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1

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

2

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

3

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

4

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).

5

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

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

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

8

Transfer-type products accompanying cold fusion reactions  

Science Journals Connector (OSTI)

Production of nuclei heavier than the target is treated for projectile-target combinations used in cold fusion reactions leading to superheavy nuclei. These products are related to transfer-type or to asymmetry-exit-channel quasifission reactions. The production of isotopes in the transfer-type reactions emitting of ? particles with large energies is discussed.

G. G. Adamian and N. V. Antonenko

2005-12-29T23:59:59.000Z

9

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).

10

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

11

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

12

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).

13

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

14

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

15

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

16

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).

17

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).

18

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...

19

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

20

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

Note: This page contains sample records for the topic "assumptions product types" 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

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

22

Table 23. Coal Mining Productivity by State, Mine Type, and Mine Production Range, 2012  

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

Mining Productivity by State, Mine Type, and Mine Production Range, 2012 Mining Productivity by State, Mine Type, and Mine Production Range, 2012 (short tons produced per employee hour) U.S. Energy Information Administration | Annual Coal Report 2012 Table 23. Coal Mining Productivity by State, Mine Type, and Mine Production Range, 2012 (short tons produced per employee hour) U.S. Energy Information Administration | Annual Coal Report 2012 Mine Production Range (thousand short tons) Coal-Producing State, Region 1 and Mine Type Above 1,000 Above 500 to 1,000 Above 200 to 500 Above 100 to 200 Above 50 to 100 Above 10 to 50 10 or Under Total 2 Alabama 1.69 2.50 1.95 1.72 1.83 0.69 0.55 1.68 Underground 1.73 - - - 1.08 0.31 - 1.64 Surface 1.36 2.50 1.95 1.72 2.11 1.19 0.55 1.75 Alaska 5.98 - - - - - - 5.98 Surface 5.98 - - - - - - 5.98 Arizona 7.38 - - - - - - 7.38 Surface

23

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

24

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

25

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).

26

Crude Oil and Petroleum Products Total Stocks Stocks by Type  

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

Product: Crude Oil and Petroleum Products Crude Oil All Oils (Excluding Crude Oil) Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Butylene Other Hydrocarbons Oxygenates (excluding Fuel Ethanol) MTBE Other Oxygenates Renewables (including Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Unfinished Oils Unfinished Oils, Naphthas & Lighter Unfinished Oils, Kerosene & Light Gas Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Comp. (MGBC) MGBC - Reformulated MGBC - Reformulated, RBOB MGBC - Reformulated, RBOB w/ Alcohol MGBC - Reformulated, RBOB w/ Ether MGBC - Reformulated, GTAB MGBC - Conventional MGBC - Conventional, CBOB MGBC - Conventional, GTAB MGBC - Conventional Other Aviation Gasoline Blending Comp. Finished Motor Gasoline Reformulated Gasoline Reformulated Gasoline Blended w/ Fuel Ethanol Reformulated Gasoline, Other Conventional Gasoline Conventional Gasoline Blended Fuel Ethanol Conventional Gasoline Blended Fuel Ethanol, Ed55 and Lower Conventional Other Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm Sulfur and under Distillate F.O., Greater than 15 to 500 ppm Sulfur Distillate F.O., Greater 500 ppm Sulfur Residual Fuel Oil Residual F.O., than 1.00% Sulfur Petrochemical Feedstocks Naphtha for Petro. Feedstock Use Other Oils for Petro. Feedstock Use Special Naphthas Lubricants Waxes Petroleum Coke Asphalt and Road Oil Miscellaneous Products Period-Unit: Monthly-Thousand Barrels Annual-Thousand Barrels

27

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

28

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

29

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.

30

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).

31

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.

32

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).

33

A Production Type GC Analysis System for Light Gases  

Science Journals Connector (OSTI)

......sonic, the gaseous combustion products are one...mixtures. In tests of hydrocarbon and metallic-hydrocarbon fuels the gas- eous combustion products which...of a coiled tube heat exchanger emersed...MIXTURES) ANALYSIS DATA; COLUMNS: SILICA......

R. C. Orth; H. B. Land

1971-06-01T23:59:59.000Z

34

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.

35

Random Sets and Invariants for (Type II) Continuous Tensor Product Systems of Hilbert  

E-Print Network [OSTI]

Random Sets and Invariants for (Type II) Continuous Tensor Product Systems of Hilbert Spaces for continuous tensor product systems of Hilbert spaces introduced by ARVESON [4] for classifying E0-semigroups continuous tensor product systems of Hilbert spaces with measure types of distributions of random (closed

Liebscher, Volkmar

36

Random Sets and Invariants for (Type II) Continuous Tensor Product Systems of Hilbert  

E-Print Network [OSTI]

Random Sets and Invariants for (Type II) Continuous Tensor Product Systems of Hilbert Spaces for continuous tensor product systems of Hilbert spaces introduced by ARVESON [4] for classifying E 0 ­semigroups continuous tensor product systems of Hilbert spaces with measure types of distributions of random (closed

Liebscher, Volkmar

37

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).

38

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

39

Development of gas production type curves for coalbed methane reservoirs.  

E-Print Network [OSTI]

??Coalbed methane is an unconventional gas resource that consists on methane production from the coal seams. The unique coal characteristic results in a dual-porosity system. (more)

Garcia Arenas, Anangela.

2004-01-01T23:59:59.000Z

40

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":""}]}

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


41

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.

42

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

43

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.

44

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

45

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

46

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

47

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

48

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

49

Abstract„Production of two types of superconducting  

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

68271-AB 68271-AB Abstract submitted to the 17 th International Conf. on Magnet Technology, Geneva, Sept. 24-28, 2001 Test Results for Prototypes of the Twin Aperture Dipoles for the LHC Insertion Region* J. Muratore, M. Anerella, J. Cozzolino, G. Ganetis, A. Ghosh, R. Gupta, M. Harrison, A. Jain, A. Marone, S. Plate, J. Schmalzle, R. Thomas, P. Wanderer, E. Willen and K.C. Wu Brookhaven National Laboratory, P.O. Box 5000, Upton, NY 11973-5000 Abstract-The Superconducting Magnet Division at Brookhaven National Laboratory (BNL) is building 26 insertion region dipoles of various types for the Large Hadron Collider (LHC) at CERN. These 9.45 m-long, 8 cm aperture magnets use the same coil design as the arc dipoles for the Relativistic Heavy Ion Collider (RHIC) at BNL. The

50

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

51

U.S. Crude Oil Production Forecast-Analysis of Crude Types  

Gasoline and Diesel Fuel Update (EIA)

oil production by crude type as it would be delivered from well-site or lease storage tanks. Once the oil enters transportation and distribution systems, it may be commingled...

52

RICOH FT MODELS PRODUCT ASU STOCK # FT 3013/3213/3513/3713 TONER TYPE 320 CP502006  

E-Print Network [OSTI]

RICOH FT MODELS PRODUCT ASU STOCK # FT 3013/3213/3513/3713 TONER TYPE 320 CP502006 DEVELOPER TYPE 310 CP502027 FT 3113/3313 TONER TYPE 310 CP502005 DEVELOPER TYPE 310 CP502027 FT 3320 TONER TYPE 3300 CP502025 DEVELOPER TYPE 3300 CP502026 FT 4415/4418/4421/4220/4222/4215 TONER TYPE 410 CP502028

Rhoads, James

53

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

54

Product symbolic status: development of a scale to assess different product types  

E-Print Network [OSTI]

for the degree of DOCTOR OF PHILOSOPHY Approved by: Chair of Committee, Charles D. Samuelson Committee Members, Stephanie C. Payne Larry G. Gresham James H. Leigh Head of Department, William S. Rholes August 2005 Major... International University Chair of Advisory Committee: Dr. Charles Samuelson The literature on status, product symbolism, product involvement, and reference group influence is reviewed to conceptually define the Product Symbolic Status construct...

Wright, James Arthur

2006-10-30T23:59:59.000Z

55

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

56

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.

57

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)

58

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),

59

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.

60

Are multiple parton interactions important at high energies? New types of hadrons production processes  

E-Print Network [OSTI]

Hadrons interaction at high energies is carried out by one color gluon exchange. All quarks and gluons contained in colliding hadrons take part in interaction and production of particles. The contribution of multiple parton interactions is negligible. Multiple hadrons production at high energies occurs only in three types of processes. The first process is hadrons production in gluon string, the second is hadrons production in two quark strings and the third is hadrons production in three quark strings. In proton-proton interaction production of only gluon string and two quark strings is possible. In proton-antiproton interaction production of gluon string, two quark strings and three quark strings is possible. Therefore multiplicity distributions in proton-proton and proton-antiproton interactions are different.

V. A. Abramovsky

2009-11-25T23:59:59.000Z

Note: This page contains sample records for the topic "assumptions product types" 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 - 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

62

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.

63

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.

64

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

65

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...

66

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

67

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

68

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

69

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).

70

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

71

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

72

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

73

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.

74

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.

75

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.

76

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

77

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.

78

AEO2011: Coal Production by Region and Type | OpenEI  

Open Energy Info (EERE)

by Region and Type by Region and Type Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 140, and contains only the reference case. The unit of measurement in this dataset is million short tons. The data is broken down into northern Appalachia, central Appalachia, southern Appalachia, eastern interior, western interior, gulf, Dakota medium, western montana, Wyoming, Rocky Mountain, Arizona/New Mexico and Washington/Alaska. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO Coal Production EIA Data application/vnd.ms-excel icon AE2011: Coal Production by Region and Type- Reference Case (xls, 122.3 KiB)

79

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.

80

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.

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


81

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.

82

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.

83

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

84

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)

85

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

86

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).

87

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).

88

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

89

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

90

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

91

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).

92

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).

93

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.

94

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

95

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

96

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,

97

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

98

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

99

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

100

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].

Note: This page contains sample records for the topic "assumptions product types" 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)

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.

102

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.

103

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.

104

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.

105

,"Crude Oil and Petroleum Products Total Stocks Stocks by Type"  

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

Total Stocks Stocks by Type" Total Stocks Stocks by Type" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks by Type",6,"Monthly","9/2013","1/15/1956" ,"Release Date:","11/27/2013" ,"Next Release Date:","Last Week of December 2013" ,"Excel File Name:","pet_stoc_typ_a_ep00_sae_mbbl_m.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_stoc_typ_a_ep00_sae_mbbl_m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov"

106

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).

107

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.

108

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.

109

2 - Types of gasifier for synthetic liquid fuel production: design and technology  

Science Journals Connector (OSTI)

Abstract There are many successful commercial coal gasifiers. The basic form and concept details, the design of the gasifier internals, and the operation of commercial coal gasifiers are closely guarded as proprietary information. In fact, the production of gas from carbonaceous feedstocks has been an expanding area of technology. This chapter will present the different categories of gasification reactors as they apply to various types of feedstocks. Within each category there are several commonly known processes, some of which are in current use and some of which are in lesser use.

J.G. Speight

2015-01-01T23:59:59.000Z

110

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

111

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.

112

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.

113

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.

114

U.S. Crude Oil and Petroleum Products Stocks by Type  

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

Product: Crude Oil and Petroleum Products Crude Oil All Oils (Excluding Crude Oil) Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Ethylene Propane/Propylene Propylene (Nonfuel Use) Normal Butane/Butylene Refinery Grade Butane Isobutane/Butylene Other Hydrocarbons Oxygenates (excluding Fuel Ethanol) MTBE Other Oxygenates Renewables (including Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Unfinished Oils Unfinished Oils, Naphthas & Lighter Unfinished Oils, Kerosene & Light Gas Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Comp. (MGBC) MGBC - Reformulated MGBC - Reformulated, RBOB MGBC - Reformulated, RBOB w/ Alcohol MGBC - Reformulated, RBOB w/ Ether MGBC - Reformulated, GTAB MGBC - Conventional MGBC - Conventional, CBOB MGBC - Conventional, GTAB MGBC - Conventional Other Aviation Gasoline Blending Comp. Finished Motor Gasoline Reformulated Gasoline Reformulated Gasoline Blended w/ Fuel Ethanol Reformulated Gasoline, Other Conventional Gasoline Conventional Gasoline Blended Fuel Ethanol Conventional Gasoline Blended Fuel Ethanol, Ed55 and Lower Conventional Other Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm Sulfur and under Distillate F.O., Greater than 15 to 500 ppm Sulfur Distillate F.O., Greater 500 ppm Sulfur Residual Fuel Oil Residual F.O., than 1.00% Sulfur Petrochemical Feedstocks Naphtha for Petro. Feedstock Use Other Oils for Petro. Feedstock Use Special Naphthas Lubricants Waxes Petroleum Coke Asphalt and Road Oil Miscellaneous Products

115

Production Of The ADD Type Kaluza-Klein Excitations At Future e+e-, ep And pp Colliders  

SciTech Connect (OSTI)

Possible production of ADD type Kaluza-Klein excitations are investigated at future high energy e+e-, ep and pp colliders. Discovery limits and signatures of such excitations are discussed at above colliders comparatively.

Billur, A. A.; Ciftci, A. K. [Physics Department, Faculty of Sciences, Ankara University, 06100 Tandogan, Ankara (Turkey); Ciftci, R. [Physics Department, Faculty of Sciences and Arts, Gazi University, 06500 Teknikokullar (Turkey); Inan, S. C. [Physics Department, Faculty of Sciences and Arts, Cumhuriyet University, 58140, Sivas (Turkey); Sultansoy, S. [Physics Department, Faculty of Sciences and Arts, Gazi University, 06500 Teknikokullar (Turkey); Institute of Physics, Academy of Sciences, H. Cavid Avenue 33, Baku (Azerbaijan)

2007-04-23T23:59:59.000Z

116

Production of the Randall-Sundrum Type Kaluza-Klein Excitations at Future e+e-, ep and pp Colliders  

SciTech Connect (OSTI)

Possible production of Randall-Sundrum type Kaluza-Klein excitations are investigated at future high energy e+e-, ep and pp colliders. Discovery limits and signatures of such excitations are discussed at above colliders comparatively.

Billur, A. A.; Ciftci, A. K. [Physics Department, Faculty of Sciences, Ankara University, 06100 Tandogan, Ankara (Turkey); Ciftci, R. [Physics Department, Faculty of Sciences and Arts, Gazi University, 06500 Teknikokullar (Turkey); Inan, S. C. [Physics Department, Faculty of Sciences and Arts, Cumhuriyet University, 58140, Sivas (Turkey); Sultansoy, S. [Physics Department, Faculty of Sciences and Arts, Gazi University, 06500 Teknikokullar (Turkey); Institute of Physics, Academy of Sciences, H. Cavid Avenue 33, Baku (Azerbaijan)

2007-04-23T23:59:59.000Z

117

Component tissues of different morphological types of tomato fruit and their qualitative and quantitative effects on quality of processed product  

E-Print Network [OSTI]

COMPONENT TISSUES OF DIFFERENT MORPHOLOGICAL TYPES OF TOMATO FRUIT AND THEIR QUALITATIVE AND QUANTITATIVE EFFECTS ON QUALITY OF PROCESSED PRODUCT A Thesis by Alfred Bernhart Wagner, Jr. Submitted to the Graduate College of Texas A... of Tomato Fruit and Their Qualitative and Quantitative Effects on Quality of Processed Product (December 1972) Alfred Bernhart Wagner, Jr. , B. S. , Texas A&M University Directed by: Dr. E. E. Burns Tissue regions of five morphological types of tomato...

Wagner, Alfred Bernhart

1972-01-01T23:59:59.000Z

118

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

119

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

120

Report Title: Oil and Gas Production and Economic Growth In New Mexico Type of Report: Technical Report  

E-Print Network [OSTI]

Report Title: Oil and Gas Production and Economic Growth In New Mexico Type of Report: Technical agency thereof. #12;Page | ii Oil and Gas Production and Economic Growth in New Mexico James Peach and C Mexico's marketed value of oil and gas was $19.2 billion (24.0 percent of state GDP). This paper

Johnson, Eric E.

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


121

Assumptions to 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

122

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

123

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

124

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

125

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.

126

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

127

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

128

Id-1 gene and gene products as therapeutic targets for treatment of breast cancer and other types of carcinoma  

DOE Patents [OSTI]

A method for treatment of breast cancer and other types of cancer. The method comprises targeting and modulating Id-1 gene expression, if any, for the Id-1 gene, or gene products in breast or other epithelial cancers in a patient by delivering products that modulate Id-1 gene expression. When expressed, Id-1 gene is a prognostic indicator that cancer cells are invasive and metastatic.

Desprez, Pierre-Yves; Campisi, Judith

2014-08-19T23:59:59.000Z

129

Comparisons of type and volume of growth media and two cropping systems for production of greenhouse tomatoes Lycopersicon esculentum Mill  

E-Print Network [OSTI]

COMPARISONS OF TYPE AND VOLUME OF GROWTH MEDIA AND TWO CROPPING SYSTEMS FOR PRODUCTION OF GREENHOUSE TOMATOES LYCOPERSICON ESCULENTUM MILL. A Thesis by JOHN DARRYL BYRD Submitted to the Graduate College of Texas A & M University in partial... fulfillment of the requirement for the degree of MASTER OF SCIENCE August 1977 Major Subject: Horticulture COMPARISONS OF TYPE AND VOLUME OF GROWTH MEDIA AND TWO CROPPING SYSTEMS FOR PRODUCTIOF OF GREENHOUSE TOMATOES LYCOPERSICON ESCULENTUM MILL. A...

Byrd, John Darryl

2012-06-07T23:59:59.000Z

130

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

131

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

132

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

133

Aluminum (Al) Etch Instructions The CEPSR cleanroom stores Aluminum Etchant Type A, a pre-made product used for  

E-Print Network [OSTI]

Aluminum (Al) Etch Instructions The CEPSR cleanroom stores Aluminum Etchant Type A, a pre-made product used for removing or etching away aluminum. This etchant is stored inside the acid or corrosive a specific thickness of aluminum that is desired. Note: Once the bottle is empty or you find that it's etch

Kim, Philip

134

Antibody production by injection of living cells expressing non self antigens as cell surface type II transmembrane fusion protein  

Science Journals Connector (OSTI)

Antigen expression and purification are laborious, time consuming and frequently difficult steps in the process of antibody production. In the present study, we developed a method avoiding these two steps. This method relies on the injection of histocompatible living cells stably expressing the antigen as a cell surface type II transmembrane fusion protein. A vector, nicknamed pCD1-CD134L, was constructed to express the antigen fused at the carboxyterminal end of the human CD134 ligand (CD134L) type II transmembrane protein on the surface of eucaryotic cells. This vector was shown to induce cell surface expression of epitopes from human c-Myc (soluble protein), uterogloblin-related protein 1 (secreted protein) and CD94 (type II transmembrane protein). Using this vector, we developed a method to produce antibodies without antigen production. The flowchart of this method is as follows: (i) cloning of the antigen in the pCD1-CD134L vector; (ii) production of a histocompatible cell line stably expressing the CD134L-antigen fusion protein; (iii) testing for cell surface expression of the fusion protein by targeting the CD134L carrier; and (iv) prime-boost immunisation with living cells expressing the fusion protein. This method was successfully used for production of polyclonal antibodies raised against Ixodes ricinus calreticulin (secreted protein) in mice and for production of monoclonal antibodies raised against an epitope of Vaccinia virus A56 (type I transmembrane protein) protein in rat. The present study is the first to demonstrate the use of a type II transmembrane protein as a carrier for cell surface display of antigens.

Yannick Nizet; Laurent Gillet; Hlne Schroeder; Corinne Lecuivre; J. Louahed; J.-C. Renauld; Pierre Gianello; Alain Vanderplasschen

2011-01-01T23:59:59.000Z

135

Development of water production type curves for horizontal wells in coalbed methane reservoirs.  

E-Print Network [OSTI]

??Coalbed methane is an unconventional gas resource that consists of methane production from the coal seams. The key parameters for the evaluation of coalbed methane (more)

Burka Narayana, Praveen Kumar.

2007-01-01T23:59:59.000Z

136

Development of gas production type curves for horizontal wells in coalbed methane reservoirs.  

E-Print Network [OSTI]

??Coalbed methane is an unconventional gas resource that consists of methane production from coal seams .The unique difference between CBM and conventional gas reservoirs is (more)

Nfonsam, Allen Ekahnzok.

2006-01-01T23:59:59.000Z

137

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.

138

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

139

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

140

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

Note: This page contains sample records for the topic "assumptions product types" 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 - 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

142

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

143

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.

144

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

145

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.

146

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.

147

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.

148

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.

149

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.

150

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.

151

Project Summary This project is to investigate how hypoxia affects the production of specific types of  

E-Print Network [OSTI]

Project Summary This project is to investigate how hypoxia affects the production of specific and established procedures in the GrandeAllen lab. The figure below outlines the experimental setup

Richards-Kortum, Rebecca

152

Effect of rearing and laying house environments on performance of incross egg production type pullets  

E-Print Network [OSTI]

'ts ~ ~ ~ ~ ~ ~ ~ ~ e e ~ e ~ ~ ~ ~ ~ ~ ~ ~ F 10 Experimental design of rearing treatments of incross pullets ~ o ~ ~ a ~ ~ a ~ ~ e ~ ~ e ~ ~ ~ ~ ~ ~ F 11 Experimental design of the laying phase of incross pullets. . . e e . . . . . . . . . . . . . . . . . , . 12 IV...' colony cage. . . 34 Egg production of birds from the different laying managements ~ ~ ~ ~ ~ ~ ~ o o ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ 36 Statistical analysi. s of egg product1on of birds from the d1ffsrsnt lay1ng managements . ~ . . ~ . ~ ~ ~ ~ F 37 Average...

Shupe, William Dale

2012-06-07T23:59:59.000Z

153

Acid-Functionalized SBA-15-Type Periodic Mesoporous Organosilicas and Their Use in the Continuous Production of 5-Hydroxymethylfurfural  

Science Journals Connector (OSTI)

Acid-Functionalized SBA-15-Type Periodic Mesoporous Organosilicas and Their Use in the Continuous Production of 5-Hydroxymethylfurfural ... The activity, selectivity, and stability of several supported acid catalysts were evaluated in tubular reactors designed to produce 5-hydroxymethylfurfural (HMF) continuously from fructose dissolved in a single-phase solution of THF and H2O (4:1 w/w). ... 5-hydroxymethylfurfural; continuous dehydration; packed-bed reactor; SBA-15; periodic mesoporous organosilicas; propylsulfonic acid; catalyst deactivation rate ...

