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1

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. . . . . . . . . . . . .

2

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

3

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

4

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).

5

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).

6

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).

7

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

8

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

9

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

10

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.

11

Natural Gas Transmission and Distribution Module  

Gasoline and Diesel Fuel Update (EIA)

U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and...

12

Natural Gas Transmission and Distribution Module  

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

31, 2012, Washington, DC Major assumption changes for AEO2013 Oil and Gas Working Group Natural Gas Transmission and Distribution Module DRAFT WORKING GROUP PRESENTATION DO NOT...

13

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.

14

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.

15

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

16

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)

17

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.

18

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

19

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

20

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

Note: This page contains sample records for the topic "distribution module assumption" 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

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).

22

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.

23

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).

24

Assumptions to the Annual Energy Outlook 2002 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. 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 19). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated

25

Assumptions to the Annual Energy Outlook 2002 - Electricity Market Module  

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 2002, DOE/EIA- M068(2002) January 2002. 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

26

Assumptions to the Annual Energy Outlook 2002 - Residential Demand Module  

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

27

Assumptions to the Annual Energy Outlook 2001 - Electricity Market Module  

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 2001, DOE/EIA- M068(2001) January 2001. 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

28

Assumptions to the Annual Energy Outlook 2001 - Residential Demand Module  

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

29

Assumptions to the Annual Energy Outlook 2001 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. 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

30

Assumptions to the Annual Energy Outlook 2002 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. 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

31

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,

32

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,

33

Assumptions to the Annual Energy Outlook 2000 - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

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(99), (Washington, DC, February 1999).

34

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.

35

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.

36

Assumptions to the Annual Energy Outlook 2001 - Petroleum Market Module  

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

37

Assumptions to the Annual Energy Outlook 2002 - Petroleum Market Module  

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

38

Assumptions to the Annual Energy Outlook 2001 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Comleted Copy in PDF Format Comleted Copy in PDF Format Related Links Annual Energy Outlook 2001 Supplemental Data to the AEO 2001 NEMS Conference To Forecasting Home Page EIA Homepage Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. 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 19). The

39

Assumptions to the Annual Energy Outlook 2000 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. The energy-intensive industries are modeled through the use of a detailed process flow accounting procedure, whereas the nonenergy-intensive and the nonmanufacturing industries are modeled with substantially less detail (Table 14). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated by using the SEDS24 data.

40

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

commercial.gif (5196 bytes) commercial.gif (5196 bytes) The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. 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

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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.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

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.

42

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.

43

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

44

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.

45

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.

46

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

47

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

48

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.

49

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 . . . . . . . . . . . . . . . . . .

50

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

51

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.

52

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

53

Assumptions to the Annual Energy Outlook 2001 - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. 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(2001), (Washington, DC, January 2001). 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 gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. OGSM encompasses domestic crude oil and natural gas supply by both

54

Assumptions to the Annual Energy Outlook 2002 - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. 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(2002), (Washington, DC, January 2002). 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 gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. OGSM encompasses domestic crude oil and natural gas supply by both

55

Impact of assumption of log-normal distribution on monthly rainfall estimation from TMI  

E-Print Network [OSTI]

The log-normal assumption for the distribution of the rain rates used for the estimation of monthly rain totals proposed in Wilheit et al 1991 was examined. Since the log-normal assumption was originally used for the SSM/I, it is now necessary to re...

Lee, Dong Heon

2012-06-07T23:59:59.000Z

56

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

57

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.

58

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.

59

Natural Gas Transmission and Distribution Module  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 129 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 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 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 network that links them. Natural gas flow patterns are a function of the pattern in the previous year, coupled

60

Natural Gas Transmission and Distribution Module This  

Gasoline and Diesel Fuel Update (EIA)

This This page inTenTionally lefT blank 127 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 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 a regional interstate representative pipeline 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 network that links them. Natural gas flow patterns are a function of the

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


61

Assumptions to the Annual Energy Outlook 1999 - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

oil.gif (4836 bytes) oil.gif (4836 bytes) The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. 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(99), (Washington, DC, January 1999). 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 gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. OGSM encompasses domestic crude oil and natural gas supply by both conventional and nonconventional recovery techniques. Nonconventional recovery includes enhanced oil recovery and unconventional gas recovery from tight gas formations, gas shale, and coalbeds. Foreign gas transactions may occur via either pipeline (Canada or Mexico) or transport ships as liquefied natural gas (LNG).

62

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

63

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

64

D:\assumptions_2001\assumptions2002\currentassump\demand.vp  

Gasoline and Diesel Fuel Update (EIA)

2 2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Petroleum Market Module. . . . . . . . . . . . .

65

127 Natural Gas Transmission and Distribution Module  

E-Print Network [OSTI]

and border prices, end-use prices, and flows of natural gas through a regional interstate representative pipeline 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 network that links them. Natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of the supply options available to bring gas to market centers within each of the NGTDM regions (Figure 9). The major assumptions used within the NGTDM are grouped into four general categories. They relate to (1) structural components of the model, (2) capacity expansion and pricing of transmission and distribution services, (3) Arctic pipelines, and (4) imports and exports. A complete listing of NGTDM assumptions and in-depth

Key Assumptions

66

Natural Gas Transmission and Distribution Module  

Gasoline and Diesel Fuel Update (EIA)

5, DOE/EIA-M062(2005) (Washington, DC, 2005). 5, DOE/EIA-M062(2005) (Washington, DC, 2005). Energy Information Administration/Assumptions to the Annual Energy Outlook 2006 101 Primary Flows Secondary Flows Pipeline Border Crossing Specific LNG Terminals Primary Flows Secondary Flows Pipeline Border Crossing Specific LNG Terminals Generic LNG Terminals Alaska Alaska MacKenzie W. Canada E. Canada Canada Offshore & LNG Pacific (9) Mountain (8) CA (12) AZ/NM (11) W. South Central (7) E. South Central (6) W. North Central (4) E. North Central (3) Mid Atlantic (2) New Engl. (1) S. Atlantic (5) FL (10) Bahamas Mexico Figure 8. Natural Gas Transmission and Distribution Model Regions Source: Energy Information Administration, Office of Integrated Analysis and Forecasting Report #:DOE/EIA-0554(2006) Release date: March 2006 Next release date: March 2007

67

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . 99 Petroleum Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Coal Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Renewable Fuels Module . . . . . . . . . . .

68

Assumptions to the Annual Energy Outlook 2006  

Gasoline and Diesel Fuel Update (EIA)

6) 6) Release date: March 2006 Next release date: March 2007 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Natural Gas Transmission and Distribution Module. . . . . . . . . . . . . . . . . . . . . . 101 Petroleum Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Coal Market Module

69

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).

70

Modules Whose Lattice of Submodules is Distributive  

Science Journals Connector (OSTI)

......Then (A + B)nC = (A + B)*-1 = Aoc^ + B*-1 = {AnC) + (BnC). (i...ofaD module M and a G End M. (i) IfA+Aoc = B + Boc, then A = B. (i)' If A n...proposition, A = {A + AAoc)*-1 = {B + Boc) n{B + Boc......

W. Stephenson

1974-03-01T23:59:59.000Z

71

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

72

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

73

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

74

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

75

The joint probability distributions of structure-factor doublets in displacive incommensurately modulated structures and their applicability to direct methods  

Science Journals Connector (OSTI)

The joint probability distribution of the phase sum of two first-order satellite reflections in structures with an incommensurately displacive modulation is derived under the assumption that the phase of the associated main reflection can be calculated from the known main (or averaged) structure. The functional (dis-)similarities with conventional direct methods, employing normalized structure factors and the Cochran distribution, are assessed and test results are presented showing a significant improvement of the direct-methods phase-sum statistics when the new distribution is used.

Peschar, R.

2001-06-21T23:59:59.000Z

76

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

77

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).

78

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

79

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.

80

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

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While these samples are representative of the content of NLEBeta,
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We encourage you to perform a real-time search of NLEBeta
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81

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

82

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).

83

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

84

Key Assumptions Policy Issues  

E-Print Network [OSTI]

11/13/2014 1 Key Assumptions and Policy Issues RAAC Steering Committee November 17, 2014 Portland Supply Limitations 8 Withi h B l i8. Within-hour Balancing 9. Capacity and Energy Values for Wind/Solar t b it d d li d· Thermal: must be sited and licensed · Wind/solar: must be sited and licensed · EE

85

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

86

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.

87

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.

88

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

89

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

90

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

91

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.

92

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.

93

Coal Market Module This  

Gasoline and Diesel Fuel Update (EIA)

51 51 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 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 2012, DOE/EIA-M060(2012) (Washington, DC, 2012). 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-one separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations

94

Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 153 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 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 2011, DOE/EIA-M060(2011) (Washington, DC, 2011). 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-one separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations

95

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

96

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. 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(2003), (Washington, DC, February 2003). 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 gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers.

97

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.

98

Section 25: Future State Assumptions  

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

the Compliance Certification Application (CCA), Chapter 6.0, Section 6.2 and Appendices SCR and MASS (U.S. DOE 1996). Many of these future state assumptions were derived from the...

99

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.

100

A 10 GS/s Distributed Waveform Generator for Sub-Nanosecond Pulse Generation and Modulation in Standard Digital CMOS  

E-Print Network [OSTI]

A 10 GS/s Distributed Waveform Generator for Sub-Nanosecond Pulse Generation and Modulation, Email:hwu@ece.rochester.edu Abstract-- A distributed waveform generator is presented for sub a distributed waveform generator (DWG) circuit in a time-interleaved architecture suitable for standard CMOS

Wu, Hui

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


101

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).

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

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

104

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).

105

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).

106

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).

107

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).

108

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).

109

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.

110

Automated Data Collection for Determining Statistical Distributions of Module Power Undergoing Potential-Induced Degradation: Preprint  

SciTech Connect (OSTI)

We propose a method for increasing the frequency of data collection and reducing the time and cost of accelerated lifetime testing of photovoltaic modules undergoing potential-induced degradation (PID). This consists of in-situ measurements of dark current-voltage curves of the modules at elevated stress temperature, their use to determine the maximum power at 25 degrees C standard test conditions (STC), and distribution statistics for determining degradation rates as a function of stress level. The semi-continuous data obtained by this method clearly show degradation curves of the maximum power, including an incubation phase, rates and extent of degradation, precise time to failure, and partial recovery. Stress tests were performed on crystalline silicon modules at 85% relative humidity and 60 degrees C, 72 degrees C, and 85 degrees C. Activation energy for the mean time to failure (1% relative) of 0.85 eV was determined and a mean time to failure of 8,000 h at 25 degrees C and 85% relative humidity is predicted. No clear trend in maximum degradation as a function of stress temperature was observed.

Hacke, P.; Spataru, S.

2014-08-01T23:59:59.000Z

111

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.

112

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

113

Beam energy distribution influences on density modulation efficiency in seeded free-electron lasers  

E-Print Network [OSTI]

The beam energy spread at the entrance of undulator system is of paramount importance for efficient density modulation in high-gain seeded free-electron lasers (FELs). In this paper, the dependences of high harmonic micro-bunching in the high-gain harmonic generation (HGHG), echo-enabled harmonic generation (EEHG) and phase-merging enhanced harmonic generation (PEHG) schemes on the electron energy spread distribution are studied. Theoretical investigations and multi-dimensional numerical simulations are applied to the cases of uniform and saddle beam energy distributions and compared to a traditional Gaussian distribution. It shows that the uniform and saddle electron energy distributions significantly enhance the performance of HGHG-FELs, while they almost have no influence on EEHG and PEHG schemes. A numerical example demonstrates that, with about 84keV RMS uniform and/or saddle slice energy spread, the 30th harmonic radiation can be directly generated by a single-stage seeding scheme for a soft x-ray FEL f...

Wang, Guanglei; Deng, Haixiao; Zhang, Weiqing; Wu, Guorong; Dai, Dongxu; Wang, Dong; Zhao, Zhentang; Yang, Xueming

2015-01-01T23:59:59.000Z

114

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

115

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.

116

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,

117

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

118

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

119

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].

120

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

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121

Model documentation coal market module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the approaches used in developing the Annual Energy Outlook 1995 (AEO95). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of the coal market module`s three submodules. These are the Coal Production Submodule (CPS), the Coal Export Submodule (CES), the Coal Expert Submodule (CES), and the Coal Distribution Submodule (CDS).

NONE

1995-03-01T23:59:59.000Z

122

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.

123

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

124

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.

125

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

126

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

127

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.

128

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.

129

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),

130

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

131

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

132

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

133

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.

134

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.

135

Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

1 1 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze crude oil and natural gas exploration and development on a regional basis (Figure 8). 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[1], 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(2011), (Washington, DC, 2011). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum

136

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.

137

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.

138

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

139

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.

140

Assumptions to the Annual Energy Outlook 2002 - Natural Gas Transmission  

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

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


141

Assumptions to the Annual Energy Outlook 2001 - Natural Gas Transmission  

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

142

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.

143

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

144

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

145

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

146

Climate Action Planning Tool Formulas and Assumptions  

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

147

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.

148

DNA search efficiency is modulated by charge composition and distribution in the intrinsically disordered tail  

Science Journals Connector (OSTI)

...the charges on the tail, ?r?, calculated as {sigma}ri...along the tail. Values of ?r? range from 01, where a value of zero indicates that...3 14 . 13 Tran HT Mao A Pappu RV ( 2008 ) Role of backbone-solvent...Crick SL Vitalis A Chicoine CL Pappu RV ( 2010 ) Net charge per residue modulates...

Dana Vuzman; Yaakov Levy

2010-01-01T23:59:59.000Z

149

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.

150

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

151

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module 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(2003), (Washington, DC, January 2003).

152

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network [OSTI]

Preliminary Assumptions for Natural Gas Peaking Technologies Gillian Charles and Steve Simmons GRAC, Reciprocating Engines Next steps 2 #12;Definitions Baseload Energy: power generated (or conserved) across a period of time to serve system demands for electricity Peaking Capacity: capability of power generating

153

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network [OSTI]

Preliminary Assumptions for Natural Gas Peaking Technologies Gillian Charles GRAC 2/27/14 #12;Today Vernon, WA PSE Klamath Generation Peakers June 2002 (2) 54 MW P&W FT8 Twin- pac 95 MW Klamath, OR IPP; winter-only PPA w/ PSE Dave Gates Generating Station Jan 2011 (3) P&W SWIFTPAC 150 MW Anaconda, MT North

154

Empirically Revisiting the Test Independence Assumption  

E-Print Network [OSTI]

Empirically Revisiting the Test Independence Assumption Sai Zhang, Darioush Jalali, Jochen Wuttke}@cs.washington.edu ABSTRACT In a test suite, all the test cases should be independent: no test should affect any other test's result, and running the tests in any order should produce the same test results. Techniques such as test

Ernst, Michael

155

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.

156

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

157

Frequency stabilization of an InGaAsP distributed feedback laser to an NH/sub 3/ absorption line at 15137 A with an external frequency modulator  

SciTech Connect (OSTI)

The oscillation frequency of a 1.5-..mu..m InGaAsP distributed feedback laser is stabilized to an NH/sub 3/ linear absorption line at 15137 A. A LiNbO/sub 3/ external frequency modulator is used instead of direct frequency modulation of the laser to extract error signals. An effective bandwidth of 100 kHz for the feedback loop is obtained through this external modulation scheme. Frequency stability of sigma(2,tau) = 4 x 10/sup -11/ is achieved for an averaging time of 1 s< or =tau< or =100 s.

Yanagawa, T.; Saito, S.; Machida, S.; Yamamoto, Y.; Noguchi, Y.

1985-11-15T23:59:59.000Z

158

Model documentation Coal Market Module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents objectives and conceptual and methodological approach used in the development of the National Energy Modeling System (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1996 (AEO96). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s three submodules: Coal Production Submodule, Coal Export Submodule, and Coal Distribution Submodule.

NONE

1996-04-30T23:59:59.000Z

159

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

160

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

Note: This page contains sample records for the topic "distribution module assumption" 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

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

162

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.

163

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

164

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.

165

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 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 20). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated by using the SEDS24 data. The energy-intensive industries (food and kindred products, paper and allied products, bulk chemicals, glass and glass products, hydraulic cement, blast furnace and basic steel products, and aluminum) are modeled in considerable detail. Each industry is modeled as three separate but interrelated components consisting of the Process Assembly (PA) Component, the Buildings Component (BLD), and the Boiler/Steam/Cogenera- tion (BSC) Component. The BSC Component satisfies the steam demand from the PA and BLD Components. In some industries, the PA Component produces byproducts that are consumed in the BSC Component. For the manufacturing industries, the PA Component is separated into the major production processes or end uses.

166

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.

167

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

168

Assumptions to the Annual Energy Outlook 2013  

Gasoline and Diesel Fuel Update (EIA)

for EIA (SENTECH Incorporated, 2010). Wind: The Cost and Performance of Distributed Wind Turbines, 2010-35 (ICF International, 2010). 31 U.S. Energy Information Administration |...

169

Manufacturing Energy and Carbon Footprint Definitions and Assumptions, October 2012  

Broader source: Energy.gov [DOE]

Definitions of parameters and table of assumptions for the Manufacturing Energy and Carbon Footprint

170

Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

171

Assumptions to the Annual Energy Outlook 2013  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

and U.S. Energy Information Administration, The Cost and Performance of Distributed Wind Turbines, 2010-35 Final Report, ICF International, August 2010. 43 U.S. Energy Information...

172

On the use of computed radiography plates for quality assurance of intensity modulated radiation therapy dose distributions  

SciTech Connect (OSTI)

Purpose: As traditional film is phased out in most radiotherapy centers, computed radiography (CR) systems are increasingly being purchased as a replacement. CR plates can be used for patient imaging, but may also be used for a variety of quality assurance (QA) purposes and can be calibrated in terms of dose. This study looks at their suitability for verification of intensity modulated radiation therapy (IMRT) dose distributions. Methods: A CR plate was calibrated in terms of the relative dose and the stability of response over 1 year was studied. The effect of exposing the CR plate to ambient light and of using different time delays before scanning was quantified. The CR plate was used to verify the relative dose distributions for ten IMRT patients and the results were compared to those obtained using a two dimensional (2D) diode array. Results: Exposing the CR plate to 10 s of ambient light between irradiation (174 cGy) and scanning erased approximately 80% of the signal. Changes in delay time between irradiation and scanning also affected the measurement results. The signal on the plate was found to decay at a rate of approximately 3.6 cGy/min in the first 10 min after irradiation. The use of a CR plate for IMRT patient-specific QA resulted in a significantly lower distance to agreement (DTA) and gamma pass rate than when using a 2D diode array for the measurement. This was primarily due to the over-response of the CR phosphor to low energy scattered radiation. For the IMRT QA using the CR plate, the average gamma pass rate was 97.3%. For the same IMRT QA using a diode array, the average gamma pass rate was 99.7%. The gamma criteria used were 4% dose difference and 4 mm DTA for head and neck treatments and 3% dose difference and 3 mm DTA for prostate treatments. The gamma index tolerance was 1. The lowest 10% of the dose distribution was excluded from all gamma and DTA analyses. Conclusions: Although the authors showed that CR plates can be used for patient specific IMRT QA, the practical problems such as the over-response to low energy scatter and signal fading with light exposure and time mean that alternative detectors such as radiochromic film or diode arrays will be a more sensible choice for most radiotherapy departments.

Day, R. A.; Sankar, A. P.; Nailon, W. H.; MacLeod, A. S. [Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU (United Kingdom)

2011-02-15T23:59:59.000Z

173

2010 Manufacturing Energy and Carbon Footprints: Definitions and Assumptions  

Broader source: Energy.gov [DOE]

This 13-page document provides definitions and assumptions used in the Manufacturing Energy and Carbon Footprints (MECS 2010)

174

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

175

Electricity Market Module  

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

Market Module Market Module This page inTenTionally lefT blank 101 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 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, electricity load and demand, 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 2013, DOE/EIA-M068(2013). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

176

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.

177

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

178

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

179

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 51 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing 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 procedure, whereas the non- manufacturing industries are modeled with substantially less detail. The petroleum refining industry is not included in the Industrial Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Module calculates

180

MONITORED GEOLOGIC REPOSITORY LIFE CYCLE COST ESTIMATE ASSUMPTIONS DOCUMENT  

SciTech Connect (OSTI)

The purpose of this assumptions document is to provide general scope, strategy, technical basis, schedule and cost assumptions for the Monitored Geologic Repository (MGR) life cycle cost (LCC) estimate and schedule update incorporating information from the Viability Assessment (VA) , License Application Design Selection (LADS), 1999 Update to the Total System Life Cycle Cost (TSLCC) estimate and from other related and updated information. This document is intended to generally follow the assumptions outlined in the previous MGR cost estimates and as further prescribed by DOE guidance.

R.E. Sweeney

2001-02-08T23:59:59.000Z

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


181

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

182

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

183

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

184

Idaho National Engineering Laboratory installation roadmap assumptions document. Revision 1  

SciTech Connect (OSTI)

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

185

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page inTenTionally lefT blank 91 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 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, electricity load and demand, 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 2012, DOE/EIA-M068(2012). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

186

Liquid Fuels Market Module  

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

Liquid Fuels Market Module Liquid Fuels Market Module This page inTenTionally lefT blank 145 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Liquid Fuels Market Module The NEMS Liquid Fuels Market Module (LFMM) 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, esters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the LFMM projects capacity expansion and fuel consumption at domestic refineries. The LFMM contains a linear programming (LP) representation of U.S. petroleum refining

187

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 95 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 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, electricity load and demand, 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 2011, DOE/EIA-M068(2011). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

188

Renewable Fuels Module This  

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

Fuels Module Fuels Module This page inTenTionally lefT blank 175 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 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 wind [1]. 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

189

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 23 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 International Energy Module The NEMS 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 NEMS IEM computes world oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into

190

Assumptions to the Annual Energy Outlook 2001 - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module 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

191

COMPARING ALASKA'S OIL PRODUCTION TAXES: INCENTIVES AND ASSUMPTIONS1  

E-Print Network [OSTI]

1 COMPARING ALASKA'S OIL PRODUCTION TAXES: INCENTIVES AND ASSUMPTIONS1 Matthew Berman In a recent analysis comparing the current oil production tax, More Alaska Production Act (MAPA, also known as SB 21 oil prices, production rates, and costs. He noted that comparative revenues are highly sensitive

Pantaleone, Jim

192

Reasoning by Assumption: Formalisation and Analysis of Human Reasoning Traces  

E-Print Network [OSTI]

for the traces acquired in experiments undertaken. 1 Introduction Practical reasoning processes are often not limited to single reasoning steps, but extend to traces or trajectories of a number of interrelated by assumption'. This (non-deductive) practical reasoning pattern in- volves a number of interrelated reasoning

Treur, Jan

193

Interplay effects between dose distribution quality and positioning accuracy in total marrow irradiation with volumetric modulated arc therapy  

SciTech Connect (OSTI)

Purpose: To evaluate the dosimetric consequences of inaccurate isocenter positioning during treatment of total marrow (lymph-node) irradiation (TMI-TMLI) using volumetric modulated arc therapy (VMAT).Methods: Four patients treated with TMI and TMLI were randomly selected from the internal database. Plans were optimized with VMAT technique. Planning target volume (PTV) included all the body bones; for TMLI, lymph nodes and spleen were considered into the target, too. Dose prescription to PTV was 12 Gy in six fractions, two times per day for TMI, and 2 Gy in single fraction for TMLI. Ten arcs on five isocenters (two arcs for isocenter) were used to cover the upper part of PTV (i.e., from cranium to middle femurs). For each plan, three series of random shifts with values between ?3 and +3 mm and three between ?5 and +5 mm were applied to the five isocenters simulating involuntary patient motion during treatment. The shifts were applied separately in the three directions: leftright (L-R), anteriorposterior (A-P), and cranialcaudal (C-C). The worst case scenario with simultaneous random shifts in all directions simultaneously was considered too. Doses were recalculated for the 96 shifted plans (24 for each patient).Results: For all shifts, differences <0.5% were found for mean doses to PTV, body, and organs at risk with volumes >100 cm{sup 3}. Maximum doses increased up to 15% for C-C shifted plans. PTV covered by the 95% isodose decreased of 2%8% revealing target underdosage with the highest values in C-C direction.Conclusions: The correct isocenter repositioning of TMI-TMLI patients is fundamental, in particular in C-C direction, in order to avoid over- and underdosages especially in the overlap regions. For this reason, a dedicated immobilization system was developed in the authors' center to best immobilize the patient.

