamos National Laboratory

2012-08-27T23:59:59.000Z

387

Technology Capabilities  

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

Homeland Security & Defense Homeland Security & Defense Information Technology & Communications Information Technology & Communications Sensors, Electronics &...

388

The London Accord 1 Dynamics of technological development in the energy sector  

E-Print Network (OSTI)

of the initial installation, to technologies such as coal or natural gas fired power plants, where 2010 0 1 2 3 4 5 6 7 8 Coal Natural gas $/GJ Year Figure 9. Cost of coal and natural gas in the U a significant effect on the cost of coal-based electricity. Figure 9 also shows the cost of natural gas, which

389

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

LBL-34045 UC-1600 Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting-uses include Heating, Ventilation and Air Conditioning (HVAC). Our analysis uses the modeling framework provided by the HVAC module in the Residential End-Use Energy Planning System (REEPS), which was developed

390

Preliminary Review of Models, Assumptions, and Key Data used in Performance Assessments and Composite Analysis at the Idaho National Laboratory  

SciTech Connect

This document is in response to a request by Ming Zhu, DOE-EM to provide a preliminary review of existing models and data used in completed or soon to be completed Performance Assessments and Composite Analyses (PA/CA) documents, to identify codes, methodologies, main assumptions, and key data sets used.

Arthur S. Rood; Swen O. Magnuson

2009-07-01T23:59:59.000Z

391

A Graphical Approach to Diagnosing the Validity of the Conditional Independence Assumptions of a Bayesian Network Given Data  

SciTech Connect

Bayesian networks have attained widespread use in data analysis and decision making. Well studied topics include: efficient inference, evidence propagation, parameter learning from data for complete and incomplete data scenarios, expert elicitation for calibrating Bayesian network probabilities, and structure learning. It is not uncommon for the researcher to assume the structure of the Bayesian network or to glean the structure from expert elicitation or domain knowledge. In this scenario, the model may be calibrated through learning the parameters from relevant data. There is a lack of work on model diagnostics for fitted Bayesian networks; this is the contribution of this paper. We key on the definition of (conditional) independence to develop a graphical diagnostic method which indicates if the conditional independence assumptions imposed when one assumes the structure of the Bayesian network are supported by the data. We develop the approach theoretically and describe a Monte Carlo method to generate uncertainty measures for the consistency of the data with conditional independence assumptions under the model structure. We describe how this theoretical information and the data are presented in a graphical diagnostic tool. We demonstrate the approach through data simulated from Bayesian networks under different conditional independence assumptions. We also apply the diagnostic to a real world data set. The results indicate that our approach is a reasonable way of visualizing and inspecting the conditional independence assumption of a Bayesian network given data.

Walsh, Stephen J.; Whitney, Paul D.

2012-12-14T23:59:59.000Z

392

MODELING ASSUMPTIONS FOR THE ADVANCED TEST REACTOR FRESH FUEL SHIPPING CONTAINER  

SciTech Connect

The Advanced Test Reactor Fresh Fuel Shipping Container (ATR FFSC) is currently licensed per 10 CFR 71 to transport a fresh fuel element for either the Advanced Test Reactor, the University of Missouri Research Reactor (MURR), or the Massachusetts Institute of Technology Research Reactor (MITR-II). During the licensing process, the Nuclear Regulatory Commission (NRC) raised a number of issues relating to the criticality analysis, namely (1) lack of a tolerance study on the fuel and packaging, (2) moderation conditions during normal conditions of transport (NCT), (3) treatment of minor hydrogenous packaging materials, and (4) treatment of potential fuel damage under hypothetical accident conditions (HAC). These concerns were adequately addressed by modifying the criticality analysis. A tolerance study was added for both the packaging and fuel elements, full-moderation was included in the NCT models, minor hydrogenous packaging materials were included, and fuel element damage was considered for the MURR and MITR-II fuel types.

Rick J. Migliore

2009-09-01T23:59:59.000Z

393

Assessment of Gasification-Based Biorefining at Kraft Pulp and Paper Mills in the United States, Part A: Background and Assumptions  

Science Conference Proceedings (OSTI)

Commercialization of black liquor and biomass gasification technologies is anticipated in the 2010-2015 time frame, and synthesis gas from gasifiers can be converted into liquid fuels using catalytic synthesis technologies that are already commercially established in the gas-to-liquids or coal-to-liquids industries. This set of two papers describes key results from a major assessment of the prospective energy, environmental, and financial performance of commercial gasification-based biorefineries integrated with kraft pulp and paper mills [1]. Seven detailed biorefinery designs were developed for a reference mill in the southeastern United States, together with the associated mass/energy balances, air emissions estimates, and capital investment requirements. The biorefineries provide chemical recovery services and co-produce process steam for the mill, some electricity, and one of three liquid fuels: a Fischer-Tropsch synthetic crude oil (which could be refined to vehicle fuels at an existing petroleum refinery), dimethyl ether (a diesel engine fuel or propane substitute), or an ethanol-rich mixed-alcohol product. This paper describes the key assumptions that underlie the biorefinery designs. Part B will present analytical results.

Larson, E. D.; Consonni, S.; Katofsky, R. E.; Iisa, K.; Frederick, W. J., Jr.

2008-11-01T23:59:59.000Z

394

Thermoelectric figure of merit of Ag{sub 2}Se with Ag and Se excess  

Science Conference Proceedings (OSTI)

In the temperature range of 100-300 K, the electric ({sigma}) and thermoelectric ({alpha}{sub 0}) properties of Ag{sub 2}Se with an excess of Ag as high as {approx}0.1 at. % and Se as high as {approx}1.0 at. %, respectively, are investigated. From the data on {sigma}, {alpha}{sub 0}, and {chi}{sub tot} (thermal conductivities), the thermoelectric power {alpha}{sub 0}{sup 2}{sigma} and the figure of merit Z are calculated. It is found that {alpha}{sub 0}{sup 2}{sigma} and Z attain the peak values at room temperature and the electron concentration n {approx} 6.5 x 10{sup 18} cm{sup -3}.

Aliev, F. F., E-mail: farzali@physics.ab.az; Jafarov, M. B.; Eminova, V. I. [Azerbaijan National Academy of Sciences, Institute of Physics (Azerbaijan)

2009-08-15T23:59:59.000Z

395

Portugal Egypt Figure 2. Natural gas supply and disposition in the United States, 2012  

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

Portugal Egypt Figure 2. Natural gas supply and disposition in the United States, 2012 (trillion cubic feet) Natural Gas Plant Liquids Production Gross Withdrawals From Gas and Oil Wells Nonhydrocarbon Gases Removed Vented/Flared Reservoir Repressuring Production Dry Gas Imports Canada Trinidad/Tobago Natural Gas Storage Facilities Exports Japan Canada Mexico Additions Withdrawals Gas Industry Use Residential Commercial Industrial Vehicle Fuel Electric Power 29.5 0.8 0.2 3.3 2.963 0.112 0.620 0.971 0.014 24.1 1.3 2.9 2.8 2.5 2.9 7.2 0.03 9.1 0.003 Sources: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition"; Form EIA-895, "Annual Quantity and

396

PHENIX (Pioneering High Energy Nuclear Interaction eXperiment): Data Tables and Figures from Published Papers  

DOE Data Explorer (OSTI)

The PHENIX Experiment is the largest of the four experiments currently taking data at the Relativistic Heavy Ion Collider. PHENIX, the Pioneering High Energy Nuclear Interaction eXperiment, is an exploratory experiment for the investigation of high energy collisions of heavy ions and protons. PHENIX is designed specifically to measure direct probes of the collisions such as electrons, muons, and photons. The primary goal of PHENIX is to discover and study a new state of matter called the Quark-Gluon Plasma. More than 60 published papers and preprints are listed here with links to the full text and separate links to the supporting PHENIX data in plain text tables and to EPS and GIF figures from the papers.