Mark H. Tucker; Anthony J. Crisci; Bethany N. Wigington; Neelay Phadke; Ricardo Alamillo; Jinping Zhang; Susannah L. Scott; James A. Dumesic

2012-07-09T23:59:59.000Z

154

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

155

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

156

Monitoring of Total Type II Pyrethroid Pesticides in Citrus Oils and Water by Converting to a Common Product 3-Phenoxybenzoic Acid  

E-Print Network [OSTI]

Monitoring of Total Type II Pyrethroid Pesticides in Citrus Oils and Water by Converting to a Common Product 3-Phenoxybenzoic Acid Mark R. McCoy, Zheng Yang, Xun Fu,§ Ki Chang Ahn, Shirley J. Gee an alternative method that converts the type II pyrethroids to a common chemical product, 3-phenoxybenzoic acid

Hammock, Bruce D.

157

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.

158

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.

159

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

160

A diverse range of gene products are effectors of the type I interferon antiviral response  

Science Journals Connector (OSTI)

... HCV (b), HIV-1 (d) and YFV (e). ISGs are colour coded: Fluc control (red), inhibitory (black) and enhancing (green). Data were ... K., Tassello, J. & Rice, C. M. Hepatitis C virus p7 and NS2 proteins are essential for production of infectious virus. J. Virol. 81, 83748383 ...

John W. Schoggins; Sam J. Wilson; Maryline Panis; Mary Y. Murphy; Christopher T. Jones; Paul Bieniasz; Charles M. Rice

2011-04-10T23:59:59.000Z

Note: This page contains sample records for the topic "assumptions product types" 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

Scalable serum-free production of recombinant adeno-associated virus type 2 by transfection of 293 suspension cells  

Science Journals Connector (OSTI)

Recombinant adeno-associated virus (rAAV) has emerged in recent years as a promising gene therapy vector that may be used in the treatment of diverse human diseases. The major obstacle to broadening the usage of rAAV vectors remains the limited capacity of available production systems to provide sufficient rAAV quantities for preclinical and clinical trials. The impracticality of expanding commonly used adherent cell lines represents a limitation to large-scale production. This paper describes successful productions of rAAV type 2 using suspension-growing human embryonic kidney (HEK293) cells in serum-free medium. The developed process, based on triple transfection employing polyethylenimine (PEI) as DNA transporter, allowed for a serum-free production of AAV, yielding viral vector titer up to 4.5נ1011 infectious viral particles (IVP) in a 3.5-L bioreactor. A maximum ratio of VG:IVP in the order of 200:1 was obtained, indicating the efficient encapsidation of viral vectors in HEK293 cells. The effect of varying the ratio of three plasmids and the influence of cell density at transfection were studied. The conditioned medium did not limit or inhibit the rAAV production; therefore, the elimination of the medium exchange step before or after transfection greatly simplified the scale-up of rAAV production. The cell-specific viral titers obtained in bioreactor suspension cultures were similar or higher than those obtained with control adherent cell cultures which further supported the scalability of the process. From multiple aspects including process simplicity, scalability, and low operating costs, this transfection method appears to be the most promising technology for large-scale production of rAAV.

Yves Durocher; Phuong Lan Pham; Gilles St-Laurent; Danielle Jacob; Brian Cass; Parminder Chahal; Cara J. Lau; Josphine Nalbantoglu; Amine Kamen

2007-01-01T23:59:59.000Z

162

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

163

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

164

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

165

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.

166

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

167

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

168

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.

169

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

170

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

171

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

172

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

173

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

174

Production of exotic, short lived carbon isotopes in ISOL-type facilities  

E-Print Network [OSTI]

The beam intensities of short-lived carbon isotopes at Isotope Separation On-Line (ISOL) facilities have been limited in the past for technical reasons. The production of radioactive ion beams of carbon isotopes is currently of high interest for fundamental nuclear physics research. To produce radioactive ions a target station consisting of a target in a container connected to an ion source via a transfer line is commonly used. The target is heated to vaporize the product for transport. Carbon in elementary form is a very reactive element and react strongly with hot metal surfaces. Due to the strong chemisorption interaction, in the target and ion source unit, the atoms undergo significant retention on their way from the target to the ion source. Due to this the short lived isotopes decays and are lost leading to low ion yields. A first approach to tackle these limitations consists of incorporating the carbon atoms into less reactive molecules and to use materials for the target housing and the transfer line ...

Franberg, Hanna; Kster, Ulli; Ammann, Markus

2008-01-01T23:59:59.000Z

175

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.

176

Manufacturing Energy and Carbon Footprint Definitions and Assumptions...  

Energy Savers [EERE]

The age of the boiler, boiler size, maintenance practices, and fuel type are important factors. Power generation losses vary depending on whether cogeneration is employed (systems...

177

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,

178

Long-term patterns of fruit production in five forest types of the South Carolina upper coastal plain.  

SciTech Connect (OSTI)

ABSTRACT Fleshy fruit is a key food resource for many vertebrates and may be particularly important energy source to birds during fall migration and winter. Hence, land managers should know how fruit availability varies among forest types, seasons, and years. We quantified fleshy fruit abundance monthly for 9 years (1995-2003) in 56 0.1-ha plots in 5 forest types of South Carolina's upper Coastal Plain, USA. Forest types were mature upland hardwood and bottomland hardwood forest, mature closed-canopy loblolly (Pinus taeda) and longleaf pine (P. palustris) plantation, and recent clearcut regeneration harvests planted with longleaf pine seedlings. Mean annual number of fruits and dry fruit pulp mass were highest in regeneration harvests (264,592 _ 37,444 fruits; 12,009 _ 2,392 g/ha), upland hardwoods (60,769 _ 7,667 fruits; 5,079 _ 529 g/ha), and bottomland hardwoods (65,614 _ 8,351 fruits; 4,621 _ 677 g/ha), and lowest in longleaf pine (44,104 _ 8,301 fruits; 4,102 _ 877 g/ha) and loblolly (39,532 _ 5,034 fruits; 3,261 _ 492 g/ha) plantations. Fruit production was initially high in regeneration harvests and declined with stand development and canopy closure (1995-2003). Fruit availability was highest June-September and lowest in April. More species of fruit-producing plants occurred in upland hardwoods, bottomland hardwoods, and regeneration harvests than in loblolly and longleaf pine plantations. Several species produced fruit only in 1 or 2 forest types. In sum, fruit availability varied temporally and spatially because of differences in species composition among forest types and age classes, patchy distributions of fruiting plants both within and among forest types, fruiting phenology, high inter-annual variation in fruit crop size by some dominant fruit-producing species, and the dynamic process of disturbance-adapted species colonization and decline, or recovery in recently harvested stands. Land managers could enhance fruit availability for wildlife by creating and maintaining diverse forest types and age classes. .

Greenberg, Cathryn H.; Levey, Douglas J.; Kwit, Charles; McCarty, John P.; Pearson, Scott F.; Sargent, Sarah; Kilgo, John

2012-02-06T23:59:59.000Z

179

The purpose of this chapter is to illustrate the types of guns and other products that are available at gun shows. Details on the  

E-Print Network [OSTI]

4 What's for Sale The purpose of this chapter is to illustrate the types of guns and other products that are available at gun shows. Details on the properties, use in crime, and lethality of particular firearms are available from many other sources. The Prominence of Assault Weapons All types of guns are available at gun

Leistikow, Bruce N.

180

Production of 1-m size uniform plasma by modified magnetron-typed RF discharge with a subsidiary electrode for resonance  

Science Journals Connector (OSTI)

A large-diameter uniform plasma of 1 m in size is produced using a modified magnetron-typed (MMT) RF plasma source at the frequency of 13.56 MHz. The construction and operation of the MMT RF plasma source are very simple and we can place two substrates simultaneously. To achieve an efficient production of high density plasma, a parallel resonance circuit is connected to one of the substrates which acts as a subsidiary RF electrode controlling the plasma parameters. In the case of the resonance the plasma density increases to approximately three times as much as that in case of non-resonance. The plasma density reaches?11011/cm3 in Ar at 1 mtorr when the RF input power is 2.8 kW. The MMT RF plasma source provides a plasma with uniformity within several percent over 1 m in diameter in front of the substrate in the low gas pressure regime.

Yuji Urano; Yunlong Li; Keiichi Kanno; Satoru Iizuka; Noriyoshi Sato

1998-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "assumptions product types" 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

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

182

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.

183

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

184

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

185

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

186

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

187

Production  

Science Journals Connector (OSTI)

Production is obtained from proved reserves but the determinants of the scale of production in the industry and country components of the world total are many and complex with some unique to the individual com...

D. C. Ion

1980-01-01T23:59:59.000Z

188

Productivity Techniques and Quality Aspects in the Criticality Safety Evaluation of Y-12 Type-B Fissile Material Packages  

SciTech Connect (OSTI)

The inventory of certified Type-B fissile material packages consists of ten performance-based packages for offsite transportation purposes, serving transportation programs at the Y-12 National Security Complex. The containment vessels range from 5 to 19 in. in diameter and from 17 to 58 in. in height. The drum assembly external to the containment vessel ranges from 18 to 34 in. in diameter and from 26 to 71 in. in height. The weight of the packaging (drum assembly and containment vessel) ranges from 239 to 1550 lb. The older DT-nn series of Cellotex-based packages are being phased-out and replaced by a new generation of Kaolite-based ('Y-12 patented insulation') packages capable of withstanding the dynamic crush test 10 CFR 71.73(c)(2). Three replacement packages are in various stages of development; two are in use. The U.S. Department of Transportation (DOT) 6M specification package, which does not conform to the U.S. Nuclear Regulatory Commission requirements for Type-B packages, is no longer authorized for service on public roads. The ES-3100 shipping package is an example of a Kaolite-based Type-B fissile material package developed as a replacement package for the DOT 6M. With expanded utility, the ES-3100 is designed and licensed for transporting highly enriched uranium and plutonium materials on public roads. The ES-3100 provides added capability for air transport of up to 7-kg quantities of uranium material. This paper presents the productivity techniques and quality aspects in the criticality safety evaluation of Y-12 packages using the ES-3100 as an example.

DeClue, J. F.

2011-06-28T23:59:59.000Z

189

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).

190

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.

191

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

192

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

193

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.

194

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.

195

Production  

Broader source: Energy.gov [DOE]

Algae production R&D focuses on exploring resource use and availability, algal biomass development and improvements, characterizing algal biomass components, and the ecology and engineering of...

196

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

197

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).

198

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

199

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).

200

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

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

Note: This page contains sample records for the topic "assumptions product types" 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 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,

202

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

203

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,

204

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

205

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

206

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

207

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

208

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

209

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

210

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.

211

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.

212

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.

213

Assumptions to the Annual Energy Outlook 1999 - Table 2  

Gasoline and Diesel Fuel Update (EIA)

Carbon Emission Factors (Kilograms-carbon per million Btu) Carbon Emission Factors (Kilograms-carbon per million Btu) Fuel Type Carbon Coefficient at Full Combustion Combustion Fraction Adjusted Emissions Factor Petroleum Motor Gasoline 19.35 0.990 19.16 Liquefied Petroleum Gas Used as Fuel 16.87 0.995 16.79 Used as Feedstock 17.11 0.200 3.42 Jet Fuel 19.33 0.990 19.14 Distillate Fuel 19.95 0.990 19.75 Residual Fuel 21.49 0.990 21.28 Asphalt and Road Oil 20.62 0.000 0.00 Lubricants 20.24 0.600 12.14 Petrochemical Feedstocks 19.37 0.200 3.87 Kerosene 19.72 0.990 19.52 Petroleum Coke 27.85 0.500 13.93 Petroleum Still Gas 17.51 0.995 17.42 Other Industrial 20.31 0.990 20.11 Coal Residential and Commercial 25.92 0.990 25.74 Metallurgical 25.55 0.990 25.28 Industrial Other 25.61 0.990 25.38 Electric Utility1 25.74 0.990 25.48 Natural Gas Used as Fuel

214

Production  

Broader source: Energy.gov [DOE]

Algae production R&D focuses on exploring resource use and availability, algal biomass development and improvements, characterizing algal biomass components, and the ecology and engineering of cultivation systems.

215

When innovativeness in form matters: the joint impact of form innovativeness and expected innovativeness type on product evaluations over time  

E-Print Network [OSTI]

assessment or it could be based on the technology involved in the product or the usage or benefits that the product offers. The confounding issue is that the researcher simply does not know what the respondent is considering when thinking about overall.... Meanwhile, innovativeness in product technology can be implemented in new products to provide improvements in performance and increased benefits to consumers (Danneels and Kleinschmidt 2001; Shrivastava and Souder 1987). This, in turn, can provide a...

Kroff, Michael William

2007-09-17T23:59:59.000Z

216

The UL45 gene product is required for herpes simplex virus type 1 glycoprotein B-induced fusion.  

Science Journals Connector (OSTI)

...required for herpes simplex virus type 1 glycoprotein B-induced fusion. E J Haanes C M Nelson C L Soule...required for herpes simplex virus type 1 glycoprotein B-induced fusion. | Herpes simplex virus type 1 (HSV-1) syncytial (syn...

E J Haanes; C M Nelson; C L Soule; J L Goodman

1994-09-01T23:59:59.000Z

217

A New Type Curve Analysis for Shale Gas/Oil Reservoir Production Performance with Dual Porosity Linear System  

E-Print Network [OSTI]

matching program.................. ...................... 46 6.2 Synthetic case generated with Stehfest to test the accuracy of the type curve shape................... ........................................................................... 47... 6.3 Synthetic case generated with CMG to test the accuracy of type curve results which show very close values.................... ................................ 48 6.4 Synthetic case generated with CMG to test the accuracy of type curve...

Abdulal, Haider Jaffar

2012-02-14T23:59:59.000Z

218

Modified Atmosphere Packaged Cheddar Cheese Shreds:? Influence of Fluorescent Light Exposure and Gas Type on Color and Production of Volatile Compounds  

Science Journals Connector (OSTI)

Modified Atmosphere Packaged Cheddar Cheese Shreds:? Influence of Fluorescent Light Exposure and Gas Type on Color and Production of Volatile Compounds ... The cheese block was shredded with a hand shredder. ... Aldehydes were the major constituent of the volatile fraction of shredded Cheddar cheese packaged under CO2. ...

Llori M. Colchin; Sandra L. Owens; Galina Lyubachevskaya; Elizabeth Boyle-Roden; Estelle Russek-Cohen; Scott A. Rankin

2001-04-13T23:59:59.000Z

219

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

220

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

Note: This page contains sample records for the topic "assumptions product types" 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

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

222

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.

223

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

224

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

225

Metabolic Engineering of Light and Dark Biochemical Pathways in Wild-Type and Mutant Strains of Synechocystis PCC 6803 for Maximal, 24-Hour Production of Hydrogen Gas  

SciTech Connect (OSTI)

This project used the cyanobacterial species Synechocystis PCC 6803 to pursue two lines of inquiry, with each line addressing one of the two main factors affecting hydrogen (H2) production in Synechocystis PCC 6803: NADPH availability and O2 sensitivity. H2 production in Synechocystis PCC 6803 requires a very high NADPH:NADP+ ratio, that is, the NADP pool must be highly reduced, which can be problematic because several metabolic pathways potentially can act to raise or lower NADPH levels. Also, though the [NiFe]-hydrogenase in PCC 6803 is constitutively expressed, it is reversibly inactivated at very low O2 concentrations. Largely because of this O2 sensitivity and the requirement for high NADPH levels, a major portion of overall H2 production occurs under anoxic conditions in the dark, supported by breakdown of glycogen or other organic substrates accumulated during photosynthesis. Also, other factors, such as N or S limitation, pH changes, presence of other substances, or deletion of particular respiratory components, can affect light or dark H2 production. Therefore, in the first line of inquiry, under a number of culture conditions with wild type (WT) Synechocystis PCC 6803 cells and a mutant with impaired type I NADPH-dehydrogenase (NDH-1) function, we used H2 production profiling and metabolic flux analysis, with and without specific inhibitors, to examine systematically the pathways involved in light and dark H2 production. Results from this work provided rational bases for metabolic engineering to maximize photobiological H2 production on a 24-hour basis. In the second line of inquiry, we used site-directed mutagenesis to create mutants with hydrogenase enzymes exhibiting greater O2 tolerance. The research addressed the following four tasks: 1. Evaluate the effects of various culture conditions (N, S, or P limitation; light/dark; pH; exogenous organic carbon) on H2 production profiles of WT cells and an NDH-1 mutant; 2. Conduct metabolic flux analyses for enhanced H2 production profiles using selected culture conditions and inhibitors of specific pathways in WT cells and an NDH-1 mutant; 3. Create Synechocystis PCC 6803 mutant strains with modified hydrogenases exhibiting increased O2 tolerance and greater H2 production; and 4. Integrate enhanced hydrogenase mutants and culture and metabolic factor studies to maximize 24-hour H2 production.

Ely, Roger L.; Chaplen, Frank W.R.

2014-03-11T23:59:59.000Z

226

Multiple-part-type systems in high volume manufacturing : long-term capacity planning & time-based production control  

E-Print Network [OSTI]

This project examines a production station that faces fluctuating demand with seasonal pattern. The cumulative capacity exceeds the cumulative demand in a one year period; however, its weekly capacity is not able to meet ...

Hua, Xia, M. Eng. Massachusetts Institute of Technology

2008-01-01T23:59:59.000Z

227

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

228

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

229

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.

230

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

231

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

232

Towards a desalination initiative using cogeneration with an advanced reactor type and uranium recovered from Moroccan phosphoric acid production  

Science Journals Connector (OSTI)

Morocco is known to be among the first few countries to produce phosphate and phosphoric acid. Moroccan phosphate contains substantial amounts of uranium. This uranium can be recovered from the phosphate ore as a by-product during the production of phosphoric acid. Uranium extraction processes linked with phosphoric acid fabrication have been used industrially in some countries. This is done mainly by solvent extraction. Although, the present price of uranium is low in the international market, such uranium recovery could be considered as a side product of phosphoric acid production. The price of uranium has a very small impact on the cost of nuclear energy obtained from it. This paper focuses on the extraction of uranium salt from phosphate rock. If uranium is recovered in Morocco in the proposed manner, it could serve as feed for a number of nuclear power plants. The natural uranium product would have to be either enriched or blended as mixed-oxide fuel to manufacture adequate nuclear fuel. Part of this fuel would feed a desalination initiative using a high temperature reactor of the new generation, chosen for its intrinsic safety, sturdiness, ease of maintenance, thermodynamic characteristics and long fuel life between reloads, that is, good economy. ?n international cooperation based on commercial contract schemes would concern: the general project and uranium extraction; uranium enrichment and fuel fabrication services; the nuclear power plant; and the desalination plant. This paper presents the overall feasibility of the general project with some quantitative preliminary figures and cost estimates.

Michel Lung; Abdelaali Kossir; Driss Msatef

2005-01-01T23:59:59.000Z

233

Assessing the effect of requirement definition and management on performance outcomes: Role of interpersonal conflict, product advantage and project type  

Science Journals Connector (OSTI)

Abstract Early planning in many cases is not performed well in new product development (NPD). Most NPD literature has focused more on the product rather than on the development process (Funk, 1992). Thus, the primary purpose of this research was to investigate the relationships among requirement definition and management (RDM) practice, interpersonal conflict, product advantage, and NPD performance in terms of project and market performance. The structural equation modeling (SEM) approach was used to validate the research model. The results suggest that RDM practice in terms of RDM implementation process and training & improvement is associated with requirement quality and stability. The findings also indicate that the number of groups moderates the relationship between requirement quality & stability and project performance.

Li-Ren Yang; Jieh-Haur Chen; Xing-Liang Wang

2014-01-01T23:59:59.000Z

234

Design of a photochemical water electrolysis system based on a W-typed dye-sensitized serial solar module for high hydrogen production  

Science Journals Connector (OSTI)

Abstract A W-typed dye-sensitized serial solar module (W-typed DSSM) was designed for hydrogen production from water electrolysis. The optimal thickness and width of the TiO2 electrode film were 12?m and 5mm, and the optimal thickness of Pt counter electrode film was 4nm, respectively. The photocurrent density, open circuit voltage, and fill factor were 2.13mAcm?2, 3.51V, and 0.61, respectively, for a serial module assembled from five unit cells, which resulted in an overall conversion efficiency of 4.56%. The obtained voltage increased with increasing number of unit cells connected, and was 3.51V in the five column fabricated W-typed DSSM. 2.1mLh?1 of hydrogen gas was emitted when a W-typed DSSM assembled from five columns was connected to carbon electrodes in a water electrolysis system. The rate of hydrogen evolution in the five columned W-typed DSSM was 0.00213Lh?1. Therefore, the actual light-hydrogen conversion was calculated to be 2.02%.

Byeong Sub Kwak; Jinho Chae; Misook Kang

2014-01-01T23:59:59.000Z

235

Silicon carbide grains of type C provide evidence for the production of the unstable isotope $^{32}$Si in supernovae  

E-Print Network [OSTI]

Carbon-rich grains are observed to condense in the ejecta of recent core-collapse supernovae, within a year after the explosion. Silicon carbide grains of type X are C-rich grains with isotpic signatures of explosive supernova nucleosynthesis have been found in primitive meteorites. Much rarer silicon carbide grains of type C are a special sub-group of SiC grains from supernovae. They show peculiar abundance signatures for Si and S, isotopically heavy Si and isotopically light S, which appear to to be in disagreement with model predictions. We propose that C grains are formed mostly from C-rich stellar material exposed to lower SN shock temperatures than the more common type X grains. In this scenario, extreme $^{32}$S enrichments observed in C grains may be explained by the presence of short-lived $^{32}$Si ($\\tau$$_{1/2}$ = 153 years) in the ejecta, produced by neutron capture processes starting from the stable Si isotopes. No mixing from deeper Si-rich material and/or fractionation of Si from S due to mole...

Pignatari, M; Bertolli, M G; Trappitsch, R; Hoppe, P; Rauscher, T; Fryer, C; Herwig, F; Hirschi, R; Timmes, F X; Thielemann, F -K

2013-01-01T23:59:59.000Z

236

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

237

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

238

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.

239

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

240

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

Note: This page contains sample records for the topic "assumptions product types" 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

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

242

Relating horsepower to drilling productivity  

SciTech Connect (OSTI)

Many technological advancements have been made in explosive products and applications over the last 15 years resulting in productivity and cost gains. However, the application of total energy (engine horsepower) in the majority of rotary drilling technology, has remained virtually unchanged over that period. While advancements have been made in components, efficiency, and types of hydraulic systems used on drills, the application of current hydraulic technology to improve drilling productivity has not been interactive with end users. This paper will investigate how traditional design assumptions, regarding typical application of horsepower in current rotary drill systems, can actually limit productivity. It will be demonstrated by numeric analysis how changing the partitioning of available hydraulic energy can optimize rotary drill productivity in certain conditions. Through cooperative design ventures with drill manufacturers, increased penetration rates ranging from 20% to 100% have been achieved. Productivity was increased initially on some rigs by careful selection of optional hydraulic equipment. Additional gains were made in drilling rates by designing the rotary hydraulic circuit to meet the drilling energies predicted by computer modeling.