Mancosu, Pietro; Navarria, Piera; Reggiori, Giacomo; Tomatis, Stefano; Alongi, Filippo; Scorsetti, Marta [Department of Radiation Oncology, Humanitas Clinical and Research Center, Rozzano, Milan 20089 (Italy)] [Department of Radiation Oncology, Humanitas Clinical and Research Center, Rozzano, Milan 20089 (Italy); Castagna, Luca; Sarina, Barbara [Bone Marrow Transplantation Unit, Humanitas Clinical and Research Center, Rozzano, Milan 20089 (Italy)] [Bone Marrow Transplantation Unit, Humanitas Clinical and Research Center, Rozzano, Milan 20089 (Italy); Nicolini, Giorgia; Fogliata, Antonella; Cozzi, Luca [Medical Physics Unit, Oncology Institute of Southern Switzerland, Bellinzona 6500 (Switzerland)] [Medical Physics Unit, Oncology Institute of Southern Switzerland, Bellinzona 6500 (Switzerland)

2013-11-15T23:59:59.000Z

194

Distribution:  

Office of Legacy Management (LM)

JAN26 19% JAN26 19% Distribution: OR00 Attn: h.H.M.Roth DFMusser ITMM MMMann INS JCRyan FIw(2) Hsixele SRGustavson, Document rocm Formal file i+a@mmm bav@ ~@esiaw*cp Suppl. file 'Br & Div rf's s/health (lic.only) UNITED STATES ATOMIC ENERGY COMMISSION SPECIAL NUCLEAB MATERIAL LICENSE pursuant to the Atomic Energy Act of 1954 and Title 10, Code of Federal Regulations, Chapter 1, P&t 70, "Special Nuclear Material Reg)llatiqm," a license is hereby issued a$hortztng the licensee to rekeive and possess the special nuclear material designated below; to use such special nuclear mat&ial for the purpose(s) and at the place(s) designated below; and to transfer such material to per&s authorized to receive it in accordance with the regula,tions in said Part.

195

Assumptions to the Annual Energy Outlook 2002 - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

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

196

Assumptions to the Annual Energy Outlook 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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, (Washington, DC, February 1994), plus Macroeconomic Activity Module (MAM): Kernel Regression Documentation of the National Energy Modeling System 1999, DOE/EIA-M065(99), Washington, DC, 1999).

197

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads 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

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  

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

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

Cost and Performance Assumptions for Modeling Electricity Generation Technologies  

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

Note: This page contains sample records for the topic "distribution module assumption" 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 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

202

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.

203

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.

204

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.

205

Macroeconomic Activity Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 19 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook2011 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.

206

Assumptions to the Annual Energy Outlook 1999 - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

macroeconomic.gif (5367 bytes) macroeconomic.gif (5367 bytes) 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, (Washington, DC, February 1994).

207

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.

208

Diversion assumptions for high-powered research reactors  

SciTech Connect (OSTI)

This study deals with diversion assumptions for high-powered research reactors -- specifically, MTR fuel; pool- or tank-type research reactors with light-water moderator; and water, beryllium, or graphite reflectors, and which have a power level of 25 MW(t) or more. The objective is to provide assistance to the IAEA in documentation of criteria and inspection observables related to undeclared plutonium production in the reactors described above, including: criteria for undeclared plutonium production, necessary design information for implementation of these criteria, verification guidelines including neutron physics and heat transfer, and safeguards measures to facilitate the detection of undeclared plutonium production at large research reactors.

Binford, F.T.

1984-01-01T23:59:59.000Z

209

Oil and Gas Supply Module  

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

Oil and Gas Supply Module Oil and Gas Supply Module This page inTenTionally lefT blank 119 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze crude oil and natural gas exploration and development on a regional basis (Figure 8). 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[1], 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(2011), (Washington, DC, 2011). The OGSM provides

210

PDSF Modules  

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

Modules Modules Modules Modules Approach to Managing The Environment Modules is a system which you can use to specify what software you want to use. If you want to use a particular software package loading its module will take care of the details of modifying your environment as necessary. The advantage of the modules approach is that the you are not required to explicitly specify paths for different executable versions and try to keep their related man paths and environment variables coordinated. Instead you simply "load" and "unload" specific modules to control your environment. Getting Started with Modules If you're using the standard startup files on PDSF then you're already setup for using modules. If the "module" command is not available, please

211

The contour method cutting assumption: error minimization and correction  

SciTech Connect (OSTI)

The recently developed contour method can measure 2-D, cross-sectional residual-stress map. A part is cut in two using a precise and low-stress cutting technique such as electric discharge machining. The contours of the new surfaces created by the cut, which will not be flat if residual stresses are relaxed by the cutting, are then measured and used to calculate the original residual stresses. The precise nature of the assumption about the cut is presented theoretically and is evaluated experimentally. Simply assuming a flat cut is overly restrictive and misleading. The critical assumption is that the width of the cut, when measured in the original, undeformed configuration of the body is constant. Stresses at the cut tip during cutting cause the material to deform, which causes errors. The effect of such cutting errors on the measured stresses is presented. The important parameters are quantified. Experimental procedures for minimizing these errors are presented. An iterative finite element procedure to correct for the errors is also presented. The correction procedure is demonstrated on experimental data from a steel beam that was plastically bent to put in a known profile of residual stresses.

Prime, Michael B [Los Alamos National Laboratory; Kastengren, Alan L [ANL

2010-01-01T23:59:59.000Z

212

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

6, DOE/EIA- 6, 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. EMM Regions The supply regions used in EMM are based on the North American Electric Reliability Council regions and

213

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. 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

214

Lack of Osteoradionecrosis of the Mandible After Intensity-Modulated Radiotherapy for Head and Neck Cancer: Likely Contributions of Both Dental Care and Improved Dose Distributions  

SciTech Connect (OSTI)

Purpose: To assess the prevalence and dosimetric and clinical predictors of mandibular osteoradionecrosis (ORN) in patients with head and neck cancer who underwent a pretherapy dental evaluation and prophylactic treatment according to a uniform policy and were treated with intensity-modulated radiotherapy (IMRT). Methods and Materials: Between 1996 and 2005, all patients with head-and-neck cancer treated with parotid gland-sparing IMRT in prospective studies underwent a dental examination and prophylactic treatment according to a uniform policy that included extractions of high-risk, periodontally involved, and nonrestorable teeth in parts of the mandible expected to receive high radiation doses, fluoride supplements, and the placement of guards aiming to reduce electron backscatter off metal teeth restorations. The IMRT plans included dose constraints for the maximal mandibular doses and reduced mean parotid gland and noninvolved oral cavity doses. A retrospective analysis of Grade 2 or worse (clinical) ORN was performed. Results: A total of 176 patients had a minimal follow-up of 6 months. Of these, 31 (17%) had undergone teeth extractions before RT and 13 (7%) after RT. Of the 176 patients, 75% and 50% had received {>=}65 Gy and {>=}70 Gy to {>=}1% of the mandibular volume, respectively. Falloff across the mandible characterized the dose distributions: the average gradient (in the axial plane containing the maximal mandibular dose) was 11 Gy (range, 1-27 Gy; median, 8 Gy). At a median follow-up of 34 months, no cases of ORN had developed (95% confidence interval, 0-2%). Conclusion: The use of a strict prophylactic dental care policy and IMRT resulted in no case of clinical ORN. In addition to the dosimetric advantages offered by IMRT, meticulous dental prophylactic care is likely an essential factor in reducing ORN risk.

Ben-David, Merav A. [Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI (United States); Diamante, Maximiliano [Department of Oral and Maxillofacial Surgery/Hospital Dentistry, University of Michigan Medical School, Ann Arbor, MI (United States); Radawski, Jeffrey D. [Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI (United States); Vineberg, Karen A. [Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI (United States); Stroup, Cynthia [Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI (United States); Murdoch-Kinch, Carol-Anne [Department of Oral and Maxillofacial Surgery/Hospital Dentistry, University of Michigan Medical School, Ann Arbor, MI (United States); Zwetchkenbaum, Samuel R. [Department of Oral and Maxillofacial Surgery/Hospital Dentistry, University of Michigan Medical School, Ann Arbor, MI (United States); Eisbruch, Avraham [Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI (United States)]. E-mail: eisbruch@med.umich.edu

2007-06-01T23:59:59.000Z

215

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

216

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

217

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).

218

Natural Gas Transmission and Distribution Model of the National Energy Modeling System. Volume 1  

SciTech Connect (OSTI)

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. Subsequent chapters of this report provide: an overview of NGTDM; a description of the interface between the NEMS and NGTDM; an overview of the solution methodology of the NGTDM; the solution methodology for the Annual Flow Module; the solution methodology for the Distributor Tariff Module; the solution methodology for the Capacity Expansion Module; the solution methodology for the Pipeline Tariff Module; and a description of model assumptions, inputs, and outputs.

NONE

1998-01-01T23:59:59.000Z

219

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 39 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 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.

220

Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 137 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 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. The PMM contains a linear programming (LP) representation of U.S. refining activities in the five Petroleum Administration for

Note: This page contains sample records for the topic "distribution module assumption" 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

Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 167 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 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 wind [1]. 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

222

Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page inTenTionally lefT blank 135 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 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, esters, 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 activities in the five Petroleum Administration for

223

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 International Energy Module The NEMS 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 NEMS IEM computes oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into the United States by export region. Changes in the oil price (WTI), which is defined as the price of light, low-sulfur crude oil delivered to Cushing, Oklahoma in

224

Assumptions to the Annual Energy Outlook 2014 - Abbreviations  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

CO 2: Carbon dioxide CO 2 -EOR: Carbon dioxide-enhanced oil recovery CSAPR: Cross-State Air Pollution Rule CTL: Coal-to-liquids DG: Distributed generation DGE: Diesel gallon...

225

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.

226

Linking species abundance distributions in numerical abundance and biomass through simple assumptions about community structure  

Science Journals Connector (OSTI)

...typically recorded. Biomass is an alternative...of resource use; energy flow is correlated...that the same total energy flux would support a larger biomass of a large bodied...by a decrease in biomass, community energy use remained approximately...

2010-01-01T23:59:59.000Z

227

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

228

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,

229

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.

230

Testing assumptions and predictions of star formation theories  

Science Journals Connector (OSTI)

......are uncommon also in driven, MHD supersonic, isothermal turbulent...whether this result persists in the MHD case. As in Paper I, we subdivide...distribution of points in this diagram becomes more elongated in the...0.35 to 0.5, the present MHD simulations exhibit a weaker......

Alejandro Gonzlez-Samaniego; Enrique Vzquez-Semadeni; Ricardo F. Gonzlez; Jongsoo Kim

2014-01-01T23:59:59.000Z

231

Module Configuration  

DOE Patents [OSTI]

A stand alone battery module including: (a) a mechanical configuration; (b) a thermal management configuration; (c) an electrical connection configuration; and (d) an electronics configuration. Such a module is fully interchangeable in a battery pack assembly, mechanically, from the thermal management point of view, and electrically. With the same hardware, the module can accommodate different cell sizes and, therefore, can easily have different capacities. The module structure is designed to accommodate the electronics monitoring, protection, and printed wiring assembly boards (PWAs), as well as to allow airflow through the module. A plurality of modules may easily be connected together to form a battery pack. The parts of the module are designed to facilitate their manufacture and assembly.

Oweis, Salah (Ellicott City, MD); D'Ussel, Louis (Bordeaux, FR); Chagnon, Guy (Cockeysville, MD); Zuhowski, Michael (Annapolis, MD); Sack, Tim (Cockeysville, MD); Laucournet, Gaullume (Paris, FR); Jackson, Edward J. (Taneytown, MD)

2002-06-04T23:59:59.000Z

232

On the self-similarity assumption in dynamic models for large eddy simulations  

E-Print Network [OSTI]

that the present formulation of the DP is usually incompatible with its under- lying self-similarity assumption SSAOn the self-similarity assumption in dynamic models for large eddy simulations Daniele Carati eddy simulations and their underlying self-similarity assumption is discussed. The interpretation

Van Den Eijnden, Eric

233

Preliminary Thermal Modeling of HI-STORM 100 Storage Modules at Diablo Canyon Power Plant ISFSI  

SciTech Connect (OSTI)

Thermal analysis is being undertaken at Pacific Northwest National Laboratory (PNNL) in support of inspections of selected storage modules at various locations around the United States, as part of the Used Fuel Disposition Campaign of the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) Fuel Cycle Research and Development. This report documents pre-inspection predictions of temperatures for two modules at the Diablo Canyon Power Plant ISFSI identified as candidates for inspection. These are HI-STORM 100 modules of a site-specific design for storing PWR 17x17 fuel in MPC-32 canisters. The temperature predictions reported in this document were obtained with detailed COBRA-SFS models of these storage systems, with the following boundary conditions and assumptions. storage module overpack configuration based on FSAR documentation of HI-STORM100S-218, Version B; due to unavailability of site-specific design data for Diablo Canyon ISFSI modules Individual assembly and total decay heat loadings for each canister, based on at-loading values provided by PG&E, aged to time of inspection using ORIGEN modeling o Special Note: there is an inherent conservatism of unquantified magnitude informally estimated as up to approximately 20% -- in the utility-supplied values for at-loading assembly decay heat values Axial decay heat distributions based on a bounding generic profile for PWR fuel. Axial location of beginning of fuel assumed same as WE 17x17 OFA fuel, due to unavailability of specific data for WE17x17 STD and WE 17x17 Vantage 5 fuel designs Ambient conditions of still air at 50F (10C) assumed for base-case evaluations o Wind conditions at the Diablo Canyon site are unquantified, due to unavailability of site meteorological data o additional still-air evaluations performed at 70F (21C), 60F (16C), and 40F (4C), to cover a range of possible conditions at the time of the inspection. (Calculations were also performed at 80F (27C), for comparison with design basis assumptions.) All calculations are for steady-state conditions, on the assumption that the surfaces of the module that are accessible for temperature measurements during the inspection will tend to follow ambient temperature changes relatively closely. Comparisons to the results of the inspections, and post-inspection evaluations of temperature measurements obtained in the specific modules, will be documented in a separate follow-on report, to be issued in a timely manner after the inspection has been performed.

Cuta, Judith M.; Adkins, Harold E.

2014-04-17T23:59:59.000Z

234

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

4 4 The commercial module forecasts consumption by fuel 15 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 16 for eleven building categories 17 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

235

Permanent polarization and charge distribution in organic light-emitting diodes (OLEDs): Insights from near-infrared charge-modulation spectroscopy of an operating OLED  

SciTech Connect (OSTI)

Vapor-deposited Alq{sub 3} layers typically possess a strong permanent electrical polarization, whereas NPB layers do not. (Alq{sub 3} is tris(8-quinolinolato)aluminum(III); NPB is 4,4?-bis[N-(1-naphthyl)-N-phenylamino]biphenyl.) The cause is a net orientation of the Alq{sub 3} molecules with their large dipole moments. Here we report on consequences for an organic light-emitting diode (OLED) with an NPB hole-transport layer and Alq{sub 3} electron-transport layer. The discontinuous polarization at the NPB|Alq{sub 3} interface has the same effect as a sheet of immobile negative charge there. It is more than compensated by a large concentration of injected holes (NPB{sup +}) when the OLED is running. We discuss the implications and consequences for the quantum efficiency and the drive voltage of this OLED and others. We also speculate on possible consequences of permanent polarization in organic photovoltaic devices. The concentration of NPB{sup +} was measured by charge-modulation spectroscopy (CMS) in the near infrared, where the NPB{sup +} has a strong absorption band, supplemented by differential-capacitance and current-voltage measurements. Unlike CMS in the visible, this method avoids complications from modulation of the electroluminescence and electroabsorption.

Marchetti, Alfred P.; Haskins, Terri L.; Young, Ralph H.; Rothberg, Lewis J. [Department of Chemistry, University of Rochester, Rochester, New York 14627 (United States)

2014-03-21T23:59:59.000Z

236

Thermal Modeling Studies for Active Storage Modules in the Calvert Cliffs ISFSI  

SciTech Connect (OSTI)

Temperature measurements obtained for two storage modules in the Calvert Cliffs Nuclear Power Stations Independent Spent Fuel Storage Installation (ISFSI) as part of the Used Fuel Disposition Campaign of the Department of Energy (DOE) were used to perform validation and sensitivity studies on detailed computational fluid dynamics (CFD) models of the concrete storage modules, including the dry storage canister within the modules. The storage modules in the Calvert Cliffs Nuclear Power Stations ISFSI are a site-specific version of the standard NUHOMS HSM. The two modules inspected each contained a 24P DSC loaded with 24 CE 14x14 spent fuel assemblies. The thermal analysis was performed using the STAR-CCM+ package, and the models developed for the specific ISFSI modules yielded temperature predictions in actual storage conditions for the concrete structure, the DSC and its contents, including preliminary estimates of fuel cladding temperatures for the used nuclear fuel. The results of this work demonstrate that existing CFD modeling tools can be used to obtain reasonable and accurate detailed representations of spent fuel storage systems with realistic decay heat loadings when the model omits specific conservatisms and bounding assumptions normally used in design-basis and safety-basis calculations. This paper presents sensitivity studies on modeling detail (for the storage module and the DSC), boundary conditions, and decay heat load, to evaluate the effect of the modeling approach on predicted temperatures and temperature distributions. Because nearly all degradation mechanisms for materials and structures comprising dry storage and transportation systems are dependent on temperature, accurate characterization of local temperatures and temperature gradients that the various components of these systems will experience over the entire storage period has been identified as a primary requirement for evaluation of very long term storage of used nuclear fuel.

Adkins, Harold E.; Fort, James A.; Suffield, Sarah R.; Cuta, Judith M.; Collins, Brian A.

2013-06-14T23:59:59.000Z

237

OIKOS 101: 499504, 2003 Do seedlings in gaps interact? A field test of assumptions in ESS  

E-Print Network [OSTI]

OIKOS 101: 499­504, 2003 Do seedlings in gaps interact? A field test of assumptions in ESS seed seedlings in gaps interact? A field test of assumptions in ESS seed size models. ­ Oikos 101: 499­504. ESS for the occupancy of `safe sites' or vegetation gaps. If mortality rates are high and/or frequency-independent, ESS

Silvertown, Jonathan

238

Granular Matter 4(3) (2002) How good is the equipartition assumption for the transport  

E-Print Network [OSTI]

Granular Matter 4(3) (2002) How good is the equipartition assumption for the transport properties of a granular mixture? Meheboob Alam (1) , Stefan Luding (1;2) ? Abstract Kinetic-theory, with the assumption of equipar- tition of granular energy, suggests that the pressure and viscosity of a granular mixture vary

Luding, Stefan

239

A new scenario framework for climate change research: The concept of Shared Climate Policy Assumptions  

SciTech Connect (OSTI)

The paper presents the concept of shared climate policy assumptions as an important element of the new scenario framework. Shared climate policy assumptions capture key climate policy dimensions such as the type and scale of mitigation and adaptation measures. They are not specified in the socio-economic reference pathways, and therefore introduce an important third dimension to the scenario matrix architecture. Climate policy assumptions will have to be made in any climate policy scenario, and can have a significant impact on the scenario description. We conclude that a meaningful set of shared climate policy assumptions is useful for grouping individual climate policy analyses and facilitating their comparison. Shared climate policy assumptions should be designed to be policy relevant, and as a set to be broad enough to allow a comprehensive exploration of the climate change scenario space.

Kriegler, Elmar; Edmonds, James A.; Hallegatte, Stephane; Ebi, Kristie L.; Kram, Tom; Riahi, Keywan; Winkler, Harald; Van Vuuren, Detlef

2014-04-01T23:59:59.000Z

240

Model documentation, Renewable Fuels Module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the Annual Energy Outlook 1998 (AEO98) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. For AEO98, the RFM was modified in three principal ways, introducing capital cost elasticities of supply for new renewable energy technologies, modifying biomass supply curves, and revising assumptions for use of landfill gas from municipal solid waste (MSW). In addition, the RFM was modified in general to accommodate projections beyond 2015 through 2020. Two supply elasticities were introduced, the first reflecting short-term (annual) cost increases from manufacturing, siting, and installation bottlenecks incurred under conditions of rapid growth, and the second reflecting longer term natural resource, transmission and distribution upgrade, and market limitations increasing costs as more and more of the overall resource is used. Biomass supply curves were also modified, basing forest products supplies on production rather than on inventory, and expanding energy crop estimates to include states west of the Mississippi River using information developed by the Oak Ridge National Laboratory. Finally, for MSW, several assumptions for the use of landfill gas were revised and extended.

NONE

1998-01-01T23:59:59.000Z

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


241

Moldy Assumptions  

E-Print Network [OSTI]

sustainability movements. 2 Despite these noble intentions, using human responsibility as a base for architecture

Heully, Gustave Paul

2012-01-01T23:59:59.000Z

242

CBE UFAD cost analysis tool: Life cycle cost model, issues and assumptions  

E-Print Network [OSTI]

Building Maintenance and Repair Cost Reference. WhitestoneJ. Wallis and H. Lin. 2008. CBE UFAD Cost Analysis Tool:UFAD First Cost Model, Issues and Assumptions. Center for

Webster, Tom; Benedek, Corinne; Bauman, Fred

2008-01-01T23:59:59.000Z

243

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

Science Journals Connector (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

244

Behavioral Assumptions Underlying California Residential Sector Energy Efficiency Programs (2009 CIEE Report)  

Broader source: Energy.gov [DOE]

This paper examines the behavioral assumptions that underlie Californias residential sector energy efficiency programs and recommends improvements that will help to advance the states ambitious greenhouse gas reduction goals.

245

Length measurement of a moving rod by a single observer without assumptions concerning its magnitude  

E-Print Network [OSTI]

We extend the results presented by Weinstein concerning the measurement of the length of a moving rod by a single observer, without making assumptions concerning the distance between the moving rod and the observer who measures its length.

Bernhard Rothenstein; Ioan Damian

2005-07-03T23:59:59.000Z

246

Assumptions about the U.S., the EU, NATO, and their Impact on the Transatlantic Agenda  

Science Journals Connector (OSTI)

I propose in this paper to discuss, from an American perspective, the assumptions and assertions that influence the way that I look at foreign policy events at the end of this decade. I will conclude with a fe...