397

Flawed Assumptions, Models and Decision Making: Misconceptions Concerning Human Elements in Complex System  

SciTech Connect

The history of high consequence accidents is rich with events wherein the actions, or inaction, of humans was critical to the sequence of events preceding the accident. Moreover, it has been reported that human error may contribute to 80% of accidents, if not more (dougherty and Fragola, 1988). Within the safety community, this reality is widely recognized and there is a substantially greater awareness of the human contribution to system safety today than has ever existed in the past. Despite these facts, and some measurable reduction in accident rates, when accidents do occur, there is a common lament. No matter how hard we try, we continue to have accidents. Accompanying this lament, there is often bewilderment expressed in statements such as, ''There's no explanation for why he/she did what they did''. It is believed that these statements are a symptom of inadequacies in how they think about humans and their role within technological systems. In particular, while there has never been a greater awareness of human factors, conceptual models of human involvement in engineered systems are often incomplete and in some cases, inaccurate.

FORSYTHE,JAMES C.; WENNER,CAREN A.

1999-11-03T23:59:59.000Z

398

Vendor / Technology  

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

Brake Assessment Tools Commercial Motor Vehicle Roadside Technology Corridor Safety Technology Showcase October 14, 2010 Commercial Motor Vehicle Roadside Technology Corridor...

399

Vendor / Technology  

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

Brake-Related Research Commercial Motor Vehicle Roadside Technology Corridor Safety Technology Showcase October 14, 2010 Commercial Motor Vehicle Roadside Technology Corridor...

400

Faience Technology  

E-Print Network (OSTI)

by Joanne Hodges. Faience Technology, Nicholson, UEE 2009Egyptian materials and technology, ed. Paul T. Nicholson,Nicholson, 2009, Faience Technology. UEE. Full Citation:

Nicholson, Paul

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "technology assumptions figure" 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

Technology Search Results | Brookhaven Technology ...  

There are no technology records available that match the search query. Find a Technology. Search our technologies by categories or by keywords.

402

Technology Transfer: Available Technologies  

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

test test Please refer to the list of technologies below for licensing and research collaboration availability. If you can't find the technology you're interested in, please contact us at TTD@lbl.gov. Energy ENERGY EFFICIENT TECHNOLOGIES Aerosol Sealing Aerosol Remote Sealing System Clog-free Atomizing and Spray Drying Nozzle Air-stable Nanomaterials for Efficient OLEDs Solvent Processed Nanotube Composites OLEDS with Air-stable Structured Electrodes APIs for Online Energy Saving Tools: Home Energy Saver and EnergyIQ Carbon Dioxide Capture at a Reduced Cost Dynamic Solar Glare Blocking System Electrochromic Device Controlled by Sunlight Electrochromic Windows with Multiple-Cavity Optical Bandpass Filter Electrochromic Window Technology Portfolio Universal Electrochromic Smart Window Coating

403

Technology Search Results | Brookhaven Technology ...  

Staff Directory; BNL People Technology Commercialization & Partnerships. Home; For BNL Inventors; ... a nonprofit applied science and technology organization. ...

404

Technology Search Results | Brookhaven Technology ...  

Non-Noble Metal Water Electrolysis Catalysts; Find a Technology. Search our technologies by categories or by keywords. Search ...

405

Technology Search Results | Brookhaven Technology ...  

BSA 08-04: High Temperature Interfacial Superconductivity; Find a Technology. Search our technologies by categories or by keywords. Search ...

406

Technology Search Results | Brookhaven Technology ...  

Receive Technology Updates. Get email notifications about new or improved technologies in your area of interest. Subscribe

407

Technology Transfer: Available Technologies  

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

Please refer to the list of technologies below for licensing and research Please refer to the list of technologies below for licensing and research collaboration availability. If you can't find the technology you're interested in, please contact us at TTD@lbl.gov. Biotechnology and Medicine DIAGNOSTICS AND THERAPEUTICS CANCER CANCER PROGNOSTICS 14-3-3 Sigma as a Biomarker of Basal Breast Cancer ANXA9: A Therapeutic Target and Predictive Marker for Early Detection of Aggressive Breast Cancer Biomarkers for Predicting Breast Cancer Patient Response to PARP Inhibitors Breast Cancer Recurrence Risk Analysis Using Selected Gene Expression Comprehensive Prognostic Markers and Therapeutic Targets for Drug-Resistant Breast Cancers Diagnostic Test to Personalize Therapy Using Platinum-based Anticancer Drugs Early Detection of Metastatic Cancer Progenitor Cells

408

Technology Transfer: Available Technologies  

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

Software and Information Technologies Software and Information Technologies Algorithm for Correcting Detector Nonlinearites Chatelet: More Accurate Modeling for Oil, Gas or Geothermal Well Production Collective Memory Transfers for Multi-Core Processors Energy Efficiency Software EnergyPlus:Energy Simulation Software for Buildings Tools, Guides and Software to Support the Design and Operation of Energy Efficient Buildings Flexible Bandwidth Reservations for Data Transfer Genomic and Proteomic Software LABELIT - Software for Macromolecular Diffraction Data Processing PHENIX - Software for Computational Crystallography Vista/AVID: Visualization and Allignment Software for Comparative Genomics Geophysical Software Accurate Identification, Imaging, and Monitoring of Fluid Saturated Underground Reservoirs

409

LBL-34046 UC-350 Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the U.S. residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute (McMenamin et al. 1992). In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70 % of electricity consumption and 30 % of natural gas consumption in the U.S. residential sector (EIA 1993). Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific

J. Hwang; Francis X. Johnson; Richard E. Brown; James W. Hanford; Jonathan G. Koomey

1994-01-01T23:59:59.000Z

410

Cost estimate guidelines for advanced nuclear power technologies  

SciTech Connect

To make comparative assessments of competing technologies, consistent ground rules must be applied when developing cost estimates. This document provides a uniform set of assumptions, ground rules, and requirements that can be used in developing cost estimates for advanced nuclear power technologies. 10 refs., 8 figs., 32 tabs.

Delene, J.G.; Hudson, C.R. II.

1990-03-01T23:59:59.000Z

411

Residential/commercial market for energy technologies  

SciTech Connect

The residential/commercial market sector, particularly as it relates to energy technologies, is described. Buildings account for about 25% of the total energy consumed in the US. Market response to energy technologies is influenced by several considerations. Some considerations discussed are: industry characteristics; market sectors; energy-consumption characeristics; industry forecasts; and market influences. Market acceptance may be slow or nonexistent, the technology may have little impact on energy consumption, and redesign or modification may be necessary to overcome belatedly perceived market barriers. 7 figures, 20 tables.

Glesk, M.M.