Givens, R.; Williams, G.; Wingfield, B.

1996-12-31T23:59:59.000Z

243

Resource Constraints in Petroleum Production Potential  

Science Journals Connector (OSTI)

...the assumption of 2% consumption growth and the low scenario, OPEC would achieve 50% ofworld production in 1998. OPEC's highest crude oil production was 32 mmbbl per day in 1973 and 1979. About 10% ofthe liquid petroleum produced outside...

C. D. MASTERS; D. H. ROOT; E. D. ATTANASI

1991-07-12T23:59:59.000Z

244

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

245

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

246

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.

247

Next-to-next-to-leading order QCD corrections to light Higgs pair production via vector boson fusion in type-II two-Higgs-doublet model  

E-Print Network [OSTI]

We present the precision predictions on the pair production of light, $CP$-even Higgs in weak vector boson fusion (VBF) up to the QCD next-to-next-to-leading-order (NNLO) at hadron colliders within the $CP$-conserving type-II two-Higgs-doublet model (2HDM(II)) by adopting the structure function approach. We investigate the model parameter dependence, residual uncertainties from the factorization/renormalization scale, PDFs and $\\alpha_s$ on the integrated cross section at the QCD NNLO, and find that the NNLO QCD corrections can reduce the scale uncertainty significantly. By analyzing the kinematic distributions of final Higgs bosons, we can extract the $CP$-even Higgs resonance via $H^0 \\to h^0 h^0$ channel as a means of probing the extension of the Standard Model (SM) Higgs sector.

Li Wei-Hua; Zhang Ren-You; Ma Wen-Gan; Guo Lei; Ling Liu-Sheng; Li Xiao-Zhou

2014-03-12T23:59:59.000Z

248

Next-to-next-to-leading order QCD corrections to light Higgs pair production via vector boson fusion in type-II two-Higgs-doublet model  

E-Print Network [OSTI]

We present the precision predictions on the pair production of light, $CP$-even Higgs in weak vector boson fusion (VBF) up to the QCD next-to-next-to-leading-order (NNLO) at hadron colliders within the $CP$-conserving type-II two-Higgs-doublet model (2HDM(II)) by adopting the structure function approach. We investigate the model parameter dependence, residual uncertainties from the factorization/renormalization scale, PDFs and $\\alpha_s$ on the integrated cross section at the QCD NNLO, and find that the NNLO QCD corrections can reduce the scale uncertainty significantly. By analyzing the kinematic distributions of final Higgs bosons, we can extract the $CP$-even Higgs resonance via $H^0 \\to h^0 h^0$ channel as a means of probing the extension of the Standard Model (SM) Higgs sector.

Wei-Hua, Li; Wen-Gan, Ma; Lei, Guo; Liu-Sheng, Ling; Xiao-Zhou, Li

2014-01-01T23:59:59.000Z

249

Next-to-next-to-leading order QCD corrections to light Higgs pair production via vector boson fusion in the type II two-Higgs-doublet model  

Science Journals Connector (OSTI)

We present the precision predictions on the pair production of light, CP-even Higgs boson in weak vector boson fusion (VBF) up to the QCD next-to-next-to-leading order (NNLO) at hadron colliders within the CP-conserving type II two-Higgs-doublet model [2HDM(II)] by adopting the structure function approach. We investigate the model parameter dependence, residual uncertainties from the factorization/renormalization scale, PDFs, and ?s on the integrated cross section at the QCD NNLO and find that the NNLO QCD corrections can reduce the scale uncertainty significantly. By analyzing the kinematic distributions of final Higgs bosons, we can extract the CP-even Higgs resonance via the H0?h0h0 channel as a means of probing the extension of the standard model (SM) Higgs sector.

Wei-Hua Li; Ren-You Zhang; Wen-Gan Ma; Lei Guo; Liu-Sheng Ling; Xiao-Zhou Li

2014-04-08T23:59:59.000Z

250

Trap types vs productivity of significant Wilcox gas fields in the south Texas, listric growth fault trend, and the divergent origin of its two largest producers  

SciTech Connect (OSTI)

Detailed mapping and analysis of 23 Wilcox fields in the subject trend indicates that gas production is related to trap type. Of total cumulative production of 3.4 TCFG, 65% is from upthrown fault blocks implying very effective fault seals due to differential pressure and/or shale smears. NE Thompsonville and Bob West fields have produced 650 and 200 BCFG, respectively, with 400 BCFG remaining reserves in the latter. The field structures are not attributed to listric growth faulting, as is suggested by their trend location. NE Thompsonville is a 9-mile-long turtle structure that originated through depositional loading of an upper slope basin, followed by tilting, and then eventual collapse of a sediment squeeze-up mound due to gravitational instability. These events provide an excellent example of basin evolution through sediment loading accompanied by withdrawal of a salt-shale substrate; the basin flanks are defined by basin-dipping listric faulting that accommodated subsidence and merge beneath its floor. Bob West Field lies along the edge of the Laramide fold belt. The 1-1/2 x 4 mile field anticline adjoins a deep-seated fault that slices over and across a buried structural ridge of probable Cretaceous age. Uplift of the latter, immediately following deposition of 20+ stacked, shelf-bar producing sands, upwarped the fault and resulted in rollover growth of the Wilcox anticline. The fault shows no downward decrease in dip typical of listric faults. NE Thompsonville and Bob West fields both produce upthrown along crestal faults. This analysis indicates that {open_quotes}high-side{close_quotes} closures, irrespective of diverse origins, have achieved head-of-the-class stature as Wilcox gas producers.

Stricklin, F.L. Jr. [Wilcox Exploration Enterprises, Woodlands, TX (United States)

1996-09-01T23:59:59.000Z

251

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

252

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

253

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

254

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

255

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.

256

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

257

Facility Type!  

Office of Legacy Management (LM)

ITY: ITY: --&L~ ----------- srct-r~ -----------~------~------- if yee, date contacted ------------- cl Facility Type! i I 0 Theoretical Studies Cl Sample 84 Analysis ] Production 1 Diepasal/Storage 'YPE OF CONTRACT .--------------- 1 Prime J Subcontract&- 1 Purchase Order rl i '1 ! Other information (i.e., ---------~---~--~-------- :ontrait/Pirchaee Order # , I C -qXlJ- --~-------~~-------~~~~~~ I I ~~~---~~~~~~~T~~~ FONTRACTING PERIODi IWNERSHIP: ,I 1 AECIMED AECMED GOVT GOUT &NTtiAC+OR GUN-I OWNED ----- LEEE!? M!s LE!Ps2 -LdJG?- ---L .ANDS ILJILDINGS X2UIPilENT IRE OR RAW HA-I-L :INAL PRODUCT IASTE Z. RESIDUE I I kility l pt I ,-- 7- ,+- &!d,, ' IN&"E~:EW AT SITE -' ---------------- , . Control 0 AEC/tlED managed operations

258

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

259

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

260

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).

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


261

Aspen Ecology in the MixedAspen Ecology in the Mixed Conifer TypeConifer Type  

E-Print Network [OSTI]

Aspen Ecology in the MixedAspen Ecology in the Mixed Conifer TypeConifer Type Wayne D. Shepperd Colorado State University Fort Collins, CO Aspen Ecology in the MixedAspen Ecology in the Mixed ConiferAssumptions Mixed conifer forests are a collection of different species, each with different ecologic requirements

262

Type Ia Supernova Explosion: Gravitationally Confined Detonation  

Science Journals Connector (OSTI)

We present a new mechanism for Type Ia supernova explosions in massive white dwarfs. The scenario follows from relaxing assumptions of symmetry and involves a detonation born near the stellar surface. The explosion begins with an essentially central ignition of a deflagration that results in the formation of a buoyancy-driven bubble of hot material that reaches the stellar surface at supersonic speeds. The bubble breakout laterally accelerates fuel-rich outer stellar layers. This material, confined by gravity to the white dwarf, races along the stellar surface and is focused at the location opposite to the point of the bubble breakout. These streams of nuclear fuel carry enough mass and energy to trigger a detonation just above the stellar surface that will incinerate the white dwarf and result in an energetic explosion. The stellar expansion following the deflagration redistributes mass in a way that ensures production of intermediate-mass and iron group elements with ejecta having a strongly layered structure and a mild amount of asymmetry following from the early deflagration phase. This asymmetry, combined with the amount of stellar expansion determined by details of the evolution (principally the energetics of deflagration, timing of detonation, and structure of the progenitor), can be expected to create a family of mildly diverse Type Ia supernova explosions.

T. Plewa; A. C. Calder; D. Q. Lamb

2004-01-01T23:59:59.000Z

263

Testing Surrogacy Assumptions: Can Threatened and Endangered Plants Be Grouped by Biological Similarity  

E-Print Network [OSTI]

of species in need of management but limited resources and data. One type of surrogate approach involves@sesync.org Introduction Policy makers and conservation managers strive to use the best available science to determine conservation and management [1­3]. Surrogate approaches lie between generic rules of thumb and detailed study

Neel, Maile

264

Blood Types  

E-Print Network [OSTI]

Broadcast Transcript: According to the Japanese, you can tell a lot about a person by their blood type: Type A is the farmer, calm and responsible; Type B is the hunter, independent and creative; Type AB is humanistic, ...

Hacker, Randi; Tsutsui, William

2007-03-14T23:59:59.000Z

265

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.

266

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

267

Id-1 and Id-2 genes and products as therapeutic targets for treatment of breast cancer and other types of carcinoma  

DOE Patents [OSTI]

A method for treatment and amelioration of breast, cervical, ovarian, endometrial, squamous cells, prostate cancer and melanoma in a patient comprising targeting Id-1 or Id-2 gene expression with a delivery vehicle comprising a product which modulates Id-1 or Id-2 expression.

Desprez, Pierre-Yves; Campisi, Judith

2014-09-30T23:59:59.000Z

268

Sources of Corn for Ethanol Production in the United States: A Review and Decomposition Analysis of the Empirical Data  

SciTech Connect (OSTI)

The use of corn for ethanol production in the United States quintupled between 2001 and 2009, generating concerns that this could lead to the conversion of forests and grasslands around the globe, known as indirect land-use change (iLUC). Estimates of iLUC and related food versus fuel concerns rest on the assumption that the corn used for ethanol production in the United States would come primarily from displacing corn exports and land previously used for other crops. A number of modeling efforts based on these assumptions have projected significant iLUC from the increases in the use of corn for ethanol production. The current study tests the veracity of these assumptions through a systematic decomposition analysis of the empirical data from 2001 to 2009. The logarithmic mean divisia index decomposition method (Type I) was used to estimate contributions of different factors to meeting the corn demand for ethanol production. Results show that about 79% of the change in corn used for ethanol production can be attributed to changes in the distribution of domestic corn consumption among different uses. Increases in the domestic consumption share of corn supply contributed only about 5%. The remaining contributions were 19% from added corn production, and 2% from stock changes. Yield change accounted for about two-thirds of the contributions from production changes. Thus, the results of this study provide little support for large land-use changes or diversion of corn exports because of ethanol production in the United States during the past decade.

Oladosu, Gbadebo A [ORNL; Kline, Keith L [ORNL; Uria Martinez, Rocio [ORNL; Eaton, Laurence M [ORNL

2011-01-01T23:59:59.000Z

269

EERE Publication and Product Library  

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

ANDOR select additional criteria (Information For, Information Type, Product Type, or EERE Office Name) to narrow your search results, AND PRESS 'SEARCH'. Search the Library...

270

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

271

Assumptions to the Annual Energy Outlook 2001 - Table 2. Carbon Dioxide  

Gasoline and Diesel Fuel Update (EIA)

Carbon Dioxide Emission Factors Carbon Dioxide Emission Factors (Kilograms-carbon equivalent per million Btu) Fuel Type Carbon Dioxide Coefficient at Full Combustion Combustion Fraction Adjusted Emissions Factor Petroleum Motor Gasoline 19.36 0.990 19.17 Liquefied Petroleum Gas Used as Fuel 17.18 0.995 17.09 Used as Feedstock 16.88 0.200 3.38 Jet Fuel 19.33 0.990 19.14 Distillate Fuel 19.95 0.990 19.75 Residual Fuel 21.49 0.990 21.28 Asphalt and Road Oil 20.62 0.000 0.00 Lubricants 20.24 0.600 12.14 Petrochemical Feedstocks 19.37 0.200 3.87 Kerosene 19.72 0.990 19.52 Petroleum Coke 27.85 0.500 13.93 Petroleum Still Gas 17.51 0.995 17.42 Other Industrial 20.31 0.990 20.11 Coal Residential and Commercial 26.00 0.990 25.74 Metallurgical 25.56 0.990 25.30 Industrial Other 25.63 0.990 25.38 Electric Utility1 25.76 0.990 25.50 Natural Gas

272

Assumptions to the Annual Energy Outlook 2000-Table 2. Carbon Emission  

Gasoline and Diesel Fuel Update (EIA)

Carbon Emission Factors Carbon Emission Factors (Kilograms-carbon per million Btu) Fuel Type Carbon Coefficient at Full Combustion Combustion Fraction Adjusted Emissions Factor Petroleum Motor Gasoline 19.33 0.990 19.14 Liquefied Petroleum Gas Used as Fuel 17.20 0.995 17.11 Used as Feedstock 16.87 0.200 3.37 Jet Fuel 19.33 0.990 19.14 Distillate Fuel 19.95 0.990 19.75 Residual Fuel 21.49 0.990 21.28 Asphalt and Road Oil 20.62 0.000 0.00 Lubricants 20.24 0.600 12.14 Petrochemical Feedstocks 19.37 0.200 3.87 Kerosene 19.72 0.990 19.52 Petroleum Coke 27.85 0.500 13.93 Petroleum Still Gas 17.51 0.995 17.42 Other Industrial 20.31 0.990 20.11 Coal Residential and Commercial 25.92 0.990 25.66 Metallurgical 25.55 0.990 25.29 Industrial Other 25.61 0.990 25.39 Electric Utility1 25.74 0.990 24.486 Natural Gas Used as Fuel

273

STIGMERGY: A DESIGN PATTERN FOR PRODUCT-DRIVEN SYSTEMS  

E-Print Network [OSTI]

STIGMERGY: A DESIGN PATTERN FOR PRODUCT-DRIVEN SYSTEMS Rémi Pannequin, André Thomas Research Centre be used to develop product-driven systems. Agent-oriented components which implement it are presented) is based on the assumption that the product is the core object is this system. Indeed, the product

Paris-Sud XI, Université de

274

Particle-type dependence of azimuthal anisotropy and nuclearmodification of particle production in Au+Au collisions at sNN = 200GeV  

SciTech Connect (OSTI)

We present STAR measurements of the azimuthal anisotropy parameter v{sub 2} and the binary-collision scaled centrality ratio R{sub CP} for kaons and lambdas ({Lambda} + {bar {Lambda}}) at mid-rapidity in Au+Au collisions at {radical}s{sub NN} = 200 GeV. In combination, the v{sub 2} and R{sub CP} particle-type dependencies contradict expectations from partonic energy loss followed by standard fragmentation in vacuum. We establish p{sub T} {approx} 5 GeV/c as the value where the centrality dependent baryon enhancement ends. The K{sub S}{sup 0} and {Lambda} + {bar {Lambda}} v{sub 2} values are consistent with expectations of constituent-quark-number scaling from models of hadron formation by parton coalescence or recombination.

Adams, J.; Adler, C.; Aggarwal, M.M.; Ahammed, Z.; Amonett, J.; Anderson, B.D.; Anderson, M.; Arkhipkin, D.; Averichev, G.S.; Badyal,S.K.; Balewski, J.; Barannikova, O.; Barnby, L.S.; Baudot, J.; Bekele,S.; Belaga, V.V.; Bellwied, R.; Berger, J.; Bezverkhny, B.I.; Bhardwaj,S.; Bhaskar, P.; Bhati, A.K.; Billmeier, A.; Bland, L.C.; Blyth, C.O.; Bonner, B.E.; Botje, M.; Boucham, A.; Brandin, A.; Bravar, A.; Cadman,R.V.; Cai, X.Z.; Caines, H.; Calderon de la Barca Sanchez, M.; Carroll,J.; Castillo, J.; Castro, M.; Cebra, D.; Chaloupka, P.; Chattopadhyay,S.; Chen, H.F.; Chen, Y.; Chernenko, S.P.; Cherney, M.; Chikanian, A.; Choi, B.; Christie, W.; Coffin, J.P.; Cormier, T.M.; Cramer, J.G.; Crawford, H.J.; Das, D.; Das, S.; Derevschikov, A.A.; Didenko, L.; Dietel, T.; Dong, W.J.; Dong, X.; Draper, J.E.; Du, F.; Dubey, A.K.; Dunin, V.B.; Dunlop, J.C.; Dutta Majumdar, M.R.; Eckardt, V.; Efimov,L.G.; Emelianov, V.; Engelage, J.; Eppley, G.; Erazmus, B.; Fachini, P.; Faine, V.; Faivre, J.; Fatemi, R.; Filimonov, K.; Filip, P.; Finch, E.; Fisyak, Y.; Flierl, D.; Foley, K.J.; Fu, J.; Gagliardi, C.A.; Gagunashvili, N.; Gans, J.; Ganti, M.S.; Gutierrez, T.D.; Gaudichet, L.; Germain, M.; Geurts, F.; Ghazikhanian, V.; Ghosh, P.; Gonzalez, J.E.; Grachov, O.; Grigoriev, V.; Gronstal, S.; Drosnick, D.; Guedon, M.; Guertin, S.M.; Gushin, E.; Hallman, T.J.; Hardtke, D.; Harris, J.W.; Heinz, M.; Henry, T.W.; Heppelmann, S.; Herston, T.; Hippolyte, B.; Hirsch, A.; Hjort, E.; Hoffmann, G.W.; Horsley, M.; Huang, H.Z.; Huang,S.L.; Humanic, T.J.; Igo, G.; Ishihara, A.; Jacobs, P.; Jacobs, W.W.; Janik, M.; Johnson, I.; Jones, P.G.; Judd, E.G.; Kabana, S.; Kaneta, M.; Kaplan, M.; Keane, D.; Kiryluk, J.; Kisiel, A.; Klay, J.; Klein, S.R.; Klyachko, A.; Koetke, D.D.; Kollegger, T.; Konstantinov, A.; Kopytine,S.M.; Kotchenda, L.; Kovalenko, A.D.; Kramer, M.; Kravtsov, P.; Krueger,K.; Kuhn, C.; Kulikov, A.I.; Kunde, G.J.; Kunz, C.L.; Kutuev, R.K.; et al.

2003-06-18T23:59:59.000Z

275

Type Fusion  

Science Journals Connector (OSTI)

Fusion is an indispensable tool in the arsenal ... Less well-known, but equally valuable is type fusion, which states conditions for fusing an application ... algebra. We provide a novel proof of type fusion base...

Ralf Hinze

2011-01-01T23:59:59.000Z

276

The use of post detonation analysis of stable isotope ratios to determine the type and production process of the explosive involved  

SciTech Connect (OSTI)

The detonation of a series of explosives was performed in a controlled manner to collect the resulting, solid residue or {open_quotes}soot.{close_quotes} This residue was examined to determine the ratios of the stable carbon, hydrogen, and nitrogen isotopes. The goal of the experiment was to determine if these ratios could be used to indicate, from the post detonation residues, the type and origin of the detonated explosive. The ratios of the stated stable isotopes in the undetonated explosive were also determined. Despite some reservations in the quality of the data resulting from contamination by nonexplosive components, certain trends can be discerned. (1) Carbon isotopes allow aromatic explosives to be distinguished from nonaromatic explosives. This trend seems to carry through the detonation so that the distinction might be made after the fact. (2) The amination process for TATB can be detected through the hydrogen and, to some extent, the nitrogen isotope ratios. Unfortunately, the data are not sufficiently good to determine if this differential carries through the detonation. (3) The relative magnitude and sign of the nitrogen isotope ratio seems to carry through the detonation: some exchange with atmospheric nitrogen is probable. Even though this set of experiments must also be viewed as preliminary, there is a definite indication that certain qualitative characteristics of explosives can be detected after the detonation. This {open_quotes}signature{close_quotes} could have application to both intelligence and counter terrorism.

McGuire, R.R.; Velsko, C.A.; Lee, C.G.; Raber, E.

1993-03-05T23:59:59.000Z

277

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

278

Federal Energy Management Program: Lighting Control Types  

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

Lighting Control Lighting Control Types to someone by E-mail Share Federal Energy Management Program: Lighting Control Types on Facebook Tweet about Federal Energy Management Program: Lighting Control Types on Twitter Bookmark Federal Energy Management Program: Lighting Control Types on Google Bookmark Federal Energy Management Program: Lighting Control Types on Delicious Rank Federal Energy Management Program: Lighting Control Types on Digg Find More places to share Federal Energy Management Program: Lighting Control Types on AddThis.com... Energy-Efficient Products Federal Requirements Covered Product Categories Product Designation Process Low Standby Power Energy & Cost Savings Calculators Model Acquisitions Language Working Group Resources Technology Deployment Renewable Energy

279

TYPE OF OPERATION  

Office of Legacy Management (LM)

3!NEEi_S1 3!NEEi_S1 past: -~~~-~~~~~-~~~---------- current: ------------_------------- Owner contacted q yes g no; if ye=, date contacted TYPE OF OPERATION --~~__--~-~~~---- 5 Research & Development 5 Facility Type 0 Production scale testing c1 Pilot Scale 0 Bench Scale Process z Theareti cal Studi es Sample Sr Analysis 0 Production D Disposal/Storage TYPE OF CONTRACT ---------------- 0 Manufacturing 0 University 0 Research Clrganization B Government Cpanaored Faci 1 i ty 0 Other ~~---~~---_--~~-----_ a Prime 13 Subcontract& D PurcSase Order 0 Other information (i.e., cost + fixed fee, unit price, time & material, +z) ----_----------------------- Cantract/Purchaae Order #-d-z=&-/) -2_7~-------------Is_------------ PERIOD: CONTRACTING I%~(?) - 1465

280

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

Note: This page contains sample records for the topic "assumptions product types" 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

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

E-Print Network [OSTI]

Conservation Standards for Consumer Products: Room Air Conditioners, Water Heaters, Direct Heating Equipment, Mobile Home Furnaces, Kitchen Ranges and Ovens, Pool

Johnson, F.X.