Stanley Sloan

2000-01-01T23:59:59.000Z

247

Development of Hydrogen Selective Membranes/Modules as Reactors/Separators for Distributed Hydrogen Production - DOE Hydrogen and Fuel Cells Program FY 2012 Annual Progress Report  

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

3 3 FY 2012 Annual Progress Report DOE Hydrogen and Fuel Cells Program Paul KT Liu Media and Process Technology Inc. (M&P) 1155 William Pitt Way Pittsburgh, PA 15238 Phone: (412) 826-3711 Email: pliu@mediaandprocess.com DOE Managers HQ: Sara Dillich Phone: (202) 586-7925 Email: Sara.Dillich@ee.doe.gov GO: Katie Randolph Phone: (720) 356-1759 Email: Katie.Randolph@go.doe.gov Contract Number: DE-FG36-05GO15092 Subcontractor: University of Southern California Project Start Date: July 1, 2005 Projected End Date: December 31, 2012 Fiscal Year (FY) 2012 Objectives The water-gas shift (WGS) reaction becomes less efficient when high CO conversion is required, such as for distributed hydrogen production applications. Our project

248

NEMS Freight Transportation Module Improvement Study  

Reports and Publications (EIA)

The U.S. Energy Information Administration (EIA) contracted with IHS Global, Inc. (IHS) to analyze the relationship between the value of industrial output, physical output, and freight movement in the United States for use in updating analytic assumptions and modeling structure within the National Energy Modeling System (NEMS) freight transportation module, including forecasting methodologies and processes to identify possible alternative approaches that would improve multi-modal freight flow and fuel consumption estimation.

2015-01-01T23:59:59.000Z

249

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

SciTech Connect (OSTI)

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

250

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

SciTech Connect (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

251

A critical evaluation of secondary cancer risk models applied to Monte Carlo dose distributions of 2-dimensional, 3-dimensional conformal and hybrid intensity-modulated radiation therapy for breast cancer  

Science Journals Connector (OSTI)

The comparison of radiotherapy techniques regarding secondary cancer risk has yielded contradictory results possibly stemming from the many different approaches used to estimate risk. The purpose of this study was to make a comprehensive evaluation of different available risk models applied to detailed whole-body dose distributions computed by Monte Carlo for various breast radiotherapy techniques including conventional open tangents, 3D conformal wedged tangents and hybrid intensity modulated radiation therapy (IMRT). First, organ-specific linear risk models developed by the International Commission on Radiological Protection (ICRP) and the Biological Effects of Ionizing Radiation (BEIR) VII committee were applied to mean doses for remote organs only and all solid organs. Then, different general non-linear risk models were applied to the whole body dose distribution. Finally, organ-specific non-linear risk models for the lung and breast were used to assess the secondary cancer risk for these two specific organs. A total of 32 different calculated absolute risks resulted in a broad range of values (between 0.1% and 48.5%) underlying the large uncertainties in absolute risk calculation. The ratio of risk between two techniques has often been proposed as a more robust assessment of risk than the absolute risk. We found that the ratio of risk between two techniques could also vary substantially considering the different approaches to risk estimation. Sometimes the ratio of risk between two techniques would range between values smaller and larger than one, which then translates into inconsistent results on the potential higher risk of one technique compared to another. We found however that the hybrid IMRT technique resulted in a systematic reduction of risk compared to the other techniques investigated even though the magnitude of this reduction varied substantially with the different approaches investigated. Based on the epidemiological data available, a reasonable approach to risk estimation would be to use organ-specific non-linear risk models applied to the dose distributions of organs within or near the treatment fields (lungs and contralateral breast in the case of breast radiotherapy) as the majority of radiation-induced secondary cancers are found in the beam-bordering regions.

A Joosten; F Bochud; R Moeckli

2014-01-01T23:59:59.000Z

252

TOB Module Assembly  

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

SiTracker Home Page Participating Institutions and Principal Contacts Useful Links Notes Images TOB Module Assembly and Testing Project TOB Integration Data Tracker Offline DQM LHC Fluence Calculator Total US Modules Tested Graph Total US Modules Tested Graph Total US Modules Tested Total US Modules Tested US Modules Tested Graph US Modules Tested Graph US Modules Tested US Modules Tested Rod Assembly TOB Modules on a Rod TOB Rod Insertion Installation of a TOB Rod Completed TOB Completed Tracker Outer Barrel TOB Module Assembly and Testing Project All 5208 modules of the CMS Tracker Outer Barrel were assembled and tested at two production sites in the US: the Fermi National Accelerator Laboratory and the University of California at Santa Barbara. The modules were delivered to CERN in the form of rods, with the last shipment taking

253

Calculation Theory of Uniform Distribution in Cleanroom  

Science Journals Connector (OSTI)

Calculation of the dust concentration is the core of the design calculation for cleanroom. The theoretical calculation in this chapter is ... the assumption that particles are uniformly distributed in cleanroom.

Zhonglin Xu

2014-01-01T23:59:59.000Z

254

Campus Recreation at Sonoma State University RELEASE OF LIABILITY -PROMISE NOT TO SUE ASSUMPTION OF  

E-Print Network [OSTI]

Campus Recreation at Sonoma State University RELEASE OF LIABILITY - PROMISE NOT TO SUE ASSUMPTION OF RISK - AGREEMENT TO PAY CLAIMS PERMISSION TO USE VISUAL LIKENESS Activities: a) USE OF SSU RECREATION RECREATION PROGRAMS. Effective Locations and Time Periods: a) RECREATION CENTER: DURING HOURS OF OPERATION

Ravikumar, B.

255

Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric IRT  

E-Print Network [OSTI]

Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric IRT Brian of the monotonicity conditions discussed in Section 4. #12;Abstract In recent years, as cognitive theories of learning" on student achievement relative to theory-driven lists of examinee skills, beliefs and other cognitive

Junker, Brian

256

Draft -F. Nicoud 1 About the zero Mach number assumption in  

E-Print Network [OSTI]

Draft - F. Nicoud 1 About the zero Mach number assumption in the calculation of thermoacoustic as the the flame forcing ('Rayleigh') term. Besides, the net effect of the non zero Mach number terms the frequency of oscillation and growth rate are modified when the Mach number is not zero. It is demonstrated

Nicoud, Franck

257

Models of transcription factor binding: Sensitivity of activation functions to model assumptions  

E-Print Network [OSTI]

on statistical physics, a Markov-chain model and a computational simulation. Comparison of these models suggests for cooperativity. The simulation model suggests that direct interactions between TFs are unlikely to be the main in this contribution, the assumption of the cell being a well stirred reactor makes a qualitative difference

Kent, University of

258

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

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

259

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

SciTech Connect (OSTI)

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

260

Photovoltaic module mounting system  

DOE Patents [OSTI]

A solar array mounting system having unique installation, load distribution, and grounding features, and which is adaptable for mounting solar panels having no external frame. The solar array mounting system includes flexible, pedestal-style feet and structural links connected in a grid formation on the mounting surface. The photovoltaic modules are secured in place via the use of attachment clamps that grip the edge of the typically glass substrate. The panel mounting clamps are then held in place by tilt brackets and/or mid-link brackets that provide fixation for the clamps and align the solar panels at a tilt to the horizontal mounting surface. The tilt brackets are held in place atop the flexible feet and connected link members thus creating a complete mounting structure.

Miros, Robert H. J.; Mittan, Margaret Birmingham; Seery, Martin N; Holland, Rodney H

2012-09-18T23:59:59.000Z

Note: This page contains sample records for the topic "distribution module assumption" 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

Photovoltaic module mounting system  

DOE Patents [OSTI]

A solar array mounting system having unique installation, load distribution, and grounding features, and which is adaptable for mounting solar panels having no external frame. The solar array mounting system includes flexible, pedestal-style feet and structural links connected in a grid formation on the mounting surface. The photovoltaic modules are secured in place via the use of attachment clamps that grip the edge of the typically glass substrate. The panel mounting clamps are then held in place by tilt brackets and/or mid-link brackets that provide fixation for the clamps and align the solar panels at a tilt to the horizontal mounting surface. The tilt brackets are held in place atop the flexible feet and connected link members thus creating a complete mounting structure.

Miros, Robert H. J. (Fairfax, CA); Mittan, Margaret Birmingham (Oakland, CA); Seery, Martin N. (San Rafael, CA); Holland, Rodney H. (Novato, CA)

2012-04-17T23:59:59.000Z

262

NERSC Modules Software Environment  

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

Environment » Modules Environment Environment » Modules Environment Modules Software Environment NERSC uses the module utility to manage nearly all software. There are two huge advantages of the module approach: NERSC can provide many different versions and/or installations of a single software package on a given machine, including a default version as well as several older and newer versions; and Users can easily switch to different versions or installations without having to explicitly specify different paths. With modules, the MANPATH and related environment variables are automatically managed. Users simply ``load'' and ``unload'' modules to control their environment. The module utility consists of two parts: the module command itself and the modulefiles on which it operates. Module Command

263

Modulational effects in accelerators  

SciTech Connect (OSTI)

We discuss effects of field modulations in accelerators, specifically those that can be used for operational beam diagnostics and beam halo control. In transverse beam dynamics, combined effects of nonlinear resonances and tune modulations influence diffusion rates with applied tune modulation has been demonstrated. In the longitudinal domain, applied RF phase and voltage modulations provide mechanisms for parasitic halo transport, useful in slow crystal extraction. Experimental experiences with transverse tune and RF modulations are also discussed.

Satogata, T.

1997-12-01T23:59:59.000Z

264

A continuous distribution method for reliability evaluation of interconnected power systems.  

E-Print Network [OSTI]

??Recursive algorithms and approximations using continuous distributions are the two basic techniques for reliability calculations of generation systems. Within assumptions common to both methodologies, recursive (more)

Chintaluri, Gouri Mohana

2012-01-01T23:59:59.000Z

265

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

SciTech Connect (OSTI)

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

266

Diversion assumptions for high-powered research reactors. ISPO C-50 Phase 1  

SciTech Connect (OSTI)

This study deals with diversion assumptions for high-powered research reactors -- specifically, MTR fuel; pool- or tank-type research reactors with light-water moderator; and water, beryllium, or graphite reflectors, and which have a power level of 25 MW(t) or more. The objective is to provide assistance to the IAEA in documentation of criteria and inspection observables related to undeclared plutonium production in the reactors described above, including: criteria for undeclared plutonium production, necessary design information for implementation of these criteria, verification guidelines including neutron physics and heat transfer, and safeguards measures to facilitate the detection of undeclared plutonium production at large research reactors.

Binford, F.T.

1984-01-01T23:59:59.000Z

267

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

268

module 4 | Department of Energy  

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

module 4 module 4 HR5 TRANSITION BRIEFING module 4 More Documents & Publications Microsoft Word - Rev5functionalaccountabilityimplementationplan..doc Management (WFP) DEPARTMENT OF...

269

Modulation of whistler waves in nonthermal plasmas  

SciTech Connect (OSTI)

The modulation of whistler waves in nonthermal plasmas is investigated. The dynamics of the magnetized plasma is described by the fluid equations and the electron velocity distribution function is modeled via a nonthermal {kappa} distribution. A multiscale perturbation analysis based on the Krylov-Bogoliubov-Mitropolsky method is carried out and the nonlinear Schroedinger equation governing the modulation of the high-frequency whistler is obtained. The effect of the superthermal electrons on the stability of the wave envelope and soliton formation is discussed and a comparison with previous results is presented.

Rios, L. A.; Galvao, R. M. O. [Centro Brasileiro de Pesquisas Fisicas and Instituto Nacional de Ciencia e Tecnologia de Sistemas Complexos, Rua Xavier Sigaud 150, 22290-180 Rio de Janeiro (Brazil)

2011-02-15T23:59:59.000Z

270

Advanced silicon photonic modulators  

E-Print Network [OSTI]

Various electrical and optical schemes used in Mach-Zehnder (MZ) silicon plasma dispersion effect modulators are explored. A rib waveguide reverse biased silicon diode modulator is designed, tested and found to operate at ...

Sorace, Cheryl M

2010-01-01T23:59:59.000Z

271

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

SciTech Connect (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

272

Modulating lignin in plants  

SciTech Connect (OSTI)

Materials and methods for modulating (e.g., increasing or decreasing) lignin content in plants are disclosed. For example, nucleic acids encoding lignin-modulating polypeptides are disclosed as well as methods for using such nucleic acids to generate transgenic plants having a modulated lignin content.

Apuya, Nestor; Bobzin, Steven Craig; Okamuro, Jack; Zhang, Ke

2013-01-29T23:59:59.000Z

273

Distributed Algorithms Distributed Transactions  

E-Print Network [OSTI]

Algorithms© Gero Mühl 8 Concurrency Control serial RC (ReCoverable) ACA (Avoiding Cascading Aborts) ST (StricDistributed Algorithms Distributed Transactions PD Dr.-Ing. Gero Mühl Kommunikations- und Betriebssysteme Fakultät für Elektrotechnik u. Informatik Technische Universität Berlin #12;Distributed Algorithms

Wichmann, Felix

274

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

275

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

276

Thermoelectrics Partnership: Automotive Thermoelectric Modules...  

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

Solution for Automotive Thermoelectric Modules Application Thermoelectrics Partnership: Automotive Thermoelectric Modules with Scalable Thermo- and Electro-Mechanical Interfaces...

277

The Ccr4-Not Complex Independently Controls both Msn2-Dependent Transcriptional Activationvia a Newly Identified Glc7/Bud14 Type I Protein Phosphatase Moduleand TFIID Promoter Distribution  

Science Journals Connector (OSTI)

...subjected to heat stress, the distribution pattern of TBP...promoters. Loss of Not5 caused...Accordingly, loss of Not5 consistently...mentioning that the heat shock-induced changes in distribution of Taf8 (and...unaffected by the loss of Not5 (Table...

Eve Lenssen; Nicole James; Ivo Pedruzzi; Frdrique Dubouloz; Elisabetta Cameroni; Ruth Bisig; Laurent Maillet; Michel Werner; Johnny Roosen; Katarina Petrovic; Joris Winderickx; Martine A. Collart; Claudio De Virgilio

2005-01-01T23:59:59.000Z

278

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

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

279

Special relativity as the limit of an Aristotelian universal friction theory under Reye's assumption  

E-Print Network [OSTI]

This work explores a classical mechanical theory under two further assumptions: (a) there is a universal dry friction force (Aristotelian mechanics), and (b) the variation of the mass of a body due to wear is proportional to the work done by the friction force on the body (Reye's hypothesis). It is shown that mass depends on velocity as in Special Relativity, and that the velocity is constant for a particular characteristic value. In the limit of vanishing friction the theory satisfies a relativity principle as bodies do not decelerate and, therefore, the absolute frame becomes unobservable. However, the limit theory is not Newtonian mechanics, with its Galilei group symmetry, but rather Special Relativity. This result suggests to regard Special Relativity as the limit of a theory presenting universal friction and exchange of mass-energy with a reservoir (vacuum). Thus, quite surprisingly, Special Relativity follows from the absolute space (ether) concept and could have been discovered following studies of Aristotelian mechanics and friction. We end the work confronting the full theory with observations. It predicts the Hubble law through tired light, and hence it is incompatible with supernova light curves unless both mechanisms of tired light (locally) and universe expansion (non-locally) are at work. It also nicely accounts for some challenging numerical coincidences involving phenomena under low acceleration.

E. Minguzzi

2014-11-28T23:59:59.000Z

280

Cavity enhanced terahertz modulation  

SciTech Connect (OSTI)

We present a versatile concept for all optical terahertz (THz) amplitude modulators based on a Fabry-Prot semiconductor cavity design. Employing the high reflectivity of two parallel meta-surfaces allows for trapping selected THz photons within the cavity and thus only a weak optical modulation of the semiconductor absorbance is required to significantly damp the field within the cavity. The optical switching yields to modulation depths of more than 90% with insertion efficiencies of 80%.

Born, N., E-mail: norman.born@physik.uni-marburg.de [College of Optical Sciences, University of Arizona, 1630 E University Boulevard, Tucson, Arizona 85721 (United States); Faculty of Physics and Material Sciences Center, Philipps-Universitt Marburg, Renthof 5, 35032 Marburg (Germany); Scheller, M.; Moloney, J. V. [College of Optical Sciences, University of Arizona, 1630 E University Boulevard, Tucson, Arizona 85721 (United States)] [College of Optical Sciences, University of Arizona, 1630 E University Boulevard, Tucson, Arizona 85721 (United States); Koch, M. [Faculty of Physics and Material Sciences Center, Philipps-Universitt Marburg, Renthof 5, 35032 Marburg (Germany)] [Faculty of Physics and Material Sciences Center, Philipps-Universitt Marburg, Renthof 5, 35032 Marburg (Germany)

2014-03-10T23:59:59.000Z

Note: This page contains sample records for the topic "distribution module assumption" 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

Detailed Course Module Description  

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

Course Module Description Course Module Description Module/Learning Objectives Level of Detail in Module by Audience Consumers Gen Ed/ Community College Trades 1. Energy Issues and Building Solutions High High High Learning Objectives: * Define terms of building science, ecological systems, economics of consumption * Relate building science perspective, ecology, social science * Explain historical energy and environmental issues related to buildings * Compare Site and source energy * Examine the health, safety and comfort issues in buildings * Examine the general context for building solutions (zero energy green home with durability as the goal) * Explain a basic overview of alternative energy (total solar flux) - do we have enough energy * Examine cash flow to homeowners

282

Bracket for photovoltaic modules  

DOE Patents [OSTI]

Brackets for photovoltaic ("PV") modules are described. In one embodiment, a saddle bracket has a mounting surface to support one or more PV modules over a tube, a gusset coupled to the mounting surface, and a mounting feature coupled to the gusset to couple to the tube. The gusset can have a first leg and a second leg extending at an angle relative to the mounting surface. Saddle brackets can be coupled to a torque tube at predetermined locations. PV modules can be coupled to the saddle brackets. The mounting feature can be coupled to the first gusset and configured to stand the one or more PV modules off the tube.

Ciasulli, John; Jones, Jason

2014-06-24T23:59:59.000Z

283

Integrated LED Headlamp Module  

Science Journals Connector (OSTI)

LED headlamp module integrates all necessary optics, electronics, and heat management into one compact unit that fits into standard mechanical headlamp frame. It provides high beam,...

Popelek, Jan

284

Model documentation Renewable Fuels Module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analaytical approach and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1996 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described.

NONE

1996-01-01T23:59:59.000Z

285

Ultrafast population dynamics in electrically modulated terahertz quantum cascade lasers  

Science Journals Connector (OSTI)

The ultrafast population dynamics in electrically modulated three-well terahertz quantum cascade lasers (QCLs) is studied by using the self-consistent BlochPoisson equations. In the modulation process, the non-equilibrium oscillations of the population inversion are found before the population equilibrium recovers. The equilibrium formation time increases nonlinearly with the period number. This phenomenon stems from the non-uniform distribution of the electric potential. In different periods, different responses to the electrical modulation are also explored. An in-depth understanding of electron transport in the cascade structure is obtained. Finally, we demonstrate the feasibility of a modulation frequency up to gigahertz in terahertz QCLs.

F Wang; X G Guo; C Wang; J C Cao

2013-01-01T23:59:59.000Z

286

Module title Marketing Management Module code INT3602  

E-Print Network [OSTI]

Module title Marketing Management Module code INT3602 Academic year(s) 2013/4 Credits 15 Basic - summary of the module content Module description This module will introduce new marketing students to the fascinating world of modern marketing in an innovative and comprehensive yet practical and enjoyable way

Mumby, Peter J.

287

RETI Phase 1B Final Report Update NET SHORT RECALCULATION AND NEW PV ASSUMPTIONS  

E-Print Network [OSTI]

of distributed PV capacity by the year 2016.8 In response to the California Solar Initiative, a component,7 However, California has established the Go Solar California program with a goal of installing 3,000 MW of the Go Solar California program, 158 MW were installed in 2008 alone.9 The reasonableness of the CEC

288

Working with Modules within Python  

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

Working with Modules within Perl and Python Working with Modules within Perl and Python Working with Modules within Perl and Python It can often be convenient to work with the modules system from within perl or python scripts. You can do this! Using Modules within Python The EnvironmentModules python package gives access to the module system from within python. The EnvironmentModules python package has a single function: module. Using this function you can provide the same arguments you would to "module" on the command line. The module() function accepts a list of arguments, like ['load','']; or ['unload','']. >>> import EnvironmentModules as EnvMod >>> EnvMod.module(['load','blast+']) It is important to understand that this is most effective for scripts

289

DSM of Newton type for solving operator equations F(u) = f with minimal smoothness assumptions on F  

Science Journals Connector (OSTI)

This paper is a review of the authors' results on the Dynamical Systems Method (DSM) for solving operator equation (*) F(u) = f. It is assumed that (*) is solvable. The novel feature of the results is the minimal assumption on the smoothness of F. It is assumed that F is continuously Frechet differentiable, but no smoothness assumptions on F?(u) are imposed. The DSM for solving equation (*) is developed. Under weak assumptions global existence of the solution u(t) is proved, the existence of u(?) is established, and the relation F(u(?)) = f is obtained. The DSM is developed for a stable solution of equation (*) when noisy data f? are given, ''f ? f?'' ? ?.

N.S. Hoang; A.G. Ramm

2010-01-01T23:59:59.000Z

290

Membrane module assembly  

DOE Patents [OSTI]

A membrane module assembly is described which is adapted to provide a flow path for the incoming feed stream that forces it into prolonged heat-exchanging contact with a heating or cooling mechanism. Membrane separation processes employing the module assembly are also disclosed. The assembly is particularly useful for gas separation or pervaporation. 2 figures.

Kaschemekat, J.

1994-03-15T23:59:59.000Z

291

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are further subdivided 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, whereas the non- manufacturing industries are modeled with substantially less detail. The petroleum refining industry is not included in the Industrial Demand Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Demand Module calculates energy consumption for the four Census Regions (see Figure 5) and disaggregates the energy consumption

292

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

he International Energy Module determines changes in the world oil price and the supply prices of crude he 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).

293

Photovoltaic module and interlocked stack of photovoltaic modules  

DOE Patents [OSTI]

One embodiment relates to an arrangement of photovoltaic modules configured for transportation. The arrangement includes a plurality of photovoltaic modules, each photovoltaic module including a frame. A plurality of individual male alignment features and a plurality of individual female alignment features are included on each frame. Adjacent photovoltaic modules are interlocked by multiple individual male alignment features on a first module of the adjacent photovoltaic modules fitting into and being surrounded by corresponding individual female alignment features on a second module of the adjacent photovoltaic modules. Other embodiments, features and aspects are also disclosed.

Wares, Brian S.

2014-09-02T23:59:59.000Z

294

Module bay with directed flow  

DOE Patents [OSTI]

A module bay requires less cleanroom airflow. A shaped gas inlet passage can allow cleanroom air into the module bay with flow velocity preferentially directed toward contaminant rich portions of a processing module in the module bay. Preferential gas flow direction can more efficiently purge contaminants from appropriate portions of the module bay, allowing a reduced cleanroom air flow rate for contaminant removal. A shelf extending from an air inlet slit in one wall of a module bay can direct air flowing therethrough toward contaminant-rich portions of the module bay, such as a junction between a lid and base of a processing module.