1979-08-01T23:59:59.000Z

412

2011 Fuel Cell Technologies Market Report  

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

2011 FUEL CELL 2011 FUEL CELL TECHNOLOGIES MARKET REPORT ii Authors This report was a collaborative effort by staff of the Breakthrough Technologies Institute, Inc., in Washington, DC. Acknowledgement The authors relied upon the hard work and valuable contributions of many men and women in government and in the fuel cell industry. The authors especially wish to thank Sunita Satyapal and the staff of the US Department of Energy's Fuel Cell Technologies Program for their support and guidance. The authors also wish to thank Rachel Gelman of the National Renewable Energy Laboratory and the many others who made this report possible. iii Contents List of Figures .....................................................................................................................................................v

413

Development of Figure of Merits (FOMs) for Intermediate Coolant Characterization and Selection  

Science Conference Proceedings (OSTI)

This paper focuses on characterization of several coolant performances in the IHTL. There are lots of choices available for the IHTL coolants; gases, liquid metals, molten salts, and etc. Traditionally, the selection of coolants is highly dependent on engineer's experience and decisions. In this decision, the following parameters are generally considered: melting point, vapor pressure, density, thermal conductivity, heat capacity, viscosity, and coolant chemistry. The followings are general thermal-hydraulic requirements for the coolant in the IHTL: (1) High heat transfer performance - The IHTL coolant should exhibit high heat transfer performance to achieve high efficiency and economics; (2) Low pumping power - The IHTL coolant requires low pumping power to improve economics through less stringent pump requirements; (3) Low amount of coolant volume - The IHTL coolant requires less coolant volume for better economics; (4) Low amount of structural materials - The IHTL coolant requires less structural material volume for better economics; (5) Low heat loss - The IHTL requires less heat loss for high efficiency; and (6) Low temperature drop - The IHTL should allow less temperature drop for high efficiency. Typically, heat transfer coolants are selected based on various fluid properties such as melting point, vapor pressure, density, thermal conductivity, heat capacity, viscosity, and coolant chemistry. However, the selection process & results are highly dependent on the engineer's personal experience and skills. In the coolant selection, if a certain coolant shows superior properties with respect to the others, the decision will be very straightforward. However, generally, each coolant material exhibits good characteristics for some properties but poor for the others. Therefore, it will be very useful to have some figures of merits (FOMs), which can represent and quantify various coolant thermal performances in the system of interest. The study summarized in this paper focuses on developing general FOMs for the IHTL coolant selection and shows some estimation results.

Eung Soo Kim; Piyush Sabharwall; Nolan Anderson

2011-06-01T23:59:59.000Z

414

Figure 73. Sales of light-duty vehicles using non-gasoline ...  

U.S. Energy Information Administration (EIA)

Sales of light-duty vehicles using non-gasoline technologies by type, 2011, 2025, ... Hybrid electric Flex-fuel Micro Total 2011.00 0.06 5.38E-03 0.54 0.25 1.61 0.01 2.49

415

Figure 1. "Brian 2.0" a Socially Assistive Robot playing a card memory game with a person.  

E-Print Network (OSTI)

as the main processing unit through a designed software package. This system will be able to be integrated for position tracking · Weight sensing · Capacitive sensing · Two tray system with load cell array to track computer for analysis Figure 3. ­ Easy to use interface #12;

Sun, Yu

416

Technology Transfer: Available Technologies  

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

Ion Sources and Beam Technologies Ion Sources and Beam Technologies GENERATORS AND DETECTORS Compact, Safe and Energy Efficient Neutron Generator Fast Pulsed Neutron Generator High Energy Gamma Generator Lithium-Drifted Silicon Detector with Segmented Contacts Low Power, High Energy Gamma Ray Detector Calibration Device Nested Type Coaxial Neutron Generator Neutron and Proton Generators: Cylindrical Neutron Generator with Nested Option, IB-1764 Neutron-based System for Nondestructive Imaging, IB-1794 Mini Neutron Tube, IB-1793a Ultra-short Ion and Neutron Pulse Production, IB-1707 Mini Neutron Generator, IB-1793b Compact Spherical Neutron Generator, IB-1675 Plasma-Driven Neutron/Gamma Generators Portable, Low-cost Gamma Source for Active Interrogation ION SOURCES WITH ANTENNAS External Antenna for Ion Sources

417

CCN predictions using simplified assumptions of organic aerosol composition and mixing state: A synthesis from six different locations  

SciTech Connect

An accurate but simple quantification of the fraction of aerosol particles that can act as cloud condensation nuclei (CCN) is needed for implementation in large-scale models. Data on aerosol size distribution, chemical composition, and CCN concentration from six different locations have been analyzed to explore the extent to which simple assumptions of composition and mixing state of the organic fraction can reproduce measured CCN number concentrations. Fresher pollution aerosol as encountered in Riverside, CA, and the ship channel in Houston, TX, cannot be represented without knowledge of more complex (size-resolved) composition. For aerosol that has experienced processing (Mexico City, Holme Moss (UK), Point Reyes (CA), and Chebogue Point (Canada)), CCN can be predicted within a factor of two assuming either externally or internally mixed soluble organics although these simplified compositions/mixing states might not represent the actual properties of ambient aerosol populations, in agreement with many previous CCN studies in the literature. Under typical conditions, a factor of two uncertainty in CCN concentration due to composition assumptions translates to an uncertainty of {approx}15% in cloud drop concentration, which might be adequate for large-scale models given the much larger uncertainty in cloudiness.

Ervens, B.; Wang, J.; Cubison, M. J.; Andrews, E.; Feingold, G.; Ogren, J. A.; Jimenez, J. L.; Quinn, P. K.; Bates, T. S.; Zhang, Q.; Coe, H.; Flynn, M.; Allan, J. D.

2010-05-01T23:59:59.000Z

418

Tools & Technologies  

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

Weprovide leadership for transforming workforce development through the power of technology. It develops corporate educational technology policy and enables the use of learning tools and...

419

Available Technologies  

The technologys subnanometer resolution is a result of superior ... Additional R&D will be required ... U.S. DEPARTMENT OF ENERGY OFFICE OF SCIENCE ...

420

Statistical Approaches and Assumptions  

Science Conference Proceedings (OSTI)

... during the PCR amplification process This is highly affected by DNA quantity and quality ... PCR inhibitors present in the sample may reduce PCR ...

2012-10-16T23:59:59.000Z

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


421

Vehicle Technologies Office: Vehicle Technologies Office Organization...  

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

Organization and Contacts Organization Chart for the Vehicle Technologies Program Fuel Technologies and Deployment, Technology Managers Advanced Combustion Engines, Technology...

422

Fuel Cell Technologies Office: Technology Validation  

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

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

423

Chemistry - Technology Transfer: Available Technologies  

Please refer to the list of technologies below for licensing and research collaboration availability. If you can't find the technology you ...

424

Technology Analysis - Heavy Vehicle Technologies  

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

the GPRA benefits estimates for EERE's Vehicle Technologies Program's heavy vehicle technology research activities. Argonne researchers develop the benefits analysis using four...

425

Available Technologies  

APPLICATIONS OF TECHNOLOGY: Thermal management for: microelectronic devices; solar cells and solar energy management systems ; refrigerators

426

Available Technologies  

Energy Storage and Recovery; Renewable Energy; Environmental Technologies. Monitoring and Imaging; Remediation; Modeling; Imaging & Lasers.

427

Program on Technology Innovation: Nuclear Energy in a Carbon-Constrained World  

Science Conference Proceedings (OSTI)

This report explores the economic value of advanced nuclear reactor and fuel system technologies in addressing global warming in a carbon-constrained world. Under a range of reasonable assumptions, the projected value of advanced nuclear technology options is in the trillions of dollars even in scenarios that take into account competing technologies such as carbon capture and storage (CCS).