2010-01-01T23:59:59.000Z

282

Melanin Types  

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

Melanin Types Melanin Types Name: Irfan Location: N/A Country: N/A Date: N/A Question: What are different types of melanins? And what are the functions of these types? Replies: Hi Irfan! Melanin is a dark compound or better a photoprotective pigment. Its major role in the skin is to absorb the ultraviolet (UV) light that comes from the sun so the skin is not damaged. Sun exposure usually produces a tan at the skin that represents an increase of melanin pigment in the skin. Melanin is important also in other areas of the body, as the eye and the brain., but it is not completely understood what the melanin pigment does in these areas. Melanin forms a special cell called melanocyte. This cell is found in the skin, in the hair follicle, and in the iris and retina of the eye.

283

TYPE OF OPERATION  

Office of Legacy Management (LM)

_---------_-- _---------_-- Research & Development 0 Production scale testing Cl Pilat Scale 0 Bench Scale Process 0 Theoretical Studies Cl Sample SC Analysis !J Production 0 Dis.posal/Storage 0 Prime ." 0 Subcontract& 0 Purchase Order 0 Facility Type 0 Manufacturing 0 University 0 Research Org&ization 0 Government Sponsored Facility Cl Other ---------_---__-____- Other information (i.e., cost + fixed fee, unit price, time & material, gtr) Coni+act/Purchase Order # ---------------------_--_________ C!2kEE~_CIL_N_G-EE~LE~: /5J--L-,r4 53 -------------------------------------- OWNERSHIP: AEC/MED AEC/MED GOVT GOVT CONTRACTOR CONTRACTOR !w!!E? ___--- " EWNED LEASED L_EesEE OWNED LEASED ---------_ --_------ LANDS BUILDINGS ' EQUIPMENT

284

TYPE OF OPERATION  

Office of Legacy Management (LM)

Owner c:ontacted Owner c:ontacted TYPE OF OPERATION ----------------_ jJ Research & Development 0 Production scale testing Cl Pilot Scale 0 Bench Scale Process i Theoretical Studies Sample & Analysis B Production 0 Disposal/Storage $r Prime 0 Subcontract& 0 Purchase Order 0 Facility Type 0 Manufacturing 0 University 0 Research Organization a Other information (i.e., cost + fixed fern, unit price,' time & mate ~r~~-r~~tf~-_~_-_~-~f-~~J~ d ial, etc)_kl/Jlfits ---- -7---- -- Contract/Purchase Order # w?@7-e?-b $ 6, i;,_~~~~~----------------- - ----- C_O!!IF!KXYE-PEELEg: -lTlL-/L?~J --------------------------- OWNERSHXP: AEWHEC AEC/HED' GOVT GB' JT SiXiRACTOR CONiRkCiGR WEE LEAs_EE a!!!%? IEEE!? --------_ ..---LEASED ._ OWNED LANDS BUILDINGS EQUIPMENT

285

TYPE OF OPERATION  

Office of Legacy Management (LM)

~~__--------_____ ~~__--------_____ q Research & Development q Production scale testing Cl Pilat Scale 0 Bench Scale Process 0 Theoretical Studies a Sample & Analysis c] Production 0 Disposal/Storage TYPE OF CONTRACT ~~__-------_--__ 0 Prime 0 Subcontractor 0 Purchase Order a d//F- a Faci 1 i ty Type a tlanuf acturi ng 0 University q Research Organization 0 Government Sponsored Facility a other --------------__----- Other information (i.e., cost + fixed fee, unit price, time & material, qtr) ------- -1------------------_L______ Contract/Purchase Order # CONTRACTING PE?IOD- 42 --------------L---- --------- ----------------_---______ OWNERSHIP: AEC/MED AEC/tlED OWNED ----- LE_A_sEE GOUT GO' JT CONTRACTOR E!!!!E!z LEASED - ----_ ---_OW_E!L LANDS BUILDINGS

286

TYPE OF OPERATION  

Office of Legacy Management (LM)

______ ______ 0 Research & Development 9 Faciiity Type 0 Production scale testing Cl Pilot Scale 0 Bench Scale Process 0 Theoretical Studies Cl Sample 84 Analysis Production Di aposal /Storage g ;E:"V',;=:;;';"" IJ Research Organization 0 Government Sponeored Facility q Other --------------------- 0 Prime q ,@ Subcontract& Other information (i.e., cost 0 Purchase Order + fixed fee, unit price, time ?8 material, etc) -------mm----+------------- Contract/Purchase Order # CONTRACTING PERIODr c&L&.& rqs-z i i -----~_--~~~_----_ -------------------------------------- OWNERSHIP8 CIEC/tlED CIEC/MED GOUT WNED LE&xU _o!!EED LANDS BUILDINGS EQUIPMENT iii E : ORE OR RAW MATL IJ : E FINCIL PRODUCT [7 WCISTE b RESIDUE q GOUT

287

Rock types, pore types, and hydrocarbon exploration  

SciTech Connect (OSTI)

A proposed exploration-oriented method of classifying porosity in sedimentary rocks is based on microscopic examination cores or cuttings. Factors include geometry, size, abundance, and connectivity of the pores. The porosity classification is predictive of key petrophysical characteristics: porosity-permeability relationships, capillary pressures, and (less certainly) relative permeabilities. For instance, intercrystalline macroporosity typically is associated with high permeability for a given porosity, low capillarity, and favorable relative permeabilities. This is found to be true whether this porosity type occurs in a sucrosic dolomite or in a sandstone with pervasive quartz overgrowths. This predictive method was applied in three Rocky Mountain oil plays. Subtle pore throat traps could be recognized in the J sandstone (Cretaceous) in the Denver basin of Colorado by means of porosity permeability plotting. Variations in hydrocarbon productivity from a Teapot Formation (Cretaceous) field in the Powder River basin of Wyoming were related to porosity types and microfacies; the relationships were applied to exploration. Rock and porosity typing in the Red River Formation (Ordovician) reconciled apparent inconsistencies between drill-stem test, log, and mud-log data from a Williston basin wildcat. The well was reevaluated and completed successfully, resulting in a new field discovery. In each of these three examples, petrophysics was fundamental for proper evaluation of wildcat wells and exploration plays.

Coalson, E.B.; Hartmann, D.J.; Thomas, J.B.

1985-05-01T23:59:59.000Z

288

Price Corrected Domestic Technology AssumptionA Method To Assess Pollution Embodied in Trade Using Primary Official Statistics Only. With a Case on CO2 Emissions Embodied in Imports to Europe  

Science Journals Connector (OSTI)

For various countries, it has been shown that apparent decoupling of CO2 emissions or primary material use from GDP growth is actually the result of the relocation of material and energy-intensive production abroad. ... Compiling MR EE IO databases demands a high level of harmonization and consolidation of different data sources which often conflict (e.g., trade statistics usually differ from trade data in SUIOT). ... Figure 3. CO2 emissions per capita, 20002006: (a) emitted at EU27 territory; (b) embodied in EU27 imports; (c) embodied in EU27 exports; and (d) embodied in EU27 domestic final demand, calculated with Domestic Technology Assumption (standard) and with price adjustments. ...

Arnold Tukker; Arjan de Koning; Richard Wood; Stephan Moll; Maaike C. Bouwmeester

2012-12-26T23:59:59.000Z

289

Measurements of Methane Emissions at Natural Gas Production Sites  

E-Print Network [OSTI]

Measurements of Methane Emissions at Natural Gas Production Sites in the United States #12;Why = 21 #12;Need for Study · Estimates of methane emissions from natural gas production , from academic in assumptions in estimating emissions · Measured data for some sources of methane emissions during natural gas

Lightsey, Glenn

290

Type: Renewal  

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

1 INCITE Awards 1 INCITE Awards Type: Renewal Title: -Ab Initio Dynamical Simulations for the Prediction of Bulk Properties‖ Principal Investigator: Theresa Windus, Iowa State University Co-Investigators: Brett Bode, Iowa State University Graham Fletcher, Argonne National Laboratory Mark Gordon, Iowa State University Monica Lamm, Iowa State University Michael Schmidt, Iowa State University Scientific Discipline: Chemistry: Physical INCITE Allocation: 10,000,000 processor hours Site: Argonne National Laboratory Machine (Allocation): IBM Blue Gene/P (10,000,000 processor hours) Research Summary: This project uses high-quality electronic structure theory, statistical mechanical methods, and

291

Bacteria Types  

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

Bacteria Types Bacteria Types Name: Evelyn Location: N/A Country: N/A Date: N/A Question: What is the significance of S. marcescens,M.luteus, S.epidermidis, and E. Coli? Which of these are gram-positive and gram-negative, and where can these be found? Also, what problems can they cause? When we culture these bacteria, we used four methods: plates, broth, slants, and pour plates. The media was made of TSB, TSA, NAP, and NAD. What is significant about these culturing methods? Replies: I could give you the answer to that question but it is more informative, and fun, to find out yourself. Start with the NCBI library online (http://www.ncbi.nlm.nih.gov/) and do a query with the species name, and 'virulence' if you want to know what they're doing to us. Have a look at the taxonomy devision to see how they are related. To find out if they're gram-pos or neg you should do a gram stain if you can. Otherwise you'll find that information in any bacteriology determination guide. Your question about the media is not specific enough so I can't answer it.

292

Hydrogen Production Infrastructure Options Analysis  

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

Production Production Infrastructure Options Analysis January 26, 2006 Brian D. James Julie Perez Peter Schmidt (703) 243 - 3383 Brian_James@DirectedTechnologies.com Directed Technologies, Inc. Page 1 of 39 26 January 2006 2006-1-26 DOE Transition Workshop Agenda 1. Project Description and Objective 2. Team Members 3. Approach 4. Model Theory, Structure and Assumptions 5. Model Description 1. Logic 2. Features 3. Cost Components (Production, Delivery & Dispensing) 6. Los Angeles Transitional Example 7. Model Flexibility Page 2 of 39 26 January 2006 2006-1-26 DOE Transition Workshop Team Members & Interactions Start: May 2005 (effective) End: Summer 2007 * Directed Technologies, Inc.- Prime * Sentech, Inc., Research Partner * Air Products, Industrial Gas Supplier * Advisory Board * Graham Moore, Chevron Technology Ventures

293

TYPE OF OPERATION  

Office of Legacy Management (LM)

----------------- ----------------- 0 Research & Development .a Production scale testing 0 Pilat Scale 0 Bench Scale Process 0 Thearetical Studies Cl Sample 84 Analysis 0 Production *i DiaposalKitorage Cl Facility Tybe q Government Sponsored Facility Other R.L- 6:e 14 1 1 ---------- --------- I I I TYPE OF CONTRACT ~-__-----------_ fl Prime *I 0 Subcantractbr Other infuriation (i.e., L.t + fixed fee, kit price, 0 Purchase Order time k mat*iik, gtc) /I -~---------'-t-----------~- ----------II---------------- Contract/Purchase Order # I EP!EBEII!G-PEEI9E: ---------------------------------~---- , OWNERSHiP: : I I j ,' / 1 AEC/tlED AEC/MED GOUT GOUT E!!NE_D LEASEI! !z%!NE_D CONTTACTOR CONTf?qCTOR LEASE?? ---w!En- ---LEL3SEI! i I I I LANDS BUILDINGS EIXIIPMENT

294

Higherorder Boussinesqtype equations for surface gravity waves: derivation and analysis  

Science Journals Connector (OSTI)

...1998 research-article Higher-order Boussinesq-type equations for surface gravity...Agern Alle 5, 2970 Horsholm, Denmark Boussinesq-type equations of higher order in...of u under the assumption that mu 1. Boussinesq equations are then derived from the...

1998-01-01T23:59:59.000Z

295

TYPE OF OPERATION  

Office of Legacy Management (LM)

OWNEF? (S) OWNEF? (S) Current: ____ LcrcJksLG! _________ Owner contacted n yes WI-IO; if yes, date contacted-- TYPE OF OPERATION ----_-------_---- m Research & Development Cl Pilot Scale Cl Disposal/Storaqe TYPE OF CDNTRACT ---__------__--- q Prime 0 Subcnntractor Cl Purchase Order 0 Other infcrmation (i.e., cnst + fixed fee, unit price, time 84 materi+, e.tc) v-7Y07-&G-W ---------------------------- Contract/Pur&aae Order # 0 -?+7- FJc-(CL --___--------~----_______________ CONTRACTING PEXIOD: fl& ,&I;'"'-?;': (&e-?)_-- ' ------------------ OWNERSHIP: AEC/MED GEC/MED SOVT GOVT CONTRACTOR CCNTRACTOR OWNE3 LEASE3 OWNE3 LEASED OWNE3 ----- ------ ----- ------ -__------- LE.352 LANDS u u q BUILDINGS EQUIPMENT 0 FINAL PRODUCT WASTE G RESIDUE a

296

Assessment of Plutonium-238 (Pu-238) Production Alternatives  

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

Plutonium-238 Plutonium-238 Production Alternatives Briefing for Nuclear Energy Advisory Committee April 21, 2008 Dennis Miotla Deputy Assistant Secretary for Nuclear Power Deployment Miotla - April 2008 NEAC Mtg - DM183874 (2) Statement of Work Desired end state: - Reliable, sustainable, affordable supply of Pu-238 suitable for NASA applications Assumptions: - NASA obtains funding for planned missions - Russia is out of material to sell to US - DOE maintains balance of radioisotope power source infrastructure during period of depleted supply Independently evaluate the Pu-238 heat source requirements for NASA's mission projections and assess Pu-238 production assumptions, strategy and alternatives for meeting those requirements Miotla - April 2008 NEAC Mtg - DM183874 (3)

297

Maximum Utility Product Pricing Models and Algorithms Based on Reservation Prices  

E-Print Network [OSTI]

Maximum Utility Product Pricing Models and Algorithms Based on Reservation Prices R. Shioda L. Tun for pricing a product line with several customer segments under the assumption that customers' product choices utility model and formulate it as a mixed-integer programming problem, design heuristics and valid cuts

Tunçel, Levent

298

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

299

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

300

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

Note: This page contains sample records for the topic "assumptions product types" 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

Indication of anomalous heat energy production in a reactor device  

E-Print Network [OSTI]

An experimental investigation of possible anomalous heat production in a special type of reactor tube named E-Cat HT is carried out. The reactor tube is charged with a small amount of hydrogen loaded nickel powder plus some additives. The reaction is primarily initiated by heat from resistor coils inside the reactor tube. Measurement of the produced heat was performed with high-resolution thermal imaging cameras, recording data every second from the hot reactor tube. The measurements of electrical power input were performed with a large bandwidth three-phase power analyzer. Data were collected in two experimental runs lasting 96 and 116 hours, respectively. An anomalous heat production was indicated in both experiments. The 116-hour experiment also included a calibration of the experimental set-up without the active charge present in the E-Cat HT. In this case, no extra heat was generated beyond the expected heat from the electric input. Computed volumetric and gravimetric energy densities were found to be far above those of any known chemical source. Even by the most conservative assumptions as to the errors in the measurements, the result is still one order of magnitude greater than conventional energy sources.

Giuseppe Levi; Evelyn Foschi; Torbjrn Hartman; Bo Histad; Roland Pettersson; Lars Tegnr; Hanno Essn

2013-06-07T23:59:59.000Z

302

Barley Production in Texas.  

E-Print Network [OSTI]

in Texas is used for livestock fezd. Large acreages are grown 'exclusively for winter pasture and grazed to maiurity. Most of the baliley is fall sown, although when conditions are favorable, some is spring sown in the northwestern part of the State... production. All barley varieties grown in Texas are of the common six-row aw.ned type. True winter-type varieties such as Kearney, Reno and Ward are the most winter hardy. Intermediate winter-type varieties make up the majority of the acreage. Spring...

Atkins, I. M.; Gardenhire, J. H.; Porter, K. B.

1958-01-01T23:59:59.000Z

303

Energy Conservation in Fertilizer Production  

E-Print Network [OSTI]

oil. Table 1 shows current United States fertilizer production estimates. No. of Total Annual No. of PCR Annual Type of Plants in Plaot liSA Production lToos) PCR Type Plaots Production l,IoosJ NPKS 100 10 x 10 6 28 2.5 x 10 6 DAP/MAP 26... 10.9 x 10 6 4 3 x 10 6 . Table I USA Fertilizer Production - 1984, Estimated PCR Technology The Pipe-Cross Reactor was developed initially to contain the violent reaction in fertilizer pro duction which occurred during ammoniating of sulfu ric...

Mings, W. J.; Sonnett, W. M.

1984-01-01T23:59:59.000Z

304

Material efficiency: providing material services with less material production  

Science Journals Connector (OSTI)

...fitting production functions to data related to a broad set of manufacturing...money flow. (This is clearly a big assumption, when energy prices...households voluntarily reduced electricity consumption by up to 15-20...computing, and as yet we have no data to support the (marketing...

2013-01-01T23:59:59.000Z

305

Analysis of K-Meson Production by p Annihilation  

Science Journals Connector (OSTI)

K-meson production by p annihilation has been investigated using an isobar model. A comparison of the predictions of this model with the experimental data excludes the assumption of an isobar state of (??) having a mass greater than three pion masses.

T. F. Hoang

1961-03-01T23:59:59.000Z

306

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

307

Chemical Signals Production  

E-Print Network [OSTI]

Chemical Signals · Types · Production · Transmission · Reception · Reading: Ch 10 except boxes 10.1 and 10.2 #12;What is chemical communication? · Movement of molecules from sender to receiver · Methods compounds are volatile. - 5-20 carbon compounds - carbon (MW=12) + hydrogen is less dense than oxygen (MW

Wilkinson, Gerald S.

308

By-Products Utilization  

E-Print Network [OSTI]

ash. Paving applications, such as Roller Compacted Concrete for industrial plants, parking lots be used in Self-Consolidating Concrete applications. This type of concrete requires additional fines that concrete Bricks, Blocks, and Paving Stones can also be made with the Corn Products' coal ash. Additionally

Wisconsin-Milwaukee, University of

309

Environmental assessment for proposed energy conservation standards for two types of consumer products; refrigerators, refrigerator-freezers, and freezers; small gas furnaces; and a proposed No standard standard for television sets  

SciTech Connect (OSTI)

This environmental assessment (EA) evaluates the environmental impacts resulting from new or amended energy-efficiency standard for refrigerators, refrigerator-freezers, freezers, small gas furnaces, and television sets as mandated by the National Appliance Energy Conservation Act of 1987. A complete description of the Engineering and Economic Analysis of the proposed standards may be found elsewhere in the Technical Support Document (TSD). Four of the 14 scenarios for product design changes described in the Engineering Analysis of the TSD are chosen for environmental assessment based on their relative importance as design measures. Values for energy savings that result from product design changes are also taken from the TSD. The two main environmental concerns addressed are emissions from fossil fuel-fired electricity generation and the chlorofluorcarbons used in the production of rigid insulation foam. Each of the 12 design options for refrigerators and freezers result in decreased electricity use and and, therefore, reduced power plant emissions. Design changes that call for additional rigid foam insulation per appliance are of interest because they affect chlorofluorocarbon consumption. There is strong evidence that chlorofluorocarbons migrate to the stratosphere, break down, and catalyze the destruction of stratospheric ozone.

Not Available

1988-01-01T23:59:59.000Z

310

OPEC Crude Oil Production 1999-2001  

Gasoline and Diesel Fuel Update (EIA)

EIA assumes in its base case that OPEC 10 production averages about EIA assumes in its base case that OPEC 10 production averages about 0.6 million barrels per day less in the 1st quarter of 2001 than was produced in the 4th quarter of 2000. This is based on the assumption that beginning in February 2001, OPEC 10 production is 1 million barrels per day less than the estimate for December 2000. Over the course of the past year, worldwide oil production has increased by about 3.7 million barrels per day to a level of 77.8 million barrels per day in the last months of 2000. After being nearly completely curtailed in December 2000, EIA's base case assumes that Iraqi oil exports only partially return in January. By February, EIA assumes Iraqi crude oil production reaches 3 million barrels per day, roughly the peak levels reached last year.

311

Synthetic Rubber Production in Canada  

Science Journals Connector (OSTI)

... called the Polymer Corporation, Ltd., with headquarters in Toronto, which will undertake the production in Canada of synthetic ... in Canada of synthetic rubber of the Buna type. According to the Ottawa correspondent of The Times, Mr. ...

1942-03-21T23:59:59.000Z

312

Alternative Fuels Data Center: Biofuels Production Incentive  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuels Production Biofuels Production Incentive to someone by E-mail Share Alternative Fuels Data Center: Biofuels Production Incentive on Facebook Tweet about Alternative Fuels Data Center: Biofuels Production Incentive on Twitter Bookmark Alternative Fuels Data Center: Biofuels Production Incentive on Google Bookmark Alternative Fuels Data Center: Biofuels Production Incentive on Delicious Rank Alternative Fuels Data Center: Biofuels Production Incentive on Digg Find More places to share Alternative Fuels Data Center: Biofuels Production Incentive on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biofuels Production Incentive The Mississippi Department of Agriculture and Commerce (Department) provides incentive payments to qualified ethanol and biodiesel producers

313

Covered Product Category: Faucets, Showerheads, Toilets, and...  

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

and a purchasing specification for this product type. For more information, see Federal Water Efficiency Best Management Practices for Faucets and Showerheads and Environmental...

314

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

315

Outer Continental Shelf Production  

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

Reference case projections. 3 The complete AEO2014, which was released in May, includes alternative assumptions regarding resources, technology advances, and world energy prices...

316

RMOTC - Production  

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

Production Production RMOTC Pumpjack in action During the process of the sale of NPR-3, RMOTC will focus on maximizing the value of the NPR-3 site and will continue with its Production Optimization Projects. NPR-3 includes 9,481 acres with more than 400 oil-producing wells. Current oil production is at approximately 240 barrels of oil per day. In July 2013, RMOTC began working on a number of Production Optimization Projects within the NPR-3 field, with the goal to optimize and improve flow and efficiency. Production Optimization Projects include repairing and replacing existing infrastructure with new infrastructure in order to optimize current wells and bring additional wells online. These Production Optimization Projects will continue throughout 2013 and are focused on improving current production and creating revenue for the America tax payer.