Torczynski, John R. (Albuquerque, NM)

2001-02-27T23:59:59.000Z

295

Optical Modulation of Molecular Conductance  

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

Optical Modulation of Molecular Conductance Authors: Battacharyya, S., Kibel, A., Kodis, G., Liddell, P. A., Gervaldo, M., Gust, D., and Lindsay, S. Title: Optical Modulation of...

296

Older People With Dementia Cared for Mostly at Home Study challenges assumption that most patients die in nursing homes  

E-Print Network [OSTI]

Older People With Dementia Cared for Mostly at Home Study challenges assumption that most patients die in nursing homes -- Robert Preidt FRIDAY, May 11 (HealthDay News) -- Many elderly people with dementia live and die at home rather than in nursing homes, a new study has found. The findings challenge

Belogay, Eugene A.

297

Siemens SOFC Test Article and Module Design  

SciTech Connect (OSTI)

Preliminary design studies of the 95 kWe-class SOFC test article continue resulting in a stack architecture of that is 1/3 of 250 kWe-class SOFC advanced module. The 95 kWeclass test article is envisioned to house 20 bundles (eight cells per bundle) of Delta8 cells with an active length of 100 cm. Significant progress was made in the conceptual design of the internal recirculation loop. Flow analyses were initiated in order to optimize the bundle row length for the 250 kWeclass advanced module. A preferred stack configuration based on acceptable flow and thermal distributions was identified. Potential module design and analysis issues associated with pressurized operation were identified.

None

2011-03-31T23:59:59.000Z

298

Scannerless loss modulated flash color range imaging  

DOE Patents [OSTI]

Scannerless loss modulated flash color range imaging methods and apparatus are disclosed for producing three dimensional (3D) images of a target within a scene. Apparatus and methods according to the present invention comprise a light source providing at least three wavelengths (passbands) of illumination that are each loss modulated, phase delayed and simultaneously directed to illuminate the target. Phase delayed light backscattered from the target is spectrally filtered, demodulated and imaged by a planar detector array. Images of the intensity distributions for the selected wavelengths are obtained under modulated and unmodulated (dc) illumination of the target, and the information contained in the images combined to produce a 3D image of the target.

Sandusky, John V. (Albuquerque, NM); Pitts, Todd Alan (Rio Rancho, NM)

2008-09-02T23:59:59.000Z

299

Scannerless loss modulated flash color range imaging  

DOE Patents [OSTI]

Scannerless loss modulated flash color range imaging methods and apparatus are disclosed for producing three dimensional (3D) images of a target within a scene. Apparatus and methods according to the present invention comprise a light source providing at least three wavelengths (passbands) of illumination that are each loss modulated, phase delayed and simultaneously directed to illuminate the target. Phase delayed light backscattered from the target is spectrally filtered, demodulated and imaged by a planar detector array. Images of the intensity distributions for the selected wavelengths are obtained under modulated and unmodulated (dc) illumination of the target, and the information contained in the images combined to produce a 3D image of the target.

Sandusky, John V. (Albuquerque, NM); Pitts, Todd Alan (Rio Rancho, NM)

2009-02-24T23:59:59.000Z

300

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 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

Note: This page contains sample records for the topic "distribution module assumption" 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

Sonication standard laboratory module  

DOE Patents [OSTI]

A standard laboratory module for automatically producing a solution of cominants from a soil sample. A sonication tip agitates a solution containing the soil sample in a beaker while a stepper motor rotates the sample. An aspirator tube, connected to a vacuum, draws the upper layer of solution from the beaker through a filter and into another beaker. This beaker can thereafter be removed for analysis of the solution. The standard laboratory module encloses an embedded controller providing process control, status feedback information and maintenance procedures for the equipment and operations within the standard laboratory module.

Beugelsdijk, Tony (Los Alamos, NM); Hollen, Robert M. (Los Alamos, NM); Erkkila, Tracy H. (Los Alamos, NM); Bronisz, Lawrence E. (Los Alamos, NM); Roybal, Jeffrey E. (Santa Fe, NM); Clark, Michael Leon (Menan, ID)

1999-01-01T23:59:59.000Z

302

Module Title: Project Module Code: OPTO6005  

E-Print Network [OSTI]

Ibsen, Dr Ping Hua, Prof James Wilkinson Contact (email ID) sm@orc.soton.ac.uk, mi@orc.soton.ac.uk, ph2@orc.soton.ac.uk, jsw@orc.soton.ac.uk Is the module subject to external accreditation? No If yes and optical labs of the ORC 3. Train in technical and hands-on research skills to gain technical insight

Anderson, Jim

303

RESTRICTED MODULES AND CONJECTURES FOR MODULES OF CONSTANT JORDAN TYPE  

E-Print Network [OSTI]

RESTRICTED MODULES AND CONJECTURES FOR MODULES OF CONSTANT JORDAN TYPE SEMRA ¨OZT¨URK KAPTANO GLU give a method to construct new restricted k[E]-modules of constant Jordan type from k[E]-modules of constant Jordan type and use it to realize several Jordan types. The constraints on the Jordan type

Kaptanoglu, Semra Ozturk

304

RESTRICTED MODULES AND CONJECTURES FOR MODULES OF CONSTANT JORDAN TYPE  

E-Print Network [OSTI]

RESTRICTED MODULES AND CONJECTURES FOR MODULES OF CONSTANT JORDAN TYPE SEMRA ¨OZT¨URK KAPTANO GLU Abstract. We introduce the class of restricted k[A]-modules and pt-Jordan types for a finite abelian p on Jordan types for modules of constant Jordan type when t is 1. We state conjectures giving constraints

Kaptanoglu, Semra Ozturk

305

Procedures in Modules (1) Including all procedures within modules  

E-Print Network [OSTI]

Procedures in Modules (1) Including all procedures within modules works very well in almost all designing these if possible #12;Procedures in Modules (2) These are very much like internal procedures Works very well in almost all programs Everything accessible in the module can also be used in the procedure

306

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 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 housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type

307

Digital optical conversion module  

DOE Patents [OSTI]

A digital optical conversion module used to convert an analog signal to a computer compatible digital signal including a voltage-to-frequency converter, frequency offset response circuitry, and an electrical-to-optical converter. Also used in conjunction with the digital optical conversion module is an optical link and an interface at the computer for converting the optical signal back to an electrical signal. Suitable for use in hostile environments having high levels of electromagnetic interference, the conversion module retains high resolution of the analog signal while eliminating the potential for errors due to noise and interference. The module can be used to link analog output scientific equipment such as an electrometer used with a mass spectrometer to a computer.

Kotter, Dale K. (North Shelley, ID); Rankin, Richard A. (Ammon, ID)

1991-02-26T23:59:59.000Z

308

Digital optical conversion module  

DOE Patents [OSTI]

A digital optical conversion module used to convert an analog signal to a computer compatible digital signal including a voltage-to-frequency converter, frequency offset response circuitry, and an electrical-to-optical converter. Also used in conjunction with the digital optical conversion module is an optical link and an interface at the computer for converting the optical signal back to an electrical signal. Suitable for use in hostile environments having high levels of electromagnetic interference, the conversion module retains high resolution of the analog signal while eliminating the potential for errors due to noise and interference. The module can be used to link analog output scientific equipment such as an electrometer used with a mass spectrometer to a computer. 2 figs.

Kotter, D.K.; Rankin, R.A.

1988-07-19T23:59:59.000Z

309

Absorbance modulation optical lithography  

E-Print Network [OSTI]

In this thesis, the concept of absorbance-modulation optical lithography (AMOL) is described, and the feasibility experimentally verified. AMOL is an implementation of nodal lithography, which is not bounded by the diffraction ...

Tsai, Hsin-Yu Sidney

2007-01-01T23:59:59.000Z

310

Assumptions to the Annual Energy Outlook 2001 - Table 4. Coefficients of  

Gasoline and Diesel Fuel Update (EIA)

Coefficients of Linear Equations for Natural Gas- and Coefficients of Linear Equations for Natural Gas- and Oil-Related Methane Emissions Emissions Sources Intercept Variable Name and Units Coefficient Variable Name and Units Coefficient Natural Gas -38.77 Time trend (calendar year) .02003 Dry gas production (thousand cubic feet .02186 Natural Gas Processing -0.9454 Natural gas liquids production (million barrels per day) .9350 Not applicable Natural Gas Transmission and Storage 2.503 Pipeline fuel use (thousand cubic feet) 1.249 Dry gas production (thousand cubic feet) -0.06614 Natural Gas Distribution -58.16 Time trend (calendar year) .0297 Natural gas consumption (quadrillion Btu) .0196 Oil production, Refining, and Transport 0.03190 Oil consumption (quadrillion Btu) .002764 Not applicable Source: Derived from data used in Energy Information Administration, Emissions of Greenhouse Gases in the United States 1999, DOE/EIA-0573(99), (Washington, DC, October 2000).

311

Three dimensional, multi-chip module  

DOE Patents [OSTI]

A plurality of multi-chip modules are stacked and bonded around the perimeter by sold-bump bonds to adjacent modules on, for instance, three sides of the perimeter. The fourth side can be used for coolant distribution, for more interconnect structures, or other features, depending on particular design considerations of the chip set. The multi-chip modules comprise a circuit board, having a planarized interconnect structure formed on a first major surface, and integrated circuit chips bonded to the planarized interconnect surface. Around the periphery of each circuit board, long, narrow dummy chips'' are bonded to the finished circuit board to form a perimeter wall. The wall is higher than any of the chips on the circuit board, so that the flat back surface of the board above will only touch the perimeter wall. Module-to-module interconnect is laser-patterned on the sides of the boards and over the perimeter wall in the same way and at the same time that chip to board interconnect may be laser-patterned.

Bernhardt, A.F.; Petersen, R.W.

1993-08-31T23:59:59.000Z

312

Three dimensional, multi-chip module  

DOE Patents [OSTI]

A plurality of multi-chip modules are stacked and bonded around the perimeter by sold-bump bonds to adjacent modules on, for instance, three sides of the perimeter. The fourth side can be used for coolant distribution, for more interconnect structures, or other features, depending on particular design considerations of the chip set. The multi-chip modules comprise a circuit board, having a planarized interconnect structure formed on a first major surface, and integrated circuit chips bonded to the planarized interconnect surface. Around the periphery of each circuit board, long, narrow "dummy chips" are bonded to the finished circuit board to form a perimeter wall. The wall is higher than any of the chips on the circuit board, so that the flat back surface of the board above will only touch the perimeter wall. Module-to-module interconnect is laser-patterned o the sides of the boards and over the perimeter wall in the same way and at the same time that chip to board interconnect may be laser-patterned.

Bernhardt, Anthony F. (Berkeley, CA); Petersen, Robert W. (Pleasanton, CA)

1993-01-01T23:59:59.000Z

313

Model documentation, Coal Market Module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives and the conceptual and methodological approach used in the development of the National Energy Modeling System`s (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1998 (AEO98). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s two submodules. These are the Coal Production Submodule (CPS) and the Coal Distribution Submodule (CDS). CMM provides annual forecasts of prices, production, and consumption of coal for NEMS. In general, the CDS integrates the supply inputs from the CPS to satisfy demands for coal from exogenous demand models. The international area of the CDS forecasts annual world coal trade flows from major supply to major demand regions and provides annual forecasts of US coal exports for input to NEMS. Specifically, the CDS receives minemouth prices produced by the CPS, demand and other exogenous inputs from other NEMS components, and provides delivered coal prices and quantities to the NEMS economic sectors and regions.

NONE

1998-01-01T23:59:59.000Z

314

DISTRIBUTED AND COLLABORATIVE SYNTHETIC ENVIRONMENTS  

E-Print Network [OSTI]

the functions required for the geometric engine of a synthetic environment system. · A distribution on networked desktop machines. Geometric Engine A critical subsystem in all synthetic environment systems is the geometric engine, or the software module responsible for creating a realistic view of the simulated world

Texas at Austin, University of

315

A Model of U.S. Commercial Distributed Generation Adoption  

SciTech Connect (OSTI)

Small-scale (100 kW-5 MW) on-site distributed generation (DG) economically driven by combined heat and power (CHP) applications and, in some cases, reliability concerns will likely emerge as a common feature of commercial building energy systems over the next two decades. Forecasts of DG adoption published by the Energy Information Administration (EIA) in the Annual Energy Outlook (AEO) are made using the National Energy Modeling System (NEMS), which has a forecasting module that predicts the penetration of several possible commercial building DG technologies over the period 2005-2025. NEMS is also used for estimating the future benefits of Department of Energy research and development used in support of budget requests and management decisionmaking. The NEMS approach to modeling DG has some limitations, including constraints on the amount of DG allowed for retrofits to existing buildings and a small number of possible sizes for each DG technology. An alternative approach called Commercial Sector Model (ComSeM) is developed to improve the way in which DG adoption is modeled. The approach incorporates load shapes for specific end uses in specific building types in specific regions, e.g., cooling in hospitals in Atlanta or space heating in Chicago offices. The Distributed Energy Resources Customer Adoption Model (DER-CAM) uses these load profiles together with input cost and performance DG technology assumptions to model the potential DG adoption for four selected cities and two sizes of five building types in selected forecast years to 2022. The Distributed Energy Resources Market Diffusion Model (DER-MaDiM) is then used to then tailor the DER-CAM results to adoption projections for the entire U.S. commercial sector for all forecast years from 2007-2025. This process is conducted such that the structure of results are consistent with the structure of NEMS, and can be re-injected into NEMS that can then be used to integrate adoption results into a full forecast.

LaCommare, Kristina Hamachi; Ryan Firestone; Zhou, Nan; Maribu,Karl; Marnay, Chris

2006-01-10T23:59:59.000Z

316

Nonlocal Modulation of Entangled Photons  

E-Print Network [OSTI]

We consider ramifications of the use of high speed light modulators to questions of correlation and measurement of time-energy entangled photons. Using phase modulators, we find that temporal modulation of one photon of an entangled pair, as measured by correlation in the frequency domain, may be negated or enhanced by modulation of the second photon. Using amplitude modulators we describe a Fourier technique for measurement of biphoton wave functions with slow detectors.

S. E. Harris

2008-08-06T23:59:59.000Z

317

Int. J. Spray and Comb. Dynamics -Accepted for publication 1 About the zero Mach number assumption in  

E-Print Network [OSTI]

as much as the the flame forcing ('Rayleigh') term. Besides, the net effect of the non zero Mach numberInt. J. Spray and Comb. Dynamics - Accepted for publication 1 About the zero Mach number assumption in the calculation of thermoacoustic instabilities By F. N I C O U D1 AND K. W I E C Z O R E K1,2 1 University

Paris-Sud XI, Université de

318

Electricity Distribution  

Science Journals Connector (OSTI)

High voltage (HV) distribution grids have nominal voltages of up ... the grid that connects distribution to the transmission substations and also supplies large industrial customers requiri...

Toms Gmez

2013-01-01T23:59:59.000Z

319

Approved Module Information for ME2011, 2014/5 Module Title/Name: Thermodynamics and Fluids Module Code: ME2011  

E-Print Network [OSTI]

Approved Module Information for ME2011, 2014/5 Module Title/Name: Thermodynamics and Fluids Module Code: ME2011 School: Engineering and Applied Science Module Type: Standard Module New Module? No Module in which available: BEng/MEng Mechanical Engineering. BEng/MEng Electromechanical Engineering. Available

Neirotti, Juan Pablo

320

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and 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 SEDS 27 data.

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


321

Power module assembly  

DOE Patents [OSTI]

A power module assembly of the type suitable for deployment in a vehicular power inverter, wherein the power inverter has a grounded chassis, is provided. The power module assembly comprises a conductive base layer electrically coupled to the chassis, an insulating layer disposed on the conductive base layer, a first conductive node disposed on the insulating layer, a second conductive node disposed on the insulating layer, wherein the first and second conductive nodes are electrically isolated from each other. The power module assembly also comprises a first capacitor having a first electrode electrically connected to the conductive base layer, and a second electrode electrically connected to the first conductive node, and further comprises a second capacitor having a first electrode electrically connected to the conductive base layer, and a second electrode electrically connected to the second conductive node.

Campbell, Jeremy B. (Torrance, CA); Newson, Steve (Redondo Beach, CA)

2011-11-15T23:59:59.000Z

322

Floatable solar heat modules  

SciTech Connect (OSTI)

A floating solar heat module for swimming pools comprises a solid surface for conducting heat from the sun's rays to the water and further includes a solid heat storage member for continual heating even during the night. A float is included to maintain the solar heat module on the surface of the pool. The solid heat storage medium is a rolled metal disk which is sandwiched between top and bottom heat conducting plates, the top plate receiving the heat of the sun's rays through a transparent top panel and the bottom plate transferring the heat conducted through the top plate and rolled disk to the water.

Ricks, J.W.

1981-09-29T23:59:59.000Z

323

Q:\asufinal_0107_demand.vp  

Gasoline and Diesel Fuel Update (EIA)

00 00 (AEO2000) Assumptions to the January 2000 With Projections to 2020 DOE/EIA-0554(2000) Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution

324

Module Handbook Specialisation Biomass Energy  

E-Print Network [OSTI]

Module Handbook Specialisation Biomass Energy 2nd Semester for the Master Programme REMA/EUREC Course 2008/2009 University of Zaragoza Specialisation Provider: Biomass Energy #12;Specialisation Biomass Energy, University of Zaragoza Modul: Introduction and Basic Concepts

Damm, Werner

325

Thermoelectrics Partnership: Automotive Thermoelectric Modules...  

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

Partnership: Automotive Thermoelectric Modules with Scalable Thermo- and Electro-Mechanical Interfaces Novel Nanostructured Interface Solution for Automotive Thermoelectric...

326

Transportation radiological risk assessment for the programmatic environmental impact statement: An overview of methodologies, assumptions, and input parameters  

SciTech Connect (OSTI)

The U.S. Department of Energy is considering a broad range of alternatives for the future configuration of radioactive waste management at its network of facilities. Because the transportation of radioactive waste is an integral component of the management alternatives being considered, the estimated human health risks associated with both routine and accident transportation conditions must be assessed to allow a complete appraisal of the alternatives. This paper provides an overview of the technical approach being used to assess the radiological risks from the transportation of radioactive wastes. The approach presented employs the RADTRAN 4 computer code to estimate the collective population risk during routine and accident transportation conditions. Supplemental analyses are conducted using the RISKIND computer code to address areas of specific concern to individuals or population subgroups. RISKIND is used for estimating routine doses to maximally exposed individuals and for assessing the consequences of the most severe credible transportation accidents. The transportation risk assessment is designed to ensure -- through uniform and judicious selection of models, data, and assumptions -- that relative comparisons of risk among the various alternatives are meaningful. This is accomplished by uniformly applying common input parameters and assumptions to each waste type for all alternatives. The approach presented can be applied to all radioactive waste types and provides a consistent and comprehensive evaluation of transportation-related risk.

Monette, F.; Biwer, B.; LePoire, D.; Chen, S.Y.

1994-02-01T23:59:59.000Z

327

Renewable Fuels Module This  

Gasoline and Diesel Fuel Update (EIA)

or other natural resource factors, as the best sites are utilized, (2) increasing cost of upgrading existing local and network distribution and transmission lines to accommodate...

328

Residential Demand Module  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

for EIA (SENTECH Incorporated, 2010). Wind: The Cost and Performance of Distributed Wind Turbines, 2010-35 (ICF International, 2010). 33 U.S. Energy Information Administration |...

329

Flywheel Energy Storage Module  

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

kWh/100 kW kWh/100 kW Flywheel Energy Storage Module * 100KWh - 1/8 cost / KWh vs. current State of the Art * Bonded Magnetic Bearings on Rim ID * No Shaft / Hub (which limits surface speed) * Flexible Motor Magnets on Rim ID * Develop Touch-down System for Earthquake Flying Rim Eliminate Shaft and Hub Levitate on Passive Magnetic Bearings Increase Rim Tip Speed Larger Diameter Thinner Rim Stores More Energy 4 X increase in Stored Energy with only 60% Increase in Weight Development of a 100 kWh/100 kW Flywheel Energy Storage Module High Speed, Low Cost, Composite Ring with Bore-Mounted Magnetics Current State of the Art Flywheel Limitations of Existing Flywheel * 15 Minutes of storage * Limited to Frequency Regulation Application * Rim Speed (Stored Energy) Limited by Hub Strain and Shaft Dynamics

330

Detection of amplitude modulation, frequency modulation, and quasifrequency modulation by the budgerigar (Melopsittacus undulatus)  

Science Journals Connector (OSTI)

In budgerigars as in humans the detection of amplitude modulation (AM) remains relatively constant as modulation frequency increases while detection of frequency modulation(FM) improves. The point at which FM and AM are equal defines the critical modulation frequency (CMF). The CMF is approximately half the size of the critical band in humans because phase information is lost outside the critical band. At small modulation indices the power spectrum of FM is almost identical to the power spectrum of AM with the difference being the relative phase of the components. The power spectrum of quasifreqeuncy modulation (QFM) is exactly the same as AM even at high?modulation indices. In this experiment two budgerigars were trained by operant conditioning to detect AM FM and QFM at several modulation rates at three carrier frequencies. Budgerigars show nearly identical thresholds for detecting modulation in FM and QFM tones at low?modulation rates and similar thresholds for detecting modulation in FM AM and QFM tones at higher modulation rates. These results argue for an insensitivity to phase differences in budgerigars when they fall outside the frequency bandwidths of the auditory system. [Work supported by NIH Grant Nos. DC?00198 and MH?00982 to RJD.

Jian?Yu Lin; Robert J. Dooling

1997-01-01T23:59:59.000Z

331

Multi-processor including data flow accelerator module  

DOE Patents [OSTI]

An accelerator module for a data flow computer includes an intelligent memory. The module is added to a multiprocessor arrangement and uses a shared tagged memory architecture in the data flow computer. The intelligent memory module assigns locations for holding data values in correspondence with arcs leading to a node in a data dependency graph. Each primitive computation is associated with a corresponding memory cell, including a number of slots for operands needed to execute a primitive computation, a primitive identifying pointer, and linking slots for distributing the result of the cell computation to other cells requiring that result as an operand. Circuitry is provided for utilizing tag bits to determine automatically when all operands required by a processor are available and for scheduling the primitive for execution in a queue. Each memory cell of the module may be associated with any of the primitives, and the particular primitive to be executed by the processor associated with the cell is identified by providing an index, such as the cell number for the primitive, to the primitive lookup table of starting addresses. The module thus serves to perform functions previously performed by a number of sections of data flow architectures and coexists with conventional shared memory therein. A multiprocessing system including the module operates in a hybrid mode, wherein the same processing modules are used to perform some processing in a sequential mode, under immediate control of an operating system, while performing other processing in a data flow mode.

Davidson, George S. (Albuquerque, NM); Pierce, Paul E. (Albuquerque, NM)

1990-01-01T23:59:59.000Z

332

Processing module operating methods, processing modules, and communications systems  

DOE Patents [OSTI]

A processing module operating method includes using a processing module physically connected to a wireless communications device, requesting that the wireless communications device retrieve encrypted code from a web site and receiving the encrypted code from the wireless communications device. The wireless communications device is unable to decrypt the encrypted code. The method further includes using the processing module, decrypting the encrypted code, executing the decrypted code, and preventing the wireless communications device from accessing the decrypted code. Another processing module operating method includes using a processing module physically connected to a host device, executing an application within the processing module, allowing the application to exchange user interaction data communicated using a user interface of the host device with the host device, and allowing the application to use the host device as a communications device for exchanging information with a remote device distinct from the host device.