2005-12-14T23:59:59.000Z

428

Fuel Cell Technologies Office: Technology Validation  

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

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

429

Figure A.9 Technical drawings of the plastic holder end for the iron cores in the ferrofluid-magnetic pipet.  

E-Print Network (OSTI)

Field intensity in the air gap of a core as a function of current and type of material comprising Field flux den- sity B weber/m2 = Tesla (T) Gauss (G) = maxwell/cm2 1 T = 104 G Field flux weber 8 0 2 4 6 8 10 12 applied current in Amps percenterrorfromidealairgapfield 4 3 2 #12;64 Figure A.3

430

An Agent Based Simulation of Smart Metering Technology Adoption  

E-Print Network (OSTI)

of Households Adopting Smart Meters Figure 15: The S-curve Model of Smart Metering Technology Adoption in the Telegestore Project (Data Source: Enel, Italy) The "Lock-in" Effect in the UK Electrcity Market 0 5 10 15 20 25 30 Dec-02 Jun-03 Dec-03 Jun...

Zhang, Tao; Nuttall, William J

431

arXiv:1004.0236v1[astro-ph.CO]1Apr2010 Figures of merit for present and future dark energy probes  

E-Print Network (OSTI)

arXiv:1004.0236v1[astro-ph.CO]1Apr2010 Figures of merit for present and future dark energy probes constraints on dynamical dark energy models from Type Ia supernovae and the cosmic microwave background using figures of merit based on the volume of the allowed dark energy parameter space. For a two-parameter dark

Hu, Wayne

432

Zevenhoven & Kilpinen PARTICULATES 4.2.2004 5-33 Figure 5.33 Baghouse filter systems based on inside out (left)  

E-Print Network (OSTI)

those from fluidised bed combustion, or gasification (Scott and Carpenter, 1996). For temperatures below-44 Figure 5.44 Options for HTHP gasification fuel gas cleaning (picture from Mitchell, 1997) Figure 5.43 Typical HTHP gas cleaning system for gasification product gas (picture from ETSU, 1998) 5.11 High

Zevenhoven, Ron

433

Processing Technology  

Science Conference Proceedings (OSTI)

Aug 5, 2013... relevant polymers and hybrid nanocomposite material systems. ... technology to perform lightweight manufacturing of car components.

434

Technology Transfer  

A new search feature has been implemented, which allows searching of technology transfer information across the Department of Energy Laboratories.

435

Technology Transfer  

Science Conference Proceedings (OSTI)

... get started on understanding accessibility in elections and voting technology. ... bibliography was created by the Georgia Tech Research Institute ...

2013-09-17T23:59:59.000Z

436

Technology Strategies  

Science Conference Proceedings (OSTI)

From the Book:PrefaceTechnology as the Strategic AdvantageWhen I began writing this book I struggled with the direction I wanted it to take. Is this book to be about business, technology, or even the business of technology? I ...

Cooper Smith

2001-07-01T23:59:59.000Z

437

Resource-technology combinations for domestic lighting in rural India: A comparative financial evaluation  

Science Conference Proceedings (OSTI)

Financial analysis and evaluation of various resource-technology combinations for rural domestic lighting is undertaken. The options include kerosene lamps, liquefied petroleum gas (LPG) and biogas lamps, solar photovoltaic lighting systems, and electric lamps. The figures of merit considered for financial comparison are the cost per hour of lighting and the cost per unit of useful energy for lighting. Sensitivity of these figures of merit to the uncertainties in the values of some of the input variables has also been studied.

Rubab, S.; Kandpal, T.C. [Indian Inst. of Tech., New Delhi (India). Centre for Energy Studies

1997-10-01T23:59:59.000Z

438

Faculty of Technology Heat Engineering Laboratory course 424508 E Ron Zevenhoven  

E-Print Network (OSTI)

Faculty of Technology Heat Engineering Laboratory course 424508 E Ron Zevenhoven TRP exam 9 jan;Faculty of Technology Heat Engineering Laboratory course 424508 E Ron Zevenhoven TRP exam 9 jan 2008 2/(m.K), determine numerically, using the grid shown in the Figure: a. the temperatures at the points 1, 2, 3, 4, 5

Zevenhoven, Ron

439

Figures of merit for focusing mega-electron-volt ion beams in biomedical imaging and proton beam writing  

SciTech Connect

A figure of merit (FOM) has been developed for focusing quadrupole multiplet lenses for ion micro- and nanobeam systems. The method which is based on measurement of the central peak of the two-dimensional autocorrelation function of an image provides separate FOM for the horizontal and vertical directions. The approach has been tested by comparison with the edge widths obtained by nonlinear fitting the edge widths of a Ni grid and found to be reliable. The FOM has the important advantage for ion beam imaging of biomedical samples that the fluence needed is considerably lower than for edge fitting.

Ren Minqin; Whitlow, Harry J.; Ananda Sagari, A. R.; Kan, Jeroen A. van; Osipowicz, Thomas; Watt, Frank [Department of Physics, University of Jyvaeskylae, P.O. Box 35 (YFL), FIN-40014 (Finland); Centre for Ion Beam Applications, Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore 117542 (Singapore)

2008-01-01T23:59:59.000Z

440

Technology '90  

Science Conference Proceedings (OSTI)

The US Department of Energy (DOE) laboratories have a long history of excellence in performing research and development in a number of areas, including the basic sciences, applied-energy technology, and weapons-related technology. Although technology transfer has always been an element of DOE and laboratory activities, it has received increasing emphasis in recent years as US industrial competitiveness has eroded and efforts have increased to better utilize the research and development resources the laboratories provide. This document, Technology '90, is the latest in a series that is intended to communicate some of the many opportunities available for US industry and universities to work with the DOE and its laboratories in the vital activity of improving technology transfer to meet national needs. Technology '90 is divided into three sections: Overview, Technologies, and Laboratories. The Overview section describes the activities and accomplishments of the DOE research and development program offices. The Technologies section provides descriptions of new technologies developed at the DOE laboratories. The Laboratories section presents information on the missions, programs, and facilities of each laboratory, along with a name and telephone number of a technology transfer contact for additional information. Separate papers were prepared for appropriate sections of this report.

Not Available

1991-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "technology assumptions figure" 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

The Role Of Modeling Assumptions And Policy Instruments in Evaluating The Global Implications Of U.S. Biofuel Policies  

Science Conference Proceedings (OSTI)

The primary objective of current U.S. biofuel law the Energy Independence and Security Act of 2007 (EISA) is to reduce dependence on imported oil, but the law also requires biofuels to meet carbon emission reduction thresholds relative to petroleum fuels. EISA created a renewable fuel standard with annual targets for U.S. biofuel use that climb gradually from 9 billion gallons per year in 2008 to 36 billion gallons (or about 136 billion liters) of biofuels per year by 2022. The most controversial aspects of the biofuel policy have centered on the global social and environmental implications of its potential land use effects. In particular, there is an ongoing debate about whether indirect land use change (ILUC) make biofuels a net source, rather sink, of carbon emissions. However, estimates of ILUC induced by biofuel production and use can only be inferred through modeling. This paper evaluates how model structure, underlying assumptions, and the representation of policy instruments influence the results of U.S. biofuel policy simulations. The analysis shows that differences in these factors can lead to divergent model estimates of land use and economic effects. Estimates of the net conversion of forests and grasslands induced by U.S. biofuel policy range from 0.09 ha/1000 gallons described in this paper to 0.73 ha/1000 gallons from early studies in the ILUC change debate. We note that several important factors governing LUC change remain to be examined. Challenges that must be addressed to improve global land use change modeling are highlighted.