317

PRODUCTS & MATERIALS  

Science Journals Connector (OSTI)

...1995-96 Spectrum Chemical and Safety Prod-ucts Catalog features products for molecular and life science laboratories and cleanroom environments. Spectrum Chemical Manu-facturing. Circle 150. SCIENCE * VOL. 268 * 23 JUNE 1995

1995-06-23T23:59:59.000Z

318

Effects of spent fuel types on offsite consequences of hypothetical accidents  

SciTech Connect (OSTI)

Argonne National Laboratory (ANL) conducts experimental work on the development of waste forms suitable for several types of spent fuel at its facility on the Idaho National Engineering and Environmental Laboratory (INEEL) located 48 km West of Idaho Falls, ID. The objective of this paper is to compare the offsite radiological consequences of hypothetical accidents involving the various types of spent nuclear fuel handled in nonreactor nuclear facilities. The highest offsite total effective dose equivalents (TEDEs) are estimated at a receptor located about 5 km SSE of ANL facilities. Criticality safety considerations limit the amount of enriched uranium and plutonium that could be at risk in any given scenario. Heat generated by decay of fission products and actinides does not limit the masses of spent fuel within any given operation because the minimum time elapsed since fissions occurred in any form is at least five years. At cooling times of this magnitude, fewer than ten radionuclides account for 99% of the projected TEDE at offsite receptors for any credible accident. Elimination of all but the most important nuclides allows rapid assessments of offsite doses with little loss of accuracy. Since the ARF (airborne release fraction), RF (respirable fraction), LPF (leak path fraction) and atmospheric dilution factor ({chi}/Q) can vary by orders of magnitude, it is not productive to consider nuclides that contribute less than a few percent of the total dose. Therefore, only {sup 134}Cs, {sup 137}Cs-{sup 137m}Ba, and the actinides significantly influence the offsite radiological consequences of severe accidents. Even using highly conservative assumptions in estimating radiological consequences, they remain well below current Department of Energy guidelines for highly unlikely accidents.

Courtney, J. C.; Dwight, C. C.; Lehto, M. A.

2000-02-18T23:59:59.000Z

319

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

320

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

Note: This page contains sample records for the topic "assumptions product types" 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

Types of Commissioning  

Broader source: Energy.gov [DOE]

Several commissioning types exist to address the specific needs of equipment and systems across both new and existing buildings. The following commissioning types provide a good overview.

322

Granuloma annulare, patch type  

E-Print Network [OSTI]

Granuloma annulare, patch type Frank C Victor MD, Stephaniewas consistent with patch-type granuloma annulare. He wascm, annular, erythematous patch without scale was present on

Victor, Frank C; Mengden, Stephanie

2008-01-01T23:59:59.000Z

323

production | OpenEI  

Open Energy Info (EERE)

production production Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed

324

Property:NrelPartnerType | Open Energy Information  

Open Energy Info (EERE)

NrelPartnerType NrelPartnerType Jump to: navigation, search Property Name NrelPartnerType Property Type String Description Partnership Type. Pages using the property "NrelPartnerType" Showing 25 pages using this property. (previous 25) (next 25) 1 1366 Technologies + Incubator + 3 3M + CRADA + A A.O. Smith + Test & Evaluation Partner + A123Systems + CRADA + AAON + Test & Evaluation Partner + AQUA Products + Test & Evaluation Partner + AVL Powertrain Engineering + Licensing Agreement + AWS Truewind + Test & Evaluation Partner + Abengoa Solar + CRADA + Abound Solar + Other Relationship + Advanced Energy Products + Test & Evaluation Partner + Affiliated International Management (AIM) + Test & Evaluation Partner + Affordable Comfort + Test & Evaluation Partner +

325

OPEC Crude Oil Production 1999-2001  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: EIA assumes in its base case that OPEC 10 production averages about 0.6 million barrels per day less in the 1st quarter of 2001 than was produced in the 4th quarter of 2000. This is based on the assumption that beginning in February 2001, OPEC 10 production is 1 million barrels per day less than the estimate for December 2000. From the fourth quarter of 1999 to the 4th quarter of 2000, worldwide oil production increased by about 3.7 million barrels per day to a level of 77.8 million barrels per day. After being sharply curtailed in December 2000, EIA's base case assumes that Iraqi oil exports only partially return in January. By February, EIA assumes Iraqi crude oil production reaches 3 million barrels per day, roughly the peak levels reached last year.

326

OPEC Crude Oil Production 1998-2001  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: EIA assumes in its base case that OPEC 10 production averages about 0.6 million barrels per day less in the 1st quarter of 2001 than was produced in the 4th quarter of 2000. This is based on the assumption that beginning in February 2001, OPEC 10 production is 1 million barrels per day less than the estimate for December 2000. From the fourth quarter of 1999 to the 4th quarter of 2000, worldwide oil production increased by about 3.8 million barrels per day to a level of 77.9 million barrels per day. After being sharply curtailed in December and January, EIA's base case assumes that Iraqi oil exports return closer to more normal levels in February. By the second half of 2001, EIA assumes Iraqi crude oil production reaches 3 million barrels per day, roughly the peak levels

327

On Energy and Entropy Influxes in the Green-Naghdi Type III Theory of Heat Conduction  

E-Print Network [OSTI]

The energy-influx/entropy-influx relation in the Green-Naghdi Type III theory of heat conduction is examined within a thermodynamical framework \\`a la Mueller-Liu, where that relation is not specified a priori irrespectively of the constitutive class under attention. It is shown that the classical assumption, i.e., that the entropy influx and the energy influx are proportional via the absolute temperature, holds true if heat conduction is, in a sense that is made precise, isotropic. In addition, it is proven that the standard assumption does not hold in case of transversely isotropic conduction.

Swantje Bargmann; Antonino Favata; Paolo Podio-Guidugli

2012-09-13T23:59:59.000Z

328

Types of Costs Types of Cost Estimates  

E-Print Network [OSTI]

first cost or capital investment): ­ Expenditures made to acquire or develop capital assets ­ Three main· Types of Costs · Types of Cost Estimates · Methods to estimate capital costs MIN E 408: Mining-site management or corporate level expenditure · Direct vs. Indirect Costs ­ Direct (or variable) costs apply

Boisvert, Jeff

329

Types of Costs Types of Cost Estimates  

E-Print Network [OSTI]

-Revenue Relationships · Capital Costs (or first cost or capital investment): ­ Expenditures made to acquire or develop05-1 · Types of Costs · Types of Cost Estimates · Methods to estimate capital costs MIN E 408 ­ off-site management or corporate level expenditure · Direct vs. Indirect Costs ­ Direct (or variable

Boisvert, Jeff

330

AQUA Products | Open Energy Information  

Open Energy Info (EERE)

AQUA Products AQUA Products Jump to: navigation, search Name AQUA Products Place Prosperity, SC Zip 29127 Product Manufacturer of small tonnage chiller systems Year founded 1993 Website http://www.aquaproducts.us/ Coordinates 34.2093079°, -81.5331602° 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":34.2093079,"lon":-81.5331602,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

331

MEMORANDUM TO: FILE TYPE OF OPERATION  

Office of Legacy Management (LM)

TYPE OF OPERATION TYPE OF OPERATION _--__---~~--~---~ a Research & Development cl Facility Type 0 Production scale testing 0 Pilot Scale 0 Bench Scale Process 0 Theoretical Studies a Sample SC Analysis 0 Hanuf actuiing 0 University a Research Organization 0 Government Sponsored Facility 0 Other ~---~~--_--_~-___--~ 0 Production 0 Disposal/Storage IYPLPEs!b!Iw!EI 0 Prime a 0 Subcontract& Other information (i.e., cost + fixed fee. unit price, *! Purchase Order time & material, qtc) _------ -------------42-----__--_---- ContFact/Purchase Order # ud IdlijL1\^IIJ ---------------------------- --------------------------------- OWNERSHIP: GOUT GOVT CONTRACTOR -CONTRACTOR awED LE_ASED OWNED ---------- ~-~LE!sEn LANDS BUILDINGS EQUIPMENT ORE OR RAW MATL 0 FINAL PRODUCT 0

332

PRODUCTS & MATERIALS  

Science Journals Connector (OSTI)

...Phar-macia Biotech. Circle 141. Cell Culture Production The CellCube offers the fastest, most com-pact system available for high-volume...culture production, according to the manu-facturer. The CellCube not only saves up to four times the space of roller bottles...

1995-08-04T23:59:59.000Z

333

NEW PRODUCTS:  

Science Journals Connector (OSTI)

......There are 7 types of TSK standard poly(ethylene oxide) standards available and 20 types...savings of more than 50% over new container prices for most gases. Lecture Bottle Gases...chromatography. Features, de- scriptions, and prices are included for columns, packings......

New Products

1979-12-01T23:59:59.000Z

334

Notice Type: Presolicitation  

E-Print Network [OSTI]

: 334 -- Computer and Electronic Product Manufacturing/334513 -- Instruments and Related Products Manufacturing for Measuring, Displaying, and Controlling Industrial Process Variables Synopsis: Added: Jul 19 QUADRUPOLE Mass Spectrometer. (Microsoft IE required). Additional specifications and opening and closing

335

Quality attributes of four morphological types of tomatoes  

E-Print Network [OSTI]

ABSTRACT QUALITY ATTRIBUTL'S OF FOUR MORPHOLOGICAL TYPES OF TOMATOES December 1971 RONNIE J. SHAW B. S. , Texas A&M University Directed by: Dr. E, E. Burns Field ripened tomato fruit of four morphological types (blocky- pear, pear, plum, cherry...) were evaluated for raw fruit characteristics and for product characteristics of tomato juice and canned whole tomatoes produced from these fruit types. Correlations between attributes of raw tomato fruit and product quality were noted. Comparisons...

Shaw, Ronnie Joe

1971-01-01T23:59:59.000Z

336

Structuring product development processes  

Science Journals Connector (OSTI)

This paper proposes operational frameworks for structuring product development processes. The primary objective of this research is to develop procedures to minimize iterations during the development process which adversely affect development time and costs. Several procedures are introduced to restructure the development process. The computation of the corresponding product development times is facilitated by two Markov models addressing different types of learning. The methodologies are employed to identify a set of managerial concerns in restructuring the product development processes. The developed framework has become an integral part of a re-engineering project for the development of rocket engines at Rocketdyne Division of Rockwell International. Throughout the paper, the methodologies are illustrated with the help of this process.

Reza Ahmadi; Thomas A. Roemer; Robert H. Wang

2001-01-01T23:59:59.000Z

337

Types of Hydropower Plants  

Broader source: Energy.gov [DOE]

There are three types of hydropower facilities: impoundment, diversion, and pumped storage. Some hydropower plants use dams and some do not. The images below show both types of hydropower plants.

338

USDA Forest Products Laboratory | Open Energy Information  

Open Energy Info (EERE)

Forest Products Laboratory Forest Products Laboratory Jump to: navigation, search Name USDA Forest Products Laboratory Place Madison, WI Website http://www.fpl.fs.fed.us/ References USDA Forest Products Laboratory [1] Information About Partnership with NREL Partnership with NREL Yes Partnership Type Test & Evaluation Partner Partnering Center within NREL Electricity Resources & Building Systems Integration LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! USDA Forest Products Laboratory is a company located in Madison, WI. References ↑ "USDA Forest Products Laboratory" Retrieved from "http://en.openei.org/w/index.php?title=USDA_Forest_Products_Laboratory&oldid=381741" Categories: Clean Energy Organizations Companies Organizations

339

Recurrence formulas for Macdonald polynomials of type A  

E-Print Network [OSTI]

Recurrence formulas for Macdonald polynomials of type A Michel Lassalle Centre National de la://www.mat.univie.ac.at/~schlosse Abstract We consider products of two Macdonald polynomials of type A, indexed by dominant weights which­th fundamental weight. We give the explicit decomposition of any Macdonald polynomial of type A in terms

Schlosser, Michael

340

Recurrence formulas for Macdonald polynomials of type A  

E-Print Network [OSTI]

Recurrence formulas for Macdonald polynomials of type A Michel Lassalle Centre National de la://www.mat.univie.ac.at/~schlosse Abstract We consider products of two Macdonald polynomials of type A, indexed by dominant weights which-th fundamental weight. We give the explicit decomposition of any Macdonald polynomial of type A in terms

Schlosser, Michael

Note: This page contains sample records for the topic "assumptions product types" 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

Typing aspects for MATLAB  

Science Journals Connector (OSTI)

The MATLAB programming language is heavily used in many scientific and engineering domains. Part of the appeal of the language is that one can quickly prototype numerical algorithms without requiring any static type declarations. However, this lack of ... Keywords: MATLAB, dynamic type assertions, typing aspects

Laurie Hendren

2011-03-01T23:59:59.000Z

342

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Backorders Under the (R,r) Policy  

E-Print Network [OSTI]

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Backorders Under the (R Infinitesimal Perturbation Analysis (IPA) in the class of Make-to Stock (MTS) production-inventory systems regularity assumptions. The paper then analyzes the SFM counterpart and derives closed-form IPA derivative

343

Accelerating Cosmologies with Extended Product Spaces  

E-Print Network [OSTI]

Accelerating cosmologies in extra dimensional spaces have been studied. These extra dimensional spaces are products of many spaces. The physical behaviors of accelerating cosmologies are investigated from Einstein's field equation in higher dimensional Friedmann-Robertson-Walker (FRW) universe and superstring/M theory points of view. It is found that if some assumptions of flatness are made for sector of the FRW universe, the remaining sector needs to be hyperbolic. These properties are in parallel with those found in the model of superstring/M theory. The extended product made for the superstring model did not show any more new features other than those already found. A similar accelerating phase of this product space cosmology was found with difference in numerical values of the accelerating period.

Han Siong Ch'ng

2008-10-15T23:59:59.000Z

344

Alternative Fuels Data Center: Ethanol Production Incentive  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol Production Ethanol Production Incentive to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Incentive on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Incentive on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Google Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Delicious Rank Alternative Fuels Data Center: Ethanol Production Incentive on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Incentive on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Incentive The Ethanol Production Incentive provides qualified ethanol producers with quarterly payments based on production volume during times when ethanol

345

New Products  

Science Journals Connector (OSTI)

...security of unmatched sample traceability. Manufactured from high-quality polypropylene in a fully automated class-7 cleanroom environment ensures the laser-etched alphanumeric tubes exhibit absolute product consistency, near-zero contaminants...

2013-01-11T23:59:59.000Z

346

New Products  

Science Journals Connector (OSTI)

...bind cells and biomolecules through passive hydrophobic interactions. Molded from ultrapure polystyrene in a class 100,000 cleanroom production environment, the untreated culture plates are supplied with lids in individual sterile packs. The plates include...

2013-06-28T23:59:59.000Z

347

Production Materials  

Science Journals Connector (OSTI)

It is obvious that we must bring a number of things into our controlled environment besides clean conditioned air, equipment, and ultrapure water. If we are to do any production work, or research involving the pr...

M. Kozicki; S. Hoenig; P. Robinson

1991-01-01T23:59:59.000Z

348

New Products  

Science Journals Connector (OSTI)

...Finally, as a personal pipetting system, Liquidator 96 fits any benchtop or laminar-flow cabinet making it suitable for cleanroom conditions. Mettler Toledo For info: 800-472-4646 www.mt.com/liquidator Electronically submit your new product...

2014-01-03T23:59:59.000Z

349

Forest Products  

Broader source: Energy.gov [DOE]

Purchased energy remains the third largest manufacturing cost for the forest products industrydespite its extensive use of highly efficient co-generation technology. The industry has worked with...

350

NEW PRODUCTS:  

Science Journals Connector (OSTI)

......also be used with other heating elements and probes...content of diesel and heating oils. A highly specific titration...requirements for fuel oil products are consistently...de- scriptions, and prices are included for columns......

New Products

1979-12-01T23:59:59.000Z

351

New Products  

Science Journals Connector (OSTI)

...the area scanned. When the earth's thermal gradient appears, the vibrating mirror...Write for a Product Data Sheet giving specifications, typical drying perform-ance, and...pebble-bed heaters and electrical insulation at elevated temperatures. (Minneapolis-Honeywell...

Joshua Stern

1961-11-10T23:59:59.000Z

352

Hydrogen Production  

Fuel Cell Technologies Publication and Product Library (EERE)

This 2-page fact sheet provides a brief introduction to hydrogen production technologies. Intended for a non-technical audience, it explains how different resources and processes can be used to produ

353

Malczewski Product Design LLC | Open Energy Information  

Open Energy Info (EERE)

Malczewski Product Design LLC Malczewski Product Design LLC Jump to: navigation, search Name Malczewski Product Design LLC Place Neenah, Wisconsin Zip 54956 Sector Wind energy Product Product development start-up planning to design, develop, patent, and distribute a new type of wind generator. Coordinates 44.186095°, -88.461954° 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":44.186095,"lon":-88.461954,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

354

Production and Use of Alcohol on the Farm.  

E-Print Network [OSTI]

projects. 4. The plant manufacturer should be able to guarantee the following production factors: ? Yield factor (gallons of alcohol produced per unit volume or weight of feedstock at a given dry starch and/or sugar content; for example, gallons per... of Operation Capital recovery (depreciation and interest) $ 90,000 x 0.1598 $125,000 x 0.1598 Insurance (estimated) Property taxes (estimated) Mise. (permits, bonding, ete.) Total Fixed Costs Average Fixed Cost Per Gallon Assumptions: Salvage value...

O'Neal, Henry; Rothe, Joe M.

1981-01-01T23:59:59.000Z

355

Notice Type: Presolicitation  

E-Print Network [OSTI]

-- Fabricated Metal Product Manufacturing/332996 -- Fabricated Pipe and Pipe Fitting Manufacturing Synopsis Materials. (Microsoft IE required). Additional specifications and opening and closing dates will appear

356

Notice Type: Presolicitation  

E-Print Network [OSTI]

NAICS Code: 332 -- Fabricated Metal Product Manufacturing/332322 -- Sheet Metal Work Manufacturing Storage Container. (Microsoft IE required). Additional specifications and opening and closing dates

357

EV Solar Products | Open Energy Information  

Open Energy Info (EERE)

Solar Products Solar Products Jump to: navigation, search Logo: EV Solar Products Name EV Solar Products Address 2655 N. Highway 89 Place Chino Valley, Arizona Zip 86323 Sector Solar Product renewable energy products and services Year founded 1991 Phone number (928) 636-2201 Website http://www.evsolar.com/ Coordinates 34.8387989°, -112.4600036° 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":34.8387989,"lon":-112.4600036,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

358

Alternative Fuels Data Center: Ethanol Production Incentive  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Production Production Incentive to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Incentive on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Incentive on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Google Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Delicious Rank Alternative Fuels Data Center: Ethanol Production Incentive on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Incentive on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Incentive Montana-based ethanol producers are eligible for a tax incentive of $0.20 per gallon of ethanol produced solely from Montana agricultural products or

359

Alternative Fuels Data Center: Biodiesel Production Incentive  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biodiesel Production Biodiesel Production Incentive to someone by E-mail Share Alternative Fuels Data Center: Biodiesel Production Incentive on Facebook Tweet about Alternative Fuels Data Center: Biodiesel Production Incentive on Twitter Bookmark Alternative Fuels Data Center: Biodiesel Production Incentive on Google Bookmark Alternative Fuels Data Center: Biodiesel Production Incentive on Delicious Rank Alternative Fuels Data Center: Biodiesel Production Incentive on Digg Find More places to share Alternative Fuels Data Center: Biodiesel Production Incentive on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biodiesel Production Incentive A qualified Kansas biodiesel producer is eligible for a production incentive of $0.30 per gallon of biodiesel sold. The incentive is payable

360

Alternative Fuels Data Center: Biofuels Production Grants  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuels Production Biofuels Production Grants to someone by E-mail Share Alternative Fuels Data Center: Biofuels Production Grants on Facebook Tweet about Alternative Fuels Data Center: Biofuels Production Grants on Twitter Bookmark Alternative Fuels Data Center: Biofuels Production Grants on Google Bookmark Alternative Fuels Data Center: Biofuels Production Grants on Delicious Rank Alternative Fuels Data Center: Biofuels Production Grants on Digg Find More places to share Alternative Fuels Data Center: Biofuels Production Grants on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biofuels Production Grants The Biofuels Production Incentive Grant Program provides grants to producers of advanced biofuels, specifically fuels derived from any

Note: This page contains sample records for the topic "assumptions product types" 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

Alternative Fuels Data Center: Ethanol Production Incentive  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol Production Ethanol Production Incentive to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Incentive on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Incentive on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Google Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Delicious Rank Alternative Fuels Data Center: Ethanol Production Incentive on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Incentive on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Incentive Ethanol producers may qualify for an income tax credit equal to 30% of production facility nameplate capacity between 500,000 and 15 million

362

Alternative Fuels Data Center: Biofuels Production Incentive  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuels Production Biofuels Production Incentive to someone by E-mail Share Alternative Fuels Data Center: Biofuels Production Incentive on Facebook Tweet about Alternative Fuels Data Center: Biofuels Production Incentive on Twitter Bookmark Alternative Fuels Data Center: Biofuels Production Incentive on Google Bookmark Alternative Fuels Data Center: Biofuels Production Incentive on Delicious Rank Alternative Fuels Data Center: Biofuels Production Incentive on Digg Find More places to share Alternative Fuels Data Center: Biofuels Production Incentive on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biofuels Production Incentive Qualified ethanol and biodiesel producers are eligible for production incentives on a per gallon basis. To be eligible for the incentive, the

363

Alternative Fuels Data Center: Ethanol Production Incentive  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol Production Ethanol Production Incentive to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Incentive on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Incentive on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Google Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Delicious Rank Alternative Fuels Data Center: Ethanol Production Incentive on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Incentive on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Incentive Qualified ethanol producers are eligible for a production incentive payable from the Kansas Qualified Agricultural Ethyl Alcohol Producer Fund. An

364

Nongenetic Techniques for Isolating Fusion Products between Different Cell Types  

Science Journals Connector (OSTI)

Until recently, virtually all investigations into the behavior of cell hybrids have employed genetic selection techniques, such as the hypoxanthine-aminopterin-thymidine (HAT) system (Littlefield, 1964), to isola...