McCown, Steven Harvey; Derr, Kurt W.; Moore, Troy

2014-09-09T23:59:59.000Z

333

Distribution Workshop  

Broader source: Energy.gov [DOE]

On September 24-26, 2012, the GTT presented a workshop on grid integration on the distribution system at the Sheraton Crystal City near Washington, DC.

334

Fuzzy logic based operated device identification in power distribution systems  

E-Print Network [OSTI]

of an operated device identification algorithm to be used as one of four modules in an automated modular scheme for fault section estimation on radial distribution systems. This algorithm will be executed in tandem with the other fault location modules that form...

Manivannan, Karthick Muthu

2002-01-01T23:59:59.000Z

335

Hilbert von Neumann modules  

E-Print Network [OSTI]

We introduce a way of regarding Hilbert von Neumann modules as spaces of operators between Hilbert space, not unlike [Skei], but in an apparently much simpler manner and involving far less machinery. We verify that our definition is equivalent to that of [Skei], by verifying the `Riesz lemma' or what is called `self-duality' in [Skei]. An advantage with our approach is that we can totally side-step the need to go through $C^*$-modules and avoid the two stages of completion - first in norm, then in the strong operator topology - involved in the former approach. We establish the analogue of the Stinespring dilation theorem for Hilbert von Neumann bimodules, and we develop our version of `internal tensor products' which we refer to as Connes fusion for obvious reasons. In our discussion of examples, we examine the bimodules arising from automorphisms of von Neumann algebras, verify that fusion of bimodules corresponds to composition of automorphisms in this case, and that the isomorphism class of such a bimodule...

Bikram, Panchugopal; Srinivasan, R; Sunder, V S

2011-01-01T23:59:59.000Z

336

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

NONE

1998-01-01T23:59:59.000Z

337

Photovoltaic concentrator module improvements study  

SciTech Connect (OSTI)

This report presents results of a project to design and fabricate an improved photovoltaic concentrator module. Using previous work as a baseline, this study conducted analyses and testing to select major module components and design features. The lens parquet and concentrator solar cell were selected from the highest performing, available components. A single 185X point-focus module was fabricated by the project team and tested at Sandia. Major module characteristics include a 6 by 4 compression-molded acrylic lens parquet (0.737 m{sup 2} area), twenty-four 0.2 ohms-cm, FZ, p-Si solar cells (1.56 cm{sup 2} area) soldered to ceramic substrates and copper heat spreaders, and an aluminized steel housing with corrugated bottom. This project marked the first attempt to use prismatic covers on solar cells in a high-concentration, point-focus application. Cells with 15 percent metallization were obtained, but problems with the fabrication and placement of prismatic covers on these cells lead to the decision not to use covers in the prototype module. Cell assembly fabrication, module fabrication, and module optical design activities are presented here. Test results are also presented for bare cells, cell assemblies, and module. At operating conditions of 981 watts/m{sup 2} DNI and an estimated cell temperature of 65{degrees}C, the module demonstrated an efficiency of 13.9 percent prior to stressed environmental exposure. 12 refs., 56 figs., 7 tabs.

Levy, S.L.; Kerschen, K.A. (Black and Veatch, Kansas City, MO (United States)); Hutchison, G. (Solar Kinetics, Inc., Dallas, TX (United States)); Nowlan, M.J. (Spire Corp., Bedford, MA (United States))

1991-08-01T23:59:59.000Z

338

Approved Module Information for ME2501, 2014/5 Module Title/Name: Design for Use Module Code: ME2501  

E-Print Network [OSTI]

process How to gather user data The role of creativity within engineering design. #12;Module Delivery2501 School: Engineering and Applied Science Module Type: Standard Module New Module? No Module Credits and Management. BSc Transport Product Design. BEng/MEng Mechanical Engineering. BEng/MEng Electromechanical

Neirotti, Juan Pablo

339

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

and clothes drying. In addition to the major equipment-driven and clothes drying. In addition to the major equipment-driven end-uses, the average energy consumption per household is projected for other electric and nonelectric Energy Information Administration/Assumptions to the Annual Energy Outlook 2006 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 South Atlantic Mountain Figure 5. United States Census Divisions Source:Energy Information Administration,Office of Integrated Analysis and Forecasting. Report #:DOE/EIA-0554(2006) Release date: March 2006

340

Module Title: Metamaterials, Nanophotonics and Plasmonics Module Code: OPTO6004  

E-Print Network [OSTI]

Module lecturers Dr Nicholas Papasimakis, Dr Eric Plum, Dr Vassili A Fedotov Contact (email ID) np3@orc.soton.ac.uk; erp@orc.soton.ac.uk; vaf@orc.soton.ac.uk Is the module subject to external accreditation? No If yes

Anderson, Jim

Note: This page contains sample records for the topic "distribution module assumption" 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

Proposal for New Module Module Title: Photonic Materials  

E-Print Network [OSTI]

Information Academic Unit responsible for the module ORC Core/Compulsory/Optional Compulsory Programme, Dr. S. M. Ganapathy, Dr. G. Brambilla Contact (email ID) acp@orc.soton.ac.uk; smg@orc.soton.ac.uk; gb2@orc.soton.ac.uk Will the module be subject to external accreditation? No If yes, by which body

Southampton, University of

342

Module title Human Resource Management Module code INT3604  

E-Print Network [OSTI]

working and the positive management of conflict and cultural difference Syllabus plan Syllabus planModule title Human Resource Management Module code INT3604 Academic year(s) 2013/4 Credits 15 Basic in the context of human resource management principles and practice as currently applied within organisations

Mumby, Peter J.

343

Module Code ST2004 Module Title Applying Probability: Introduction  

E-Print Network [OSTI]

: Dekker, Kraaikamp, Lopuhaa, Meester: A Modern Introduction to Probability and Statistics, Springer,2005 Probability, 2nd ed, Cambridge, 2007 Swift, L: Mathematics and Statistics for Business, Management and FinanceModule Code ST2004 Module Title Applying Probability: Introduction Pre-requisites None ECTS 5

O'Mahony, Donal E.

344

Observation of Nonlocal Modulation with Entangled Photons  

E-Print Network [OSTI]

We demonstrate a new type of quantum mechanical correlation where phase modulators at distant locations, acting on the photons of an entangled pair, interfere to determine the apparent depth of modulation. When the modulators have the same phase, the modulation depth doubles; when oppositely phased, the modulators negate each other.

S. Sensarn; G. Y. Yin; S. E. Harris

2009-09-27T23:59:59.000Z

345

Distributional Differential Privacy for Large-Scale Smart Mrk Jelasity  

E-Print Network [OSTI]

, a natural requirement in the smart grid. We propose novel differentially private mechanisms that solve this problem for sum queries. We evaluate our methods and assumptions using a theoretical analysis as well as publicly available measurement data and show that the extra noise needed to protect distribution parameters

Jelasity, Márk

346

Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

other refinery inputs including alcohols, ethers, bioesters, other refinery inputs including alcohols, ethers, 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 activities in the five Petroleum Area Defense Districts (PADDs) (Figure 9). The model is created by aggregating individual refineries into one linear programmming representation for each PADD. 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, certain PMM inputs and outputs are converted from PADD regions to other regional structures and vice versa. The linear programming results are used to determine

347

Light modulating device  

DOE Patents [OSTI]

In a device for transmitting light, means for controlling the transmissivity of the device, including a ceramic, reversibly electrochromic, crystalline element having a highly reflective state when injected with electrons and charge compensating ions and a highly transmissive state when the electrons and ions are removed, the crystalline element being characterized as having a reflectivity of at least 50% in the reflective state and not greater than 10% in the transmissive state, and means for modulating the crystalline element between the reflective and transmissive states by injecting ions into the crystalline element in response to an applied electrical current of a first polarity and removing the ions in response to an applied electrical current of a second polarity.

Rauh, R. David (Newton, MA); Goldner, Ronald B. (Lexington, MA)

1989-01-01T23:59:59.000Z

348

Light modulating device  

DOE Patents [OSTI]

In a device for transmitting light, means for controlling the transmissivity of the device, including a ceramic, reversibly electrochromic, crystalline element having a highly reflective state when injected with electrons and charge compensating ions and a highly transmissive state when the electrons and ions are removed, the crystalline element being characterized as having a reflectivity of at least 50% in the reflective state and not greater than 10% in the transmissive state, and means for modulating the crystalline element between the reflective and transmissive states by injecting ions into the crystalline element in response to an applied electrical current of a first polarity and removing the ions in response to an applied electrical current of a second polarity are disclosed. 1 fig.

Rauh, R.D.; Goldner, R.B.

1989-12-26T23:59:59.000Z

349

Argonne's SpEC Module  

ScienceCinema (OSTI)

Jason Harper, an electrical engineer in Argonne National Laboratory's EV-Smart Grid Interoperability Center, discusses his SpEC Module invention that will enable fast charging of electric vehicles in under 15 minutes. The module has been licensed to BTCPower.

Harper, Jason

2014-06-05T23:59:59.000Z

350

Hierarchical classification of modulation signals  

E-Print Network [OSTI]

features are extracted and used to classify 11 modulation signals plus white noise in a hierarchical fashion. The modulation signals include carrier wave (CW), AM, FM, SSB, FSK2, FSK4, PSK2, PSK4, OOK, QAM16, and QAM32. A hierarchy of classifiers...

Kim, Nam Jin

2012-06-07T23:59:59.000Z

351

Wealth Distribution  

Science Journals Connector (OSTI)

Walter: What is a just wealth distribution? In my view, it is one that results from respect for proper initial homesteading, for resulting private property rights, and, finally, from any legitimate subsequent ...

Four Arrows; Walter Block

2011-01-01T23:59:59.000Z

352

Special Distribution  

Office of Legacy Management (LM)

Special Distribution Special Distribution Issued: December 1977 ',, Radiological Survey and Decontamination of the Former Main Technical Area (TA-1) at Los Alamos, New Mexico Compiled by A. John Ahlquist Alan K. Stoker Linda K. Trocki c laboratory of, the University of California LOS ALAMOS, NEW MEXICO 87545 An Alfirmdve Action/Equal Opportunity Employer ..-_- .-- .--.-. c T -,--... _ _._-r..l __,.. - .-,_.. ..- _._ -- .--. " . . _ . - . c- - . . . _ -. . _ . - . - . _ - - n - _ _~ ~_. __ _ ~~_ --..&e+ L.';; CONTENTS ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .._____ 1 EXECUTIVE SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .._... _._ 2 I. BACKGROUND .............................................. 15

353

Diagnosis of ion velocity distribution from pin to plate geometry in atmospheric argon dielectric barrier discharge  

SciTech Connect (OSTI)

A new method, fast Fourier transform, is presented to calculate ion velocity distribution by analyzing electromagnetic radiation signal from plasma. This method is based on a dipole model that does not require the assumption of thermodynamic equilibrium. To understand the discharge evolution, the ion velocity distribution is calculated in different oscillation cycles. Results show that the ion velocity distribution deviates from Maxwell distribution over time. The ion velocity and relative ion number fluctuate regularly with time.

Qi, Bing; Pan, Lizhu; Huang, Jianjun; Liu, Ying [Applied Low Temperature Plasma Laboratory, Shenzhen Key Laboratory of Sensors Technology, School of Physics, Shenzhen University, Shenzhen 518060 (China)] [Applied Low Temperature Plasma Laboratory, Shenzhen Key Laboratory of Sensors Technology, School of Physics, Shenzhen University, Shenzhen 518060 (China)

2013-07-15T23:59:59.000Z

354

Integrated Module Heat Exchanger | Department of Energy  

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

Module Heat Exchanger Integrated Module Heat Exchanger 2012 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting...

355

Alternative Energy Sources - An Interdisciplinary Module for...  

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

Alternative Energy Sources - An Interdisciplinary Module for Energy Education Alternative Energy Sources - An Interdisciplinary Module for Energy Education Below is information...

356

EIA model documentation: Electricity market module - electricity fuel dispatch  

SciTech Connect (OSTI)

This report documents the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM) as it was used for EIA`s Annual Energy Outlook 1997. It replaces previous documentation dated March 1994 and subsequent yearly update revisions. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This document serves four purposes. First, it is a reference document providing a detailed description of the model for reviewers and potential users of the EFD including energy experts at the Energy Information Administration (EIA), other Federal agencies, state energy agencies, private firms such as utilities and consulting firms, and non-profit groups such as consumer and environmental groups. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports. Third, it facilitates continuity in model development by providing documentation which details model enhancements that were undertaken for AE097 and since the previous documentation. Last, because the major use of the EFD is to develop forecasts, this documentation explains the calculations, major inputs and assumptions which were used to generate the AE097.

NONE

1997-01-01T23:59:59.000Z

357

Photovoltaic solar concentrator module  

SciTech Connect (OSTI)

This invention consists of a planar photovoltaic concentrator module for producing an electrical signal from incident solar radiation which includes an electrically insulating housing having a front wall, an opposing back wall and a hollow interior. A solar cell having electrical terminals is positioned within the interior of the housing. A planar conductor is connected with a terminal of the solar cell of the same polarity. A lens forming the front wall of the housing is operable to direct solar radiation incident to the lens into the interior of the housing. A refractive optical element in contact with the solar cell and facing the lens receives the solar radiation directed into the interior of the housing by the lens and directs the solar radiation to the solar cell to cause the solar cell to generate an electrical signal. An electrically conductive planar member is positioned in the housing to rest on the housing back wall in supporting relation with the solar cell terminal of opposite polarity. The planar member is operable to dissipate heat radiated by the solar cell as the solar cell generates an electrical signal and further forms a solar cell conductor connected with the solar cell terminal to permit the electrical signal generated by the solar cell to be measured between the planar member and the conductor.

Chiang, C.J.

1991-05-16T23:59:59.000Z

358

Photovoltaic module with adhesion promoter  

DOE Patents [OSTI]

Photovoltaic modules with adhesion promoters and methods for fabricating photovoltaic modules with adhesion promoters are described. A photovoltaic module includes a solar cell including a first surface and a second surface, the second surface including a plurality of interspaced back-side contacts. A first glass layer is coupled to the first surface by a first encapsulating layer. A second glass layer is coupled to the second surface by a second encapsulating layer. At least a portion of the second encapsulating layer is bonded directly to the plurality of interspaced back-side contacts by an adhesion promoter.

2013-10-08T23:59:59.000Z

359

Quantum modulation against electromagnetic interference  

E-Print Network [OSTI]

Periodic signals in electrical and electronic equipment can cause interference in nearby devices. Randomized modulation of those signals spreads their energy through the frequency spectrum and can help to mitigate electromagnetic interference problems. The inherently random nature of quantum phenomena makes them a good control signal. I present a quantum modulation method based on the random statistics of quantum light. The paper describes pulse width modulation schemes where a Poissonian light source acts as a random control that spreads the energy of the potential interfering signals. I give an example application for switching-mode power supplies and comment the further possibilities of the method.

Juan Carlos Garcia-Escartin

2014-11-26T23:59:59.000Z

360

Ion impact energy distribution and sputtering of Si and Ge M. Z. Hossain,a)  

E-Print Network [OSTI]

suggest that the energy deposition distri- bution differs from Sigmund's ellipsoidal assumption. It hasIon impact energy distribution and sputtering of Si and Ge M. Z. Hossain,a) J. B. Freund, and H. T 2012) The spatial distribution of ion deposited energy is often assumed to linearly relate to the local

Freund, Jonathan B.

Note: This page contains sample records for the topic "distribution module assumption" 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

PERFORMANCE ASSESSMENT OF PV MODULES RELATIONSHIP BETWEEN STC RATING AND FIELD PERFORMANCE  

E-Print Network [OSTI]

in the spectral distribution. They depend on average annual daylight temperature, but only very weakly on the temperature distribution. The two key module parameters that control the effective efficiency are series, such as standard test conditions (STC) with one-sun irradiance (1 kW/m 2 , AM1.5 spectrum) and cell temperature (Tj

Sites, James R.

362

Photovoltaic Module Qualification Plus Testing  

SciTech Connect (OSTI)

This report summarizes a set of test methods that are in the midst of being incorporated into IEC 61215 for certification of a module design or other tests that go beyond certification to establish bankability.

Kurtz, S.; Wohlgemuth, J.; Kempe, M.; Bosco, N.; Hacke, P.; Jordan, D.; Miller, D. C.; Silverman, T. J.; Phillips, N.; Earnest, T.; Romero, R.

2013-12-01T23:59:59.000Z

363

Titel des Moduls: Schallmesstechnik und  

E-Print Network [OSTI]

Titel des Moduls: Schallmesstechnik und Signalverarbeitung (Measurement Technique and Signal. Fortgeschrittene" und/oder mit Modulen TA 2 und TA 6 "Noise and Vibration Control", "Advanced Noise and Vibration

Berlin,Technische Universität

364

Approved Module Information for CH3108, 2014/5 Module Title/Name: Polymer III Module Code: CH3108  

E-Print Network [OSTI]

Additives for Polymer Modification [Part 2]:To illustrate the role of different additives in plastics School: Engineering and Applied Science Module Type: Standard Module New Module? No Module Credits: 20 and their effects in modifying polymer properties and performance using different modification methods

Neirotti, Juan Pablo

365

Approved Module Information for ME4504, 2014/5 Module Title/Name: Renewable Energy Module Code: ME4504  

E-Print Network [OSTI]

turbine Renewable energy system design Renewable Energy Policy: UK and international perspectives ModuleApproved Module Information for ME4504, 2014/5 Module Title/Name: Renewable Energy Module Code: ME understanding of the origins and nature of renewable energy flows and their capture and conversion into useful

Neirotti, Juan Pablo

366

Compact magnetic energy storage module  

DOE Patents [OSTI]

A superconducting compact magnetic energy storage module in which a plurality of superconducting toroids, each having a toroidally wound superconducting winding inside a poloidally wound superconducting winding, are stacked so that the flow of electricity in each toroidally wound superconducting winding is in a direction opposite from the direction of electrical flow in other contiguous superconducting toroids. This allows for minimal magnetic pollution outside of the module.

Prueitt, Melvin L. (Los Alamos, NM)

1994-01-01T23:59:59.000Z

367

Compact magnetic energy storage module  

DOE Patents [OSTI]

A superconducting compact magnetic energy storage module in which a plurality of superconducting toroids, each having a toroidally wound superconducting winding inside a poloidally wound superconducting winding, are stacked so that the flow of electricity in each toroidally wound superconducting winding is in a direction opposite from the direction of electrical flow in other contiguous superconducting toroids. This allows for minimal magnetic pollution outside of the module. 4 figures.

Prueitt, M.L.

1994-12-20T23:59:59.000Z

368

NEMS integrating module documentation report  

SciTech Connect (OSTI)

The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to a variety of assumptions. The assumptions encompass macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, technology characteristics, and demographics. NEMS produces a general equilibrium solution for energy supply and demand in the U.S. energy markets on an annual basis through 2015. Baseline forecasts from NEMS are published in the Annual Energy Outlook. Analyses are also prepared in response to requests by the U.S. Congress, the DOE Office of Policy, and others. NEMS was first used for forecasts presented in the Annual Energy Outlook 1994.

NONE

1997-05-01T23:59:59.000Z

369

Liquid Metal Thermal Electric Converter bench test module  

SciTech Connect (OSTI)

This report describes the design, fabrication, and test of a Liquid Metal Thermal Electric Converter Bench Test Module. The work presented in this document was conducted as a part of Heat Engine Task of the US Department of Energy's (DOE) Solar Thermal Technology Program. The objective of this task is the development and evaluation of heat engine technologies applicable to distributed receiver systems, in particular, dish electric systems.

Lukens, L.L.; Andraka, C.E.; Moreno, J.B.

1988-04-01T23:59:59.000Z

370

DISTRIBUTION CATEGORY  

Office of Scientific and Technical Information (OSTI)

DISTRIBUTION CATEGORY DISTRIBUTION CATEGORY uc-11 I A W E N C E LIVERMORE IABORATORY University of Cahfmia/Livermore, California/94550 UCRL-52658 CALCULATION OF CHEMICAL EQUILIBRIUM BETWEEN AQUEOUS SOLUTION AND MINERALS: THE EQ3/6 - - SOFTWARE PACKAGE T. J. Wolery MS. date: February 1, 1979 . . - . . - . Tho rcpon rn prepared as an account of work sponsored by the United Stater Government. Seither Lhc Urutcd Stater nor the Umted Stater Department of Energy, nor any of their employees. nor any of their E O ~ ~ ~ B C I O I S . rubcontracton. o r their employees. makes any warranr)., exprcs or !mplwd. or assumes any legal liability or respanability io: the ~ c c u o c y . complctencn or uvfulneu of any miormarlon. apparatcr. product or p r o m s dtwlorcd. or r c p r e v n u that its UP would not infringe privately owned r

371

Apparatus for encapsulating a photovoltaic module  

DOE Patents [OSTI]

The subject inventions concern various photovoltaic module designs to protect the module from horizontal and vertical impacts and degradation of solar cell efficiency caused by moisture. In one design, a plurality of panel supports that are positioned adjacent to the upper panel in a photovoltaic module absorb vertical forces exerted along an axis perpendicular to the upper panel. Other designs employ layers of glass and tempered glass, respectively, to protect the module from vertical impacts. A plurality of button-shaped channels is used around the edges of the photovoltaic module to absorb forces applied to the module along an axis parallel to the module and direct moisture away from the module that could otherwise penetrate the module and adversely affect the cells within the module. A spacer is employed between the upper and lower panels that has a coefficient of thermal expansion substantially equivalent to the coefficient of thermal expansion of at least one of the panels.

Albright, Scot P. (El Paso, TX); Dugan, Larry M. (Boulder, CO)

1995-10-24T23:59:59.000Z

372

Annual Energy Outlook with Projections to 2025  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the nnual Energy Outlook Assumptions to the nnual Energy Outlook EIA Glossary Assumptions to the Annual Energy Outlook 2004 Report #: DOE/EIA-0554(2004) Release date: February 2004 Next release date:February 2005 The Assumptions to the Annual Energy Outlook presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook. Table of Contents Introduction Macroeconomic Activity Module International Energy Module Household Expenditures 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 Appendix A Adobe Acrobat Logo

373

Attractor Spaces as Modules: A Semi-Eliminative Reduction of Symbolic AI to Dynamic Systems Theory  

Science Journals Connector (OSTI)

I propose a semi-eliminative reduction of Fodor's concept of module to the concept of attractor basin which is used in Cognitive Dynamic Systems Theory (DST). I show how attractor basins perform the same explanatory function as modules in several DST ... Keywords: Central Pattern Generator, Dynamic Systems Theory, Fodor, GOFAI, Kelso, Mezernich and Kaas, Port, Thelen and Smith, Van Gelder, Walter Freeman, animal locomotion, attractor spaces, bifurcations, collective variable, connectionism, distributed processing, invariant sets, modularity, orbit, symbolic systems hypothesis

Teed Rockwell

2005-02-01T23:59:59.000Z

374

Percent Distribution  

Gasoline and Diesel Fuel Update (EIA)

. . Percent Distribution of Natural Gas Supply and Disposition by State, 1996 Table State Estimated Proved Reserves (dry) Marketed Production Total Consumption Alabama................................................................... 3.02 2.69 1.48 Alaska ...................................................................... 5.58 2.43 2.04 Arizona..................................................................... NA 0 0.55 Arkansas.................................................................. 0.88 1.12 1.23 California.................................................................. 1.25 1.45 8.23 Colorado .................................................................. 4.63 2.90 1.40 Connecticut.............................................................. 0 0 0.58 D.C...........................................................................