Oladosu, Gbadebo A [ORNL; Kline, Keith L [ORNL

2010-01-01T23:59:59.000Z

442

Building Technologies Office: Technology Research, Standards...  

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

to someone by E-mail Share Building Technologies Office: Technology Research, Standards, and Codes in Emerging Technologies on Facebook Tweet about Building Technologies...

443

Ceramic technology for advanced heat engines project  

DOE Green Energy (OSTI)

The Ceramic Technology for Advanced Heat Engines Project was developed by the Department of Energy's Office of Transportation Systems in Conservation and Renewable Energy. This project was developed to meet the ceramic technology requirements of the OTT's automotive technology programs. This project is managed by ORNL and is closely coordinated with complementary ceramics tasks funded by other DOE offices, NASA, DoD, and industry. Research is discussed under the following topics; Turbomilling of SiC Whiskers; microwave sintering of silicon nitride; and milling characterization; processing of monolithics; silicon nitride matrix; oxide matrix; silicate matrix; thermal and wear coatings; joining; design; contact interfaces; time-dependent behavior; environmental effects; fracture mechanics; nondestructive evaluation; and technology transfer. References, figures, and tables are included with each topic.

Not Available

1990-09-01T23:59:59.000Z

444

Targeted Technology Transfer to US Independents  

SciTech Connect

The Petroleum Technology Transfer Council (PTTC) was established by domestic crude oil and natural gas producers in 1994 as a national not-for-profit organization to address the increasingly urgent need to improve the technology-transfer process in the U.S. upstream petroleum industry. Coordinated from a Headquarters (HQ) office in Houston, PTTC maintains an active grassroots program executed by 10 Regional Lead Organizations (RLOs) and two satellite offices (Figure 1). Regional Directors interact with domestic oil and gas producers through technology workshops, resource centers, websites, newsletters, technical publications and cooperative outreach efforts. HQ facilitates inter-regional technology transfer and implements a comprehensive communications program. Active volunteers on the National Board and in Producer Advisory Groups (PAGs) in each of the 10 regions focus effort in areas that will create the most impact for domestic producers. Focused effort by dedicated individuals across the country has enabled PTTC to achieve the milestones outlined in Appendix A.

Donald F. Duttlinger; E. Lance Cole

2006-09-29T23:59:59.000Z

445

ZEOLITE CATALYSIS - TECHNOLOGY  

E-Print Network (OSTI)

Rheume, eta/. XBL 805-1065 FIGURE 3 l --Catalytic reforminga--Catalytic reforming+ selectoforming Q) E Q) +w u 70

Heinemann, Heinz

2013-01-01T23:59:59.000Z

446

Available Technologies  

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

6 News Stories (and older) 6 News Stories (and older) 12.21.2005___________________________________________________________________ Genzyme acquires gene therapy technology invented at Berkeley Lab. Read more here. 07.19.2005 _________________________________________________________________ Symyx, a start up company using Berkeley Lab combinatorial chemistry technology licensed by the Technology Transfer Department and developed by Peter Schultz and colleagues in the Materials Sciences Division, will be honored with Frost & Sullivan's 2005 Technology Leadership Award at their Excellence in Emerging Technologies Awards Banquet for developing enabling technologies and methods to aid better, faster and more efficient R&D. Read more here. 07.11.2005 _________________________________________________________________ Nanosys, Inc., a Berkeley Lab startup, is among the solar nanotech companies investors along Sand Hill Road in Menlo Park hope that thinking small will translate into big profits. Read more here.

447

NETL: Technologies  

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

projects are designed to: enhance domestic oil and natural gas supplies through advanced exploration and production technology; examine water related concerns; investigate...

448

Technology Update  

Science Conference Proceedings (OSTI)

A Novel Solvent Extraction Process With Bottom Gas Injection for Liquid Waste ... Membrane Technology for Treatment of Wastes Containing Dissolved Metals:...

449

Microwave Technology  

Science Conference Proceedings (OSTI)

Oct 20, 2011 ... These wastes are found in the market. ... Cherian1; Michael Kirksey1; Sandwip Dey2; 1Spheric Technologies Inc; 2Arizona State University

450

Transmission Technologies  

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

electronically (shift-by-wire) and performed by a hydraulic system or electric motor. In addition, technologies can be employed to make the shifting process smoother than...

451

Test procedures and protocols: Their relevance to the figure of merit for thermal distribution systems. Volume 1: Informal report  

Science Conference Proceedings (OSTI)

A conceptual framework is developed that categorizes measurement protocols for forced-air thermal distribution systems in small buildings. This framework is based on the distinction between two generic approaches. The {open_quote}system-comparison{close_quote} approach seeks to determine, via a pair of whole-house energy-use measurements, the difference in energy use between the house with the as-found duct system and the same house with no energy losses attributable to the thermal distribution system. The {open_quote}component loss-factor{close_quote} approach identifies and measures the individual causes of duct losses, and then builds up a value for the net overall duct efficiency, usually with the help of computer simulation. Examples of each approach are analyzed and related to a proposed Figure of Merit for thermal distribution systems. This Figure of Merit would serve as the basis for a Standard Method of Test analogous to those already in place for furnaces, boilers, air conditioners, and heat pumps.

Andrews, J.W.

1993-09-01T23:59:59.000Z

452

Metering Technology  

Science Conference Proceedings (OSTI)

Utilities are looking to replace meters that only measure kilowatt-hours with advanced meters with greater features and functions. This White Paper describes the smart metering technology that is already available or will be available in the near future. It also provides a high-level overview of the wired and wireless communication technologies used in the metering industry.

2008-06-20T23:59:59.000Z

453

Technology Search Results | Brookhaven Technology ...  

BSA 11-30: Enhanced Alkane production by Aldehyde Decarbonylase Fusion Constructs; BSA 12-36: Oil Accumulation in Plant Leaves; Find a Technology.

454

Technology Search Results | Brookhaven Technology ...  

There are 9 technologies tagged "cancer". BSA 01-02: ... a limited-liability company founded by the Research Foundation for the State University of ...

455

Manufacturing Science and Technology: Technologies  

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

Courtesy of ZCorp The Rapid Prototyping Laboratory (RPL) supports internal design, manufacturing, and process development with three rapid prototyping (RP) technologies:...

456

Manufacturing Science and Technology: Technologies  

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

parts Brazing large complex parts The joining and heat-treating technologies in the Thin Film, Vacuum, & Packaging department include brazing, heat-treating, diffusion...

457

Vehicle Technologies Office: Graduate Automotive Technology Education  

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

Deployment Deployment Site Map Printable Version Share this resource Send a link to Vehicle Technologies Office: Graduate Automotive Technology Education (GATE) to someone by E-mail Share Vehicle Technologies Office: Graduate Automotive Technology Education (GATE) on Facebook Tweet about Vehicle Technologies Office: Graduate Automotive Technology Education (GATE) on Twitter Bookmark Vehicle Technologies Office: Graduate Automotive Technology Education (GATE) on Google Bookmark Vehicle Technologies Office: Graduate Automotive Technology Education (GATE) on Delicious Rank Vehicle Technologies Office: Graduate Automotive Technology Education (GATE) on Digg Find More places to share Vehicle Technologies Office: Graduate Automotive Technology Education (GATE) on AddThis.com...