Woodring E. Wright

1987-01-01T23:59:59.000Z

365

MEMORANDUM TO: FILE FROM: TYPE OF OPERATION  

Office of Legacy Management (LM)

, , TYPE OF OPERATION ~_--_-----_---___ 69 Research & Development a Facility. Type 0 Production scale testing Cl Pilat Scale IK Bench Scale Process 0 Theoretical Studies u Sample & Analysis q Production 0 Disposal/Storage a Manufacturing 0 University 0 Research Organization 0 Government Sponsored Facility 0 Other --------------__----- TYPE OF CONTRACT ---------------- 0 Prime 0 Other information (i.e., cost 0 Subcontractor + fixed fee, unit price, 5 Purchase Order ~SlvtM ay LuPo~l- time & material, r+c) _L-G~-~~~ ------GA------ Contract/Purchase Order # 3 I -? ciYl---------------------------- AZ. FG CONTRACTING PERIOD: --------__--_____- ----&-b&-f zw------ ______________ OWNERSHIP: AEC/MED AEC/MED OWE_3 LE_A_sEQ GOUT GOVT CONTRACTOR CONTRACTOR

366

New Products  

Science Journals Connector (OSTI)

...syrris.com Crimping Tool The La-Pha-Pack stainless steel cleanroom crimping tools are designed for a controlled, low-effort...product range is ideal for highly sensitive chromatography cleanroom applications where it is essential that the environment remains...

2011-01-14T23:59:59.000Z

367

New Products  

Science Journals Connector (OSTI)

...qiagen.com Crimping Tool The La-Pha-Pack stainless steel cleanroom crimping tools are designed for a controlled, low-effort...product range is ideal for highly sensitive chromatography cleanroom applications where it is essential that the environment remains...

2011-01-21T23:59:59.000Z

368

New Products  

Science Journals Connector (OSTI)

...three regulated d-c power supplies, a digital...Product Data Sheet giving specifications, typical drying perform-ance...than 4 lb. Nominal power consumption is less...heaters and electrical insulation at elevated temperatures...and 0.01 xsec. Power source is a 5-Mw...

Joshua Stern

1961-11-10T23:59:59.000Z

369

EERE Publication and Product Library  

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

Browse By Topic Browse By Topic Browse the Products and Publications by expanding/selecting from the topic tree below. Make selection(s) in the 'Information For' box to filter your results by audience type. Similarly, use the 'Information Type' box to filter your results by the type of information presented. Topics Bioenergy Technologies Office Building Technologies Office Federal Energy Management Program Geothermal Technologies Office Fuel Cell Technologies Office Advanced Manufacturing Office Solar Energy Technologies Program Vehicle Technologies Office Wind Program Weatherization & Intergovernmental Program General Topics Energy Savers Water Power Program Energy Analysis State and Local Energy Efficiency Action Network (SEE Action) Office of EERE Select Clear Topic Skip Navigation Links.

370

Product Efficiency Cases  

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

product-efficiency-cases Office of Hearings and product-efficiency-cases Office of Hearings and Appeals 1000 Independence Ave., SW Washington, DC, 20585 202-287-1566 en EXC-13-0004 - In the Matter of Liebherr Canada Ltd. http://energy.gov/oha/downloads/exc-13-0004-matter-liebherr-canada-ltd EXC-13-0004 - In the Matter of Liebherr Canada Ltd.

371

Broiler Production.  

E-Print Network [OSTI]

,","efficient broiler production. ,. . , .: I-A +>+ Panels or translucent plastic curtains which close and open easily when weather varies are helpful in providing comfortable temperatures for the birds. A damper is needed so that ridge ventilatm can be dosed... easily during ooM weather. inclement weather. However, poultry housing costs should be kept within a range whereby earnings can justify the investment. Location Orient the house with the long axis run- ning east and west to prevent the early morn...

Cawley, W. O.; Wormeli, B. C.; Quisenberry, J. H.

1962-01-01T23:59:59.000Z

372

Optimising Shewhart charts in parallel production lines  

Science Journals Connector (OSTI)

I describe a methodology for optimising n Shewhart x-charts operating on parallel production lines in a factory. The goal is to maximise the factory-wide probability of detecting an out-of-control condition subject to a constraint on the expected number of false signals. I use non-linear programming to appropriately set the x-charts' control limits incorporating information about the probability of each production line going out-of-control. Using this approach, factories can set their quality control systems to optimally detect out-of-control conditions. Given some distributional assumptions, I also present a one-dimensional optimisation methodology that allows for the efficient optimisation of very large factories.

Ronald D. Fricker; Jr."> Jr.

2009-01-01T23:59:59.000Z

373

Alternative Fuels Data Center: Ethanol Production Credit  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol Production Ethanol Production Credit to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Credit on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Credit on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Credit on Google Bookmark Alternative Fuels Data Center: Ethanol Production Credit on Delicious Rank Alternative Fuels Data Center: Ethanol Production Credit on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Credit on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Credit County governments are eligible to receive waste reduction credits for using yard clippings, clean wood waste, or paper waste as feedstock for the

374

Alternative Fuels Data Center: Biofuels Production Promotion  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuels Production Biofuels Production Promotion to someone by E-mail Share Alternative Fuels Data Center: Biofuels Production Promotion on Facebook Tweet about Alternative Fuels Data Center: Biofuels Production Promotion on Twitter Bookmark Alternative Fuels Data Center: Biofuels Production Promotion on Google Bookmark Alternative Fuels Data Center: Biofuels Production Promotion on Delicious Rank Alternative Fuels Data Center: Biofuels Production Promotion on Digg Find More places to share Alternative Fuels Data Center: Biofuels Production Promotion on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biofuels Production Promotion The state legislature supports the Federal "25 x 25" initiative, under which 25% of the total energy consumed in the United States by 2025 would

375

Evaluation of hierarchical forecasting for substitutable products  

Science Journals Connector (OSTI)

This paper addresses hierarchical forecasting in a production planning environment. Specifically, we examine the relative effectiveness of Top-Down (TD) and Bottom-Up (BU) strategies for forecasting the demand for a substitutable product (which belongs to a family) as well as the demand for the product family under different types of family demand processes. Through a simulation study, it is revealed that the TD strategy consistently outperforms the BU strategy for forecasting product family demand. The relative superiority of the TD strategy further improves by as much as 52% as the product demand variability increases and the degree of substitutability between the products decreases. This phenomenon, however, is not always true for forecasting the demand for the products within the family. In this case, it is found that there are a few situations wherein the BU strategy marginally outperforms the TD strategy, especially when the product demand variability is high and the degree of product substitutability is low.

S. Viswanathan; Handik Widiarta; R. Piplani

2008-01-01T23:59:59.000Z

376

Alternative Fuels Data Center: Biodiesel Production Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biodiesel Production Biodiesel Production Tax to someone by E-mail Share Alternative Fuels Data Center: Biodiesel Production Tax on Facebook Tweet about Alternative Fuels Data Center: Biodiesel Production Tax on Twitter Bookmark Alternative Fuels Data Center: Biodiesel Production Tax on Google Bookmark Alternative Fuels Data Center: Biodiesel Production Tax on Delicious Rank Alternative Fuels Data Center: Biodiesel Production Tax on Digg Find More places to share Alternative Fuels Data Center: Biodiesel Production Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biodiesel Production Tax A private biodiesel producer that produces less than 5,000 gallons of biodiesel annually is subject to the annual state motor fuel tax. The

377

Alternative Fuels Data Center: Ethanol Production Incentive  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol Production Ethanol Production Incentive to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Incentive on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Incentive on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Google Bookmark Alternative Fuels Data Center: Ethanol Production Incentive on Delicious Rank Alternative Fuels Data Center: Ethanol Production Incentive on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Incentive on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Incentive The Missouri Department of Agriculture manages the Missouri Ethanol Producer Incentive Fund (Fund), which provides monthly grants to qualified

378

Notice Type: Presolicitation  

E-Print Network [OSTI]

radiation equipment NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334511 -- Search, Detection, Navigation, Guidance, Aeronautical, and Nautical System and Instrument Manufacturing Synopsis. (Microsoft IE required). Additional specifications and opening and closing dates will appear in the RFQ

379

Notice Type: Presolicitation  

E-Print Network [OSTI]

-- Computer and Electronic Product Manufacturing/334515 -- Instrument Manufacturing for Measuring and Testing power handling P/N: XPDV4121R-WF-FP. (Microsoft IE required). Additional specifications and opening

380

Notice Type: Presolicitation  

E-Print Network [OSTI]

: 334 -- Computer and Electronic Product Manufacturing/334515 -- Instrument Manufacturing for Measuring-SMU and 1 each Ultra-Fast I-V Module P/N: 4225-PMU. (Microsoft IE required). Additional specifications

Note: This page contains sample records for the topic "assumptions product types" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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381

Notice Type: Presolicitation  

E-Print Network [OSTI]

-- Computer and Electronic Product Manufacturing/334515 -- Instrument Manufacturing for Measuring and Testing Polarization P/N: WS-AA-2000S-ZZ-H. (Microsoft IE required). Additional specifications and opening and closing

382

Kaon and Lambda productions in relativistic heavy ion collisions  

Science Journals Connector (OSTI)

A microscopic approach has been employed to study the kaon and ? productions in heavy ion collisions. The productions of K + and ? have been studied within the framework of Boltzmann transport equation for various beam energies. We find a non-monotonic horn like structure for K + / p i + and ? / ? when plotted against centre of mass energies ( s N N ) with the assumption of initial partonic phase for s N N shows a monotonic nature when a hadronic initial state is considered for all s N N . Experimental values of K ? / ? ? for different s N N are also reproduced within the ambit of the same formalism.

Jajati K. Nayak; Sarmistha Banik; Jan-e Alam

2011-01-01T23:59:59.000Z

383

Alternative Fuels Data Center: Ethanol Production Equipment Tax Exemption  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol Production Ethanol Production Equipment Tax Exemption to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Equipment Tax Exemption on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Equipment Tax Exemption on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Equipment Tax Exemption on Google Bookmark Alternative Fuels Data Center: Ethanol Production Equipment Tax Exemption on Delicious Rank Alternative Fuels Data Center: Ethanol Production Equipment Tax Exemption on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Equipment Tax Exemption on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Equipment Tax Exemption

384

Alternative Fuels Data Center: Biofuels Production Facility Grants  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuels Production Biofuels Production Facility Grants to someone by E-mail Share Alternative Fuels Data Center: Biofuels Production Facility Grants on Facebook Tweet about Alternative Fuels Data Center: Biofuels Production Facility Grants on Twitter Bookmark Alternative Fuels Data Center: Biofuels Production Facility Grants on Google Bookmark Alternative Fuels Data Center: Biofuels Production Facility Grants on Delicious Rank Alternative Fuels Data Center: Biofuels Production Facility Grants on Digg Find More places to share Alternative Fuels Data Center: Biofuels Production Facility Grants on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biofuels Production Facility Grants The Renewable Fuels Development Program provides grants for the

385

Alternative Fuels Data Center: Biodiesel Production Investment Tax Credit  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biodiesel Production Biodiesel Production Investment Tax Credit to someone by E-mail Share Alternative Fuels Data Center: Biodiesel Production Investment Tax Credit on Facebook Tweet about Alternative Fuels Data Center: Biodiesel Production Investment Tax Credit on Twitter Bookmark Alternative Fuels Data Center: Biodiesel Production Investment Tax Credit on Google Bookmark Alternative Fuels Data Center: Biodiesel Production Investment Tax Credit on Delicious Rank Alternative Fuels Data Center: Biodiesel Production Investment Tax Credit on Digg Find More places to share Alternative Fuels Data Center: Biodiesel Production Investment Tax Credit on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biodiesel Production Investment Tax Credit

386

Alternative Fuels Data Center: Hydrogen Production and Retail Requirements  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Hydrogen Production Hydrogen Production and Retail Requirements to someone by E-mail Share Alternative Fuels Data Center: Hydrogen Production and Retail Requirements on Facebook Tweet about Alternative Fuels Data Center: Hydrogen Production and Retail Requirements on Twitter Bookmark Alternative Fuels Data Center: Hydrogen Production and Retail Requirements on Google Bookmark Alternative Fuels Data Center: Hydrogen Production and Retail Requirements on Delicious Rank Alternative Fuels Data Center: Hydrogen Production and Retail Requirements on Digg Find More places to share Alternative Fuels Data Center: Hydrogen Production and Retail Requirements on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Hydrogen Production and Retail Requirements

387

Alternative Fuels Data Center: Biofuels Production Property Tax Exemption  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuels Production Biofuels Production Property Tax Exemption to someone by E-mail Share Alternative Fuels Data Center: Biofuels Production Property Tax Exemption on Facebook Tweet about Alternative Fuels Data Center: Biofuels Production Property Tax Exemption on Twitter Bookmark Alternative Fuels Data Center: Biofuels Production Property Tax Exemption on Google Bookmark Alternative Fuels Data Center: Biofuels Production Property Tax Exemption on Delicious Rank Alternative Fuels Data Center: Biofuels Production Property Tax Exemption on Digg Find More places to share Alternative Fuels Data Center: Biofuels Production Property Tax Exemption on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biofuels Production Property Tax Exemption

388

Alternative Fuels Data Center: Ethanol Production Investment Tax Credits  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol Production Ethanol Production Investment Tax Credits to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Investment Tax Credits on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Investment Tax Credits on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Investment Tax Credits on Google Bookmark Alternative Fuels Data Center: Ethanol Production Investment Tax Credits on Delicious Rank Alternative Fuels Data Center: Ethanol Production Investment Tax Credits on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Investment Tax Credits on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Investment Tax Credits

389

Document Type: Subject Terms  

E-Print Network [OSTI]

Title: Authors: Source: Document Type: Subject Terms: Abstract: Full Text Word Count: ISSN the department back on track. The action is to call a meeting of the team leaders and stress the urgency o

Major, Arkady

390

Heartland Corn Products | Open Energy Information  

Open Energy Info (EERE)

Corn Products Corn Products Jump to: navigation, search Name Heartland Corn Products Place Winthrop, Minnesota Zip 55396 Product Heartland Corn Products is farmer-owned cooperative that produces corn-derived ethanol. Coordinates 48.47373°, -120.177559° 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":48.47373,"lon":-120.177559,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

391

Positive Energy Conservation Products | Open Energy Information  

Open Energy Info (EERE)

Positive Energy Conservation Products Positive Energy Conservation Products Jump to: navigation, search Name Positive Energy Conservation Products Address PO Box 7568 Place Boulder, Colorado Zip 80306 Sector Efficiency Product Distributor of energy efficiency products - lighting, heating, cooling, water Website http://www.positive-energy.com Coordinates 40.0153°, -105.2702° 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":40.0153,"lon":-105.2702,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

392

Ashworths Products Ltd | Open Energy Information  

Open Energy Info (EERE)

Ashworths Products Ltd Ashworths Products Ltd Jump to: navigation, search Name Ashworths Products Ltd Place Lancashire, England, United Kingdom Product Lancashire-based producer of biodiesel from waste animal and vegetable fats, most of which is used for energy production through co-firing. Coordinates 53.86121°, -2.56483° 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":53.86121,"lon":-2.56483,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

393

MARINE BIOMASS SYSTEM: ANAEROBIC DIGESTION AND PRODUCTION OF METHANE  

E-Print Network [OSTI]

Design Parameters Marine Biomass Production Sea Farmof Various Types of Biomass . Biomethanation Parameters.Proceedings, Fuels from Biomass Symposium. University of

Haven, Kendall F.

2011-01-01T23:59:59.000Z

394

Type I Tanks  

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

I Tanks I Tanks * 12 Type I tanks were built between 1951-53 * 750,000 gallon capacity; 75 feet in diameter by 24 ½ feet high * Partial secondary containment with leak detection * Contain approximately 10 percent of the waste volume * 7 Type I tanks have leaked waste into the tank annulus; the amount of waste stored in these tanks is kept below the known leak sites that have appeared over the decades of

395

Jansen type of spondylometaphyseal dysplasia  

Science Journals Connector (OSTI)

Metaphyseal dysplasia, type Jansen (JMD), is a rare skeletal dysplasia ... we propose the term spondylometaphyseal dysplasia, type Jansen.

J. B. Campbell; Kazimierz Kozlowski; Tadeusz Lejman; J. Sulko

2000-04-01T23:59:59.000Z

396

Sugar Production  

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

Sugar Production Sugar Production Name: Lauren Location: N/A Country: N/A Date: N/A Question: This is the experiment I did: our class took 6 sugars, placed them in test tubes and put three drops of yeast in each test tube. we then placed them in the incubator for one day and the next day looked at our results. the purpose was to find out with sugar would produce the most carbon dioxide. two of the sugars that we tested were LACTOSE and STARCH. my question is, why are lactose and starch the only sugars who didn't produce any, or very very little, carbon dioxide? and how is this process related to glycolysis? Replies: Bacteria and yeast are very efficient with their enzyme systems. They don't make enzymes they can't use. Yeast don't have the enzymes necessary to metabolize lactose. Starch is a complex sugar and yeast needs certain enzymes to break starch down into sugar. Every chemical reaction needs its own enzyme.

397

Video Production Services Computing and IT  

E-Print Network [OSTI]

#12;#12;#12;#12;#12;#12;#12;#12;#12;#12;#12;#12;Video Production Services Computing Captioning software #12;#12;Laptop/ speed typing software Encoder/ Decoder Video feed Captioning software Screen display #12;#12;Laptop/ speed typing software Encoder/ Decoder Video feed Captioning software

Bolding, M. Chad

398

Determination of Hydrocarbons Types and Oxygenates in Motor Gasoline: A Comparative Study by Different Analytical Techniques  

Science Journals Connector (OSTI)

Various standard and published methods based on chromatographic and spectroscopic techniques are routinely used for hydrocarbon types (aromatics, olefins, oxygenates, etc.) in gasoline range fuel products for the assessment of product quality monitoring (...

V. Bansal; G. J. Krishna; A. P. Singh; A. K. Gupta; A. S. Sarpal

2007-12-04T23:59:59.000Z

399

Types of quantum information  

E-Print Network [OSTI]

Quantum, in contrast to classical, information theory, allows for different incompatible types (or species) of information which cannot be combined with each other. Distinguishing these incompatible types is useful in understanding the role of the two classical bits in teleportation (or one bit in one-bit teleportation), for discussing decoherence in information-theoretic terms, and for giving a proper definition, in quantum terms, of ``classical information.'' Various examples (some updating earlier work) are given of theorems which relate different incompatible kinds of information, and thus have no counterparts in classical information theory.

Robert B. Griffiths

2007-07-25T23:59:59.000Z

400

Types of quantum information  

Science Journals Connector (OSTI)

Quantum, in contrast to classical, information theory, allows for different incompatible types (or species) of information which cannot be combined with each other. Distinguishing these incompatible types is useful in understanding the role of the two classical bits in teleportation (or one bit in one-bit teleportation), for discussing decoherence in information-theoretic terms, and for giving a proper definition, in quantum terms, of classical information. Various examples (some updating earlier work) are given of theorems which relate different incompatible kinds of information, and thus have no counterparts in classical information theory.

Robert B. Griffiths

2007-12-21T23:59:59.000Z

Note: This page contains sample records for the topic "assumptions product types" 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

Production Services  

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

Welcome Welcome The Production Services site contains links to each of the division's groups with descriptions of their services. Our goal is to update this website frequently to reflect ongoing service upgrades which, by planning and design, are added so that we can continue to meet your needs in a constantly changing work environment. Note: The Graphic Design Studio has been relocated to the second floor in the north wing of the Research Support Building 400. The telephone number remains the same, X7288. If you have any questions, please call supervisor, Rick Backofen, X6183. Photography Photography services are available at no charge to BNL and Guest users. See a list of the complete range of photography services available. Video Video services are available at no charge to BNL and Guest users. See a list of the complete range of video services available.

402

Zygote formation and recombination between like mating types in the yeast Saccharomycopsis lipolytica by protoplast fusion  

Science Journals Connector (OSTI)

Protoplasts from auxotrophic strains of the alkane yeast, Saccharomycopsis (Candida) lipolytica, will hybridize despite identity in mating type. Fusion products following regeneration and selection form stable .....

Ulf Stahl

403

Type B Accident Investigation of the Arc Flash at Brookhaven National Laboratory, April 14, 2006  

Broader source: Energy.gov [DOE]

This report is an independent product of the Type B Accident Investigation Board appointed by Elizabeth D. Sellers, Manager, Idaho Operations Office, U.S. Department of Energy.

404

Table 14. U.S. Propane (Consumer Grade) Prices by Sales Type  

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

and EIA-782B, "Resellers'Retailers' Monthly Petroleum Product Sales Report." 14. U.S. Propane (Consumer Grade) Prices by Sales Type 28 Energy Information Administration ...