375

Distributed Generation  

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

Untapped Value of Backup Generation Untapped Value of Backup Generation While new guidelines and regulations such as IEEE (Institute of Electrical and Electronics Engineers) 1547 have come a long way in addressing interconnection standards for distributed generation, utilities have largely overlooked the untapped potential of these resources. Under certain conditions, these units (primarily backup generators) represent a significant source of power that can deliver utility services at lower costs than traditional centralized solutions. These backup generators exist today in large numbers and provide utilities with another option to reduce peak load, relieve transmission congestion, and improve power reliability. Backup generation is widely deployed across the United States. Carnegie Mellon's Electricity

376

Introduction  

Gasoline and Diesel Fuel Update (EIA)

9) 9) Release date: March 2009 Next release date: March 2010 Assumptions to the Annual Energy Outlook 2009 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2. Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3. International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4. Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 5. Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 6. Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 7. Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 8. Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 9. Oil and Gas Supply Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 10. Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . 123 11. Petroleum Market Module

377

Active combustion flow modulation valve  

DOE Patents [OSTI]

A flow modulation valve has a slidably translating hollow armature with at least one energizable coil wound around and fixably attached to the hollow armature. The energizable coil or coils are influenced by at least one permanent magnet surrounding the hollow armature and supported by an outer casing. Lorentz forces on the energizable coils which are translated to the hollow armature, increase or decrease the flow area to provide flow throttling action. The extent of hollow armature translation depends on the value of current supplied and the direction of translation depends on the direction of current flow. The compact nature of the flow modulation valve combined with the high forces afforded by the actuator design provide a flow modulation valve which is highly responsive to high-rate input control signals.

Hensel, John Peter; Black, Nathaniel; Thorton, Jimmy Dean; Vipperman, Jeffrey Stuart; Lambeth, David N; Clark, William W

2013-09-24T23:59:59.000Z

378

The assess facility descriptor module  

SciTech Connect (OSTI)

The Facility Descriptor (Facility) module is part of the Analytic System and Software for Evaluating Safeguards and Security (ASSESS). Facility is the foundational software application in the ASSESS system for modelling a nuclear facility's safeguards and security system to determine the effectiveness against theft of special nuclear material. The Facility module provides the tools for an analyst to define a complete description of a facility's physical protection system which can then be used by other ASSESS software modules to determine vulnerability to a spectrum of insider and outsider threats. The analyst can enter a comprehensive description of the protection system layout including all secured areas, target locations, and detailed safeguards specifications. An extensive safeguard component catalog provides the reference data for calculating delay and detection performance. Multiple target locations within the same physical area may be specified, and the facility may be defined for two different operational states such as dayshift and nightshift. 6 refs., 5 figs.

Jordan, S.E.; Winblad, A.; Key, B.; Walker, S.; Renis, T.; Saleh, R.

1989-01-01T23:59:59.000Z

379

Solid-state membrane module  

DOE Patents [OSTI]

Solid-state membrane modules comprising at least one membrane unit, where the membrane unit has a dense mixed conducting oxide layer, and at least one conduit or manifold wherein the conduit or manifold comprises a dense layer and at least one of a porous layer and a slotted layer contiguous with the dense layer. The solid-state membrane modules may be used to carry out a variety of processes including the separating of any ionizable component from a feedstream wherein such ionizable component is capable of being transported through a dense mixed conducting oxide layer of the membrane units making up the membrane modules. For ease of construction, the membrane units may be planar.

Gordon, John Howard (Salt Lake City, UT); Taylor, Dale M. (Murray, UT)

2011-06-07T23:59:59.000Z

380

Progress of MICE RFCC Module  

SciTech Connect (OSTI)

Recent progress on the design and fabrication of the RFCC (RF and superconducting Coupling Coil) module for the international MICE (Muon Ionization Cooling Experiment) are reported. The MICE ionization cooling channel has two RFCC modules, each having four 201- MHz normal conducting RF cavities surrounded by one superconducting coupling coil (solenoid) magnet. The magnet is designed to be cooled by three cryocoolers. Fabrication of the RF cavities is complete; preparation for the cavity electro-polishing, low power RF measurements, and tuning are in progress at Lawrence Berkeley National Laboratory (LBNL). Fabrication of the cold mass of the first coupling coil magnet has been completed in China and the cold mass arrived at LBNL in late 2011. Preparations for testing the cold mass are currently under way at Fermilab. Plans for the RFCC module assembly and integration are being developed and are described.

Li, D.; Bowring, D.; DeMello, A.; Gourlay, S.; Green, M.; Li, N.; Niinikoski, T.; Pan, H.; Prestemon, S.; Virostek, S.; Zisman, M.; Bross, A.; Carcagno, R.; Kashikhin, V.; Sylvester, C.; Chen, A.B.; Guo, Bin; Li, Liyi; Xu, Fengyu; Cao, Y.; Sun, S.; Wang, Li; Yin, Lixin; Luo, Tianhuan; Summers, Don; Smith, B.; Radovinsky, A.; Zhukovsky, A.; Kaplan, D.

2012-05-20T23:59:59.000Z

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


381

Development of a tool dedicated to the evaluation of hydrogen term source for technological Wastes: assumptions, physical models, and validation  

SciTech Connect (OSTI)

In radioactive waste packages hydrogen is generated, in one hand, from the radiolysis of wastes (mainly organic materials) and, in the other hand, from the radiolysis of water content in the cement matrix. In order to assess hydrogen generation 2 tools based on operational models have been developed. One is dedicated to the determination of the hydrogen source term issues from the radiolysis of the wastes: the STORAGE tool (Simulation Tool Of Emission Radiolysis Gas), the other deals with the hydrogen source term gas, produced by radiolysis of the cement matrices (the Damar tool). The approach used by the STORAGE tool for assessing the production rate of radiolysis gases is divided into five steps: 1) Specification of the data packages, in particular, inventories and radiological materials defined for a package medium; 2) Determination of radiochemical yields for the different constituents and the laws of behavior associated, this determination of radiochemical yields is made from the PRELOG database in which radiochemical yields in different irradiation conditions have been compiled; 3) Definition of hypothesis concerning the composition and the distribution of contamination inside the package to allow assessment of the power absorbed by the constituents; 4) Sum-up of all the contributions; And finally, 5) validation calculations by comparison with a reduced sampling of packages. Comparisons with measured values confirm the conservative character of the methodology and give confidence in the safety margins for safety analysis report.

Lamouroux, C. [CEA Saclay, Nuclear Energy Division /DANS, Department of physico-chemistry, 91191 Gif sur yvette (France); Esnouf, S. [CEA Saclay, DSM/IRAMIS/SIS2M/Radiolysis Laboratory , 91191 Gif sur yvette (France); Cochin, F. [Areva NC,recycling BU, DIRP/RDP tour Areva, 92084 Paris La Defense (France)

2013-07-01T23:59:59.000Z

382

A Search for the Dark Matter Annual Modulation in South Pole Ice  

E-Print Network [OSTI]

Astrophysical observations and cosmological data have led to the conclusion that nearly one quarter of the Universe consists of dark matter. Under certain assumptions, an observable signature of dark matter is the annual modulation of the rate of dark matter-nucleon interactions taking place in an Earth-bound experiment. To search for this effect, we introduce the concept for a new dark matter experiment using NaI scintillation detectors deployed deep in the South Pole ice. This experiment complements dark matter search efforts in the Northern Hemisphere and will investigate the observed annual modulation in the DAMA/LIBRA and DAMA/NaI experiments. The unique location will permit the study of background effects correlated with seasonal variations and the surrounding environment. This paper describes the experimental concept and explores the sensitivity of a 250 kg NaI experiment at the South Pole.

Cherwinka, J; Cowen, D F; Grant, D; Halzen, F; Heeger, K M; Hsu, L; Karle, A; Kudryavtsev, V A; Maruyama, R; Pettus, W; Robinson, M; Spooner, N J C

2011-01-01T23:59:59.000Z

383

Parametric Instability in Long Optical Cavities and Suppression by Dynamic Transverse Mode Frequency Modulation  

E-Print Network [OSTI]

Three mode parametric instability has been predicted in Advanced gravitational wave detectors. Here we present the first observation of this phenomenon in a large scale suspended optical cavity designed to be comparable to those of advanced gravitational wave detectors. Our results show that previous modelling assumptions that transverse optical modes are stable in frequency except for frequency drifts on a thermal deformation time scale is unlikely to be valid for suspended mass optical cavities. We demonstrate that mirror figure errors cause a dependence of transverse mode offset frequency on spot position. Combined with low frequency residual motion of suspended mirrors, this leads to transverse mode frequency modulation which suppresses the effective parametric gain. We show that this gain suppression mechanism can be enhanced by laser spot dithering or fast thermal modulation. Using Advanced LIGO test mass data and thermal modelling we show that gain suppression factors of 10-20 could be achieved for ind...

Zhao, Chunnong; Fang, Qi; Blair, Carl; Qin, Jiayi; Blair, David; Degallaix, Jerome; Yamamoto, Hiroaki

2015-01-01T23:59:59.000Z

384

Percent Distribution  

Gasoline and Diesel Fuel Update (EIA)

. . Percent Distribution of Natural Gas Delivered to Consumers by State, 1996 Table State Residential Commercial Industrial Vehicle Fuel Electric Utilities Alabama..................................... 1.08 0.92 2.27 0.08 0.23 Alaska ........................................ 0.31 0.87 0.85 - 1.16 Arizona....................................... 0.53 0.92 0.30 3.91 0.70 Arkansas.................................... 0.88 0.98 1.59 0.11 1.24 California.................................... 9.03 7.44 7.82 43.11 11.64 Colorado .................................... 2.12 2.18 0.94 0.58 0.20 Connecticut................................ 0.84 1.26 0.37 1.08 0.38 D.C............................................. 0.33 0.52 - 0.21 - Delaware.................................... 0.19 0.21 0.16 0.04 0.86 Florida........................................

385

Distribution Category:  

Office of Legacy Management (LM)

- - Distribution Category: Remedial Action and Decommissioning Program (UC-70A) DOE/EV-0005/48 ANL-OHS/HP-84-104 ARGONNE NATIONAL LABORATORY 9700 South Cass Avenue Argonne, Illinois 60439 FORMERLY UTILIZED MXD/AEC SITES REMEDIAL ACTION PROGRAM RADIOLOGICAL SURVEY OF THE HARSHAW CHEMICAL COMPANY CLEVELAND. OHIO Prepared by R. A. Wynveen Associate Division Director, OHS W. H. Smith Senior Health Physicist C. M. Sholeen Health Physicist A. L. Justus Health Physicist K. F. Flynn Health Physicist Radiological Survey Group Health Physics Section Occupational Health and Safety Division April 1984 Work Performed under Budget Activity DOE KN-03-60-40 and ANL 73706 iii PREFACE AND EXECUTIVE SUMMARY This is one in a series of reports resulting from a program initiated

386

7-117 The claim of a heat pump designer regarding the COP of the heat pump is to be evaluated. Assumptions The heat pump operates steadily.  

E-Print Network [OSTI]

7-47 7-117 The claim of a heat pump designer regarding the COP of the heat pump is to be evaluated. Assumptions The heat pump operates steadily. HP Wnet,in QH QL TL TH Analysis The maximum heat pump coefficient of performance would occur if the heat pump were completely reversible, 5.7 K026K300 K300 COP maxHP, LH H TT

Bahrami, Majid

387

Review of technical justification of assumptions and methods used by the Environmental Protection Agency for estimating risks avoided by implementing MCLs for radionuclides  

SciTech Connect (OSTI)

The Environmental Protection Agency (EPA) has proposed regulations for allowable levels of radioactive material in drinking water (40 CFR Part 141, 56 FR 33050, July 18, 1991). This review examined the assumptions and methods used by EPA in calculating risks that would be avoided by implementing the proposed Maximum Contaminant Levels for uranium, radium, and radon. Proposed limits on gross alpha and beta-gamma emitters were not included in this review.

Morris, S.C.; Rowe, M.D.; Holtzman, S.; Meinhold, A.F.

1992-11-01T23:59:59.000Z

388

Module Handbook Specialisation Wind Energy  

E-Print Network [OSTI]

of Wind Turbines Module name: Wind potential, Aerodynamics & Loading of Wind Turbines Section Classes Evaluation of Wind Energy Potential Wind turbine Aerodynamics Static and dynamic Loading of Wind turbines Wind turbine Aerodynamics Static and dynamic Loading of Wind turbines Credit points 8 CP

Habel, Annegret

389

Approved Module Information for CE1102, 2014/5 Module Title/Name: Organic Chemistry for Engineers Module Code: CE1102  

E-Print Network [OSTI]

Approved Module Information for CE1102, 2014/5 Module Title/Name: Organic Chemistry for Engineers Module Code: CE1102 School: Engineering and Applied Science Module Type: Standard Module New Module chemistry. Part 2: Introduction to Laboratory Skills To enable the student to develop good practical skills

Neirotti, Juan Pablo

390

High Heat Flux Thermoelectric Module Using Standard Bulk Material...  

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

Heat Flux Thermoelectric Module Using Standard Bulk Material High Heat Flux Thermoelectric Module Using Standard Bulk Material Presents high heat flux thermoelectric module design...

391

Hail Impact Testing on Crystalline Si Modules with Flexible Packaging...  

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

Hail Impact Testing on Crystalline Si Modules with Flexible Packaging Hail Impact Testing on Crystalline Si Modules with Flexible Packaging Presented at the PV Module Reliability...

392

Overview of the PV Module Model in PVWatts (Presentation)  

SciTech Connect (OSTI)

Overview of the PV module model. PVWatts module power estimates were compared with those using the Sandia model for three modules and data sets.

Marion, B.

2010-09-22T23:59:59.000Z

393

Approved Module Information for EE3OEL, 2014/5 Module Title/Name: Optoelectronics Module Code: EE3OEL  

E-Print Network [OSTI]

Approved Module Information for EE3OEL, 2014/5 Module Title/Name: Optoelectronics Module Code: EE3: * To provide a broad overview of updated optoelectronic principles, devices and applications. The students optoelectronic devices and their important functions for applications in optical communication, signal processing

Neirotti, Juan Pablo

394

Approved Module Information for ME1601, 2014/5 Module Title/Name: Engineering Science Module Code: ME1601  

E-Print Network [OSTI]

to apply the basic engineering principles of mechanics, solid mechanics and thermo fluids to a variety and understanding of the fundamental engineering principles of mechanics, solid mechanics and thermo-fluidsApproved Module Information for ME1601, 2014/5 Module Title/Name: Engineering Science Module Code

Neirotti, Juan Pablo

395

Approved Module Information for PD2003, 2014/5 Module Title/Name: Engineering Principles 2 Module Code: PD2003  

E-Print Network [OSTI]

to apply further engineering principles of mechanics, solid mechanics, energy systems and thermo-fluids and understanding of the fundamental engineering principles of mechanics, solid mechanics and thermo- fluidsApproved Module Information for PD2003, 2014/5 Module Title/Name: Engineering Principles 2 Module

Neirotti, Juan Pablo

396

FUEL CELLS SOLID OXIDE FUEL CELLS | Gas Distribution  

Science Journals Connector (OSTI)

A uniform distribution of the reactants over the total available electrode surfaces in solid oxide fuel cells (SOFCs) is a prerequisite for the proper operation of the fuel cell. The gas distribution plays a dominant role not only in the current density distribution but also in the temperature distribution over the cell areas and in the stack and modules. Several transport mechanisms for mass transport occurring in the SOFC are introduced and discussed. General flow configurations and structures for the gas distribution at three different levels, i.e., stack/module, cell/tube, and electrode/electrolyte, are discussed for both tubular and planar type cells and illustrated with examples of concentration and temperature profiles.

L.G.J. de Haart; M. Spiller

2009-01-01T23:59:59.000Z

397

New Camshaft Phaser Module for Automobile Engines  

Science Journals Connector (OSTI)

?...shows the functional scheme of the camshaft phaser module. The function components which are integrated into the module are encircled in a chain dotted line. A spring loaded piston pressure r...

Dr.-Ing. Uwe Meinig; Dipl.-Ing. (FH) Jrgen Bohner

2013-07-01T23:59:59.000Z

398

Experimental determination of the distribution of tail states of hydrogenated amorphous silicon: A transient photocurrent analysis  

SciTech Connect (OSTI)

Recent experimental developments have cast doubt on the validity of the common assumption that the distribution of tail states of hydrogenated amorphous silicon exhibits a single exponential functional form. The authors employ transient photocurrent decay measurements to determine this distribution of tail states. In their approach, however, they determine the distribution of tail states directly from the experimental data, without assuming, a priori, a specific functional form. It is found that these experimental results are consistent with other more recent experimental determinations of the distribution of tail states, suggesting the possibility of deviations from a single exponential distribution of tail states in hydrogenated amorphous silicon.

Webb, D.P.; Chan, F.Y.M.; Zou, X.C.; Chan, Y.C.; Lam, Y.W.; Lin, S.H.; O'Leary, S.K.; Lim, P.K.

1997-07-01T23:59:59.000Z

399

Amplitude modulation free, wide band frequency modulated oscillator  

E-Print Network [OSTI]

oscillator- - - - - ? ? - ? 3 15 ~ Iiide Bmd Frc saency Lodulator Relatively Free of A@elf tude Modulation-? ? 35 1~'i. Tank Uoltare Versus Fx~tuency or . 'evcral Loads ? - ? ? - 35 17. Screon Voltage Versus Frequency? 10. Amclitude Lodulafion Envelope... of Conventional Design- - ? 39 19 ' ~litude Ltodulation Eave" ope of !iem Design- - - ? - - ? 39 20. Tank Voltage Versus 11~-, coney of Conventisnal Design Hew Design INTRODUCTION The accurate and rapid determination and location of faults is very important...

Nelson, Dick Frank

1951-01-01T23:59:59.000Z

400

Crossed modules of racks Alissa S. Crans  

E-Print Network [OSTI]

Crossed modules of racks Alissa S. Crans Loyola Marymount University Friedrich Wagemann Universit to that of a crossed module of racks. We investigate the relation to categorified racks, namely strict 2-racks, and trunk-like objects in the category of racks, generalizing the relation between crossed modules of groups

Wagemann, Friedrich

Note: This page contains sample records for the topic "distribution module assumption" 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

Nutrient Management Module No. 15 Sustainable  

E-Print Network [OSTI]

Nutrient Management Module No. 15 Sustainable Agriculture by Ann McCauley, Soil Scientist, Clain for those wanting more in-depth information about sustainable agriculture. This module covers Rocky Mountain Source and Applications, with the focus on sustainable agriculture. Objectives After reading this module

Lawrence, Rick L.

402

Rank Modulation with Multiplicity Anxiao (Andrew) Jiang  

E-Print Network [OSTI]

Rank Modulation with Multiplicity Anxiao (Andrew) Jiang Computer Science and Eng. Dept. Texas A&M University College Station, TX 77843 yuewang@cse.tamu.edu Abstract--Rank modulation is a scheme that uses-change memories, etc. An extension of rank modulation is studied in this paper, where multiple cells can have

Jiang, Anxiao "Andrew"

403

A Stability of LCLS Linac Modulators  

SciTech Connect (OSTI)

Information concerning to a stability of LCLS RF linac modulators is allocated in this paper. In general a 'pulse-to-pulse' modulator stability (and RF phase as well) is acceptable for the LCLS commission and FEL programs. Further modulator stability improvements are possible and approaches are discussed based on our experimental results.

Decker, F.-J.; Krasnykh, A.; Morris, B.; Nguyen, M.; /SLAC

2012-06-13T23:59:59.000Z

404

Interface module for transverse energy input to dye laser modules  

DOE Patents [OSTI]

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

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

1994-01-01T23:59:59.000Z

405

Degradation Pathway Models for Photovoltaics Module Lifetime Performance  

E-Print Network [OSTI]

Degradation Pathway Models for Photovoltaics Module Lifetime Performance Nicholas R. Wheeler, Laura data from Underwriter Labs, featuring measurements taken on 18 identical photovoltaic (PV) modules in modules and their effects on module performance over lifetime. Index Terms--photovoltaics, statistical

Rollins, Andrew M.

406

A Novel Distributed Machine Learning Method for Classification: Parallel Covering Algorithm  

Science Journals Connector (OSTI)

In this paper, we propose a novel distributed machine learning method: Parallel Covering Algorithm, which is inspired by the module feature of CA (Covering Algorithm). Classic method of CA is ... by utilizing its...

Yanping Zhang; Yuehua Wang; Shu Zhao

2012-01-01T23:59:59.000Z

407

SiC Power Module  

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

R&D 100 Entry R&D 100 Entry SiC Power Module 2 R&D 100 Entry SiC Power Module Submitting OrganizatiOn Sandia National Laboratories PO Box 5800, MS 1033 Albuquerque, NM 87185-1033 USA Stanley Atcitty Phone: 505-284-2701 Fax: 505-844-2890 satcitt@sandia.gov AFFIRMATION: I affirm that all information submitted as a part of, or supplemental to, this entry is a fair and accurate representation of this product. _____________________________________ Stanley Atcitty JOint Entry Arkansas Power Electronics International, Inc.; University of Arkansas; Rohm Co., LTD.; and the Department of Energy/ Energy Storage Program. 1. 1. Arkansas Power Electronics International, Inc. 535 W. Research Center Blvd. Fayetteville, AR 72701 USA Alexander B. Lostetter, President & CEO Phone: 479-443-5759

408

Modulation Field Induces Universe Rotation  

E-Print Network [OSTI]

In this paper, we consider a time dependent module field on spacetime extension without modifying commutative relation on noncommutative quantum plane. The significant idea is that $Lorentz$ symmetry is conserved in module and unmodule coordinate. We focus on the redefinition of spacetime structure without considering noncommutative bosonic gas in deforming the product between fields. Which the null vector is a vector on orthogonal $D$ dimensional $Hilbert$ spacetime. In $Riemann$ geometry, the equation of motion is deformed from an induced rotation. Particle field survives on the state composed by two theoretical assumed $null$ vectors, one is commutative, another is anticommutative. In the point of view, neutrino and photon mass are produced by its shift, the rotated effect generates a horizon in redefining particle field.

Chien Yu Chen

2008-06-30T23:59:59.000Z

409

introduction.vp  

Gasoline and Diesel Fuel Update (EIA)

10) 10) Release date:April 2010 Next release date: April 2011 Assumptions to the Annual Energy Outlook 2010 [PAGE LEFT BLANK INTENTIONALLY] 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2. Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3. International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4. Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 5. Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 6. Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 7. Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 8. Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 9. Oil and Gas Supply Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 10. Natural Gas Transmission and Distribution Module

410

The National Transport Code Collaboration Module Library  

Science Journals Connector (OSTI)

This paper reports on the progress in developing a library of code modules under the auspices of the National Transport Code Collaboration (NTCC). Code modules are high quality, fully documented software packages with a clearly defined interface. The modules provide a variety of functions, such as implementing numerical physics models; performing ancillary functions such as I/O or graphics; or providing tools for dealing with common issues in scientific programming such as portability of Fortran codes. Researchers in the plasma community submit code modules, and a review procedure is followed to insure adherence to programming and documentation standards. The review process is designed to provide added confidence with regard to the use of the modules and to allow users and independent reviews to validate the claims of the modules' authors. All modules include source code; clear instructions for compilation of binaries on a variety of target architectures; and test cases with well-documented input and output. All the NTCC modules and ancillary information, such as current standards and documentation, are available from the NTCC Module Library Website http://w3.pppl.gov/NTCC. The goal of the project is to develop a resource of value to builders of integrated modeling codes and to plasma physics researchers generally. Currently, there are more than 40 modules in the module library.