458

Building Technologies Office: Emerging Technologies Activities  

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

Emerging Technologies Emerging Technologies Activities to someone by E-mail Share Building Technologies Office: Emerging Technologies Activities on Facebook Tweet about Building Technologies Office: Emerging Technologies Activities on Twitter Bookmark Building Technologies Office: Emerging Technologies Activities on Google Bookmark Building Technologies Office: Emerging Technologies Activities on Delicious Rank Building Technologies Office: Emerging Technologies Activities on Digg Find More places to share Building Technologies Office: Emerging Technologies Activities on AddThis.com... About Take Action to Save Energy Partner with DOE Activities Appliances Research Building Envelope Research Windows, Skylights, & Doors Research Space Heating & Cooling Research Water Heating Research

459

Vehicle Technologies Office: Vehicle Technologies Office Recognizes  

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

Vehicle Technologies Vehicle Technologies Office Recognizes Outstanding Researchers to someone by E-mail Share Vehicle Technologies Office: Vehicle Technologies Office Recognizes Outstanding Researchers on Facebook Tweet about Vehicle Technologies Office: Vehicle Technologies Office Recognizes Outstanding Researchers on Twitter Bookmark Vehicle Technologies Office: Vehicle Technologies Office Recognizes Outstanding Researchers on Google Bookmark Vehicle Technologies Office: Vehicle Technologies Office Recognizes Outstanding Researchers on Delicious Rank Vehicle Technologies Office: Vehicle Technologies Office Recognizes Outstanding Researchers on Digg Find More places to share Vehicle Technologies Office: Vehicle Technologies Office Recognizes Outstanding Researchers on AddThis.com...

460

FUEL CELL TECHNOLOGIES PROGRAM Technologies  

E-Print Network (OSTI)

.eere.energy.gov/informationcenter hydrogen and electricity for fuel cell and plug-in hybrid electric vehicles while using proven stationary vehicles with its own fuel cell technology. Currently, advanced vehicle technologies are being evalu- ated and fuel cells offer great promise for our energy future. Fuel cell vehicles are not yet commercially

Note: This page contains sample records for the topic "technology assumptions figure" 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

Building Technologies Office: Emerging Technologies  

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

Creating the Next Generation of Energy Efficient Technology Creating the Next Generation of Energy Efficient Technology The Emerging Technologies team partners with national laboratories, industry, and universities to advance research, development, and commercialization of energy efficient and cost effective building technologies. These partnerships help foster American ingenuity to develop cutting-edge technologies that have less than 5 years to market readiness, and contribute to the goal to reduce energy consumption by at least 50%. Sandia Cooler's innovative, compact design combines a fan and a finned metal heat sink into a single element, efficiently transferring heat in microelectronics and reducing energy use. Supporting Innovative Research to Help Reduce Energy Use and Advance Manufacturing Learn More

462

This book adds an important nuance to the traditional historiographical assumption that trade in the Early Modern period was mostly conducted between family and those of the same  

E-Print Network (OSTI)

This book adds an important nuance to the traditional historiographical assumption that trade group. Rather, it is the assertion of this book, that there were very real and quite important trade relationships between merchants of different groups, and the book uses a case study of the Sephardim

van den Brink, Jeroen

463

Technology Analysis  

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

* Heavy Vehicle Technologies * Heavy Vehicle Technologies * Multi-Path Transportation Futures * Idling Studies * EDrive Vehicle Monthly Sales Transportation Research and Analysis Computing Center Working With Argonne Contact TTRDC Technology Analysis truck Heavy vehicle techologies are one subject of study. Research Reducing Greenhouse Gas Emissions from U.S. Transportation Heavy Vehicle Technologies Multi-Path Transportation Futures Study Idling Studies Light Duty Electric Drive Vehicles Monthly Sales Updates Lithium-Ion Battery Recycling and Life Cycle Analysis Reports Propane Vehicles: Status, Challenges, and Opportunities (pdf; 525 kB) Natural Gas Vehicles: Status, Barriers, and Opportunities (pdf; 696 kB) Regulatory Influences That Will Likely Affect Success of Plug-in Hybrid and Battery Electric Vehicles (pdf; 1.02 MB)

464

Fabrication Technology  

SciTech Connect

The mission of the Fabrication Technology thrust area is to have an adequate base of manufacturing technology, not necessarily resident at Lawrence Livermore National Laboratory (LLNL), to conduct the future business of LLNL. The specific goals continue to be to (1) develop an understanding of fundamental fabrication processes; (2) construct general purpose process models that will have wide applicability; (3) document findings and models in journals; (4) transfer technology to LLNL programs, industry, and colleagues; and (5) develop continuing relationships with the industrial and academic communities to advance the collective understanding of fabrication processes. The strategy to ensure success is changing. For technologies in which they are expert and which will continue to be of future importance to LLNL, they can often attract outside resources both to maintain their expertise by applying it to a specific problem and to help fund further development. A popular vehicle to fund such work is the Cooperative Research and Development Agreement with industry. For technologies needing development because of their future critical importance and in which they are not expert, they use internal funding sources. These latter are the topics of the thrust area. Three FY-92 funded projects are discussed in this section. Each project clearly moves the Fabrication Technology thrust area towards the goals outlined above. They have also continued their membership in the North Carolina State University Precision Engineering Center, a multidisciplinary research and graduate program established to provide the new technologies needed by high-technology institutions in the US. As members, they have access to and use of the results of their research projects, many of which parallel the precision engineering efforts at LLNL.

Blaedel, K.L.

1993-03-01T23:59:59.000Z

465

Figure 1 - TMS  

Science Conference Proceedings (OSTI)

The inset shows a detail of the major ampullate gland silk (MAS) fibers. The double fiber structure is known as a bave, and each individual monofilament is a brin...

466

KT Monograph Pottery Figures  

E-Print Network (OSTI)

-692 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 0 10 28 Excavations at Kilise Tepe 1994-98: D6:1 - Iron Age Cypriot jugs in Leeds Museum D 37 2 19 64 D 36 5 19 64 10 0 29 Excavations at Kilise Tepe 1994-98: D6:2 - Level II ceramics...

Rickhards, T; Postgate, E; Thomas, D C; Postgate, J N

2005-03-16T23:59:59.000Z

467

Figures for CERN Courier  

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

Collider (FMC), Next Muon Collider (NMC), Next Linear Collider (NLC), and Very Large Hadron Collider (VLHC). These are compared with the footprint of the LHC at CERN, and the...

468

APPENDIX A: FIGURES  

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

Ohio 44023 The Renaissance Group, InstallerProject Manager, 440-256-2800 690480 Transformer Wind Turbine Main Switchgear Interconnect Point 4 Buried 4" Conduits See Included...

469

Figure 6 - TMS  

Science Conference Proceedings (OSTI)

The image below appears as part of the hypertext-enhanced article "The Design and Application of Multifunctional Structure-Battery Materials Systems" which...