405

Notice Type: Presolicitation  

E-Print Network [OSTI]

radiation equipment NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334220 -- Radio and Television Broadcasting and Wireless Communications Equipment Manufacturing Synopsis: Added: Aug 25, 2014 6 Assembly P/N: 130-314700. (Microsoft IE required). Additional specifications and opening and closing dates

406

Notice Type: Presolicitation  

E-Print Network [OSTI]

components NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334111 -- Electronic Computer Manufacturing Synopsis: Added: Sep 03, 2014 9:57 am The Naval Research Laboratory has a requirement for 2 each S required). Additional specifications and opening and closing dates will appear in the RFQ. The proposed

407

Notice Type: Presolicitation  

E-Print Network [OSTI]

radiation equipment NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334220 -- Radio and Television Broadcasting and Wireless Communications Equipment Manufacturing Synopsis: Added: Jul 15, 2014 7 and transmitter plug-in modules. (Microsoft IE required). Additional specifications and opening and closing dates

408

Notice Type: Presolicitation  

E-Print Network [OSTI]

: 334 -- Computer and Electronic Product Manufacturing/334516 -- Analytical Laboratory Instrument Manufacturing Synopsis: Added: Aug 21, 2014 2:43 pm The Naval Research Laboratory has a requirement for 1 each i-00105. (Microsoft IE required). Additional specifications and opening and closing dates will appear in the RFQ

409

Notice Type: Presolicitation  

E-Print Network [OSTI]

: 334 -- Computer and Electronic Product Manufacturing/334515 -- Instrument Manufacturing for Measuring and Testing Electricity and Electrical Signals Synopsis: Added: Jul 25, 2014 9:09 am The Naval Research processor P/N: N9094AK-PC4, 1 each Waveguide Harmonic Mixer P/N: M1970W, 1 each USB Cables P/N: M1970W-202

410

Notice Type: Presolicitation  

E-Print Network [OSTI]

-- Computer and Electronic Product Manufacturing/334515 -- Instrument Manufacturing for Measuring and Testing Electricity and Electrical Signals Synopsis: Added: Apr 30, 2014 9:39 am The Naval Research Laboratory has. S., 125VAC, 15A P/N: 763830-01, 1 each DisplayPort to VGA Adapter Cable P/N: 782271-01, 1 each NI

411

Notice Type: Presolicitation  

E-Print Network [OSTI]

: 334 -- Computer and Electronic Product Manufacturing/334516 -- Analytical Laboratory Instrument Manufacturing Synopsis: Added: Sep 05, 2014 1:20 pm The Naval Research Laboratory has a requirement for 1 each. (Microsoft IE required). Additional specifications and opening and closing dates will appear in the RFQ

412

Notice Type: Presolicitation  

E-Print Network [OSTI]

: 334 -- Computer and Electronic Product Manufacturing/334516 -- Analytical Laboratory Instrument Manufacturing Synopsis: Added: Aug 21, 2014 1:14 pm The Naval Research Laboratory has a requirement for 1 each required). Additional specifications and opening and closing dates will appear in the RFQ. The proposed

413

Notice Type: Presolicitation  

E-Print Network [OSTI]

components NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334419 -- Other Electronic Component Manufacturing Synopsis: Added: Sep 05, 2014 1:28 pm The Naval Research Laboratory has a requirement for 1 each Microwave Power Module P/N: M1245-XX. (Microsoft IE required). Additional

414

Notice Type: Presolicitation  

E-Print Network [OSTI]

components NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334417 -- Electronic Connector Manufacturing Synopsis: Added: Sep 03, 2014 2:13 pm The Naval Research Laboratory has a requirement for 3,200 each MADP-12934 SMPS (F) to SMPM (F) Bullet. (Microsoft IE required). Additional specifications

415

Notice Type: Presolicitation  

E-Print Network [OSTI]

components NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334419 -- Other Electronic Component Manufacturing Synopsis: Added: Sep 03, 2014 2:53 pm The Naval Research Laboratory has a requirement for 1 each 6-18 GHz Activity Detection Module P/N: N13-4167. (Microsoft IE required). Additional

416

Notice Type: Presolicitation  

E-Print Network [OSTI]

components NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334413 -- Semiconductor and Related Device Manufacturing Synopsis: Added: Sep 05, 2014 8:45 am The Naval Research Laboratory has a requirement for 1 each P/N: NUU102E UV Laser Engineering Module. (Microsoft IE required). Additional

417

Notice Type: Presolicitation  

E-Print Network [OSTI]

: 334 -- Computer and Electronic Product Manufacturing/334516 -- Analytical Laboratory Instrument Manufacturing Synopsis: Added: Sep 05, 2014 8:59 am The Naval Research Laboratory has a requirement for 1 each P IE required). Additional specifications and opening and closing dates will appear in the RFQ

418

Notice Type: Presolicitation  

E-Print Network [OSTI]

components NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334417 -- Electronic Connector Manufacturing Synopsis: Added: Aug 14, 2014 4:06 pm The Naval Research Laboratory has a requirement for 576 each MM4S-13420 MM4S Female 50-OHM Termination. (Microsoft IE required). Additional specifications

419

Notice Type: Presolicitation  

E-Print Network [OSTI]

: 334 -- Computer and Electronic Product Manufacturing/334516 -- Analytical Laboratory Instrument Manufacturing Synopsis: Added: Sep 03, 2014 2:31 pm The Naval Research Laboratory has a requirement for 1 each/N: 999800.528. (Microsoft IE required). Additional specifications and opening and closing dates will appear

420

Notice Type: Presolicitation  

E-Print Network [OSTI]

radiation equipment NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334220 -- Radio and Television Broadcasting and Wireless Communications Equipment Manufacturing Synopsis: Added: Jul 25, 2014 6 1x4) Multicouple 30 MHz to 6 GHz M/N: 8MDP-206000E. (Microsoft IE required). Additional

Note: This page contains sample records for the topic "assumptions product types" 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

Notice Type: Presolicitation  

E-Print Network [OSTI]

: 334 -- Computer and Electronic Product Manufacturing/334419 -- Other Electronic Component Manufacturing Synopsis: Added: Jul 02, 2014 1:54 pm The Naval Research Laboratory has a requirement for 1 each No: 12072-2-RFB. (Microsoft IE required). Additional specifications and opening and closing dates

422

Notice Type: Presolicitation  

E-Print Network [OSTI]

components NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334413 -- Semiconductor and Related Device Manufacturing Synopsis: Added: Sep 05, 2014 8:20 am The Naval Research Laboratory has System P/N: ATC-2200-HY. (Microsoft IE required). Additional specifications and opening and closing dates

423

Notice Type: Presolicitation  

E-Print Network [OSTI]

components NAICS Code: 334 -- Computer and Electronic Product Manufacturing/334413 -- Semiconductor and Related Device Manufacturing Synopsis: Added: Sep 03, 2014 9:36 am The Naval Research Laboratory has-39-FC/APC-V-1. (Microsoft IE required). Additional specifications and opening and closing dates

424

Fusion systems of -type  

Science Journals Connector (OSTI)

We prove results on 2-fusion systems related to the 2-fusion systems of groups of Lie type over the field of order 2 and certain sporadic groups. The results are used in a later paper to determine the N-systems: the 2-fusion systems of N-groups.

Michael Aschbacher

2013-01-01T23:59:59.000Z

425

Pruning Simply Typed -terms  

Science Journals Connector (OSTI)

......looking for the smallest pout > r /) 6out > //_ gout > B,, c/) pout > p such that: pout...and pout h ^out . Bout b y minimaiKy o f tout gout pout w e deduce; 6out gout gout^ pout < pout Pruning Simply Typed A-terms......

STEFANO BERARDI

1996-10-01T23:59:59.000Z

426

Alternative Fuels Data Center: Ethanol and Biobutanol Production Incentive  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol and Biobutanol Ethanol and Biobutanol Production Incentive to someone by E-mail Share Alternative Fuels Data Center: Ethanol and Biobutanol Production Incentive on Facebook Tweet about Alternative Fuels Data Center: Ethanol and Biobutanol Production Incentive on Twitter Bookmark Alternative Fuels Data Center: Ethanol and Biobutanol Production Incentive on Google Bookmark Alternative Fuels Data Center: Ethanol and Biobutanol Production Incentive on Delicious Rank Alternative Fuels Data Center: Ethanol and Biobutanol Production Incentive on Digg Find More places to share Alternative Fuels Data Center: Ethanol and Biobutanol Production Incentive on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol and Biobutanol Production Incentive

427

Alternative Fuels Data Center: Biofuels Production and Distribution  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuels Production Biofuels Production and Distribution Contracts to someone by E-mail Share Alternative Fuels Data Center: Biofuels Production and Distribution Contracts on Facebook Tweet about Alternative Fuels Data Center: Biofuels Production and Distribution Contracts on Twitter Bookmark Alternative Fuels Data Center: Biofuels Production and Distribution Contracts on Google Bookmark Alternative Fuels Data Center: Biofuels Production and Distribution Contracts on Delicious Rank Alternative Fuels Data Center: Biofuels Production and Distribution Contracts on Digg Find More places to share Alternative Fuels Data Center: Biofuels Production and Distribution Contracts on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type

428

Alternative Fuels Data Center: Alternative Fuel Production Subsidy  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Fuel Fuel Production Subsidy Prohibition to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Production Subsidy Prohibition on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Production Subsidy Prohibition on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Production Subsidy Prohibition on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Production Subsidy Prohibition on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Production Subsidy Prohibition on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Production Subsidy Prohibition on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Production Subsidy Prohibition

429

Alternative Fuels Data Center: Sustainable Biofuels Production Practices  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Sustainable Biofuels Sustainable Biofuels Production Practices to someone by E-mail Share Alternative Fuels Data Center: Sustainable Biofuels Production Practices on Facebook Tweet about Alternative Fuels Data Center: Sustainable Biofuels Production Practices on Twitter Bookmark Alternative Fuels Data Center: Sustainable Biofuels Production Practices on Google Bookmark Alternative Fuels Data Center: Sustainable Biofuels Production Practices on Delicious Rank Alternative Fuels Data Center: Sustainable Biofuels Production Practices on Digg Find More places to share Alternative Fuels Data Center: Sustainable Biofuels Production Practices on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Sustainable Biofuels Production Practices

430

Covered Product Category: Light Fixtures (Luminaires)  

Broader source: Energy.gov [DOE]

FEMP provides acquisition guidance and Federal efficiency requirements across a variety of product categories, including luminaires, or light fixtures. The luminaires product category is very broad and covers a wide variety of lighting products. Both ENERGY STAR and FEMP provide programmatic guidance for various types of luminaires. See table 2 for more information about which types of light fixtures are covered by which program (FEMP or ENERGY STAR). Federal laws and requirements mandate that agencies meet these efficiency requirements in all procurement and acquisition actions that are not specifically exempted by law.

431

List of Portfolio Manager property types, definitions, and use details |  

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

List of Portfolio Manager property types, definitions, and use List of Portfolio Manager property types, definitions, and use details Secondary menu About us Press room Contact Us Portfolio Manager Login Facility owners and managers Existing buildings Commercial new construction Industrial energy management Small business Service providers Service and product providers Verify applications for ENERGY STAR certification Design commercial buildings Energy efficiency program administrators Commercial and industrial program sponsors Associations State and local governments Federal agencies Tools and resources Training In This Section Campaigns Commercial building design Communications resources Energy management guidance Financial resources Portfolio Manager Products and purchasing Recognition Research and reports Service and product provider (SPP) resources

432

An integrated cost model for production scheduling and perfect maintenance  

Science Journals Connector (OSTI)

Production scheduling deals with scheduling production jobs on a machine (single or multiple) in order to optimise a specific objective such as total weighted completion times or total weighted tardiness. The assumption that machines are always available for processing jobs is generally used in the production scheduling literature. In reality, machines often are unavailable due to preventive maintenance activities or machine failure. Production scheduling and preventive maintenance planning are interrelated, but are most often treated separately. This interdependency seems to be overlooked in the literature. This work integrates, simultaneously, the decisions of preventive maintenance and job order sequencing for a single machine. The objective is to find the job order sequence and maintenance decisions that would minimise the expected cost.

Laith A. Hadidi; Umar M. Al-Turki; M. Abdur Rahim

2011-01-01T23:59:59.000Z

433

Product lines for digital information products.  

E-Print Network [OSTI]

??Digital information products are an important class of widely used digital products, whose core benefit is the delivery of information or education (e.g., electronic books, (more)

Pankratius, Victor

2007-01-01T23:59:59.000Z

434

Int. J. Computing Science and Mathematics, Vol. 3, Nos. 1/2, 2010 3 DSM of Newton type for solving operator equations  

E-Print Network [OSTI]

Int. J. Computing Science and Mathematics, Vol. 3, Nos. 1/2, 2010 3 DSM of Newton type for solving (DSM) for solving operator equation (*) F(u) = f. It is assumed that (*) is solvable. The novel feature differentiable, but no smoothness assumptions on F (u) are imposed. The DSM for solving equation (*) is developed

435

CalStar Products | Open Energy Information  

Open Energy Info (EERE)

CalStar Products CalStar Products Jump to: navigation, search Name CalStar Products Place Newark, California Zip 94560 Product California-based environmentally friendly brick and paving stone manufacturer. Coordinates 44.690435°, -71.951685° 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":44.690435,"lon":-71.951685,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

436

RSI Silicon Products LLC | Open Energy Information  

Open Energy Info (EERE)

RSI Silicon Products LLC RSI Silicon Products LLC Jump to: navigation, search Name RSI Silicon Products LLC Place Easton, Massachusetts Zip 18040 Sector Solar Product Early-stage startup which is developing a process for solar-grade silicon manufacture at low energy intensity, spinoff from MIT. Coordinates 47.237806°, -121.179542° 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":47.237806,"lon":-121.179542,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

437

Advanced Solar Products | Open Energy Information  

Open Energy Info (EERE)

Products Products Jump to: navigation, search Name Advanced Solar Products Place Flemington, New Jersey Zip 8822 Product New Jersey-based PV systems installer and project developer. Coordinates 39.266175°, -80.132549° 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":39.266175,"lon":-80.132549,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

438

Mid America Agri Products | Open Energy Information  

Open Energy Info (EERE)

Mid America Agri Products Mid America Agri Products Jump to: navigation, search Name Mid America Agri Products Place Madrid, Nebraska Zip 69150 Product Ethanol producer located in Madrid, Nebraska. Coordinates 40.4203°, -3.705774° 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":40.4203,"lon":-3.705774,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

439

CMC/ BMC Utility Products | Open Energy Information  

Open Energy Info (EERE)

CMC/ BMC Utility Products CMC/ BMC Utility Products Jump to: navigation, search Name CMC/ BMC Utility Products Address 3501 Symmes Road Place Hamilton, Ohio Zip 45015 Sector Services, Solar, Wind energy Product Installation; Maintenance and repair;Manufacturing Phone number 513-860-4455 Website http://www.cmclugs.com Coordinates 39.3443592°, -84.5062904° 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":39.3443592,"lon":-84.5062904,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

440

Predicting production performance of CBM reservoirs  

Science Journals Connector (OSTI)

Prediction of gas production from the coalbed methane (CBM) reservoirs is challenging due to the complex interaction of storage and transport mechanisms. The vast majority of the gas in CBM reservoirs is stored by adsorption in the coal matrix which practically has no permeability. The flow to production wells however takes place through the cleats or the natural fracture system which store relatively small amounts of gas. These unique coal characteristics have resulted in classification of CBM as an unconventional gas resource. Gas production from CBM reservoirs is governed by gas diffusion through coal matrix followed by gas desorption into the cleat system through which the gas flows to the wellbore generally under two-phase conditions. As a result, the production profile of the CBM reservoirs greatly differs from conventional gas reservoirs. This precludes the use of common techniques such as decline curves to forecast the recovery, future revenues, and well performance. Numerical reservoir models (simulators) that incorporate the unique flow and storage characteristics of CBM reservoirs are by far the best tools for predicting the gas production from the CBM reservoirs. It is however cumbersome, time consuming, and expensive to use a complex reservoir simulator for evaluating CBM prospects when the required reservoir parameters are not available. Therefore, there is a need for a quick yet reliable tool for predicting production performance of CBM reservoirs. This paper presents a set of production type curves that can be used for predicting gas and water the production from CBM prospects. The type curves are particularly useful for parametric studies when the key characteristics are not well established. A numerical reservoir model that incorporated the unique flow and storage characteristics of CBM reservoirs was employed to develop the type curves. The impact of various reservoir parameters on the type curves was investigated to confirm the uniqueness of the type curves. The application and limitation of the type curves have been also discussed.

K. Aminian; S. Ameri

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "assumptions product types" 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

Thermonuclear supernova models, and observations of Type Ia supernovae  

E-Print Network [OSTI]

In this paper, we review the present state of theoretical models of thermonuclear supernovae, and compare their predicitions with the constraints derived from observations of Type Ia supernovae. The diversity of explosion mechanisms usually found in one-dimensional simulations is a direct consequence of the impossibility to resolve the flame structure under the assumption of spherical symmetry. Spherically symmetric models have been successful in explaining many of the observational features of Type Ia supernovae, but they rely on two kinds of empirical models: one that describes the behaviour of the flame on the scales unresolved by the code, and another that takes account of the evolution of the flame shape. In contrast, three-dimensional simulations are able to compute the flame shape in a self-consistent way, but they still need a model for the propagation of the flame in the scales unresolved by the code. Furthermore, in three dimensions the number of degrees of freedom of the initial configuration of the white dwarf at runaway is much larger than in one dimension. Recent simulations have shown that the sensitivity of the explosion output to the initial conditions can be extremely large. New paradigms of thermonuclear supernovae have emerged from this situation, as the Pulsating Reverse Detonation. The resolution of all these issues must rely on the predictions of observational properties of the models, and their comparison with current Type Ia supernova data, including X-ray spectra of Type Ia supernova remnants.

E. Bravo; C. Badenes; D. Garcia-Senz

2004-12-07T23:59:59.000Z

442

Microbial reverse-electrodialysis chemical-production cell for acid and alkali production  

E-Print Network [OSTI]

Microbial reverse-electrodialysis chemical-production cell for acid and alkali production Xiuping Accepted 7 March 2013 Available online 15 March 2013 Keywords: Microbial fuel cell Reverse electrodialysis Bioenergy A new type of bioelectrochemical system, called a microbial reverse-electrodialysis chemical

443

Rate types for stream programs  

Science Journals Connector (OSTI)

We introduce RATE TYPES, a novel type system to reason about and optimize data-intensive programs. Built around stream languages, RATE TYPES performs static quantitative reasoning about stream rates -- the frequency of data items in a stream being ... Keywords: data processing rates, data throughput, performance reasoning, stream programming, type systems

Thomas W. Bartenstein, Yu David Liu

2014-10-01T23:59:59.000Z

444

Geothermal Energy Production from Low Temperature Resources, Coproduced  

Open Energy Info (EERE)

Energy Production from Low Temperature Resources, Coproduced Energy Production from Low Temperature Resources, Coproduced Fluids from Oil and Gas Wells, and Geopressured Resources Jump to: navigation, search Geothermal ARRA Funded Projects for Geothermal Energy Production from Low Temperature Resources, Coproduced Fluids from Oil and Gas Wells, and Geopressured Resources Loading map... {"format":"googlemaps3","type":"ROADMAP","types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"limit":200,"offset":0,"link":"all","sort":[""],"order":[],"headers":"show","mainlabel":"","intro":"","outro":"","searchlabel":"\u2026

445

Traffic flow models and service rules for complex production systems  

E-Print Network [OSTI]

Traffic flow models and service rules for complex production systems C. Ringhofer Abstract We emphasis is given to the implementation of service rules for complex systems, involving multiple product flow type models for complex production systems. Traffic flow models represent, in some sense

Ringhofer, Christian

446

Refinery & Blender Net Production of Total Finished Petroleum Products  

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

& Blender Net Production & Blender Net Production Product: Total Finished Petroleum Products Liquefied Refinery Gases Ethane/Ethylene Ethane Ethylene Propane/Propylene Propane Propylene Normal Butane/Butylene Normal Butane Butylene Isobutane/Isobutylene Isobutane Isobutylene Finished Motor Gasoline Reformulated Gasoline Reformulated Blended w/ Fuel Ethanol Reformulated Other Gasoline Conventional Gasoline Conventional Blended w/ Fuel Ethanol Conventional Blended w/ Fuel Ethanol, Ed55 and Lower Conventional Blended w/ Fuel Ethanol, Greater than Ed55 Conventional Other Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm Sulfur and under Distillate F.O., Greater than 15 ppm to 500 ppm Sulfur Distillate F.O., Greater than 500 ppm Sulfur Residual Fuel Oil Residual Fuel Less Than 0.31 Percent Sulfur Residual Fuel 0.31 to 1.00 Percent Sulfur Residual Fuel Greater Than 1.00 Percent Sulfur Petrochemical Feedstocks Naphtha For Petro. Feed. Use Other Oils For Petro. Feed. Use Special Naphthas Lubricants Waxes Petroleum Coke Marketable Petroleum Coke Catalyst Petroleum Coke Asphalt and Road Oil Still Gas Miscellaneous Products Processing Gain(-) or Loss(+) Period-Unit: Monthly-Thousand Barrels Monthly-Thousand Barrels per Day Annual-Thousand Barrels Annual-Thousand Barrels per Day

447

Non-LTE Balmer line formation in late-type spectra: Effects of atomic processes involving hydrogen atoms  

E-Print Network [OSTI]

(*** abridged ***) Context: The wings of Balmer lines are often used as effective temperature diagnostics for late-type stars under the assumption they form in local thermodynamic equilibrium. Aims: Our goal is to investigate the non-LTE formation of Balmer lines in late-type stellar atmospheres, to establish if the assumption of LTE is justified. Furthermore, we aim to determine which collision processes are important for the problem; in particular, the role of collision processes with hydrogen atoms is investigated. Method: A model hydrogen atom for non-LTE calculations has been constructed accounting for various collision processes using the best available data from the literature. The processes included are inelastic collisions with electrons and hydrogen atoms, mutual neutralisation and Penning ionisation. Non-LTE calculations are performed, and the relative importance of the collision processes is investigated. Results: Our calculations show electron collisions alone are not sufficient to establish LTE for the formation of Balmer line wings. The role of inelastic collisions with neutral hydrogen is unclear. The available data for these processes is of questionable quality, and different prescriptions for the rate coefficents give significantly different results for the Balmer line wings. Conclusions: Improved calculations or experimental data are needed for excitation and, particularly, ionisation of hydrogen atoms in low-lying states by hydrogen atom impact at near threshold energies. Until such data are available, the assumption of LTE for the formation of Balmer line wings in late-type stars is questionable.

P. S. Barklem

2007-02-08T23:59:59.000Z

448

HEAVY AND THERMAL OIL RECOVERY PRODUCTION MECHANISMS  

SciTech Connect (OSTI)

This technical progress report describes work performed from October 1 through December 31, 2002 , for the project ''Heavy and Thermal Oil Recovery Production Mechanisms.'' In this project, a broad spectrum of research is undertaken related to thermal and heavy-oil recovery. The research tools and techniques used are varied and span from pore-level imaging of multiphase fluid flow to definition of reservoir-scale features through streamline-based history-matching techniques. During this period, experimental data regarding multidimensional imbibition was analyzed to obtain shape factors appropriate for dual-porosity simulation. It is shown that the usual assumption of constant, time-independent shape factors is incorrect. In other work, we continued to study the mechanisms by which oil is produced from fractured media at high pressure and high temperature. High temperature significantly increased the apparent wettability and affected water relative permeability of cores used in previous experiments. A phenomenological and mechanistic cause for this behavior is sought. Our work in the area of primary production of heavy oil continues with field cores and crude oil. On the topic of reservoir definition, work continued on developing techniques that integrate production history into reservoir models using streamline-based properties.

Anthony R. Kovscek

2003-01-01T23:59:59.000Z

449

Advanced Energy Products | Open Energy Information  

Open Energy Info (EERE)

Products Products Jump to: navigation, search Name Advanced Energy Products Address 123 C Street Place Davis, CA Zip 95616 Website http://www.advancedenergyprodu Coordinates 38.542214°, -121.743393° 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":38.542214,"lon":-121.743393,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

450

American Environmental Products | Open Energy Information  

Open Energy Info (EERE)

Logo: American Environmental Products / Sunwave Lighting Name American Environmental Products / Sunwave Lighting Address Box 18432 Place Boulder, Colorado Zip 80308 Sector Efficiency Product Spectrally Enhanced Energy Efficient Lighting Phone number 303-581-9296 Website http://www.sunwavelighting.net Coordinates 40.0153°, -105.2702° 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":40.0153,"lon":-105.2702,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

451

Covered Product Category: Cool Roof Products  

Broader source: Energy.gov [DOE]

FEMP provides acquisition guidance across a variety of product categories, including cool roof products, which are an ENERGY STAR-qualified product category. Federal laws and requirements mandate that agencies meet these efficiency requirements in all procurement and acquisition actions that are not specifically exempted by law.