A.H. Kritz; G. Bateman; J. Kinsey; A. Pankin; T. Onjun; A. Redd; D. McCune; C. Ludescher; A. Pletzer; R. Andre; L. Zakharov; L. Lodestro; L.D. Pearlstein; R. Jong; W. Houlberg; P. Strand; J. Wiley; P. Valanju; H.St. John; R. Waltz; J. Mandrekas; T.K. Mau; J. Carlsson; B. Braams

2004-01-01T23:59:59.000Z

411

Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

States, acquire natural gas from foreign producers for resale States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. 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. Foreign gas transactions may occur via either pipeline (Canada or Mexico) or transport ships as liquefied natural gas (LNG). Energy Information Administration/Assumptions to the Annual Energy Outlook 2006 89 Figure 7. Oil and Gas Supply Model Regions Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Report #:DOE/EIA-0554(2006) Release date: March 2006

412

Quality control of polymer solar modules by lock-in thermography  

Science Journals Connector (OSTI)

We have characterized lateral imperfections of photovoltaic modules based on solution processed polymer-fullerene semiconductor blends by means of lock-in thermography (LIT). The active layer of the solar cell modules is based on the heterogeneous organic semiconductor system poly(3-hexylthiophene):phenyl- C 61 -butyric acid methyl ester and the power conversion efficiency of the modules reached nearly 2% under irradiation of an AM 1.5 solar simulator. Applying highly sensitive LIT allowed us to detect several kinds of laterally distributed defects originating from imperfections in the respective functional layers as well as in the quality of encapsulation. We show that LIT is a powerful method for the quality control of large area polymersolar cells and modules enabling fast feedback for optimization of production parameters.

Harald Hoppe; Jonas Bachmann; Burhan Muhsin; Karl-Heinz Dre; Ingo Riedel; Gerhard Gobsch; Claudia Buerhop-Lutz; Christoph J. Brabec; Vladimir Dyakonov

2010-01-01T23:59:59.000Z

413

Electrically tunable terahertz wave modulator based on complementary metamaterial and graphene  

SciTech Connect (OSTI)

In this paper, we design and numerically demonstrate an electrically controllable light-matter interaction in a hybrid material/metamaterial system consisting of an artificially constructed cross cut-wire complementary metamaterial and an atomically thin graphene layer to realize terahertz (THz) wave modulator. By applying a bias voltage between the metamaterial and the graphene layer, this modulator can dynamically control the amplitude and phase of the transmitted wave near 1.43 THz. Moreover, the distributions of current density show that this large modulation depth can be attributed to the resonant electric field parallel to the graphene sheet. Therefore, the modulator performance indicates the enormous potential of graphene for developing sophisticated THz communication systems.

He, Xun-jun, E-mail: hexunjun@hrbust.edu.cn; Li, Teng-yue; Wang, Lei; Wang, Jian-min; Jiang, Jiu-xing [Department of Electronic Science and technology, School of Applied Sciences, Harbin University of Science and Technology, Harbin 150080 (China); Yang, Guo-hui; Meng, Fan-yi; Wu, Qun [Department of Electronic and Communications Engineering, School of Electronic Information Engineering, Harbin Institute of Technology, Harbin 150001 (China)

2014-05-07T23:59:59.000Z

414

The National Energy Modeling System: An Overview 1998 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

COAL MARKET MODULE COAL MARKET MODULE blueball.gif (205 bytes) Coal Production Submodule blueball.gif (205 bytes) Coal Distribution Submodule blueball.gif (205 bytes) Coal Export Component The coal market module (CMM) represents the mining, transportation, and pricing of coal, subject to end-use demand. Coal supplies are differentiated by heat and sulfur content. The CMM also determines the minimum cost pattern of coal supply to meet exogenously defined U.S. coal export demands as a part of the world coal market. Coal supply is projected on a cost-minimizing basis, constrained by existing contracts. Twelve different coal types are differentiated with respect to thermal grade, sulfur content, and underground or surface mining. The domestic production and distribution of coal is forecast for 13 demand regions and 11 supply

415

The harmonization of Canadian and U.S. window programs and standards. Impact on U-factor and SHGC of differences in simulation styles and assumptions  

SciTech Connect (OSTI)

The thermal performance of a window is currently characterized by the window`s thermal transmittance (U-factor) and its solar heat gain coefficient. The National Fenestration Rating Council (NFRC) has established a system for rating the thermal performance of windows. the U-factor is determined through computer simulation and validated with physical tests. The solar heat gain coefficient is determined for homogeneous products through computer simulation. Test methods exist for measuring solar heat gain through more complex products, although there is currently no standard. Under the NFRC`s rating program, a window must be simulated using the Window 4.1 and Frame 3.1 computer programs. There is some debate as to how accurately these computer programs simulate actual windows. This report addresses the differences in simulation styles and assumptions and what impact these differences have on the U-factor and solar heat gain coefficient. Section 2.0 covers center-of-glass modeling, section 3.0 covers spacer modeling, section 4.0 covers frame modeling, and section 5.0 concludes by weight the relative importance of the assumptions discussed. The focus of this research is on U-factor. For a more detailed study of solar heat gain coefficients refer to Wright (1995). This report also addresses the efficacy of various techniques, such as increasing glazing gap width or applying low-emittance coatings to interior glazing surfaces, at reducing total window U-factors.

NONE

1995-05-31T23:59:59.000Z

416

Approved Module Information for ME4501, 2014/5 Module Title/Name: Computational Fluid Dynamics and  

E-Print Network [OSTI]

-requisites: Thermodynamics and Fluids (ME3011). Engineering Mathematics 2 (AM21EM). Co-requisites: None Specified ModuleApproved Module Information for ME4501, 2014/5 Module Title/Name: Computational Fluid Dynamics and Applications Module Code: ME4501 School: Engineering and Applied Science Module Type: Standard Module New

Neirotti, Juan Pablo

417

Lyapunov-Based Distributed Control of the Safety Factor Profile in a Tokamak Plasma  

E-Print Network [OSTI]

Lyapunov-Based Distributed Control of the Safety Factor Profile in a Tokamak Plasma Federico safety-factor profile in a tokamak plasma. Using relevant physical models and simplifying assumptions within a tokamak plasma is a key issue to achieve (and maintain) in a safe manner high

Boyer, Edmond

418

Pursuit-Evasion Game for Normal Distributions Chanyoung Jun Subhrajit Bhattacharya  

E-Print Network [OSTI]

to this line of research. In particular, we propose some weak assumptions and design control strategies distributions that evolve according to a Kalman filter as new sensor readings (observation from overhead camera/satellite images) are obtained. The objective is to design the control commands issued by the pursuer (which

Ghrist, Robert W.

419

DHCVIM: A direct heating containment vessel interactions module  

SciTech Connect (OSTI)

Models for prediction of direct containment heating phenomena as implemented in the DHCVIM computer module are described. The models were designed to treat thermal, chemical and hydrodynamic processes in the three regions of the Sandia National Laboratory Surtsey DCH test facility: the melt generator, cavity and vessel. The fundamental balance equations, along with constitutive relations are described. A combination of Eulerian treatment for the gas phase and Lagrangian treatment for the droplet phase is used in the modeling. Comparisons of calculations and DCH-1 test results are presented. Reasonable agreement is demonstrated for the vessel pressure rise, melt generator pressure decay and particle size distribution.

Ginsberg, T.; Tutu, N.K.

1987-01-01T23:59:59.000Z

420

EFFECTIVE EFFICIENCY AND PERFORMANCE RATIO AS ENERGY RATING SYSTEM FOR PV MODULES Marko Topic1  

E-Print Network [OSTI]

conditions (STC) with one-sun irradiance (G0 = 1 kW/m2 , AM1.5 spectrum) and cell temperature (Tj) of 25 º irradiance, ambient temperature, and solar- incidence-angle distributions at the installation site daylight ambient temperature. Five PV modules are evaluated by both approaches in Ljubljana for different

Sites, James R.

Note: This page contains sample records for the topic "distribution module assumption" 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

Preliminary Assumptions for Wind Technologies  

E-Print Network [OSTI]

of operation Investment Tax Credit (ITC) alternative 30% towards developer's income tax for qualifying solar" prior to 12/31/16 Post-2016, credit drops to 10% - solar PV, geothermal 6 #12;Status of Regional RPS utilities Wind development in the PNW has slowed down significantly compared to the past decade Little new

422

Modules over principal ideal rings  

E-Print Network [OSTI]

need to note, however, , the difference between the two types of "union" of a set of submodules N 1 of a module N, The first is the "set-theoretic union" con- sisting of representatives of all the distinct elements to be found in the Ni... ideal R, which cons1sts of the elements of the ring. Consider the subset B of R of all elements of the form ra + na, where r and a are ring ele- ments and n is an integer. If rla + nla, r2a + n2a s B, then la + nla 2 2a la r2a + la 2 = (rl - r2)a...

Vieaux, Jules Bellin

2012-06-07T23:59:59.000Z

423

Unifying distribution functions: some lesser known distributions  

E-Print Network [OSTI]

We show that there is a way to unify distribution functions that describe simultaneously a signal in space and (spatial) frequency. Probably the most known of them is the Wigner distribution function. Here we show how to unify functions of the Cohen class, Rihacek's complex energy function, Husimi and Glauber-Sudarshan distribution functions.

Moya-Cessa, J R; Berriel-Valdos, L R; Aguilar-Loreto, O; Barberis-Blostein, P

2008-01-01T23:59:59.000Z

424

Summary and Presentations from Estimating the Benefits and Costs of Distributed Energy Technologies Workshop Now Available  

Broader source: Energy.gov [DOE]

Beginning on September 30, 2014, the Department of Energy hosted a two-day workshop on Estimating the Benefits and Costs of Distributed Energy Technologies in Washington DC. The purpose of the workshop was to foster discussion about the analytic challenges associated with valuing the diverse impacts of deploying distributed energy technologies. Many valuation studies have been published in recent years, using different methods and assumptions.

425

Approved Module Information for BH3328, 2014/5 Module Title/Name: Psychology and Work Module Code: BH3328  

E-Print Network [OSTI]

* Organizational culture, climate, and change * Applying the Psychology of Work and Organizations The learning communication Planning and organizing Interpersonal discussion and communication Indicative Module Content

Neirotti, Juan Pablo

426

In-Line Post-Process Scribing for Reducing Cell to Module Efficiency Gap in Monolithic Thin Film Photovoltaics  

E-Print Network [OSTI]

The gap between cell and module efficiency is a major challenge for all photovoltaic (PV) technologies. For monolithic thin film PV modules, a significant fraction of this gap has been attributed to parasitic shunts, and other defects, distributed across the module. In this paper, we show that it is possible to contain or isolate these shunt defects, using the state of the art laser scribing processes, after the fabrication of the series connected module is finished. We discuss three possible alternatives, and quantify the performance gains for each technique. We demonstrate that using these techniques, it is possible to recover up to 50% of the power lost to parasitic shunts, which results in 1-2% (absolute) increase in module efficiencies for typical thin film PV technologies.

Dongaonkar, Sourabh

2013-01-01T23:59:59.000Z

427

Commissioning of intensity modulated neutron radiotherapy (IMNRT)  

SciTech Connect (OSTI)

Purpose: Intensity modulated neutron radiotherapy (IMNRT) has been developed using inhouse treatment planning and delivery systems at the Karmanos Cancer Center/Wayne State University Fast Neutron Therapy facility. The process of commissioning IMNRT for clinical use is presented here. Results of commissioning tests are provided including validation measurements using representative patient plans as well as those from the TG-119 test suite. Methods: IMNRT plans were created using the Varian Eclipse optimization algorithm and an inhouse planning system for calculation of neutron dose distributions. Tissue equivalent ionization chambers and an ionization chamber array were used for point dose and planar dose distribution comparisons with calculated values. Validation plans were delivered to water and virtual water phantoms using TG-119 measurement points and evaluation techniques. Photon and neutron doses were evaluated both inside and outside the target volume for a typical IMNRT plan to determine effects of intensity modulation on the photon dose component. Monitor unit linearity and effects of beam current and gantry angle on output were investigated, and an independent validation of neutron dosimetry was obtained. Results: While IMNRT plan quality is superior to conventional fast neutron therapy plans for clinical sites such as prostate and head and neck, it is inferior to photon IMRT for most TG-119 planning goals, particularly for complex cases. This results significantly from current limitations on the number of segments. Measured and calculated doses for 11 representative plans (six prostate/five head and neck) agreed to within -0.8 {+-} 1.4% and 5.0 {+-} 6.0% within and outside the target, respectively. Nearly all (22/24) ion chamber point measurements in the two phantom arrangements were within the respective confidence intervals for the quantity [(measured-planned)/prescription dose] derived in TG-119. Mean differences for all measurements were 0.5% (max = 7.0%) and 1.4% (max = 4.1%) in water and virtual water, respectively. The mean gamma pass rate for all cases was 92.8% (min = 88.6%). These pass rates are lower than typically achieved with photon IMRT, warranting development of a planar dosimetry system designed specifically for IMNRT and/or the improvement of neutron beam modeling in the penumbral region. The fractional photon dose component did not change significantly in a typical IMNRT plan versus a conventional fast neutron therapy plan, and IMNRT delivery is not expected to significantly alter the RBE. All other commissioning results were considered satisfactory for clinical implementation of IMNRT, including the external neutron dose validation, which agreed with the predicted neutron dose to within 1%. Conclusions: IMNRT has been successfully commissioned for clinical use. While current plan quality is inferior to photon IMRT, it is superior to conventional fast neutron therapy. Ion chamber validation results for IMNRT commissioning are also comparable to those typically achieved with photon IMRT. Gamma pass rates for planar dose distributions are lower than typically observed for photon IMRT but may be improved with improved planar dosimetry equipment and beam modeling techniques. In the meantime, patient-specific quality assurance measurements should rely more heavily on point dose measurements with tissue equivalent ionization chambers. No significant technical impediments are anticipated in the clinical implementation of IMNRT as described here.

Burmeister, Jay; Snyder, Michael [Karmanos Cancer Center, Wayne State University School of Medicine, Detroit, Michigan 48201 (United States); Spink, Robyn; Liang Liang; Bossenberger, Todd; Halford, Robert [Karmanos Cancer Center, Detroit, Michigan 48201 (United States); Brandon, John [Michigan State University, East Lansing, Michigan 48201 (United States); Delauter, Jonathan [Wayne State University School of Medicine, Detroit, Michigan 48201 (United States)

2013-02-15T23:59:59.000Z

428

Definition: PV module | Open Energy Information  

Open Energy Info (EERE)

Definition Definition Edit with form History Facebook icon Twitter icon » Definition: PV module Jump to: navigation, search Dictionary.png PV module A unit comprised of several PV cells, and the principal unit of a PV array; it is intended to generate direct current power under un-concentrated sunlight.[1][2] View on Wikipedia Wikipedia Definition A solar panel is a set of solar photovoltaic modules electrically connected and mounted on a supporting structure. A photovoltaic module is a packaged, connected assembly of photovoltaic cells. The solar module can be used as a component of a larger photovoltaic system to generate and supply electricity in commercial and residential applications. Each module is rated by its DC output power under standard test conditions (STC), and

429

Power module assemblies with staggered coolant channels  

DOE Patents [OSTI]

A manifold is provided for supporting a power module assembly with a plurality of power modules. The manifold includes a first manifold section. The first face of the first manifold section is configured to receive the first power module, and the second face of the first manifold section defines a first cavity with a first baseplate thermally coupled to the first power module. The first face of the second manifold section is configured to receive the second power module, and the second face of the second manifold section defines a second cavity with a second baseplate thermally coupled to the second power module. The second face of the first manifold section and the second face of the second manifold section are coupled together such that the first cavity and the second cavity form a coolant channel. The first cavity is at least partially staggered with respect to second cavity.

Herron, Nicholas Hayden; Mann, Brooks S; Korich, Mark D

2013-07-16T23:59:59.000Z

430

INTEGRATING ENGINEERING WEB SERVICES WITH DISTRIBUTED DATA FLOWS AND  

E-Print Network [OSTI]

INTEGRATING ENGINEERING WEB SERVICES WITH DISTRIBUTED DATA FLOWS AND MOBILE CLASSES David Liu1 engineering web services. Software modules have been designed and implemented to facilitate the construction approach for integrating large engineering software services. KEY WORDS Engineering web services; service

Stanford University

431

ECOC 2014, Cannes -France Fully-Distributed Co  

E-Print Network [OSTI]

an proposed solution achieves low state-of-the-art GMPLS/PCE arch Introduction The routing, modulation RMSA with a distributed There are two different networ GMPLS 3 and GMPLS with pa element (GMPLS/PCE 4 ). In G each node maintains its own information and work for routin and optical spectrum assignmen GMPLS/PCE

Yoo, S. J. Ben

432

Distributed feedback laser biosensor incorporating a titanium dioxide nanorod surface  

E-Print Network [OSTI]

Distributed feedback laser biosensor incorporating a titanium dioxide nanorod surface Chun Ge,1 emission wavelength is modulated by the adsorption of biomolecules, whose greater dielectric permittivity- dimensional volume overlap between the DFBLB resonant mode and the region where biomolecule adsorption can oc

Cunningham, Brian

433

Topic 5: Renewable Power 1Networking and Distributed Systems  

E-Print Network [OSTI]

Communications and Control in Smart Grid 10 · Wave power is the energy from ocean surface waves. · Orbital motion the device to the ocean floor to hold it. cable Power modules Tubular section #12;Wave Energy Converter DrTopic 5: Renewable Power 1Networking and Distributed Systems Department of Electrical & Computer

Mohsenian-Rad, Hamed

434

An ultrafast carbon nanotube terahertz polarisation modulator  

SciTech Connect (OSTI)

We demonstrate ultrafast modulation of terahertz radiation by unaligned optically pumped single-walled carbon nanotubes. Photoexcitation by an ultrafast optical pump pulse induces transient terahertz absorption in nanowires aligned parallel to the optical pump. By controlling the polarisation of the optical pump, we show that terahertz polarisation and modulation can be tuned, allowing sub-picosecond modulation of terahertz radiation. Such speeds suggest potential for semiconductor nanowire devices in terahertz communication technologies.

Docherty, Callum J.; Stranks, Samuel D.; Habisreutinger, Severin N.; Joyce, Hannah J.; Herz, Laura M.; Nicholas, Robin J.; Johnston, Michael B., E-mail: m.johnston@physics.ox.ac.uk [Department of Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU (United Kingdom)

2014-05-28T23:59:59.000Z

435

In-line thermoelectric module  

DOE Patents [OSTI]

A thermoelectric module with a plurality of electricity generating units each having a first end and a second end, the units being arranged first end to second end along an in-line axis. Each unit includes first and second elements each made of a thermoelectric material, an electrically conductive hot member arranged to heat one side of the first element, and an electrically conductive cold member arranged to cool another side of the first element and to cool one side of the second element. The hot member, the first element, the cold member and the second element are supported in a fixture, are electrically connected respectively to provide an electricity generating unit, and are arranged respectively in positions along the in-line axis. The individual components of each generating unit and the respective generating units are clamped in their in-line positions by a loading bolt at one end of the fixture and a stop wall at the other end of the fixture. The hot members may have a T-shape and the cold members an hourglass shape to facilitate heat transfer. The direction of heat transfer through the hot members may be perpendicular to the direction of heat transfer through the cold members, and both of these heat transfer directions may be perpendicular to the direction of current flow through the module.

Pento, Robert (Algonquin, IL); Marks, James E. (Glenville, NY); Staffanson, Clifford D. (S. Glens Falls, NY)

2000-01-01T23:59:59.000Z

436

In-Line Thermoelectric Module  

SciTech Connect (OSTI)

A thermoelectric module with a plurality of electricity generating units each having a first end and a second end, the units being arranged first end to second end along an-in-line axis. Each unit includes first and second elements each made of a thermoelectric material, an electrically conductive hot member arranged to heat one side of the first element, and an electrically conductive cold member arranged to cool another side of the first element and to cool one side of the second element. The hot member, the first element, the cold member and the second element are supported in a fixture, are electrically connected respectively to provide an electricity generating unit, and are arranged respectively in positions along the in-line axis. The individual components of each generating unit and the respective generating units are clamped in their in-line positions by a loading bolt at one end of the fixture and a stop wall at the other end of the fixture. The hot members may have a T-shape and the cold members an hourglass shape to facilitate heat transfer. The direction of heat transfer through the hot members may be perpendicular to the direction of heat transfer through the cold members, and both of these heat transfer directions maybe perpendicular to the direction-of current flow through the module.

Pento, Robert; Marks, James E.; Staffanson, Clifford D.

1998-07-28T23:59:59.000Z

437

Photovoltaic Energy Technology Module | Open Energy Information  

Open Energy Info (EERE)

Photovoltaic Energy Technology Module Photovoltaic Energy Technology Module Jump to: navigation, search Tool Summary Name: Photovoltaic Energy Technology Module Agency/Company /Organization: World Bank Sector: Energy Focus Area: Renewable Energy, Solar Topics: Technology characterizations Website: web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTENERGY2/EXTRENENERGYTK/0,, References: Photovoltaic Energy Technology Module[1] Resources Portable Solar Photovoltaic Lanterns: Performance and Certification Specification, and Type Approval, ESMAP TECHNICAL PAPER 078 Testing of Storage Batteries used in Stand Alone Photovoltaic Power Systems, Test procedures and examples of test results Technical Specifications for Solar Home Systems (SHS), Rural Electrification and Renewable Energy Development (PV Component) Project

438

Frequencies Studies Applied to Photovoltaic Modules.  

E-Print Network [OSTI]

?? This master thesis proposes to study applications of frequencies studies to the case of photovoltaic modules and photovoltaic plants. Such studies are little used (more)

Miquel, Clment

2011-01-01T23:59:59.000Z

439

Solid State Marx Modulators for Emerging Applications  

SciTech Connect (OSTI)

Emerging linear accelerator applications increasingly push the boundaries of RF system performance and economics. The power modulator is an integral part of RF systems whose characteristics play a key role in the determining parameters such as efficiency, footprint, cost, stability, and availability. Particularly within the past decade, solid-state switch based modulators have become the standard in high-performance, high power modulators. One topology, the Marx modulator, has characteristics which make it particularly attractive for several emerging applications. This paper is an overview of the Marx topology, some recent developments, and a case study of how this architecture can be applied to a few proposed linear accelerators.

Kemp, M.A.; /SLAC

2012-09-14T23:59:59.000Z

440

Multiple Layer Graphene Optical Modulator - Energy Innovation...  

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

Materials Advanced Materials Find More Like This Return to Search Multiple Layer Graphene Optical Modulator Lawrence Berkeley National Laboratory Contact LBL About This...