470

Market-analysis system for conservation technologies. Draft final report  

SciTech Connect

A prototype market analysis methodology to provide DOE decision makers guidance in evaluating and selecting strategies that promote energy conservation technologies is discussed. The methodology, named MASCOT (Market Analysis System for COnservation Technologies), was designed for the residential water heating market. However, the basic logic can be extended to other market segments, such as space heating and conditioning, and the commercial sector. MASCOT forecasts the market performance of any arbitrary set of technologies that the user chooses. The methodology captures the time-varying effects of technological and economic changes in the market, determines the critical features for new water heating technologies, calculates the likely energy impacts from the use of the actual technologies, and provides information concerning the sensitivity of the results to assumptions about market conditions, technology characteristics, and the factors underlying market penetration. (PSB)

Morris, P.A.; Thapa, M.N.; Bauman, D.S.; Froker, D.B.

1981-12-14T23:59:59.000Z

471

Building Technologies Office: 2013 DOE Building Technologies...  

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

2013 DOE Building Technologies Office Program Review to someone by E-mail Share Building Technologies Office: 2013 DOE Building Technologies Office Program Review on Facebook Tweet...

472

National Energy Technology Laboratory Technology Marketing ...  

National Energy Technology Laboratory Technology Marketing Summaries. Here youll find marketing summaries for technologies available for licensing from the ...

473

2008 Solar Technologies Market Report  

E-Print Network (OSTI)

88 Figure 4.4. Net Metering Policies, OctoberNet Metering ..interconnection and net metering rules, have further

Price, S.

2010-01-01T23:59:59.000Z

474

Advanced Integrated Systems Technology Development  

E-Print Network (OSTI)

refrigeration, and fire protection systems. Figure 2.1.2-1: CalSTRS Headquarters, Sacramento, CA (Mechanical design

2013-01-01T23:59:59.000Z

475

Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results  

SciTech Connect

This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

Koomey, J.G.; Brown, R.E.; Richey, R. [and others

1995-12-01T23:59:59.000Z

476

NREL: Geothermal Technologies - Projects  

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

and Technology Technology Transfer Technology Deployment Energy Systems Integration Geothermal Technologies Search More Search Options Site Map Printable Version Projects The NREL...

477

NREL: Geothermal Technologies - Capabilities  

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

and Technology Technology Transfer Technology Deployment Energy Systems Integration Geothermal Technologies Search More Search Options Site Map Printable Version Capabilities The...

478

NREL: Geothermal Technologies - News  

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

and Technology Technology Transfer Technology Deployment Energy Systems Integration Geothermal Technologies Search More Search Options Site Map Printable Version Geothermal News...

479

Building Technologies Office: News  

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

Technologies Office: News on Twitter Bookmark Building Technologies Office: News on Google Bookmark Building Technologies Office: News on Delicious Rank Building Technologies...

480

Building Technologies Office: About  

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

Technologies Office: About on Twitter Bookmark Building Technologies Office: About on Google Bookmark Building Technologies Office: About on Delicious Rank Building Technologies...

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


481

Technology Transfer  

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

Energy Efficiency & Renewable and Energy - Commercialization Energy Efficiency & Renewable and Energy - Commercialization Deployment SBIR/STTR - Small Business Innovation Research and Small Business Technology Transfer USEFUL LINKS Contract Opportunities: FBO.gov FedConnect.net Grant Opportunities DOE Organization Chart Association of University Technology Managers (AUTM) Federal Laboratory Consortium (FLC) Feedback Contact us about Tech Transfer: Mary.McManmon@science.doe.gov Mary McManmon, 202-586-3509 link to Adobe PDF Reader link to Adobe Flash player Licensing Guide and Sample License The Technology Transfer Working Group (TTWG), made up of representatives from each DOE Laboratory and Facility, recently created a Licensing Guide and Sample License [762-KB PDF]. The Guide will serve to provide a general understanding of typical contract terms and provisions to help reduce both

482

Manufacturing technology  

SciTech Connect

The specific goals of the Manufacturing Technology thrust area are to develop an understanding of fundamental fabrication processes, to construct general purpose process models that will have wide applicability, to document our findings and models in journals, to transfer technology to LLNL programs, industry, and colleagues, and to develop continuing relationships with industrial and academic communities to advance our collective understanding of fabrication processes. Advances in four projects are described here, namely Design of a Precision Saw for Manufacturing, Deposition of Boron Nitride Films via PVD, Manufacturing and Coating by Kinetic Energy Metallization, and Magnet Design and Application.

Blaedel, K.L.

1997-02-01T23:59:59.000Z

483

PNNL: Available Technologies - Browse Technologies by Portfolio  

Search PNNL. PNNL Home; About; Research; Publications; Jobs; News; Contacts; Browse Technologies by Portfolio. Select a technology portfolio to view ...

484

Idaho National Laboratory - Technology Transfer - Technologies ...  

Idaho National Laboratory Technologies Available for Licensing ... Fossil Energy; Information Technology; Manufacturing ; Materials; National Security; Non-Nuclear ...

485

Geothermal Technologies Office: Geothermal Electricity Technology...  

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

and Renewable Energy EERE Home | Programs & Offices | Consumer Information Geothermal Technologies Office Search Search Help Geothermal Technologies Office HOME ABOUT...

486

Geothermal Technologies Office: Enhanced Geothermal Systems Technologi...  

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

and Renewable Energy EERE Home | Programs & Offices | Consumer Information Geothermal Technologies Office Search Search Help Geothermal Technologies Office HOME ABOUT...

487

NETL: Technology Transfer - Available Technologies for Partnership  

Technology Transfer Available Technologies for Partnership Software and Modeling. Month Posted. Partnership Opportunity. Patent Information. 12/2011: ...

488

Healthy technology  

Science Conference Proceedings (OSTI)

One of the biggest struggles user experience teams face is breaking through traditional notions of product strategy, planning and development to bring actionable awareness to the bigger picture around delivering full experiences that people really care ... Keywords: design management, design process, ethnography, experience, healthy technology, industry, lifecycle, metaphor, platform, reliability, research, security, strategy, sustainability

Ashwini Asokan; Michael .J. Payne

2008-04-01T23:59:59.000Z

489

Technologies Applications  

E-Print Network (OSTI)

evaporation systems n Potential mining applications (produced water) nIndustry applications for which silicaLicensable Technologies Applications: n Cooling tower systems n Water treatment systems n Water needed n Decreases the amount of makeup water and subsequent discharged water (blowdown) n Enables

490

Manufacturing technologies  

SciTech Connect

The Manufacturing Technologies Center is an integral part of Sandia National Laboratories, a multiprogram engineering and science laboratory, operated for the Department of Energy (DOE) with major facilities at Albuquerque, New Mexico, and Livermore, California. Our Center is at the core of Sandia`s Advanced Manufacturing effort which spans the entire product realization process.

NONE

1995-09-01T23:59:59.000Z

491

Vacuum Technology  

SciTech Connect

The environmental condition called vacuum is created any time the pressure of a gas is reduced compared to atmospheric pressure. On earth we typically create a vacuum by connecting a pump capable of moving gas to a relatively leak free vessel. Through operation of the gas pump the number of gas molecules per unit volume is decreased within the vessel. As soon as one creates a vacuum natural forces (in this case entropy) work to restore equilibrium pressure; the practical effect of this is that gas molecules attempt to enter the evacuated space by any means possible. It is useful to think of vacuum in terms of a gas at a pressure below atmospheric pressure. In even the best vacuum vessels ever created there are approximately 3,500,000 molecules of gas per cubic meter of volume remaining inside the vessel. The lowest pressure environment known is in interstellar space where there are approximately four molecules of gas per cubic meter. Researchers are currently developing vacuum technology components (pumps, gauges, valves, etc.) using micro electro mechanical systems (MEMS) technology. Miniature vacuum components and systems will open the possibility for significant savings in energy cost and will open the doors to advances in electronics, manufacturing and semiconductor fabrication. In conclusion, an understanding of the basic principles of vacuum technology as presented in this summary is essential for the successful execution of all projects that involve vacuum technology. Using the principles described above, a practitioner of vacuum technology can design a vacuum system that will achieve the project requirements.