452

Innovation flow through social networks: Productivity distribution  

E-Print Network [OSTI]

A detailed empirical analysis of the productivity of non financial firms across several countries and years shows that productivity follows a non-Gaussian distribution with power law tails. We demonstrate that these empirical findings can be interpreted as consequence of a mechanism of exchanges in a social network where firms improve their productivity by direct innovation or/and by imitation of other firm's technological and organizational solutions. The type of network-connectivity determines how fast and how efficiently information can diffuse and how quickly innovation will permeate or behaviors will be imitated. From a model for innovation flow through a complex network we obtain that the expectation values of the productivity level are proportional to the connectivity of the network of links between firms. The comparison with the empirical distributions reveals that such a network must be of a scale-free type with a power-law degree distribution in the large connectivity range.

T. Di Matteo; T. Aste; M. Gallegati

2004-06-19T23:59:59.000Z

453

Aesculap, Inc. Air Products  

E-Print Network [OSTI]

Aesculap, Inc. Air Products Air Products Foundation Alaric Compliance Services, LLC Alvin H. Butz & Herger, Inc. Sodexo Campus Services Sodexo Inc. and Affiliates Stupp Bros., Inc. Sugarbush Products, Inc

Napier, Terrence

454

Attributive types for proof erasure  

Science Journals Connector (OSTI)

Proof erasure plays an essential role in the paradigm of programming with theorem proving. In this paper, we introduce a form of attributive types that carry an attribute to determine whether expressions assigned such types are eligible for erasure before ...

Hongwei Xi

2007-05-01T23:59:59.000Z

455

Exotic Ungulate Production: Summary of Survey Results.  

E-Print Network [OSTI]

Dietrich are gratefully acknowledged as is typing by Kristy McCollough. 1 'fI Exotic Ungulate Production: Summary Of Survey Results James W. Mjelde J. Richard Conner Jerry W. Stuth J ames Jensen Chia-Cheun Chang James B. Jones The authors... Dietrich are gratefully acknowledged as is typing by Kristy McCollough. 1 'fI Exotic Ungulate Production: Summary Of Survey Results James W. Mjelde J. Richard Conner Jerry W. Stuth J ames Jensen Chia-Cheun Chang James B. Jones The authors...

Mjelde, James W.; Conner, J. Richard; Stuth, Jerry W.; Jensen, James; Chang, Chia-Cheun; Jones, James B.

1992-01-01T23:59:59.000Z

456

Partnering Institution Name Partnering Institution Name Place Type  

Open Energy Info (EERE)

Partnering Institution Name Partnering Institution Name Place Type Partnering Institution Name Partnering Institution Name Place Type of Partnership Partner Center Partner Year Partner Description Link Technologies Technologies North Lexington Massachusetts Incubator National Center for Photovoltaics M M St Paul Minnesota CRADA http www nrel gov pv pv manufacturing html A O Smith A O Smith Milwaukee Wisconsin Test Evaluation Partner Electricity Resources Building Systems Integration A123Systems A123Systems Watertown Massachusetts CRADA Transportation Technologies and Systems http www nrel gov news press html AAON AAON Tulsa Oklahoma Test Evaluation Partner Electricity Resources Building Systems Integration AQUA Products AQUA Products Prosperity South Carolina Test Evaluation Partner Electricity Resources Building Systems Integration

457

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

458

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 . . . . . . . . . . .

459

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.

460

Assumptions to the Annual Energy Outlook 2013  

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

set using a discount rate of 10 percent. The model limits the annual builds to one two-train facility a year, with total annual export capacity of 400 billion cubic feet. The...

Note: This page contains sample records for the topic "assumptions product types" 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

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 |...

462

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...

463

Assumptions to the Annual Energy Outlook 2014  

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

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...

464

Supply-side Resources & Planning Assumptions  

E-Print Network [OSTI]

with forecast escalation/deescalation. Capital cost expressed as "overnight" total plant cost; w 90% 100% 16% 55% 26% 10% 20% 30% 40% 50% 60% 70% 80% Cash expended Annual expenditure Cumulative expenditure (excl EDC & IDC) 1% 2% 0% 10% 1 2 3 4 5 Year 96/19/2013 Construction schedule & cash flow

465

Appendix MASS: Performance Assessment Modeling Assumptions  

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

Rock Units MASS-12.2 Historical Context of the Salado Conceptual Model MASS-12.3 The Fracture Model MASS-12.4 Flow in the DRZ MASS-12.5 Actinide Transport in the Salado MASS-13.0...

466

Assumptions to the Annual Energy Outlook 2013  

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

Act of 2006 (AB32) AB32 established a comprehensive, multi-year program to reduce Green House Gas (GHG) emissions in California, including a cap-and-trade program. In...

467

Assumptions to the Annual Energy Outlook 2013  

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

Rule (CAIR), which was reinstated as binding legislation after the Cross- State Air Pollution Rule (CSAPR) 4 was vacated on August 21, 2012; updated handling of the...

468

Phenomenology: history, its methodological assumptions and application .  

E-Print Network [OSTI]

??This study aims to provide a deeper understanding of phenomenology firstly by tracing its historical roots and locating it within its philosophical framework. This aim (more)

Mohamed-Patel, Rahima

2008-01-01T23:59:59.000Z

469

Tornado type wind turbines  

DOE Patents [OSTI]

A tornado type wind turbine has a vertically disposed wind collecting tower with spaced apart inner and outer walls and a central bore. The upper end of the tower is open while the lower end of the structure is in communication with a wind intake chamber. An opening in the wind chamber is positioned over a turbine which is in driving communication with an electrical generator. An opening between the inner and outer walls at the lower end of the tower permits radially flowing air to enter the space between the inner and outer walls while a vertically disposed opening in the wind collecting tower permits tangentially flowing air to enter the central bore. A porous portion of the inner wall permits the radially flowing air to interact with the tangentially flowing air so as to create an intensified vortex flow which exits out of the top opening of the tower so as to create a low pressure core and thus draw air through the opening of the wind intake chamber so as to drive the turbine.

Hsu, Cheng-Ting (Ames, IA)

1984-01-01T23:59:59.000Z

470

from Isotope Production Facility  

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

Cancer-fighting treatment gets boost from Isotope Production Facility April 13, 2012 Isotope Production Facility produces cancer-fighting actinium 2:32 Isotope cancer treatment...

471

Alternative Fuels Data Center: Biofuel Production Facility Tax Credit  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuel Production Biofuel Production Facility Tax Credit to someone by E-mail Share Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Facebook Tweet about Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Twitter Bookmark Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Google Bookmark Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Delicious Rank Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Digg Find More places to share Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biofuel Production Facility Tax Credit Companies that invest in the development of a biofuel production facility

472

Alternative Fuels Data Center: Ethanol Production Tax Credit  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Production Tax Production Tax Credit to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Tax Credit on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Tax Credit on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Tax Credit on Google Bookmark Alternative Fuels Data Center: Ethanol Production Tax Credit on Delicious Rank Alternative Fuels Data Center: Ethanol Production Tax Credit on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Tax Credit on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Tax Credit An ethanol facility is eligible for a credit of $0.075 per gallon of ethanol, before denaturing, for new production for up to 36 consecutive

473

Alternative Fuels Data Center: Ethanol Production Facility Fee  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol Production Ethanol Production Facility Fee to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Facility Fee on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Facility Fee on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Facility Fee on Google Bookmark Alternative Fuels Data Center: Ethanol Production Facility Fee on Delicious Rank Alternative Fuels Data Center: Ethanol Production Facility Fee on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Facility Fee on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Facility Fee The cost to submit an air quality permit application for an ethanol production plant is $1,000. An annual renewal fee is also required for the

474

Type B Accident Investigation of the March 20, 2003, Stair Installation Accident at Building 752, Sandia National Laboratories  

Broader source: Energy.gov [DOE]

This report is an independent product of the Type B Accident Investigation Board appointed by Karen L. Boardman, Manager, Sandia Site Office (SSO), National Nuclear Security Administration (NNSA).

475

Type B Investigation Board Report on the June 19, 1997, Occupational Illness at the Y-12 Plant, Oak Ridge, Tennessee  

Broader source: Energy.gov [DOE]

This report is an independent product of the Type B Investigation Board (Board) appointed by James C. Hall, Manager, Oak Ridge Operations.

476

Type B Accident Investigation Board Report on the September 7, 2001, Burn Accident at Oak Ridge National Laboratory, Building 9210  

Broader source: Energy.gov [DOE]

This report is an independent product of the Type B Investigation Board appointed by G. Leah Dever, Manager, Oak Ridge Operations Office, U.S. Department of Energy.

477

Product Supplied for Total Crude Oil and Petroleum Products  

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

Product: Total Crude Oil and Petroleum Products Crude Oil Natural Gas Liquids and LRGs Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Isobutylene Other Liquids Hydrogen/Oxygenates/Renewables/Other Hydrocarbons Unfinished Oils Motor Gasoline Blend. Comp. (MGBC) MGBC - Reformulated MGBC - Conventional Aviation Gasoline Blend. Comp. Finished Petroleum Products Finished Motor Gasoline Reformulated Gasoline Conventional Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm and under Sulfur Distillate F.O., Greater than 15 to 500 ppm Sulfur Distillate F.O., Greater than 500 ppm Sulfur Residual Fuel Oil Petrochemical Feedstocks Naphtha for Petro. Feed. Use Other Oils for Petro. Feed Use Special Naphthas Lubricants Waxes Petroleum Coke Petroleum Coke - Marketable Petroleum Coke - Catalyst Asphalt and Road Oil Still Gas Miscellaneous Products Period-Unit: Monthly-Thousand Barrels Monthly-Thousand Barrels per Day Annual-Thousand Barrels Annual-Thousand Barrels per Day

478

General inner products for energy eigenstates  

E-Print Network [OSTI]

The features of the inner products between all the types of real and complex-energy solutions of the Schr\\"odinger equation for 1-dimensional cut-off quantum potentials are worked out using a Gaussian regularization. A general Master Solution is introduced which describes any of the above solutions as particular cases. From it, a Master Inner Product is obtained which yields all the particular products. We show that the Outgoing and the Incoming Boundary Conditions fully determine the location of the momenta respectively in the lower and upper half complex plane even for purely imaginary momenta (anti-bound and bound solutions).

J. Julve; S. Turrini; F. J. de Urres

2013-02-04T23:59:59.000Z

479

Announcement Notice Options By STI Type | Scientific and Technical  

Office of Scientific and Technical Information (OSTI)

Notices Notices Announcement Notice Options By STI Type Print page Print page Email page Email page The following list provides basic information regarding which announcement notice should be used by which audience for the various types of STI. For more information, see Submittal Basics. Announcement Options STI Product Types Announcement Notice Audiences AN 241.1 Web Version AN 241.1 Transmission Option Books/Monographs (non-copyrighted) Books/Monographs (copyrighted) Conference Papers/Presentations/Proceedings (non-copyrighted Conference Papers/Presentations/Proceedings (copyrighted) Journal Article Reprints (announcement notice only with adequate information to enable linking via Digital Object Identifier (DOI)) Journal Articles - Accepted manuscript Patents Program Documents

480

By-Products Utilization  

E-Print Network [OSTI]

Center for By-Products Utilization PROPERTIES OF CONCRETE CONTAINING SCRAP TIRE RUBBER in a variety of rubber and plastic products, thermal incineration of waste tires for production of electricity rubber in asphalt mixes, (ii) thermal incineration of worn-out tires for the production of electricity

Wisconsin-Milwaukee, University of

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


481

On the asymptotic homotopy type of inductive limit Type ...  

E-Print Network [OSTI]

In this note we exhibit large classes of (projeetionless) stable, nuclear C*- algebras whose asymptotic homotopy type is determined by K-theoretical data.

482

NREL: Learning - Geothermal Electricity Production  

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

Electricity Production Electricity Production Photo of a geothermal power plant. This geothermal power plant generates electricity for the Imperial Valley in California. Geothermal power plants use steam produced from reservoirs of hot water found a few miles or more below the Earth's surface to produce electricity. The steam rotates a turbine that activates a generator, which produces electricity. There are three types of geothermal power plants: dry steam, flash steam, and binary cycle. Dry Steam Dry steam power plants draw from underground resources of steam. The steam is piped directly from underground wells to the power plant where it is directed into a turbine/generator unit. There are only two known underground resources of steam in the United States: The Geysers in northern California and Yellowstone National Park in Wyoming, where there's

483

DOE Hydrogen Analysis Repository: Hydrogen Production by  

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

Production by Photovoltaic-powered Electrolysis Production by Photovoltaic-powered Electrolysis Project Summary Full Title: Production of Hydrogen by Photovoltaic-powered Electrolysis Project ID: 91 Principal Investigator: D.L. Block Keywords: Hydrogen production; electrolysis; photovoltaic (PV) Purpose To evaluate hydrogen production from photovoltaic (PV)-powered electrolysis. Performer Principal Investigator: D.L. Block Organization: Florida Solar Energy Center Address: 1679 Clearlake Road Cocoa, FL 32922 Telephone: 321-638-1001 Email: block@fsec.ucf.edu Sponsor(s) Name: Michael Ashworth Organization: Florida Energy Office Name: Neil Rossmeissl Organization: DOE/Advanced Utilities Concepts Division Name: H.T. Everett Organization: NASA/Kennedy Space Center Project Description Type of Project: Analysis Category: Hydrogen Fuel Pathways

484

Energy Efficiency Product Standards | Department of Energy  

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

Efficiency Product Standards Efficiency Product Standards Energy Efficiency Product Standards < Back Program Info State New Jersey Program Type Appliance/Equipment Efficiency Standards Provider New Jersey Board of Public Utilities '' Note: The federal government has imposed and updated appliance efficiency standards through several legislative acts,* and now has standards in place or under development for 30 classes of products. In general, states which had set standards prior to federal action may enforce their own standards until the federal standards take effect. States that had not set standards prior to federal action must use the federal standards. This summary addresses (1) state appliance standards that will be in place until the federal standards take effect and (2) products for

485

Exergetic assessment of solar hydrogen production methods  

Science Journals Connector (OSTI)

Hydrogen is a sustainable fuel option and one of the potential solutions for the current energy and environmental problems. Its eco-friendly production is really crucial for better environment and sustainable development. In this paper, various types of hydrogen production methods namely solar thermal (high temperature and low temperature), photovoltaic, photoelecrtolysis, biophotolysis etc are discussed. A brief study of various hydrogen production processes have been carried out. Various solar-based hydrogen production processes are assessed and compared for their merits and demerits in terms ofexergy efficiency and sustainability factor. For a case study the exergy efficiency of hydrogen production process and the hydrogen system is discussed in terms of sustainability.

Anand S. Joshi; Ibrahim Dincer; Bale V. Reddy

2010-01-01T23:59:59.000Z

486

By Type of STI | Scientific and Technical Information Program  

Office of Scientific and Technical Information (OSTI)

Type of STI Type of STI Print page Print page Email page Email page STI Types are provided to OSTI using various announcement options and transmission methods. Some STI types are always required to be submitted or made available via a unique URL, while other STI types may only be announced to OSTI (commercially published and copyrighted). In cases where an announcement notice is acceptable, information regarding the STI Product's availability is required. DOE Programs should have an established format for providing STI to OSTI. If an established process does not exist, please email or telephone Kim Buckner at bucknerk@osti.gov or (865) 576-1228. Major Site/Facility Management Contractors have an established formal procedure for providing STI to OSTI. For more information, contact your

487

Window Types | Department of Energy  

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

Window Types Window Types Window Types June 18, 2012 - 8:06am Addthis A wood-frame window with insulated window glazing. | Photo courtesy of ©iStockphoto/chandlerphoto A wood-frame window with insulated window glazing. | Photo courtesy of ©iStockphoto/chandlerphoto What does this mean for me? If you have old windows, they are likely losing large amounts of energy through the frames and glazing. By upgrading old windows, you can reduce heating and cooling costs in your home. Windows come in a number of different frame and glazing types. By combining an energy-efficient frame choice with a glazing type tailored to your climate and application, you can customize each of your home's windows. Types of Window Frames Improving the thermal resistance of the frame can contribute to a window's

488

Window Types | Department of Energy  

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

Window Types Window Types Window Types June 18, 2012 - 8:06am Addthis A wood-frame window with insulated window glazing. | Photo courtesy of ©iStockphoto/chandlerphoto A wood-frame window with insulated window glazing. | Photo courtesy of ©iStockphoto/chandlerphoto What does this mean for me? If you have old windows, they are likely losing large amounts of energy through the frames and glazing. By upgrading old windows, you can reduce heating and cooling costs in your home. Windows come in a number of different frame and glazing types. By combining an energy-efficient frame choice with a glazing type tailored to your climate and application, you can customize each of your home's windows. Types of Window Frames Improving the thermal resistance of the frame can contribute to a window's

489

Biological Safety Cabinets n Product protection  

E-Print Network [OSTI]

2.7 #12;Biological Safety Cabinets Purpose n Product protection n Personal protection n Environmental protection 2.7 #12;Biological Safety Cabinets Types A. Class I n inward airflow protects worker n" work area n use for work with aerosol-transmissible micro- organisms n use also for tissue culture

Collins, Gary S.

490

Biochemical Evidence for a Distinct Type of Primary Gout  

Science Journals Connector (OSTI)

... Adult patients with gout characterized by over-production of uric acid show a similar but less marked pattern of ... uric acid4'5. Recently, it has been shown that in the adult type of gout the shunt pathway can be abolished by administration of the synthetic purines azathioprine ('Imuran ...

LEIF B. SORENSEN; PAUL J. BENKE

1967-03-18T23:59:59.000Z

491

{phi}-meson production in proton-proton collisions  

SciTech Connect (OSTI)

The production of {phi} mesons in proton-proton collisions is investigated within a relativistic meson-exchange model of hadronic interactions. The experimental prerequisites for extracting the NN{phi} coupling strength from this reaction are discussed. In the absence of a sufficient set of data, which would enable an accurate determination of the NN{phi} coupling strength, we perform a combined analysis, based on some reasonable assumptions, of the existing data for both {omega}- and {phi}-meson production. We find that the recent data from the DISTO Collaboration on the angular distribution of the {phi} meson indicate that the NN{phi} coupling constant is small. The analysis yields values for g{sub NN{phi}} that are compatible with the Okubo-Zweig-Iizuka rule. {copyright} {ital 1999} {ital The American Physical Society}

Nakayama, K.; Durso, J.W.; Haidenbauer, J.; Hanhart, C.; Speth, J. [Institut fuer Kernphysik, Forschungszentrum Juelich GmbH, D-52425 Juelich (Germany)] [Institut fuer Kernphysik, Forschungszentrum Juelich GmbH, D-52425 Juelich (Germany); Nakayama, K. [Department of Physics and Astronomy, University of Georgia, Athens, Georgia 30602 (United States)] [Department of Physics and Astronomy, University of Georgia, Athens, Georgia 30602 (United States); Durso, J.W. [Physics Department, Mount Holyoke College, South Hadley, Massachusetts 01075 (United States)] [Physics Department, Mount Holyoke College, South Hadley, Massachusetts 01075 (United States); Hanhart, C. [Institut fuer Theoretische Kernphysik, Universitaet Bonn, D-53115 Bonn (Germany)] [Institut fuer Theoretische Kernphysik, Universitaet Bonn, D-53115 Bonn (Germany); Hanhart, C. [Department of Physics and INT, University of Washington, Seattle, Washington 98195 (United States)] [Department of Physics and INT, University of Washington, Seattle, Washington 98195 (United States)

1999-11-01T23:59:59.000Z

492

Strangeness production in small and large collisions systems at RHIC  

E-Print Network [OSTI]

We present measurements of strange and multi-strange hadrons in p+p collisions at $\\sqrt{s}$= 200 GeV measured by STAR. We will compare these preliminary results to leading-order (LO) and next-to-leading order (NLO) perturbative QCD models widely believed to describe the production mechanisms. In particular we will point out recent changes of the model calculations which improve the agreement with our data significantly and will discuss the physics consequences. In larger collision systems, produced with heavy ions at RHIC, we observe the centrality dependence of strange and multi-strange particle production. The non-linear dependency between (anti)-hyperon yields and the system size \\Npart seems to indicate that the correlation volume does not scale exactly with \\Npart in contradiction to previous assumptions by thermal models.

Mark Heinz

2006-04-13T23:59:59.000Z

493

Portfolio Manager Space Type Discussion  

Broader source: Energy.gov [DOE]

This presentation, given through the DOE's Technical Assitance Program (TAP), provides a discussion about space/type in regards to the Portfolio Manager Initiative.

494

Alternative Fuels Data Center: Biofuel Production Facility Tax Credit  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuel Production Biofuel Production Facility Tax Credit to someone by E-mail Share Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Facebook Tweet about Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Twitter Bookmark Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Google Bookmark Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Delicious Rank Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on Digg Find More places to share Alternative Fuels Data Center: Biofuel Production Facility Tax Credit on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biofuel Production Facility Tax Credit A taxpayer who processes biodiesel, ethanol, or gasoline blends consisting

495

Alternative Fuels Data Center: Ethanol Production Tax Credit  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Ethanol Production Tax Ethanol Production Tax Credit to someone by E-mail Share Alternative Fuels Data Center: Ethanol Production Tax Credit on Facebook Tweet about Alternative Fuels Data Center: Ethanol Production Tax Credit on Twitter Bookmark Alternative Fuels Data Center: Ethanol Production Tax Credit on Google Bookmark Alternative Fuels Data Center: Ethanol Production Tax Credit on Delicious Rank Alternative Fuels Data Center: Ethanol Production Tax Credit on Digg Find More places to share Alternative Fuels Data Center: Ethanol Production Tax Credit on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Ethanol Production Tax Credit Qualified ethanol producers are eligible for an income tax credit of $1.00 per gallon of corn- or cellulosic-based ethanol that meets ASTM

496

Alternative Fuels Data Center: Biofuels Production Tax Deduction  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Biofuels Production Biofuels Production Tax Deduction to someone by E-mail Share Alternative Fuels Data Center: Biofuels Production Tax Deduction on Facebook Tweet about Alternative Fuels Data Center: Biofuels Production Tax Deduction on Twitter Bookmark Alternative Fuels Data Center: Biofuels Production Tax Deduction on Google Bookmark Alternative Fuels Data Center: Biofuels Production Tax Deduction on Delicious Rank Alternative Fuels Data Center: Biofuels Production Tax Deduction on Digg Find More places to share Alternative Fuels Data Center: Biofuels Production Tax Deduction on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biofuels Production Tax Deduction The cost of purchasing qualified biomass feedstocks to be processed into