Note: This page contains sample records for the topic "distribution module assumption" 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

Silicon Photonics for Modulation, Switching, and Tuning  

Science Journals Connector (OSTI)

Thermal and electro-refractive silicon photonic modulators, switches, and tunable filters have been demonstrated with ultralow switching energies and high-speed operation. These...

Watts, Michael

442

D-modules on smooth toric varieties  

E-Print Network [OSTI]

D-MODULES ON SMOOTH TORIC VARIETIES. MIRCEA MUSTAT A, GREGORY G. SMITH, HARRISON TSAI,. AND ULI WALTHER. Abstract. Let X be a smooth...

443

Encapsulation of High Temperature Thermoelectric Modules  

Broader source: Energy.gov [DOE]

Presents concept for hermetic encapsulation of TE modules addressing key failure mechanism, TE material oxidation, which severely impacts long term performance

444

Detailed Course Module Description | Department of Energy  

Energy Savers [EERE]

lists the course modules for building science courses offered at Cornell's Collaborator Sustainable Buildingi Practice course. coursemodule.pdf More Documents & Publications...

445

Explosives detection with a frequency modulation spectrometer  

Science Journals Connector (OSTI)

An explosives detection instrument was designed and tested at SRI International. The instrument uses frequency modulation spectroscopy with midinfrared lead-salt diode lasers to...

Riris, H; Carlisle, C B; McMillen, D F; Cooper, D E

1996-01-01T23:59:59.000Z

446

The Effects of Anchor Length, Test Difficulty, Population Ability Differences, Mixture of Populations and Sample Size on the Psychometric Properties of Levine Observed Score Linear Equating Method for Different Assumptions  

E-Print Network [OSTI]

+ b?A, and ?Y = c + d?A. i.e. the true scores of X and A and Y and A are linearly related. This is the congenericity assumption. However, the two sets differ on the third assumption that they make. For the first set, the third assumption is L3... is equity, which states that it must be a matter of indifference to the test taker whether he or she takes X or Y. Although equatability is a prerequisite for equity, it does not imply equity because two tests that measure the same construct can differ...

Carvajal, Jorge E.

2011-02-15T23:59:59.000Z

447

Assumptions and Criteria for Performing a Feasability Study of the Conversion of the High Flux Isotope Reactor Core to Use Low-Enriched Uranium Fuel  

SciTech Connect (OSTI)

A computational study will be initiated during fiscal year 2006 to examine the feasibility of converting the High Flux Isotope Reactor from highly enriched uranium fuel to low-enriched uranium. The study will be limited to steady-state, nominal operation, reactor physics and thermal-hydraulic analyses of a uranium-molybdenum alloy that would be substituted for the current fuel powder--U{sub 3}O{sub 8} mixed with aluminum. The purposes of this document are to (1) define the scope of studies to be conducted, (2) define the methodologies to be used to conduct the studies, (3) define the assumptions that serve as input to the methodologies, (4) provide an efficient means for communication with the Department of Energy and American research reactor operators, and (5) expedite review and commentary by those parties.

Primm, R.T., III; Ellis, R.J.; Gehin, J.C.; Moses, D.L.; Binder, J.L.; Xoubi, N. (U. of Cincinnati)

2006-02-01T23:59:59.000Z

448

Annual Coal Distribution Report  

Gasoline and Diesel Fuel Update (EIA)

Distribution Report Release Date: December 19, 2013 | Next Release Date: December 12, 2014 | full report | RevisionCorrection Revision to the Annual Coal Distribution Report...

449

Distribution Grid Integration  

Broader source: Energy.gov [DOE]

The DOE Systems Integration team funds distribution grid integration research and development (R&D) activities to address the technical issues that surround distribution grid planning,...

450

Module Title: Solid state and ultrafast lasers Module Code: OPTO6002  

E-Print Network [OSTI]

Module lecturers Prof Andy Clarkson, Dr Bill Brocklesby Contact (email ID) wac@orc.soton.ac.uk, wsb@orc

Anderson, Jim

451

Module No: 410331International Trade LawModule Title: Pre-requisite  

E-Print Network [OSTI]

and technology transfer contracts; also, a brief study of international trade arbitration and its rulesModule No: 410331International Trade LawModule Title: Pre-requisite: Module Type: specialization Description The international trade law course is a brief study of the topics of electronic commerce

452

Modular ITT Module D Modular ITT Module D Version 1 16/02/2012  

E-Print Network [OSTI]

manage health and safety at work. Your responses should include: basic statement on safety awarenessModular ITT ­ Module D Modular ITT ­ Module D Version 1 16/02/2012 Module D ­ Health & Safety an overall failing of your bid. This section allows us to assess your competency for health and safety. We

453

AC PV Modules Take a standard DC PV module and connect a microinverter  

E-Print Network [OSTI]

modules. These inverters range in power from 700 watts up to 1 megawatt. DC maximum system voltages can and up to 13 inverters for the 210 W version to be installed on the same AC output cable. home power 136, and secure a listing to UL1741 for a pre-assembled module/inverter device, and you have an AC PV module

Johnson, Eric E.

454

Effect of collisional heat transfer in ICRF power modulation experiment on ASDEX Upgrade  

SciTech Connect (OSTI)

ICRF (ion cyclotron range of frequencies) heating experiments were performed in D-H plasmas at various H concentrations on ASDEX Upgrade. The rf power was modulated to measure the electron power deposition profile from electron temperature modulation. To minimize the contribution from indirect collisional heating and the effect of radial transport, the rf power was modulated at 50 Hz. However, peaking of electron temperature modulation was still observed around the hydrogen cyclotron resonance indicating collisional heating contribution. Time dependent simulation of the hydrogen distribution function was performed for the discharges, using the full-wave code AORSA (E.F. Jaeger, et al., Phys. Plasmas, Vol. 8, page 1573 (2001)) coupled to the Fokker-Planck code CQL3D (R.W. Harvey, et al., Proc. IAEA (1992)). In the present experimental conditions, it was found that modulation of the collisional heating was comparable to that of direct wave damping. Impact of radial transport was also analyzed and found to appreciably smear out the modulation profile and reduce the phase delay.

Tsujii, N. [Max-Planck-Institut fr Plasmaphysik, Garching (Germany); University of Tokyo, Kashiwa (Japan); D'Inca, R.; Bilato, R.; Bobkov, Vl. V.; Brambilla, M.; Schneider, P. [Max-Planck-Institut fr Plasmaphysik, Garching (Germany); Noterdaeme, J.-M. [Max-Planck-Institut fr Plasmaphysik, Garching, Germany and Universiteit Gent, Gent (Belgium); Van Eester, D.; Lerche, E. A. [JET-EFDA Culham Science Center, Abingdon (United Kingdom); LPP-ERM/KMS, Association EURATOM - Belgian State, Brussels (Belgium); Harvey, R. W. [CompX, Del Mar (United States); Jaeger, E. F. [XCEL Engineering, Oak Ridge (United States); Collaboration: ASDEX Upgrade Team

2014-02-12T23:59:59.000Z

455

Journal of Peasant Studies 37(4), 2010, forthcoming [version that was sent to the journal for production] Franco et al_EU biofuels_JPS_prodn-corr, 21/07/2010 Assumptions in the European Union biofuels policy:  

E-Print Network [OSTI]

The biofuel project is an agro-industrial development and politically contested policy process where governments increasingly become global actors. European Union (EU) biofuels policy rests upon arguments about societal benefits of three main kinds namely, environmental protection (especially greenhouse gas savings), energy security and rural development, especially in the global South. Each argument involves optimistic assumptions about what the putative benefits mean and how they can be fulfilled. After examining those assumptions, we

unknown authors

456

Performance characterization of an internsity-modulated fiber optic displacement sensor  

SciTech Connect (OSTI)

A testbed simulating an intensity-modulated fiber optic displacement sensor is experimentally characterized, and the implications regarding sensor design are discussed. Of interest are the intensity distribution of the transmitted optical signal and the relationships between sensor architecture and performance. Particularly, an intensity-modulated sensor's sensitivity, linearity, displacement range, and resolution are functions of the relative positioning of its transmitting and receiving fibers. In this paper, sensor architectures with various combinations of these performance metrics are discussed. A sensor capable of micrometer resolution is reported, and it is concluded that this work could lead to an improved methodology for sensor design.

Moro, Erik Allan [Los Alamos National Laboratory; Todd, Michael D [Los Alamos National Laboratory; Puckett, Santhony D [Los Alamos National Laboratory

2010-09-30T23:59:59.000Z

457

Analysis and Design of Smart PV Module  

E-Print Network [OSTI]

This thesis explores the design of a smart photovoltaic (PV) module- a PV module in which PV cells in close proximity are electrically grouped to form a pixel and are connected to dc-dc converter blocks which reside embedded in the back pane...

Mazumdar, Poornima

2012-12-10T23:59:59.000Z

458

Testing Protocol for Module Encapsulant Creep (Presentation)  

SciTech Connect (OSTI)

Recently there has been an interest in the use of thermoplastic encapsulant materials in photovoltaic modules to replace chemically crosslinked materials, e.g., ethylene-vinyl acetate. The related motivations include the desire to: reduce lamination time or temperature; use less moisture-permeable materials; or use materials with better corrosion characteristics. However, the use of any thermoplastic material in a high-temperature environment raises safety and performance concerns, as the standardized tests currently do not expose the modules to temperatures in excess of 85C, yet modules may experience temperatures above 100C in operation. Here we constructed eight pairs of crystalline-silicon modules and eight pairs of glass/encapsulation/glass mock modules using different encapsulation materials of which only two were designed to chemically crosslink. One module set was exposed outdoors with insulation on the back side in Arizona in the summer, and an identical set was exposed in environmental chambers. High precision creep measurements and performance measurements indicate that despite many of these polymeric materials being in the melt state at some of the highest outdoor temperatures achievable, very little creep was seen because of their high viscosity, temperature heterogeneity across the modules, and in the case of the crystalline-silicon modules, the physical restraint of the backsheet. These findings have very important implications for the development of IEC and UL qualification and safety standards, and in regards to the necessary level of cure during the processing of crosslinking encapsulants.

Kempe, M. D.; Miller, D. C.; Wohlgemuth, J. H.; Kurtz, S. R.; Moseley, J. M.; Shah, Q.; Tamizhmani, G.; Sakurai, K.; Inoue, M.; Doi, T.; Masuda, A.

2012-02-01T23:59:59.000Z

459

Nutrient Management Module No. 12 Water Quality  

E-Print Network [OSTI]

Nutrient Management Module No. 12 Water Quality Considerations and Regulations by Susan Mc Management Competency Area II: Nutrient movement in soil and water. Objectives After completing this module issues 3.Become familiar with federal and state water quality regulations 4.Identify Best Management

Lawrence, Rick L.

460

Identification coding schemes for modulated reflectance systems  

DOE Patents [OSTI]

An identifying coding apparatus employing modulated reflectance technology involving a base station emitting a RF signal, with a tag, located remotely from the base station, and containing at least one antenna and predetermined other passive circuit components, receiving the RF signal and reflecting back to the base station a modulated signal indicative of characteristics related to the tag.

Coates, Don M. (Santa Fe, NM); Briles, Scott D. (Los Alamos, NM); Neagley, Daniel L. (Albuquerque, NM); Platts, David (Santa Fe, NM); Clark, David D. (Santa Fe, NM)

2006-08-22T23:59:59.000Z

Note: This page contains sample records for the topic "distribution module assumption" 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

Workplace Training Module: Enhancing Ecotourism Business Performance  

E-Print Network [OSTI]

Workplace Training Module: Enhancing Ecotourism Business Performance (Level 5 ­ 10 credits as part on understanding best practice in ecotourism development and management (see second part of Appendix 1). The module focuses on the ecotourism business dimension ­ emphasizing best case examples of what creates successful

462

Electro-Optic Modulation of Single Photons  

E-Print Network [OSTI]

We use the Stokes photon of a biphoton pair to set the time origin for electro-optic modulation of the wave function of the anti-Stokes photon thereby allowing arbitrary phase and amplitude modulation. We demonstrate conditional single-photon wave functions composed of several pulses, or instead, having gaussian or exponential shapes.

Pavel Kolchin; Chinmay Belthangady; Shengwang Du; G. Y. Yin; S. E. Harris

2008-08-02T23:59:59.000Z

463

Module Handbook Core Univ. of Oldenburg  

E-Print Network [OSTI]

· Mechanical and Electrical Systems of the WEC Content: Energy conversion process in Wind Turbines · Wind/EUREC Course 2008/2009 #12;EUREC Core Courses at University of Oldenburg, 1st Semester Wind Energy Module Module Description: Wind Energy Field: Core Oldenburg Courses: Wind Energy Wind Energy

Habel, Annegret

464

Raising the Bar for Quality PV Modules  

Office of Energy Efficiency and Renewable Energy (EERE)

Since the development and codification of testing standards for PV modules requires a lengthy multiyear process, Department of Energys SunShot Initiative and National Renewable Energy Laboratory worked together on an accelerated schedule for nine months in 2013 to develop a voluntary standard that goes beyond current test protocols to qualify superior PV modules.

465

Ion transport membrane module and vessel system  

DOE Patents [OSTI]

An ion transport membrane system comprising (a) a pressure vessel having an interior, an exterior, an inlet, and an outlet; (b) a plurality of planar ion transport membrane modules disposed in the interior of the pressure vessel and arranged in series, each membrane module comprising mixed metal oxide ceramic material and having an interior region and an exterior region, wherein any inlet and any outlet of the pressure vessel are in flow communication with exterior regions of the membrane modules; and (c) one or more gas manifolds in flow communication with interior regions of the membrane modules and with the exterior of the pressure vessel. The ion transport membrane system may be utilized in a gas separation device to recover oxygen from an oxygen-containing gas or as an oxidation reactor to oxidize compounds in a feed gas stream by oxygen permeated through the mixed metal oxide ceramic material of the membrane modules.

Stein, VanEric Edward (Allentown, PA); Carolan, Michael Francis (Allentown, PA); Chen, Christopher M. (Allentown, PA); Armstrong, Phillip Andrew (Orefield, PA); Wahle, Harold W. (North Canton, OH); Ohrn, Theodore R. (Alliance, OH); Kneidel, Kurt E. (Alliance, OH); Rackers, Keith Gerard (Louisville, OH); Blake, James Erik (Uniontown, OH); Nataraj, Shankar (Allentown, PA); Van Doorn, Rene Hendrik Elias (Obersulm-Willsbach, DE); Wilson, Merrill Anderson (West Jordan, UT)

2012-02-14T23:59:59.000Z

466

Ion transport membrane module and vessel system  

DOE Patents [OSTI]

An ion transport membrane system comprising (a) a pressure vessel having an interior, an exterior, an inlet, and an outlet; (b) a plurality of planar ion transport membrane modules disposed in the interior of the pressure vessel and arranged in series, each membrane module comprising mixed metal oxide ceramic material and having an interior region and an exterior region, wherein any inlet and any outlet of the pressure vessel are in flow communication with exterior regions of the membrane modules; and (c) one or more gas manifolds in flow communication with interior regions of the membrane modules and with the exterior of the pressure vessel.The ion transport membrane system may be utilized in a gas separation device to recover oxygen from an oxygen-containing gas or as an oxidation reactor to oxidize compounds in a feed gas stream by oxygen permeated through the mixed metal oxide ceramic material of the membrane modules.

Stein, VanEric Edward (Allentown, PA); Carolan, Michael Francis (Allentown, PA); Chen, Christopher M. (Allentown, PA); Armstrong, Phillip Andrew (Orefield, PA); Wahle, Harold W. (North Canton, OH); Ohrn, Theodore R. (Alliance, OH); Kneidel, Kurt E. (Alliance, OH); Rackers, Keith Gerard (Louisville, OH); Blake, James Erik (Uniontown, OH); Nataraj, Shankar (Allentown, PA); van Doorn, Rene Hendrik Elias (Obersulm-Willsbach, DE); Wilson, Merrill Anderson (West Jordan, UT)

2008-02-26T23:59:59.000Z

467

Likelihood analysis of earthquake focal mechanism distributions  

E-Print Network [OSTI]

In our paper published earlier we discussed forecasts of earthquake focal mechanism and ways to test the forecast efficiency. Several verification methods were proposed, but they were based on ad-hoc, empirical assumptions, thus their performance is questionable. In this work we apply a conventional likelihood method to measure a skill of forecast. The advantage of such an approach is that earthquake rate prediction can in principle be adequately combined with focal mechanism forecast, if both are based on the likelihood scores, resulting in a general forecast optimization. To calculate the likelihood score we need to compare actual forecasts or occurrences of predicted events with the null hypothesis that the mechanism's 3-D orientation is random. For double-couple source orientation the random probability distribution function is not uniform, which complicates the calculation of the likelihood value. To better understand the resulting complexities we calculate the information (likelihood) score for two rota...

Kagan, Y Y

2014-01-01T23:59:59.000Z

468

A Comparison of Key PV Backsheet and Module Properties from Fielded...  

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

of Key PV Backsheet and Module Properties from Fielded Module Exposures and Accelerated Test Conditions A Comparison of Key PV Backsheet and Module Properties from Fielded Module...

469

Root-Water-Uptake Based upon a New Water Stress Reduction and an Asymptotic Root Distribution Function  

Science Journals Connector (OSTI)

A water stresscompensating root-water-uptake module was developed based upon a newly proposed water stress reduction function and an asymptotic root distribution function. The water stress reduction function takes into account both soil water ...

K. Y. Li; R. De Jong; M. T. Coe; N. Ramankutty

2006-06-01T23:59:59.000Z

470

A Graphene-based Polarization-Insensitive Optical Modulator  

Science Journals Connector (OSTI)

We present a polarization-insensitive modulator. The performance of the designed modulator is comprehensively evaluated, showing a 3-dB modulation with 910-nm long waveguide, an...

hu, xiao; Gui, Chengcheng; Wang, Jian

471

CHARGED PARTICLE IDENTIFICATION WITH MODULES OF THE PLASTIC BALL  

E-Print Network [OSTI]

WITH MODULES OF THE PLASTIC BALL H.H. Gutbrod, M.R. Maier,WITH MODULES OF THE PLASTIC BALL H.H. Gutbrod, M.R. Maier*,of modules of the Plastic Ball detector for positive pions

Gutbrod, H.H.

2010-01-01T23:59:59.000Z

472

Approved Module Information for EE2EDP, 2014/5 Module Title/Name: Electronics Design Project Module Code: EE2EDP  

E-Print Network [OSTI]

Code: EE2EDP School: Engineering and Applied Science Module Type: Standard Module New Module? No Module Engineering Systems. BEng Electrical and Electronic Engineering. BEng Electronic Engineering and Computer competition among the groups to produce a 'best' system. * Students will be required to use creativity

Neirotti, Juan Pablo

473

Distributed Power Electronics for PV Systems (Presentation)  

SciTech Connect (OSTI)

An overview of the benefits and applications of microinverters and DC power optimizers in residential systems. Some conclusions from this report are: (1) The impact of shade is greater than just the area of shade; (2) Additional mismatch losses include panel orientation, panel distribution, inverter voltage window, soiling; (3) Per-module devices can help increase performance, 4-12% or more depending on the system; (4) Value-added benefits (safety, monitoring, reduced design constraints) are helping their adoption; and (5) The residential market is growing rapidly. Efficiency increases, cost reductions are improving market acceptance. Panel integration will further reduce price and installation cost. Reliability remains an unknown.

Deline, C.

2011-12-01T23:59:59.000Z

474

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This report serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, section 57(b)(1)). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

NONE

1995-02-01T23:59:59.000Z

475

Model documentation renewable fuels module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA`s ongoing mission to provide analytical and forecasting information systems.

NONE

1997-04-01T23:59:59.000Z

476

Model documentation report: Commercial sector demand module of the national energy modeling system  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This document serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

NONE

1994-08-01T23:59:59.000Z

477

Model documentation report: Residential sector demand module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document providing a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

NONE

1995-03-01T23:59:59.000Z

478

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

SciTech Connect (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

479

Criticality Calculations for Step?2 GPHS Modules  

Science Journals Connector (OSTI)

The Multi?Mission Radioisotope Thermoelectric Generator (MMRTG) will use an improved version of the General Purpose Heat Source (GPHS) module as its source of thermal power. This new version referred to as the Step?2 GPHS Module has additional and thicker layers of carbon fiber material (Fine Weaved Pierced Fabric) for increased strength over the original GPHS module. The GPHS uses alpha decay of 238 Pu in the oxide form as the primary source of heat and small amounts of other actinides are also present in the oxide fuel. Criticality calculations have been performed by previous researchers on the original version of the GPHS module (Step 0). This paper presents criticality calculations for the present Step?2 version. The Monte Carlo N?Particle eXtended code (MCNPX) was used for these calculations. Numerous configurations of GPHS module arrays surrounded by wet sand and other materials (to reflect the neutrons back into the stack with minimal absorption) were modeled. For geometries with eight GPHS modules (from a single MMRTG) surrounded by wet sand the configuration is extremely sub?critical; k eff is about 0.3. It requires about 1000 GPHS modules (from 125 MMRTGs) in a close?spaced stack to approach criticality ( k eff ?=?1.0) when surrounded by wet sand. The effect of beryllium in the MMRTG was found to be relatively small.

Ronald J. Lipinski; Danielle L. Hensen

2008-01-01T23:59:59.000Z

480

Criticality Calculations for Step-2 GPHS Modules  

SciTech Connect (OSTI)

The Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) will use an improved version of the General Purpose Heat Source (GPHS) module as its source of thermal power. This new version, referred to as the Step-2 GPHS Module, has additional and thicker layers of carbon fiber material (Fine Weaved Pierced Fabric) for increased strength over the original GPHS module. The GPHS uses alpha decay of {sup 238}Pu in the oxide form as the primary source of heat, and small amounts of other actinides are also present in the oxide fuel. Criticality calculations have been performed by previous researchers on the original version of the GPHS module (Step 0). This paper presents criticality calculations for the present Step-2 version. The Monte Carlo N-Particle eXtended code (MCNPX) was used for these calculations. Numerous configurations of GPHS module arrays surrounded by wet sand and other materials (to reflect the neutrons back into the stack with minimal absorption) were modeled. For geometries with eight GPHS modules (from a single MMRTG) surrounded by wet sand, the configuration is extremely sub-critical; k{sub eff} is about 0.3. It requires about 1000 GPHS modules (from 125 MMRTGs) in a close-spaced stack to approach criticality (k{sub eff} = 1.0) when surrounded by wet sand. The effect of beryllium in the MMRTG was found to be relatively small.

Lipinski, Ronald J. [Advanced Nuclear Concepts Department, Sandia National Laboratories, P.O Box 5800, Albuquerque, NM 87185 (United States); Hensen, Danielle L. [Risk and Reliability Department Sandia National Laboratories, P.O Box 5800, Albuquerque, NM 87185 (United States)

2008-01-21T23:59:59.000Z

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481

Criticality calculations for Step-2 GPHS modules.  

SciTech Connect (OSTI)

The Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) will use an improved version of the General Purpose Heat Source (GPHS) module as its source of thermal power. This new version, referred to as the Step-2 GPHS Module, has additional and thicker layers of carbon fiber material (Fine Weaved Pierced Fabric) for increased strength over the original GPHS module. The GPHS uses alpha decay of {sup 238}Pu in the oxide form as the primary source of heat, and small amounts of other actinides are also present in the oxide fuel. Criticality cal