Biltoft, P J

2004-10-15T23:59:59.000Z

492

Technological Change and Its Effects on Mitigation Costs  

Science Conference Proceedings (OSTI)

This report emphasizes that understanding the way technologies evolve and penetrate the market is essential to understanding methods of addressing global climate change. The focus of this chapter is on the ways in which technological change is captured by climate change policy modelers, with particular attention on two idealized approaches: top-down and bottom-up. The conclusion is that in order to understand the implications of large-scale economic models of the climate change problem, it is essential to understand first the assumptions that have been made regarding the path of technological progress.

Edmonds, James A.; Roop, Joseph M.; Scott, M. J.

2001-01-01T23:59:59.000Z

493

Pervasive Information Technology Homepage  

Science Conference Proceedings (OSTI)

Pervasive Information Technology. Pervasive information technology is the trend towards increasingly ubiquitous connected ...

2011-07-05T23:59:59.000Z

494

Renewable Energy Technology Costs and Drivers | Open Energy Information  

Open Energy Info (EERE)

Renewable Energy Technology Costs and Drivers Renewable Energy Technology Costs and Drivers Jump to: navigation, search Tool Summary Name: Renewable Energy Technology Costs and Drivers Agency/Company /Organization: National Renewable Energy Laboratory Sector: Energy Focus Area: Renewable Energy Topics: Finance, Market analysis, Technology characterizations Resource Type: Publications Website: prod-http-80-800498448.us-east-1.elb.amazonaws.com//w/images/6/63/RE_C Renewable Energy Technology Costs and Drivers Screenshot References: Renewable Energy Technology Costs and Drivers[1] Summary "Provided herein is a preliminary, high-level summary of future and projected cost estimates for 1) Biofuels, 2) Solar (PV & CSP), and 3) Vehicle Batteries. Cost estimates are dependent on various assumptions and

495

TECHNOLOGY TRANSFER  

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

404-NOV. 1, 2000 404-NOV. 1, 2000 TECHNOLOGY TRANSFER COMMERCIALIZATION ACT OF 2000 VerDate 11-MAY-2000 04:52 Nov 16, 2000 Jkt 089139 PO 00000 Frm 00001 Fmt 6579 Sfmt 6579 E:\PUBLAW\PUBL404.106 APPS27 PsN: PUBL404 114 STAT. 1742 PUBLIC LAW 106-404-NOV. 1, 2000 Public Law 106-404 106th Congress An Act To improve the ability of Federal agencies to license federally owned inventions. Be it enacted by the Senate and House of Representatives of the United States of America in Congress assembled, SECTION 1. SHORT TITLE. This Act may be cited as the ''Technology Transfer Commer- cialization Act of 2000''. SEC. 2. FINDINGS. The Congress finds that- (1) the importance of linking our unparalleled network of over 700 Federal laboratories and our Nation's universities with United States industry continues to hold great promise

496

Manufacturing technology  

SciTech Connect

This bulletin depicts current research on manufacturing technology at Sandia laboratories. An automated, adaptive process removes grit overspray from jet engine turbine blades. Advanced electronic ceramics are chemically prepared from solution for use in high- voltage varistors. Selective laser sintering automates wax casting pattern fabrication. Numerical modeling improves performance of photoresist stripper (simulation on Cray supercomputer reveals path to uniform plasma). And mathematical models help make dream of low- cost ceramic composites come true.

Leonard, J.A.; Floyd, H.L.; Goetsch, B.; Doran, L. [eds.

1993-08-01T23:59:59.000Z

497

Biomass Technologies  

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

There are many types of biomassorganic matter such as plants, residue from agriculture and forestry, and the organic component of municipal and industrial wastesthat can now be used to produce fuels, chemicals, and power. Wood has been used to provide heat for thousands of years. This flexibility has resulted in increased use of biomass technologies. According to the Energy Information Administration, 53% of all renewable energy consumed in the United States was biomass-based in 2007.

498

TECHNOLOGY ADMINISTRATION  

E-Print Network (OSTI)

This report originated in the authors participation in a multi-country study of national innovation systems and their impact on new technology development, sponsored by the Organization for Economic Cooperation and Development (OECD). Our task was to look at the U.S. national innovation systems impact on the commercial development of Proton Exchange Membrane (PEM) fuel cells for residential power applications. Early drivers of PEM fuel cell innovation were the aerospace and defense programs, in particular the National Aeronautics and Space Administration (NASA), which used fuel cells on its spacecraft. In the early 1990s, deregulation hit the electric utility industry, which made utilities and entrepreneurs see the potential in generating electricity from distributed power. Throughout the 1990s, the Department of Energy funded a significant portion of civilian fuel cell research, while the Department of Defense and NASA funded more esoteric military and space applications. In 1998, the Department of Commerces Advanced Technology Program (ATP) awarded the first of 25 fuel cell projects, as prospects for adoption and commercialization of fuel cell technologies improved.

John M. Nail; Gary Anderson; Gerald Ceasar; Christopher J. Hansen; John M. Nail; Gerald Ceasar; Christopher J. Hansen; Carlos M. Gutierrez; Hratch G. Samerjian; Acting Director; Marc G. Stanley; Director Abstract

2005-01-01T23:59:59.000Z

499

Technology disrupted  

SciTech Connect

Three years ago, the author presented a report on power generation technologies which in summary said 'no technology available today has the potential of becoming transformational or disruptive in the next five to ten years'. In 2006 the company completed another strategic view research report covering the electric power, oil, gas and unconventional energy industries and manufacturing industry. This article summarises the strategic view findings and then revisits some of the scenarios presented in 2003. The cost per megawatt-hour of the alternatives is given for plants ordered in 2005 and then in 2025. The issue of greenhouse gas regulation is dealt with through carbon sequestration and carbon allowances or an equivalent carbon tax. Results reveal substantial variability through nuclear power, hydro, wind, geothermal and biomass remain competitive through every scenario. Greenhouse gas scenario analysis shows coal still be viable, albeit less competitive against nuclear and renewable technologies. A carbon tax or allowance at $24 per metric ton has the same effect on IGCC cost as a sequestration mandate. However, the latter would hurt gas plants much more than a tax or allowance. Sequestering CO{sub 2} from a gas plant is almost as costly per megawatt-hour as for coal. 5 refs., 5 figs., 5 tabs.

Papatheodorou, Y. [CH2M Hill (United States)

2007-02-15T23:59:59.000Z

500

Figure 5. The LAT and the GLAST spacecraft. GLAST will also carry a gamma-ray burst monitor, the GBM instrument. For more information about GLAST, see  

E-Print Network (OSTI)

Figure 5. The LAT and the GLAST spacecraft. GLAST will also carry a gamma-ray burst monitor-energy gamma-ray astronomy, owing to the poor angular resolutions of the detectors and the limited statistics of the diffuse interstellar gamma-ray intensity. The LAT collaboration will develop a model of th e interstellar

Strong, Andrew W.